From 22b7f3dd6acb005b8e5191ab61b5f9133a7b88db Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 10:28:04 +0200 Subject: [PATCH 01/32] Rename notebook: hamiltonian simulation guide --- tests/resources/timeouts.yaml | 6 +++--- .../hamiltonian_simulation_guide.ipynb | 6 +++--- ...miltonian_simulation_guide_exponentiation.metadata.json} | 0 ...mod => hamiltonian_simulation_guide_exponentiation.qmod} | 0 ..._simulation_guide_exponentiation.synthesis_options.json} | 0 ...on => hamiltonian_simulation_guide_qdrift.metadata.json} | 0 ...qdrift.qmod => hamiltonian_simulation_guide_qdrift.qmod} | 0 ...iltonian_simulation_guide_qdrift.synthesis_options.json} | 0 ...n => hamiltonian_simulation_guide_trotter.metadata.json} | 0 ...otter.qmod => hamiltonian_simulation_guide_trotter.qmod} | 0 ...ltonian_simulation_guide_trotter.synthesis_options.json} | 0 11 files changed, 6 insertions(+), 6 deletions(-) rename tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/{exponentiation.metadata.json => hamiltonian_simulation_guide_exponentiation.metadata.json} (100%) rename tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/{exponentiation.qmod => hamiltonian_simulation_guide_exponentiation.qmod} (100%) rename tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/{exponentiation.synthesis_options.json => hamiltonian_simulation_guide_exponentiation.synthesis_options.json} (100%) rename tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/{qdrift.metadata.json => hamiltonian_simulation_guide_qdrift.metadata.json} (100%) rename tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/{qdrift.qmod => hamiltonian_simulation_guide_qdrift.qmod} (100%) rename tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/{qdrift.synthesis_options.json => hamiltonian_simulation_guide_qdrift.synthesis_options.json} (100%) rename tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/{trotter.metadata.json => hamiltonian_simulation_guide_trotter.metadata.json} (100%) rename tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/{trotter.qmod => hamiltonian_simulation_guide_trotter.qmod} (100%) rename tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/{trotter.synthesis_options.json => hamiltonian_simulation_guide_trotter.synthesis_options.json} (100%) diff --git a/tests/resources/timeouts.yaml b/tests/resources/timeouts.yaml index 1f2ad0289..2a57cb661 100644 --- a/tests/resources/timeouts.yaml +++ b/tests/resources/timeouts.yaml @@ -290,10 +290,10 @@ tutorials/popular_usage_examples/basic_tutorials/prepare_state/prepare_state.qmo tutorials/popular_usage_examples/exponentiation/exponentiation.ipynb: 216 tutorials/popular_usage_examples/exponentiation/exponentiation.qmod: 92 tutorials/popular_usage_examples/exponentiation/exponentiation_minimize_error.qmod: 20 -tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/exponentiation.qmod: 300 +tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_exponentiation.qmod: 300 tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide.ipynb: 1000 -tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/qdrift.qmod: 300 -tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/trotter.qmod: 300 +tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_qdrift.qmod: 300 +tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_trotter.qmod: 300 tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_with_block_encoding/hamiltonian_simulation_qsvt.qmod: 300 tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_with_block_encoding/hamiltonian_simulation_qubitization.qmod: 300 tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_with_block_encoding/hamiltonian_simulation_with_block_encoding.ipynb: 600 diff --git a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide.ipynb b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide.ipynb index fc6f93492..09ae1e071 100644 --- a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide.ipynb +++ b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide.ipynb @@ -187,7 +187,7 @@ "\n", "qmod = create_model(main)\n", "qprog = synthesize(qmod)\n", - "write_qmod(qmod, \"trotter\")\n", + "write_qmod(qmod, \"hamiltonian_simulation_guide_trotter\")\n", "show(qprog)" ] }, @@ -232,7 +232,7 @@ "\n", "\n", "qmod = create_model(main)\n", - "write_qmod(qmod, \"exponentiation\")\n", + "write_qmod(qmod, \"hamiltonian_simulation_guide_exponentiation\")\n", "qprog = synthesize(qmod)\n", "show(qprog)" ] @@ -327,7 +327,7 @@ "\n", "\n", "qmod = create_model(main)\n", - "write_qmod(qmod, \"qdrift\")\n", + "write_qmod(qmod, \"hamiltonian_simulation_guide_qdrift\")\n", "qprog = synthesize(qmod)\n", "show(qprog)" ] diff --git a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/exponentiation.metadata.json b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_exponentiation.metadata.json similarity index 100% rename from tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/exponentiation.metadata.json rename to tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_exponentiation.metadata.json diff --git a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/exponentiation.qmod b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_exponentiation.qmod similarity index 100% rename from tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/exponentiation.qmod rename to tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_exponentiation.qmod diff --git a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/exponentiation.synthesis_options.json b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_exponentiation.synthesis_options.json similarity index 100% rename from tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/exponentiation.synthesis_options.json rename to tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_exponentiation.synthesis_options.json diff --git a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/qdrift.metadata.json b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_qdrift.metadata.json similarity index 100% rename from tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/qdrift.metadata.json rename to tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_qdrift.metadata.json diff --git a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/qdrift.qmod b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_qdrift.qmod similarity index 100% rename from tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/qdrift.qmod rename to tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_qdrift.qmod diff --git a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/qdrift.synthesis_options.json b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_qdrift.synthesis_options.json similarity index 100% rename from tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/qdrift.synthesis_options.json rename to tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_qdrift.synthesis_options.json diff --git a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/trotter.metadata.json b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_trotter.metadata.json similarity index 100% rename from tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/trotter.metadata.json rename to tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_trotter.metadata.json diff --git a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/trotter.qmod b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_trotter.qmod similarity index 100% rename from tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/trotter.qmod rename to tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_trotter.qmod diff --git a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/trotter.synthesis_options.json b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_trotter.synthesis_options.json similarity index 100% rename from tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/trotter.synthesis_options.json rename to tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_trotter.synthesis_options.json From 4e838e7c99aa895310bb98b4f7580e4635a462d5 Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 10:32:01 +0200 Subject: [PATCH 02/32] Rename notebook: hamiltonian evolution --- ...tiation.ipynb => hamiltonian_evolution_exponentiation.ipynb} | 2 +- ....json => hamiltonian_evolution_exponentiation.metadata.json} | 0 ...entiation.qmod => hamiltonian_evolution_exponentiation.qmod} | 0 ...hamiltonian_evolution_exponentiation.synthesis_options.json} | 0 4 files changed, 1 insertion(+), 1 deletion(-) rename functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/{exponentiation.ipynb => hamiltonian_evolution_exponentiation.ipynb} (98%) rename functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/{exponentiation.metadata.json => hamiltonian_evolution_exponentiation.metadata.json} (100%) rename functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/{exponentiation.qmod => hamiltonian_evolution_exponentiation.qmod} (100%) rename functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/{exponentiation.synthesis_options.json => hamiltonian_evolution_exponentiation.synthesis_options.json} (100%) diff --git a/functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/exponentiation.ipynb b/functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/hamiltonian_evolution_exponentiation.ipynb similarity index 98% rename from functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/exponentiation.ipynb rename to functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/hamiltonian_evolution_exponentiation.ipynb index 9f898d515..dd6d57046 100644 --- a/functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/exponentiation.ipynb +++ b/functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/hamiltonian_evolution_exponentiation.ipynb @@ -96,7 +96,7 @@ " )\n", "\n", "\n", - "qmod = create_model(main, out_file=\"exponentiation\")\n", + "qmod = create_model(main, out_file=\"hamiltonian_evolution_exponentiation\")\n", "qprog = synthesize(qmod)" ] }, diff --git a/functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/exponentiation.metadata.json b/functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/hamiltonian_evolution_exponentiation.metadata.json similarity index 100% rename from functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/exponentiation.metadata.json rename to functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/hamiltonian_evolution_exponentiation.metadata.json diff --git a/functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/exponentiation.qmod b/functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/hamiltonian_evolution_exponentiation.qmod similarity index 100% rename from functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/exponentiation.qmod rename to functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/hamiltonian_evolution_exponentiation.qmod diff --git a/functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/exponentiation.synthesis_options.json b/functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/hamiltonian_evolution_exponentiation.synthesis_options.json similarity index 100% rename from functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/exponentiation.synthesis_options.json rename to functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/hamiltonian_evolution_exponentiation.synthesis_options.json From b8c5d6925a5a1e9fe987c3b0e0b662c164401e6f Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 10:33:57 +0200 Subject: [PATCH 03/32] Rename notebook: exponentiation example --- tests/resources/timeouts.yaml | 6 +++--- .../{exponentiation.ipynb => example_exponentiation.ipynb} | 4 ++-- ...n.metadata.json => example_exponentiation.metadata.json} | 0 .../{exponentiation.qmod => example_exponentiation.qmod} | 0 ...s.json => example_exponentiation.synthesis_options.json} | 0 ... => example_exponentiation_minimize_error.metadata.json} | 0 ...rror.qmod => example_exponentiation_minimize_error.qmod} | 0 ...le_exponentiation_minimize_error.synthesis_options.json} | 0 8 files changed, 5 insertions(+), 5 deletions(-) rename tutorials/popular_usage_examples/exponentiation/{exponentiation.ipynb => example_exponentiation.ipynb} (98%) rename tutorials/popular_usage_examples/exponentiation/{exponentiation.metadata.json => example_exponentiation.metadata.json} (100%) rename tutorials/popular_usage_examples/exponentiation/{exponentiation.qmod => example_exponentiation.qmod} (100%) rename tutorials/popular_usage_examples/exponentiation/{exponentiation.synthesis_options.json => example_exponentiation.synthesis_options.json} (100%) rename tutorials/popular_usage_examples/exponentiation/{exponentiation_minimize_error.metadata.json => example_exponentiation_minimize_error.metadata.json} (100%) rename tutorials/popular_usage_examples/exponentiation/{exponentiation_minimize_error.qmod => example_exponentiation_minimize_error.qmod} (100%) rename tutorials/popular_usage_examples/exponentiation/{exponentiation_minimize_error.synthesis_options.json => example_exponentiation_minimize_error.synthesis_options.json} (100%) diff --git a/tests/resources/timeouts.yaml b/tests/resources/timeouts.yaml index 2a57cb661..f6e532812 100644 --- a/tests/resources/timeouts.yaml +++ b/tests/resources/timeouts.yaml @@ -287,9 +287,9 @@ tutorials/popular_usage_examples/basic_tutorials/bernstein_vazirani/bernstein_va tutorials/popular_usage_examples/basic_tutorials/bernstein_vazirani/bv_tutorial.qmod: 30 tutorials/popular_usage_examples/basic_tutorials/prepare_state/prepare_state.ipynb: 20 tutorials/popular_usage_examples/basic_tutorials/prepare_state/prepare_state.qmod: 20 -tutorials/popular_usage_examples/exponentiation/exponentiation.ipynb: 216 -tutorials/popular_usage_examples/exponentiation/exponentiation.qmod: 92 -tutorials/popular_usage_examples/exponentiation/exponentiation_minimize_error.qmod: 20 +tutorials/popular_usage_examples/exponentiation/example_exponentiation.ipynb: 216 +tutorials/popular_usage_examples/exponentiation/example_exponentiation.qmod: 92 +tutorials/popular_usage_examples/exponentiation/example_exponentiation_minimize_error.qmod: 20 tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_exponentiation.qmod: 300 tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide.ipynb: 1000 tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_guide/hamiltonian_simulation_guide_qdrift.qmod: 300 diff --git a/tutorials/popular_usage_examples/exponentiation/exponentiation.ipynb b/tutorials/popular_usage_examples/exponentiation/example_exponentiation.ipynb similarity index 98% rename from tutorials/popular_usage_examples/exponentiation/exponentiation.ipynb rename to tutorials/popular_usage_examples/exponentiation/example_exponentiation.ipynb index 275b353a4..4b2430d82 100644 --- a/tutorials/popular_usage_examples/exponentiation/exponentiation.ipynb +++ b/tutorials/popular_usage_examples/exponentiation/example_exponentiation.ipynb @@ -157,7 +157,7 @@ " custom_hardware_settings=CustomHardwareSettings(basis_gates=[\"cx\", \"u\"])\n", " ),\n", ")\n", - "write_qmod(qmod, \"exponentiation\")\n", + "write_qmod(qmod, \"example_exponentiation\")\n", "\n", "qprog = synthesize(qmod)\n", "circuit = QuantumProgram.from_qprog(qprog)\n", @@ -248,7 +248,7 @@ "qmod = create_model(main)\n", "\n", "\n", - "write_qmod(qmod, \"exponentiation_minimize_error\")\n", + "write_qmod(qmod, \"example_exponentiation_minimize_error\")\n", "\n", "qprog = synthesize(qmod)\n", "show(qprog)" diff --git a/tutorials/popular_usage_examples/exponentiation/exponentiation.metadata.json b/tutorials/popular_usage_examples/exponentiation/example_exponentiation.metadata.json similarity index 100% rename from tutorials/popular_usage_examples/exponentiation/exponentiation.metadata.json rename to tutorials/popular_usage_examples/exponentiation/example_exponentiation.metadata.json diff --git a/tutorials/popular_usage_examples/exponentiation/exponentiation.qmod b/tutorials/popular_usage_examples/exponentiation/example_exponentiation.qmod similarity index 100% rename from tutorials/popular_usage_examples/exponentiation/exponentiation.qmod rename to tutorials/popular_usage_examples/exponentiation/example_exponentiation.qmod diff --git a/tutorials/popular_usage_examples/exponentiation/exponentiation.synthesis_options.json b/tutorials/popular_usage_examples/exponentiation/example_exponentiation.synthesis_options.json similarity index 100% rename from tutorials/popular_usage_examples/exponentiation/exponentiation.synthesis_options.json rename to tutorials/popular_usage_examples/exponentiation/example_exponentiation.synthesis_options.json diff --git a/tutorials/popular_usage_examples/exponentiation/exponentiation_minimize_error.metadata.json b/tutorials/popular_usage_examples/exponentiation/example_exponentiation_minimize_error.metadata.json similarity index 100% rename from tutorials/popular_usage_examples/exponentiation/exponentiation_minimize_error.metadata.json rename to tutorials/popular_usage_examples/exponentiation/example_exponentiation_minimize_error.metadata.json diff --git a/tutorials/popular_usage_examples/exponentiation/exponentiation_minimize_error.qmod b/tutorials/popular_usage_examples/exponentiation/example_exponentiation_minimize_error.qmod similarity index 100% rename from tutorials/popular_usage_examples/exponentiation/exponentiation_minimize_error.qmod rename to tutorials/popular_usage_examples/exponentiation/example_exponentiation_minimize_error.qmod diff --git a/tutorials/popular_usage_examples/exponentiation/exponentiation_minimize_error.synthesis_options.json b/tutorials/popular_usage_examples/exponentiation/example_exponentiation_minimize_error.synthesis_options.json similarity index 100% rename from tutorials/popular_usage_examples/exponentiation/exponentiation_minimize_error.synthesis_options.json rename to tutorials/popular_usage_examples/exponentiation/example_exponentiation_minimize_error.synthesis_options.json From 7fe21ba8003e86afb3e733e6cc15381fb2bd13b0 Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 10:38:38 +0200 Subject: [PATCH 04/32] Rename notebook: hhl example --- tests/resources/timeouts.yaml | 2 +- .../hhl/{hhl.ipynb => hhl_example.ipynb} | 0 2 files changed, 1 insertion(+), 1 deletion(-) rename tutorials/technology_demonstrations/hhl/{hhl.ipynb => hhl_example.ipynb} (100%) diff --git a/tests/resources/timeouts.yaml b/tests/resources/timeouts.yaml index f6e532812..2aac246b0 100644 --- a/tests/resources/timeouts.yaml +++ b/tests/resources/timeouts.yaml @@ -313,7 +313,7 @@ tutorials/technology_demonstrations/hamiltonian_evolution/hamiltonian_evolution. tutorials/technology_demonstrations/hardware_aware_mcx/hardware_aware_mcx.ipynb: 56 tutorials/technology_demonstrations/hardware_aware_mcx/hardware_aware_mcx_all_to_all.qmod: 36 tutorials/technology_demonstrations/hardware_aware_mcx/hardware_aware_mcx_linear.qmod: 44 -tutorials/technology_demonstrations/hhl/hhl.ipynb: 800 +tutorials/technology_demonstrations/hhl/hhl_example.ipynb: 800 tutorials/technology_demonstrations/oracle_generation/3sat_oracles.ipynb: 1800 tutorials/technology_demonstrations/qaoa/qaoa.ipynb: 450 tutorials/technology_demonstrations/qpe/qpe_for_grover_operator/qpe_for_grover_operator.ipynb: 1000 diff --git a/tutorials/technology_demonstrations/hhl/hhl.ipynb b/tutorials/technology_demonstrations/hhl/hhl_example.ipynb similarity index 100% rename from tutorials/technology_demonstrations/hhl/hhl.ipynb rename to tutorials/technology_demonstrations/hhl/hhl_example.ipynb From 45e10903db6d0eb39e1d22f1accf369b5f5f1f06 Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 10:40:24 +0200 Subject: [PATCH 05/32] Rename notebook: application option pricing --- ...{option_pricing.ipynb => application_option_pricing.ipynb} | 2 +- ...metadata.json => application_option_pricing.metadata.json} | 0 .../{option_pricing.qmod => application_option_pricing.qmod} | 0 ...json => application_option_pricing.synthesis_options.json} | 0 tests/resources/timeouts.yaml | 4 ++-- 5 files changed, 3 insertions(+), 3 deletions(-) rename built_in_apps/option_pricing/{option_pricing.ipynb => application_option_pricing.ipynb} (99%) rename built_in_apps/option_pricing/{option_pricing.metadata.json => application_option_pricing.metadata.json} (100%) rename built_in_apps/option_pricing/{option_pricing.qmod => application_option_pricing.qmod} (100%) rename built_in_apps/option_pricing/{option_pricing.synthesis_options.json => application_option_pricing.synthesis_options.json} (100%) diff --git a/built_in_apps/option_pricing/option_pricing.ipynb b/built_in_apps/option_pricing/application_option_pricing.ipynb similarity index 99% rename from built_in_apps/option_pricing/option_pricing.ipynb rename to built_in_apps/option_pricing/application_option_pricing.ipynb index ace23709e..762e4dff5 100644 --- a/built_in_apps/option_pricing/option_pricing.ipynb +++ b/built_in_apps/option_pricing/application_option_pricing.ipynb @@ -165,7 +165,7 @@ }, "outputs": [], "source": [ - "write_qmod(qmod, \"option_pricing\")" + "write_qmod(qmod, \"application_option_pricing\")" ] }, { diff --git a/built_in_apps/option_pricing/option_pricing.metadata.json b/built_in_apps/option_pricing/application_option_pricing.metadata.json similarity index 100% rename from built_in_apps/option_pricing/option_pricing.metadata.json rename to built_in_apps/option_pricing/application_option_pricing.metadata.json diff --git a/built_in_apps/option_pricing/option_pricing.qmod b/built_in_apps/option_pricing/application_option_pricing.qmod similarity index 100% rename from built_in_apps/option_pricing/option_pricing.qmod rename to built_in_apps/option_pricing/application_option_pricing.qmod diff --git a/built_in_apps/option_pricing/option_pricing.synthesis_options.json b/built_in_apps/option_pricing/application_option_pricing.synthesis_options.json similarity index 100% rename from built_in_apps/option_pricing/option_pricing.synthesis_options.json rename to built_in_apps/option_pricing/application_option_pricing.synthesis_options.json diff --git a/tests/resources/timeouts.yaml b/tests/resources/timeouts.yaml index 2aac246b0..84d0fe509 100644 --- a/tests/resources/timeouts.yaml +++ b/tests/resources/timeouts.yaml @@ -120,8 +120,8 @@ built_in_apps/chemistry/chemistry.ipynb: 48 built_in_apps/chemistry/chemistry.qmod: 48 built_in_apps/grover/grover.ipynb: 48 built_in_apps/grover/grover.qmod: 48 -built_in_apps/option_pricing/option_pricing.ipynb: 48 -built_in_apps/option_pricing/option_pricing.qmod: 48 +built_in_apps/option_pricing/application_option_pricing.ipynb: 48 +built_in_apps/option_pricing/application_option_pricing.qmod: 48 community/QClass_2024/Assignments/HW1_QClass2024.ipynb: 200 community/QClass_2024/Assignments/HW2_QClass2024.ipynb: 200 community/QClass_2024/Assignments/Preparation_for_Week2_Git_GitHub.ipynb: 20 From 27b85c2e6142f6557fdcabbad12e40e6d513921a Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 10:44:32 +0200 Subject: [PATCH 06/32] Rename notebook: example prepare state --- ...metadata.json => example_prepare_amplitudes.metadata.json} | 0 ...repare_amplitudes.qmod => example_prepare_amplitudes.qmod} | 0 ...json => example_prepare_amplitudes.synthesis_options.json} | 0 ...tate.metadata.json => example_prepare_state.metadata.json} | 0 .../{prepare_state.qmod => example_prepare_state.qmod} | 0 ...ions.json => example_prepare_state.synthesis_options.json} | 0 .../prepare_state_and_amplitudes.ipynb | 4 ++-- tests/resources/timeouts.yaml | 4 ++-- 8 files changed, 4 insertions(+), 4 deletions(-) rename functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/{prepare_amplitudes.metadata.json => example_prepare_amplitudes.metadata.json} (100%) rename functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/{prepare_amplitudes.qmod => example_prepare_amplitudes.qmod} (100%) rename functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/{prepare_amplitudes.synthesis_options.json => example_prepare_amplitudes.synthesis_options.json} (100%) rename functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/{prepare_state.metadata.json => example_prepare_state.metadata.json} (100%) rename functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/{prepare_state.qmod => example_prepare_state.qmod} (100%) rename functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/{prepare_state.synthesis_options.json => example_prepare_state.synthesis_options.json} (100%) diff --git a/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_amplitudes.metadata.json b/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_amplitudes.metadata.json similarity index 100% rename from functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_amplitudes.metadata.json rename to functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_amplitudes.metadata.json diff --git a/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_amplitudes.qmod b/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_amplitudes.qmod similarity index 100% rename from functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_amplitudes.qmod rename to functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_amplitudes.qmod diff --git a/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_amplitudes.synthesis_options.json b/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_amplitudes.synthesis_options.json similarity index 100% rename from functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_amplitudes.synthesis_options.json rename to functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_amplitudes.synthesis_options.json diff --git a/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state.metadata.json b/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_state.metadata.json similarity index 100% rename from functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state.metadata.json rename to functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_state.metadata.json diff --git a/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state.qmod b/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_state.qmod similarity index 100% rename from functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state.qmod rename to functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_state.qmod diff --git a/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state.synthesis_options.json b/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_state.synthesis_options.json similarity index 100% rename from functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state.synthesis_options.json rename to functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_state.synthesis_options.json diff --git a/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state_and_amplitudes.ipynb b/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state_and_amplitudes.ipynb index 749d2aad1..e8f3788b1 100644 --- a/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state_and_amplitudes.ipynb +++ b/functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state_and_amplitudes.ipynb @@ -129,7 +129,7 @@ " prepare_state(probabilities=probabilities, bound=0.01, out=x)\n", "\n", "\n", - "qmod = create_model(main, out_file=\"prepare_state\")" + "qmod = create_model(main, out_file=\"example_prepare_state\")" ] }, { @@ -211,7 +211,7 @@ " num_shots=1,\n", " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator_statevector\"),\n", ")\n", - "write_qmod(qmod, \"prepare_amplitudes\", decimal_precision=15)" + "write_qmod(qmod, \"example_prepare_amplitudes\", decimal_precision=15)" ] }, { diff --git a/tests/resources/timeouts.yaml b/tests/resources/timeouts.yaml index 84d0fe509..eb8ed1621 100644 --- a/tests/resources/timeouts.yaml +++ b/tests/resources/timeouts.yaml @@ -223,8 +223,8 @@ functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/qdrift/ functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/qdrift/qdrift.qmod: 10 functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/suzuki_trotter/suzuki_trotter.ipynb: 20 functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/suzuki_trotter/suzuki_trotter.qmod: 10 -functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_amplitudes.qmod: 10 -functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state.qmod: 10 +functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_amplitudes.qmod: 10 +functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/example_prepare_state.qmod: 10 functions/qmod_library_reference/qmod_core_library/prepare_state_and_amplitudes/prepare_state_and_amplitudes.ipynb: 20 functions/qmod_library_reference/qmod_core_library/standard_gates/CRX.qmod: 10 functions/qmod_library_reference/qmod_core_library/standard_gates/CX.qmod: 10 From 9d949dfe04e165d024355818cac9b024d333d422 Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 11:09:41 +0200 Subject: [PATCH 07/32] Fix rename --- tests/resources/timeouts.yaml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/resources/timeouts.yaml b/tests/resources/timeouts.yaml index eb8ed1621..133b3afba 100644 --- a/tests/resources/timeouts.yaml +++ b/tests/resources/timeouts.yaml @@ -217,8 +217,8 @@ functions/qmod_library_reference/classiq_open_library/special_state_preparations functions/qmod_library_reference/classiq_open_library/variational_data_encoding/encode_in_angle.qmod: 10 functions/qmod_library_reference/classiq_open_library/variational_data_encoding/encode_on_bloch.qmod: 10 functions/qmod_library_reference/classiq_open_library/variational_data_encoding/variational_data_encoding.ipynb: 20 -functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/exponentiation.ipynb: 20 -functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/exponentiation.qmod: 10 +functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/hamiltonian_evolution_exponentiation.ipynb: 20 +functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/exponentiation/hamiltonian_evolution_exponentiation.qmod: 10 functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/qdrift/qdrift.ipynb: 20 functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/qdrift/qdrift.qmod: 10 functions/qmod_library_reference/qmod_core_library/hamiltonian_evolution/suzuki_trotter/suzuki_trotter.ipynb: 20 From 4049cf44cc4e0b9df3748a3606273cb23bd14152 Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 11:28:55 +0200 Subject: [PATCH 08/32] Add test for unique notebook names --- tests/internal/test_notebook_unique_name.py | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) create mode 100644 tests/internal/test_notebook_unique_name.py diff --git a/tests/internal/test_notebook_unique_name.py b/tests/internal/test_notebook_unique_name.py new file mode 100644 index 000000000..d73e8ab39 --- /dev/null +++ b/tests/internal/test_notebook_unique_name.py @@ -0,0 +1,19 @@ +from pathlib import Path + + +ROOT = Path(__file__).parents[2] + + +def test_unique_notebook_name(): + all_notebooks = ROOT.rglob("*.ipynb") + assert _are_all_base_names_unique(all_notebooks) + + +def test_unique_qmod_name(): + all_qmods = ROOT.rglob("*.qmod") + assert _are_all_base_names_unique(all_qmods) + + +def _are_all_base_names_unique(files: Iterable[Path]) -> bool: + base_names = [f.name for f in files] + return len(base_names) == len(set(base_names)) From 08ed7ee33e33360bd60ea45e2b83831c1c7b42e1 Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 11:30:02 +0200 Subject: [PATCH 09/32] Update timeouts to be relative paths --- tests/resources/timeouts.yaml | 658 +++++++++++++++++----------------- 1 file changed, 329 insertions(+), 329 deletions(-) diff --git a/tests/resources/timeouts.yaml b/tests/resources/timeouts.yaml index 133b3afba..1305243ce 100644 --- a/tests/resources/timeouts.yaml +++ b/tests/resources/timeouts.yaml @@ -1,329 +1,329 @@ -algorithms/dqi/dqi_max_xorsat.ipynb: 200 -algorithms/dqi/dqi_max_xorsat.qmod: 200 -algorithms/algebraic/discrete_log/discrete_log.ipynb: 600 -algorithms/algebraic/discrete_log/discrete_log.qmod: 300 -algorithms/algebraic/discrete_log/discrete_log_large.qmod: 600 -algorithms/algebraic/hidden_shift/hidden_shift.ipynb: 272 -algorithms/algebraic/hidden_shift/hidden_shift_complex.qmod: 100 -algorithms/algebraic/hidden_shift/hidden_shift_no_dual.qmod: 92 -algorithms/algebraic/hidden_shift/hidden_shift_simple.qmod: 20 -algorithms/algebraic/shor/doubly_controlled_modular_adder.qmod: 100 -algorithms/algebraic/shor/shor.ipynb: 104 -algorithms/algebraic/shor/shor.qmod: 88 -algorithms/algebraic/shor/shor_modular_exponentiation.ipynb: 300 -algorithms/algebraic/shor/shor_modular_exponentiation.qmod: 300 -algorithms/amplitude_estimation/qmc_user_defined/qmc_user_defined.ipynb: 176 -algorithms/amplitude_estimation/qmc_user_defined/qmc_user_defined.qmod: 136 -algorithms/amplitude_estimation/quantum_counting/quantum_counting.ipynb: 300 -algorithms/amplitude_estimation/quantum_counting/quantum_counting_iqae.qmod: 200 -algorithms/amplitude_estimation/quantum_counting/quantum_counting_qpe.qmod: 200 -algorithms/bernstein_vazirani/bernstein_vazirani.ipynb: 32 -algorithms/bernstein_vazirani/bernstein_vazirani_example.qmod: 32 -algorithms/deutsch_jozsa/complex_deutsch_jozsa.qmod: 32 -algorithms/deutsch_jozsa/deutsch_jozsa.ipynb: 48 -algorithms/deutsch_jozsa/simple_deutsch_jozsa.qmod: 16 -algorithms/differential_equations/discrete_poisson_solver/discrete_poisson_solver.ipynb: 300 -algorithms/differential_equations/discrete_poisson_solver/discrete_poisson_solver.qmod: 300 -algorithms/differential_equations/hhl_jungle/hhl_jungle.ipynb: 450 -algorithms/grover/3_sat_grover/3_sat_grover.ipynb: 36 -algorithms/grover/3_sat_grover/3_sat_grover.qmod: 48 -algorithms/grover/3_sat_grover/3_sat_grover_large.qmod: 10 -algorithms/grover/grover_max_cut/grover_max_cut.ipynb: 220 -algorithms/grover/grover_max_cut/grover_max_cut.qmod: 188 -algorithms/hhl/hhl/hhl.ipynb: 312 -algorithms/hhl/hhl/hhl_exact.qmod: 100 -algorithms/hhl/hhl/hhl_trotter.qmod: 100 -algorithms/oblivious_amplitude_amplification/oblivious_amplitude_amplification.ipynb: 20 -algorithms/oblivious_amplitude_amplification/oblivious_amplitude_amplification.qmod: 10 -algorithms/qml/hybrid_qnn/hybrid_qnn_for_subset_majority.ipynb: 120 -algorithms/qml/qgan/qgan_bars_and_strips.ipynb: 360 -algorithms/qml/qsvm/qsvm.ipynb: 204 -algorithms/qml/qsvm/qsvm.qmod: 104 -algorithms/qml/qsvm_pauli_feature_map/qsvm_pauli_feature_map.ipynb: 68 -algorithms/qml/qsvm_pauli_feature_map/qsvm_pauli_feature_map.qmod: 60 -algorithms/qml/quantum_autoencoder/quantum_autoencoder.ipynb: 120 -algorithms/qpe/qpe_for_matrix/qpe_for_matrix.ipynb: 748 -algorithms/qpe/qpe_for_matrix/qpe_for_matrix.qmod: 760 -algorithms/qsvt/qsvt_fixed_point_amplitude_amplification/qsvt_fixed_point_amplitude_amplification.ipynb: 376 -algorithms/qsvt/qsvt_fixed_point_amplitude_amplification/qsvt_fixed_point_amplitude_amplification.qmod: 340 -algorithms/qsvt/qsvt_matrix_inversion/qsvt_matrix_inversion.ipynb: 180 -algorithms/qsvt/qsvt_matrix_inversion/qsvt_matrix_inversion.qmod: 156 -algorithms/simon/simon.ipynb: 40 -algorithms/simon/simon_example.qmod: 30 -algorithms/simon/simon_shallow_example.qmod: 20 -algorithms/swap_test/swap_test.ipynb: 40 -algorithms/swap_test/swap_test.qmod: 40 -algorithms/vqls/lcu_vqls/vqls_with_lcu.ipynb: 1200 -algorithms/vqls/lcu_vqls/vqls_with_lcu.qmod: 20 -applications/benchmarking/quantum_volume/quantum_volume.ipynb: 516 -applications/benchmarking/randomized_benchmarking/randomized_benchmarking.ipynb: 60 -applications/chemistry/molecular_energy_curve/molecular_energy_curve.ipynb: 1200 -applications/chemistry/molecular_energy_curve/molecular_energy_curve.qmod: 90 -applications/chemistry/molecule_eigensolver/molecule_eigensolver.ipynb: 84 -applications/chemistry/molecule_eigensolver/molecule_eigensolver.qmod: 60 -applications/chemistry/protein_folding/protein_folding.ipynb: 240 -applications/chemistry/protein_folding/protein_folding.qmod: 240 -applications/chemistry/qpe_for_molecules/qpe_for_molecules.ipynb: 1332 -applications/chemistry/qpe_for_molecules/qpe_for_molecules.qmod: 1292 -applications/chemistry/second_quantized_hamiltonian/second_quantized_hamiltonian.ipynb: 44 -applications/chemistry/second_quantized_hamiltonian/second_quantized_hamiltonian.qmod: 40 -applications/cybersecurity/link_monitoring/link_monitoring.ipynb: 76 -applications/cybersecurity/link_monitoring/link_monitoring.qmod: 88 -applications/cybersecurity/patching_management/patch_min_vertex_cover.qmod: 52 -applications/cybersecurity/patching_management/patching_managment.ipynb: 36 -applications/cybersecurity/whitebox_fuzzing/whitebox_fuzzing.ipynb: 720 -applications/cybersecurity/whitebox_fuzzing/whitebox_fuzzing.qmod: 720 -applications/finance/credit_card_fraud/credit_card_fraud.ipynb: 1084 -applications/finance/credit_card_fraud/credit_card_fraud.qmod: 1064 -applications/finance/option_pricing/option_pricing.ipynb: 140 -applications/finance/option_pricing/option_pricing.qmod: 140 -applications/finance/portfolio_optimization/portfolio_optimization.ipynb: 96 -applications/finance/portfolio_optimization/portfolio_optimization.qmod: 112 -applications/logistics/facility_location/facility_location.ipynb: 1656 -applications/logistics/facility_location/facility_location.qmod: 1592 -applications/logistics/task_scheduling_problem/task_scheduling_problem.ipynb: 840 -applications/logistics/task_scheduling_problem/task_scheduling_problem.qmod: 64 -applications/logistics/task_scheduling_problem/task_scheduling_problem_large.qmod: 688 -applications/logistics/traveling_salesman_problem/traveling_saleman_problem.qmod: 1088 -applications/logistics/traveling_salesman_problem/traveling_salesman_problem.ipynb: 1068 -applications/optimization/electric_grid_optimization/electric_grid_optimization.ipynb: 996 -applications/optimization/electric_grid_optimization/electric_grid_optimization.qmod: 1152 -applications/optimization/integer_linear_programming/integer_linear_programming.ipynb: 296 -applications/optimization/integer_linear_programming/integer_linear_programming.qmod: 340 -applications/optimization/knapsack_binary/knapsack_binary.ipynb: 72 -applications/optimization/knapsack_binary/knapsack_binary.qmod: 52 -applications/optimization/knapsack_integer/knapsack_integer.ipynb: 116 -applications/optimization/knapsack_integer/knapsack_integer.qmod: 116 -applications/optimization/max_clique/max_clique.ipynb: 276 -applications/optimization/max_clique/max_clique.qmod: 260 -applications/optimization/max_cut/max_cut.ipynb: 36 -applications/optimization/max_cut/max_cut.qmod: 32 -applications/optimization/max_independent_set/max_independent_set.ipynb: 60 -applications/optimization/max_independent_set/max_independent_set.qmod: 64 -applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.ipynb: 1028 -applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.qmod: 1008 -applications/optimization/max_k_vertex_cover/max_k_vertex_cover.ipynb: 184 -applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod: 148 -applications/optimization/min_graph_coloring/min_graph_coloring.ipynb: 1800 -applications/optimization/min_graph_coloring/min_graph_coloring.qmod: 1800 -applications/optimization/minimum_dominating_set/minimum_dominating_set.ipynb: 620 -applications/optimization/minimum_dominating_set/minimum_dominating_set.qmod: 588 -applications/optimization/rectangles_packing/rectangles_packing.qmod: 1800 -applications/optimization/rectangles_packing/rectangles_packing_grid.ipynb: 1800 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+max_k_vertex_cover.qmod: 148 +maximum_float_example.qmod: 10 +maximum_integer_example.qmod: 10 +mcx.ipynb: 236 +mcx_10_ctrl_depth.qmod: 10 +mcx_14_ctrl_cx.qmod: 28 +mcx_14_ctrl_depth.qmod: 28 +mcx_14_ctrl_hardware.qmod: 724 +mcx_50_ctrl.qmod: 140 +mcx_example.ipynb: 20 +mcx_example.qmod: 10 +min_graph_coloring.ipynb: 1800 +min_graph_coloring.qmod: 1800 +minimum_2vars_example.qmod: 10 +minimum_dominating_set.ipynb: 620 +minimum_dominating_set.qmod: 588 +modular_exp_example.ipynb: 100 +modular_exp_example.qmod: 100 +modulo_example.ipynb: 20 +modulo_example.qmod: 10 +Mohammadreza_Khodajou_Masouleh_HW3_QClass2024.ipynb: 30 +molecular_energy_curve.ipynb: 1200 +molecular_energy_curve.qmod: 90 +molecule_eigensolver.ipynb: 84 +molecule_eigensolver.qmod: 60 +multiplication.ipynb: 20 +multiplication_2vars_example.qmod: 10 +multiplication_float_example.qmod: 10 +negation_example.ipynb: 20 +negation_example.qmod: 10 +Noah_Nzeki_William_HW3_VQE.ipynb: 30 +oblivious_amplitude_amplification.ipynb: 20 +oblivious_amplitude_amplification.qmod: 10 +optimize.ipynb: 20 +optimize.qmod: 10 +option_pricing.ipynb: 140 +option_pricing.qmod: 140 +Otmane_Ainelkitane_HW3_VQE.ipynb: 30 +part1_arithmetic.ipynb: 30 +part2_state_preparation.ipynb: 30 +part3_deutsch_jozsa.ipynb: 20 +part4_ghz_state.ipynb: 60 +part5_grover.ipynb: 60 +patch_min_vertex_cover.qmod: 52 +patching_managment.ipynb: 36 +PHASE.qmod: 10 +phase_kickback.ipynb: 1000 +phase_kickback.qmod: 1000 +portfolio_optimization.ipynb: 96 +portfolio_optimization.qmod: 112 +Preparation_for_Week2_Git_GitHub.ipynb: 20 +prepare_bell_state.ipynb: 20 +prepare_bell_state.qmod: 10 +prepare_exponential_state.ipynb: 20 +prepare_exponential_state.qmod: 10 +prepare_ghz_state.ipynb: 20 +prepare_ghz_state.qmod: 10 +prepare_int.ipynb: 20 +prepare_int.qmod: 10 +prepare_partial_uniform_state.ipynb: 20 +prepare_state.ipynb: 20 +prepare_state.qmod: 20 +prepare_state_and_amplitudes.ipynb: 20 +prepare_uniform_interval_state.qmod: 10 +prepare_uniform_trimmed_state.qmod: 10 +Priyabrata_Bag_HW4.ipynb: 40 +protein_folding.ipynb: 240 +protein_folding.qmod: 240 +qaoa.ipynb: 450 +qct_qst.ipynb: 30 +qct_qst_type1.qmod: 20 +qct_qst_type2.qmod: 20 +qct_type2.qmod: 20 +qdrift.ipynb: 20 +qdrift.qmod: 10 +qft.ipynb: 20 +qft.qmod: 10 +qgan_bars_and_strips.ipynb: 360 +qmc_user_defined.ipynb: 176 +qmc_user_defined.qmod: 136 +qml_with_classiq_guide.ipynb: 300 +QMOD_Workshop_Part_1.ipynb: 400 +QMOD_Workshop_Part_2.ipynb: 80 +QMOD_Workshop_Part_3.ipynb: 80 +qnn_with_pytorch.qmod: 300 +qpe.ipynb: 20 +qpe.qmod: 10 +qpe_flexible.qmod: 10 +qpe_for_grover_operator.ipynb: 1000 +qpe_for_matrix.ipynb: 748 +qpe_for_matrix.qmod: 760 +qpe_for_molecules.ipynb: 1332 +qpe_for_molecules.qmod: 1292 +qpe_for_unitary_matrix.ipynb: 600 +qst_type2.qmod: 20 +qsvm.ipynb: 204 +qsvm.qmod: 104 +qsvm_pauli_feature_map.ipynb: 68 +qsvm_pauli_feature_map.qmod: 60 +qsvt.ipynb: 20 +qsvt.qmod: 10 +qsvt_fixed_point_amplitude_amplification.ipynb: 376 +qsvt_fixed_point_amplitude_amplification.qmod: 340 +qsvt_matrix_inversion.ipynb: 180 +qsvt_matrix_inversion.qmod: 156 +quantum_autoencoder.ipynb: 120 +quantum_counting.ipynb: 300 +quantum_counting_iqae.qmod: 200 +quantum_counting_qpe.qmod: 200 +quantum_operations.ipynb: 20 +quantum_operations.qmod: 10 +quantum_variables_and_functions.ipynb: 20 +quantum_variables_and_functions.qmod: 10 +quantum_volume.ipynb: 516 +quantum_walk_circle.qmod: 25 +quantum_walk_circle_balanced_coin.qmod: 25 +quantum_walk_hypercube.qmod: 30 +R.qmod: 10 +rainbow_options_bruteforce_method.ipynb: 1000 +rainbow_options_bruteforce_method.qmod: 1000 +rainbow_options_direct_method.ipynb: 1000 +rainbow_options_direct_method.qmod: 1000 +rainbow_options_integration_method.ipynb: 1000 +rainbow_options_integration_method.qmod: 1000 +randomized_benchmarking.ipynb: 60 +rectangles_packing.qmod: 1800 +rectangles_packing_grid.ipynb: 1800 +RZ.qmod: 10 +RZZ.qmod: 10 +Samyak_Jain_HW3_VQE.ipynb: 30 +second_quantized_hamiltonian.ipynb: 44 +second_quantized_hamiltonian.qmod: 40 +Session1.ipynb: 20 +set_cover.ipynb: 1440 +set_cover.qmod: 1216 +set_partition.ipynb: 152 +set_partition.qmod: 160 +shor.ipynb: 104 +shor.qmod: 88 +shor_modular_exponentiation.ipynb: 300 +shor_modular_exponentiation.qmod: 300 +simon.ipynb: 40 +simon_example.qmod: 30 +simon_shallow_example.qmod: 20 +simple_deutsch_jozsa.qmod: 16 +standard_gates.ipynb: 20 +subtraction_2vars_example.qmod: 10 +subtraction_example.ipynb: 20 +subtraction_float_example.qmod: 10 +superposition.ipynb: 20 +suzuki_trotter.ipynb: 20 +suzuki_trotter.qmod: 10 +SWAP.qmod: 10 +swap_test.ipynb: 40 +swap_test.qmod: 40 +tanh.qmod: 20 +task_scheduling_problem.ipynb: 840 +task_scheduling_problem.qmod: 64 +task_scheduling_problem_large.qmod: 688 +traveling_saleman_problem.qmod: 1088 +traveling_salesman_problem.ipynb: 1068 +U.qmod: 10 +unitary.ipynb: 20 +unitary.qmod: 10 +variational_data_encoding.ipynb: 20 +vqe.ipynb: 20 +vqe_primitive.qmod: 300 +vqe_primitives.qmod: 10 +vqls_with_lcu.ipynb: 1200 +vqls_with_lcu.qmod: 20 +week1_QClass_workshop_with_sol.ipynb: 20 +whats_classiq.ipynb: 400 +whats_classiq.qmod: 1000 +whitebox_fuzzing.ipynb: 720 +whitebox_fuzzing.qmod: 720 +X.qmod: 10 +Yasir_Mansour_HW3_VQE.ipynb: 30 +Yasir_Mansour_HW4_molecule_eigensolver.ipynb: 600 From 0ca9a5b6c7811a40db8ff25e33ede3a086bf8a85 Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 11:32:59 +0200 Subject: [PATCH 10/32] Update test to test for relative paths --- tests/internal/test_notebook_timeouts.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/tests/internal/test_notebook_timeouts.py b/tests/internal/test_notebook_timeouts.py index 70aa64dd5..75a4dd125 100644 --- a/tests/internal/test_notebook_timeouts.py +++ b/tests/internal/test_notebook_timeouts.py @@ -39,7 +39,7 @@ def test_notebook_timeouts(timeouts: dict[str, float]) -> None: relative_path = file_path.relative_to(ROOT) if _can_skip(relative_path): continue - if str(relative_path) not in timeouts: + if relative_path.name not in timeouts: missing_notebooks.append(file_path) assert ( @@ -50,8 +50,7 @@ def test_notebook_timeouts(timeouts: dict[str, float]) -> None: def test_unused_timeouts(timeouts: dict[str, float]) -> None: unused_timeouts: list[str] = [] for notebook in timeouts: - full_notebook_path = ROOT / notebook - if not full_notebook_path.exists(): + if not list(ROOT.rglob(notebook)): unused_timeouts.append(notebook) assert ( From 2c2a91a5c2ddc56d3f4f7928878426d26bdedb9f Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 11:37:23 +0200 Subject: [PATCH 11/32] Fix --- tests/internal/test_notebook_unique_name.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/internal/test_notebook_unique_name.py b/tests/internal/test_notebook_unique_name.py index d73e8ab39..6e5f812ed 100644 --- a/tests/internal/test_notebook_unique_name.py +++ b/tests/internal/test_notebook_unique_name.py @@ -1,5 +1,5 @@ from pathlib import Path - +from typing import Iterable ROOT = Path(__file__).parents[2] From 9a39da79d853fd0b3b5c796f6adc590e49258f82 Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 11:43:46 +0200 Subject: [PATCH 12/32] Update error message --- tests/internal/test_notebook_unique_name.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/tests/internal/test_notebook_unique_name.py b/tests/internal/test_notebook_unique_name.py index 6e5f812ed..00934ff47 100644 --- a/tests/internal/test_notebook_unique_name.py +++ b/tests/internal/test_notebook_unique_name.py @@ -1,3 +1,4 @@ +from collections import Counter from pathlib import Path from typing import Iterable @@ -6,14 +7,14 @@ def test_unique_notebook_name(): all_notebooks = ROOT.rglob("*.ipynb") - assert _are_all_base_names_unique(all_notebooks) + assert not duplicate_base_names(all_notebooks) def test_unique_qmod_name(): all_qmods = ROOT.rglob("*.qmod") - assert _are_all_base_names_unique(all_qmods) + assert not duplicate_base_names(all_qmods) -def _are_all_base_names_unique(files: Iterable[Path]) -> bool: +def duplicate_base_names(files: Iterable[Path]) -> bool: base_names = [f.name for f in files] - return len(base_names) == len(set(base_names)) + return [name for name, count in Counter(base_names).items() if count > 1] From b977aef99e04e51357cf905baeaf3970039be472 Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 12 Dec 2024 12:07:32 +0200 Subject: [PATCH 13/32] Allow functions qmods to have duplicates --- tests/internal/test_notebook_unique_name.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/tests/internal/test_notebook_unique_name.py b/tests/internal/test_notebook_unique_name.py index 00934ff47..5c58620a5 100644 --- a/tests/internal/test_notebook_unique_name.py +++ b/tests/internal/test_notebook_unique_name.py @@ -12,7 +12,9 @@ def test_unique_notebook_name(): def test_unique_qmod_name(): all_qmods = ROOT.rglob("*.qmod") - assert not duplicate_base_names(all_qmods) + # exclude `functions/` + qmods = [path for path in all_qmods if "functions" not in path.parts] + assert not duplicate_base_names(qmods) def duplicate_base_names(files: Iterable[Path]) -> bool: From 4954af6c9a1ac5ffa4f0731099d298bd8acefa3c Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Sun, 15 Dec 2024 11:54:55 +0200 Subject: [PATCH 14/32] changed dqi notebook name --- algorithms/dqi/dqi_max_xorsat.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/algorithms/dqi/dqi_max_xorsat.ipynb b/algorithms/dqi/dqi_max_xorsat.ipynb index 28032b698..fa72d8f14 100644 --- a/algorithms/dqi/dqi_max_xorsat.ipynb +++ b/algorithms/dqi/dqi_max_xorsat.ipynb @@ -5,7 +5,7 @@ "id": "9de82aaa-b542-49fa-810c-f008a28a4133", "metadata": {}, "source": [ - "# Optimizing max-XORSAT using the Decoded Quantum Interferometry algorithm" + "# Decoded Quantum Interferometry Algorithm" ] }, { From 8a3c369503ba902d7b5ccb4cca3964d142cc5e78 Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Sun, 8 Dec 2024 12:20:11 +0200 Subject: [PATCH 15/32] refactored set_partition, max_clique, ilp, ising --- .../integer_linear_programming.ipynb | 406 ++---- .../integer_linear_programming.qmod | 1093 +---------------- ..._linear_programming.synthesis_options.json | 44 +- .../optimization/max_clique/max_clique.ipynb | 449 +++---- .../optimization/max_clique/max_clique.qmod | 771 +----------- .../max_clique.synthesis_options.json | 44 +- .../set_partition/set_partition.ipynb | 439 ++----- .../set_partition/set_partition.qmod | 732 +---------- .../set_partition.synthesis_options.json | 44 +- .../ising_model/ising_model.ipynb | 312 ++--- .../ising_model/ising_model.qmod | 170 +-- .../ising_model.synthesis_options.json | 44 +- 12 files changed, 804 insertions(+), 3744 deletions(-) diff --git a/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb b/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb index 62a5e07f8..1ee489202 100644 --- a/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb +++ b/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb @@ -45,28 +45,6 @@ "We go through the steps of solving the problem with the Classiq platform, using QAOA algorithm [[2](#QAOA)]. The solution is based on defining a pyomo model for the optimization problem we would like to solve." ] }, - { - "cell_type": "code", - "execution_count": 1, - "id": "49a9588b-e79e-4813-b7c5-ac068d7b930c", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:03.709227Z", - "iopub.status.busy": "2024-05-07T16:03:03.708726Z", - "iopub.status.idle": "2024-05-07T16:03:04.242888Z", - "shell.execute_reply": "2024-05-07T16:03:04.242261Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "import networkx as nx\n", - "import numpy as np\n", - "import pyomo.core as pyo\n", - "from IPython.display import Markdown, display\n", - "from matplotlib import pyplot as plt" - ] - }, { "cell_type": "markdown", "id": "8517ef73-faf6-4fd8-9db8-4088551398e0", @@ -79,14 +57,12 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "48889b21-557b-481c-80c5-3c0b5c91adb6", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:04.245996Z", - "iopub.status.busy": "2024-05-07T16:03:04.245397Z", - "iopub.status.idle": "2024-05-07T16:03:04.250669Z", - "shell.execute_reply": "2024-05-07T16:03:04.250107Z" + "ExecuteTime": { + "end_time": "2024-10-27T14:14:26.846158Z", + "start_time": "2024-10-27T14:14:26.840633Z" }, "tags": [] }, @@ -125,14 +101,12 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "6e5295f4-7ba6-4ff6-8782-1c4c2c7f85e4", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:04.253099Z", - "iopub.status.busy": "2024-05-07T16:03:04.252586Z", - "iopub.status.idle": "2024-05-07T16:03:04.257612Z", - "shell.execute_reply": "2024-05-07T16:03:04.257011Z" + "ExecuteTime": { + "end_time": "2024-10-27T14:14:27.078661Z", + "start_time": "2024-10-27T14:14:27.071956Z" } }, "outputs": [], @@ -147,17 +121,12 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "345330b2-9c14-41f6-b4ba-e11fb9ca1565", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:04.259676Z", - "iopub.status.busy": "2024-05-07T16:03:04.259506Z", - "iopub.status.idle": "2024-05-07T16:03:04.264367Z", - "shell.execute_reply": "2024-05-07T16:03:04.263732Z" - }, - "jupyter": { - "outputs_hidden": true + "ExecuteTime": { + "end_time": "2024-10-27T14:14:27.096276Z", + "start_time": "2024-10-27T14:14:27.091814Z" }, "tags": [] }, @@ -210,134 +179,31 @@ "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):" + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the qaoa algorithm, with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "816b468f-a59f-4f2f-8337-4a9d66548425", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:04.266876Z", - "iopub.status.busy": "2024-05-07T16:03:04.266379Z", - "iopub.status.idle": "2024-05-07T16:03:06.767843Z", - "shell.execute_reply": "2024-05-07T16:03:06.767070Z" - }, "tags": [] }, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "qaoa_config = QAOAConfig(num_layers=3)" - ] - }, - { - "cell_type": "markdown", - "id": "db34d5ac-6877-4285-8dec-7bf7b37eb783", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "e41d0dd3-4135-4330-9ba3-c1b30c339a74", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:06.773025Z", - "iopub.status.busy": "2024-05-07T16:03:06.771615Z", - "iopub.status.idle": "2024-05-07T16:03:06.776787Z", - "shell.execute_reply": "2024-05-07T16:03:06.776135Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "optimizer_config = OptimizerConfig(max_iteration=90, alpha_cvar=0.7)" - ] - }, - { - "cell_type": "markdown", - "id": "214d6051-43b8-4b9d-8454-f9cdb62b4cf0", - "metadata": {}, - "source": [ - "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "0243019c-6fc3-435f-b6ec-8b4355d6660c", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:06.781190Z", - "iopub.status.busy": "2024-05-07T16:03:06.780012Z", - "iopub.status.idle": "2024-05-07T16:03:09.997939Z", - "shell.execute_reply": "2024-05-07T16:03:09.997174Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=ilp_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "1fcc3812-c9d0-421c-84bb-38047297b33f", - "metadata": {}, - "source": [ - "We also set the quantum backend we want to execute on:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "53bc041f-065c-44d2-b220-dafd9d0504ac", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:10.003163Z", - "iopub.status.busy": "2024-05-07T16:03:10.001962Z", - "iopub.status.idle": "2024-05-07T16:03:10.044489Z", - "shell.execute_reply": "2024-05-07T16:03:10.043733Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", + "combi = CombinatorialProblem(pyo_model=ilp_model, num_layers=3, penalty_factor=10)\n", "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", - ")" + "qmod = combi.get_model()" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 5, "id": "62ec28b3-cb49-411a-8c4a-8004fff6c105", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:10.050654Z", - "iopub.status.busy": "2024-05-07T16:03:10.049516Z", - "iopub.status.idle": "2024-05-07T16:03:10.111490Z", - "shell.execute_reply": "2024-05-07T16:03:10.110833Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "write_qmod(qmod, \"integer_linear_programming\")" @@ -355,15 +221,9 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 6, "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:10.116541Z", - "iopub.status.busy": "2024-05-07T16:03:10.115462Z", - "iopub.status.idle": "2024-05-07T16:03:15.845871Z", - "shell.execute_reply": "2024-05-07T16:03:15.845158Z" - }, "pycharm": { "name": "#%%\n" }, @@ -374,39 +234,58 @@ "name": "stdout", "output_type": "stream", "text": [ - "Opening: https://platform.classiq.io/circuit/183bcd6c-83c8-4610-828f-d7cd40f9fb85?version=0.41.0.dev39%2B79c8fd0855\n" + "Opening: https://nightly.platform.classiq.io/circuit/ae0c345f-e27c-496d-a3d8-a7eab1675d72?version=0.61.0.dev7\n" ] } ], "source": [ - "qprog = synthesize(qmod)\n", + "qprog = combi.get_qprog()\n", "show(qprog)" ] }, { "cell_type": "markdown", - "id": "80238cf9-d7bd-46e5-9d48-b7cf23a6b304", + "id": "b119464b-9d46-4ea0-ba4a-1734f3e0e3e5", "metadata": {}, "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" + "We also set the quantum backend we want to execute on:" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 7, + "id": "7d188c69-21d1-4afe-86b1-46229e91a01e", + "metadata": {}, + "outputs": [], + "source": [ + "from classiq.execution import *\n", + "\n", + "execution_preferences = ExecutionPreferences(\n", + " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\"),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "07621d7c-0e54-4adb-9c47-8fd99a346e29", + "metadata": {}, + "source": [ + "We now solve the problem by calling the `optimize` method of the `CombinatorialProblem` object. For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`maxiter`) and the $\\alpha$-parameter (`quantile`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, "id": "62d12d20-1c80-4a9e-bb6b-b1fddc6cbe40", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:15.848412Z", - "iopub.status.busy": "2024-05-07T16:03:15.848000Z", - "iopub.status.idle": "2024-05-07T16:03:33.645387Z", - "shell.execute_reply": "2024-05-07T16:03:33.644679Z" - }, "tags": [] }, "outputs": [], "source": [ - "result = execute(qprog).result_value()" + "cost_values = []\n", + "optimized_params = combi.optimize(\n", + " execution_preferences, maxiter=90, cost_trace=cost_values, quantile=0.7\n", + ")" ] }, { @@ -419,33 +298,41 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 9, "id": "02454398-b229-403c-824a-b1eb539fbc1f", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:33.648272Z", - "iopub.status.busy": "2024-05-07T16:03:33.647738Z", - "iopub.status.idle": "2024-05-07T16:03:33.672693Z", - "shell.execute_reply": "2024-05-07T16:03:33.672075Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/jpeg": 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", "text/plain": [ - "" + "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 12, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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dQgghhGQ1FDuEEEIIyWoodgghhBCS1VDsEEIIISSrodghhBBCSFZDsUMIIYSQrIZihxBCCCFZDcUOISSr6XJ5030IhJA0Q7FDCMlaVu1uxuS738GfFm9O96EQQtIIxQ4hJGtZt68Fbq/AV7sOpftQCCFphGKHEJK1uD0+AIDHJ9J8JISQdEKxQwjJWqTIcXt9aT4SQkg6odghhGQtroDIcXvp7BCSy1DsEEKyFk9A5Hjo7BCS01DsEEKyFjedHUIIKHYIIVmMLGN5fHR2CMllKHYIIVmLLGPR2SEkt6HYIYRkLcEyFp0dQnIZih1CSNbiVgLKdHYIyWUodgghWYubmR1CCCh2CCFZDLuxCCEAxQ4hJIsJBpTp7BCSy6RV7Dz++OOYPHkySkpKUFJSgtraWrz11lvK/aeeeipMJlPI13XXXRfyGrt27cKcOXNQUFCAgQMH4tZbb4XH4+ntUyGEZCBK6zmdHUJyGms633zIkCG4//77MXr0aAgh8Mwzz+Ccc87BV199hYkTJwIArrnmGtxzzz3KcwoKCpT/9nq9mDNnDqqqqrBs2TLs378fl19+OWw2G37zm9/0+vkQQjILOTnZzcwOITlNWsXO2WefHfL9fffdh8cffxzLly9XxE5BQQGqqqo0n//uu+9i/fr1eO+991BZWYkjjjgC9957L2677TbcddddsNvtKT8HQkjmIrM6QgBen4DFbErzERFC0kHGZHa8Xi9eeOEFdHR0oLa2Vrn9ueeeQ3l5OQ4//HDMnz8fnZ2dyn2ffvopJk2ahMrKSuW2WbNmobW1FevWrevV4yeEZB4uVVaHuR1Ccpe0OjsA8PXXX6O2thbd3d0oKirCq6++igkTJgAAvvvd72LYsGEYPHgw1qxZg9tuuw0bN27EK6+8AgCoq6sLEToAlO/r6up039PpdMLpdCrft7a2Jvu0CCEZgCdM7OTZLGk8GkJIuki72Bk7dixWrVqFlpYWvPzyy5g7dy6WLl2KCRMm4Nprr1UeN2nSJAwaNAjTp0/H1q1bMXLkyITfc8GCBbj77ruTcfiEkAxG3XLOkDIhuUvay1h2ux2jRo3C1KlTsWDBAkyZMgUPP/yw5mOPO+44AMCWLVsAAFVVVaivrw95jPxeL+cDAPPnz0dLS4vytXv37mScCiEkw1CXrhhSJiR3SbvYCcfn84WUmNSsWrUKADBo0CAAQG1tLb7++ms0NDQoj1m0aBFKSkqUUpgWDodDaXeXX4SQ7EMtdujsEJK7pLWMNX/+fMyePRtDhw5FW1sbnn/+eSxZsgTvvPMOtm7diueffx5nnnkmBgwYgDVr1uCWW27BySefjMmTJwMAZs6ciQkTJuCyyy7DAw88gLq6Otx+++2YN28eHA5HOk+NEJIBeHxBgcOAMiG5S1rFTkNDAy6//HLs378fpaWlmDx5Mt555x2cfvrp2L17N9577z089NBD6OjoQHV1NS644ALcfvvtyvMtFgsWLlyI66+/HrW1tSgsLMTcuXND5vIQQnIXt0cdUKazQ0iuklax8+STT+reV11djaVLl8Z8jWHDhuHNN99M5mERQrIElzqgzMwOITlLxmV2CCEkWagFDjM7hOQuFDuEkKxFXcZyMbNDSM5CsUMIyVrcPs7ZIYRQ7BBCshQhRFjrOZ0dQnIVih1CSFbi9QkIlZmjdnkIIbkFxQ4hJCvxhIkbOjuE5C4UO4SQrCQ8kMyhgoTkLhQ7hJCsJDyQzKGChOQuFDuEkKwk3MnhUEFCcheKHUJIVuLyhJex6OwQkqtQ7BBCspLwgDIzO4TkLhQ7hJCsJKKMRWeHkJyFYocQkpWEix06O4TkLhQ7hJCsJDyjE17WIoTkDhQ7hJCsJLKMRWeHkFyFYocQkpWEix0XMzuE5CwUO4SQrCSijEVnh5CchWKHEJKVhIsbZnYIyV0odgghWQm7sQghEoodQkhWEp7RodghJHeh2CGEZCURZSwGlAnJWSh2CCFZSWQZi2KHkFyFYocQkpVEDhVkGYuQXIVihxCSlXA3FiFEQrFDCMlKwsWNiwFlQnIWih1CSFYixY3Z5P+eQwUJyV0odgghWYksY+XbLAA4VJCQXIZihxCSlcgyVr7dCoBzdgjJZSh2CCFZiRQ3BXZL4Hs6O4TkKhQ7hJCsRIobpYxFZ4eQnIVihxCSlSjOjoPODiG5DsUOISQrCS9jcaggIbkLxQ4hJCuJLGPR2SEkV6HYIYRkJUrreaAbi0MFCcldKHYIIVmJLFvl2/y/5ujsEJK7UOwQQrISl8cvbgoCzg4zO4TkLhQ7hJCshHN2CCESih1CSFYSLGNJsUNnh5BchWKH5Czvf1OP+a+sQbfbm+5DISnA7ZHrItiNRUiuQ7FDcpaH3tuMf63YjXfX16f7UEgKcPtkGcsa8j0hJPeg2CE5y8EOFwBg/b7WNB8JSQXhmR0hAC83nxOSk1DskJylpdMNANiwn2InGwkvYwHM7RCSq1DskJzE4/WhzekBAKyn2MlK3GEBZYBih5BchWKH5CSt3R7lvxvbnGhsc6bxaEgqCC9jAQwpE5KrUOyQnKSlyx3yPUtZ2YcUNg6rBSaT/zaGlAnJTSh2SE5CsZP9SGfHbjXDZubKCEJyGYodkpM0d7pCvmduJ/twefxix2oxwWrxWzvM7BCSm1DskJxEOjsWs/8iSGcn+/AE2sztFjOsZil26OwQkotQ7JCcpDUgdiYdVgoA2NrYwUnKWYZ0cawWE+zWQBkrRmbH6fFif0tXyo+NENK7UOyQnKQ5MGNnbGUx+hXY4PUJbK5vT/NRkWQhhFBcHJvFDKvBzM68577CtPvfx64DnSk/RkJI70GxQ3ISWcYqK7BhwuASAMD6/S3pPCSSRDyqSck2s9lwZmdrYzt8AthxoCOlx0cI6V0odkhOIsVOSb4N46v8YmfD/rZ0HhJJImoHx2Y1wWbx/6qLldmRoWYGmQnJLqzpPgBC0kGzytkZVJoHgDuysgmXSqzYVAFlTwwR46TYISQrodghOYl0dkrzbRhZUQTA35ElhIBJTqAjfRa1WLGaVc5OjEWgLo8/pO5i1xYhWQXLWCQnkUtApdixW8xoc3qw5xA7cbIBjxJONsFkMsFmMebsSEco1uMIIX0Lih2SkygB5Xw77FYzRg30uzscLpgdKG3ngS4sq5LZiSF2WMYiJCuh2CE5ibqMBSDYkcXcTlYgxYp0dIwMFfR4fZBVLpaxCMkuKHZIzuH0eNEVGCBYWuAXO+MHyY4sip1sQIoaOUzQyFBBdajZ7aGzQ0g2QbFDcg7p6phMQLHDn9GfMEjO2qHYyQYiylgGnB2nWyV2WMYiJKug2CE5h1wVUZJngzlwEZRiZ8+hroiN6KTvoZSxrIEyliX2BOUQZ4dih5CsgmKH5BxyVURZoIQF+MtZh5XlAwC+obuT0Xi8PnS5ou8xU1ZFBJwdm4EJyi5V6YqZHUKyC4odknOEh5Ml4wcVA2BuJ9P5zhPLcdID70cVPB4loCzLWLG7sZweOjuEZCsUOyTn0BM7zO30DVbvaUZTuwv7omwnd4WVsaTo8UQZKqh2dhhQJiS7oNghOUdzp56zwx1ZmY7H61NKVOpAcTjyMdawMla0YYHM7BCSvaRV7Dz++OOYPHkySkpKUFJSgtraWrz11lvK/d3d3Zg3bx4GDBiAoqIiXHDBBaivrw95jV27dmHOnDkoKCjAwIEDceutt8Lj8fT2qZA+hK6zE5i1s7G+jRN0M5RulePi9MQuY9llGSsgdqJlcZjZISR7SavYGTJkCO6//36sXLkSX3zxBU477TScc845WLduHQDglltuwRtvvIGXXnoJS5cuxb59+3D++ecrz/d6vZgzZw5cLheWLVuGZ555Bk8//TTuuOOOdJ0S6QPoiZ3qfgUotFvg8viwrakjHYdGYqDO6XRHcXakS2NVhgrKbixjAWU6O4RkF2kVO2effTbOPPNMjB49GmPGjMF9992HoqIiLF++HC0tLXjyySfx4IMP4rTTTsPUqVPx1FNPYdmyZVi+fDkA4N1338X69evx7LPP4ogjjsDs2bNx77334tFHH4XL5UrnqZEMpqUrshsLAMxmk1LK4iTlzKTbHRQ70Z0duRsrfKhgtNbz4OtR7BCSXWRMZsfr9eKFF15AR0cHamtrsXLlSrjdbsyYMUN5zLhx4zB06FB8+umnAIBPP/0UkyZNQmVlpfKYWbNmobW1VXGHtHA6nWhtbQ35IrmDnrMDcJJyphMqdqJldsK7seJrPY82j4cQ0vdIu9j5+uuvUVRUBIfDgeuuuw6vvvoqJkyYgLq6OtjtdpSVlYU8vrKyEnV1dQCAurq6EKEj75f36bFgwQKUlpYqX9XV1ck9KZLRNHf6XT8tsaPsyKLYyUi63Ooylr6zE7Eby8BQQWdIZofODiHZRNrFztixY7Fq1Sp89tlnuP766zF37lysX78+pe85f/58tLS0KF+7d+9O6fuRzCLo7Ngj7lOXsYTgX/eZhjqzE93ZCS1j2eJ0dljGIiS7sKb7AOx2O0aNGgUAmDp1Kj7//HM8/PDDuPjii+FyudDc3Bzi7tTX16OqqgoAUFVVhRUrVoS8nuzWko/RwuFwwOFwJPlMSF+hpcvfrafl7Iyt9A8WPNDhQmuXR1kUSjKD0G6s2GUsa5izE203FlvPCcle0u7shOPz+eB0OjF16lTYbDYsXrxYuW/jxo3YtWsXamtrAQC1tbX4+uuv0dDQoDxm0aJFKCkpwYQJE3r92EnmI4RAS5e/jBUeUAaAfLtFKX10ujnCINMIcXailLFkEFm2nitzdqJtPQ8ZKkhXj5BsIq3Ozvz58zF79mwMHToUbW1teP7557FkyRK88847KC0txdVXX40f//jH6N+/P0pKSnDjjTeitrYWxx9/PABg5syZmDBhAi677DI88MADqKurw+2334558+bRuSGadLm9yl/3Ws4OAORZLXB7PVFbm0l6MBpQlsJFOjs2I4tAmdkhJGtJq9hpaGjA5Zdfjv3796O0tBSTJ0/GO++8g9NPPx0A8Mc//hFmsxkXXHABnE4nZs2ahccee0x5vsViwcKFC3H99dejtrYWhYWFmDt3Lu655550nRLJcGRex2o2ocBu0XyMw2ZBm9MTNQBL0kOI2Inq7IR1YylDBbkbi5BcJK1i58knn4x6f15eHh599FE8+uijuo8ZNmwY3nzzzWQfGslS1BvPTSaT5mMcgZks0ZwDkh66DLeeh5WxOFSQkJwm4zI7hKQS6eyU6JSwACDP5v+/BZ2dzMNo63lEGcsqMztGA8rM7BCSTVDskJxCbwmomjybv7xFsZN5qHNU0ZydiDKWWXZjGXN2XHT1CMkqKHZITtEqV0UYEju84GUahicoe8Lm7Chbz40NFWQZi5DsgmKH5BTRVkVIgpkdOjuZRuhQwSgTlBVnJ3QRKIcKEpKbUOyQnKK5S39VhEQ6O84cdHY27G/FtPvfx39W7kn3oWgSmtkxPkFZZneMDhXkbixCsguKHZJTKM5OQeSqCIkSUM5BZ+fttXXY29yFd9bp75ZLJ0a3nruVgHJg67mcsxN1qGDw9Thnh5DsgmKH5BTRVkVI8qy5G1De2tgOIHQtQyYROmcndkDZHsciUJaxCMleKHZIThFt47nEobSe594Fb2tjBwCg25WZQi+kjBXF2XEFRI3M6hgZKqi+zycAb5Q2dUJI34Jih+QURrqxHAFnJ9cCyj6fwDbF2cnMcw9pPY/m7ASEi80aPlTQmLMD0N0hJJug2CE5RTCzw9bzcPY2dynt112Z6uy4jE5QDi1jBYcKGuvGApjbISSboNghOUWzoTk7uTlBWeZ1gNByUSZhNKAcUcZSWs+NzdkBgiFnQkjfh2KH5Aw+n1DKWNHn7OSms7OlISh2MlXodRtsPY8oYylDBY1ldgCujCAkm6DYITlDm9MDmTk1shsr1zI7MpwMZK7Q6zLaei7Fjjm0GyvqnB1mdgjJWih2SM4gXZ08m1nJ5WiRq5md8DKWEJnnbIRvPdc7RhlEDgaUA0MFmdkhJCeh2CE5g5FVEUDuOjvbVGLH6xMZV8YRQoQIUCH0BYm8Pbgby6w8R6+lPCKzQ7FDSNZAsUNyBiMbz4HcHCrY3OlCU7sr5LZMaz/X6r7S68iSQsWqlLFMEfeFE1HG8mSW2COEJA7FDskZWpROLP1VEUBuDhWUeZ2qkjxYAgIh0wYLarXD683akWUsuzXU2QGiiB2lXd0c8j0hpO9DsUNyBil2ooWTgaCzk0tlLJnXGTWwCHkBgZBp7efSabJZTDFLja5wZ8ccdHa0Bgt6fUIpbxU6LIHHUewQki1Q7JCcwcjGcwBw5GBAWYqdkRWFyLf7zz/TxI50dvJslpjjATxhW88tZhNMAb2jFVJWl7AKHVb/4zIss0QISRxrug+AkN5CKWNFmZ4M5OZQwa0N/jLWyIFFGduNJsVXns0C6dPoOTvusICyyWSCzWyGy+vTdHbUYqdIETuZdf6EkMSh2CE5g5GBgoB6qGDuiJ1tirNThPyA2Mm0lRFSfOWrxgZoBZSFEPD4pLMTLF9ZLSa4vNplLKfXf64mExRni5kdQrIHih2SMxjuxlLyILlxsXN5fNh5sBOAX+wEnZ1MEzv+48m3WeALzNfROkZ1+UnO2QGCuR0tESOdHbvFrASU6ewQkj1Q7JCcwXgZSwaU/UPrTCZT1Mf3dXYd7IDXJ1Bot6CyxKE4J5kmdoKZHTO8AbGjJUjVIkVuOweCJS2tZaCK2LGalQ4uih1CsgcGlEnOIJ2dmN1YMcok2cYWVV7HZDIhL0MDyrIbSx1Q1mo9V5ep1GUsRexoZXYCwsZhNSuP45wdQrIHih2SM7QY2HgO+C94kkxzN1LBVlVeB0DGtp5LZyffbonaeq4uU1nMoZkdQNuxUZexopW7CCF9E5axSM5gNKBss5hhMZvg9YmccHbUbedAMKCbeQHlgLNjtcAcKC1qOju+oHBRlyBtUZaBqstYNpaxCMk66OyQnMDj9aHN6QEQW+wAQXcjN5ydQBkr4OzkqzJLmYR0mvLtFsV903J2ZPlJXcICggFlrWGBIZkdBpQJyToodkhO0NrtUf7bkNjJ0FkzyUYIgW0NwenJQPDcM8/Z8f8s8myWkBB5OMr0ZEvorzfF2dFYBOr0qpwdpdzFzA4h2QLLWCQnkHmdIoc14iKohSNHnJ3GNifanB5YzCYMHVAAQCV2Muzcg0MFzRBRWs9lGcsWIXYMODuWYEA5fDEoIaTvQrFDcoLmTmOrIiSZOmsm2WwJuDpD+xcoHU75mSp2XKo5O74ored6ZSyjmR2WsQjJOih2SE7QYjCcLHFkaG4l2YSHkwEg356ZrpbM5+TbLMqEZE2xo+PsyMyOlohxKmLHoszZ8WiUuwghfROKHZITxCt2cmU/Vng4GchcV0u9CFQKFqfWBGWPFDuhzo6hoYKWYGaHZSxCsgeKHZITxC125H6sLL/ghc/YATI3oKxkduwWJYSsFSB3h208l0QLHrsCrpGDZSxCshJ2Y5GcoKXT2KoIiSNXnJ1AZmfkQFUZK0M70dSLQKO2nuuVsQxMUGZmh5DshGKH5ATNCTo72ZzZ6XB6sK+lGwAwojzo7GRsQFm1CDRapkqWsawRZSxjE5TtUYLMhJC+CcUOyQlkGSvWXiyJso4gwy74yWR7kz+vM6DQjn6FduX2TM3sdKtaz6ONBpDB4siAsr5jE9qNxXURhGQbFDskJzC68VySqRf8ZKKV1wGC3ViZ5ux0q50dpYylv/XcHlHGCszZiTJU0KFeF5HFrh4huQbFDskJZGbHcOu54hxk7wUvmNcJFTuZKvTUAWVHlDKjS6eMZVcyOzGcnSgOECGkb0Kxk8O4PD489cl27AiUM7KZ4MZze4xH+gmuI8isC34yCbadF4bcnrHdWK7Aughr9K3numWsqN1Y6kWgXBdBSLZBsZPD/HfVXtz9xnr89u1v0n0oKSfRoYJZ7ew0ajs7mdqN5QxZBKp/jNKRiVwEajSzE1gXQWeHkKyBYieHWbOnBQBQ39qd5iNJPc1d8a6L6Fnr+dbGdvxp8Wa0dbsTen6q8foEtgUcvVHhmZ2A2HF5ffBm0BTh0G6sKK3nMebsaGV2XKqcD1vPCck+KHZymPX7WwEEXY9sxenxKg5AqdE5Oz0cKvjI4s14cNEmvLF6f0LPTzV7D3XB5fHBYTVjcFl+yH35dovy35mS23F7fYpIybOZg6MBojg70smRRBMx0tlxWNWt5xQ7hGQLFDs5is8nsCFHxI48P5MJKHYYGxreU2enoc0Z+N/MdM02N7QBAIaXF8JiDi33yHA2kDkdWeqfQ57K2dH6+biVkpT2IlDNoYIaZSytxxFC+iYUOznKzoOd6AwEUFu63BAivb/Yl287gB//exUOtDuT/tqyE6skzwZz2IVdj54OFZQCK1OFpNx2PrqyOOI+k8mkiL1MCSlL0WUy+cVY1NZznYCyLcoi0NAJypyzQ0i2QbGTo6zf16r8t9sr0v4X/O/f2YhXvtyLd9bVJ/21452xA/S8/VoRO52ZKXY2S7ETFk6W5GdYN1q3qhPLZDKFtJ6HC3W9MpY1ymRkZeu5xRKcs0OxQ0jWQLGTo6zf3xLyfTodiG63VwlLN6XA2WmOc8YOECzlJDpBWX6ezRnq7BgVO7LdO910e4KdWECwzAhEOjByjo7Nqr0uIurWc3Vmx8MyFiHZAsVOjqJ2doCgIEgHa/a0KBesgx2upL9+vG3ngNrZif9i7/UJtHV7AADNnck/n54ihFAGCo7SETt5GbYfS5bTpAiTzg4Q+TNSurF0AspaWRynRmaHzg4h2QPFTo4iO7Ek6XR2Pt9xUPnvzBE7+q3NsWgPCB31e2cSda3daHd6YDWbMGxAoeZjMk7sBI5DBpNtFhNMAeMm/GcUnLOjN1RQy9nxv4a/9ZyZHUKyDYqdHKSp3Yn6VidMJmBsIKCaKWLnUAqckHg3ngM9c3bUn2Umip3N9X5Xp6a8EHar9q8AWS7KlNZz9YwdAIHcjiw1hjs7OmWsaEMFvXR2CMlmKHZyENlyXjOgEIPK8gCk76Ls9Qms3HlI+f5Aewqcnc74BgoCqt1YCTg76s+yuTP9nW7hxMrrAD1vvU82zjCxA+iv9NArY0VbBBoyZ8eqH2QmhPRNKHZyEJnXmTCoRBEA6eoa2ljXpuRbgNQ4O02B0lh5kcPwc3rSjaUWOx6fQEeGtG9LtsTI6wDqgHLyjr3D6cGP/vUV/vbRNvjinMysLAFViR29Za166yKMDBW0W82wBlrUvT6RUROkCSGJQ7GTg8i8zoTBKrHTA2en2+1VLhbx8sVOfwlrRLk/O3Kgw5V0J6QxMOCvoti42AmuI4hsbY5F+GeZaaWsLYGBgtHETio2ny/begCvr96HX/9vAy7/+wo0xLGmRFkCGiJ2tGchKa3neusiog0VtJiV1nP1axFC+jYUOzmI2tkp66HY2X2wE9P/sBSzHvpQafmNh893+EtYMydWAfBfdDqT7ITIdvZEnB0h4g+qhn+WmdSRJYTApnpZxoocKChRnJ0kLgNVu3Yfb2nC7Ic/wgcbGww9t9sd2noO6IfIpZixhweUDWR2HDZzyPModgjJDih2coxut1fZdj1hcAlKeiB2WjrduOKpFdjb3IXtTR1oijNvI4TA59v9zs7JY8qVskSyO7KCzo7d8HPyorQ2xyLC2cmgwYJN7S60dLlhMgEjKrQ7sYDUdGPJz+GYmn4YV1WMAx0uXPnU5/j1wvUxnUGljKVyXRw6+7FcOgHlYDdWqLPj8wnlNvUiUK3HEkL6JhQ7OcbGujb4BDCg0I6BxY6Ey1hOjxfX/PMLbG3sUG6LdyDgnkNdqGvthtVswpHV/TCg0C9Gkil2ut1eJRNUUZRn+Hkhrc1xXvAjnJ0MKmPJvM7Q/gUhJaFwUtGNJT+XCYNK8Nq8abjihBoAwN8+3o4LHl8WdY+YlrMTXBmh3Xqutwg0fKig2rmzW82wmE2QW0Xo7BCSHVDs5BjqvI7JZFLETjwXZJ9P4KcvrcGK7QdR7LCissRfHpIOilFkXufww0qRb7egXwrEjhRgdosZJfnGloACgf1Q1sTazzM5syPzOtE6sYDUZHbU847ybBbc9e2J+OvlR6OswIav97bgyY+36z63W6MbS52rUiPLWBG7sXSGCoaLHfVjKXYIyQ4SEjv33HMPOjs7I27v6urCPffc0+ODIqlDndcBgLICv8BojeOC/Lt3N+KN1ftgNZvw+PemYlyV/7Ua43R2Vmz353WOqekHAOifErEjO7HsMJmMLQGVJDpYMPyzTOd06nA2K51Y+nkdAClZBKqInYJgOfH0CZWYd+ooAEBdi76zo9WNFRSjekMFdcpY4c6OSizJvI49yh4tQkjfIyGxc/fdd6O9vT3i9s7OTtx99909PiiSOtTODoC4y1jPfbYTjy/ZCgC4/4LJOHF0udLlFLezExgmeExNfwBBsZPM9nN5TOVxdGJJEh0sKD9LWZZr7sqcgLIcKBitEwtQB5STJ3b0hjuWFsT+N6jZjaXj7Lj1nB0ZUA7beaXuxJKCmMtACckuEhI7QgjNv5JXr16N/v379/igSGrw+QS+2R/q7KjFTqwW6w82NuBXr60FANwyYwz+b+oQAMEup3gyO4c6XIrLMHVYqLNzIAVlrIo4OrEkiQ4WlBftoQMK/N9nkLOzpTH2QEEgKHZSVcZSo5RSo3xOyiJQW+yAcqx1ERGZHdWMHYmyMiLBkQqEkMzCeIgBQL9+/WAymWAymTBmzJgQweP1etHe3o7rrrsu6QdJksOug53ocHnhsJoxPDDXRl5ovD6BdqcHxXn6U4b/uGgTfAL4v6lD8KPpo5TbpbMTTzfWF4GpySMrCjEgIET6B8obh5IodhRnJwGxk2hupbU7IHb6F+CrXc0Zk9lp7nQpn8fIWGLHnpirFY1WHbEjxx9EK6V2u4y3nsceKqid2QkVO3R2CMkm4hI7Dz30EIQQuOqqq3D33XejtLRUuc9ut6Ompga1tbVJP0iSHGQJa1xVsTJwLc/mH4/v8vjQ0uWOKnb2NXcBAK6aNjxE6JYX+UVKY5RumnBkCevY4UEnsH9RCp2dBMpYDpu2cxALxdnp73d2MiWzIzuxDivLR5Ej+v/1pWuS1DJWoDxZVqBdxooWkteeoKwtyHTLWMpQQR1nR/V4ZnYIyS7iEjtz584FAAwfPhzTpk2D1RrX00maUcLJgbwOAKUjq7HNiZYuN4b0036u1yeU4LAUN5KKovidnRUBsXP0MJXYSamzY3zGjiQvgTKWzycUh0IROxni7MiyYSxXBwg6KMkKKAsh0BoYARDp7Ph/NrKUqlUi746yLkK39TwioKwtYOTz6ewQkr0klNkpLi7Ghg0blO//+9//4txzz8UvfvELuFyZE8YkoawPy+tIjISUD3W6INcEyWyNJFjGMpbZ6XJ5sXZvC4BgOFn9uqloPa8oNj5jR+JIIKDc7vIon9OwAf5SYUuGTFDeYmABqETJ7CSwCFWLdqdH2TMVIXYKQkupWshJzvmaYies9dynPUHZZtbuxnJqZXYCAwnjnZ5NCMlMEhI7P/jBD7Bp0yYAwLZt23DxxRejoKAAL730En72s58Zfp0FCxbgmGOOQXFxMQYOHIhzzz0XGzduDHnMqaeequSE5Fd4LmjXrl2YM2cOCgoKMHDgQNx6663weLR/aeYyWs4OAEPLQOU28n4FtoidQzIP09zpNhToXL2nGW6vQGWJA9X985XbFbGTRHGgbj2PF8XZiaOUIz9Dh9WMgQERmCmZHSPbziXK1vMkOTvNqs8lfJhhns2iCA29z0rT2dHJVLk92rux5PdCIGTBp1YZS1ktwYAyIVlBQmJn06ZNOOKIIwAAL730Ek455RQ8//zzePrpp/Gf//zH8OssXboU8+bNw/Lly7Fo0SK43W7MnDkTHR0dIY+75pprsH//fuXrgQceUO7zer2YM2cOXC4Xli1bhmeeeQZPP/007rjjjkROLWs50O5EXWs3TCZgbFWo2DGyHyvafqnSfJuyKfpAR2x3R66IOLqmf0jJQoqd5k53zD1brd1uQyIkkSWgEnlhDXcOoqHuOJKORYcr8UWpyWRLfewFoJJkt57rdWJJymJ0ZGkOFdRxdly6AeXg9+rylFY3FjM7hGQXCYVuhBDwBazg9957D2eddRYAoLq6Gk1NTYZf5+233w75/umnn8bAgQOxcuVKnHzyycrtBQUFqKqq0nyNd999F+vXr8d7772HyspKHHHEEbj33ntx22234a677oLdHv9f9NnIhv3+C13NgMKIcKqRMpYUOwM0HBKz2YTyIgfqWrvR2ObEoNL8iMeo+TzQiXXMsNCAUGm+DSaT/y/v5i63bgdVW7cbJ/32A1T3z8fCG0/SfZ8ul1cpiyQ2Zyd+Z0fdcVScFzyfli53QoIrWbQ7PdgXGNpnROwkezeWXieWpDTfhoZAbkyLLmVdhKr1XCdArlvGUn3vUTs7Wt1YVrlHK/0ilRDScxJydo4++mj8+te/xj//+U8sXboUc+bMAQBs374dlZWVCR9MS4s/xxE+q+e5555DeXk5Dj/8cMyfPz9kevOnn36KSZMmhbzvrFmz0NrainXr1iV8LNnG+v3+zzY8rwPA0DLQYDlI+4JdHliyGSu34/UJfCnFzvDQn7PVYlYuhtFyO1sa2tHS5cbava3odOmXK+WxOKxmFMfoPtIiOMcljjKW6qJuMZtQkic/2/TmdrYGSlgVxQ5lanY01K3nseYvGSGmsxNjsKAMSjus6gnKkQFln08oJaqIMpZZ5ex4Ip0dh0ZAmZkdQrKDhJydhx56CJdeeilee+01/PKXv8SoUf6ZKy+//DJOOOGEhA7E5/Ph5ptvxrRp03D44Ycrt3/3u9/FsGHDMHjwYKxZswa33XYbNm7ciFdeeQUAUFdXFyGw5Pd1dXWa7+V0OuF0Bi/Kra2tCR1zLIQQONDhQmm+LaINtrfRy+sAMLQf60CUMpb69qa26Bf1Dftb0e70oMhhVdZMqOlfaEdzpzuq2NmvWiuw91AXRldqrz5oVB1zvKsiAJWzk2AZS/5vS5c77e3n8eR1gNBsjNPji7o01Ajy31Z427kk2mBBn08opaqQRaAaAXJ1+Di8jGVRix2fRhnLEil26OwQkh0kJHYmT56Mr7/+OuL23/3ud7BYEvulOG/ePKxduxYff/xxyO3XXnut8t+TJk3CoEGDMH36dGzduhUjR45M6L0WLFjQK2stTvztB9jb3IU3f3SSpsjoTfQ6sYDYf1UD6syOtisg289j7cf6cpff1TlqWL+Qi4+kf4Ed29ARVezIeT8AsKc5itjpwaoIILGhguFip6zAhl0H0x9S3txgPK8DBF0TwO+q9FTsyPMv0S1j2UMep0adydHO7AR/PuqMTfgfGCaTCXaLGS6vL2QZqHRvHLbIzE740lBCSN+kR3bDypUr8eyzz+LZZ5/Fl19+iby8PNhs+kPp9LjhhhuwcOFCfPDBBxgyZEjUxx533HEAgC1btgAAqqqqUF9fH/IY+b1ezmf+/PloaWlRvnbv3h33MRtB5lvUF+d00O32YmujP/QdzdmJNsFWdmMN0C1jGduPtS1wHOOrtAWKkfZztbOz55D+Z9uTVRGAKqAcR+t5+EXdyCqE3mBrnM6O1WJWLvjJaD+PVcYKuouRP3d1bkh7zo7K2fGonZ3IX2/Kyghv9G4s6QrR2SEkO0jI2WloaMDFF1+MpUuXoqysDADQ3NyMb33rW3jhhRdQUVFh6HWEELjxxhvx6quvYsmSJRg+fHjM56xatQoAMGjQIABAbW0t7rvvPjQ0NGDgwIEAgEWLFqGkpAQTJkzQfA2HwwGHI/Vh0cGl+VizpwX7WtIrdr7a1QyvT6C8yKG0Q6uJK6BcGN3ZiZXZ2RsQfof10w4xGxE7Ic7OoU7dxwU7sRILqSeyGyvS2ZHLQHtH7Hi8voisCmB827kah83vgiRjsKAUe3KAYDjSXdQS3FLs2C3mEDdQy3mT5SmzCZrOocztqLM4mnN2mNkhJKtIyNm58cYb0d7ejnXr1uHgwYM4ePAg1q5di9bWVvzoRz8y/Drz5s3Ds88+i+effx7FxcWoq6tDXV0durr8F7OtW7fi3nvvxcqVK7Fjxw68/vrruPzyy3HyySdj8uTJAICZM2diwoQJuOyyy7B69Wq88847uP322zFv3rxeETTRGFzmv6DvjeI+9AaL1vudrlPHVmhmV4y4D0pAWackZNTZkZ/FkJ6InbDMjh49dXb05rhEI3xKcGm+/++J3hgs+Nu3v8ER9yzCm1/vD7m92+3FroN+UWi0jAUkt/082I2l/fdVtH+DwRk7ob+uNJ0dr3Y4WSJFjEcrsxPSjaW9IZ0Q0jdJSOy8/fbbeOyxxzB+/HjltgkTJuDRRx/FW2+9Zfh1Hn/8cbS0tODUU0/FoEGDlK8XX3wRgH/f1nvvvYeZM2di3Lhx+MlPfoILLrgAb7zxhvIaFosFCxcuhMViQW1tLb73ve/h8ssvxz333JPIqSWVwWX+qb1701jGEkJg0QZ/UHvGeO1OuVjOjhAimNkp1AsoG+vGUpydsgLN+w2VsUKcHf3PtseZHWWoYOJlrLIoWZRks2xLE9qdHtzw/Jd4eeUe5fatje0Qwu+exDNcMdiRlcQylk5AOVpuTDpL4bkhpVtOJXbkfKbwtnOJZhlLeU7w9e0MKBOSVSRUxvL5fJrZHJvNpszfMUKsltbq6mosXbo05usMGzYMb775puH37S0OCzg76czsbG5ox+6DXbBbzThpdLnmY+QFqLXbDZ9PwBxm/3e4vMoFpVynJDTQgLPT1u1WLmaxyliHdJwQl8cXEoKOJiSlG9XjzE6PylixO92SRUdAFPgE8NOXVqPL5cFltTUhayLi6UrLN7Au4/XV+/DZtgO4+9sTdd0UIJjFiZnZieLsqDuxANXWc3UZS2cvlkSry0rT2WFmh5CsIiFn57TTTsNNN92Effv2Kbft3bsXt9xyC6ZPn560g+vrDFbEjvFt4MlGlrBOHFWOQp1ZM/JCIwTQprGbqCkgYPJtFhTYtV9Dtp63dnt0xYEUJqX5Nt2t2/0CYueAzlLR+tZuCAHIa3Zjm1PXeUheN5bxC1748LzeDCh3BH52UtT+6r/r8JelWxWxE09eBwiW8aJldn7/zkY899kurAzMTtIjKAK1xXI0d7FbYy+W+vi6NcpYeqMegmUsjYAyMzuEZC0JiZ0///nPaG1tRU1NDUaOHImRI0di+PDhaG1txSOPPJLsY+yzSLFT39adtr8QpdjRK2EB/nKA/CtZKyAqV0DouToAArOEAisjdIRKrLwOEAxA6zk7shNraP8CFAb+0tdzd3qc2UlkN1YaA8pS7Nz17Ym44Vv+2Vf3v/UN/vHpTgDx5XUAID/wbyJaZkduqG+IkdWSO8P0hwrql/vk+zsiylgBQeIJDj50xypjyWWgMYYKWlnGIiSrSKiMVV1djS+//BLvvfcevvnmGwDA+PHjMWPGjKQeXF+nvMgOu9UMl8eHupZuVPfXzqmkiobWbqza3QwAmDF+YNTHlubb0O12ornTjerQwcZKOWiATl4H8M8wKS9yYH+Lf2WEFHpqgnkdfbHTL3DRO9DhghAiouwiS4KDSvOQZ7VgY30b9h7qwsiK0At5h9ODzoAj0VNnx+huLCGE5lBBIHpbfzIQQihlrCKHFT+dNRYFDgseeHujckxG284lsQLKbq9PcQKjlS+9PqE8LlYZq93pgdvrC3FmlFUROgFlIDj4MFYZSxExWusiVO9pl2WsDAwoa5WaCSHRicvZef/99zFhwgS0trbCZDLh9NNPx4033ogbb7wRxxxzDCZOnIiPPvooVcfa5zCZTGnN7Sz+pgEAMKW6DANL8qI+NlqQNtoSUDXlMdrPpbOjl9cBgrOJXB6fIlbUyDb+waX5yutohZTlMeTbLIoDFC9amZBodLi8yqqCiMxOiruxnB6f8t4FgfP94amjcPe3JwLwt2KP05ltpEdwzpD2+asFXLRgelu3GzKepyd2SvKCf3eFC0OtJaDq4/Mfo1+wxCpj2ZWAsrr1PNDarlHGyjRnZ1N9G6bc8y4e/WBLug+FkD5FXGLnoYcewjXXXIOSEo3BdKWl+MEPfoAHH3wwaQeXDciOrHTM2pElrJkTYu8ri5aZOKDsxYreyROrI0uKkmjOTr7NovzFrtWRtT+QfxpUlqeUw7Rm7SgCrdie0KoIQJXZMejsyM/ObjErQkm9Ud7nS51LoBaG6lzV3BNq8Nz3j8P/u+zomII3nFjOjro0F83ZkZ9Lgd0SIijUWC3B/WXhJT+9gLLVbII0OKRgUZwdHecjWJ7qm5mdFdsPoq3bg482N6b7UAjpU8QldlavXo0zzjhD9/6ZM2di5cqVPT6obGJwqbGQ8sEOF85+5GM88eHWpLxvp8uDj7f4N9BHy+tIoi0DNersVMToyNrTLDM7+uU8k8mk5HY0xU6LLGPlK2JHK7OjDBRMMK8DxJ/ZkbmUknybIrDk5+rTCX8nC5nXybdZIobpTRtVjtMNCN5w8uwyoKx9wVeHrqOtCYk1PVlSqtN+rrSeW0PFjslkimg/ly3luqLKHNll5dSaoGzNTGdHfjZdcYTmCSFxip36+vqo6yCsVisaG/kXhxplsGCMMtaHmxrx9d4WJUzaUz7c1ASXx4eh/QswpjJ2ViPauP7gqohYzo4sYyUeUAaCHVlaYkeKxsPK8pVZPVplrMYYW9qNoJ7Qa2Tzd4vG4Lw8W/Twd7LoCGx/L3T0bIeVGqX1XKe7zmgZqzlGOFmiuIud4c6O/8Kep1GOVEqNgWOUTkzsbqzoredKZifDdmPJQHiXK3XCmZBsJC6xc9hhh2Ht2rW6969Zs0ZZ40D8GM3sbGv0twfvbe5KyhC39zYEu7CMlHGiDXVrTIKz0+32KhfEaGUsIPpgQcXZiVHGCq6K6IHYCbgGPmHsoqfnYMg8VCrbz6WzozdeIBGkkNBrPVcLYyNlrFhiR+/fYJdOZgcIDhbsVjI7scpYkSJGCSj3gczOoU7p7PT8dwQhuURcYufMM8/Er371K3R3R5Zkurq6cOedd+Kss85K2sFlA0ZXRmxr8i/IFALYeUB/35MRvD6B9wPhZKPli2hdQwfkXiyDzo5WSUM6WwV2i3JR00NvsGCXy6v8sleXsRranBGzfYyW3qKh3oJtZLBg+IwdSXCwYOpCyh1O//HpzUFKhPwY6zLU4q2p3aWbSTJcxsrXDnPrrYsAgj8j+fOJVcZSnB2DmZ1MEzstXdLZodghJB7i+s14++2345VXXsGYMWNwww03YOzYsQCAb775Bo8++ii8Xi9++ctfpuRA+ypKQLm5S7OVWiK3gfv/ux1j4+ycUfPlrkM42OFCab4Nx9T0M/ScaAFlo5OIo3VjqUtYsZwmKXYOhDk7MuRdaLco3Tt5NjO63T7sb+5GTXmh8thkODvq1uZutw/FMfK9rd2hqyIkvTFYsFOWsRLsPNMiL1ZAWXU+Xp9Ac5db+dmpMS52ZEdgaIlGrxsLUO3HCjg7rhjOjpwFpVXGcli0xE6GlbGks0OxQ0hcxCV2KisrsWzZMlx//fWYP3++kmMwmUyYNWsWHn30UVRWxh+EzGaks9Ph8qK1y6O5G8jnE9jepBI7qv/Wo7HNiZU7D+K0cZURf8W+F+jCOm3cwKgj/NXoXZBdHp9ysRrQgzKWkRk7kv6BWTuHwsROsBMrKJiG9CvAloZ27DnUFSJ2kuHs+AOwZjg9PkOlRb2LupGt8j2lPeDsJLOMFWs3Vvj5NLY5o4qdWI6engPWpTg7Wpmd0FyRJ0brudUcHEQo0Spj2a2ZuS5Cul6dgRxZop2GhOQacf9mlHuoDh06hC1btkAIgdGjR6NfP2MOQq6RZ7NgQKEdBzpc2NvcpSl26lq7Q/563hrI70TjV6+txdvr6jBqYBHuO/dwHDdigHKfkanJ4eh1wsjcjMVsUtqo9ZDOT1u3B91ub8jFyciMHUn/oujOzqDSoMUypF8+tjS0Y29zaOkv6OwYX3ypRZ7NAqfHZ6iMpZvZiZKHShadKQgoy8ySXudPeLmpsc2p6UjGmp4s0ROFeotAgUhnxx0joKwsAtVYF+FQdXsprecGxw70FvKPESGCgxQJIbFJaF0EAPTr1w/HHHMMjj32WAqdGAyOEVJWl7C0vtdCTkbe0tCOi59YjltfWo2DHS5sbWzHtqYO2CwmnDxGe/GnFnoXGumQ9C+0x5zaWpJvVdp3w4VKrG3namI5O2p3SP63uiNLvaW9oii+2TLhyJyIkf1Y+mJHBpRTl9lplwHlZGZ2pLOjUzLR+7ei97iYAWW9biyP9m4sIHLzeVDsaP9btSuZnViLQDMvsyOECJlBxFIWIcZJWOwQ48QaLLitye/kVPf3X7i3NbZHbXVu7nShrtV/4b/o6CEAgJdW7sH0PyzBff/bAACoHVmO4rzoFxc1scTOAI3yRDj+lRH+x4WXsmTHVKy2c0C/G0s9Y0ciZ/aoxU6706OIk2j7vIwQvJgad3bSktlJRRnL4FBBmRPS68iSZanwzyUcvX+DUmyFDxUEVM6OMlQwRhlLqxsrqtjJnMxOm9OjTMkG2JFFSDxQ7PQC0s3Qm7UjnZzTxg6EyeTfHB7ujKj5pq4NgF84PPB/U/Cf60/AuKpiHOp0B7uwYuzCCkdeaNq6Q3+hyhk7RoO+cg9VU9iFL64ylhQ7neFlrOD0ZIl8PXW3mwxUF9r1t7QbJTnOTurLWHLOTkESA8oO5dx1nJ2AeBsZ2LmlN1hQBo6lw6VHqZLZ0W491+rGCt9MH9yNFT2zEzJUULP1PPMyO80doZ+L1joVQog2FDu9QLAjS3uKsszojB9UopRlopWyvtnfCgAYV+Vf2zF1WD+8ceOJmD97HPJtFhTnWTFzYlVcx6i+QGsNizPi7ADa7edur09xooYYCSgXBufSqMsNsgw4OMTZiZy1Ix2GRBeAqsmL0X6tJlZAOZWbz1MxZ8eosyO3qYcLXIleS344upmdKAHlcGfHoyz1jNWN5Rf0Qoigs6PZjZU5Yid8FEMy5nERkitQ7PQCsQYLSmEzoqIIIwLbu7c36YeUN9b7nR31YkebxYwfnDISn84/DYtuOQWVce5BslnMSjlCfbGRDpPRriYZUlZf+OpauuET/ouJkdcpzbdBNpnIC6oQAvvlxvOy0IAy4A95ywtTMK+TBLETlgmJhu6cHdlSnUAZa2tju6GLmtx4nszW82jdWD6fUDJIo2I4O/JxsYcKBj8ndRk3auu5LTSg7AqUnXSdnTARoy5Tae7GyqCAcrhYprNDiHEodnqBaAHlbrdXyfKMqCjEiED7dDRnZ8P+gNgZFNn5UlZgR1VpYqFcrb+sFWfHoHCQGRl1WHWPqoQVK+QM+C9I8lhkbqe126Nc0NXOTnmhA3arGT7hF1Xq9+5J27kkVilHIoSIWcaKd6jg5zsOYvofluJnL6+J+djOgLNTkAJnR6uE1+7yQFY7RwUEulZmx+31KT+3WN188nNzeX0hblJ3VGcntPU8VjdW+FBB9aJPR8i6iMzL7IQH3JnZIcQ4FDu9gBQ79Sr3QbLjQAeEAEryrBhQaMeICr/Y2aojdnw+gU0azk4yKNEotzQZ3HguqdAoY8UzY0cSHlKW4eR+BbaQoKrZbFJKY7sDpaxkDBSUhK8j0KPL7VUujMmas/O/NfsBGBtFICcoFyV1XUSwjBUemJcuVZ7NrITEtbqx1CXRWAHlQrtFGQbYotF1ZMTZiVnGMocOFVQ7N6GLQDMvsxPencj9WIQYh2KnFxhQaI9wHyTqEpbJZMKIcv9fydt0yli7D3Wi0+WF3WpGzYBCzcckilaQ9kCcLkkwoBz8xayEk+MROwVhYkcOFCyNfI3wkHIynZ08g86O/MysZlNESFgGb7vdxoYTSpZs9IfN27pjX9RSEVCWYsfrExEOhzIoMN+uiMoDHa6QjJX6ccUOa8Q29nBMJlNE55oQIth6rtmNFVpmNFrGcnlE4Hn+n4fVbApxHYMLQ4WhJbC9ActYhCQOxU4vYDabMLg0uDZCjVwAKstX0tnZdaBT869K2Yk1emCR4enIRolWxjIsdjRWRsiBf0Y6sSThzo4s9Q0uiyzRBUPK/sck09kJn9Crh7qEFT7VVn2hN+ru7GjqwI7AjrS27tjPkQHlZDo7aiclvGSi3mTev9AOs8k/6C68g65Zpx1fj/Dhlm6vULoD86zGA8r6ZSxtZyd8Crn6+ZlSygofXcAyFiHGodjpJZTcTku42JHOjl/kVJXkId9mgccnsPtg5ELQb2ReJ9CJlUzCl4EKIZTW81hLQCVaKyOSUsaK4uyEz9ppjLP0Fo28sDKJHq2B9mqti7qWYxGLpZsalf9u6/bEdBdkLiaZi0BtFhOk2eEMFzuB/FFpgQ0Wswn9C7VXhRhdFSEpC/uc1Bf0PLvx1nO9oYIRmR0dsWMPETuZUcqKyOzQ2SHEMBQ7vUQwpBxaxtraFCxjAX4XaHiUkPLGetl2nty8DhDp7LR0uZUWXaNiRzo7bU6PUrLZo1oCapQIZ0ejE0siX1c6SE2pyOwYdHb0HIzgRdxYSFmWsAB/KSVWZqjTmfx1ESaTSbf9XIoReV56e9GMtp1LwgW3FFlmU6gAkUQMFfQZHSroCzwvsu3c//ygWMoUsSOXgMpjo9ghxDgUO72EFDvqwYJCiGAZqyKYv5H/rZXb+SZKJ1ZPKQ27IMtwcnGeNWRvUDRK8oIrIxrbnPD5RHDNQzLKWFqZHdXKCCGEEo5OZmYnlrMTayWC3u4xLbrdXny67UDIbdFKWT6fCLaeJ7GMBQRzMuFiJ9yxkWJH/puRNBvciyVRVmsEnCP1jB2tpZdBsRNwdjwxylhhQwW1loAC/l1w8u1cGSJ25P8vZbdlJ8tYhBiGYqeXOKwsMrPT1O5CW7cHJhNCwsbS5Ql3drrdXuw44L9Na+FiTymVc04CF7JE5tWYTCbVhc+JxnYnXF4fLGYTquKY/SPFjhyktj8Q7B6sUQqTZaz9Ld1o7nQrpYmkZHas+rNm1MQUO3EMFvxs+0F0u32oKslDcZ5fvLRGCSmrhUgyd2MBkWUiibzwSnGitybE6F4sSbi72BVlxk7o8YW2nlt1yljhi0D1ylgmkynjVkbIfztS8NPZIcQ4FDu9hFwZoRY70tU5rCw/ZIbISMXZCRU7m+vb4RN+IZCMgXnhhF9o4s3rSOSFr6ndpZSwqkry4gpU9wuInQPtLv9AQbkqQmOG0MBiB2wWE7w+gbX7WgD4Q8HJ2AgtXyPWUMHgRV1bbOgtudRi6UZ/XueUMRUoCew3k4s+tZDhZLNJe6VCT1Daz13azk5pjDKW8jiDmZ3wbJMUWXo/y3BnR4oYrZIXEDlUUGt6skSZtZMhgwVl67kU/BQ7hBiHYqeXkF1EewOlFiAoZqSTI9HL7GyoC+Z1tCz9nhIUO/6LZ6It3MrKiDZnMJwcRwkLCK6nONTpwoEOF1weH0wmaA5MNJtNygXgq13N/mNIgqsDGB8qGCubEl6eicaSTf68zqljKxRnJ1oZKzg92Zr0fxf5OusywstTFRpdeEASnB2X/l4sAHBIMeoOFS96zo6cvxMeUHZYI18/k/Zjebw+xd2Tgp/dWIQYh2Knl5AX4w6XV/mltV2KnfLQeTlS7DS1O9GqushtDLSdp6KEBaguNIESxQFlenJ8zo66jKVsO4+jEwsA+gXEwYEOl+KGVRQ5dLMYMqS8anez8thkkOwyVqzMzu6DndjW2AGr2YRpo8tVYie2s1OQxHCyRDegrJPZCXd24s/shH5OyqoInflBEa3nsQLKMrPjC52grJVJU2byZIDYUZcxpdjhnB1CjEOx00vk2SyKWyEv3rKMNbIiVOwU59kwMHDxULs73wScnfEpaDsHVKWWwIVGtnAPKEzM2Wlqd8a17VyNFFgujw9bGvyf06AogmlIoEwoxY5cW9FTHAa3nhvO7MQoY8kurKOG9UNJng3FeXIbfRRnJwVLQCV6zlaL0o3l/5y1JmcDQcdLPi4W4aIw2l4sQL/1XL+MFXBrPGFlLA1nJ5NWRsjsWrHDiqKAAOYiUEKMQ7HTi4TvyFJPTw5H6chSrQroLWenw+WF2+sLTk+OsySkDqsmMmMH8F/c5F/t6/b5Rd7gKDu/pJiS3VtJc3aUzE7PnB2t6dRaLFHldQAYcnY6VWWsZKPv7MiAcng3Vs/KWMoesbA5O0YzO7HKWMHJyLHFTiaVsZRW/0Ib8m3+n3Mn10UQYhiKnV5Eye00d8Ht9WFXYGjgiDBnx39baEdWY5sTTe0umEzAmMrUiB31jJjWLncws1MYbxnLf55qZ0d2TBnFZDIpTtjavf7QsVYnliR8hk8y2s6B4MXUqLOjO2enILaz0+32YtlWf8v5qWNDxU60bqz2FMzYkSit567omR35eau74QDV8EHDmZ1AtqkzsvVci3jLWOFDBZ1RnCBbBgWU5efRr8CuGgeQ/uMipK9AsdOLqGft7DrYCY9PIN9mQWVxpGOhbD8PzNqRrk7NgELd/EJPsZhNKA6UQpq73DgQcEl64uzsSbCMBQQ7stbv9zs7Wp1YknAxlYy2cyCxdRFayIt4NGfnix2H0OX2YmCxAxMG+UuVsozVHtXZCYidFDo76pJJt9urOClSxJXm2xQn5EBH0N1JNKDc5vTAqxqmGKuM5TQ4QVkpYxlydjIns3NIJS4LFAFKZ4cQo1Ds9CKHqaYoS8dmeHlhyAJCycgwZ+cbVSdWKlEPv5OTiAfE7ez4hcbuQ13KX+bRhIoectaOLOFEc3bCxVSynJ3wi6keirOTFyuzo9+NJfM6p4ypULqq5K6r6JmdwKqIFGR2tObsyHO1mE3K8ZnNJiXbJUPK3W6v8rx4W8+F8J9zrMyOdHZcXh98PqE4NjGHCnqiz9kBAJs11AVKJyHOjk5pkRCiD8VOL6LO7GhNTlYjb9/e1AGfTygLQFOV15HIi01Da7fS0hy3sxN4vFzgWFHsSGjmTf8wkRVNMFUWO2BVicbkOTuxW8+73V7loql3UZcOSGu3R/lcwlkS2Id16tiBym0lcXRjFaWgjJWncWFVl7DUre7hHVkynGwyQXEMY2G3mhXnoqXLbbj1HPALHunCyK6rcKwGF4ECwTb1jMrsFNgUZ5fdWIQYh2KnFwkVO/rhZMBflrFZTHB6fNjX0qVydlLTiSWRYmdr4PjsFrPhC5Wk2GENuXjEsxNLTbjYiebsWC3mkL1ZSZuzY409VFBe1M0moEinlFQalocKZ8+hTmxpaIfFbMKJo8uV25VuLGfsOTvJXAIq0XIRlOnJYaWp8JCy2u3Sci/1UC8DlSIzL0brOeB335RuLKteQFkKmEBmJ1CejJbZyYwyVnBitRSD7MYixDgUO72IDCjXt3ZjU4PfqQlvO5dYzCYMC6yQ2NzQjs31fico5WUsRez436+8yB73oDqTyRTSDRVvJ5akf0FQ7NgsppgdVur3ScbGc8CYs6MOJ+td1G0Ws1Ly0crtyC6so4aWhQijeObsFKYgy6V1/s06U5HDV0bEu/FcUqJqP4+1LsJmMcMS+My7Pd7YZSwloBzq7GgPFcyc1nP5mfcrsCmfhdsrMsJ1IqQvQLHTi5QXOmC3muETwJo9/g6jEeXazo7/Pr/Y+eCbBjg9PuTbLBjaP76upniRFybp7AxIMPuidlYSCScDQH+VYKksyYvpDsiQckkci0tjIYcKenxCuUCGYzSEG20/1lKNEhagcnaiiR1X6ubs5Gu4CC1hG88l4WWseMPJEqVzTSV2opVBlY4st6qMFWtdRNhQwWgB5UwQFMFdZLaQBgWWsggxBsVOL2I2m5RZMTK3MVzH2QGCJa631tYBAMZUFcdVDkgE+Vf1NpWzkwgVqufFOz1ZonZ2tLadhyPLZcnK6wChF9lunVJW3GInLKTc7fZi2ZYmAMH5OhIj6yI6eyGgrG49Dzo2of82gisj/OcX7/RkiXqwYKyAMhDafu6J0Y1lM4fmcKLuxrJmYmbHDrvFDPlrgKUsQoxBsdPLqHMnlSUOpbShhQwpy7+Ux6Vovo4apfU34CQk6uyoBUe8M3Yk6syOOo+jx7AB/vfR2p+VKKGZEO0Li1GxozdY8LWv9qLD5cVhZflKy7nEUBnLlbqAsmZmR2d2TrmOs6M3e0gPOW25pdMVs/UcCAqyDpcXMvtt0w0o+28Xwv8Hh6HW84yYsyPLWP6yssxn0dkhxBjJ/1OQREUtdqKVsIDIPM+4Qb0ndiSJtnCrn5dwGUstdgw4O7MmVuGqaa2YM7kqoffTwmw2wW4xw+X1xXR2Yl3UtcSOzyfw14+2AQCunFYT4dwVO/zPcXp8cHl8mhdlZTdWCgLKWq3neo5N+MoIxQGK19lRfU7SUXJE2eYuBal6FpFN43MCQh0ft9cXHCqY4ZmdQ2Gh8DybBe1ODzefE2IQip1eJkTsRClhAZFiKNVt50DkDqNEy1jlyQgoq8TOYAPOToHdijvOnpDQe0XDYQuInR46O8HpwEGx8/43Ddja2IHiPCu+c+zQiOfIPUiAv5Sl5bTJOTu9NVQwfAmoROnG6mFmR71HLFZAGQh2zMlJ0kCUMpaqXOWJ6exkRhnL6fEqDo5ckKsMFnRzsCAhRmAZq5c5THXR1ms7l/QrtKOf6oKS6rZzIHnOjrzwlRXYEg7O+ue4+P/bSGYnVeRpXPDVxJ/ZCYqdJz70uzqXHjdMs6RpMZuULiu9UlYwoJyKdRH+XxFdWgHl8G6swM+8LeA4JCOgHGvrORB0fULEjl4ZS+WcuQNuGRBjXUSaxY78vM2mYFlTKS+60l9iI6QvQLHTy4SWsaI7O0BQEA0sdkTMnUkF4RemAQk6O9KFmnRYacLHYrWYlam81SnuQouGbL/Wm7UTb2ZHZl6+2nUIK3YchM1iwpXTanSfF6sjS1kEmtIJypGZnXAXsNhhVUpKTe3OhFvPtQLK0bqxZMdce3dwsrNekN+iFjs+X59YF6FeFSHPKzhYkM4OIUZgGauXiaeMBfjXSazceQjjBqXe1QE0xE5hYs7OyIoivP+TUzCwpGdh4fvOOxxbGtoxpjK6C5ZKZJlEz9lpNSp2AvfLx0tX55wjDkNllM+pOM+Kulb9jqzgItDe6cZSMjthIsZkMqGi2IE9h7rQ2O5Uus7idnaUgLLBMlaYs2ON0rFoMplgs5jg9vpXS0ghE3XOjie9mR31qggJV0YQEh90dnqZIf3yUV5kx6DSPENdSscO7w8AOGHkgFQfGgCNQXHFibtJIyqKonabGWHWxCrM+9aouAcbJhPF2dHZjxVrL5ZEvfl8R1MH3l7nHylw7ckjoj4v2uZztzfoTqRiqGB+lN1YWiJGlj0b25wJd2OFOjv+9zUyZ6ctIHa0SlJq1JvPg0MFI18/U9ZFHNIQlwU62+gJIdrQ2ellHFYLFt1yCswmU4ilrseFU4fguOH9UZ1g+3a8FDusMJn8rbkmU+ism1wlL6az47/IxnIw5EW/ucuNv328DUIA3xpbgTExRgoom8+dkWJHztgBUrsuwuX1wesTEEIo5TStLiv1YMEWg59LOOpyn2wl19uNBQT3Y8luLL1OLIl0foyWseQerXTR0qXh7Njp7BASDxQ7aaBfHNkbkym4NqI3MJtNKMmzoaXLjX4Fdt1JtLmEklvx9HDOTqA8U9fSjZe+2AMAuPbkkTHfvyjKYEEZTrZbzJoX7J4SMlTR7Q3JLcVydlp1hg/GQopCtZtkZKigkTIWEBo8jjpBWW5UT3MZ65DGxGr5eXDODiHG4JWMRCAvYgN6IRDdF1CvI9Ai3oByu9MDp8eHyUNKcfyI/jHfP9rmcxlQLUhBJxYQmmXpcnuV/Eixw6ophKWzs/tQpyIk4nV2ih1WhOuVqN1YAedNzhvS24slUTafq8pYmdyNpV4CKuEyUELig2KHRCAvTom2nWcb0VrPXR6fUkowKnYk1548wlAWKdiNFenstKdwxg7gd/pkCanL5dVdAiqRYmdrg3/diLp1Pp73DM/55EXZdaZkdmQZS2fGjkQtYpxRyliZktlpUaYnBz+TPDudHULigWKHRCAvyom2nWcbsttHa4KydHVMqhkoeuTbLIqDMKRfPs6YaGzSc7EjirPjTN2MHYl6sKDejB2J3Im2JSB2yvJtCYXL1SUbu9UcdSecFKPtBp2dYBZHwBUoTWbyItBDqiWgkgKb/98EMzuEGINih0RQQmcnhGjOjhQ7xQ5rzCWtJpNJuWB9/8ThhvNQ0fZjtadwVYREvTIiVslOOjsdLmNulx6lGvkUPcIzOzHLWDKg7FE5O1HKWK40r4s41BmZfVKGPdLZIcQQDCiTCIYGBvgNNzD0MBcIbtXWd3b0yjrh3DRjNFbtatZcDaGHLGO1apSxZBmjpy3+0VDPdGnu1B4oKKkoCp0XFG/buaRUY6aMHsqcHYNlLCky3b4Yc3ascs5OppSx1GIn4OxQ7BBiCIodEsG8b43CkdVlOHlMRboPJSOI5uwYHSgoufS4Ybj0uGFxvb/sxtJqPZfdWAUpmLEjyVOLnRjiLnwuU6LOjrqMFa3tHAgGlNsMl7H8Yqjb7YUImDaZnNnRKmMp3VgsYxFiCJaxSARFDitmTqyKOsgtlwjO2Yni7CR4UTdCtDJWRwqnJ0uk2Oh2e5XpyXqbzAvs1pBAcryrIiSlIWIn+r9DeXyys8pqMKCsXrWgJXas5vRndoQQmotXg0MFuS6CECNQ7BASg+AEZf3MTirFTkmUbixl43kqA8qqNmcj+65kbgfogbOjdjFiuFbh04+NZnbaVQMZNTM71vRndrrcXkXElXFdBCEJQ7FDSAyiZXZ2H+wEgKi7rXqKIWcnhQHlfNV+rFiZHSA02J6MgHK0tnMgMm9jtBtLdrKZTdAMi9syoIwlw8k2S2gLfz5bzwmJC4odQmIQLbOzOdBiHWvlQ0+QAeVOlxeesAtvRwo3nkvUmR0j+66S4eyEdGPFcHbCy1yxA8r+++Vnpzd52p4BrefNqoGC6hZ+ZRwAxQ4hhqDYISQG0dZFyHkyowembiu7en5PeEi5sxcDyt1un2Z+JJykix2DreeSeJ0dvcWh6oWh6UIvIyV/3gwoE2IMih1CYhAM6Ib+hd/u9GBvcxcAYFQKxY7NYlaOIbyU1RsBZXU+JNZQQSA5ZSx1PsURsxsrXrEjnZ2A2NEpkwXn7KSzjBW5BBRQuW10dggxBMUOITFw6JSx5EqE8iJH3Msu46XIIUPK4WIn9WWsfFXnj+LsRMns9LqzE28ZK9BlJT87rRk7AGC3Rs/stDs9uPRvy/GPT3dEfb+e0KwjLqWz4/T4t9ETQqJDsUNIDPQCyr1RwpKU6Gw+l+5EvPun4iEvcP5N7S7lwmrU2UlUBGrNlNE9vjDnJ9ZkapnZkSVAPbGjrIvQGSr4+Y6D+GTLATy9bEfU9+sJzRozdoDQidlcBkpIbCh2CImBXkBZhpNHV6Ze7Oh1ZPXKnJ2AkKpr6QbgFwfRZt8k29mJNWcnvPVcL4MjsYU5O3oB5eBuLG3nRA6UlP+bCpo1picDoQKNHVmExIZih5AY6A0V3NLQBqB3nB1l87kz9MIqL3S90Xpe3+oXO7EETDLETp7NolzQY8/ZCc/sxBgqaA11dmKJHZfXByEiBY/sTGvudGvenwxk63n4xGqz2RSyoJUQEh2uiyAkBnpDBaWzM2pg6trOJXrOjrIItBe2nu8PODuxpiIPKsnDjPEDUZxniylUolFWYEN9q9PABOXQ+2OWscyhi0P1nCD17R6fiBBR0tHx+AQ6Xd6UuGvNOgFlwC8Cu9xeOjuEGCCtzs6CBQtwzDHHoLi4GAMHDsS5556LjRs3hjymu7sb8+bNw4ABA1BUVIQLLrgA9fX1IY/ZtWsX5syZg4KCAgwcOBC33norPB6OUSfJQQZg1ZmdbrcXuwIDBVPZiSXREjtCiF5ZBJoXNq03WjgZ8LsOf5t7DP548RE9el/pCsXejZVYN1ZnjDk70gECtEPKraqfRXOKSlnydftpCExOUSbEOGkVO0uXLsW8efOwfPlyLFq0CG63GzNnzkRHR4fymFtuuQVvvPEGXnrpJSxduhT79u3D+eefr9zv9XoxZ84cuFwuLFu2DM888wyefvpp3HHHHek4JZKF5FmD5QwZ0N3W2AEh/O5DeVFqO7EAVRlLdYFVd+L0xpwdidEN7z1FiqpY5xYhdszGtp4rzk6MMhYAuD0aZaxOt+Z/JxPZel6qITCDU5T5hx0hsUhrGevtt98O+f7pp5/GwIEDsXLlSpx88sloaWnBk08+ieeffx6nnXYaAOCpp57C+PHjsXz5chx//PF49913sX79erz33nuorKzEEUccgXvvvRe33XYb7rrrLtjtqb8QkexGfbF3erwosFuxWZXXUU+2TRXSuVF3Y3WoBgwWpDKzEyY29JaAJpvLTxgGu9WME0dVRH2c1WKGxWxShJ9NR7xIgotAA86OjhNkVYkmrVk7raqfRXOXK+p7JooSUC6M/MwL7MzsEGKUjAoot7S0AAD69+8PAFi5ciXcbjdmzJihPGbcuHEYOnQoPv30UwDAp59+ikmTJqGyslJ5zKxZs9Da2op169Zpvo/T6URra2vIFyF6qJ0DGVLe0ot5HUC7jCUv1vk2Cywx3IyekBcmHhLdZB4vZ00ejGe/f1xI4FkP9THGLGMFPispjvScHZPJFHU/llrspKIjy+cTUXeRSRHOzA4hsckYsePz+XDzzTdj2rRpOPzwwwEAdXV1sNvtKCsrC3lsZWUl6urqlMeohY68X96nxYIFC1BaWqp8VVdXJ/lsSDZhtZiVv/LlX9Gb66XYSX1eB9DefN6utJ2nroQFRDo7qdzwnijqwYKxd2OF/trTEzv+19Lfj9WiEjjNKShjtTk9kPMCtQRmgTLskWKHkFhkjNiZN28e1q5dixdeeCHl7zV//ny0tLQoX7t37075e5K+TV5YSHlLY+8NFAT0nJ3Uz9gBIof6laZ4WnQiOOJxdsLEkN5QQfVraTo7XcGfRUsKnB2ZA8q3WTQ70hhQJsQ4GSF2brjhBixcuBAffPABhgwZotxeVVUFl8uF5ubmkMfX19ejqqpKeUx4d5b8Xj4mHIfDgZKSkpAvQqIR3I/lhcvjw44mf4i+NwYKAtoB5fbAULxU5nWAyIByb2V24kF9jNZYAeWw+6MNIYw2WDA0s5N8sXNIZ3qyJBhQptghJBZpFTtCCNxwww149dVX8f7772P48OEh90+dOhU2mw2LFy9Wbtu4cSN27dqF2tpaAEBtbS2+/vprNDQ0KI9ZtGgRSkpKMGHChN45EZL1OKzBMOjOAx3w+ASKHFZUleT1yvsXa6yLkFu7U7kqAtAQO72U2YkHtTsTrSwFRAaYoz3erpPZ8flESE4nFc5OUOxoO2n5XAZKiGHS2o01b948PP/88/jvf/+L4uJiJWNTWlqK/Px8lJaW4uqrr8aPf/xj9O/fHyUlJbjxxhtRW1uL448/HgAwc+ZMTJgwAZdddhkeeOAB1NXV4fbbb8e8efPgcMQONhJiBIdq8/n+lmBepzc6sQCV2FF1YHW4Ur8EFNDqxurjZSxzHJkdq3YZq8MVzNMAqWk9b4kyYwdQZXZYxiIkJmkVO48//jgA4NRTTw25/amnnsIVV1wBAPjjH/8Is9mMCy64AE6nE7NmzcJjjz2mPNZisWDhwoW4/vrrUVtbi8LCQsydOxf33HNPb50GyQHkyginx9vr4WQAKAqInXanBz6fgNlsUu3FSrGzk6ZurHhQ78eKWcayhJex9D8/ZWVE2Jyd1rBJ1ilxdjpilLHo7BBimLSKHSP7ZPLy8vDoo4/i0Ucf1X3MsGHD8Oabbybz0AgJIU/l7PR2OBkIdmMJ4XcVivNsqo3nqf2/sdViht1iVmbNlGRgZsehmrIca85OMrqxwp2cVMzZkXuxdMtYgZ87MzuExCYjAsqEZDrBbiwvNtcHBgr2UjgZ8JdpZBeRDCl3OnunjAUExYTZBBT3wvvFi9rZCS9ThWMPd3YSyOyow8lAirqxAq+pFwjnUEFCjEOxQ4gBpNjpcHqxTXZi9dJAQcA/4C68I0tZAprigDIQLJmU5ttgTuEAw0QJcXZizdkJE0OJtJ5LIVISKC+mIrNzKMoSUCD4M+G6CEJiQ7FDiAHkBXFzQxtcHh/ybGYcVpbfq8cQ3pHVW3N2gGBIWa+kkm7y1JmdWFvP43B2lMxOWOu57MQaOqDA/323R5nInCyalTJW9NZzBpQJiQ3FDiEGkM7Our3+1SIjK4p63eEIHyzYIctYveDsSDGRidOTgVBnJ9rcHCCyWyuqsyO7sTzhZSz/z2Bo/wLltrbu5Lo7zWw9JyRpUOwQYgAZUF63z7+/rTfDyZJiR6CMFShfyYByQS84O3mKs5OhYkfdem5N4lBBs3ZmR5ax+hfaFbGZ7JURMqDM1nNCeg7FDiEGkAFYOdtmdGXv5XUkReFlrICzU9QbZayA2MtYZyek9Tx5QwX1MjutSmbHpnwmyQ4pN8eYoJzHCcqEGIZihxADqMskQO/O2JGEl7HSEVDOxFURQNB5AwyUsRIYKhiR2QkIztJ8m7IrLJkrIzxen1Iq0ytjsRuLEONQ7BBiAHUAFkhPGSt887kMKPeGsyMzS5m4BBQIc3Zibj2PZzeWTuu5dHbybSjND3RkJVHsqF9LT2AGu7EodgiJBcUOIQZQ74eyW8whwdTeItLZ6Z1FoABQHTjfkRWFKX+vROjJ1vPoc3b893kixI7/Z1CSZ1PWZ7R0Jm+wYFO7K/D6Vt3uMnU3lpEBrYTkMpk3HYyQDERdJhleXhizvTkVhIudYOt56stYPz59DGZOqMSRQ/ul/L0SIVyMRiNcDCXUeq4uY6Ugs7M9MMupplxfXEpnRwjA6fFFLGwlhAShs0OIAdRlklG9ODlZTbGqjOXzCaV80RtzdvJsFhxd0x+WDBwoCIQ6O7HLWEkcKphvVQLEyezGkmJnuAGxA7D9nJBYUOwQYgC1s5OOvA4Q6ux0qkKpqd6N1RcInaAcK6AcxyLQQBt7xJwdVTdWSUqcHf/+tWhiR+4sAxDy74EQEgnFDiEGUJcIenNNhBoZRG7r9qAz0IllNoUKsVwlZDdWnM6OkcyO2tnxeH3KCILSfFvQ2Umi2NnW6Hd2RlREF9ZKbofODiFR4W9JQgygFhTpaDsHVGUsp1tpOy+0W2EyZWZpqTeRPx+r2RTz8+jpugjZEg743bZUZnZGRHF2AE5RJsQoFDuEGEA6BxazCTXlvd+JBQSXTrZ1e5S8TkEvhJP7AvLnE6uEBUQGmOMdKihLWIV2C6wWs6obKzlip6XTjQMd/m6saAFlIDhrh8tACYkOxQ4hBqgqzQMATBhUElIy6U3UW88VZ6cXwsl9ARkyjhVOBuJcF6ExZ0fdiaX+32Q5O9sCeZ3KEkfMGUpcBkqIMfibkhADjKwowovXHq/Mm0kHMqDs9QkcCMxhYTjZjwwJFxsQf+EdZdEyPtL1UYudFtVAQQCqzE5y5uwY6cSSsIxFiDH4m5IQgxw3YkBa37/AboHZBPgEUNfaDaB3Zuz0BYaXF+JXZ03ACANDD00mE2wWE9xeAbvVHDXjI/dsuTyqzI5qoCAQFD3dbh+63d4ez7sJip3Y2TA6O4QYg2KHkD6CyWRCkcOK1m4P6qXYobOjcPWJww0/1mYxw+31Rp2x43+cfhlL7SZJEdra5e6x2NlmMJwMcGUEIUZhZoeQPoTM7exv8YudAmZ2EkLmdmKJnehlLP9nbzabkjprJ9h2HlvscBkoIcag2CGkDyFzO/UBsVPEMlZCyC4ro6slPOrWc9VAQYlc1tnTWTs+n8COeDI7djo7hBiBYoeQPoS8wMrMTm8sAc1GZNdWtLZzQD1nR78bS/3fPW0/r2/rRpfbC6vZZCgMn2/z//yZ2SEkOhQ7hPQhpLOjBJTtdHYSQQaPY4udyMxOiwwoq8VOgX/WTk+dne2BEtbQ/gWGZgbl2/2PYTcWIdGh2CGkDyHFjiuwq4lzdhJDipxYYkdrXUSwjBX87JM1a2drHCUsIOjsUewQEh2KHUL6EMWqnAjAgHKiyIByzMyOElBWr4uILGOVKWWsns3akc6OUbEjO7+4CJSQ6FDsENKHKMoLFTcMKCeGXAZqOLPj0R8qCCTP2VG2nRvoxAKC3Vh0dgiJDsUOIX2I4jCxw4ByYtiUgHJ0sag5ZyeQ2QlxdpK0+Ty4ANTYslllgrKbu7EIiQbFDiF9iPAyFocKJobR1nPNzE53pLOTjDk7Lo8Puw91ATA2YwdQTVCms0NIVCh2COlDlIQ5O1wXkRhGhwoGt577Mzvdbq9S0lL/LJQ5Oz1oPd91sBNen0Ch3YKBxQ5Dz+EEZUKMQbFDSB8ivIzFbqzEsBnN7FhD5+zITiyzCSEbyWVJq7UHzo6yE6uiMOq+LjWcoEyIMSh2COlDRJSxKHYSQhkqGKsbyxzM7AghQkpYakFSloQ5O9saA+Fkg3kdgBOUCTEKxQ4hfYgIZ4dDBRPC+FBB//1CAF6fCHZihYlOdTeWEAKJsD3OGTuAKqBMsUNIVCh2COlDFDnYjZUM7FaD6yJU97u9QrMTCwh2Y3l9Au3OxDqj4tl2LlGGCrKMRUhUKHYI6UOoy1h2iznmxZpoE++6CABw+3yqMlaoyMyzWZTXSrQjS2k7N9iJBQSdHY9PhMwCIoSEwt+UhPQh1M5OATuxEkZmdmJ2Y5lVzo7Hp1vGAnrWkdXW7UZjmxMAUBNPGUtVxqS7Q4g+FDuE9CEsZpMieDhjJ3Gq+xWE/K8eZrNJaVP3l7EiV0VIetKRJV2d8iKHppDSw2YxwRI4PuZ2CNGHvy0J6WMU51nR7vRwxk4PuOG0UTh9QiUmDCqJ+VibxQyPzwu314fW7siN5xIpdhLpyEqkhAUAJpMJBTYL2pweOjuERIHODiF9DNmRxXBy4tgsZhx+WCnM5tjzbGRux+X1oaUzcuO5RIaUE8nsbGuMP5wsyVPaz7kyghA9KHYI6WPIkHJ4ZxZJDXZrcGWE1sZzSUkPMjvbEmg7l3CwICGxodghpI8hRU4BZ+z0CsrKCI/Q3IslKcv3DxZMxNlRtp0nIHa4MoKQ2FDsENLHkGUsTk/uHaTYcXmjd2MFBwu64np9IQS2yzJWhfHpyRIuAyUkNhQ7hPQxZBmLAeXeQWZ23F6fMlRQ09lJMLPT2OZEh8sLswkY2j96d5gWyhRllrEI0YVih5A+xpB++QCAQaX5aT6S3CC4+Tzo7JTmR7pqpQlmdrYGXJ3q/gUJDYksoLNDSEzogxPSx7jihBqMKC/EyWMq0n0oOYEUO063D23dUcpYCTo72xNYE6EmP9CVx8wOIfpQ7BDSxyh0WDF70qB0H0bOIMtYzV1u+AI7PqPO2YnT2QmGk+PP6wBAvs0vxljGIkQflrEIISQK0tk50O5f52C3mpFni8xLlSU4QVnZdh7nQEGJsgyUzg4hutDZIYSQKMgczYEOf5eV3joH6ey0OT3weH2wWqL/LdnS6cbra/bhi52HACRexspjQJmQmFDsEEJIFKSz0xRwdrTCyf7bgyKotduD/oX2iMd4vD58tLkJL6/cg0Xr6+Hy+jeVF+dZMXFw7NUVWhTYM2vOzo9fXIWvdjfj1R+egLKCyM+AkHRAsUMIIVGQmZ2m9oCzo5HXAQCrxYwih39vWUuXO0LsvLuuDr98ba2y3RwAxlUV4/+mDsG5Rx6WsDBQWs8zYF1EW7cbr63aC58A3v+mAecfNSTdh0QIAIodQgiJSnhmJ9pW8tJ8G9qdHjR3ugCElqX++N5mNLY50b/QjnOOGIwLjhqCiYNLYDLF3s8VDWWoYAaUsVbtblZC3B9tbqLYIRkDxQ4hhETBrogdv7OjtRdLUppvw97mroj28/rWbmzY3wqTCXj3lpNRXuRI2vFl0rqIL3YcUv77o81NEEL0WMwRkgzYjUUIIVFQnJ2OgLOjk9kB9Kcof7ipEQAw+bDSpAodILMWga7cGRQ7Te1OfFPXlsajISQIxQ4hhETBZpXrIvz1mVjODhApdpYGxM4pKRgEmZchAWWvT+CrXX6xI6d8f7y5KZ2HRIgCxQ4hhETBFtZCHi2zI50d9WBBr0/go8BF/5SxyRc7BRnSev5NXSs6XF4UO6y4vHYYAODDzY1pPSZCJBQ7hBASBXu42Ini7JRoODur9zSjpcuNkjwrpgwpS/rxZcrWc1nCOmJoGU4dOxAAsGL7wYworxFCsUMIIVEId3ailbHK8v3t42pnZ+lGv7tx0uiKmIMGE6EgQ7qxpNg5elh/jB5YhMoSB5weX0homZB0QbFDCCFRsFpCu4litZ4Doc5OKvM6QHCCcrozO1LUHF3TDyaTCSeO8p/vR1tYyiLph2KHEEKiEJHZMdSN5W9TP9Thwuo9zQCQsi31cjeWy+ODVw656WXqWrqxt7kLZhMwpboMAHDS6HIAwEebGFIm6YdihxBCohCe2YmnG+ujLU0Qwj8puao0LyXHJ8tYQPpKWV/sPAgAGD+oBEUOv/iaNsovdtbvb1VWbRCSLih2CCEkCrYEylgysyPzOqkqYQGAw2qGnNuXrpByMK/TT7mtotiB8YP8+74+2UJ3h6QXih1CCImCzRr6a7I4T7+MpXZ2fD6R8rwOAJhMJtV+rPSKnak1/UNuP1mWsjhvh6QZih1CCImCOrNT5LBG7aiSmR2nx4evdjejqd2JArsFU2v66T4nGeSncdZOp8uDdftaAQBTh4We54mK2GmEEOnJExECcDcWIYRERZ3ZKYni6gB+MWQxm+D1Cbyxeh8A4ISR5XBYLVGf11Py7Ragwy88eorT48XWhg5sqm/Dxvo2bKprw97mLtxy+hjMmlgV8fjVu1vg9QkMKs3DYWX5IfcdU9MfDqsZ9a1ObGlox+jK4h4fHyGJQLFDCCFRUDs70QYKAv6SUmm+DQc7XFi4xi92UjE1OZxkODstXW5c+dQKrN7TotnV9YtXvsbxIwZEBLRXBsLJ4a4O4G+LP3Z4f3y0uQkfbm6i2CFpI61lrA8//BBnn302Bg8eDJPJhNdeey3k/iuuuAImkynk64wzzgh5zMGDB3HppZeipKQEZWVluPrqq9He3t6LZ0EIyWbUAeVYYgcI5naaAlvSTxmderFTkIQpyq9+uQdf7mqG1ydQkmfFsTX98b3jh+KecyZiZEUhDnS48MjizRHP+0LmdTTEDhBsQf+YqyNIGkmrs9PR0YEpU6bgqquuwvnnn6/5mDPOOANPPfWU8r3DEbox+NJLL8X+/fuxaNEiuN1uXHnllbj22mvx/PPPp/TYCSG5gTqgHK0TS6J2PkaUF2LogIKUHJeaZAwWfPWrvQCAX5w5DtecNAImU1DkDRtQiLl/X4Gnl+3AJccNxciKIgCAzyfwpWpyshYnja4A8A2WbzsIp8eb8pIeIVqkVezMnj0bs2fPjvoYh8OBqqrIOjEAbNiwAW+//TY+//xzHH300QCARx55BGeeeSZ+//vfY/DgwUk/ZkJIbhGS2YkyUFCiFjupGiQYTk9XRmxtbMfqPS2wmE04/6ghIUIH8HeTTR83EIu/acCvF67HU1ceCwDY0tiO1m4P8m0WjB+kXaIaV1WM8iIHmtqd+HJnM2pHDkjoGAnpCRnfjbVkyRIMHDgQY8eOxfXXX48DBw4o93366acoKytThA4AzJgxA2azGZ999pnuazqdTrS2toZ8EUKIFurMTrSBghLZkQX0Tl4H6Pky0NcCrs7Jo8tRXuTQfMwv54yHzWLCBxsb8cHGBgDBFRFHVJfpdqmZTKbgNGWWskiayGixc8YZZ+Af//gHFi9ejN/+9rdYunQpZs+eDa/X/3/ouro6DBw4MOQ5VqsV/fv3R11dne7rLliwAKWlpcpXdXV1Ss+DENJ3Ue/GiqeMZbeacfzw3nEx8m1+xykRZ8fnE0oJ67yjhug+bkRFEa44oQYAcO/C9XB7fcrk5KNjtNafGJim/MHGRvjStNKC5DYZLXa+853v4Nvf/jYmTZqEc889FwsXLsTnn3+OJUuW9Oh158+fj5aWFuVr9+7dyTlgQkjWYY+jGwsAygr8m8+PG95fcVxSjXST3l5bh+44Bc8XOw9hz6EuFDmsOH18ZdTH3jh9NAYU2rGtsQP/+HSnktfRCydLThpTDrvFjA37W3Hn6+s4c4f0OhktdsIZMWIEysvLsWXLFgBAVVUVGhoaQh7j8Xhw8OBB3ZwP4M8BlZSUhHwRQogW8ZaxzjvyMJwwcgBunjEmlYcVwveOH4aSPCtW7W7GT15aHZd7Il2dMw6viinOSvJsuHXWWADAHxdtwo4DnTCZgCOHRhc7A4vz8MD/TYbJBPxz+U7c/9Y3FDykV+lTYmfPnj04cOAABg0aBACora1Fc3MzVq5cqTzm/fffh8/nw3HHHZeuwySEZBEhrecxhgoCwPDyQjx/zfEx3Y5kMry8EP/vsqNhs5jwvzX78ft3Nxp6Xrfbi/8F5gGdf+Rhhp5z4dHVmDCoBO1O/wDDMQOLDYnAc488DL85bxIA4P99uA1/WrzF0PsRkgzSKnba29uxatUqrFq1CgCwfft2rFq1Crt27UJ7eztuvfVWLF++HDt27MDixYtxzjnnYNSoUZg1axYAYPz48TjjjDNwzTXXYMWKFfjkk09www034Dvf+Q47sQghSSGeoYLppHbkANx//mQAwGNLtuKFFbtiPmfJxga0dntQVZKH40YYyxdZzCbcefYE5ft4VmFccuxQ3HGW/7l/fG8T/vrhNsPPJaQnpFXsfPHFFzjyyCNx5JFHAgB+/OMf48gjj8Qdd9wBi8WCNWvW4Nvf/jbGjBmDq6++GlOnTsVHH30UMmvnueeew7hx4zB9+nSceeaZOPHEE/HEE0+k65QIIVmG3RpfGSudXDB1CH40fTQA4JevrY3Z/fTKl/4S1jlHDobFbIr6WDXHjRigOEGnT4ie8wnnqhOHK6Ww+97cgH8u3xnX8wlJBJNg4RStra0oLS1FS0sL8zuEkBAOdrhw1L2LAACf/Py0iP1PmYYQAre8uAqvrdqHYocV//nhCRijsabhUIcLx/7mPbi9Am/ffBLGVcX3u8/rE9hzqBPDBhQmdJwPvP0NHluyFQBwxQk1mDG+EkfX9FMGJBJiBKPXb+7GIoSQKDj6kLMD+Ofa/Pb/JmNfczdW7DiIK5/6HH+bezTGDwq9EPzv6/1wewXGDyqJW+gA/nJWokIHAG6dNRadLi+eXrZD+cqzmXH8iAE4eXQFTh5TgZEVhREDDglJBIodQgiJQqHDihtPGwWzyYQiR9/4lemwWvD/LpuK8x9fhu1NHfj2nz/GTdNH47pTRirD/2QXltFgcrIxmfzZn+NHDMB7G+rx4aZGNLQ5sWRjI5Zs9JffKoodOHZ4fxxb0x/HDu+PsZXFMMdRbiNEwjIWWMYihGQnjW1O/PLVr/Hu+noAwOQhpfjDhVNgt5pxyu+WwGwCPp0/HZUleWk+Un/57Zu6Nny4qREfbm7E59sPweX1hTymNN+GY2r64cRR5ThxdHKdn4a2bnzwTQPOPfIw7u/qQxi9flPsgGKHEJK9CCHw31X7cMd/16K12wO7xYzJQ0rxxc5DOGl0Of55dWaO6eh2e7F6dzNWbD+IFTsOYuXOQxGLTgeX5uHE0eU4aXQFTh5dgdKCxMqMHU4PznvsE2yqb8fltcNwzzmHJ+MUSC9AsRMHFDuEkGynvrUbP//PGnywMdih9YcLp+CCqforIjIJt9eH9ftasWzrAXy8JdL5Kc234a+XH41jh2tvX9dDCIEb//UVFq7ZDwAwmYBXfzgNR1SXRX3OS1/sQaHDijmTByV0PiQ5UOzEAcUOISQXEELgpZV7cO8b61GSb8M7t5zcZ3JI4XS5vFix4yA+2tSI9zbUY8eBTtitZjxyyZGYNVF/gn44T368HfcuXA+r2YQjh5bh8x2HMH5QCd64YZructNnlu3Ana+vAwD85rxJ+O5xQ5NyTiR+KHbigGKHEJJLdLu98PhEnxU64XS7vbjh+a/w3oZ6mE3AfedNwiXHxhYgK7YfxCV/XQ6vT+DOsyfg21MGY/qDS9Hc6cYvzxyPa04eEfGclTsP4uL/txyewEoOswn429yjcdq4+OYNpRohBNqdHhQbWF7blzF6/e5T6yIIIYT0nDybJWuEDuA/n7987yhcfHQ1fAKY/8rX+NPizVH3bzW0dmPe81/C6xP49pTBuOKEGgwocuAXs8cDAB5ctAl7DnWGPqetG9c/+yU8PoE5kwfhwqlD4BPAvOe+wpo9zak8RcN0u7146YvdOPNPH2PSXe/iV6+tjXs5bDZCZwd0dgghJBsQQuAP727Cnz/w79267PhhuOvbEyOmQ7s8Pnz3r8vxxc5DGFtZjFfnnYACu1V5jYufWI4V2w/itHED8eTco2EymeD2+nDp3z7Diu0HMXpgEV6bNw12qxlXPf05PtrchPIiO1794TRU9y/o9fMG/J13zy7fiec+24mmdlfIfWMri/HId4/UHC6ZLIQQeGddPd5dVwcBwGwywWo2wWz2/6/FbMK8b41CRbEj5mvFA8tYcUCxQwgh2cMzy3bgrjfWQQigZkABRlcWY3h5IWoGFKKmvABvfr0fzy7fhWKHFa/feCKGl4cOR9zS0I7ZD38It1fgsUuPwpmTBuHehevx5MfbUeSw4r83TMPIiiIAQFu3Gxf9v+XYsL8VIyoK8Z/rTkC/QjsAv8vy4aZGvL22Dqv2NGPKkDLMmTQIJ40pT1p7+9q9LXjqkx14Y/U+JbA9qDQPc0+oQc2AQtz+2lo0tTvhsJpx+1kT8L3jhiZ9UOOOpg7c+fo6LN0UfT3J+z85BSMCn1uyoNiJA4odQgjJLhau2Ycf/3s1XB6f7mOeuGwqZuqEmR9ctAl/WrwZA4sduHnGGPzi1a8BAH/53lSccXjoc+paunHeY59gf0s3jh7WD1dMq8Hba+vw/jcNEe3yAFDssOL0iZWYM2kQjh8xAPWt3dh5oBM7DnRg54FO7DzQAavFjJNGl+PUMQMxdECoW+Ty+PDW2v14ZtkOfLmrWbn9qKFluOrE4Zg1sUpZYNvU7sRPX1qtDGqcOaESv71gMvoV2uHzCTg9Pjg9Xjg9Phxod6GutQv7mrtR19KNfS1daGh1orp/AU4dW4Fpo8pDyp/dbi/+snQrHluyFS6PD3aLGZfVDkNVSR68QsDrC/26+sThihBMFhQ7cUCxQwgh2UdTuxPr97Vix4EObGvswI4DHdjR1IH9Ld248bRRuOG00brP7XZ7Mfvhj7C9qUO57fpTR+K2M8ZpPn5jXRv+7y/L0NbtCbl9UGkezji8CscNH4DPth/Am1/vR32rM67zGF5eiFPGVOCk0eVYs6cFz6/YhcY2/2vYLCacOWkQrjihBkcO1d5A7/MJPLVsB+5/awPcXgGbxe/suL3xXf6tZhOOrumHU8cOxGFl+fjDuxux44A/13TiqHLcc87EpDs3saDYiQOKHUIIIeEs29KE7/7tMwDAtFED8MyVx+q2owPAsq1NuPYfK9G/0I7Zh1fhjMOrMGVIWciKC59PYOWuQ/jfmv148+v9aGhzIt9mwbABBagZUIhhAwowbEAhmrtcWLqxESt3HlI6v9QMLHbg0uOG4ZLjqjGw2NgE7LV7W/CjF77CtsaOiPvMJqCswI5BpXmBr3wMKstDeZED6/e1YsnGBkXYhB/HHWdPwJxJg9Kyx4xiJw4odgghhGjx0Hub8NWuZjx40RQMKIodrvX5BEwmGLrw+3wCLV1ulBXYdB/f2u3Gsi1NWLKxEZ9uO4DK4jx8r3YYzphYBbs1/oZqua3ebjXDYbXAYTXDYTVHFXGSHU0dWLKxAUs3NWJTfTtmTqzEj08fk9b2doqdOKDYIYQQQvoenLNDCCGEEAKKHUIIIYRkORQ7hBBCCMlqKHYIIYQQktVQ7BBCCCEkq6HYIYQQQkhWQ7FDCCGEkKyGYocQQgghWQ3FDiGEEEKyGoodQgghhGQ1FDuEEEIIyWoodgghhBCS1VDsEEIIISSrodghhBBCSFZjTfcBZAJCCAD+VfGEEEII6RvI67a8jutBsQOgra0NAFBdXZ3mIyGEEEJIvLS1taG0tFT3fpOIJYdyAJ/Ph3379qG4uBgmkylpr9va2orq6mrs3r0bJSUlSXvdTIPnmV3kwnnmwjkCPM9sg+cZiRACbW1tGDx4MMxm/WQOnR0AZrMZQ4YMSdnrl5SUZPU/TAnPM7vIhfPMhXMEeJ7ZBs8zlGiOjoQBZUIIIYRkNRQ7hBBCCMlqKHZSiMPhwJ133gmHw5HuQ0kpPM/sIhfOMxfOEeB5Zhs8z8RhQJkQQgghWQ2dHUIIIYRkNRQ7hBBCCMlqKHYIIYQQktVQ7BBCCCEkq6HYSSGPPvooampqkJeXh+OOOw4rVqxI9yH1iA8//BBnn302Bg8eDJPJhNdeey3kfiEE7rjjDgwaNAj5+fmYMWMGNm/enJ6DTZAFCxbgmGOOQXFxMQYOHIhzzz0XGzduDHlMd3c35s2bhwEDBqCoqAgXXHAB6uvr03TEifH4449j8uTJytCu2tpavPXWW8r92XCO4dx///0wmUy4+eablduy5TzvuusumEymkK9x48Yp92fLee7duxff+973MGDAAOTn52PSpEn44osvlPuz4XdQTU1NxM/SZDJh3rx5ALLnZ+n1evGrX/0Kw4cPR35+PkaOHIl77703ZMdVUn+egqSEF154QdjtdvH3v/9drFu3TlxzzTWirKxM1NfXp/vQEubNN98Uv/zlL8Urr7wiAIhXX3015P77779flJaWitdee02sXr1afPvb3xbDhw8XXV1d6TngBJg1a5Z46qmnxNq1a8WqVavEmWeeKYYOHSra29uVx1x33XWiurpaLF68WHzxxRfi+OOPFyeccEIajzp+Xn/9dfG///1PbNq0SWzcuFH84he/EDabTaxdu1YIkR3nqGbFihWipqZGTJ48Wdx0003K7dlynnfeeaeYOHGi2L9/v/LV2Nio3J8N53nw4EExbNgwccUVV4jPPvtMbNu2Tbzzzjtiy5YtymOy4XdQQ0NDyM9x0aJFAoD44IMPhBDZ8bMUQoj77rtPDBgwQCxcuFBs375dvPTSS6KoqEg8/PDDymOS+fOk2EkRxx57rJg3b57yvdfrFYMHDxYLFixI41Elj3Cx4/P5RFVVlfjd736n3Nbc3CwcDof417/+lYYjTA4NDQ0CgFi6dKkQwn9ONptNvPTSS8pjNmzYIACITz/9NF2HmRT69esn/va3v2XdOba1tYnRo0eLRYsWiVNOOUURO9l0nnfeeaeYMmWK5n3Zcp633XabOPHEE3Xvz9bfQTfddJMYOXKk8Pl8WfOzFEKIOXPmiKuuuirktvPPP19ceumlQojk/zxZxkoBLpcLK1euxIwZM5TbzGYzZsyYgU8//TSNR5Y6tm/fjrq6upBzLi0txXHHHdenz7mlpQUA0L9/fwDAypUr4Xa7Q85z3LhxGDp0aJ89T6/XixdeeAEdHR2ora3NunOcN28e5syZE3I+QPb9LDdv3ozBgwdjxIgRuPTSS7Fr1y4A2XOer7/+Oo4++mhceOGFGDhwII488kj89a9/Ve7Pxt9BLpcLzz77LK666iqYTKas+VkCwAknnIDFixdj06ZNAIDVq1fj448/xuzZswEk/+fJRaApoKmpCV6vF5WVlSG3V1ZW4ptvvknTUaWWuro6ANA8Z3lfX8Pn8+Hmm2/GtGnTcPjhhwPwn6fdbkdZWVnIY/vieX799deora1Fd3c3ioqK8Oqrr2LChAlYtWpV1pzjCy+8gC+//BKff/55xH3Z9LM87rjj8PTTT2Ps2LHYv38/7r77bpx00klYu3Zt1pzntm3b8Pjjj+PHP/4xfvGLX+Dzzz/Hj370I9jtdsydOzcrfwe99tpraG5uxhVXXAEgu/7N/vznP0drayvGjRsHi8UCr9eL++67D5deeimA5F9TKHYI0WHevHlYu3YtPv7443QfSkoYO3YsVq1ahZaWFrz88suYO3culi5dmu7DShq7d+/GTTfdhEWLFiEvLy/dh5NS5F/DADB58mQcd9xxGDZsGP79738jPz8/jUeWPHw+H44++mj85je/AQAceeSRWLt2Lf7yl79g7ty5aT661PDkk09i9uzZGDx4cLoPJen8+9//xnPPPYfnn38eEydOxKpVq3DzzTdj8ODBKfl5soyVAsrLy2GxWCIS8vX19aiqqkrTUaUWeV7Zcs433HADFi5ciA8++ABDhgxRbq+qqoLL5UJzc3PI4/viedrtdowaNQpTp07FggULMGXKFDz88MNZc44rV65EQ0MDjjrqKFitVlitVixduhR/+tOfYLVaUVlZmRXnqUVZWRnGjBmDLVu2ZM3Pc9CgQZgwYULIbePHj1fKddn2O2jnzp1477338P3vf1+5LVt+lgBw66234uc//zm+853vYNKkSbjssstwyy23YMGCBQCS//Ok2EkBdrsdU6dOxeLFi5XbfD4fFi9ejNra2jQeWeoYPnw4qqqqQs65tbUVn332WZ86ZyEEbrjhBrz66qt4//33MXz48JD7p06dCpvNFnKeGzduxK5du/rUeWrh8/ngdDqz5hynT5+Or7/+GqtWrVK+jj76aFx66aXKf2fDeWrR3t6OrVu3YtCgQVnz85w2bVrEGIhNmzZh2LBhALLnd5DkqaeewsCBAzFnzhzltmz5WQJAZ2cnzOZQCWKxWODz+QCk4OfZozg10eWFF14QDodDPP3002L9+vXi2muvFWVlZaKuri7dh5YwbW1t4quvvhJfffWVACAefPBB8dVXX4mdO3cKIfxtgmVlZeK///2vWLNmjTjnnHP6XNvn9ddfL0pLS8WSJUtC2j87OzuVx1x33XVi6NCh4v333xdffPGFqK2tFbW1tWk86vj5+c9/LpYuXSq2b98u1qxZI37+858Lk8kk3n33XSFEdpyjFupuLCGy5zx/8pOfiCVLlojt27eLTz75RMyYMUOUl5eLhoYGIUR2nOeKFSuE1WoV9913n9i8ebN47rnnREFBgXj22WeVx2TD7yAh/N27Q4cOFbfddlvEfdnwsxRCiLlz54rDDjtMaT1/5ZVXRHl5ufjZz36mPCaZP0+KnRTyyCOPiKFDhwq73S6OPfZYsXz58nQfUo/44IMPBICIr7lz5woh/K2Cv/rVr0RlZaVwOBxi+vTpYuPGjek96DjROj8A4qmnnlIe09XVJX74wx+Kfv36iYKCAnHeeeeJ/fv3p++gE+Cqq64Sw4YNE3a7XVRUVIjp06crQkeI7DhHLcLFTrac58UXXywGDRok7Ha7OOyww8TFF18cMn8mW87zjTfeEIcffrhwOBxi3Lhx4oknngi5Pxt+BwkhxDvvvCMAaB57tvwsW1tbxU033SSGDh0q8vLyxIgRI8Qvf/lL4XQ6lcck8+dpEkI1rpAQQgghJMtgZocQQgghWQ3FDiGEEEKyGoodQgghhGQ1FDuEEEIIyWoodgghhBCS1VDsEEIIISSrodghhBBCSFZDsUMIyUlqamrw0EMPpfswCCG9AMUOISTlXHHFFTj33HMBAKeeeipuvvnmXnvvp59+GmVlZRG3f/7557j22mt77TgIIenDmu4DIISQRHC5XLDb7Qk/v6KiIolHQwjJZOjsEEJ6jSuuuAJLly7Fww8/DJPJBJPJhB07dgAA1q5di9mzZ6OoqAiVlZW47LLL0NTUpDz31FNPxQ033ICbb74Z5eXlmDVrFgDgwQcfxKRJk1BYWIjq6mr88Ic/RHt7OwBgyZIluPLKK9HS0qK831133QUgsoy1a9cunHPOOSgqKkJJSQkuuugi1NfXK/ffddddOOKII/DPf/4TNTU1KC0txXe+8x20tbUpj3n55ZcxadIk5OfnY8CAAZgxYwY6OjpS9GkSQoxCsUMI6TUefvhh1NbW4pprrsH+/fuxf/9+VFdXo7m5GaeddhqOPPJIfPHFF3j77bdRX1+Piy66KOT5zzzzDOx2Oz755BP85S9/AQCYzWb86U9/wrp16/DMM8/g/fffx89+9jMAwAknnICHHnoIJSUlyvv99Kc/jTgun8+Hc845BwcPHsTSpUuxaNEibNu2DRdffHHI47Zu3YrXXnsNCxcuxMKFC7F06VLcf//9AID9+/fjkksuwVVXXYUNGzZgyZIlOP/888H1g4SkH5axCCG9RmlpKex2OwoKClBVVaXc/uc//xlHHnkkfvOb3yi3/f3vf0d1dTU2bdqEMWPGAABGjx6NBx54IOQ11fmfmpoa/PrXv8Z1112Hxx57DHa7HaWlpTCZTCHvF87ixYvx9ddfY/v27aiurgYA/OMf/8DEiRPx+eef45hjjgHgF0VPP/00iouLAQCXXXYZFi9ejPvuuw/79++Hx+PB+eefj2HDhgEAJk2a1INPixCSLOjsEELSzurVq/HBBx+gqKhI+Ro3bhwAv5simTp1asRz33vvPUyfPh2HHXYYiouLcdlll+HAgQPo7Ow0/P4bNmxAdXW1InQAYMKECSgrK8OGDRuU22pqahShAwCDBg1CQ0MDAGDKlCmYPn06Jk2ahAsvvBB//etfcejQIeMfAiEkZVDsEELSTnt7O84++2ysWrUq5Gvz5s04+eSTlccVFhaGPG/Hjh0466yzMHnyZPznP//BypUr8eijjwLwB5iTjc1mC/neZDLB5/MBACwWCxYtWoS33noLEyZMwCOPPIKxY8di+/btST8OQkh8UOwQQnoVu90Or9cbcttRRx2FdevWoaamBqNGjQr5Chc4alauXAmfz4c//OEPOP744zFmzBjs27cv5vuFM378eOzevRu7d+9Wblu/fj2am5sxYcIEw+dmMpkwbdo03H333fjqq69gt9vx6quvGn4+ISQ1UOwQQnqVmpoafPbZZ9ixYweamprg8/kwb948HDx4EJdccgk+//xzbN26Fe+88w6uvPLKqEJl1KhRcLvdeOSRR7Bt2zb885//VILL6vdrb2/H4sWL0dTUpFnemjFjBiZNmoRLL70UX375JVasWIHLL78cp5xyCo4++mhD5/XZZ5/hN7/5Db744gvs2rULr7zyChobGzF+/Pj4PiBCSNKh2CGE9Co//elPYbFYMGHCBFRUVGDXrl0YPHgwPvnkE3i9XsycOROTJk3CzTffjLKyMpjN+r+mpkyZggcffBC//e1vcfjhh+O5557DggULQh5zwgkn4LrrrsPFF1+MioqKiIAz4Hdk/vvf/6Jfv344+eSTMWPGDIwYMQIvvvii4fMqKSnBhx9+iDPPPBNjxozB7bffjj/84Q+YPXu28Q+HEJISTIJ9kYQQQgjJYujsEEIIISSrodghhBBCSFZDsUMIIYSQrIZihxBCCCFZDcUOIYQQQrIaih1CCCGEZDUUO4QQQgjJaih2CCGEEJLVUOwQQgghJKuh2CGEEEJIVkOxQwghhJCshmKHEEIIIVnN/wcFKdjC0Vw7swAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "result.convergence_graph" + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(nrows=1, ncols=1)\n", + "axes.plot(cost_values)\n", + "axes.set_xlabel(\"Iterations\")\n", + "axes.set_ylabel(\"Cost\")\n", + "axes.set_title(\"Cost convergence\")" ] }, { @@ -463,22 +350,22 @@ "id": "670eddd3-2da7-4a88-b571-7884ef24f60c", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm:" + "We can also examine the statistics of the algorithm. The optimization is always defined as a minimzation problem, so the positive maximization objective was tranlated to a negative minimization one by the pyomo to qmod translator." + ] + }, + { + "cell_type": "markdown", + "id": "c99a7e3e-5203-4893-b970-dc23739f6df2", + "metadata": {}, + "source": [ + "In order to get samples with the optimized parameters, we call the `get_results` method:" ] }, { "cell_type": "code", - "execution_count": 13, - "id": "516d78ba-2951-46eb-b1af-efe877513556", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:33.675397Z", - "iopub.status.busy": "2024-05-07T16:03:33.674963Z", - "iopub.status.idle": "2024-05-07T16:03:37.107224Z", - "shell.execute_reply": "2024-05-07T16:03:37.106517Z" - }, - "tags": [] - }, + "execution_count": 10, + "id": "9638f749-a60b-4176-a4ea-50d7c2bb986f", + "metadata": {}, "outputs": [ { "data": { @@ -501,79 +388,63 @@ " \n", " \n", " \n", + " solution\n", " probability\n", " cost\n", - " solution\n", - " count\n", " \n", " \n", " \n", " \n", - " 6\n", - " 0.019\n", - " 3.0\n", - " [0, 0, 1]\n", - " 19\n", + " 151\n", + " {'x_0': 0, 'x_1': 0, 'x_2': 1}\n", + " 0.001953\n", + " -3.000000e+00\n", " \n", " \n", - " 15\n", - " 0.015\n", - " 3.0\n", - " [0, 0, 1]\n", - " 15\n", + " 178\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 0}\n", + " 0.000977\n", + " -2.000000e+00\n", " \n", " \n", - " 24\n", - " 0.011\n", - " 2.0\n", - " [0, 1, 0]\n", - " 11\n", + " 11\n", + " {'x_0': 1, 'x_1': 0, 'x_2': 0}\n", + " 0.014648\n", + " -1.000000e+00\n", " \n", " \n", - " 106\n", - " 0.002\n", - " 2.0\n", - " [0, 0, 2]\n", - " 2\n", + " 4\n", + " {'x_0': 0, 'x_1': 0, 'x_2': 0}\n", + " 0.020020\n", + " 1.527468e-150\n", " \n", " \n", - " 3\n", - " 0.025\n", - " 2.0\n", - " [0, 1, 0]\n", - " 25\n", + " 68\n", + " {'x_0': 0, 'x_1': 0, 'x_2': 1}\n", + " 0.004395\n", + " 7.000000e+00\n", " \n", " \n", "\n", "" ], "text/plain": [ - " probability cost solution count\n", - "6 0.019 3.0 [0, 0, 1] 19\n", - "15 0.015 3.0 [0, 0, 1] 15\n", - "24 0.011 2.0 [0, 1, 0] 11\n", - "106 0.002 2.0 [0, 0, 2] 2\n", - "3 0.025 2.0 [0, 1, 0] 25" + " solution probability cost\n", + "151 {'x_0': 0, 'x_1': 0, 'x_2': 1} 0.001953 -3.000000e+00\n", + "178 {'x_0': 0, 'x_1': 1, 'x_2': 0} 0.000977 -2.000000e+00\n", + "11 {'x_0': 1, 'x_1': 0, 'x_2': 0} 0.014648 -1.000000e+00\n", + "4 {'x_0': 0, 'x_1': 0, 'x_2': 0} 0.020020 1.527468e-150\n", + "68 {'x_0': 0, 'x_1': 0, 'x_2': 1} 0.004395 7.000000e+00" ] }, - "execution_count": 13, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " ilp_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=False).head(5)" + "optimization_result = combi.get_results()\n", + "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { @@ -586,31 +457,15 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 11, "id": "31a4e74d-b2b8-42e0-826d-de7b51de1fe8", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:37.110324Z", - "iopub.status.busy": "2024-05-07T16:03:37.109906Z", - "iopub.status.idle": "2024-05-07T16:03:37.306818Z", - "shell.execute_reply": "2024-05-07T16:03:37.306110Z" - }, "tags": [] }, "outputs": [ { "data": { - "text/plain": [ - "array([[]], dtype=object)" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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0tDLbY2NjZRhGpfWvuP/++3X//fdXuTwAAKjfXApSmZmZatKkicaNG6fHHntMTZs2rVK9P/7xj4qOjnalaQAAgBrnUpB6++23NXz4cPn6+jpV75577tE999zjStMAAAA1zqVv7cXFxenYsWOVlsvKytKGDRtcaQoAAMDjuBSkEhMTNWPGjErLvfLKK0pMTHSlKQAAAI/jUpAyDMOpwdwAAAB1SbVMyPlbZ86ckb+///VoCgAA4LpxerB5dna2w/uCgoIy264oLS21T2jJRJYAAKCucTpIxcbGymKx2N8vW7ZMy5Ytq7COYRgaMWKE870DAADwYE4HqejoaHuQys7OVmBgoH1m8N/y9fVVixYtNHDgQD366KOu9RQAAMDDOB2krp7uwMvLS4MHD9bbb7/tzj4BAADUCi5NyLlw4ULddNNN7uoLAABAreJSkBo1apS7+gEAAFDrXJfpDwAAAOoip+5IxcXFyWKx6KuvvlLLli0VFxdX5boWi0WHDx92uoMAAACeyqkgdezYMVksFpWUlNjfV9XVUyYAAADUBU4FqaNHj0qSmjdv7vAeAACgPnIqSMXExFT4HgAAoD5hsDkAAIBJBCkAAACTnHq096c//cl0QxaLRW+99Zbp+gAAAJ7GqSCVlpZmuiGCFAAAqGucClILFy6srn4AAADUOk4FKZaEAQAA+D8MNgcAADCJIAUAAGCSU4/23nnnHUnS/fffr5CQEPv7qho5cqRT5QEAADyZU0Fq9OjRslgs6tatm0JCQuzvq4ogBQAA6hKngtTIkSNlsVgUFhbm8B4AAKA+cmkeKVfmlQIAAKjtGGwOAABgEkEKAADAJLcEqR9++EGPPPKI2rZtq+DgYAUFBalNmzZ65JFH9N1337mjCQAAAI/jcpCaO3euOnXqpDfffFMHDx7U+fPnVVRUpKysLL3xxhvq0qWL/vWvf7mjrwAAAB7FpSC1YsUKPfnkkyotLdV///d/69NPP9W3336rb7/9Vv/+9781aNAgXbp0SU8//bRWrFjhrj4DAAB4BKe+tfdbr7zyiiwWi95//30NHjzYYd+tt96qP/zhD/rwww81ZMgQvfLKK+rfv79LnQUAAPAkLt2R2rlzp+Lj48uEqKsNGjRId9xxh3bu3OlKUwAAAB7HpSBlsVjUqlWrSsu1atWKiTsBAECd41KQuu2225SVlVVpuaysLLVv396VpgAAADyOS0HqmWee0fbt2/X++++XWyYjI0Pbt2/X008/7UpTAAAAHsepwebZ2dkO77t06aKnn35aI0aM0IcffqiRI0eqZcuWkqSjR4/q3Xff1UcffaSnn35aXbt2dV+vAQAAPIBTQSo2NvaaY50Mw9BHH32kjz766Jr7XnvtNc2aNUulpaXmewq327dvn6l6ERERio6OdnNvAACofZwKUtHR0QwarwMuFZyRLBaNGDHCVH3/gEAd2L+PMAUAqPecClLHjh2rpm7gerIVF0iGofC7J8gnPMqpuiWnc3T6s1dltVoJUgCAes+lCTlRu/mER8kv8qaa7gYAALWWWxYtBgAAqI/cekcqLy9P+fn5Mgzjmvt5FAQAAOoSl4PUmTNnNGXKFH3wwQf65Zdfyi1nsVj41h4AAKhTXApSeXl56tatmw4dOqQGDRooICBA58+fV9OmTZWbmyvDMGSxWLgTBQAA6iSXxkj9/e9/V1ZWlkaOHKm8vDwNGjRIFotFP/74o86dO6d58+apYcOGSkhI0NGjR93VZwAAAI/g0h2pTz/9VBEREZo3b578/f0d5pgKDAzU+PHj1aFDB/Xs2VPdu3fXuHHjXO4wAACAp3DpjtSRI0fUpUsX+fv7S5I9SF26dMleplu3brrzzjv11ltvudIUAACAx3F5+oNGjRrZ/xwYGCjp8gD0q0VHR2v//v2uNgUAAOBRXApSzZo1048//mh/f2VQ+TfffONQ7siRI/L2Zu5PAABQt7gUpNq3b68DBw7Y3/fq1UuGYWjq1Kk6d+6cJGnRokXatm2bbrnlFtd6CgAA4GFcuk3Ur18/ffTRR1q7dq0SExN15513qkePHtq0aZMaN26s0NBQnT17VhaLRX/5y1/c1Wd4gH379l2XOgAAeDKXgtSwYcN0yy23KDY21r5t+fLleuihh7RixQqdOXNGjRo10pQpU3TPPfe42ld4gEsFZySLRSNGjKjprgAAUONcClLBwcHq0aOHw7YmTZro008/1fnz55WXl6cbb7xRXl4s6VdX2IoLJMNQ+N0T5BMe5VTdoiM7lPf1omrqGQAA11+1jQAPDAy0f4sPdY9PeJT8Im9yqk7J6Zxq6g0AADXDrUEqNzdXJ06ckGEYatGihZo2berOwwMAAHgUtzxze/PNN9W2bVs1b95cd9xxh7p166YWLVqobdu2mj9/vjuaAAAA8DguBSmbzaaUlBQ98sgjOnjwoAzDUOPGjdW4cWMZhqGDBw/qscce0+DBg2Wz2dzVZwAAAI/gUpCaM2eOPvjgA0VERGj27NnKz8/XL7/8ol9++UX5+fmaM2eObrjhBi1fvlxz5sxxV58BAAA8gktB6q233pKfn5/WrVunxx9/XMHBwfZ9wcHBeuyxx7RmzRr5+PhowYIFLncWAADAk7gUpLKysnTXXXepXbt25ZZp166dEhMTdejQIVeaAgAA8DguBang4GCHRYvL06hRI4e7VVW1fft2DRgwQA0bNlRQUJC6deumpUuXVrn+4cOHlZqaqnvvvVfNmzeXxWJxmDy0PJmZmUpISFBISIhCQ0OVmJio1atXO91/AABQt7k0/UHPnj21bds22Wy2cifdtNls2rZtm7p37+7UsdeuXavk5GT5+/tr6NChCgkJ0bJly5SSkqKcnBxNmDCh0mN8/fXXevHFF9WgQQO1a9dOubm5ldZZtGiRHnzwQTVp0kSjR4+WJGVkZKhv375aunSpBg0a5NR5AACAusulO1Kpqak6deqUnnrqKV28eLHM/pKSEj311FPKzc3Viy++WOXjlpaWauzYsfLy8tKGDRv0xhtv6NVXX9XevXt18803a9KkSTp+/Hilx+ndu7e2bNmic+fO6dtvv5WPj0+F5c+cOaMnn3xSERER2rVrl2bPnq3Zs2dr165dCg8P16OPPmpfjBkAAMCpO1LvvPNOmW1jxozR3LlztXz5cg0ZMkQtW7aUJB09elQffPCBTp48qUceeUR79+5Vhw4dqtTOmjVrdPjwYY0ZM0YdO3a0bw8LC9OkSZM0evRopaena8qUKRUeJy4uTnFxcVU+vw8++EBnz57Viy++qBYtWti3t2jRQk888YRSU1P10UcfaeTIkVU+JgAAqLucClKjR4+WxWIps90wDJ08eVKzZs0qs12SXn/9db3++utVDiDr1q2TJCUlJZXZl5ycLElav369M113S7upqalav349QQoAAEhyMkiNHDnymkHK3bKysiRJrVu3LrMvMjJSwcHB9jLXq90r2yprt7i4WMXFxfb3+fn5buwhAADwJE4FqbS0tGrqhqO8vDxJlx/lXUtoaKi9zPVqNzQ01KFMeaZPn+7UeDAAAFB7uWWtPfyfiRMnKi8vz/7Kycmp6S4BAIBq4tL0B79lGIZOnz4tSWrcuHG5UyJU5sodofLu/uTn51dp/ipX2g0PDy/T5tVlyuPn5yc/Pz+39w0AAHget9yRWr16tfr166fg4GDdeOONuvHGGxUSEqL+/fubmsiyovFIubm5KigouOY4JldV1G5F46cAAED95HKQeumll5SUlKSVK1eqqKhIhmHIMAwVFRUpMzNTSUlJevnll506ZkJCgiRp5cqVZfZlZmY6lHGnmmoXAADUTi4Fqa+++kqpqany8fHRE088od27dys/P1/5+fnas2ePnnzySfn6+mrq1Klas2ZNlY/bp08fxcXFacmSJdqzZ499e15enqZNmyZfX1+HKQhOnTql/fv3uzwAfciQIQoLC9Ps2bN14sQJ+/YTJ05ozpw5ioiI0P333+9SGwAAoO5waYzUv/71L1ksFn3yySf2+Z2uuO222zRr1iz94Q9/UP/+/TVr1iz913/9V9U65e2tBQsWKDk5Wb1793ZYIub48eOaOXOmw5p5EydOVHp6uhYuXGhf1kWSrFarnn32Wfv7kpISWa1WhzIzZ85URESEpMtrAs6ZM0cPPvigOnfurJSUFEmXl4g5ffq0MjIyFBIS4uSnBAAA6iqXgtSVNfR+G6KulpSUpO7du2vLli1OHTsxMVEbN27U1KlTlZGRoZKSErVv314zZsywB5zKFBQUKD093WFbYWGhw7bU1FR7kJKkESNGKCIiQtOmTdPChQtlsVjUpUsXTZ48Wb///e+dOgcAAFC3uRSkzp49q5iYmErLxcTE6D//+Y/Tx4+Pj9eKFSsqLZeWlnbNOa5iY2Pts6s7o1+/furXr5/T9QAAQP3i0hipiIgI7d+/v9Jy+/fvd7jrAwAAUBe4FKR69Oih3bt3a8mSJeWWWbx4sXbt2qWePXu60hQAAIDHcenR3nPPPafly5dr5MiR+vjjjzVq1Ci1bNlSknTkyBGlpaXp448/VoMGDRwGfQMAANQFLgWprl27at68eXr88cf14YcfatmyZQ77DcOQt7e35s6dq65du7rUUQAAAE/j8oScY8eO1a5du/SnP/1JcXFx9iVS4uLi9NBDD2nXrl0aO3asO/oKAADgUVy6I5WdnS2LxaLf/e53WrBggbv6BAAAUCu4dEcqNjZWQ4cOdVdfAAAAahWXglRoaKh9cDkAAEB941KQuuWWW5STk+OuvgAAANQqLgWpsWPHatOmTdq+fbu7+gMAAFBruBSkxowZo8cee0xJSUmaNm2aDhw4oOLiYnf1DQAAwKO59K29Bg0a2P/8wgsv6IUXXii3rMViUWlpqSvNAQAAeBSXgpQzCwKbWTwYAADAk7kUpGw2m7v6AQAAUOuYClKHDh3S8uXLdezYMfn5+alTp04aPHiwAgIC3N0/AAAAj+V0kHrttdf0l7/8RZcuXXLYPnnyZH3xxRf63e9+57bOAQAAeDKnvrW3ceNGTZgwQaWlpQoMDFSnTp3UqlUrWSwWnThxQgMHDuRxHwAAqDecClJz5syRYRgaNWqUcnNztWPHDh08eFC7du1Sq1atdOjQIX355ZfV1VcAAACP4lSQ2rJli1q0aKH58+crKCjIvv22227TrFmzZBiGtm7d6vZOAgAAeCKngtRPP/2k22+/Xb6+vmX29ezZU5L0888/u6dnAAAAHs6pIHXx4kU1bNjwmvtCQ0PtZQAAAOoDl5aIAQAAqM+cnv7g0KFDeuedd0ztHzlypLPNAQAAeCyng9SmTZu0adOma+6zWCzl7rdYLAQpAABQpzgVpKKjo2WxWKqrLwAAALWKU0Hq2LFj1dQNAACA2ofB5gAAACYRpAAAAEwiSAEAAJhEkAIAADDJ6ekPAFRddna2rFarqboRERGKjo52c48AAO5EkAKqSXZ2ttq0bacLRedN1fcPCNSB/ftMhSlXApxEiAOAqiJIAdXEarXqQtF5hd89QT7hUU7VLTmdo9OfvSqr1ep0oHE1wEmuhTgAqE8IUkA18wmPkl/kTdetPVcCnORaiAOA+oYgBdRR1zvAAUB9xLf2AAAATCJIAQAAmESQAgAAMIkgBQAAYBJBCgAAwCSCFAAAgEkEKQAAAJMIUgAAACYRpAAAAEwiSAEAAJhEkAIAADCJIAUAAGASQQoAAMAkghQAAIBJBCkAAACTCFIAAAAmEaQAAABMIkgBAACYRJACAAAwybumOwBcD9nZ2bJarabqRkREKDo62s09AgDUBQQp1HnZ2dlq07adLhSdN1XfPyBQB/bvI0wBAMogSKHOs1qtulB0XuF3T5BPeJRTdUtO5+j0Z6/KarUSpAAAZRCkUG/4hEfJL/Kmmu4GAKAOYbA5AACASQQpAAAAkwhSAAAAJhGkAAAATCJIAQAAmESQAgAAMMmjg9T27ds1YMAANWzYUEFBQerWrZuWLl3q1DGKi4v10ksvqXXr1vL391ezZs00btw4/fzzz2XKHjt2TBaLpdxXamqqm84MAADUBR47j9TatWuVnJwsf39/DR06VCEhIVq2bJlSUlKUk5OjCRMmVHoMm82m++67T5mZmerWrZsGDhyorKwsLViwQKtXr9bWrVvVpEmTMvU6dOigP/7xj2W233XXXW44MwAAUFd4ZJAqLS3V2LFj5eXlpQ0bNqhjx46SpClTpig+Pl6TJk3SoEGDFBMTU+Fx0tPTlZmZqWHDhmnx4sWyWCySpNdff12PPvqoJk+erPnz55ep17FjR+4+AQCASnnko701a9bo8OHDGj58uD1ESVJYWJgmTZqkixcvKj09vdLjvPnmm5Kk6dOn20OUJI0fP15xcXFavHixioqK3N5/AABQP3hkkFq3bp0kKSkpqcy+5ORkSdL69esrPMaFCxe0bds2tWnTpsydK4vFor59+6qwsFA7duwoU/fkyZOaO3eupk2bprfeekuHDx82eSYAAKAu88hHe1lZWZKk1q1bl9kXGRmp4OBge5nyHD58WDab7ZrHuPrYWVlZ6tWrl8O+VatWadWqVfb3FotFDzzwgF5//XUFBQVV2G5xcbGKi4vt7/Pz8yssDwAAai+PvCOVl5cn6fKjvGsJDQ21l3HlGFeXk6TAwEC98MIL2rlzp86ePatff/1VX331leLj47Vo0SKNHDmy0r5Pnz5dYWFh9ldUVFSldQAAQO3kkUGqptxwww166aWX1LlzZ4WFhalRo0bq06eP1qxZozZt2mj58uXatWtXhceYOHGi8vLy7K+cnJzr1HsAAHC9eeSjvSt3kcq765Sfn69GjRq5fIyry1UkMDBQDz74oCZPnqxNmzapc+fO5Zb18/OTn59fpccE4F7Z2dmyWq2m6kZERCg6OtrNPQJQH3hkkLp6/FKXLl0c9uXm5qqgoEDx8fEVHiMuLk5eXl7ljqWqaBzWtUREREiSCgsLq1QewPWTnZ2tNm3b6ULReVP1/QMCdWD/PsIUAKd5ZJBKSEjQ9OnTtXLlSg0dOtRhX2Zmpr1MRQICAhQfH6+tW7fq+PHjDt/cMwxDq1atUlBQkG6//fYq9Wnbtm2SpNjYWCfOBMD1YLVadaHovMLvniCfcOfGJZacztHpz16V1WolSAFwmkeOkerTp4/i4uK0ZMkS7dmzx749Ly9P06ZNk6+vr8PA71OnTmn//v1lHuONGzdO0uVxS4Zh2LfPnz9fR44c0QMPPKCAgAD79t27dzuUu2L58uVKT09Xo0aN1L9/f3edJgA38wmPkl/kTU69nA1eAHA1j7wj5e3trQULFig5OVm9e/d2WCLm+PHjmjlzpsOdoYkTJyo9PV0LFy7U6NGj7dtHjRqljIwMvffeezp69KgSEhJ06NAhLV++XC1bttTLL7/s0O7TTz+tw4cP684771SLFi106dIl7dq1Sxs3bpSfn5/S0tKqNKYKAADUDx4ZpCQpMTFRGzdu1NSpU5WRkaGSkhK1b99eM2bMUEpKSpWO4eXlpU8++UR/+9vf9O677+qf//ynGjdurIceekgvv/xymXX2RowYoWXLlmnr1q2yWq2y2Wxq3ry5Hn74YU2YMEFt27atjlMFAAC1lMcGKUmKj4/XihUrKi2XlpamtLS0a+7z8/PT1KlTNXXq1EqP8/DDD+vhhx92tpsAAKCe8sgxUgAAALUBQQoAAMAkghQAAIBJBCkAAACTCFIAAAAmEaQAAABMIkgBAACYRJACAAAwiSAFAABgEkEKAADAJIIUAACASQQpAAAAkwhSAAAAJhGkAAAATCJIAQAAmESQAgAAMIkgBQAAYBJBCgAAwCSCFAAAgEkEKQAAAJMIUgAAACYRpAAAAEwiSAEAAJhEkAIAADDJu6Y7AKBuyc7OltVqNVU3IiJC0dHRbu4RAFQfghQAt8nOzlabtu10oei8qfr+AYE6sH8fYQpArUGQAuA2VqtVF4rOK/zuCfIJj3KqbsnpHJ3+7FVZrVaCFIBagyAFwO18wqPkF3lTTXcDAKodg80BAABMIkgBAACYRJACAAAwiSAFAABgEkEKAADAJIIUAACASQQpAAAAkwhSAAAAJhGkAAAATCJIAQAAmESQAgAAMIkgBQAAYBKLFgNVsG/fvutSBwBQuxCkgApcKjgjWSwaMWJETXcFAOCBCFJABWzFBZJhKPzuCfIJj3KqbtGRHcr7elE19QwA4AkIUkAV+IRHyS/yJqfqlJzOcbldHikCgGcjSAEeiEeKAFA7EKRQq9SXOzQ8UgSA2oEghVqhvt6hqalHigCAqiFIoVbgDg1Qv2VnZ8tqtZqqGxERoejoaDf3CLiMIIVahTs08DT8gq9+2dnZatO2nS4UnTdV3z8gUAf27+OzRrUgSAGASfyCvz6sVqsuFJ03dUe65HSOTn/2qqxWK58zqgVBCgBM4hf89WXmjjRQ3QhSAOAifsED9ReLFgMAAJhEkAIAADCJIAUAAGASY6QAeJT6Mns9gLqBIAXAI9TX2evh2ZgnDJUhSAHwCMxeD0/DPGGoCoIUAI/C7PXwFMwThqogSAEAUIH6NE8YjzKdR5ACAAA8yjSJIAUAAHiUaRJBCgAA2NWnR5nuQJACgHqGcTCA+3h0kNq+fbumTp2qzZs3q6SkRO3bt9czzzyjIUOGVPkYxcXFmjFjht59913l5OSocePGuvvuu/Xyyy/rhhtuuGadxYsXa9asWfr+++/l6+urHj166KWXXlLnzp3ddWoA4BKzYejUqVMaOGiwii8UmWq3vo6DAcrjsUFq7dq1Sk5Olr+/v4YOHaqQkBAtW7ZMKSkpysnJ0YQJEyo9hs1m03333afMzEx169ZNAwcOVFZWlhYsWKDVq1dr69atatKkiUOdv/71r5o8ebJiYmL0yCOP6Ny5c3r//ffVvXt3rV69Wj169KiuUwaAKnF1ULAkxsEAbuKRQaq0tFRjx46Vl5eXNmzYoI4dO0qSpkyZovj4eE2aNEmDBg1STExMhcdJT09XZmamhg0bpsWLF8tisUiSXn/9dT366KOaPHmy5s+fby+flZWl1NRU3XzzzfrPf/6jsLAwSdJjjz2mbt26aezYsfruu+/k5cUShQDcw+ySOGYHBV+ZvJRxMPAktflxs0cGqTVr1ujw4cMaM2aMPURJUlhYmCZNmqTRo0crPT1dU6ZMqfA4b775piRp+vTp9hAlSePHj9ff//53LV68WK+99poCAgIkSQsXLlRpaamef/55e4iSpI4dO2rYsGFKS0vTxo0b1bt3bzeeLYD6yB1L4jB5qeczuw5kTYeD66m2T7vgkUFq3bp1kqSkpKQy+5KTkyVJ69evr/AYFy5c0LZt29SmTZsyd64sFov69u2r+fPna8eOHerVq1eV2k1LS9P69esJUgBcxpI4dZurQbmmw8H1VNunXfDIIJWVlSVJat26dZl9kZGRCg4Otpcpz+HDh2Wz2a55jKuPnZWVZQ9SWVlZCg4OVmRkZIXlK1JcXKzi4mL7+7y8PElSfn5+hfWcVVBQcLm93EOyXbzgVN0r/yOlLnWvWf/XE5KknTt32v+eVdWBAwdMt11jn1cNn6+tpNjpukbpRZfbvd6flSR5eXnJZrM5Xc+lz7mGrm/xyX2SYSi063+rQViTyitc5VLeL8rfvlyZmZlq06aNU3Wl2vs5m/lZsJVc/n1bUFDg9t+zV45nGEbFBQ0P1LdvX0OSkZWVdc39zZo1M0JDQys8xqZNmwxJxgMPPHDN/W+88YYhyfjHP/5h3+bj42M0b978muUPHjxoSDLuvffeCtudOnWqIYkXL168ePHiVQdeOTk5Ff7e98g7UrXZxIkT9cwzz9jf22w2/frrrwoPD3cYp+UO+fn5ioqKUk5OjkJDQ916bNQ8rm/dxvWt+7jGtZthGDp37pyaNWtWYTmPDFJXBnpfeSz2W/n5+WrUqJHLx7i63JU/O1P+Wvz8/OTn5+ewrWHDhhXWcVVoaCg/pHUY17du4/rWfVzj2quy3/mS5JHf469oPFJubq4KCgrKHft0RVxcnLy8vMod03StcVitW7dWQUGBcnNzq1QeAADUbx4ZpBISEiRJK1euLLMvMzPToUx5AgICFB8frwMHDuj48eMO+wzD0KpVqxQUFKTbb7/dre0CAID6wyODVJ8+fRQXF6clS5Zoz5499u15eXmaNm2afH19NXLkSPv2U6dOaf/+/WUey40bN07S5XFLxlWj7ufPn68jR47ogQcesM8hJUljxoyRt7e3/vrXvzoca8+ePXrvvffUrl079ezZ092na5qfn5+mTp1a5lEi6gaub93G9a37uMb1g8UwKvteX80ob4mY48ePa+bMmQ5LxFyZoHPhwoUaPXq0fbvNZtOAAQPsS8QkJCTo0KFDWr58uWJjY7Vt27YKl4gZOHCgfYmYixcvskQMAABw4JF3pCQpMTFRGzduVI8ePZSRkaF58+bpxhtv1Pvvv1+ldfaky3NpfPLJJ0pNTdUvv/yif/7zn9q0aZMeeughbdmypUyIkqTnn39eixYtUpMmTTRv3jwtXbpUvXr10ubNmwlRAADAgcfekQIAAPB0HntHCgAAwNMRpAAAAEwiSNVC27dv14ABA9SwYUMFBQWpW7duWrp0aU13C9cQGxsri8Vyzdddd91VpnxxcbFeeukltW7dWv7+/mrWrJnGjRunn3/+udw2Fi9erPj4eAUFBalRo0a6++67tWvXrmo8q/pn0aJFGj9+vG6//Xb5+fnJYrEoLS2t3PL5+fl65plnFBMTIz8/P8XGxuq5554rdw0ym82m2bNnq3379goICFCTJk00bNgwHTlypNw2MjMzlZCQoJCQEIWGhioxMVGrV6929VTrJWeub2pqark/0xaLRceOHbtmPWev18GDBzVkyBBFREQoICBAHTp00Lx58ypf9w3XnUfObI7ylfdtxpSUFOXk5FR5ID6un7CwMD311FNltsfGxjq8t9lsuu++++zfMh04cKCysrK0YMECrV69Wlu3bq3wW6aPPPKI/Vum3bt351umbjR58mQdP35cERERatq0aZm56a5WWFiohIQE7dmzR0lJSRo2bJh2796tmTNnav369dqwYYP8/f0d6owfP14LFizQrbfeqj//+c86efKkli5dqpUrV2rr1q1lJgJetGiRHnzwQTVp0sT+TeWMjAz17dtXS5cu1aBBg9z+GdRlzlzfK0aNGlXmZ1i69koWzl6vH374Qd27d1dRUZGGDBmiZs2a6fPPP9djjz2mH374QbNnzzZzmqguFa7EB49SUlJitGrVyvDz8zN2795t33727Fnj5ptvNnx9fY1jx47VXAdRRkxMjBETE1Olsm+//bYhyRg2bJhhs9ns2+fNm2dIMsaNG+dQ/uDBg4a3t7dx8803G2fPnrVv3717t+Hn52e0a9fOuHTpklvOo75btWqV/Wdr+vTphiRj4cKF1yw7ZcoUQ5LxP//zPw7b/+d//seQZEybNs1h+5o1awxJRu/evY3i4mL79i+++MKQZCQlJTmU//XXX42GDRsaERERDoup5uTkGBEREUZERISRn5/vyunWO85c3ysL069du7ZKxzZzvXr37m1IMr744gv7tuLiYqNXr16GJGPz5s3OnSCqFUGqFsnMzDQkGWPGjCmzLy0tzZBkvPjiizXQM5THmSB15513GpLKhGGbzWbExcUZQUFBxvnz5+3bJ06caEgy0tPTyxxr9OjRhiRj/fr1LvUfZVX0i9ZmsxnNmjUzgoODjYKCAod9BQUFRnBwsBEXF+ewfdiwYeVeq7vuusuQZBw/fty+bf78+eX+rKemppb7dwJV4+4g5ez1OnDggCHJSExMLFN+3bp15f4OQM1hjFQtsm7dOklSUlJSmX3JycmSpPXr11/PLqEKiouLlZaWpmnTpmnOnDnatm1bmTIXLlzQtm3b1KZNG8XExDjss1gs6tu3rwoLC7Vjxw77dv4+eJ6srCydPHlSPXr0UFBQkMO+oKAg9ejRQ0eOHFFOTo59+7p16+z7futa15Hr7hk2bNigGTNm6O9//7s+/vjjcse/OXu9Kirfs2dPBQUFcX09DGOkapGKFk6OjIxUcHBwuYs0o+bk5uZqzJgxDtu6du2q9957T61atZIkHT58WDabrdxFsa9eyLtXr172PwcHBysyMrLC8rh+KlvcvHXr1srMzFRWVpaioqJUWFioU6dO6Xe/+50aNGhwzfJXH7eyNrju18/UqVMd3jds2FCzZs1yWL5Mcv56VVS+QYMGatmypX744QeVlpbK25tf4Z6AO1K1yJX1/8LCwq65PzQ0tMx6g6hZY8aM0erVq/XTTz+psLBQu3fv1oMPPqjt27erT58+OnfunKSqXdury135szPlUf2cvY5mr3t5dbju1a9Dhw56++23deTIERUVFeno0aOaPXu2LBaLRo8erU8//dShvLPXqyp/J2w2m/3fDtQ84ixQjX77v9aOHTvqnXfekSS9++67evPNN/XMM8/URNcAmHD//fc7vI+NjdUTTzyhdu3aqW/fvpo8ebLuvffeGuodagJ3pGqRK/9DKe9/m/n5+eX+LwaeZfz48ZKkTZs2Saratb263JU/O1Me1c/Z62j2updXh+tec/r06aNWrVrp22+/tV8HyfnrVZW/ExaLRSEhIW7rO1xDkKpFKhr/kJubq4KCgnLHZsCzRERESLo855AkxcXFycvLq9yxLdcaN9G6dWsVFBQoNze3SuVR/Sobo/Tb6xIUFKSmTZvq6NGjunTpUqXlK2uD616zrvxcnz9/3r7N2etVUflLly7p6NGjatmyJeOjPAhBqhZJSEiQJK1cubLMvszMTIcy8GxXvrl3ZUK/gIAAxcfH68CBA2UmAzQMQ6tWrVJQUJBuv/12+3b+Pnie1q1bq1mzZtq0aZM9JF9RWFioTZs2qWXLloqKirJvT0hIsO/7rSvXsXfv3g7lJa67pyksLNT333+voKAge6CSnL9eFZXfuHGjfcJXeJCann8BVVdSUmLExcVVOCHn0aNHa6x/cLRv3z6jsLDwmtsjIyPLzB3k7IScBw4cYELOGuAJE3KGhYUxIWc1qej65ufnGwcOHCiz/fz58/b5wH47x5OZ61XZhJybNm1y8SzhThbDYOGe2qS8JWKOHz+umTNnskSMB0lNTdU//vEP9e7dWzExMQoKCtLBgwf1xRdfqKSkRBMnTtS0adPs5W02mwYMGGBfIiYhIUGHDh3S8uXLFRsbq23btlW4RMzAgQPtS8RcvHiRJWLcaMGCBdq4caMk6dtvv9WuXbvUo0cP3XTTTZIuz+/z8MMPS7p8Z6JHjx7au3evkpKS1LlzZ+3atUsrV65U165dtX79egUEBDgcf+zYsfYlYv7whz/o1KlTysjIUHBwsLZs2aKbb77ZofzVS46kpKRIurzkiNVqVUZGhgYPHlzdH0mdUtXre+zYMcXFxalr165q166dIiMj9dNPP+mrr77SiRMn1L59e61du1bh4eEOx3f2en3//ffq0aOHioqKlJKSoqZNm+rzzz/X999/ryeeeIIlYjxNTSc5OG/btm1Gv379jNDQUCMgIMCIj4833n///ZruFn5j3bp1xpAhQ4zWrVsboaGhhre3txEZGWncd999RmZm5jXrXLhwwUhNTTVatWpl+Pr6GpGRkcbDDz9s5ObmltvOokWLjNtvv90ICAgwwsLCjAEDBhg7d+6srtOql0aNGmVIKvc1atQoh/Jnz541nnrqKSMqKsrw8fExoqOjjQkTJpR7p+jSpUvGrFmzjFtvvdXw8/MzwsPDjZSUFOPQoUPl9mnFihVGr169jKCgICM4ONhISEgwVq1a5c7Trjeqen3z8vKMxx9/3OjatavRpEkTw9vb2wgJCTHi4+ONV155xWHlgd9y9nrt37/fGDRokNG4cWPDz8/PaN++vTF37lyHu9XwDNyRAgAAMInB5gAAACYRpAAAAEwiSAEAAJhEkAIAADCJIAUAAGASQQoAAMAkghQAAIBJBCkAAACTCFIAAAAmEaQAAABMIkgBQA1JS0uTxWLR6NGja7orAEwiSAEAAJhEkAIAADCJIAWgXjl//rxee+019ezZU40aNZKfn59iYmJ0zz33aMmSJWXK/u1vf1Pnzp0VEhKiwMBA3XrrrZo8ebLOnDlzzePv3LlTKSkpatGihXx9fRUaGqq4uDgNHDhQn3zyib1cbGysxowZI0lKT0+XxWKxv+66665qO38A7mUxDMOo6U4AwPWQk5Ojfv366YcfflBgYKB69Oih8PBw/fjjj/rmm2/UsGFDHTt2TJL066+/qk+fPtqzZ49CQ0N11113ycfHR+vXr5fValXLli21Zs0axcbG2o+/evVq9e/fXyUlJerQoYNat26tS5cu6ccff9TevXvVr18/ffzxx5KkZ599Vlu3btWmTZvUqlUr9ezZ036ctm3b6v/9v/93HT8ZAKYZAFAPXLp0ybj99tsNSUZSUpLx888/O+wvKioyPv/8c/v7lJQUQ5Jxxx13GFar1b793LlzRv/+/Q1JRvfu3R2OkZiYaEgyFi1aVKb9s2fPGlu2bHHYtnDhQkOSMWrUKDecIYCawKM9APXCv//9b+3YsUNNmzbVsmXL1KRJE4f9/v7+GjBggCQpOztbH3zwgSwWi9544w2Fh4fbywUHB+vNN9+Uv7+/Nm/erM2bN9v3/fTTT5JkP87VwsLC1K1bt+o4NQA1iCAFoF748ssvJUnDhw9XcHBwhWU3bNggm82mTp066bbbbiuzv3nz5kpOTpYkrV271r49Pj5ekvTAAw9o48aNKi0tdVf3AXgoghSAeuH48eOSLo8/qsyPP/4oSWrZsmW5ZVq1auVQVpKmT5+uzp07a8WKFerVq5dCQ0PVs2dPTZ48Wfv27XOl+wA8FEEKANwkMjJSO3bs0Nq1a/X888/rjjvu0K5du/TXv/5Vt956q2bMmFHTXQTgZgQpAPVCdHS0JGn//v2Vlm3evLkk6ciRI+WWubLvStkrrkxf8PLLL2vt2rX69ddfNW/ePFksFk2aNEmHDx82ewoAPBBBCkC90K9fP0nSe++9p8LCwgrL9u7dW15eXtqzZ4/27t1bZv+pU6fsY64SExMrPJa/v78eeeQR3XbbbbLZbPrmm2/s+3x9fSWJsVRALUaQAlAv3HvvverUqZNOnjypwYMH6/Tp0w77L1y4oBUrVki6fPdq8ODBMgxD48ePdyhbWFiocePG6cKFC+revbu6d+9u3zdz5kxlZ2eXaXv//v3KysqSJMXExNi3t2jRQpL0ww8/uO9EAVxXTMgJoN44fvy4kpOTdeDAAQUGBqpnz572CTn37t3rMCHn6dOn1adPH+3du1dhYWFKTEyUt7e31q9fr19++eWaE3I2bNhQeXl5atu2rdq1a6eAgACdPHnS/g2+kSNHKj093V7+4sWLatmypU6ePKlOnTqpffv28vHxUZs2bfTcc89d508HgBkEKQD1SkFBgf73f/9XH374ofbv36+LFy8qMjJSHTp00PDhw5WSkmIve/78ef3rX/9SRkaGDh48KJvNppYtW+r+++/Xs88+q0aNGjkce/HixVq9erW2b9+ukydPqrCwUJGRkbrllls0btw43XfffbJYLA51vvvuOz3//PPasmWLTp8+LZvNpoSEBK1bt+56fBwAXESQAgAAMIkxUgAAACYRpAAAAEwiSAEAAJhEkAIAADCJIAUAAGASQQoAAMAkghQAAIBJBCkAAACTCFIAAAAmEaQAAABMIkgBAACYRJACAAAw6f8D7wbOYTuwX0AAAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -620,7 +475,12 @@ } ], "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" + "optimization_result[\"cost\"].plot(\n", + " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + ")\n", + "plt.ylabel(\"Probability\", fontsize=16)\n", + "plt.xlabel(\"cost\", fontsize=16)\n", + "plt.tick_params(axis=\"both\", labelsize=14)" ] }, { @@ -633,31 +493,25 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 12, "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:37.309483Z", - "iopub.status.busy": "2024-05-07T16:03:37.308945Z", - "iopub.status.idle": "2024-05-07T16:03:37.313874Z", - "shell.execute_reply": "2024-05-07T16:03:37.313442Z" - }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ - "[0, 0, 1]" + "{'x_0': 0, 'x_1': 0, 'x_2': 1}" ] }, - "execution_count": 15, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "best_solution = optimization_result.solution[optimization_result.cost.idxmax()]\n", + "best_solution = optimization_result.solution[optimization_result.cost.idxmin()]\n", "best_solution" ] }, @@ -679,15 +533,9 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 13, "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:37.316362Z", - "iopub.status.busy": "2024-05-07T16:03:37.315830Z", - "iopub.status.idle": "2024-05-07T16:03:37.375955Z", - "shell.execute_reply": "2024-05-07T16:03:37.375336Z" - }, "pycharm": { "name": "#%%\n" }, @@ -748,7 +596,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" }, "vscode": { "interpreter": { diff --git a/applications/optimization/integer_linear_programming/integer_linear_programming.qmod b/applications/optimization/integer_linear_programming/integer_linear_programming.qmod index efe08cc4b..382226df1 100644 --- a/applications/optimization/integer_linear_programming/integer_linear_programming.qmod +++ b/applications/optimization/integer_linear_programming/integer_linear_programming.qmod @@ -1,1079 +1,20 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=152.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-11.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-11.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-25.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-25.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-50.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-24.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-24.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-49.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-25.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-25.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-51.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=10.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=10.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=10.0 - } -]; - -qfunc main(params_list: real[6], output target: qbit[11]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + x_0: qnum<2, False, 0>; + x_1: qnum<2, False, 0>; + x_2: qnum<2, False, 0>; + monotone_rule_1_slack_var_0: qbit; + monotone_rule_2_slack_var_0: qbit; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=True, -initial_point=[0.0, 0.03762827822120867, 0.018814139110604335, 0.018814139110604335, 0.03762827822120867, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=90, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=0.7 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[6], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 3) { + phase (-(((((((((10 * v.x_0) * v.x_1) + ((10 * v.x_0) * v.x_2)) - v.x_0) + ((10 * v.x_1) * v.x_2)) - (2 * v.x_1)) - (3 * v.x_2)) + (10 * (((((v.monotone_rule_1_slack_var_0 + v.x_0) + v.x_1) + v.x_2) - 1.0) ** 2))) + (10 * (((((v.monotone_rule_2_slack_var_0 + v.x_0) + v.x_1) + v.x_2) - 1.0) ** 2))), params[i]); + apply_to_all(lambda(q) { + RX(params[3 + i], q); + }, v); + } +} diff --git a/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json b/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json index 0967ef424..af12aaf3f 100644 --- a/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json +++ b/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json @@ -1 +1,43 @@ -{} +{ + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "tdg", + "ry", + "rz", + "s", + "r", + "sx", + "t", + "cy", + "p", + "u", + "h", + "cx", + "sdg", + "z", + "x", + "cz", + "u1", + "u2", + "rx", + "sxdg", + "y", + "id" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 2268737765 + } +} diff --git a/applications/optimization/max_clique/max_clique.ipynb b/applications/optimization/max_clique/max_clique.ipynb index f4d1fba38..d8af81f07 100644 --- a/applications/optimization/max_clique/max_clique.ipynb +++ b/applications/optimization/max_clique/max_clique.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "13d83b59-57f7-48ee-8bff-deda7d28edc5", + "id": "10115924-81df-4877-9ef5-0bd2c7f21980", "metadata": { "tags": [] }, @@ -14,7 +14,7 @@ }, { "cell_type": "markdown", - "id": "6d56bb6d-9f3b-45db-8e98-b50f27af7505", + "id": "b6916fad-2b36-4cc7-9f4a-b9991bdcdc29", "metadata": { "tags": [] }, @@ -28,7 +28,7 @@ }, { "cell_type": "markdown", - "id": "3b5fbdb8-373b-4629-8ca1-51ef9be82edd", + "id": "cdc179ce-71f3-4269-a128-94b42b4e00a8", "metadata": {}, "source": [ "# Solving the problem with classiq" @@ -36,7 +36,7 @@ }, { "cell_type": "markdown", - "id": "0bdc4e6a-199b-44b3-bd3f-fd24722b616b", + "id": "43c06afd-0219-4c66-bbdf-8eae31ffd1bc", "metadata": {}, "source": [ "## Define the optimization problem\n", @@ -47,14 +47,8 @@ { "cell_type": "code", "execution_count": 1, - "id": "83ddbd07-f7ab-4d80-b357-3890622d395f", + "id": "e5fc6812-3e72-4415-b4ca-5e873d81041b", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:19.815355Z", - "iopub.status.busy": "2024-05-07T15:48:19.814727Z", - "iopub.status.idle": "2024-05-07T15:48:20.366172Z", - "shell.execute_reply": "2024-05-07T15:48:20.365339Z" - }, "tags": [] }, "outputs": [], @@ -92,7 +86,7 @@ }, { "cell_type": "markdown", - "id": "3496c5d6-7df6-49fb-b5b9-5ba48d2b7d62", + "id": "eba6ce0a-dd2b-4e34-8273-67cdd7706181", "metadata": {}, "source": [ "### Initialize the model with parameters" @@ -101,20 +95,14 @@ { "cell_type": "code", "execution_count": 2, - "id": "bc9871c1-224e-4206-b39e-af7e448aca70", + "id": "2144f922-842a-4d1a-9c81-b87742fbbd73", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:20.372542Z", - "iopub.status.busy": "2024-05-07T15:48:20.370932Z", - "iopub.status.idle": "2024-05-07T15:48:21.344387Z", - "shell.execute_reply": "2024-05-07T15:48:21.343460Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/png": 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", 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JSEhIwKlTp9C8eXPW0QghMopmKAkhZebt7Q1ra2vUqVMHiYmJclsmAfmdofyKx+NhzJgxuHr1Kt68eQMTExOcO3eOdSxCiIyiQkkI+amioiJMnjwZQ4cORf/+/XHlyhW0aNGCdSyxkvdC+ZWZmRkSExNhbm6OPn36YMWKFTJ7/iYhhB0qlISQUr1+/Rq//vordu3ahR07duDQoUOoWrUq61hiJ89L3v9Wt25dhIeHY+nSpViyZAkcHBzw/v171rEIITKExynCR3BCSIVcu3YN7u7uAAB/f39YW1szTiQ5rVq1wvv37/Hx40fWUSTq7NmzGDRoEKpXrw6BQABTU1PWkQghMoBmKAkh/8FxHHbt2gUbGxu0atUKiYmJClUmAcVZ8v633r17IykpCVpaWrC2tsa+ffsU8t8DIaR8qFASQv7hy5cvGDlyJMaPH4+xY8ciKioKjRo1Yh1L4hS1UAJAixYtEBMTg5EjR2LMmDHw9PREXl4e61iEEClGhZIQ8s3Tp0/RuXNn+Pj44PDhw9i2bRvU1NRYx2JCke6h/B51dXXs3LkTR48excmTJ2FtbY2MjAzWsQghUooKJSEEAHDhwgWYmpri3bt3uHr1KoYPH846ElOKPEP5d0OHDkVcXBxyc3NhZmaG4OBg1pEIIVKICiUhCo7jOHh5eaFXr14wNjZGYmIiTExMWMdijgrl/2vbti0SEhLw66+/wsXFBfPmzUNxcTHrWIQQKUKFkhAFlpOTg/79+2P27NmYPXs2Tp8+jbp167KOJRWUlOjt8e9q1qwJgUAALy8veHl5oXfv3sjMzGQdixAiJejYIEIUVHp6OlxdXfHkyRMcPnz42/FA5C8GBgZ4+vQpcnNzWUeROtHR0ejfvz+UlZVx6tQphTsBgBDyX/QRnBAFFBoaCjMzMxQVFSEuLo7K5HfQDOWP2djYIDk5Ga1atYKNjQ22bt1KtwcQouDoHZMQBSIUCrFkyRI4OTnB1tYW8fHxMDQ0ZB1LKtE9lKVr1KgRoqKiMGXKFEyZMgUDBw5ETk4O61iEEEaoUBKiID5+/AhHR0esWLECK1euREBAAGrWrMk6ltRS9GODykJVVRXr16/HqVOnEBERAQsLC9y/f591LEIIA1QoCVEAd+7cgZmZGWJjYxEeHo4FCxbQku5P0Axl2fXr1w83btyAkpISzM3NcfLkSdaRCCESRr9RCJFzvr6+6NixIzQ0NJCQkIC+ffuyjiQTaIayfPT09BAXFwdnZ2cMGDAAU6dORWFhIetYhBAJoUJJiJwqLi7GzJkzMXDgQLi4uCA2NhatW7dmHUtmKCkp0QxlOWloaMDb2xvbt2/Hzp07YWtrixcvXrCORQiRACqUhMihzMxM9OzZE5s3b8bmzZvh7e0NDQ0N1rFkCs1QVgyPx8OECRNw+fJlPH36FMbGxoiKimIdixAiZlQoCZEzN27cgKmpKVJSUnDhwgVMmTKFylEF0Axl5XTs2BFJSUlo3749evbsibVr10IoFLKORQgREyqUhMiRAwcOoHPnzmjSpAkSExNhY2PDOhJRYPXr18eZM2cwf/58zJs3D66urvj48SPrWIQQMaBCSYgcKCgowLhx4zBq1Cj89ttviI6ORtOmTVnHkmk0QykaysrKWLFiBcLCwnD58mWYmpri5s2brGMRQkSMCiUhMu758+ewsbHBoUOHsG/fPuzZswfq6uqsY8k8uk1AtOzt7ZGUlISaNWvCysoKhw8fZh2JECJCVCgJkWHR0dEwNTXFixcvEBMTg1GjRrGOJDfoHErR++WXXxAbG4shQ4ZgxIgRGDNmDL58+cI6FiFEBKhQEiKDOI7Dli1b0L17dxgaGiIxMREWFhasY8kVOvhdPKpUqYJ9+/bhwIEDOHbsGDp16oQ///yTdSxCSCXROyYhMiYvLw9Dhw7F1KlTMWXKFERGRkJLS4t1LLlDS97i5enpidjYWHz8+BGmpqaIiIhgHYkQUglUKAmRIY8ePYK1tTUCAwPh4+ODDRs2QEVFhXUsuUSbcsTP2NgYCQkJ6Ny5M+zt7bF48WKUlJSwjkUIqQAqlITIiDNnzsDMzAw5OTm4du0aBgwYwDqSXKMZSsmoXbs2goKCsHr1aqxatQp9+/bFu3fvWMcihJQTFUpCpJxQKMSqVatgZ2cHKysr3LhxA+3atWMdS+7RPZSSo6SkhHnz5uHcuXO4efMmTExMEBcXxzoWIaQc6B2TECn2+fNnuLm5YeHChVi0aBFCQ0NRu3Zt1rEUAu3ylrzu3bsjKSkJTZs2RZcuXbBz5076/4AQGUGFkhApdf/+fVhYWODixYsICQnBsmXLaNZMgmjJm42mTZvi0qVL+P333zFhwgQMHToUubm5rGMRQn6CfjsRIoUCAgJgYWEBZWVl3LhxA46OjqwjKRwq7+yoqalhy5Yt8PHxQVBQECwtLZGamso6FiGkFPSOSYgUKSkpwbx58+Du7o6+ffsiLi4Ourq6rGMpJFryZm/AgAGIj49HSUkJzM3NIRAIWEcihPwAFUpCpERWVhb69u2LdevWYd26dTh58iQ0NTVZx1JYNEMpHQwNDREfH4++ffuiX79+mDlzJoqKiljHIoT8Cx1gR4gUSE5OhqurK3JycnDu3Dl0796ddSSFR/dQSo/q1avD19cX1tbWmDlzJuLj43Hy5Ek0atSIdTRCyP/QR3BCGDt27Bisra1Rt25dJCYmUpmUEjRDKV14PB6mTJmCS5cu4eHDhzA2NkZ0dDTrWISQ/6F3TEIYKSwsxKRJkzBs2DAMGDAAV65cQYsWLVjHIv9DM5TSqVOnTkhKSoKhoSG6d++O9evX072uhEgBKpSEMPDq1St0794de/bswc6dO3Hw4EFUrVqVdSzyN7QpR3o1aNAA586dw6xZszBr1iz069cPnz59Yh2LEIVGhZIQCYuNjYWpqSkePnz47bw9mg2TPsrKyqwjkFKoqKhgzZo1CAoKwoULF2Bubo47d+6wjkWIwqJCSYiEcByHXbt2oVu3bmjVqhUSExNhbW3NOhb5ASr5ssHZ2RkJCQmoWrUqLC0t4e3tzToSIQqJCiUhEpCfnw9PT0+MHz8eY8eORVRUFO1QlXK0KUd2aGtr49q1a/Dw8MDQoUMxfvx4FBQUsI5FiEKhY4MIEbMnT57A3d0d9+7dw5EjRzBs2DDWkUgZ0AylbKlWrRoOHz6MTp06YdKkSUhISIC/vz+aN2/OOhohCoE+ghMiRufPn4epqSmysrIQGxtLZVKG0Ayl7OHxeBgzZgyuXr2KzMxMmJiY4OzZs6xjEaIQ6B2TEDHgOA5eXl7o3bs3TE1NkZCQAGNjY9axSDnQDKXsMjMzQ2JiIszNzdG3b18sX74cQqGQdSxC5BoVSkJELCcnB/3798fs2bMxe/ZsREREoG7duqxjkXKiGUrZVrduXYSHh2Pp0qVYunQpHBwckJWVxToWIXKL3jEJEaG0tDRYWlri9OnT8Pf3x5o1a+j4GRlFhVL2KSkpYfHixTh9+jTi4uK+rRYQQkSP3jEJEZGQkBCYm5ujpKQE8fHxcHd3Zx2JVAItecuP3r17IykpCVpaWujUqRP27t1Lh9YTImJUKAmpJKFQiCVLlsDZ2Rm2traIj4+HgYEB61ikkmhmWb60aNECMTExGDlyJMaOHYsRI0YgLy+PdSxC5AYVSkIq4cOHD3B0dMSKFSuwcuVKBAQEoEaNGqxjERH4OkNJM1nyQ11dHTt37sTRo0fh5+cHKysrZGRksI5FiFygQklIBd25cwfm5ua4du0aIiIisGDBArrvTo58/f+SdgfLn6FDhyIuLg75+fkwNTVFcHAw60iEyDz67UdIBfj6+qJjx47Q1NREQkIC+vTpwzoSEbGvM5QlJSWMkxBxaNu2LW7cuIHu3bvDxcUFc+fORXFxMetYhMgsKpSElENxcTFmzJiBgQMHwsXFBbGxsWjVqhXrWEQMaIZS/tWsWRMCgQBeXl5Yv349evbsiTdv3rCORYhMokJJSBllZmaiZ8+e2LJlC7Zs2QJvb29Uq1aNdSwiJl8LJc1ayTcej4eZM2fiwoULuH//PoyNjXH16lXWsQiROVQoCSmD+Ph4mJqaIiUlBVFRUZg8eTIdKyPnaIZSsdjY2CA5ORna2tro1q0bNm/eTBuyCCkHKpSE/MSBAwfQpUsXNGnSBImJiejatSvrSEQCaIZS8TRq1AgXLlzA1KlTMW3aNPTv3x/Z2dmsYxEiE6hQEvIDBQUFGDt2LEaNGoURI0YgOjoaTZs2ZR2LSMjXGWiaoVQsqqqq8PLygr+/P86cOQNzc3OkpKSwjkWI1KNCSch3PH/+HF27dsXhw4exf/9+7N69G+rq6qxjEQn6erA5zVAqJnd3dyQkJEBVVRUWFhbw8fFhHYkQqUaFkpB/iY6OhqmpKV6+fIkrV65g5MiRrCMRBmiGkujq6uL69etwcXHBoEGDMHnyZBQWFrKORYhUokJJyP9wHIctW7age/fuMDQ0RGJiIszNzVnHIozQphwCABoaGjh27Bh27tyJ3bt3w8bGBs+fP2cdixCpQ4WSEAB5eXkYMmQIpk6diqlTpyIyMhJaWlqsYxGGvhZKOtic8Hg8/P7774iJicGLFy9gbGyMCxcusI5FiFShQkkU3qNHj2BlZYWgoCD4+Phg/fr1UFFRYR2LMEYzlOTfLC0tkZSUBGNjY/Tq1QurV6+mPx+E/A8VSqLQTp8+DVNTU+Tm5uL69esYMGAA60hEStCxQeR76tWrh9OnT2PBggVYsGABnJ2d8eHDB9axCGGOCiVRSEKhECtXroS9vT06deqEhIQEtG3blnUsIkVohpL8iLKyMpYvX46wsDBcvXoVpqamSE5OZh2LEKaoUBKF8+nTJ7i5uWHRokVYvHgxQkJCUKtWLdaxiJShGUryM/b29khMTETt2rVhbW2NQ4cOsY5ECDNUKIlCSUlJgYWFBS5evIiQkBAsXbr0W3Eg5O++/rmgx++R0vzyyy+4evUqhg4dCk9PT4wePRpfvnxhHYsQiaPfpERhCAQCWFpaQlVVFQkJCXB0dGQdiUgx2uVNyqpKlSrYu3cvDh48CG9vb3Tq1Al//vkn61iESBQVSiL3SkpKMHfuXPTr1w92dna4fv06dHR0WMciUo4KJSmvESNG4Nq1a/j48SNMTEwQHh7OOhIhEkOFksi1rKws9OnTB15eXvDy8oKvry80NTVZxyIygJ6UQyqiQ4cOSExMRJcuXeDg4IBFixbRhxKiEKhQErmVlJT0bffluXPnMHPmzG8lgZCf+fosbyoDpLxq1aqFoKAgrFmzBqtXr0afPn3w9u1b1rEIESsqlEQuHT16FJ06dUK9evWQmJiI7t27s45EZAwdG0QqQ0lJCXPnzkVkZCRu3boFExMTXL9+nXUsQsSGCiWRK4WFhZg4cSKGDx+OgQMH4sqVK2jRogXrWEQG0QwlEYVff/0VycnJaNasGbp27YodO3bQyQFELlGhJHLj1atX+PXXX7F3717s2rULBw4cQJUqVVjHIjKK7qEkotKkSRNcunQJ48ePx8SJEzFkyBDk5uayjkWISFGhJHIhNjYWpqamePToEaKjozFu3Di6X5JUytcZSjrYnIiCmpoaNm/eDF9fXwQHB8PS0hKpqamsYxEiMlQoiUzjOA47d+5Et27d0Lp1ayQlJcHKyop1LCIH6GBzIg79+/fHjRs3UFJSAjMzM/j7+7OORIhIUKEkMis/Px+enp6YMGECxo0bhwsXLqBhw4asYxE5QUveRFwMDAwQHx8Pe3t7eHh4YMaMGSgqKmIdi5BKUWEdgJCKePLkCdzc3JCSkoKjR49i6NChrCMROUNL3kScqlevDh8fH1hbW2PGjBmIj4/HyZMn0bhxY9bRCKkQmqEkMuf8+fMwNTXF+/fvERsbS2WSiAUteRNx4/F4mDx5MqKjo/Ho0SOYmJggOjqadSxCKoQKJZEZHMdh3bp16N27N0xNTZGQkABjY2PWsYicohlKIinW1tZITk6GoaEhunfvDi8vL/ogQ2QOFUoiE7Kzs8Hn8zFnzhzMmTMHERERqFu3LutYRI59vYeSfrETSdDS0sK5c+cwe/ZszJ49G25ubvj06RPrWISUGRVKIvXS0tLQsWNHnDlzBgKBAKtXr/42e0SIuNAMJZE0FRUVrF69GsHBwbh48SLMzMxw+/Zt1rEIKRMqlESqhYSEwNzcHCUlJYiPj4ebmxvrSERB0D2UhBUnJyckJiZCQ0MDHTt2xLFjx1hHIuSnqFASqSQUCrF48WI4Ozvj119/RXx8PAwMDFjHIgqEnuVNWGrdujWuXbuG/v37Y9iwYfj9999RUFDAOhYhP0SFkkidDx8+wNHREStXrsSqVasgEAhQo0YN1rGIgqFneRPWqlatioMHD2Lfvn04dOgQOnfujCdPnrCORch3UaEkUuX27dswMzPDtWvXcPr0acyfP//bTBEhkkQHmxNpwOPxMGrUKFy9ehXv3r2DiYkJzpw5U+7r5BYU497LT0h++gH3Xn5CbgHdG0xEiw42J1LDx8cHo0aNgo6ODiIjI9GqVSvWkYgCU1H56+2RZiiJNDA1NUViYiKGDBkCOzs7LFmyBIsWLSr1A3f6m2wcj3uKi6mZePo+D3+/G5gHoHmdarDV08Jgy+bQaVBd7D8DkW9UKIlI5BYU43FWLgqLhVBTUULLuhrQUC/bH6+ioiLMmTMHmzZtwuDBg7F3715Uq1ZNzIkJKR0dG0SkTZ06dRAWFoZVq1ZhyZIluH79Ory9vf9zhNqz93mYH3gHMRnvoKzEQ4nwv3+GOQBP3ufhWNwTHL72GF2062G1a1s0q0PvvaRiqFCSChPFp9/MzEzw+XxcvXoVW7duxcSJE7/9IieEJTo2iEgjJSUlLFq0CJaWlhg0aBBMTEzg7+8Pc3NzAIDvjadYEnIPxf8rkd8rk3/39euxj7LQY1M0ljkZYYB5c/H+EEQuUaEk5SaqT7/x8fFwd3dHYWEhLly4gK5du0rwpyCkdHRsEJFmvXr1QlJSEjw8PNC5c2ds3boVhTq/YkNkWoWuVyLkUCLkMDfgDt7lFGCirY6IExN5R7sdSLn43niKHpuiEfsoC0D5P/363ngKANi/fz+6dOmCpk2bIikpicokkTpfZyhpUw6RVs2bN8fly5cxatQozNwZUOEy+W/rz6Xh5P/eqwkpK5qhJGW2/WI61p+r/Kff/d5+uLB1FsaNG4fNmzdDXV1dxEkJqbyvM5S0KYdIM3V1dcxd4YWz66NQJOS+e8uQsDAfn+MCUPAyFYWv0iD8koO6dlOh2a7HD6+7OOQerFvXo3sqSZnRDCUpE98bTytcJv8to5oBJm48jl27dlGZJFKLlryJrJgfeAccT+mH958L8z7j01UfFGU9g6rWL2W6ZrGQw/zAO6KMSeQczVCSn3r2Pg9LQu5992uFb5/g05UTKHydgZLcj+CpqkO1bjPUsHRDNR3LH17z3PvaePY+jz79EqlFB5sTWZD+JhsxGe9K/R5lzTpoOvEYlDVro+BVOl4fmfbT65YIOcRkvENGZja0tehIIfJzNENJfmp+4J1vOwb/reRzJoSF+dBo2x21e4xGTev+AIC3ghXIvvnjw3fp0y+RdvToRSILjsc9hbJS6Sdj8FRUoaxZu9zXVlbiwfs63UtJyoZmKEmpfvbpt2prc1Rtbf6Pf1bd1AGvDk/F5/ggVO/Q57uvo0+/RNrRDCWRBRdTM3+6ObKiSoQcLqZlYimMxHJ9Il9ohpKUqiyffv+Np6QMler1ICzIKfX76NMvkWZ0DyWRdjkFxXj6Pk+sYzzNyqPHNJIyoRlKUqqyfvoVFn4BV1wAYUEe8tPjkP8oEdUMupT6Gvr0S6SZIs5QchwHjuMgFArL9d8r8hpxXYv16yWZ5QM0wKl3FO+fCQCPs3Jh1LimWMchso8KJfmh8nz6/RC1Hzlf75nkKaGarhXq9Pr9p6/7+um3rI9pFAdZ/EUiT78UpTXLu3d/3epx6NAhREdHS92/F1H/e+U4momtCB6PByWlv3ZYV/a/l/c1wtrNga7iLZQAUFhM9xGTn6NCSX7oSVYuyvorpoa5M6rpd0ZJdhbyHlwBxwmBkqKfvo4DYGLTG7yPL5j8gqVfohVT3l+AovylK67r/vt//52amprc/7zSci1ZysjavZefYL/titjHUVOhu+PIz1GhJD9Unk+lqnWbQbVuMwCAZtvueOO7CJn+y9Fw2MafvvFadeqCusiW6l8cinKtsl5XEdy4cQMWFhYYPHgwFi5cyDoOIf/Rsq4GeECZP/hXBO9/4xDyM1QoyQ9V5lNpNf1OeH9mO4rfv4Bq3aalfu+sGdPo/hwidb4WZzo2iEgrDXUVNK9TDU/EuDGned1qTG9JIrKD/pSQH6rMp1+uqAAAICzILfX76NMvkVYqKn+9PVKhJNLMVk8Lx+Ke/HTz5OfEUAi/5KIk5z0AID8jHsXZf90nXMPUEUpV/vs+rKzEg62uluhDE7lEhZL8UFk+/ZbkfoSyRq1//DOupBi5d6PAU1GHar3mpY5Bn36JtKKDzYksGGzZHIevPf7p932OC0TJ58xv/zsvLRZIiwUAaBrZfrdQlgg5DOlY+ns4IV/Rb3JSqp99+s06sx1cYR7Um7WBcvW6KMn5gNyUSyjOeo7av46EklrVH16bPv0Safa1UCrSsUFEtrx//x4blsxH/semqNqiHaCk/MPvbTr+YLmurazEg3WruvTgCVJmtHWLlGqwZfNSl1I0DLoAPCVkJ0fg/dmdyL4RBJXq9VDffRFqWLiWem369Euk2ddzKOkkACJthEIhDhw4AF1dXfj4+GCSZV2oq6mKdAwVJR5Wu7YV6TWJfKMZSlIqnQbV0UW7HmIfZX23WGoY2kDD0Kbc1+WEJSh5mYILgc/xy6hR3355EyItaMmbSKObN29i/PjxuHbtGoYMGQIvLy80bNgQ2jeeYm7AHZGNs9zJCM3qVBPZ9Yj8oxlK8lOrXdtCpZyPX/yZKqoq6KT2FOPGjYOFhQViY2NFen1CKos25RBp8vHjR0yePBmmpqb4/PkzoqOjcezYMTRs2BAAMMC8OfQL00Uy1qxeeuhvTqtHpHyoUJKfalanGpY5ifbxiMud2+DkgZ2IjY0Fj8dDp06dMHz4cLx+/Vqk4xBSUfQsbyINOI7DsWPHoK+vj0OHDmHdunVITk5G165d//F9O3bswNmN09C3znuoqyhBuZyTAMpKPKirKOEPt7aYYKstyh+BKAgqlKRMBpg3x8xeupW7yP9+MY80r//t06+VlRXi4uKwd+9ehIeHQ1dXFxs2bEBhYWFlIxNSKYr4LG8iXe7evYtu3bph2LBhsLGxwYMHDzBjxgyoqv7zfskzZ85g8uTJmDp1KnbNGorz02xg3aouAPy0WHLCv/58W7eqi/PTbGhmklQYFUpSZhNtdbDWrW2lPv3ybpyAz8Lf8OHDh///mrIyRo8ejfT0dAwfPhyzZ89G+/btERkZKeofgZAyoxlKwkp2djZmzpyJDh064M2bN4iMjMTJkyfRpEmT/3zvvXv30L9/f/Tt2xfr168H8Neq0rGRloic2hVDLVugRd1q+Pc7Ng9Ag2o8ZCeFw6tbDRwbaUn3TJJK4XH0bknK6dn7PMwPvIOYjHeAsKTUoyqUlXgoEXLool0Pq13bIv/dc1hZWaF9+/Y4c+YM1NTU/vOaW7duYdKkSYiJiYGrqys2btyIli1bivEnIuS/Xr16hcaNG2PSpEnYunUr6zhEAXAcBz8/P0yfPh0fPnzAokWLMH36dKirq3/3+zMzM2FpaYkaNWrgypUrqF79x0f85BYU43FWLgqLhVBTUULLuhqoqqqEpk2bgs/nY/PmzWL6qYiioBlKUm7N6lTD/iEd8MlnFgxU3/3w02+LutUw1LIFzk/r+u3Tr66uLoKCgnD16lWMHj36u7M/7du3R3R0NE6cOIG4uDgYGBhg2bJlyM/Pl8jPRwhAxwYRyXrw4AF69eqFAQMGwNLSEvfv38e8efN+WCa/fPkCFxcX5OfnIzQ0tNQyCfz1oAqjxjVh3Lw2jBrXhIa6CpSUlODh4YFTp07R5jNSeRwhFRAREcEB4G7fvs1xHMflfCni7r74yCU9ec/dffGRy/lSVOrrjx8/zgHgli1bVur3ZWdnc3PnzuVUVVW5li1bcgEBAZxQKBTZz0HIj7x9+5YDwI0fP551FCLHcnJyvr3HtW7dmouIiPjpa4RCITdw4ECuSpUqXFxcXKXGv3LlCgeAi4mJqdR1CKEZSlIhAoEAOjo6aNOmDYDvf/otzaBBg7By5UosWbIEx44d++H3aWpqYs2aNbh37x4MDAzg5uaG3r1748GDByL9eQj5Nzo2iIgTx3EIDAyEoaEhNm3ahAULFuDu3bvo27fvT1+7fPly+Pj44OjRo7CwsKhUDisrKzRp0gR+fn6Vug4hVChJuRUXFyMoKAju7u7g8Sp+PuX8+fPh6emJkSNH4tKlS6V+r46ODsLDwxESEoKHDx+ibdu2mDlzJj5//lzh8QkpDW3KIeLy8OFD2Nvbw83NDW3atMG9e/ewZMkSVKlS5aev9fHxwdKlS7Fy5Up4eHhUOsvXZW9/f3860YBUChVKUm6XL19GVlYW3NzcKnUdHo+H3bt3w8bGBq6urrh///5Pv9/R0RH37t3D0qVLsXPnTujp6eHo0aM0i0RE7usMJf2SJaKSn5+PJUuWwMjICCkpKQgKCkJYWBhat25dptfHxsZixIgRGDZsGObPny+yXHw+H69evcLVq1dFdk2ieKhQknITCARo3rw5zMzMKn0tVVVV+Pv7o0mTJrCzs8ObN29++poqVapgwYIFSE1NRdeuXTF8+HB07twZSUlJlc5DyFc0Q0lEKTw8HG3atMGaNWswY8YMpKSkwNnZucyrPI8fP4aLiwssLCywd+/eSq0O/ZulpSWaNWtGy96kUqhQknIRCoUIDAyEm5ubyN7QatasiYiICHz58gVOTk7Iy8sr0+uaNWuGkydPIioqCtnZ2TAzM8O4ceOQlZUlklxEsdEMJRGFr0XQwcEBrVu3xt27d7Fq1SpUq1b2Mx8/ffoEBwcHVK9eHQEBAT/c+V1RSkpK6NevHwQCAf15JxVGhZKUy/Xr1/Hq1Su4u7uL9LrNmzdHWFgY7t69iyFDhpTrTc3W1hbJycnYvHkzfH19oaOjg507d9IbI6kUmqEklVFQUIBVq1bB0NAQCQkJ8PPzw9mzZ6GrW74njhUXF6N///54/vw5wsPDUa9ePbHk5fP5eP36Na5cuSKW6xP5R4WSlItAIEDDhg1hbW0t8mubmprC19cXwcHBmD17drleq6KigsmTJyMtLQ2urq6YMGECTE1NERMTI/KcRDF8LZR0fy4pr8jISLRr1w5Lly7FhAkTcP/+fXh4eFRoVWfatGk4f/48/P39oa+vL4a0f7G0tETz5s1p2ZtUGBVKUmYcx0EgEMDV1fXbL1tRc3R0xJYtW7Bx40bs2LGj3K/X0tLCgQMHEBcXBzU1NXTt2hWDBw/Gy5cvxZCWKAIqlKSsnj9/Dj6fj169eqFRo0a4efMmvLy8fnro+I9s374d27dvx86dO9GjRw8Rp/0nHo9Hu71JpVChJGWWlJSEJ0+eVHp3989MnDgRU6dOxeTJkxEWFlaha1hYWOD69es4cOAAIiMjoaenh3Xr1qGwsFDEaYm8oyVv8jNFRUXw8vKCvr4+Ll++DG9vb1y8eBFGRkYVvubp06cxZcoUTJs2DWPGjBFh2h/j8/nIzMzE5cuXJTIekS9UKEmZCQQC1KlTBzY2NmIfa/369XBycsKAAQMqvHtbSUkJnp6eSEtLg6enJ+bPn4+2bdvizJkzIk5L5BnNUJLSXLp0CR06dMDcuXMxcuRIpKamYvDgwZXatHj37l30798f9vb28PLyEmHa0pmbm6NFixa07E0qhAolKZOvy93Ozs5QVVUV+3jKyso4fvw4DA0N4eDggGfPnlX4WrVq1cKWLVtw8+ZNNG7cGH379oWzszMePXokwsREXtEMJfme169fY8iQIbC1tUXNmjWRmJiILVu2oGbNmpW67ps3b+Dg4IBWrVrhxIkT354pLwk8Hg98Ph8CgQDFxcUSG5fIByqUpExSUlKQlpYm8t3dpalWrRpCQ0Ohrq4OOzs7fPr0qVLXa9OmDaKionDy5EkkJSXB0NAQixYtKvMxRUQx0f1k5O+Ki4uxZcsW6Onp4ezZszh48CCuXLmCDh06VPra+fn5cHFxQUFBAUJDQ6GpqVn5wOXE5/Px9u1bREdHS3xsItuoUJIyEQgEqF69uthvDP+3Bg0aICIiAs+fP4eHhweKiooqdb2vn8AfPHiAmTNnYt26ddDX14e/vz/NRJHvoj8X5KvY2FiYmZlh2rRpGDRoEFJTUzFixAiRbFLkOA6enp64desWQkJC0KxZMxEkLj9TU1P88ssvtOxNyo0KJSkTgUAABwcHkR+oWxYGBgYICAjApUuXMH78eJH8gtfQ0MDKlSuRkpKCDh06wMPDAz169MC9e/dEkJjIE7qHkmRmZsLT0xOdOnWCqqoq4uLisGvXLtSpU0dkYyxduhS+vr44evQozM3NRXbd8qJlb1JRVCjJT2VkZOD27dsSXe7+N1tbW+zfvx/79+/H2rVrRXbd1q1bIyQkBOHh4Xj69Cnat2+PadOmVXp5ncgPmqFUXCUlJdi1axf09PQQFBSE3bt34/r16yIvfMePH8fy5cuxevVq9OvXT6TXrgg+n4+srCxcvHiRdRQiQ6hQkp8KCAhA1apV0adPH6Y5hg0bhiVLlmD+/Pnw9fUV6bXt7Oxw9+5drFy5Evv27YOuri4OHTpEs1OE/gwoqBs3bqBjx44YP3483NzckJqairFjx4p8k0xsbCw8PT0xfPhwzJ07V6TXrihjY2O0bt2alr1JuVChJD8lEAjQt29faGhosI6CJUuWYOjQoRg+fLjIHxGmrq6OuXPnIjU1Fd27d4enpyesra1x48YNkY5DZAsVSsWSlZWFsWPHwtLSEsXFxYiNjcWBAwdQv359kY/1559/wsXFBZaWltizZ0+ljhoSpa/L3gEBAZW+b50oDiqUpFTPnj1DfHw80+Xuv+PxeNi/fz+sra3h7OyM9PR0kY/RpEkTnDhxAtHR0cjPz4elpSVGjRqFt2/finwsIv1oyVsxCIVCHDhwAHp6evD19cWWLVtw48YNWFlZiWW8T58+wcHBATVq1EBAQACT+9NLw+fz8f79e0RFRbGOQmQEFUpSqoCAAKiqqsLe3p51lG/U1NQQEBAALS0t2NnZ4d27d2IZp2vXrkhMTMS2bdsgEAigq6uLbdu20Y3qCoTH49EMpQJITk5G586dMWrUKPTt2xepqamYNGkSVFRUxDJecXEx+Hw+Xr58ibCwMNSrV08s41RG+/btoaOjQ8vepMyoUJJSCQQC9OzZs9KH9Ypa7dq1ERERgc+fP8PZ2RlfvnwRyzgqKiqYMGEC0tLS4OHhgSlTpsDExITOaFMgNEMpvz5+/IhJkybBzMwMnz9/RnR0NI4dO4aGDRuKbUyO4zBlyhRERUXB398f+vr6YhurMr4uewcGBtIja0mZUKEkP/T69WtcuXJFapa7/+2XX35BaGgokpOTMXz4cLHOJNWvXx979+5FfHw8NDQ00K1bNwwYMADPnz8X25hEOtAMpfzhOA7Hjh2Dvr4+Dh8+jHXr1iE5ORldu3YV+9jbtm3Dzp07sXPnTnTv3l3s41UGn8/Hhw8fcOHCBdZRiAygQkl+KDg4GEpKSnB2dmYd5YcsLCxw/PhxnDp1CvPnzxf7eGZmZrh69SoOHz6MS5cuQU9PD2vWrEFBQYHYxyZs0AylfLl79y5sbGwwbNgwdOvWDQ8ePMCMGTMk8kjZiIgITJs2DTNmzMDo0aPFPl5ltW3bFnp6erTsTcqECiX5IYFAgG7duqFu3bqso5TK1dUVGzZswB9//IG9e/eKfTwlJSUMHz782zEiixcvRps2bRAeHi72sYnk0QylfMjOzsaMGTPQoUMHZGZmIjIyEr6+vmjSpIlExr9z5w4GDBgABwcH/PHHHxIZs7Jo2ZuUBxVK8l3v37/HxYsX4ebmxjpKmUydOhUTJkzA+PHjcebMGYmMWbNmTWzcuBG3bt1CixYt4ODgAAcHB2RkZEhkfCJ+PB6PZihlHMdxOHnyJPT19bFr1y6sWLECt27dkuhjZF+/fg0HBwe0bt0ax48fF/lZluLE5/Px6dMnREZGso5CpBwVSvJdISEhKCkpgaurK+soZcLj8bB582b07dsXfD4ft27dktjYhoaGiIyMhL+/P+7cuQMjIyPMnz8fubm5EstAxIcKpex68OABevbsiQEDBsDS0hL379/HvHnzJHpET35+PlxcXFBUVITQ0FBoampKbGxRMDIygoGBAS17k5+iQkm+SyAQwNraGo0aNWIdpcxUVFTg4+MDbW1t2Nvb48WLFxIbm8fjwd3dHffv38fcuXOxcePGb+fZUSGRbbTkLXtyc3Mxb948tGvXDo8fP0ZERAQCAgLQokULieYQCoX47bffcPv2bYSGhqJp06YSHV8Uvi57BwUF0b3ipFRUKMl/ZGdn49y5c1K7u7s0mpqaCAsLg5KSEhwcHJCdnS3R8atVq4Zly5bh/v37MDc3x8CBA2Fra4s7d+5INAcRDVryli0cxyEwMBCGhobYtGkTFixYgLt376Jv375M8ixduhR+fn7w9vaGqakpkwyi4OHhgc+fP+PcuXOsoxApRoWS/Ed4eDgKCwtl5v7Jf2vcuDHCw8Px8OFD9O/fn8lB5L/88gsCAwNx5swZvHr1CsbGxpg8eTI+fPgg8SykcmiGUjZkZGTA3t4ebm5uaNu2LVJSUrBkyRJUqVKFSR5vb2+sWLECa9askdn30q+MjIxgZGREy96kVFQoyX8IBAKYmppKfHlIlNq2bQuBQIDIyEhMmjSJ2SxT7969cefOHaxZswaHDh2Crq4u9u/fTyVFhtAMpXTLz8/HkiVL0KZNG6SkpCAoKAihoaFo1aoVs0xXr17FyJEjMWLECMyZM4dZDlHi8/kIDg4W20MkiOyjQkn+IS8vDxERETK53P1vPXv2xO7du7F7925s2LCBWQ41NTXMmjULqamp6NOnD0aPHg1LS0vExcUxy0TKhh69KN3Cw8NhZGSENWvWYMaMGUhJSYGzszN4PB6zTI8ePYKLiws6duyI3bt3M80iSh4eHsjOzsbZs2dZRyFSigol+YezZ88iLy9PLgolAIwcORLz58/HrFmz4O/vzzRL48aNcezYMVy5cgXFxcXo2LEjPD098ebNG6a5SOlohlL6PH78GC4uLnBwcIC2tjbu3r2LVatWoVq1akxzffz4EQ4ODqhVqxYCAgKgpqbGNI8oGRgYoE2bNjh16hTrKERKUaEk/xAQEIA2bdpAV1eXdRSRWbFiBQYMGIChQ4fi+vXrrOOgU6dOSEhIwK5duxAcHAxdXV1s3rwZRUVFrKOR76BCKT0KCgqwatUqGBoaIiEhAX5+fjh79qxUvF8VFRWBz+fj1atXCAsLk/oHQlTE12Xv/Px81lGIFKJCSb4pLCxEaGio3MxOfqWkpIRDhw7BzMwMTk5OePjwIetIUFZWxrhx45CWloZBgwZh+vTp6NChA6KiolhHI39DS97SIzIyEu3atcPSpUsxYcIE3L9/Hx4eHlKxpMxxHCZPnoyLFy8iICAAenp6rCOJhYeHB3JycmjZm3wXFUryzYULF/Dp0ye5K5QAUKVKFQQFBaFWrVqwt7fH+/fvWUcCANStWxe7du1CYmIiateuje7du8PDwwNPnz5lHY38D81QsvX8+XPw+Xz06tULjRo1ws2bN+Hl5YXq1auzjvbN1q1bsXv3buzatQu2tras44iNvr4+2rVrR7u9yXdRoSTfCAQCaGtro02bNqyjiEXdunURERGBd+/ewdXVVaoO6TU2NkZMTMy3eyz19fWxYsUK2lHJGJ1DyU5RURG8vLygr6+Py5cvw9vbGxcvXoSRkRHraP8QHh6O6dOnY+bMmRg1ahTrOGLH5/MREhJCy97kP6hQEgBAcXExgoKC4O7uLhVLSOKira2NkJAQxMXFwdPTU6rKAo/Hw5AhQ5CamooJEyZg+fLlMDQ0REhIiFTlVDT0717yLl26hA4dOmDu3LkYOXIkUlNTMXjwYKl7b7p9+zYGDBgAR0dHrF27lnUcifDw8EBubi5Onz7NOgqRMlQoCQDg8uXLyMrKksvl7n+ztrbG0aNHceLECSxZsoR1nP+oUaMGvLy8cOfOHejo6MDZ2Rl2dnZIS0tjHU3h0D2UkvXq1SsMHjwYtra2qFmzJhITE7FlyxbUrFmTdbT/eP36NRwcHKCjo4Pjx49DWVmZdSSJ0NXVRYcOHWjZm/wHFUoC4K/d3c2bN4eZmRnrKBLB5/Oxdu1arFixAocOHWId57v09fVx5swZBAYG4sGDB2jTpg3mzJkj8cdJKjqaoRS/4uJibNmyBfr6+jh37hwOHjyIK1euoEOHDqyjfVd+fj6cnZ1RUlKC0NBQaGhosI4kUXw+H6GhocjLy2MdhUgRKpQEQqEQAQEBcHNzk7olJXGaPXs2xowZgzFjxuDChQus43wXj8eDi4sLUlJSsHDhQmzduhX6+vo4fvw4FR0JoHsoxe/q1aswNTXFtGnTMGjQIKSmpmLEiBFQUpLOX09CoRDDhw/H3bt3ERISgiZNmrCOJHEeHh7fHoJByFfS+TeWSNT169fx6tUrmX/ebHnxeDzs2LED3bt3h5ubG+7du8c60g9VrVoVixcvxoMHD2BlZYUhQ4aga9euuHnzJutoco8KpXhkZmZixIgR6Ny5M9TV1REfH49du3ahTp06rKOVasmSJfD394e3tzdMTU1Zx2FCW1sbJiYmtOxN/oEKJYFAIECDBg1gbW3NOorEqaiowM/PDy1btoSdnR1ev37NOlKpWrRoAX9/f0RGRiIrKwumpqaYMGGC1ByDJG9ohlL0SkpKsGvXLujp6SE4OBi7d+/GtWvXZOJ2m2PHjmHlypVYu3YtXF1dWcdhis/nIywsDLm5uayjEClBhVLBcRwHgUAAV1dXhbmp/N9q1KiB8PBwFBcXw8HBQSbeIHv06IFbt27By8sLx44dg66uLvbs2YOSkhLW0eQObcoRnfj4eFhaWmL8+PFwc3NDamoqxo4dKxPvPVeuXMGoUaPg6emJWbNmsY7DnIeHB/Lz8xEeHs46CpESVCgVXHJyMp48eaIQu7tL07RpU4SHhyM1NRWDBg2SiWKmqqqK6dOnIy0tDQ4ODhg3bhwsLCwQGxvLOprcoBlK0cjKysLYsWPRsWNHlJSUIDY2FgcOHED9+vVZRyuThw8fwsXFBdbW1ti1a5dC3Wv+I61atYKZmRkte5NvqFAqOIFAgDp16sDGxoZ1FOY6dOiAkydPIiwsDNOnT2cdp8waNmyIw4cPIzY2FjweD506dcKwYcPw6tUr1tHkAhXKihMKhThw4AD09PTg6+uLLVu24MaNG7CysmIdrcw+fvwIBwcH1KlTBwKBAGpqaqwjSQ0+n4/w8HDk5OSwjkKkABVKBfZ1udvJyQmqqqqs40gFOzs77NixA1u3bsWWLVtYxykXKysrxMXFYe/evYiIiICenh42bNiAwsJC1tFkFs1QVlxycjI6deqEUaNGwc7ODqmpqZg0aRJUVFRYRyuzoqIieHh44M2bNwgLC5P6DUOS5uHhgS9fviAsLIx1FCIFqFAqsJSUFKSmpir8cve/jRs3DjNnzsS0adMQHBzMOk65KCsrY/To0UhLS8OwYcMwe/ZstG/fHpGRkayjySy6h7J8Pn78iEmTJsHMzAzZ2dmIjo7G0aNH0bBhQ9bRyoXjOEyaNAmXLl2CQCCArq4u60hSp2XLlrCwsKBlbwKACqVCEwgEqF69Onr27Mk6itT5448/4ObmhoEDB+LGjRus45RbnTp1sH37diQlJaF+/fro1asX3Nzc8PjxY9bRZArdK1d2HMfh6NGj0NPTw+HDh7Fu3TokJyeja9eurKNVyObNm7Fnzx7s2bMHtra2rONILT6fj4iICHrgAqFCqcgCAgLg4OAAdXV11lGkjpKSEo4dO4b27dvD0dFRZotY+/btER0djRMnTiAuLg4GBgZYunQp8vPzWUeTCbTkXTZ37tyBjY0Nhg8fDltbWzx48AAzZsyQ2VtpQkNDMWPGDMyePRuenp6s40i1fv36oaCgAKGhoayjEMaoUCqohw8f4tatW7TcXYqqVasiODgYGhoasLe3x8ePH1lHqhAej4eBAwciNTUVU6dOxerVq2FgYICAgAAqSz9Bz/IuXXZ2NmbMmAFjY2NkZmYiMjISvr6+Mv30mFu3bmHgwIFwdnbGmjVrWMeRei1atEDHjh1p2ZtQoVRUAoEAVatWRZ8+fVhHkWpaWlqIiIjAq1ev4O7uLtMbXDQ1NbFmzRrcvXsXhoaGcHd3R+/evfHgwQPW0YiM4TgOvr6+0NfXx65du7BixQrcunULPXr0YB2tUl69egUHBwfo6enB29tbah//KG34fD5Onz6Nz58/s45CGKK/LQpKIBCgT58+0NDQYB1F6unp6SEoKAhXrlzBmDFjZH5WT1dXF+Hh4QgJCcHDhw/Rtm1bzJw5k34ZfAfNUP7XgwcP0LNnTwwcOBCWlpZ48OAB5s2bJ/O3zuTl5cHZ2RlCoRAhISH03lgO/fr1Q2FhIUJCQlhHIQxRoVRAz549Q3x8PC13l0PXrl1x6NAhHDlyBCtXrmQdp9J4PB4cHR1x7949LF26FDt37oSenh6OHj1KBepv6B7K/5ebm4t58+ahXbt2ePz4MSIiIhAQEIDmzZuzjlZpQqEQw4cPx7179xAaGirTS/YsNGvWDNbW1rTsreCoUCqggIAAqKqqwsHBgXUUmTJo0CCsWLECixcvhre3N+s4IlGlShUsWLAAqamp6Nq1K4YPH47OnTsjKSmJdTSpoeiFkuM4BAQEwMDAAJs2bcKCBQtw9+5d9O3bl3U0kVm0aBEEAgGOHz8OExMT1nFkEp/Px9mzZ2X2XnNSeVQoFVBAQAB69uyJmjVrso4icxYsWIARI0bA09MT0dHRrOOITLNmzXDy5ElERUXh8+fPMDMzw9ixY/Hu3TvW0ZhS9BnKjIwM2NnZwd3dHe3atUNKSgqWLFmCKlWqsI4mMkeOHMHq1avxxx9/wMXFhXUcmUXL3oQKpYJ58+YNYmJiaLm7gng8Hvbs2YOuXbvCxcVF7ja02NraIjk5GZs2bcLJkyehq6uLnTt3ysSzzcVBUQtlfn4+lixZgjZt2uD+/fsICgpCaGgoWrVqxTqaSMXExGD06NEYOXIkZs6cyTqOTGvSpAk6d+5My94KjAqlggkKCoKSkhKcnJxYR5FZqqqq8Pf3R5MmTWBnZ4fMzEzWkURKVVUVU6ZMQVpaGlxdXTFhwgSYmpoiJiaGdTSJU8RCGRYWBiMjI6xZswYzZsxASkoKnJ2d5e6Q94yMDLi6uqJz587YuXOn3P18LHh4eODcuXP48OED6yiEASqUCkYgEMDGxgb16tVjHUWm1apVC+Hh4cjPz4eTk5NcHhSupaWFAwcOIC4uDmpqaujatSsGDx6MFy9esI5GxODx48dwdnaGo6MjtLW1cffuXaxatQrVqlVjHU3kPnz4AAcHB9StWxf+/v5QU1NjHUkuuLu7o7i4WOYeWUtEgwqlAnn//j0uXrxIy90i0qJFC4SGhuLOnTsYMmSI3O6OtrCwwPXr17F//35ERkZCT08P69atk+kzOctKEY4NKigowKpVq2BoaIjExET4+fnh7Nmzcvvs6qKiIvTr1w9v375FWFgY6tSpwzqS3Pi67H3q1CnWUQgDVCgVSGhoKEpKSuDq6so6itwwMzODj48PAgMDMXv2bNZxxEZJSQkjR45EWloaRo4cifnz56Nt27Y4c+YM62hiJe/LoOfOnUPbtm2xdOlSTJgwAffv34eHh4fc/twcx2HixImIiYlBQEAAdHR0WEeSO3w+n5a9FRQVSgUiEAhgbW2NRo0asY4iV5ycnLBlyxZs2LABO3fuZB1HrGrVqoUtW7YgOTkZjRs3Rt++feHs7IxHjx6xjiYW8noP5fPnz+Hh4YHevXujcePGuHnzJry8vFC9enXW0cRq06ZN2Lt3L/bs2QMbGxvWceSSu7s7SkpKEBQUxDoKkTAqlAoiOzsb586dg5ubG+socmnSpEmYMmUKJk2ahPDwcNZxxK5t27aIiorCyZMnkZSUBENDQyxatAh5eXmso4mUvBXKwsJCeHl5QV9fHzExMfD29sbFixdhZGTEOprYhYSEYObMmZgzZw5GjBjBOo7catSoEbp27Uq7vRURRxSCj48PB4D7888/WUeRW8XFxZyzszOnoaHBJSUlsY4jMTk5OdyCBQs4NTU1rlmzZpyfnx8nFApZxxKJhg0bclpaWqxjiMTFixc5AwMDTklJiZs8eTL38eNH1pEkJjk5mdPQ0ODc3Ny4kpIS1nHk3o4dOzgVFRXu3bt3rKMQCaIZSgUhEAhgamqKli1bso4it5SVlXH8+HEYGBjA3t4ez549Yx1JIjQ0NLBy5Urcu3cP7du3B5/PR48ePXDv3j3W0SpNHmYoX716hcGDB8PW1ha1a9dGUlIStmzZojAPNnj16hUcHR2hr6+Po0ePQkmJfu2Jm5ubG4RCIS17Kxj6m6UA8vPzERERQbu7JUBDQwOhoaFQU1ODvb09Pn/+zDqSxGhrayM0NBTh4eF4+vQp2rdvj2nTpuHTp0+soymk4uJibN68GXp6ejh37hwOHjyImJgYtG/fnnU0icnLy4OTkxM4jkNISAg0NDRYR1IIDRs2hI2NDS17KxgqlArg7NmzyMvLo0IpIQ0bNkRERASePn0KDw8PFBUVsY4kUXZ2drh79y5WrlyJffv2QVdXF4cOHZLJ43dk9digq1evwtTUFNOnT8fgwYORmpqKESNGKNTsnFAoxNChQ5GSkoLQ0FA0btyYdSSFwufzceHCBYV/fKsiUZx3FwUmEAhgZGQkt+fKSSNDQ0MEBAQgKioK48ePl/ll0/JSV1fH3Llz8eDBA3Tv3h2enp6wtrbGjRs3WEcrF1k7PiczMxMjRoxA586doa6ujvj4eOzatUshz1pcuHAhAgMD4ePjA2NjY9ZxFI6bmxs4jkNgYCDrKERCqFDKucLCQoSGhtLsJAO//vor9u/fj/379+OPP/5gHYeJpk2b4sSJE7h06RLy8vJgaWmJUaNG4e3bt6yjlYms3ENZUlKCnTt3Qk9PD8HBwdi9ezeuXbsGMzMz1tGYOHz4MNasWQMvLy96zCwjWlpasLW1pWVvRcJ0SxARu4iICA4Ad+vWLdZRFNbixYs5AJyvry/rKEwVFRVx27Zt42rVqsXVrFmT27JlC1dUVMQ6VqmaNWvG1a5dm3WMUsXFxXGmpqYcAG7kyJFcZmYm60hMXbp0iVNVVeVGjRolN6cNyKo9e/ZwSkpKCv9nUlHQDKWcEwgE0NbWRtu2bVlHUVhLly7FkCFDMHz4cFy9epV1HGZUVFQwceJEpKWlgc/nY+rUqTAxMUF0dDTraD8kzTOUWVlZGDt2LDp27IiSkhLExsZi//79qF+/PutozKSnp8PNzQ1dunTBzp07Ze6WBXnj6uoKHo+HgIAA1lGIBFChlGPFxcUIDg6Gu7s7vbEyxOPxsH//fnTs2BHOzs5IT09nHYmp+vXrY+/evYiPj4eGhga6deuGAQMG4Pnz56yj/Yc0/r0RCoXYv38/9PT04Ovriy1btuDGjRuwsrJiHY2pDx8+wMHBAfXr14e/vz9UVVVZR1J49evXx6+//krL3gqCCqUci4mJwbt37+jpOFJAXV0dgYGBqFevHuzs7GjnI/56DvrVq1dx6NAhXLx4EXp6eli9ejUKCgpYR/tG2mYok5OT0alTJ4wePRp2dnZITU3FpEmToKKiwjoaU0VFRejXrx/evXuHsLAw1K5dm3Uk8j98Ph+XLl3CmzdvWEchYkaFUo4JBAI0a9YM5ubmrKMQALVr10ZERAQ+ffoEFxcXfPnyhXUk5pSUlPDbb78hLS0NY8eOxZIlS2BkZCQ1j6+UlkL58eNHTJo0CWZmZsjOzkZ0dDSOHj2Khg0bso7GHMdxGD9+PGJiYhAYGAhtbW3Wkcjf0LK34qBCKaeEQiECAgLg5uYmlct2iqpVq1YIDQ1FYmIifvvtN5k841AcatasiY0bN+LWrVto2bIlHBwc4ODggIyMDKa5WP/d4TgOR48ehZ6eHg4fPox169YhOTkZXbt2ZZpLmmzcuBH79+/Hvn376N+LFKpbty569OhBy94KgAqlnLp+/TpevXpFxwVJIUtLS3h7e8PPzw8LFy5kHUeqGBoaIjIyEv7+/rhz5w6MjIwwf/585OTkMMnDcobyzp07sLGxwfDhw2Fra4sHDx5gxowZdG/g3wQHB2PWrFmYN28ehg8fzjoO+QE+n4/o6Gi8fv2adRQiRlQo5VRAQAAaNGgAa2tr1lHId7i7u8PLywtr1qzBvn37WMeRKjweD+7u7rh//z7mzp2LjRs3Ql9fH76+vhIvd0pKShIf8/Pnz5gxYwaMjY2RmZmJyMhI+Pr6okmTJhLNIe2Sk5MxaNAguLm5YeXKlazjkFK4uLhAWVkZAoGAdRQiRjxOGm4QIiLFcRxatWqF3r17Y/fu3azjkB/gOA4TJ07Enj17EBERgV69erGOJJUePXqE6dOnIzg4GDY2Nti6dSvatWsnkbF1dXXx8uVLicyQchyHkydPYvr06fj48SMWLVqE6dOnQ11dXexjy5oXL17A0tISjRo1QnR0NKpVq8Y6EvkJOzs75ObmSvUxYaRyaIZSDiUnJ+Px48e03C3leDwetmzZgt69e6Nfv364ffs260hSqVWrVggKCsKZM2fw6tUrGBsbY/Lkyfjw4YPYx5bUs68fPHiAHj16YODAgejYsSMePHiAefPmUZn8jtzcXDg5OYHH4yEkJITKpIzg8/mIiYnBy5cvWUchYkKFUg4JBALUrl0b3bp1Yx2F/ISKigpOnjwJbW1t2Nvb05ttKXr37o07d+5g7dq1OHToEHR1dbF//36xbmwS9z2Uubm5mDdvHtq1a4cnT54gIiICAQEBaN68udjGlGVCoRDDhg1DamoqQkND0ahRI9aRSBk5OztDRUWFlr3lGBVKOcNxHAQCAZydnenmfRmhqamJsLAwAICDgwOzDSiyQE1NDbNmzUJqair69OmD0aNHw9LSEnFxcWIZT1y7vDmOQ0BAAAwMDLBp0yYsXLgQd+/eRd++fcUynryYP38+AgMD4ePjgw4dOrCOQ8qhdu3a6NWrF+32lmNUKOXM/fv3kZqaSsvdMqZx48YIDw9HRkYGBgwYgOLiYtaRpFrjxo1x7NgxXLlyBcXFxejYsSNGjBgh8sOTxTFDmZ6eDjs7O7i7u6Ndu3ZISUnB4sWLUaVKFZGOI28OHTqEP/74A+vXr4ejoyPrOKQC+Hw+rly5ghcvXrCOQsSACqWcEQgEqF69Onr06ME6Cimndu3awd/fH2fOnMHkyZOl4kBtadepUyckJCRg165dCAkJga6uLjZv3oyioqJKXzu3oBjCmo2h0kAb915+Qm5B5Up+fn4+Fi9ejDZt2uD+/fsICgpCaGgoWrVqVems8u7SpUsYM2YMxowZg2nTprGOQyrIyckJqqqq8Pf3Zx2FiAHt8pYzHTp0gIGBAXx8fFhHIRW0b98+jBkzBuvXr8eMGTNYx5EZWVlZWLhwIfbs2QMDAwNs27YNv/76a7mukf4mG8fjnuJiaiaevs/D398ceQCa16kGWz0tDLZsDp0G1ct83bCwMEyePBnPnz/HrFmzsGDBAtpMUkbp6eno2LEjjI2Ncfr0abqVR8Y5Ojri/fv3uHr1KusoRMSoUMqRhw8fQltbG6dOnUK/fv1YxyGVMG/ePPzxxx84deoU3b5QTsnJyZg4cSJiY2PRr18/bNiw4aebXJ69z8P8wDuIyXgHZSUeSoQ/flv8+vUu2vWw2rUtmtX5cTH8888/MXXqVISEhKBnz57Yvn07dHV1K/yzKZr379+jY8eOUFJSwrVr1+gZ3XLg2LFjGDZsGJ4+fYpmzZqxjkNEiJa85YhAIEDVqlXpxn45sGrVKvD5fAwZMgTXr19nHUemGBsb48qVKzh69CiuXLkCfX19rFix4ofPTve98RQ9NkUj9lEWAJRaJv/+9dhHWeixKRq+N57+53sKCgqwcuVKGBoaIjExEX5+fjh79iyVyXIoLCxEv3798P79e4SHh1OZlBNOTk5QU1Oj3d5yiGYo5YilpSWaNGmCgIAA1lGICHz58gU9evRAWloarl+/TvfaVcDnz5+xYsUKbN68Gc2aNcOmTZu+nWEIANsvpmP9ubRKjzOzly4m2uoAAM6dO4eJEyd+m51cvHgxqlcv+/I4+WsX/OjRo3H06FFcuHABXbp0YR2JiJCzszPevn2L2NhY1lGICNEMpZx49uwZ4uPjaXlUjlSpUgVBQUGoWbMm7Ozs8P79e9aRZE6NGjXg5eWFO3fuQEdHBy4uLujbty9SU1Phe+OpSMokAKw/l4ZdZ2+hX79+6N27Nxo3boybN2/Cy8uLymQFrF+/HgcOHMD+/fupTMohPp+Pa9eu4enT/87uE9lFM5RyYuvWrZg5cyYyMzNRq1Yt1nGICKWnp8PKygpt2rTB2bNn6ekpFcRxHIKDgzFt2jS8zi5C41E7UcJT/v73FhfhY4w3cu9dhPBLDlTrt0StrkNR9RfjH10dXHERCgMXYf2yeRg0aJDYzrCUd0FBQXBzc8O8efOwatUq1nGIGHz+/BlaWlpYvXo1pk+fzjoOEREqlHLCxsYGGhoaiIiIYB2FiMHVq1fRvXt3eHh44OjRo1RWKiE/Px/dVwbiRbEmeErfL5Rvg9chL/Uqapg5Q6VOY+TeOY+CV+loMHA1qjQz+u5reJwQlr/Uge/YTuKML9eSkpLQpUsX2NnZ4eTJkxJ79CWRPFdXV7x69YruEZcj9LdVDrx58wYxMTG03C3HOnXqhCNHjsDb2xtLly5lHUemPf9cjJfCmj8skwUvU5F3/zJq2QxH7V89Ub1DHzQYuBoqNbTw8dKhH16X4ynh+uOPyMjMFld0ufbixQs4OjrCyMgIR44coTIp5/h8PuLi4vD48WPWUYiI0N9YORAUFAQlJSU4OzuzjkLEqH///lizZg2WL1+Ow4cPs44js47HPYWy0o9nePNSrwI8JVTv0OfbP+OpqEGzfU8UvHiA4s9vf/haZSUevK/TfWHllZubC0dHRygrKyM4OJjO6FQADg4OqFKlCh1yLkeoUMqBgIAA2NjYoF69eqyjEDGbM2cORo8ejdGjR+PChQus48iki6mZpR4NVPjmEVTrNIGS+j9LjVoj3W9f/5ESIYeLaZmiCaoghEIhhgwZgvT0dISGhqJRo0asIxEJqF69Ouzs7OjZ3nKECqWM+/DhA6KiouDm5sY6CpEAHo+HHTt24Ndff4W7uztSUlJYR5IpOQXFePo+r9TvKcl5D2XN/555qKxZ59vXS/M0K6/Sj2lUJPPmzUNISAh8fHzQvn171nGIBPH5fNy4cQN//vkn6yhEBKhQyriQkBAUFxfD1dWVdRQiIaqqqjh16hSaN28OOzs7vH79mnUkmfEkKxc/24XIFRcCyv99vB9PRe3/v17a6wE8zsqtYELFcuDAAaxbtw4bNmyAg4MD6zhEwuzt7VG1alWcOnWKdRQiAlQoZZxAIIC1tTUaN27MOgqRoBo1aiA8PBxFRUVwdHREbi4VmLIoLBb+9Ht4KmpASdF//vnXIvm1WFZ2HEV38eJFjBs3DmPHjsWUKVNYxyEMaGpqwt7enpa95QQVShmWnZ2Nc+fO0e5uBdWsWTOEhYXh/v37GDx4MEpKSlhHknpqKj9/y1PWrIOSnA//+edfl7q/Ln1XdhxFlpaWBnd3d9ja2mLbtm10DJYC4/P5SExMxMOHD1lHIZVE73oyLCIiAgUFBXT/pAIzNjaGn58fQkNDMWPGDNZxpF7Luhr4WXVR02qFovcvICz4572WhS//eqqOWoPSH4HJ+9845Pvev38PBwcHNGjQAH5+flBV/e/tBURx2NnZoVq1arTsLQeoUMowgUAAExMTtGzZknUUwpCdnR22bduGLVu2YOvWrazjSDUNdRU0r1P6kTTV9DsBnBDZN898+2dccRFy7kRCrbEeVGrUL/X1zetWg4a6ikjyypvCwkK4ubnh/fv3CAsLo6d6EWhoaMDBwYGWveUAFUoZlZ+fj4iICFruJgCA8ePHY8aMGZg6dSpCQkJYx5FqtnpapZ5Dqd5YD9X0O+Nj9BF8uHgQ2TfP4I3PfBR/ykTtbiNKvbayEg+2ulqijiwXOI7DuHHjcO3aNQQFBaF169asIxEpwefzkZycjPT0dNZRSCVQoZRRZ8+eRW5uLhVK8s26devg5uaGgQMHIiEhgXUcqdW86Gmp51ACQD2H6ahh5ozcuxfxPnIPOGExtPotRpXmbUp9XYmQg21zmp38Hi8vLxw6dAgHDhxA586dWcchUqRv377Q0NCgZW8ZR8/yllFDhw5FcnIy7t69yzoKkSL5+fmwtbXF48ePERcXhxYtWrCOJDXu3LmDmTNn4ty5c9Aduw1FdX7BT3plufDAofhFCt76LcakSZMwf/581K793/MsFVFgYCDc3d2xYMECrFixgnUcIoUGDhyI+/fv4+bNm6yjkAqiGUoZVFhYiNDQUJqdJP9RtWpVhISEoFq1arC3t8fHjx9ZR2Lu9evXGD16NDp06IBHjx4hICAAkatGQFVZtG9/airKiFw9AvPmzcOuXbvQqlUrrF+/Hl++fBHpOLImMTERgwcPRr9+/bBs2TLWcYiU4vP5uHXrFlJTU1lHIRVEhVIGRUVF4dOnT1QoyXdpaWkhIiICL1++RL9+/VBYWPpB3PIqLy8PK1euhLa2NgQCATZu3Ih79+7B1dUVzetqYJmTkUjHW+5kBP2m9bFkyRJkZGRgwIABmDt3LvT09HDs2DEIhYp3NuWLFy/g5OSEtm3b4siRI1BSol855Pv69OkDTU1NWvaWYfS3WwYJBAK0bt0abdu2ZR2FSCl9fX0EBgbi8uXLGDduHBTpzhahUIijR49CV1cXy5cvx9ixY/Hw4UNMmTIFamr/fyj5APPmmNlLVyRjzuqlh/7mzb/974YNG2LXrl24d+8eTE1NMWzYMJiamiIyMlIk48mCnJwcODo6QllZGcHBwahatSrrSESKVa1aFU5OTrTbW4ZRoZQxxcXFCAoKgru7Ox0GTEplY2ODgwcP4tChQ1i1ahXrOBJx6dIlmJubY/jw4ejYsSPu37+PDRs2/PBexom2Oljr1hbqKkql7vz+HmUlHtRVlPCHW1tMsNX+7vfo6ekhICAAV65cQbVq1dCrVy/06tULycnJ5f7ZZElJSQmGDBmC9PR0hIWFoWHDhqwjERnA5/Nx584d3L9/n3UUUgFUKGVMTEwM3r17R8vdpEyGDBmC5cuXY9GiRTh+/DjrOGKTmpoKZ2dn2NraQkVFBTExMfD39y/T0TQDzJvj/DQbWLeqCwA/LZZfv27dqi7OT7P5x8zkj3Tq1AlXrlxBYGAgnjx5AlNTUwwdOhRPnjwpw08ne+bOnYvQ0FD4+vqiXbt2rOMQGdG7d29Ur16dlr1lFO3yljETJ05ESEgInjx5QjOUpEw4joOnpydOnDiByMhIdO3alXUkkXn37h2WLVuG3bt3o0mTJlizZg369+9f4Xv10t9k43jcU1xMy8TTrDz8/c2Rh78OLbfV1cKQjs2hrVW9QmMUFRXhwIEDWLp0KT58+PBtR3idOj9/pKMs2L9/P0aPHo3NmzfTM7pJuQ0ZMgQ3b96kE0xkEUdkRklJCde4cWNuypQprKMQGVNQUMD9+uuvXO3atbkHDx6wjlNpX7584datW8fVrFmTq1GjBrd27VouPz9fpGPkfCni5q3bwdVs1Z67++Ijl/OlSKTXz87O5pYuXcppaGhwtWrV4ry8vET+M0jahQsXOBUVFe7333/nhEIh6zhEBgUHB3MAuLt377KOQsqJlrxlSFxcHF6+fEnP7iblpqamBoFAgEaNGsHOzg5v375lHalCOI6Dn58f9PX1MW/ePAwePBgZGRmYM2cOqlSpItKxNNRV0ECtCIWv0mDUuKbIH6eoqan5bUf4wIEDZX5HeGpqKtzd3WFra4stW7bQCgqpkF69eqFGjRq07C2DqFDKEIFAAC0tLXTq1Il1FCKDatWqhfDwcOTm5sLJyQn5+fmsI5XLtWvX0KlTJ/Tv3x9t2rTBnTt3sGPHDtSvX/qztStDSUlJ7DvkGzZsiJ07d+LevXswMzPDsGHDYGJignPnzol1XFHKysqCvb09GjVqBD8/P6iqqrKORGRUlSpV4OzsTLu9ZRAVShnBcRwEAgFcXV2hrKzMOg6RUS1btkRoaChu3bqFoUOHysRM2J9//on+/fvD2toaeXl5OH/+PEJDQ2FgYCD2sXk8nsSOXNLT04NAIMDVq1ehqamJ3r17o2fPnlK/I7ywsBBubm749OkTwsLCUKtWLdaRiIzj8/m4f/8+7t27xzoKKQcqlDIiOTkZjx8/pt3dpNLMzc3h4+ODgIAAzJkzh3WcH/r48SNmzZoFfX19xMTE4ODBg0hMTET37t0lloHH40m8dFtbWyMmJgaBgYF49uwZTExMMGTIEDx+/FiiOcqC4ziMHTsW169fR1BQEFq1asU6EpEDPXv2RM2aNWmWUsZQoZQRAQEBqF27Nrp168Y6CpEDzs7O2LRpE9avX49du3axjvMPRUVF2LZtG7S1tbFz507Mnz8f6enpGDFihMRn5yWx5P09PB4PLi4uuHv3Lnbv3o3z589DT08PM2fOxPv37yWe50f++OMPHD58GAcPHqRbcYjIqKurw8XFBX5+fgr1UAaZx3BDECkHfX19bvjw4axjEDkzefJkTklJiQsPD2cdhRMKhVxQUBCnq6vL8Xg8ztPTk3vx4gXTTLt27eKUlJSYZuC4v3aEL1u27NuO8HXr1jHfES4QCDgA3KJFi5jmIPIpPDycA8Ddvn2bdRRSRjRDKQNSUlLw4MEDWu4mIrdx40Y4ODiAz+czvVcvMTERtra2cHFxQfPmzZGcnIwDBw6gcePGzDIB7GYo/01TUxOLFy/Gw4cPMWjQIMybNw+6uro4evQoSkpKJJ4nISEBQ4YMQf/+/bFs2TKJj0/kX48ePVCrVi1a9pYhVChlgEAggKamJnr27Mk6CpEzysrKOHHiBPT19eHg4IDnz59LdPxnz55h2LBhMDMzQ2ZmJsLDw3Hu3Dm0b99eojl+RJKbcsqiQYMG2LFjB1JSUmBhYYHhw4fD1NQUZ8+elVjO58+fw8nJCe3atcOhQ4foeCAiFmpqanB1daVlbxlChVIGCAQCODg4iPycPUIAQENDA2FhYVBRUYG9vT0+f/4s9jGzs7OxcOFC6Orq4syZM9i1axdu374NOzs7qSooX5+4I22/0HR1deHv74/Y2FhoamqiT58+EnlGeE5ODhwdHaGqqorg4GBUrVpVrOMRxcbn85GWlobbt2+zjkLKgAqllHv48CFu3bpFy91ErBo2bIiIiAg8fvwYfD4fRUVFYhmnuLgYe/fuhY6ODtavX49p06YhIyMD48aNg4qKaA8OF4Wv5VbaCuVXVlZWiImJQVBQkNh3hJeUlGDw4MF4+PAhwsLC0KBBA5GPQcjfde/eHbVr16ZlbxlBhVLKBQQEoEqVKujTpw/rKETOGRkZISAgABcuXMCECRNEXqLOnj0LY2NjjB07Fj169EBaWhpWr16NGjVqiHQcUfo6QynN53XyeDw4Ozvj7t272LNnDy5cuAA9PT3MmDFDpDvC58yZg7CwMPj6+qJt27Yiuy4hP6Kqqgo3Nzda9pYRVCilnEAgQJ8+faCpqck6ClEA3bt3x969e7Fv3z6sW7dOJNe8e/cu+vTpgz59+qB27dqIj4+Ht7c3mjdvLpLri5O0z1D+nYqKCsaMGYP09HQsWLAAe/fuRevWrbFu3bpKPxVp37592LBhAzZt2gQ7OzsRJSbk5/h8PjIyMnDz5k3WUchPUKGUYs+fP0dcXBwtdxOJGjFiBBYuXIi5c+dWaqnp9evXGDNmDNq3b4+HDx9CIBAgOjoa5ubmIkwrXl8LpTTPUP7b1x3hGRkZGDRoEBYsWAA9PT0cOXKkQjvCL1y4gPHjx2P8+PGYNGmSGBIT8mO2traoW7cuLXvLACqUUiwgIACqqqpwcHBgHYUomOXLl2PQoEEYNmwYrl69Wq7X5uXlYeXKldDR0YG/vz82bNiAe/fuwc3NTao23JSFtG7KKYuvO8Lv3bsHCwsL/PbbbzAxMcGZM2fK/PN8Pa6se/fu2LJli8z9/0dkHy17yw4qlFJMIBB8O4uLEEni8Xg4ePAgLC0t4ezsjIyMjJ++RigU4ujRo9DT08Py5csxevRoZGRkYOrUqVBTU5NAatGTxRnKf/v7jvAaNWqgb9++6NmzJ5KSkkp93bt37+Dg4IAmTZrg5MmTUrlpiigGPp+PR48e/fTPLGGLCqWUevPmDWJiYmi5mzCjrq6OwMBA1KtXD3Z2dsjKyvrh9166dAnm5uYYPnw4LC0tkZKSgo0bN6JOnToSTCx6sjxD+W9WVla4fPkygoKC8OLFC5iammLw4MH4888///O9BQUFcHNzw+fPnxEWFoaaNWsySEzIX7p164Z69erRsreUo0IppYKDg8Hj8eDk5MQ6ClFgderUQXh4OD58+AAXFxd8+fLlH19PS0uDi4sLbG1toaKigpiYGPj7+0NbW5tRYtGSpU05ZfF1R/idO3ewZ88eREVFQV9fHzNmzPj2gYHjOIwdOxbx8fEICgrCL7/8wjg1UXQqKipwd3enZW8pR4VSSgkEAtjY2KB+/fqsoxAF17p1a4SEhCAhIQEjRoyAUCjEu3fvMHnyZBgZGSE5ORknTpzAtWvX0LlzZ9ZxRUoWjg2qiK87wjMyMrBw4cJ/7AhfsWIFjhw5goMHD8La2pp1VEIA/LXs/fjxYyQkJLCOQn6AboqRQh8+fEBUVBQ2b97MOgohAP5aLj127Bg8PDyQmZmJxMRECIVCrFixAlOmTJHbJ6bI2wzlv2loaGDRokUYO3Ysli9fjnnz5kEoFMLZ2Rn9+/dnHY+Qb7p27QotLS34+fnJ1EkRioRmKKVQSEgIiouL4erqyjoKIQD+KlRCoRB16tRBVFQUOnTogIyMDMydO1duyyQgH5tyykJLSwvDhw+HqqoqmjVrhuDgYBgbG5drRzgh4kTL3tKPCqUUCggIgLW1NRo3bsw6CiG4du0aOnXqhP79+6Njx47o378/rly5ohAHDcvTppzSPHv2DE5OTjA2NkZaWhquXbuGWrVqlXlHOCGSwOfz8fTpU8THx7OOQr6DCqWUyc7OxtmzZ+Hm5sY6ClFwf/75J/r37w9ra2vk5eXh/PnzCA8Ph7e3N3r16oV+/frhzp07rGOKlSLMUObk5MDR0RHq6uoICgpClSpV0LFjR0RHRyM4OBgvX74sdUc4IZLSpUsXNGjQgHZ7SykqlFImIiLi25EdhLDw8eNHzJ49G/r6+oiJicHBgweRmJiI7t27A/hr6enkyZNo3bo17O3t8fLlS8aJxUfeZyhLSkowcOBAPHr0CGFhYWjQoMG3r309ZeL27dvYu3fvtx3h06dPL/UIKULERVlZGf369cOpU6fk+kOerKJCKWUEAgFMTEzoqA4icUVFRdi+fTu0tbWxY8cOzJ8/H+np6RgxYgSUlZX/8b3Vq1dHWFgYhEIhHBwckJOTwyi1eMn7DOWsWbMQEREBPz8/tGnT5rvfo6Ki8u2Q+kWLFmHfvn1o3bo1/vjjj0o/I5yQ8vLw8MCzZ88QFxfHOgr5FyqUUiQ/Px8RERF0mDmRKI7jEBISgrZt22Ly5MlwcnJCeno6lixZAg0NjR++rkmTJoiIiEBGRgYGDBiA4uJiCaaWDHmeodyzZw82bdqELVu2oE+fPj/9fg0NDSxcuBAPHz7E0KFDsXDhQujq6uLw4cMVekY4IRXRuXNnNGzYkJa9pRAVSily9uxZ5ObmUqEkEpOUlIRff/0Vzs7OaNq0KZKSknDw4MEybwhr164dTp06hTNnzmDq1KlyV7zk9dig8+fPY8KECZg4cSImTpxYrtdqaWlh27ZtSElJgZWVFUaMGAFjY2OcPn1a7v49EelDy97SiwqlFAkICIChoSH09PRYRyFy7vnz5xg+fDjMzMzw5s0bhIWFITIyEh06dCj3tXr37o2dO3dix44dcnd2qjwued+/fx/9+vVDz549sWnTpgpfR0dHB35+ft92hNvZ2aFHjx5ITEwUYVpC/ovP5+PFixe4du0a6yjkb6hQSonCwkKEhITQ7CQRq5ycHCxatAi6uro4ffo0duzYgdu3b8Pe3v5beaqIMWPGYM6cOZgxYwYCAwNFmJgteVvyfvfuHRwcHNC0aVP4+vpCRaXyz7b4uiM8JCQEr169gpmZGQYNGkQ7wonYdOrUCY0aNaJlbylDhVJKREVF4dOnT1QoiViUlJRg//790NbWhpeXF6ZMmYL09HT8/vvvIikVALB69Wp4eHhg8ODBcnPDvDzNUBYUFMDV1RXZ2dkICwtDzZo1RXZtHo8HR0fHbzvCL126BD09PUybNo12hBORU1JSgoeHB/z9/eXi76a8oEIpJQQCAVq3bo127dqxjkLkzLlz52BsbIzRo0eje/fuSE1NxZo1a0RaKIC/3uSPHDkCY2NjODo6ysUMlbzMUHIch9GjR+PGjRsIDg5Gy5YtxTLO1x3h6enpWLx4MQ4cOIDWrVtj7dq1tCOciBSfz8fLly8RGxvLOgr5HyqUUqC4uBhBQUFwd3ev1LIjIX9379499O3bF71790aNGjUQFxeH48ePo0WLFmIbs0qVKggODkbNmjVhZ2eHDx8+iG0sSZCXGcrVq1fj2LFjOHToEKysrMQ+3tcd4RkZGRg6dOi32ywOHTpEO8KJSFhZWaFJkya07C1FqFBKgStXruDdu3d0mDkRiTdv3mDs2LFo164d0tPT4e/vj5iYGFhYWEhk/Hr16iEiIgKZmZlwc3NDYWGhRMYVB3mYoTx16hQWLlyIpUuXYuDAgRId++uO8Pv378PKygqenp7o0KED7Qgnlfb3ZW/6kCIdqFBKAYFAgKZNm8Lc3Jx1FCLD8vPzsWrVKmhra+PUqVNYv349UlJSmMx86+joIDg4GLGxsRg1apTMlgdZPzYoPj4ew4YNw8CBA7F48WJmObS1teHn54fr16+jTp06sLOzQ/fu3ZGQkMAsE5F9fD4fr169wtWrV1lHIaBCyZxQKERAQADc3Ny+zYYQUh5CoRDHjh2Drq4uli1bhlGjRiEjIwPTpk2Dmpoas1ydO3fGkSNHcOzYMSxbtoxZjsqQ5SXvp0+fwsnJCcbGxjh48KBU3E5jaWmJS5cuISQkBK9fv4a5ufm3Rz8SUl6WlpZo1qwZLXtLCWowjMXFxeHly5e0u5tUSHR0NCwsLDBs2DBYWFggJSUFmzZtQp06dVhHAwAMGDAAq1evxrJly3DkyBHWccpNVpe8s7Oz4eDggKpVqyIoKAhVqlRhHembv+8I37dvH6Kjo6Gvr49p06bh3bt3rOMRGULL3tKFCiVjAoEAWlpa6NSpE+soRIakpaXB1dUV3bp1g5KSEi5fvgyBQABtbW3W0f5j7ty5GDlyJEaNGoWoqCjWccpFFmcoS0pKMHDgQDx58gRhYWHQ0tJiHem7VFRUMGrUqG+P+aQd4aQi+Hw+3rx5g5iYGNZRFB4VSoY4jkNAQABcXFygrKzMOg6RAVlZWZgyZQqMjIyQlJSE48eP4/r16+jSpQvraD/E4/Gwa9cu2Nraws3NDSkpKawjlZkszlDOnDkTp0+fhp+fH4yMjFjH+SkNDQ0sWLAADx8+xPDhw7Fo0SLo6OjQjnBSJhYWFmjevDkte0sBKpQM3bx5E3/++Sctd5OfKigowIYNG6CtrY1Dhw5hxYoVePDgAQYNGiQT996qqqri1KlTaNasGezs7PD69WvWkcpE1mYod+/ejc2bN2Pr1q3o3bs36zjlUr9+fWzduhX3799Hp06dvu0Ij4iIkKlCTySLx+OBz+dDIBCguLiYdRyFJv2/ieSYQCBA7dq1YWtryzoKkVIcx+HUqVMwNDTEnDlzMHDgQGRkZGDu3LmoWrUq63jlUrNmTYSHh6OwsBBOTk7Iy8tjHemnZGmGMjIyEhMnTsSkSZMwYcIE1nEqTFtbGydPnkRcXBzq1KkDe3t72hFOSsXn85GZmYnLly+zjqLQqFAyJBAI4OTkBFVVVdZRiBS6fv06OnfuDD6fDwMDA9y+fRs7d+6U2nviyqJ58+YICwtDSkoKBg8eLPVLmrJybND9+/fh4eGBXr16YePGjazjiISFhQUuXbqE0NBQvHnzhnaEkx8yMzNDy5YtadmbMSqUjKSkpODBgwe03E3+4/HjxxgwYACsrKyQk5ODyMhIhIWFwdDQkHU0kTAxMYGvry9CQkIwc+ZM1nFKJQtL3m/fvoW9vT2aNWsGX19fkT2bXRrweDw4ODjg1q1b2L9/Py5fvgx9fX1MnTqVdoSTb2jZWzpQoWREIBBAU1MTPXv2ZB2FSIlPnz5hzpw50NfXx+XLl3HgwAEkJSWhR48erKOJnIODA7Zu3YrNmzdj27ZtrOP8kLQveRcUFMDV1RW5ubkICwtDjRo1WEcSCxUVFYwcORLp6elYunQpDh48iNatW2PNmjUycesEET8+n493797h0qVLrKMoLCqUjAQEBMDe3l6qzocjbBQVFWHHjh3Q1tbG9u3bMXfuXKSlpcHT01Oud/9PmDAB06dPx9SpUxEaGso6zndJ8wwlx3EYNWoUEhISEBwcLNZntEuLatWqYf78+Xj48CF+++03LF68GLq6ujh48KDU3z5BxMvExAStWrWiZW+GqFAy8OjRI9y8eZOWuxUcx3EIDQ1F27ZtMWnSJDg6OiItLQ1Lly6FpqYm63gS4eXlBWdnZwwYMACJiYms4/yHNM9Qrlq1Ct7e3jhy5Ag6duzIOo5E1a9fH1u2bPm2I3zkyJG0I1zBfV32DggIQFFREes4CokKJQMCgQBVqlRB3759WUchjCQnJ6N79+5wcnJC06ZNkZSUhIMHD6JJkyaso0mUkpISvL290aZNGzg4OODJkyesI/2DtM5Q+vn5YdGiRVi2bBn69+/POg4zf98RXrduXdjb2+PXX3/FjRs3WEcjDPD5fGRlZeHixYusoygkKpQMCAQC9OnTR2Fmocj/e/HiBX777TeYmpri1atXCAsLQ2RkJDp06MA6GjPVqlVDSEgIqlSpAnt7e3z69Il1pG+kcYYyLi4Ow4cPx+DBg7Fo0SLWcaSChYUFLl68iLCwMLx9+xYWFhYYMGAAHj58yDoakaAOHTpAW1ublr0ZoUIpYc+fP0dcXBwtdyuYnJwcLF68GDo6OggPD8f27dtx+/Zt2Nvbf5sFU2QNGjRAREQEXrx4gX79+knNkpW0zVA+efIETk5OMDExwf79++nPzt/weDzY29vj1q1bOHDgAGJiYmBgYIApU6bQjnAFQcvebFGhlLDAwECoqqrCwcGBdRQiASUlJThw4AB0dHSwbt06TJ48GRkZGRg/fjydP/ovBgYGCAwMRHR0NMaNGycVs4LSNEP5+fNnODo6QkNDA0FBQbSh7weUlZXh6en5bUf4oUOH0Lp1a6xevZp2hCsAPp+PDx8+4MKFC6yjKBwqlBImEAjQvXt31KpVi3UUImaRkZEwMTHBqFGjYGtriwcPHmDt2rWoWbMm62hSq1u3bjhw4AAOHjyI1atXs44jNQebFxcXY+DAgXjy5AnCwsJQv359pnlkwb93hC9duhQ6Ojq0I1zOtWvXDrq6urTszQAVSgnKzMxETEwMLXfLuXv37sHOzg69evVC9erVcf36dZw4cQItW7ZkHU0mDB06FEuXLsXChQtx4sQJplmkZcl75syZOHv27LfHcJKy+/uO8C5dumDkyJFo3749wsPDmX9QIKLH4/Hg4eGBwMBAFBYWso6jUKhQSlBQUBAAwNnZmW0QIhZv3rzBuHHj0K5dO6SlpcHf3x8xMTGwtLRkHU3mLF68GMOGDcOIESMQExPDLIc0LHnv2rULW7ZswbZt29CrVy9mOWRd69at4evri/j4eNSrVw8ODg6wtbWlHeFyiM/n4+PHjzh//jzrKAqFCqUECQQC2NjY0HKVnMnPz8fq1auho6ODkydPYv369bh37x7c3d1p00QF8Xg87Nu3D506dYKLiwtSU1OZ5QDYzVCePXsWkyZNwuTJk/H7778zySBvzM3Nv+0If/fuHSwsLNC/f3/aES5H2rZtCz09PVr2ljAqlBLy4cMHREVFwc3NjXUUIiJCoRDe3t7Q09PDkiVL4OnpiYyMDEybNg3q6uqs48k8NTU1CAQCNGjQAHZ2dnj79q3EM7Ccobx37x74fD569+6NjRs3Snx8efbvHeFXrlz5tiOcxZ8zIlpfd3sHBQWhoKCAdRyFQYVSQkJDQ1FcXAxXV1fWUYgIfF3KHjp0KMzMzJCSkoLNmzejbt26rKPJldq1ayMiIgI5OTlwdnZGfn6+RMdnNUP59u1bODg4oEWLFvD19ZXrR3Cy9Pcd4cuWLcPhw4dpR7ic4PP5+PTpEyIjI1lHURhUKCVEIBDAyspK4Z6EIm/S09Ph5uaGrl27AgCio6MREBAAHR0dxsnkV8uWLREaGoqbN29i2LBhEi13LGYov3z5AhcXF+Tn5yM0NBTVq1eX2NiKqlq1apg3bx4ePnwIT0/PbzvCDxw4QDvCZZSRkREMDAxw6tQp1lEUBhVKCcjOzsbZs2dpd7cMe//+PaZOnQpDQ0MkJCTA29sbcXFx34olES8LCwucOHECAoEA8+bNk9i4kj42iOM4jBw5EklJSQgODkaLFi0kMi75S7169bB58+ZvO8JHjRqF9u3bIywsjHaEyxha9pY8KpQSEBERgYKCArp/UgYVFBRg48aNaN26NQ4ePIjly5cjNTUVgwcP/jZ7RSTDxcUFGzduxLp167Bnzx6JjCnpJe8VK1bgxIkTOHLkCJ0OwNDfd4TXr18fjo6OsLW1RXx8POtopBw8PDzw+fNnnDt3jnUUhUC/ESVAIBDA2NgYv/zyC+sopIw4joO/vz8MDQ0xa9YsDBgwAOnp6Zg3bx6qVq3KOp7CmjJlCiZOnIgJEybg9OnTYh9Pkkvevr6+WLJkCVasWAE+ny/28cjPmZubIyoqCuHh4Xj37h0sLS1pR7gMMTIygpGREe32lhAqlGKWn5+PiIgIWu6WIXFxcejSpQs8PDygp6eH27dvY9euXWjQoAHraAqPx+Nh8+bNsLOzA5/Px61bt8Q+HiD+Gcrr16/jt99+w5AhQ7BgwQKxjkXKh8fjwc7ODrdu3cLBgwdx9epV6OvrY/LkybQjXAbw+XwEBwfjy5cvrKPIPSqUYnbu3Dnk5uZSoZQBT548waBBg9CxY8dvyyQREREwMjJiHY38jbKyMk6cOAFdXV3Y29vj+fPnYhtLEjOUjx8/hrOzM8zMzLB//346u1RKKSsrY8SIEUhLS8OKFStw5MgRtG7dGqtWraId4VLMw8Pj2z4GIl5UKMVMIBDA0NAQ+vr6rKOQH/j06RPmzp0LPT09XLx4Efv370dycjJ69uzJOhr5AU1NTYSFhUFJSQkODg7Izs4WyzjinqH8/PkzHB0doampicDAQDq/VAZUq1YNc+fO/bYjfNmyZd92hBcXF7OOR/7FwMAAbdu2pWVvCaBCKUaFhYUICQmh2UkpVVxcjJ07d0JbWxtbt27FnDlzkJ6ejpEjR9K5fzKgUaNGiIiIwJ9//gk+ny+WX+binKEsLi7GgAED8OzZM4SFhdETtGTM1x3hDx48QNeuXWlHuBTj8/kICQmR+Dm2ioYKpRhFRUXh06dPVCilDMdxCAsLQ9u2bTFx4kQ4ODh8O9hYU1OTdTxSDm3atIFAIMD58+cxYcIEkf8iF+exQdOnT8e5c+dw6tQpGBgYiPz6RDJatWoFHx8f3LhxAw0aNICjoyO6detGO8KliIeHB3JycnDmzBnWUeQaFUoxCggIQKtWrdCuXTvWUcj/3Lx5Ez169ICjoyMaN26MxMREHDp0iA6cl2E9evTAnj17sHfvXnh5eYn02uJa8t6xYwe2bduG7du3060VcsLMzAwXLlxAREQE3r9/D0tLS/D5fGRkZLCOpvD09PTQvn17WvYWMyqUYlJSUoKgoCC4u7vTTfZS4MWLFxgxYgRMTEzw8uVLhIaG4vz58zA2NmYdjYiAp6cnFixYgDlz5oj0yRjiWPI+c+YMJk+ejKlTp2LcuHEiuy5hj8fjoW/fvrh58yYOHjyI2NhYGBgY0I5wKcDn8xEaGkobqMSICqWYxMTE4O3bt7TczVhubi6WLl0KXV1dhIWFYfv27bh9+zYcHByo6MuZFStWYNCgQRg6dChiY2NFck1Rz1Deu3cP/fv3R9++fbF+/XqRXJNIn687wtPT0/+zIzw3N5d1PIXk4eGB3NxciZxfq6ioUIqJQCBA06ZNYW5uzjqKQiopKcHBgweho6ODtWvXYtKkScjIyMD48eOhqqrKOh4RAx6Ph4MHD8LCwgLOzs4iWWoU5QxlZmYmHBwc0LJlS/j4+NDGLwVQtWrVbzvCR44c+W1H+P79+2lHuITp6OjA2NiYlr3FiAqlGAiFQgQEBMDNzY0ez8dAZGQkTExMMHLkSNjY2ODBgwdYu3YtatasyToaETN1dXUEBgaiTp06sLOzQ1ZWVqWuJ6oZyi9fvsDFxQX5+fkIDQ1F9erVK3U9Ilvq1auHTZs24cGDB+jWrRtGjx6N9u3bIzQ0lHaESxCfz0dYWBjNEosJtR0xiI+Px8uXL+nZ3RKWkpICe3t79OrVC5qamrh+/Tp8fHzQsmVL1tGIBNWtWxcRERH48OEDXFxcKvWEDFHMUHIcB09PTyQnJyMkJATNmzev8LWIbGvVqhVOnDjxbUe4k5MTunXrhri4ONbRFIKHhwfy8vIQERHBOopcokIpBgKBAFpaWujcuTPrKAohMzMTv//+O9q1a4cHDx7g1KlTuHLlCiwtLVlHI4y0bt0aISEhuHHjBjw9PSs8wyiKGcrly5fDx8cHR48ehYWFRYWvQ+THv3eEd+zYkXaES0Dr1q1hampKy95iQoVSxDiOg0AggIuLC90jJWb5+flYs2YNtLW14evri3Xr1iElJQX9+vWjDTcEVlZWOHbsGHx8fLB48eIKXaOy51D6+Phg6dKlWLlyJTw8PCp0DSKf/r4j/NChQ7h27RoMDAwwadIkZGZmso4nt/h8PsLDw5GTk8M6ivzhiEglJSVxALizZ8+yjiK3SkpKOG9vb6558+aciooKN2XKFO7du3esYxEptW7dOg4Ad+DAgXK/Ni8vjwPAeXt7l/u1sbGxnLq6Ojds2DBOKBSW+/VEseTl5XFr167latSowWlqanIrVqzgcnJyWMeSO48ePeIAcL6+vqyjyB2aoRQxgUCAWrVqwdbWlnUUuRQTE4OOHTtiyJAhMDU1RUpKCjZv3oy6deuyjkak1MyZMzF27FiMHTsWkZGR5XptRZe8Hz9+DGdnZ5ibm2Pv3r00Y05+qmrVqpgzZw4ePXqE0aNHY/ny5dDR0cG+fftoR7gI/fLLLzA3N6dlbzGgQiliAoEATk5OdDSNiKWnp8PNzQ1du3aFUChEdHQ0AgICoKOjwzoakXI8Hg/bt29Hjx490K9fP9y9e7fMr63IppxPnz7BwcEB1atXR2BgINTV1cudmSiuunXrYuPGjUhNTYWtrS3GjBmDdu3aISQkhHaEiwifz0dERASys7NZR5ErVChF6P79+3jw4AEdZi5C79+/x7Rp02BkZISEhAQcO3YM8fHx6Nq1K+toRIaoqKjAz88Pv/zyC+zs7PDy5csyva68M5TFxcXo378/nj9/jvDwcNSrV6/CmYli++WXX3D8+HEkJCSgUaNGcHZ2ho2NDe0IF4F+/frhy5cvCAsLYx1FrlChFCGBQABNTU306tWLdRSZV1hYiE2bNkFbWxv79+/H0qVLkZqaiiFDhtDZnqRCqlevjrCwMAiFQjg6OpbppvzyzlBOmzYN58+fh7+/P/T19SuVlxAAMDU1xfnz53H69Gl8/PgRHTt2hIeHB9LT01lHk1ktW7aEhYUFLXuLGP1mFiGBQAB7e3tUqVKFdRSZxf1vl7yhoSFmzpz57SiN+fPno2rVqqzjERnXtGlThIeHIy0tDQMHDkRJSUmp359XWAJVrV/wLE8Z915+Qm7Bj+9l2759O7Zv346dO3eiR48eoo5OFBiPx0OfPn2QnJyMw4cP4/r16zA0NMTEiRNpR3gF8fl8nD59Gp8/f2YdRW7wOLopQyQePXqE1q1bw8/Pj44HqaD4+HjMmDEDV65cQd++feHl5QUjIyPWsYgcOn36NBwdHfH7779j69at/9g0k/4mG8fjnuJiaiaevs/D398geQCa16kGWz0tDLZsDp0G1b9dz8HBAVOmTMHGjRsl+8MQhZOfn4+tW7dizZo1KCkpwezZszF9+nRoaGiwjiYznjx5gpYtW8Lb2xuDBw9mHUcuUKEUES8vLyxevBhv376FpqYm6zgy5cmTJ5g3bx58fHzQtm1bbNiwAT179mQdi8i5PXv2YNy4cdi0aROmTp2KZ+/zMD/wDmIy3kFZiYcS4Y/fGr9+vYt2PQw3UoNbLxt069YNgYGBdP4skZisrCysWrUKO3bsQN26dbF06VJ4enpCRUWFdTSZYGVlBS0tLQQHB7OOIheoUIqIlZUVGjRogKCgINZRZManT5+wZs0abN68GbVr18bKlSvx22+/0S9kIjFz5syBl5cXZu0KRNBzNRQLuVKL5L8p84CSokJUvR+OG76b6cMkYeLPP//EwoULceLECejr6+OPP/6Ao6MjHVf1E5s2bcLcuXORmZmJmjVrso4j8+geShF4/vw5rl+/Tru7y6i4uBi7du2Cjo4Otm7ditmzZyM9PR0jR46kMkkkas2aNbAetQwnH6ugoFhYrjIJACUcwCmrIr+tKw7feCWmlISU7u87whs3bgxnZ2d07doV169fZx1NqvXr1w+FhYUIDQ1lHUUuUKEUgcDAQKiqqsLR0ZF1FKnGcRzCw8PRrl07TJgwAXZ2dkhLS8Py5ctpZocw4Zf4HM/rmlTqGl9ngdafS8PJG09FEYuQCvn7jvDPnz/DysqKdoSXolmzZrC2tqbd3iJCS94i0K1bN1StWhWnT59mHUVq3bp1CzNmzMCFCxdga2uLDRs2wNjYmHUsosCevc9Dj03RKCj+7xmTX57cxhuf+d99XcOh66He5PtHAqmrKOH8NBs0q1NNpFkJKa+SkhJ4e3tj0aJFePXqFcaOHYvFixdDS0uLdTSpsmXLFsyePRtv3rxBrVq1WMeRaTRDWUmZmZmIiYmBm5sb6yhS6eXLl/D09ISxsTGeP3+OkJAQXLhwgcokYW5+4B0U/2SJu7qpI+o6zPjHf1RqN/rh9xcLOcwPvCPqqISUm7KyMoYPH47U1FSsWrUK3t7e+L/27jw6qipdG/hTVSEjIYGQeSJJVapCoAdsPg2KwBWQ20shoOC1bem2GVtQFyaEZghECCSMXoVWcQaExl5OaK8rQhRatBGxBeRmnouEkJCJTGSoOuf7I7diQlXGquRUVZ7fWlmykso5b1hSefY++907IiIC27ZtQ2Njo9TlWQ3DY+9PP/1U6lJsHgOlmQzdYbGxsdIWYmUaGxuRlJQElUqFzz77DPv378fVq1e5UJysQm55Pc7lVfa6ZtIpOBojJ8zo8qFw7X7xvl4QcS6vEnkVPNKNrIOLiwsSEhKQn5+P5cuXIzk5GUqlEq+//jrPCAcQGBiI++67j4+9LYCB0kwffvgh7r//fnh7e0tdilXQ6/V4++23oVKpkJKSgtWrVyMvLw+rVq3i+eZkNY5e0EIh79vARmhpgij0vAF6Zwq5DO99x7WUZF28vLywd+9eZGdn44EHHsCKFSswceJEnDhxYtifEb5o0SKcOnUKNTU1Updi0xgozVBTU4Mvv/yS3d3/Jy0tDXfddReWLFmC+++/H1lZWdi5cye3YyCrcya7ok8d3VX/8xKuvbgI2t3zcePYerSU9d7coBdEnMnh6SVknQybef/73/9GYGAgYmNjh31H+COPPAKdTsf9KM3EQGmGzz77DDqdDvPnz5e6FEllZmbioYcewqxZs+Dq6orz58/j+PHjCAsLk7o0IiMNLTpoq5t6fpFiBFzVUzDmgWXwfiQRnvc/ibabxSg/ug6tN/J7vYe2qqnHYxqJpDZp0iScPn0aJ0+e7OgIf/TRR5GTkyN1aUMuICAAU6dO5WNvMzFQmuHDDz9ETEwMAgMDpS5FEhUVFXj66acxceJEZGRk4O9//zu+/fZb3HPPPVKXRtSt4qpG9DY36RwUBe/5GzDyl7PhqrobHjEL4bd4DwAZav55qNd7iACKqtj4QNZNJpPhwQcfxI8//ohDhw7h+++/R3R0NFatWoXy8nKpyxtSixYtwunTp1FdXS11KTaLgXKA6uvr8cUXXwzL7u7m5makpqZCqVTi2LFj2LlzJzIzM7Fw4UI23JDVazWxTVBfjBgdABfV3WjW/tSnNZUDvQ/RUFMoFFi8eDGys7OxY8cOHD16FEqlElu3bkVDQ4PU5Q2JRx55BHq9nqfdmYGBcoA+//xztLS0DKv1k4Ig4NixY1Cr1UhMTMRTTz2F/Px8xMXFwcnJSeryiLql1+uRk5ODTz75BEfefWfA13EYNRbQ6yC2tfT62pP/8w989913qK2tHfD9iIaSi4sL1q5di4KCAqxYsQLbt2+HSqXCwYMH7b4j3M/PD9OmTeNjbzNwY/MBeuyxx5Cbm4sff/xR6lKGxDfffIPnn38eFy9eRGxsLHbu3InIyEipyyLqQq/Xo6CgAOnp6cjIyEB6ejrS09ORlZWFlpb2EOg51hceS94EBjCbfvPjHbid/wOC4z6ATNbDeFwUod23EGJbMwDA19cXGo0GUVFR0Gg0HR/BwcGQyzmuJ+tUVFSETZs24ejRo9BoNEhNTcXcuXPt9knUq6++imeeeQbl5eXw8vKSuhybw0A5ALdv34a3tzfWr1+PjRs3Sl3OoMrLy8O6devw0Ucf4a677sLevXsxbdo0qcuiYU6v16OwsLAjMBrCY1ZWFpqb20Ocp6cnoqOjMX78eERHR3d8+Pn5YfqesyjuoTFH33TLaL/J1vIClB16Hi7hd8Hn0cQe6wv1csXnT9+NnJwcZGVldfnIzs7uqNHFxQVqtbpLyNRoNIiMjISLi4uZf0tElvHjjz9i3bp1SEtLw7333ovdu3cjJiZG6rIsrry8HAEBATh48CCWLl0qdTk2h4FyAE6cOIHY2FhkZmZCozF9BJutq66uRnJyMg4cOABfX1+kpKTgd7/7HWdTaEjp9XoUFRV1BEdDeMzMzOwIZR4eHh1hsXN49Pf373YmJenTdBy5UNzt1kE3jm2AfIQjnAKjIHf1QFvlNTRcOQnIHeD/5B6MGBvcbc0KuQxP3h2KpLnRJr8uCAK0Wi0yMzONwmZFRft2QzKZDKGhoUYzmhqNBt7e3nY7Q0TW7dSpU0hISMCVK1ewYMECpKSk2N2TqgceeAAKhQKnTp2SuhSbw0A5AIsXL8YPP/yAjIwMqUuxuNbWVrzyyivYunUr2trasH79eqxZs4azJTSoBEFAYWFhl8fUhhnH27dvAwBGjRrVZabRECADAgL6HbByy+sx67+/7vbrdT98isb0s9DVlEFobYLC1QPOob+Ex32PY8TogF6vn7bmfih93PtVE9A+kMvOzjYKmvn5+dDr2xuBRo8ebRQyNRoNwsPD4eDg0O97EvWHIAg4evQoNm7ciOvXr2P58uXYsmULfH19pS7NIg4ePIhVq1ahrKyMB5b0EwNlP7W2tsLX1xerV6/Gtm3bpC7HYkRRxMcff4x169ahoKAAS5cuxdatW+3mTYKsgyAIKCoqMgqOmZmZXYLjnY+po6OjBxQce/LkWxfwr4KqPm1w3lcKuQxTwr1wZMndFrsm0P6+k5eXZxQ0s7KyUF/ffszjiBEjoFKpjIKmWq3GqFGjLFoPUXNzMw4cOIDt27dDp9MhPj4ecXFxGDlypNSlmeXmzZvw8/PDq6++iuXLl0tdjk1hoOynL774AnPmzMGlS5fwq1/9SupyLOLixYuIi4vDuXPnMGfOHOzevRsTJkyQuiyyYYIgoLi42GiNY2ZmJpqa2tcuuru7m1zjGBgYOCSPdK9VN2Hmi/9EiwW393FykCNtzTQEj3G12DV7IooiysrKjEJmZmYmSkpKOl4XEBBgclYzKCiIj8/JLNXV1dixYwf279+P0aNH44UXXsCSJUtserZ81qxZEEURaWlpUpdiUxgo+2n58uX48ssvkZeXZ/NvxFqtFuvXr8exY8cwceJE7NmzB7Nnz5a6LLIhhvWAptY4Nja2b+zt7u7eERo7h0drCDPHL2rxl4+uWux6OxdMxGOTQyx2PXPU19ebbArKyclBa2srAMDNzc1k0FQqlXB2dpb4JyBbUlRUhMTERLz33ntQq9VITU3FvHnzJP83PhBvvPEGVq5cibKyMvj4+Ehdjs1goOwHvV4Pf39//PGPf8SuXbukLmfA6urqkJKSghdffBGjR4/Gtm3b8NRTT0GhUEhdGlkpQRBw7dq1LsHRMONoCI4jR47sEhgNfw4ODrbqXyoHzuRizynzj5tbO1uNVTOUFqhocBkanTrPZhr+azglRC6XIywsrEvINDQIcTsV6smlS5ewbt06nD59GlOmTMHu3bsxZcoUqcvql8rKSvj5+eHAgQNYuXKl1OXYDAbKfjh79ixmzJiB8+fP2+TxgjqdDm+++SY2b96MhoYGxMfHIyEhwebXvJDliKIIrVZrco2j4cQMNzc3o8fU48ePR0hIiFUHx54cv6jFlk/ToRPEfq2pVMhlcJDLsHVutNXMTJqjsrLS5DrNwsJCCEL70oCxY8eanNUcN24cB6XU4c6O8B07dkCtVktdVp/Nnj0bOp0OX331ldSl2AwGyn549tln8dFHH0Gr1drU9jmiKOLzzz/H2rVrkZmZicWLFyM5ORlBQUFSl0YSEUWxY8axc3jMyMgwCo53hkd73Yz7WnUTNnx8FefyKqGQy3oMloavT1WOxY75E4dszaRUmpubkZeXZ3KrI8OaWCcnp46moM7bHUVGRnLQOkwZOsI3bdqE0tJSm+oIf/PNN7FixQqUlpbCz89P6nJsAgNlHwmCgJCQECxYsAAvv/yy1OX02ZUrVxAfH4+0tDRMnz4de/fuxaRJk6Qui4aIKIooKSkxao7JyMjo6A52dXU1ucYxJCTELoNjb3LL63H0ghZnciqgrWpC5zdIGYAQL1fMiPTB7+8JGdDWQPZEEASUlpaanNW8fv16x+uCg4NNzmr2tFco2Y/OHeFtbW1Yu3at1XeEV1VVwdfXFy+//DKefvppqcuxCQyUffTdd98hJiYGZ8+etYmTYq5fv47ExES88847UKlU2L17Nx5++GG+edspURRRWlpq1ByTkZGBuro6AO3BMSoqymiNY2ho6LAMjn3R2KJDUVUjWnUCHB3kGOflBjcn2+1eHUp1dXUmg2Zubm7HudDu7u5GazQ1Gg0iIiLg6Ogo8U9AllZdXY2UlBS8/PLLGD16NJKSkrBkyRKMGDFC6tJMmjNnDpqbm3H27FmpS7EJDJR9tHbtWhw6dAhlZWVWvU6osbERe/bswa5du+Di4oKkpCSsWLHCav/BUv+Ioojr168bNcd0Do4uLi5dgqMhPI4bN47BkSTX1taGwsJCo22OsrKyUFtbCwBQKBSIiIgwOas5evRoaX8AMltxcXFHR3hkZCRSUlIQGxtrdRMeb7/9NpYuXYrS0lL4+/tLXY7VY6DsA1EUERERgZkzZ+L111+XuhyT9Ho9Dh8+jE2bNqGyshLPPfccNmzYAE9PT6lLowEwBMc7m2MyMjJw69YtAD8HxzvXODI4ki0SRREVFRUmZzWLi4th+FXl4+NjNKOp0WiG7RINW2btHeHV1dXw9fXFiy++iNWrV0tdjtVjoOyDS5cuYdKkSTh58iQefPBBqcsx8tVXXyEuLg6XL1/GY489hpSUFISFhUldFvWBYWNqU80xhtkaZ2fnjhnHzuGRXbU0XDQ1NSE3N7fLbGZWVhays7M7znR3dnaGWq02mtGMjIyEq6t9N03Zus4d4fPnz0dKSorVdIT/9re/RUNDA77+uvujWqkdA2UfJCYm4sCBAygvL7eqdT1ZWVlYu3Yt/vGPfyAmJgb79u2zye2MhgNRFHHjxg2j5pj09PQuwVGj0RitcQwLC2NwJDLBsLG+qVnN8vJyAIBMJkNoaKjJx+c+Pj5W95h1uBIEAceOHcPGjRtRWlqKZcuWYcuWLZJ3WL/77rv405/+hJKSEgQEBEhai7VjoOyD8ePHY/LkyTh06JDUpQBoP2s0KSkJBw8eREhICHbu3IlHH32Ub4xWQBRFlJeXm1zjWFNTA6B9e5XOwdEQHsPDwxkciSykpqbGZNDMz8+HXq8HAHh6ehqFzKioKISFhXHduUSam5vx17/+FcnJyWhra0N8fDzi4+Ml6wivqamBr68v9u7di2eeeUaSGmwFA2UvMjMzMX78eJw4cQJz586VtJbm5ma89NJL2LFjB2QyGTZt2oRnnnkGTk5OktY1HBnWe5kKjobTRhwdHY2CY3R0NIMjkYRaW1uRn59v8vxzw1ZaI0aMgFKpNAqbarUaHh4eEv8Ew4OhI3z//v3w9PSUtCP8oYcewq1bt3Du3Lkhv7ctYaDsRXJyMlJTU1FZWSnZ2baiKOL48eNYv349SktL8ec//xmbN2/G2LFjJalnOOkcHO9skDEVHDuvcQwPD4eDA7eYIbIFhvXMpmY1r1271vE6f39/k0dSWsPZ9Paoc0e4SqVCamrqkHeEHz58GH/4wx9QUlKCwMDAIbuvrWGg7MWvf/1rREZG4v3335fk/t9++y2ef/55fP/995g3bx527dqFyMhISWqxd51nHDuHx6qqKgDtwVGtVhutcYyIiGBwJLJjDQ0NyMnJMdrmKCcnB62trQDaT5Yy1RSkUqkkm4ywJ5cvX8a6detw6tQpTJkyBbt27cK99947JPeura2Fr68vdu3aheeee25I7mmLGCh7UFBQgIiICLz//vtYtGjRkN47Pz8ff/nLX/DBBx9g0qRJ2Lt3L6ZPnz6kNdirmzdvGj2mTk9PR2VlJYD2x12dg6MhPCqVSgZHIuqg1+tRVFRkclbT8H4ik8kQFhZmcgN3PmXqv9OnTyMhIQGXL19GbGwsUlJSoNFoBv2+c+fORVVVFb799ttBv5etYqDswZ49e5CYmIibN28O2YLgmpoaJCcnY//+/fD19cWOHTvwxBNPcH+1AaisrDS5xvHmzZsA2oNjZGSk0RrHiIgILsgnIrNUVlYiOzvb6PzzwsJCCIIAAPDy8jLZfT5u3DgOXnsgCAL+9re/YePGjSgpKRmSjvD33nsPTz75JLRaLYKDgwftPraMgbIHMTEx8PX1xSeffDLo92ptbcWrr76KrVu3oqWlBevXr8eaNWu4f1ofVFZWGq1vTE9P7wiODg4OHTOOndc4KpVKBkciGlLNzc3Iy8szOavZ2NgIoH15jUqlMtq8Xa1WW/X510PN0BG+fft2tLa2Ij4+HnFxcXB3d7f4verq6uDj44OUlBSsWbPG4te3BwyU3SgpKUFwcDAOHz6MJ598ctDuI4oiPvnkEyQkJKCgoABLlizB1q1bJd97yxpVVVWZbI6pqKgA0B4cO884GsKjSqVicCQiqyaKIkpKSkwGzevXr3e8LigoyOSsZkBAwLBtCqqpqek4I9zDwwNJSUlYunSpxd/3Y2NjUV5ejvPnz1v0uvaCgbIb+/fvx/PPP4+KiopBOzv2hx9+QFxcHL7++ms8+OCD2LNnDyZMmDAo97Il1dXVJptjDBsVOzg4QKVSGa1xVKlUVrXxPBGRJdTV1SE7O9soaObm5qKtrQ0A4O7ubjJoKpXKYfO+qNVqkZiYiCNHjkClUiElJQXz58+3WNA+duwYnnjiCRQVFSE0NNQi17QnDJTdmD59OpydnXHy5EmLX1ur1WLDhg04evQoJkyYgD179ljlkY6DraamxuQaxxs3bgAAFAqFUXA0zDgOlzdIIqLutLW1obCw0OSemoYTuBQKBcLDw02GzTFjxkj7AwySK1euYN26dfjiiy8QExOD3bt3W6QjvL6+Ht7e3ti+fTvi4uIsUKl9YaA0oaKiAv7+/njttdewbNkyi123vr4eqamp2LdvHzw8PLBt2zY89dRTdr/4ura21mRwLCsrA/BzcOy8vjE6OhqRkZEMjkRE/SSKIm7evGkUMrOyslBcXAzDr30fHx+TQTMkJMQuDl9IS0tDQkICLl26ZLGO8AULFqC0tBQXLlywUJX2g4HShDfeeAMrV67EjRs34O3tbfb1dDod3nrrLWzevBn19fWIi4tDQkLCoCwclpIhON65xrFzcFQqlUbNMZGRkTzth4hoCDQ1NSE3N9doVjM7Oxu3b98GADg7OyMyMtJoA/fIyEibaxS9syN86dKl2LJlC/z9/Qd0vePHj+Pxxx9HYWEhvP2DUFTViFadAEcHOcZ5ucHNyb4niHrCQGnCnDlz0NLSgjNnzph1HVEUcfLkScTHxyMjIwOLFy/G9u3bERQUZKFKpXHr1i2TaxwNC8flcnlHcOwcHtVqNYMjEZEVEgQB165d6zKbafgwrF8HgNDQUJOzmr6+vlbdFNTc3IxXXnkFycnJaGlp6TgjvL8TO1cKyzHrz1vhd9dM1AuO6BygZABCxrhihtoHT9wdApWvfU0a9WbYB8rGFl2XEYanog3jgvyxb98+sw6C/+mnnxAfH4/Tp09j+vTp2Lt3LyZNmmTBygffrVu3ugRGw59LS0sBtAfHiIgIo+YYtVrNkyGIiOxETU2NyaagvLw86PV6AICHh4fJzdvDw8OtapeNmpoapKam4qWXXoKHhwe2bNmCZcuW9VrjteombPj4Ks7lVQKiAMi63xtaIZdBL4iYqhyLHfMnIniMbc3qDtSwDJS55fU4ekGLM9kV0FY3oetfgIi2mjI8Pu0XWPEf4/s9wigrK0NiYiLeeecdKJVK7N69Gw8//LBVj9zq6uqMHlNnZGSgpKQEwM/B8c41jgyORETDV2trK/Lz801udVRXVwegfVcOpVJpclbTw8NDstq1Wi02b96Mw4cPQ6lUIiUlBQsWLDD5u/r4RS22fJoOnSBCL/Q9MinkMjjIZXhhbjT+a3KIJcu3SsMqUHYeYRhGEN3p7wijsbERe/fuxa5du+Ds7IykpCSsWLHCqkZmdXV1yMzMNAqO165dA9B+RJhhxrFzeFSr1XBxcZG4eiIisgWiKOLGjRsmg6ZWq+14nZ+fn9Hm7RqNBkFBQUN2OtydHeG7du3Cfffd1/H1A2dysedUjtn3iZ8didUzVGZfx5oNm0A5WCMMQRBw5MgRbNiwAZWVlXj22WexceNGeHp6WrD6/qmvr0dGRobRrGPn4BgeHm60xlGj0TA4EhHRoGloaEBOTo5R0MzJyUFLSwsAwNXVFWq12ihoqlSqQfsd1bkjfN68eUhNTcXlelf85aOrFrvHzgUT8Zgdz1QOi0A5WCOMM2fOIC4uDpcuXcKiRYuQmpqKsLAws+/TVw0NDR2hsXN4NIwAZTIZwsLCjNY4ajQam+vUIyIi+6XX61FcXGy0zVFWVhYqKysB/Pw7zdTj87Fjx5q9tEwQBBw/fhwbNmxAWX0rApe9BkHW/fZJLTfycOubY2gpyYCoa4ODpy9G/moORv1mrsnXOznIkbZmmt2uqbT7QHn8otbiI4xfujchISEBn332Ge655x7s27cPMTExFrvHnRoaGro8qjaEx+LiYgA//yO7c40jgyMREdm6yspKk01BBQUFEAQBADBmzBiTQTMsLKzfez23tLRg5vYT0LY4QyY3HShvF/6Iig+2wtE3Am6aqZA5OkNXewMQBYye8SeT36OQyzAl3AtHltzdv78AG2HXgfJadRNmvvhPtOiEXl9761/vo/brIxgxNgQBS1/p9nVyUY/SN1Yi0MMZqampWLhwocUabhobG02ucSwqKup4jWHGsXN41Gg0cHNzs0gNREREtqClpQV5eXlG2xxlZWWhsbERAODo6AiVSmUUNNVqdbdbBuWW12PWf3/d7X2FliaUvr4cToFR8J6/HrIeOr5NSVtzP5Q+9relkF3vwLnh46vQ9WG9pK6uErfO/x2yEb13LOtF4P+tehFpG2MHvKdiY2MjsrKyjE6P6Rwcx40bh+joaCxatKgjPEZFRTE4EhERAXBycuqYWOlMFEWUlpYahcx33323Y9s7AAgMDDQKmlFRUXjv3zU9Nu42ZpyF0FiL0fcvhkwmh9DaDNkIxz4FS4Vchve+0yJpbnSvr7U1dhsoc8vr2/eL6oOaM2/BKUANURAg3K7r8bUyuQLX2kbi2q1WKH16DpRNTU3IzMw0ao4pKirqOPoqNDQU0dHRWLhwYcfMY1RUFEaOHNm3H5SIiIg6yGQyBAUFISgoCDNnzuzytbq6OqPH52fOnMHrr7+OtrY2AEDQyjeh8PTr9vrNRZchc3KFrqEKFR8lQ1ddCtkIZ7hNmIExDyyDzKH7I4P1gogzORVIAgOlzTh6Qdvr1kAA0Kz9XzRlfQv/p15G9enX+nTtO0cYTU1NXWYcDQGysLCwS3AcP348HnnkkY4RFYMjERHR0Bk1ahQmT56MyZMnd/m8TqdDYWEhLqdnYe2FnpextVVfBwQ9bn64DSN/MRvO0/6AZu1V1P/7MwjNjfCel9Dj92urmtDYorO7Yxrt66fp5Ex2Ra9hUhT0qD79Gkb+cjYcfcb1+dp6QcQH5zNx6a0NSE9PR0FBQUdwDAkJQXR0NObPn98lONrbud1ERET2wsHBASqVCq1uPsCFb3p8rdjWDLGtBSN//Z8YM2sFAMBVPQWivg0Nl0+ibeoTGDEmsPvvB1BU1YjoAOk2dh8MdhkoG1p00FY39f66S59DV3cTvo9v7/c96kVnNOtExMbGdqxxHD9+PIMjERGRjWrtQxOv4ZG2W9S0Lp93Gz8dDZdPoqU0q8dA2df72Bq7DJTFVY3orRVHf7sOteeOwnPKY1C49n+UIJPJsO+NI3Y3wiAiIhquHB360Fgz0gttlVoo3Dy7ft6tPQ8IzQ0WuY+tsb+fCH1L/rVfH4HcZSTcf/PwoN6HiIiIbMM4Lzf0thGgo18EAEBXX9Xl87r6agDodZJK9n/3sTd2GSh7S/5t1aVouPwF3O+aC319NXS15dDVlkPUt0EU9NDVlkN/u97s+xAREZHtcHNyQEgvJ9m4aaYCABp+OtXl8w0/nQLkCjiFTOzx+0O8XO2uIQew00fehhFGd4+99fVVgCigJu0gatIOGn299LUlcP/NXIyZubzbe9jrCIOIiGg4m6H2wZELxd029jr6RcDtF7PQ+NNp3BQEOIdMQLP2KpqyvsGomIVwcPfq9toKuQwzIn0Gq3RJ2WWgNIwwirtpzBnhHQrvBRuNPl/79REIrbcxZuZyOHj693gPex1hEBERDWdP3B2Cd88X9fgarwdXwWGUNxp+SkNTznk4eHhj9APLMGryvB6/Ty+I+P09IRas1nrYbSLqaYShcPWAa6Tx2dt1F08AgMmvdfl+Ox5hEBERDWcqX3dMVY7Fvwqqup2llCkc4Hnf7+B53+/6fF3DWd72eOwiYKdrKIH2EUZv+1AOlD2PMIiIiIa7HfMnwkHeW3tO/zjIZdgxv+f1lbbMbgOlYYSh6Mf/EH5PpCJg6Ss9vkYhl2GqcqzdjjCIiIiGu+AxrnjBwudtb50bjeBeGn5smd0GSoAjDCIiIhqY/5ocgvjZkRa51trZajw22b6fbNp1oOQIg4iIiAZq9QwVUhdMhJODvF9PPIH2J5pODnLsXDARq2YoB6lC6yETDYdQ27EDZ3Kx51SO2ddZO1s9LP6nICIiop9dq27Cho+v4lxeJRRyWY89GoavT1WOxY75E4fNJNSwCJQAcPyiFls+TYdOEPvVrKOQy+Agl2Hr3Gi7n64mIiKi7uWW1+PoBS3O5FRAW9XUZb9rGdq3FJwR6YPf3xMy7Hothk2gBDjCICIiIstobNGhqKoRrToBjg5yjPNyG9b7Uw+rQGnAEQYRERGR5QzLQNkZRxhERERE5hn2gZKIiIiIzGPX2wYRERER0eBjoCQiIiIiszBQEhEREZFZGCiJiIiIyCwMlERERERkFgZKIiIiIjILAyURERERmYWBkoiIiIjMwkBJRERERGZhoCQiIiIiszBQEhEREZFZGCiJiIiIyCwMlERERERkFgZKIiIiIjILAyURERERmYWBkoiIiIjMwkBJRERERGZhoCQiIiIiszBQEhEREZFZGCiJiIiIyCwMlERERERkFgZKIiIiIjILAyURERERmYWBkoiIiIjMwkBJRERERGZhoCQiIiIiszBQEhEREZFZGCiJiIiIyCwMlERERERkFgZKIiIiIjILAyURERERmYWBkoiIiIjMwkBJRERERGZhoCQiIiIiszBQEhEREZFZGCiJiIiIyCwMlERERERklv8Po8Ns/8tLXuwAAAAASUVORK5CYII=", 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" ] @@ -131,85 +119,58 @@ }, { "cell_type": "markdown", - "id": "abd17e36-857b-4101-9188-1be70206177e", + "id": "17ea14ec-dbb7-487c-b4f1-cabc8d5e3c29", "metadata": { "tags": [] }, "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):" + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the QAOA algorithm [[1](#QAOA)], with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`." ] }, { "cell_type": "code", "execution_count": 3, - "id": "4233341d-139c-493b-b4af-210f71e3354a", + "id": "816b468f-a59f-4f2f-8337-4a9d66548425", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:21.352378Z", - "iopub.status.busy": "2024-05-07T15:48:21.350949Z", - "iopub.status.idle": "2024-05-07T15:48:23.150678Z", - "shell.execute_reply": "2024-05-07T15:48:23.150039Z" - }, "tags": [] }, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "qaoa_config = QAOAConfig(num_layers=20)" - ] - }, - { - "cell_type": "markdown", - "id": "e8e4f132-55d7-4a46-846c-b4d4b5edac57", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" + "combi = CombinatorialProblem(pyo_model=max_clique_model, num_layers=20)\n", + "\n", + "qmod = combi.get_model()" ] }, { "cell_type": "code", "execution_count": 4, - "id": "7384872d-a28f-49e3-918d-a5749c70d873", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:23.153812Z", - "iopub.status.busy": "2024-05-07T15:48:23.153151Z", - "iopub.status.idle": "2024-05-07T15:48:23.157294Z", - "shell.execute_reply": "2024-05-07T15:48:23.156687Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, + "id": "62ec28b3-cb49-411a-8c4a-8004fff6c105", + "metadata": {}, "outputs": [], "source": [ - "optimizer_config = OptimizerConfig(max_iteration=1, alpha_cvar=1)" + "write_qmod(qmod, \"max_clique\")" ] }, { "cell_type": "markdown", - "id": "01c3df80-5e78-4cf6-9429-4ef0eaafed78", + "id": "943291f0-6a9f-4286-a69d-ef13a0a12ef6", "metadata": {}, "source": [ - "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:" + "## Synthesizing the QAOA Circuit and Solving the Problem\n", + "\n", + "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" ] }, { "cell_type": "code", - "execution_count": 5, - "id": "3f848bc5-1ded-440a-b426-2f40e21949aa", + "execution_count": null, + "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:23.160101Z", - "iopub.status.busy": "2024-05-07T15:48:23.159651Z", - "iopub.status.idle": "2024-05-07T15:48:23.462012Z", - "shell.execute_reply": "2024-05-07T15:48:23.461349Z" - }, "pycharm": { "name": "#%%\n" }, @@ -217,16 +178,13 @@ }, "outputs": [], "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=max_clique_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" + "qprog = combi.get_qprog()\n", + "show(qprog)" ] }, { "cell_type": "markdown", - "id": "4e28c1f5-d1df-4600-a364-0ef54dab8209", + "id": "b119464b-9d46-4ea0-ba4a-1734f3e0e3e5", "metadata": {}, "source": [ "We also set the quantum backend we want to execute on:" @@ -235,139 +193,68 @@ { "cell_type": "code", "execution_count": 6, - "id": "794a44cd-6d2a-47b1-9e71-fb2d05a8442b", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:23.465067Z", - "iopub.status.busy": "2024-05-07T15:48:23.464641Z", - "iopub.status.idle": "2024-05-07T15:48:23.482772Z", - "shell.execute_reply": "2024-05-07T15:48:23.482176Z" - }, - "tags": [] - }, + "id": "7d188c69-21d1-4afe-86b1-46229e91a01e", + "metadata": {}, "outputs": [], "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", + "from classiq.execution import *\n", "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", + "execution_preferences = ExecutionPreferences(\n", + " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\"),\n", ")" ] }, - { - "cell_type": "code", - "execution_count": 7, - "id": "1acdcc28-3101-4a80-9b36-87cd5780abbb", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:23.485247Z", - "iopub.status.busy": "2024-05-07T15:48:23.484855Z", - "iopub.status.idle": "2024-05-07T15:48:23.511694Z", - "shell.execute_reply": "2024-05-07T15:48:23.511113Z" - } - }, - "outputs": [], - "source": [ - "write_qmod(qmod, \"max_clique\")" - ] - }, { "cell_type": "markdown", - "id": "6e3057bc-33bc-4a2c-818e-b967598c2141", + "id": "07621d7c-0e54-4adb-9c47-8fd99a346e29", "metadata": {}, "source": [ - "## Synthesizing the QAOA Circuit and Solving the Problem\n", - "\n", - "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" + "We now solve the problem by calling the `optimize` method of the `CombinatorialProblem` object. For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`maxiter`) and the $\\alpha$-parameter (`quantile`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[2](#cvar)]:" ] }, { "cell_type": "code", - "execution_count": 8, - "id": "ad8e435d-4482-4d5f-ad53-886581d4fea0", + "execution_count": 7, + "id": "62d12d20-1c80-4a9e-bb6b-b1fddc6cbe40", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:23.514439Z", - "iopub.status.busy": "2024-05-07T15:48:23.513955Z", - "iopub.status.idle": "2024-05-07T15:48:49.929603Z", - "shell.execute_reply": "2024-05-07T15:48:49.928841Z" - }, - "pycharm": { - "name": "#%%\n" - }, "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Opening: https://platform.classiq.io/circuit/88ddbcbe-e798-4683-b7be-3052b1efec1a?version=0.41.0.dev39%2B79c8fd0855\n" - ] - } - ], + "outputs": [], "source": [ - "qprog = synthesize(qmod)\n", - "show(qprog)" + "optimized_params = combi.optimize(execution_preferences, maxiter=1, quantile=1)" ] }, { "cell_type": "markdown", - "id": "1f78ae22-4ab8-4890-ad74-227dedcbde75", - "metadata": {}, - "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "27afef0a-52a4-4930-8a3a-f509bd5956bd", + "id": "615ed612-b835-4bf0-aa92-92d30ef8006d", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:49.934524Z", - "iopub.status.busy": "2024-05-07T15:48:49.933310Z", - "iopub.status.idle": "2024-05-07T15:48:56.641053Z", - "shell.execute_reply": "2024-05-07T15:48:56.640136Z" - }, "tags": [] }, - "outputs": [], "source": [ - "result = execute(qprog).result_value()" + "# Optimization Results" ] }, { "cell_type": "markdown", - "id": "f4f0b68a-e56f-4d11-b9f8-fe3b9bdab697", - "metadata": { - "tags": [] - }, + "id": "2510a439-9181-4e39-a033-0bd53e8f87f6", + "metadata": {}, "source": [ - "# Optimization Results" + "We can also examine the statistics of the algorithm. The optimization is always defined as a minimzation problem, so the positive maximization objective was tranlated to a negative minimization one by the pyomo to qmod translator." ] }, { "cell_type": "markdown", - "id": "bdacb755-5cdc-45c2-95d5-037efe20f9d6", + "id": "e06ae35f-7aac-4631-9fe9-4f46a36c8cea", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm:" + "In order to get samples with the optimized parameters, we call the `get_results` method:" ] }, { "cell_type": "code", - "execution_count": 10, - "id": "0134df1a-8894-4a1f-b6da-dc1883a49599", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:56.653630Z", - "iopub.status.busy": "2024-05-07T15:48:56.645232Z", - "iopub.status.idle": "2024-05-07T15:48:56.764591Z", - "shell.execute_reply": "2024-05-07T15:48:56.763847Z" - }, - "tags": [] - }, + "execution_count": 8, + "id": "9638f749-a60b-4176-a4ea-50d7c2bb986f", + "metadata": {}, "outputs": [ { "data": { @@ -390,105 +277,76 @@ " \n", " \n", " \n", + " solution\n", " probability\n", " cost\n", - " solution\n", - " count\n", " \n", " \n", " \n", " \n", - " 115\n", - " 0.001\n", - " 4.0\n", - " [0, 1, 1, 1, 0, 1, 0]\n", - " 1\n", + " 99\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'...\n", + " 0.000977\n", + " -4.0\n", " \n", " \n", - " 90\n", - " 0.003\n", - " 4.0\n", - " [1, 1, 1, 1, 0, 0, 0]\n", - " 3\n", + " 102\n", + " {'x_0': 1, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'...\n", + " 0.000977\n", + " -4.0\n", " \n", " \n", - " 107\n", - " 0.001\n", - " 3.0\n", - " [0, 1, 0, 0, 0, 1, 1]\n", - " 1\n", + " 17\n", + " {'x_0': 1, 'x_1': 0, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.015137\n", + " -3.0\n", " \n", " \n", - " 111\n", - " 0.001\n", - " 3.0\n", - " [1, 0, 0, 1, 1, 0, 0]\n", - " 1\n", + " 26\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'...\n", + " 0.012695\n", + " -3.0\n", " \n", " \n", - " 89\n", - " 0.003\n", - " 3.0\n", - " [0, 1, 1, 0, 0, 1, 0]\n", - " 3\n", + " 27\n", + " {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.012695\n", + " -3.0\n", " \n", " \n", "\n", "" ], "text/plain": [ - " probability cost solution count\n", - "115 0.001 4.0 [0, 1, 1, 1, 0, 1, 0] 1\n", - "90 0.003 4.0 [1, 1, 1, 1, 0, 0, 0] 3\n", - "107 0.001 3.0 [0, 1, 0, 0, 0, 1, 1] 1\n", - "111 0.001 3.0 [1, 0, 0, 1, 1, 0, 0] 1\n", - "89 0.003 3.0 [0, 1, 1, 0, 0, 1, 0] 3" + " solution probability cost\n", + "99 {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'... 0.000977 -4.0\n", + "102 {'x_0': 1, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'... 0.000977 -4.0\n", + "17 {'x_0': 1, 'x_1': 0, 'x_2': 0, 'x_3': 1, 'x_4'... 0.015137 -3.0\n", + "26 {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'... 0.012695 -3.0\n", + "27 {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.012695 -3.0" ] }, - "execution_count": 10, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " max_clique_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=False).head(5)" - ] - }, - { - "cell_type": "markdown", - "id": "2724dafb-eb26-4756-8086-e415cecb0e78", - "metadata": {}, - "source": [ - "## Resulting Clique" + "optimization_result = combi.get_results()\n", + "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { "cell_type": "code", - "execution_count": 11, - "id": "4d99764d-8ff1-4397-9dac-c5e584862bfb", + "execution_count": 9, + "id": "9b868135-e219-441c-8d98-6b43d894a130", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:56.769629Z", - "iopub.status.busy": "2024-05-07T15:48:56.768261Z", - "iopub.status.idle": "2024-05-07T15:48:57.012646Z", - "shell.execute_reply": "2024-05-07T15:48:57.011984Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/png": 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bUAIvlxZy27MHGbt2oVl5ObR69EDiihWsYxFCFBSP45RwTIcQIlGVpaW46OwM9+RkRJubo1t8PBrq6bGOJVXHGjeGbkUF3CorWUeRusK0NGS4uKBbfj4iP/0UbidPKvwsfUKIbFEPJSHkox4lJyPVyAguycmIGDYMPW7fVvpiEnh5D6Uy91C+Tc/SEt1ycxHZqxfczp1DorExijIyWMcihCgQKigJIR907a+/IO7SBYYlJbj5559wP3BAae+XfBcHKOWknA/hq6vD49w5XF62DOb5+XhuZYUbe/awjkUIURCqcWYghNQKJxYjcsQIWH35JR41bgxeYiJsv/ySdSyZ4niq0j/5b/YLFqA0KgrFWlpo+/nniBwzhp6uQwipFhWUhJB/KX/yBNHt28PtwAHE2NqifU4ODDt3Zh1L5jgeT2UPkC179IBFTg7ibGzg9s8/iLayQml+PutYhBA5pqrHS0LIe2THxOCOiQns09IQPWkS3JOToamtzToWMzwVGvJ+VwMdHbhdv47oL79Et/R0PDA1RebZs6xjEULkFBWUhBAAwOU1a9CgRw/ovHiBe3v2oOfWrawjMSVW4R7Kt/X8809kHTmCBlVVaNanD+Lmz2cdiRAih2jZIEJUHCcWI8LHB65hYbiqp4c2sbHQs7RkHYu5w02bolVJCRyqqlhHkQvF9+/jhpMTnHJzEe7khJ7nz0NdS4t1LEKInKALcEJUWEleHmJbtYJHWBiinJzQOTeXislXVPkeyvdpamYGx6wshHt5oWdsLJKNjfE4JYV1LEKInKDjJSEq6t7p08ht3Rods7IQM2sWPGJioKapyTqW3FCldShrisfnwyMkBNfXr0fL4mKIOnXCtS1bWMcihMgBKigJUUHxP/wA3X79oC4W4+GxY3Bes4Z1JLlDBeWHdZ4+HVxiIh5pa6P9lCmIGDKElhYiRMVRQUmIChGLRAh3d4fDsmW42aIF9NLTYTFwIOtYckuVFjavLcPOndEhNxcXunWDe0AAYlq3RkleHutYhBBGqKAkREUUZ2Yi0dgYbpGRCO/TB90fPEBTMzPWseQX9VBWS6NRI3hcuoSYb79FxwcP8LBVK2SEhLCORQhhgApKQlTAbaEQTywsYJmfj8QlS+Bx+jT46uqsY8k1MRWUNeb866/IDwuDmMeDoY8PLk6fzjoSIUTGqKAkRMldnDYNJkOHolxdHcVnzqD7okWsIykMKihrru1nn8H4/n0ktWoFl40bEdGlCypKSljHIoTICBWUhCgpUXk5wu3t4fLbb7jaqhVaZmai1aefso6lMGjZoNpr3Lw5XO7cQYS/P5yvXsVNY2PkXrrEOhYhRAboeEmIEnqckoJrRkbomZiIiMGD4XLnDho3b846lmKhIe864fH5cD90CLe3boVBaSnUHRxw5ddfWccihEgZFZSEKJnUXbtQaWeHlsXFuL5+PdwDAsDj0z/12uJ4PJV+lnd9dZw0CZrXruG+ri46zZqF8AEDIBaJWMcihEgJnWUIUSJR48bBfNw4FGppQRQXh840OaLOaMi7/gysrdE5NxdRPXvC4+RJJJiaojgzk3UsQogU0PGSECXw4ulTRHboANdduxDXvj0sc3Jg1L0761iKjYa8JUJNUxMeUVFI+PFHWD18iCcWFrh18CDrWIQQCaOCkhAFl5uQgDRjYzjeuIGoMWPgduMGGujosI6l8OhJOZLVffFiPAsPR6mGBsyGD0f0pEmsIxFCJIgKSkIU2NUNG6Du6Ai98nKk79gB1127WEdSKlRQSpapmxva5OQgwcoKPbdvR6S1NcqfPGEdixAiAVRQEqKAOLEYEX5+6DhjBrKaNoVGUhJsxo9nHUupcHw+HSClQKtZM7jdvImocePQ/eZN3DU2xoPISNaxCCH1RMdLQhRMaX4+Lpqbw/3oUUR36wbb3Fx8YmPDOpZSoh5K6XHduROZ+/ahUWUltD08kLBkCetIhJB6oIKSEAVyPzwcD0xN0fnePVycOhUely5BXUuLdSylRD2U0td+xAg0vX0bt5s3R/fFixHu5oaqigrWsQghdUDHS0IUxKVly9Dk00+hJRIh+/BhuGzcyDqS0qMeSulr1qYNumdlIbxfP7hGReGqkREKbt1iHYsQUktUUBIi58QiEcL79kXXH35AuoEBmt6+jXZDh7KOpfz4fCooZYSvrg6PkyeRtHo1zIqKUG5jg+vbt7OORQipBSooCZFjT7OykGBqCo8zZxDp5oZuOTlo1qYN61gqgRY2l72u338PUVwcChs2RLtJkxAxfDg4sZh1LEJIDdDxkhA5lRESgnxzc7TPy0P8woXwiIgAX12ddSyVQj2UsmfUvTuscnMRY2cH94MHcdHcHM8fPWIdixBSDSooCZFDsbNno7mPD8Q8HgpPnIDD0qWsI6kempTDjKa2NtyvXsXFqVNhd+8ecszMcOf4cdaxCCEfQcdLQuRIVUUFwp2d4bRmDa63bIkW9+6hTf/+rGOpJnpSDnMuGzci79gx8DkOBp6eiPn+e9aRCCEfQAUlIXKiMC0NV42M4Bobi3BPTzhlZkK7RQvWsVQW3UMpHywGDkTzu3dx3dQUzr/8gnB7e1SWlrKORQh5Bx0vCZEDN/fvR6m1NVoXFSFp9Wp4hIaCx6d/nkxRD6XcaGJsDOd79xAxeDB6JCYi1cgID69eZR2LEPIWOmMRwlj0lCloNXIknmlqoiwqCl1pWE8+0LJBcoXH58M9IAA3Nm1C85IS8Lp1w9UNG1jHIoS8QgUlIYxUlJQgolMn9NyyBZcsLNA6Kwste/RgHYu8QkPe8qnTV19BPSkJ2To66DhjBsK9vWlpIULkAB0vCWHg4dWruGFiAudr1xA5fDh63rqFhnp6rGORd1APpXz6pGNH2ObmItrJCR6hoYgzNUXx/fusYxGi0qigJETGrm3ZAq5bNxiWlODWn3/Cbf9+ul9SHqmp0QFSjqlracEjJgZx8+bBOicHhRYWuC0Uso5FiMqi4yUhMsKJxYgcMQJWU6bgUePG4CUmwvbLL1nHIh9Ck3IUguPy5Xhy5gwq1NTQcuhQXPjqK9aRCFFJVFASIgNlhYWItrKC24EDiLG1RfucHBh27sw6FvkYuodSYbTq3RumDx7gctu26PHnn4js2BEvnj5lHYsQlULHS0KkLOvCBdw1NYV9ejqiv/gC7snJ0NTWZh2LVId6KBVKIwMD9EhLQ+SoUXBMSUG6sTGyY2JYxyJEZVBBSYgUXV69Gg1dXdGkogKZ+/ah519/sY5EaoqWDVI4PD4fbnv2IGPXLjQtL4dWjx649PPPrGMRohKooCRECjixGOFeXrCbMwd39fTQODUV7UeMYB2L1AYNeSusDmPGoNGNG7ijr4+uCxci/NNPIRaJWMciRKnR8ZIQCSvJy0Nsq1bwCAtDlJMTuuTkQM/SknUsUls05K3Q9Cwt0S03F5G9esHt/HkkGhujMC2NdSxClBYVlIRI0N2TJ5HXujU6ZmUhZtYseMTEQE1Tk3UsUhd8Ph0gFRxfXR0e587h8rJlMM/PR6m1NVJ372YdixClRMdLQiQkbsEC6A0YAD7H4VFwMJzXrGEdidQH9VAqDfsFC1AaFYViLS2Yjx2LyNGj6ek6hEgYFZSE1JNYJEK4uzscly/HzRYtYJCRAXNvb9axSD3x1NSgxjoEkZiWPXrAIicHcTY2cNu7FxfatUNpfj7rWIQoDSooCamHJ3fvItHYGG6RkQjv0wfdHzyATsuWrGMRSeC97J+knizl0UBHB27XryP6yy/RNSMDD0xNkXn2LOtYhCgFKigJqaPbQiGK27WDRX4+Li9dCo/Tp8FXV2cdi0jKq8dhiquqGAchktbzzz+RdeQINKuq0KxPH8TNn886EiEKjwpKQurg4rRpMBk6FOXq6nh27hzsFy5kHYlI2qseyipabkYptRsyBHrp6bhhZATHFSsQ7uQEUXk561iEKCwqKAmpBVF5OcLt7eHy22+42qoVTB88gJmHB+tYRBpeFZTUQ6m8mpqZwTErC+FeXugZF4drRkZ4fP0661iEKCQqKAmpoccpKbhmZISeiYmI8PODy507aGRgwDoWkZZXQ96iigrGQYg08fh8eISE4Pr69TB5+hRVdnZI3ryZdSxCFA4VlITUQMrOnai0s0PL4mKkbNwId6EQPD7981FmPLqHUqV0nj4dXGIiHmprw/rrrxExeDBNyCKkFuiMSEg1osaNg8WECSjU0oIoLg52U6eyjkRkgXooVY5h587okJuLC/b2cA8MRGyrVniWk8M6FiEKgQpKQj7gxdOniLS2huuuXYiztoZlTg6MundnHYvICt1DqZI0GjWCR0ICYmbNgk1WFh63aYP0oCDWsQiRe1RQEvIeuQkJSDM2huPNm4gaOxZuqalooKPDOhaRIZ7ay2XNqyorGSchLDivWYOCEydQxeOhha8vLtLIBCEfRQUlIe+4umED1B0doVdejoy//4br33+zjkRYoB5Kldemf38Y37+PpNat4fL774iws0NFSQnrWITIJSooCXmFE4sR4eeHjjNmIKtpU2gkJaHD2LGsYxFGaFIOAYDGzZvDJSMDkcOHwzk5GbeMjJCbkMA6FiFyhwpKQgCU5ufjYtu2cD96FNHdusE2Nxef2NiwjkVYelVQ0pA34fH5cNu/H7e3bYNeWRk0HB1xec0a1rEIkStUUBKVdz88HA9MTdE5MxMXp06Fx6VLUNfSYh2LMPa6h5KWjiGvdZw4EVopKcjU1YXd7NkI79cPYnqSEiEAqKAkKi7hp5+g8+mn0BKJkH3kCFw2bmQdicgLWjaIvIe+lRU65+YiytUVHqdP45KJCZ7cvcs6FiHMUUFJVJJYJEJ4nz7o9uOPuP3JJ2iWno52Q4awjkXkCPVQkg9R09SER2QkEn78EZaPH+Npu3a4uX8/61iEMEUFJVE5xffvI8HUFB5nzyLS3R322dlo2qoV61hE3lAPJalG98WLURIejucaGmg1ciSiJkxgHYkQZqigJColPSgIhRYWaJ+Xh/iFC+ERHg6+ujrrWEQOUQ8lqQlTNze0yclBQvv2cN25E5Ht26P8yRPWsQiROSooicqI+f57GPr6QsTno+jUKTgsXco6EpFjb5YNokkXpBpazZrB7cYNRI0fj+63buGusTEeREayjkWITFFBSZReVUUFwp2c4PzLL7hmagqje/fQum9f1rGIvKN1KEktue7YgfsHDqBRZSWaeHggYfFi1pEIkRkqKIlSK0xLw1UjI7jGxSHcywvO9+5Bu0UL1rGIAqCFzUldWA0bhmbp6bjVvDm6L1mCcFdXVNF9uEQFUEFJlNaNvXtRam2N1kVFSFq9Gh4hIW+KBEKq8/pZ3jTkTWqraatW6J6VhfD+/eEaHY2rRkbIv3GDdSxCpIrOrkQpRU+ejNajR+NpgwYoi4pC1++/Zx2JKBjqoST1wVdXh8eJE0j+5ReYFRWhwtYW17dtYx2LEKmhgpIolYqSEkR06oSeW7fikqUl2mZno2WPHqxjEQVEPZREErp89x1E8fEoaNgQ7b74AhECAa0cQJQSFZREaTy8ehU3jY3hfO0aIkeMQM+bN6HVrBnrWERR8XgAaNkgUn9G9vawys1FTOfOcD98GBfbtsXzR49YxyJEoqigJErh2pYt4Lp1Q/Pnz3Fryxa47dtH90uSenm9PmlVZSXjJEQZaGprw/3KFVycNg12mZnIMTPDnePHWcciRGLojEsUGicWI2L4cFhNmYKH2trgX7kC28mTWcciSoAWNifS4LJhAx4GB4PPcfjE0xMx333HOhIhEkEFJVFYZYWFiLaygvvBg4jp1AnW2dlo3qkT61hEWdCQN5ESc29vNL97F9dMTeG8di3C7e1RWVrKOhYh9UIFJVFIWRcu4F7LlrBPT0f0l1/CPSkJmtrarGMRJfJ6Ug4NeRNpaGJsDOd79xDh54ceiYlINTJC3uXLrGMRUmdUUBKFc3n1ajR0dYV2ZSUy9+1Dzz//ZB2JKCEa8ibSxuPz4S4U4uaff6J5SQn43bvj6oYNrGMRUidUUBKFwYnFCPf0hN2cObirp4fGqaloP2IE61hESdGkHCIrtl9+CfXkZGTr6KDjjBkI9/KiCxmicKigJArhWU4OYs3M4HH8OKKcndElJwd6lpasYxFl9uoeSnAc2xxEJXxiYwPb3FxEOzvDIywMcS1bovj+fdaxCKkxKiiJ3Lt78iQetm2LjtnZiP3+e3hcvAg1TU3WsYiSox5KImvqWlrwuHgRcfPnwzo3F0UWFrh95AjrWITUCBWURK7FLVgAvQEDwOc4PAoOhtPq1awjERXxZh1T6qEkMub48894cvYsXqipoaW/P6KnTGEdiZBqUUFJ5JJYJEK4mxscly/HDSMjGGRkwNzbm3UsokLoWd6EpVaffgqz7GwkWlig55YtiLSxwYunT1nHIuSDqKAkcufJ3btINDaGW1QUwvv2hcP9+9Bp2ZJ1LKJiXg95c1RQEkYa6umh561biBozBg6pqcgwMkLWhQusYxHyXlRQErly+8gRFLdrB4v8fFxetgwep069ObETIlOvJuVQDyVhicfnw3XXLtz95x80qahAI1dXXFq2rNb7eV7wBBmnonDr2GlknIrC84Inkg9LVBoVlERuXJw6FSb+/ihXV8ezc+dgv2AB60hEhalpaACgHkoiH6xHj4b2zZvIMDBA1x9+QHivXhCLRB/dJjMyAXHeo5BtYIKGBrow7+8Gq0H9YN7fDQ0NdJFtYII471HIjEyQ0W9BlBl1/RCJeF7wBHmJ1yAqK4d6Qy206GaLxvrNarRtZWkpLri6wuPyZVxo3RpdEhLQyMBAuoEJqQ49epHIGV1zc3TLyUFk//5wO3cOiUZGML948T9LqOVcSUXB6PGwTY2HCY8Pde6/f4f5AEwKcmAYdgDqoftwrYMD9PfshHGXDjL6bYiyoR5KUmeSuPp9nJKCFGNj9Lh8GRFDhsAlI4OKSSIXXt9qUV0vECGyxFdXh8fZs7iyfDnaFhSg1Noaqbt2vXk/fsEq6Dl0gfWNSwDw3mLyba/ft75xCXoOXRC/YJX0whOlRgUlqbWcK6m4ZuOIVu4O6BZ2ACYFOf/5i/T66rdb2AG0cnfANRtH5FxJ/ddnUnbuRKWdHUyePkXqxo1wP3Lk/5dqIYQxevQikWfd5s1D+YULeKKlBfNx4xA5ahRiJsyEw/K5aCCqqLaQfJc6J0YDUQUcls9FzMRvpZSaKDM6e5NakdTVb9TYsbCYMAEFDRtCFB8Pu6lTpRuckFpSez0ZjApKIqdMnJ1hmZOD2I4doRVxFc471wMAeHXc3+vtnHesQ/xCWvOX1A4VlKTGYiZ+K5Gr3+PWTnDdvRtxHTqgXXY2jOztpZSYkLrjqakBoFneRL410NGB5e6D6PQwHR9agj8PgDsAA7w86fMATPrIPjkAnVb98J9RJUI+hgpKUiPxC1bBecc6APW/+v3sZhyCPQbCLSUFDXR0JJKPEEmjIW+iKApGj4d6leiDx+Z0AJEAngBoWoP98QCoV4lQMHq8hBISVUAFJalWzpVUdFq96L1Xv8cAtASggZcHIT5eHrB++Mj+OAB9o0/Q1S+Ra7SwOVEEmZEJsE2N/+ioUScASQBEADbUcL/qnBi2qfHIjL4kgZREFVBBSar1savfqwDKAfQE8DmAQa9+vgzA6A/sj65+iSLgvxryph5KIs/yVq+HiPfxU7kOXhaVtSXi8ZG3cl2dchHVQwUl+ajqrn5/BJAP4DyA3QACADwGoAXg8Ef2S1e/RN5RDyVRBC1jw2t9T3tNqXNimMRGSGXfRPlQQUk+qiZXv+/SxMsr4upW76OrXyLP6B5KIu9K8otgVJAj1TaMC7LpMY2kRuhJOeSjanr1+whAEYBsABtffd+qmm3o6pfIszdD3irUQ8mJxeDEYohFompfc1VV///6rffAcR/+XDWvwXH/+V4sEr335x98/epz73uNV+293ubNZ169B44Dx3HAu9tw3Mv339r+3Z+/u+3rP29//vXn3nxf3etq3nuGhvCR8t8JPoC8xGsw7+cq5ZaIoqOCknxQba5+PQDceOt7E7wcBq/O66vfmj6mURred1Ks6Yn0QyfRt7+v7vV7T5bVnFSrPXG+54T70ZPqx06ib33u7fc/dFL9z0m0pifPmrwGwHv3PQDguH//nOPAe9/rt7d//Rp48/7bX3llZQCA9nv2IOHYsf9+/tXXGr1+92fv/BwA+B94j/fuz97e5n3vvf75u5/5yOv3vUdqRvzqD/fqz4decwA4Hu+/P3/1s/d+/57XACB+9VjQHL2WsvgVISorl0k7RLFRQUk+6OHl6zCv4Wd/AXAdL5enOIaXB8znNdiODyDJ2g4tivP+e4L92Gv89yTKw79PyjU5kb79GgDUavj7qrqanEBfvwZengw/dnJ9+zPve8295+uH3nv352++r+nrV9+//jshBlD1epHztz7zr68AOD7/zbbg8V5+/57X4PP/v523/vxr+9evX33+X5/90Hsfeq2mBt4HPsN763uemlrNX7/els9/s+/X7/H4/P9s87qd2rx+3/fvtvH2z6t7DR4PfHX19773+ufvfqa618DLYwizAvxUFNDfTerNqDfUknobRPFRQUk+qDZXpZ6v/gDAXwD0ATgBeIrqD7b5pq1QYfZJ/U6a7550X594qju5vj4hvj55vfrZ2z9/70n39UnprZPe29tXe9J8z8nx3RPl65NbtT+v4Qn17W2qO7FWe0Kty18oBXM1JATw8cENgQAj33pWMiHyokU3W4gh3YJW/KodQqpDBSX5oPpclX4GYC+Ak69ef4zNip/p/hwid948V54m5RA51Vi/GbL1jWEixYk5OfomaMnwliSiOFSho4HU0eur37ooffU1r5rP0dUvkVdqGhoAoFKTcojiyXLyqNFKHP4A+gB4/YTu46++7wPg/ge2EfH4yHZyl0RMogKooCQf1Fi/GXL1jT/6mZT3/KwUwIlXr6vrnczRN2E6IYeQD6GFzYkiaDF7Ro1W4jgK4Cz+/5id8+r7s/hwQanOidFi7kxJxCQqgApK8lHVXf32BaAHoBeAsXh5tasLoAzAQAAtPrJvuvol8uzNOpTUQ0nkVFFGBjKnjMU1Q/NqeylFeGdS3Ft/er7v8zw+rnVwQKue9hJOTZQVFZTko6q7+h2Kl7NhI/HySTnnAGgDmI+Xs70/hq5+iTx7PeT9eokhQuSFWCRC1LhxEFtawu7GDTywt4NITR2S+pvKARCpqUN/z04J7ZGoAiooyUe1cuuOax0cPnj1uxFAAYAq/P9SMQUAfq5mvyIeH0mG5sjcvA5VFRWSjEyIRLwe8qZJOUSe3Dp4ECm6unDdtQs3WrfGi6QkeIYIkTz7pzdLXdUXD0DynKUw7tJBQnskqoAKSlIt/T07pXL1m9usMdz27cPtZs1wbcsWCe2dEMl4MymHCkoiB4ozMxFhZweL4cOhVVmJpI0b0fPOHTTv1AkA4PDzHPzd4+XibXU9Vr/eLnbit3BYNrv+oYlKoYKSVMu4SwepXP0OuJmEa1u2gOPxYDtlCqLNzfEoOVlCrRBSP296KGnImzDEicWInjIFL9q2RdfkZER5e6N1YSHspk791+f++OMPjL8Qhj1DJuCFumaNZn6/TcTj44W6JuIXrILTtl8l+SsQFUEFJakRh5/nIGbCy/sd63v1e27kV2+ufm0nT4ZVUREiP/8c1nfvQsvODuE+PqgoKal/aELqgf/q6Tg0KYewknb0KJL09NBzyxakm5igJCEBHsHB0GjU6F+fO3HiBKZNm4YZM2Zg9JHtKIy/ghvWLyfTVDtZ59X7N6ztURh/hXomSZ1RQUlqzHn7WsTPX1mvq9851o745ko4ioqK3rynpqkJt927oZaRgSu2tnANCcEDfX0krlwp6V+BkBqjHkrCyrOcHITb26ONnx90yspwedUquNy/DyP7/864TklJwbBhw/DZZ5/hl19+AfByVMk2JQ6ZEfFI9ByOLH2T/6wpLAbwQM8I21ta48Rfu2GbEkf3TJJ64XEcHS1J7eRcSUXB6PGwTY2HiMf/6Czw1+9f6+AA/T07UdJYHc7OzrCzs8OJEyegqan5n21uHTqE8i++gN3Tp4g1MkLLQ4fQsuf7FrYgRHry0tLQol07/N2/P8adOFH9BoTUEycWI2bmTLT5/Xc0FYsR368fnA8fRgMdnfd+/tGjR3B0dISOjg6io6PRpEmTD+77ecET5CVeg6isHOoNtdCimy0a6uqgZcuWEAgEWL9+vZR+K6IqqIeS1Jpxlw5odzkSTkZtEdqt1wevfrP0TZDoORyZUQlvrn7btWuHwMBAXLhwAV988QXedz1jJRCgU1ERLn7zDVo9fAh9V1eE9+qFssJCmfx+hAD/P+RNPZREFu6EheHyJ5/AZeNGZBoaojA6Gh4nT36wmCwvL8egQYNQVlaG4ODgjxaTwMsHVZj3c4WVb1+Y93NFY/1m4PP58Pf3x+HDhyGmyWeknqigJHVy7tw5xOXeQdsd69AyPwtl+UXIOBmJW4GnkHEyEmX5RWiZnwXHkL3/WRjX1dUVO3fuxO7du7F06dL37p/H58Plt9/QJDsbcU5OcAkPR76hIWLnzKFZt0QmaNkgIgvPHz1CuLMzWnp5weDpUyQsWQKnnBy07NHjg9twHIcJEybgypUrCAoKgpmZWZ3bFwgEyMnJwcWLF+u8D0IAABwhdTBx4kTO0tKSE4vFdd7HsmXLOADc7t27q/3s3VOnuPhPPuE4gLukp8dlhIbWuV1CaqIoN5fjAG7Hp5+yjkKUkLiqiouZPZt7oKbGlQHceQ8PrqyoqEbbLl68mAPAHTp0qN45qqqqOBMTE27q1Kn13hdRbdRDSWpNJBIhMDAQQ4YMAY9X98WE5s+fjwkTJmDixIkIDw//6Gdb9+0L+7w8xC9cCIOnT2Hq5YVwe3s8zcqqc/uEfAxNyiHSknnuHC61aAGn1auRq6eHh2fPwuP8eWg1a1bttvv378fixYuxbNky+Pv71zvL62HvI0eOoIpWNCD1QAUlqbXIyEgUFBTAz8+vXvvh8Xj4888/4e7ujsGDB+PGjRsf/zyfD4elS2H4+DEu9OkDh8RElLVqhejJkyEWieqVhZB3qb+aMEbLBhFJKSssRLi7Owx794ZRYSHi5s2DfV4eWn36aY22v3jxIsaPH48xY8Zg/vz5EsslEAiQm5uLCxcuSGyfRPVQQUlqTSgUwszMDPbvWcKitjQ0NHDkyBGYmJjA09MTDx8+rHYbrWbN4HH6NJ7ExiLDxAQ9t25Fiq4ubuzdW+88hLxGPZREkhIWL8YjQ0O4REYi1sUFenl5cFy+HDx+zU7D9+7dw6BBg+Dg4IC//vqrXqND73J0dISpqSkOHToksX0S1UMFJakVsViMo0ePws/PT2IHtKZNmyIsLAzl5eUYOHAgSktLa7SdsaMjXO7fx5Vff4VWZSWsRo9GZIcOKExLk0guotpe91DSpBxSH1nR0YgzMkL3JUuQr6OD7BMn4HHhAhoZGNR4H8XFxfD29kaTJk0QEBCABg0aSDQjn8/H0KFDIRQKadib1BkVlKRWYmNjkZubiyFDhkh0v2ZmZggJCcH169cxevToWh3Uunz7Ldo8eYIoPz/Y3bgBnpUVIoYPR1VFhUQzEtVCPZSkPl48fYrwvn2h5+oKs0ePEDNzJro+fow2/fvXaj8ikQjDhg1DVlYWQkNDYVCLQrQ2BAIB8vLyEB0dLZX9E+VHBSWpFaFQiBYtWsDFxUXi++7WrRsOHDiAY8eOYfbs2j3+S11LC+5CISquX8d1Cwu4HzyI9KZNkfT77xLPSVQDLRtE6ipx5UrkGBigx5kziLe3h/aDB3Beu7bGw9tvmzlzJs6cOYMjR46gffv2Ukj7kqOjI8zMzGjYm9QZFZSkxjiOg1AoxODBg8Gvw4GxJnx8fLBhwwasXbsWf/zxR623/8TGBq63byNlxw6I1NRgN3UqLrRujbzLl6WQlig7MUDrnpIay01IQIypKbrNm4fiRo2QGRgIj4QENDE2rtP+fv/9d/z+++/YtGkT+vTpI+G0/8bj8Wi2N6kXKihJjV2+fBmZmZn1nt1dnW+++QYzZszAtGnTEBISUqd92IwfD+snTxA1bhza3b+Pxt26IdzTExUlJRJOS5QZB9CQN6lWZWkpwr280MTBAeY5Objw1VewKyyEha9vnfd5/PhxTJ8+HTNnzsTkyZMlmPbDBAIBHj16hMjISJm0R5QLFZSkxoRCIfT09ODu7i71tn755RcMHDgQw4cPx+U69i7y1dXhunMnNO/exWU7O/Q8fhzZenq4tGyZhNMSZSUGaMibfNTV9euRqacH17AwJNrZocHdu+ixaVOdhrdfu379OoYNGwYvLy+sWbNGgmk/rnv37mjVqhUNe5M6oYKS1Mjr4W5fX19oaGhIvT01NTXs3bsXHTp0gLe3Nx48eFDnfTVt1QruV6/ibkAAnjRuDPsffkCckRHuV7OYOiHUQ0k+5FFyMi60aYPOM2eiTEMD6QcOwP3qVTStx2MQAeDhw4fw9vZG27ZtsW/fPqi9vpdXBng8HgQCAYRCIUS0ti+pJSooSY2kpqbi9u3bEp/d/TGNGjVCcHAwGjRoAE9PTxQXF9drf5aDB6NzQQEuzpgB08eP0bxXL4S7uqI0P19CiYmyoR5K8i5ReTki/PzQwM4OVpmZiBo/HjZFRbAaNqze+y4rK8OgQYPw4sULBAcHQ1tbWwKJa0cgEODx48eIiIiQedtEsVFBSWpEKBSiSZMmUr8x/F2GhoYICwtDVlYW/P39UVlZWa/98fh8uKxbh6Y5OYjt0QPO0dEoatECMd99R5MvyH9QDyV527UtW5ChqwvXo0eR1KED1NLS4LpjB/jq6vXeN8dxmDBhApKSkhAUFARTU1MJJK69bt26oU2bNjTsTWqNCkpSI0KhEN7e3hJfULcmrK2tERAQgPDwcHz99dfgJHCCb9y8OTyio5F39iyyDAzgvHYtrhgYIP3YMQkkJsqCA6iHkuBxSgqi2rWD7ZQpqOLzcfPvv+GWkgJdc3OJtbF48WIcOHAAu3fvRvfu3SW239qiYW9SV1RQkmqlp6cjOTlZpsPd7+rVqxe2bduGbdu2YeXKlRLbb6tPP4VjXh4SFi+GXkkJWg8ahIiuXVF8/77E2iCKSwxQD6UKq6qoQOSIEdCwtUXH9HREjhwJq6IidBg7VqLt7N27Fz/99BOWL1+OoUOHSnTfdSEQCFBQUIDz58+zjkIUCBWUpFoBAQFo2LAhBgwYwDTHmDFj8OOPP2L+/Pk4cOCARPfd/ccfYZSfj+j+/dHtyhVUtG6NqAkTIKYrdJVGQ96qK3XXLtzS1YXbgQO4ZmGBqpQUuO3dC7XXj+SUkIsXL2LChAkYO3Ys5s6dK9F911WXLl1gbm5Ow96kVqigJNUSCoX47LPP0LhxY9ZR8OOPP+Lzzz/H2LFjJf6IsAY6OvA4cQLPEhJw28wMrjt3IrVZM6Tu2iXRdojioEk5qqcwLQ2R1tZoP24c+ByHa1u2wPX2bRhYW0u8rbt372LQoEFwdHTEli1bwOPxJN5GXbwe9g4ICKj3fetEdVBBST7qwYMHiI+PZzrc/TYej4dt27bBxcUFvr6+SEtLk3gbRvb26HHvHpI2boRGVRXajxuHKCsr5N+4IfG2iHyjHkrVIRaJEDVuHDgrK9jdvImoIUNgUVgIWyktKl5cXAxvb2/o6OggICCAyf3pHyMQCFBYWIhz586xjkIUBBWU5KMCAgKgoaEBLy8v1lHe0NTUREBAAJo3bw5PT0/kS2nZH7upU2FeVIQof3/YpqVB3cYGEUOHQlReLpX2iPwRA+BRQan0bu7fjxRdXbju2oUbrVvjRVIS3I8cgbqWllTaE4lEEAgEyMnJQUhICAwMDKTSTn3Y2dnB0tKShr1JjVFBST5KKBSib9++aNq0Keso/6Krq4uwsDA8ffoUvr6+KJdSkaeupQX3Q4cgSklBspUVXIVC3NHVxdUNG6TSHpEv1EOp3IozMxHRqRMsR46EVmUlkjZuRM87d9C8UyeptclxHKZPn45z587hyJEjaN++vdTaqo/Xw95Hjx5FRUUF6zhEAVBBST4oLy8P0dHRcjPc/a42bdogODgYV65cwdixYyGW4r1uBtbWcLtxAzd37cILdXV0njEDF83MkJuQILU2CXu0bJBy4sRiRE+Zghdt26LrtWuI8vZG68JC2E2dKvW2f/vtN2zatAmbNm1C7969pd5efQgEAhQVFeHs2bOsoxAFQAUl+aBjx46Bz+fD19eXdZQPcnBwwN69e3H48GHMnz9f6u11GDMGNkVFiJ40CRbZ2dBxcEB4//548fSp1NsmskelpPJJO3oUybq66LllC9JNTFCSkACP4GBoNGok9bbDwsIwc+ZMfPfdd/jiiy+k3l592drawsrKioa9SY1QQUk+SCgUwsPDA/r6+qyjfNTgwYPx66+/YtWqVfjrr7+k3h5fXR09t25Fg7t3kdC1K3qcOoVcAwMkLF4s9baJbHEAeNRDqRSe5eQg3N4ebfz80KS8HJdXrYLL/fswsreXSfvXrl3D8OHD4e3tjVWrVsmkzfqiYW9SG1RQkvcqLCzE+fPn4efnxzpKjcyYMQP/+9//8PXXX+PEiRMyabOpmRk8EhOReewYCrW10X3JEsQbGiKThoeUBi1srvg4sRgXp09HiakpHBITEd2vH0weP0bX2bNlliEvLw/e3t4wNzfH3r17oaamJrO260sgEKC4uBinT59mHYXIOSooyXsFBQWhqqoKgwcPZh2lRng8HtavX4/PPvsMAoEASUlJMmvbYuBAdMnPR8ysWTAuKECLPn0Q7uKC548eySwDkQ6alKPY7oSF4YqBAVw2bkSmoSEKo6PhcfIkGujoyCxDWVkZBg0ahMrKSgQHB0NbW1tmbUuCjY0NrK2tadibVIsKSvJeQqEQLi4uMDIyYh2lxtTV1bF//35YWFjAy8sL2dnZMmubx+fDec0a6OXlIcbNDU4xMXhqZISL06aBoyFThUXLBimm548eIdzZGS29vKD/7BkSliyBU04OWvboIdMcYrEY48aNQ3JyMoKDg9GyZUuZti8Jr4e9AwMD8eLFC9ZxiByjgpL8x7Nnz3Dq1Cm5nd39Mdra2ggJCQGfz4e3tzeePXsm0/YbGRjAIyICjyMikGloCJfffkOSnh5uC4UyzUEkg3ooFQsnFiN2zhwUGRvDKTYWFz08YPj4MbovWsQkz+LFi3Ho0CHs2bMH3bp1Y5JBEvz9/fH06VOcOnWKdRQix6igJP8RGhqKiooKhbl/8l3GxsYIDQ1FRkYGhg0bBhGD53GburnBKScHl5YtQ9PSUrQdOhQRdnZ4cveuzLOQuqOCUnFknj2LSy1awGn1auTo6+PR+fPwOH8eWs2aMcmzZ88eLF26FCtWrFDYY+lrNjY2sLGxoWFv8lFUUJL/EAqF6NatG1q1asU6Sp3Z2tpCKBTi9OnTmDp1KjhGRYH9ggUwKSxEtKcnuiYnQ2RujqixYyFmUOSS2qMhb/lXVliIcHd3GPbpA6PCQsTNm4fuubkw8/BglunChQuYOHEixo8fjzlz5jDLIUkCgQDHjh2T2kMkiOKjgpL8S2lpKcLCwhRyuPtdffv2xZ9//ok///wTv/76K7Mcmtra8AgNxfPERNxs3Rquu3fjZtOmuL59O7NMpGaoh1K+JSxejMeGhnCJjESsiwv08vLguHw5eHx2p7Y7d+5g0KBBcHJywp9//gkej8csiyT5+/vj2bNnOHnyJOsoRE5RQUn+5eTJkygtLVWKghIAJk6ciPnz5+P777/HkSNHmGZp0bUret65g+RNm8DnOHScNAlR7drh8fXrTHORD6MeSvmUFR2NOCMjdF+yBI91dJB94gQ8LlxAI8bPxH7y5Am8vb3RrFkzBAQEQFNTk2keSbK2tkbHjh1x+PBh1lGInKKCkvxLQEAAOnbsiHbt2rGOIjFLly7F8OHD8fnnnyM2NpZ1HHT66itYPnmCyBEjYJOeDk1bW0QMHozK0lLW0cg7qIdSvrx4+hThfftCz9UVZo8eIWbmTHR9/Bht+vdnHQ2VlZUQCATIzc1FSEiI3D8Qoi5eD3uXlZWxjkLkEBWU5I2KigoEBwcrTe/ka3w+Hzt37oS9vT0GDhyIjIwM1pGgpqkJt337gFu3kNShA1wDA5Gpp4crDIfmyX9xoB5KeZG4ciVyDAzQ48wZxNvbQ/vBAzivXct0ePs1juMwbdo0nD9/HgEBAbCysmIdSSr8/f1RUlJCw97kvdj/SyRy4+zZsyguLla6ghIAtLS0EBgYiGbNmsHLywuFhYWsIwEA9Cwt4ZaSgtv79qFUUxNdZs1CTMuWyI6JYR2NgHoo5UFuQgJiTE3Rbd48FDdqhMzAQHgkJKCJsTHraG9s3LgRf/75JzZv3oxevXqxjiM17du3R6dOnWi2N3kvKijJG0KhEBYWFujYsSPrKFKhr6+PsLAw5OfnY/DgwXK1SG/7ESNg++QJLkyZgra5udB1cUF4794of/KEdTSVRj2U7FSWliLcywtNHBxgnpODC199BbvCQlj4+rKO9i+hoaH49ttvMWvWLEyaNIl1HKkTCAQICgqiYW/yH1RQEgCASCRCYGAghgwZojSzEt/HwsICQUFBiIuLw4QJE5gtJ/Q+PD4fPTZvRsPMTMTb26PHuXN49MkniFuwgJ62wwj9V2fj6vr1yNTTg2tYGBLt7NDg7l302LRJLoa335acnIzhw4fDx8cHK1euZB1HJvz9/fH8+XMcP36cdRQiZ+TrXydhJjIyEgUFBUo53P0uFxcX7N69G/v27cOPP/7IOs5/6LRsCY+EBDwIDcWjpk3huHw5Lhka4i7dtyRzHI8HHhXzMvPw6lVcaN0anWfORJmGBtIPHID71atoambGOtp/5OXlwdvbG5aWlti7dy/U1NRYR5KJdu3aoXPnzjTsTf6DCkoC4OXsbjMzM9jb27OOIhMCgQArV67E0qVLsXPnTtZx3qutpye6PXqEuLlz0eLJE5gMGIBwR0c8y8lhHU1liAEob3+9/BCVlyPCzw9aXbrA6v59RI0fD5uiIlgNG8Y62nuVlZXB19cXVVVVCA4ORuPGjVlHkimBQIDg4GCU0soU5C1UUBKIxWIEBATAz89PqYe73zV79mxMnjwZkydPxtmzZ1nHeS8enw/HFStg8PAhLvbqBcf4eJSYmuLC11/TMLgM0D2U0pe8eTMydHXhevQokjp0gFpaGlx37ABfXZ11tPcSi8UYO3Ysrl+/jqCgIJiYmLCOJHP+/v5vHoJByGtUUBLExsYiNzdX4Z83W1s8Hg9//PEHevfuDT8/P6SkpLCO9EEN9fTgce4cCqKjcc/ICD02b0ayri5uHTzIOppSEwM0y1tKHqekIMrSEp2+/hoiNTXc3LULbikp0DU3Zx3to3788UccOXIEe/bsQbdu3VjHYcLCwgJdu3alYW/yL1RQEgiFQhgaGsLFxYV1FJlTV1fHoUOH0Lp1a3h6eiIvL491pI9q2aMHnLOycHnVKmiXl8Ni+HBE2NqiSA7W1lRWqtNnLxtVFRWIHDECGra26JiRgciRI9G+sBAdxoxhHa1a//zzD5YtW4aVK1di8ODBrOMwJRAIEBISgufPn7OOQuQEFZQqjuM4CIVCDB48WGVuKn+Xjo4OQkNDIRKJ4O3trRAHyK6zZ8OsqAhRAweiy/XrEFtaInLUKFRVVLCOplRoHUrJStm5E7d0deF24ACuWVigKiUFbnv3Qk0BHlEYHR2NSZMmYcKECfj+++9Zx2HO398fZWVlCA0NZR2FyAkqKFXclStXkJmZqRKzuz+mZcuWCA0Nxa1btzBy5EhUVVWxjlQtjUaN4HHsGMqTknCjbVu47duH282a4dqWLayjKQ0xj0f3UEpAYVoaIq2tYT1hAvgch2tbtsD19m0YWFuzjlYjGRkZGDRoEFxcXLB582aVutf8Q9q2bQt7e3sa9iZvUEGp4oRCIfT09ODu7s46CnOdO3fGwYMHERISgm+//ZZ1nBpr3qkTeqan49qWLeB4PNhOmYJoc3M8vHqVdTSFR5Ny6kcsEiFq3DhwVlawu3kTUUOGwKKwELaTJ7OOVmNPnjyBt7c39PT0IBQKoakAvamyIhAIEBoaipKSEtZRiBygglKFvR7uHjhwIDQ0NFjHkQuenp74448/sHHjRmzYsIF1nFqxnTwZVkVFiPz8c1jfvYuGXbog3McHFXSwrzOaR193N/fvR4quLlx37cKNNm3wIikJ7keOQF1Li3W0GqusrIS/vz8ePnyIkJAQ6OnpsY4kV/z9/VFeXo6QkBDWUYgcoIJShaWmpuLWrVsqP9z9rilTpmDWrFmYOXMmjh07xjpOrahpasJt927w09JwxdYWriEheKCvj0QVeYqHpFEPZe0VZ2YiolMnWI4cCa3KSiRt3IieGRlo3qkT62i1wnEcpk6divDwcAiFQrRr1451JLnTunVrODg40LA3AUAFpUoTCoVo0qQJ+vbtyzqK3Fm1ahX8/PwwYsQIJCQksI5Ta7rm5nBPTkb6wYMo0dJCt3nzEGtsjKzoaNbRFAoHmuVdU5xYjOjJk1HRpg26XruGKG9vtC4shN3Uqayj1cn69euxZcsWbNmyBb169WIdR24JBAKEhYXh2bNnrKMQxqigVGEBAQHw9vZGgwYNWEeRO3w+H//88w/s7Ozg4+ODe/fusY5UJ1YCAToVFeHiN9+g1cOH0Hd1RbiHB8oKC1lHUwjUQ1kzt4VCJOvqoufWrUhr2RIlCQnwCA6GRqNGrKPVSXBwML777jvMnj0bEyZMYB1Hrg0dOhQvXrxAcHAw6yiEMSooVVRGRgaSkpJouPsjGjZsiGPHjqFx48bw8vLCkydPWEeqEx6fD5fffkOT7GzEOTnBJSICBc2bI3b2bHraTjVolvfHPcvJQbi9PdoOHYom5eW4vGoVXO7fh5ECP8I1KSkJI0aMgK+vL1asWME6jtxr1aoVnJycaNibUEGpqoRCIRo2bIgBAwawjiLXmjdvjrCwMOTm5mLIkCGoUOB1HrVbtIBHTAyyT5xArp4enNasweVPPsEdenzaB9GQ9/txYjEuTpuGElNTOCQmIrpfP5g8foyus2ezjlYvubm58Pb2hpWVFfbs2QM+n06RNSEQCHD8+HE8ffqUdRTCEP1rUVFCoRADBgxA48aNWUeRe1ZWVggMDER0dDQmT54MTsF7rNr07w/7vDzEL1wIg6dPYerlhXB7ezzNymIdTS5RD+W/3QkLwxUDA7j89hsyDQ1RdPEiPE6eRAMdHdbR6qW0tBS+vr4Qi8UICgqiY2MtDB06FBUVFQgKCmIdhTBEBaUKevDgAeLj42m4uxbc3Nywc+dO7Nq1C8uWLWMdp954fD4cli6F4ePHuNCnDxwSE1HWqhWiJ0+GWCRiHU9uiHk8elLOK88fPUK4szNaenlB/9kzJCxZAqecHJg4O7OOVm9isRhjx45FSkoKgoODYWJiwjqSQjE1NYWLiwsNe6s4KihVUEBAADQ0NODt7c06ikIZOXIkli5dikWLFmHPnj2s40iEVrNm8Dh9Gk9iY5FhYoKeW7ciRVcXN/buZR1NLtCQ98vh7djZs/HE2BhOsbG46OEBw8eP0X3RItbRJOaHH36AUCjE3r170bVrV9ZxFJJAIMDJkycV9l5zUn9UUKqggIAA9O3bF02bNmUdReEsWLAA48ePx4QJExAREcE6jsQYOzrC5f59XPn1V2hVVsJq9GhEWluj4NYt1tGYEkO1h7wzz57FJUNDOK1Zg2x9fTw6fx4e589Dq1kz1tEkZteuXVi+fDlWrVqFQYMGsY6jsGjYm/A4Rb8hjNTKw4cPYWRkhG3bttFyGHVUWVmJzz77DImJiYiJiUH79u1ZR5KoytJSXBw9Gp2PHoWYx0OyQICeu3dDTQUfOReuoYFnGhrwKS1lHUWmygoLETd4MJwiI5Gvpobs2bPhsGwZeEo2SSUqKgq9e/fGmDFjsHXrVnpGdz25urqiadOm9OQcFaVcRwdSrcDAQPD5fAwcOJB1FIWloaGBI0eOwMTEBJ6ennj06BHrSBKl0agR3AMCUHH9Oq5bWMD94EGkN22KpN9/Zx1N5lRx2aD4RYvw2NAQLpGRiHVxgV5eHhyXL1e6YjI9PR2DBw9Gz549sWnTJiomJcDf3x+nTp1CUVER6yiEAeU6QpBqCYVCuLu7w8DAgHUUhdasWTOEhoairKwMAwcORFlZGetIEveJjQ1cb99Gyo4dEKmpwW7qVFxo3Rq5ly6xjiYzqnQPZVZ0NOKMjOCwdCke6+gg+8QJeFy4gEZKeKwoKiqCt7c39PX1ceTIEWiqYO+7NAwZMgQikUjhHllLJIMKShVSWFiI8+fP0+xuCWnVqhWCg4Nx7do1jB49GmIlXSTcZvx4WD95gqixY9Hu/n006d4d4Z6eqCgpYR1NJpS9h/LF06cI79sXeq6uMHv0CDEzZ6Lr48do078/62hSUVlZiaFDh+Lx48cICQmBnp4e60hKw8TEBD179sThw4dZRyEMUEGpQoKDg1FVVYXBgwezjqI07O3tsX//fhw9ehSzFXxR54/hq6vD9e+/oXn3LhLt7NDz+HFk6+nhkhIsofQxYh5PqXsoE1esQI6BAXqcOYN4e3toP3gA57VrlW54+zWO4/DNN98gKioKAQEBsLS0ZB1J6QgEAhr2VlHKedQg7yUUCuHi4gIjIyPWUZTKwIEDsWHDBvz666/YtGkT6zhS1bRVK7hfvYo7R47gSePGsP/hB8QZGeF+eDjraFKjjAVlbkICYlq2RLf581HcqBEyAwPhkZCAJsbGrKNJ1bp16/DXX39hy5YtcHd3Zx1HKQ0ZMgRVVVUIDAxkHYXIGBWUKuLZs2c4deoU/Pz8WEdRSlOnTsX06dMxdepUhIaGso4jde2GDEHnggJcnDEDpo8fo3mvXgh3dUVpfj7raBKlbMsGVZSUINzLC00cHGCem4sLX30Fu8JCWPj6so4mdUFBQZg1axbmzJmD8ePHs46jtIyMjODm5kaLnKsgKihVRGhoKF68eEEFpRT9+uuv8PHxwbBhw3DlyhXWcaSOx+fDZd06NM3JQWyPHnCOjkZRixaI+fZbcEpyPynH4ynNQfLq+vV4oK8P17AwJNrZocHdu+ixaZPSDm+/7erVqxg5ciQGDx6M5cuXs46j9AQCAc6cOYOCggLWUYgM0TqUKsLf3x93797FJRWaocvC8+fP4eHhgezsbMTFxcHU1JR1JJnJPHsWD0eOhMOjR7isqwudnTsVvufruJYW1DkOfV+8YB2lzh5evYr0QYPQIzMTyU2aoMG2bbASCFjHkpnc3Fw4ODjA0NAQERER9IxuGcjLy4OJiQn++usvTJw4kXUcIiPKf2lKUFZWhrCwMJrdLQONGzdGcHAwNDU14eXlhadPn7KOJDOteveGw8OHSFi8GHolJWg9aBAiunZF8f37rKPVmSIvGyQqL0fE4MFo2KULrO7fR9T48ehYWKhSxWRpaSkGDhwIjuMQFBRExaSMtGjRAu7u7jTsrWKooFQBJ0+eRGlpKRWUMtKiRQuEhYXh/v378Pf3R2VlJetIMtX9xx9hlJ+P6P790e3KFVS0bo2oCRMgFolYR6s1TkEXNk/evBkZurpwDQzE1Q4doJaWBtcdO8BXV2cdTWbEYjE+//xzpKamIjg4GMZKPuFI3ggEApw9exb5SnZfNfkwKihVgFAohI2NDdq1a8c6isro0KEDAgICcO7cOXz99ddQtTtLGujowOPECTyLj8dtMzO47tyJ1GbNkLprF+totaJoPZSPU1IQZWmJTl9/DZGaGm7u2gW3lBTompuzjiZzCxcuxNGjR7F//3506dKFdRyV4+fnB47jcPToUdZRiIxQQankKioqEBwcTL2TDHz66afYtm0btm3bhlWrVrGOw4RR9+7oce8erq5fD82qKrQfNw5RVlbIv3GDdbQa4Xg88BXgYqCqogIRw4dDw9YWHTMyEDlyJNoXFqLDmDGsozHx999/Y8WKFVizZg09ZpaR5s2bo1evXjTsrUKooFRyZ8+eRXFxMRWUjIwdOxaLFi3CvHnzcPDgQdZxmOk8fTraFhUhauhQ2KalQaNDB0QMGQJReTnraB8l/6UkkLJzJ27p6sL94EFcs7REVUoK3PbuhZqKPk4wIiICkydPxqRJk/Dtt9+yjqPSBAIBzp07h8ePH7OOQmSACkolJxQKYWFhAVtbW9ZRVNbixYsxevRojB07FhcuXGAdhxl1LS24Hz4MUUoKktq3h2tAAO7o6uLqhg2so32QPC8bVJiWhkhra1hPmAA+x+Hali1wvXULBtbWrKMxk5aWBj8/P7i6umLTpk3g8RTphgXlM3jwYPB4PAQEBLCOQmSAlg1SYiKRCEZGRpg4cSJWrlzJOo5Ke/HiBfr374/r168jJiaGHvkGIHX3blT973+wLSnBRVNTtBEKYdS9O+tY/xLYuDH0KyrgKkcTq8QiES5MnIgO//wDdY7D1SFD0GPPHqhrabGOxlRRURGcnJzA4/EQExMDXV1d1pEIgH79+qGqqgpnz55lHYVImbxefBMJiIqKQn5+Pi1mLgcaNGiAo0ePwsDAAJ6enjTzEUCHMWNgU1SE6IkTYZmVBR0HB4T364cX8rTUkpzN8r65fz9SdHXhuns3brRpgxdJSXA/ckTli8nKykoMHToU+fn5CAkJoWJSjggEAoSHh+Phw4esoxApo4JSiQmFQpiamqK7nPX6qCpdXV2EhYWhuLgYgwYNQrmc3z8oC3x1dfTctg2a9+4hoWtX9Dh9Gnn6+khYvJh1NADyM8u7ODMTEZ06wXLkSGhVViJp40b0zMhA806dWEdjjuM4fP3114iKisLRo0dhYWHBOhJ5Cw17qw4qKJWUWCxGQEAA/Pz86D4iOdK2bVsEBwcjMTER48aNg1hJHlFYX03NzOCRmIjMY8dQ0KQJui9ZgnhDQ2QyHibjeDymBSUnFiN68mRUtGmDrteuIcrbG60LC2E3dSrDVPJl7dq12LZtG7Zu3Qo3NzfWccg79PX10adPH5rtrQKooFRSsbGxyM3NpdndcsjR0RF79uzBoUOHsHDhQtZx5IrFwIHokp+PmFmzYFxQgBZ9+iDcxQUleXlM8rBcNui2UIhkXV303LoVaS1boiQhAR7BwdBo1IhJHnl07NgxfP/995g3bx7Gjh3LOg75AIFAgIiICOQx+ndMZIMKSiUVEBAAQ0NDuLi4sI5C3mPIkCFYs2YNVqxYga1bt7KOI1d4fD6c16yBXl4eYtzc4BQTg2cmJrg4bRo4GffosuihfJqVhXB7e7QdOhRNystxedUquNy/DyN7exknkW9XrlzByJEj4efnh2XLlrGOQz5i0KBBUFNTg1AoZB2FSBHN8lZCHMehbdu26N+/P/7880/WccgHcByHb775Blu2bEFYWBj69evHOpJcuh8ejtwRI+CYl4erTZui0bZtaDd0qEzaPty0KVqVlMChqkrqbXFiMWJmzEDbP/6AjliM+H794Hz4MBro6Ei9bUWTnZ0NR0dHGBkZISIiAo2o11bueXp64vnz54iIiGAdhUgJ9VAqoStXruDevXs03C3neDweNmzYgP79+2Po0KFITk5mHUkumXl4wDE3F5eWLUPT0lKY+/sjws4OT+7elXrbsuqhvBMWhisGBnD57TfcMzRE0cWL8Dh5korJ93j+/DkGDhwIHo+HoKAgKiYVhEAgQFRUFHJyclhHIVJCBaUSEgqF0NXVhYeHB+sopBrq6uo4ePAgLCws4OXlRQfbj7BfsAAmhYWI8vRE1+RkiMzNETV2LMQikVTbleZB8vmjRwh3dkZLLy/oP3uGhCVL4JSTAxNnZym2qrjEYjHGjBmDW7duITg4GEZGRqwjkRry9fWFuro6DXsrMSoolQzHcRAKhfD19YWGhgbrOKQGtLW1ERISAgDw9vZGSUkJ40TyS1NbGx6hoXiemIibrVvDdfdu3GzaFNe3b5dOg1LqoeTEYsTOno0nxsZwio3FxV69YPj4MbovWiSF1pTH/PnzcfToUezfvx+dO3dmHYfUgq6uLvr160ezvZUYFZRK5saNG7h16xYNdysYY2NjhIaGIj09HcOHD4dIyr1uiq5F167oeecOkjdtAp/j0HHSJERZWuLx9esSbUcshYXN750+jUuGhnBaswbZ+vp4dP48PM6dg1azZhJtR9ns3LkTq1atwi+//AIfHx/WcUgdCAQCREdHIzs7m3UUIgVUUCoZoVCIJk2aoE+fPqyjkFrq1KkTjhw5ghMnTmDatGmg+XLV6/TVV7B88gSRI0bAJiMDmra2iBg8GJWlpfXe9/OCJ6jU/gQF+qbIOBWF5wVP6rW/ssJChLu5wahfPxgVFSFu3jx0z82FGd2aUq3w8HBMnjwZkydPxsyZM1nHIXU0cOBAaGho4MiRI6yjECmgWd5KpnPnzrC2tsb+/ftZRyF1tHXrVkyePBm//PILvvvuO9ZxFEZhWhquDxqEnqmpuNOgAZ79/DO61PK/X2ZkAvJWr0fL2HAYFeT864pbDCBX3xhZTh5oMXsGWrnV/AlU8YsWocWKFWghEuGiiwscjh1DIwODWmVTVWlpaXByckKXLl1w/PhxupVHwfn4+KCwsBAXLlxgHYVIGkeURnp6OgeAO3z4MOsopJ7mzp3L8Xg87siRI6yjKJwb+/ZxSU2acBzAXTQx4bIuXqx2m+zLKVxyBweOA7hKHp/jgA/+ef1+cgcHLvtyykf3ez8igott0YLjAO6Snh5358QJSf2aKqGgoICztLTkrKysuMLCQtZxiATs3r2bA8Ddv3+fdRQiYTTkrUSEQiEaNmyIzz77jHUUUk8///wzBAIBRo8ejdjYWNZxFEr7ESNg++QJor/8Em1zc6Hr4oLw3r1R/uTJez8fv2AV9By6wPrGJQCAOvfxxdNfv2994xL0HLogfsGq/3zmxdOnCO/TBwbu7jB79AgxM2ei6+PHaNO/f/1+ORVSUVGBoUOHorCwEKGhodDV1WUdiUjAwIEDoampSbO9lRANeSsRR0dHmJiYICAggHUUIgHl5eXo06cPbt++jdjYWLRt25Z1JIXzNCsLlwcPRo9Ll5Crro7c77+Hw7Jl4PFfXkvHTPwWzjvWgQPqNJv79XYxE2bCeftaAEDiihXQ+/FHtKysxAV7e3Q7dgxNjI0l9SupBI7j8MUXX2D37t04e/YsXF1dWUciEuTr64vHjx/j4sWLrKMQCaKCUkk8ePAAZmZm2LNnD0aNGsU6DpGQ/Px8ODs7Q01NDRcvXoSenh7rSArpTlgYCseMgX1BAS7p60Pvn3+QH50Mh+VzJdZG+OTv0SB0H5yzs3G1aVNo79oFC19fie1flaxZswazZ8/Grl27MGbMGNZxiITt3bsXo0ePRmZmJszMzFjHIRJCQ95K4ujRo9DQ0ICXlxfrKESCDAwMEBYWhvz8fPj5+eHFixesIymktp6e6PboEeLmzoVhcTHUho1Bp9WL8KGr6acAHAGo4WUPpDaAlR/ZPwfAaccG6DyrwIWvvoJdYSEVk3UUGBiIOXPmYP78+VRMKikfHx80aNCAZnsrGeqhVBLu7u5o3LgxwsLCWEchUnDhwgX07t0b/v7+2L17N3g8WTwQUDmVFRbihl0PdMq+/cH7JVsBuA/AHoAVgGMASgD8AeDrD+xXxOMjxaor7G4kSCG1arh8+TJcXV3h6emJgwcPgs+nPg9lNXjwYOTm5tI94kqE/rUqgYcPHyIqKooWM1diPXr0wK5du7Bnzx4sXryYdRyF9uh6Brpm3fxgMbkTL4tJLwAJAPYAeABAHcCcj+xXnRPD7uYlZEZfknBi1ZCdnQ0fHx/Y2Nhg165dVEwqOYFAgLi4ONy7d491FCIh9C9WCQQGBoLP58OXhtiU2rBhw7BixQr89NNP+Pvvv1nHUVh5q9dDxPvwoW/zq69/vvWzZgA+xcteyriP7FvE4yNv5br6RlQ5z58/h4+PD9TU1HDs2DE0atSIdSQiZd7e3tDS0qJhbyVCBaUSCAgIgLu7OwxooWSlN2fOHHzxxRf44osvcPbsWdZxFFLL2PCPLg2UAUATQMt3fv762VMhH9m3OieGSWxE/QKqGLFYjNGjRyMtLQ3BwcEwMjJiHYnIQJMmTeDp6UnP9lYiVFAquKKiIpw7dw5+fn6soxAZ4PF4+OOPP/Dpp59iyJAhSE1NZR1JoZTkF8GoIOejn3kOoPF7fm716uudatowLsiu92MaVcm8efMQFBSE/fv3w87OjnUcIkMCgQAJCQm4e/cu6yhEAqigVHBBQUEQiUQYPHgw6yhERjQ0NHD48GGYmZnB09MTeXl5rCMpjIeXr1d70KvCy/sl36Xz6mt1TwnnA8hLvFbbaCpp+/btWL16NX799Vd4e3uzjkNkzMvLCw0bNsThw4dZRyESQAWlghMKhXBxcYExLZysUnR0dBAaGorKykr4+Pjg+fPnrCMpBFFZebWfUQMges/Pn776WpO7+2rSjqo7f/48pkyZgi+//BLTp09nHYcwoK2tDS8vLxr2VhJUUCqwZ8+e4dSpUzS7W0WZmpoiJCQEN27cwKhRo1BVVcU6ktxTb6hV7Wca4+Ww97tuvfpak+cV1aQdVXb79m0MGTIEvXr1wm+//UbLYKkwgUCAxMREZGRksI5C6okKSgUWFhaGFy9e0P2TKqxLly44dOgQgoOD8d1337GOI/dadLPFx5/U/bJgrACQ9c7PT7/6Wt3ArPhVO+T9CgsL4e3tDUNDQxw6dAgaGhqsIxGGPD090ahRIxr2VgJUUCowoVCIrl27onXr1qyjEIY8PT3x22+/YcOGDdi4cSPrOHKtsX4z5Op//PaQKe98BV4Od4fjZe+lYzVt5OiboLF+szomVG4VFRXw8/NDYWEhQkJC0KxZM9aRCGONGzeGt7c3DXsrASooFVRZWRnCwsJouJsAAL7++mt89913mDFjBoKCgljHkWtZTh4fXYdyIl4uGRQKwAHA6FffVwJYUc2+RTw+sp3cJZRUuXAchylTpiAmJgaBgYEwNzdnHYnICYFAgCtXriAtLY11FFIPVFAqqJMnT+L58+dUUJI3Vq9eDT8/P4wYMQKXLtHTWj4ku4/bR9ehBIBrePnYxUQAe/FyGHsZgKnV7FudE4M/YZQkYiqdNWvWYOfOndi+fTt69uzJOg6RI5999hkaN25Mw94KjgpKBSUUCmFjYwMrK6vqP0xUAp/Pxz///ANbW1t4e3sjMzOTdSS5cu3aNfTv3x9DZk5BtEn7j/ZSNsPLxy5WAeDw8gk5C6rZv4jHR4SRJVxH+uH7779HUVGRpKIrvKNHj2Lu3LlYuHAhRo8ezToOkTONGjWCj48PDXsrOCooFVBFRQWCg4Opd5L8R8OGDREUFIRGjRrBy8sLT548YR2Juby8PHzxxRfo3Lkz7ty5g4CAALQJOgKRmjo4CbXBARCpqaPlkX2YN28eNm/ejLZt2+KXX35BeblqLyGUmJiIUaNGYejQoViyZAnrOEROCQQCJCUl4datW9V/mMglKigV0Llz51BcXEwFJXmv5s2bIywsDDk5ORg6dCgqKipYR2KitLQUy5Ytg4WFBYRCIdauXYuUlBQMHjwYJl1tkDz7J0hqsRoegOQ5S2HuYo8ff/wR6enpGD58OObOnQsrKyv8888/EIurm1+ufLKzszFw4EDY2tpi165d4PPplEPeb8CAAdDW1qZhb0XGEYUzadIkztzcnBOLxayjEDkWHh7OaWhocOPHj1epvytVVVXcrl27OBMTE05DQ4P79ttvucLCwvd+9uKEmRwHcGKA4+rw5/V2MRO/fe/+b968yQ0ePJgDwHXu3Jk7deqUNH91ufLs2TOuS5cunKmpKZebm8s6DlEAI0eO5GxtbVnHIHVEBaWCqays5AwMDLjZs2ezjkIUwD///MMB4JYuXco6ikycP3+e69q1KweAGzJkCJeenl7tNnHzV3Jl6ppcJY9fq2KyksfnytQ1ubgFq6ptIzo6mnNxceEAcH379uUuX74siV9XbolEIs7X15fT1tbmkpKSWMchCiIwMJADwKWmprKOQuqACkoFc+7cOQ4AFxcXxzoKURA//fQTB4Dbs2cP6yhSc/PmTW7gwIEcAM7BwYGLioqq1fbZl1O45A4ObwrF6gpJDuCSOzhw2ZdTatyGWCzmjh49yrVr147j8Xjc6NGjuXv37tX2V1UIs2bN4vh8PhcSEsI6ClEgZWVlXJMmTbglS5awjkLqgApKBfO///2PMzU1VakhTFI/YrGYGzduHKepqclFRESwjiNRjx8/5r755htOXV2da9WqFbdv3z6uqqqqzvu7FxHPxXqN5B7om3BV7xSSVQD3QN+Ei/Uayd2LSqhzGxUVFdzmzZs5Q0NDTlNTk/vuu++4goKCOu9P3mzdupUDwK1fv551FKKARo0axdnY2LCOQeqACkoFUlVVxRkbG3PTp09nHYUomBcvXnCffvopp6ury928eZN1nHorLy/nVq9ezTVt2pTT0dHhVq5cyZWVlUm0jZL8Im7jjLncp8YWXPrJSK4kv0ii+3/27Bm3ePFirnHjxlyzZs24NWvWSPx3kLWzZ89y6urq3FdffUUXvaROjh07xgHgrl+/zjoKqSWacqdA4uLikJOTQ8/uJrWmqakJoVAIIyMjeHp64vHjx6wj1QnHcTh06BDat2+PefPmYdSoUUhPT8ecOXOgpaUl0bYa6zeDuHULxBRlw7yfq8Qfp6itrf1mRviIESMUfkb4rVu3MGTIEPTq1QsbNmwAjyepOfRElfTr1w86Ojo021sBUUGpQIRCIZo3b44ePXqwjkIUULNmzRAaGornz59j4MCBKCsrYx2pVmJiYtCjRw8MGzYMHTt2xLVr1/DHH3/gk08+kVqbfD4fHCep1Srfr0WLFti0aRNSUlJgb2+PMWPGoGvXrjh16pRU25WkgoICeHl5wcjICIcOHYKGhgbrSERBaWlpwdfXlxY5V0BUUCoIjuMgFAoxePBgqKmpsY5DFFTr1q0RHByMpKQkfP755wrRE3b37l0MGzYMLi4uKC0txZkzZxAcHAxra2upt83j8aReUL5mZWUFoVCICxcuQFtbG/3790ffvn1x5coVmbRfVxUVFfDz80NxcTFCQkLQrFkz1pGIghMIBLhx4wZSUlJYRyG1QAWlgrhy5Qru3btHi5mTeuvevTv279+PgIAAzJkzh3WcD3ry5Am+//57tG/fHlFRUdixYwcSExPRu3dvmWXg8XgyL7pdXFwQFRWFo0eP4sGDB+jatStGjx6Ne/fuyTRHTXAchy+//BKxsbEIDAxE27ZtWUciSqBv375o2rQp9VIqGCooFURAQAB0dXXh4eHBOgpRAr6+vli3bh1++eUXbN68mXWcf6msrMRvv/0GCwsLbNq0CfPnz0daWhrGjx8v8955WQx5vw+Px8OgQYNw/fp1/Pnnnzhz5gysrKwwa9YsFBYWyjzPh6xatQp///03duzYQbfiEIlp0KABBg0ahEOHDjH590fqiOGEIFIL7du358aOHcs6BlEy06ZN4/h8PhcaGso6CicWi7nAwMA36zROmDCBy87OZppp8+bNHJ/PZ5qB417OCF+yZMmbGeGrV69mPiNcKBRyALgffviBaQ6inEJDQzkAXHJyMusopIaoh1IBpKam4ubNmzTcTSRu7dq18Pb2hkAgYHqvXmJiInr16oVBgwbBzMwMV65cwfbt22FsbMwsE8Cuh/Jd2traWLRoETIyMjBy5EjMmzcP7dq1w+7du1FVVSXzPJcuXcLo0aMxbNgwLFmyRObtE+XXp08fNGvWjIa9FQgVlApAKBRCW1sbffv2ZR2FKBk1NTXs27cP7du3h7e3N7KysmTa/oMHDzBmzBjY29vj0aNHCA0NxalTp2BnZyfTHB8iy0k5NWFoaIg//vgDqampcHBwwNixY9GtWzecPHlSZjmzsrIwcOBAdOrUCTt37qTlgYhUaGpqYvDgwTTsrUCooFQAQqEQ3t7eEl9njxAAaNy4MUJCQqCurg4vLy88ffpU6m0+e/YMCxcuRLt27XDixAls3rwZycnJ8PT0lKsChc9/eYiUtxNau3btcOTIEVy8eBHa2toYMGAA+vXrJ/Ve5pKSEvj4+EBDQwPHjh1Dw4YNpdoeUW0CgQC3b99GcnIy6yikBqiglHMZGRlISkqi4W4iVS1atEBYWBju3bsHgUCAyspKqbQjEonw119/wdLSEr/88gtmzpyJ9PR0TJkyBerq6lJpsz5eF7fyVlC+5uzsjKioKAQGBkp9RnhVVRVGjRqFjIwMhISEwNDQUOJtEPK23r17Q1dXl4a9FQQVlHIuICAAWlpaGDBgAOsoRMnZ2NggICAAZ8+exf/+9z+JF1EnT55Ely5d8OWXX6JPnz64ffs2li9fDh0dHYm2I0mveyjleb1OHo8HX19fXL9+HVu2bMHZs2dhZWWF7777TqIzwufMmYOQkBAcOHAAtra2EtsvIR+ioaEBPz8/GvZWEFRQyjmhUIgBAwZAW1ubdRSiAnr37o2//voLW7duxerVqyWyz+vXr2PAgAEYMGAAdHV1ER8fjz179sDMzEwi+5cmee+hfJu6ujomT56MtLQ0LFiwAH/99RfMzc2xevXqej8VaevWrfj111+xbt06eHp6SigxIdUTCARIT0/H1atXWUch1aCCUo5lZWUhLi6OhruJTI0fPx4LFy7E3Llz6zXUlJeXh8mTJ8POzg4ZGRkQCoWIiIhA9+7dJZhWul4XlPLcQ/mu1zPC09PTMXLkSCxYsABWVlbYtWtXnWaEnz17Fl9//TW+/vprTJ06VQqJCfmwXr16QV9fn4a9FQAVlHIsICAAGhoa8Pb2Zh2FqJiffvoJI0eOxJgxY3DhwoVabVtaWoply5bB0tISR44cwa+//oqUlBT4+fnJ1YSbmpDXSTk18XpGeEpKChwcHDBu3Dh07doVJ06cqPHv83q5st69e2PDhg0K9/+PKD4a9lYcVFDKMaFQ+GYtLkJkicfjYceOHXB0dISvry/S09Or3UYsFmP37t2wsrLCTz/9hC+++ALp6emYMWMGNDU1ZZBa8hSxh/Jdb88I19HRwWeffYa+ffvi8uXLH90uPz8f3t7eMDExwcGDB+Vy0hRRDQKBAHfu3Kn27yxhiwpKOfXw4UNERUXRcDdhpkGDBjh69CgMDAzg6emJgoKCD342PDwc3bt3x9ixY+Ho6IjU1FSsXbsWenp6MkwseYrcQ/kuZ2dnREZGIjAwENnZ2ejWrRtGjRqFu3fv/uezL168gJ+fH54+fYqQkBA0bdqUQWJCXvLw8ICBgQENe8s5Kijl1LFjx8Dj8TBw4EDWUYgK09PTQ2hoKIqKijBo0CCUl5f/6/3bt29j0KBB6NWrF9TV1REVFYUjR47AwsKCUWLJUqRJOTXxekb4tWvXsGXLFpw7dw7t27fHd9999+aCgeM4fPnll4iPj0dgYCDatGnDODVRderq6hgyZAgNe8s5KijllFAohLu7Oz755BPWUYiKMzc3R1BQEC5duoTx48dDLBYjPz8f06ZNg42NDa5cuYJ9+/YhJiYGPXv2ZB1XohRh2aC6eD0jPD09HQsXLvzXjPClS5di165d2LFjB1xcXFhHJQTAy2Hve/fu4dKlS6yjkA+gm2LkUFFREc6dO4f169ezjkIIgJfDpf/88w/8/f3x6NEjJCYmQiwWY+nSpZg+fbrSPjFF2Xoo39W4cWP88MMP+PLLL/HTTz9h3rx5EIvF8PX1xbBhw1jHI+QNNzc3NG/eHIcOHVKolSJUCfVQyqGgoCCIRCIMHjyYdRRCALwsqMRiMfT09HDu3Dl07twZ6enpmDt3rtIWk4ByTMqpiebNm2Ps2LHQ0NCAqakpjh07hi5dutRqRjgh0kTD3vKPCko5FBAQABcXFxgbG7OOQghiYmLQo0cPDBs2DE5OThg2bBiio6NVYqFhZZqU8zEPHjzAwIED0aVLF9y+fRsxMTFo1qxZjWeEEyILAoEA9+/fR3x8POso5D2ooJQzz549w8mTJ+Hn58c6ClFxd+/exbBhw+Di4oLS0lKcOXMGoaGh2LNnD/r164ehQ4fi2rVrrGNKlSr0UJaUlMDHxwcNGjRAYGAgtLS04OTkhIiICBw7dgw5OTkfnRFOiKy4urrC0NCQZnvLKSoo5UxYWNibJTsIYeHJkyeYPXs22rdvj6ioKOzYsQOJiYno3bs3gJdDTwcPHoS5uTm8vLyQk5PDOLH0KHsPZVVVFUaMGIE7d+4gJCQEhoaGb957vcpEcnIy/vrrrzczwr/99tuPLiFFiLSoqalh6NChOHz4sFJf5CkqKijljFAoRNeuXWmpDiJzlZWV+P3332FhYYE//vgD8+fPR1paGsaPHw81NbV/fbZJkyYICQmBWCyGt7c3SkpKGKWWLmXvofz+++8RFhaGQ4cOoWPHju/9jLq6+ptF6n/44Qds3boV5ubmWLVqVb2fEU5Ibfn7++PBgweIi4tjHYW8gwpKOVJWVoawsDBazJzIFMdxCAoKgq2tLaZNm4aBAwciLS0NP/74Ixo3bvzB7UxMTBAWFob09HQMHz4cIpFIhqllQ5l7KLds2YJ169Zhw4YNGDBgQLWfb9y4MRYuXIiMjAx8/vnnWLhwIdq1a4e///67Ts8IJ6QuevbsiRYtWtCwtxyiglKOnDx5Es+fP6eCksjM5cuX8emnn8LX1xctW7bE5cuXsWPHjhpPCOvUqRMOHz6MEydOYMaMGUpXeCnrskFnzpzB//73P3zzzTf45ptvarVt8+bN8dtvvyE1NRXOzs4YP348unTpguPHjyvdfycif2jYW35RQSlHAgIC0KFDB1hZWbGOQpRcVlYWxo4dC3t7ezx8+BAhISE4ffo0OnfuXOt99e/fH5s2bcIff/yhdGunKuOQ940bNzB06FD07dsX69atq/N+LC0tcejQoTczwj09PdGnTx8kJiZKMC0h/yUQCJCdnY2YmBjWUchbqKCUExUVFQgKCqLeSSJVJSUl+OGHH9CuXTscP34cf/zxB5KTk+Hl5fWmeKqLyZMnY86cOfjuu+9w9OhRCSZmS9mGvPPz8+Ht7Y2WLVviwIEDUFev/7MtXs8IDwoKQm5uLuzt7TFy5EiaEU6kpkePHjAyMqJhbzlDBaWcOHfuHIqLi6mgJFJRVVWFbdu2wcLCAmvWrMH06dORlpaGr776SiJFBQAsX74c/v7+GDVqlNLcMK9MPZQvXrzA4MGD8ezZM4SEhKBp06YS2zePx4OPj8+bGeHh4eGwsrLCzJkzaUY4kTg+nw9/f38cOXJEKf5tKgsqKOWEUCiEubk5OnXqxDoKUTKnTp1Cly5d8MUXX6B37964desWVqxYIdGCAnh5kN+1axe6dOkCHx8fpeihUpYeSo7j8MUXXyAhIQHHjh1D69atpdLO6xnhaWlpWLRoEbZv3w5zc3OsXLmSZoQTiRIIBMjJycHFixdZRyGvUEEpB0QiEQIDAzFkyJB6DTsS8raUlBR89tln6N+/P3R0dBAXF4e9e/eiVatWUmtTS0sLx44dQ9OmTeHp6YmioiKptSULytJDuXz5cvzzzz/YuXMnnJ2dpd7e6xnh6enp+Pzzz9/cZrFz506aEU4kwtnZGSYmJjTsLUeooJQD0dHRyM/Pp8XMiUQ8fPgQX375JTp16oS0tDQcOXIEUVFRcHBwkEn7BgYGCAsLw6NHj+Dn54eKigqZtCsNytBDefjwYSxcuBCLFy/GiBEjZNr26xnhN27cgLOzMyZMmIDOnTvTjHBSb28Pe9NFinygglIOCIVCtGzZEt27d2cdhSiwsrIy/Pzzz7CwsMDhw4fxyy+/IDU1lUnPt6WlJY4dO4aLFy9i0qRJCls8KPqyQfHx8RgzZgxGjBiBRYsWMcthYWGBQ4cOITY2Fnp6evD09ETv3r1x6dIlZpmI4hMIBMjNzcWFCxdYRyGggpI5sViMgIAA+Pn5vekNIaQ2xGIx/vnnH7Rr1w5LlizBpEmTkJ6ejpkzZ0JTU5NZrp49e2LXrl34559/sGTJEmY56kORh7zv37+PgQMHokuXLtixY4dc3E7j6OiI8PBwBAUFIS8vD927d3/z6EdCasvR0RGmpqY07C0nqIJhLC4uDjk5OTS7m9RJREQEHBwcMGbMGDg4OCA1NRXr1q2Dnp4e62gAgOHDh2P58uVYsmQJdu3axTpOrSnqkPezZ8/g7e2Nhg0bIjAwEFpaWqwjvfH2jPCtW7ciIiIC7du3x8yZM5Gfn886HlEgNOwtX6igZEwoFKJ58+bo0aMH6yhEgdy+fRuDBw+Gh4cH+Hw+IiMjIRQKYWFhwTraf8ydOxcTJ07EpEmTcO7cOdZxakUReyirqqowYsQIZGZmIiQkBM2bN2cd6b3U1dUxadKkN4/5pBnhpC4EAgEePnyIqKgo1lFUHhWUDHEch4CAAAwaNAhqamqs4xAFUFBQgOnTp8PGxgaXL1/G3r17ERsbC1dXV9bRPojH42Hz5s3o1asX/Pz8kJqayjpSjSliD+WsWbNw/PhxHDp0CDY2NqzjVKtx48ZYsGABMjIyMHbsWPzwww+wtLSkGeGkRhwcHGBmZkbD3nKACkqGrl69irt379JwN6nWixcv8Ouvv8LCwgI7d+7E0qVLcfPmTYwcOVIh7r3V0NDA4cOHYWpqCk9PT+Tl5bGOVCOK1kP5559/Yv369di4cSP69+/POk6tfPLJJ9i4cSNu3LiBHj16vJkRHhYWplAFPZEtHo8HgUAAoVAIkUjEOo5Kk/8zkRITCoXQ1dVFr169WEchcorjOBw+fBgdOnTAnDlzMGLECKSnp2Pu3Llo2LAh63i10rRpU4SGhqKiogIDBw5EaWkp60jVUqQeytOnT+Obb77B1KlT8b///Y91nDqzsLDAwYMHERcXBz09PXh5edGMcPJRAoEAjx49QmRkJOsoKo0KSoaEQiEGDhwIDQ0N1lGIHIqNjUXPnj0hEAhgbW2N5ORkbNq0SW7viasJMzMzhISEIDU1FaNGjZL7IU1FWTboxo0b8Pf3R79+/bB27VrWcSTCwcEB4eHhCA4OxsOHD2lGOPkge3t7tG7dmoa9GaOCkpHU1FTcvHmThrvJf9y7dw/Dhw+Hs7MzSkpKcPr0aYSEhKBDhw6so0lE165dceDAAQQFBWHWrFms43yUIgx5P378GF5eXjA1NcWBAwck9mx2ecDj8eDt7Y2kpCRs27YNkZGRaN++PWbMmEEzwskbNOwtH6igZEQoFEJbWxt9+/ZlHYXIieLiYsyZMwft27dHZGQktm/fjsuXL6NPnz6so0mct7c3Nm7ciPXr1+O3335jHeeD5H3I+8WLFxg8eDCeP3+OkJAQ6OjosI4kFerq6pg4cSLS0tKwePFi7NixA+bm5lixYoVC3DpBpE8gECA/Px/h4eGso6gsKigZCQgIgJeXl1ytD0fYqKysxB9//AELCwv8/vvvmDt3Lm7fvo0JEyYo9ez///3vf/j2228xY8YMBAcHs47zXvLcQ8lxHCZNmoRLly7h2LFjUn1Gu7xo1KgR5s+fj4yMDIwbNw6LFi1Cu3btsGPHDrm/fYJIV9euXdG2bVsa9maICkoG7ty5g6tXr9Jwt4rjOA7BwcGwtbXF1KlT4ePjg9u3b2Px4sXQ1tZmHU8m1qxZA19fXwwfPhyJiYms4/yHPPdQ/vzzz9izZw927doFJycn1nFk6pNPPsGGDRvezAifOHEizQhXca+HvQMCAlBZWck6jkqigpIBoVAILS0tfPbZZ6yjEEauXLmC3r17Y+DAgWjZsiUuX76MHTt2wMTEhHU0meLz+dizZw86duwIb29vZGZmso70L/LaQ3no0CH88MMPWLJkCYYNG8Y6DjNvzwjX19eHl5cXPv30UyQkJLCORhgQCAQoKCjA+fPnWUdRSVRQMiAUCjFgwACV6YUi/y87Oxvjxo1Dt27dkJubi5CQEJw+fRqdO3dmHY2ZRo0aISgoCFpaWvDy8kJxcTHrSG/IYw9lXFwcxo4di1GjRuGHH35gHUcuODg44Pz58wgJCcHjx4/h4OCA4cOHIyMjg3U0IkOdO3eGhYUFDXszQgWljGVlZSEuLo6Gu1VMSUkJFi1aBEtLS4SGhuL3339HcnIyvLy83vSCqTJDQ0OEhYUhOzsbQ4cOlZshK3nroczMzMTAgQPRtWtXbNu2jf7uvIXH48HLywtJSUnYvn07oqKiYG1tjenTp9OMcBVBw95sUUEpY0ePHoWGhga8vb1ZRyEyUFVVhe3bt8PS0hKrV6/GtGnTkJ6ejq+//prWH32HtbU1jh49ioiICEyZMkUuegXlqYfy6dOn8PHxQePGjREYGEgT+j5ATU0NEyZMeDMjfOfOnTA3N8fy5ctpRrgKEAgEKCoqwtmzZ1lHUTlUUMqYUChE79690axZM9ZRiJSdPn0aXbt2xaRJk9CrVy/cvHkTK1euRNOmTVlHk1seHh7Yvn07duzYgeXLl7OOIzcLm4tEIowYMQKZmZkICQnBJ598wjSPInh3RvjixYthaWlJM8KVXKdOndCuXTsa9maACkoZevToEaKiomi4W8mlpKTA09MT/fr1Q5MmTRAbG4t9+/ahdevWrKMphM8//xyLFy/GwoULsW/fPqZZ5GXIe9asWTh58uSbx3CSmnt7RrirqysmTpwIOzs7hIaGMr9QIJLH4/Hg7++Po0ePoqKignUclUIFpQwFBgYCAHx9fdkGIVLx8OFDTJkyBZ06dcLt27dx5MgRREVFwdHRkXU0hbNo0SKMGTMG48ePR1RUFLMc8jDkvXnzZmzYsAG//fYb+vXrxyyHojM3N8eBAwcQHx8PAwMDeHt7o1evXjQjXAkJBAI8efIEZ86cYR1FpVBBKUNCoRDu7u40XKVkysrKsHz5clhaWuLgwYP45ZdfkJKSgiFDhtCkiTri8XjYunUrevTogUGDBuHWrVvMcgDseihPnjyJqVOnYtq0afjqq6+YZFA23bt3fzMjPD8/Hw4ODhg2bBjNCFcitra2sLKyomFvGaOCUkaKiopw7tw5+Pn5sY5CJEQsFmPPnj2wsrLCjz/+iAkTJiA9PR0zZ85EgwYNWMdTeJqamhAKhTA0NISnpyceP34s8wwseyhTUlIgEAjQv39/rF27VubtK7N3Z4RHR0e/mRHO4u8ZkazXs70DAwPx4sUL1nFUBhWUMhIcHAyRSITBgwezjkIk4PVQ9ueffw57e3ukpqZi/fr10NfXZx1Nqejq6iIsLAwlJSXw9fVFWVmZTNtn1UP5+PFjeHt7o1WrVjhw4IBSP4KTpbdnhC9ZsgR///03zQhXEgKBAMXFxTh9+jTrKCqDCkoZEQqFcHZ2VrknoSibtLQ0+Pn5wc3NDQAQERGBgIAAWFpaMk6mvFq3bo3g4GBcvXoVY8aMkWlxx6KHsry8HIMGDUJZWRmCg4PRpEkTmbWtqho1aoR58+YhIyMDEyZMeDMjfPv27TQjXEHZ2NjA2toahw8fZh1FZVBBKQPPnj3DyZMnaXa3AissLMSMGTPQoUMHXLp0CXv27EFcXNybwpJIl4ODA/bt2wehUIh58+bJrF1ZLxvEcRwmTpyIy5cv49ixY2jVqpVM2iUvGRgYYP369W9mhE+aNAl2dnYICQmhGeEKhoa9ZY8KShkICwvDixcv6P5JBfTixQusXbsW5ubm2LFjB3766SfcunULo0aNetN7RWRj0KBBWLt2LVavXo0tW7bIpE1ZD3kvXboU+/btw65du2h1AIbenhH+ySefwMfHB7169UJ8fDzraKQW/P398fTpU5w6dYp1FJVAZ0QZEAqF6NKlC9q0acM6CqkhjuNw5MgRdOjQAd9//z2GDx+OtLQ0zJs3Dw0bNmQdT2VNnz4d33zzDf73v//h+PHjUm9PlkPeBw4cwI8//oilS5dCIBBIvT1Sve7du+PcuXMIDQ1Ffn4+HB0daUa4ArGxsYGNjQ3N9pYRKiilrKysDGFhYTTcrUDi4uLg6uoKf39/WFlZITk5GZs3b4ahoSHraCqPx+Nh/fr18PT0hEAgQFJSktTbA6TfQxkbG4tx48Zh9OjRWLBggVTbIrXD4/Hg6emJpKQk7NixAxcuXED79u0xbdo0mhGuAAQCAY4dO4by8nLWUZQeFZRSdurUKTx//pwKSgWQmZmJkSNHwsnJ6c0wSVhYGGxsbFhHI29RU1PDvn370K5dO3h5eSErK0tqbcmih/LevXvw9fWFvb09tm3bRmuXyik1NTWMHz8et2/fxtKlS7Fr1y6Ym5vj559/phnhcszf3//NPAYiXVRQSplQKESHDh3Qvn171lHIBxQXF2Pu3LmwsrLC+fPnsW3bNly5cgV9+/ZlHY18gLa2NkJCQsDn8+Ht7Y1nz55JpR1p91A+ffoUPj4+0NbWxtGjR2n9UgXQqFEjzJ07982M8CVLlryZES4SiVjHI++wtraGra0tDXvLABWUUlRRUYGgoCDqnZRTIpEImzZtgoWFBTZu3Ig5c+YgLS0NEydOpHX/FICRkRHCwsJw9+5dCAQCqZzMpdlDKRKJMHz4cDx48AAhISH0BC0F83pG+M2bN+Hm5kYzwuWYQCBAUFCQzNexVTVUUErRuXPnUFxcTAWlnOE4DiEhIbC1tcU333wDb2/vNwsba2trs45HaqFjx44QCoU4c+YM/ve//0n8RC7NZYO+/fZbnDp1CocPH4a1tbXE909ko23btti/fz8SEhJgaGgIHx8feHh40IxwOeLv74+SkhKcOHGCdRSlRgWlFAUEBKBt27bo1KkT6yjklatXr6JPnz7w8fGBsbExEhMTsXPnTlpwXoH16dMHW7ZswV9//YU1a9ZIdN/SGvL+448/8Ntvv+H333+nWyuUhL29Pc6ePYuwsDAUFhbC0dERAoEA6enprKOpPCsrK9jZ2dGwt5RRQSklVVVVCAwMxJAhQ+gmezmQnZ2N8ePHo2vXrsjJyUFwcDDOnDmDLl26sI5GJGDChAlYsGAB5syZI9EnY0hjyPvEiROYNm0aZsyYgSlTpkhsv4Q9Ho+Hzz77DFevXsWOHTtw8eJFWFtb04xwOSAQCBAcHEwTqKSICkopiYqKwuPHj2m4m7Hnz59j8eLFaNeuHUJCQvD7778jOTkZ3t7eVOgrmaVLl2LkyJH4/PPPcfHiRYnsU9I9lCkpKRg2bBg+++wz/PLLLxLZJ5E/r2eEp6Wl/WdG+PPnz1nHU0n+/v54/vy5TNavVVVUUEqJUChEy5Yt0b17d9ZRVFJVVRV27NgBS0tLrFy5ElOnTkV6ejq+/vpraGhosI5HpIDH42HHjh1wcHCAr6+vRIYaJdlD+ejRI3h7e6N169bYv38/TfxSAQ0bNnwzI3zixIlvZoRv27aNZoTLmKWlJbp06ULD3lJEBaUUiMViBAQEwM/Pjx7Px8Dp06fRtWtXTJw4Ee7u7rh58yZWrlyJpk2bso5GpKxBgwY4evQo9PT04OnpiYKCgnrtT1I9lOXl5Rg0aBDKysoQHByMJk2a1Gt/RLEYGBhg3bp1uHnzJjw8PPDFF1/Azs4OwcHBNCNchgQCAUJCQqiXWEqo2pGC+Ph45OTk0LO7ZSw1NRVeXl7o168ftLW1ERsbi/3796N169asoxEZ0tfXR1hYGIqKijBo0KB6PSFDEj2UHMdhwoQJuHLlCoKCgmBmZlbnfRHF1rZtW+zbt+/NjPCBAwfCw8MDcXFxrKOpBH9/f5SWliIsLIx1FKVEBaUUCIVCNG/eHD179mQdRSU8evQIX331FTp16oSbN2/i8OHDiI6OhqOjI+tohBFzc3MEBQUhISEBEyZMqHMPoyR6KH/66Sfs378fu3fvhoODQ533Q5THuzPCnZycaEa4DJibm6Nbt2407C0lVFBKGMdxEAqFGDRoEN0jJWVlZWVYsWIFLCwscODAAaxevRqpqakYOnQoTbghcHZ2xj///IP9+/dj0aJFddpHfdeh3L9/PxYvXoxly5bB39+/TvsgyuntGeE7d+5ETEwMrK2tMXXqVDx69Ih1PKUlEAgQGhqKkpIS1lGUD0ck6vLlyxwA7uTJk6yjKK2qqipuz549nJmZGaeurs5Nnz6dy8/PZx2LyKnVq1dzALjt27fXetvS0lIOALdnz55ab3vx4kWuQYMG3JgxYzixWFzr7YlqKS0t5VauXMnp6Ohw2tra3NKlS7mSkhLWsZTOnTt3OADcgQMHWEdROtRDKWFCoRDNmjVDr169WEdRSlFRUXBycsLo0aPRrVs3pKamYv369dDX12cdjcipWbNm4csvv8SXX36J06dP12rbug5537t3D76+vujevTv++usv6jEn1WrYsCHmzJmDO3fu4IsvvsBPP/0ES0tLbN26lWaES1CbNm3QvXt3GvaWAiooJUwoFGLgwIG0NI2EpaWlwc/PD25ubhCLxYiIiEBAQAAsLS1ZRyNyjsfj4ffff0efPn0wdOhQXL9+vcbb1mVSTnFxMby9vdGkSRMcPXoUDRo0qHVmorr09fWxdu1a3Lp1C7169cLkyZPRqVMnBAUF0YxwCREIBAgLC8OzZ89YR1EqVFBK0I0bN3Dz5k1azFyCCgsLMXPmTNjY2ODSpUv4559/EB8fDzc3N9bRiAJRV1fHoUOH0KZNG3h6eiInJ6dG29W2h1IkEmHYsGHIyspCaGgoDAwM6pyZqLY2bdpg7969uHTpEoyMjODr6wt3d3eaES4BQ4cORXl5OUJCQlhHUSpUUEqQUCiEtrY2+vXrxzqKwquoqMC6detgYWGBbdu2YfHixbh16xZGjx5Na3uSOmnSpAlCQkIgFovh4+NTo5vya9tDOXPmTJw5cwZHjhxB+/bt65WXEADo1q0bzpw5g+PHj+PJkydwcnKCv78/0tLSWEdTWK1bt4aDgwMNe0sYnZklSCgUwsvLC1paWqyjKCzu1Sz5Dh06YNasWW+W0pg/fz4aNmzIOh5RcC1btkRoaChu376NESNGoKqq6qOfL62ogkbzNnhQqoaUnGI8f/Hhe9l+//13/P7779i0aRP69Okj6ehEhfF4PAwYMABXrlzB33//jdjYWHTo0AHffPMNzQivI4FAgOPHj+Pp06esoygNHkc3ZUjEnTt3YG5ujkOHDtHyIHUUHx+P7777DtHR0fjss8+wZs0a2NjYsI5FlNDx48fh4+ODr776Chs3bvzXpJm0h8+wN+4+zt96hPuFpXj7AMkDYKbXCL2smmOUoxksDZu82Z+3tzemT5+OtWvXyvaXISqnrKwMGzduxIoVK1BVVYXZs2fj22+/RePGjVlHUxiZmZlo3bo19uzZg1GjRrGOoxSooJSQNWvWYNGiRXj8+DG0tbVZx1EomZmZmDdvHvbv3w9bW1v8+uuv6Nu3L+tYRMlt2bIFU6ZMwbp16zBjxgw8KCzF/KPXEJWeDzU+D1XiDx8aX7/vamGAsTaa8OvnDg8PDxw9epTWnyUyU1BQgJ9//hl//PEH9PX1sXjxYkyYMAHq6uqsoykEZ2dnNG/eHMeOHWMdRSlQQSkhzs7OMDQ0RGBgIOsoCqO4uBgrVqzA+vXroauri2XLlmHcuHF0QiYyM2fOHKxZswbfbz76f+3deVSTZ94+8CsJsqqgKKuASEKi1Jlqf74tdlHftur0VEVtdWY6tYtWO1XbY0GsC2oRBRd0qk4du9dtbM+0bp23VrHaWl+1ti7jYUeWACIYQNlkSfL8/uANBRPWBJ4kXJ9zOG0hPM8XTw3XfT/3975xuMARWr3QZpC8n0wC6Brq4ZL6b1w6+DcOJkkUOTk5WLVqFQ4cOACVSoWNGzdiypQp3K6qHdu2bcM777yDkpISuLu7i12OzeMaSgsoKCjAhQsX2N3dQVqtFrt27YJCocD27dsRHR2NzMxMzJ07l2GSelR8fDzGznsXX+Q6oE6r71SYBACdAAiyPrg3cjo+u1TUTVUSta15R7ifnx+mTZuGJ554AhcuXBC7NKv23HPPob6+HseOHRO7FLvAQGkBhw4dQp8+fTBlyhSxS7FqgiDg3//+N373u99h4cKFeOaZZ5CRkYHY2FjO7JAovvy1AAWeo826hmEWaMuJDHxxSW2Jsoi6pHlHeEVFBcLDw9kR3oaAgACMHTuW3d4WwkfeFjB+/Hi4uLjg22+/FbsUq3Xt2jVERkbi1KlTmDBhAhITEzFq1Cixy6JeLL+sBk9t+wF1WuM9Jit+Pozy7z8y+X0DJy9Gvwcnmfyak4MUSUvGIWCgq0VrJeosnU6Hffv2ISYmBkVFRViwYAFWr14NLy8vsUuzKu+99x6io6NRXFwMDw8PscuxaZyhNFNJSQnOnj2LGTNmiF2KVbp58yZeffVVjBo1CgUFBTh69ChOnTrFMEmiW3HoOrTtPOLu4xWMvg/+ocWHU0DrOw9o9QJWHLpu6VKJOk0mk+Gll15Ceno61q9fj3379iEkJATr1q1DdXW12OVZDcNj76NHj4pdis1joDSToTssIiJC3EKsTHV1NdauXQuFQoFjx45hx44duH79OheKk1XILK7E2SxNu2smnYN+D8/JC1t8OHoOafX1Or2As1kaZJXwSDeyDi4uLoiOjsaNGzcwf/58xMXFQS6X44MPPuAZ4QD8/f3x2GOP8bG3BTBQmumrr77CE088gcGDB4tdilXQ6XT45JNPoFAoEB8fj0WLFiErKwsLFy7k+eZkNfZfVEMm7djARltZCr22vsPXlkkl2HeBaynJunh6eiIxMRHp6el48sknsWDBAowcORJHjhzp9WeEz5o1CydOnEB5ebnYpdg0BkozlJeX49SpU+zu/j9JSUl46KGHMHfuXDzxxBNIS0vDxo0buR0DWZ3T6SUd6uiuvHQYhX9/CflbZkC9bTaqrp9q93t0egGnM3h6CVknw2bev/76K/z9/REREdHrO8JnzpwJrVbL/SjNxEBphmPHjkGr1WL69OlilyKq1NRUPPvss3j66afh6uqK8+fP4+DBgwgODha7NCIjVXVaqMtq2n5RHyfI+g6E2wNPon/4LDgHj4ZQV4PSf29DdfIP7d5DXVrT5jGNRGIbPXo0Tp48iePHjzd1hD/33HPIyMgQu7Qe5+fnh8cff5yPvc3EQGmGr776CuHh4fD39xe7FFGUlJTgjTfewMiRI5GSkoIvv/wS586dwyOPPCJ2aUStyiutRntzk/1H/QFDFu3BoGeXYMC4OfCeHQuvP64DAJQl7W73HgKA3FI2PpB1k0gkmDRpEi5fvozPP/8cP//8M8LCwrBw4UIUFxeLXV6PmjVrFk6ePImysjKxS7FZDJRdVFlZie+++65XdnfX1tYiISEBcrkcBw4cwMaNG5Gamornn3+eDTdk9epNbBPUES5DH4Ss/2Do71V0aE1lV+9D1NNkMhnmzJmD9PR0bNiwAfv374dcLkdsbCyqqqrELq9HzJw5EzqdjqfdmYGBsou+/fZb1NXV9ar1k3q9HgcOHIBSqURMTAxeeeUV3LhxA5GRkXBychK7PKJW6XQ6ZGRk4PDhw9j72addvo7MzQMAoK+paPe1x//nG1y4cAF37tzp8v2IepKLiwuWLl2K7OxsLFiwAOvXr4dCocDu3bvtviPcx8cH48aN42NvM3Bj8y6aPXs2MjMzcfnyZbFL6RE//fQT3n77bVy6dAkRERHYuHEjQkNDxS6LqAWdTofs7GwkJycjJSUFycnJSE5ORlpaGurq6gAAHoO84T73I6ALs+kFO+dAV1WGgOjDkEodWn+hIEC99XkIDbUAAG9vb6hUKgwfPhwqlarpIyAgAFIpx/VknXJzc7Fq1Srs378fKpUKCQkJmDp1qt0+idq1axcWL16M4uJieHp6il2OzWGg7IJ79+5h8ODBWL58OVauXCl2Od0qKysLy5Ytw9dff42HHnoIiYmJGDdunNhlUS+n0+mQk5PTFBgN4TEtLQ21tY0hzsPDA2FhYRgxYgTCwsKaPnx8fDB+yxnktdGYU6/Jh+OggBafq049C82RjZC6eSBg8b426wvydMW3bzyMjIwMpKWltfhIT09vqtHFxQVKpbJFyFSpVAgNDYWLi4uZf0pElnH58mUsW7YMSUlJePTRR7F582aEh4eLXZbFFRcXw8/PD7t378a8efPELsfmMFB2wZEjRxAREYHU1FSoVCqxy+kWZWVliIuLw86dO+Ht7Y34+Hj8+c9/5mwK9SidTofc3Nym4GgIj6mpqU2hzN3dvSksNg+Pvr6+rc6krD2ajL0X81rdOki9bTYkMgc4egVD6jYADbfz0FCSDQAYPHM1XBX/1WrNMqkELz4chLVTTZ+oo9froVarkZqaahQ2S0oatxuSSCQICgoymtFUqVQYPHiw3c4QkXU7ceIEoqOjce3aNcyYMQPx8fF296TqySefhEwmw4kTJ8QuxeYwUHbBnDlz8MsvvyAlJUXsUiyuvr4e77//PmJjY9HQ0IDly5djyZIlnC2hbqXX65GTk9PiMbVhxvHevXsAgP79+7eYaTQESD8/v04HrMziSjz9tx9b/XrJ1xtQm3O56ZE1JBLI+nvB8w+L4TL0wXavn7TkCci9+nWqJqBxIJeenm4UNG/cuAGdTgcAGDBggFHIVKlUGDZsGBwc2ngMT2QBer0e+/fvx8qVK3Hz5k3Mnz8fa9asgbe3t9ilWcTu3buxcOFCFBUV8cCSTmKg7KT6+np4e3tj0aJFWLdundjlWIwgCDh06BCWLVuG7OxszJs3D7GxsXbzJkHWQa/XIzc31yg4pqamtgiO9z+mDgsL61JwbMuLH1/E/2aXdmiD846SSSUYO8wTe+c+bLFrAo3vO1lZWUZBMy0tDZWVjcc89unTBwqFwihoKpVK9O/f36L1ENXW1mLnzp1Yv349tFotoqKiEBkZib59+4pdmllu374NHx8f7Nq1C/Pnzxe7HJvCQNlJ3333HSZPnowrV67gwQcfFLsci7h06RIiIyNx9uxZTJ48GZs3b8YDDzwgdllkw/R6PfLy8ozWOKampqKmpnHtYr9+/UyucfT39++RR7r5ZTV4atsPqLPg9j5ODlIkLRmHgIGuFrtmWwRBQFFRkVHITE1NRUFBQdPr/Pz8TM5qDhkyhI/PySxlZWXYsGEDduzYgQEDBuDdd9/F3LlzbXq2/Omnn4YgCEhKShK7FJvCQNlJ8+fPx6lTp5CVlWXzb8RqtRrLly/HgQMHMHLkSGzZsgUTJ04UuyyyIYb1gKbWOFZXN27s3a9fv6bQ2Dw8WkOYOXhJjXe+vm6x622cMRKzxwRa7HrmqKysNNkUlJGRgfr6xn003dzcTAZNuVwOZ2dnkX8CsiW5ubmIiYnBvn37oFQqkZCQgGnTpon+d7wrPvzwQ7z++usoKiqCl5eX2OXYDAbKTtDpdPD19cXLL7+MTZs2iV1Ol1VUVCA+Ph7btm3DgAEDsG7dOrzyyiuQyWRil0ZWSq/XIz8/v0VwNMw4GoJj3759WwRGw78HBARY9S+VnaczseWE+cfNLZ2oxMIJcgtU1L0MjU7NZzMN/zScEiKVShEcHNwiZBoahLidCrXlypUrWLZsGU6ePImxY8di8+bNGDt2rNhldYpGo4GPjw927tyJ119/XexybAYDZSecOXMGEyZMwPnz523yeEGtVouPPvoIq1evRlVVFaKiohAdHW3za17IcgRBgFqtNrnG0XBihpubm9Fj6hEjRiAwMNCqg2NbDl5SY83RZGj1QqfWVMqkEjhIJYidGmY1M5Pm0Gg0Jtdp5uTkQK9vXBowaNAgk7OaQ4cO5aCUmtzfEb5hwwYolUqxy+qwiRMnQqvV4vvvvxe7FJvBQNkJb775Jr7++muo1Wqb2j5HEAR8++23WLp0KVJTUzFnzhzExcVhyJAhYpdGIhEEoWnGsXl4TElJMQqO94dHe92MO7+sBisOXcfZLA1kUkmbwdLw9cflg7Bh+sgeWzMpltraWmRlZZnc6siwJtbJyampKaj5dkehoaEctPZSho7wVatWobCw0KY6wj/66CMsWLAAhYWF8PHxEbscm8BA2UF6vR6BgYGYMWMGtm/fLnY5HXbt2jVERUUhKSkJ48ePR2JiIkaPHi12WdRDBEFAQUGBUXNMSkpKU3ewq6uryTWOgYGBdhkc25NZXIn9F9U4nVECdWkNmr9BSgAEerpiQqgX/vJIYJe2BrIner0ehYWFJmc1b9682fS6gIAAk7Oabe0VSvajeUd4Q0MDli5davUd4aWlpfD29sb27dvxxhtviF2OTWCg7KALFy4gPDwcZ86csYmTYm7evImYmBh8+umnUCgU2Lx5M6ZMmcI3bzslCAIKCwuNmmNSUlJQUdF47rSrqyuGDx9utMYxKCioVwbHjqiu0yK3tBr1Wj0cHaQY6ukGNyfb7V7tSRUVFSaDZmZmZtO50P369TNao6lSqRASEgJHR0eRfwKytLKyMsTHx2P79u0YMGAA1q5di7lz56JPnz5il2bS5MmTUVtbizNnzohdik1goOygpUuX4vPPP0dRUZFVrxOqrq7Gli1bsGnTJri4uGDt2rVYsGCB1f6Fpc4RBAE3b940ao5pHhxdXFxaBEdDeBw6dCiDI4muoaEBOTk5RtscpaWl4c6dOwAAmUyGkJAQk7OaAwYMEPcHILPl5eU1dYSHhoYiPj4eERERVjfh8cknn2DevHkoLCyEr6+v2OVYPQbKDhAEASEhIXjqqafwwQcfiF2OSTqdDnv27MGqVaug0Wjw1ltvYcWKFfDw8BC7NOoCQ3C8vzkmJSUFd+/eBfBbcLx/jSODI9kiQRBQUlJiclYzLy8Phl9VXl5eRjOaKpWq1y7RsGXW3hFeVlYGb29vbNu2DYsWLRK7HKvHQNkBV65cwejRo3H8+HFMmjRJ7HKMfP/994iMjMTVq1cxe/ZsxMfHIzg4WOyyqAMMG1Obao4xzNY4Ozs3zTg2D4/sqqXeoqamBpmZmS1mM9PS0pCent50pruzszOUSqXRjGZoaChcXe27acrWNe8Inz59OuLj462mI/yZZ55BVVUVfvyx9aNaqREDZQfExMRg586dKC4utqp1PWlpaVi6dCm++eYbhIeHY+vWrTa5nVFvIAgCbt26ZdQck5yc3CI4qlQqozWOwcHBDI5EJhg21jc1q1lcXAwAkEgkCAoKMvn43MvLy+oes/ZWer0eBw4cwMqVK1FYWIjXXnsNa9asEb3D+rPPPsOrr76KgoIC+Pn5iVqLtWOg7IARI0ZgzJgx+Pzzz8UuBUDjWaNr167F7t27ERgYiI0bN+K5557jG6MVEAQBxcXFJtc4lpeXA2jcXqV5cDSEx2HDhjE4EllIeXm5yaB548YN6HQ6AICHh4dRyBw+fDiCg4O57lwktbW1+Pvf/464uDg0NDQgKioKUVFRonWEl5eXw9vbG4mJiVi8eLEoNdgKBsp2pKamYsSIEThy5AimTp0qai21tbV47733sGHDBkgkEqxatQqLFy+Gk5OTqHX1Rob1XqaCo+G0EUdHR6PgGBYWxuBIJKL6+nrcuHHD5Pnnhq20+vTpA7lcbhQ2lUol3N3dRf4JegdDR/iOHTvg4eEhakf4s88+i7t37+Ls2bM9fm9bwkDZjri4OCQkJECj0Yh2tq0gCDh48CCWL1+OwsJC/PWvf8Xq1asxaNAgUerpTZoHx/sbZEwFx+ZrHIcNGwYHB24xQ2QLDOuZTc1q5ufnN73O19fX5JGU1nA2vT1q3hGuUCiQkJDQ4x3he/bswUsvvYSCggL4+/v32H1tDQNlO0aNGoXQ0FB88cUXotz/3LlzePvtt/Hzzz9j2rRp2LRpE0JDQ0Wpxd41n3FsHh5LS0sBNAZHpVJptMYxJCSEwZHIjlVVVSEjI8Nom6OMjAzU19cDaDxZylRTkEKhEG0ywp5cvXoVy5Ytw4kTJzB27Fhs2rQJjz76aI/c+86dO/D29samTZvw1ltv9cg9bREDZRuys7MREhKCL774ArNmzerRe9+4cQPvvPMO/vWvf2H06NFITEzE+PHje7QGe3X79m2jx9TJycnQaDQAGh93NQ+OhvAol8sZHImoiU6nQ25urslZTcP7iUQiQXBwsMkN3PmUqfNOnjyJ6OhoXL16FREREYiPj4dKper2+06dOhWlpaU4d+5ct9/LVjFQtmHLli2IiYnB7du3e2xBcHl5OeLi4rBjxw54e3tjw4YNeOGFF7i/WhdoNBqTaxxv374NoDE4hoaGGq1xDAkJ4YJ8IjKLRqNBenq60fnnOTk50Ov1AABPT0+T3edDhw7l4LUNer0e//znP7Fy5UoUFBT0SEf4vn378OKLL0KtViMgIKDb7mPLGCjbEB4eDm9vbxw+fLjb71VfX49du3YhNjYWdXV1WL58OZYsWcL90zpAo9EYrW9MTk5uCo4ODg5NM47N1zjK5XIGRyLqUbW1tcjKyjI5q1ldXQ2gcXmNQqEw2rxdqVRa9fnXPc3QEb5+/XrU19cjKioKkZGR6Nevn8XvVVFRAS8vL8THx2PJkiUWv749YKBsRUFBAQICArBnzx68+OKL3XYfQRBw+PBhREdHIzs7G3PnzkVsbKzoe29Zo9LSUpPNMSUlJQAag2PzGUdDeFQoFAyORGTVBEFAQUGByaB58+bNptcNGTLE5Kymn59fr20KKi8vbzoj3N3dHWvXrsW8efMs/r4fERGB4uJinD9/3qLXtRcMlK3YsWMH3n77bZSUlHTb2bG//PILIiMj8eOPP2LSpEnYsmULHnjggW65ly0pKysz2Rxj2KjYwcEBCoXCaI2jQqGwqo3niYgsoaKiAunp6UZBMzMzEw0NDQCAfv36mQyacrm817wvqtVqxMTEYO/evVAoFIiPj8f06dMtFrQPHDiAF154Abm5uQgKCrLINe0JA2Urxo8fD2dnZxw/ftzi11ar1VixYgX279+PBx54AFu2bLHKIx27W3l5uck1jrdu3QIAyGQyo+BomHHsLW+QREStaWhoQE5Ojsk9NQ0ncMlkMgwbNsxk2Bw4cKC4P0A3uXbtGpYtW4bvvvsO4eHh2Lx5s0U6wisrKzF48GCsX78ekZGRFqjUvjBQmlBSUgJfX1/84x//wGuvvWax61ZWViIhIQFbt26Fu7s71q1bh1deecXuF1/fuXPHZHAsKioC8FtwbL6+MSwsDKGhoQyORESdJAgCbt++bRQy09LSkJeXB8OvfS8vL5NBMzAw0C4OX0hKSkJ0dDSuXLlisY7wGTNmoLCwEBcvXrRQlfaDgdKEDz/8EK+//jpu3bqFwYMHm309rVaLjz/+GKtXr0ZlZSUiIyMRHR3dLQuHxWQIjvevcWweHOVyuVFzTGhoKE/7ISLqATU1NcjMzDSa1UxPT8e9e/cAAM7OzggNDTXawD00NNTmGkXv7wifN28e1qxZA19f3y5d7+DBg/jTn/6EnJwcDPYdgtzSatRr9XB0kGKopxvcnOx7gqgtDJQmTJ48GXV1dTh9+rRZ1xEEAcePH0dUVBRSUlIwZ84crF+/HkOGDLFQpeK4e/euyTWOhoXjUqm0KTg2D49KpZLBkYjICun1euTn57eYzTR8GNavA0BQUJDJWU1vb2+rbgqqra3F+++/j7i4ONTV1TWdEd7ZiZ1rOcV4+q+x8HnoKVTqHdE8QEkABA50xQSlF154OBAKb/uaNGpPrw+U1XXaFiMMD1kDhg7xxdatW806CP4///kPoqKicPLkSYwfPx6JiYkYPXq0BSvvfnfv3m0RGA3/XlhYCKAxOIaEhBg1xyiVSp4MQURkJ8rLy002BWVlZUGn0wEA3N3dTW7ePmzYMKvaZaO8vBwJCQl477334O7ujjVr1uC1115rt8b8shqsOHQdZ7M0gKAHJK3vDS2TSqDTC3hcPggbpo9EwEDbmtXtql4ZKDOLK7H/ohqn00ugLqtByz8AAQ3lRfjTuN9hwX+P6PQIo6ioCDExMfj0008hl8uxefNmTJkyxapHbhUVFUaPqVNSUlBQUADgt+B4/xpHBkciot6rvr4eN27cMLnVUUVFBYDGXTnkcrnJWU13d3fRaler1Vi9ejX27NkDuVyO+Ph4zJgxw+Tv6oOX1FhzNBlavQCdvuORSSaVwEEqwbtTw/DHMYGWLN8q9apA2XyEYRhBtKazI4zq6mokJiZi06ZNcHZ2xtq1a7FgwQKrGplVVFQgNTXVKDjm5+cDaDwizDDj2Dw8KpVKuLi4iFw9ERHZAkEQcOvWLZNBU61WN73Ox8fHaPN2lUqFIUOG9NjpcPd3hG/atAmPPfZY09d3ns7ElhMZZt8namIoFk1QmH0da9ZrAmV3jTD0ej327t2LFStWQKPR4M0338TKlSvh4eFhweo7p7KyEikpKUazjs2D47Bhw4zWOKpUKgZHIiLqNlVVVcjIyDAKmhkZGairqwMAuLq6QqlUGgVNhULRbb+jmneET5s2DQkJCbha6Yp3vr5usXtsnDESs+14prJXBMruGmGcPn0akZGRuHLlCmbNmoWEhAQEBwebfZ+OqqqqagqNzcOjYQQokUgQHBxstMZRpVLZXKceERHZL51Oh7y8PKNtjtLS0qDRaAD89jvN1OPzQYMGmb20TK/X4+DBg1ixYgWKKuvh/9o/oJe0vn1SVfJplJ/6GPqaO42fkPWBS8gYeM1YYfL1Tg5SJC0ZZ7drKu0+UB68pLb4COP3/WoQHR2NY8eO4ZFHHsHWrVsRHh5usXvcr6qqqsWjakN4zMvLA/DbX7L71zgyOBIRka3TaDQmm4Kys7Oh1+sBAAMHDjQZNIODgzu913NdXR2eWn8E6jpnSKSmA+Wd81/i7g97IOnjDOeg30Pi5Apt+U1A0MP3pW0mv0cmlWDsME/snftw5/4AbIRdB8r8sho8te0H1Gn17b62+OAq1OZeBWR9ELT0UKuvkwo6FH74OvzdnZGQkIDnn3/eYg031dXVJtc45ubmNr3GMOPYPDyqVCq4ublZpAYiIiJbUFdXh6ysLKNtjtLS0lBdXQ0AcHR0hEKhMAqaSqWy1S2DMosr8fTffmz1vtoKDQp3vQKp2wD4v/EJpNLOBdakJU9A7mV/WwrZ9Q6cKw5dh7YD6yXrbmY0hskO0AnAfy3chqSVEV3eU7G6uhppaWlGp8c0D45Dhw5FWFgYZs2a1RQehw8fzuBIREQEwMnJqWlipTlBEFBYWGgUMj/77LOmbe8AwN/f3yhoDh8+HPt+LW+zcbf8zCeAIMBz0iJIpQ7QVt+B1KVvh4KlTCrBvgtqrJ0a1u5rbY3dzlC2N8JoruD9lyHU10IQ9BC0DW3OUBp0ZIRRU1OD1NRUo+aY3NzcpqOvgoKCjNY4Dh8+HH379u1Q7URERNQxFRUVJh+fZ2ZmoqGhAQAw5PWPIPPwafUaBTvnQFdVBo/xL+POj/sAvRYA4DAoAL5/2Qypc9u/v4M8XfFD1ATL/VBWwm5nKPdfVLe7NRAAVPxyFLoKDQZFLEfpt+916Nr3jzBqampazDgaAmROTk6L4DhixAjMnDmzKTwyOBIREfWc/v37Y8yYMRgzZkyLz2u1WuTk5OBqchqWXmx7GZvuXiUA4M6Zz9BncDBcgkfhXs4VNNzOwc1PFmPIG5+2+f3q0hpU12nt7phG+/ppmjmdXtJumNRr61F++lM4eAbATfVohwOlTi/gX+dTceXjFUhOTkZ2dnZTcAwMDERYWBimT5/eIjja27ndRERE9sLBwQEKhQL1bl7AxZ/afrHQ2JfhMCgAfnN3AAAGACj88K/QlubjXs5luAS3fjKeACC3tBphfuJt7N4d7DJQVtVpoS6rafd1pd9sBXQNGDzddIt/WyoFZ9RqBURERDStcRwxYgSDIxERkY2q70ATb+Oxizr0e/APLT7db9QfUJ70AWrSzrUZKDt8Hxtjl4Eyr7Qa7S0MrS8rRE3aT3AJGQPHQQGdvodEIsHWD/fa3QiDiIiot3J0aP+EHmkfZ+h1DegzwK/F5x0G+AIAdDUVFrmPrbG/nwgdS/63v44DpDIMmra0W+9DREREtmGopxva2wjQYWBjkKzXqFt8vkHTeBqdrO/ANr9f8n/3sTd2GSjbS/73ci5Dq8mHi/wR1N/KQa06GbXqZECvBwQBtepkNJQXmX0fIiIish1uTg4IbOckm/4PTQUAVP76TYvPG/677++fbvP7Az1d7a4hB7DTR96GEUZrj70bbjeOKu5lnMO9jHNGXy8+sAx9vIbB79Xtrd7DXkcYREREvdkEpRf2XsxrtbHXLWwc7vy0H9rymyj4+8tw8h+OusJU6Co1cPRXwclH3uq1ZVIJJoR6dVfporLLQGkYYeS10pjjHPL/0N9w9mYzFZeOAHod+j88A44+CuNvbMZeRxhERES92QsPB+Kz87ltvsb3le0o+de7qMtPRk3aWUAqg4viEXjNXNXm9+n0Av7ySKAFq7UedpuI2hphOHoOgeP4l40+X3nlfyBogQEmvtacPY8wiIiIejOFdz88Lh+E/80ubXWWUuroDJ8/x3fquoazvO3x2EXATtdQAo0jjPb2oewqex5hEBER9XYbpo+Eg7S99pzOcZBKsGH6SIte05rYbaA0jDBknfgfInDJl+0euyiTSvC4fJDdjjCIiIh6u4CBrnjXwudtx04NQ0A7DT+2zG4DJcARBhEREXXNH8cEImpiqEWutXSiErPH2PeTTbsOlBxhEBERUVctmqBAwoyRcHKQduqJJ9D4RNPJQYqNM0Zi4YTWO7/thUQwHEJtx3aezsSWExlmX2fpRGWv+J+CiIiIfpNfVoMVh67jbJYGMqmkzR4Nw9cflw/Chukje80kVK8IlABw8JIaa44mQ6sXOtWsI5NK4CCVIHZqmN1PVxMREVHrMosrsf+iGqczSqAurWmx37UEjVsKTgj1wl8eCex1vRa9JlACHGEQERGRZVTXaZFbWo16rR6ODlIM9XTr1ftT96pAacARBhEREZHl9MpA2RxHGERERETm6fWBkoiIiIjMY9fbBhERERFR92OgJCIiIiKzMFASERERkVkYKImIiIjILAyURERERGQWBkoiIiIiMgsDJRERERGZhYGSiIiIiMzCQElEREREZmGgJCIiIiKzMFASERERkVkYKImIiIjILAyURERERGQWBkoiIiIiMgsDJRERERGZhYGSiIiIiMzCQElEREREZmGgJCIiIiKzMFASERERkVkYKImIiIjILAyURERERGQWBkoiIiIiMgsDJRERERGZhYGSiIiIiMzCQElEREREZmGgJCIiIiKzMFASERERkVkYKImIiIjILAyURERERGQWBkoiIiIiMgsDJRERERGZhYGSiIiIiMzCQElEREREZmGgJCIiIiKzMFASERERkVkYKImIiIjILAyURERERGSW/w8oQ4VEp4t0VgAAAABJRU5ErkJggg==", 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", "text/plain": [ "
" ] @@ -498,8 +356,8 @@ } ], "source": [ - "solution = optimization_result.solution[optimization_result.cost.idxmax()]\n", - "solution_nodes = [v for v in graph.nodes if solution[v]]\n", + "solution = optimization_result.solution[optimization_result.cost.idxmin()]\n", + "solution_nodes = [v for v in graph.nodes if solution[f\"x_{v}\"]]\n", "solution_edges = [\n", " (u, v) for u, v in graph.edges if u in solution_nodes and v in solution_nodes\n", "]\n", @@ -516,7 +374,7 @@ }, { "cell_type": "markdown", - "id": "d4d30ce4-f2b3-4049-b0e0-3cdc7b4897a1", + "id": "687f492b-a4a5-49c6-964c-8959b035bb93", "metadata": {}, "source": [ "And the histogram:" @@ -524,70 +382,87 @@ }, { "cell_type": "code", - "execution_count": 12, - "id": "c3233840-123c-4e29-8368-87ea3c135863", + "execution_count": 13, + "id": "31a4e74d-b2b8-42e0-826d-de7b51de1fe8", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:57.016876Z", - "iopub.status.busy": "2024-05-07T15:48:57.015879Z", - "iopub.status.idle": "2024-05-07T15:48:57.334652Z", - "shell.execute_reply": "2024-05-07T15:48:57.333914Z" - }, "tags": [] }, "outputs": [ { "data": { + "image/png": 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", "text/plain": [ - "array([[]], dtype=object)" + "
" ] }, - "execution_count": 12, "metadata": {}, - "output_type": "execute_result" - }, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "optimization_result[\"cost\"].plot(\n", + " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + ")\n", + "plt.ylabel(\"Probability\", fontsize=16)\n", + "plt.xlabel(\"cost\", fontsize=16)\n", + "plt.tick_params(axis=\"both\", labelsize=14)" + ] + }, + { + "cell_type": "markdown", + "id": "a3a890a1-c5d4-409d-b9a3-d7ffd4fdd6c0", + "metadata": {}, + "source": [ + "Let us plot the solution:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", + "metadata": { + "tags": [] + }, + "outputs": [ { "data": { - "image/png": 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", "text/plain": [ - "
" + "{'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4': 0, 'x_5': 1, 'x_6': 0}" ] }, + "execution_count": 14, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" + "best_solution = optimization_result.solution[optimization_result.cost.idxmin()]\n", + "best_solution" ] }, { "cell_type": "markdown", - "id": "896bd3ad-ac54-4e21-b654-ba00743ece86", + "id": "149932e1-bfa8-4c27-b5f9-037e74eba400", "metadata": {}, "source": [ - "Lastly, we can compare to the classical solution of the problem:" + "## Comparison to a classical solver" ] }, { "cell_type": "markdown", - "id": "c9b54c5b-10e5-4f9c-9e00-44ac2cf24a33", + "id": "dde1905d-aeff-4297-a9d3-ad14910e6161", "metadata": {}, "source": [ - "## Classical optimizer results" + "Lastly, we can compare to the classical solution of the problem:" ] }, { "cell_type": "code", - "execution_count": 13, - "id": "dd5a1911-0eea-47fc-82f6-8942c8a4eac8", + "execution_count": 15, + "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:57.339572Z", - "iopub.status.busy": "2024-05-07T15:48:57.338409Z", - "iopub.status.idle": "2024-05-07T15:48:57.474823Z", - "shell.execute_reply": "2024-05-07T15:48:57.474130Z" - }, "pycharm": { "name": "#%%\n" }, @@ -598,28 +473,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Model unknown\n", - "\n", - " Variables:\n", - " x : Size=7, Index=x_index\n", - " Key : Lower : Value : Upper : Fixed : Stale : Domain\n", - " 0 : 0 : 1.0 : 1 : False : False : Binary\n", - " 1 : 0 : 1.0 : 1 : False : False : Binary\n", - " 2 : 0 : 1.0 : 1 : False : False : Binary\n", - " 3 : 0 : 1.0 : 1 : False : False : Binary\n", - " 4 : 0 : 0.0 : 1 : False : False : Binary\n", - " 5 : 0 : 3.9960192291414966e-08 : 1 : False : False : Binary\n", - " 6 : 0 : 0.0 : 1 : False : False : Binary\n", - "\n", - " Objectives:\n", - " value : Size=1, Index=None, Active=True\n", - " Key : Active : Value\n", - " None : True : 4.0000000399601925\n", - "\n", - " Constraints:\n", - " clique_constraint : Size=1\n", - " Key : Lower : Body : Upper\n", - " None : 0.0 : 7.992038458282993e-08 : 0.0\n" + "Classical solution: [1, 1, 1, 1, 0, 0, 0]\n" ] } ], @@ -628,27 +482,23 @@ "\n", "solver = SolverFactory(\"couenne\")\n", "solver.solve(max_clique_model)\n", - "\n", - "max_clique_model.display()" + "classical_solution = [\n", + " int(pyo.value(max_clique_model.x[i])) for i in range(len(max_clique_model.x))\n", + "]\n", + "print(\"Classical solution:\", classical_solution)" ] }, { "cell_type": "code", - "execution_count": 14, - "id": "5fccfe7a-4567-4c2c-8287-1cae1b75e875", + "execution_count": 16, + "id": "79666d4d-e105-4706-b44e-e5c73b928af3", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:48:57.479695Z", - "iopub.status.busy": "2024-05-07T15:48:57.478528Z", - "iopub.status.idle": "2024-05-07T15:48:57.808411Z", - "shell.execute_reply": "2024-05-07T15:48:57.807685Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -673,6 +523,24 @@ " edge_color=\"r\",\n", ")" ] + }, + { + "cell_type": "markdown", + "id": "e82b5953-122a-4707-8ab6-f741f14f13a5", + "metadata": { + "pycharm": { + "name": "#%% md\n" + }, + "tags": [] + }, + "source": [ + "\n", + "## References\n", + "\n", + "[1]: [Farhi, Edward, Jeffrey Goldstone, and Sam Gutmann. \"A quantum approximate optimization algorithm.\" arXiv preprint arXiv:1411.4028 (2014).](https://arxiv.org/abs/1411.4028)\n", + "\n", + "[2]: [Barkoutsos, Panagiotis Kl, et al. \"Improving variational quantum optimization using CVaR.\" Quantum 4 (2020): 256.](https://arxiv.org/abs/1907.04769)\n" + ] } ], "metadata": { @@ -691,7 +559,12 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" + }, + "vscode": { + "interpreter": { + "hash": "a07aacdcc8a415e7643a2bc993226848ff70704ebef014f87460de9126b773d0" + } } }, "nbformat": 4, diff --git a/applications/optimization/max_clique/max_clique.qmod b/applications/optimization/max_clique/max_clique.qmod index 72f12c9ab..f2779147b 100644 --- a/applications/optimization/max_clique/max_clique.qmod +++ b/applications/optimization/max_clique/max_clique.qmod @@ -1,755 +1,22 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=30.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-6.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-6.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-8.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-17.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-23.5 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-23.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=16.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=7.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=9.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=9.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=13.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=13.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=-2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-4.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-4.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-3.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-3.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=-3.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-3.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - } -]; - -qfunc main(params_list: real[40], output target: qbit[7]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + x_0: qbit; + x_1: qbit; + x_2: qbit; + x_3: qbit; + x_4: qbit; + x_5: qbit; + x_6: qbit; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=True, -initial_point=[0.0, 0.0683371298405467, 0.0035966910442392997, 0.0647404387963074, 0.007193382088478599, 0.0611437477520681, 0.0107900731327179, 0.057547056707828795, 0.014386764176957199, 0.053950365663589496, 0.017983455221196498, 0.050353674619350204, 0.0215801462654358, 0.0467569835751109, 0.0251768373096751, 0.0431602925308716, 0.028773528353914397, 0.0395636014866323, 0.032370219398153696, 0.035966910442393, 0.035966910442392995, 0.0323702193981537, 0.0395636014866323, 0.028773528353914397, 0.0431602925308716, 0.025176837309675102, 0.04675698357511089, 0.021580146265435807, 0.0503536746193502, 0.0179834552211965, 0.053950365663589496, 0.014386764176957199, 0.057547056707828795, 0.010790073132717903, 0.061143747752068094, 0.007193382088478607, 0.06474043879630739, 0.0035966910442393036, 0.0683371298405467, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=1, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=1 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[40], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 20) { + phase (-((((((((-v.x_0) - v.x_1) - v.x_2) - v.x_3) - v.x_4) - v.x_5) - v.x_6) + (2 * ((((((((2 * v.x_0) * v.x_5) + (v.x_1 * v.x_4)) + (v.x_2 * (v.x_4 + v.x_6))) + (v.x_3 * v.x_6)) + (v.x_4 * ((v.x_1 + v.x_2) + v.x_6))) + (v.x_6 * ((v.x_2 + v.x_3) + v.x_4))) ** 2))), params[i]); + apply_to_all(lambda(q) { + RX(params[20 + i], q); + }, v); + } +} diff --git a/applications/optimization/max_clique/max_clique.synthesis_options.json b/applications/optimization/max_clique/max_clique.synthesis_options.json index 0967ef424..bcb7020f0 100644 --- a/applications/optimization/max_clique/max_clique.synthesis_options.json +++ b/applications/optimization/max_clique/max_clique.synthesis_options.json @@ -1 +1,43 @@ -{} +{ + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "sx", + "y", + "cy", + "t", + "sdg", + "p", + "cz", + "s", + "id", + "u", + "r", + "rz", + "ry", + "rx", + "u2", + "u1", + "cx", + "tdg", + "sxdg", + "h", + "z", + "x" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 264602322 + } +} diff --git a/applications/optimization/set_partition/set_partition.ipynb b/applications/optimization/set_partition/set_partition.ipynb index 2e21044d2..e5c00499d 100644 --- a/applications/optimization/set_partition/set_partition.ipynb +++ b/applications/optimization/set_partition/set_partition.ipynb @@ -34,12 +34,6 @@ "execution_count": 1, "id": "49a9588b-e79e-4813-b7c5-ac068d7b930c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:41.367157Z", - "iopub.status.busy": "2024-05-07T16:03:41.366691Z", - "iopub.status.idle": "2024-05-07T16:03:42.091526Z", - "shell.execute_reply": "2024-05-07T16:03:42.090734Z" - }, "tags": [] }, "outputs": [], @@ -47,7 +41,6 @@ "import networkx as nx\n", "import numpy as np\n", "import pyomo.core as pyo\n", - "from IPython.display import Markdown, display\n", "from matplotlib import pyplot as plt" ] }, @@ -66,17 +59,13 @@ "execution_count": 2, "id": "48889b21-557b-481c-80c5-3c0b5c91adb6", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:42.097597Z", - "iopub.status.busy": "2024-05-07T16:03:42.095951Z", - "iopub.status.idle": "2024-05-07T16:03:42.103326Z", - "shell.execute_reply": "2024-05-07T16:03:42.102649Z" - }, "tags": [] }, "outputs": [], "source": [ "# we define a matrix which gets a set of integers s and returns a pyomo model for the partitioning problem\n", + "\n", + "\n", "def partite(s) -> pyo.ConcreteModel:\n", " model = pyo.ConcreteModel()\n", " SetSize = len(s) # the set size\n", @@ -98,12 +87,6 @@ "execution_count": 3, "id": "69359e3e-ed85-4b56-9afb-9dd4b9997ada", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:42.107922Z", - "iopub.status.busy": "2024-05-07T16:03:42.106745Z", - "iopub.status.idle": "2024-05-07T16:03:42.115540Z", - "shell.execute_reply": "2024-05-07T16:03:42.114863Z" - }, "tags": [] }, "outputs": [ @@ -111,7 +94,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "This is my list: [4, 8, 11, 7, 1, 8, 8, 5, 7, 11]\n" + "This is my list: [3, 10, 5, 5, 9, 6, 1, 4, 7, 1]\n" ] } ], @@ -127,12 +110,7 @@ "execution_count": 4, "id": "4a985b32-0670-42f3-ba50-5c0097eb75f5", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:42.121294Z", - "iopub.status.busy": "2024-05-07T16:03:42.120080Z", - "iopub.status.idle": "2024-05-07T16:03:42.128345Z", - "shell.execute_reply": "2024-05-07T16:03:42.127656Z" - }, + "scrolled": true, "tags": [] }, "outputs": [ @@ -162,7 +140,7 @@ "1 Objective Declarations\n", " cost : Size=1, Index=None, Active=True\n", " Key : Active : Sense : Expression\n", - " None : True : minimize : ((2*x[0] - 1)*4 + (2*x[1] - 1)*8 + (2*x[2] - 1)*11 + (2*x[3] - 1)*7 + 2*x[4] - 1 + (2*x[5] - 1)*8 + (2*x[6] - 1)*8 + (2*x[7] - 1)*5 + (2*x[8] - 1)*7 + (2*x[9] - 1)*11)**2\n", + " None : True : minimize : ((2*x[0] - 1)*3 + (2*x[1] - 1)*10 + (2*x[2] - 1)*5 + (2*x[3] - 1)*5 + (2*x[4] - 1)*9 + (2*x[5] - 1)*6 + 2*x[6] - 1 + (2*x[7] - 1)*4 + (2*x[8] - 1)*7 + 2*x[9] - 1)**2\n", "\n", "3 Declarations: x_index x cost\n" ] @@ -174,102 +152,83 @@ }, { "cell_type": "markdown", - "id": "17ea14ec-dbb7-487c-b4f1-cabc8d5e3c29", + "id": "0b790906-3951-49e9-b8f7-3e692255563b", "metadata": { "tags": [] }, "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):" + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the qaoa algorithm, with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { "cell_type": "code", "execution_count": 5, - "id": "816b468f-a59f-4f2f-8337-4a9d66548425", + "id": "2c26a32e-1035-482c-a5f4-d8dcb428b0a8", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:42.132929Z", - "iopub.status.busy": "2024-05-07T16:03:42.131750Z", - "iopub.status.idle": "2024-05-07T16:03:44.605811Z", - "shell.execute_reply": "2024-05-07T16:03:44.605152Z" - }, "tags": [] }, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "qaoa_config = QAOAConfig(num_layers=3)" - ] - }, - { - "cell_type": "markdown", - "id": "db34d5ac-6877-4285-8dec-7bf7b37eb783", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" + "combi = CombinatorialProblem(\n", + " pyo_model=set_partition_model, num_layers=3, penalty_factor=10\n", + ")\n", + "\n", + "qmod = combi.get_model()" ] }, { "cell_type": "code", "execution_count": 6, - "id": "e41d0dd3-4135-4330-9ba3-c1b30c339a74", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:44.608883Z", - "iopub.status.busy": "2024-05-07T16:03:44.608215Z", - "iopub.status.idle": "2024-05-07T16:03:44.611547Z", - "shell.execute_reply": "2024-05-07T16:03:44.610977Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, + "id": "4192e734-85ed-47f3-a8a3-b463f0dadcea", + "metadata": {}, "outputs": [], "source": [ - "optimizer_config = OptimizerConfig(max_iteration=60, alpha_cvar=0.7)" + "write_qmod(qmod, \"set_partition\")" ] }, { "cell_type": "markdown", - "id": "214d6051-43b8-4b9d-8454-f9cdb62b4cf0", + "id": "a5c8e5a9-8fe8-4ca8-a31c-89c9e9b75fc2", "metadata": {}, "source": [ - "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:" + "## Synthesizing the QAOA Circuit and Solving the Problem\n", + "\n", + "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" ] }, { "cell_type": "code", "execution_count": 7, - "id": "0243019c-6fc3-435f-b6ec-8b4355d6660c", + "id": "d6bcc87b-7504-41ee-8412-c1161256d0ba", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:44.613782Z", - "iopub.status.busy": "2024-05-07T16:03:44.613487Z", - "iopub.status.idle": "2024-05-07T16:03:44.714090Z", - "shell.execute_reply": "2024-05-07T16:03:44.713444Z" - }, "pycharm": { "name": "#%%\n" }, + "scrolled": true, "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Opening: https://nightly.platform.classiq.io/circuit/6d0b5153-963f-45d5-84a0-ea52307aa923?version=0.61.0.dev7\n" + ] + } + ], "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=set_partition_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" + "qprog = combi.get_qprog()\n", + "show(qprog)" ] }, { "cell_type": "markdown", - "id": "1fcc3812-c9d0-421c-84bb-38047297b33f", + "id": "34c6ac30-97f4-4cc1-9eb3-c32a79b23c66", "metadata": {}, "source": [ "We also set the quantum backend we want to execute on:" @@ -278,111 +237,43 @@ { "cell_type": "code", "execution_count": 8, - "id": "53bc041f-065c-44d2-b220-dafd9d0504ac", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:44.717234Z", - "iopub.status.busy": "2024-05-07T16:03:44.716619Z", - "iopub.status.idle": "2024-05-07T16:03:44.733981Z", - "shell.execute_reply": "2024-05-07T16:03:44.733405Z" - }, - "tags": [] - }, + "id": "2b2c8aea-0228-41a6-88c7-bddea1e29eba", + "metadata": {}, "outputs": [], "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", + "from classiq.execution import *\n", "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", + "execution_preferences = ExecutionPreferences(\n", + " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\"),\n", ")" ] }, - { - "cell_type": "code", - "execution_count": 9, - "id": "7738571f-3a9f-498f-9a15-9c874f3c3dfd", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:44.736412Z", - "iopub.status.busy": "2024-05-07T16:03:44.735967Z", - "iopub.status.idle": "2024-05-07T16:03:44.761670Z", - "shell.execute_reply": "2024-05-07T16:03:44.761038Z" - } - }, - "outputs": [], - "source": [ - "write_qmod(qmod, \"set_partition\")" - ] - }, { "cell_type": "markdown", - "id": "943291f0-6a9f-4286-a69d-ef13a0a12ef6", + "id": "edbf9187-9329-487d-abed-1a3640aa25ad", "metadata": {}, "source": [ - "## Synthesizing the QAOA Circuit and Solving the Problem\n", - "\n", - "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" + "We now solve the problem by calling the `optimize` method of the `CombinatorialProblem` object. For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`maxiter`) and the $\\alpha$-parameter (`quantile`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" ] }, { "cell_type": "code", - "execution_count": 10, - "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:44.764221Z", - "iopub.status.busy": "2024-05-07T16:03:44.763821Z", - "iopub.status.idle": "2024-05-07T16:03:49.214351Z", - "shell.execute_reply": "2024-05-07T16:03:49.213612Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Opening: https://platform.classiq.io/circuit/0ff868cf-2ccd-47e7-b5f7-4500845af8c3?version=0.41.0.dev39%2B79c8fd0855\n" - ] - } - ], - "source": [ - "qprog = synthesize(qmod)\n", - "show(qprog)" - ] - }, - { - "cell_type": "markdown", - "id": "80238cf9-d7bd-46e5-9d48-b7cf23a6b304", - "metadata": {}, - "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "62d12d20-1c80-4a9e-bb6b-b1fddc6cbe40", + "execution_count": 9, + "id": "5dcfa7ce-09e6-41ac-be81-298a281ba051", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:49.217154Z", - "iopub.status.busy": "2024-05-07T16:03:49.216634Z", - "iopub.status.idle": "2024-05-07T16:03:58.972236Z", - "shell.execute_reply": "2024-05-07T16:03:58.971471Z" - }, "tags": [] }, "outputs": [], "source": [ - "result = execute(qprog).result_value()" + "cost_values = []\n", + "optimized_params = combi.optimize(\n", + " execution_preferences, maxiter=60, cost_trace=cost_values, quantile=0.7\n", + ")" ] }, { "cell_type": "markdown", - "id": "620ea6a0-cd05-41a9-a2ed-9631c680d2e6", + "id": "c2cd6e58-981a-47c8-8fd7-5f2a9bebbc31", "metadata": {}, "source": [ "We can check the convergence of the run:" @@ -390,38 +281,46 @@ }, { "cell_type": "code", - "execution_count": 12, - "id": "02454398-b229-403c-824a-b1eb539fbc1f", + "execution_count": 10, + "id": "6542ba4a-9493-4b01-8eea-8202d70b1f2c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:58.977492Z", - "iopub.status.busy": "2024-05-07T16:03:58.976250Z", - "iopub.status.idle": "2024-05-07T16:03:59.020166Z", - "shell.execute_reply": "2024-05-07T16:03:59.019553Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/jpeg": 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", "text/plain": [ - "" + "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 12, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "result.convergence_graph" + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(nrows=1, ncols=1)\n", + "axes.plot(cost_values)\n", + "axes.set_xlabel(\"Iterations\")\n", + "axes.set_ylabel(\"Cost\")\n", + "axes.set_title(\"Cost convergence\")" ] }, { "cell_type": "markdown", - "id": "615ed612-b835-4bf0-aa92-92d30ef8006d", + "id": "d96714fd-2d11-4d13-9d21-4fc111a95670", "metadata": { "tags": [] }, @@ -431,25 +330,17 @@ }, { "cell_type": "markdown", - "id": "670eddd3-2da7-4a88-b571-7884ef24f60c", + "id": "96ea8543-29cb-4570-8741-7199dea8a948", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm:" + "We can also examine the statistics of the algorithm. In order to get samples with the optimized parameters, we call the `get_results` method:" ] }, { "cell_type": "code", - "execution_count": 13, - "id": "516d78ba-2951-46eb-b1af-efe877513556", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:59.023922Z", - "iopub.status.busy": "2024-05-07T16:03:59.023674Z", - "iopub.status.idle": "2024-05-07T16:03:59.177765Z", - "shell.execute_reply": "2024-05-07T16:03:59.177036Z" - }, - "tags": [] - }, + "execution_count": 11, + "id": "bbc7c2ca-1d3a-4342-9a37-5b8fc8980fbe", + "metadata": {}, "outputs": [ { "data": { @@ -472,85 +363,68 @@ " \n", " \n", " \n", + " solution\n", " probability\n", " cost\n", - " solution\n", - " count\n", " \n", " \n", " \n", " \n", - " 525\n", - " 0.001\n", - " 0.0\n", - " [0, 1, 1, 1, 1, 0, 1, 0, 0, 0]\n", - " 1\n", + " 0\n", + " {'x_0': 0, 'x_1': 0, 'x_2': 1, 'x_3': 1, 'x_4'...\n", + " 0.019043\n", + " 1.0\n", " \n", " \n", - " 29\n", - " 0.004\n", - " 0.0\n", - " [1, 1, 1, 0, 0, 0, 0, 1, 1, 0]\n", - " 4\n", + " 281\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'...\n", + " 0.000977\n", + " 1.0\n", " \n", " \n", - " 511\n", - " 0.001\n", - " 0.0\n", - " [1, 1, 0, 0, 0, 1, 1, 0, 1, 0]\n", - " 1\n", + " 59\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.004395\n", + " 1.0\n", " \n", " \n", - " 494\n", - " 0.001\n", - " 0.0\n", - " [0, 1, 0, 0, 0, 1, 1, 0, 0, 1]\n", - " 1\n", + " 282\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'...\n", + " 0.000977\n", + " 1.0\n", " \n", " \n", - " 424\n", - " 0.001\n", - " 0.0\n", - " [0, 0, 0, 1, 1, 1, 1, 0, 0, 1]\n", - " 1\n", + " 284\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.000977\n", + " 1.0\n", " \n", " \n", "\n", "" ], "text/plain": [ - " probability cost solution count\n", - "525 0.001 0.0 [0, 1, 1, 1, 1, 0, 1, 0, 0, 0] 1\n", - "29 0.004 0.0 [1, 1, 1, 0, 0, 0, 0, 1, 1, 0] 4\n", - "511 0.001 0.0 [1, 1, 0, 0, 0, 1, 1, 0, 1, 0] 1\n", - "494 0.001 0.0 [0, 1, 0, 0, 0, 1, 1, 0, 0, 1] 1\n", - "424 0.001 0.0 [0, 0, 0, 1, 1, 1, 1, 0, 0, 1] 1" + " solution probability cost\n", + "0 {'x_0': 0, 'x_1': 0, 'x_2': 1, 'x_3': 1, 'x_4'... 0.019043 1.0\n", + "281 {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'... 0.000977 1.0\n", + "59 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.004395 1.0\n", + "282 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'... 0.000977 1.0\n", + "284 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.000977 1.0" ] }, - "execution_count": 13, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " set_partition_model,\n", - " vqe_result=result,\n", - " penalty_energy=qaoa_config.penalty_energy,\n", - ")\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=True).head(5)" + "optimization_result = combi.get_results()\n", + "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { "cell_type": "markdown", - "id": "687f492b-a4a5-49c6-964c-8959b035bb93", + "id": "2a6d978a-f2a2-46a0-8deb-bdfa6c9c3405", "metadata": {}, "source": [ "And the histogram:" @@ -558,31 +432,15 @@ }, { "cell_type": "code", - "execution_count": 14, - "id": "31a4e74d-b2b8-42e0-826d-de7b51de1fe8", + "execution_count": 12, + "id": "85fdf055-cb4e-4756-8983-3a607cc22382", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:59.182649Z", - "iopub.status.busy": "2024-05-07T16:03:59.181402Z", - "iopub.status.idle": "2024-05-07T16:03:59.666268Z", - "shell.execute_reply": "2024-05-07T16:03:59.665547Z" - }, "tags": [] }, "outputs": [ { "data": { - "text/plain": [ - "array([[]], dtype=object)" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - 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", "text/plain": [ "
" ] @@ -592,7 +450,12 @@ } ], "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" + "optimization_result[\"cost\"].plot(\n", + " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + ")\n", + "plt.ylabel(\"Probability\", fontsize=16)\n", + "plt.xlabel(\"cost\", fontsize=16)\n", + "plt.tick_params(axis=\"both\", labelsize=14)" ] }, { @@ -600,20 +463,14 @@ "id": "a3a890a1-c5d4-409d-b9a3-d7ffd4fdd6c0", "metadata": {}, "source": [ - "Let us plot the solution:" + "Let us plot the best solution:" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:59.669215Z", - "iopub.status.busy": "2024-05-07T16:03:59.668565Z", - "iopub.status.idle": "2024-05-07T16:03:59.672400Z", - "shell.execute_reply": "2024-05-07T16:03:59.671836Z" - }, "tags": [] }, "outputs": [], @@ -623,15 +480,9 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, "id": "f349d9fb-132e-4ca0-8433-db1e2d61efa1", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:59.674917Z", - "iopub.status.busy": "2024-05-07T16:03:59.674535Z", - "iopub.status.idle": "2024-05-07T16:03:59.679208Z", - "shell.execute_reply": "2024-05-07T16:03:59.678640Z" - }, "tags": [] }, "outputs": [ @@ -639,15 +490,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "P1= [7, 1, 8, 8, 11] , total sum: 35\n", - "P2= [4, 8, 11, 5, 7] , total sum: 35\n", - "difference= 0\n" + "P1= [3, 10, 6, 7] , total sum: 26\n", + "P2= [5, 5, 9, 1, 4, 1] , total sum: 25\n", + "difference= 1\n" ] } ], "source": [ - "p1 = [mylist[i] for i in range(len(mylist)) if best_solution[i] == 0]\n", - "p2 = [mylist[i] for i in range(len(mylist)) if best_solution[i] == 1]\n", + "p1 = [mylist[i] for i in range(len(mylist)) if best_solution[f\"x_{i}\"] == 0]\n", + "p2 = [mylist[i] for i in range(len(mylist)) if best_solution[f\"x_{i}\"] == 1]\n", "print(\"P1=\", p1, \", total sum: \", sum(p1))\n", "print(\"P2=\", p2, \", total sum: \", sum(p2))\n", "print(\"difference= \", abs(sum(p1) - sum(p2)))" @@ -663,15 +514,9 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 15, "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:59.682282Z", - "iopub.status.busy": "2024-05-07T16:03:59.681909Z", - "iopub.status.idle": "2024-05-07T16:03:59.740657Z", - "shell.execute_reply": "2024-05-07T16:03:59.739961Z" - }, "pycharm": { "name": "#%%\n" }, @@ -689,19 +534,19 @@ " Key : Lower : Value : Upper : Fixed : Stale : Domain\n", " 0 : 0 : 1.0 : 1 : False : False : Binary\n", " 1 : 0 : 1.0 : 1 : False : False : Binary\n", - " 2 : 0 : 1.0 : 1 : False : False : Binary\n", - " 3 : 0 : 0.0 : 1 : False : False : Binary\n", - " 4 : 0 : 1.0 : 1 : False : False : Binary\n", + " 2 : 0 : 0.0 : 1 : False : False : Binary\n", + " 3 : 0 : 1.0 : 1 : False : False : Binary\n", + " 4 : 0 : 0.0 : 1 : False : False : Binary\n", " 5 : 0 : 0.0 : 1 : False : False : Binary\n", " 6 : 0 : 0.0 : 1 : False : False : Binary\n", " 7 : 0 : 0.0 : 1 : False : False : Binary\n", - " 8 : 0 : 0.0 : 1 : False : False : Binary\n", + " 8 : 0 : 1.0 : 1 : False : False : Binary\n", " 9 : 0 : 1.0 : 1 : False : False : Binary\n", "\n", " Objectives:\n", " cost : Size=1, Index=None, Active=True\n", " Key : Active : Value\n", - " None : True : 0.0\n", + " None : True : 1.0\n", "\n", " Constraints:\n", " None\n" @@ -719,15 +564,9 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 16, "id": "2e5c1b07-6060-455d-81ed-e48a2207c81b", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:59.743360Z", - "iopub.status.busy": "2024-05-07T16:03:59.742870Z", - "iopub.status.idle": "2024-05-07T16:03:59.746421Z", - "shell.execute_reply": "2024-05-07T16:03:59.745852Z" - }, "tags": [] }, "outputs": [], @@ -737,15 +576,9 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 17, "id": "a7524894-b5c5-42d4-8f92-a019bef5e7da", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:03:59.748666Z", - "iopub.status.busy": "2024-05-07T16:03:59.748361Z", - "iopub.status.idle": "2024-05-07T16:03:59.752921Z", - "shell.execute_reply": "2024-05-07T16:03:59.752289Z" - }, "tags": [] }, "outputs": [ @@ -753,9 +586,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "P1= [7, 8, 8, 5, 7] , total sum: 35\n", - "P2= [4, 8, 11, 1, 11] , total sum: 35\n", - "difference= 0\n" + "P1= [5, 9, 6, 1, 4] , total sum: 25\n", + "P2= [3, 10, 5, 7, 1] , total sum: 26\n", + "difference= 1\n" ] } ], @@ -804,7 +637,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" }, "vscode": { "interpreter": { diff --git a/applications/optimization/set_partition/set_partition.qmod b/applications/optimization/set_partition/set_partition.qmod index 98a0674fb..2b37221c3 100644 --- a/applications/optimization/set_partition/set_partition.qmod +++ b/applications/optimization/set_partition/set_partition.qmod @@ -1,713 +1,25 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=324.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=18.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=18.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=18.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=18.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=18.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=18.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=18.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=18.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=18.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=18.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=24.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=24.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=24.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=24.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=24.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=30.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=30.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=30.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=30.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=30.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=36.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=36.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=36.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=36.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=36.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=40.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=48.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=54.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=54.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=54.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=54.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=54.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=60.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=66.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=66.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=66.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=66.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=66.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=72.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=88.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=90.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=108.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=110.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=132.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=198.0 - } -]; - -qfunc main(params_list: real[6], output target: qbit[10]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + x_0: qbit; + x_1: qbit; + x_2: qbit; + x_3: qbit; + x_4: qbit; + x_5: qbit; + x_6: qbit; + x_7: qbit; + x_8: qbit; + x_9: qbit; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=False, -initial_point=[0.0, 0.006952841596130592, 0.003476420798065296, 0.003476420798065296, 0.006952841596130592, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=60, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=0.7 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[6], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 3) { + phase (-((((((((((((6 * v.x_0) + (20 * v.x_1)) + (10 * v.x_2)) + (10 * v.x_3)) + (18 * v.x_4)) + (12 * v.x_5)) + (2 * v.x_6)) + (8 * v.x_7)) + (14 * v.x_8)) + (2 * v.x_9)) - 51) ** 2), params[i]); + apply_to_all(lambda(q) { + RX(params[3 + i], q); + }, v); + } +} diff --git a/applications/optimization/set_partition/set_partition.synthesis_options.json b/applications/optimization/set_partition/set_partition.synthesis_options.json index 0967ef424..df25d261f 100644 --- a/applications/optimization/set_partition/set_partition.synthesis_options.json +++ b/applications/optimization/set_partition/set_partition.synthesis_options.json @@ -1 +1,43 @@ -{} +{ + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "cz", + "x", + "u2", + "ry", + "rz", + "s", + "r", + "z", + "u", + "t", + "u1", + "id", + "sxdg", + "sdg", + "h", + "sx", + "rx", + "tdg", + "y", + "p", + "cx", + "cy" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 2863520222 + } +} diff --git a/applications/physical_systems/ising_model/ising_model.ipynb b/applications/physical_systems/ising_model/ising_model.ipynb index 75dc17651..cdd184f07 100644 --- a/applications/physical_systems/ising_model/ising_model.ipynb +++ b/applications/physical_systems/ising_model/ising_model.ipynb @@ -29,12 +29,6 @@ "execution_count": 1, "id": "c6bb59fb-285b-439d-871e-7952c2df8db2", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:22:54.176458Z", - "iopub.status.busy": "2024-05-07T15:22:54.174237Z", - "iopub.status.idle": "2024-05-07T15:22:54.375957Z", - "shell.execute_reply": "2024-05-07T15:22:54.375173Z" - }, "tags": [] }, "outputs": [], @@ -64,12 +58,6 @@ "execution_count": 2, "id": "37e95f02-075e-45f6-94f1-6951ea81b0a4", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:22:54.381762Z", - "iopub.status.busy": "2024-05-07T15:22:54.380282Z", - "iopub.status.idle": "2024-05-07T15:22:54.389802Z", - "shell.execute_reply": "2024-05-07T15:22:54.389106Z" - }, "tags": [] }, "outputs": [], @@ -114,12 +102,6 @@ "execution_count": 3, "id": "c053de5b-bbb4-4c8e-b86a-840d792c407f", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:22:54.394509Z", - "iopub.status.busy": "2024-05-07T15:22:54.393412Z", - "iopub.status.idle": "2024-05-07T15:22:54.399755Z", - "shell.execute_reply": "2024-05-07T15:22:54.399079Z" - }, "tags": [] }, "outputs": [], @@ -136,124 +118,79 @@ "source": [ "## 3. Optimize Using to Quantum Optimization Algorithm\n", "\n", - "We will now create a QAOA model for the optimization problem. The results of the model is the sequance of qubit values giving the minimized energy for the protein. In order to optimize the results, we recommend the user to explore the number of repatitions for the model (`num_layers`) and the number of iterations for the optimizer (`max_iteration`)." + "We will now create a QAOA model for the optimization problem. The results of the model is the sequance of qubit values giving the minimized energy for the protein. In order to optimize the results, we recommend the user to explore the number of repatitions for the model (`num_layers`) and the number of iterations for the optimizer (`maxiter`)." ] }, { "cell_type": "code", - "execution_count": 4, - "id": "0cad145c-b78a-4c9e-945a-fffb7e4fef45", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:22:54.404600Z", - "iopub.status.busy": "2024-05-07T15:22:54.403259Z", - "iopub.status.idle": "2024-05-07T15:22:57.272833Z", - "shell.execute_reply": "2024-05-07T15:22:57.262051Z" - }, - "tags": [] - }, + "execution_count": 5, + "id": "b2c6406f-8aa3-4674-870e-13b5a36b50dc", + "metadata": {}, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", - "\n", - "qaoa_config = QAOAConfig(num_layers=5)\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "optimizer_config = OptimizerConfig(\n", - " max_iteration=100,\n", - " alpha_cvar=0.7,\n", - ")\n", + "combi = CombinatorialProblem(pyo_model=ising_model, num_layers=5, penalty_factor=10)\n", "\n", - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=ising_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" + "qmod = combi.get_model()\n", + "write_qmod(qmod, \"ising_model\")" ] }, { "cell_type": "markdown", - "id": "ae3233b3-9805-4c8a-b115-d4fa9defcd92", + "id": "5f476b81-ce50-4cc5-a8d7-13c7b5033e0e", "metadata": {}, "source": [ - "We also set the quantum backend we want to execute on:" + "Now we can create a quantum circuit using the `get_qprog` command and show it" ] }, { "cell_type": "code", - "execution_count": 5, - "id": "4f779a6a-dae4-4235-92be-f90820fbfbeb", + "execution_count": 9, + "id": "0b28f2dc-26ec-4975-9e1f-41adfdd75cb4", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:22:57.280659Z", - "iopub.status.busy": "2024-05-07T15:22:57.280120Z", - "iopub.status.idle": "2024-05-07T15:22:57.308215Z", - "shell.execute_reply": "2024-05-07T15:22:57.305665Z" + "pycharm": { + "name": "#%%\n" }, "tags": [] }, - "outputs": [], - "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", - "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "2425da2e-35c9-49a7-8479-c1856ee34f75", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:22:57.312667Z", - "iopub.status.busy": "2024-05-07T15:22:57.312406Z", - "iopub.status.idle": "2024-05-07T15:22:57.344678Z", - "shell.execute_reply": "2024-05-07T15:22:57.343993Z" + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Opening: https://nightly.platform.classiq.io/circuit/0b452fbf-fc23-4a09-b800-6ad828f47e96?version=0.61.0.dev7\n" + ] } - }, - "outputs": [], + ], "source": [ - "write_qmod(qmod, \"ising_model\")" + "qprog = combi.get_qprog()\n", + "show(qprog)" ] }, { "cell_type": "markdown", - "id": "5f476b81-ce50-4cc5-a8d7-13c7b5033e0e", + "id": "b2ae85bb-2625-47ea-a112-5bbbd37fd6d5", "metadata": {}, "source": [ - "Now we can create a quantum circuit using the `synthesize` command and show it" + "We also set the quantum backend we want to execute on:" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "0b28f2dc-26ec-4975-9e1f-41adfdd75cb4", + "execution_count": 15, + "id": "4f779a6a-dae4-4235-92be-f90820fbfbeb", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:22:57.347982Z", - "iopub.status.busy": "2024-05-07T15:22:57.347558Z", - "iopub.status.idle": "2024-05-07T15:23:01.963192Z", - "shell.execute_reply": "2024-05-07T15:23:01.962520Z" - }, - "pycharm": { - "name": "#%%\n" - }, "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Opening: https://platform.classiq.io/circuit/e1a07618-2899-4a95-9d21-8eeb100cb053?version=0.41.0.dev39%2B79c8fd0855\n" - ] - } - ], + "outputs": [], "source": [ - "qprog = synthesize(qmod)\n", - "show(qprog)" + "from classiq.execution import *\n", + "\n", + "execution_preferences = ExecutionPreferences(\n", + " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", + ")" ] }, { @@ -261,25 +198,32 @@ "id": "8ce840ba-1d3e-461c-99f2-5045d8cb8e29", "metadata": {}, "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" + "We now solve the problem by calling the `optimize` function:" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 16, "id": "6daf89c6-2e5c-41b5-b162-dfd048014919", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:23:01.965793Z", - "iopub.status.busy": "2024-05-07T15:23:01.965322Z", - "iopub.status.idle": "2024-05-07T15:23:09.428158Z", - "shell.execute_reply": "2024-05-07T15:23:09.427541Z" - }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 8.15 s, sys: 211 ms, total: 8.36 s\n", + "Wall time: 2min 39s\n" + ] + } + ], "source": [ - "result = execute(qprog).result_value()" + "%%time\n", + "cost_values = []\n", + "optimized_params = combi.optimize(\n", + " execution_preferences, maxiter=100, cost_trace=cost_values, quantile=0.7\n", + ")" ] }, { @@ -292,33 +236,41 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 17, "id": "370e71c6-764e-4296-882a-d5daa14d3176", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:23:09.430991Z", - "iopub.status.busy": "2024-05-07T15:23:09.430811Z", - "iopub.status.idle": "2024-05-07T15:23:09.458569Z", - "shell.execute_reply": "2024-05-07T15:23:09.457962Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/jpeg": 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", "text/plain": [ - "" + "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 9, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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x48fjhx9+SPSSiIiIKAkclcHRokWLMHv2bDzwwANYu3YtRo0ahalTp6K+vj7RSyMFl0tEp92Z6GUQEdFR5qgMjp566ilcd911uPrqqzF06FA8//zzyMjIwMsvv5zopZHCtf9ejQnzlqC5w57opcRcp92JLbUWiKKY6KUQER31jrrgyGazYc2aNZgyZYp8m0ajwZQpU7BixYqA661WKywWi88XxZ4oili+vQFH2u3Y09CW6OXE3MMfbca0+d9g2bZDiV4KEdFR76gLjhoaGuB0OlFaWupze2lpKWprawOunzdvHnJzc+WvioqKeC31qNbYZoPN6QIAtNvSv7S2vb4FALCvsT3BKyEioqMuOArXnDlz0NzcLH/t27cv0Us6KtQ0d8p/7rA7EriS+GjucP+MNifLakREiaZL9ALiraioCFqtFnV1dT6319XVoaysLOB6o9EIo9EYr+WRR60yOLK5EriS+LB4+qrszvT/WYmIkt1RlzkyGAwYO3YslixZIt/mcrmwZMkSTJgwIYErI6Uaizc4arcdDZkjd3BkczA4IiJKtKMucwQAs2fPxowZMzBu3DiccMIJmD9/Ptra2nD11VcnemnkUdvcIf853bfzO5wutFrdASAzR0REiXdUBkeXX345Dh06hPvvvx+1tbU47rjj8OmnnwY0aVPiKHuO0r0h29LpzYwxc0RElHhHXVlNcuutt2Lv3r2wWq1YuXIlxo8fn+glkUJtigZHR9psuOnVNViyua77iz2Uc5xszBwRESXcUZk5ouSnzBylUllt6ZZ6fLKhFodarJg8RF0mUhkcsaxGRJR4R23miJKXKIqoUfQcpVLmqMkT6Ow/0tHNlV4+mSOW1YiIEo7BESWd5g47Ou3eIKEjhTJH0pb8upZOWB3q1u2bOeKcIyKiRGNwRElHWVIDgI4UyhxZOt2BjigCNU2d3VzteQwzR0RESYXBESWdWr/gKJXmHCmzQGpLa2zIJiJKLgyOKOkEZI5SqqzmDeT2H1F3TpqFDdlEREmFwRElHWkAZFmOCUBqltWAHmaOWFYjIko4BkeUdKTMUf/iTACpljlSBkfqMkfcyk9ElFwYHFHSqbX4BkeptJXfEmnPUQwyR/9ZsQdz3v0ZLhd3whERqcHgiJKOnDkqygKQamU1Zc9RTxqyox/APPH5Nvz3h2rsPNQa9ecmIkpHDI4o6dSmaFlNeYAsoH7WUSzLai6XKPdBpcr7SESUaAyOKKm0dNrlAEPOHNmdEMXkLwkpAyOjTqN61lEsy2otnQ5Ib52Vzd5ERKowOKKkImWNcs16FGQZALgHKionZicrKcjJMGjRtyADQPelNadLRIuiFBftzJFy95w1Bd5DIqJkwOCIkspBT3BUnmuCWa+Vb0+FkpA04yjHpEeffDOA7nestSiCFyD6mSPffqbkfw+JiJIBgyNKKvKMo1wTtBoBBp37VzQVpmRLWZocsw598tVljpTBCxD9CdnK3XPMHBERqcPgKIntqG/BU4u3+ZRG0l2NInMEuEtUANCZApkjKdAJJ3PkHxxFu6ymfH72HBERqcPgKIk99ulW/G3Jdny4vibRS4kbqeeoLMcdXEiltVSYdSRlaXLNevSWgyN1maP8DD2A6JfVlIE1p28TEanD4CiJ/XygGQBwpN2W4JXEj3/myGxIoeBILqvpwy6rFWcbAQAu0d2kHS2+maPkfw+JiJIBg6Mk1dhmkwMF5W6mdCdnjqTgyJM5Sq2GbJ1cVutu1pEUvBRlGeXbopnhUR6Ey7IaEZE6DI6S1MaDzfKf26xHT3BU42nI9u85SoUp2XLPkVmPwkwDTPruZx35Z46A6DZls+eIiCh8DI6S1MaDFvnPrUdJcNRmdcjHb8iZI4MOQGoER1JZLdeshyAIqkprUvBSmOkNjqLZlO0z54jBERGRKgyOkpQyODpaymrSgbNZRh2yTe4GZbPes5U/Jcpq3t1qAFTtWFM2cRu07p81mmU19hwREYWPwVGSOhrLav79RgCQIWeOkv89kLJeOWb3mvuo2LHWLAdHOui1AoAoZ44454iIKGwMjpJQm9WB3Q1t8vdHS1nNf6ca4N2t1mFL/g/25oDMkVRW6zpzJAdHGXp54GWsMkfRHjBJRJSuGBwloS21FijPWT1agiN5OnaOIjiS5hzZk/89sCgasoFwM0d66KWyWlR7jhS71Zg5IiJShcFREpL6jaQg4WjpOQqWOZInZKdYQzaAsBqyc83ezJHdyTlHRESJxOAoCW3yBEfj+xcACN1ztHpPIy76+7dYv68pHkuLqRq558gs32ZKkQnZVocTnZ7MjH9DdqhZR83tsWvI7rQ7fZ6LE7KJiNRhcJSEpMzRCVXu4KjD7oSji1LL++sP4sfqJny8IfWPGJEzR3mBmaNk362mHLaYZXI3ZHc368jlEtFilZq4vWW1aDVkW/zObeNWfiIidRgcJRm704WttS0AgPFVhfLtbdbgwYH0AZgO/SS1fgMggdQpq0kltWyTDlqNe9eZctbRgabA0lpLp0PuLVOW1aKV4fE/1JZlNSIidRgcJZkd9a2wOV3INurQvyhT/sBs7WIru9SPlOpZgU67E0c8JabynNQrq/nPOJKEmnUkBS8mvQZGnVbeyh+thmzlAEiAZTUiIrUYHCUZqaQ2pFcONBoB2UZ3iaa1i6Zs6QMw1bMC0owjs14rzwkCFHOOkr2s1uktjymF2rGmbMYGoGjIjlXmiMEREZEaDI6SjDT8cVivHADe/pVWqz3o9VKvS6p/8Cl3qgmCIN8uHzyb5Jkj74wjnc/toXas+QdH+ig3ZEu/GzpPmS/Vf0eIiOKFwVGSkTJHw3rlAgAyPZmTrrbzt3SmR89RrcUz40jRbwR4h0Am+5wji1+gI1FTVpMzR1FuyJaevyjLfW4by2pEROowOEoiLpeIzXJw5Js56rIhW+45So7MiiiKmP3mOvzl481hPe5QixUAUKI4nR7wNmQn+4RsqbwZWFZTnzmSG7KjNOdICtiKPe9psvyOEBElO133l1C87D/SgRarAwatBgNLsgDA23MUpKzmdIny9OxISyZN7Tbc/sY61HuCFEl5rglP//I4+SDY7uxr7MC7aw8AAM4f2Qsj+uSqepzUcJ1h9P2V9JbVkj1z5Ok56qIhu9bSCZvDJQdAgKIUF6OyWnNAcJTcASYRUbJg5iiJSP1Gg8uy5A/KTGPXZTVlk3akH3zfbG/Asm2HsLnG4vO1dEs9Vuw8rPp5lEedLPhuj+rHSQMUTTqtz+1y5sjuhChGb3J0tPlngSQ+s46aO0I+JtoN2VI2S8rGsaxGRKQOg6MkIvcblXuzLaHKasqt2tYId3NJDc+jKvLwn2tOwH+uOQEjervX0RZG1qZD0Rv0wU8HcbjVGuJqr07P+k16319Jkyc4conJnfnwltV8M1/KWUfVjb59R7FuyGbmiIioZxgcJRF5p1rvHPm2UGU1nxPXI/zgk/pReuWacMqgYpwyqBi9PJOqu+p3CkZ5rc3hwhur9ql6nDc48sscKb5P5h1rXc05AoCBxe4SqTTcU35Mp39DtntXWfQmZLsDVSk4crrELietExGRF4OjJLLRrxkbALLk4Cgwe9MSxbKa9HijoidGnjEURlAi9Q5Ju/Ff/X6vqg97KTgy+wVHOq1G3sWVzLOOLB3BG7IBYEi5++9zU40l6GMCG7KjnDnK8ja5R+u5iYjSWdoER3v27ME111yDqqoqmM1mDBgwAA888ABsNpvPNYIgBHx9//33CVy526EWK+pbrBAE4Ngyb3CUKQdH3ZTVItyJJAUnRkXPj9TvE05Zrd1z7QmVBSjKMqCmuROfb6xT8fqeniN94K+kdFsyT8mWdg369xwBwJDybADA5hrfzFHM5xx1+pbVgNQf+UBEFA9ps1tty5YtcLlc+Oc//4mBAwdiw4YNuO6669DW1oYnnnjC59ovvvgCw4YNk78vLCz0f7q4k0pqVUWZckAEKIZAdgaW1ZQHi0b6oSdljpTBibSOcIIS6dq8DD2uOKEvnlm6Awu/24NzR5aHfFynJ7gz+mWOAHcGy9LpkAO4ZOTNHAX+X2qoJxO4o77FZ8davCZk52caoNMIcLhE9h0REamQNsHRtGnTMG3aNPn7/v37Y+vWrfjHP/4REBwVFhairKws3ksMaXTffLwy8/iAD69stWW1CD9Q5cyRIjiRSlxtQV67K1LmKNOgw5Xj++EfX+3ED3sasemgRQ4SQr2+f88R4M1gJWvmSBRFb0N2kJ6j3nlm5JjcAd6O+lb5fYhl5silGPOQY3IfauuwObljjYhIhbQpqwXT3NyMgoKCgNt/8YtfoKSkBCeffDLef//9kM9htVphsVh8vmIh16zH6ceWYNpw36At1FZ+ZVnN5nBFtNVdzhzplJmj8I/ukBqyzQYtynJNmOr5eRZ2s63fu5U/WFlNCo6Sc9ZRh90Ju2dwY7CeI0EQcKyn72izp+/I5RIDe47kCdmRjyxo6XRA+nXIMevkXjIOgiQi6l7aBkc7duzAM888gxtuuEG+LSsrC08++STeeustfPTRRzj55JNx4YUXhgyQ5s2bh9zcXPmroqIiHsuXyVv5gwQG0m4kSSQlE6ksp8wcSQ3Z4W3ld3/4SkHd1RMrAQD/t+4AjrTZunqYqsxRspbVpL8HrUZApiFw/QAw1C84arU54JKDl+g3ZEuBs0mvgVGnlXvJWFYjIupe0gdH9957b9AmauXXli1bfB5z4MABTJs2DdOnT8d1110n315UVITZs2dj/PjxOP744/HII4/gqquuwuOPP97l68+ZMwfNzc3y17596ramR4tcVguSOWrx60OK5INP7vkJkjkKp5wlleCkktzYfvkY1isHVocL/7fuQNevb/dmnPyZk7ys5i2p6XwOzVWSmrKlHWvN7e7HGHUaOSCMZlmtq34mBkdERN1L+p6ju+66CzNnzgx5Tf/+/eU/Hzx4EKeffjomTpyIF154odvnHz9+PBYvXtzl/UajEUajscv7Yy0zRM+RJSA4cgJQd8yHv2CZI7M+/IZsqQQnBVaCIOCkgUXYeNCCg02B54tJupqQ7V5HkgdHIbbxS4Z6BnturrFAFMWgE7X1UZxz5D93iWU1IiL1kj44Ki4uRnFxsaprDxw4gNNPPx1jx47FK6+8Ao2m+8TYunXrUF4eeidVIkllNbtThNXh9NlqH1BWi2DHWqjMUTgN2VIJTirJAYrz0UKUxaTXD7aVP9nLas0hBkBKBpVmQasRcKTdjjqLNaDfCFCU1WKQOTLqmTkiIlIr6YMjtQ4cOIBJkyahX79+eOKJJ3Do0CH5Pmln2sKFC2EwGDB69GgAwLvvvouXX34ZL774YkLWrEamIsho7XTAmOUNjlqs0SurWeU5Q4E9Rz3Zyp+hKI9JZbEOW9frC9VzlCpltWAzjiQmvRb9izKxvb4Vm2qa5ffbJzjSRm8rv/c4E99mb845IiLqXtoER4sXL8aOHTuwY8cO9OnTx+c+5S6uhx56CHv37oVOp8Oxxx6LRYsW4dJLL433clXTagRkGLRotznRanWgUDHtOLAhu+fBgzVI5qgnW+i9wVFg5qirzI8oinJZzRgkcySV95J1Qrb09xBsxpHSkPIcbK9vxeaaFhRmGgB0kTmKwm61gMyRJ+PICdlERN1L+oZstWbOnAlRFIN+SWbMmIFNmzahra0Nzc3NWLlyZVIHRpKsLrbzB/YcRVBWk4ITZVlNzhyFUVazSmW1wHlJXQU3ynUHzxx5jg9J1syRirIa4B0GuanG0kXPUfTKanLA5inLymW1JA0wiYiSSdoER+lM3s6v6P0RRVEOlqQPwEhKJlZHYFkrQ7FbzeVSl83wbuX3Po9JLqsF/2BWZpSCNWRn9CBIi6dmFQ3ZgPeMtc2K4CgnSHAUjbJaYOaIPUdERGoxOEoBwQ6fbbc54fQELEWes7MiK6sFO3jWG6h0qnxueQikXn1DtpS10moEeceWkvfxyfnBrqbnCPBu59/d0IZaS2fAY6LZkB3QcySV1RgcERF1i8FRCggWHEkffnqtIH/ARqOspswcmXRaSGN72oIcfBtMh3R8iDGwrNZVz5HcjK3TBJ0T5G3oTs7MkX8Jqysl2SYUZRkgisCqPY0AYteQ7Z+ZYuaIiEg9BkcpIFhw5C2p6eVSVES71YI0ZGs0AjLCOLpDFEW024M0ZEs9Q10FR0FKekpSBitpG7I71ZXVAG9pbV+je+ZTsMwR5xwRESUWg6MUIPUcKadkSx9+2SZdVJptgw2BBABzGNv5O+0u+TwvZUlOCnq67jkKzFopmZJ8CKSaOUcS6RgRSbAhkNHI7nQ1IZtlNSKi7jE4SgGhymo5Zn3EJROXS5S3ePsf/Oo9QqT7zJHyDDazXv1uNamsFmwbP6DIHCVpcNSTzJEkNyM2DdmWTt/xAjxbjYhIPQZHKSBocNThLasZI2y2Vc6+8c8cyYfPqug5koIXs14LjcbbO2TuZsK1t+coRctqnr+L3G7mHAFBgiNFQGWM5YRsltWIiFRjcJQCgpXVpENns026iDNHvlvpfX8lvIMg1WeOlM3YgDdzZHeKQbMioQ6dBZK7rOZyifLfhZqyWv/iTLnxGgg+58glQt6J2BOddqccYOWwrEZEFDYGRykgeFlNkTnSR5YVkIIqrUaATttVcNT9c8vb+P2CHGUvUbDskbfnqKuymvvn70zC4KjV5oAUx6gpq+m1Ggwuy5K/D9aQDURWWpP60TQCkGWQymrcrUZEpBaDoxQQvKwm9bnoIu4nkXt+dIG/DtKU7DYVgYlUVlOeByc9r7RDP1hpTG1Zrd3u9Jl4ngykvweDTtNlQ7m/IWU5QR+jVwSmkQQxym38UnlTKpfybDUiou4xOEoBoTJH2Sa9nHHo6Qef9EEc7MNdnpJtVV9W888cCYLgnXUU5PDZUIfOKm93KhrHk4Wy90stqe/If2ikcgBmRJmjIGU+o3Q0SZK9f0REyYjBUQqQg6POILvVfHqOelhWC3KumiScslpXmSPl8wTNHEnTubvZrQYED64SqVmRwVNrdN88AECvPLPP7YIgyP1IkfQGBTu3LdLSKxHR0UT9v+iUMHJDdtCyml4+VqPHZbUQQxjDOXxWyhxlBGmsNoXYzt9d5kiv1UCnEeBwiWi3O5AL9VmaWAuWpenO6L75eP6qsRhcmhVwn14rwOaMtOfIdxs/oOg5YlmNiKhbDI5SQKgJ2dkmPZra3R/QPQ2OQmeOwu85ChYcmUMMguzopucIcJfqWjodSTfryBIkS6PGtOFlQW836DRoszkjCo6CZY7k3WosqxERdYtltRSgDI6khmSfslqEE7JDNWSHM4BR2q2WYQyMuUPNOpKCM+mYkWDCKe/Fk3fYYnSyWVJTdiQN2f5HhwCKIZDMHBERdYvBUQqQymqi6A0OvKUTfcS71axyz0/XDdltKhqypdJbRpDnUVVWC5U56mbKdqJ4jw6JThLWOyW757vygvYccQgkEZFqDI5SgFmvhTRwWiqtBR8C2dM5R91v5VeTsZGuCZo5CjHIsbueI8B7xluyltWilTmKxpTsYMeZcAgkEZF6DI5SgCAIPqW1TrtTzvZE42y1UAe/mnswITtkz1EPhkC6H6/xrCPJgqPOnvUcdSUa56s1BwnYeLYaEZF6DI5ShHI7v9SMLXgmIEc64C9amSPvVv6ug6xgU66l3XLBynoSeUp2kpXVejLnKJRoNE571xRktxqDIyKibjE4ShHK7fxSSS3LqINGI0ShrCbtVgvRc6QqcyTtVgssq0WylR9QZrCSLTgKf85RKNIgyGjPOWJZjYhIPQZHKUJZVlOeqwZEnhXwBieR7Vbr6GFZTZrTZA4VHOnVl/fiqSdzjkKJRlktWM+RUZGRckVwqC0R0dGAwVGKyFSU1fybgKWMT0+zAqEyR/LZatZIt/K7f9WCBVnWEMGZJCPEKIBEkmZMRavnKBoZnuATsr1/t5x1REQUGoOjFJHtU1Zz+NzmPRoihpkjuxPObjIOUlYoVOYoWHCTqmW1vYfbUGvphFYjoF9hRlSe0xBh5sjlEuUdjb5zjhSH2nLWERFRSAyOUoRvWc23lBPTniNF/1B3M4akWUjhHx/i2a2mYs5RMgVHn26oBQCc2L8AeRmGqDyntyG7Z6Wvlk4HPHNCffqgdBoBgmcchNUZu/dw5a7DuPyfK7Cl1hKz1yAiijUGRykiUxkc+TUBK7dpSxO0wyEfHxIkc2TSa+QP1e76fdpDNGSbQ/Quec92S62y2qcb3cHRtGHBjwLpCX2EB89KgbNJr/EJdgVBiMv5agu+24OVuxvx0U81MXsNIqJYY3CUIrKDbOWXMkdStkEUezZZWQ5OgmzlFwTBu50/RN+RKIpy8BR0K3+Eu9VMSZY5qmnuwI/VTRAEYGoMgqOeltWC9RtJ4jHr6OcDzQC8u/iIiFIRg6MUodzKrzxXDfDrJ+lBac2bOQoenEhZm1Db+a0OF6SWpFATsv0zP6IoymW1YJkr7xo8E7KTJHP0+cY6AMCYvvkoyTFF7XkjbcgOdq5atJ67O0fabNh/pMO9js7k2lVIRBSO6AxnoZjLDHL4rHe3mjI4ciE7zOcONQQSULedX5nRCbYl32QInjlSZjFCbeUPZ6RAPHyywV02Ont49LJGAGDwzDmKTeYotuerbTjYLP9ZmsVFRJSKGBylCOWEbGlOjbRbTRAEGHQa2ByuHpVMrCGODwG8WZu2EIGJ1Ixt0muglQ6CU5DLan7PocwkqSurJT4jcbjVih92NwKIbkkNUPQc9TA4CjbjSBLrKdlSSQ3wTukmIkpFDI5ShHIrv8PlOVfNb6u2zeGSZwaFo7vMUaZnSna7tesPPO82/uC/Ut6ymu8Hs/S9ViPIgUEw3pECid+GvnhTHVwiMLx3DioKorOFXxJp6etQixVA8MyRIcJ5WN3ZoAyOmDkiohTGnqMU4R3G6PCenRWlg0VDHTwLAGYV56uF2sbvfo7gZTW5GbuLwCzg8UmQOZJ2qZ09vDzqzx1JQ7bLJeKdtQcAAMdV5AXcH8/MUQt7jogohTFzlCKkhuwWqwN6T9kqO0oHi3abOTJ0X9LybuPvIjjqqqzm6H6nms/jE9yQ3dxhx7c7GgBEv6QGRJY5WrKlHrsb2pBt0uHSsX0C7o9lz1FTuw37Gjvk77lbjYhSGTNHKSLb6M4StXYGnq0GKKZk9yB4kHeLdTGEUU3PUagZR4Bv5kg5i6m7rJV3Dcmxlf/LLfWwO0UMKsnCwJKsqD+/d0J2+CMZXvxmFwDgV+P7yg38Ps8dw91qGw64hz5KOyhbbQ6e4UZEKYvBUYqQMkcddqf3eIgoldWs3QxhVBOYyDOOjKEzR/5rDHV0ic/jk2S3Wqx2qUn0nt1q4TZk/7y/GSt3N0KnETBzYmXQa2I550gqqY3vXwjAPXOrJUSPGhFRMmNwlCKCBR3RK6t1kzlS0ZAtBU5mffDMkTIzpAxwOlQMgASADM/zOlxiRCfWR6Ld5sCybYcAAFNjFBz1tGn6xeXurNF5I8tRnmsOek0k2cXuSM3YY/vly7+LLK0RUapicJQijDqtXHIB3JkY5e6unvaTuIcwhs7eZIaxlb+rzJFWI8hlHWXfkFVlcGQyeNeWqNLa19sOodPuQt+CDAwtz4nJa+h7MOfoYFMHPvQc13HtKf27vM4Y4ZiAUKTM0Yjeucj2lHvZlE1EqYrBUQrJUmSKlIeKAt7p1uFmHBwuUZ5s3XXPUfc7xTq6acgGgh8e6+05Cv2raNB65ycl6ny1LbUtAICJAwohCIGznKKhJ31BC7/bA6dLxIn9CzC8d26X13kzR9ENjprb7ahubAcADO+VK/9ucjs/EaUqBkcpRJmVyfY7HqKnZTXl9V0d36FqCGQ3DdlA8CNEvFv5Q2eOBEFARoLPV2tqd3/YF2QaYvYahjC38rdaHXj9h2oAwHUhskZA7HqOpMnYfQsykJuhlzcKsKxGRKkqrYKjyspKCILg8/XII4/4XPPTTz/hlFNOgclkQkVFBR577LEErTZ8WUZvQJRj8ssc6XrWT6IMVLodAhlyK3/oOUdA8FlHag6dlZhUjBSIJUuIozmixTshW91OrzdX7UNLpwP9izNx+jElIa+Vs1JRLqspS2qAtxeOZTUiSlVpN+foT3/6E6677jr5++xs70ljFosFZ511FqZMmYLnn38eP//8M2bNmoW8vDxcf/31iVhuWLKNyrKaf+aoZ1kB6XqDTtNlqUjK+LRZe76VH/AGQMqG7E6pGbybspr7uYMfXhsvTZ7gKC8jdsFROGW1NqsDLy3fDQC45uQqaIIc26LU0wC6O1JwJJX0pN9NltWIKFWlXXCUnZ2NsrLgO4lee+012Gw2vPzyyzAYDBg2bBjWrVuHp556KiWCo1BlNUMPy2pqJlRLM3NCHzyrInOkD2zIll4/1KGz3scnuqxmAxCfzFF3ZTVRFDHn3Z9xoKkDZTkmXDImcOijv1hNyN7glznKYUM2EaW4tCqrAcAjjzyCwsJCjB49Go8//jgcDu8/0CtWrMCpp54Kg8HbMzJ16lRs3boVR44cScRyw5JlUlFWC3O3mtScawwRnEgBT1sEE7IBb1lNmflRu5Vf+fhEzTrynngfw54jlZmjV1dW4/31B6HVCHj2V6NVvX/GGJyt1txhx97Dnmbs3u4dfNLvJnuOiChVpVXm6LbbbsOYMWNQUFCA7777DnPmzEFNTQ2eeuopAEBtbS2qqqp8HlNaWirfl5+fH/CcVqsVVqtV/t5iscTwJwgtK1RZrYc7kbo7OgTwZo5CDoH0lNyCTWaWBDtCxKpytxqgPHw2scFRTMtqKjJH6/c14aEPNgEA5px9LMZVFqh77hhkjjZ6skYVBWbkZbiDRpbViCjVJX3m6N577w1osvb/2rJlCwBg9uzZmDRpEkaOHIkbb7wRTz75JJ555hmf4CZc8+bNQ25urvxVUVERrR8tbFk+ZTX/zFHPeo7UHN/hLWeFyBzZ3feZQ2SOTEHOR1O7W813HfEPjkRRVGSOYlhW04Wec9TUbsPNr62FzenC1GGluObkqqDXBROLs9X8m7EBNmQTUepL+szRXXfdhZkzZ4a8pn//4FuYx48fD4fDgT179uCYY45BWVkZ6urqfK6Rvu+qT2nOnDmYPXu2/L3FYklYgOS7W62rrfxhltXCyBx12l1wukR53pCSnDlSsZW/p7vVzIbue59ipd3mlM87i0fmKFiQ63KJmP3mehxo6kC/wgw8Pn1UWPOW5OxiFDNH/s3YgPd3k5kjIkpVSR8cFRcXo7i4uEePXbduHTQaDUpK3FucJ0yYgD/84Q+w2+3Q693/gC9evBjHHHNM0JIaABiNRhiNxp4tPsp8h0BGZ86RmsyRso+o3eYIaAZ33x5Gz1EPhkACkOccJaKsJu1U02sFVc3jPRWqIXvR6n1YuqUeRp0Gf79yTECA3B2DNvpzjvybsQHvgFJLBzNHRJSakr6sptaKFSswf/58rF+/Hrt27cJrr72GO++8E1dddZUc+PzqV7+CwWDANddcg40bN2LRokV4+umnfTJDySxkWc3zgR2LniOjTgMpWdRV1qZN1W61IJkjR2o0ZDe3e5uxYzUdG/D+PdiDzDn6sdq9aWDWyVUY1qvrSdjdPXe0giNLpx17DnsnY0u8x4cwc0REqSnpM0dqGY1GvPHGG3jwwQdhtVpRVVWFO++80yfwyc3Nxeeff45bbrkFY8eORVFREe6///6U2MYPxKqsJh0623VwJAgCMg06tFgdQadki6IY3pwj5W41W/jBUSJ6jpo63Nv4Y1lSA7yZI6dLDChhSj085bmmHj13tA+ePdjUAcA9MTxfMTXcW1Zj5oiIUlPaBEdjxozB999/3+11I0eOxDfffBOHFUWfsqyW63+2Wk+PD1HZ85Nh1LqDI2vgB57N6e5Fkq7rijfz412jNARSVXAkB1fx/9D1Zo5iHBwpglS70wWtxvu+SMGRf9ZQLUOUD55t9azHf6yEVFZr6bRDFMWYZtqIiGIhbcpqRwPlVv7As9Uim5AdKnMEeDNCwfp92hWTszNU7HpTzjnyBmdhbOVPRFlN2sYf4+BICmCAwL/LFk9gqswghqOnpdeueIM13/VI39udotxTRkSUShgcpRCfOUf+wZG+Z2U1tbvF5EGQQTJH7Z7nMOg00Gm7/pWKfLdaIstqnsxRzMtq3iyLf1O21MPT08xRLHqOAN/fSwDINGjlHjXuWCOiVMTgKIXkZ7o/mDMN2oBMizGMM7mU1GaOpC36wQKTdk/AlBmiGRvwHhzbEWy3WpLPOYrHjCPA3d/V1SDIiMtq8u9IdN6/rtYjCAKbsokopaVNz9HRoCTbhEcvGYGCTGNAH0fEZbVuMjehsjZqmrGB4FvxvbvVuo/Te+WZAQB7G9u6vTbamtqlslrsjg6R6LUCbM7AQFfOHPW0rBblzFFXZTXA3XfU3GFHM7fzE1EKYnCUYi4/vm/Q270nrkf/4FnAe+htsCnZarbxA8HPVgunrDa4NBsAsK+xA+02R7fBWDQ1d0iHzsb+NfU6DWBz+mSO7E6XnGXreVnNG0BHo1G61dp1mc9d9u1gWY2IUhLLamnC1MOeIzUHzwLerFCbteuG7O6CI/+t/KIoqhpCKSnINKAoy5252VHf2u310eQ9Vy32maNgU7JbFdvisyIsqwHB5yiFq6WL3WoAjxAhotTG4ChN9Lys1v0QSMAb+ATLHEkN2d1lcvwPnlWuVU1ZDfBmj7bWtqi6PlqkslqsG7IB5ZRsbwAjBRlmvVa+P1zKv+NonK8WsqwmzTrqYOaIiFIPg6M00dMT1zvDzByFbMgOMeMICJxwrSyvqckcAd7gaHuCMkexbsgGlFOyvX+X8s6wHmaNlM8LRKfvqCXEmqTjbVhWI6JUxOAoTUgffE6XCEcYQ/7UZo4yQ2WOPMGOWW3myC4FR+51ajWC6mzIoNIsAMC2uvhmjprb4zPnCPBmjpQN2a3WyHaqAb474fybvf+5bCfO/ds3aGq3qX4+S4jdcyyrEVEqY3CUJoyKrfDhZAXU9vxkGEP0HNnUbeWXgiOHS/Q0GKtrBlc6xpM52hbHsprD6ZIHMMYjc6TXuRullZOsQ5WwwtHVjrVFq/dh40ELVu05ovq5WFYjonTF4ChNGHpYMgm/56jrrfzmbucceV+jw+6Ut/F39zilQZ7g6GBzZ9xm6CjPCItHcBQsuyP9rMGan8PR1bDQw63ujFFzGMFMqN1qzBwRUSpjcJQm3KUpd8YhnGZbq8qzzUI2ZHuCo8xuymoGrUaenNxpc3r7nVQMgJTkmvUozTECiF/fkVRqyjbqQk4AjxZ9kCGQrfLRIZEFR8ECL5vDJQdF4QRHoXarseeIiFIZg6M0Iu9YC2PWkVTaUjshuy1o5sizk6qbDJAgCD59R1JjttqdapLBcS6tSUeH5MQhawR4s4D2oGW1SDNHgbsajyj6jNQGR6IosqxGRGmLwVEa6ckEZPUHz0o7zYINgZQyR+rPR1OW1dTuVJPIwVFdfDJH3hlHcQqOgmR3LPK5alHqOVIE0A2tVu/rqAxmOuxOOF3uUQPBslk5LKsRUQpjcJRGvMGR+rJaVBqyPSWfDBUlH5Ni1pE1jOnYSoM9O9a218cncyTvVItTcCTvVgsy5yjizJF0vprT+/co9RsB6jNH0nq0GiHo8E+W1YgolTE4SiPBSibdieZW/u4mZAO+2/m9gVl4v4aD4jwIMp4zjgDlAbGBE7Ij7jkKkjk63ObNHKkPjuzyeoIdQ+ItqzFzRESph8FRGunJ+WpqG7LVHDzbXUO28nk67U7FVv7wMkeDStyZo/oWq5zViSV5OnYcDp0Fgjdke3erRVpWCwygI8kcdZXJkm7vsPueEUdElAoYHKWRYCWTUFwuUc5OqG3ItjpcAUMm1TZkA8qymmLOURhb+QF3303vPDMAYFscSmtN8qGz8cocuTMxdkcMGrKDZKUaIgqOgr8nynWy74iIUg2DozQS7m415ZDBbo8PURwN0m73Db7Cyhwpy2pS1irMzBHgnZQdj9Jawhqyg+xWi+T4EEB5zIyy56gnZbXQwZpOq5HLrPGaR0VEFC0MjtKId8CfuuDI52yzbjJHBq0GWs+Qog5b8OBITeYoGlv5Ae+k7O1xOEYknkeHAMqG7GDHh0R/Qvbhtp5kjjy750L0QLHviIhSFYOjNBLubjXpA1KrEbodbigI3l1JbVbfDzv5+JBuDp4FFD1Htp5v5QcUTdlxCI6akqAh27uVP9KyWrCeI2/myOZw+QTNXVFT5ssxu+/jjjUiSjUMjtJIsA++UKTym9qzzaSymbIp2+Zwwe7Zcp6hD2Mrv93pff0eZI7k7fxxmHUk71aL81Z+qZHZ5RKjcvAsoCyrBe85AtRlj1pUzF2S7mNZjYhSDYOjNBJsm3YoUuamu34jSbDMkbLEFm5Zrae71QBgYEkWBMFdElIOMYwF7261OE/IdriDzna7E6Jn5FG2MVplNfd7L4qiz1Z+QGVwpCJYkwZBsqxGRKmGwVEaCbusZle3U00iNWUrG7LbPCU1g1bjc/htl88hT9r2BkfhHDzrfR4dKvIzAADbYlhaE0VRnhqdlxGfrfz+DdlS5kWnEXqUZVOS+9I8f/ftijPupDPr1GWOuu+B4iBIIkpVDI7SSLjHh1jD7PnJkMpqiinZ4TRjK6/rVAyBVJu58heP0lqH3SkHKfFryHY3vnuDI2+WJtjAxXAYtFqf55ZmHGUYtCjLMQGAqtlRLSp6oKT7LNzKT0QphsFRGgl3QnZnmJkjaUp2m2JKttyMrTI4UvYcdchltZ79GnrPWItd5kgqqem6OCYjFgyeMqPUkK2mv0ct/8xRg6ekVphlkDM94WWO1OxWY+aIiFILg6M04p2QrXa3Wrg9R56px7YIMkf6wLJaT3arAfEJjpQzjiLN2qglZY7sfpmjSI8OAQJLr1LmqDDTKPdURSs48jZkM3NERKmFwVEaCbesFm7mKCNU5kjlB7fZ4H4tnyGQPQyOpEGQ2+paIYpiN1f3TLybsQFFQ3aQslq0nlvKSknb+IuyDGEGR91ns7iVn4hSFYOjNBL2Vn6Vh85KpABI2XPU5vmzWWWAo8wcWe09HwIJAAOKs6AR3B/mh1pis2Mt3ofOAoqGbId/cBSFsprf74g0ADLczJGa0QIsqxFRqmJwlEa8E7LDGwKpNnMT7PBZqcSmNnNkCraVv4eZI5Nei8rCTADu7FEsNHvOVYvXTjVAOSHbnQ3zHjob/bKaNAahUJE5UhPMWFQEbFLgxLIaEaUaBkdpxBjunCN7mJkjOTjyfthJJTa1zcq+c45cPrf1RO989wG0Nc0dPX6OUBJZVpMyR1KWJtJz1YI9t9xzlKU+c2R1OOXHh56Qza38RJSaIv/XlpKGVDJRnskVipQ5Mqocwig1ZLcFachWHRwFPT6k5zF6qWf7eX0aldX8J2RHs+fIvy9NGgBZlGWQy3ndBUfKTFCow4ZZViOiVMXgKI30NHOkNjjxDnAMbMjOCPEhqRTs4Fm1wVkw0uDCektnj58jlCbFbrV4Meh8d6tZormV37/nSLFbzXOusOrgKMuokw8jDkYqA7ZaHXC5RGhCXEtElExYVksjPe05Up058vQVtQUZAqk2cyT1F7XbnGH3PAVTku3OHNVZYpQ5SkRZTes756g1hrvVGuSymvo5R2oGQALesppL9N3h2FOiKAYcekxEFAsMjtJIjw+eVZk5knqOLJ12HG614nCrFUc8u53Ub+UPXGNkZTV35qiuJTaZo+YEZI70uvjMOXK5RDS2BTZkN3UTHKkN1ow6jTyzKRpN2Xe9uR5jHlqMfY3tET8XEVEoLKulkbDnHDnCK2tJgc3GgxaM/fMXvveFuZVfKaLMkdRzFKPMUZNnt1oitvJLf48tVmm3WuRrMOm9z93UYYfLMx6qIMMgn5lnc7jQaXd2+feiZqcaAAiCgByTHofbbLB02tEL5ojWvnJ3I6wOF9bvb0JFQUZEz0VEFAozR2lEzhypnZAtn22m7tdgeO9c9A3yoZSXoceJ/QtVPYf/B65OI8gNyD1Rku3pOWrpjMkgSG9Ddvy38semIdtbspMGQOZn6KHTapBl0KnqO1JbVgMUO9Y6IssciaKIQ5711jbHJktIRCRh5iiNGHqYOVJ7tlmOSY9ld08Kep/aozW0GgEGnUbueYkkawQAxZ7gyO4UcaTdjoLMwCCmztKJ5dsbcP6oXvJ7pJa0lT++DdlScOQO9qQyVjS38lsdLkW/kfs91GgE5Jj1aGq3o7nDLu8E9BdOmc876yiyHWstVof8O1PD4IiIYoyZozQSblnNmzlSH6AIghD0KxzK0lok/UaAOxMiBUT1XfQdzft4M+56az0+/OlgWM/tdIlyIJCIsprTJfqsITq71bzPLb1fhYqAUs2so3DWI2/njzA4Uk5AZ+aIiGItbYKjr776qssP7lWrVgEA9uzZE/T+77//PsGrj47wd6tFPmeoJ5TBUSTb+CVSaa2rHWvb693Ts3fUhzdFWzmfJ65zjhTZrdZOhzy3KpplNQA42OQOMoo8mSNAERy1d19WUzOxW1pzpGW1BkVwFKuBn0REkrQpq02cOBE1NTU+t913331YsmQJxo0b53P7F198gWHDhsnfFxaq65dJdtIHn93pzjiEmkEDKDJHUQhQwmE2RC9zBLibsrfUtqCui1lH+490+PyvWtKurUyDNqK+qHAZFK8lDWkEgCyVs6RCPrci8DrY5H4/CrPCyxypOVdNImWOIi2rSf1GADNHRBR7aRMcGQwGlJWVyd/b7Xa89957+O1vfxtQ9iksLPS5Nl0ojwGxOVw+QUgw4R48Gy0mn7Ja5IFZqSdzFOzwWUunXf6g338kvC3gTe3xP1cNgLz9HQAaPaMSsoy6qAxR1GoE6DQCHC7RGxxlejNHamYdhVVWM3syRxFu5Vf+3da1WFUF/0REPZU2ZTV/77//Pg4fPoyrr7464L5f/OIXKCkpwcknn4z3338/AauLDWWQo6a0Fo0hjD1hVmSLovHaJdKsoyCZowOKbFG4maNEHB0CuPu6pADpsCc4ikZJTSL9nhzoYebIEsZutewgR4jsOtSK3/73R/y0v0n1mhsUmSOnS/T5nogo2tI2OHrppZcwdepU9OnTR74tKysLTz75JN566y189NFHOPnkk3HhhReGDJCsVissFovPV7LSaTXyf02racoO9+DZaFEeNRLJobMSaVdVsOBIGRDVt1jln9mfpdOO//243+f+RAVHgLe01hiD4EgqrUmZo6Iwg6NwdqvlyLvV3I+xOpy4+bW1+GD9Qfz5o82q1+yfFeSONSKKpaQPju69994uG62lry1btvg8Zv/+/fjss89wzTXX+NxeVFSE2bNnY/z48Tj++OPxyCOP4KqrrsLjjz/e5evPmzcPubm58ldFRUVMfs5oCed8tURljkxR3K0GeI8QCXb4rH8pTQoI/P3jq524c9F6PPj+Rvm2REzHlkhN2d7gKHprkHrMpFJXYZCG7FCHxbaEcdabPOfI85inPt+GLbUtAIAfdjdi7+E2VWuWxg5I2HdERLGU9MHRXXfdhc2bN4f86t+/v89jXnnlFRQWFuIXv/hFt88/fvx47Nixo8v758yZg+bmZvlr3759Ef9MsaQ8HqI7icocKXuhwhkj0JUS+fDZwODogF8p7UAXwdGGA80AgLfW7MeuQ+5dbYmYcSSRGsClg2GjcXSIxH/oZ8+38odRVut04Ptdh/HCN7sAAL3z3NOy31mzX9WapcyRdIZfLXesEVEMJX1DdnFxMYqLi1VfL4oiXnnlFfzmN7+BXt/9h9q6detQXl7e5f1GoxFGo7HL+5ONOytgV1VWC/fg2Wjx6TmKwmtLZTVpSrayAd+/z6irvqPdDe4MhtMl4qnF2/Dsr8bIwVFOAstq0m61qJbV/HbeBcscqdmtpuY4E6msVtfcibveXA9RBH55fAUmDizCbf/9Ee+sPYA7pgzuttlcCo6G9crBqj1HUNPFzkQiomhI+uAoXEuXLsXu3btx7bXXBty3cOFCGAwGjB49GgDw7rvv4uWXX8aLL74Y72XGjFFxdlZ3vGW1xM05isZrF2d1PSV7f5O7rNY7z4wDTR1Bd6x12p0+GaUPf6rBTZOavWW1OB4dIjHEsqymeM/1WsFnXlF3wZHD6UK7zelZk/rMUa0nmKkoMOOP5w2FTiMg26TDgaYOrNh1GCcNLOryOVwuUQ4Sh/fOxao9R1hWI6KY6tEn05/+9Ce0twd+yHR0dOBPf/pTxIuKxEsvvYSJEyfi2GOPDXr/Qw89hLFjx2L8+PF47733sGjRoqA72lKV2rKa3emC03PqaLwzRyZDdLfyG3QaOSDyb8qWMkXj+xf4fK9U3dgOUXR/2J8/qhcA4InPtqI5AYfOSgx+ZTU1AxfVUv59F2YafTJt3QVHUtYIUHecibSVHwA0AvDXy45DllEHk16LX3je67dWhy5VN3fY5aNUhvfKBcCGbCKKrR4FR3PnzkVra+C04fb2dsydOzfiRUXi9ddfx7fffhv0vhkzZmDTpk1oa2tDc3MzVq5ciUsvvTTOK4wt+fDZbjJHyvvVHjwbLcrMUTR2qwHKKdneD82WTrtcGjuxyj3oM1hwtOuQu6TWvygTs88cDK1GwJdbD2H13iMAEtWQ7Q5YlHOOokVZVlNu4we6D46kfiOTXqNqMKayJHnjaQMwrrJA/n76OPfmhk821IY8XkTatp+XoUffQvfBx8wcEVEs9ehT0b+vQ7J+/XoUFBQEeQTFi9rdasot63FvyI5yWQ1Q9h15m7KlUllehh7HlmcDCD4IUuo3qirKRFVRJi7zfGjLDdkJyBzpY7iVXxkMK/uNAG8wY3W4go49sISxUw1w9yVdPq4C544sxx1TBvvcN6pPLgaVZMHqcOGjn2q6eAZvv1FxlhFlnr/n2mZ3fxkRUSyE9cmUn5+PgoICCIKAwYMHo6CgQP7Kzc3FmWeeicsuuyxWayUV1J6vJmWODDpN2AfHRsoc5bIa4M0c1SsyR/sb3cFRn3wz+uS7Mw51FmvAe7O7wZ0FrSrKAgDcNnmgzzEbiWzI9p6rFs2t/N6frSjTN3OUbdRB+nUItp0/nJ1qkkcvHYnnfjXG5z0F3MMuLx3rnkMWqrQmHR1SlGWUg2Cb0yUHjkRE0RbWf47Onz8foihi1qxZmDt3LnJzc+X7DAYDKisrMWHChKgvktSTPlS7Lat5sgKmOGeNAN+AKBpb+QHlIEhv5kjKEvXJy0B+hh4ZBi3abU4cbOpEVVGmfJ1UVqsqdt9WnmvGb07shxeX7waQmLKafyChpr9H/XMreo78ymoajYAckx7NHe5jV0o876ukNYyjQ9S4aHRvPPbZVqytbsKO+lYMLMkKuEbOHGUbYdBpUJRlREOrFTXNnQGZLyKiaAjrX9wZM2YAAKqqqnDSSSdBp0u7zW4pT23PUad06GycB0ACfmW1KAVnpdKsoxZF5uiIN3MkCAJ655mxvb4VB450+ARHUlmtv+K2m08fiHd/PAABvqfWx4v/dvtYHB8CBJbVAHcwKAVH/lqsnvEGUVpPSY4Jpw0uxtIt9Xhn7X78v2mBGymUmSMAKM81oaHVitrmTgzvnRtwPRFRpHr0yZSdnY3Nm72j/9977z1ceOGF+P3vfw+bjanuRJLLal0ckyGRSkvx3sYP+PccRSc4K84OzBxJPUd98s0+/6vsO2put8vnlykDpoJMAz69/RR8fPspcZ8gDiCg2VnNTCG1fIKjzMAxBaGasntSVuvOdE9p7d21++FwBgb1DS3uv59iT+m0LNf9d81ZR0QUKz36ZLzhhhuwbds2AMCuXbtw+eWXIyMjA2+99RbuueeeqC6QwuPdyq8ycxTnbfxAbHqO5MyRJTBz1NvTbyT1HSl3rO32HF9RmmNEpt+OsJIck1yuize9LnaZI2XJLlhWTE1wFM3dc5OHlCLbpEOdxSofLaLkzRy5A7lyT3BUxx1rRBQjPQqOtm3bhuOOOw4A8NZbb+G0007D66+/jgULFuCdd96J5vooTOq38ifm6BDANyCK1lZ+KYg51GqFyzO/Se45CpE58jZje7NGycC/rBbV40NC9BwB3gb0YMFRuLvV1DDoNDi2zL2bcOehwBEhyp4jwPt3zVlHRBQrPd7K73K5P3y/+OILnHPOOQCAiooKNDQ0RG91FDa1QyATdegsEJut/EU+U7JtaLU6cMSzFb+3HBwFyRxJzdhFgY3AiWTQ+e4gjNVutWA9R/EuqwGQG7F31gcGR9KcIyk4kjJHtZb4nq92sKkDGw82x/U1iSgxevTJNG7cOPz5z3/Gf/7zHyxbtgznnnsuAGD37t0oLS2N6gIpPN6eI3VzjhKROYpFWc2g08j9M3UWq3zgbK5ZL/freDNH3g/VnUGasZOBMnNk1GkCdq9FwmfOUZg9R9HerSYZUOwJjjzBqsTpEnG41TvnCFD0HMU5c3TViytx4XPf+jT9E1F66tG/uPPnz8fatWtx66234g9/+AMGDhwIAHj77bcxceLEqC6QwhPuhOx0yRwBkLed17d0BpTUlH+ua+mUM2vezFFyBUfKhuxoByJS4CUd4+EvdOZIKqtFN3MkBUc7/DJHR9ptcImAIEA+IqY81/33GM9BkA6nC7sa2mB3ithRF5jdIqL00qN/4UaOHImff/454PbHH38cWm38P2zJK9yyWkIyR8o5R1FsCC/JNmJzDVBvsaLDkxlTBkcFmQaY9Bp02l2oaepEv8IM7zb+4iQLjnTK4Ci6gYg0viFYvxHgDY5CDYGM5llvgDc42t3QBqdLhFbjLitK/UYFGQboPEGdNCW73eaEpdMRl7PvlAMngx1BQ0TpJaJ/4dasWSNv6R86dCjGjBkTlUVRz0nBjk3lEMiENGQbvK8ZzcyVtGOtztIpNw5LfUaAeyJzn/wM7KhvxYGmDpj0WnTYndBqBFQUZAR9zkQxaGMYHHn+zoOV1AC1u9WiG5D0zjfDqNPA6nBh/5F29Ct0B6v+zdiAuyybl6FHU7sdtc2dcQmOGloVwVETgyOidNejf3Xr6+tx+eWXY9myZcjLywMANDU14fTTT8cbb7yB4uLiaK6RwiBlBZK5rGbUaXH5uAq0WO3y9uxoUJ6vdrjN/aGqzBxJ3++ob8X+I+3yMRl9CzJUHaIaT4YYZo6GludArxVwfFXwcxATUVbTagRUFWViS20Ldh5qlYOjBr8BkJKyHBOa2u2oae7AMZ6dbrEk/T4Bwc/nI6L00qNPhN/+9rdobW3Fxo0b0djYiMbGRmzYsAEWiwW33XZbtNdIYVA/5yhxmSPAfd7W368cG9Vz3UrkI0Q6FdOxfTNCyqZs5YGzycYncxTlLM3w3rlYd/9ZuDfINGogMbvVAGCAvGPN25QdLHMEKHasxakp+3Ary2pER5Me/Qv36aef4osvvsCQIUPk24YOHYrnnnsOZ511VtQWR+GTG7K7nZCduMxRrEiHz9a1WH2ODlFSbufvsLnfo2QMjvRab9AYzXPVJP4DL5W6Co5cLhGtttjsVgOAgUGasv238UvKPE3Z8dqxJq0DgLwTkojSV4/+1XW5XNDrA/9x1Ov18vwjSgy1maNE9hzFilRW23u4DU1+M44kykGQ0od/UgZHMSyrdUcaAtlpd8HqcMoBd5vNAWlzWEwzR4pBkFLmyL/8Gu/MkbLnqNbSCYfTJTeIE1H66dH/u8844wzcfvvtOHjwoHzbgQMHcOedd2Ly5MlRWxyFT55zlMQHz8aK1JAtBUY5Jl3AmWTKzFGwA2eThSGGW/m7k23Uyf1YyuyRVFIzaDUxyTgO8OwY9AmOusoc5UiDIONVVvNmjpwuMW6vS0SJ0aPg6Nlnn4XFYkFlZSUGDBiAAQMGoKqqChaLBc8880y010hhkD5Uu9/Kn36Zo6IsI5QtTP79RgDQO88zI8fSiepGd2Nt/+Lkmo4N+DZkR3vbfHc0GkEOKpvbA4OjWJT5AKB/URYEATjSbpe3zkuHzgY0ZMe756jN90Bt9h0Rpbce/StXUVGBtWvX4osvvsCWLVsAAEOGDMGUKVOiujgKn7xbrdsJ2emXOdJr3VOypRKIf78R4C7PSFvGnaIIs14rZ5ySiTJzFM1z1dTKNevR3GH3yxzFZqeaxGzQoneeGfuPdGBHfStOqCroMnNULk/Jjk+QIvUcaQTAJTI4Ikp3YaUNli5diqFDh8JisUAQBJx55pn47W9/i9/+9rc4/vjjMWzYMHzzzTexWiupoLrnyJM5MqVR5ggASrJN8p+DZY7cs468QVNVUWZUd8xFSywnZKsRrCk7ljvVJN5jRFphd7pwpD105sjS6UCb1RGz9Uik3WqDStxjA9iUTZTewvpknD9/Pq677jrk5OQE3Jebm4sbbrgBTz31VNQWR+ELe0J2GmWOAKBEkQUKljly3+4NmqqSbDK2JJEN2UAXwZEnCIn2aAElOTiqb0Vjmw2i6J6BlJ/h25CdbdLLGbVY9/+IoihnjkZV5ALgrCOidBdWcLR+/XpMmzaty/vPOussrFmzJuJFUc+pHQKZ6DlHsVLqkznqKjjy3p6MzdiAX1ktWYKjGJfVAGBAibcpW9qpVphpkI8TUYpX31GbzSn//2lURR4AltWI0l1Yn4x1dXVBt/BLdDodDh06FPGiqOeUx4eEOpQzHeccAfDpHwpWVvO/PRm38QOAQecNBuLdkA14t/MHL6vFLnMkzzo61Cr3G/mX1CTevqPYBkcNniAtw6D1ltV4hAhRWgsrOOrduzc2bNjQ5f0//fQTysvLI14U9ZwyExQqe5SumaPiHG/myH/GkcS/5ygZGRQHOCdPz1E8Mkfu4Gj/kQ7s9+wm9G/Glsjb+WPclC0dHVKYZZB/dw42dcDp6vo/PogotYX1r9w555yD++67D9OmTYPJZPK5r6OjAw888ADOO++8qC6QwqM85f60x7+Epotm43rPfw2nXebI80GaY9J1eSCpb1kt+bbxA4BekTlKmp6jODRkF2Ya5J1yP+w5AiAJMkeeZuzCTCNKc0zQaQQ4XCLqWzpRnhs8ACei1BbWv3J//OMf8e6772Lw4MG49dZbccwxxwAAtmzZgueeew5OpxN/+MMfYrJQUkevFdC/KBO7GtpQZ7GGvNak16Bvkp1GH6lhvXOh1woYVxn8UFUAGFiShRyTDr3yzMjNiH9WRg1pt5pWI8CcgABWCo4snuCo3ebAwSZ3EBLL4EgQBAwozsTa6ias3HUYQIjMkScwiXXPkbRTrSjLCK1GQHmeCfsaO7D/SAeDI6I0Fda/cqWlpfjuu+9w0003Yc6cOXJPiyAImDp1Kp577jmUlpbGZKGkjiAI+Oi2U3ymDHelV54ZBZmGbq9LJb3zzPh+zmS5ZyaYbJMe39xzhjxNPBn1yjWjKMuIysKMhIwakIKjNXuPYOpfv8b2+hZIVaQ8c2x/ZwaWZGFtdZOc3ewqOCrPc2eOvt3ZgIXf7cGvT+wHTZDG7UgdbvU9wqRPXoYnOGrH8SGCcCJKXWH/J2C/fv3w8ccf48iRI9ixYwdEUcSgQYOQn58fi/VRD5gNWgzvnZvoZSRMYRdlGKVkzRhJzAYtvrnndJ8DaONJCkiOtNtxxDMluzTHiPFVhThzaGz/A2iA38Ry/3PVJCcPLMKE/oVYseswHnh/Iz5YfxCPXDISA0uiWyqVtvEXetYh9bJx1hFR+upxfjw/Px/HH398NNdCRApmQ+L6wcb1y8fsMwfD5nBhZJ9cjKrIkw/2jTX/4KirzJFeq8Fr147Hayv34pFPtmD13iM45+lvcPuUQbh50oCoZdwa2rw9R4Dy8GIGR0TpKv6dnkSU9DQaAbdNHpSQ1/bP/BSHyARqNAJ+PaESZwwpxR/+9zO+2noIj3+2FX0LMnD+qF5RWY9cVsuWgiN3nx638xOlr+RtuiCio1KffLPPEMyuMkdKvfPMeGXm8fjNhH4AgC8210VtPXJDtqc/Tzq8mJkjovTF4IiIkopOq0FlkTs7o9cKXY5k8CcIAs4e7p6z9u2OBri6mEO0va4Fd7+1XvUuN2/PkW9Z7cCRji5fg4hSG4MjIko6Ut9RUZYxrN6hMf3yYNZr0dBqw5balqDX/OXjzXhrzX48++X2bp/P4XTJDelSQ3Z5rglajQCb0yUHTkSUXhgcEVHSkfqO1JTUlIw6Lcb3d2+vX74j8CgjS6cd3+5wz09aurk+5BE7ANDY7i6paQTIh9/qtBp5Ovc+ltaI0hKDIyJKOqP65AEI3LmmxskDiwAA32xvCLjvyy31sDndx+ocbO7EphpLyOeS+o0K/A6/7S3vWGsPe31ElPwYHBFR0pk8pASvXjMeD54/LOzHnjKoGADww+5G+QxByWcbawEAUqXui031IZ9L7jfK9M1gyX1H3LFGlJYYHBFR0hEEAScPKurRsM7BpVkoyTbC6nBhzd4j8u2ddie+3OIutV05vi8AYMmW0LvapMxRod8gyj7csUaU1hgcEVFaEQQhaGntm+0N6LA70SvXhNsmD4IgAD/tb0adpetda/471STyrCMGR0RpicEREaWdkwe5gyNlU/anG9wltanDy1CSbcJxFXkAgCWbuy6tHW6TDp31zRyx54govaVMcPTwww9j4sSJyMjIQF5eXtBrqqurce655yIjIwMlJSW4++674XA4fK756quvMGbMGBiNRgwcOBALFiyI/eKJKK6kzNHGgxY0ttlgd7rkwZDThpUBAKYMcZ8RF2pgZEOLdOhs1z1H3e14I6LUkzLBkc1mw/Tp03HTTTcFvd/pdOLcc8+FzWbDd999h4ULF2LBggW4//775Wt2796Nc889F6effjrWrVuHO+64A9deey0+++yzeP0YRBQHJTkmHFOaDVEEvtvZgJW7GtHcYUdhpgHjKt1b/ScPKQHgHhjZYXMGfZ7D8rlqvpmj8lwzBAHotLvka4gofaRMcDR37lzceeedGDFiRND7P//8c2zatAmvvvoqjjvuOJx99tl46KGH8Nxzz8Fmc//j9fzzz6OqqgpPPvkkhgwZgltvvRWXXnop/vrXv8bzRyGiOJBLa9sb8OnGGgDAWcNK5S35x5Rmo0++GVaHC8t3BG77B7znqvn3HBl0GpRmu2cdsSmbKP2kTHDUnRUrVmDEiBEoLS2Vb5s6dSosFgs2btwoXzNlyhSfx02dOhUrVqzo8nmtVissFovPFxElPyk4+mZ7Az7b6C6dTfWU1AB347ZcWtsUvLTW0MVuNcBbWmPfEVH6SZvgqLa21icwAiB/X1tbG/Iai8WCjo7g//U3b9485Obmyl8VFRUxWD0RRdv4qgIYtBocaOrAoRYrso06TBxQ5HONFBwt2VIfcE6aKIrybrXirMBJ3coz1ogovSQ0OLr33nshCELIry1btiRyiZgzZw6am5vlr3379iV0PUSkToZBhzH98uTvJw8pgUHn+0/eCVUFyDbq0NBqxfr9TT73tdmcsDrc07SDZY68O9YYHBGlG10iX/yuu+7CzJkzQ17Tv39/Vc9VVlaGH374wee2uro6+T7pf6XblNfk5OTAbDYHfV6j0QijMbzznYgoOZwyqBjf72oEAEwbXhZwv0GnwamDi/HRzzVYsrkeo/vmy/dJ/UZmvRYZhsB/KnvnuWcdHeSUbKK0k9DMUXFxMY499tiQXwZD4H+xBTNhwgT8/PPPqK/3zixZvHgxcnJyMHToUPmaJUuW+Dxu8eLFmDBhQvR+KCJKGqd6jhIx67U4dXBx0GumDHXvWvPf0h+q3wgASjyH4h7yBFFElD4SmjkKR3V1NRobG1FdXQ2n04l169YBAAYOHIisrCycddZZGDp0KH7961/jscceQ21tLf74xz/illtukTM/N954I5599lncc889mDVrFpYuXYo333wTH330UQJ/MiKKlRF9cvHoJSNQlmsOmv0BgEmDS6DVCNhS24K9h9vQrzATgHc6tv+MI0mRJziSZiERUfpImYbs+++/H6NHj8YDDzyA1tZWjB49GqNHj8bq1asBAFqtFh9++CG0Wi0mTJiAq666Cr/5zW/wpz/9SX6OqqoqfPTRR1i8eDFGjRqFJ598Ei+++CKmTp2aqB+LiGLs8uP74rQuskYAkJ9pwIn93bOPPv65Vr5dOlfNfzq2pFgKjlptHARJlGZSJnO0YMGCbqdZ9+vXDx9//HHIayZNmoQff/wxiisjolR3zohyfLvjMD7+uQY3TRoAQDHjKDN45kgaDGlzumDpcPTokFwiSk4pkzkiIoqVqcPKoBGAnw80o/qwe26RPB27i8yRSa9Ftsn935fsOyJKLwyOiOioV5RlxIn9CwEAH29wT9PurucI8M4/amBwRJRWGBwREcFdWgOAj3/2DY66yhwB3sCJwRFRemFwREQE9xwkjQD8tL8Z+xrbFQ3ZXWeOirLdgRN3rBGlFwZHRERwB0Hjq9yltU821HTbcyQ9BvDORCKi9MDgiIjI45yR7tLaB+trcKTdExx1sVsNYFmNKF0xOCIi8pim2LUmioAgAAWZ3WeODrGsRpRWGBwREXkUZxtxQlWB/H1BhgFajRDyeoCZI6J0w+CIiEjhXM+uNSB0vxHgnZ7NniOi9MLgiIhIYerwMgieZFGofiNAUVZrtfIIEaI0wuCIiEihJNuE4yvdpTXpcNmuSGU1m8OFFqsj5msjovhgcERE5GfmxEoA8Ok/Csak1yLL6D5ChLOOiNJHyhw8S0QUL+eMKMeGuVORadB2e21RlgGtVgcaWm3oXxyHxRFRzDFzREQURJZRB0HoeqeahLOOiNIPgyMioghw1hFR+mFwREQUAfl8NWaOiNIGgyMioggUZ5kAMDgiSicMjoiIIiBljg61cBAkUbpgcEREFAE2ZBOlHwZHREQRYHBElH4YHBERRaBYERzxCBGi9MDgiIgoAlLPUafdhTabM8GrIaJoYHBERBSBDIMOGZ5J2px1RJQeGBwREUWIfUdE6YXBERFRhIqyPIMgmTkiSgsMjoiIIlSczcwRUTphcEREFCH5fLVWDoIkSgcMjoiIIsSeI6L0wuCIiChCRVJZjT1HRGmBwRERUYSKpYZsZo6I0gKDIyKiCHl7jhgcEaUDBkdERBGSe45a2JBNlA4YHBERRUjqOeqwO9FmdSR4NUQUKQZHREQRyjRoYda7jxBh3xFR6mNwREQUIUEQ5ANoGRwRpT4GR0REUSA3ZbPviCjlMTgiIooCDoIkSh8MjoiIooDBEVH6YHBERBQF0iDIQ5ySTZTyUiY4evjhhzFx4kRkZGQgLy8v4P7169fjiiuuQEVFBcxmM4YMGYKnn37a55qvvvoKgiAEfNXW1sbppyCidCUfIcLMEVHK0yV6AWrZbDZMnz4dEyZMwEsvvRRw/5o1a1BSUoJXX30VFRUV+O6773D99ddDq9Xi1ltv9bl269atyMnJkb8vKSmJ+fqJKL15y2psyCZKdSkTHM2dOxcAsGDBgqD3z5o1y+f7/v37Y8WKFXj33XcDgqOSkpKg2Sciop5izxFR+kiZslpPNDc3o6CgIOD24447DuXl5TjzzDPx7bffhnwOq9UKi8Xi80VE5K9YKqux54go5aVtcPTdd99h0aJFuP766+XbysvL8fzzz+Odd97BO++8g4qKCkyaNAlr167t8nnmzZuH3Nxc+auioiIeyyeiFFPkachusznRYXMmeDVEFImEBkf33ntv0AZp5deWLVvCft4NGzbgggsuwAMPPICzzjpLvv2YY47BDTfcgLFjx2LixIl4+eWXMXHiRPz1r3/t8rnmzJmD5uZm+Wvfvn09+lmJKL1lGXUw6tz/pLK0RpTaEtpzdNddd2HmzJkhr+nfv39Yz7lp0yZMnjwZ119/Pf74xz92e/0JJ5yA5cuXd3m/0WiE0WgMaw1EdPQRBAFFWUYcaOpAfYsVFQUZiV4SEfVQQoOj4uJiFBcXR+35Nm7ciDPOOAMzZszAww8/rOox69atQ3l5edTWQERHr36FGTjQ1IEd9S0Y2y8/0cshoh5Kmd1q1dXVaGxsRHV1NZxOJ9atWwcAGDhwILKysrBhwwacccYZmDp1KmbPni3PLtJqtXIANn/+fFRVVWHYsGHo7OzEiy++iKVLl+Lzzz9P1I9FRGlkRJ9cfLfzMNbvb8blxyd6NUTUUykTHN1///1YuHCh/P3o0aMBAF9++SUmTZqEt99+G4cOHcKrr76KV199Vb6uX79+2LNnDwD3rKS77roLBw4cQEZGBkaOHIkvvvgCp59+elx/FiJKT6P65AEAftrflNB1EFFkBFEUxUQvIpVYLBbk5uaiubnZZ5AkEdH+I+04+dEvodMI2DB3Kkx6baKXREQe4Xx+p+1WfiKieOudZ0ZBpgEOl4gttS2JXg4R9RCDIyKiKBEEASP75AJgaY0olTE4IiKKopGevqP1+5oTuxAi6jEGR0REUTTKkzn6+UBTYhdCRD3G4IiIKIpGeIKjHfWtaLM6ErwaIuoJBkdERFFUkm1Cea4JLhHYcIClNaJUxOCIiCjKRsqlNQZHRKmIwRERUZTJTdn7GRwRpSIGR0REUcbt/ESpjcEREVGUjeydBwDYe7gdze32xC6GiMLG4IiIKMpyM/ToV5gBAPiJW/qJUg6DIyKiGBgpH0LLviOiVMPgiIgoBqRhkOv3NSV2IUQUNgZHREQxIGWOuJ2fKPUwOCIiioFhvXKgEYCa5k7Ut3QmejlEFAYGR0REMZBp1GFgSRYA4CceQkuUUnSJXgARUboa2ScP2+pasXrvEQwqzUJNcydqmzshCMD5I3tBoxESvUQiCoLBERFRjIzsk4u31+zH88t24vllO33uczhFXDK2T4JWRkShsKxGRBQjpw0uhkHn/mfWqNOgqigTVUWZAICPf65J5NKIKARmjoiIYqRfYSbW/HEKnC4RuWY9BEHA1toWTJ3/Nb7Z0YA2qwOZRv4zTJRsmDkiIoqhbJMeeRkGCIK7v2hwaRb6FWbA5nDh622HErw6IgqGwRERURwJgoCpw8oAAJ9trE3waogoGAZHRERxdtbQUgDAki31sDtdCV4NEfljcEREFGej++ajKMuIlk4Hvt91ONHLISI/DI6IiOJMqxFw5tASAMDnG+sSvBoi8sfgiIgoAc4a6u47WrypDi6XmODVEJESgyMiogSYOLAQmQYtai2d+ImH0xIlFQZHREQJYNRpMelYqbTGXWtEyYTBERFRgkhb+j/fxL4jomTC4IiIKEEmHVMMvVbAjvpW7DzUmujlEJEHgyMiogTJMekxYUARAO5aI0omDI6IiBJo6jD3QEhOyyZKHgyOiIgS6LTBxQCADQeaOS2bKEkwOCIiSqDeeWZkGrRwuETsPdye6OUQERgcEREllCAIGFCSBQDYUc+mbKJkwOCIiCjBBhS7gyPuWCNKDgyOiIgSbKAnc7STmSOipMDgiIgowQYUZwIAdoTIHLVaHWizOuK1JKKjGoMjIqIEU2aORDHwEFqrw4mzn/4a5/7tG+5oI4qDlAmOHn74YUycOBEZGRnIy8sLeo0gCAFfb7zxhs81X331FcaMGQOj0YiBAwdiwYIFsV88EVEI/QozodMIaLM5UWvpDLh/c00L9jV2YM/hdmypaUnAComOLikTHNlsNkyfPh033XRTyOteeeUV1NTUyF8XXnihfN/u3btx7rnn4vTTT8e6detwxx134Nprr8Vnn30W49UTEXVNr9Wgb2EGgOA71n7a3yT/eW31kXgti+iopUv0AtSaO3cuAHSb6cnLy0NZWVnQ+55//nlUVVXhySefBAAMGTIEy5cvx1//+ldMnTo1quslIgrHwOIs7DrUhp31rThlULHPfev3Nct//rH6CGZMrIzz6oiOLimTOVLrlltuQVFREU444QS8/PLLPvX7FStWYMqUKT7XT506FStWrOjy+axWKywWi88XEVG0SX1HwZqyfTNHTQH3E1F0pUzmSI0//elPOOOMM5CRkYHPP/8cN998M1pbW3HbbbcBAGpra1FaWurzmNLSUlgsFnR0dMBsNgc857x58+SsFRFRrEizjvzLaq1Wh0/AVN3YjoZWK4qyjHFdH9HRJKGZo3vvvTdoE7Xya8uWLaqf77777sNJJ52E0aNH4//9v/+He+65B48//nhEa5wzZw6am5vlr3379kX0fEREwcg71g61+dz+8/5miCLQK9eEwaXua9Yxe0QUUwnNHN11112YOXNmyGv69+/f4+cfP348HnroIVitVhiNRpSVlaGurs7nmrq6OuTk5ATNGgGA0WiE0cj/QiOi2JKOEDnUYkVzhx25Zj0Ab0ltZJ885Jr12FbXirXVRzBlaGlXT0VEEUpocFRcXIzi4uLuL+yhdevWIT8/Xw5uJkyYgI8//tjnmsWLF2PChAkxWwMRkRpZRh3KckyotXRiR30rxvbLBwD8tN/djD2yIhcFGQYsWr0PPzJzRBRTKdNzVF1djcbGRlRXV8PpdGLdunUAgIEDByIrKwsffPAB6urqcOKJJ8JkMmHx4sX4y1/+gt/97nfyc9x444149tlncc8992DWrFlYunQp3nzzTXz00UcJ+qmIiLwGlmSh1tKJnYe8wdF6T+ZoVJ88FGcb5dscThd02rTbU0OUFFImOLr//vuxcOFC+fvRo0cDAL788ktMmjQJer0ezz33HO68806IooiBAwfiqaeewnXXXSc/pqqqCh999BHuvPNOPP300+jTpw9efPFFbuMnoqQwsCQLy3c0yGesHW61Yv+RDgDAiD65yDLokG3UocXqwLa6VgztlZPI5RKlrZQJjhYsWBByxtG0adMwbdq0bp9n0qRJ+PHHH6O4MiKi6JDPWPMERz8dcJfU+hdnIsfk7kE6rm8evtnegB/3HWFwRBQjzMkSESWJAfKONU9w5Bn+OKpPnnzN6Ar3n9fubYrn0oiOKgyOiIiShLSdv7qxHZ12p2KnWq58zei+7l6kH/fxGBGiWGFwRESUJIqzjMg26eASgT2H27Be2qmmyBwd58kc7TrUhqZ2WwJWSZT+GBwRESUJQRDk7NHy7Q1oaLVCpxEwTNFblJ9pQP8id2/Sj/uaErFMorTH4IiIKIkM9Bwj8s7aAwCAwaXZMOm1Ptcc1zcPADjviChGGBwRESURqSl7c437kOtRFbkB14yR+o6q2XdEFAsMjoiIkoiUOZIo+40koz2Zo3XVTXC5xDisiujowuCIiCiJSJkjyaggwdExpdnIMGjRYnXI2/4jsaO+FZZOe8TPQ5QuGBwRESWRinwzDJ5jQUx6DQaXZgVco9Nq5O39ayMsrW040Iyz/roMt7y2NqLnIUonDI6IiJKITqtBlWc32rBeuV2enyb1HS3fcTii11uyuR4uEVi+owGHWqwRPRdRumBwRESUZAaUuIMj5fBHf9OGlwEAPt9YG1FJbPXeRgCAKAJfba3v8fMQpRMGR0RESeaak/vjlEFFmDGhsstrRvTOxaCSLFgdLnz8U02PXsfhdGHtXm9ZbukWBkdEAIMjIqKkM7ZfPv5zzXhUesprwQiCgIvH9AEAvLN2f49eZ1ONBW02JzSC+/uvtx2C1eHs0XMRpRMGR0REKeqi0b2hEYBVe45g7+G2sB//w253Se3UwcUozjaizeaUbyM6mjE4IiJKUWW5Jpw0sAiAd6J2OFbtcQdCJ1QV4IxjSgC4G7SJjnYMjoiIUtilY92ltXfX7g9rIKQoili9x91vdEJlAc4Y4gmOttRBFDlYko5uDI6IiFLYWUPLkGXUYf+RDjkTpMauhjYcbrPBoNNgRJ9cnDywCAadBvsaO6IyWJIolTE4IiJKYWaDFueOKAcQXmP2Kk9v0XEVeTDqtMg06jChfyEA4AuW1ugox+CIiCjFXeIprX38cy06bOp2m/3gyTIdX5kv3zbZU1pb6hccNbbZcNOra/DEZ1tZcqOjAoMjIqIUd3xlPvoWZKDV6sBnG2tVPWaVHBwVyLed7mnKXr23EU3tNgBAS6cdM17+AZ9sqMWzX+7Av1fsjfLqiZIPgyMiohTnnnnUG4C60lptcyf2NXZAI7hnKkkqCjJwTGk2XCKwbNshdNicuGbhavx8oBkGnfvj4s8fbcKPEZ7nRpTsGBwREaWBSzwDIZfvaMCmg5aQ10pZoyHlOcg26X3uk0prn26oxU2vrcEPuxuRbdTh3Zsm4uzhZbA7Rdzy2locabPF4KcgSg4MjoiI0kBFQQbOHl4GUQRmv7kOnfaue4+CldQkUnD0yYZafLX1EEx6DV6++ngM752Lxy4diaqiTBxs7sQdi9Z1Ozqg1erAB+sPYsnmOmytbUGr1RHBT0gUP7pEL4CIiKLjoQuHY9WeRmypbcFTi7fh9+cMCXqdNAU7WHB0XEU+8jP0ONJuh14r4J+/Hidfl23S4+9XjsGFz32LZdsO4bkvd+C3kwcFfY3Fm+pw/3sbUNPc6XN7XoYeI3rn4p6px2JEiIN1iRKJmSMiojRRlGXEIxePBAD865tdWLHzcMA1zR12bK1rAQAcX5UfcL9WI+DK8f2QYdDib78cjdMGF/vcP6Q8B3++cDgA4KkvtmH2m+vw6YYatHmyQvWWTtz82hpc9+/VqGnuRO88M4b1ykGu2V2+a2q345vtDfjFc8sx592fcLjVGr03gChKBJH7MsNisViQm5uL5uZm5OTkJHo5REQB7n3nJ7yxah9655nxyR2nIEfRV/TllnpcvWAVKgsz8NXdp3f5HA6nCzpt1//9/Pv//YzXV1bL3xt0GoyvKsC6fU1o6XRAqxFw3Sn9cfvkQTAbtADcZba9h9vwr6934f/WHQQAZJt0mH3mYFxxQl+Y9NqA12m3ObB4Ux2WbqlHWY4J543sheG9cyAIQtjvCx3dwvn8ZnAUJgZHRJTsWq0OnPP0N6hubMfFY3rjqcuOA+A+MuSRT7fgn8t2YfrYPnh8+qgev4Yoivh+VyO+2FyHxZvqUN3YLt83qk8u5l08EkN7df1v5Ko9jXjgvY3YVONuHtdrBQzvnYvjKwswtl8+dBoB768/iM831qHDr3+qsjAD543shSlDS5GfoYdZr4VRr4VJr0GHzYmGVhsOt1rR2GZDi9WB0hwTeueZ0SffHDQAC/azAUiaAKzd5kBNcyeKMo3IMeuSZl2phsFRDDE4IqJUsHpPIy775wq4RGBURR6OtNlQ39KJTrsLAPDYpSNx2biKqLyWKIrYUd+Kr7YeQmGWARcc1xtaTfcf4E6XiDdWVePZpTsCepOU+hVm4JwR5ag+3I4lW+rkn6EnirIMyM8wQK/VwKDTwKDVQKsR0GZzwNJhh6XTgZZOO1wikGfWIy9Dj/wMA/Iy9NBpfDNpWq2AHJMOOSY9sk06ZJv0EATA5nDB7hRhc7jgEkUY9RqYdFqY9FqYDRoIEOB0iXCKIlwuEQ6XCLvT5fkSYXW4cKilE7sb2rC7oQ11Fm/pMcuokwO9wiwDDDqN+2fRuv/XJXqf1+kCBAEweV7fbHAHkdpugisRIuwOFzodLnTYnOh0OGF3iDDoNDB7glCzQQu9VgOtIECjEaDTuP/XoBXkNek9763y1Vwi0GF3os3qkL9EuHvR8swG+f3OzzTIpdhoYXAUQwyOiChVPP7ZFjz35c6A2ysLM/DOTRNRmGVMwKoCiaIonw23eu8RrN7TiDarE2cOLcWFo3tjVJ9cOVvSZnXgi811+GB9DdbtO4IOmxMddieUG+eyTToUZRlRmGlAhlGHuuZO7D/SjjaV08OTUYZBi/YUXn+4hpbn4OPbT4nqczI4iiEGR0SUKpwuEZ9sqIFGEFCSbURJtgnF2Ua5ByhdiKIIu1NEh90Jk14Doy7w5xNFEc0dduw/0gFLpx12pzs7Yne6YHeJyDJqkW3Sy1kgQXA3jx9pt6G53Y6mDjucfqML7E4XWjyZJkuHA5ZOOwQBchZHr9NAIwBWuwsddic67S502p0QIUIjCNBqBDnzImWxDFoN9DoBBRkGVBVnorIwE1VFmcjLMKDD5sSBpg7sP9KOA00daGq3w+50eTJV7qyTIABaz3NrNAJEEei0O+Uv/0CyKwatBiYpS6TXQqfVwOZw/xxWz/PYnS5PBgyeDJgLDqc7C2bz/K//ewYAZr0WmUb3eX6ZBh0gAM2e97qp3Y6mdhuO65uH1649sce/E8EwOIohBkdERESx5XSJqkqz4Qjn85tb+YmIiCipRDswCheDIyIiIiIFBkdERERECgyOiIiIiBQYHBEREREpMDgiIiIiUmBwRERERKSQMsHRww8/jIkTJyIjIwN5eXkB9y9YsACCIAT9qq+vBwB89dVXQe+vra2N809DREREyUqX6AWoZbPZMH36dEyYMAEvvfRSwP2XX345pk2b5nPbzJkz0dnZiZKSEp/bt27d6jMAyv9+IiIiOnqlTHA0d+5cAO4MUTBmsxlms1n+/tChQ1i6dGnQQKqkpCRo9omIiIgoZcpq4fr3v/+NjIwMXHrppQH3HXfccSgvL8eZZ56Jb7/9NgGrIyIiomSVMpmjcL300kv41a9+5ZNNKi8vx/PPP49x48bBarXixRdfxKRJk7By5UqMGTMm6PNYrVZYrVb5e4vFEvO1ExERUeIkNHN07733dtlELX1t2bIl7OddsWIFNm/ejGuuucbn9mOOOQY33HADxo4di4kTJ+Lll1/GxIkT8de//rXL55o3bx5yc3Plr4qKirDXQ0RERKkjoZmju+66CzNnzgx5Tf/+/cN+3hdffBHHHXccxo4d2+21J5xwApYvX97l/XPmzMHs2bPl7y0WCwMkIiKiNJbQ4Ki4uBjFxcVRfc7W1la8+eabmDdvnqrr161bh/Ly8i7vNxqNMBqN8veiKAJgeY2IiCiVSJ/b0ud4KCnTc1RdXY3GxkZUV1fD6XRi3bp1AICBAwciKytLvm7RokVwOBy46qqrAp5j/vz5qKqqwrBhw9DZ2YkXX3wRS5cuxeeff656HS0tLQDA7BEREVEKamlpQW5ubshrUiY4uv/++7Fw4UL5+9GjRwMAvvzyS0yaNEm+/aWXXsLFF18cdKu+zWbDXXfdhQMHDiAjIwMjR47EF198gdNPP131Onr16oV9+/YhOzsbgiD0+OcJRirZ7du3z2cOE0Uf3+v44XsdP3yv44fvdfxE670WRREtLS3o1atXt9cKopr8EsWFxWJBbm4umpub+X+2GON7HT98r+OH73X88L2On0S812k754iIiIioJxgcERERESkwOEoiRqMRDzzwgM/uOIoNvtfxw/c6fvhexw/f6/hJxHvNniMiIiIiBWaOiIiIiBQYHBEREREpMDgiIiIiUmBwRERERKTA4ChJPPfcc6isrITJZML48ePxww8/JHpJKW/evHk4/vjjkZ2djZKSElx44YXYunWrzzWdnZ245ZZbUFhYiKysLFxyySWoq6tL0IrTxyOPPAJBEHDHHXfIt/G9jp4DBw7gqquuQmFhIcxmM0aMGIHVq1fL94uiiPvvvx/l5eUwm82YMmUKtm/fnsAVpyan04n77rsPVVVVMJvNGDBgAB566CGfs7n4Xvfc119/jfPPPx+9evWCIAj4v//7P5/71by3jY2NuPLKK5GTk4O8vDxcc801aG1tjXhtDI6SwKJFizB79mw88MADWLt2LUaNGoWpU6eivr4+0UtLacuWLcMtt9yC77//HosXL4bdbsdZZ52FtrY2+Zo777wTH3zwAd566y0sW7YMBw8exMUXX5zAVae+VatW4Z///CdGjhzpczvf6+g4cuQITjrpJOj1enzyySfYtGkTnnzySeTn58vXPPbYY/jb3/6G559/HitXrkRmZiamTp2Kzs7OBK489Tz66KP4xz/+gWeffRabN2/Go48+isceewzPPPOMfA3f655ra2vDqFGj8NxzzwW9X817e+WVV2Ljxo1YvHgxPvzwQ3z99de4/vrrI1+cSAl3wgkniLfccov8vdPpFHv16iXOmzcvgatKP/X19SIAcdmyZaIoimJTU5Oo1+vFt956S75m8+bNIgBxxYoViVpmSmtpaREHDRokLl68WDzttNPE22+/XRRFvtfR9P/+3/8TTz755C7vd7lcYllZmfj444/LtzU1NYlGo1H873//G48lpo1zzz1XnDVrls9tF198sXjllVeKosj3OpoAiP/73//k79W8t5s2bRIBiKtWrZKv+eSTT0RBEMQDBw5EtB5mjhLMZrNhzZo1mDJlinybRqPBlClTsGLFigSuLP00NzcDAAoKCgAAa9asgd1u93nvjz32WPTt25fvfQ/dcsstOPfcc33eU4DvdTS9//77GDduHKZPn46SkhKMHj0a//rXv+T7d+/ejdraWp/3Ojc3F+PHj+d7HaaJEydiyZIl2LZtGwBg/fr1WL58Oc4++2wAfK9jSc17u2LFCuTl5WHcuHHyNVOmTIFGo8HKlSsjen1dRI+miDU0NMDpdKK0tNTn9tLSUmzZsiVBq0o/LpcLd9xxB0466SQMHz4cAFBbWwuDwYC8vDyfa0tLS1FbW5uAVaa2N954A2vXrsWqVasC7uN7HT27du3CP/7xD8yePRu///3vsWrVKtx2220wGAyYMWOG/H4G+zeF73V47r33XlgsFhx77LHQarVwOp14+OGHceWVVwIA3+sYUvPe1tbWoqSkxOd+nU6HgoKCiN9/Bkd0VLjllluwYcMGLF++PNFLSUv79u3D7bffjsWLF8NkMiV6OWnN5XJh3Lhx+Mtf/gIAGD16NDZs2IDnn38eM2bMSPDq0subb76J1157Da+//jqGDRuGdevW4Y477kCvXr34Xqc5ltUSrKioCFqtNmDXTl1dHcrKyhK0qvRy66234sMPP8SXX36JPn36yLeXlZXBZrOhqanJ53q+9+Fbs2YN6uvrMWbMGOh0Ouh0Oixbtgx/+9vfoNPpUFpayvc6SsrLyzF06FCf24YMGYLq6moAkN9P/psSubvvvhv33nsvfvnLX2LEiBH49a9/jTvvvBPz5s0DwPc6ltS8t2VlZQEblxwOBxobGyN+/xkcJZjBYMDYsWOxZMkS+TaXy4UlS5ZgwoQJCVxZ6hNFEbfeeiv+97//YenSpaiqqvK5f+zYsdDr9T7v/datW1FdXc33PkyTJ0/Gzz//jHXr1slf48aNw5VXXin/me91dJx00kkBIym2bduGfv36AQCqqqpQVlbm815bLBasXLmS73WY2tvbodH4fkxqtVq4XC4AfK9jSc17O2HCBDQ1NWHNmjXyNUuXLoXL5cL48eMjW0BE7dwUFW+88YZoNBrFBQsWiJs2bRKvv/56MS8vT6ytrU300lLaTTfdJObm5opfffWVWFNTI3+1t7fL19x4441i3759xaVLl4qrV68WJ0yYIE6YMCGBq04fyt1qosj3Olp++OEHUafTiQ8//LC4fft28bXXXhMzMjLEV199Vb7mkUceEfPy8sT33ntP/Omnn8QLLrhArKqqEjs6OhK48tQzY8YMsXfv3uKHH34o7t69W3z33XfFoqIi8Z577pGv4Xvdcy0tLeKPP/4o/vjjjyIA8amnnhJ//PFHce/evaIoqntvp02bJo4ePVpcuXKluHz5cnHQoEHiFVdcEfHaGBwliWeeeUbs27evaDAYxBNOOEH8/vvvE72klAcg6Ncrr7wiX9PR0SHefPPNYn5+vpiRkSFedNFFYk1NTeIWnUb8gyO+19HzwQcfiMOHDxeNRqN47LHHii+88ILP/S6XS7zvvvvE0tJS0Wg0ipMnTxa3bt2aoNWmLovFIt5+++1i3759RZPJJPbv31/8wx/+IFqtVvkavtc99+WXXwb9N3rGjBmiKKp7bw8fPixeccUVYlZWlpiTkyNeffXVYktLS8RrE0RRMeqTiIiI6CjHniMiIiIiBQZHRERERAoMjoiIiIgUGBwRERERKTA4IiIiIlJgcERERESkwOCIiIiISIHBERGRCpWVlZg/f36il0FEccDgiIiSzsyZM3HhhRcCACZNmoQ77rgjbq+9YMEC5OXlBdy+atUqXH/99XFbBxElji7RCyAiigebzQaDwdDjxxcXF0dxNUSUzJg5IqKkNXPmTCxbtgxPP/00BEGAIAjYs2cPAGDDhg04++yzkZWVhdLSUvz6179GQ0OD/NhJkybh1ltvxR133IGioiJMnToVAPDUU09hxIgRyMzMREVFBW6++Wa0trYCAL766itcffXVaG5ull/vwQcfBBBYVquursYFF1yArKws5OTk4LLLLkNdXZ18/4MPPojjjjsO//nPf1BZWYnc3Fz88pe/REtLi3zN22+/jREjRsBsNqOwsBBTpkxBW1tbjN5NIlKLwRERJa2nn34aEyZMwHXXXYeamhrU1NSgoqICTU1NOOOMMzB69GisXr0an376Kerq6nDZZZf5PH7hwoUwGAz49ttv8fzzzwMANBoN/va3v2Hjxo1YuHAhli5dinvuuQcAMHHiRMyfPx85OTny6/3ud78LWJfL5cIFF1yAxsZGLFu2DIsXL8auXbtw+eWX+1y3c+dO/N///R8+/PBDfPjhh1i2bBkeeeQRAEBNTQ2uuOIKzJo1C5s3b8ZXX32Fiy++GDzukijxWFYjoqSVm5sLg8GAjIwMlJWVybc/++yzGD16NP7yl7/It7388suoqKjAtm3bMHjwYADAoEGD8Nhjj/k8p7J/qbKyEn/+859x44034u9//zsMBgNyc3MhCILP6/lbsmQJfv75Z+zevRsVFRUAgH//+98YNmwYVq1aheOPPx6AO4hasGABsrOzAQC//vWvsWTJEjz88MOoqamBw+HAxRdfjH79+gEARowYEcG7RUTRwswREaWc9evX48svv0RWVpb8deyxxwJwZ2skY8eODXjsF198gcmTJ6N3797Izs7Gr3/9axw+fBjt7e2qX3/z5s2oqKiQAyMAGDp0KPLy8rB582b5tsrKSjkwAoDy8nLU19cDAEaNGoXJkydjxIgRmD59Ov71r3/hyJEj6t8EIooZBkdElHJaW1tx/vnnY926dT5f27dvx6mnnipfl5mZ6fO4PXv24LzzzsPIkSPxzjvvYM2aNXjuuecAuBu2o02v1/t8LwgCXC4XAECr1WLx4sX45JNPMHToUDzzzDM45phjsHv37qivg4jCw+CIiJKawWCA0+n0uW3MmDHYuHEjKisrMXDgQJ8v/4BIac2aNXC5XHjyySdx4oknYvDgwTh48GC3r+dvyJAh2LdvH/bt2yfftmnTJjQ1NWHo0KGqfzZBEHDSSSdh7ty5+PHHH2EwGPC///1P9eOJKDYYHBFRUqusrMTKlSuxZ88eNDQ0wOVy4ZZbbkFjYyOuuOIKrFq1Cjt37sRnn32Gq6++OmRgM3DgQNjtdjzzzDPYtWsX/vOf/8iN2srXa21txZIlS9DQ0BC03DZlyhSMGDECV155JdauXYsffvgBv/nNb3Daaadh3Lhxqn6ulStX4i9/+QtWr16N6upqvPvuuzh06BCGDBkS3htERFHH4IiIktrvfvc7aLVaDB06FMXFxaiurkavXr3w7bffwul04qyzzsKIESNwxx13IC8vDxpN1/+sjRo1Ck899RQeffRRDB8+HK+99hrmzZvnc83EiRNx44034vLLL0dxcXFAQzfgzvi89957yM/Px6mnnoopU6agf//+WLRokeqfKycnB19//TXOOeccDB48GH/84x/x5JNP4uyzz1b/5hBRTAgi940SERERyZg5IiIiIlJgcERERESkwOCIiIiISIHBEREREZECgyMiIiIiBQZHRERERAoMjoiIiIgUGBwRERERKTA4IiIiIlJgcERERESkwOCIiIiISIHBEREREZHC/wfYtpq2MGQokAAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "result.convergence_graph" + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(nrows=1, ncols=1)\n", + "axes.plot(cost_values)\n", + "axes.set_xlabel(\"Iterations\")\n", + "axes.set_ylabel(\"Cost\")\n", + "axes.set_title(\"Cost convergence\")" ] }, { @@ -328,24 +280,16 @@ "source": [ "## 4. Present Quantum Results\n", "\n", - "We hereby present the optimization results. Since this is a quantum solution with probabilistic results, there is a defined probability for each result to be obtained by a measurement (presented by an histogram), where the solution is chosen to be the most probable one.\n", + "we call the `get_results` method to get samples with the optimzied parameters. We hereby present the optimization results. Since this is a quantum solution with probabilistic results, there is a defined probability for each result to be obtained by a measurement (presented by an histogram), where the solution is chosen to be the most probable one.\n", "\n", "We remind that in the notation of the solution \"0\" indicate \"-1\" spin value, and \"1\" indicates \"1\" spin value." ] }, { "cell_type": "code", - "execution_count": 10, - "id": "da738964-b1ba-4b94-997a-ae7a46254f6c", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:23:09.461338Z", - "iopub.status.busy": "2024-05-07T15:23:09.460808Z", - "iopub.status.idle": "2024-05-07T15:23:09.487645Z", - "shell.execute_reply": "2024-05-07T15:23:09.487039Z" - }, - "tags": [] - }, + "execution_count": 18, + "id": "2c35bcde-2d6e-4ed0-aa70-325dbf5a7846", + "metadata": {}, "outputs": [ { "data": { @@ -368,91 +312,99 @@ " \n", " \n", " \n", + " solution\n", " probability\n", " cost\n", - " solution\n", - " count\n", " \n", " \n", " \n", " \n", " 0\n", - " 0.189\n", + " {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'...\n", + " 0.608887\n", " -180.0\n", - " [0, 0, 0, 0, 0, 0]\n", - " 189\n", " \n", " \n", - " 7\n", - " 0.033\n", + " 21\n", + " {'z_0': 1, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'...\n", + " 0.007812\n", " -100.0\n", - " [0, 0, 1, 0, 0, 0]\n", - " 33\n", " \n", " \n", - " 8\n", - " 0.032\n", + " 19\n", + " {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'...\n", + " 0.008789\n", " -100.0\n", - " [0, 1, 0, 0, 0, 0]\n", - " 32\n", " \n", " \n", - " 9\n", - " 0.030\n", + " 16\n", + " {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 1, 'z_4'...\n", + " 0.010254\n", " -100.0\n", - " [0, 0, 0, 0, 0, 1]\n", - " 30\n", " \n", " \n", - " 10\n", - " 0.030\n", + " 14\n", + " {'z_0': 0, 'z_1': 0, 'z_2': 1, 'z_3': 0, 'z_4'...\n", + " 0.011230\n", " -100.0\n", - " [0, 0, 0, 0, 1, 0]\n", - " 30\n", " \n", " \n", "\n", "" ], "text/plain": [ - " probability cost solution count\n", - "0 0.189 -180.0 [0, 0, 0, 0, 0, 0] 189\n", - "7 0.033 -100.0 [0, 0, 1, 0, 0, 0] 33\n", - "8 0.032 -100.0 [0, 1, 0, 0, 0, 0] 32\n", - "9 0.030 -100.0 [0, 0, 0, 0, 0, 1] 30\n", - "10 0.030 -100.0 [0, 0, 0, 0, 1, 0] 30" + " solution probability cost\n", + "0 {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'... 0.608887 -180.0\n", + "21 {'z_0': 1, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'... 0.007812 -100.0\n", + "19 {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'... 0.008789 -100.0\n", + "16 {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 1, 'z_4'... 0.010254 -100.0\n", + "14 {'z_0': 0, 'z_1': 0, 'z_2': 1, 'z_3': 0, 'z_4'... 0.011230 -100.0" ] }, - "execution_count": 10, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " ising_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=True).head(5)" + "optimization_result = combi.get_results()\n", + "optimization_result.sort_values(by=\"cost\").head(5)" + ] + }, + { + "cell_type": "markdown", + "id": "06d70826-8ba1-4705-ae87-1a3c4ba5d69a", + "metadata": {}, + "source": [ + "Best Solution:" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "1b2775b1-7b12-4a0a-9931-eacdee4e5127", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4': 0, 'z_5': 0}" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "optimization_result.sort_values(by=\"cost\").iloc[0].solution" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 19, "id": "81d6f1dd-7e65-4118-bc8b-9ee662c72a68", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:23:09.490132Z", - "iopub.status.busy": "2024-05-07T15:23:09.489947Z", - "iopub.status.idle": "2024-05-07T15:23:09.702616Z", - "shell.execute_reply": "2024-05-07T15:23:09.701922Z" - }, "tags": [] }, "outputs": [ @@ -462,13 +414,13 @@ "array([[]], dtype=object)" ] }, - "execution_count": 11, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -518,7 +470,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" }, "vscode": { "interpreter": { diff --git a/applications/physical_systems/ising_model/ising_model.qmod b/applications/physical_systems/ising_model/ising_model.qmod index aeea9aad6..a40985b4c 100644 --- a/applications/physical_systems/ising_model/ising_model.qmod +++ b/applications/physical_systems/ising_model/ising_model.qmod @@ -1,155 +1,21 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-20.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-20.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-20.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-20.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-20.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-20.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=-10.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-10.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=-10.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-10.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-10.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-10.0 - } -]; - -qfunc main(params_list: real[10], output target: qbit[6]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + z_0: qbit; + z_1: qbit; + z_2: qbit; + z_3: qbit; + z_4: qbit; + z_5: qbit; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=False, -initial_point=[0.0, 0.027272727272727275, 0.006818181818181819, 0.020454545454545454, 0.013636363636363637, 0.013636363636363637, 0.020454545454545454, 0.006818181818181819, 0.027272727272727275, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=100, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=0.7 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[10], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 5) { + phase (-(((((((((((((40.0 * v.z_0) + (40.0 * v.z_1)) + (40.0 * v.z_2)) + (40.0 * v.z_3)) + (40.0 * v.z_4)) + (40.0 * v.z_5)) + ((10 - (20 * v.z_0)) * ((2 * v.z_1) - 1))) + ((10 - (20 * v.z_0)) * ((2 * v.z_5) - 1))) + ((10 - (20 * v.z_1)) * ((2 * v.z_2) - 1))) + ((10 - (20 * v.z_2)) * ((2 * v.z_3) - 1))) + ((10 - (20 * v.z_3)) * ((2 * v.z_4) - 1))) + ((10 - (20 * v.z_4)) * ((2 * v.z_5) - 1))) - 120.0), params[i]); + apply_to_all(lambda(q) { + RX(params[5 + i], q); + }, v); + } +} diff --git a/applications/physical_systems/ising_model/ising_model.synthesis_options.json b/applications/physical_systems/ising_model/ising_model.synthesis_options.json index 0967ef424..cb806fc57 100644 --- a/applications/physical_systems/ising_model/ising_model.synthesis_options.json +++ b/applications/physical_systems/ising_model/ising_model.synthesis_options.json @@ -1 +1,43 @@ -{} +{ + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "ry", + "tdg", + "id", + "t", + "cx", + "sx", + "h", + "u2", + "y", + "s", + "p", + "sdg", + "sxdg", + "x", + "cy", + "u1", + "rz", + "r", + "cz", + "z", + "rx", + "u" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 234206522 + } +} From 1327fd2e8d8a0fac9eea6f7ec897b0fbf89e7612 Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Sun, 8 Dec 2024 14:54:13 +0200 Subject: [PATCH 16/32] removed knapsack binary notebook --- .../knapsack_binary/knapsack_binary.ipynb | 642 ------------------ .../knapsack_binary.metadata.json | 7 - .../knapsack_binary/knapsack_binary.qmod | 265 -------- .../knapsack_binary.synthesis_options.json | 1 - 4 files changed, 915 deletions(-) delete mode 100644 applications/optimization/knapsack_binary/knapsack_binary.ipynb delete mode 100644 applications/optimization/knapsack_binary/knapsack_binary.metadata.json delete mode 100644 applications/optimization/knapsack_binary/knapsack_binary.qmod delete mode 100644 applications/optimization/knapsack_binary/knapsack_binary.synthesis_options.json diff --git a/applications/optimization/knapsack_binary/knapsack_binary.ipynb b/applications/optimization/knapsack_binary/knapsack_binary.ipynb deleted file mode 100644 index 077e929aa..000000000 --- a/applications/optimization/knapsack_binary/knapsack_binary.ipynb +++ /dev/null @@ -1,642 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "13d83b59-57f7-48ee-8bff-deda7d28edc5", - "metadata": { - "tags": [] - }, - "source": [ - "\n", - "# Binary Knapsack\n" - ] - }, - { - "cell_type": "markdown", - "id": "6d56bb6d-9f3b-45db-8e98-b50f27af7505", - "metadata": {}, - "source": [ - "## Background\n", - "\n", - "Given a set of items, determine how many items to put in the knapsack to maximize their summed value.\n", - "\n", - "#### Define:\n", - "\n", - "- $x_i$ is the number of items from each type.\n", - "\n", - "- $v_i$ is the value of each item.\n", - "\n", - "- $w_i$ is the weight of each item.\n", - "\n", - "- $D$ is the range of $x$.\n", - "\n", - "Find $x$ that maximizes the value: $\\begin{aligned}\n", - "\\max_{x_i \\in D} \\Sigma_i v_i x_i\\\\\n", - "\\end{aligned}$\n", - "\n", - "and constrained by the weight: $\\begin{aligned}\n", - "\\Sigma_i w_i x_i = C\n", - "\\end{aligned}$\n", - "\n", - "## Problem Versions\n", - "\n", - "**Binary Knapsack**\n", - "\n", - "Range: $D = \\{0, 1\\}$\n", - "\n", - "**Integer Knapsack**\n", - "\n", - "Range: $D = [0, b]$\n" - ] - }, - { - "cell_type": "markdown", - "id": "fdbcef63-3c8e-4f0a-a4fb-9058807fa3a8", - "metadata": { - "tags": [] - }, - "source": [ - "## Knapsack with binary variables and equality constraint\n" - ] - }, - { - "cell_type": "markdown", - "id": "0bdc4e6a-199b-44b3-bd3f-fd24722b616b", - "metadata": {}, - "source": [ - "### Define the optimization problem" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "83ddbd07-f7ab-4d80-b357-3890622d395f", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:29.057270Z", - "iopub.status.busy": "2024-05-07T16:07:29.055577Z", - "iopub.status.idle": "2024-05-07T16:07:29.609395Z", - "shell.execute_reply": "2024-05-07T16:07:29.608466Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "import numpy as np\n", - "import pyomo.environ as pyo\n", - "\n", - "\n", - "def define_knapsack_model(weights, values, max_weight):\n", - " model = pyo.ConcreteModel()\n", - " num_items = len(weights)\n", - "\n", - " model.x = pyo.Var(range(num_items), domain=pyo.Binary)\n", - "\n", - " x_variables = np.array(list(model.x.values()))\n", - "\n", - " model.weight_constraint = pyo.Constraint(expr=x_variables @ weights == max_weight)\n", - "\n", - " model.value = pyo.Objective(expr=x_variables @ values, sense=pyo.maximize)\n", - "\n", - " return model" - ] - }, - { - "cell_type": "markdown", - "id": "3496c5d6-7df6-49fb-b5b9-5ba48d2b7d62", - "metadata": {}, - "source": [ - "### Initialize the model with parameters" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "62a98e1c-5dbe-42f9-989e-83ee1df7196b", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:29.613987Z", - "iopub.status.busy": "2024-05-07T16:07:29.613427Z", - "iopub.status.idle": "2024-05-07T16:07:29.621699Z", - "shell.execute_reply": "2024-05-07T16:07:29.621009Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "knapsack_model = define_knapsack_model(\n", - " weights=[2, 3, 2.1, 1, 1, 2], values=[3, 5, 2, 1.5, 1.2, 2.7], max_weight=5\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "c78b22a0-9420-44bf-a60d-a7ce136dcaaf", - "metadata": { - "tags": [] - }, - "source": [ - "## Setting Up the Classiq Problem Instance\n", - "\n", - "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "947293d1-ac9d-41aa-a162-f60ee16608dd", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:29.626219Z", - "iopub.status.busy": "2024-05-07T16:07:29.625007Z", - "iopub.status.idle": "2024-05-07T16:07:32.195601Z", - "shell.execute_reply": "2024-05-07T16:07:32.194974Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", - "\n", - "qaoa_config = QAOAConfig(num_layers=5)" - ] - }, - { - "cell_type": "markdown", - "id": "fdfcb551-77c3-40f4-a54e-4231c7775f19", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "311e4855-403b-4f3d-a64e-7147be629470", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:32.198391Z", - "iopub.status.busy": "2024-05-07T16:07:32.198019Z", - "iopub.status.idle": "2024-05-07T16:07:32.201281Z", - "shell.execute_reply": "2024-05-07T16:07:32.200682Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "optimizer_config = OptimizerConfig(max_iteration=60, alpha_cvar=0.7)" - ] - }, - { - "cell_type": "markdown", - "id": "0f153f82-829a-44df-98c3-47f693d984df", - "metadata": {}, - "source": [ - "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "fb32b921-1a7d-4c79-9cb0-6993b0eb6b6c", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:32.203585Z", - "iopub.status.busy": "2024-05-07T16:07:32.203227Z", - "iopub.status.idle": "2024-05-07T16:07:32.322318Z", - "shell.execute_reply": "2024-05-07T16:07:32.321660Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=knapsack_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "78d21bb2-0ac5-471e-a1c9-fb77df0400e7", - "metadata": {}, - "source": [ - "We also set the quantum backend we want to execute on:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "cc69a9e9-38d5-4c91-93dd-ad43bab0ca6d", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:32.325437Z", - "iopub.status.busy": "2024-05-07T16:07:32.324838Z", - "iopub.status.idle": "2024-05-07T16:07:32.335989Z", - "shell.execute_reply": "2024-05-07T16:07:32.335376Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", - "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "a0ee5250-26c9-4329-a69e-d8075d05ebc6", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:32.338229Z", - "iopub.status.busy": "2024-05-07T16:07:32.338050Z", - "iopub.status.idle": "2024-05-07T16:07:32.351757Z", - "shell.execute_reply": "2024-05-07T16:07:32.351182Z" - } - }, - "outputs": [], - "source": [ - "write_qmod(qmod, \"knapsack_binary\")" - ] - }, - { - "cell_type": "markdown", - "id": "1a47c1c9-1b39-4c3a-b291-7e2082fb592e", - "metadata": {}, - "source": [ - "## Synthesizing the QAOA Circuit and Solving the Problem\n", - "\n", - "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "10f219ca-2836-4573-9764-70f39b685fca", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:32.354433Z", - "iopub.status.busy": "2024-05-07T16:07:32.353950Z", - "iopub.status.idle": "2024-05-07T16:07:36.930198Z", - "shell.execute_reply": "2024-05-07T16:07:36.929444Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Opening: https://platform.classiq.io/circuit/db610424-2d79-4db4-8c6c-17734c34b003?version=0.41.0.dev39%2B79c8fd0855\n" - ] - } - ], - "source": [ - "qprog = synthesize(qmod)\n", - "show(qprog)" - ] - }, - { - "cell_type": "markdown", - "id": "ce31eb36-c7df-4a0d-9e89-5ef477cc1a8c", - "metadata": {}, - "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "c862d5d4-6d4a-4251-a0e1-d2d55b3a37f3", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:36.941434Z", - "iopub.status.busy": "2024-05-07T16:07:36.941056Z", - "iopub.status.idle": "2024-05-07T16:07:43.555821Z", - "shell.execute_reply": "2024-05-07T16:07:43.555252Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "result = execute(qprog).result_value()" - ] - }, - { - "cell_type": "markdown", - "id": "d2da3c33-14fe-42c3-ac39-6d4e412ceb74", - "metadata": {}, - "source": [ - "We can check the convergence of the run:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "9172ab29-cfd7-4451-a992-02e50e2ec0ff", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:43.560073Z", - "iopub.status.busy": "2024-05-07T16:07:43.559090Z", - "iopub.status.idle": "2024-05-07T16:07:43.585488Z", - "shell.execute_reply": "2024-05-07T16:07:43.584830Z" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "image/jpeg": 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- "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "result.convergence_graph" - ] - }, - { - "cell_type": "markdown", - "id": "2d1824ea-80be-4f20-b7ce-d4836483c33f", - "metadata": { - "tags": [] - }, - "source": [ - "# Optimization Results" - ] - }, - { - "cell_type": "markdown", - "id": "2736d59a-20db-4d26-9880-affa35b1e4ef", - "metadata": {}, - "source": [ - "We can also examine the statistics of the algorithm:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "8b90f0c5-da3a-467e-be89-509ce00ccaea", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:43.587793Z", - "iopub.status.busy": "2024-05-07T16:07:43.587613Z", - "iopub.status.idle": "2024-05-07T16:07:43.615672Z", - "shell.execute_reply": "2024-05-07T16:07:43.614990Z" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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probabilitycostsolutioncount
620.0038.0[1, 1, 0, 0, 0, 0]3
240.0177.7[0, 1, 0, 1, 1, 0]17
590.0077.7[0, 1, 0, 0, 0, 1]7
20.0287.5[1, 1, 0, 1, 0, 0]28
110.0247.2[0, 1, 0, 1, 0, 1]24
\n", - "
" - ], - "text/plain": [ - " probability cost solution count\n", - "62 0.003 8.0 [1, 1, 0, 0, 0, 0] 3\n", - "24 0.017 7.7 [0, 1, 0, 1, 1, 0] 17\n", - "59 0.007 7.7 [0, 1, 0, 0, 0, 1] 7\n", - "2 0.028 7.5 [1, 1, 0, 1, 0, 0] 28\n", - "11 0.024 7.2 [0, 1, 0, 1, 0, 1] 24" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " knapsack_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=False).head(5)" - ] - }, - { - "cell_type": "markdown", - "id": "b5c79c0e-6be3-4a27-97dd-3da93dbae5e6", - "metadata": {}, - "source": [ - "And the histogram:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "2709135d-366d-4f27-8eff-4dd28a4545e5", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:43.618252Z", - "iopub.status.busy": "2024-05-07T16:07:43.617881Z", - "iopub.status.idle": "2024-05-07T16:07:43.813012Z", - "shell.execute_reply": "2024-05-07T16:07:43.812308Z" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[]], dtype=object)" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" - ] - }, - { - "cell_type": "markdown", - "id": "2004e2d2-bcdb-43f8-b068-b8cf5b2beb95", - "metadata": {}, - "source": [ - "Lastly, we can compare to the classical solution of the problem:" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "777c97cb-00c6-46e5-a145-a22f511d66c0", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:43.815782Z", - "iopub.status.busy": "2024-05-07T16:07:43.815309Z", - "iopub.status.idle": "2024-05-07T16:07:43.864718Z", - "shell.execute_reply": "2024-05-07T16:07:43.863986Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Model unknown\n", - "\n", - " Variables:\n", - " x : Size=6, Index=x_index\n", - " Key : Lower : Value : Upper : Fixed : Stale : Domain\n", - " 0 : 0 : 0.9999999999999998 : 1 : False : False : Binary\n", - " 1 : 0 : 1.0 : 1 : False : False : Binary\n", - " 2 : 0 : 0.0 : 1 : False : False : Binary\n", - " 3 : 0 : 0.0 : 1 : False : False : Binary\n", - " 4 : 0 : 0.0 : 1 : False : False : Binary\n", - " 5 : 0 : 2.220446049250313e-16 : 1 : False : False : Binary\n", - "\n", - " Objectives:\n", - " value : Size=1, Index=None, Active=True\n", - " Key : Active : Value\n", - " None : True : 8.0\n", - "\n", - " Constraints:\n", - " weight_constraint : Size=1\n", - " Key : Lower : Body : Upper\n", - " None : 5.0 : 5.0 : 5.0\n" - ] - } - ], - "source": [ - "from pyomo.opt import SolverFactory\n", - "\n", - "solver = SolverFactory(\"couenne\")\n", - "solver.solve(knapsack_model)\n", - "\n", - "knapsack_model.display()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.9" - }, - "vscode": { - "interpreter": { - "hash": "a07aacdcc8a415e7643a2bc993226848ff70704ebef014f87460de9126b773d0" - } - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/applications/optimization/knapsack_binary/knapsack_binary.metadata.json b/applications/optimization/knapsack_binary/knapsack_binary.metadata.json deleted file mode 100644 index f3da2e957..000000000 --- a/applications/optimization/knapsack_binary/knapsack_binary.metadata.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "friendly_name": "Knapsack: Binary Variables", - "description": "Solving Knapsack with Binary Variables Using the QAOA Algorithm", - "problem_domain_tags": ["optimization"], - "qmod_type": ["application"], - "level": ["demos"] -} diff --git a/applications/optimization/knapsack_binary/knapsack_binary.qmod b/applications/optimization/knapsack_binary/knapsack_binary.qmod deleted file mode 100644 index af98415ef..000000000 --- a/applications/optimization/knapsack_binary/knapsack_binary.qmod +++ /dev/null @@ -1,265 +0,0 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.61 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-1.31 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-0.35 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-0.7 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-0.8 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-0.85 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=2.1 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=2.1 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=4.2 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=4.2 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=6.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=6.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=6.3 - } -]; - -qfunc main(params_list: real[10], output target: qbit[6]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); -} - -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=True, -initial_point=[0.0, 0.12820512820512817, 0.03205128205128204, 0.09615384615384612, 0.06410256410256408, 0.06410256410256408, 0.09615384615384612, 0.03205128205128204, 0.12820512820512817, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=60, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=0.7 -) - -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` diff --git a/applications/optimization/knapsack_binary/knapsack_binary.synthesis_options.json b/applications/optimization/knapsack_binary/knapsack_binary.synthesis_options.json deleted file mode 100644 index 0967ef424..000000000 --- a/applications/optimization/knapsack_binary/knapsack_binary.synthesis_options.json +++ /dev/null @@ -1 +0,0 @@ -{} From 92b79c84c01240ab2e3d851f8820278e7567baff Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Sun, 8 Dec 2024 15:28:25 +0200 Subject: [PATCH 17/32] with max_k_vertex_cover --- .../max_k_vertex_cover.ipynb | 430 +++------ .../max_k_vertex_cover.qmod | 882 +----------------- .../max_k_vertex_cover.synthesis_options.json | 44 +- 3 files changed, 191 insertions(+), 1165 deletions(-) diff --git a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.ipynb b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.ipynb index 23e165fe7..a299238ad 100644 --- a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.ipynb +++ b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.ipynb @@ -50,12 +50,6 @@ "execution_count": 1, "id": "49a9588b-e79e-4813-b7c5-ac068d7b930c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:01.828768Z", - "iopub.status.busy": "2024-05-07T15:49:01.828308Z", - "iopub.status.idle": "2024-05-07T15:49:02.672170Z", - "shell.execute_reply": "2024-05-07T15:49:02.671553Z" - }, "tags": [] }, "outputs": [], @@ -82,12 +76,6 @@ "execution_count": 2, "id": "48889b21-557b-481c-80c5-3c0b5c91adb6", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:02.675329Z", - "iopub.status.busy": "2024-05-07T15:49:02.674765Z", - "iopub.status.idle": "2024-05-07T15:49:02.679496Z", - "shell.execute_reply": "2024-05-07T15:49:02.678928Z" - }, "tags": [] }, "outputs": [], @@ -115,26 +103,19 @@ "\n", "- Index set declarations (model.Nodes, model.Arcs).\n", "- Binary variable declaration for each node (model.x) indicating whether the variable is chosen for the set.\n", - "- Constraint rule \u2013 ensures that the set is of size k.\n", - "- Objective rule \u2013 counts the number of edges not covered; i.e., both related variables are zero." + "- Constraint rule – ensures that the set is of size k.\n", + "- Objective rule – counts the number of edges not covered; i.e., both related variables are zero." ] }, { "cell_type": "code", "execution_count": 3, "id": "439b4081-cb00-4a59-bc23-20a21a291f67", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:02.681807Z", - "iopub.status.busy": "2024-05-07T15:49:02.681487Z", - "iopub.status.idle": "2024-05-07T15:49:03.007232Z", - "shell.execute_reply": "2024-05-07T15:49:03.006530Z" - } - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -158,12 +139,7 @@ "execution_count": 4, "id": "345330b2-9c14-41f6-b4ba-e11fb9ca1565", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:03.009901Z", - "iopub.status.busy": "2024-05-07T15:49:03.009417Z", - "iopub.status.idle": "2024-05-07T15:49:03.015488Z", - "shell.execute_reply": "2024-05-07T15:49:03.014894Z" - }, + "scrolled": true, "tags": [] }, "outputs": [ @@ -210,102 +186,80 @@ }, { "cell_type": "markdown", - "id": "17ea14ec-dbb7-487c-b4f1-cabc8d5e3c29", + "id": "b85b6a8c-d327-4043-b082-44d82135b51b", "metadata": { "tags": [] }, "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):" + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the qaoa algorithm, with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { "cell_type": "code", "execution_count": 5, - "id": "816b468f-a59f-4f2f-8337-4a9d66548425", + "id": "9709fd60-fb81-4af0-882b-efa216477fec", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:03.018150Z", - "iopub.status.busy": "2024-05-07T15:49:03.017651Z", - "iopub.status.idle": "2024-05-07T15:49:05.001488Z", - "shell.execute_reply": "2024-05-07T15:49:05.000681Z" - }, "tags": [] }, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "qaoa_config = QAOAConfig(num_layers=3)" - ] - }, - { - "cell_type": "markdown", - "id": "db34d5ac-6877-4285-8dec-7bf7b37eb783", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" + "combi = CombinatorialProblem(pyo_model=mvc_model, num_layers=3, penalty_factor=10)\n", + "\n", + "qmod = combi.get_model()" ] }, { "cell_type": "code", "execution_count": 6, - "id": "e41d0dd3-4135-4330-9ba3-c1b30c339a74", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:05.006362Z", - "iopub.status.busy": "2024-05-07T15:49:05.005049Z", - "iopub.status.idle": "2024-05-07T15:49:05.009888Z", - "shell.execute_reply": "2024-05-07T15:49:05.009276Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, + "id": "133ddfff-b7f4-436a-b656-81a32a236a98", + "metadata": {}, "outputs": [], "source": [ - "optimizer_config = OptimizerConfig(max_iteration=60, alpha_cvar=0.7)" + "write_qmod(qmod, \"max_k_vertex_cover\")" ] }, { "cell_type": "markdown", - "id": "214d6051-43b8-4b9d-8454-f9cdb62b4cf0", + "id": "411eeb04-f598-4585-87bf-a168787714f3", "metadata": {}, "source": [ - "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:" + "## Synthesizing the QAOA Circuit and Solving the Problem\n", + "\n", + "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" ] }, { "cell_type": "code", "execution_count": 7, - "id": "0243019c-6fc3-435f-b6ec-8b4355d6660c", + "id": "69d7c8ac-29c6-42b7-9111-fcf88a4e816a", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:05.014101Z", - "iopub.status.busy": "2024-05-07T15:49:05.012999Z", - "iopub.status.idle": "2024-05-07T15:49:05.454332Z", - "shell.execute_reply": "2024-05-07T15:49:05.453564Z" - }, "pycharm": { "name": "#%%\n" }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Opening: https://nightly.platform.classiq.io/circuit/9e9127b4-7c66-4b81-b66c-57745580a2ec?version=0.61.0.dev8\n" + ] + } + ], "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=mvc_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" + "qprog = combi.get_qprog()\n", + "show(qprog)" ] }, { "cell_type": "markdown", - "id": "1fcc3812-c9d0-421c-84bb-38047297b33f", + "id": "7300af19-c7c4-4e93-a01b-fa7305a60b4d", "metadata": {}, "source": [ "We also set the quantum backend we want to execute on:" @@ -314,111 +268,43 @@ { "cell_type": "code", "execution_count": 8, - "id": "53bc041f-065c-44d2-b220-dafd9d0504ac", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:05.459516Z", - "iopub.status.busy": "2024-05-07T15:49:05.458347Z", - "iopub.status.idle": "2024-05-07T15:49:05.490549Z", - "shell.execute_reply": "2024-05-07T15:49:05.489834Z" - }, - "tags": [] - }, + "id": "c052e252-745c-4b93-8df7-992d3c5d3277", + "metadata": {}, "outputs": [], "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", + "from classiq.execution import *\n", "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", + "execution_preferences = ExecutionPreferences(\n", + " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\"),\n", ")" ] }, - { - "cell_type": "code", - "execution_count": 9, - "id": "91fea2e9-0ce2-43cb-850c-3ba65a8a76c4", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:05.495462Z", - "iopub.status.busy": "2024-05-07T15:49:05.494337Z", - "iopub.status.idle": "2024-05-07T15:49:05.546829Z", - "shell.execute_reply": "2024-05-07T15:49:05.546110Z" - } - }, - "outputs": [], - "source": [ - "write_qmod(qmod, \"max_k_vertex_cover\")" - ] - }, { "cell_type": "markdown", - "id": "943291f0-6a9f-4286-a69d-ef13a0a12ef6", + "id": "62a5d189-4c7d-42d9-8c8b-5a24d0ed2271", "metadata": {}, "source": [ - "## Synthesizing the QAOA Circuit and Solving the Problem\n", - "\n", - "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" + "We now solve the problem by calling the `optimize` method of the `CombinatorialProblem` object. For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`maxiter`) and the $\\alpha$-parameter (`quantile`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" ] }, { "cell_type": "code", - "execution_count": 10, - "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", + "execution_count": 22, + "id": "066869ce-6c80-4e8a-9943-77ceabe74388", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:05.552136Z", - "iopub.status.busy": "2024-05-07T15:49:05.550905Z", - "iopub.status.idle": "2024-05-07T15:49:10.398718Z", - "shell.execute_reply": "2024-05-07T15:49:10.398036Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Opening: https://platform.classiq.io/circuit/308cc52e-d608-47d6-9ccb-ceb9f2e932a2?version=0.41.0.dev39%2B79c8fd0855\n" - ] - } - ], - "source": [ - "qprog = synthesize(qmod)\n", - "show(qprog)" - ] - }, - { - "cell_type": "markdown", - "id": "80238cf9-d7bd-46e5-9d48-b7cf23a6b304", - "metadata": {}, - "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "62d12d20-1c80-4a9e-bb6b-b1fddc6cbe40", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:10.401335Z", - "iopub.status.busy": "2024-05-07T15:49:10.400809Z", - "iopub.status.idle": "2024-05-07T15:49:20.990694Z", - "shell.execute_reply": "2024-05-07T15:49:20.990084Z" - }, "tags": [] }, "outputs": [], "source": [ - "result = execute(qprog).result_value()" + "cost_values = []\n", + "optimized_params = combi.optimize(\n", + " execution_preferences, maxiter=90, cost_trace=cost_values, quantile=0.7\n", + ")" ] }, { "cell_type": "markdown", - "id": "620ea6a0-cd05-41a9-a2ed-9631c680d2e6", + "id": "ab153f29-2a25-422f-aed8-69283f6691e0", "metadata": {}, "source": [ "We can check the convergence of the run:" @@ -426,33 +312,41 @@ }, { "cell_type": "code", - "execution_count": 12, - "id": "02454398-b229-403c-824a-b1eb539fbc1f", + "execution_count": 23, + "id": "be6bc7ec-c1f8-4925-be2b-0dceb20d73cc", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:20.993567Z", - "iopub.status.busy": "2024-05-07T15:49:20.993008Z", - "iopub.status.idle": "2024-05-07T15:49:21.013136Z", - "shell.execute_reply": "2024-05-07T15:49:21.012480Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/jpeg": 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", "text/plain": [ - "" + "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 12, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "result.convergence_graph" + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(nrows=1, ncols=1)\n", + "axes.plot(cost_values)\n", + "axes.set_xlabel(\"Iterations\")\n", + "axes.set_ylabel(\"Cost\")\n", + "axes.set_title(\"Cost convergence\")" ] }, { @@ -467,25 +361,17 @@ }, { "cell_type": "markdown", - "id": "670eddd3-2da7-4a88-b571-7884ef24f60c", + "id": "0e49c243-8621-4893-9033-ddb45087f30d", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm:" + "We can also examine the statistics of the algorithm. In order to get samples with the optimized parameters, we call the `get_results` method:" ] }, { "cell_type": "code", - "execution_count": 13, - "id": "516d78ba-2951-46eb-b1af-efe877513556", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:21.015680Z", - "iopub.status.busy": "2024-05-07T15:49:21.015305Z", - "iopub.status.idle": "2024-05-07T15:49:21.093102Z", - "shell.execute_reply": "2024-05-07T15:49:21.092387Z" - }, - "tags": [] - }, + "execution_count": 24, + "id": "778d3344-c84e-47cd-89b6-55d1df980813", + "metadata": {}, "outputs": [ { "data": { @@ -508,83 +394,68 @@ " \n", " \n", " \n", + " solution\n", " probability\n", " cost\n", - " solution\n", - " count\n", " \n", " \n", " \n", " \n", - " 0\n", - " 0.058\n", - " 1.0\n", - " [1, 1, 0, 0, 1, 0, 1, 0, 1, 0]\n", - " 58\n", + " 128\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'...\n", + " 0.002441\n", + " 2.0\n", " \n", " \n", - " 2\n", - " 0.024\n", - " 1.0\n", - " [1, 1, 0, 1, 1, 0, 0, 0, 1, 0]\n", - " 24\n", + " 335\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'...\n", + " 0.000977\n", + " 2.0\n", " \n", " \n", - " 272\n", - " 0.001\n", + " 204\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'...\n", + " 0.001953\n", " 2.0\n", - " [0, 1, 1, 0, 1, 0, 1, 0, 1, 0]\n", - " 1\n", " \n", " \n", - " 220\n", - " 0.001\n", + " 191\n", + " {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.001953\n", " 2.0\n", - " [1, 1, 0, 1, 1, 1, 0, 0, 0, 0]\n", - " 1\n", " \n", " \n", - " 156\n", - " 0.002\n", + " 116\n", + " {'x_0': 1, 'x_1': 0, 'x_2': 1, 'x_3': 0, 'x_4'...\n", + " 0.002441\n", " 2.0\n", - " [1, 1, 0, 0, 1, 1, 0, 0, 1, 0]\n", - " 2\n", " \n", " \n", "\n", "" ], "text/plain": [ - " probability cost solution count\n", - "0 0.058 1.0 [1, 1, 0, 0, 1, 0, 1, 0, 1, 0] 58\n", - "2 0.024 1.0 [1, 1, 0, 1, 1, 0, 0, 0, 1, 0] 24\n", - "272 0.001 2.0 [0, 1, 1, 0, 1, 0, 1, 0, 1, 0] 1\n", - "220 0.001 2.0 [1, 1, 0, 1, 1, 1, 0, 0, 0, 0] 1\n", - "156 0.002 2.0 [1, 1, 0, 0, 1, 1, 0, 0, 1, 0] 2" + " solution probability cost\n", + "128 {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'... 0.002441 2.0\n", + "335 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'... 0.000977 2.0\n", + "204 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'... 0.001953 2.0\n", + "191 {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.001953 2.0\n", + "116 {'x_0': 1, 'x_1': 0, 'x_2': 1, 'x_3': 0, 'x_4'... 0.002441 2.0" ] }, - "execution_count": 13, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " mvc_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=True).head(5)" + "optimization_result = combi.get_results()\n", + "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { "cell_type": "markdown", - "id": "687f492b-a4a5-49c6-964c-8959b035bb93", + "id": "ea88e99f-300d-4a18-b122-d0f2b31080a8", "metadata": {}, "source": [ "And the histogram:" @@ -592,31 +463,15 @@ }, { "cell_type": "code", - "execution_count": 14, - "id": "31a4e74d-b2b8-42e0-826d-de7b51de1fe8", + "execution_count": 25, + "id": "26f85e77-a110-4e9c-a8ac-3354eae3c8da", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:21.095943Z", - "iopub.status.busy": "2024-05-07T15:49:21.095378Z", - "iopub.status.idle": "2024-05-07T15:49:21.326954Z", - "shell.execute_reply": "2024-05-07T15:49:21.326200Z" - }, "tags": [] }, "outputs": [ { "data": { - "text/plain": [ - "array([[]], dtype=object)" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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jRozQRx99pGXLlunpp5+27bt06ZJmzJih0NBQHTp0SK1bt5Yk/f73v1ePHj00ffp0xcXFKSgoqHZOHAAANGhu+ahx69atOnnypMaOHWsLXZIUEhKiOXPmqKioSElJSZUew8vLS3PnzrULXaXbZ8+eLUnasWOH3b61a9fq8uXLmjFjhi10SVLr1q31xBNPKDs7Wx988IGTZwcAABortwxe27dvlyTFxsaW2RcXFyepbGhyhJeXlyTJ09P+hl9ttwsAABo3t3zUmJ6eLknq0KFDmX1hYWEKDAy0lamJt99+W1LZgFVZu6Xbqmq3sLBQhYWFtu+5ubk17icAAGhYnLrjdenSJVf1w05OTo6k648WyxMcHGwr46iUlBQtX75cnTt31iOPPFLtdoODg+3KVGTRokUKCQmxfdq0cexdiAAAoOFyKni1bt1aU6ZM0eHDh13UndqVlpam+Ph4hYSEaO3atfLx8XF5G7Nnz1ZOTo7tk5nJuw0BAMB1TgWvoqIivfXWW+rVq5cGDBig5ORklZSUON2p0jtOFd1dys3NrfBuWEUOHDig2NhYeXh4KDU1VXfccYdD7ZY+MqyqXR8fHwUHB9t9AAAAJCeDV0ZGhp555hndcsst2r17t8aOHau2bdtq4cKFysrKqvFxK5tPlZWVpby8vHLnYVXkwIEDGjx4sKxWq1JTU9W7d2+H261s/hcAAEB1OBW8WrZsqYULFyojI0OrV6/WPffco6ysLD333HMKDw/XmDFjtGvXLoePGx0dLUnatGlTmX2pqal2ZapSGrquXbumjRs36u677zalXQAAgJ9yyXISnp6eGj16tD777DMdOXJEjz76qLy9vZWcnKzo6Gj16NFDb731VqWv6bnRoEGDFBkZqdWrV9vNH8vJyVFCQoK8vb01YcIE2/bz58/r6NGjZR4RHjx4UIMHD1ZJSYlSUlLUt2/fStt96KGHFBISoldffVVnz561bT979qyWLl2q0NBQDR8+vFrnAAAA8FMuX8erS5cuWr58uc6ePaunnnpKhmHoiy++0NSpU3XrrbfqmWeeqXKJBU9PT61YsUJWq1UDBw7U1KlTNWvWLHXr1k3Hjx9XQkKCIiIibOVnz56tzp072y1uevHiRQ0ePFiXL19W//79tXnzZi1YsMDu89JLL9m127RpUy1dulTZ2dnq2bOnZsyYoRkzZqhnz566cOGC/vrXv7JqPQAAqLFaWcfrs88+09KlS7VhwwZJkre3t7p3765//etfSkhI0MqVKyuc4F4qJiZGu3bt0vz585WcnKzi4mJ16dJFixcvVnx8fJV9yM3NtS13sXHjRm3cuLFMmfDwcM2cOdNu27hx4xQaGmrrp8ViUa9evTRv3jz9/Oc/r/4gAAAA/ITLgtfVq1f17rvvatmyZfr3v/8twzDUsmVLTZ8+XdOmTVOLFi2Unp6uZ555RmvWrNGsWbPKDUM3ioqKUkpKSpVtJyYmKjEx0W5bRESEDMOo0bkMGTJEQ4YMqVFdAACAijgdvE6cOKFly5YpKSlJOTk5MgxDUVFR+s1vfqOHHnrI7rU8HTp00Pvvv68zZ85o3759zjYNAABQrzgVvIYOHarNmzfLarXKy8tLo0eP1m9+85tKfzkoSbfffrv+9a9/OdM0AABAveNU8EpNTVWLFi00depUPf7442rZsmW16v3yl79U27ZtnWkaAACg3nEqeL399tsaO3asvL29Hap3//336/7773emaQAAgHrHqeUkIiMjdfr06SrLpaena+fOnc40BQAAUO85FbxiYmK0ePHiKsv98Y9/VExMjDNNAQAA1HtOBS/DMGq8ZAMAAEBj4/KV68tz6dIl+fr6mtEUAACA23J4cn1GRobd97y8vDLbSpWUlOirr77Spk2b1L59+5r1EAAAoIFwOHhFRETIYrHYvq9bt07r1q2rtI5hGBo3bpzjvQMAAGhAHA5ebdu2tQWvjIwM+fv7KzQ0tNyy3t7eat26tUaMGKHp06c711MAAIB6zuHgdePyER4eHho1apTefvttV/YJAACgQXJqAdWVK1fqtttuc1VfAAAAGjSngtfEiRNd1Q8AAIAGz5TlJAAAAODgHa/IyEhZLBZ9+umnateunSIjI6td12Kx6OTJkw53EAAAoKFwKHidPn1aFotFxcXFtu/VdeMSFAAAAI2RQ8Hrm2++kSTdeuutdt8BAABQNYeCV3h4eKXfAQAAUDEm1wMAAJiE4AUAAGAShx41/upXv6pxQxaLRW+99VaN6wMAANR3DgWvxMTEGjdE8AIAAI2dQ8Fr5cqVtdUPAACABs+h4MUrggAAAGqOyfUAAAAmIXgBAACYxKFHje+8844kafjw4QoKCrJ9r64JEyY4VB4AAKAhcSh4TZo0SRaLRX369FFQUJDte3URvAAAQGPmUPCaMGGCLBaLQkJC7L4DAACgak6t4+XMul4AAACNDZPrAQAATELwAgAAMIlLgtd//vMfPfbYY+rUqZMCAwMVEBCgjh076rHHHtO///1vVzQBAABQ7zkdvJYtW6YePXrozTff1PHjx3XlyhVdvXpV6enpeuONN9SrVy+98sorrugrAABAveZU8EpJSdGMGTNUUlKi//3f/9U//vEPffnll/ryyy/10UcfaeTIkbp27Zp++9vfKiUlxVV9BgAAqJcc+lXjT/3xj3+UxWLR+++/r1GjRtntu+OOO/SLX/xCf//73/XQQw/pj3/8o4YOHepUZwEAAOozp+54HTx4UFFRUWVC141Gjhypu+++WwcPHnSmKQAAgHrPqeBlsVjUvn37Ksu1b9+ehVYBAECj51Tw6tq1q9LT06ssl56eri5dujjTFAAAQL3n1ByvJ598UiNGjND777+v0aNHl1smOTlZaWlpWrt2rTNNAfVSRkaGsrOza1Q3NDRUbdu2dXGPAAB1yaHglZGRYfe9V69e+u1vf6tx48bp73//uyZMmKB27dpJkr755hu9++67+uCDD/Tb3/5WvXv3dl2vgXogIyNDHTt1VsHVKzWq7+vnr2NHvyZ8AUAD4lDwioiIKHeulmEY+uCDD/TBBx+Uu++ll17Syy+/rJKSkpr3FKhnsrOzVXD1iprfN0tezds4VLf4QqYufPyisrOzCV4A0IA4FLzatm3LJHnAQV7N28gn7La67gYAwA04FLxOnz5dS90AAABo+Nz6JdlpaWkaNmyYmjRpooCAAPXp00dr1qypdv2TJ09qwYIFeuCBB3TrrbfKYrEoIiKi0joWi6XCz6RJk5w7IQAA0Kg59avG2rRt2zbFxcXJ19dXo0ePVlBQkNatW6f4+HhlZmZq1qxZVR7js88+08KFC3XTTTepc+fOysrKqlbb4eHh5Yas7t27O3gWAAAAP3Jp8MrJyVFubq4Mwyh3f3UnCZeUlGjKlCny8PDQzp07bYHn2WefVVRUlObMmaORI0cqPDy80uMMHDhQe/fuVbdu3eTn5ydfX99qtR8REaEFCxZUqywAAEB1Of2o8dKlS5oxY4bCwsLUrFkzRUREqF27dmU+kZGR1T7m1q1bdfLkSY0dO9buLlNISIjmzJmjoqIiJSUlVXmcyMhI9enTR35+fjU5NQAAAJdy6o5XTk6O+vTpoxMnTuimm26Sn5+frly5opYtWyorK0uGYchisTj8c/jt27dLkmJjY8vsi4uLkyTt2LHDma5X6vLly3rjjTeUnZ2tZs2aqV+/ftVeeb+wsFCFhYW277m5ubXVTQAAUM84dcfrT3/6k9LT0zVhwgTl5ORo5MiRslgs+vbbb/XDDz/otddeU5MmTRQdHa1vvvmm2sctfQ1Rhw4dyuwLCwtTYGBgtV5VVFNHjhzRtGnTNHfuXE2fPl1du3bV0KFD9d1331VZd9GiRQoJCbF92rRxbP0mAADQcDkVvP7xj38oNDRUr732mvz8/OzW+PL399e0adP0z3/+U6tWrdIbb7xR7ePm5ORIuv5osTzBwcG2Mq42a9Ys7dmzR9nZ2crNzdWePXs0dOhQbdy4Uffdd5+uXbtWaf3Zs2crJyfH9snMzKyVfgIAgPrHqeB16tQp9erVyzZpvTR43RhO+vTpo759++qtt95ypinTLFmyRH379lXz5s0VFBSkvn376uOPP1Z0dLTS0tL04YcfVlrfx8dHwcHBdh8AAADJBZPrmzZtavtnf39/Sdcn3N+obdu2Onr0aLWPWXqnq6K7Wrm5uRXeDasNHh4emjJliiRp9+7dprULAAAaFqeCV6tWrfTtt9/avpdOov/iiy/syp06dUqentWfx186t6u8eVxZWVnKy8srd/5XbQoNDZUk5efnm9ouAABoOJwKXl26dNGxY8ds3wcMGCDDMDR//nz98MMPkqRVq1Zp//79uv3226t93OjoaEnSpk2byuxLTU21K2OW/fv3S1KVK98DAABUxKngNWTIEH333Xfatm2bJKlv377q16+fdu/erWbNmql58+aaOHGiLBaLfve731X7uIMGDVJkZKRWr16tw4cP27bn5OQoISFB3t7emjBhgm37+fPndfToUacn3H/55ZcqLi4us33Pnj1avHixvLy8NGrUKKfaAAAAjZdT63iNGTNGt99+u91doPXr1+uRRx5RSkqKLl26pKZNm+rZZ5/V/fffX/1OeXpqxYoViouL08CBA+1eGXTmzBktWbLErs3Zs2crKSlJK1eutHvVT3Z2tp566inb9+LiYmVnZ9uVWbJkie0x4osvvqh//vOf6t+/v9q0aSMvLy999dVX2rRpkywWi5YtW6b27ds7PE4AAACSk8ErMDBQ/fr1s9vWokUL/eMf/9CVK1eUk5OjW265RR4ejt9Yi4mJ0a5duzR//nwlJyeruLhYXbp00eLFixUfH1+tY+Tl5ZVZ4T4/P99u24IFC2zB68EHH9Tly5d15MgRbd68WUVFRQoLC9Po0aM1c+ZMRUVFOXweAAAApWrtJdn+/v62XznWVFRUlFJSUqosl5iYqMTExDLbIyIiKnxvZHmGDx+u4cOHO9JFAACAanNp8MrKytLZs2dlGIZat26tli1buvLwAAAA9ZrT63hJ0ptvvqlOnTrp1ltv1d13360+ffqodevW6tSpk5YvX+6KJgAAAOo9p4KX1WpVfHy8HnvsMR0/flyGYahZs2Zq1qyZDMPQ8ePH9fjjj2vUqFGyWq2u6jMAAEC95FTwWrp0qdauXavQ0FC9+uqrys3N1ffff6/vv/9eubm5Wrp0qW6++WatX79eS5cudVWfAQAA6iWngtdbb70lHx8fbd++Xb/+9a8VGBho2xcYGKjHH39cW7dulZeXl1asWOF0ZwEAAOozp4JXenq67r33XnXu3LnCMp07d1ZMTIxOnDjhTFMAAAD1nlPBKzAw0O4l2RVp2rSp3d0wAACAxsip4NW/f3/t37+/0onzVqtV+/fv1z333ONMUwAAAPWeU8FrwYIFOn/+vGbOnKmioqIy+4uLizVz5kxlZWVp4cKFzjQFAABQ7zm0gOo777xTZtvkyZO1bNkyrV+/Xg899JDatWsnSfrmm2+0du1anTt3To899piOHDmibt26uabXAAAA9ZBDwWvSpEmyWCxlthuGoXPnzunll18us12SXn/9db3++uuaMGGCE10FAACo3xwKXhMmTCg3eAEAAKBqDgWv8l5EDQAAgOpxybsaAQAAUDWH7nhVxTAMXbhwQZLUrFkzeXiQ6wAAAEq5JBlt2bJFQ4YMUWBgoG655RbdcsstCgoK0tChQ7VlyxZXNAEAAFDvOR28nnvuOcXGxmrTpk26evWqDMOQYRi6evWqUlNTFRsbq+eff94VfQUAAKjXnApen376qRYsWCAvLy898cQT+vzzz5Wbm6vc3FwdPnxYM2bMkLe3t+bPn6+tW7e6qs8AAAD1klPB65VXXpHFYtGHH36oV155Rd26dVNgYKACAwPVtWtXvfzyy/rwww8lqcwaXwAAAI2NU8Gr9B2McXFxFZaJjY3VPffco7179zrTFAAAQL3nVPC6fPmywsPDqywXHh6unJwcZ5oCAACo95wKXqGhoTp69GiV5Y4eParQ0FBnmgIAAKj3nApe/fr10+eff67Vq1dXWOa9997ToUOH1L9/f2eaAgAAqPecWkD16aef1vr16zVhwgRt2LBBEydOVLt27SRJp06dUmJiojZs2KCbbrpJTz31lEs6DAAAUF85Fbx69+6t1157Tb/+9a/197//XevWrbPbbxiGPD09tWzZMvXu3dupjgIAANR3Ti+gOmXKFB06dEi/+tWvFBkZKR8fH/n4+CgyMlKPPPKIDh06pClTpriirwAAAPWaU3e8MjIyZLFYdOedd2rFihWu6hMAAECD5NQdr4iICI0ePdpVfQEAAGjQnApewcHBtsn0AAAAqJxTwev2229XZmamq/oCAADQoDkVvKZMmaLdu3crLS3NVf0BAABosJwKXpMnT9bjjz+u2NhYJSQk6NixYyosLHRV3wAAABoUp37VeNNNN9n++ZlnntEzzzxTYVmLxaKSkhJnmgMAAKjXnApehmHUSlkAAICGyKngZbVaXdUPAACABq9GwevEiRNav369Tp8+LR8fH/Xo0UOjRo2Sn5+fq/sHAADQYDgcvF566SX97ne/07Vr1+y2z5s3T5988onuvPNOl3UOAACgIXHoV427du3SrFmzVFJSIn9/f/Xo0UPt27eXxWLR2bNnNWLECB4/AgAAVMCh4LV06VIZhqGJEycqKytLBw4c0PHjx3Xo0CG1b99eJ06c0MaNG2urrwAAAPWaQ8Fr7969at26tZYvX66AgADb9q5du+rll1+WYRjat2+fyzsJAADQEDgUvP773//qrrvukre3d5l9/fv3lyR99913rukZAABAA+NQ8CoqKlKTJk3K3RccHGwrAwAAgLKcemUQAAAAqs/h5SROnDihd955p0b7J0yY4GhzAAAADYbDwWv37t3avXt3ufssFkuF+y0WC8ELAAA0ag4Fr7Zt28pisdRWX8pIS0vT/PnztWfPHhUXF6tLly568skn9dBDD1Wr/smTJ/Xuu+/q0KFDOnjwoM6dO6fw8HCdPn260nqpqalKSEjQoUOHZLFY1KtXL82bN0+DBg1ywVkBAIDGyqHgVVVgcaVt27YpLi5Ovr6+Gj16tIKCgrRu3TrFx8crMzNTs2bNqvIYn332mRYuXKibbrpJnTt3VlZWVpV1Vq1apfHjx6tFixaaNGmSJCk5OVmDBw/WmjVrNHLkSGdPDQAANFJOvSS7tpSUlGjKlCny8PDQzp071b17d0nSs88+q6ioKM2ZM0cjR45UeHh4pccZOHCg9u7dq27dusnPz0++vr6Vlr906ZJmzJih0NBQHTp0SK1bt5Yk/f73v1ePHj00ffp0xcXFKSgoyCXnCQAAGhe3/FXj1q1bdfLkSY0dO9YWuiQpJCREc+bMUVFRkZKSkqo8TmRkpPr06VPtl3evXbtWly9f1owZM2yhS5Jat26tJ554QtnZ2frggw8cPh8AAADJTYPX9u3bJUmxsbFl9sXFxUmSduzY4ZbtFhYWKjc31+4DAAAguWnwSk9PlyR16NChzL6wsDAFBgbaypjVbum2qtpdtGiRQkJCbJ82bdq4vJ8AAKB+csvglZOTI+n6o8XyBAcH28qY1W7pyvxVtTt79mzl5OTYPpmZmS7vJwAAqJ/ccnJ9febj4yMfH5+67gYAAHBDbnnHq/SOU0V3l3Jzcyu8G1Zb7ZbO1aqNdgEAQOPglsGrsvlUWVlZysvLK3ceVm22W9n8LwAAgOpwy+AVHR0tSdq0aVOZfampqXZlGkK7AACgcXDL4DVo0CBFRkZq9erVOnz4sG17Tk6OEhIS5O3tbffex/Pnz+vo0aNOT7h/6KGHFBISoldffVVnz561bT979qyWLl2q0NBQDR8+3Kk2AABA4+WWk+s9PT21YsUKxcXFaeDAgXavDDpz5oyWLFmiiIgIW/nZs2crKSlJK1eutL3mR5Kys7P11FNP2b4XFxcrOzvbrsySJUsUGhoqSWratKmWLl2q8ePHq2fPnoqPj5d0/ZVBFy5cUHJyMqvWAwCAGnPL4CVJMTEx2rVrl+bPn6/k5GTbS7IXL15sC0RVycvLK7PCfX5+vt22BQsW2IKXJI0bN06hoaFKSEjQypUr7V6S/fOf/9w1JwcAABoltw1ekhQVFaWUlJQqyyUmJioxMbHM9oiICBmG4XC7Q4YM0ZAhQxyuBwAAUBm3nOMFAADQEBG8AAAATELwAgAAMAnBCwAAwCQELwAAAJMQvAAAAExC8AIAADAJwQsAAMAkBC8AAACTELwAAABMQvACAAAwCcELAADAJAQvAAAAkxC8AAAATELwAgAAMAnBCwAAwCQELwAAAJMQvAAAAExC8AIAADAJwQsAAMAkBC8AAACTELwAAABMQvACAAAwCcELAADAJAQvAAAAkxC8AAAATELwAgAAMAnBCwAAwCQELwAAAJMQvAAAAExC8AIAADAJwQsAAMAkBC8AAACTELwAAABMQvACAAAwCcELAADAJAQvAAAAkxC8AAAATELwAgAAMAnBCwAAwCQELwAAAJMQvAAAAExC8AIAADAJwQsAAMAkbh280tLSNGzYMDVp0kQBAQHq06eP1qxZ49AxCgsL9dxzz6lDhw7y9fVVq1atNHXqVH333Xdlyp4+fVoWi6XCz4IFC1x0ZgAAoDHyrOsOVGTbtm2Ki4uTr6+vRo8eraCgIK1bt07x8fHKzMzUrFmzqjyG1WrVgw8+qNTUVPXp00cjRoxQenq6VqxYoS1btmjfvn1q0aJFmXrdunXTL3/5yzLb7733XhecGQAAaKzcMniVlJRoypQp8vDw0M6dO9W9e3dJ0rPPPquoqCjNmTNHI0eOVHh4eKXHSUpKUmpqqsaMGaP33ntPFotFkvT6669r+vTpmjdvnpYvX16mXvfu3bm7BQAAXM4tHzVu3bpVJ0+e1NixY22hS5JCQkI0Z84cFRUVKSkpqcrjvPnmm5KkRYsW2UKXJE2bNk2RkZF67733dPXqVZf3HwAAoDxuGby2b98uSYqNjS2zLy4uTpK0Y8eOSo9RUFCg/fv3q2PHjmXujFksFg0ePFj5+fk6cOBAmbrnzp3TsmXLlJCQoLfeeksnT56s4ZkAAAD8yC0fNaanp0uSOnToUGZfWFiYAgMDbWUqcvLkSVmt1nKPceOx09PTNWDAALt9mzdv1ubNm23fLRaLHn74Yb3++usKCAiotN3CwkIVFhbavufm5lZaHgAANB5ueccrJydH0vVHi+UJDg62lXHmGDeWkyR/f38988wzOnjwoC5fvqyLFy/q008/VVRUlFatWqUJEyZU2fdFixYpJCTE9mnTpk2VdQAAQOPglsGrrtx888167rnn1LNnT4WEhKhp06YaNGiQtm7dqo4dO2r9+vU6dOhQpceYPXu2cnJybJ/MzEyTeg8AANydWwav0rtUFd3Vys3NrfBOliPHuLFcZfz9/TV+/HhJ0u7duyst6+Pjo+DgYLsPAACA5KZzvG6cf9WrVy+7fVlZWcrLy1NUVFSlx4iMjJSHh0eFc8Eqm0dWntDQUElSfn5+tcoDaBwyMjKUnZ1do7qhoaFq27ati3sEwJ25ZfCKjo7WokWLtGnTJo0ePdpuX2pqqq1MZfz8/BQVFaV9+/bpzJkzdr9sNAxDmzdvVkBAgO66665q9Wn//v2SpIiICAfOBEBDlpGRoY6dOqvg6pUa1ff189exo18TvoBGxC2D16BBgxQZGanVq1frN7/5jW0tr5ycHCUkJMjb29tuovv58+eVk5Ojli1b2j06nDp1qvbt26fZs2fbLaC6fPlynTp1SlOnTpWfn5+t/Oeff67u3bvbrfklSevXr1dSUpKaNm2qoUOH1uKZA6hPsrOzVXD1iprfN0tezR37IU3xhUxd+PhFZWdnE7yARsQtg5enp6dWrFihuLg4DRw40O6VQWfOnNGSJUvs7jzNnj1bSUlJWrlypSZNmmTbPnHiRCUnJ+tvf/ubvvnmG0VHR+vEiRNav3692rVrp+eff96u3d/+9rc6efKk+vbtq9atW+vatWs6dOiQdu3aJR8fHyUmJlZrThiAxsWreRv5hN1W190AUA+4ZfCSpJiYGO3atUvz589XcnKyiouL1aVLFy1evFjx8fHVOoaHh4c+/PBD/eEPf9C7776rv/zlL2rWrJkeeeQRPf/882Xe0zhu3DitW7dO+/btU3Z2tqxWq2699VY9+uijmjVrljp16lQbpwoAABoJtw1ekhQVFaWUlJQqyyUmJioxMbHcfT4+Ppo/f77mz59f5XEeffRRPfroo452EwAAoFrccjkJAACAhojgBQAAYBKCFwAAgEkIXgAAACYheAEAAJiE4AUAAGASghcAAIBJCF4AAAAmIXgBAACYhOAFAABgEoIXAACASQheAAAAJiF4AQAAmITgBQAAYBKCFwAAgEkIXgAAACYheAEAAJiE4AUAAGASghcAAIBJCF4AAAAmIXgBAACYhOAFAABgEoIXAACASQheAAAAJiF4AQAAmITgBQAAYBKCFwAAgEkIXgAAACYheAEAAJjEs647ALi7jIwMZWdnO1zv66+/roXeANfV9LqUpNDQULVt29bFPQJQHQQvoBIZGRnq2KmzCq5eqeuuADbOXpe+fv46dvRrwhdQBwheQCWys7NVcPWKmt83S17N2zhU9+qpA8r5bFUt9QyNmTPXZfGFTF34+EVlZ2cTvIA6QPACqsGreRv5hN3mUJ3iC5lOt1vTx5U8SmocanJdAqhbBC/ADV3LuyRZLBo3blyN6vMoCQDcE8ELcEPWwjzJMHiUBAANDMELcGM8SgKAhoV1vAAAAEzCHS8AqEM1+QEFa8TBHbG2XPUQvACgDjj7AwrAnbC2XPURvACgDjjzAwrWiIO7YW256iN4AUAdqqs14oDawA+CqsbkegAAAJMQvAAAAEzCo0YAAFDnGssr0gheAACgzjS2V6S5dfBKS0vT/PnztWfPHhUXF6tLly568skn9dBDD1X7GIWFhVq8eLHeffddZWZmqlmzZrrvvvv0/PPP6+abby63znvvvaeXX35ZX331lby9vdWvXz8999xz6tmzp6tODQAAqPG9Is1tg9e2bdsUFxcnX19fjR49WkFBQVq3bp3i4+OVmZmpWbNmVXkMq9WqBx98UKmpqerTp49GjBih9PR0rVixQlu2bNG+ffvUokULuzovvPCC5s2bp/DwcD322GP64Ycf9P777+uee+7Rli1b1K9fv9o6ZQAAGq3G8otItwxeJSUlmjJlijw8PLRz5051795dkvTss88qKipKc+bM0ciRIxUeHl7pcZKSkpSamqoxY8bovffek8VikSS9/vrrmj59uubNm6fly5fbyqenp2vBggX62c9+pn/9618KCQmRJD3++OPq06ePpkyZon//+9/y8OA3CQAAwHFumSC2bt2qkydPauzYsbbQJUkhISGaM2eOioqKlJSUVOVx3nzzTUnSokWLbKFLkqZNm6bIyEi99957unr1qm37ypUrVVJSorlz59pClyR1795dY8aM0ddff61du3a54AwBAEBj5JbBa/v27ZKk2NjYMvvi4uIkSTt27Kj0GAUFBdq/f786duxY5s6YxWLR4MGDlZ+frwMHDri0XQAAgIq45aPG9PR0SVKHDh3K7AsLC1NgYKCtTEVOnjwpq9Va7jFuPHZ6eroGDBhg++fAwECFhYVVWr4yhYWFKiwstH3PycmRJOXm5lZaz1F5eXnX28s6IWtRgUN1S1e9Nr3uxbOSpIMHD9r67wgPDw9ZrVaH6zlT99ixY5Ia1zhLdTPW9bFuY7w+6tu/I+qaU7fO/iz8/9dzXl6ey/+eLT2eYRguPa4MNzR48GBDkpGenl7u/latWhnBwcGVHmP37t2GJOPhhx8ud/8bb7xhSDL+/Oc/27Z5eXkZt956a7nljx8/bkgyHnjggUrbnT9/viGJDx8+fPjw4dMAPpmZmZX+ve8ot7zjVZ/Nnj1bTz75pO271WrVxYsX1bx5c7t5ZjWVm5urNm3aKDMzU8HBwU4frz5jLH7EWPyIsfgRY/EjxuJHjMWPKhsLwzD0ww8/qFWrVi5t0y2DV+nE9tLHdD+Vm5urpk2bOn2MG8uV/rMj5cvj4+MjHx8fu21NmjSptE5NBAcHN/o/MKUYix8xFj9iLH7EWPyIsfgRY/Gjisaiqr/za8ItJ9dXNp8qKytLeXl5Fc7dKhUZGSkPD48K52SVN4+sQ4cOysvLU1ZWVrXKAwAAOMItg1d0dLQkadOmTWX2paam2pWpiJ+fn6KionTs2DGdOXPGbp9hGNq8ebMCAgJ01113ubRdAACAirhl8Bo0aJAiIyO1evVqHT582LY9JydHCQkJ8vb21oQJE2zbz58/r6NHj5Z5TDh16lRJ1+ddGTf8KmH58uU6deqUHn74Yfn5+dm2T548WZ6ennrhhRfsjnX48GH97W9/U+fOndW/f39Xn65DfHx8NH/+/DKPMxsjxuJHjMWPGIsfMRY/Yix+xFj8qC7GwmIYrv6dpGtU9MqgM2fOaMmSJXavDJo0aZKSkpK0cuVKTZo0ybbdarVq2LBhtlcGRUdH68SJE1q/fr0iIiK0f//+Sl8ZNGLECNsrg4qKinhlEAAAcIpb3vGSpJiYGO3atUv9+vVTcnKyXnvtNd1yyy16//33q/WeRun6eiQffvihFixYoO+//15/+ctftHv3bj3yyCPau3dvmdAlSXPnztWqVavUokULvfbaa1qzZo0GDBigPXv2ELoAAIBT3PaOFwAAQEPjtne8AAAAGhqCFwAAgEkIXvVEWlqahg0bpiZNmiggIEB9+vTRmjVr6rpbtSYiIkIWi6Xcz7333lumfGFhoZ577jl16NBBvr6+atWqlaZOnarvvvvO/M7XwKpVqzRt2jTddddd8vHxkcViUWJiYoXlc3Nz9eSTTyo8PFw+Pj6KiIjQ008/XeG796xWq1599VV16dJFfn5+atGihcaMGaNTp07V0hnVnCNjsWDBggqvE4vFotOnT5dbLzU1VdHR0QoKClJwcLBiYmK0ZcuW2jupGvr222/10ksvKTY2Vm3btpW3t7fCwsI0YsQI7d+/v9w6DfXacHQsGvK1UVBQoCeffFIDBw5Uq1at5Ovrq7CwMPXr108rV65UcXFxmToN9bpwdCzc4bpwy5XrYa+iX3jGx8crMzOz2j82qG9CQkI0c+bMMtsjIiLsvlutVj344IO2X6+OGDFC6enpWrFihbZs2aJ9+/aV+0MKdzJv3jydOXNGoaGhatmyZZm1526Un5+v6OhoHT58WLGxsRozZow+//xzLVmyRDt27NDOnTvl6+trV2fatGlasWKF7rjjDv3mN7/RuXPntGbNGm3atEn79u1zq4WBHRmLUhMnTixzXUjlvzVi1apVGj9+vFq0aGH7FXRycrIGDx6sNWvWaOTIkU6egeu8+uqrWrx4sdq3b6/Y2Fi1aNFC6enp2rBhgzZs2KDVq1crPj7eVr4hXxuOjkWphnht5OXl6bXXXlNUVJR+8YtfqEWLFrp06ZJSUlL0q1/9Su+//75SUlLk4XH93kpDvi4cHYtSdXpduPTNj3C54uJio3379oaPj4/x+eef27ZfvnzZ+NnPfmZ4e3sbp0+frrsO1pLw8HAjPDy8WmXffvttQ5IxZswYw2q12ra/9tprhiRj6tSptdRL19m8ebPt3+OiRYsMScbKlSvLLfvss88akozf//73dtt///vfG5KMhIQEu+1bt241JBkDBw40CgsLbds/+eQTQ5IRGxvr2pNxkiNjUfpS+m3btlXr2BcvXjSaNGlihIaG2r34NjMz0wgNDTVCQ0ON3NxcZ0/BZdatW2ds3769zPadO3caXl5eRtOmTY2CggLb9oZ8bTg6Fg352rh27Zrdv69SxcXFxr333mtIMj7++GPb9oZ8XTg6Fu5wXRC83FxqaqohyZg8eXKZfYmJiYYkY+HChXXQs9rlSPDq27evIalMALVarUZkZKQREBBgXLlypRZ6WTsqCxtWq9Vo1aqVERgYaOTl5dnty8vLMwIDA43IyEi77WPGjDEkGTt27ChzvNL/MJ05c8al5+Aqrg5ey5cvr/DPzIIFCwxJRlJSkhM9Nk9sbKwhyUhLSzMMo/FdGzf66VgYRuO9Nl5++WVDkvHSSy8ZhtG4r4ufjoVhuMd1wRwvN7d9+3ZJUmxsbJl9cXFxkqQdO3aY2SXTFBYWKjExUQkJCVq6dGm58zgKCgq0f/9+dezYUeHh4Xb7LBaLBg8erPz8fB04cMCsbteq9PR0nTt3Tv369VNAQIDdvoCAAPXr10+nTp1SZmambfv27dtt+36qoVxDO3fu1OLFi/WnP/1JGzZsqHDeSkP68+Tl5SVJ8vS8PmOkMV8bPx2LGzWma8NqtWrjxo2SpDvvvFNS470uyhuLG9XldcEcLzdX2cu5w8LCFBgYWOGLwOu7rKwsTZ482W5b79699be//U3t27eXJJ08eVJWq7XC+QY3vnB9wIABtdthE1T1svYOHTooNTVV6enpatOmjfLz83X+/Hndeeeduummm8otf+Nx66v58+fbfW/SpIlefvllu1eLSZWPX30ai4yMDH366adq2bKlunTpIqnxXhvljcWNGvK1UVRUpISEBBmGoQsXLmjLli06evSoJk+erEGDBklqPNdFdcbiRnV5XXDHy82VvjMyJCSk3P3BwcFl3lHZEEyePFlbtmzRf//7X+Xn5+vzzz/X+PHjlZaWpkGDBumHH36QVL3xubFcfefo+Tb08enWrZvefvttnTp1SlevXtU333yjV199VRaLRZMmTdI//vEPu/KVjUd9GYvi4mKNHz9ehYWFWrx4se0vx8Z4bVQ0FlLjuDaKioq0cOFCPffcc1q2bJmOHTump556Sm+88YatTGO5LqozFpJ7XBfc8YJb+un/jXTv3l3vvPOOJOndd9/Vm2++qSeffLIuugY3Mnz4cLvvEREReuKJJ9S5c2cNHjxY8+bN0wMPPFBHvXM9q9WqSZMmaefOnZoyZYrGjx9f112qM1WNRWO4NgIDA2UYhqxWq86dO6ePPvpIc+bM0d69e/XJJ5/YgkFjUN2xcIfrgjtebq40ZVeUqHNzcyv8P5OGaNq0aZKk3bt3S6re+NxYrr5z9Hwb2/iUGjRokNq3b68vv/zSdo5S5ePh7mNhtVr1q1/9SqtXr9a4ceP0+uuv2+1vTNdGVWNRmYZ4bXh4eKh169aaPn263njjDe3evVsvvPCCpMZ1XUiVj0VlzLwuCF5urrJnyFlZWcrLy3Ob9VTMEBoaKun6ujSSFBkZKQ8PjwqfsVc1v6G+qWpOwU/PNyAgQC1bttQ333yja9euVVm+ISm9Vq5cuWLbVtn4ufNYWK1WTZ48WUlJSRozZowSExPLrEvUWK6N6oxFVRrStfFTpZPASyeFN5brojw/HYuqmHVdELzcXHR0tCRp06ZNZfalpqbalWkMSn/ZWLrwnZ+fn6KionTs2LEyC20ahqHNmzcrICBAd911l9ldrRUdOnRQq1attHv3blv4LJWfn6/du3erXbt2atOmjW17dHS0bd9PlV5DAwcOrN2Omyw/P19fffWVAgICbP8xlernn6fSoPHOO+8oPj5e7777boWTnhv6tVHdsahMQ7o2ynPu3DlJP/7SszFcFxX56VhUxtTrwqHFJ2C64uJiIzIystIFVL/55ps6619t+Prrr438/Pxyt4eFhZVZX6YhLKB6o8a+gOqNKhuL3Nxc49ixY2W2X7lyxbYO0U/Xv7t48aIREhJSLxbJNIzri0NOnDjRkGSMGjXKKC4urrR8Q742HBmLhn5tfPXVV+X+NzI/P98YMmSIIcl44YUXbNsb8nXhyFi4y3VhMQzDcCyqwWwVvTLozJkzWrJkSYN7ZdCCBQv05z//WQMHDlR4eLgCAgJ0/PhxffLJJyouLtbs2bOVkJBgK2+1WjVs2DDbK4Oio6N14sQJrV+/XhEREdq/f7/bvzJoxYoV2rVrlyTpyy+/1KFDh9SvXz/ddtttkqT+/fvr0UcflXT9/8z69eunI0eOKDY2Vj179tShQ4e0adMm9e7dWzt27JCfn5/d8adMmWJ7/ccvfvELnT9/XsnJyQoMDNTevXv1s5/9zNwTrkR1x+L06dOKjIxU79691blzZ4WFhem///2vPv30U509e1ZdunTRtm3b1Lx5c7vj3/j6j9JXzCQnJys7O1vJyckaNWqUuSdciQULFmjhwoUKDAzU//3f/5W7TtUvf/lLde/eXVLDvjYcGYuGfm2U/jeyf//+ioiIUHBwsL799lulpKTowoULGjBggFJTU23/rhv6dVHdsXCb68KhmIY6s3//fmPIkCFGcHCw4efnZ0RFRRnvv/9+XXerVmzfvt146KGHjA4dOhjBwcGGp6enERYWZjz44INGampquXUKCgqMBQsWGO3btze8vb2NsLAw49FHHzWysrJM7n3NlP6ffEWfiRMn2pW/fPmyMXPmTKNNmzaGl5eX0bZtW2PWrFkV/p/XtWvXjJdfftm44447DB8fH6N58+ZGfHy8ceLECRPOzjHVHYucnBzj17/+tdG7d2+jRYsWhqenpxEUFGRERUUZf/zjHyt9W0FKSooxYMAAIyAgwAgMDDSio6ONzZs3m3SG1VfVWKicu4EN9dpwZCwa+rWRlpZmTJkyxbjjjjuMJk2aGJ6enkbz5s2NmJgYY/ny5eXeDWyo14UjY+Eu1wV3vAAAAEzC5HoAAACTELwAAABMQvACAAAwCcELAADAJAQvAAAAkxC8AAAATELwAgAAMAnBCwAAwCQELwAAAJMQvAAAAExC8AKAOpKYmCiLxaJJkybVdVcAmITgBQAAYBKCFwAAgEkIXgAalStXruill15S//791bRpU/n4+Cg8PFz333+/Vq9eXabsH/7wB/Xs2VNBQUHy9/fXHXfcoXnz5unSpUvlHv/gwYOKj49X69at5e3treDgYEVGRmrEiBH68MMPbeUiIiI0efJkSVJSUpIsFovtc++999ba+QOoWxbDMIy67gQAmCEzM1NDhgzRf/7zH/n7+6tfv35q3ry5vv32W33xxRdq0qSJTp8+LUm6ePGiBg0apMOHDys4OFj33nuvvLy8tGPHDmVnZ6tdu3baunWrIiIibMffsmWLhg4dquLiYnXr1k0dOnTQtWvX9O233+rIkSMaMmSINmzYIEl66qmntG/fPu3evVvt27dX//79bcfp1KmT/t//+38mjgwA0xgA0Ahcu3bNuOuuuwxJRmxsrPHdd9/Z7b969arxz3/+0/Y9Pj7ekGTcfffdRnZ2tm37Dz/8YAwdOtSQZNxzzz12x4iJiTEkGatWrSrT/uXLl429e/fabVu5cqUhyZg4caILzhBAfcCjRgCNwkcffaQDBw6oZcuWWrdunVq0aGG339fXV8OGDZMkZWRkaO3atbJYLHrjjTfUvHlzW7nAwEC9+eab8vX11Z49e7Rnzx7bvv/+97+SZDvOjUJCQtSnT5/aODUA9QjBC0CjsHHjRknS2LFjFRgYWGnZnTt3ymq1qkePHuratWuZ/bfeeqvi4uIkSdu2bbNtj4qKkiQ9/PDD2rVrl0pKSlzVfQANBMELQKNw5swZSdfnT1Xl22+/lSS1a9euwjLt27e3KytJixYtUs+ePZWSkqIBAwYoODhY/fv317x58/T11187030ADQTBCwBcJCwsTAcOHNC2bds0d+5c3X333Tp06JBeeOEF3XHHHVq8eHFddxFAHSN4AWgU2rZtK0k6evRolWVvvfVWSdKpU6cqLFO6r7RsqdLlIJ5//nlt27ZNFy9e1GuvvSaLxaI5c+bo5MmTNT0FAA0AwQtAozBkyBBJ0t/+9jfl5+dXWnbgwIHy8PDQ4cOHdeTIkTL7z58/b5szFhMTU+mxfH199dhjj6lr166yWq364osvbPu8vb0liblgQCNC8ALQKDzwwAPq0aOHzp07p1GjRunChQt2+wsKCpSSkiLp+t2xUaNGyTAMTZs2za5sfn6+pk6dqoKCAt1zzz265557bPuWLFmijIyMMm0fPXpU6enpkqTw8HDb9tatW0uS/vOf/7juRAG4NRZQBdBonDlzRnFxcTp27Jj8/f3Vv39/2wKqR44csVtA9cKFCxo0aJCOHDmikJAQxcTEyNPTUzt27ND3339f7gKqTZo0UU5Ojjp16qTOnTvLz89P586ds/3CccKECUpKSrKVLyoqUrt27XTu3Dn16NFDXbp0kZeXlzp27Kinn37a5NEBYAaCF4BGJS8vT3/961/197//XUePHlVRUZHCwsLUrVs3jR07VvHx8bayV65c0SuvvKLk5GQdP35cVqtV7dq10/Dhw/XUU0+padOmdsd+7733tGXLFqWlpencuXPKz89XWFiYbr/9dk2dOlUPPvigLBaLXZ1///vfmjt3rvbu3asLFy7IarUqOjpa27dvN2M4AJiM4AUAAGAS5ngBAACYhOAFAABgEoIXAACASQheAAAAJiF4AQAAmITgBQAAYBKCFwAAgEkIXgAAACYheAEAAJiE4AUAAGASghcAAIBJCF4AAAAm+f8AIM1KlGo/aNcAAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -626,7 +481,12 @@ } ], "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" + "optimization_result[\"cost\"].plot(\n", + " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + ")\n", + "plt.ylabel(\"Probability\", fontsize=16)\n", + "plt.xlabel(\"cost\", fontsize=16)\n", + "plt.tick_params(axis=\"both\", labelsize=14)" ] }, { @@ -639,42 +499,30 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 26, "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:21.329517Z", - "iopub.status.busy": "2024-05-07T15:49:21.329322Z", - "iopub.status.idle": "2024-05-07T15:49:21.332804Z", - "shell.execute_reply": "2024-05-07T15:49:21.332219Z" - }, "tags": [] }, "outputs": [], "source": [ - "best_solution = optimization_result.solution[optimization_result.cost.idxmin()]" + "best_solution = optimization_result.solution[optimization_result.cost.idxmin()]\n", + "best_solution = [best_solution[f\"x_{v}\"] for v in range(len(best_solution))]" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 27, "id": "2449caf6-d3c2-49b1-81cd-0e33e248cc18", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:21.335350Z", - "iopub.status.busy": "2024-05-07T15:49:21.334887Z", - "iopub.status.idle": "2024-05-07T15:49:21.339246Z", - "shell.execute_reply": "2024-05-07T15:49:21.338598Z" - } - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[1, 1, 0, 0, 1, 0, 1, 0, 1, 0]" + "[1, 1, 1, 0, 0, 0, 1, 0, 1, 0]" ] }, - "execution_count": 16, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -685,20 +533,13 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 28, "id": "fed415f4-67ed-4a85-9138-553c75972ac8", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:21.341589Z", - "iopub.status.busy": "2024-05-07T15:49:21.341144Z", - "iopub.status.idle": "2024-05-07T15:49:21.493854Z", - "shell.execute_reply": "2024-05-07T15:49:21.493175Z" - } - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -744,15 +585,9 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 29, "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:21.496514Z", - "iopub.status.busy": "2024-05-07T15:49:21.496111Z", - "iopub.status.idle": "2024-05-07T15:49:21.561467Z", - "shell.execute_reply": "2024-05-07T15:49:21.560785Z" - }, "pycharm": { "name": "#%%\n" }, @@ -769,16 +604,9 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 30, "id": "1894641b-b166-47da-a3b8-5851d9042054", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:21.564260Z", - "iopub.status.busy": "2024-05-07T15:49:21.563927Z", - "iopub.status.idle": "2024-05-07T15:49:21.568416Z", - "shell.execute_reply": "2024-05-07T15:49:21.567758Z" - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -786,7 +614,7 @@ "[1, 1, 0, 1, 1, 0, 0, 0, 1, 0]" ] }, - "execution_count": 19, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -797,21 +625,15 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 31, "id": "a7524894-b5c5-42d4-8f92-a019bef5e7da", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:21.570739Z", - "iopub.status.busy": "2024-05-07T15:49:21.570457Z", - "iopub.status.idle": "2024-05-07T15:49:21.725756Z", - "shell.execute_reply": "2024-05-07T15:49:21.724890Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/png": 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", 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Zd/DAA/n06qXMEPf1qFTtCQgoxGar/bnfQtQnq9XCsmUjgWdAZ+L3wyK41RNzavLXCZ2IusmCH+H4ZMhbCNEsVc+VHEdU1B7AFV/ftYwYMVXpWL8QHDwUD4/vSUs7RKtW/ZSOI1qY/PxLbN48kNat80lNHcrs2d+i1Tpj1l7kzW1JdW7/96PaMbWPzJ0UclKOEKIZOnz4Ey5cmEtIiIGMjKFMn/4Vrq6eSse6royM41y61IOKit9zzz1vKB1HtCAHD64kLW0erq5WnJ1fZPToP1/z+NpD6fxl0xksNvsNV35fj0atQqtW8dcJnaSYFD+SHkohRLNhMFSydu14IiO/o7pXcjUjRkxXOlaNoqK6c+iQmtLSPUpHES2EzWZj3brZ+PmtwmBwp3v3b2jTZvAvnjetTzSDWgfy3IZT7E0uRI0NWw0z4TRqFVabnYFxAbw6qYsMc4trSEEphGgWjhz5lPPn5xAVZSA9fQjTp29psr2SP1dcHIJGU/fhRSFupqKikE8+6Ud8fArJyR2ZMWM/bm7eN3x+lL87Kxb042JeBc8teZ2UqhiKTeHXLNlRUb1p+bC2wczsHy2rucV1SUEphGjSjEY9a9aMIzJyNyqVC15eK5g3b6bSsW6Jk1NnAgO/xWq1oNHI265oGOfOfcvRoxOIjDRQXPxrEhL+W+tr24R4cU/4u5hMwUyflcTlIh0miw1nrZrYAA85AUfclPyECCGarKNHP+Ps2dlERVWRnj6YadO+qrG3pamKjByBRvMt585to3PnsUrHEQ5o8+ZnUKv/gUbjRGjo53TvPumWrq+oKCQ8XEdBQT88XLR0CvdpoKTCUcm2QUKIJsdo1LN06XCKiiajVtuu9ErubZbFJEC3btWrzy9c2KRwEuFojEY9ixb1xsvrH+TkRDB6dMotF5MAR4+uQauFtm1v/VohQHoohRBNzLFj6zl9etaVXslBTJu2pdkWklcFBsaQl+dERcV+paMIB5KefpSdO4cRE1NOVta9zJ+/HrX69vqJ0tK+IjAQBg++t35DihZDCkohRJNgNOpZu3YC4eE70Ghc8PRcxrx5s5WOVW8qKiJwdk5ROoZwELt3v0tp6VN4e4OLy/vMmPFIndozm4+Tm+uPVutcTwlFSyMFpRBCcVd7JSMjq0hLG8D06Vubfa/kz7m59SAoaAMGQ2WzWZ0umh6bzcbKleOIiNhKSYkvo0btJSKic53bDArKp6hoSD2lFC2RzKEUQijGbDawbNlICgsfQKu14eGxlPnzf3C4YhIgJmY0zs5w6tRGpaOIZqqwMI0lSyKIjt5KWtoAZs7MqXMxCXDhwg68ve1ERIyqh5SipZKCUgihiOPHN7B2bQCRkdvJyOjPxIm59O8/R+lYDaZbt/uxWuHSpS1KRxHN0OHDn7BzZzwhIXno9S8wf/4PODm51kvbZ858is0GPXs2r+24RNMiQ95CiEZlNhtYvXoCYWHVZwq7uy9m/vx5SsdqcF5egeTkuGEwHFI6imhm1q2bh7f3UkwmN7p3/5a2be+s1/ZLS/dhMrlw110x9dquaFmkoBRCNJoTJzZy8uSDREbqSUvrx7RpW3F391U6VqMxGGJwc7usdAzRTOh0xaxZ05/4+IskJ7fjwQcPNMjvi7t7Knp9q3pvV7QsMuQthGhw1XMlR5OXdy9arQV394XMn98wH45NmZdXH0JDDZSX5ysdRTRxSUm72bAhkqioixQWLiAh4XyD/L4UFqYRGmrE1/eXZ30LcSukoBRCNKiTJzexZk0gkZHbyMzsy8SJeQwYsEDpWIqIjx+PRgMnTnymdBTRhG3Z8jwXLw7D2dlMYOAnPPDAwga719GjK1GroVOnKQ12D9EySEEphGgQZrOB5cvvJjd3Ik5OZtzcPmb+/MQW1yv5U127TsBggLS0b5SOIpogs9nA4sX9cXd/lZycMO66K5levRq20MvK2kZ5uYp27YY36H2E45M5lEKIenfq1JccOzaNiAgdly/3Ydq0rXh4+CsdS3FOTq7k5XlhNh9XOopoYrKyTrNt2xBiYkrJyBjL/Pmbb/vUm1tht5+moCC4Ue4lHJv8BAkh6o3FYmL58rHk5NyDs7MJV9cPWbDgoBSTP2GxtMbbO1vpGKIJ2bv3fQ4e7IavbzkazbvMmvVVoxR4FouJ0NBinJy6N/i9hOOTHkohRL04fXoLR49OITJSR2pqL6ZN2yaF5HX4+w/Ez+84eXkXCQlpo3QcoSCbzcaqVRMJD/+SsjIfhg/fTVRU90a7/4kTX+DuDjEx4xrtnsJxSQ+lEKJOLBYTK1aMIzt7HM7OJpydP2DBgsNSTN5A+/b3AnDixKfKBhGKKi5OZ/HiKKKivuTy5T7MmJHbqMUkQFLSBiwW6NlzeqPeVzgm6aEUQty26l7JqURGVkqvZC21azecS5dUFBXtAp5XOo5QwLFj60lKmk5YmJnKymdYsOB1RXLodImYzR54eQUqcn/hWKSgFELcMovFxJo19xES8hUuLk44Ob3PggWPKB2rWVCr1eTn+2G3n1E6ilDA+vW/xsPjQywWV+LivqJDh5GKZfH2zqCiou5ngQsBUlAKIW7RmTNfc/jwFKKiKklN7cmUKd9ID8cta4+//wFsNpusrm0h9PpSVq8eSHz8OZKT45k6db+ivzeZmScJDrbg4nKnYhmEY5F3MiFErVTPlbyHzMyxuLoacXL6DwsWHJFi8jaEhAzFz89GevoRpaOIRnDx4j7Wr48gOvoc+fmzmT//guK/N8ePrwKgW7cHFc0hHIcUlEKImzp79htWrQokIuJLMjN7MHZsNkOGPKp0rGarc+f7ATh9Wk7McXRbt77E+fNDcXU14ee3kilTljWJXum8vJ0UFWmIje2jdBThIGTIWwhxQxaLibVrpxAUtBFXVye02vdYsOAxpWM1ezExvTlyRE1p6V6lo4gGUt2jP5xWrfaRlRXMhAkHCApqpXSsH2m1FygpCVc6hnAgUlAKIa7r3LlvOXjwfqKiKkhN7c6UKd8qPkznSEpKglGrzysdQzSAnJxzfP31YGJiiklLG8XcuV+h0TSdj9uqqnLCwiooKFBuQZBwPMr3uwshmhSLxcTKlfeSnj4KN7cqNJp/sWDBMSkm65lW25ng4BKsVovSUUQ9+v77j9i/vzMBASWoVG8yZ843TaqYBDh27FOcnSE+fqLSUYQDkYJSCPGj8+d3sHJlEJGRG8nI6MqYMVncccfjSsdySBERw/HwgAsXdigdRdSD6lNv7qeq6mEqKjzo3v0gd931lNKxrislZTMGA3Tv/oDSUYQDkYJSCIHVamHVqvu4fHkE7u564F0SEk7g7R2sdDSH1a3bVADOn/9C2SCizkpLs1m8OJaIiM9JS+vJtGm5xMT0VjrWDRkMR8jN9cHFxV3pKMKBNK1+eCFEozt/fgcHDtxHbGw5ycldmDJluxSSjSAoqBV5eU5UVOxXOoqog5MnN3HmzGTCw02Ulz/JggVvKR2pRjabjYCAHEpK+ikdRTgYKSiFaKGsVgtr104lIOBzPDy0wDskJPxO6VgtSkVFOE5Ol5SOIW7Thg2P4+r6b+x2F2JittCp091KR7qpS5d+wM/PhqvrCKWjCAcjBaUQLdCFCzvZv/8+YmPLSE7uwuTJ2/DxCVU6Vovj5taDwMAvMBr1MvzYjFRVlbNq1WDi40+RnNyKKVMONJte/dOn1+DnBz16zFA6inAwModSiBbEarWwevUDpKYOx8NDh93+FgkJJ6WYVEh09ChcXODUqY1KRxG1lJKyn3XrwomOPkVu7nTmz09uNsUkQFHRXnJznQkNbad0FOFgpKAUooVIStrNihWBhIevJzOzM6NGZTBs2JNKx2rRunefjNUKly59pXQUUQvffvsap08Pwt3dgLf3UqZNW90kTr25Fa6uyVRWxigdQzggGfIWwsFZrRY+/fRBfH3X4eGhxWZ7k4SEprmdSUvj5RVIbq4rVVWHlY4iamC1WlixYiTR0bspLAxk3LgfCAlpo3SsW1ZWlktYWBWFhf2VjiIckBSUQjiwpKQ9fP/9RFq1KiU5uRMPPLANX185bq0pqaqKwc0tTekY4gZycy+wZcsgYmOLSE+/q0luVF5bR46sQqOB9u3vVzqKcEDNq69eCFErVquFNWumcOnSHXh5VWC1vkFCwmkpJpsgL6/ehIYaqKgoVDqK+Jn9+5ewb18nAgOLsVpfZe7cHc22mATIyPganQ46dx6ndBThgKSgFMLBJCXtYfnyIMLC1pGV1YERI9IZPvz3SscSN9C69Tg0Gjh+fJ3SUcQVNpuNNWumUVk5H73elS5d9jNy5B+VjlVnFstJ8vICm3VRLJouKSiFcBDVvZLTf9Ir+ToJCWelV7KJ69JlIkYjpKdvUzqKAMrL81m8uDVhYZ+QltaVKVNyadWq+W8CbrVaCAkpRK3uqnQU4aDka4oQDuDixX3s2zeBVq1KSE7uwAMPbJdCsplwcXEnN9cTs/mY0lFavNOnt3Dq1H1ERBgpLX2chIR/KR2p3pw5swVPTztubmOUjiIclBSUQjRjNpuNTz+dibf3Gry9NVgsr5GQ8KzSscQtMptb4+V1VukYLdrGjU/i5PQO4ExExEa6dp2gdKR6df78egICoFcv2dBcNAwpKIVoppKTv2fv3nuu9Eq25/77v8XPL1LpWOI2+PsPxN//BPn5lwgObq10nBbFaNSzcuVgWrc+RnJyNJMnJzrkRv/l5fsxmdxk5EI0GJlDKUQzY7PZWLt2BklJg/H2LsdsfpWEhHNSTDZj7dtPBODEiU8VTtKyXL58iLVrQ4mOPkZ29v3Mn5/qkMUkgIdHGgaDfFkRDUd6KIVoRlJS9rN793ji4opJTm7Hffdtw98/WulYoo7atRtOaioUFu4Emv9q4uZgx45/UFn5Bzw91Xh4fMzIkQlKR2oweXkXCQszUVw8ROkowoFJQSlEM2Cz2Vi3bi5eXivw8dFgMv2NhITnlY4l6olGoyU/3w+b7bTSURye1Wph5cq7iYzcTlGRP3ffvY+wsA5Kx2pQx46twtUVOneepnQU4cCkoBSiibu2V7It9933rfRKOiC7vT1+folKx3BoBQWpbNrUn9at80lNHcrs2d+i1TorHavBZWd/i5+fmqFDBysdRTgwmUMpRBNls9n45JPZnD8/EB+fMkyml0lIuCDFpIMKDh6Cv7+NtDQ517shHDy4kt272xIcXIDR+BLz5n3XIopJAJXqLEVFoajV8pEvGo78dAnRBKWmJrJ0aTAhISvIzm7DsGEpjBr1gtKxRAPq3PkBAE6fXq9wEsdS/cVsJqWlszAYnGnffg+jR/9Z6ViNxmjUExZWiotLT6WjCAcnQ95CNCE2m43PPpuPh8cyfH3VGI0vkZDQcj78WrLo6F4cO6ampGSP0lEcRkVFIZ980p/4+EskJ3dkxoz9uLl5Kx2rUZ048TmurhAXd4/SUYSDk4JSiCbi8uVD7Nw5lri4QpKT23Dvvd8SGBijdCzRSNRqNcXFwahU55WO4hDOnfuWo0cnEBlpoLj41yQk/FfpSIpITv6CwEDo108W5IiGJQWlEAqz2WysX78Ad/el+PqqMRheJCHhL0rHEgrQajsRELATm80m893qYPPmZ1Cr/4FG40Ro6Od07z5J6UiK0esPkZPj1eJ6ZkXjk3csIRR0+fIhliwJJShoKTk5rRkyJJkxY6SYbKnCwobh6WnnwoUdSkdploxGPYsW9cbL6x/k5EQwenRKiy4mAXx9s7BY2ikdQ7QAUlAKoYDqfSXnc+ZMX/z9izAY/kJCQjJBQa2UjiYU1L179bDk+fNfKBukGcrIOM6aNWHExBwhM3Mi8+ent/jToy5fPkRgoJWQkLuUjiJaABnyFqKRpaUdZvv2sbRuXUBychwTJ26XQlIAEBzcmt27tVRU/KB0lGZl9+5/Ulr6JN7e4OLyPjNnPqJ0pCbhxIk1+PhA9+4zlI4iWgApKIVoJDabjc8/fxg3t4X4+6vR618gIeFlpWOJJqa8PBwnp0tKx2gWbDYbK1eOIyJiKyUlvowatZeIiM5Kx2oyCgt3YzJpufPOrkpHES2AFJRCNILqXslxtG6dT3JyHBMmbCM4uLXSsUQT5Orag8DAjRiNelxc3JWO02QVFqaxcWN/WrfOJSVlALNm7cTJyVXpWE2Kk1MSZWUte9hfNB6ZQylEA6reV/IhTp3qi79/4ZVeyUtSTIobiokZhasrnDq1WekoTdbhw5+wc2c8ISF56PUvMH/+D1JM/oxOV0x4uA4Pj35KRxEthBSUQjSQ9PSjLFkSRmDgQnJzYxk0KImxY2WIW9SsW7cHsFrh0qWvlI7SJK1bN5+iommYTE60bbtTfqdu4MiR1Wi10KZNy17lLhqPDHkLcYXOaOFykQ6TxYazVk1sgAceLrf+K2Kz2diw4VFcXD7C31+FXv8cCQmvNEBi4Yi8vYPJzXWlquqQ0lGaFJ2umDVrBhAfn0RycjsefPAA7u6+Ssdqsi5f/orAQBg0aKLSUUQLIQWlaNEu5lWwKjGdXRfySS/WY//JYyog2t+dYe2CmdEvmjYhXjdtLyPjONu2jaF16zySk2OZMGG7DG+LW1ZVFY2ra5rSMZqMpKTdHDw4lqioKgoK5pGQsFjpSE2e2XycvDw/mQogGo0UlKJFyijW89yGU+xNLkSjVmG12X/xHDuQVqxnRWIaS/dfZkh8IK9O6kKU/y8XSthsNr744v9wcvqQgAAVOt2zJCS81givRDgiT8/eBAUlUVFRiJdXoNJxFLVly/PY7a/i7KwlIGAto0dPVTpSk2ez2QgMzKO4eLDSUUQLInMoRYuz9lA6I975jh9SigCuW0z+1NXHf0gpYsQ737H2UPo1j2dmnmTJkgj8/T8gLy+aAQPOM26cFJPi9rVuPRaNBk6cWK90FMWYzQYWLx6Au/ur5OSEcdddyfTuLcVkbSQl7cLHx05ExCilo4gWRApK0aL8e9dFnv38FEaL7aaF5M9ZbXaMFhvPfn6Kf++6eGVfyUc5dqw7AQF5VFY+Q0LCZUJC2jRQetFSdO06CZMJ0tK+UTqKIrKyTrNyZRgxMQfIyBjL/PmZBAbGKB2r2Thz5hMAevacpXAS0ZLIkLdoMdYeSufNbUn10tab25I4d+x5JvdcR3JyNOPHbyM0VM7LFfXDxcWd3FxPTKajSkdpdHv3vk9h4eP4+YFG8y6zZv1W6UjNTknJPoxGF+68U4pw0XikoBQtQkaxnr9sOlPjc4y5yZTtW40x8yx2ixmtbwie3cfg3XvCdZ5tZ1vhNHoXtCch4a8NE1q0aCZTHF5e55SO0WhsNhurV08iLGwTZWU+DB++m6io7krHapbc3FLR6+U4V9G4pKAULcJzG05hqWGIuyr1KPmf/RXnkNb4DJyGytkVS2ku1orCG1yhwoYLO8vHMa9hIosWzs9vAAEBJyksTHP44d6SkkzWr+9PfHwWly71YfbsPbI6+TYVF6cTFmaguHiQ0lFECyMFpXB4F/Mq2Jt8o8IQbEY9hV++jVvrPgRN+iMqVe2mFlvtsDe5kOT8CuKDb76lkBC3on37iRQUfMiJE58wfPgzSsdpMMeOrScpaTphYWYqK59hwYLXlY7UrB05sgonJ+jYcbLSUUQLI4tyhMNblZiORq264eO6s7ux6UrxGzoblUqNzWTAbrfVqm2NWsXKA+k3f6IQt6h9+5HodJCZuV3pKA1m/fpfk5f3ABaLhri4bYwfL8VkXWVlfUN5uYr27UcqHUW0MNJDKRzergv5Na7oNlw+jsrFHUtlEfmf/w1LcRYqJ1c8Og/Df/hDqLTON7zWarOzKymfF+nUENFFC6bRaMnP98NqPa10lHqn15eyevVA4uPPkZwcz9Sp+1v8fpv1xWY7RUFBMGq19BeJxiU/ccKhVRotpBfra3yOuTgbbFYK1r+MW6ueBE16Ds+uI6k89jWFX71703ukF+nRGS31lFiI/7Hb2+Hvn6d0jHp18eI+1q+PIDr6HPn5s5k//4IUk/XEYjERGlqMk1N3paOIFkgKSuHQ0op03Gy3SbvZgN1sxKPzXfiPfBj3dgPxH/kwnt3HoD+3B3NxVs3XA5eLdPWWWYirgoKG4O9vIz3dMbYP2rr1Jc6fH4qrqwk/v5VMmbJMetLq0cmTm3B3h5iYcUpHES2Q/CYLh2ay3Hwu5NUhbY8Od1zz5x4d7wTAmHW+Xu4jxK3q3Pl+AE6d+kzhJHVjsZhYsmQIrq4vkp8fxJ13JtGnzwylYzmcpKTPsVigZ8/pSkcRLZAUlMKhOWtv/iOu8Qyo/l8P32v/3MMHAJuhsl7uI8StionpQ2mpmvz8PUpHuW05OedYvjyM6Oh9pKWNYu7cLIKCZI/EhlBZmUhOjrtMIRCKkE9B4dBiAzy48fruas6hrQGwVBRd8+eWimIANO4+NV6vunIfIeqbWq2mqCgIu/3mveRN0ffff8QPP3QhIKAElepN5sz5Bo1G1oI2FG/vdIxGOfpVKEMKSuHQPFy0RPu71/yc9kMAqDy57Zo/rzy5DdQaXKK71Hh9oGs2n6wKZcWKcRw+vAarVRboiPqj0XQiKKgYm635TKuw2WysWnU/VVUPU1npTvfuB7nrrqeUjuXQsrJOExxsITDwjps/WYgGIF8VhcMb1i6YFYlpN9w6yDm0NR5dR6I7+S0FNhuu0Z0xpJ9Cf34f3gMmo/UKuGHbapWd1u5FgIqgoC1UVm7hq69mkJ8fiZfXnfTokUDbtkMb6JWJliA8fBjOzjtJStpF+/bDlY5zU6Wl2Xz2WX/i4zO4dKknM2fuxcWl5i91ou6OH1+Fhwd06/ag0lFECyU9lMLhzegXXeM+lAABo/8Pn8EPYsy+QPH2jzHlXcJv+EP43TGnxutsdhW9vA8xbtwP3HFHGfAuRUWDcHYuITBwBdnZd/Dpp04sXNiBjRufJC/vYj2+MtESdOs2FYBz575QNkgtnDy5ia+/bkV4eAZlZU+wYMERKSYbSW7uDoqKNLRq1U/pKKKFkh5K4fBC3SHAnE+h2h/VDeZvqTRafAc/iO/g2n+716gg2vUiXWI+59ixz8nM7Madd/6HO+/8LQCFhWkkJn5IefmXeHhcwMfnHc6ceYdt29wwm7sQHT2JAQN+hYeHf728TuGYQkLa8N13Wioqvlc6So02bHgcV9d/Y7e7EBOzhU6d7lY6Uoui0VygpCRc6RiiBVPZ7fabbdMnRLO1a9cu5s+fT5ERguf+C4u9/jrlXbRqtj9xB06mDLZufZiAgD24u9tJTY2lZ89/0LPnA9c8//LlQxw+/BGlpTsICEjDz8+GyQRZWX6o1X1o1+5BeveejraGk3lEy7RwYTROTqXMmVOudJRfMBgqWblyIPHxp0hObsWUKQfw9g5WOlaLYjBUsmePFwUFk5gx43Ol44gWSgpK4ZB0Oh1//OMfee+997jjjjtYvHgxB4u0PPv5qXq7x+v3dWFqn+gf///y8nw2b34EF5eNBAZauXQpiNatn2fo0Md/sXmzzWbj1KnNnD69DIPhe8LC8nF3h8pKFbm5YXh4DKV79/m0azdcNn4WrFhxD0FBXzJ8eBVOTq5Kx/lRSsp+9u0bSWiojuLi6UyZslJ+XhWwf/8ijMYEXF2X0r9/zdN0hGgoUlAKh/P9998zd+5csrKy+Pvf/85jjz3244fcv3dd5M1tSXW+x+9HteP/hsVf9zGjUc9XXz1FVdVSIiIMpKd74O//f9x99ys33DLFaNRz8OAyLl36FDhKZGQ5Wi0UFmooLY0jIGA0ffs+TERE5zpnF83Pnj3/xmZ7HG/vdb/o+VbKt9++RlXV85hMaiIjF0kho6CVK+8lMHAjw4bpZM6qUIwUlMJhVFVV8ac//Ym3336bAQMGsGTJEtq2bfuL5609lM5fNp3BYrPfdLHOT2nUKrRqFX+d0OmanskbsdlsbNv2Mrm57xAbW0ZurjNq9XTuuedfuLl513htaWk2Bw58RFbWJtzczhIebgQgK8sVg6ETkZET6N//V/j4hNY6v2i+ysvzOXQohKKi2UyZskzRLFarhRUrRhEdvYvLlwMZN+4HQkJk70MlLVwYiVZbydy5pUpHES2YFJTCISQmJjJ37lxSU1P529/+xhNPPIFGo7nh8zOK9Ty34RR7kwvRqFU1FpZXHx8SH8irk7oQdZN9La/nhx8Wcvbsn4mLy6G0VI1ON4bx4z/Ezy+yVtdnZBzn0KGPKC7+Fj+/VAICrJjNkJXlA/SiTZup9O07u0kNh4r6tXq1K3p9KxISzimWIS/vIl99NZDY2ELS0+9i1izZqFxpNpuNL75worS0L/Pn71c6jmjBpKAUzZrRaOTFF1/kjTfeoFevXixbtowOHTrU+vqLeRWsSkxnV1I+aUU6+Mm5OiogOsCdYW2Dmdk/mvhgrzrnPXPma/bv/x0xMUmYTJCX159Roz4kMrJrrduw2WycO/cNJ08uQafbR1hYDh4eoNNBbm4obm6D6NJlLp06jZX5bA5k4cK2uLpmMnOmXpH779+/hKysh3B2tuHm9gojR/5RkRziWsnJ35OZORi9/gXGjn1Z6TiiBZOCUjRbR44cYc6cOSQlJfHiiy/yzDPPoNXefm/JZ188i079KVExmwgJiiI2wAMPl4bpfUlPP8q33/6asLBDaLWQnt6eQYP+RYcOI2+5LbPZwOHDq0hKWovNdpiIiFKcnaG4WE1xcSx+fiPp0+dXREf3bIBXIhrL2rUPEhS0hv79ixp1qymbzcYnnzxIYOAn5OR4MGTIDtnrsAnZsOFx/Pz+Tfv25wkNbad0HNGCSUEpmh2TycQrr7zCK6+8QteuXVm2bBldutR8PGJtXH1j7tkzr9G2PSksTGPLlofx9v4Wb28bKSkRdO78Sp0WOJSX53PgwMdkZHyBi8sZIiOrAMjJcUGna094+D0MGPBwrYfbRdNw8OBK9PpZODl9yKBBv2qUe5aX5/Ppp/2Ij79McnJXZs78HldXz0a5t6idhQu74ul5nmnTTEpHES2cFJSiWTl58iRz5szh9OnTvPDCCzz33HM4OTnVS9uffZZAYOAiBg1q/K1Z9PpSNm9+DPiUkBAzqam+REQ8zYgRf6zzsHVOzjkSEz+gsPAbfH2TCQy0YrVCZqYXNlsPWreeTN++c6VQaOL+t9fgfcyYsb7B73fmzNecODEJPz8jRuPj3Hvvvxr8nuLWrVjhjtEYQUKCnMIllCWzqUWzYLFYeP3113nppZdo3749iYmJ9OxZv0O4FksVViuKLGxxd/dl6tSVWCyL2bLlj2i1H+Ds/AKrV7+Ch8cCxo//x23nCgvrwL33/hOoHr68eHE3x44twmz+jpCQvdhse9i163Gys4NwcRlIp06z6NZtksy/bGJcXT3JzfXAZDrW4PfauPFJnJzeQaVyJiJiI127Tmjwe4pbV1aWS3h4FYWFA5SOIoQUlKLpO3v2LHPmzOHo0aM8++yz/PnPf8bFxaXe72O1GjCb673ZW6LVOjNhwlvYbP/gu+/exWR6lcjIf/PFFx9gsUxi/Pj38fIKvO321Wo17drdRbt2dwFgsZg4evRT0tNXoVIdJDh4I2VlG9m0SUVhYTQ+PnfRq9dDxMXJB1ZTYDLF4el5vsHaNxr1rFw5mNatj5GcHM3kyYmyNVUTdvToajQaaN/+fqWjCCFD3qLpslqtvP322/zpT3+iVatWLFu2jL59+zbY/VasGIef39eMH29rsHvcjsOHP+H48T/QqlUaOp2K4uJh3H33Bw2y959OV8yBA4tIS/scJ6eTREToUashN9eJysp2hITcTf/+jxAU1Kre7y1ubv36XxEQ8DGdO18mMDCmXttOSzvM7t13ER5eQUHB/Uyb9qn0Ujdxy5aNJDBwO2PGmGX7JqE4KShFk5SUlMTcuXM5cOAATz31FC+//DKurg07FL1s2Qh8fHZx773WBr3P7UpK2sOePY8RFXUKmw2ys7szbNj7Ddp7mJ9/icTED8jL24KX10VCQsxYrZCV5YHF0pXY2Pvp338B7u6+DZZB/M/p01soLByH1foGw4f/vt7a3bHjH1RW/gGLRU1Y2AcMHJhQb22LhrNoUTAqlZ358wuUjiKEFJSiabHZbPzrX//ij3/8I1FRUSxdupSBAwc2yr2XLBmCl9d+HnjA0ij3u105OefYuvVhAgP34eZm5/LlOHr3fpPu3Sc1+L0vXtzHsWMLKS/fRVBQBj4+doxGyMryR6vtR4cOM+jZc6r0ljQQq9XC1q1OFBaOYs6cb+qlvZUrxxIZ+S1paf7cffc+wsJqv4+rUI7VamHLFmeKiu5k7tydSscRQuZQiqbj0qVLzJs3j7179/Kb3/yG1157DXf3xjuX1mYzYrU2/SG+sLAOzJu3h7KyXL788hH8/DZTWnofixYF06bNnxg8+NEGG6ps02YwbdoMBqo/0I4f/5zMzFXY7fsJDv4ane5rvvpqFvn5EXh53UGPHr+ibduhDZKlJdJotOTn+2K1nqpzWwUFqWza1J/WrfNJTR3K7NnfotU610NK0RjOnt2Kl5cdd/cxSkcRApAeStEE2Gw2PvjgA5555hmCg4NZsmQJd9xxR6PnWLiwO+7u53nwQUOj37sujEY9X375O4zG5YSHG0lL8yQw8HHGjPlro/YUGgyVJCYuISVlHWr1MSIjK9FoID9fS3l5PEFBd9Ov38Oy+XIdLV7cDx+fI9x//+33pB88uJK0tHm4ulpxdn6R0aP/XI8JRWP49NO5BAQso2fPDNlTVjQJUlAKRaWlpbFgwQJ27NjBI488whtvvIGnpzL7IS5c2BEXlzRmzdIpcv+6stlsbNv2V3Jz3yE2tpycHGe02ge55573FNljsrg4nQMHPiQ7+0s8PM4TFma6MvfTDaOxM9HRk+jf/6E6rVpviTZv/j1eXm/SuvUxoqK639K1NpuNdevm4ue3grw8d/r3/+bHHmfRvCxc2BY3twxmzKhSOooQgBSUQiF2u51Fixbx5JNP4uvry+LFixkxYoSimRYubIOTUx5z5pQrmqM+fP/9R5w//xdat86luFiNTnc348d/oGhPRlraYQ4f/oiSkh0EBFzGz8+GyQRZWb6o1X1o23Y6ffrMkGHXm0hJ2U96+kD0+ucYO/aVWl9XUVHIJ5/0Jz7+EsnJHZkxYz9ubt4NmFQ0pDVrXNDp2pCQcFrpKEIAUlAKBWRmZvLQQw+xdetWFixYwFtvvYWPj4/SsVi4MBaNpox580qUjlJvTp36ksTEJ4mJuYjJBHl5Axg9+iMiIjormstms3H69JecOrUMg+F7wsLycHeHykoVubmheHgMpVu3ebRvP1K2rvkZm83Gpk1aSkoGMW/e3lpdc+7ctxw9OoGAAAN6/a+5777/NnBK0ZDy8y9x9mw8xcXybymaDlmUIxqN3W5nxYoV/OY3v8HDw4MtW7Zw9913Kx3rJ8zY7Y71K9Gly3i6dBnP5cuH2LHjEcLC9nPmTBe+/roDgwe/R/v2wxXJpVar6dp1wo8nsBiNeg4dWkFh4SdotUcICvqE/PxPOHdOQ0lJHAEBI+nb9xHFC+GmQK1WU1QUhEp1rlbP//LLP6BSvYFG40Ro6OeNshuAaFhHj67E1RU6d56qdBQhfiQ9lKJR5Obm8qtf/YrNmzcze/Zs3n33Xfz8/JSOdY1Fi0IANQsW5CgdpcEUFKSyZcvD+Phsx8vLTmpqJF27vkbfvjOVjnaNsrJc9u//kKysTbi6niUionqhVFaWKwZDRyIiJjBgwMMt9hSXpUvvIiBgN+PGWW7Yg2s2G1i+fAitWx8mOTmC++8/IIs3HMSSJYPx89vPhAlm6cEXTYYUlKJB2e121q5dy2OPPYaTkxMffvghEydOVDrWdS1eHIDN5kFCQrrSURqcTlfM5s2PoVavIzjYQmqqH5GRv2f48D80yQ+ozMyTHDr0IUVF3+Lnl0JAgBWLBTIzvYFexMdPpU+fWbi4NN42U0r65pu/4uLyF8LCdvx4jOZPZWQcZ8eOO4iMLCc3dyIPPvh5k/x3FbdnyRI/rFY3EhKylY4ixI+koBQNJj8/n0cffZT169czbdo03nvvPQIDm+6K3qVLfbBYAklIuKR0lEZjsZj46qtnKS//kKgoPZmZbnh6JjBu3Bs4OTXsyUS3y2azcf78t5w4sQSdbg9hYTl4eIBeDzk5Ibi6DqJLlzl07jzeYYuo3NwLnD/fntLSx7n33n9d89ju3f+ktPRJbDYICvo3Q4Y8olBK0RDMZgM7drhRUDCOWbO+VDqOED+SglI0iPXr1/PII49gt9t5//33mTx5stKRbmr5ck9MpkgSEs4rHaXR2Ww2du16i7S0vxMXV0x+vhar9X4mTHgfDw9/pePVyGw2cPjwGpKS1mCzHSIiohRnZygpUVNUFIuf33B69/4VMTG9lY5ar9atc6K8vBsLFhwGqv8NV64cT0TE16Sn+zJq1F6Zc+qADh1ahU43E632AwYPfljpOEL8SApKUa+Kiop4/PHHWbNmDffddx///e9/CQ4OVjpWraxa5UZVVRsSEk4qHUVRhw6t4sSJP9KqVQaVlSpKS+/i7rs/JDi4tdLRaqWiopADBz4mPX0DLi6niYys3qcvJ8cZna494eHj6d//Yfz9oxVOWjcLF0aj1ZYxd24ZhYVpbNzYn9atc0lJGcCsWTubbA+zqJvVqycTGPgZgweX4O7uq3QcIX4kBaWoN5s2beJXv/oVJpOJf//730yfPh2VSqV0rFpbu9YFna7Ljz0+Ld2FCzvZu/c3REWdubIheU/uuut9WrXqp3S0W5KTc46DBz+ioGArPj7JBAVZsFohM9MTm60HcXGT6ddvniKbv9fFihXjCQr6Cl/fZaSnL8Dd3Ypa/Txjx76sdDTRgBYujMXJqYg5cyqUjiLENaSgFHVWWlrKb3/7W5YvX8748eP56KOPCAsLUzrWLVu3zomKij7Mn/+D0lGalOzsM3zzzcMEBf2Aq6udy5db07fv2z9u+dPcJCXt5tixhVRUfEdISBZeXnYMBsjKCsLFZQAdO86iW7d7G/XYytvx3XfvYbf/BpMJ8vPd6Nt3C23b3ql0LNHAPvtMS1lZd/niK5ocKShFnWzdupWEhAQqKyv55z//yezZs5tVr+RPbdigoazsDubO3al0lCaptDSbL798FDe3LwkIsHLpUght2/6ZIUMeVTrabbNaLRw9+gnnzq3CYkkkIqIYFxcoLVVRWBiNj88wevX6FXFxA5SOeg2drpjVq/vQpk0Kly97M2VKmgx/tgBpaYdJTe1DRcXvueeeN5SOI8Q1pKAUt6W8vJynnnqKhQsXMnr0aBYuXEhkZPPe427zZjUlJaOZPftrpaM0aQZDJV9++QRm8wrCwoykpXkRFPQ4o0e/1OR79W5Gry/lwIFFXL68Hq32JJGROtRqyMtzoqKiLSEhY+nf/xGCglopljEpaTcHD44lKKgKnU5NcXE7EhLOKpZHNJ5Nm57C2/vt2zrHXYiGJgWluGU7duxg/vz5FBcX8/bbb5OQkNBseyV/6uuvVRQX38uMGRuUjtIsWK0WvvnmJQoK/klMTAU5OS44Oc1k/Ph3m918xBvJz79EYuKH5OVtwcsriZAQM1YrZGV5YLF0JTb2fvr3X9BovYNbtvwJm+0V9HoNcXErOX78BVxcspg1S98o9xfKWrSoF97eJ5k82ax0FCF+wTE3aRMNorKykkcffZQRI0bQunVrTp06xUMPPeQQxSSAkxOo1bIytrY0Gi1jx77MnDnlaDTvo9f7Ehi4iK++8mXlyomUljb/TZeDg1tzzz1vkJBwmqlTTURG7qO4eC4mUyABAQdQq59m714/Fi8OYPnysRw6tAqr1VLvOcxmA4sXD8Dd/W/k5oZy113J9O49FQ+P3oSFVaHXl9b7PUXT4+R0gbKy5j0SJByX9FCKWtmzZw/z5s0jNzeXN954g0ceecShNo22Wi3s3etEQcFcJk9eonScZuvEiY0cOvQUsbGXMBhUFBQMZNSoDxxyP0Sr1cKJE19w9uwKjMb9REQU4OoK5eUq8vMj8PK6gx49Euq8UCYr6zTbtg0hOrqU7OyxzJix+cffvcTE5VRVzcHZ+WMGDkyoh1clmiqdrpgffgigsHAq06evVTqOEL8gBaWokV6v57nnnuNf//oXgwcPZsmSJbRu3Tz2I7wVOl0xhw4FUFz8CPfd977ScZq91NREdu58lPDwo6jVkJHRkSFD3rvuMYGOwmCoJDFxCSkp61CrjxEZWYlGAwUFWsrK4gkKGkO/fr8mNLRdrdvcu/d9CgsfR6UCX9+3ufPO3/7innv2eFFYeD8PPvhZfb8k0YTs3fs+Vuv/4em5lt69pyodR4hfkIJS3ND+/fuZM2cOGRkZvPrqq/z2t791qF7JnyosTOP06VjKy59kwoS3lI7jMPLzL/H11w/j67sTT087qalRdOv2Gn36zFA6WoMrLk7nwIEPyc7+Eg+P84SFmQDIzHTDaOxMdPQk+vd/CC+vXx5HarPZWL16EmFhm8jI8GH48N03XIRRfcJTSIs6MrQlWr58LEFBXzNiRJVsWi+aJMesDkSdGAwG/vCHPzB48GACAgI4fvw4TzzxhMMWkwBGY/UmwVqtu8JJHEtwcGvmzNnOiBGF5OdPw9s7B51uJosXB7BjxxvYbDalIzYYf/9oxo59hYSEE0yfbqRVq0MUFT2EwRCGv/8RnJyeY//+IJYs8WPZslHs378Ei8VESUkmixdHExm5icuX+zBjRm6NK3pNpjg8PTMb74UJRZjNx8jN9ZNiUjRZ0kMprnHo0CHmzJnDpUuXePnll3nqqafQaDRKx2pwKSn7SU8fiNn8KiNH/lHpOA7LbDbw1Vd/oLLyYyIjq8jIcMPb+2HGjXsdrdZZ6XiNxmazcfr0l5w6tQyD4XvCwvJwdwe9HlQqUKuhqGgy06atvekXuc8+e4jAwIV07ZrW7I+TFNdns9nYtElLSckg5s3bq3QcIa7LcbucxC0xGo288MILDBgwAHd3d44ePcozzzzTIopJAKOxEgAnJ+mhbEhOTq7ce+8/efDBSiyW17BYXPHxeZfPP/dgzZrp6HTFSkdsFGq1mq5dJzBjxnoWLMhl+HAdqalDcHKqLig1GggPX8eGDc4sXNiWDRv+j6ys09dtq23bewA4fnxdY74E0YguXtyNr6+d8PCRSkcR4oakoBQcP36cPn368MYbb/Diiy+yf/9+OnXqpHSsRnW1oHR29lA4ScugVqsZMeJZ5s0rxs1tGeXloQQHr+XbbwNZtmwkBQWpSkdsNFVV5axY0YdWrfaSlhbPoEEF9OmTg8HwIqWl3XBzy8DP730uXuzCqlVuLFrUi61bX6KsLBeAjh3HoNdDZuZ2hV+JaCinT38KQM+esxROIsSNyZB3C2Y2m3nttdd4+eWX6dSpE8uWLaNbt25Kx1LEwYMr0etn4em5mt69pysdp0U6f34H+/b9hujos1gskJPTi+HD/0tsbB+lozWYixf3ceDAaEJC9JSWzuaBB5Zcd4g7M/Mkhw59SFHRt/j5pRAQYMVigcxMb6AXWu0BDAYfEhJyGv9FiAa3cGEnPDwuMX26QekoQtxQ8z4nTdy206dPM2fOHE6cOMFzzz3HCy+8gLNzy5nD9nMmkw6QHkoltW8/nPbtz5CVdZpvvnmYkJD9XLzYl+3b4+nX7x26dBmvdMR6tXXrS5jNL+HqqsHPbyWjRt145XtkZFciI/8DVM+nu3BhB8ePL8Zi2UNo6G48Pe3YbFUsWhSKq+sgunSZQ+fO4x16IV1L4uaWgk4Xq3QMIWokPZQtjMVi4R//+Acvvvgibdq0YdmyZfTq1UvpWIrbtettVKqnCAvb4dB7JTYnpaXZbN78MB4eW/D3t3HpUijt2r3I4MEPKx2tTiwWEytWjKBVq71cuhTMhAkH6nQ2uMViYtWqCcTEfMPly96Eh5fj7AwlJWqKimLx9b2LPn0eJiamdz2+CtFYSkoyOXYsiqKieUyevFjpOELckHx9bUHOnz/PoEGDeOGFF3jiiSc4cuSIFJNXmM3VZyG7uHgpnERc5esbzqxZmxk7toyCgnm4uxdjsfyapUt9+PrrPzfIEYcNLSfnHMuXhxEdvZe0tFHMnZtVp2ISQKt1ZtCgPwEQHPwbBgwowGJ5jZKS3ri45ODvv5DU1D6sWePCwoXd2LLleYqL0+vj5YhGcOTIStRq6NhxstJRhKiR9FC2AFarlXfffZfnn3+e2NhYli5dSv/+/ZWO1aR89dVzeHi8Rrt2ZwkL66B0HHEdVquFrVv/TGHhe8TEVJKd7YKz8yzGj38HV1dPpePd1Pfff0Ru7qNotTa8vP7BXXc9VW9t22w2Nm/WUlw8mHnz9lzzWG7uBRITP6Sg4Gu8vZMJDrZgtUJmpic2Ww/i4ibTr9+8ZvF32BItXTqMgIDvGDfOIlMYRJMmBaWDu3jxIvPmzeOHH37giSee4G9/+xtubm5Kx2pyNm58Ah+fd+nWLQM/v0il44ga2Gw29u17n4sXX6Z163yKijRUVY3nnns+wMcntEHuqSsqJffIKSxVBrRuroT26oJHgG+t865ZM5mQkM/JyvLizjt3Nsjw86JFwahUdubPL6jxeUlJuzl2bDEVFbsJDs7E29uOwQBZWUG4uAygY8dZdOt2LxqNTLFvChYvDsRu17BgQZ7SUYSokbxjOCibzcZ//vMf/vCHPxAeHs53333HkCFDlI7VZFksVQC4unornETcjFqtZujQxxg69DGOH99AcvLTxMZuZM+eTRQWDmL06A8ID6/7tldpew6R+8a7RB7YTVhRNj89wd4GZAWEk9n/TkKf+R0xQ6+/Er2sLJd16/oSH5/BpUs9mTlzLy4uDbPXqUbTCX//77DZbDX2ZLVteydt294JVPf6Hju2joyMlahUiQQFbaK8fBObN6soLIzGx2cYPXokEB8/qEEyi5pZLCZCQoooLByldBQhbkp6KB1Qamoq8+fPZ/fu3Tz22GP8/e9/x8NDVi/X5JNPZhMSsoKhQ60yrNQMpaTsZ9euR4mIOI5KBRkZnRk69L0fC6dbkX3sLEUz59Hl7EEsKjVa+42Ph7z6+KmOfQlYuYTwHh1/fOzkyU2cOTMZHx8TZvMTTJz49u28tFrbuvUlXF1fJDx81229bgC9vpTExMWkpq5Hqz1BRIQOjQby8pyoqGhDSMhY+vX7NcHBrW/emKizY8fWU1b2APAud975W6XjCFEjKSgdiN1u56OPPuLpp58mICCAxYsXc9ddsmK5Nlavnkxg4GeMGiW/Ds1ZXt5Fvv761/j778LDw05qajTdu/+91nuLHnz+dbq+8We0VkuNheTPWVRqLBotJ5/5K31f+QMbNjyOq+u/KSlxoVu3DXTqdPftvqRay8k5x4ULHSkt/Q333vvPemmzoCCVxMQPyM3dgqfnBUJDzdhskJXljtnclZiY+xgw4CHc3X3r5X7iWmvXziAoaDV9+xbg5RWodBwhaiQFpYPIyMhgwYIFfPvtt/zqV7/izTffxMtLVizX1ooV9xAQ8CVjx8qvgyOoqCjkyy8fRavdQFCQhZSUAGJj/8iddz5xwx7o/QueZMDid7ADqtu459Xr1o/uT8CzB0hObsWUKQfw9g6uwyu5NZ99pqWsrDsLFhxukPZTUvZz5MjHlJXtJDAwHV9fO0YjZGX5o9X2pX37GfTsOaVFncvekBYubI2LSy6zZumUjiLETckcymbObrezZMkSnnjiCby9vfnmm28YNUrm29wqm82IxXI7ZYRoiry8Apk+/VPMZgNffvl7XFwWolY/zapVf8bb+2HGjfv7NUXPwedfZ8Did4DbKyZ/et393xzgk4BxzF+xqdGnT5SWhqHVXmyw9uPiBhAXNwConqd94sQGzpxZgd3+A0FBW9Hrt/L117PJywvH0/MOevRYQJs2d8o0ktvk5ZVBRUXHmz9RiCZAeiibsezsbB566CG2bNnC3Llzeeedd/D19VU6VrO0ZMkd+Pjs4777rEpHEQ3AZrOxfftrZGW9SatWpeTlOWG3T2bChP9QeiEb/749cLGYflFMVgL/ABKBg0AJsASYW8O97IBR60zxwWPXzKlsDCtWjCMwcAsjRxobvZfQYKjk4MGlXLq0DrX6GJGRFWg0UFCgpaysNYGBo+nX79eyLVctZWefISmpc71OYRCiIUlB2QzZ7XZWrVrF448/jqurKx9//DHjxzvWsXSNbfHi/nh6HmHKFLPSUUQDO3BgGadPP09cXBbl5Woinm5Lj5Sk686ZvAy0AqKBOGA3Ny8ooXpO5bkOvelyJrFes9/M7t3vAk/g6/s53btPatR7/1xJSSb7939IdvZmPDzOExZmBCAz0w2jsRNRUfcyYMDDMjfwBq7ujRsTc4BWrfopHUeIm5JxiGYmLy+P++67j1mzZjFu3DjOnDkjxWQ9sNtNWK0apWOIRtC//xwSEjIJC9tG/pGe9Ll0/oYLcMKAHCCN6p7K2tLabXQ5e5C0fQ0zl/FGunefgs0GFy9ubtT7Xo+fXyRjx75MQsJxpk83EBd3hKKihzEYwvDzO4qz8wvs3x/EkiV+LFs2kv37F2E2G5SO3WTk5e2gqEgjxaRoNmQOZTPy6aef8uijj6JWq/n888+ZNEnZHghHUl1QyverlqRDh5GUH1uKRXX0hgWlC3C7W6VbVGpy//4OMV+uuu2Mt8rXN5y8PBd0usbtGa2N6OieREd/AFRPQThzZgunTi3FZvuekJDtGI3b2bYtgZycMDw8BtO16zw6dBjdYudfqtXnKSkJUzqGELUmBWUzUFhYyKOPPsq6deuYPHky//nPfwgKClI6loMxYbNJD2VLE3lg9y1tD3QrtHYbEQe+a5C2a6LTReLicrnR73sr1Go1XbqMp0uX6tEVs9nAwYPLKSj4BK32CIGB6ygoWMf58xpKSlrh7z+Svn1/TWRkV4WTNw6DoZKwsHIKC2XbN9F8SEHZxH3xxRc8/PDDWCwW1q5dy9SpU5WO5KDMUlC2MJWFJYQVZTfoPcKLstAVldb6mMb64OHRk8DAdej1pc1mf0gnJ1cGDfoVgwb9Cqg+YejAgY8oLd2Em9sZ/P3/S3Lyf9mzx4Wqqo5EREygf/9f4esbrnDyhnHs2DpcXCAuboLSUYSotZY5ltAMFBcXM3PmTCZNmsSAAQM4c+aMFJMNyozNJt+vWpK8o6cb/A1QDeQeOdXAd7lWq1bjcHKCEyfWN+p965OPTyijR/+ZBQsOM2NGFW3anKKk5DH0+mh8fU/i6voShw9HsHSpD0uXDmPv3v9iNOqVjl1vUlI2YTRCjx6TlY4iRK3JJ2gT9NVXX/HQQw9RVVXFihUrmDFjBiqV7JHYkFQqC3a7/Do4IpvNRn7+RXJyTlNUdJGyshR0ugzMpypojAME9+x4lSOlwXh6RuPnF0dQUFvCwzs1WO9ht26T2LdvLtnZWxkwYEGD3KOxRUR0ZtKk94Dqf88LF3Zw/PhiLJY9hIZ+h9W6mx07HiUnJxhX10F07jyHLl3uabbzL6uqDpOT442rq6fSUYSoNfkEbULKysp44oknWLJkCXfffTcff/wxERERSsdqEVQqCzabq9IxxC0wmw1kZ58mN/csRUUXqahIpaoqC4slH5WqGCenCjw8DHh7W3Fyqr5Gq4WAAHBxUVHsEdUoOd19TxEYmIVaDUYjZGZW/6fTQWWlE1VVblgsXoAfWm0Qrq5heHlF4+vbiqCgtoSGdryl03bc3LzJzXXHaDzacC9KQWq1mg4dRtKhw0gALBYThw+vIS1tNWr1IYKCNlBSsoGNG9UUFcXg6zuc3r1/RWxsH4WT35iuqJTcI6ewVBnQuLri41JEhbllzBcVjkP2oWwitm3bxoIFCygrK+Pdd99l3rx50ivZiJYu9cVi8SMhIVXpKC1eRUUh2dknyc8/T0nJJSor0zAYsrHZClCrS3Bx0eHpacTLy85PO6CsVigvV6PTuWA0emK3+6LRBOPqGo6nZyz+/vEEBbUnIqIzHh7+6IpKcQv0q/Ww92GgD7Xbh/IqG1BVWIKztyu5uefJy7tAcXEyFRVp6PVZmEx52O3FqNVluLjo8fAw4eVlQ/Oz6bxVVVBRoaWqyhWz2QvwQaMJwtU1FA+PKHx9WxEY2IbQ0A74+kayeHE3PDySmD7dWMukjqOiopDExIWkp2/AyekUERFVqNWQk+OMTteOsLDxDBjwa/z9oxXNmbbnELlvvEvkgd2EFWVf83NoA7L8QsgeOJzQZ35HzNCmWwwLcZUUlAqrqKjg97//PR9++CEjRoxg0aJFREcr+0bXEi1f7oXJFEZCQpLSURySzWajqCiNnJxTFBRcuDLsnI7JlIvdXohGU46bmx4vLxMeHtdeazJBebkGvd4Nk8kLCECrDcbdPRJv71YEBLQhNLQToaHtcXK6tV7mrMAIImq5MOd2CsrMgAgiCzNvKZPFYiI//yL5+UkUFSVTXn4ZnS4LkykXm60IlaoMZ+dKPDyMeHnZfux9vcpoBKNRhZeXnZSUAOz2ANTqQFxcQvHwiMTXtxUBAfGEhHQgMLBVsx0Wrq28vIskJn5Afv7XeHtfJDjYgtUKWVmeWK3dadXqAfr1m4ebm3ej5Mk+dpaimfPocvYgFpW6xl0Grj5+qmNfAlYuafSTl4S4FVJQKmjXrl3Mnz+fgoIC3nzzTR5++GHplVTIypXuGAxxJCScVjpKs2KxmMjJOUtu7hmKii5SXn6ZqqpMzOY8oAhn5wrc3avw9rbi/LOTAHU6qKhwwmBwx2LxQaUKxNk5FA+PaHx84ggMbEtYWOcGLXoSx8+g15a1NX6o/xsoBbKB/wL3AT2uPPY44HOD6ywqNd8O6EvXTz8mIqJz/YX+CZvNRmFhKnl55ygqSqa0NBWdLhO9/gxt2lwgLc0DlQrc3Q3X/Tcwm6GiorpX12TyxG73Qa0OuPLvEIG3d+yV4rM9wcFt0Gia/yyppKQ9HD++iPLyXQQHZ+LtbcdggOzsQJyc+tOx4yy6d7+vQV7rwedfp+sbf0ZrtdzSdlUWlRqLRsvJZ/5K31f+UO+5hKgPUlAqQKfT8eyzz/Lvf/+bO+64g8WLFxMXF6d0rBZtzRpX9PqOLFjgmPPObpVeX0pW1mny889SXJxMZeVlDIZsrNZ8VKpSXFyqe8i8vX85PFtWpqKy0gWj0QObzQ+1OggXlzA8PWPw948nOLg9YWGdb2leYENJ23OImDv61vicWKpPyrme1CuP38iGf4bg2SGPtLQo4uOfYujQxxulR9BiMfHtty4UFNzN7NlbgOris7Q0k9zccxQWXrxSfGZgMORitRagUpXi5FSJm5sBLy8Lrj/r7L06pUCvd77yb+uDSuWPs3PIld7iGPz9WxMc3Pa2eouVYLVaOHZsPefOrcBsPkB4eBGurtU/wwUFUXh7D6Nnz4eIjx9U53vtX/AkAxa/gx1+cWZ8bVy9bv/8Jxiw6O065xGivklB2cj27dvHvHnzyMrK4u9//zuPPfaYww85NQeffupEZWUv5s8/oHSUBnO1oMjOPk1BwXlKSy+h02ViNGZfGXYuw9VVh5eXGU/Pa98WzObqYWedrnoOn93uh1YbgptbBF5e1cPOISEdCAvrhIuLu0Kv8Pac6tSPDucO1+sG51fP8g7dvZZt255Eo/mK0FAzOTku2O3jGTPm7Qafw1c9L9iThIRbG3K/qqwsl9zcsxQUXKS0NIXKygwMhhwslgKgBK22Eje3Kjw9zb+YpmCzQWWlispKZ4xGd6xWb1Qqf5ycgnFzC8fL62rx2Y7Q0A5NZjVzVVU5iYmLSU39DI3mOBEROjQayMtzoqKiDSEhY+nX79cEB9/a/gAHn3+dvq8+W285Dz7/On3/9ky9tSdEfZCCspFUVVXxwgsv8M477zBgwACWLl1KmzZtlI4lrli/Xkt5+SDmzWv8k03qymq1kJd3gZycMxQVJVFWloJen4nZnAsU4+RUjptbFd7ev+x1qqqC8vKrK419UKkCcHIKwd096pph56Cg1g4x3Hk92cfO4t+3By4W0231HP2cHTBqnSk+eOzHOW82m43du98hJeUdWrXKwmyGzMz2dO/+Z3r3nl4Pd/2lRYv64ONzjAcesDRI+z+l0xWTk3OOgoIkSkpSqKxMp6oqG7M5n+risxwXl+ri08vrlx85FRUqKiudMBrdsFi8Ab8fi8/G2m7pegoKUklM/IDc3K/x9LxAaKgJmw2ystwxm7sSE3MfAwY8VGOmW/35egV4AegEXG8CzvV+voRoCqSgbASJiYnMmTOHy5cv88orr/C73/0Ozc/HCYWiNm5UU1o6gjlztikd5UcGQyXZ2afIy6sedi4v/+mwc/GVhRkGfHx+OexcXl7dO2QweGCz+V5ZlBGOh0c0fn5Xh507OexJI7di9+53KVn6MZOWna23NmvqQUpPP8rOnU/j7f0d/v420tM9cHefzt13v46Hh3+9Zdi48Ql8fN6lbdvThId3qrd268pgqCQ39xz5+RcoLr5ERUXaj8Wn3V6MRlOOi4seT08Tnp7XruSHhttuqTZSUxM5cuRjSkt3EBiYjq+vDaMRsrL80Wr70r79DHr2nIJW+7/JqrfSA54JtKN6aDuW6xeU8L8e8C5nmt6Z7aLlkoKyARmNRl588UXeeOMNevXqxbJly+jQoYPSscR1fPWViuLi8cyatbnB71Vamk1Ozpkr2+Iko9OlYzRmY7MVolaX4uqqw9PThLf3tb+aViuUlanR6VyvLKDw/3FbHG/v6m1xQkI6EhbWqdFWrDZ327f/HYvlj2Rn+9P2u+kMXv6fOs9xO7DgSfovfOumzzebDWzb9hJ5eR8TF1dERYWK/PyeDBz42o97LNbFxYv7yMoagsHwF8aMebHO7SnBbDY06nZLtzL9yGazcfLkRs6cWY7B8APh4fm4uVX3tublhePpeQdR3MWg6Qm1bnMaUABYgUJuXFBelbb3EDGDe9e6fSEakhSUDeTIkSPMmTOHpKQkXnrpJX7/+9+j1TrmkKEj2LZNRWHhAzz44Lrbuv6np7EUFl477Gy3F6HVll0Zdjbj5nbttQYDlJdrqapyw2z2BvxxcgrF3T0SH584AgKqe1tCQtpe0/Mh6mbr1pdQq18kIyOI6dOTcHf3rfsq3D+8fFtz286f38H33z9LUNARvL3tpKT4ExS0gDFj/nrbi1tsNhtffqmlqGhIs5zKcauubreUl3ee4uKUGrdb8va28fO3Y6MRKio06PWumM0e2O2+t7TdksFQyaFDy7l06VNUqqNERlbA3zpxx3fnavWztAe4CzhG9e4BNysoLSo1R8ZOo9+Xq27tL0qIBiIFZT0zmUy88sorvPLKK3Tt2pVly5bRpUsXpWOJGthsNvbs0ZCXN4upU5df85jRqCcn58yVbVl+ehpLHipVyXVPY7mqslJ1ZVscD6zW6m1xqoedI/H1bU1QUHvCwzvfcs+IqLuvvnoOZ+fXSE8P5cEHL1zTo6vkPoF6fSlff/0slZWriImppLhYTXn5EIYNe5OYmFvviVq0qHrId8GC/DrlcjQ32m7JaMzFZiu8suJdV6ftllxdfYm+509EleTdNI8V6AkMAD4A7qR2PZS3s8+pEA1FCsp6dOLECebOncvp06d54YUXeO6553D6eZUhmoSfnsZSUHAGf//3uXQpGLvdu86nsQQHdyQ8vGO9zocT9Wfjxifx8HiHy5cjmTXrwg1XpV89ySTiwHeEF2X94iST7IAIsvrfQeizTzTIsOORI59y7NiLREScw9kZUlPDiI39DcOGPV3rBVJLltxBQMBexo+3yJeW23S72y2Zyl0ZMdFQq5OY/gM8D1wEgqh9QXn1JCaPAN/bfHVC1J8WX1DqjBYuF+kwWWw4a9XEBnjg4XJrQ9MWi4W///3v/PWvf6V9+/YsXbqUnj17NlBicSNXex1+Ouz809NYtNoyXF2rrnsaC1TvPVdW5vHjaSxOTtXb4tT1NBbRdGzY8H94e79PamoMc+acr/W/5U/PWta6uRLaq0ujfYiXlGSydevT2O1fEB5uJC/PCZNpNKNGvU1ISM07RWzd+iKuri8RHv4dbdsObZS8Ld3V7ZYubdvD2N+8dNPnFwFtgeeAp6782Z3UrqAEuPTNHlqPGnKbaYWoPy2yoLyYV8GqxHR2XcgnvVjPT/8CVEC0vzvD2gUzo180bUK8amzr7NmzzJkzh2PHjvHss8/ypz/9CRcXlwbN39L88jSWVPT6TCyWfGp3GoszVVVX98K79jSWoKB2aLVu5OePQqd7lnHjXlPkNYqG99lnCfj7LyIlJZ65c880u/moNpuN77//gAsX3iA6unqr9fT0ODp2/CP9+8+/bg9kdvYZkpI6U1b2OyZOfKexI7doFzZ+S7t7R930eY8A24EzwNWfyDupfUF54YtttJtY90VcQtRVi1olklGs57kNp9ibXIhGrcJq+2UtbQfSivWsSExj6f7LDIkP5NVJXYjyv3ZYzGq18tZbb/GnP/2J1q1bs3//fvr06dNIr8Qx6PWlZGaeJD//HCUll2p1GourKz+eZHH1NBaTKRSLJQiTKRxPzxj8/FoTHNye8PCueHkF3jTH5cuHANBq3W7yTNFcffLJTEJCVpGc3J558041yz011Wo1Q4Y8ypAhj5KdfYbt25/Gx2c7JtNDrF79G5yc7mPMmDfx8Qn98Zrw8E788IOGsrJ9CiZvmbRuN+/9vgh8BLxL9dGeVxkAM3AZqF6mV7f7CNEYWkwP5dpD6fxl0xksNvt1C8kb0ahVaNUqXprQiWl9qk+2SEpKYs6cOSQmJvL000/z17/+Fdef7xjdQl3vNJbKynRMphzs9qI6n8YSGtqR0NCO9Xoay4ULO8nJGY7d/hbDhj1Zb+2KpmH16smEh39GcnIX5s8/7lBzCa1WC9u3v0pm5vvExuZhMEBOThf69HmZbt0mArBwYSRabSVz55YqG7aF0RWV4hboV+Mcyt3AsJu081uqC87rkTmUoilpfl/Tb8O/d13kzW1Jt3Wt9UoB+uznpygoN2A9tYU//vGPREVFsW/fPgYOHFjPaZsmq9VCbu55cnLOUFx88bqnsbi7V10zKV2lAj+/6h7Fn57GotfHYDaHYjRG4e3dSvHTWIzGSgCcnK4zsVI0aytXTiQychOXLvVi/vyDDlVMAmg0WkaP/jPwZ5KTv2fPnmcIDNxPScm9LF3qja/vHJycOhIc/C0Wi6nZDfM3Zx4BvmQFhBNRlH3D53QGNlznz18AKoB/AjUd8pgdEEGkFJOiiXD4gnLtofTbLiZ/7q3tFynasoWHH36YV199FXf35nVm8fVc/zSWrCvDziXXPY3F2RmCgq49jcVsDqKiIhCT6drTWMLDu1wzBNcUmUw6AJydpaB0JMuWjSYmZhspKQOYN2+fwxWTPxcfP4j4+O8xGCrZuvV5YBm+vu+h1YKbG+za9SYjRz6ndMwWJbP/nYRsWXvDracCgXuv8+fvXvnf6z12lUWlJqv/HUTWJaAQ9cihh7wzivWMeOc7jJZf/jIb0k6St+b6b66hs97EJaL9Lx+w23HSqNj51LBfzKlsakpLs8nOPkV+/nlKS1OuexqLl5fpF+fq3ug0luph51j8/VsTEtKR8PAuuLp6KvTq6tcPPyzEZHoIX9/P6d59ktJxRB3ZbDaWLx9ObOxuLl++k9mzdzh8MXkjJ09u4uDBZ2nd+hx2O6SmBhMR8QgjRjwnvZWNIG3PIWLu6HvL192JnJQjmh+HLihnLUrkh5Si686ZvFpQevW6B+ewttc85hbXE427z3Xb1KhVDIwLYMWCfg2SuSbXP40lA5Opeti5rqexhIV1IiSkXbNcsFAXu3f/E/gdISHb6uXIO6Ecm83G0qWDiYvbT1raKObM+UbpSE3C2rUuVFW5odWaiIqqorBQg043nJEj325S53w7ols5y7u25Cxv0RQ5bOVwMa+CvcmFN32eS1QnPNoPrnW7VpudvcmFJOdXEB9c85ZCtXX1NJbc3LMUFydRUZF209NYnJwgMLD63NjKyurTWCwWfyorAzGbrw47tyYwsK2cxnITZrMeJydwcXGMHteWymazsWRJX1q3PkJGxnjmzGn4c9mbi8rKSFxccpkxo5LExGWUlr5KVNQ2zpzpzJYt0bRp8zRDhvyfvEc0gICVS7D07YHGYrqtM+J/zg5YNFoCVi6ph9aEqD8OW1CuSky/4dZAP2cz6lE5uaBSa2rVtkatYuWBdF6cUPM3+5+exlJcnExlZdqVYecC1OrS657G4u4OLi7XnsZiMkVgtV7dFud/p7FERHTG3d23VpnFjf2voKyfLwii8dlsNhYv7kF8/Emys+9n1qzPlI7UpLi79yQo6DOMxkoGDJjHgAHzyM+/xLZtT+HpuQW7/TesXft74B7GjHkLf/9opSM7jPAeHdmyYD5jP/ygXtpTAdvmxFN0/NfM6bZbvgSIJsNhC8pdF/JrVUwWbfkndlMVqNS4RHXCb9h8XMJqPn3CarPzzalUhnh8RWnp/4ad/3caix5vbzM/XbPj41M9Mb68XINe74bJ5EVVVRgWSwhGY+SV01jiCQ3tRFhYR5nf1IgsFj0gBWVzZbVaWLKkC/Hx58nLm8GDD65UOlKT06rVWIzGzzhxYgP9+88BIDi4NTNnfoHNZmPXrrfQ6/9Jq1afkZj4GVlZ7ene/c/07j1d4eTN39mz32C++0M+T+/GfV+fwA631VN59br985+gdOg5WkVvZfHiOB588Lh0LIgmwSHnUFYaLXR58RtqemGGzHNUHNqAW1xv1O4+mAvTKT+4AbvZQOjMf+AcWtNmDQB2Phg+GVet4WensfhcOY0l5JrTWMLCuhAQECPfJpugzz9/FH///9KnT5Gcv93MWCwmli7tRFxcMkVF85g8ebHSkZqkqqpy9u3zobBwMtOnf3rD56WnH2Xnzqfx9v4Of38b6ekeuLtP5+67X5ffjduQmprIkSODMJs1DBt2kvT3vqDrG39Ga7Xc0pxKi0qNRaPl5B9epu/fngFg06ancHF5m9xcT0aNOkhYWIeGehlC1IpDFpRnsssY996tnwxhLskmZ9HjuER1ImTqX2/6/PfvcWFIl+61Oo1FNF3r1s0jKGgpQ4aYW9yCpObMbDawbFl7WrVKo6zsEe67732lIzVpK1Z4YDSGkZCQfNPnms0Gtm17iby8j4mLK6KiQkV+fk8GDnxNFq7VUk7OOb77rjtarZXevfcTG1t9ktqyN+6jy8KT9Lx4CYtKXWNhefXxUx37ErByCeE9Ol7z+P79S8jLS8BsVtO+/Qa6dBnfoK9JiJo4ZHeZ6TrbBNWGk184bm36YUg/id1mvenzwyJ7STHpACwWAxYLUkw2I0ajnmXL2tCqVRqVlb+TYrIWjMZYPDwya/VcJydXxo17jfnzCwkN3U5+fi+Cg4+SlzeKxYsD2Lz5GcxmQwMnbr5KSjLZvr0Xrq4WOnX6+sdisqqqHK/4jRx9xk7adwc5MnYamQER/PwTywZkBkRwZOw00vYeosuZxF8UkwADBsyjc+c9mM0a0tPvYceOfzT8ixPiBhzyE9RZe/t1stY7EKwW7GYjqpsc71eX+4imw2YzYDYrnULUVlVVOatWtScmJgeD4VkmTnxN6UjNgo9PPwICzlJamo2vb3itr2vffjjt2x9Cpytm69Zn0WrX4OX1DzZvfovy8iEMG/YmMTGyF+JVOl0xGzd2JiioitDQT67p0d206TGCgmy0afNPYrr0IWboquprikrJPXIKS5UBrZsrob26EBngW6tNy+PjB+Hvn8QXX/QkOvoZPv30NFOmLGugVyfEjTlkRRQb4HHb2zNYSnNRaZ1ROdd8Nrfqyn1E82e1GrBY6mNDD9HQ9PpSVq+OJzo6B6v1L4wbJ8VkbbVpcw9qNRw/fuM5lDXx8PDn/vs/YvbsCjw911Jc3JaQkO9ITu7DwoUR7NjxBlarpZ5TNy9Go561azsQGlqGt/f79Oo15cfHzGYDavUaUlIifzE07RHgS+tRQ2g3cSStRw255bO5/f2jmTUrk8uXOxEcvJzFi/u1+H8L0fgcsqD0cNESfZOTbKz6sl/8mSkvBf3Fg7jG9kClqvmvJjrAHQ8Xh+zgbXFsNqMUlM1ARUUha9e2JjKyAJXqVcaMeVHpSM1K587jqKqCjIxv69xW795TSUg4R//+GeTnT8bdvQiN5g989pk7K1dOJD//Uj0kbl6sVgsrVnQkOjoftfpvDBnyyDWPb9r0O4KCLPTo8VaD3N/JyZX580+SlXUvsbEHWbIkhoqKm+/FLER9cciCEmBYu2A06hsXCQVfvE7+uhcp++ETKo5vpXj7x+Su/D0qJxf87pxbY9satYphbYPrObFQSnVB6bC/Cg6hrCyXzz5rQ3h4Mc7ObzFy5B+VjtTsaLXO5OX5YDSerLc2/fwimT79U6ZN06NWv0dFRTghIZs4diyehQvj2b9/ETZb/Z0Q01RVb6rfg7i4NPT6Jxg16vlrHrdaLZhMS7h0KfiaXsv6plarmTFjAwbDc0RGZvPFFzFkZBxvsPsJ8VMO+yk6o190jftQurftj1VfTvnBLyje9l/05/fi3nYgYXPfwSkwqsa2rTY7M/vLxr+Owm43YrU67K9Cs1dSksmGDe0ICSnF3f09hg17UulIzZbVGo+vb069t6tWqxk69DESEi7TqdNp8vJG4+OThtGYwOrVnnzyyWzKy/Pr/b5NxbJldxAff5qCgllMnPj2Lx7/6qs/EBZmokOHVxolz9ixrxAQsBIPDwMHD/bm2LH1jXJf0bI55LZBV9V0lvftUvIsb9EwFi7sipvbRWbMqFI6iviZwsI0tmzpRECADj+/jxk4MEHpSM3aF1/8Fl/ff9Gu3dkG37fQYjGxfftrZGW9T6tW+VRVQU5OF/r2/Rtdu05o0Hs3ppUrJxIZuYmMjLHMmvXVLx632WysWeOB0ejO/PlFjZrt8uVD7Nt3B/7+VWg0LzF69J8b9f6iZXHobplXJ3VBW8Ow962zo1WreHVSl3psUyjPhNVau2M3RePJz7/E1193xM9PT1DQCikm60HHjpMAOHHi9hbm3Aqt1pkxY/7CggV5REfvIy9vIIGBpykunsjSpb588cVvMBgqGzxHQ1q3bh6RkZtISel/3WIS4JtvXiQiwkBc3J8aOR3ExvbhnntSyMkJQav9C2vWNNxwuxAOXVBG+bvz0k3O2741KsYEfUuEb80rwEVzY8Zmk4KyKcnJOce333bGx6eK8PC19O07U+lIDiE+fijl5Spyc3c18n0HMX/+94wZU05p6W8A8PV9j61bvVm8eCAXL976QRRK27z59/j7LyU5uQNz535/3efYbDYKCt4mLc2LoUN/08gJq/n4hDJnTjqXL/cgLGwdixb1wGIxKZJFODaHLigBpvWJ5ulRbeulrbsC9zCp6zssXtxVfiEdihm7XQrKpiIz8yS7dvXAw8NEdPT6Bl3E0NKo1WoKCwOwWs8qcn9XV0/uvfefzJ1bir//RgoLuxASsp+MjCEsWhTC1q0vNov31u3b/46Ly5ukpkYxd+7xGx6pu2vXW0RH6wgLe0bRY3e1WmcWLDhKTs40YmOPs2xZFGVluYrlEY7J4QtKgMeGteHv93XBRauuceX39WjUKly0al6/rwuLn3qd/Pw5tGp1hmXLZEsGR6FSmbHZZAuopiAt7TD79vXBzc1MfPxmunefpHQkh6NSdSAwsFDx1dddu04gIeEEQ4bkUVg4G2fnClxdX2LDBg+WLRtNdvYZRfPdyA8/LMRs/iMZGUHMnHkWrdb5hs9NT3+VjAx3Rox4rhET3tj06WuwWl8mLCyfzZvjuHz5kNKRhANpEQUlVPdUbn/iDgbGBQDctLC8+vjAuAC2P3EHU/tUr+qeMmUpFstLhIfnsmFDLDk55xo2uGhwKpUFu10KSqWlpOwnMXEATk5WOnTYRufOY5WO5JBCQ+/Ex8dOSsp+paMA4O0dzJQpy5gxoxIXl8WUlcUSGrqNM2c6s3BhDN99957ixe9Vx46tp6joV+TleTNlyllcXT1v+Ny9e/9Lq1al+Pk9pmjv5M+NGvUCYWGf4epq4ujR/hw6tErpSMJBOPQq7xu5mFfBqsR0diXlk16k56d/ASqqNy0f1jaYmf2jiQ/2um4bBw+uJDt7Dkajhm7dvqZ9++GNkl3UvyVL/LBavUlISFM6SouVlLSHEyeqf4e6d99FmzaDFU7kuLKyTnPxYhfKyp647hY3TUF+/iW2bXsKrXYLoaFmsrNdgHsYM+Yt/P2V2bLtwoWdnD07Ep3OhTFjzhEYGFPj8xctCsbNrZypUyvRaJreF9bMzJPs3DmQ4GAdVusfGTfuVaUjiWauRRaUP6UzWrhcpMNkseGsVRMb4FHrE3CSkvZw9OhI3N3NBAV9zIABCxo4rWgIy5Z5YzaHkJBwUekoLdL58zs4c2Y0VquKPn320aqVbMnV0Nav11Ja2pMFCw4qHaVGNpuNXbveIjX1n7RqlYXJBFlZ7ene/UV6957aaDnS04+SmNgPq1XF0KHHCA+vebHnwYMr0etnUVLyGJMmvddIKW9dRUUhn3zSnbi4LLKzJ/Lgg583qd5U0by0+IKyrvLyLrJ1ay9CQiqw2Z5j7NjG2bhW1J8VKzwwGmNISFBmoUJLdvr0Fi5evAejUcvAgfuJju6pdKQWYeHCCDQaPfPmlSgdpdbS0g6za9fv8fbeg7+/jfR0Tzw8pnP33W/g7u7bYPfNy7vIzp1dcHa20KPHXuLiBtz0moULw/HyKuT++ytrnGPZFFitFpYtG0Jc3AGSkzsyZ84RnJxkJxNx6+SrSB2FhLRh8uR0MjMjcHF5lTVrpikdSdwijcYKNO03fUd0/PgGkpPHU1XlxJAhR6SYbETOzl0JCSltFiuqr4qJ6c3cubu45x4dlZXPYLE4ExDwMTt2+LNoUW/On99R7/csLc3mm2+qdxxo125TrYrJ48c3EB+fg1o9o8kXkwAajZb58/eTnz+H2NizrFgRSXFxutKxRDMkBWU9cHf3Zd68y1f2+fqExYv7Y7ValI4lakmjsaFSNf03fkdy+PAnpKffj07nwrBhx4iI6Kx0pBYlMnIE7u5w9uxWpaPcMicnV8aPf53584sICdlGfn5PgoOPkps7gsWLA/jyyz9gNhvqfB+9vpQNGzoTGKgjNHR5rReJHT78BIWFGu65p+kOdV/PlClLUavfJDi4mK1b2zbLvUGFsqSgrCcajZYFC46SmTmR2NhEliyJp6qqXOlYohY0GhtqtYvSMVqMxMTl5ORMp6zMjZEjTzf4EYDil7p3nwxAUtJmhZPUTYcOI1mw4DB33VVIUdFDaLUmPD3fYPNmD5YuHUZ6+tHbatdsNrB6dUfCw0twd3+31hvrnzv3La1apWE2P1DjCvCm6q67niI29ku0Witnzgxl//5FSkcSzYgUlPVs5swvqKh4gujoNNaujaGwUFYON3VarV0Kykby/fcfUVg4h5ISD+6++yzBwa2VjtQi+ftHk5PjTGlpotJR6oWHhz/33/8Rs2dX4Om5luLitoSE7ObixV4sXBjBjh1v1HrUqHpOYRdiY3Ow2f7EnXf+ttY5vv/+/ygvVzNx4ge3+1IU17nzWIYMOUlZmSfl5Qls3Pik0pFEMyEFZQOYOPFtXF3fIzCwjG3b2pGa6hhv2o5KCsrGsWfPvykre5iCAm8mTLhw021XRMPS6SJxdk5ROka96917KgkJ5+jXL438/Mm4uxeh0fyBzz5zZ+XKieTnX7rhtTabjaVL+xIXl0xFxaPcffdfa33flJT9xMZepLJybIMuEmoMYWEdmDw5nYyMGHx83mHZstFNZi9Q0XRJQdlAhg59jNjYTTg7Wzh2bCBHj36mdCRxA9UFpaxqbEg7d76FXv84eXm+3HffRXx9w5WO1OK5u/cgNFSHwVCpdJQG4e8fzfTpnzJtmh61+j0qKsIJCdnEsWPxLFwYz/79i35RJC1fPpLWrY+RlzeVSZP+c0v327nzYfR6FRMmfFyfL0Mx7u6+zJ+fQmrqUGJitrF4cXuH/VkR9UMKygbUpct4+vc/ik7nQk7OZHbs+IfSkcR1ODmBRiMFZUPZtu0VzOanyc4O4IEHLuLtHax0JAHExo7B2RlOnPhc6SgNSq1WM3ToYyQkXKZTp9Pk5Y3GxycNozGB1as9+eST2ZSX57N69QPExu4kLW0E06evvaV7ZGQcJzr6FCUlw/HxCW2gV9L41Go18+Z9R3Hxr4mOvsiaNVE19vCKlk0KygYWGdmVe+5JJi8vELv9Gdav/7XSkcRPmM0GNBrQat2UjuKQvv76z8ALZGYGM21aMl5egUpHEld07/4AFgukpGxROkqjCQ/vxOzZW5k0SYfB8CJGoxdBQSv44YcQwsPXc/Fia2bN+uaW2922LQGzGcaNW9gAqZV3333/xdX1PQICyti5s0ODbNEkmj8pKBuBr284M2akcflyWwICPpT5KE3I1ZX4Go0UlPXtyy//gFb7MunpYcyYcanZzytzNO7uvuTkuKHTHVE6SqPTap0ZM+YvLFiQR0HBbJydwWiENm0usXy5P1988dtaD+/m5l4gPPwI+fmDHHpe8NChj9G27bcAJCWNZO/e9xVOJJoaKSgbiYuLO/Pnn+Py5WFX5qN0rpe90kTdGAwVgPRQ1reNG5/Aze0N0tKimDUruVluodISGI2xuLtnKB1DMbt2vY2f33JSUiIYNKiI0tLfAODr+y+2bvVh8eJBJCd/X2MbX3+dgEoFd9/t+FvstG8/nLvuOkdRkQ9VVf/H558/qnQk0YRIQdmI1Go1c+fupKBgHq1anWP58hjKy/OVjtWiGY3VBaWTk7vCSRzH558/gqfnu6SmtmLOnCRcXOTvtqny8elHaKiR0tJspaM0usTE5VRVPUVmpj8zZpzF09Ofe+/9J3PnluLvv5HCws6EhPxAWtpgFi0KYevWl35xslBhYRrBwfvIyupFaGg7hV5J4woObs306Rmkp7fG3/+/LF16p4y4CUAKSkVMnrwYq/VvhIXl88UXcWRnn1E6Uot1dVhLCsr6sW7dPHx9PyA1tQ1z556XM4GbuPj48ajVcPz4OqWjNKqTJzeRlzeXwkJP7r//DG5u3tc83rXrBBISTjBkSB6FhbNwcanA1fVFNmzwYPnyMT++Z3/1VQJOTjBqlGPOnbwRV1dP5s9PIi1tJLGx37F4cRx6fanSsYTCpKBUyKhRzxMcvBovryr27evO2bO3PhFc1J3JJD2U9WXt2hkEBS0lJaUD8+adbRbnGLd0nTuPw2CAjIxvlY7SaC5e3Edy8iQqK50ZM+Z4jauyvb2DmTp1OQ8+WImLy0LKymIICfmGM2c68/HHkQQGbic9vRNRUd0b7wU0EWq1mjlztlFW9juiotJYty6anJxzSscSCpKCUkG9e0+nS5c9WK1qkpPv5vvvP1I6UotjNOoAcHLyUDhJ87Z69QOEhq4mObkr8+efRqPRKh1J1IKTkyu5ud4YjSeVjtIoMjNPcvToXVgsaoYMOVDrk5rUajUDBiwgISGZHj2SycubQHBwNh4e4OmZxJo1UygpyWzg9E3TxInv4OX1MT4+lezd25XTp1vOrgHiWlJQKiw+fhDDh5+luNiLysqH+eqrPyodqUUxmaoLSmdnKShv14oV4wkPX8+lS72ZP/8YarW8rTQnVmsbfHxylI7R4AoL0/juu344O1vp3n3HbfcqBge35r77lmGzqUhJCaSyMojg4HUcOBDFwoUdOHz4k/oN3gwMHJhAp057sFo1XL48np0731I6klCAvPM3AcHBrZkyJY2MjCjc3P7O6tWTlY7UYlwd8nZxkVXIt2PZspFERX1Fauog5s1LlGKyGQoIGEhQkMWhhyvLy/P56qsueHsbiYv7nLZth9apvY0bf423t40BA1aTkJBFfPwh8vLuxN8/icrKaSxf7sX69b9qUfMK27QZzOjRSeTn+2GzPc26dfOVjiQambz7NxHu7r7Mm5dCamovwsM/Y9GivlitFqVjOTyzWQ+As7MUlLfCZrOxZMkdxMRs5/LlYcybt0+KyWaqQ4d7ATh50jEX5hgMlXz2WUeCgysIDPyYbt0m1qk9o1GPk9NnpKbG0KHDSABiYnozd+4u7rlHR2XlM1gszgQEfMyOHf4sWtS7xWwE7u8fzYwZGVy+3IGgoCUsXjxAPsdaEPkEaEI0Gi0LFhwmK2sSrVodYsmS1j9uvC0axtWCUvZJrD2bzcbSpYNo1WoP6emjmTt3p9KRRB20aXMnFRUqcnJ2Kx2l3lksJlau7EBkZBHOzm8wYMCCOre5adNjBAZa6d37nV885uTkyvjxrzN/fhEhIdvIz+9JcPBRcnNHsHhxAF9++QeH33+4es/l02RmTiA29gBLlsSi0xUrHUs0Aikom6AZMz5Hp3uaqKh0PvkkmoKCVKUjOayrBaWLi5fCSZqH6p7JPsTFHSAzcyKzZ29VOpKoI7VaTUGBP1arY21fVv3FpyutWmViNj/L8OG/r3ObFosJm20lyclhdO8+qcbndugwkgULDnPXXYUUFT2EVmvC0/MNNm/2YOnSYaSnH61znqZKrVYzc+ZGqqqeJTIyi/Xro8nKOq10LNHApKBsou655x+4u79PQEA527d3ICVlv9KRHJLFUgWAq6sUlDdjtVpYvLg7rVsfJSdnMjNnfqF0JFFPVKoOBAQUONQG1UuXDiA+/gIlJQmMG/davbT55ZdPExJipmvXN2p9jYeHP/ff/xGzZ1fg6bma4uK2hITs5uLFXixcGMmOHf9wqL/3nxo37jX8/Vfg5VXF/v3dOX58g9KRRAOSgrIJGzLkEeLivkKrtXLixOAWuXqwoVmt1QWlnDNdM6vVwpIlnYmLO0Ve3iymT/9U6UiiHoWEDMXX187ly4lKR6kXy5ePIS7uIFlZk3jggY/rpU2r1YJe/xEpKYH07Tvzttro3Xs6CQnn6Ncvjfz8yXh4FKLRPMOnn7qycuW9Djka1bfvTHr0OIDR6ERW1n1s2/aK0pFEA5GCsonr1OluBgw4QmWlK/n509i+/e9KR3IoFksVVityoksNLBYTS5a0Jy7uAsXFC5g6dbnSkUQ969KlemeJ06c/UzhJ3a1dO4Po6G9ITR3KjBmf11u7W7f+ifBwI23a/LXObfn7RzN9+qdMnapHpfoXlZVhhIRs5OjROBYubMP+/UscqtcyNrYP48ZdIjc3GI3mBdasma50JNEApKBsBiIjuzJhwiVycoKAP/LZZw8pHclhWK0GzGalUzRdZrOBpUvb0qrVJcrKHuWBB1rWEXMtRVRUd4qKNBQW7lM6Sp188cVvCA6u3mB/zpxd9dauzWajuPhfXL7sw5Ahj9Rbu2q1mjvueJyEhDQ6djxFbu4ofH1TMRrns2qVJ59+Oofy8vx6u5+SfH3DmTMng9TUboSFrWXRol6/OBtdNG9SUDYTPj6hzJ6dzuXL7QkMXMiyZSMc6husUmw2AxaLSukYTZLRqGfZsnhiY9PQ6Z5k0qT/KB1JNKCSkmBUqiSlY9y2rVtfwtPzPVJS4pg370i9bmO1fftrREXpiYp6rt7a/LmIiM7MmfMN996rx2D4CyaTF4GBy9m7N4SFC7tx6tSXDXbvxqLVOpOQcJzs7AeIjT3KsmUxlJXlKh1L1BMpKJsRJydX5s8/Q1racGJidrB4cUeH34KiodlsRikor6OqqpyVK1sTE5OF0fhHJkyQky8cnbNzV0JCSpvlvoF79vwbeJG0tFBmzTpVr0d/2mw2cnJeJz3dg2HDnq63dm9Eq3VmzJgXWbAgj6ioveTlDSAw8BRFRfewdKkvX3zxWwyGygbP0ZAefHAdZvOLhIXlsnlzHGlph5WOJOqBFJTNjFqtZs6c7RQWJhAbe4Hly6PlG14dSEH5SzpdMatXxxMVlYvV+iLjxr2qdCTRCCIihuPuDmfPNq+toA4fXkNFxePk5Pgyffo5XFzc67X9PXveIyamgqCgJxt98/42bQYzf/4PjBlTTmnp4wD4+v6LrVt9WLx4EMnJ3zdqnvo0ZsxfCA1dh5ubiSNH+nH48BqlI4k6koKymapeufgaYWEFbNrUWvb4uk02mxGrVX4NrqqoKOSTT9oQEVGAWv0aY8b8RelIopF06zYFgKSkTQonqb2zZ78hK2sGxcXuTJp0pkF2a0hJ+StZWa6MHv1ivbddW66untx777+YO7cUP78vKCzsREjID6SlDWbRohC2bn2pWc5H7NnzAfr2PYxO50pBwYNs2fInpSOJOpBP0mZsxIhnCQ5ei6engR9+6MGZM18rHanZsdtNUlBeUVaWy2eftSEsrBhX13cYMeJZpSOJRhQYGENurhMlJQeUjlIrqamJnD07Dr3eiZEjj+LrG17v99i/fxFxccV4ej7SZI4W7dZtIgkJJxk8OIfCwlm4uFTg6voiGzZ4sHz5GLKzm9cG9VFR3Zk4MZWsrDBcXf/GqlWTZH1AM9U0fkPEbevdeyrduu3DYtGQkjKOvXv/q3SkZsaE1apROoTiSkoy+eKLtoSElOLp+T533vk7pSMJBVRWRuLsnKJ0jJvKyTlHYuJQAAYM2EdoaLsGuc/Zs8+Tk+PMuHFNb7s2H59Qpk5dzoMPVuLispCyshhCQr7h9OnOLFwYy9697zebwszbO5h589JJTe1DRMQXLF7cTdYHNENSUDqAuLgBjBhxjqIib6qqHmXz5rofMdZymLHZWnZBWVCQyubN7QkMrMDPb2G9bosimhc3tx6Ehuqa9KKP4uJ0tm/vhaurhc6dvyE2tk+D3Ofw4U9o3ToPZ+d5aLXODXKP+qBWqxkwYAEJCcn06JFMfv4EvLyysVr/j7Vr3VmzZholJZlKx7wpjUbLggUHycubRatWp1mxIqpZ5Bb/IwWlgwgKasXUqemkp0fj4fEmq1bdp3SkZqJlF5R5eRfZurUTfn56goJWMGDAAqUjCQXFxo7G2RlOnvxC6SjXpdMVs2lTV/z8DERFraF9++ENdq/jx5+moEDLhAnvNtg96ltwcGtmztzIAw/osVheQ6/3Jzj4Ew4ciGLhwo4cOdL0T7iqPjjhdUJCCvn66/hmvfCopZGC0oG4uXkzb94lLl/uS0TEBhYt6t0stwBpXGbs9vrbYqQ5yc4+w/btXfHxMRAevva2j5MTjqN79wewWCAlZYvSUX7BaNSzdm0HQkPL8PX9L716TWmwe50+vYW4uExstqnN8hQtjUbLiBHPkpCQTXz8IfLy7sDf/wIVFVNZtsyL9et/jV5fqnTMGxo+/Bmiojbi5GTl9OmhHDiwTOlIohakoHQwGo2W+fMTyc5+gFatjrBkSVyTfuNQmkplaZEFZUbGcb77rhceHiZiYjY06IezaD48PPzJzXWjsrJp7QtotVpYsaIj0dH5qNV/Y/Dghxv0fgcOPE5pqZoJE95v0Ps0hpiY3sydu5tx4yqoqPg9VqszAQEfsn27P4sW9eHChZ1KR7yurl0nMGjQccrK3CktnStTuZoBKSgd1IMPrkOvf4aoqAw+/TSG/PxLSkdqkqoLSielYzSqtLTDfP99X1xczPx/e/cdX2V993/8dUY22SE7IQkBBERAkCGIqIiAgqBWRNmku3bdre1tf1ZrW9va5d3etx2yRVEcSBREBNnKqIBMWZmQnRCyxxm/P5IgIwRCzsnJSd7Px6MP0us61/f7SR9NePO9rs/17dXrAwYOfNDVJUkHUlPTA1/fLFeXcYHNZmPJksEkJWVSVfUjxo//hVPnO3FiC4mJaVRXT8XHJ8Cpc7UnLy9fJk9+kfnzi4mI2EBh4a2Eh39Obu49LF4cxtq1/93hGmGio/vzta9lc+ZMPP7+f2L58klu02jUFSlQdmIPPPAHunX7FyEh5Wza1I+TJ917n15nMBotQNcJlKdO7WT37pF4eNjo128D/ftPdHVJ0sEEBAwjIqK2w2yYsGzZnSQnH6awcBYPPvgXp8+3bdt3qKgwMGXKv5w+l6v07XsvCxb8h7vvLqKoKAWzuQY/v9+TmtqNpUvvJitrn6tLvMDXN4h5806Tnn4H8fEfsnhxX2prq1xdljRDgbKTGzXqGyQnf4jJZOPw4Tu1G8FljEYrXSVQnjixhQMH7sRggFtu2eLUhgZxX8nJkzGZ4MCBt1xdCitWPEhi4g6ysyc1Nms4V0bGXuLjj3H+/H34+4c5fT5X8/ML4ZFHXmH27Aq6dXudc+d6ERm5mRMnhrBwYSybNv2xQ6wImkxm5s3bRnHx1+nR4wSvvx5LYWG6q8uSyyhQdgH9+t3H6NEHKC/3oaDgcTZs+K2rS+owTCYr0HFfCeIox459zKFD47BajQwduoNevUa7uiTpoAYMeICaGsjK2uDSOt56ax6xsamkpY1g1qy17TLnpk3foLbWwOTJr7TLfB3J0KEzSEk5xrBhmRQUPIKfXxEm01OsWuXNihVTO0SAe/jhf+Pp+TfCwkrZuPEmTpzY4uqS5CIKlF1EdHR/pk5NIzc3HJPp//HWW/NcXVKHYDLZMBg6d6A8dOgDvvxyAnV1Jm6/fQ+JicNdXZJ0YB4e3uTn+1Nb+4XLanj//Z8SErKUU6f6MXdu+7w2JifnCDExByguHkNwcGy7zNkRhYTE8/jjbzF9ehUGw9+oqIgiImIN+/YlsXBhL5d3XN9555MkJ3+E0Wjnyy/vZseOzvtogrtRoOxCAgLCmT07k/T0vnTvvpSlS+/qELczXKmzB8r9+98hLW0K1dUejBnzOXFxg1xdkrgBi6UXAQG5Lpl748bf4+X1J9LT45k7d3+7bXm4fn0KNhtMmrSoXebr6IxGI3fe+SQpKZn063eIvLzxBAWlU1Mzl1df9WPVqrmUlRW4pLa+fe9l7NgjlJQEUFX1LVavftIldcilFCi7GA8Pb+bPP0xm5ngSErawePFNXfoBZ7PZhtHo5eoynOI//1lJdvbXKC/35u67vyAm5mZXlyRuIiTkdsLDLeTlHW/XeXfu/DcWy3+Tnd2dmTOPtNsONQUFp4mM3EVe3nDCw3u2y5zuJCbmZubM+YipU6uoqXmWurpuhIUtY/v2CBYuHMShQx+0e00REb0aN/NIIjj4f1m69J4uv0DiagqUXZDRaGTOnI8oKfkWPXqc5LXX4iktzXF1WS5hNts7ZaDctWsZeXlPcP68D+PHH3LaXsfSOfXtOxWAgwfbrzFn//53OHfuW+TlBfDoo0fx9u7WbnOvW5eC0QgTJmh1siVmsycTJjzHggX5xMVtJz9/JGFhBykunsySJcGsWfOjdt2208cngPnzT5KZOY6EhE9YvLgX1dVl7Ta/XEqBsgt76KF/YDS+SEREMR98kEx29gFXl9TuGgKl++2E0ZIdO/5FcfFciov9uP/+Y1pxkVbr3fsuyssN5ORsbpf5jh//hIyMRykt9eaBBw62a4d1aWkOoaFbOXNmINHR/dttXnfXq9do5s//lAkTyigtfRKDwU5g4EusXx/IkiWjSUv7rF3qaFgg+ZjS0ieJj0/jzTfj2n1lXRooUHZx99zzU6Ki3sLXt5bdu4e65NaFK3l4gMnk4+oyHGbr1r9TXv4tCgsDePDB44SExLu6JHFDRqORwsIQrNbDTp8rK2sfBw/eR22tibvv3ktYWA+nz3mx1NQUvL3tjBvX9Tq7HcHbuxtTp/6NuXNLCQp6l6Ki/kRE7CQ9/XYWLYrko4+eb5ctgKdO/Rt+fv8iOLicbdtu5siRD50+p1xKgVK49dZHuPXWXdTVmcnImMK2bf/r6pLahdVqwWwGs7lzrFBu2vRHqqu/T15eMA89dJKgoGhXlyRuzGC4idDQIqc+l5aff5KdO2/HaLQzbNjWdl8hLC8vIiBgPZmZN5GQcFu7zt0ZDRo0jZSUg4walUtR0RN4eZXh5fUs777rw/LlE8nNPebU+UeN+gZ9+36C1WokLe1+tmx5yanzyaUUKAWAhITbGD/+OEVFgdTUPMmaNT92dUlOV1PT8KxNZ1ih3LDhN1gsT5GTE8qjj54iICDc1SWJmwsPH0NQkI3MzL1OGb+0NIePPhqMn18dffqkkpQ00inztCQ19Zv4+9sZM+Yf7T53ZxYYGMn06St4/PEKPD1f4fz5eCIj13PoUD8WLkxg+/aXnfYPld69x3LvvScoKgqivv5HvP12ilPmkSspUMoFYWE9eOyxTLKyEvD3/ysrVkx1dUlOVV1dDoDZ7N6Bct26Z4BnOHMmnMceO4WfX4irS5JO4JZbHgXg8OF3HD52VVUpq1ffTFhYJZGRy7n55kkOn+NaqqvL8PF5j/T0JHr3Htvu83cFRqOR229PISXlNAMHniA//wH8/XOwWr/LypV+rFz5GOfOnXH4vGFhPXj88TNkZvYhLGwRixePapfb7l2dAqVcwscngHnzTpKRMYLY2DUsWjQYi6XO1WU5RW1tU6D0dXElN+7995/C0/M3ZGVF88QTp/H1DXJ1SdJJxMUNoqTESGHhNoeOW19fw+uv9yM6+hy+vi8xbNhMh45/vVJTv0dQkI3hw//HJfN3NRERvZg1630eeaQKi+V3VFcHEx7+Jp99FsfChf34/PNVDp3Py8uX+fOPkp09iYSET1myJInKyhKHziGXUqCUK5hMZubP/4zc3OkkJBxg6dLO+YPYFCg9PNwzUL733vfx9f0jGRlxzJp1sl1fsyJdQ0lJBAbDCYeNZ7VaWLZsAAkJudhszzB27A8cNnZr1NfXYDSuJC0tlgEDHnBJDV2VyWRm3Lifk5KSQ3LyXgoK7iQk5Djl5dNZtiyAd9/9NlVVpQ6Zy2g0MmvWWiorf0psbDbvvBPP2bPObzTrqhQo5apmzHiD2tqniY09y9tvJ5Cff9LVJTlUbW3D+9LcMVC+88438Pf/O+npScyZcwIvL/f7HqTj8/C4mfDwcw65XWiz2Vi6dBhJSacoL/8OEyc+74AKb0xq6g/p3t3C4MF/dlkNAj16DGXu3C3cf3855eU/xWr1ICTkn2zcGMKiRcM4fvwTh8wzefKLBAUtxd+/mk8/HcwXX6xxyLhyKQVKadGkSb8lMHAhwcEVbN58MydOOPb2lys1BUpPTz8XV9I6q1bNJTj4FdLTezF37jE8PDpHl7p0PLGx4/Dzg2PHNrR5rOXLx9Gz537y8x9j2rT/c0B1N8ZqtVBXt4TTp8MZMuRRl9UhX/Hy8mXy5BeZP7+Y8PD1FBbeSnj4f8jNvYfFi8NYu/Zp6utr2jTHiBFzGDhwB3V1Zs6cmcrGjb93UPXSRIFSrmnkyAX07v0xRqONo0fvYvfu5a4uySHq6ioB9wqUK1fOIDx8GWlp/Zk372i7bU0nXdPAgdMBOH48tU3jvP76IyQkbCYzcxwzZqx0RGk3bO3anxEVVUffvr91aR3SvH797mPBgv9w991FFBWlYDbX4Of3O1JTu7F06T1t2oAjKWkkkyadJC+vOwbDf/Pmm655frezUqCU63LTTfdwxx0HKSvzoaRkDuvX/8rVJbWZuwXK1157iKioNzh9ehDz5x/EZDK7uiTp5MLCepCf78G5cze+68k773yL6Oh3OH16CLNmfeTA6lrPZrNRXv4yaWkh3H67XifTkfn5hfDII68we3YF3bq9zrlzvYiM/ITjxwezcGEsn3zy5xt69VBwcCyzZ2eRnj6AiIjXWLRoaKdtPG1vCpRy3aKi+jJtWgY5OZF4eDzHqlVzXF1Sm9TXNwRKL6+O38yyfPkkYmJWc/r0bcyb9zlGo350pX2Ul8fg6Zl2Q9euW/cLgoL+xalTvZg3b4/L/3/70UfPERNTQ1LSMy6tQ1pn6NAZpKQcY9iwTAoKHsHPrwij8SesWuXDa69No7AwvVXjeXh4k5JykJych0lI+JylSxMoKytwUvVdh/5Wklbx9w9jzpxM0tP7Ex6+nCVLxjh1Jw1nqq+vAsDLy9/FlbRs2bJxxMd/SHr6aObN2+Xyv5Sla/HxGUxkZAXFOWc5vWE7x9d8zOkN26ksLm3xus2b/4LZ/ALp6THMnXvY5f+/tdlsFBb+hcxMf8aM+b5La5EbExISz+OPv8X06VUYDH+joiKS8PD3+PzzJBYu7M2uXctaNd7jj79Nff2zREfnsmZNIllZ+5xUeddgsNvtdlcXIe7HZrOxYsX9xMev59SpnsyaddDtOo3Xrn0aP7/f0afPUaKi+rq6nCvYbDaWLRtLYuJ2MjLuZu7cTa4uSbqYzG17OfXcM/Q+sI+Yc4WXrEDYgNzQaM6MGEvkUz+kx5ivti7cvXs5xcVzyMsLYcaMdHx8Atq99stt2vRHTKanqKv7NePH/z9XlyMOcvbsYTZu/C/8/DYRFmYlO9sXL6+vMXHin/D3D7uuMT7/fBUZGY8DkJDw+nU3a1XWWsgorqTOYsPTbCQh1A8/r677KJICpbTJ6tXfpVu3l8nODmHatC8IDo51dUnXbc2aHxEY+BIDB2Z3uLobXrEykqSkPWRlTWT27HWuLkm6kJz9RymeOY8BR/dgMRgx269+F6Lp/KF+wwhdsYQi0ykyMqZSWurHgw+eJDAwsh0rv7olS4Ixm+t44olyl6+WiuNZLHV8/PFvyMn5J4mJhVRXQ27uQEaMeOG6dmLKytrH1q2jCQ2txmh8lgkTnmv2cyfzy3ltdxabjxeQVVLFxQHKAMSH+HJXn3CeGB5Pr4iOfffL0RQopc02b/4LVVX/RWmpN3fcsZP4+FtdXdJ1eeedbxEa+i+GDz/fIVZQmthsNpYsGULPngc4e3YqTzyx2tUlSRey5xd/4JYXf4nZamkxSF7OYjBiMZn54LFe1E08xbhxRwgP7+nESq/f9u3/wGr9DhUVT/HAA39wdTniZCdObGPHjp8RGrqbwEA76elBhITMY8KE37R4J62srIC33hpIQkIe+fkP8/jjb184l11SxdOrD7H9VBEmowGr7erRqen8HclhvDBtAHEh7nX37kYpUIpD7N//DmlpDa8YSU5+h4EDH3RxRde2atUcwsOXM2aMtcOsWFitFpYsGURy8hFyc6czY8Ybri5JupDPFvyYkYv/ip2G1ZbWarpuy+MpjH3tFccW1waLFoXj41PG9OkVejtCF1JdXcb69b/g/PnlJCSUce6ckdLS2xk79k8kJg5v9hqLpY5ly26nZ8/POXVqAHPm7OGdAwU8m3oEi83eYpC8nMlowGw08Ksp/XnstnhHfVsdVsf4W1Tc3uDBDzNkyGfU1HiQnT2NLVs6/v64Vms1dXV0sDDZn6SkIxQUzFaYlHa15xd/YOTivwI3FiYvvm7s6wvZ8/9edEhdbbVnzwp69izEx+frCpNdjI9PANOm/Z25c88TFPQuxcX9iYjYQVraCBYtimLDht9csQuU2ezJggX/IS/vcRITD/H1l77Dz989RK3F1qowCWC12am12Pj5u4f4382da6e55miFUhyqpCSLNWsGERNzjqqqJ5k69W+uLumqVqx4kJCQVCZNcv2PgMVSx9KlfUlMTKO09Os8/PC/XV2SdCE5+48SMmwwXpa6ZsPkSeAZYAdQAsQDjwM/AZq7mWcHas2elOzZT/Tgfs4q+7osXBiNv38RDz9coY0AhPPn81i//ifU179LbGw1BQVmamru5d57/3xFc+Yvl/2L5V867vn6Pzw0gOmdeKWyYyzNSKcREhLPjBlZZGUlEhT0d1599YEO+1ohq7Uai+VG12Icp7a2iqVLe5GYmEZZ2fcUJqXdFc+ch9lqaTZMZgPDgF3A94CXgJHAs8CMq4xnAMxWC8Uz5zmh2ut34MBqkpNzMRqfUJgUAAIDI5k+fQWPP16Bp+crlJXFExn5IYcO9WPhwkS2b/8HNpuN7JIq3jwVDzS/4FCbd4r8N39J1l++RtZfvkb+G89Ql9/y+1p/mXqE7JIqJ3xXHYNWKMUpGrqU7yAp6VNOnbqFuXP3drhf6EuW3Elg4A4eesjqshpqaipYsaIPCQk5VFf/hMmT/+iyWqRryty2lx53Drvq+ReAXwCHgf4XHZ8DLKdhxTK4pfG376XH6KEOqLT1Fi5MICjoDA88UIq3d8ffwEBcIz//JBs2/BhPz4+IiKjn7FlvlmT8jfTKaKzNJKTavFPkr3gKk38Y/oMmYMdO+b512GrKiZr9FzxCm1/VNBkN3J4UyqsLmn9+091phVKcwmg0Mn/+zsbnUA6ydGkClZUlri7rEnZ7LRaL634EqqvLeO21ZOLjc6ire1phUlwi78WXsBiu/nNQ1vhnxGXHo2j4C6SlfyZaDEbyfv/XthV4g44d+5jExEzq6x9RmJQWRUT0Ytas93nkkSoslt+Rdb4fpyqaD5MA57evwGD2JHL2nwgY/hCBwx8mctYfwW6ndOvyq85jtdnZfqqIUwXlTvpOXEuBUpzqscdeo67uGWJjc3n77R7k5R13dUkX2O11WK2u+RGorCxh5cqexMXlA79m0qTfuqQOkdhdW1p8PdDYxj8XAAdouAX+JvAP4PuAXwtjm+02YnZtdUidrbVz53cpKzPy4IP/dMn84n5MJjPjxv2c2tjlmFp4Gqom+wjeCYMwXfS6OXO3ELzjbqbq9B5sddVXn8NoYMWuLEeW3WEoUIrTTZz4PEFBSwkKqmTr1gGcOLHF1SUBTYHS1O7zlpUVsGpVMtHRRZhMf9CuHeIyFUXniCrOafEzE4BfAx8Dg2loyHkMeBK4nrXH6OKz19ym0dHS0j4jIeEkFRWT8PUNate5xf1tPl5w1dVJALu1HkMzj3AZPLzAaqG+MPOq11ptdjaf6Jz7husdCtIuRoyYw/HjcRw4MIGjR++mpGQJI0bMcXFVddhs7RsoS0tzeO+9fkRGnsfb+yXGjv1Bu84vcrH8fYe5nlePJwBjgIeBUGAtDc9WRtLQqNMSI7Dqpccx9bLR0K5jwGAwXPR107rG5cebvqbxa+NVjzcda/qzomI1ERHg4RHAO+9845LPNH/dpTU0/PeLv764PuMln2ka76trjM1c19w1xmavu/hcw1yXjvfV180fv/jzzZ+7vL6vjhmNF19jbOa6q4136XVGo6HZ4w3nrnbNpcdd9Tq3iloLWddonPEIiaU25zh2mxWDseHvELu1ntqchjtwlvJivFq4Pqu4ispaS6fbprFzfTfSofXpczeBgYfYsGEo3t5z+fDD00yc+LwLK6pv10BZUpLF++/3Jzy8gm7dXuaOO77dbnOLNMdSXXPNz7wBfAM4ATS1GjxEw17eP6Oh0zv0GmP4mo/gE5RNY17CYACDwX7h6yYNx6/8+uL/fvF5gOZyR/fujfP6vn7N789V7PaG/8i12Wxf/W918Z/Nfd3cuYY/DVdcf+WfBs5UJGKn5fco+986iZKPXqZ43d8IGPEw2G2c//RNrBXnGsay1LV4vR3IKK6kf3Rgi59zNwqU0q4iI/swbVo6b755C4mJv+aNN07z2GOvuaiaemy29vkRKCxM58MPBxAaWkVw8GJGjnTt61Sk66msLOHUqe2cObOLkpKD1NamYUiz0uca171Mw63uy/tWpwBLgf3AuGuMMXTkCnqOv+OG6r5eNpsNu93GkiXDiYrax5AhXxIcHIfdbrvkPxd/tvlz9quea/j6yvMN57463jC+/cI5sDV77eXXXfz1pefsl4xxeS0N5+xXXAf2yz5HM8davq7ptTmX1tHc8eavaTje3HWXHmv67FfnWrru8mub0uTF//3SMS8+funXl15XWn15+9mV/AdPwlJWRNnud6k8vAkAz8heBIx4mLJP38To6X3NMeosHfN1em2hQCntzt8/jLlzM1i6dCjJya+zeHEGc+dub/dbHAaDBbvd+T8CeXnH2bhxMMHBNUREvMpttz3h9Dmla6qqKuXkya2cObO7MTSexmTKJyCgjOBgK0Yj+Pk1rO6VlPhQFRmFjZYfps+n+dcC1Tf+aWnm3MVsQOSQATfw3bSO0WgkL+8kMTH7yMsbRWTktaKyyJWO5Jxn4d93XPNzwXfOJmD4Q9QXZmL08sMzPIFzW5cBYA6Jueb1nubO18KiQCkuYTZ7Mn/+AV57bQpJSWtZvLgXM2d+0a6v9zAYLNhs1/6XZFvk5Bxh8+ah+PvXEhOziltvfcSp80nnV1VVyqlT28jO3kVJyaHG0JiHv38ZISFXhsaamlDOn++L3d6XiIhbSUoaQ1RUvwv/gDv7fAwxLTTm9AY20HDLu/dFx1fSEERvuUa9OaExxIYGteVbvm4ffphCVBRMnLioXeaTzich1A8DV3ud+aVM3t0wxX31dtaajAOY/MOu+h7KJobGeTobBUpxGaPRyKxZH/Dee98nPv7vrFwZz4MPHiAkpH22pjIaLdhsHk4bPzv7ADt2DMfX10Ji4nvccssUp80lnUt1dVljaPyM4uKG29MmU+4VodFohOLihtBYVnYTdvtNREYOJTFxNNHRN1/Xqv+ZEWOJWPfGVV8d9FPgQ+AOGhpwQoEPGo+lANEtjG0xGDk74s4rbpc7Q1FRJuHhOzh7dggTJmh1Um6Mn5eZ+BBfMlu5o03lsW3U5Z4k+K75FzU8NS8+1LfTNeSAAqV0AFOn/o0tW3rSvfuP+PDDPowevZ0ePZy/s4bRaAWcEygzMvaye/covLys9Omzjn797nPKPOK+vgqNDbena2pOYTTmERBw/kJo9PVtWmn0prq6KTT2ISJiCElJY647NLYk8qkfYl579eaVMcCnwHM0PE9ZDCQCvwWeusbYZruNyJ//qE31Xa+1axtWJ8ePX9gu80nndVefcF7dnYnV1vw6ZU3WYc7vXIl34mCMPgHU5XxJxcGNeCcNwf+2B1sc22Q0cFfvcGeU7XIKlNIhjB37A774IoHa2of5z39GcO7cWwwaNM2pczYESsdvB3ny5A4OHLgLk8lO//4f06fP3Q6fQ9xDTU0Fp05tIyvrM0pKDjWGxqaVRgsmU0NobFhpbAqNvbHbbyI8/FaSku4gJuYWpz5f3GPMbRzqN4y+x/5z1VXKYcC6Vo5rMRg51ncoA9ph28WysgKCgzeRlXUz48cPcvp80rk9MTyepZ9lXPW8yT8UjEbKdr+Lra4ac1AEQWNmETBs6oXXCF2N1WZn5oj2uQvX3hQopcMYOPBBgoP3sH37KM6efYhz5/7MXXf92GnzmUw2DAbHBsrjxz/h0KHxgIFBg7aSnDzKoeNLx1NTU8Hp09vJymq4PV1TcxqjMafF0Fhe3gu7/SYiIoaQmDiK2NhBLnvvHkDoiiVYhg3GZKmjhQ1CrpsdsJjMhK5Y4oDRri019etERtoZO1a74kjb9Yrw547kMD5NK252ldIjOIqI6b9u9bhNe3knh/s7oswOR4FSOpT4+FuZNOkkq1cPJC7uv1i9+jTTpv2fU+YymawODZRHjnzI8eMPYLWaGD58JwkJtzlsbHGtptCYnb2b4uIvqK5uWmk8fyE0+vhAWFhTaAyhvDz5kpVGV4fGlkQP7seep55n2As/d8h4BuDgz37NsMH9HDJeS6qqSvHz+4CMjF6MG6d/wIljvDBtAOP+uvWqt71vhNlo4IVpzn/jgasoUEqHExwcyxNPZPPqq7eQnPwyy5enMXPmWof/ZWwy2TEYWtrP4PodPJhKWto0amvNjB69m7i4QQ4ZV9pPbW1V40rjrotCYw7dup0nNLQhNHp7N4VGL6qqQigvvxWbrQ8REbeSmDia2NhBmEzu+Wt12G9/xmd5+Yxc/FfscEMrlU3X7VrwY0b85lpPWDrGmjXfJjzcxk03OecfntI1xYX48qsp/fn5u4ccNubzU/oTF+LrsPE6Gvf8zSednpeXL/Pnn2DZsrEkJq5n8eKBzJ37OeZm9k+9UWazDaOx7YFy3763yc5+lMpKL+666z9ER/e/9kXiErW1VaSl7SQz81OKiw9SXX3yOkLj4MaVxkEkJt5BXNxgtw2N1zJy0V/YExnBLS/+ErPVctVnKptjMRixmMwc/Nmv2y1M1tZW4eHxFunpPbjnnnvbZU7pOh67LZ6iilr+tOFEm8f66fg+TL+tcz472cRg/+oV8yId0qpVcwgNXU5GRiSPPnoIf/8wh4y7dq2BkpIHmDXr/RseY+/e18jLm8X5897ce+8XRET0ckhtcuNqa6tIT/+MzMydFBVdvNJYeiE0AtTVQVFRQ2g0GGLo1q0P4eG3kpAwivj4IZ02NF6PnP1HKZ45jwFH92AxGFsMlk3nD/UbRuiKJUS3w23uJm+9NZ/u3ZcQFPSu05v4pOt6Y28Wz6YewWKzt+oWuMlowGw08PyU/p0+TIICpbiJ9et/BTxHQYEf9967l6iovm0ec8MGA0VFj/D442/d0PWffbaE4uIFlJT4MnHiIbp3T2xzTXJ96utrOH16J1lZn1FUdICqqpMYDLmNobEec2MWrKtrWmkMBmLw82sIjYmJo7t8aLwemdv2kvfiS0R9upHYcwWX7Khjo+Gl5WdH3Enkz39Ej3bo5r6YxVLHO+90o7w8jJSUq7+YXcQRskuqeHr1IbafKsJkNLQYLJvO35EcxgvTBnTq29wXU6AUt7F793Jyc+dSW2tm4MAPuemme254LJvNxrZtJvLzZzF9+vJWX799+z8oL/8OhYX+TJ58uN1ext6V1NfXkJb2KZmZn1JU9EVjaMy5Smj0pKoqhIbQ2Jvu3QeTmDiaHj1uU2hsI5vNxocfmsjPGs+dPf8fluoazD7eRA4ZgF877YDTnPfe+z5BQX/H1/dVhg2b6bI6pGs5mV/Oa7uz2HyigKziqkt21DHQ8NLyu3qHM3NEfKft5r4aBUpxKydObGPfvnvx9a2ne/dXGDlywQ2NU1NTwa5d/hQXf52HH/53q67dsuUlqqt/RH5+IFOnHiUoqKW9QqQl9fU1pKfvIiNjJ0VFB6iuPgWcbSE0BgOxjaFxED16jCIh4TaHPlsrl8rOPsDp04OpqHiKBx74g6vLAcBqtfDmm92oqfFn/vxCV5cjXVRlrYWM4krqLDY8zUYSQv065Q4416vrfufilnr3HkNg4GHWrx+Cp2cK69alMWnSb1s9Tk1NGQAmk0+rrtu06UXq639GXl4wDz/8JQEBnXPHA0eyWOoaVxo/o6hoP1VVJ4Ec/PzOERpaj4cHeHo2NcI0hMaKigHYbL0JDx9MfPztJCYOU2h0kZMnN2E0QkLCna4u5YL1658hOroWk+mvri5FujA/LzP9owNdXUaHoUApbiciohePPJLBypW3kJj4AitXpjFjxspWjVFdfR4AD4/rf7blo4+ex2B4lpycMKZPP46fX0ir5uzMGkLjrguNMFVVJ4Cz+PmVEhpah4cHeHh8FRorK4OorLwZu71ppXG0QmMHlZ+/m+7doVevsa4uBWi4BV9S8jcKCwOZO/fbri5HRBopUIpb8vMLYe7cNJYtG07Pnm+weHEGc+Zsv67n5SqLS8n4ZDdlZ+OwGGqoHFF6zWfB1q37BWbzC2RnR/D44yfw8Qlw0HfiPiyWOtLT95CZuYPCwgONK41nrgiN3btDUZEHlZXBVFb2x25PJixsMD16jCIxcRgeHt6u/lakFSorvwS88PLqGI0FGzf+jri4KqzWjnH7XUQa6BlKcXsrVkwlNnYNp0714IknDjYb9pq6VWN3bSGqOOeKbtXc0GjOjBhL5FM/pMeYS3e4SU39L3x9/0JGRgwzZ36Jt3c3535DLmSx1JGRsZfMzJ0UFOy/sNLo63uO0NA6PD2bPtcUGoOAGHx9exEaOpCEhFEkJo5QaOxEliwJxmr1IyXljKtLwWaz8eqrQRgMNmbOLOuwOw+JdEUKlNIprFnzI3x8XuLs2SAmTz5AWFgPoO3v01u9+kkCAv6X9PR45sw53imCktVqIT19N5mZn1JYuJ/KyqbQWHJFaCwu9qCiIgi7PRpf316EhQ2iR4+RJCXd3in+t5BrW73aRGnp7cybt93VpbBly/8AP6S6+hkmTnze1eWIyEUUKKXT2Lr175SX/4CyMk9GjtxK4cItbdrx4/3pEwmZt4b09CTmzj3mVs/3Wa0WMjP3kp7ecHu6svI4X6001l4IjVZrw0rjV6ExuTE03q7QKBQVZXL4cALnzn2HadNcv7Xh4sWheHlVMWNGpVYnRToYPUMpncaddz7JoUOJHD8+lYPf/zoPfnDohvYkNtttmCx1fO21NbxTNIx5a3d2yHcZWq0WsrI+Jz19BwUF+xpXGs9cEhpNpoZnGo1GMxUVQVRW9sFmSyYsbGDjM40jO8yzcdLxHD/+EQBxcWNcXAl89tkikpJKOH/+RwqTIh2QViil09n8w59z1/847oH9Pb/4A8PaaW/iyzWFxoyMnRQU7KOi4jh2e9Pt6Vq8vJo+B8XFZioqArHZovHx6UVo6C2NK42jFBrlhqxaNZewsGUMH17s8rcaLFoUia/vOb72tXK3ulsg0lV0vGUXkTbI2X+Ukf/316uuTNYCvwReBc4BtwC/Ae69ynh24JY/PEPOww84bY9iq9VCdvZ+0tO3U1BwgIqKL7Hbz1wSGg2GhlfuGAwNobGqqjd2ezKhoQOJjx9BUtKoTt0sJK5RXn4Yg8Hs8jD5+eer6Nkzn+LibypMinRQCpTSqRTPnEe41XLV29xzgbeBHwK9gKXAJGAzMLqZzxsAs9VC8cx5RB/ZfcN1Wa0Wzpw5QHr6DvLz91FZeRybLRtf3xJCQmrx9v4qNBqNZsrLm0Jjz8bQOFKhUVwgi7KyYFcXwf79PyEw0MzUqS+5uhQRuQoFSuk0MrftZcDRPVc9vwd4A/gj8JPGY7OBm4GngE+vcp3ZbmPA0T1k7vgPPUYPver4NpuN7Ox9pKc33Z7+EpvtDD4+JYSG1uDd2N/yVWgMoKqqF3Z7MiEhA4iPH0nPnncoNEqHERBwjrKygS6t4fDhdSQlZVNY+ISaxEQ6MAVK6TTyXnyJmBZeDfQ2YAK+cdExb2AB8DSQDcRdZWyLwUje7/9KXOqrnDlzgLS07RQU7G8MjdnNhkaDoSE0Vlf3pKgomdDQW4iLG0HPnqO75IvRxb2UlxcRGmoBBri0jl27niQkxMiUKS+7tA4RaZkCpXQasbu2tPh6oP1Ab+DyKDes8c8DXD1Qmu02oj7dyIYNpstWGk2UlQVSXZ1EUVEyISG3EBc3nOTkMQqN4taOH/8YoxGio0e6rIYTJ7aQmJhGXt5D+nkS6eAUKKVTqCg6R1RxToufyQWimjnedKzlqyH2XAGfZD5AeNwtxMWNpGfP0fj6BrW+WBE3kJ29g+Bg6NPnPpfVsG3bd+je3cCUKf9yWQ0icn0UKKVTyN93mJ7X+Ew14NXMce+LzrfECNyR+BQ9x9/R2vJE3E5p6UHAeGHXqfaWkbGX+Phj5OVNwN8/zCU1iMj109thpVOwVNdc8zM+NLw26HI1F513xDwinYHVmk5paaDL5t+06RvU1hqYPPkVl9UgItdPgVI6BbPPtbs/o2i47X25pmPRDppHpDPw8yvEao11ydw5OUeIiTlAcfEYgoNdU4OItI4CpXQKkUMGcK3dugcBJ4Cyy47vvuh8S2yN84h0drW1VXTvXoef300umX/9+hRsNpg0aZFL5heR1lOglE7BLzSI3NCW1xgfAazAvy86VgssAYZz9Q7vJjmhMfiFBrWhShH3cPLkFsxmiIgY3u5zFxScJjJyF3l5wwkPv9aT0SLSUShQSqdxZsRYLIar/196OPA14L9peJH5v4G7gQzgxWuMbTEYOTviTscUKtLBZWRsBaB376ttSuo869alYDTChAlanRRxJwqU0mlEPvXDFt9DCbCchm0XXwW+D9QDHwBjrjG22W7jyG3nKC8vckClIh1bcfF+KioMREff3K7zlpbmEBq6lTNnBhId3b9d5xaRtlGglE6jx5jbONRvWIurlN40bL2YS0N39x7gWm/ZsxiM7E3qTdztH/LxxxG89dY8LJY6h9Ut0tHU15+kuNgPo7F9/4pITU3B29vOuHHq7BZxNwqU0qmErliCxWTG7qDx7IDFZCbm7dXEx2+ipCSG7t2XsmpVAOvXP4fNdq1WIBH34+WVT319c9sAOE95eREBAevJzLyJhITb2nVuEWk7BUrpVKIH9+PgU89jcNB4BuDgz35N9OB+9OlzNykpWXh7L6Wuzhtv71+xbFkou3Ytc9BsIq5ntVro3r0aL6/e7Tpvauo38fe3M2bMP9p1XhFxDAVK6XSG/fZnfDb/RwA3vFLZdN2uBT9m2G+euuTciBFzmD27hJqaZ/HyqqamZi4LF8Zz/PgnN160SAeRnr4bb2/o3r39Vgmrq8vw9l5DenoSvXuPbbd5RcRxFCilUxq56C/sefr31Jo9W3ymsjkWg5Fasyd7fvEHRiz8c7OfMRqNTJjwHI8+WkZh4VxCQs6SlXUPCxcOIi/vuCO+BRGXOH16EwBJSXe125ypqd8jONjK8OH/025ziohjGex2u6MeNxPpcHL2H6V45jwGHN2DxWBssQu86fyhfsMIXbGE6MH9rnue8vIi3n33CcLCNgBQVHQvDz30uvYgFrezYsWDhIWlcu+99ZhMZqfPV19fw3vv+XP+fCQpKdlOn09EnEMrlNKpRQ/ux4Aju8ncuofPJz3GmdCYK3bUsQFnQmP4fNJjZG7fy4Aju1sVJgH8/cOYM+cjhgz5kry8QURHf6yOcHFLNTXHKSryaZcwCZCa+kO6d7cwaNCf2mU+EXEOrVBKl1NZXEre54ewVNdg9vEmcsgAh++Ac/z4J2zfPpfk5GxycrwICfk548f/st1fwyLSWsuWBVBfH0JKSobT57JaLaxa5UdVVRALFuQ7fT4RcR4FShEn2rVrGceO/ZDExFIyMgK56ab/YcSIOa4uS6RZNpuNtWvNlJTczZw5G50+X2rqfxEQ8Bc8PV/h9ttTnD6fiDiPlktEnGjEiDnMmVNMTc1zeHrWqCNcOrTc3KP4+9sJCRns9LlsNhvl5S+TlhaiMCnSCShQijhZQ0f4s40d4fMu6ggfSG7uMVeXJ3LByZMNq5I9etzh9Lk++ug5YmJqSEp6xulziYjz6Za3SDu7uCPcYIDCQnWES8ewcuUMund/g9Gjy/H27ua0eWw2GytWBGC3G5k1q1TPFot0AvopFmlnF3eE5+Z+1RG+atVc6utrXF2edGGVlUcpLPR0apgE2Lz5z8THVxIV9ZTCpEgnoZ9kEReJjOzDggX76dFjMyUlsYSHL+Ptt4P48MNfao9wcQmTKZvKylCnz5OV9QLZ2b6MG/e00+cSkfahQCniYr17jyUlJRMfn2XU1Pjg4/Nrli8P4bPPlri6NOliAgPPYzQmOnWO7dv/QWJiKcHB39PqpEgnop9mkQ5i+PDZl3SE19bOV0e4tJuSkixCQmwEBQ106jwnTjxLTo4XEyf+1qnziEj7UqAU6UCa6wjPzlZHuDjf8eMfAxAXN8ppc+zZs4KePQvx8fl6u+3EIyLtQ13eIh1YeXkRq1fPJDT0o8aO8HE89NBKdYSLw739dgphYYu49dZ8AgLCnTLHwoXR+PsX8fDDFZjNnk6ZQ0RcQyuUIh2Yv38Ys2evb+wIH0x09MbGjvA56ggXhzp//iBFRSanhckvvlhDcnIuRuMTCpMinZACpYgbaOgI39fYER5HePhy3n47iHXrnlFHuDhIJmVlwU4bfe/eH1BUZGLy5L87bQ4RcR0FShE30tARnnGhI9zX9zeNHeGLXF2auDl//xLs9h5OGfvYsY9JTMykvv4Rp7/jUkRcQ4FSxA01dYTX1v6qsSM8hYUL4/jyy02uLk3cUGVlCaGhFvz9+ztl/J07v0tZmZEHH/ynU8YXEddToBRxU0ajkfvu+yWPPlpGUdECgoNzOXNmHAsX3kJOzhFXlydu5MsvN2IyQVTUCIePnZb2GQkJJ6momISvb5DDxxeRjkGBUsTNmc2ePPLIQiZMKCAnZwJRUYc4cOBmli27l7KyAleXJ24gO3sHAH36jHf42J988k2qqgxMmfKKw8cWkY5DgVKkk/DzC2H27A8ZOvQEubm3Eh29kU2botQRLtd07twXlJYaCQ/v6dBxs7MPEB9/iHPn7iEwMNKhY4tIx6JAKdLJRET0YsGCz+nRYyvFxU0d4YHqCJerslrTOHcuwOHjbtiQQn093H//QoePLSIdiwKlSCfVu/cYUlIy8PV9lZoav8aO8GB1hMsVfH0LsVpjHDpmXt5xoqM/p6BgFGFhzukeF5GOQ4FSpJMbNmwmc+YUUVf3azw86tQRLpeor6+he/dafH1vcui4H36YgsEAEyfqHzAiXYECpUgXYDQaGT/+/zF9+nl1hMslTp7ciocHREQMd9iYRUWZhIfv4OzZIURG9nHYuCLScSlQinQhV+8IH6eO8C4qPX0rAL163eOwMdeuTcHDA8aP17OTIl2FAqVIF3R5R3hU1CY2bYrizTdnqyO8iyku3kdlJcTGDnLIeGVlBQQHbyIr62bi4hwzpoh0fAqUIl1YU0d4QkJDR3hExKuNHeG/UEd4F1FXd5LiYj+MRsf8dZCa+nV8fe2MHatdcUS6EgVKEWmmI/wFdYR3EV5eedTVRTlkrKqqUvz8PiAjoxfJyaMcMqaIuAcFShG5oPmO8FiOHfvY1aWJE9hsNkJDq/Dy6u2Q8das+TYBATZGjfo/h4wnIu5DgVJELnFpR3gKwcF5nD07Xh3hnVBm5l58fSEsbEibx6qtrcLD4y3S03vQt++9DqhORNyJAqWINKuhI/yVxo7wiRc6wpcuvUcd4Z3EqVOfAJCUNLbNY6Wmfo+wMCtDh/61zWOJiPtRoBSRFjV0hK9r7AgfQnT0J40d4TPVEe7mCgr2UFcHPXuObtM4FksdNtsKTp2KYtCgaQ6qTkTciQKliFyXho7w/5CYuJ3i4ngiIl7j7bcDWbv2aXWEu6nq6i8pLPTGbPZs0zgffPATIiLqGTDg9w6qTETcjQKliLRKr16jSUlJx89vBTU1fvj5/Y7ly4P59FO9xNrdmM05VFeHt2kMq9VCVdW/SUsLY/jw2Q6qTETcjQKliNyQ2257orEj/Dd4eNRRV/d1Fi6M5ejRj1xdmlynkJByzOaebRpj/fpniI6upVev5x1UlYi4IwVKEblhDR3hv2D69PMUF3+d4OA8cnImsHDhAM6ePezq8qQFubnHCAiwExw86IbHsNlslJT8jYyMQO6449uOK05E3I4CpYi0mdnsycMP/5sJEwrIzZ1EVNRhvvhiAEuX3s3583muLk+aceLERgASEu684TE2bvwdcXFVxMU97aiyRMRNGex2u93VRYhI51JQcJr3359OXNznVFYaqaubwUMPLcTDw9vVpUmjN954gu7dX2fUqHK8vbu1+nqbzcarrwZhMNiYObPMYVs3ioh70m8AEXG48PCe6gjv4Corj1JY6HFDYRJg27a/06NHOd27/1hhUkQUKEXEedQR3nEZDNlUVobe8PVpac9z9qw39933nOOKEhG3pUApIk6njvCOJzCwFIMh4Yau/eyzRSQlldCt27e1OikigAKliLST5jrCc3PVEe4KpaU5hIZaCQwceEPXHz36C3JzPbn/fr3IXEQaKFCKSLtq6gifOLGInJxJREYeUUd4O/vyy48BiI29vdXXfv75Knr2zMfTc16bd9gRkc5DgVJEXMLXN4hZs9YybNjJxj3CN7N5cwxvvPGE9gh3srNndwJw003jW33t/v0/obDQzJQpLzm4KhFxZwqUIuJSF3eEFxX1IDLydd55J5C1a/9bHeFOcv78QYqLTQQGRrbqusOH15GUlI3NNl2vgBKRSyhQikiH0NARnka3bq9TVdUNP7/f8+qrQezc+W9Xl9bp2O2ZnD8f1Orrdu16ktJSI1OmvOz4okTErSlQikiHMnToDObPL6a+/gXM5nrq67/JwoUx6gh3oG7dirHb41t1zYkTW0hMTKO6+kF8fAKcVJmIuCsFShHpkO6997957LFyiou/SXBwfmNH+M3qCG+j6uoywsLq6datX6uu27btO1RUGJgyRSvGInIlBUoR6bBMJjMPP/zPxo7w+4mMPMrBgwNYuvQudYTfoC+//BiTCaKiRlz3NRkZe4mPP8b58/fh7x/mxOpExF0pUIpIh9fQEf4Bw4adJCdnKNHRWxo7wh+ntrbK1eW5laysHQD06XPfdV+zadM3qK01MHnyK84qS0TcnAKliLiNho7wvSQl7aCoKIHw8JWsXh2sjvBWOHfuAOfPG4iI6HVdn8/JOUJMzAGKi8cQHBzr5OpExF0pUIqI20lOHkVKymkCAi7tCN+x41+uLq3Ds1hOc+7c9TfVrF+fgs0GkyYtcmJVIuLuFChFxG1d3hFusXyLhQujOXLkQ1eX1mH5+BRisURf12cLCk4TGbmLvLzhhIf3dHJlIuLOFChFxO01dYSXlHyLoKAC8vImsXBhf86cOejq0joUi6WO7t1r8PHpe12fX7cuBaMRJkzQ6qSItEyBUkQ6BZPJzEMP/YNJk4rIyXmAyMhjHDo0UB3hFzl1ajuenhARcds1P1tamkNo6FbOnBlIdHT/dqhORNyZAqWIdCoNHeHvqyO8GWlpWwBITr7nmp9NTU3B29vOuHHq7BaRa1OgFJFOqfmO8CA++OBnXbYjvKjoc6qqID5+SIufKy8vIiBgPZmZN5GQcO3VTBERBUoR6dS+6gh/g6qqALp1e7HLdoTX1Z2gqMgPo7HlX/2pqd/E39/OmDH/aKfKRMTdKVCKSJcwdOh05s8vwmL5HSaT5UJH+OHD61xdWrvx9Myjri6yxc9UV5fh7b2G9PQkevce2z6FiYjbU6AUkS5l3LifM2NG2YWO8Pz8+7tER7jNZiMsrBJPz5ZfaJ6a+j2Cg60MH/4/7VSZiHQGCpQi0uVc3hEeEdHUET6W0tIcV5fnFNnZ+/D1hbCwW6/6mfr6GozGlaSlxTJgwAPtWJ2IuDsFShHpspo6wkeMOE1Ozm1ER29ly5ZYVq6c0ek6wk+d+gSAxMSxV/1MauoP6d7dwqBBf2qfokSk01CgFJEur3v3RBYs2ENy8qcUFSUSEfEGq1cH8f77T3WajvC8vN3U1UFy8h3NnrdaLdTVLeH06XCGDp3eztWJiLtToBQRaZSUNJKUlNMEBr5JVVUA/v5/5NVXA9m+3f27naurv6Sw0BsPD+9mz69d+zOiouro2/e37VyZiHQGCpQiIpcZMuTRizrCrVit33H7jnCz+SzV1d2bPWez2Sgvf5m0tBBuvz2lnSsTkc5AgVJE5Cq+6gj/9kUd4f3csiM8KKgMszmp2XMfffQcMTE1JCU9085ViUhnoUApItKCho7wl5k0qYjc3ClERHzJoUMDWbLkTrfpCM/PP0lQkJ3g4MFXnLPZbBQW/oXMTH/GjPm+C6oTkc5AgVJE5Dr4+gYxc+YaRow4TW7uMGJitrlNR/iJEx8DEB8/+opzmzf/mfj4SqKinrrmDjoiIlej3x4iIq3QvXsi8+fvbuwIT3KLjvCcnF1YrXDTTfdecS4r6wWys30ZN+5pF1QmIp2FAqWIyA1o6Ag/1UxH+MuuLu0KFRVHKCrywMcn4JLj27f/g8TEUoKDv6fVSRFpE/0GERFpg6aOcKv1D40d4d9l0aKoDtURbjBkUVERcsXxEyeeJSfHi4kT9aogEWkbBUoREQe4556nmDGjjHPnvkNgYOGFjvDs7AOuLo2AgHMYDAmXHNuzZwU9exbi4/N1TCazawoTkU5DgVJExEFMJjPTpv0f999fcqEj/MiRwS7tCD9/Po+wMCsBAQMuOX7w4FPk53swefKfXVKXiHQuCpQiIg7m4xNwoSM8J+fijvDH2r0j/PjxjQDExNx+4dgXX6whOTkXo/EJzGbPdq1HRDonBUoRESe5siP8Td57L4j33/9pu3WEnzmzE7i0w3vv3h9QVGRi8uS/t0sNItL5KVCKiDhZU0d4UNBbVFYG4u//J1asCGTbtv91+tylpV9QXGwiODgWgGPHPiYxMZP6+kfw9u7m9PlFpGtQoBQRaSe33voI8+cXYrW+iMFgxWZ7kkWLojh06AOHzlNZa+FIznn2Z50jp9pK4bnwC+d27vwuZWVGHnzwnw6dU0S6NoPdbre7uggRka7GarWQmvoDLJZ/ExJiIT39Ju67byVxcYNuaLyT+eW8tjuLzccLyCqp4tJf7HZ6hPhxa5SVwd3mYygfyKxZ7zvguxARaaBAKSLiQtXVZbzzzmwCA1Px8LCTm3sH06a9QVBQ9HVdn11SxdOrD7H9VBEmowGr7eq/0g1YsWNiRII/f/zaUOJCfB31bYhIF6dAKSLSARQVZZKaOp3Y2N1UVxuoqnqEhx5aipfX1UPfG3uzeDb1CBabvcUgeTmT0YDZaOBXU/rz2G3xjihfRLo4BUoRkQ4kPX03mzbNJCnpFIWFHvj4PMkDD/zxiq0R/3fzSf604USb5/vJ+N58765ebR5HRLo2BUoRkQ5o37632b//O/TsWUhWVjcSEn7HmDHfAxpWJn/+7iGHzfWHhwYwXSuVItIGCpQiIh3Ypk1/JCfnWeLiqjl9OpL4fq/wvXUmai1Xvsey6IO/Unl401XHivnuUsz+YVcc9zIb2fijO/VMpYjcMAVKEZEOrqEj/EdYLP9kScYvOVYyEDumKz5Xe/YY9efyLjtqp+Sj/8McGEF0ysvNjm8yGrg9KZRXFwx3QvUi0hWYXV2AiIi0rGGP8L9zKOtpju7bd9XPecX0xSum7yXHarKPYK+vxa/f2KteZ7XZ2X6qiFMF5SSH+zuqbBHpQvRicxERN/HOgRJMRkOrrqk8uhUw4NfvzhY/ZzIaWLErqw3ViUhXpkApIuImNh8vaNXrgexWC1Vf7sArti/moIgWP2u12dl8oqCtJYpIF6VAKSLiBipqLWSVVLXqmur0fdiqy1q83X2xrOIqKmstN1CdiHR1CpQiIm4gs7iS1nZQVh7dCkYzvn1HX9fn7UBGcWWraxMRUaAUEXEDdc28Jqgltrpqqk/uwidxMCafAKfNIyICCpQiIm7B09y6X9dVJ3Y1dHf3H+vUeUREQIFSRMQtJIT60Zr+7sqjWzB4+uDT6/rfLWlonEdEpLUUKEVE3ICfl5n469zJxlp1npqMA/j2GoHRw/u654gP9cXPS68nFpHWU6AUEXETd/UJv673UFYe2wY2a6tud5uMBu7qHd6G6kSkK1OgFBFxE08Mj7+u91BWHtmC0TcI74RB1z221WZn5oj4NlQnIl2Z7m2IiLiJXhH+3JEcxqdpxS0Gy6jZf27VuE17eWvbRRG5UVqhFBFxIy9MG4C5ldsvXovZaOCFaQMcOqaIdC0KlCIibiQuxJdfTenv0DGfn9KfuOts+BERaY4CpYiIm3nstnh+Mr63Q8b66fg+TL9Nz06KSNsY7HZ7a3fzEhGRDuCNvVk8m3oEi81+Xc06TUxGA2ajgeen9FeYFBGHUKAUEXFj2SVVPL36ENtPFWEyGloMlk3n70gO44VpA3SbW0QcRoFSRKQTOJlfzmu7s9h8ooCs4iou/sVuoOGl5Xf1DmfmiHh1c4uIwylQioh0MpW1FjKKK6mz2PA0G0kI9dMOOCLiVAqUIiIiItIm6vIWERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTZRoBQRERGRNlGgFBEREZE2UaAUERERkTb5/5geiMDbGeEHAAAAAElFTkSuQmCC", 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" ] @@ -861,7 +683,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" }, "vscode": { "interpreter": { diff --git a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod index e66df54a8..405b870cb 100644 --- a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod +++ b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod @@ -1,863 +1,25 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=10.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=0.75 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=0.75 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=0.75 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=0.75 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=0.75 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.25 - } -]; - -qfunc main(params_list: real[6], output target: qbit[10]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + x_0: qbit; + x_1: qbit; + x_2: qbit; + x_3: qbit; + x_4: qbit; + x_5: qbit; + x_6: qbit; + x_7: qbit; + x_8: qbit; + x_9: qbit; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=False, -initial_point=[0.0, 0.4, 0.2, 0.2, 0.4, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=60, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=0.7 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[6], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 3) { + phase (-(((((((((((((((((((((((1 - v.x_0) * (1 - v.x_1)) + ((1 - v.x_0) * (1 - v.x_5))) + ((1 - v.x_0) * (1 - v.x_6))) + ((1 - v.x_0) * (1 - v.x_7))) + ((1 - v.x_0) * (1 - v.x_8))) + ((1 - v.x_1) * (1 - v.x_2))) + ((1 - v.x_1) * (1 - v.x_4))) + ((1 - v.x_1) * (1 - v.x_5))) + ((1 - v.x_1) * (1 - v.x_6))) + ((1 - v.x_1) * (1 - v.x_9))) + ((1 - v.x_2) * (1 - v.x_3))) + ((1 - v.x_2) * (1 - v.x_4))) + ((1 - v.x_3) * (1 - v.x_6))) + ((1 - v.x_3) * (1 - v.x_8))) + ((1 - v.x_4) * (1 - v.x_6))) + ((1 - v.x_4) * (1 - v.x_7))) + ((1 - v.x_4) * (1 - v.x_8))) + ((1 - v.x_4) * (1 - v.x_9))) + ((1 - v.x_5) * (1 - v.x_6))) + ((1 - v.x_7) * (1 - v.x_8))) + ((1 - v.x_8) * (1 - v.x_9))) + (20 * (((((((((((v.x_0 + v.x_1) + v.x_2) + v.x_3) + v.x_4) + v.x_5) + v.x_6) + v.x_7) + v.x_8) + v.x_9) - 5) ** 2))), params[i]); + apply_to_all(lambda(q) { + RX(params[3 + i], q); + }, v); + } +} diff --git a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json index 0967ef424..2d6c6696b 100644 --- a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json +++ b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json @@ -1 +1,43 @@ -{} +{ + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "u", + "s", + "r", + "rx", + "cy", + "sdg", + "z", + "ry", + "rz", + "sx", + "cz", + "h", + "cx", + "x", + "sxdg", + "tdg", + "t", + "p", + "y", + "u2", + "u1", + "id" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 2694895972 + } +} From 177904bb015f18d23d67156740ea4c7139ee707c Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Mon, 16 Dec 2024 10:54:24 +0200 Subject: [PATCH 18/32] updated notebooks accord\ing to CR comments and new CombiProblem interface --- .../integer_linear_programming.ipynb | 158 +++++++----- .../integer_linear_programming.qmod | 6 +- ..._linear_programming.synthesis_options.json | 32 +-- .../optimization/max_clique/max_clique.ipynb | 233 ++++++++++++------ .../optimization/max_clique/max_clique.qmod | 16 +- .../max_clique.synthesis_options.json | 32 +-- .../max_k_vertex_cover.ipynb | 170 +++++++------ .../max_k_vertex_cover.qmod | 13 +- .../max_k_vertex_cover.synthesis_options.json | 34 +-- .../set_partition/set_partition.ipynb | 208 +++++++++------- .../set_partition/set_partition.qmod | 13 +- .../set_partition.synthesis_options.json | 28 +-- .../ising_model/ising_model.ipynb | 177 +++++++------ .../ising_model/ising_model.qmod | 9 +- .../ising_model.synthesis_options.json | 32 +-- 15 files changed, 664 insertions(+), 497 deletions(-) diff --git a/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb b/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb index 1ee489202..702813b48 100644 --- a/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb +++ b/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb @@ -42,7 +42,7 @@ "\n", "# Solving with the Classiq platform\n", "\n", - "We go through the steps of solving the problem with the Classiq platform, using QAOA algorithm [[2](#QAOA)]. The solution is based on defining a pyomo model for the optimization problem we would like to solve." + "We go through the steps of solving the problem with the Classiq platform, using QAOA algorithm [[2](#QAOA)]. The solution is based on defining a Pyomo model for the optimization problem we would like to solve." ] }, { @@ -52,12 +52,12 @@ "source": [ "## Building the Pyomo model from a graph input\n", "\n", - "We proceed by defining the pyomo model that will be used on the Classiq platform, using the mathematical formulation defined above:" + "We proceed by defining the Pyomo model that will be used on the Classiq platform, using the mathematical formulation defined above:" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "48889b21-557b-481c-80c5-3c0b5c91adb6", "metadata": { "ExecuteTime": { @@ -101,7 +101,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "6e5295f4-7ba6-4ff6-8782-1c4c2c7f85e4", "metadata": { "ExecuteTime": { @@ -121,7 +121,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "345330b2-9c14-41f6-b4ba-e11fb9ca1565", "metadata": { "ExecuteTime": { @@ -179,12 +179,12 @@ "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the qaoa algorithm, with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the Pyomo model to a quantum model of the QAOA algorithm, with cost hamiltonian translated from the Pyomo model. We can choose the number of layers for the QAOA ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "816b468f-a59f-4f2f-8337-4a9d66548425", "metadata": { "tags": [] @@ -201,7 +201,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "62ec28b3-cb49-411a-8c4a-8004fff6c105", "metadata": {}, "outputs": [], @@ -221,7 +221,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", "metadata": { "pycharm": { @@ -234,7 +234,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Opening: https://nightly.platform.classiq.io/circuit/ae0c345f-e27c-496d-a3d8-a7eab1675d72?version=0.61.0.dev7\n" + "Opening: https://nightly.platform.classiq.io/circuit/ef888bc5-02f8-4150-b49f-76cd8bbc7ecf?version=0.62.0.dev9\n" ] } ], @@ -253,7 +253,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "7d188c69-21d1-4afe-86b1-46229e91a01e", "metadata": {}, "outputs": [], @@ -275,17 +275,22 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "62d12d20-1c80-4a9e-bb6b-b1fddc6cbe40", "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Optimization Progress: 72%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌ | 65/90 [03:27<01:19, 3.19s/it]\n" + ] + } + ], "source": [ - "cost_values = []\n", - "optimized_params = combi.optimize(\n", - " execution_preferences, maxiter=90, cost_trace=cost_values, quantile=0.7\n", - ")" + "optimized_params = combi.optimize(execution_preferences, maxiter=90, quantile=0.7)" ] }, { @@ -298,7 +303,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "02454398-b229-403c-824a-b1eb539fbc1f", "metadata": { "tags": [] @@ -310,13 +315,13 @@ "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -328,11 +333,10 @@ "source": [ "import matplotlib.pyplot as plt\n", "\n", - "fig, axes = plt.subplots(nrows=1, ncols=1)\n", - "axes.plot(cost_values)\n", - "axes.set_xlabel(\"Iterations\")\n", - "axes.set_ylabel(\"Cost\")\n", - "axes.set_title(\"Cost convergence\")" + "plt.plot(combi.cost_trace)\n", + "plt.xlabel(\"Iterations\")\n", + "plt.ylabel(\"Cost\")\n", + "plt.title(\"Cost convergence\")" ] }, { @@ -350,7 +354,7 @@ "id": "670eddd3-2da7-4a88-b571-7884ef24f60c", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm. The optimization is always defined as a minimzation problem, so the positive maximization objective was tranlated to a negative minimization one by the pyomo to qmod translator." + "We can also examine the statistics of the algorithm. The optimization is always defined as a minimzation problem, so the positive maximization objective was tranlated to a negative minimization one by the Pyomo to qmod translator." ] }, { @@ -358,12 +362,12 @@ "id": "c99a7e3e-5203-4893-b970-dc23739f6df2", "metadata": {}, "source": [ - "In order to get samples with the optimized parameters, we call the `get_results` method:" + "In order to get samples with the optimized parameters, we call the `sample` method:" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, "id": "9638f749-a60b-4176-a4ea-50d7c2bb986f", "metadata": {}, "outputs": [ @@ -395,33 +399,33 @@ " \n", " \n", " \n", - " 151\n", - " {'x_0': 0, 'x_1': 0, 'x_2': 1}\n", - " 0.001953\n", + " 32\n", + " {'x': [0, 0, 1]}\n", + " 0.004883\n", " -3.000000e+00\n", " \n", " \n", - " 178\n", - " {'x_0': 0, 'x_1': 1, 'x_2': 0}\n", - " 0.000977\n", + " 0\n", + " {'x': [0, 1, 0]}\n", + " 0.281738\n", " -2.000000e+00\n", " \n", " \n", - " 11\n", - " {'x_0': 1, 'x_1': 0, 'x_2': 0}\n", - " 0.014648\n", + " 8\n", + " {'x': [1, 0, 0]}\n", + " 0.016113\n", " -1.000000e+00\n", " \n", " \n", - " 4\n", - " {'x_0': 0, 'x_1': 0, 'x_2': 0}\n", - " 0.020020\n", + " 73\n", + " {'x': [0, 0, 0]}\n", + " 0.001465\n", " 1.527468e-150\n", " \n", " \n", - " 68\n", - " {'x_0': 0, 'x_1': 0, 'x_2': 1}\n", - " 0.004395\n", + " 104\n", + " {'x': [0, 0, 1]}\n", + " 0.000977\n", " 7.000000e+00\n", " \n", " \n", @@ -429,43 +433,61 @@ "" ], "text/plain": [ - " solution probability cost\n", - "151 {'x_0': 0, 'x_1': 0, 'x_2': 1} 0.001953 -3.000000e+00\n", - "178 {'x_0': 0, 'x_1': 1, 'x_2': 0} 0.000977 -2.000000e+00\n", - "11 {'x_0': 1, 'x_1': 0, 'x_2': 0} 0.014648 -1.000000e+00\n", - "4 {'x_0': 0, 'x_1': 0, 'x_2': 0} 0.020020 1.527468e-150\n", - "68 {'x_0': 0, 'x_1': 0, 'x_2': 1} 0.004395 7.000000e+00" + " solution probability cost\n", + "32 {'x': [0, 0, 1]} 0.004883 -3.000000e+00\n", + "0 {'x': [0, 1, 0]} 0.281738 -2.000000e+00\n", + "8 {'x': [1, 0, 0]} 0.016113 -1.000000e+00\n", + "73 {'x': [0, 0, 0]} 0.001465 1.527468e-150\n", + "104 {'x': [0, 0, 1]} 0.000977 7.000000e+00" ] }, - "execution_count": 10, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "optimization_result = combi.get_results()\n", + "optimization_result = combi.sample(optimized_params)\n", "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { "cell_type": "markdown", - "id": "687f492b-a4a5-49c6-964c-8959b035bb93", + "id": "f08c8085-b50a-41a1-9359-46413f60739c", "metadata": {}, "source": [ - "And the histogram:" + "We will also want to compare the optimized results to uniformly sampled results:" ] }, { "cell_type": "code", - "execution_count": 11, - "id": "31a4e74d-b2b8-42e0-826d-de7b51de1fe8", + "execution_count": 13, + "id": "25277397-d7a5-4466-af4c-fee2e17bc8b9", + "metadata": {}, + "outputs": [], + "source": [ + "uniform_result = combi.sample_uniform()" + ] + }, + { + "cell_type": "markdown", + "id": "91831ceb-ca0b-44d5-9a1d-e8c70a139592", + "metadata": {}, + "source": [ + "And compare the histograms:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "77668ce1-64f6-4086-b0fe-597ded8ad0e0", "metadata": { "tags": [] }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -476,8 +498,22 @@ ], "source": [ "optimization_result[\"cost\"].plot(\n", - " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + " kind=\"hist\",\n", + " bins=30,\n", + " edgecolor=\"black\",\n", + " weights=optimization_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"optimized\",\n", + ")\n", + "uniform_result[\"cost\"].plot(\n", + " kind=\"hist\",\n", + " bins=30,\n", + " edgecolor=\"black\",\n", + " weights=uniform_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"uniform\",\n", ")\n", + "plt.legend()\n", "plt.ylabel(\"Probability\", fontsize=16)\n", "plt.xlabel(\"cost\", fontsize=16)\n", "plt.tick_params(axis=\"both\", labelsize=14)" @@ -493,7 +529,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 15, "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", "metadata": { "tags": [] @@ -502,10 +538,10 @@ { "data": { "text/plain": [ - "{'x_0': 0, 'x_1': 0, 'x_2': 1}" + "{'x': [0, 0, 1]}" ] }, - "execution_count": 12, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -533,7 +569,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 16, "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { "pycharm": { diff --git a/applications/optimization/integer_linear_programming/integer_linear_programming.qmod b/applications/optimization/integer_linear_programming/integer_linear_programming.qmod index 382226df1..1b153d454 100644 --- a/applications/optimization/integer_linear_programming/integer_linear_programming.qmod +++ b/applications/optimization/integer_linear_programming/integer_linear_programming.qmod @@ -1,7 +1,5 @@ qstruct QAOAVars { - x_0: qnum<2, False, 0>; - x_1: qnum<2, False, 0>; - x_2: qnum<2, False, 0>; + x: qnum<2, False, 0>[3]; monotone_rule_1_slack_var_0: qbit; monotone_rule_2_slack_var_0: qbit; } @@ -12,7 +10,7 @@ qfunc main(params: real[6], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); repeat (i: 3) { - phase (-(((((((((10 * v.x_0) * v.x_1) + ((10 * v.x_0) * v.x_2)) - v.x_0) + ((10 * v.x_1) * v.x_2)) - (2 * v.x_1)) - (3 * v.x_2)) + (10 * (((((v.monotone_rule_1_slack_var_0 + v.x_0) + v.x_1) + v.x_2) - 1.0) ** 2))) + (10 * (((((v.monotone_rule_2_slack_var_0 + v.x_0) + v.x_1) + v.x_2) - 1.0) ** 2))), params[i]); + phase (-(((((((((10 * v.x[0]) * v.x[1]) + ((10 * v.x[0]) * v.x[2])) - v.x[0]) + ((10 * v.x[1]) * v.x[2])) - (2 * v.x[1])) - (3 * v.x[2])) + (10 * (((((v.monotone_rule_1_slack_var_0 + v.x[0]) + v.x[1]) + v.x[2]) - 1.0) ** 2))) + (10 * (((((v.monotone_rule_2_slack_var_0 + v.x[0]) + v.x[1]) + v.x[2]) - 1.0) ** 2))), params[i]); apply_to_all(lambda(q) { RX(params[3 + i], q); }, v); diff --git a/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json b/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json index af12aaf3f..0ae05c835 100644 --- a/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json +++ b/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ + "sx", "tdg", - "ry", + "z", "rz", - "s", - "r", - "sx", - "t", - "cy", - "p", - "u", + "y", "h", - "cx", + "cy", + "t", "sdg", - "z", - "x", - "cz", "u1", - "u2", + "r", + "id", + "cx", + "cz", "rx", + "u", + "p", + "ry", "sxdg", - "y", - "id" + "x", + "u2", + "s" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 2268737765 + "random_seed": 2943844644 } } diff --git a/applications/optimization/max_clique/max_clique.ipynb b/applications/optimization/max_clique/max_clique.ipynb index d8af81f07..b84d89a14 100644 --- a/applications/optimization/max_clique/max_clique.ipynb +++ b/applications/optimization/max_clique/max_clique.ipynb @@ -126,7 +126,7 @@ "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the QAOA algorithm [[1](#QAOA)], with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`." + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` python class. Under the hood it tranlates the Pyomo model to a quantum model of the QAOA algorithm [[1](#QAOA)], with cost hamiltonian translated from the Pyomo model. We can choose the number of layers for the QAOA ansatz using the argument `num_layers`." ] }, { @@ -141,7 +141,7 @@ "from classiq import *\n", "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "combi = CombinatorialProblem(pyo_model=max_clique_model, num_layers=20)\n", + "combi = CombinatorialProblem(pyo_model=max_clique_model, num_layers=3)\n", "\n", "qmod = combi.get_model()" ] @@ -168,7 +168,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", "metadata": { "pycharm": { @@ -176,7 +176,15 @@ }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Opening: https://nightly.platform.classiq.io/circuit/12b0d353-e44e-4992-bcb8-deb3a88a482b?version=0.62.0.dev7\n" + ] + } + ], "source": [ "qprog = combi.get_qprog()\n", "show(qprog)" @@ -219,9 +227,56 @@ "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Optimization Progress: 51it [02:27, 2.88s/it] \n" + ] + } + ], + "source": [ + "optimized_params = combi.optimize(execution_preferences, maxiter=50, quantile=0.7)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "b52604ae-fc57-426f-8566-9e3760250e81", + "metadata": { + "scrolled": true, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Cost convergence')" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "optimized_params = combi.optimize(execution_preferences, maxiter=1, quantile=1)" + "import matplotlib.pyplot as plt\n", + "\n", + "plt.plot(combi.cost_trace)\n", + "plt.xlabel(\"Iterations\")\n", + "plt.ylabel(\"Cost\")\n", + "plt.title(\"Cost convergence\")" ] }, { @@ -239,7 +294,7 @@ "id": "2510a439-9181-4e39-a033-0bd53e8f87f6", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm. The optimization is always defined as a minimzation problem, so the positive maximization objective was tranlated to a negative minimization one by the pyomo to qmod translator." + "We can also examine the statistics of the algorithm. The optimization is always defined as a minimzation problem, so the positive maximization objective was tranlated to a negative minimization one by the Pyomo to qmod translator." ] }, { @@ -247,12 +302,12 @@ "id": "e06ae35f-7aac-4631-9fe9-4f46a36c8cea", "metadata": {}, "source": [ - "In order to get samples with the optimized parameters, we call the `get_results` method:" + "In order to get samples with the optimized parameters, we call the `sample` method:" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "9638f749-a60b-4176-a4ea-50d7c2bb986f", "metadata": {}, "outputs": [ @@ -284,33 +339,33 @@ " \n", " \n", " \n", - " 99\n", - " {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'...\n", - " 0.000977\n", + " 93\n", + " {'x': [0, 1, 1, 1, 0, 1, 0]}\n", + " 0.000488\n", " -4.0\n", " \n", " \n", - " 102\n", - " {'x_0': 1, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'...\n", - " 0.000977\n", + " 86\n", + " {'x': [1, 1, 1, 1, 0, 0, 0]}\n", + " 0.000488\n", " -4.0\n", " \n", " \n", - " 17\n", - " {'x_0': 1, 'x_1': 0, 'x_2': 0, 'x_3': 1, 'x_4'...\n", - " 0.015137\n", + " 50\n", + " {'x': [0, 1, 1, 0, 0, 1, 0]}\n", + " 0.003418\n", " -3.0\n", " \n", " \n", - " 26\n", - " {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'...\n", - " 0.012695\n", + " 41\n", + " {'x': [1, 1, 0, 1, 0, 0, 0]}\n", + " 0.004883\n", " -3.0\n", " \n", " \n", - " 27\n", - " {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", - " 0.012695\n", + " 44\n", + " {'x': [1, 0, 1, 1, 0, 0, 0]}\n", + " 0.004395\n", " -3.0\n", " \n", " \n", @@ -318,58 +373,40 @@ "" ], "text/plain": [ - " solution probability cost\n", - "99 {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'... 0.000977 -4.0\n", - "102 {'x_0': 1, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'... 0.000977 -4.0\n", - "17 {'x_0': 1, 'x_1': 0, 'x_2': 0, 'x_3': 1, 'x_4'... 0.015137 -3.0\n", - "26 {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'... 0.012695 -3.0\n", - "27 {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.012695 -3.0" + " solution probability cost\n", + "93 {'x': [0, 1, 1, 1, 0, 1, 0]} 0.000488 -4.0\n", + "86 {'x': [1, 1, 1, 1, 0, 0, 0]} 0.000488 -4.0\n", + "50 {'x': [0, 1, 1, 0, 0, 1, 0]} 0.003418 -3.0\n", + "41 {'x': [1, 1, 0, 1, 0, 0, 0]} 0.004883 -3.0\n", + "44 {'x': [1, 0, 1, 1, 0, 0, 0]} 0.004395 -3.0" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "optimization_result = combi.get_results()\n", + "optimization_result = combi.sample(combi.optimized_params)\n", "optimization_result.sort_values(by=\"cost\").head(5)" ] }, + { + "cell_type": "markdown", + "id": "d2631766-717e-41d1-889d-a2c83ff479e3", + "metadata": {}, + "source": [ + "We will also want to compare the optimized results to uniformly sampled results:" + ] + }, { "cell_type": "code", - "execution_count": 9, - "id": "9b868135-e219-441c-8d98-6b43d894a130", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": 10, + "id": "ce23d35b-4780-4feb-a1fa-58e302e3feb3", + "metadata": {}, + "outputs": [], "source": [ - "solution = optimization_result.solution[optimization_result.cost.idxmin()]\n", - "solution_nodes = [v for v in graph.nodes if solution[f\"x_{v}\"]]\n", - "solution_edges = [\n", - " (u, v) for u, v in graph.edges if u in solution_nodes and v in solution_nodes\n", - "]\n", - "nx.draw_kamada_kawai(graph, with_labels=True)\n", - "nx.draw_kamada_kawai(\n", - " graph,\n", - " with_labels=True,\n", - " nodelist=solution_nodes,\n", - " edgelist=solution_edges,\n", - " node_color=\"r\",\n", - " edge_color=\"r\",\n", - ")" + "uniform_result = combi.sample_uniform()" ] }, { @@ -377,12 +414,12 @@ "id": "687f492b-a4a5-49c6-964c-8959b035bb93", "metadata": {}, "source": [ - "And the histogram:" + "And compare the histograms:" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 16, "id": "31a4e74d-b2b8-42e0-826d-de7b51de1fe8", "metadata": { "tags": [] @@ -390,7 +427,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -400,11 +437,23 @@ } ], "source": [ - "import matplotlib.pyplot as plt\n", - "\n", "optimization_result[\"cost\"].plot(\n", - " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + " kind=\"hist\",\n", + " bins=40,\n", + " edgecolor=\"black\",\n", + " weights=optimization_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"optimized\",\n", ")\n", + "uniform_result[\"cost\"].plot(\n", + " kind=\"hist\",\n", + " bins=40,\n", + " edgecolor=\"black\",\n", + " weights=uniform_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"uniform\",\n", + ")\n", + "plt.legend()\n", "plt.ylabel(\"Probability\", fontsize=16)\n", "plt.xlabel(\"cost\", fontsize=16)\n", "plt.tick_params(axis=\"both\", labelsize=14)" @@ -420,7 +469,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", "metadata": { "tags": [] @@ -429,10 +478,10 @@ { "data": { "text/plain": [ - "{'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4': 0, 'x_5': 1, 'x_6': 0}" + "{'x': [1, 1, 1, 1, 0, 0, 0]}" ] }, - "execution_count": 14, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -442,6 +491,41 @@ "best_solution" ] }, + { + "cell_type": "code", + "execution_count": 13, + "id": "9b868135-e219-441c-8d98-6b43d894a130", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "solution_nodes = [v for v in graph.nodes if best_solution[\"x\"][v]]\n", + "solution_edges = [\n", + " (u, v) for u, v in graph.edges if u in solution_nodes and v in solution_nodes\n", + "]\n", + "nx.draw_kamada_kawai(graph, with_labels=True)\n", + "nx.draw_kamada_kawai(\n", + " graph,\n", + " with_labels=True,\n", + " nodelist=solution_nodes,\n", + " edgelist=solution_edges,\n", + " node_color=\"r\",\n", + " edge_color=\"r\",\n", + ")" + ] + }, { "cell_type": "markdown", "id": "149932e1-bfa8-4c27-b5f9-037e74eba400", @@ -460,7 +544,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { "pycharm": { @@ -490,7 +574,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "id": "79666d4d-e105-4706-b44e-e5c73b928af3", "metadata": { "tags": [] @@ -534,7 +618,6 @@ "tags": [] }, "source": [ - "\n", "## References\n", "\n", "[1]: [Farhi, Edward, Jeffrey Goldstone, and Sam Gutmann. \"A quantum approximate optimization algorithm.\" arXiv preprint arXiv:1411.4028 (2014).](https://arxiv.org/abs/1411.4028)\n", diff --git a/applications/optimization/max_clique/max_clique.qmod b/applications/optimization/max_clique/max_clique.qmod index f2779147b..bceade30c 100644 --- a/applications/optimization/max_clique/max_clique.qmod +++ b/applications/optimization/max_clique/max_clique.qmod @@ -1,22 +1,16 @@ qstruct QAOAVars { - x_0: qbit; - x_1: qbit; - x_2: qbit; - x_3: qbit; - x_4: qbit; - x_5: qbit; - x_6: qbit; + x: qbit[7]; } -qfunc main(params: real[40], output v: QAOAVars) { +qfunc main(params: real[6], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); - repeat (i: 20) { - phase (-((((((((-v.x_0) - v.x_1) - v.x_2) - v.x_3) - v.x_4) - v.x_5) - v.x_6) + (2 * ((((((((2 * v.x_0) * v.x_5) + (v.x_1 * v.x_4)) + (v.x_2 * (v.x_4 + v.x_6))) + (v.x_3 * v.x_6)) + (v.x_4 * ((v.x_1 + v.x_2) + v.x_6))) + (v.x_6 * ((v.x_2 + v.x_3) + v.x_4))) ** 2))), params[i]); + repeat (i: 3) { + phase (-((((((((-v.x[0]) - v.x[1]) - v.x[2]) - v.x[3]) - v.x[4]) - v.x[5]) - v.x[6]) + (2 * ((((((((2 * v.x[0]) * v.x[5]) + (v.x[1] * v.x[4])) + (v.x[2] * (v.x[4] + v.x[6]))) + (v.x[3] * v.x[6])) + (v.x[4] * ((v.x[1] + v.x[2]) + v.x[6]))) + (v.x[6] * ((v.x[2] + v.x[3]) + v.x[4]))) ** 2))), params[i]); apply_to_all(lambda(q) { - RX(params[20 + i], q); + RX(params[3 + i], q); }, v); } } diff --git a/applications/optimization/max_clique/max_clique.synthesis_options.json b/applications/optimization/max_clique/max_clique.synthesis_options.json index bcb7020f0..bbb495713 100644 --- a/applications/optimization/max_clique/max_clique.synthesis_options.json +++ b/applications/optimization/max_clique/max_clique.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ + "r", + "id", + "u", + "cx", "sx", + "h", "y", - "cy", - "t", - "sdg", - "p", - "cz", + "u1", "s", - "id", - "u", - "r", - "rz", + "u2", "ry", + "rz", + "p", + "t", + "cz", "rx", - "u2", - "u1", - "cx", + "sdg", + "cy", + "x", "tdg", "sxdg", - "h", - "z", - "x" + "z" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 264602322 + "random_seed": 4176492311 } } diff --git a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.ipynb b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.ipynb index a299238ad..6ec67e78c 100644 --- a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.ipynb +++ b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.ipynb @@ -42,7 +42,7 @@ "\n", "# Solving with the Classiq platform\n", "\n", - "We go through the steps of solving the problem with the Classiq platform, using QAOA algorithm [[2](#QAOA)]. The solution is based on defining a pyomo model for the optimization problem we would like to solve." + "We go through the steps of solving the problem with the Classiq platform, using QAOA algorithm [[2](#QAOA)]. The solution is based on defining a Pyomo model for the optimization problem we would like to solve." ] }, { @@ -68,7 +68,7 @@ "source": [ "## Building the Pyomo model from a graph input\n", "\n", - "We proceed by defining the pyomo model that will be used on the Classiq platform, using the mathematical formulation defined above:" + "We proceed by defining the Pyomo model that will be used on the Classiq platform, using the mathematical formulation defined above:" ] }, { @@ -193,7 +193,7 @@ "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the qaoa algorithm, with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` python class. Under the hood it tranlates the Pyomo model to a quantum model of the QAOA algorithm, with cost hamiltonian translated from the Pyomo model. We can choose the number of layers for the QAOA ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { @@ -235,7 +235,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "69d7c8ac-29c6-42b7-9111-fcf88a4e816a", "metadata": { "pycharm": { @@ -248,7 +248,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Opening: https://nightly.platform.classiq.io/circuit/9e9127b4-7c66-4b81-b66c-57745580a2ec?version=0.61.0.dev8\n" + "Opening: https://nightly.platform.classiq.io/circuit/6cb47285-352a-47be-8371-154272108ce1?version=0.62.0.dev9\n" ] } ], @@ -267,7 +267,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "c052e252-745c-4b93-8df7-992d3c5d3277", "metadata": {}, "outputs": [], @@ -289,17 +289,22 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 10, "id": "066869ce-6c80-4e8a-9943-77ceabe74388", "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Optimization Progress: 77%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊ | 69/90 [04:58<01:30, 4.32s/it]\n" + ] + } + ], "source": [ - "cost_values = []\n", - "optimized_params = combi.optimize(\n", - " execution_preferences, maxiter=90, cost_trace=cost_values, quantile=0.7\n", - ")" + "optimized_params = combi.optimize(execution_preferences, maxiter=90, quantile=0.7)" ] }, { @@ -312,7 +317,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 11, "id": "be6bc7ec-c1f8-4925-be2b-0dceb20d73cc", "metadata": { "tags": [] @@ -324,13 +329,13 @@ "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 23, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -342,11 +347,10 @@ "source": [ "import matplotlib.pyplot as plt\n", "\n", - "fig, axes = plt.subplots(nrows=1, ncols=1)\n", - "axes.plot(cost_values)\n", - "axes.set_xlabel(\"Iterations\")\n", - "axes.set_ylabel(\"Cost\")\n", - "axes.set_title(\"Cost convergence\")" + "plt.plot(combi.cost_trace)\n", + "plt.xlabel(\"Iterations\")\n", + "plt.ylabel(\"Cost\")\n", + "plt.title(\"Cost convergence\")" ] }, { @@ -364,12 +368,12 @@ "id": "0e49c243-8621-4893-9033-ddb45087f30d", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm. In order to get samples with the optimized parameters, we call the `get_results` method:" + "We can also examine the statistics of the algorithm. In order to get samples with the optimized parameters, we call the `sample` method:" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 13, "id": "778d3344-c84e-47cd-89b6-55d1df980813", "metadata": {}, "outputs": [ @@ -401,33 +405,33 @@ " \n", " \n", " \n", - " 128\n", - " {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'...\n", - " 0.002441\n", - " 2.0\n", + " 289\n", + " {'x': [1, 1, 0, 0, 1, 0, 1, 0, 1, 0]}\n", + " 0.000977\n", + " 1.0\n", " \n", " \n", - " 335\n", - " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'...\n", + " 399\n", + " {'x': [1, 1, 0, 1, 1, 0, 0, 0, 1, 0]}\n", " 0.000977\n", - " 2.0\n", + " 1.0\n", " \n", " \n", - " 204\n", - " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'...\n", - " 0.001953\n", + " 665\n", + " {'x': [1, 1, 0, 1, 1, 1, 0, 0, 0, 0]}\n", + " 0.000488\n", " 2.0\n", " \n", " \n", - " 191\n", - " {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", - " 0.001953\n", + " 325\n", + " {'x': [1, 0, 1, 0, 1, 0, 1, 0, 1, 0]}\n", + " 0.000977\n", " 2.0\n", " \n", " \n", - " 116\n", - " {'x_0': 1, 'x_1': 0, 'x_2': 1, 'x_3': 0, 'x_4'...\n", - " 0.002441\n", + " 436\n", + " {'x': [1, 1, 1, 0, 0, 0, 1, 0, 1, 0]}\n", + " 0.000977\n", " 2.0\n", " \n", " \n", @@ -435,43 +439,61 @@ "" ], "text/plain": [ - " solution probability cost\n", - "128 {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'... 0.002441 2.0\n", - "335 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'... 0.000977 2.0\n", - "204 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'... 0.001953 2.0\n", - "191 {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.001953 2.0\n", - "116 {'x_0': 1, 'x_1': 0, 'x_2': 1, 'x_3': 0, 'x_4'... 0.002441 2.0" + " solution probability cost\n", + "289 {'x': [1, 1, 0, 0, 1, 0, 1, 0, 1, 0]} 0.000977 1.0\n", + "399 {'x': [1, 1, 0, 1, 1, 0, 0, 0, 1, 0]} 0.000977 1.0\n", + "665 {'x': [1, 1, 0, 1, 1, 1, 0, 0, 0, 0]} 0.000488 2.0\n", + "325 {'x': [1, 0, 1, 0, 1, 0, 1, 0, 1, 0]} 0.000977 2.0\n", + "436 {'x': [1, 1, 1, 0, 0, 0, 1, 0, 1, 0]} 0.000977 2.0" ] }, - "execution_count": 24, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "optimization_result = combi.get_results()\n", + "optimization_result = combi.sample(optimized_params)\n", "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { "cell_type": "markdown", - "id": "ea88e99f-300d-4a18-b122-d0f2b31080a8", + "id": "b97b9f81-4d6d-4f65-947f-a8465643f442", "metadata": {}, "source": [ - "And the histogram:" + "We will also want to compare the optimized results to uniformly sampled results:" ] }, { "cell_type": "code", - "execution_count": 25, - "id": "26f85e77-a110-4e9c-a8ac-3354eae3c8da", + "execution_count": 14, + "id": "98d47d34-e05b-43c7-8f3d-bd407fe81342", + "metadata": {}, + "outputs": [], + "source": [ + "uniform_result = combi.sample_uniform()" + ] + }, + { + "cell_type": "markdown", + "id": "655de6d1-0a33-4b2b-ab35-053684a4a6d0", + "metadata": {}, + "source": [ + "And compare the histograms:" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "cb86cd46-9c67-4a2d-9acd-5bf90921e9db", "metadata": { "tags": [] }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -482,8 +504,22 @@ ], "source": [ "optimization_result[\"cost\"].plot(\n", - " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + " kind=\"hist\",\n", + " bins=40,\n", + " edgecolor=\"black\",\n", + " weights=optimization_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"optimized\",\n", ")\n", + "uniform_result[\"cost\"].plot(\n", + " kind=\"hist\",\n", + " bins=40,\n", + " edgecolor=\"black\",\n", + " weights=uniform_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"uniform\",\n", + ")\n", + "plt.legend()\n", "plt.ylabel(\"Probability\", fontsize=16)\n", "plt.xlabel(\"cost\", fontsize=16)\n", "plt.tick_params(axis=\"both\", labelsize=14)" @@ -499,47 +535,37 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 16, "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", "metadata": { "tags": [] }, - "outputs": [], - "source": [ - "best_solution = optimization_result.solution[optimization_result.cost.idxmin()]\n", - "best_solution = [best_solution[f\"x_{v}\"] for v in range(len(best_solution))]" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "2449caf6-d3c2-49b1-81cd-0e33e248cc18", - "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[1, 1, 1, 0, 0, 0, 1, 0, 1, 0]" + "[1, 1, 0, 0, 1, 0, 1, 0, 1, 0]" ] }, - "execution_count": 27, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "best_solution = optimization_result.solution[optimization_result.cost.idxmin()][\"x\"]\n", "best_solution" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 17, "id": "fed415f4-67ed-4a85-9138-553c75972ac8", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -585,7 +611,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 18, "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { "pycharm": { @@ -604,7 +630,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 19, "id": "1894641b-b166-47da-a3b8-5851d9042054", "metadata": {}, "outputs": [ @@ -614,7 +640,7 @@ "[1, 1, 0, 1, 1, 0, 0, 0, 1, 0]" ] }, - "execution_count": 30, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -625,7 +651,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 20, "id": "a7524894-b5c5-42d4-8f92-a019bef5e7da", "metadata": { "tags": [] diff --git a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod index 405b870cb..dcd187633 100644 --- a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod +++ b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod @@ -1,14 +1,5 @@ qstruct QAOAVars { - x_0: qbit; - x_1: qbit; - x_2: qbit; - x_3: qbit; - x_4: qbit; - x_5: qbit; - x_6: qbit; - x_7: qbit; - x_8: qbit; - x_9: qbit; + x: qbit[10]; } @@ -17,7 +8,7 @@ qfunc main(params: real[6], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); repeat (i: 3) { - phase (-(((((((((((((((((((((((1 - v.x_0) * (1 - v.x_1)) + ((1 - v.x_0) * (1 - v.x_5))) + ((1 - v.x_0) * (1 - v.x_6))) + ((1 - v.x_0) * (1 - v.x_7))) + ((1 - v.x_0) * (1 - v.x_8))) + ((1 - v.x_1) * (1 - v.x_2))) + ((1 - v.x_1) * (1 - v.x_4))) + ((1 - v.x_1) * (1 - v.x_5))) + ((1 - v.x_1) * (1 - v.x_6))) + ((1 - v.x_1) * (1 - v.x_9))) + ((1 - v.x_2) * (1 - v.x_3))) + ((1 - v.x_2) * (1 - v.x_4))) + ((1 - v.x_3) * (1 - v.x_6))) + ((1 - v.x_3) * (1 - v.x_8))) + ((1 - v.x_4) * (1 - v.x_6))) + ((1 - v.x_4) * (1 - v.x_7))) + ((1 - v.x_4) * (1 - v.x_8))) + ((1 - v.x_4) * (1 - v.x_9))) + ((1 - v.x_5) * (1 - v.x_6))) + ((1 - v.x_7) * (1 - v.x_8))) + ((1 - v.x_8) * (1 - v.x_9))) + (20 * (((((((((((v.x_0 + v.x_1) + v.x_2) + v.x_3) + v.x_4) + v.x_5) + v.x_6) + v.x_7) + v.x_8) + v.x_9) - 5) ** 2))), params[i]); + phase (-(((((((((((((((((((((((1 - v.x[0]) * (1 - v.x[1])) + ((1 - v.x[0]) * (1 - v.x[5]))) + ((1 - v.x[0]) * (1 - v.x[6]))) + ((1 - v.x[0]) * (1 - v.x[7]))) + ((1 - v.x[0]) * (1 - v.x[8]))) + ((1 - v.x[1]) * (1 - v.x[2]))) + ((1 - v.x[1]) * (1 - v.x[4]))) + ((1 - v.x[1]) * (1 - v.x[5]))) + ((1 - v.x[1]) * (1 - v.x[6]))) + ((1 - v.x[1]) * (1 - v.x[9]))) + ((1 - v.x[2]) * (1 - v.x[3]))) + ((1 - v.x[2]) * (1 - v.x[4]))) + ((1 - v.x[3]) * (1 - v.x[6]))) + ((1 - v.x[3]) * (1 - v.x[8]))) + ((1 - v.x[4]) * (1 - v.x[6]))) + ((1 - v.x[4]) * (1 - v.x[7]))) + ((1 - v.x[4]) * (1 - v.x[8]))) + ((1 - v.x[4]) * (1 - v.x[9]))) + ((1 - v.x[5]) * (1 - v.x[6]))) + ((1 - v.x[7]) * (1 - v.x[8]))) + ((1 - v.x[8]) * (1 - v.x[9]))) + (20 * (((((((((((v.x[0] + v.x[1]) + v.x[2]) + v.x[3]) + v.x[4]) + v.x[5]) + v.x[6]) + v.x[7]) + v.x[8]) + v.x[9]) - 5) ** 2))), params[i]); apply_to_all(lambda(q) { RX(params[3 + i], q); }, v); diff --git a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json index 2d6c6696b..2d889877c 100644 --- a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json +++ b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "u", - "s", - "r", - "rx", - "cy", - "sdg", + "id", "z", - "ry", - "rz", "sx", - "cz", - "h", - "cx", + "sdg", + "s", "x", - "sxdg", - "tdg", "t", - "p", "y", - "u2", "u1", - "id" + "cx", + "h", + "sxdg", + "cz", + "cy", + "p", + "r", + "rz", + "ry", + "tdg", + "rx", + "u2", + "u" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 2694895972 + "random_seed": 3857045423 } } diff --git a/applications/optimization/set_partition/set_partition.ipynb b/applications/optimization/set_partition/set_partition.ipynb index e5c00499d..2e8d0247c 100644 --- a/applications/optimization/set_partition/set_partition.ipynb +++ b/applications/optimization/set_partition/set_partition.ipynb @@ -51,7 +51,7 @@ "source": [ "## Building the Pyomo model from a graph input\n", "\n", - "We proceed by defining the pyomo model that will be used on the Classiq platform, using the mathematical formulation defined above:" + "We proceed by defining the Pyomo model that will be used on the Classiq platform, using the mathematical formulation defined above:" ] }, { @@ -64,8 +64,6 @@ "outputs": [], "source": [ "# we define a matrix which gets a set of integers s and returns a pyomo model for the partitioning problem\n", - "\n", - "\n", "def partite(s) -> pyo.ConcreteModel:\n", " model = pyo.ConcreteModel()\n", " SetSize = len(s) # the set size\n", @@ -94,7 +92,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "This is my list: [3, 10, 5, 5, 9, 6, 1, 4, 7, 1]\n" + "This is my list: [8, 8, 8, 5, 5, 6, 5, 6, 8, 11]\n" ] } ], @@ -140,7 +138,7 @@ "1 Objective Declarations\n", " cost : Size=1, Index=None, Active=True\n", " Key : Active : Sense : Expression\n", - " None : True : minimize : ((2*x[0] - 1)*3 + (2*x[1] - 1)*10 + (2*x[2] - 1)*5 + (2*x[3] - 1)*5 + (2*x[4] - 1)*9 + (2*x[5] - 1)*6 + 2*x[6] - 1 + (2*x[7] - 1)*4 + (2*x[8] - 1)*7 + 2*x[9] - 1)**2\n", + " None : True : minimize : ((2*x[0] - 1)*8 + (2*x[1] - 1)*8 + (2*x[2] - 1)*8 + (2*x[3] - 1)*5 + (2*x[4] - 1)*5 + (2*x[5] - 1)*6 + (2*x[6] - 1)*5 + (2*x[7] - 1)*6 + (2*x[8] - 1)*8 + (2*x[9] - 1)*11)**2\n", "\n", "3 Declarations: x_index x cost\n" ] @@ -159,7 +157,7 @@ "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the qaoa algorithm, with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` python class. Under the hood it tranlates the Pyomo model to a quantum model of the QAOA algorithm, with cost hamiltonian translated from the Pyomo model. We can choose the number of layers for the QAOA ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { @@ -217,7 +215,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Opening: https://nightly.platform.classiq.io/circuit/6d0b5153-963f-45d5-84a0-ea52307aa923?version=0.61.0.dev7\n" + "Opening: https://nightly.platform.classiq.io/circuit/aec5c205-9edc-4e25-9812-ce23575c5542?version=0.62.0.dev9\n" ] } ], @@ -258,17 +256,22 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 31, "id": "5dcfa7ce-09e6-41ac-be81-298a281ba051", "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Optimization Progress: 70%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌ | 56/80 [02:08<00:55, 2.29s/it]\n" + ] + } + ], "source": [ - "cost_values = []\n", - "optimized_params = combi.optimize(\n", - " execution_preferences, maxiter=60, cost_trace=cost_values, quantile=0.7\n", - ")" + "optimized_params = combi.optimize(execution_preferences, maxiter=80, quantile=0.7)" ] }, { @@ -281,7 +284,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 32, "id": "6542ba4a-9493-4b01-8eea-8202d70b1f2c", "metadata": { "tags": [] @@ -293,13 +296,13 @@ "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 10, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -309,13 +312,10 @@ } ], "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "fig, axes = plt.subplots(nrows=1, ncols=1)\n", - "axes.plot(cost_values)\n", - "axes.set_xlabel(\"Iterations\")\n", - "axes.set_ylabel(\"Cost\")\n", - "axes.set_title(\"Cost convergence\")" + "plt.plot(combi.cost_trace)\n", + "plt.xlabel(\"Iterations\")\n", + "plt.ylabel(\"Cost\")\n", + "plt.title(\"Cost convergence\")" ] }, { @@ -333,14 +333,16 @@ "id": "96ea8543-29cb-4570-8741-7199dea8a948", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm. In order to get samples with the optimized parameters, we call the `get_results` method:" + "We can also examine the statistics of the algorithm. In order to get samples with the optimized parameters, we call the `sample` method:" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 33, "id": "bbc7c2ca-1d3a-4342-9a37-5b8fc8980fbe", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { @@ -370,77 +372,95 @@ " \n", " \n", " \n", - " 0\n", - " {'x_0': 0, 'x_1': 0, 'x_2': 1, 'x_3': 1, 'x_4'...\n", - " 0.019043\n", - " 1.0\n", + " 139\n", + " {'x': [0, 0, 1, 1, 1, 1, 1, 1, 0, 0]}\n", + " 0.001953\n", + " 1.183052e-271\n", " \n", " \n", - " 281\n", - " {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'...\n", + " 278\n", + " {'x': [1, 1, 0, 0, 0, 0, 1, 1, 1, 0]}\n", " 0.000977\n", - " 1.0\n", + " 1.183052e-271\n", " \n", " \n", - " 59\n", - " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", - " 0.004395\n", - " 1.0\n", + " 545\n", + " {'x': [1, 0, 1, 0, 0, 0, 0, 0, 1, 1]}\n", + " 0.000488\n", + " 1.183052e-271\n", " \n", " \n", - " 282\n", - " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'...\n", - " 0.000977\n", - " 1.0\n", + " 515\n", + " {'x': [0, 0, 1, 0, 1, 0, 1, 1, 0, 1]}\n", + " 0.000488\n", + " 1.183052e-271\n", " \n", " \n", - " 284\n", - " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", - " 0.000977\n", - " 1.0\n", + " 438\n", + " {'x': [0, 0, 0, 1, 1, 1, 0, 0, 1, 1]}\n", + " 0.000488\n", + " 1.183052e-271\n", " \n", " \n", "\n", "" ], "text/plain": [ - " solution probability cost\n", - "0 {'x_0': 0, 'x_1': 0, 'x_2': 1, 'x_3': 1, 'x_4'... 0.019043 1.0\n", - "281 {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 0, 'x_4'... 0.000977 1.0\n", - "59 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.004395 1.0\n", - "282 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'... 0.000977 1.0\n", - "284 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.000977 1.0" + " solution probability cost\n", + "139 {'x': [0, 0, 1, 1, 1, 1, 1, 1, 0, 0]} 0.001953 1.183052e-271\n", + "278 {'x': [1, 1, 0, 0, 0, 0, 1, 1, 1, 0]} 0.000977 1.183052e-271\n", + "545 {'x': [1, 0, 1, 0, 0, 0, 0, 0, 1, 1]} 0.000488 1.183052e-271\n", + "515 {'x': [0, 0, 1, 0, 1, 0, 1, 1, 0, 1]} 0.000488 1.183052e-271\n", + "438 {'x': [0, 0, 0, 1, 1, 1, 0, 0, 1, 1]} 0.000488 1.183052e-271" ] }, - "execution_count": 11, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "optimization_result = combi.get_results()\n", + "optimization_result = combi.sample(optimized_params)\n", "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { "cell_type": "markdown", - "id": "2a6d978a-f2a2-46a0-8deb-bdfa6c9c3405", + "id": "a55201b4-31b1-4477-a9fd-06a35352f0a1", + "metadata": {}, + "source": [ + "We will also want to compare the optimized results to uniformly sampled results:" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "acc7cbeb-b7a8-41a4-8922-0280d29b58af", + "metadata": {}, + "outputs": [], + "source": [ + "uniform_result = combi.sample_uniform()" + ] + }, + { + "cell_type": "markdown", + "id": "ccca8f9a-b252-4aeb-a92f-96deb4109d87", "metadata": {}, "source": [ - "And the histogram:" + "And compare the histograms:" ] }, { "cell_type": "code", - "execution_count": 12, - "id": "85fdf055-cb4e-4756-8983-3a607cc22382", + "execution_count": 35, + "id": "8b0f949c-015a-4bbe-8bc1-8feb0e6c4480", "metadata": { "tags": [] }, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -451,8 +471,22 @@ ], "source": [ "optimization_result[\"cost\"].plot(\n", - " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + " kind=\"hist\",\n", + " bins=50,\n", + " edgecolor=\"black\",\n", + " weights=optimization_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"optimized\",\n", ")\n", + "uniform_result[\"cost\"].plot(\n", + " kind=\"hist\",\n", + " bins=50,\n", + " edgecolor=\"black\",\n", + " weights=uniform_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"uniform\",\n", + ")\n", + "plt.legend()\n", "plt.ylabel(\"Probability\", fontsize=16)\n", "plt.xlabel(\"cost\", fontsize=16)\n", "plt.tick_params(axis=\"both\", labelsize=14)" @@ -468,7 +502,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 36, "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", "metadata": { "tags": [] @@ -480,7 +514,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 37, "id": "f349d9fb-132e-4ca0-8433-db1e2d61efa1", "metadata": { "tags": [] @@ -490,15 +524,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "P1= [3, 10, 6, 7] , total sum: 26\n", - "P2= [5, 5, 9, 1, 4, 1] , total sum: 25\n", - "difference= 1\n" + "P1= [5, 6, 5, 8, 11] , total sum: 35\n", + "P2= [8, 8, 8, 5, 6] , total sum: 35\n", + "difference= 0\n" ] } ], "source": [ - "p1 = [mylist[i] for i in range(len(mylist)) if best_solution[f\"x_{i}\"] == 0]\n", - "p2 = [mylist[i] for i in range(len(mylist)) if best_solution[f\"x_{i}\"] == 1]\n", + "p1 = [mylist[i] for i in range(len(mylist)) if best_solution[\"x\"][i] == 0]\n", + "p2 = [mylist[i] for i in range(len(mylist)) if best_solution[\"x\"][i] == 1]\n", "print(\"P1=\", p1, \", total sum: \", sum(p1))\n", "print(\"P2=\", p2, \", total sum: \", sum(p2))\n", "print(\"difference= \", abs(sum(p1) - sum(p2)))" @@ -514,7 +548,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 38, "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { "pycharm": { @@ -532,21 +566,21 @@ " Variables:\n", " x : Size=10, Index=x_index\n", " Key : Lower : Value : Upper : Fixed : Stale : Domain\n", - " 0 : 0 : 1.0 : 1 : False : False : Binary\n", - " 1 : 0 : 1.0 : 1 : False : False : Binary\n", + " 0 : 0 : 0.0 : 1 : False : False : Binary\n", + " 1 : 0 : 0.0 : 1 : False : False : Binary\n", " 2 : 0 : 0.0 : 1 : False : False : Binary\n", " 3 : 0 : 1.0 : 1 : False : False : Binary\n", - " 4 : 0 : 0.0 : 1 : False : False : Binary\n", - " 5 : 0 : 0.0 : 1 : False : False : Binary\n", - " 6 : 0 : 0.0 : 1 : False : False : Binary\n", - " 7 : 0 : 0.0 : 1 : False : False : Binary\n", + " 4 : 0 : 1.0 : 1 : False : False : Binary\n", + " 5 : 0 : 1.0 : 1 : False : False : Binary\n", + " 6 : 0 : 1.0 : 1 : False : False : Binary\n", + " 7 : 0 : 1.0 : 1 : False : False : Binary\n", " 8 : 0 : 1.0 : 1 : False : False : Binary\n", - " 9 : 0 : 1.0 : 1 : False : False : Binary\n", + " 9 : 0 : 0.0 : 1 : False : False : Binary\n", "\n", " Objectives:\n", " cost : Size=1, Index=None, Active=True\n", " Key : Active : Value\n", - " None : True : 1.0\n", + " None : True : 0.0\n", "\n", " Constraints:\n", " None\n" @@ -564,19 +598,7 @@ }, { "cell_type": "code", - "execution_count": 16, - "id": "2e5c1b07-6060-455d-81ed-e48a2207c81b", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "classical_solution = [pyo.value(set_partition_model.x[i]) for i in range(len(mylist))]" - ] - }, - { - "cell_type": "code", - "execution_count": 17, + "execution_count": 28, "id": "a7524894-b5c5-42d4-8f92-a019bef5e7da", "metadata": { "tags": [] @@ -586,15 +608,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "P1= [5, 9, 6, 1, 4] , total sum: 25\n", - "P2= [3, 10, 5, 7, 1] , total sum: 26\n", - "difference= 1\n" + "P1= [8, 8, 8, 11] , total sum: 35\n", + "P2= [5, 5, 6, 5, 6, 8] , total sum: 35\n", + "difference= 0\n" ] } ], "source": [ - "p1 = [mylist[i] for i in range(len(mylist)) if classical_solution[i] == 0]\n", - "p2 = [mylist[i] for i in range(len(mylist)) if classical_solution[i] == 1]\n", + "p1 = [mylist[i] for i in range(len(mylist)) if round(classical_solution[i]) == 0]\n", + "p2 = [mylist[i] for i in range(len(mylist)) if round(classical_solution[i]) == 1]\n", "print(\"P1=\", p1, \", total sum: \", sum(p1))\n", "print(\"P2=\", p2, \", total sum: \", sum(p2))\n", "print(\"difference= \", abs(sum(p1) - sum(p2)))" diff --git a/applications/optimization/set_partition/set_partition.qmod b/applications/optimization/set_partition/set_partition.qmod index 2b37221c3..703f5e6db 100644 --- a/applications/optimization/set_partition/set_partition.qmod +++ b/applications/optimization/set_partition/set_partition.qmod @@ -1,14 +1,5 @@ qstruct QAOAVars { - x_0: qbit; - x_1: qbit; - x_2: qbit; - x_3: qbit; - x_4: qbit; - x_5: qbit; - x_6: qbit; - x_7: qbit; - x_8: qbit; - x_9: qbit; + x: qbit[10]; } @@ -17,7 +8,7 @@ qfunc main(params: real[6], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); repeat (i: 3) { - phase (-((((((((((((6 * v.x_0) + (20 * v.x_1)) + (10 * v.x_2)) + (10 * v.x_3)) + (18 * v.x_4)) + (12 * v.x_5)) + (2 * v.x_6)) + (8 * v.x_7)) + (14 * v.x_8)) + (2 * v.x_9)) - 51) ** 2), params[i]); + phase (-((((((((((((16 * v.x[0]) + (16 * v.x[1])) + (16 * v.x[2])) + (10 * v.x[3])) + (10 * v.x[4])) + (12 * v.x[5])) + (10 * v.x[6])) + (12 * v.x[7])) + (16 * v.x[8])) + (22 * v.x[9])) - 70) ** 2), params[i]); apply_to_all(lambda(q) { RX(params[3 + i], q); }, v); diff --git a/applications/optimization/set_partition/set_partition.synthesis_options.json b/applications/optimization/set_partition/set_partition.synthesis_options.json index df25d261f..ac5cce353 100644 --- a/applications/optimization/set_partition/set_partition.synthesis_options.json +++ b/applications/optimization/set_partition/set_partition.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "cz", + "u", + "u1", + "cx", "x", "u2", - "ry", - "rz", + "sdg", "s", "r", - "z", - "u", - "t", - "u1", + "cz", "id", + "cy", "sxdg", - "sdg", - "h", - "sx", + "ry", "rx", - "tdg", + "rz", "y", + "sx", + "tdg", + "t", + "z", "p", - "cx", - "cy" + "h" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 2863520222 + "random_seed": 1468870560 } } diff --git a/applications/physical_systems/ising_model/ising_model.ipynb b/applications/physical_systems/ising_model/ising_model.ipynb index cdd184f07..1aa183609 100644 --- a/applications/physical_systems/ising_model/ising_model.ipynb +++ b/applications/physical_systems/ising_model/ising_model.ipynb @@ -44,7 +44,7 @@ "source": [ "## 1. Define the Optimization Problem\n", "\n", - "We created a python pyomo model to describe an Ising model as optimization problem over the configuration of spins. We take a simple manifestation of the 1d Ising model, described as [6]:\n", + "We created a python Pyomo model to describe an Ising model as optimization problem over the configuration of spins. We take a simple manifestation of the 1d Ising model, described as [6]:\n", "\n", "$H(\\sigma) = -\\sum\\limits _{i,j}J\\sigma_{i}\\sigma_{j}-\\sum\\limits _{i} h\\sigma_{i}$\n", "\n", @@ -123,7 +123,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "b2c6406f-8aa3-4674-870e-13b5a36b50dc", "metadata": {}, "outputs": [], @@ -147,7 +147,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 5, "id": "0b28f2dc-26ec-4975-9e1f-41adfdd75cb4", "metadata": { "pycharm": { @@ -160,7 +160,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Opening: https://nightly.platform.classiq.io/circuit/0b452fbf-fc23-4a09-b800-6ad828f47e96?version=0.61.0.dev7\n" + "Opening: https://nightly.platform.classiq.io/circuit/40d4cb3e-8ee4-4b6e-be8b-bd120647f993?version=0.62.0.dev9\n" ] } ], @@ -179,7 +179,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 6, "id": "4f779a6a-dae4-4235-92be-f90820fbfbeb", "metadata": { "tags": [] @@ -203,27 +203,22 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 8, "id": "6daf89c6-2e5c-41b5-b162-dfd048014919", "metadata": { "tags": [] }, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "CPU times: user 8.15 s, sys: 211 ms, total: 8.36 s\n", - "Wall time: 2min 39s\n" + "Optimization Progress: 101it [03:14, 1.92s/it] \n" ] } ], "source": [ - "%%time\n", - "cost_values = []\n", - "optimized_params = combi.optimize(\n", - " execution_preferences, maxiter=100, cost_trace=cost_values, quantile=0.7\n", - ")" + "optimized_params = combi.optimize(execution_preferences, maxiter=100, quantile=0.7)" ] }, { @@ -236,7 +231,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 9, "id": "370e71c6-764e-4296-882a-d5daa14d3176", "metadata": { "tags": [] @@ -248,13 +243,13 @@ "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 17, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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REREpMDgiIiIiUmBwRFnJ4fbA45UyfRlERNQNMTiirGN3eXDsQ1/gFy8sz/SlEBFRN2TM9AUQpVttix37W+w40O7M9KUQEVE3xMwRZR231+v7r8eb4SshIqLuiMERZR2Xx9dr5JXAviMiIgrB4IiyjtsTCIhczB4REZEKgyPKOi5vICByM3NEREQqDI4o6wRljtzMHBERUTAGR5R1lI3YyiwSERER0MuCo3vuuQc6nS7o1+jRo+WP2+12zJ07F3379kVBQQHOPPNM1NXVZfCKKRNcilKaMotEREQE9LLgCADGjRuH/fv3y7+WLl0qf+zmm2/GBx98gLfffhtLlizBvn37cMYZZ2TwaikTlKU0NmQTEZFar1sCaTQaUVlZGXJ7S0sL/vrXv+K1117D8ccfDwB46aWXMGbMGCxfvhyHH354ui+VMsTtVQZHzBwREVGwXpc52rp1K/r374+hQ4fi/PPPR01NDQBg1apVcLlcmDVrlnzf0aNHY9CgQVi2bFnYx3M4HLDZbEG/qGdTBkRu9hwREZFKrwqOpk+fjpdffhmffvopnn32WezcuRNHH300WltbUVtbC7PZjOLi4qDPqaioQG1tbdjHXLBgAYqKiuRfVVVVKf4qKNWUARF7joiISK1XldVOOukk+f8nTpyI6dOnY/DgwXjrrbeQm5ub0GPeeeeduOWWW+Tf22w2Bkg9nDJz5GTPERERqfSqzJFacXExRo4ciW3btqGyshJOpxPNzc1B96mrq9PsURIsFgusVmvQL+rZlNkiZo6IiEitVwdHbW1t2L59O/r164epU6fCZDJh0aJF8sc3b96MmpoazJgxI4NXSekWXFZj5oiIiIL1qrLar371K5x66qkYPHgw9u3bh3nz5sFgMOC8885DUVERLrvsMtxyyy3o06cPrFYrrr/+esyYMYOTalmGZTUiIoqkVwVHP/74I8477zwcOHAAZWVlOOqoo7B8+XKUlZUBAP70pz9Br9fjzDPPhMPhwJw5c/DMM89k+Kop3ZTZIpbViIhIrVcFR2+88UbEj+fk5ODpp5/G008/naYrou5IedgsR/mJiEitV/ccEWlRbsV2MnNEREQqDI4o6wRPqzFzREREwRgcUdZxcQkkERFFwOCIso6b02pERBQBgyPKOsHTagyOiIgoGIMjyjrOoINnWVYjIqJgDI4o67iDptWYOSIiomAMjijrBO05YkM2ERGpMDiirONizxEREUXA4IiyjjJb5GLPERERqTA4oqyjPDLE5WbmiIiIgjE4oqzj4rQaERFFwOCIsk5Q5og9R0REpMLgiLKOMnPE4IiIiNQYHFHWCd6QzbIaEREFY3BEWUfZZ8RpNSIiUmNwRFknqKzGaTUiIlJhcERZJ6is5mVwREREwRgcUdYJKqux54iIiFQYHFHWcbo5yk9EROExOKKsoyylcVqNiIjUGBxR1gk+W42ZIyIiCsbgiLKOspTGshoREakxOKKso2zIZlmNiIjUGBxR1nHz+BAiIoqAwRFlHWWfkZsbsomISIXBEWUVj1eCpIiHuCGbiIjUGBxRVlGX0Xi2GhERqTE4oqyiLqO52XNEREQqDI4oq6iDIR4fQkREagyOKKuogyFOqxERkRqDI8oqbtVGbE6rERGRGoMjyirqpY8erwRvBgKkLzbXY09TR9qfl4iIomNwRFlFlNF0OsVtaT5fbeWuJlz80re48Y3v0vq8REQUGwZHlFVEz1GuySDflu4jRBZuqAMA1NkcaX1eIiKKDYMjyioic6QMjtLdlP355noAgN3lSevzEhFRbBgcUVYRDdg5QcFR+jJH+5o7saWuDQDQyeCIiKhbYnBEWUXsOTIadDAZfI1H6gm2VPpic4P8/50uDySJ03JERN0NgyPKKiJLZNTrYDL4/vins+dIlNQAQJIAB892IyLqdhgcUVYRWSKTQQ+j3pc5cqap58jp9uLrbY1BtzlcDI6IiLobBkeUVUSWyFdWS2/maOWuJrQ7PSgtMMuBGfuOiIi6HwZHlFXEZJpRr5eDo3RNq4mS2syR5cg1+xrCGRwREXU/DI4orDV7mvHU4q1dDh7W7mnGL15Yjs21rUm6ssSJaTWzQQ+jvyE7XcGRaMY+dlSZvEqg08ngiIiou2FwRGH98eONePi/W7Bs+4EuPc4jC7fg6+0H8O7qH5N0ZYlzBU2r+ctqaTg+5MeDHdha3wa9DjhmRBkzR0RE3RiDIwqrpcMFADjY4ezSY4gm5OYuPE6yBHqOAg3Z6cgciazRlEElKMozyZkjLoIkIup+GBxRWA637427owuln8821smZmWZ/sJVJ8rSaYpQ/HUsglSU1ILCEkmU1IqLuh8ERhWX3j5l3JTj6ZF2t/P/NnZkPjlxB02r+JZApzhw53B58vd2XPTt2VDmAwPElLKsREXU/DI4oLLvIHDncCX1+m8ONL7cGNkK3dIfMkdxzpIcxTZmjb3ceRIfTg7JCC8b1twIAe46IiLoxBkcUluiH6UjwDfzzTfVwur0w+4OQ5s5u0HPkL/H5ymrp6Tn6wj/Cf+zIMuh0vudkzxERUffF4Ig0SZIkl9US7Yv51F9Smz2uAgDQkoKy2hOLtuLoBxejvtUe0/2disxRYFottcHRyt0HAQBHjSiVb2PPERFR98XgiDQpj9RoT6CsZnd55KWH5x02yH+bN+mZkk/X1WJPUye+q2mO6f5iWs1k0Cmm1VJbVhOvX1mhRb4t1+z7q8eyGhFR98PgiDTZFWd+JVJWW7KlAR1ODwYU52LG0L4w+AORZGePxERdrEGXOwMbskWgaTEa5NvYkE1E1H0xOCJNDsWbdiKlH1FSO3F8JfR6HYpyTQCSP84vgrhYgyOXN/1nq4nDZS3GwF83UVazs6xGRNTtMDgiTcrMUbxlNYfbg8821AEAThpfCQAoloOj5DZlO9zx9UWJzJEpjceHiOyWVnDEzBERUffD4Ig0iTF+IP438K+3HUCrw43yQgumDCoBAFhFcJSqspo7tgBH3nOkT9/xISKA0y6rpedct57G7fHig7X7UGeLrdGeiCiZGByRJkcXMkefrNsPAJgzzldSA4DiPF9wlPSeozgn6sRkmm9azZ85ijGwSpQcHJkCf93kPUcsq2n6fHMDrn/9O9z30cZMXwoRZSEGR6QpKHMUxxu42+PFQlVJDQiU1ZK5CNLrleRm59gbsgN7jox6f0N2CjNHbo8XHv/jK8tq3HMUmcgYNbY5MnwlRJSNGByRJuWbdjzTanubO3GwwwWLUY/DqvvItxfnmQEkdxGkQ5HxibkhWwRHxkDPUSqPD1GuRDCz5yhm4vuZjkOBiYjUGByRpqBRfkfsb+Ctdl8JrijXJB/PIX4PJHdazZFAX5RcVtPr5M3dqXwDVpYnzQaW1WIlgiNnikueRERaGByRJmXg4fR4Yw4g2vz9SQU5xqDbRc9RMhuylZmjWBubA0sgldNqqSuriWs06nVBwSLLapGJYNeZ4jULRERaGByRJrsq2OiIMcMhmrcLLcHBUVEKeo7sCexicsnHhwR6jlJ5fIjWGD/AJZDRdDp93xOW1YgoExgckSZ1RiPW4ENkjvIt2pmjZE6rKTNHykxXJIGDZ/VyD5DLnbrshFOeVDME3c7jQyITAwEsqxFRJmRtcPT0009jyJAhyMnJwfTp0/HNN99k+pK6FXVw1OGMbZxf9BwVhGSOkt+Q3fXMkb+sltLMke+xlf1GAA+ejUZsDmfmiIgyISuDozfffBO33HIL5s2bh9WrV2PSpEmYM2cO6uvrM31p3YbDnVhZLWrPUVIbspU9R/GN8hsNerkHKJXHh8hlNZN2Wc3h9sKb4iWUPVEnG7KJKIOyMjh69NFHccUVV+CSSy7B2LFj8dxzzyEvLw8vvvhipi+t23CEZI661nMk9hy12t1JG51XToLFPsrvPz5Er4M5DceHaJ2rBgSm1YDgnVLkE2jIZnBEROmXdcGR0+nEqlWrMGvWLPk2vV6PWbNmYdmyZRm8su5FfRxHvGU1dc+RaMgGAJs9vo3b4SgDInUDeTiBg2cDmaN0TKspjw4BgBzF78OV1t5auQdfbmlI2bV1ZxzlJ6JMyrrgqLGxER6PBxUVFUG3V1RUoLa2NuT+DocDNpst6Fc2CO056lpZzWjQy9mkZB0+m1hZLbTnKLXTatqZI71eJ9+mde37Wzpx+zvf49pXV8sbtrOJWM3AniMiyoSsC47itWDBAhQVFcm/qqqqMn1JaZFwcGTXLqsBgcNnkzWxlkhDduD4EMW0WirLav6SmdkY+ldNlNa0SoIH2nwBZJvDjZ2NbSm7vu5KNGR7JWRlcEhEmZV1wVFpaSkMBgPq6uqCbq+rq0NlZWXI/e+88060tLTIv/bs2ZOuS82o0D1HsZXC2p3amSMg+Ysgg44PcXsgSdHfRF1eZeYonWU1jeBIXgQZGpy1KQ77Xb8vO7KVSso+LJbWiCjdsi44MpvNmDp1KhYtWiTf5vV6sWjRIsyYMSPk/haLBVarNehXNlDvDYo1cyT3HJnDB0fJWgSpzLhIUuiEnZbAhmxdWs5WC9dzBEReBNlmT11w1OF04+H/bMa6vS1JfdxkUmYC2ZRNROmWdcERANxyyy144YUX8Morr2Djxo245ppr0N7ejksuuSTTl9ZtiGxGnr/009WeIwAoFruOUtBzBMQ2sSb3HOn18u4hdwrLNmLqTz3KD0TedRScOUpuELNwQx2e+nwb5n+wPqmPm0zKgJGZIyJKt9B3sCxwzjnnoKGhAXfffTdqa2txyCGH4NNPPw1p0s5mItAoyTOjw9mJDkdsZbVAz5Ep5GNFSS+rBQcVsUysBabVApmjVL75iqyHZlnNHD5z1Koqq0mSBJ1Ol5RrOtjuC07X/tgCh9ujmdXKNOWaBjZlE1G6ZWXmCACuu+467N69Gw6HAytWrMD06dMzfUndihjl75Pvy/Z0xDgN1h4xc5TcRZDqYCiWiTWROTIb9Iqz1VKZOfI/X8Seo8hlteYOF/a12JN2TaL06XR7u2Vpze3xBpXSGBwRUbplbXBEkYlykAiOYpkG83oltDnFnqPQbITYdWRLUeYolmtUbsg2ZbjnKHJZLfg1Wp/EIEZZslu562DSHjdZ1Du2WFYjonRjcESaxJt6ib8U1h5DWa3D5YEYGNMqqyV7Wi2RzJE8rabXwZSWJZD+nqM4y2rtjuDbktmUrVzCuWp39wuO1MEiG7KJKN0YHJEmuedIZI5iCDxEKcig1yFHowG5KOkN2cHXpD7yREtgWk0v9xylds9RpGm18EsgRemrwmoBAGzYn7zgSJk5WrX7YEwrENJJXWZk5oiI0o3BEWkSb1B9/cFRLJkjeVLNYtRsHk7lniMgegAnSZLcX2Q0BDJHqew5Em/sWtNqcs9RhLLaYdV9AQAbkpg5arMHXv8D7U7sOtCRtMdOBnVwlMrMHhGRFgZHpEmUrETmKJZRfmVwpCXZe47UmaJowZEyCDLp9YGyWgozEyKAE2sDlHIilNXEa3lYdR8AwN7mTnnKrKtaVWfbrdzVlJTHTRb168HMERGlG4MjCiFJkryhuG8CZbWwwZEoq3W6klLKCd1zFPlNVFk+U56t5krl2WoR9hzFsgSyf1EOBvXJA5C80poIvMYP8C007W59R+rvI6fViCjdGBxRCJdHkhuri/NEWS2WzJEvI6Q1xu97LF/myOOVgvpeEiXKL6KCFy2AU5ZngspqaTk+JNK0Wuibf6siCzeuvy+ISdYySJE5OnZkOYDuFxyFZI4YHBFRmjE4ohDKc60Co/yx9Bz5Pi9c5ijHZJD3/STj8FkReFhzfEGXVu+OknJk31dW84/ye6WUNSVHnFaLYc9RQY4yOEpO5qjV33M0c1QZAGBrfVvSmuSTIWRajWU1IkozBkcUQpmREdke35h+5ABCNPqGC46A5C6CFAsWxTXG2nOk1wF6vQ5GRR9Qqpp+nTEcPKs9yh/YND6ufxGA5ARHkhTI2g3uk4ehpfkAgNU13Sd7FNqQzeCIiNKLwRGFEEGHxahHnv8AWUmK3tMTrSEbUDRlJyFzJDJcovQX7Ww18SYrgiKROQIAd4r6juSGbI3gSG7IVmVKPF4J7f7b8i0GOXO0o6EtpkWXkXQ4PRB96QU5RkwdXAKgey2D5Cg/EWUagyMKId6cckwGObsB+E5zj6Q1wtEhQuDw2eRljsTm7aiZI7HjyN+IbVJmjtypKqtF2nOknTlqV7zOBTlGlFtzUFpggVcCNtV2LXvUqthFlWsyYNoQf3DUjfqO1K8HM0dElG4MjiiEeEPPMRqCFjpGG+dvjyFzFDh8tus9LnLmyB8cRcscieyQyByJaTUgdRNrcs9RpD1HqusW/UZmg14OqsYmqe9Ibpr376KaOti3KmDtnuZuE4SogyP1VCIRUaoxOKIQdtX4eb6/tBYtOIo2yg+kpudIHHESfZRfbMf2BUU6XWCcP1UTa8oSpVquWXtDdptGBi5ZTdni6JBC/2MPLc1HcZ4JDrc3qUeUdEXoKD+XQBJRejE4ohDizSnHn7UQZ4BFK6tpvamriZ6jrh4+K0mSnJUpyovtcFz50Fl94I99qo8QEWPo8Rw826oRZIrgaEMXx/nVAaxer8PUQaLvqHssg2RDNhFlGoMjChHoOfL98ciTg6PIwYfWm7paUZIyRy6PJDcWF8fYcyRKZyZjoJwWOHw2RWW1SJmjMD1HWo3tYmJtU21r0EqCeLWqMkcAMNXfd9Rd9h1xlJ+IMo3BEYWwy30yvjfvvBjLaqKROFLmSGR5utpzpDx0NuZRfrkhO/DHPpXnqymzW9plNe2eI63ercF98lBgMcLh9mJ7Q3vC1yR6jgr9u6EABDJH3eQQWjZkE1GmMTiiECLbkSMHRzGW1URWIg09R8q+FLEEUn3WmppbHuUPZI7kI0RS8Abs9gayW5Gm1VweKej5lQsgBb1ehzH9CgF0bVO2VnZvUlUxTAYdGlod+PFgZ8KPnSwiWMz3/7ljQzYRpRuDIwphV2U7Yi2riXJQfhr2HCkzMnkRDnBVcnlDe44CZbXkZ0yUb+pa02o5ijUJyuxRa5ipv5EVvuBoRxcyR1pltRyTAWP6+XqaftibnCNKukK8FlZ/IM3MERGlG4MjCmEPyRzFVlaLpecoWXuOHIrN05FOt1cSmSPl8kf5CJEUvAEre2XMhtC/ahajXvNcOK3MERAILMXxH4kI1zQ/otwXeG2rb0v4sZNFvBYiI8ieIyJKNwZHFEJuyFZnjiIcFuvyeOWApTCGabWuZo60FlXGOsqvPDbEmNLMke8aTQYd9IqdSoJOpwtcu+LwWbkvSBVkij4hEYQmQgRWVkXPEQAMLy8A0D2CI/F9tOb6vn5mjogo3RgcUQiHIvAAFJmjCJmZdkXgFKmsZlVMlkVb2hjxGkXmyKSXrzPawbPy8SH69EyrBSbVQvuNBK2JtXDHsIigszVCkBpNuMcWwdHWbhAciWk1EcBxzxERpRuDIwohb8hWjfJH2iMkshkWoz7oWA61QosRIjbpyq6jQHbLEPEAVyWxIVt5fXJZLQUbsh0RDp0VcjSuvTVMWU0ENF0pq2n1HAGB4GhHQxs8KZjci4f43oq1D8luyK632fHSVzuTcr4fEfVODI4ohLwhW7UEsj1CxkJkJCKV1ADf1JW866gLb07KzJEIjtxeKWIGKFBW05pWS11ZLVJwlKsReLaHaWy3JqWspp05qirJhdmoh8Ptxd4MT6x1prgh+/kvd2D+Bxvw9so9SX1cIuo9GBxRiEBDtjg+xN9zFCEzE65co6U4r+tN2Q5FAKecBItUqtPakJ3KsppTDuCil9XsGmW10J4jY9DHEyGyTuqslNGgx9DSfADAtobWhB8/GeRpNf81Jrshu6ndt2PrYEfXz/cjot6JwRGFEKP8IT1HMWSOIi2AFAJbshN/c1KW/sJNfakFymqhPUepOFtNXKPWpJqgVRIMV1ZLRkO2+D6pG7IBYFg3acpOdeZI/Pl2RGngJ6LsxeCIQgQOnlWfrRYhc+R/wxaH1EaSjIk1ZbNzuKkvNe1ptdQtgZTLaho7joQcjS3Z4bJwIlhqtbsS3mQdad3C8LLMB0eSJAWm1cQof7KDI//jc7kkEYXD4IhCyFkZf69MviV6w3OsPUdAYEt2V4KjQHbLd42xNGXLe470yp6jFI7yRzhXTcj1X7/WtJr6tRS/d3mkhN7YPV5JDnC1vk/dYZxf+XWJUf5kl9VEIKo8goaISInBEYUIyRyZfG9SERuyY1gAKSTj8Fn1mHyORu+Omjg/TdmQbTamY1othlF+f9AiSZLitQwufRUosnKJlNaUvUpa5U9lcJSpM9aUjemBUf7kfm865eCImSMi0sbgiELIDdnG2Ef54+o5SsLhs4GJOt815mhkYNTkPUfKsloKM0fOGEb51YfPOtxeOYgTGTtBr9d1aZxffI7ZqNcM2KpL86HXATa7Gw1tjrgfPxnE989sCGw+T1lZjT1HRBRG9HcySju7y4NlOw5g4YY6bNpvQ1WfPAwvK8CIigIMLy9AdWkBDBobl5P5/EAgGyPepGOZVou0AFJIxuGzgYbs4L6oyGU1X9Bh1ug5SsXxIaJsY45jz5Eyu6PVv1WYY0Sbwx02c2R3efDfDXU4ZkSpPBUohJuCU15LVZ887D7QgW11bSgvzAl73akSyFrq5e+Ty53cwNXBshoRRcHgqJto6XDhs411+GxjHb7c0oB2RZZmdU1z0H0Pq+6Dt66akbJrCQ08xLRa9IbscG+8SklpyFbtEMrxZ0IckTJH3tAN2eZUbsiOJXMkl9V891WWJ7WOHCnMMWJ/S/hx/rdX7sFd763HpUdW4+5TxwZ9LNwCSKXhZQW+4KihDUcMLw17v1QRQWKuySAHlcnPHLGsRkSRMTjqJlbsPIBb314r/77SmoNZY8tx6JA+2Ndsx9b6Vmyta8MPe1vwzc4m2F2eoFPdkylwfEjwniOnxwuXx6u5ATu+PUdJaMgWPUcJZI60p9VSN8ofz/Eh0V7HwDi/9mv3o3+B464D7SEfC3egrdLwigIs2lSfsaZsEbjkmg2BHVTJbsh2c1qNiCJjcNRNHD2iDJOqijFzRClmja3AhAFF0OmCMweSJGHM3Z/C7vKizmbH4L75KbkWu+pNXQQegG+cvyg3QnCksT9HrSg3CUsg1ZkjVQZGizytZgidVktJQ7aiRBSOuuco3I4jQQRNtjBlNRFw1rfaQz5mEwsgIwSwmR7nF9+/XJNB/j6lLnPEshoRaWNw1E3kmg14b+6REe+j0+lQYc3B7gMdqG1JYXCkyhyZDXoY9Dp4vBI6nR552kwpkPGIns1KxhJIu2pMXuuMMjWXN3RDtijdpCRz5IleVrOoptWiZ478W7LDBEci4GxoDW2oDqwICB/AZnqcXzkpqSyrSZIU8o+FRPj2KHEJJBFFxmm1HqbC6muSrdN480sG5ZuHCDh0Op08sdbh1H5TDjd+rkWU1Wx2d8KHnDpUW7zFvqDIx4eIaTWts9VSkTnyb8iOpedILqv5gptwfUHRtmSLCcDGNmfIa9saQ1+Y2JJd3+qQM03pFOg5CjRkSxKSdhiuyyNBPBTLakQUDoOjHkYOjlpCyybJ4PYG3jxyFL0yeVG2ZCdyfAiQ+PlW6mZnrTPK1ER2KKislobjQ+LqOYqyabwwJ/Iof0un7/M9XinktW2LoSHbmmNChdUCIDPZI62GbCB5pTW7opTGshoRhcPgqIep9L9x1dlSExwpgwtlr4x8vlq04CiGhmyTQY+yQt/XUZtgkKfObuXEsItJ3nOkLKul4/iQiHuOgjNebf6JwHBBpsj6hJtWa1EERPW24OxiuENn1TJZWnMovq/Kxv9kjfMr/3wzc0RE4TA46mFSXVazK/owlG/qInPUrlFWkyQpruAIAPoX5wIA9jZ3JnSd6syRyHLZI2QD3BEyR6mdVothz5EzuKwWrecofFktkFFSL3JsjaHnCAg0ZW/PcObIqNfJBwo7PNrf19U1B9EYx8JKZZ9Rso8lIaLeg8FRD5Pqsppy87SyATbSlmy7yyv3hMRSVgOAAcW+r2NfgsGRvMVbPcofaVpN7DkK2pCduuNDxJuvOYGyWrjSl5gG1OoHcrq9QZm9elV2MdYjXkTmaGsmgiP/9y/H7DtQ2BQheN1S14oznvkaN77xXcyPz8wREcWCwVEPE8gcpSY4Ujc6C5HKaq3+bIdOB+TFuHupf5Evc5RocKQuWcXTcxS0BFKeVsvQEkj1KH+M02pamSP13qiQzFEMPUdAoCk7kz1HIhNojrDr6MeDHf7/xv5nSJkZ9XillGxGJ6Kej8FRD1PpD45qW+wpORw0kJEJ/qMRaVqtXfTJmLW3OmsZUNLFsppqCWQsZ6uJ7JApTWerxbTnSF1Wi7LnSB7l1+g5alGdVafuOQqM8kcOjkaUFwIA9hzsiBhspkJgCaR/jUSELdniz2q4PjjNx1eVXZk9IiItDI56mHJ/Q7bD7YWtM/6T2aMJlznKjTCtJk9YxdhvBCh7jhLLgAWuM3jPUUyZo6Ceo1SerRbftFosvVvWCBuyo2eORD9T5J6j0gIzinJNkCRgR0Popu1Usit6joBAf5hWf5C4b6Qm/HCfIzA4IiItDI56mByTQd4TVJuCiTX1ckUhP4ayWqz9RgAwoLiLZTVXcOCh7t3R4taYVjOl5fiQCA3Z/qDTK/myI9GCI3G7VllNvXG8IcHMkU6nC0ysNaS3tNapmkKMlDkS9xWBZSzsqsWPHOcnIi0MjnqgCv9p6akY51ePyAtyWU2jnBNro6+SyBw1tDoSeoOyqzJHuTGM8rv9TeNmYyBzZErhwbNO/zXGsgQSAOzO6MGRCGw6nJ6QxYgiOBKvifoIEVsc36dMHSOi/vMX6Xw1Eeh4vFLMe5DUwTO3ZBORFgZHPVBFkb/vKIWZoxxjmLKaRmZGjPdHy0goleSZ5MAg3K6jF77cgbmvrQ4peXm8kpzpEZkj8WYaqUwSaMgO7TlyJ2kDs1IsmSOTQS83iHe6PFF7jpS3q48QEWU1kfVRHiHicHvk0pQ1hvPvxGOke5y/0xU4Ww0INGRr9xwF/izGWlpjWY2IYsHgqAeq8C9QVI9qJ4M8BWYKU1aLkDkKt9VZi06nQ3//OP9ejWkjr1fCnz7bgo++348N+21BH1P2n6in1SJmjjSODzFluOcICC4JyqWvMH1BFmNgc7R6nF/sOBrpb6hud3rQ7n88ZSCVH8P5d8PKfef27WhMc8+RUzRkB5fVtDJ7ykAn1qZsR0hwxLIaEYVicNQDVaYjcxRHQ3ZrHEeHKEVaBLnfZpefS91oHLTFO46DZ0V2SDmtZpIzE5mZVgMCfUftDrf8NUd6La1hxvlt/tepX3GOXAYV2SMRdOWZDUF7nsIpLfAF4C1dOBw4EYGeI981yt8fjQ3ZiQRHoT1HzBwRUSgGRz1Qudh1ZEv+lmzlEkgleQmkRvCRSM8RoGzKDg3ylOUcdXAk3tCMep38Rh/LKH/g+JB0T6tF/msmMkfK6bJI2R2x4Vo9zt/sD2SKc80oF9lFf3DUGuf3KNoBt6mi7jmKXFbzhnxerI8vsOeIiLQwOOqBKq0pbMiOsgSyXaOs1h7jFJRa/wgTa8pGYPXKAq2mcRFgON1eeMP0DwWODwnNHCW750iSAk3CkRqyAUVw5A9kzAZ9xFJcYGJNu6xWlGeSz65rUAVHsX6P5GWTDndI43cqdapH+Y2RGrITyByF7DliWY2IQjE46oEqUnj4bPQlkOHLavHsOQIUmaOW0OBoe0P0zJEyIyPKfkD489Vcmj1HomyT3AyCyyNBTJdH6znKUZXAopUnw23JFq9TUa4J5f6JRjGxJk/BxdCMrXwO5eemQzyZo86g4Ci2a2RZjYhiweCoBxKZo4ZWR9LLQfJyRdUbuijzJLOsJvccaTRkK4MjdeOxVuZIeb3hmrJdGnuOUnW2mjIjEb2s5vu4OEA12uuozOootfhH+YtztTJHvo8Vxvg9UjZ+ay2cTBW7elrNKPZQRS6rJT6txswREYVicNQD9S2wwKDXwSsBB9qT2zDrCNeQbRJlNY3gKMGy2gBFQ7Z6id+2+sCUVCyZI71eJ7+Z28NkAwIN2aGZI3eSG7IdGhN14ajLatGDI+0t2aKsVpxnloOjelVDdjzfI2ua+44kSQqU1cyqzJHG91QZ2CTckM2eIyLSwOCoBzLodSjzTxOF2xGUqKgN2Rrli2iLC8OpKLJAp/MFEk2KIK+lwyVnUYDAFJbgCLNcMdo4v1s+PiR0Q3asSwTVlm0/gNdW1ITcLoIjs1EPnS7yeXO5cZbVtLZkS5IUVFYL13MUz/co3FRcqrg8ktzfpF4CqVlWU3yfIzXiK/FsNSKKBYOjHipVfUdhN2RbAksg1VmetgR7jixGgxzkKSfWtjcGLx4MHeUPl92KfL6aSxw8q09e5uhXb6/Fb/71A3aojtkQmQ5LDGPzOapptWilLxG0KHcXtSkap4vzTGGn1Qpj7Dny3df3POrgNFWUAY48yi83ZGuM8isCnVjLatxzRESxYHDUQ1WkaGItfEO2741SkkJLE4n2HAHAgJLQXUdiUk3EMDZV5kJeVKnKHEUa5/d4Aw3SysyRPMqfYM/RQf/4vHIbddA1RtlxBASCusaYG7JDy2ri6BCLUY8ckyFsz1E8u6jk53GkJzgSgYteFyinBRqyQ7+nyj+H8ZbVxGvOshoRaWFw1ENVpGjXUeBNXTsrA4ROBiXacwRoL4IUzdgjK3ybntWZi3CZo5wImSNlQ69yWk00Z/umy+LLHil7ZEICONXBuJGI11Y8RrQMXIFGuUtZUgMgT6sdaPc17YvvkTWenqPc9JbVlGP8ohQZ2JAd+r1RZos6XLFOq/k+R7xOLKsRkRYGRz1UqrZkhws8DHqdnJlR/ivd45UCW50TyRxp7Dra7m/GnjK4BIBWQ7Z25ijS4bPKPUYmxbSaWZFFinfXkcPtlbNRoX1RsS2ABILXEADRy2pao/wtcjO2702/T74ZBr0OkgQ0tTsT6jkSR5ikOzhS/tmLtSHbHueeo0BwxLIaEYVicNRDiZ6SpJfVwgQeQKC0pgyO2hVZpHh7jgCgvz/I26eROZoyyBcc2TpdQVkdOSujzhwZw68bcIfLHCn+P96+I+XroF43EK5pXIs6EI15Wk0xyt8sj/GbAfiC2b75vv+vb3XIpc/u3HOkFZhHasjuSlmNmSMiioTBUQ8lMkep6zkKLQcFFkEqGoH9b7omgy6mLInagJI8AIHgyOH2oKapAwAwZVAxAF9GR/nmJ2/xDpM50uojUZZltI4PAeKfWFMGYeot3s54Mkfq4CjmJZCBoEVkjqy5geCn3BroO7J1oedIXTJMlU7VobNAILjUyhwFbciO8/iQIn+GjT1HRKSFwVEPlbKeI5d24AFob8lWjvFHG1nX0r/Y93Xs9U+r1RzogMcrocBiRHVpvhzIKDMzgcxRmFF+rcyRmFQz6IKuU1lii3ehpnKtQWjmKI6eI3OcmSONUf7mTv+5anmB4EhMAta32hPqC9MKwlIpMCkZumpBvQTS5fEGlUHjXQLJshoRRcLgqIcSwVFLpyvmQzdjId7UtTJHuRplNbmXJYFmbCDQc9TY5oDd5ZEn1YaV5UOn08lvYsq+I3uYLd45kYIjseNIH/xHXq/XwSBvyY6vrNbpDLxhh9vFFM+0mhAtgFEePCvKjXLPkTJzVBjYpC4HR/HsOcrNTM+R8vUINGQHB0fqP/PxHh/CshoRRcLgqIey5hjlf2Ens7QWbs8RAORrlNXa5cxR7L0sSkW5Jjkjtb/FLvcbDSsrABB4g1aWrcJljuRRfo0sgta5aoLITmkdURFJR6TMkSv2spp6bUK03i0RPHm8gWk5cXRIkSI4Um7JTiSIzVzmKHpDtnqdRGeM5TFOqxFRLBgc9VA6nU4+Yy2ZW7LDbcgGopXVopePtOh0Onmcf19zJ7Y3+CbVhpUHB0fKzFG4kpW8BFKjVBI4OiT06xJvwFrj4pFE6jmKp6wWb0N2ntkg74ASQY/ckJ0X2nNU09QhL4hMqCE7g5mjQEN28PdGnTnS2tyu5laU4lhWI6JIelVwNGTIEOh0uqBf999/f9B9vv/+exx99NHIyclBVVUVHnzwwQxdbdeVi76j1uT1HdnjLKt1ZQGkoDxjLVBW8wdHGhNTDo3eFN/1+YOjSJkjvUbmSCyCjLvnKPA86nUDTsXxIdHEW1bT6XQhR4jIe47yzPL9RM/RDn/AqdMBeRrf13CsYc5wSxXxeuZolNWcqiAmtKwWPchRnrknB0dsyCYiDQkFR7///e/R0dERcntnZyd+//vfd/miuuL3v/899u/fL/+6/vrr5Y/ZbDbMnj0bgwcPxqpVq/DQQw/hnnvuwfPPP5/BK06cyBzVJSlz5PJ4FWdbhf7RkMtqihFyMU5eEEdGQk1eBHmwUy6rDS/PBwDNnqNwWZlIPUciK6SVOTImI3MUZpQ/kT1HsZQo1VuymztDy2oic7TnYIf/cY3QawSH4Z8jvUsgxfdVK3Ok/t6ElNViCY4U3y+x4JJlNSLSklBwNH/+fLS1tYXc3tHRgfnz53f5orqisLAQlZWV8q/8/Hz5Y6+++iqcTidefPFFjBs3Dueeey5uuOEGPProoxm84sQl+3w15RuFduYocL6a0J7gobNKA/wTa6trDqLD6YFRr8Pgvr7vm9xzpAg+tKaalNesfuMEAlkhrZ6jQFkt3p4jZVmtC0sg4xzlB0IDlxb/MSbKhuyyAt/rKlZExdOMDQQyRx1OT9xZtURojfJbwjRki8BUZAJjyhwpSsaimZ9lNSLSklBwJEmS5tj22rVr0adPny5fVFfcf//96Nu3LyZPnoyHHnoIbnfgX73Lli3DMcccA7M5UHqYM2cONm/ejIMHD2o+nsPhgM1mC/rVXVQkuaym/Jd1xJ4jReaoqz1HQCBztGJnEwBgUN88OWMQT+Yo0ii/S55Wi1BWi/N8NeXr1epww6uYdpOvMYYyljIQjbX0FRIcdYb2HImG7MDnxJfdUwZpbY7UZ4/E980SNMofriHbd98S/6LLTo0DkdWUO7zEczBzRERa4vqnZElJidzLM3LkyKAAyePxoK2tDVdffXXSLzJWN9xwA6ZMmYI+ffrg66+/xp133on9+/fLmaHa2lpUV1cHfU5FRYX8sZKSkpDHXLBgQcazYeFUJLmsJt5wzEa9ZvCrtSE7cCxF18tq4g1Q9BsBgexFcHAULnOkD/o6lAJ7jjTKavK0WuIbsiUJaHO65et1RGhsV1NmSgrMsZW+AuP8LjjdXrQ7g6ewxOMWWoyK0md8mSOTQY9ckwGdLg9snW4UK/qZUsGu2ZDtey3UCzrFffvkmeXDde0ub0iJUutzckx6ObBmzxERaYnrp+Vjjz0GSZJw6aWXYv78+SgqKpI/ZjabMWTIEMyYMSOpF3jHHXfggQceiHifjRs3YvTo0bjlllvk2yZOnAiz2YyrrroKCxYsgMViifAI4d15551Bj2uz2VBVVZXQYyWbvCW7NVnBkf9f1mHe0PNUZTWn24utda0AEt9zBAQasoXh5YHgqEhjlN8e5lBXOXOkdbaayBxplNVMCZbV1BkqW6dLDo7Em7lZIxhTUwYDsR7BoswcicBRpwvNDpVZLWhtSPxg4MIcoy84SkNTdqQ9R+rMkbivMlPW4XRHDI4CQbVBDlpZViMiLXH9tLzooosAANXV1TjyyCNhNCb+hhirW2+9FRdffHHE+wwdOlTz9unTp8PtdmPXrl0YNWoUKisrUVdXF3Qf8fvKykrNx7BYLAkHVqlWURgY5Q9X6oxHpB1HAJAvMkcON1o6XLj6H6uwcvdBGPQ6TK9OvJxaWZQDnS7QG6PMHAWCo9DMkTorkyOm1TTe8ALTaqHBigiO4j1bTR2E2TrdgD/5GG4Xkxbl6x1rkCl6vGyK4MiaY5IXWgrlhRZ5Wi2RvjBrriloT1Iqaf35Cxe4itc332KExaiHw+1Fh9ODvhEfXwT/hkDmiGU1ItKQUHRTWFiIjRs3YsKECQCA9957Dy+99BLGjh2Le+65J6inp6vKyspQVlaW0OeuWbMGer0e5eXlAIAZM2bgt7/9LVwuF0wm35vuwoULMWrUKM2SWncnppEcbi9snW75vKhERdqODQTKP3sOduLM577Gtvo2FFiMePr8KRg/oEjzc2JhMuhRUZiDWn9j+bCyQBO9mCoKbsjW7ueJmDmS9xyF7znqyhJI9TXGs+fIoNfBbNTD6fbGHMDIZTW7Gy3+o0OUJTWhzB9A+z4nscwRkJ5xfrkh2xTakB3Sc6QoreaZDXC4vZq9ZkGfoyyrseeIiCJIqCH7qquuwpYtWwAAO3bswDnnnIO8vDy8/fbbuP3225N6gbFatmwZHnvsMaxduxY7duzAq6++iptvvhkXXHCBHPj84he/gNlsxmWXXYb169fjzTffxOOPPx5UNutJckwGuaxQm4SJtXD7gwRRVttW34Zt9W3oV5SDt6+egZkjEwtelcQZa0BgASQQriE7TOYowrRaxMyRPtFR/uDniSW7FY4ICGINYJRBi9YCSKFc0ZQdb0O28nPSsQhSzuyYtTJH2ksgc4wGuRcu2ji/MqgW3xePV0rLJB4R9SwJBUdbtmzBIYccAgB4++23MXPmTLz22mt4+eWX8e677ybz+mJmsVjwxhtvYObMmRg3bhzuu+8+3HzzzUE7jIqKivDf//4XO3fuxNSpU3Hrrbfi7rvvxpVXXpmRa04GeddREoIju/yGrp3tEG9CADC2nxX/uvZIjOln7fLzAsCAkjwAvjdzq+JNXPy/MvBQTh0pyRuyI52tptVzZExsWk29lVkZQASm1eILjmLPHIX2HGlnjgLBUSJltbRmjiL1HKlH+Z2BQEoE89HG+ZVlO+WfcWaPiEgtobKaJEnw+t9IPvvsM5xyyikAgKqqKjQ2Nibv6uIwZcoULF++POr9Jk6ciP/9739puKL0KLfmYFNta1IyR4GgQ/sNfdwAK4aXF2BUZSEeOHNil3YbqYnMkbLfCAi84bc7PXB5vDAZ9GGzMpFG+UXgo9UgbUw4c+R7HtEvZdNYN2A2xLbiQJQs4w6OHIHMkVZwFJw5SqDnKI2LILX2VylH+ZV9dcrDh+XMkSvyNQY+Rx+0udzh9iK/e7YVElGGJPTuNm3aNPzhD3/ArFmzsGTJEjz77LMAgJ07d8qj8ZQelWIRZBLG+aM1ZFtzTPjslpldfh4thw7ugz9jB44cHtxSq3xDb7W7UZJnCpuVkQ+e9e+8UTaouyJOqyXac+R7vUoLLGhodYTpOYotcyRe85in1SyBnqNmjR1HQlczR+k8QkRrlF8ZzLq9kvy9UgZSuRpn/mk/fiDjaNDrYDLo4PJInFgjohAJBUePPfYYzj//fPz73//Gb3/7WwwfPhwA8M477+CII45I6gVSZAP95ahdB0KPc4lXPE3EyTZrbAVW3/UTlKje4I0GPQosRrQ5fOWjfItBnmpTB3GiV0WSfF+L8uOBDdmRptUSO1ut0prjC44U6wYcGgsNI8n13y/W7E6BIqMjMlbFuaGDEOVBDdmJ9BylL3PUqRGcKzM8TrdX/l4pA3nRCxe95yg4M2UxGuDyuLnriIhCJBQcTZw4ET/88EPI7Q899BAMMZYRKDlG+JuXt9W3dvmxwh3LkS598rWnHK05vuDI1ulC34LAfcKV1QDfqHdQcCSm1TQ3ZHetrFZhteCHvcHTas44A81Ey2o2uxvNHZGm1bpWVgs0ZKdvWi1HYwkkEJzZE1mgXJMhYjlVSZ0ZtRj1aHOw54iIQnWpaWTVqlXYuHEjAGDs2LGYMmVKUi6KYjeiQgRHbV3edRRuuWKmWXNN2NdiR0unS36D0+lC+4dMBj2Meh3cXgmdLg+KEAgWAmU1rWm1RBuyRXDky85o9RzFWlYT5auSGLdQWxUbsuWGbI2yWnGuSS4fdW2UP33TaspFjkaDHnod4JWCx/kTK6sFl+24CJKIwkkoOKqvr8c555yDJUuWoLi4GADQ3NyM4447Dm+88UbCe4kofoP75sOo16Hd6cH+Frt8FEciMp05CseqGOeXlyuGOeIkx2RAm8MdkkUQJTOtPUfhxsWjCQmONHqOzDEGR3OPG44BxbmYM157GamaCFrsLi8a20IPnRX0eh2mDe6D9fta5MN845GuUX6PV5In0tQH8fqa8L1BE2uBc9gCZbVYe47EfizxX2aOiEgtoXfB66+/Hm1tbVi/fj2amprQ1NSEdevWwWaz4YYbbkj2NVIEJoMe1aW+N72t9W1deqxoSyAzRd6SbXdFvUZxu7r/JNKeo0SXQIo36Eo5c6Qc5Y9vz9H4AUX43SljNUtjWpSN2z8e9PWbhfvcv192GL6+84SYH1vJmqZRfuX6BXVwLgJMZfCqzAIF9hxFmVYL6TnyZ47Yc0REKgkFR59++imeeeYZjBkzRr5t7NixePrpp/HJJ58k7eIoNqK0Js45S1S3zRwpDp8V1xgu6Mg1+xt2VaUSlzf62WrxHB/idHvlPiaxqbxFq6yWokBTHAoLAAflJZDaJTnR1J4IOXPUmdrMkTLTl6Mq65oV4/yCcvIs5p4jEVgbWVYjosgSehf0er3y8RtKJpNJ3n9E6TO8vBCAr++oKxyK3THdifLw2WgTdeLa7c5wZTWtabX4M0fKN2JxALAoq0mSpGjITl2gqe4h0hrlT9ZzpCtzZDHqoVc1zWudr9aVnqNAQzbLakSkLaGf3McffzxuvPFG7Nu3T75t7969uPnmm3HCCSck7eIoNmJiratlNXsch6WmkzhfzddzFDm7Jd4o1VkEuSE7SdNqomxn1OvQ179BsM3hhtcrBb3ZpjI4Uh9Sm0jZLBqRtXO4vSHnmyWTXCYzhwa9ZjnDoxUcdWGU38TMERFpS+gn91NPPQWbzYYhQ4Zg2LBhGDZsGKqrq2Gz2fDkk08m+xopCmVZTZLiaypWirYEMlO0eo7CZo7CnK8mJtGSNa2mPOpCZFckCWh1uIMah2NtyE6Ecm+RxahPyfetIGgJZ3KyR3aXB++t2YuWjsDjyceBaHxftTJ7WqP80TJHDtWxM+w5IqJwEmpEqKqqwurVq/HZZ59h06ZNAIAxY8Zg1qxZSb04ik11aT70Ot9EUUOrA+XWnKCPS5KEZdsPYFJVccQNzA53+DeoTAqU1VyB0l+YzFFOmP4T0U8Uec9R7G+SHf7m31yzwX9Wl2+iytbpCl5iqBGMJYtVEbikoqQGAAa9Tl7C2Wp3o29B18/ZeGvlHtz93npccPgg/OFnEwAogk3NzJHvtqCeI8Wfg5gPnnWrG7JZViMibXH95F68eDHGjh0Lm80GnU6Hn/zkJ7j++utx/fXX49BDD8W4ceN61bllPYXFaMCQvuEn1t78dg9+8ZcVePi/myM+jtz30d3KaorDZ6PtYspVHCGiFHHPURfKauLN3BqU3Qr0z3Rl71Q0yp6jVJTU1M+TrEWQtf6jbr7cEjiHMVLW0qyRORKvv8WoKKvFugSSDdlEFEVc74KPPfYYrrjiClitoSexFxUV4aqrrsKjjz6atIuj2A0vDz+x9t8NdQCAZdsPRHyMbltWy1PsOYoyIi9KLCEN2d5Ie478ZbUEGrLF84ksTnDTeGqDTOUEmtbRIcmS7EWQ7Q7f49Q0dWBvcycA5dEhoa9ZYJTf97pKUqCvS2TugEA2L5zQPUcsqxGRtrh+eq9duxYnnnhi2I/Pnj0bq1at6vJFUfzkviNV5sjl8WL5jgPyx+wR/nVtd6XnTT1eVsUiQruqb0RNZHLUX6c7UkO2XmQmYs8cdagyR0F9Uao34VRR9hxpbcdO9vMkq+eoXRG4rvD/2dQ6dFYQmT0RECnLYF09W039eEREQJzBUV1dneYIv2A0GtHQ0NDli6L4jfCP86uDozV7muU3co9Xwqba8LuQAj0Z3SxzlBv7niPxhhdaVvNnjjQ+z2SMv+dIXEeeuqzW6ZIbslPZbwSkr6xmVZzjlgzKDM/yOIIjEbwqg6Acoz6wITuBs9UAltWIKFRcP70HDBiAdevWhf34999/j379+nX5oih+w8sDZ6wp/W9rY9Dv1+1tCfsY6mme7kKM8nu8Epr8h6yGy8qEG+UPHDyrNa2mD7pPLOTMkVxWC2S3HGnq3Qouq6U+c6Q8O64r2hyB783yHU0AtA+dFURZTTRkiyDeZNDBaAjsOYrekB1mWo2ZIyJSieun909/+lPcddddsNvtIR/r7OzEvHnzcMoppyTt4ih2w8oKoNMBTe1OHGhzyLd/tc0XHPXzLypcvy9CcBRlEixTck0GuS+oweb72qL2HKn6SOTjQzR6jhI5PiTQkO0LUEQA55uoS88BvlZFWS1V02pA8nuOOhyBxxF9R50RAnOzappQLq36X18xreZwe+EJE+B6vIHFnDlGsefIX1ZjzxERqcT1Lvi73/0OTU1NGDlyJB588EG89957eO+99/DAAw9g1KhRaGpqwm9/+9tUXStFkGs2oKokD0CgtNZqd2HNnmYAwGVHVQMAfoiQOVK/6XQXOp1ODgTqW/3BUdhRfv/xIeF6jiJOqyXSkO373EDmyJW2huz0TauJnqMkNWT7A0vR/rV8+wHFKH/4hmw5c6Q4dBYILsWFm1hTls5YViOiaOL66V1RUYGvv/4a48ePx5133onTTz8dp59+On7zm99g/PjxWLp0KSoqKlJ1rRTFcNWm7BU7muDxShjSNw9zxvlOe99c2xp203F3HeUHAm/+9a2+rGW4AE4+ZyvctJpGQ3ZgWi3+Uf48OXOkPOIkvkNnE6Vc0FgU5ly1ZEj2ESJiWm3a4D4AfH1Hjog9R77vj+jlUk+25Zj0EBsTwk2sKTOJLKsRUTRx//QePHgwPv74YzQ2NmLFihVYvnw5Ghsb8fHHH6O6ujoV10gxEseIbPOP8y/1l9SOHF6KgSW5KMo1weWRsEVj3N/tCRyk2t0yRwBQmBtr5ijK8SEamSOjv+fIlUDPUU5Iz5FLDj5TuR0bCJ5WS2XPkQj8klZW8wcwJ4wpBwAs33lAEfCE7zkKlNWCAymdThc2KBbE55gMOhj8ATKn1YgonIR/epeUlODQQw/FYYcdhpKSkmReEyVInTkS/UZHDS+FTqfDhAFFALT7jtTj0d2NyBw1+4+cCJs5CjPKH6nnSJ5Wi+NNsjNkWi39PUfpn1ZLVubI99rNHFUGg16HPU2d2N7g+zOr9WdPlD1F0Kk1OBBtEaR6ASTAs9WIKLzuVz+hhI2oCIzz19ns2FrfBp0OmDGsLwBg3ADf8k6tviNlMNHd9hwBwUdlABEyR8bIe460p9USOFvNn/2Qg6MMTKsVpuH4EOXzJCNz5PFKcgBTVmDBxIG+gP2bnb6pNa2ymrohW2thpAiKw52vpl4ACfBsNSIKr/u9C1LCROaoodWBj77fDwCYMKAIxf5+lPH9fW9E6/baQj7XrigF6TX6cjJNnRmJljkKKat5w2eORKktrp4jVRnIGnT+W3oasq05JrmpuSQ/lT1HyVsCqewJyrcYcfhQX+Auyp4xjfJrlOCiltU0JjFZViOicBgc9SIFFiP6+0f2/7ZsFwBfv5Ew3l9W27jfFnJURrTliplmVQVH4bIyIoNzsCP4jVzOHEUY5XfGdfCsqqyWk/6yWo7JgN+fNh7zTh0bNNafbNYw02p2lwc/f/ZrXPfaanhj7NcSr5tBr4PFqJeDI0FrWk0uq/m/h1pb0sVKhfCZo9CGb06rEVE44Y9opx5peEUh9rXYsetABwBfv5EwuE+efML6toY2jK4MnJHXXc9VE9SZo3CBR6U/OGxsc8Dl8cpvrCIYNGqU1cwJZI7Ub7Zy07LDLWeV0hFoXnD44JQ/h7KsJkmSfJjumj3NWLn7IABfEH7eYYOiPlabI1CO1Ol0mDa4BEa9Th4G0CyrGcOV1RQ9R1HOV9PqUwr0HDFzRETBumeagBImJtYA35vz1MGBZnm9Xodx/X0Bkbq05pC3B3fPPxIhZbUw19k33wyTQQdJCky2AYFJtEhLIOPpOVKfrabs/xFLOLtrFi5e4mtzerxBgcSGfYE/Qws+3ogGxesdToe/GVts9863GOW+I0B787m6Iduu2jEFBDJ44c4OVJ+rBijKauw5IiKV3vHTm2TK4Oiw6j4hmSBRWlMfI6I1zdOdqMtG4TJHer0O5YW+7FFtS2CTu8gcmSKM8ofb/6SlU5U5shgN8huvCBJ6S3CUbzbKe4SUE2sb9geCI5vdjfs+2hD1sdpVjewAgkprsWSOHFo9R9EasjXODWRZjYjC6R0/vUk2oiIQHCn7jYTx/ok19Th/dz1XTYg1cwQEjkoJDo78mSONZnO5rBbHniP1EkggEMA1iMxRN30t46XX6+RMj7LvSGSO5h43DDod8O81+/C/rZEPnhYLIPMV58JFDY5ET5h8tppGz5EpSnDkCu0DY0M2EYXD4KiXGV5WKP//UVrBUX+x68gWdA5VYzcvBYk9QkKkZmfRd7S/pVO+TUyraWaOEtiQHSirBR5P9B31tswRENqU7XR7sbXet0z03EMH4aIZQwAAd/17XdjSFhA4OiRfEVROG1IiB63KjJIQaMj29xyJBZzG0LJatCWQQWU19hwRURi956c3AQCK8ky44fjhuGjGYIztZw35+NCyAuSaDOhwerCzsR0AUGez44FPNwMADqkqTuflxiy0ITv8H91Ka/jMUaTgyOnxQpJiC5ACZ4EpM0e+/z/Q5gSQ+g3Z6VSomMYDgK31rXB5JBTmGDGwJBe3zh6JCqsFuw504OnPt4V9nA45c6Rc4GjEr08cjZ9PHYhhZQUhnxN2lN+sLKv5ri/8EkiNhmz/43q8Usj0JhFlt97z05tkt8wehfmnjdfcV2TQ6zC2f6C05vJ4MffV1Whsc2B0ZSFunT0q3ZcbE3XPUaTyn8gc1dp8wZEkSXLJTKsh26wImMKd6q6kPOFdWQYSAZx4rt6cORIltbH9rNDpdCjMMeGeU8cBAJ5bsh3b/Fva1QLTasGZwCuOGYqHz5qk+WdWfTCwXFYzKgOsaGW18A3ZALNHRBSs9/z0ppiNlyfWWrDg401YufsgCi1GPHvBVLmxtbspVG/IjhB49CvKBRDIHCl7ibQ2ZCvPW4ul70iZnVCWgUJ2MXXT5vZEqA+fFc3Y4/oHJs1OHF+Jo0eUwuWR5CWkaiJ4UfYcRRNoyPZ9bzqdGqP8clktzMGz7tCBA2Vmj8ERESkxOMpC4/wTa++u3osXv9oJAHjk7EmoLs3P5GVFZDTo5aZgILbM0X4RHCl6iTRH+RXZClcM5RWxS0enCw7SQifqes9fL/URInLmqH+gdKs8v6+506n5OGJaLT+OINysPlvNHdrvlROtIVsjoDLodfJSUE6sEZFS7/npTTETb2BN7b43sKtnDsPscZWZvKSYKPuOIvYc+YOjOpsdXq8kN2MDYQ6eVWSOXDE0ZdudgZKaWIgIaDSNd9OdUYmQl1zaXZAkSc4cqfvaAseoaGdwxLRaXkKZI1XPkUZZLXrPUfD3hLuOiEhL7/npTTEbXl4gv+HMGNoXv5o9MsNXFBuRvTAbIp//Vl5ogU7nK5EdaHfCpSiZaJXVDHqdfEZZLI25HS7fG7x67FydOTIbel9ZzWZ348eDnWi1u2Ey6OTz/ITAAbza57AFlkDG/tqI4FWUvjQ3ZEebVtPYcwQodx0xOCKiAAZHWchk0OOKo6sxvboPnjhvclDPTXcmMkfRylUmgx5lBRYAvr4j0Uek1yFsUCVeA1csPUeq7dhCrOe/9USFiqBnvb+kNrKiMGQiTz3VphZYAhl75kiUvgKZo8TPVlPvnuIiSCLSwrPVstRtc0Zn+hLiJoKPWIKOfkU5qG91YH9LJ0ryfZ8XKQg06XVwAkFZpnA6VYfOyteXJT1H4UpqgKKsZg9XVhMN2bFnjsTr6FSX1TSOD4laVlN9T0SwxMwRESn1np/e1OsFMkfR31grrIG+I3nHUYRSnMkotmTHEBxpnPAOxLeosqcpzAn0HGk1YwtW1VSbWqAhO57MkT+rp95zpLkhO8y0WpiDleXMEXuOiEiBmSPqMURmJtbMEeCbWBMBT6TMkThfLZaGbPWhs+rrE3pT5sgql8vc2NPk2zweMXMUpqzW4ej6KL92WS3a2Wrax+OwrEZEWhgcUY8hMkexHI5bqdh15JK3Y0fIHKn6WiIJnzlSNWT3ouBIZI72NneixR/4jNHMHPkzTA43vF4ppMcrsAQy/oZsscHcrvH6i8cLd3SJQ6MUB/B8NSLS1nt+elOvV+QvW8WdOZIPnY3Qc2SIPXOkdegsEMiuCL0xcyQCo0F98kIyZUCgN0mSgDaNEpcoexUkkDkCfIGpaLAP6jky+R7P5ZE0A9ywZTWTdubI65WwubY1po3pRNT79J6f3tTrleSbAcTWr6LsOXLJZbXwmaPA4bOxZ47Ub7SF6rJahEWVPY36a9MqqQG+10QEM1qlNXHwbFx7jhTl0FZFo7fy9c9RLITUKq0FGrK1y2pOVebo3dU/Ys5jX+LZL8KfE0dEvReDI+oxjh9djrOmDsQ1xw6Lel+tzJHWobOCKYGeI3VpyGzUB5V6elXmSNVsrtWMLd9XdQ6b4PJ45SAkng3Zyu+bMuBSvr5mgx4GfwlPa9eRXWOrtu8xtMtqG/e3AgB2NLTHfJ1E1Huw54h6jMIcEx46a1JM9xVbsjtdHhxocwAIPiZEzWT09xzFMq3mLw1pnUNnzTWi0+WBXhf5+XqaXJMBBr1OLjOFyxwBvtegsc0RkjkSzdhAfHuODHqd/NxiuWSOSR+0nVyn0yHPZECrw605zi/vOQqTOVJPqx1o9/2ZaXVoT78RUe/We/5pS6SQYzKgJM+XwfjxoG+6KlLmSPQjuWPpOQrTkA0EsiZmY/Cbd0+n0+mCDv8dNyB65ki960iM8ZsN+rib1UXDvDiWROtsvcDEWvDz+pq4w0yrhek5OtDmO1qnncERUVZicES9lug72nOwA0DyptXCjfIDikWVvWjHkSCCo5I8Eyr9r22k+6kzR4Fz1eJ/bUTfkZw50nh9wx0hoiyZxTqt1ujPNrYxOCLKSgyOqNcSfUd7mnzBUcQN2fK0WvTgSJRotMbRYz3ipCcqtPi+trH9rRGzYoEt2argyB+0xLMAUpCbvO3hS5o58iJIVXDk8obcRwh3ttoB/6HMbWE2fRNR79b7foIT+YldR6KsFqkHSAROsZTVxJuvVmlHjLz3pnPVBNGUHanfCAjfkN3hz8LEc3SIIGeO/NkoreAzL8wiSNGMbdDrQkqrgZ6jwOd4vRKaRHDEzBFRVup9P8GJ/OTMkVxWi3y2GhDj8SFhptWA3l1Wqy4tAAAcPrRvxPuJIEpdVgssgIw/cySOdxEBl1ZgKh5XvQhSfL/U56oB2merNXe65MZzBkdE2YnTatRrib4Y0Ywbac9RYAtz7A3ZmsGRaMiOEIj1VPNOHYvzDqvChAFFEe8XaMhWTav5g5R4FkAKJlXPkVYzfLgjRETmSCug0iqrielG8VgerySvCSCi7ND7foIT+YlxfiHShuy4lkBGKqvFscW7p8kxGTBxYHHUKTzlOWxKYlotnqNDBHVZTd1YrXxc9bRauEk1QPtstUb/pJr6uokoe/S+n+BEfv1UwVHkabX4e460ykPy4bi9sCE7VmEbsuWeo8TLarYIZTWRTVJPq8k7jjQCKnlaTdG0LXYcqa+biLJH9v4Ep14vJHMUcc+RL3ByxjGtplXamTK4BPlmQ9S+nN4sXEN2uyN8OTIai0H0HMVQVnNpB0da4/+BPUfKslpw5ogTa0TZhz1H1GsV5piQbzbII+SmiBuyE8kchb7ZjqwoxNp5syMGYr2d3JAd0nMU/6GzgthgLk+raTZkh8scibKaVuYotKym7DkC2JRNlI2y9yc4ZQVl9ihSQ7boabGrNiWrSZIU9uDZwPNk918ruSE7ZFotfDkymsASSFFW0+o58j1u6BLISA3ZodNqje2qzBGDI6Ksk90/xanX6+ffdQREDlpKC8wAQrMGanZFb0oi5aFsUKg4PkSSApk4kTlKZM+RSVVWi9RzFLasFqkhW/F9bWxVZY5YViPKOgyOqFdTZo4ildXKCi0AgIbWyMGR8lDTcJmjbCfKah6vFDRWL3qOutKQLYLTSD1HnWGn1bT2HGmU1Zg5Isp6DI6oV1OeARY5c+QLjtRj3Goi+2Ex6rn7Joxck0FucFc2Zctnq3WhIVuINMrfGU9DtkZZTWQPy/0BM4MjouzD4Ih6taDMUYTgKObMUYRDZ8lHp9NpjvPLZbVENmSHBEcRymphGrK1mri1l0D6AuQhffMBcJSfKBsxOKJerV9QcBS9rNbY5oDXG35iTd6OzZJaRIFFkIHgSD54NoGymtkYPTgK15Ad2JAdac+R7z52lwet/mBocN88AJB/T0TZg8ER9WpB02oRNmT3zfcFR26vhGbVlJWSfOgsM0cRFWocIdLehYNnY8ochTs+JFJDtmrPkThw1mTQoV9xbtB1E1H2YHBEvVpwz1GEUX6jHiV5vjf0SKW1SOeqUUDg8FmtnqMkZI40NpBHK6tp9xz591t5Jbg9Xrmk1jffIme/OK1GlH16THB033334YgjjkBeXh6Ki4s171NTU4OTTz4ZeXl5KC8vx2233Qa3O/gH2xdffIEpU6bAYrFg+PDhePnll1N/8ZQxffLN8o6cSGU1ILi0Fo4o2eSZuD81ksCWbF/mSJKkLh08a1Z977R6vkTAalc1ZIuSWa45fFkN8G1HF9/7vgVmufwn9jMRUfboMcGR0+nEWWedhWuuuUbz4x6PByeffDKcTie+/vprvPLKK3j55Zdx9913y/fZuXMnTj75ZBx33HFYs2YNbrrpJlx++eX4z3/+k64vg9JMp9PJpbVIZTUgMLEWMXPEslpMrIpdR4CvbOX293Llpaispjx4VrlfyR5hCaQyI+VwKYMjixzEtTnCl1mJqHfqMf/8nT9/PgCEzfT897//xYYNG/DZZ5+hoqIChxxyCO699178+te/xj333AOz2YznnnsO1dXVeOSRRwAAY8aMwdKlS/GnP/0Jc+bMSdeXQmlWWZSDmqaOmDNHkYKjDjZkxyRQVvMFFspSVyKvXWhZLXzPkVfyBWM5qoNotT7HoNfBZNDB5ZHgcHvlHUel+WY5OGpn5ogo6/SYzFE0y5Ytw4QJE1BRUSHfNmfOHNhsNqxfv16+z6xZs4I+b86cOVi2bFlar5XSa8bQvjDodRjTzxrxfmUicxShrGbnKH9M1A3Zot8ox6RP6HiV0MxR+J4jIHhiLTDKr/28gV1HHnnHUd8CMwpEzxEbsomyTo/JHEVTW1sbFBgBkH9fW1sb8T42mw2dnZ3Izc2FmsPhgMMReLO02WzJvnRKsZt/MhJXHDM0aq9LTJkjBkcxCYzy+wKL9i7sOAJiG+U3GvQwG/RwerzocHlQ4r89UlkN8DVltzl82Sa5IbvAIl9rKxuyibJORjNHd9xxB3Q6XcRfmzZtyuQlYsGCBSgqKpJ/VVVVZfR6KDGxNAHHEhyJaTWt4ysoQL0EUpSmEuk3AgIHzwrhAp3AESKhmaNIwRHg7zlqF9NqZhTmiLIagyOibJPRzNGtt96Kiy++OOJ9hg4dGtNjVVZW4ptvvgm6ra6uTv6Y+K+4TXkfq9WqmTUCgDvvvBO33HKL/HubzcYAqZcKHCESqSE78SMwsom6Ibsr27EBrcyR9r/r8swGtHS6goIjh3x8SJiymim0rFZaaJGn1TpdHrg93oTKgUTUM2U0OCorK0NZWVlSHmvGjBm47777UF9fj/LycgDAwoULYbVaMXbsWPk+H3/8cdDnLVy4EDNmzAj7uBaLBRaLJSnXSN1bPJkjHjobmcgctXYG9xwlsh0biG1aDVAuggxkeyItgQSCjxARgXFpviVoWWW704OiXAZHRNmix/xtr6mpwZo1a1BTUwOPx4M1a9ZgzZo1aGtrAwDMnj0bY8eOxYUXXoi1a9fiP//5D373u99h7ty5cnBz9dVXY8eOHbj99tuxadMmPPPMM3jrrbdw8803Z/JLo25CBEdNHU64PF7N+4ieI2aOIhMlqZCyWoKvm3LS0KjXhT0nTx7nV+w6srtjK6vZXR5Fz5EZFqNBzlixKZsou/SY4Ojuu+/G5MmTMW/ePLS1tWHy5MmYPHkyVq5cCQAwGAz48MMPYTAYMGPGDFxwwQX45S9/id///vfyY1RXV+Ojjz7CwoULMWnSJDzyyCP4y1/+wjF+AgCU5Jlh0OsgSYFjJNTs7DmKidxz1BlcVktkASQQXFaLlLXLNWn1HIU/Ww0ITKs1tDrkXUx98s1B18u+I6Ls0mOm1V5++eWo26wHDx4cUjZTO/bYY/Hdd98l8cqotzDodeibb0Z9qwMNrQ5UKI4eETitFhsxreb0eGF3eeQt04kcHQIEN2RHCo5EMLN4Uz1OHFcJnS6Gspo/aNrX3AkAKLQY5fsWWIxoandyYo0oy/SYzBFROsh9R2GasjmtFpt8sxF6fyXMZncFGrITnVYLyhyF/7F1zqGDoNMB76z6Eb/99zo43F74k0GaSyCBQFltb7MdgK+kJn8dzBwRZSUGR0QK0Y4Qkc9WSzADki30el1gEWSnW+45SkZDdqTM0YnjK/HwzydBpwNe/6YGv3p7rfyxaEsgReaob0FgAKPQwkWQRNmIwRGRQrSJtUBZjX91olE2ZcvTagmWI2PNHAHAmVMH4rFzDoFeB3z4/X4AgE4XyBCpidv3tfiCo9KgzJHvettYViPKKvwJT6QQLTgKlNWYOYpG3nXU6ZI3ZCeacVNmjmIpaZ52yAA8fu5kGPy1PYtRD51O+2w9kVHaL5fVApmjAv/XwMwRUXZhcESkEO18tU6O8sdMHD7banfLmaOEp9ViLKspnTqpP546bzKMeh2GlhaEvZ8oqzn96xtK8wOZowKROWJwRJRV+M9fIoVImSNJkgKZIwZHUVkVh8+2O7t4fIiiJGYJ01it5aQJ/bB0UEnERnB1uS0oc8SGbKKsxOCISCHSESJOjxce/+gTg6PolLuOunp8iHIJZLyvfWVR6EoGpdDgSJk58m/6ZnBElFVYViNSiJQ5sjsDW7M5yh9dcEN216bVghqywzRWJ8qi+l72zQ9kjkTGiZkjouzC4IhIQQRHrXa3vDxQ6HD53iBNhvDHV1BAUEO2o2sH9sY6yp8IdeZIOa0mAjxOqxFlF/6EJ1Kw5hjlLIU6eySasXnobGzkw2ftbnkFQsKZI0Pso/zxCg2OlJkj7jkiykYMjogUdDpd2Ik1HjobH3GESItilD/RDdl6vQ5G/1h+skuaygZvg16HIn9QBwQashkcEWUXBkdEKqK01qjKHPHQ2fiIzFGdzQ7Jf4RHog3ZQKC0pu4R6irl5uw++Wbo9YHmb06rEWUnBkdEKqVRMke5PDokJqJfp9Zml2/rSmApyp2p7Dnqq9hxBAAFOcwcEWUjBkdEKuEm1gLbsfnXJhaiIbu5wwXAd3SIMisTL5E5SmVZTdlvBAQyXa1syCbKKvwpT6QSNjjiobNxUfbuAEBegs3YgkXOHKWuIVu54wgIZL8cbi9cHi+IKDswOCJSiZY54rRabETmSEj00FlBLIJMelnNpCyrqTJHioCOfUdE2YPBEZEKp9WSQ/TrCImO8QtpKasVBmeOTAa9nFli3xFR9mBwRKQiT6upgqPvf2wGAPSLchwF+Rj0uqCDZrsyqQYA04aUoMBixOh+hV29tCDKslqpKnMEKBZBMjgiyhoMjohU5MxRqwOSfwa90+nBwg11AIATx1dm7Np6Gqsie5ToobPCH0+fgFV3zUK/otyuXlYQZeZI3XMEBDJeLKsRZQ8GR0QqorRid3nlbMHiTfXocHowsCQXh1QVZ/Dqeharoim7q5kjnU4XFMgkS1DPUUFo5khkvzixRpQ9GBwRqeSZjfIbomjK/mDtPgDAqZP6Q6dLfBw92yibshPdjp1qkfYcAcrMkSfkY0TUOzE4ItKgnFhrtbuweHM9AOCUif0yeVk9jjVXUVbrpisQ8sxG5JoMyDHp5e+7UqF8hIgr3ZdGRBnSPX9aEWVYWYEFOxvb0djmxMINdXC6vRhalo+x/ayZvrQepSdkjsxGPV659DDodNprAgKHzzJzRJQtGBwRaRB9Rw2tdizZ0gAAOHUiS2rxKlQ0ZHd1lD+VDqvuE/Zj8hEi7DkiyhosqxFpEBNrW+rb8L+tjQCAUyexpBavZDZkZ0oBy2pEWYfBEZEG0Xvy3nd74fZKGNPPiuHlyd2vkw2UZbWeujyzgGU1oqzD4IhIgwiO2v1bsZk1SoyyIbugG5fVIgkERyyrEWULBkdEGtRTS6dO7J+hK+nZgjJHPTw44hJIouzB4IhIQ1lB4IiQQ6qKUdUnL4NX03MVKqfVempZjQ3ZRFmHwRGRBuUBpKdOYtYoUcqyWneeVoskn2U1oqzD4IhIQ2mBBdYcI8wGPU6ewH6jRAXtOerx02oMjoiyRc/8aUWUYiaDHq9efjjcXi8qi3KifwJpUo7yd/Xg2UxhzxFR9mFwRBTGhIFFmb6EHq8o14T+RTnwSBKKFYFSTyJ6jloZHBFlDQZHRJQyBr0On958DCQJMBp6ZhW/wF8OdLq9cLq9MBt75tdBRLHj33IiSilrjglFPTRrBASfCZeu0lptix0vfLkDLZ3cyk2UCQyOiIgiMBr0yDH5flSmqyn7sc+24L6PN+L1b2rS8nxEFIzBERFRFAUWX+YrXcHRdzXNAICdDe1peT4iCsbgiIgoisKc9I3zdzjd2FrfCgDY29yZ8ucjolAMjoiIohB9R+kIjjbut8Er+f6fwRFRZjA4IiKKQl4EmYYjRH74sUX+/73NnfCKSImI0obBERFRFOlcBPnDXpv8/063F43tjpQ/JxEFY3BERBRFOo8QWbe3Jej3ew+ytEaUbgyOiIiiSNfhs51Oj9yMXdUnFwD7jogygcEREVEU4giRVPccbfA3Y5cWWDBlUAkAZo6IMoHBERFRFOIIkVRnjkRJbcIAKwYUM3NElCk8W42IKIqCNO05+kEOjopQUZQDgJkjokxgcEREFEW6eo5E5mj8gCL5gFtmjojSj8EREVEUhWkY5e90erClzteMPWFgkfxczBwRpR+DIyKiKERZrTWFDdmBZmwzKq056HR5fM/pcKOl04WiXFPKnpuIgjE4IiKKQpTV2p3xBUd7mztx/gvLUWuzB91elGvCSxcfhrH9rfJtypKaTqdDntmIPvlmNLU7sfdgJ4MjojTitBoRURSFCR4f8qeFW7DrQAfsLm/QrzqbA/M/WA9JChwNIpqxJw4okm9LxcTa69/U4Jp/rEJHnIEeUTZh5oiIKAo5c+TwxPw52+pb8c/VPwIAXr7kUAwvLwAANHe4cOazX2PFziYs2liPWWMrAARnjoQBxbn4YW8L9h7sSMrXAQBPLtqKfS12nDShH/5vUv+kPS5Rb8LMERFRFKLnyOnxwuGOLUD608Kt8ErAT8ZW4NhR5RhYkoeBJXkYP6AIlx5VDQBY8MlGuD1e2F0ebK1vA+Brxhb6Jzlz5HB7sN9f4ltT05yUxyTqjRgcERFFkW8OJNljKa2t29uCj37YD50OuHX2yJCPX3PsMPTJN2N7Qzve+HYPNuy3weOV5GZsYUBJcoOjvQc7ISp5a/YcTMpjEvVGDI6IiKIw6HXIMxsAIKS5Wssj/90MADh1Yn+MrrSGfNyaY8INxw8HADz22Ras2NEEINCMLcg9R0ka59/dFCjPrdtng9PtTcrjEvU2DI6IiGJw+NC+AICnP98W8X6rdjfh880NMOh1uPknoVkj4RfTB2NI3zw0tjnx+KItAHybsZUGJjlztEcRHDndXmzcb0vK4xL1NgyOiIhicPuJo6DXAR//UItvdzVp3keSJDz4qS9rdNbUgaguzQ/7eGajHnecNBoAYHf5MjjjVcGRyBw1tjlhd8XeDB5OzYHgxu41e5q7/JhEvRGDIyKiGIyutOKcQ6sAAH/4aCO8XinkPku3NWLFziaYDXpcf8KIqI85Z1wlpg0ukX+vzhwV55nkcl4yskc1/sxRaYEFAIMjonAYHBERxejmn4xEvtmAtXua8cH3+4I+tqepA7/79zoAwC+mD5KzPpHodDr85uQx0OuAQX3y0K8oJ+Tjyew7EsHRKRP7AWBwRBQOgyMiohiVF+bgmmOHAQAe/HSzXOraVGvDmc9+jd0HOjCgOBfX+ZutYzFlUAnem3sUXr18elAztpCsiTVJkuTg6FT/fqOdje1o7nB26XGJeiMGR0REcbjsqKHoV5SDvc2d+OvSnfh2VxPOfm4Z6lsdGFVRiHevOUIuW8VqwsAiVPXJ0/xYsjJHB9qd6HB6oNMB4wdY5X4oZo+IQjE4IiKKQ67ZgNtPHAXAN7l2wV9WwGZ3Y9rgErx11QxUqkpjXZWszJHIGvWz5sBiNOCQqmIADI6ItDA4IiKK02mTBmDiwCJ0OD1wuL04YXQ5/n7ZdBTlJf9w2GRljsQYv8hQieDoO27KJgrRY4Kj++67D0cccQTy8vJQXFyseR+dThfy64033gi6zxdffIEpU6bAYrFg+PDhePnll1N/8UTUq+j1Otx72nj0L8rBhYcPxp8vnIpc/1RZsiVr19Fu/xj/IFVwtPbH5qADcImoBx0863Q6cdZZZ2HGjBn461//GvZ+L730Ek488UT598pAaufOnTj55JNx9dVX49VXX8WiRYtw+eWXo1+/fpgzZ04qL5+IeplJVcX46o7jNZuok2lAsS+YqbXZ4fZ4YTQk9m9aUVYTwdGYflaYjXo0d7iw60BHxJ1MRNmmxwRH8+fPB4ComZ7i4mJUVlZqfuy5555DdXU1HnnkEQDAmDFjsHTpUvzpT39icEREcUt1YAQA5YUWmAw6uDwSam12DCzRbtyORg6O+vo+32zUY1x/K76racaaPQcZHBEp9JiyWqzmzp2L0tJSHHbYYXjxxReD0sXLli3DrFmzgu4/Z84cLFu2LOzjORwO2Gy2oF9EROmi1+vQr6jrfUd7VJkjIFBaW6PqO3r2i+2Y86cvsbOxPeHnI+rJelVw9Pvf/x5vvfUWFi5ciDPPPBPXXnstnnzySfnjtbW1qKioCPqciooK2Gw2dHZq/9BZsGABioqK5F9VVVUp/RqIiNTkpmxF35HXK2F1zUE0tDqifr7d5ZEPzNUMjhQTa6+tqMEDn27C5rpWPLU48jlyRL1VRstqd9xxBx544IGI99m4cSNGjx4d0+Pddddd8v9PnjwZ7e3teOihh3DDDTckfI133nknbrnlFvn3NpuNARIRpZU8zu/PHDndXtz85hp89MN+AL6AZ+rgEkwZVIxjRpZhcN/gEtmPBzshSUC+2YA++Wb59slVvqNLNuy3we7yYNmOA7jrvXXyxz9Yuw+/PmkUyguTu56AqLvLaHB066234uKLL454n6FDhyb8+NOnT8e9994Lh8MBi8WCyspK1NXVBd2nrq4OVqsVubnaq/4tFgsslvgWuhERJZMyc2R3eXDtq6uxeFM9DHodvP7N1zVNHfjXd3thNuqx9PbjUG4NBDRySa1vflCfVFWfXPTNN+NAuxNvr/oRCz7eCI9XwhlTBmBnYzu+q2nGP5bX4JafjEzvF0yUYRkNjsrKylBWVpayx1+zZg1KSkrk4GbGjBn4+OOPg+6zcOFCzJgxI2XXQETUVSJztK2+DZe98i2+2nYAFqMez/9yGiYPKsaammasrjmIN7/dg/0tdizaVI/zDhskf35gUi34H4E6nQ6HVBVj0aZ63OU/F+7I4X1x/xkT8d8Ntbjute/w6vLduPbYYcgxJXdVgcPtwb5mO3482IEDbU4cM7IsKKtFlEk9ZlqtpqYGTU1NqKmpgcfjwZo1awAAw4cPR0FBAT744APU1dXh8MMPR05ODhYuXIg//vGP+NWvfiU/xtVXX42nnnoKt99+Oy699FIsXrwYb731Fj766KMMfVVERNEN9GeOVu4+CMBXHvvrxYfi8KF9AQDHjCzDMSPLYNDp8MjCLVgcNjgKnXQTwREAjKooxLMXTIXZqMeJ4yoxoDgXe5s78f6afTj70K61E7g9XnyxuQHvrv4R39U0o67VDuV6pZPGV+LZC6Z26TmIkqXHNGTffffdmDx5MubNm4e2tjZMnjwZkydPxsqVKwEAJpMJTz/9NGbMmIFDDjkEf/7zn/Hoo49i3rx58mNUV1fjo48+wsKFCzFp0iQ88sgj+Mtf/sIxfiLq1kTmCACsOUb84/LpcmCkdNzocgDA0q2N8qG4QOTg6IjhvsepsFrw0iWHwprj2/JtNOhx0RGDAQAvfrUz4UWRW+ta8cePN+LwBYtx+d9W4pN1tai1+QKjHJMeQ/0rBBZvqkeH053QcwBAu8ONU59cijv/+X3Cj0Ek6CSuRo2LzWZDUVERWlpaYLVaM305RJQFXB4vjn/kC3Q6vXjl0kMxrn+R5v0kScLhCxahzubAK5cehpkjfW0Lc/70JTbXtQbdpvT19kYMLy8Iabxu6XRhxoJF6HB68I/LpuOoEaVxXffr39Tgzn/+IP++b74ZP5s8ACeNr8SQ0nz09ZfRjn7wc/x4sBPPXTAVJ47X3lMXzeJNdbj05ZXQ64C182ajMCf5R7lQzxbP+3ePyRwREWUrk0GPhTfPxNJfHxc2MAJ8PUTH+7NHn/tLZZK/YRvQzhwBwBHDSjUn0opyTThr6kAAvuxRPLbVt+Ge99cDAI4dVYY/XzgVy+48AXedMhbThvRBaYFFPuZp9lhfQLRwQ12kh4zo+x9bAABeiYfpUtcxOCIi6gFyTIaYmqKPG+ULjhZtqoMkSWhsc6LT5YFOF5h6i8fFR1ZDp/OVvbY3tMX0OS6Pb9WAw+3F0SNK8dLFh2LOuEqYjdpvOT8Z69s/t3hTHdweb9zXCADr9rbI/79y18GEHoNIYHBERNSLHDm8FGaDHnuaOrG9oU3OGvUvyg0bnERSXZqPE/zZqMc/24pOpyfKZwBPLt6GH/a2oCjXhId+PinqMSuHDilBcZ4JBztcctN5vH5QBEerEnwMIoHBERFRL5JvMeLwYb4m68Wb6jWPDYnXZUf59s29v3YfZty/CA98ugn7mrVPFfiu5iCe/ty3WfsPPxuPyqLoCySNBj2O92e8Eimt1dvsqLMFNoV/V3MQHi/baSlxDI6IiHqZ40f5mq4XbazH7gNdD45mDOuLB86cgKo+uWjucOHZL7bj6Ac/xzX/WIW3Vu7BzsZ2SJKEDqcbt7y1Fh6vhNMO6Y9TJ/WP+Tlmj/OV1hZuqIt7Mk5kjYaV5aPQYkS704NNtTwHkxLXY/YcERFRbI4fXYF7PtiAlbsPwprrm9oa1Dfx4AgAzjl0EH4+tQqLNtbhpa92YdmOA/hkXS0+WVcLACgtsKC0wIydje2otObg9/83Pq7HP3pEGcxGPWqaOrClrg2jKgtj/lzRjD2pqhgNrQ78b2sjVu0+GLF5nSgSZo6IiHqZQX3zMLy8AB6vhMX+qbWqLmSOBINeh9njKvH6lYfjkxuPxjXHDsOhQ0pgNujR2ObAptpWAMDDZ01CUV58o/T5FiOOGu5bFfDf9bVxfa5oxp4woAhTB/vOi2PfEXUFM0dERL3Q8aPLsa2+Te69GZyE4EhpTD8rxvTz7YqxuzxYt7cFq3YfxKA+eXHvQxJmj63A4k31WLixDtefMCLmz/veHxxNHFiETqdv2o0Ta9QVzBwREfVCYqRf6ErPUTQ5JgOmDemDq2YOw0kT+iX8OCeMqYBO5yuT7W/RbvhWq7PZ0dDqgF4HjO1XhEMGFUOv8x3SW9tiT/haKLsxOCIi6oWmDSlBYY6vOFBoMaI4zjJXJpQVWjC5qhgA8FmMU2ui32hEeSFyzQYUWIwYXenLaLG0RolicERE1AuZDHoc4z8qpKpPXtRdQ93F7HG+bdn/jTE4EpNq4wcEmq+nDfH1Ha3c3ZTkq6NsweCIiKiXOs0/Sj9lcHFmLyQOYlv28h0H8PbKPWhodUS8/zpFv5EgmrJXM3NECWJDNhFRLzV7XCU+vuFoDClNXb9Rsg0rK8CoikJsrmvFbe98D8AX+Bw7qhwXHD4o6Aw4SZLkspoycySCo/X7bOh0epBrjn7sCpESM0dERL3Y2P5W5Jl71r+D/3LRNFx//HCMH+DrHfr+xxY8sWgrznt+OVyKs9fqbA40tolm7MAp6wOKc1FpzYHbK/EQWkoIgyMiIupWqvrk4dbZo/Dh9Ufjm9+egId+PhF9883Y3tCOfyzfLd/v+x+bAQAjKwqDskM6nQ5T/X1Hq2sCpbXaFjsufflbzH1tNRxu7TPivF4JCz7ZiBvf+A5N7c6Yr7nOZsfFL32Dvy3bFcdXSt0VgyMiIuq2ygtzcNa0KtwyeyQA4LHPtqK5wxe0rNNoxhamDvI3Ze/yNWWv3dOM/3tqKRZvqsdH3+/H3f9er3lMyROLt+LPS3bgvTX7cMYzX2FnY3vUa/R4Jdz4xnf4YnMD5r2/Hst3HEjsi6Vug8ERERF1e+dMq8KoikK0dLrw+KKtAIKXP6qJibVVuw/ivTV7cfafl6G+1YHBffOg1wFvrtyDf6yoCfqcT9ftx2Of+R67T74Zuw504PRnvsK3uyJPvT37xTYs3+G7jyQBN7+5Rg7g1OI9N44yg8ERERF1e0aDHr87ZQwA4O/LdmN7Q1vEzNGYflbkmgyw2d248Y01cLi9OH50OT68/ijcfuJoAMD899fjm52+oGZTrQ23vLUWAHDxEUPwn5uOwaSqYjR3uHD+Cyvw3pq9mte1ancT/uQPqO49bRyqS/Oxv8WOO979ISQQ+t/WBsxYsBjn/HkZ6m1cUBlOfasd+5pjWwKaKgyOiIioRzh6RBmOH10Ot1fCrW+tRWObEwa9LqgZWzAZ9JhUFQiarjpmKF745TQU5phw1TFDccrEfnB7JVz76ips2GfDFX9biQ6nB0cM64vfnTwGZYUWvHHF4ZgzrgJOjxc3vrEGv/v3D0Fbt1s6XLjh9TXweCX87JD+uODwwXji3MkwGXT4dH0tXv9mDwBfH9OTi7bily9+g1qbHSt2NuG0p7+Sgzul5g4nnli0FS99tRNeb2xZJo9Xwn/W1+KG17/Dwgj7obbVt+HyV1bihS93dCmD1dDqwHnPL8ek+f/FzIc+x2lPf4WLXvwGt729Fhv328J+ntcrYcWOA2HXM+xv6cQ976/H0Q98jvs/2ZTw9SWDTmKOLy42mw1FRUVoaWmB1Rr6F5KIiFJnW30bTnzsS7j9gcPoykJ8etMxmvf98Pt9ePDTzbjhhBH4+dSBQR/rcLpx5rPLsHG/DQa9Dh6vhEF98vDe3CNRkm+W7+fxSljw8Ub8ZelOAIDZqMcvDhuEa48dhnnvr8cn62oxuG8ePrz+KBTm+LaQP//ldvzx403IMenx6uXT8fTn2+UDgM+cMhBr9hzE9oZ25Jj0ePTsQ/DTCf3Q5nDjpaU78fyXO9DqcAPwnY/3p3MOQVGu9nbzTqcH76z+EX/93w7sOtAh337tscNw6+xRMOgDiz8Xb6rDja+vkR/7pPGVePisSci3xDfJ2NLpwrnPLw8bBOWY9HjgzIk47ZABQbfX2ey45a01+GrbAeh0wKGD++DE8ZU4cXwlPF4Jz3yxHe+s2gOXx/d9nTq4BK9fcTjMxuTlcOJ5/2ZwFCcGR0REmXXP++vx8te7AABnTxuIB38+KaHH2dPUgVOfWormDhfyzQb889ojMaqyUPO+X29vxGMLt+Ibf/+RUa+D2yvBqNfh3WuOwCT/sSeAL0Ny0Uvf4H9bG+XbLEY97v3ZeJw9rQo2uwvXv/YdlmxpAACcPnkAvtzSgAP+6bgR5QWoaeqAw+3FkL55eP6X0zCyInBdW+ta8e7qvXjz2xoc7HABAKw5RhxW3QefbfQFYceMLMMT5/oCq2e+2I6H/7sZkuQrN26rb4XLI2F0ZSFe+OU0VMV47l6H040L//oNVu0+iNICM57+xRQY9Doc7HChucOJ99fuk7/mS4+sxp0/HQ2TQY+FG+pw+ztrcbDDBZNBJwdAgl4HiCTZYdV9cMPxI3Dk8L5J3+rO4CiFGBwREWXWwXYnjn34C7R0unDvaeNw4YwhCT/Wyl1NeHzRVlx5zFAcPaIs4n0lScJX2w7gT59tkc9t+81PR+PKY4aF3LfeZseJj/8PTe1ODOqTh2fOnxLUG+X2eLHgk034qz8jBQBD+ubhltmjcMqEftiw34ar/r4Ke5s7kWc2YP7/jUNLpwv/+m4v1u8LZG2q+uTisiOrcda0KuRbjHhvzV78+t3vYXd5UdUnF2MqrfJRLBccPgh3nzIOP+xtxlV/X43GNgdK8kx46hdTcOTw0ohfu8PtweWvrMT/tjbCmmPEm1fNwBhVOdPjlfDows14+vPtAIDp1X0wvLwAr/ob38f1t+KJ8yYjx2TAp+tq8em6/Vi5+yAkCTh6RCmuO244pg/tG/E6uoLBUQoxOCIiyrwlWxrw3nd7Mf+0cXI5K10kScKy7QdQ3+rA/03qD71eO8Oxcb8Nn2+ux/mHDUZRmIN/3165B2+v/BFnTBmAM6cOhMkQKCM1tTtx/eur8dW24NUARr0Ox44qx8+nDsBPxlYGlc8AYMM+G676x0rsaeqU7z//tHE4f/pg+T77Wzpx1d9XyRvGK605GD+gCBMGFGHCQCvKC3NgNOhg1Oth1Ouw4JON+M/6OuSZDfjH5dMxxb8qQcun62px61tr0O4M7JK64uhq/GrOKFiMwdvK61vtsDu9GNQ39VvcGRylEIMjIiJKF7fHi4f+uxl/+d9OTBpYhNMnD8DJE/ujj6IvSktzhxN3vPsDNte14oEzJ+Kw6j4h97G7PJj33nq8tWoPYokEzAY9Xrrk0KhZJgDYVt+Kua9+h5ZOFx74+UTMHBk5K5cODI5SiMERERGlm9vjhdGQmgHzNocbG/bZ8MPeFqzf24J1+1rQ0umCxyvB5ZHg9nhhzTXh3tPGY5b/YOBYSJIESULYzFq6xfP+3bMO3CEiIspCqQqMAKDA4mvm1soudYVOp0OSe6rThnuOiIiIiBQYHBEREREpMDgiIiIiUmBwRERERKTA4IiIiIhIgcERERERkQKDIyIiIiIFBkdERERECgyOiIiIiBQYHBEREREpMDgiIiIiUmBwRERERKTA4IiIiIhIgcERERERkYIx0xfQ00iSBACw2WwZvhIiIiKKlXjfFu/jkTA4ilNraysAoKqqKsNXQkRERPFqbW1FUVFRxPvopFhCKJJ5vV7s27cPhYWF0Ol0SX1sm82Gqqoq7NmzB1arNamPTcH4WqcPX+v04WudPnyt0ydZr7UkSWhtbUX//v2h10fuKmLmKE56vR4DBw5M6XNYrVb+ZUsTvtbpw9c6ffhapw9f6/RJxmsdLWMksCGbiIiISIHBEREREZECg6NuxGKxYN68ebBYLJm+lF6Pr3X68LVOH77W6cPXOn0y8VqzIZuIiIhIgZkjIiIiIgUGR0REREQKDI6IiIiIFBgcERERESkwOOomnn76aQwZMgQ5OTmYPn06vvnmm0xfUo+3YMECHHrooSgsLER5eTl+9rOfYfPmzUH3sdvtmDt3Lvr27YuCggKceeaZqKury9AV9x73338/dDodbrrpJvk2vtbJs3fvXlxwwQXo27cvcnNzMWHCBKxcuVL+uCRJuPvuu9GvXz/k5uZi1qxZ2Lp1awavuGfyeDy46667UF1djdzcXAwbNgz33ntv0NlcfK0T9+WXX+LUU09F//79odPp8O9//zvo47G8tk1NTTj//PNhtVpRXFyMyy67DG1tbV2+NgZH3cCbb76JW265BfPmzcPq1asxadIkzJkzB/X19Zm+tB5tyZIlmDt3LpYvX46FCxfC5XJh9uzZaG9vl+9z880344MPPsDbb7+NJUuWYN++fTjjjDMyeNU937fffos///nPmDhxYtDtfK2T4+DBgzjyyCNhMpnwySefYMOGDXjkkUdQUlIi3+fBBx/EE088geeeew4rVqxAfn4+5syZA7vdnsEr73keeOABPPvss3jqqaewceNGPPDAA3jwwQfx5JNPyvfha5249vZ2TJo0CU8//bTmx2N5bc8//3ysX78eCxcuxIcffogvv/wSV155ZdcvTqKMO+yww6S5c+fKv/d4PFL//v2lBQsWZPCqep/6+noJgLRkyRJJkiSpublZMplM0ttvvy3fZ+PGjRIAadmyZZm6zB6ttbVVGjFihLRw4UJp5syZ0o033ihJEl/rZPr1r38tHXXUUWE/7vV6pcrKSumhhx6Sb2tubpYsFov0+uuvp+MSe42TTz5ZuvTSS4NuO+OMM6Tzzz9fkiS+1skEQPrXv/4l/z6W13bDhg0SAOnbb7+V7/PJJ59IOp1O2rt3b5euh5mjDHM6nVi1ahVmzZol36bX6zFr1iwsW7Ysg1fW+7S0tAAA+vTpAwBYtWoVXC5X0Gs/evRoDBo0iK99gubOnYuTTz456DUF+Fon0/vvv49p06bhrLPOQnl5OSZPnowXXnhB/vjOnTtRW1sb9FoXFRVh+vTpfK3jdMQRR2DRokXYsmULAGDt2rVYunQpTjrpJAB8rVMpltd22bJlKC4uxrRp0+T7zJo1C3q9HitWrOjS8/Pg2QxrbGyEx+NBRUVF0O0VFRXYtGlThq6q9/F6vbjppptw5JFHYvz48QCA2tpamM1mFBcXB923oqICtbW1GbjKnu2NN97A6tWr8e2334Z8jK918uzYsQPPPvssbrnlFvzmN7/Bt99+ixtuuAFmsxkXXXSR/Hpq/Uzhax2fO+64AzabDaNHj4bBYIDH48F9992H888/HwD4WqdQLK9tbW0tysvLgz5uNBrRp0+fLr/+DI4oK8ydOxfr1q3D0qVLM30pvdKePXtw4403YuHChcjJycn05fRqXq8X06ZNwx//+EcAwOTJk7Fu3To899xzuOiiizJ8db3LW2+9hVdffRWvvfYaxo0bhzVr1uCmm25C//79+Vr3ciyrZVhpaSkMBkPI1E5dXR0qKyszdFW9y3XXXYcPP/wQn3/+OQYOHCjfXllZCafTiebm5qD787WP36pVq1BfX48pU6bAaDTCaDRiyZIleOKJJ2A0GlFRUcHXOkn69euHsWPHBt02ZswY1NTUAID8evJnStfddtttuOOOO3DuuediwoQJuPDCC3HzzTdjwYIFAPhap1Isr21lZWXI4JLb7UZTU1OXX38GRxlmNpsxdepULFq0SL7N6/Vi0aJFmDFjRgavrOeTJAnXXXcd/vWvf2Hx4sWorq4O+vjUqVNhMpmCXvvNmzejpqaGr32cTjjhBPzwww9Ys2aN/GvatGk4//zz5f/na50cRx55ZMhKii1btmDw4MEAgOrqalRWVga91jabDStWrOBrHaeOjg7o9cFvkwaDAV6vFwBf61SK5bWdMWMGmpubsWrVKvk+ixcvhtfrxfTp07t2AV1q56akeOONNySLxSK9/PLL0oYNG6Qrr7xSKi4ulmprazN9aT3aNddcIxUVFUlffPGFtH//fvlXR0eHfJ+rr75aGjRokLR48WJp5cqV0owZM6QZM2Zk8Kp7D+W0miTxtU6Wb775RjIajdJ9990nbd26VXr11VelvLw86R//+Id8n/vvv18qLi6W3nvvPen777+XTjvtNKm6ulrq7OzM4JX3PBdddJE0YMAA6cMPP5R27twp/fOf/5RKS0ul22+/Xb4PX+vEtba2St9995303XffSQCkRx99VPruu++k3bt3S5IU22t74oknSpMnT5ZWrFghLV26VBoxYoR03nnndfnaGBx1E08++aQ0aNAgyWw2S4cddpi0fPnyTF9SjwdA89dLL70k36ezs1O69tprpZKSEikvL086/fTTpf3792fuonsRdXDE1zp5PvjgA2n8+PGSxWKRRo8eLT3//PNBH/d6vdJdd90lVVRUSBaLRTrhhBOkzZs3Z+hqey6bzSbdeOON0qBBg6ScnBxp6NCh0m9/+1vJ4XDI9+FrnbjPP/9c82f0RRddJElSbK/tgQMHpPPOO08qKCiQrFardMkll0itra1dvjadJClWfRIRERFlOfYcERERESkwOCIiIiJSYHBEREREpMDgiIiIiEiBwRERERGRAoMjIiIiIgUGR0REREQKDI6IiGIwZMgQPPbYY5m+DCJKAwZHRNTtXHzxxfjZz34GADj22GNx0003pe25X375ZRQXF4fc/u233+LKK69M23UQUeYYM30BRETp4HQ6YTabE/78srKyJF4NEXVnzBwRUbd18cUXY8mSJXj88ceh0+mg0+mwa9cuAMC6detw0kknoaCgABUVFbjwwgvR2Ngof+6xxx6L6667DjfddBNKS0sxZ84cAMCjjz6KCRMmID8/H1VVVbj22mvR1tYGAPjiiy9wySWXoKWlRX6+e+65B0BoWa2mpgannXYaCgoKYLVacfbZZ6Ourk7++D333INDDjkEf//73zFkyBAUFRXh3HPPRWtrq3yfd955BxMmTEBubi769u2LWbNmob29PUWvJhHFisEREXVbjz/+OGbMmIErrrgC+/fvx/79+1FVVYXm5mYcf/zxmDx5MlauXIlPP/0UdXV1OPvss4M+/5VXXoHZbMZXX32F5557DgCg1+vxxBNPYP369XjllVewePFi3H777QCAI444Ao899hisVqv8fL/61a9Crsvr9eK0005DU1MTlixZgoULF2LHjh0455xzgu63fft2/Pvf/8aHH36IDz/8EEuWLMH9998PANi/fz/OO+88XHrppdi4cSO++OILnHHGGeBxl0SZx7IaEXVbRUVFMJvNyMvLQ2VlpXz7U089hcmTJ+OPf/yjfNuLL76IqqoqbNmyBSNHjgQAjBgxAg8++GDQYyr7l4YMGYI//OEPuPrqq/HMM8/AbDajqKgIOp0u6PnUFi1ahB9++AE7d+5EVVUVAOBvf/sbxo0bh2+//RaHHnooAF8Q9fLLL6OwsBAAcOGFF2LRokW47777sH//frjdbpxxxhkYPHgwAGDChAldeLWIKFmYOSKiHmft2rX4/PPPUVBQIP8aPXo0AF+2Rpg6dWrI53722Wc44YQTMGDAABQWFuLCCy/EgQMH0NHREfPzb9y4EVVVVXJgBABjx45FcXExNm7cKN82ZMgQOTACgH79+qG+vh4AMGnSJJxwwgmYMGECzjrrLLzwwgs4ePBg7C8CEaUMgyMi6nHa2tpw6qmnYs2aNUG/tm7dimOOOUa+X35+ftDn7dq1C6eccgomTpyId999F6tWrcLTTz8NwNewnWwmkyno9zqdDl6vFwBgMBiwcOFCfPLJJxg7diyefPJJjBo1Cjt37kz6dRBRfBgcEVG3Zjab4fF4gm6bMmUK1q9fjyFDhmD48OFBv9QBkdKqVavg9XrxyCOP4PDDD8fIkSOxb9++qM+nNmbMGOzZswd79uyRb9uwYQOam5sxduzYmL82nU6HI488EvPnz8d3330Hs9mMf/3rXzF/PhGlBoMjIurWhgwZghUrVmDXrl1obGyE1+vF3Llz0dTUhPPOOw/ffvsttm/fjv/85z+45JJLIgY2w4cPh8vlwpNPPokdO3bg73//u9yorXy+trY2LFq0CI2NjZrltlmzZmHChAk4//zzsXr1anzzzTf45S9/iZkzZ2LatGkxfV0rVqzAH//4R6xcuRI1NTX45z//iYaGBowZMya+F4iIko7BERF1a7/61a9gMBgwduxYlJWVoaamBv3798dXX30Fj8eD2bNnY8KECbjppptQXFwMvT78j7VJkybh0UcfxQMPPIDx48fj1VdfxYIFC4Luc8QRR+Dqq6/GOeecg7KyspCGbsCX8XnvvfdQUlKCY445BrNmzcLQoUPx5ptvxvx1Wa1WfPnll/jpT3+KkSNH4ne/+x0eeeQRnHTSSbG/OESUEjqJc6NEREREMmaOiIiIiBQYHBEREREpMDgiIiIiUmBwRERERKTA4IiIiIhIgcERERERkQKDIyIiIiIFBkdERERECgyOiIiIiBQYHBEREREpMDgiIiIiUmBwRERERKTw/6t6vuTxnuMqAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -266,11 +261,10 @@ "source": [ "import matplotlib.pyplot as plt\n", "\n", - "fig, axes = plt.subplots(nrows=1, ncols=1)\n", - "axes.plot(cost_values)\n", - "axes.set_xlabel(\"Iterations\")\n", - "axes.set_ylabel(\"Cost\")\n", - "axes.set_title(\"Cost convergence\")" + "plt.plot(combi.cost_trace)\n", + "plt.xlabel(\"Iterations\")\n", + "plt.ylabel(\"Cost\")\n", + "plt.title(\"Cost convergence\")" ] }, { @@ -280,16 +274,18 @@ "source": [ "## 4. Present Quantum Results\n", "\n", - "we call the `get_results` method to get samples with the optimzied parameters. We hereby present the optimization results. Since this is a quantum solution with probabilistic results, there is a defined probability for each result to be obtained by a measurement (presented by an histogram), where the solution is chosen to be the most probable one.\n", + "We call the `sample` method to get samples with the optimzied parameters. We hereby present the optimization results. Since this is a quantum solution with probabilistic results, there is a defined probability for each result to be obtained by a measurement (presented by an histogram), where the solution is chosen to be the most probable one.\n", "\n", "We remind that in the notation of the solution \"0\" indicate \"-1\" spin value, and \"1\" indicates \"1\" spin value." ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 10, "id": "2c35bcde-2d6e-4ed0-aa70-325dbf5a7846", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { @@ -320,32 +316,32 @@ " \n", " \n", " 0\n", - " {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'...\n", - " 0.608887\n", + " {'z': [0, 0, 0, 0, 0, 0]}\n", + " 0.589355\n", " -180.0\n", " \n", " \n", - " 21\n", - " {'z_0': 1, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'...\n", - " 0.007812\n", + " 1\n", + " {'z': [0, 0, 0, 0, 0, 1]}\n", + " 0.045410\n", " -100.0\n", " \n", " \n", - " 19\n", - " {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'...\n", - " 0.008789\n", + " 2\n", + " {'z': [0, 0, 1, 0, 0, 0]}\n", + " 0.041992\n", " -100.0\n", " \n", " \n", - " 16\n", - " {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 1, 'z_4'...\n", - " 0.010254\n", + " 3\n", + " {'z': [0, 0, 0, 1, 0, 0]}\n", + " 0.038574\n", " -100.0\n", " \n", " \n", - " 14\n", - " {'z_0': 0, 'z_1': 0, 'z_2': 1, 'z_3': 0, 'z_4'...\n", - " 0.011230\n", + " 4\n", + " {'z': [0, 1, 0, 0, 0, 0]}\n", + " 0.038086\n", " -100.0\n", " \n", " \n", @@ -353,84 +349,119 @@ "" ], "text/plain": [ - " solution probability cost\n", - "0 {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'... 0.608887 -180.0\n", - "21 {'z_0': 1, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'... 0.007812 -100.0\n", - "19 {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4'... 0.008789 -100.0\n", - "16 {'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 1, 'z_4'... 0.010254 -100.0\n", - "14 {'z_0': 0, 'z_1': 0, 'z_2': 1, 'z_3': 0, 'z_4'... 0.011230 -100.0" + " solution probability cost\n", + "0 {'z': [0, 0, 0, 0, 0, 0]} 0.589355 -180.0\n", + "1 {'z': [0, 0, 0, 0, 0, 1]} 0.045410 -100.0\n", + "2 {'z': [0, 0, 1, 0, 0, 0]} 0.041992 -100.0\n", + "3 {'z': [0, 0, 0, 1, 0, 0]} 0.038574 -100.0\n", + "4 {'z': [0, 1, 0, 0, 0, 0]} 0.038086 -100.0" ] }, - "execution_count": 18, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "optimization_result = combi.get_results()\n", + "optimization_result = combi.sample(combi.optimized_params)\n", "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { "cell_type": "markdown", - "id": "06d70826-8ba1-4705-ae87-1a3c4ba5d69a", + "id": "242936e1-23e9-44c0-ae34-62dfbf61ce4b", "metadata": {}, "source": [ - "Best Solution:" + "We will also want to compare the optimized results to uniformly sampled results:" ] }, { "cell_type": "code", - "execution_count": 32, - "id": "1b2775b1-7b12-4a0a-9931-eacdee4e5127", + "execution_count": 11, + "id": "a26c4460-f73e-436e-ae26-26eaa485930e", "metadata": {}, + "outputs": [], + "source": [ + "uniform_result = combi.sample_uniform()" + ] + }, + { + "cell_type": "markdown", + "id": "70a99eba-a999-40c4-8030-b84cde4c5d0a", + "metadata": {}, + "source": [ + "And compare the histograms:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "67b0d5fa-49ee-4245-9953-3b4a937a3c08", + "metadata": { + "tags": [] + }, "outputs": [ { "data": { + "image/png": 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", "text/plain": [ - "{'z_0': 0, 'z_1': 0, 'z_2': 0, 'z_3': 0, 'z_4': 0, 'z_5': 0}" + "
" ] }, - "execution_count": 32, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "optimization_result.sort_values(by=\"cost\").iloc[0].solution" + "optimization_result[\"cost\"].plot(\n", + " kind=\"hist\",\n", + " bins=30,\n", + " edgecolor=\"black\",\n", + " weights=optimization_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"optimized\",\n", + ")\n", + "uniform_result[\"cost\"].plot(\n", + " kind=\"hist\",\n", + " bins=30,\n", + " edgecolor=\"black\",\n", + " weights=uniform_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"uniform\",\n", + ")\n", + "plt.legend()\n", + "plt.ylabel(\"Probability\", fontsize=16)\n", + "plt.xlabel(\"cost\", fontsize=16)\n", + "plt.tick_params(axis=\"both\", labelsize=14)" + ] + }, + { + "cell_type": "markdown", + "id": "06d70826-8ba1-4705-ae87-1a3c4ba5d69a", + "metadata": {}, + "source": [ + "Best Solution:" ] }, { "cell_type": "code", - "execution_count": 19, - "id": "81d6f1dd-7e65-4118-bc8b-9ee662c72a68", - "metadata": { - "tags": [] - }, + "execution_count": 13, + "id": "1b2775b1-7b12-4a0a-9931-eacdee4e5127", + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([[]], dtype=object)" + "{'z': [0, 0, 0, 0, 0, 0]}" ] }, - "execution_count": 19, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" - }, - { - "data": { - "image/png": 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8JSYmqrKyUg6HQ1VVVf0u093drTvvvFMlJSWaNWvWiAoGAADjy4RAJnd1dampqUkFBQX+sfDwcGVmZqqhoaHf5R5++GFNmzZNd999t373u98Nuh2PxyOPx+N/7Ha7JUler1derzeQkgdlj7CCur6xEEgPzs0Ndt8wMPpuBn0fe/TcjFDp+1DrCyiMnDx5Ut3d3YqNje0xHhsbq/379/e5zOuvv66f/vSnam5uHvJ2SktLVVJS0mv85ZdflsPhCKTkQT2ZFtTVjYkdO3YEvExNTc0oVILB0Hcz6PvYo+dmnO997+zsHNK8gMJIoE6fPq277rpLGzduVExMzJCXKygokMvl8j92u91KSEhQVlaWoqOjg1rjvOKdQV3fWNhTnD3kuV6vVzU1NVqwYIFsNtsoVoUvou9m0PexR8/NCJW+n7uyMZiAwkhMTIwiIiLU1tbWY7ytrU1xcXG95r///vs6dOiQbrnlFv+Yz+f7bMMTJujAgQO66qqrei1nt9tlt9t7jdtstqA33dMdFtT1jYXh9GA0eofB0Xcz6PvYo+dmnO99H2ptAd3AGhkZqZSUFNXW1vrHfD6famtrlZGR0Wv+nDlz9Pbbb6u5udn/9e1vf1vf+ta31NzcrISEhEA2DwAAxqGAL9O4XC7l5uYqNTVVaWlpKi8vV0dHh/Ly8iRJS5YsUXx8vEpLSxUVFaV58+b1WH7SpEmS1GscAABcmAIOIzk5OTpx4oQKCwvV2tqq5ORkVVdX+29qbWlpUXg4b+wKAACGZlg3sObn5ys/P7/P5+rq6gZcdtOmTcPZJAAAGKc4hQEAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMCoYYWRiooKOZ1ORUVFKT09XY2Njf3O/Z//+R+lpqZq0qRJuvjii5WcnKyf/exnwy4YAACMLwGHka1bt8rlcqmoqEi7d+9WUlKSsrOzdfz48T7nT5kyRd///vfV0NCgt956S3l5ecrLy9POnTtHXDwAAAh9AYeRsrIyLV26VHl5eUpMTFRlZaUcDoeqqqr6nP/Nb35Tt956q+bOnaurrrpKK1eu1Pz58/X666+PuHgAABD6JgQyuaurS01NTSooKPCPhYeHKzMzUw0NDYMub1mWXnnlFR04cEBPPPFEv/M8Ho88Ho//sdvtliR5vV55vd5ASh6UPcIK6vrGQiA9ODc32H3DwOi7GfR97NFzM0Kl70OtL8yyrCH/NT569Kji4+NVX1+vjIwM//iDDz6o1157Tbt27epzuVOnTik+Pl4ej0cRERF66qmn9M///M/9bqe4uFglJSW9xjdv3iyHwzHUcgEAgEGdnZ1avHixTp06pejo6H7nBXRmZLguueQSNTc368yZM6qtrZXL5dKsWbP0zW9+s8/5BQUFcrlc/sdut1sJCQnKysoacGeGY15x6N27sqc4e8hzvV6vampqtGDBAtlstlGsCl9E382g72OPnpsRKn0/d2VjMAGFkZiYGEVERKitra3HeFtbm+Li4vpdLjw8XFdffbUkKTk5Wfv27VNpaWm/YcRut8tut/cat9lsQW+6pzssqOsbC8PpwWj0DoOj72bQ97FHz8043/s+1NoCuoE1MjJSKSkpqq2t9Y/5fD7V1tb2uGwzGJ/P1+OeEAAAcOEK+DKNy+VSbm6uUlNTlZaWpvLycnV0dCgvL0+StGTJEsXHx6u0tFSSVFpaqtTUVF111VXyeDzasWOHfvazn+npp58O7p4AAICQFHAYycnJ0YkTJ1RYWKjW1lYlJyerurpasbGxkqSWlhaFh39+wqWjo0PLli3TX/7yF1100UWaM2eOnn/+eeXk5ARvLwAAQMga1g2s+fn5ys/P7/O5urq6Ho8fffRRPfroo8PZDAAAuADw2TQAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMGlYYqaiokNPpVFRUlNLT09XY2Njv3I0bN+rGG2/U5MmTNXnyZGVmZg44HwAAXFgCDiNbt26Vy+VSUVGRdu/eraSkJGVnZ+v48eN9zq+rq9N3v/tdvfrqq2poaFBCQoKysrJ05MiRERcPAABCX8BhpKysTEuXLlVeXp4SExNVWVkph8OhqqqqPuf//Oc/17Jly5ScnKw5c+bov/7rv+Tz+VRbWzvi4gEAQOibEMjkrq4uNTU1qaCgwD8WHh6uzMxMNTQ0DGkdnZ2d8nq9mjJlSr9zPB6PPB6P/7Hb7ZYkeb1eeb3eQEoelD3CCur6xkIgPTg3N9h9w8Douxn0fezRczNCpe9DrS/Msqwh/zU+evSo4uPjVV9fr4yMDP/4gw8+qNdee027du0adB3Lli3Tzp07tXfvXkVFRfU5p7i4WCUlJb3GN2/eLIfDMdRyAQCAQZ2dnVq8eLFOnTql6OjofucFdGZkpNauXastW7aorq6u3yAiSQUFBXK5XP7Hbrfbf6/JQDszHPOKdwZ1fWNhT3H2kOd6vV7V1NRowYIFstlso1gVvoi+m0Hfxx49NyNU+n7uysZgAgojMTExioiIUFtbW4/xtrY2xcXFDbjs+vXrtXbtWv32t7/V/PnzB5xrt9tlt9t7jdtstqA33dMdFtT1jYXh9GA0eofB0Xcz6PvYo+dmnO99H2ptAd3AGhkZqZSUlB43n567GfWLl23+1pNPPqlHHnlE1dXVSk1NDWSTAABgnAv4Mo3L5VJubq5SU1OVlpam8vJydXR0KC8vT5K0ZMkSxcfHq7S0VJL0xBNPqLCwUJs3b5bT6VRra6skaeLEiZo4cWIQdwUAAISigMNITk6OTpw4ocLCQrW2tio5OVnV1dWKjY2VJLW0tCg8/PMTLk8//bS6urr0ne98p8d6ioqKVFxcPLLqAQBAyBvWDaz5+fnKz8/v87m6uroejw8dOjScTQAAgAsEn00DAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAoyaYLgAAQpFzzXbTJQTs0NqFpksA+sSZEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFHDCiMVFRVyOp2KiopSenq6Ghsb+527d+9e3X777XI6nQoLC1N5eflwawUAAOPQhEAX2Lp1q1wulyorK5Wenq7y8nJlZ2frwIEDmjZtWq/5nZ2dmjVrlu644w7df//9QSkawPjiXLM9KOuxR1h6Mk2aV7xTnu6woKwTwOgLOIyUlZVp6dKlysvLkyRVVlZq+/btqqqq0po1a3rN/+pXv6qvfvWrktTn833xeDzyeDz+x263W5Lk9Xrl9XoDLXlA9ggrqOsbC4H04NzcYPcNA6PvgQnWz6E93OrxX/Q0Gscjx7oZodL3odYXZlnWkH9qu7q65HA4tG3bNi1atMg/npubq/b2dr300ksDLu90OnXffffpvvvuG3BecXGxSkpKeo1v3rxZDodjqOUCAACDOjs7tXjxYp06dUrR0dH9zgvozMjJkyfV3d2t2NjYHuOxsbHav3//8CrtQ0FBgVwul/+x2+1WQkKCsrKyBtyZ4ZhXvDOo6xsLe4qzhzzX6/WqpqZGCxYskM1mG8Wq8EX0PTDB+jm0h1t6JNWnh94Il8fHZZq/FcjvjqHiWDcjVPp+7srGYAK+TDMW7Ha77HZ7r3GbzRb0pofideXh9GA0eofB0fehCfbPoccXFpI/26NtNI9FjnUzzve+D7W2gF5NExMTo4iICLW1tfUYb2trU1xcXCCrAgAAkBRgGImMjFRKSopqa2v9Yz6fT7W1tcrIyAh6cQAAYPwL+DKNy+VSbm6uUlNTlZaWpvLycnV0dPhfXbNkyRLFx8ertLRU0mc3vb7zzjv+fx85ckTNzc2aOHGirr766iDuCgAACEUBh5GcnBydOHFChYWFam1tVXJysqqrq/03tba0tCg8/PMTLkePHtW1117rf7x+/XqtX79e3/jGN1RXVzfyPQAAACFtWDew5ufnKz8/v8/n/jZgOJ1OBfDqYQAAcIHhs2kAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRw/rUXuBC4VyzfVjL2SMsPZkmzSveKU93WJCrGtihtQvHdHsAMFKcGQEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFO8zAgA4bw33vX5M4r1+AseZEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGDXBdAEAAIwnzjXbR30b9ghLT6ZJ84p3ytMdNuL1HVq7MAhVDR9nRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRwwojFRUVcjqdioqKUnp6uhobGwec/8ILL2jOnDmKiorSV77yFe3YsWNYxQIAgPEn4DCydetWuVwuFRUVaffu3UpKSlJ2draOHz/e5/z6+np997vf1d13360333xTixYt0qJFi7Rnz54RFw8AAEJfwGGkrKxMS5cuVV5enhITE1VZWSmHw6Gqqqo+5//nf/6n/uEf/kGrVq3S3Llz9cgjj+i6667Tj3/84xEXDwAAQl9AH5TX1dWlpqYmFRQU+MfCw8OVmZmphoaGPpdpaGiQy+XqMZadna0XX3yx3+14PB55PB7/41OnTkmSPv74Y3m93kBKHtSETzuCur6x8NFHHw15rtfrVWdnpz766CPZbLZRrGp8Gu7xMcFnqbPTpwnecHX7Rv4hVoEI5Pg4XwTr59Bk30PBaBwbo/07JhR/R4+FYB/ro/V74/Tp05Iky7IGnBdQGDl58qS6u7sVGxvbYzw2Nlb79+/vc5nW1tY+57e2tva7ndLSUpWUlPQav/LKKwMpd9yK+aHpCjAUiw1t90I/Pkz1PRRc6MfGeBPMY320j43Tp0/r0ksv7ff5gMLIWCkoKOhxNsXn8+njjz/WZZddprAw/m8nEG63WwkJCfrzn/+s6Oho0+VcMOi7GfR97NFzM0Kl75Zl6fTp05oxY8aA8wIKIzExMYqIiFBbW1uP8ba2NsXFxfW5TFxcXEDzJclut8tut/cYmzRpUiCl4m9ER0ef1wfseEXfzaDvY4+emxEKfR/ojMg5Ad3AGhkZqZSUFNXW1vrHfD6famtrlZGR0ecyGRkZPeZLUk1NTb/zAQDAhSXgyzQul0u5ublKTU1VWlqaysvL1dHRoby8PEnSkiVLFB8fr9LSUknSypUr9Y1vfEM//OEPtXDhQm3ZskVvvPGGnnnmmeDuCQAACEkBh5GcnBydOHFChYWFam1tVXJysqqrq/03qba0tCg8/PMTLtdff702b96sH/zgB/qP//gPfelLX9KLL76oefPmBW8v0C+73a6ioqJel70wuui7GfR97NFzM8Zb38OswV5vAwAAMIr4bBoAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhZJx47LHHdP3118vhcPT7brVhYWG9vrZs2dJjTl1dna677jrZ7XZdffXV2rRp0+gXH8KG0veWlhYtXLhQDodD06ZN06pVq/Tpp5/2mEPfR8bpdPY6tteuXdtjzltvvaUbb7xRUVFRSkhI0JNPPmmo2vGloqJCTqdTUVFRSk9PV2Njo+mSxpXi4uJex/acOXP8z589e1bLly/XZZddpokTJ+r222/v9a7noYAwMk50dXXpjjvu0L333jvgvGeffVbHjh3zfy1atMj/3IcffqiFCxfqW9/6lpqbm3Xffffpe9/7nnbu3DnK1Yeuwfre3d2thQsXqqurS/X19Xruuee0adMmFRYW+ufQ9+B4+OGHexzb//Zv/+Z/zu12KysrSzNnzlRTU5PWrVun4uJi3nxxhLZu3SqXy6WioiLt3r1bSUlJys7O1vHjx02XNq5cc801PY7t119/3f/c/fffr1//+td64YUX9Nprr+no0aO67bbbDFY7TBbGlWeffda69NJL+3xOkvW///u//S774IMPWtdcc02PsZycHCs7OzuIFY5P/fV9x44dVnh4uNXa2uofe/rpp63o6GjL4/FYlkXfg2HmzJnWhg0b+n3+qaeesiZPnuzvuWVZ1urVq63Zs2ePQXXjV1pamrV8+XL/4+7ubmvGjBlWaWmpwarGl6KiIispKanP59rb2y2bzWa98MIL/rF9+/ZZkqyGhoYxqjA4ODNygVm+fLliYmKUlpamqqoqWV94z7uGhgZlZmb2mJ+dna2GhoaxLnPcaGho0Fe+8hX/OxRLn/XU7XZr7969/jn0feTWrl2ryy67TNdee63WrVvX41JYQ0OD/u7v/k6RkZH+sezsbB04cECffPKJiXJDXldXl5qamnocu+Hh4crMzOTYDbL33ntPM2bM0KxZs3TnnXeqpaVFktTU1CSv19vjezBnzhxdccUVIfc9CPjt4BG6Hn74Yf393/+9HA6HXn75ZS1btkxnzpzRihUrJEmtra09/mhKUmxsrNxut/7617/qoosuMlF2SOuvp+eeG2gOfR+6FStW6LrrrtOUKVNUX1+vgoICHTt2TGVlZZI+6/GVV17ZY5kvfh8mT5485jWHupMnT6q7u7vPY3f//v2Gqhp/0tPTtWnTJs2ePVvHjh1TSUmJbrzxRu3Zs0etra2KjIzsdb9abGys//dLqCCMnMfWrFmjJ554YsA5+/bt63Ez00Aeeugh/7+vvfZadXR0aN26df4wgs8Eu+8YnkC+Dy6Xyz82f/58RUZG6l/+5V9UWlo6bj67Axemm266yf/v+fPnKz09XTNnztR///d/j6v/USGMnMceeOAB/dM//dOAc2bNmjXs9aenp+uRRx6Rx+OR3W5XXFxcr7uw29raFB0dPa4O+sEEs+9xcXG9Xl1wrsdxcXH+/9L33kbyfUhPT9enn36qQ4cOafbs2f32WPr8+4DAxMTEKCIios++0tPRM2nSJH35y1/WwYMHtWDBAnV1dam9vb3H2ZFQ/B4QRs5jU6dO1dSpU0dt/c3NzZo8ebL//xwzMjK0Y8eOHnNqamqUkZExajWcj4LZ94yMDD322GM6fvy4pk2bJumznkZHRysxMdE/h773NpLvQ3Nzs8LDw/09z8jI0Pe//315vV7ZbDZJn/V49uzZXKIZpsjISKWkpKi2ttb/qjyfz6fa2lrl5+ebLW4cO3PmjN5//33dddddSklJkc1mU21trW6//XZJ0oEDB9TS0hJ6vz9M30GL4Dh8+LD15ptvWiUlJdbEiROtN99803rzzTet06dPW5ZlWb/61a+sjRs3Wm+//bb13nvvWU899ZTlcDiswsJC/zo++OADy+FwWKtWrbL27dtnVVRUWBEREVZ1dbWp3TrvDdb3Tz/91Jo3b56VlZVlNTc3W9XV1dbUqVOtgoIC/zro+8jU19dbGzZssJqbm63333/fev75562pU6daS5Ys8c9pb2+3YmNjrbvuusvas2ePtWXLFsvhcFg/+clPDFYe+rZs2WLZ7XZr06ZN1jvvvGPdc8891qRJk3q8egwj88ADD1h1dXXWhx9+aP3+97+3MjMzrZiYGOv48eOWZVnWv/7rv1pXXHGF9corr1hvvPGGlZGRYWVkZBiuOnCEkXEiNzfXktTr69VXX7Usy7J+85vfWMnJydbEiROtiy++2EpKSrIqKyut7u7uHut59dVXreTkZCsyMtKaNWuW9eyzz479zoSQwfpuWZZ16NAh66abbrIuuugiKyYmxnrggQcsr9fbYz30ffiampqs9PR069JLL7WioqKsuXPnWo8//rh19uzZHvP+9Kc/WTfccINlt9ut+Ph4a+3atYYqHl9+9KMfWVdccYUVGRlppaWlWX/4wx9MlzSu5OTkWNOnT7ciIyOt+Ph4Kycnxzp48KD/+b/+9a/WsmXLrMmTJ1sOh8O69dZbrWPHjhmseHjCLOsLr+0EAAAYY7zPCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKP+HyDdwHyRRT05AAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" } ], "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" + "optimization_result.sort_values(by=\"cost\").iloc[0].solution" ] }, { diff --git a/applications/physical_systems/ising_model/ising_model.qmod b/applications/physical_systems/ising_model/ising_model.qmod index a40985b4c..6108af2c7 100644 --- a/applications/physical_systems/ising_model/ising_model.qmod +++ b/applications/physical_systems/ising_model/ising_model.qmod @@ -1,10 +1,5 @@ qstruct QAOAVars { - z_0: qbit; - z_1: qbit; - z_2: qbit; - z_3: qbit; - z_4: qbit; - z_5: qbit; + z: qbit[6]; } @@ -13,7 +8,7 @@ qfunc main(params: real[10], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); repeat (i: 5) { - phase (-(((((((((((((40.0 * v.z_0) + (40.0 * v.z_1)) + (40.0 * v.z_2)) + (40.0 * v.z_3)) + (40.0 * v.z_4)) + (40.0 * v.z_5)) + ((10 - (20 * v.z_0)) * ((2 * v.z_1) - 1))) + ((10 - (20 * v.z_0)) * ((2 * v.z_5) - 1))) + ((10 - (20 * v.z_1)) * ((2 * v.z_2) - 1))) + ((10 - (20 * v.z_2)) * ((2 * v.z_3) - 1))) + ((10 - (20 * v.z_3)) * ((2 * v.z_4) - 1))) + ((10 - (20 * v.z_4)) * ((2 * v.z_5) - 1))) - 120.0), params[i]); + phase (-(((((((((((((40.0 * v.z[0]) + (40.0 * v.z[1])) + (40.0 * v.z[2])) + (40.0 * v.z[3])) + (40.0 * v.z[4])) + (40.0 * v.z[5])) + ((10 - (20 * v.z[0])) * ((2 * v.z[1]) - 1))) + ((10 - (20 * v.z[0])) * ((2 * v.z[5]) - 1))) + ((10 - (20 * v.z[1])) * ((2 * v.z[2]) - 1))) + ((10 - (20 * v.z[2])) * ((2 * v.z[3]) - 1))) + ((10 - (20 * v.z[3])) * ((2 * v.z[4]) - 1))) + ((10 - (20 * v.z[4])) * ((2 * v.z[5]) - 1))) - 120.0), params[i]); apply_to_all(lambda(q) { RX(params[5 + i], q); }, v); diff --git a/applications/physical_systems/ising_model/ising_model.synthesis_options.json b/applications/physical_systems/ising_model/ising_model.synthesis_options.json index cb806fc57..9c23bd269 100644 --- a/applications/physical_systems/ising_model/ising_model.synthesis_options.json +++ b/applications/physical_systems/ising_model/ising_model.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "ry", - "tdg", - "id", - "t", + "u1", "cx", - "sx", - "h", - "u2", - "y", - "s", "p", - "sdg", - "sxdg", + "cz", + "h", "x", - "cy", - "u1", + "sx", + "y", + "tdg", "rz", + "cy", + "id", + "s", "r", - "cz", + "t", "z", "rx", - "u" + "u", + "sdg", + "ry", + "sxdg", + "u2" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 234206522 + "random_seed": 2916469319 } } From af28c7ba964ac7c7220cee0a3d251a382545e22e Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Mon, 16 Dec 2024 11:04:37 +0200 Subject: [PATCH 19/32] updated timeouts --- tests/resources/timeouts.yaml | 26 ++++++++++++-------------- 1 file changed, 12 insertions(+), 14 deletions(-) diff --git a/tests/resources/timeouts.yaml b/tests/resources/timeouts.yaml index 1305243ce..93113b94e 100644 --- a/tests/resources/timeouts.yaml +++ b/tests/resources/timeouts.yaml @@ -125,12 +125,10 @@ HW_4_Bill_Wisotsky.ipynb: 300 hw_aware_synthesis.ipynb: 20 hybrid_qnn_for_subset_majority.ipynb: 120 inplace_prepare_int.qmod: 10 -integer_linear_programming.ipynb: 296 -integer_linear_programming.qmod: 340 -ising_model.ipynb: 48 -ising_model.qmod: 48 -knapsack_binary.ipynb: 72 -knapsack_binary.qmod: 52 +integer_linear_programming.ipynb: 400 +integer_linear_programming.qmod: 400 +ising_model.ipynb: 300 +ising_model.qmod: 300 knapsack_integer.ipynb: 116 knapsack_integer.qmod: 116 learning_optimization.ipynb: 80 @@ -140,16 +138,16 @@ linear_pauli_rotations.ipynb: 20 linear_pauli_rotations.qmod: 10 link_monitoring.ipynb: 76 link_monitoring.qmod: 88 -max_clique.ipynb: 276 -max_clique.qmod: 260 +max_clique.ipynb: 300 +max_clique.qmod: 300 max_cut.ipynb: 36 max_cut.qmod: 32 max_independent_set.ipynb: 60 max_independent_set.qmod: 64 max_induced_k_color_subgraph.ipynb: 1028 max_induced_k_color_subgraph.qmod: 1008 -max_k_vertex_cover.ipynb: 184 -max_k_vertex_cover.qmod: 148 +max_k_vertex_cover.ipynb: 300 +max_k_vertex_cover.qmod: 300 maximum_float_example.qmod: 10 maximum_integer_example.qmod: 10 mcx.ipynb: 236 @@ -197,8 +195,8 @@ patching_managment.ipynb: 36 PHASE.qmod: 10 phase_kickback.ipynb: 1000 phase_kickback.qmod: 1000 -portfolio_optimization.ipynb: 96 -portfolio_optimization.qmod: 112 +portfolio_optimization.ipynb: 400 +portfolio_optimization.qmod: 400 Preparation_for_Week2_Git_GitHub.ipynb: 20 prepare_bell_state.ipynb: 20 prepare_bell_state.qmod: 10 @@ -284,8 +282,8 @@ second_quantized_hamiltonian.qmod: 40 Session1.ipynb: 20 set_cover.ipynb: 1440 set_cover.qmod: 1216 -set_partition.ipynb: 152 -set_partition.qmod: 160 +set_partition.ipynb: 350 +set_partition.qmod: 350 shor.ipynb: 104 shor.qmod: 88 shor_modular_exponentiation.ipynb: 300 From f61ef26f1613894676eecce612b21d601b290e0e Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Mon, 16 Dec 2024 11:45:23 +0200 Subject: [PATCH 20/32] with portfolio optimization as well --- .../portfolio_optimization.ipynb | 488 ++++++------- .../portfolio_optimization.qmod | 678 +----------------- ...tfolio_optimization.synthesis_options.json | 44 +- tests/resources/timeouts.yaml | 3 +- 4 files changed, 260 insertions(+), 953 deletions(-) diff --git a/applications/finance/portfolio_optimization/portfolio_optimization.ipynb b/applications/finance/portfolio_optimization/portfolio_optimization.ipynb index 938fcaaba..5fff5f122 100644 --- a/applications/finance/portfolio_optimization/portfolio_optimization.ipynb +++ b/applications/finance/portfolio_optimization/portfolio_optimization.ipynb @@ -56,12 +56,6 @@ "execution_count": 1, "id": "952d49b3-5dc6-41a1-8822-0622df536cf7", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:07.327339Z", - "iopub.status.busy": "2024-05-07T15:06:07.326871Z", - "iopub.status.idle": "2024-05-07T15:06:07.542423Z", - "shell.execute_reply": "2024-05-07T15:06:07.541631Z" - }, "tags": [] }, "outputs": [], @@ -77,7 +71,7 @@ "source": [ "# The Portfolio Optimization Problem Parameters\n", "\n", - "First we define the parameters of the optimization problem, which include the expected return vector, the covariance matrix, the total budget and the asset-specific budgets:" + "First we define the parameters of the optimization problem, which include the expected return vector, the covariance matrix and the total budget:" ] }, { @@ -85,12 +79,6 @@ "execution_count": 2, "id": "6212e51c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:07.547954Z", - "iopub.status.busy": "2024-05-07T15:06:07.546656Z", - "iopub.status.idle": "2024-05-07T15:06:07.552727Z", - "shell.execute_reply": "2024-05-07T15:06:07.552195Z" - }, "pycharm": { "name": "#%%\n" }, @@ -99,17 +87,15 @@ "outputs": [], "source": [ "returns = np.array([3, 4, -1])\n", - "# fmt: off\n", "covariances = np.array(\n", " [\n", - " [ 0.9, 0.5, -0.7],\n", - " [ 0.5, 0.9, -0.2],\n", - " [-0.7, -0.2, 0.9],\n", + " [0.9, 0.5, -0.7],\n", + " [0.5, 0.9, -0.2],\n", + " [-0.7, -0.2, 0.9],\n", " ]\n", ")\n", - "# fmt: on\n", - "total_budget = 6\n", - "specific_budgets = [2, 2, 2]" + "\n", + "total_budget = 6" ] }, { @@ -127,12 +113,6 @@ "execution_count": 3, "id": "42650f31-8efe-4ca9-8ed6-f5d9d440bee4", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:07.556775Z", - "iopub.status.busy": "2024-05-07T15:06:07.555783Z", - "iopub.status.idle": "2024-05-07T15:06:07.565348Z", - "shell.execute_reply": "2024-05-07T15:06:07.564551Z" - }, "tags": [] }, "outputs": [], @@ -141,14 +121,11 @@ "num_assets = len(returns)\n", "\n", "# setting the variables\n", - "portfolio_model.w = pyo.Var(\n", - " range(num_assets),\n", - " domain=pyo.Integers,\n", - " bounds=lambda _, idx: (0, specific_budgets[idx]),\n", - ")\n", + "portfolio_model.w = pyo.Var(range(num_assets), domain=pyo.Integers, bounds=(0, 6))\n", + "\n", "w_array = list(portfolio_model.w.values())\n", "\n", - "# setting the constraint\n", + "# global budget constraint\n", "portfolio_model.budget_rule = pyo.Constraint(expr=(sum(w_array) <= total_budget))\n", "\n", "# setting the expected return and risk\n", @@ -163,102 +140,80 @@ }, { "cell_type": "markdown", - "id": "c671eeac-5b61-4ab4-9e92-cfcb2ed8170b", + "id": "ea100320-dab7-4a4c-aed9-e08e3a70fb78", "metadata": { "tags": [] }, "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):" + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` python class. Under the hood it tranlates the Pyomo model to a quantum model of the QAOA algorithm, with cost hamiltonian translated from the Pyomo model. We can choose the number of layers for the QAOA ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { "cell_type": "code", "execution_count": 4, - "id": "c044e30f-2b4f-41ef-9bc0-11b951cb88db", + "id": "9503e674-3194-44ad-b248-fffa6fc3a9b2", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:07.570439Z", - "iopub.status.busy": "2024-05-07T15:06:07.569306Z", - "iopub.status.idle": "2024-05-07T15:06:10.280055Z", - "shell.execute_reply": "2024-05-07T15:06:10.275821Z" - }, "tags": [] }, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "qaoa_config = QAOAConfig(num_layers=1)" - ] - }, - { - "cell_type": "markdown", - "id": "dce2689a-d47f-42c0-9468-5faa4da21d20", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" + "combi = CombinatorialProblem(pyo_model=portfolio_model, num_layers=3, penalty_factor=10)\n", + "\n", + "qmod = combi.get_model()" ] }, { "cell_type": "code", "execution_count": 5, - "id": "7c4a6a91-aece-4a3b-9fa2-e7f76c90f296", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:10.287616Z", - "iopub.status.busy": "2024-05-07T15:06:10.287145Z", - "iopub.status.idle": "2024-05-07T15:06:10.292183Z", - "shell.execute_reply": "2024-05-07T15:06:10.291510Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, + "id": "86d783b7-820a-40a8-90af-aedb735b7678", + "metadata": {}, "outputs": [], "source": [ - "optimizer_config = OptimizerConfig(max_iteration=60, alpha_cvar=0.7)" + "write_qmod(qmod, \"portfolio_optimization\")" ] }, { "cell_type": "markdown", - "id": "a78aeea0-246b-4a58-9d7f-94cded812348", + "id": "696f5c22-eb43-488a-a948-aa057c005bed", "metadata": {}, "source": [ - "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:" + "## Synthesizing the QAOA Circuit and Solving the Problem\n", + "\n", + "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" ] }, { "cell_type": "code", "execution_count": 6, - "id": "d3988443-adff-4196-981f-d22307de17c9", + "id": "25bc3abe-18a1-4e41-ab3d-084cd49d463b", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:10.297071Z", - "iopub.status.busy": "2024-05-07T15:06:10.295820Z", - "iopub.status.idle": "2024-05-07T15:06:12.171845Z", - "shell.execute_reply": "2024-05-07T15:06:12.171188Z" - }, "pycharm": { "name": "#%%\n" }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Opening: https://nightly.platform.classiq.io/circuit/79e25a43-a916-476c-a108-022dfec85da8?version=0.62.0.dev9\n" + ] + } + ], "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=portfolio_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" + "qprog = combi.get_qprog()\n", + "show(qprog)" ] }, { "cell_type": "markdown", - "id": "0d64c135-ec3b-490e-ae60-2d72f0ff633c", + "id": "b06ce4de-2fce-4360-bade-6af4d2c0558d", "metadata": {}, "source": [ "We also set the quantum backend we want to execute on:" @@ -267,111 +222,48 @@ { "cell_type": "code", "execution_count": 7, - "id": "e0b0013d-5152-4221-a8d5-d35820c3a878", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:12.174681Z", - "iopub.status.busy": "2024-05-07T15:06:12.174351Z", - "iopub.status.idle": "2024-05-07T15:06:12.190978Z", - "shell.execute_reply": "2024-05-07T15:06:12.190335Z" - }, - "tags": [] - }, + "id": "fcddad02-a283-4812-a22e-289da66dcae7", + "metadata": {}, "outputs": [], "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", + "from classiq.execution import *\n", "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", + "execution_preferences = ExecutionPreferences(\n", + " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\"),\n", ")" ] }, - { - "cell_type": "code", - "execution_count": 8, - "id": "804e8e99-2e63-43df-9168-f1cb8497bdad", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:12.193308Z", - "iopub.status.busy": "2024-05-07T15:06:12.192932Z", - "iopub.status.idle": "2024-05-07T15:06:12.333982Z", - "shell.execute_reply": "2024-05-07T15:06:12.333340Z" - } - }, - "outputs": [], - "source": [ - "write_qmod(qmod, \"portfolio_optimization\")" - ] - }, { "cell_type": "markdown", - "id": "b098aa8a-e47f-474a-b5a4-75f3b98d2628", + "id": "a22a913a-720f-4ca9-806f-3ae70a5ba57a", "metadata": {}, "source": [ - "## Synthesizing the QAOA Circuit and Solving the Problem\n", - "\n", - "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" + "We now solve the problem by calling the `optimize` method of the `CombinatorialProblem` object. For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`maxiter`) and the $\\alpha$-parameter (`quantile`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" ] }, { "cell_type": "code", - "execution_count": 9, - "id": "73cccd8c", + "execution_count": 8, + "id": "ff59d10e-c215-42a2-b232-df77fd775aff", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:12.336365Z", - "iopub.status.busy": "2024-05-07T15:06:12.336172Z", - "iopub.status.idle": "2024-05-07T15:06:14.856707Z", - "shell.execute_reply": "2024-05-07T15:06:14.855692Z" - }, - "pycharm": { - "name": "#%%\n" - }, "tags": [] }, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Opening: https://platform.classiq.io/circuit/5c17bd7f-2b65-4deb-94a5-6fb8708345d1?version=0.41.0.dev39%2B79c8fd0855\n" + "Optimization Progress: 61it [04:44, 4.67s/it] \n" ] } ], "source": [ - "qprog = synthesize(qmod)\n", - "show(qprog)" - ] - }, - { - "cell_type": "markdown", - "id": "45f19792-d1ec-48b4-bc15-0fe881e48cd9", - "metadata": {}, - "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "c6607c43-7b33-44dd-9e38-b90c2db888e5", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:14.861747Z", - "iopub.status.busy": "2024-05-07T15:06:14.861264Z", - "iopub.status.idle": "2024-05-07T15:06:18.624172Z", - "shell.execute_reply": "2024-05-07T15:06:18.623365Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "result = execute(qprog).result_value()" + "optimized_params = combi.optimize(execution_preferences, maxiter=60, quantile=0.7)" ] }, { "cell_type": "markdown", - "id": "90c622a1-d8ae-47ac-a924-86d5b73bbd45", + "id": "2d0f1a15-90ac-44dc-ae1b-b3c1c62d3d92", "metadata": {}, "source": [ "We can check the convergence of the run:" @@ -379,55 +271,75 @@ }, { "cell_type": "code", - "execution_count": 11, - "id": "7cff5dd0-312b-45b3-8af3-0fd6fa04b6e9", + "execution_count": 9, + "id": "858ea131-6109-47cc-ba00-55ba0e8f09f9", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:18.628597Z", - "iopub.status.busy": "2024-05-07T15:06:18.628037Z", - "iopub.status.idle": "2024-05-07T15:06:18.667398Z", - "shell.execute_reply": "2024-05-07T15:06:18.666685Z" - }, + "scrolled": true, "tags": [] }, "outputs": [ { "data": { - "image/jpeg": 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", "text/plain": [ - "" + "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 11, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "result.convergence_graph" + "import matplotlib.pyplot as plt\n", + "\n", + "plt.plot(combi.cost_trace)\n", + "plt.xlabel(\"Iterations\")\n", + "plt.ylabel(\"Cost\")\n", + "plt.title(\"Cost convergence\")" + ] + }, + { + "cell_type": "markdown", + "id": "23969de4-f4b9-4e55-a09d-df4cbe4eb3ac", + "metadata": { + "tags": [] + }, + "source": [ + "# Optimization Results" ] }, { "cell_type": "markdown", - "id": "a5a26d5c-ffc0-40bc-9964-e9fb6e16f232", + "id": "9159388c-fe90-436d-b0aa-9cf6d6148c5f", "metadata": {}, "source": [ - "And print the optimization results:" + "We can also examine the statistics of the algorithm. The optimization is always defined as a minimzation problem, so the positive maximization objective was tranlated to a negative minimization one by the Pyomo to qmod translator." + ] + }, + { + "cell_type": "markdown", + "id": "93232ede-dfc9-4eba-8270-e6039af36c38", + "metadata": {}, + "source": [ + "In order to get samples with the optimized parameters, we call the `sample` method:" ] }, { "cell_type": "code", - "execution_count": 12, - "id": "9e5789ba-f1a5-4108-a0fa-a1b90870da1f", + "execution_count": 10, + "id": "f0fb79e2-719a-42f6-a9bd-18a67d490aad", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:18.670930Z", - "iopub.status.busy": "2024-05-07T15:06:18.670670Z", - "iopub.status.idle": "2024-05-07T15:06:19.843274Z", - "shell.execute_reply": "2024-05-07T15:06:19.842574Z" - }, - "tags": [] + "scrolled": true }, "outputs": [ { @@ -451,144 +363,102 @@ " \n", " \n", " \n", + " solution\n", " probability\n", " cost\n", - " solution\n", - " count\n", " \n", " \n", " \n", " \n", - " 98\n", - " 0.003\n", - " -4.8\n", - " [1, 2, 1]\n", - " 3\n", + " 1022\n", + " {'w': [1, 2, 0], 'budget_rule_slack_var': [1, ...\n", + " 0.000488\n", + " -4.5\n", " \n", " \n", - " 141\n", - " 0.003\n", - " -4.8\n", - " [1, 2, 1]\n", - " 3\n", + " 847\n", + " {'w': [2, 2, 2], 'budget_rule_slack_var': [0, ...\n", + " 0.000488\n", + " -4.4\n", " \n", " \n", - " 35\n", - " 0.006\n", - " -4.8\n", - " [2, 1, 1]\n", - " 6\n", + " 367\n", + " {'w': [0, 3, 0], 'budget_rule_slack_var': [1, ...\n", + " 0.000977\n", + " -3.9\n", " \n", " \n", - " 5\n", - " 0.010\n", - " -4.8\n", - " [2, 1, 1]\n", - " 10\n", + " 101\n", + " {'w': [1, 3, 1], 'budget_rule_slack_var': [1, ...\n", + " 0.001465\n", + " -3.7\n", " \n", " \n", - " 210\n", - " 0.002\n", - " -4.8\n", - " [1, 2, 1]\n", - " 2\n", + " 1023\n", + " {'w': [2, 1, 0], 'budget_rule_slack_var': [0, ...\n", + " 0.000488\n", + " -3.5\n", " \n", " \n", "\n", "" ], "text/plain": [ - " probability cost solution count\n", - "98 0.003 -4.8 [1, 2, 1] 3\n", - "141 0.003 -4.8 [1, 2, 1] 3\n", - "35 0.006 -4.8 [2, 1, 1] 6\n", - "5 0.010 -4.8 [2, 1, 1] 10\n", - "210 0.002 -4.8 [1, 2, 1] 2" + " solution probability cost\n", + "1022 {'w': [1, 2, 0], 'budget_rule_slack_var': [1, ... 0.000488 -4.5\n", + "847 {'w': [2, 2, 2], 'budget_rule_slack_var': [0, ... 0.000488 -4.4\n", + "367 {'w': [0, 3, 0], 'budget_rule_slack_var': [1, ... 0.000977 -3.9\n", + "101 {'w': [1, 3, 1], 'budget_rule_slack_var': [1, ... 0.001465 -3.7\n", + "1023 {'w': [2, 1, 0], 'budget_rule_slack_var': [0, ... 0.000488 -3.5" ] }, - "execution_count": 12, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " portfolio_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=True).head(5)" + "optimization_result = combi.sample(optimized_params)\n", + "optimization_result.sort_values(by=\"cost\").head(5)" + ] + }, + { + "cell_type": "markdown", + "id": "ac53b57d-8168-498e-ab04-e8dcbea1cfc1", + "metadata": {}, + "source": [ + "We will also want to compare the optimized results to uniformly sampled results:" ] }, { "cell_type": "code", - "execution_count": 13, - "id": "05449034-19e5-4b5d-80ea-7b2ba7ccd877", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:19.845777Z", - "iopub.status.busy": "2024-05-07T15:06:19.845472Z", - "iopub.status.idle": "2024-05-07T15:06:19.849615Z", - "shell.execute_reply": "2024-05-07T15:06:19.848912Z" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "x = [2, 1, 1] , cost = -4.800000000000001\n" - ] - } - ], + "execution_count": 11, + "id": "843cff7f-5230-4855-a1dc-13cbe386fa40", + "metadata": {}, + "outputs": [], "source": [ - "idx = optimization_result.cost.idxmin()\n", - "print(\n", - " \"x =\", optimization_result.solution[idx], \", cost =\", optimization_result.cost[idx]\n", - ")" + "uniform_result = combi.sample_uniform()" ] }, { "cell_type": "markdown", - "id": "b170b0ef-1e3f-4680-a7d4-82b4e537d785", + "id": "9c96cee5-1621-41b1-ace7-b3b59104acb4", "metadata": {}, "source": [ - "And the histogram:" + "And compare the histograms:" ] }, { "cell_type": "code", - "execution_count": 14, - "id": "f48034c6-8000-4bcf-83b0-e3a76a38d9c7", + "execution_count": 12, + "id": "b6eaa101-6f7a-4497-a208-0b6a2d33416a", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:19.851995Z", - "iopub.status.busy": "2024-05-07T15:06:19.851643Z", - "iopub.status.idle": "2024-05-07T15:06:20.087635Z", - "shell.execute_reply": "2024-05-07T15:06:20.086888Z" - }, "tags": [] }, "outputs": [ { "data": { - "text/plain": [ - "array([[]], dtype=object)" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -598,7 +468,52 @@ } ], "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" + "optimization_result[\"cost\"].plot(\n", + " kind=\"hist\",\n", + " bins=40,\n", + " edgecolor=\"black\",\n", + " weights=optimization_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"optimized\",\n", + ")\n", + "uniform_result[\"cost\"].plot(\n", + " kind=\"hist\",\n", + " bins=40,\n", + " edgecolor=\"black\",\n", + " weights=uniform_result[\"probability\"],\n", + " alpha=0.6,\n", + " label=\"uniform\",\n", + ")\n", + "plt.legend()\n", + "plt.ylabel(\"Probability\", fontsize=16)\n", + "plt.xlabel(\"cost\", fontsize=16)\n", + "plt.tick_params(axis=\"both\", labelsize=14)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "05449034-19e5-4b5d-80ea-7b2ba7ccd877", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "x = [3, 1, 2] , cost = -4.6\n" + ] + } + ], + "source": [ + "best_solution = optimization_result.loc[optimization_result.cost.idxmin()]\n", + "print(\n", + " \"x =\",\n", + " best_solution.solution[\"w\"],\n", + " \", cost =\",\n", + " best_solution.cost,\n", + ")" ] }, { @@ -611,15 +526,9 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 43, "id": "324c9a09", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:06:20.092527Z", - "iopub.status.busy": "2024-05-07T15:06:20.091284Z", - "iopub.status.idle": "2024-05-07T15:06:20.178692Z", - "shell.execute_reply": "2024-05-07T15:06:20.177959Z" - }, "pycharm": { "name": "#%%\n" }, @@ -634,20 +543,21 @@ "\n", " Variables:\n", " w : Size=3, Index=w_index\n", - " Key : Lower : Value : Upper : Fixed : Stale : Domain\n", - " 0 : 0 : 1.9999999999999998 : 2 : False : False : Integers\n", - " 1 : 0 : 1.0000000000000002 : 2 : False : False : Integers\n", - " 2 : 0 : 1.0000000000000002 : 2 : False : False : Integers\n", + " Key : Lower : Value : Upper : Fixed : Stale : Domain\n", + " 0 : 0 : 2.0 : 6 : False : False : Integers\n", + " 1 : 0 : 1.0 : 6 : False : False : Integers\n", + " 2 : 0 : 1.0 : 6 : False : False : Integers\n", "\n", " Objectives:\n", " cost : Size=1, Index=None, Active=True\n", " Key : Active : Value\n", - " None : True : -4.8\n", + " None : True : -4.800000000000001\n", "\n", " Constraints:\n", " budget_rule : Size=1\n", " Key : Lower : Body : Upper\n", - " None : None : 4.0 : 6.0\n" + " None : None : 4.0 : 6.0\n", + "Classical solution: [2, 1, 1]\n" ] } ], @@ -657,7 +567,11 @@ "solver = SolverFactory(\"couenne\")\n", "solver.solve(portfolio_model)\n", "\n", - "portfolio_model.display()" + "portfolio_model.display()\n", + "classical_solution = [\n", + " round(pyo.value(portfolio_model.w[i])) for i in range(len(portfolio_model.w))\n", + "]\n", + "print(\"Classical solution:\", classical_solution)" ] }, { @@ -704,7 +618,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" }, "vscode": { "interpreter": { diff --git a/applications/finance/portfolio_optimization/portfolio_optimization.qmod b/applications/finance/portfolio_optimization/portfolio_optimization.qmod index f5008b88e..363c48bc6 100644 --- a/applications/finance/portfolio_optimization/portfolio_optimization.qmod +++ b/applications/finance/portfolio_optimization/portfolio_optimization.qmod @@ -1,667 +1,17 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=7.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=0.8 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=0.8 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=0.8 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=0.8 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-0.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-0.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-0.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=0.65 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=0.65 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=0.65 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=0.65 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=0.9 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=0.9 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=0.9 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=0.9 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=1.25 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=6.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=1.45 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=1.45 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.45 - } -]; - -qfunc main(params_list: real[2], output target: qbit[9]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + w: qnum<3, False, 0>[3]; + budget_rule_slack_var: qbit[3]; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=False, -initial_point=[0.0, 0.2239532619279455], -optimizer=Optimizer.COBYLA, -max_iteration=60, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=0.7 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[6], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 3) { + phase (-(((((((v.w[0] * (((0.9 * v.w[0]) + (0.5 * v.w[1])) - (0.7 * v.w[2]))) - (3 * v.w[0])) + (v.w[1] * (((0.5 * v.w[0]) + (0.9 * v.w[1])) - (0.2 * v.w[2])))) - (4 * v.w[1])) + (v.w[2] * ((((-0.7) * v.w[0]) - (0.2 * v.w[1])) + (0.9 * v.w[2])))) + v.w[2]) + (360.0 * ((((((((0.1667 * v.budget_rule_slack_var[0]) + (0.3333 * v.budget_rule_slack_var[1])) + (0.5 * v.budget_rule_slack_var[2])) + (0.1667 * v.w[0])) + (0.1667 * v.w[1])) + (0.1667 * v.w[2])) - 1) ** 2))), params[i]); + apply_to_all(lambda(q) { + RX(params[3 + i], q); + }, v); + } +} diff --git a/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json b/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json index 0967ef424..cf711f93e 100644 --- a/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json +++ b/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json @@ -1 +1,43 @@ -{} +{ + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "tdg", + "z", + "u2", + "id", + "s", + "rz", + "sx", + "sdg", + "cy", + "x", + "cz", + "u", + "y", + "t", + "u1", + "rx", + "h", + "p", + "cx", + "r", + "ry", + "sxdg" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 3453328217 + } +} diff --git a/tests/resources/timeouts.yaml b/tests/resources/timeouts.yaml index 93113b94e..49a59efc6 100644 --- a/tests/resources/timeouts.yaml +++ b/tests/resources/timeouts.yaml @@ -1,3 +1,4 @@ + 3_sat_grover.ipynb: 36 3_sat_grover.qmod: 48 3_sat_grover_large.qmod: 10 @@ -324,4 +325,4 @@ whitebox_fuzzing.ipynb: 720 whitebox_fuzzing.qmod: 720 X.qmod: 10 Yasir_Mansour_HW3_VQE.ipynb: 30 -Yasir_Mansour_HW4_molecule_eigensolver.ipynb: 600 +Yasir_Mansour_HW4_molecule_eigensolver.ipynb: 600 \ No newline at end of file From 5c49b473d0caf6565cefdde343dcc4566e3cc4ac Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Mon, 16 Dec 2024 15:07:52 +0200 Subject: [PATCH 21/32] fixed failing notebooks --- .../optimization/set_partition/set_partition.ipynb | 12 +++++++++++- tests/resources/timeouts.yaml | 7 +++---- 2 files changed, 14 insertions(+), 5 deletions(-) diff --git a/applications/optimization/set_partition/set_partition.ipynb b/applications/optimization/set_partition/set_partition.ipynb index 2e8d0247c..a08237c9a 100644 --- a/applications/optimization/set_partition/set_partition.ipynb +++ b/applications/optimization/set_partition/set_partition.ipynb @@ -598,7 +598,17 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 40, + "id": "4a8215b7-1a7c-4f6c-ad8f-24754816038c", + "metadata": {}, + "outputs": [], + "source": [ + "classical_solution = [pyo.value(set_partition_model.x[i]) for i in range(len(mylist))]" + ] + }, + { + "cell_type": "code", + "execution_count": 41, "id": "a7524894-b5c5-42d4-8f92-a019bef5e7da", "metadata": { "tags": [] diff --git a/tests/resources/timeouts.yaml b/tests/resources/timeouts.yaml index 49a59efc6..a461d6ace 100644 --- a/tests/resources/timeouts.yaml +++ b/tests/resources/timeouts.yaml @@ -1,4 +1,3 @@ - 3_sat_grover.ipynb: 36 3_sat_grover.qmod: 48 3_sat_grover_large.qmod: 10 @@ -147,8 +146,8 @@ max_independent_set.ipynb: 60 max_independent_set.qmod: 64 max_induced_k_color_subgraph.ipynb: 1028 max_induced_k_color_subgraph.qmod: 1008 -max_k_vertex_cover.ipynb: 300 -max_k_vertex_cover.qmod: 300 +max_k_vertex_cover.ipynb: 600 +max_k_vertex_cover.qmod: 600 maximum_float_example.qmod: 10 maximum_integer_example.qmod: 10 mcx.ipynb: 236 @@ -325,4 +324,4 @@ whitebox_fuzzing.ipynb: 720 whitebox_fuzzing.qmod: 720 X.qmod: 10 Yasir_Mansour_HW3_VQE.ipynb: 30 -Yasir_Mansour_HW4_molecule_eigensolver.ipynb: 600 \ No newline at end of file +Yasir_Mansour_HW4_molecule_eigensolver.ipynb: 600 From 7731ee6cc6a641259b6613824b711df068679e38 Mon Sep 17 00:00:00 2001 From: ori-opher Date: Mon, 16 Dec 2024 18:15:54 +0200 Subject: [PATCH 22/32] Fix imports --- .../shor/shor_modular_exponentiation.ipynb | 8 ++--- ...Hisham_Mansour_HW4_qpe_for_molecules.ipynb | 36 +------------------ 2 files changed, 5 insertions(+), 39 deletions(-) diff --git a/algorithms/algebraic/shor/shor_modular_exponentiation.ipynb b/algorithms/algebraic/shor/shor_modular_exponentiation.ipynb index 30dbe04b2..203ed5548 100644 --- a/algorithms/algebraic/shor/shor_modular_exponentiation.ipynb +++ b/algorithms/algebraic/shor/shor_modular_exponentiation.ipynb @@ -175,7 +175,7 @@ "metadata": {}, "outputs": [], "source": [ - "from classiq.qmod import QNum, bind, control, within_apply\n", + "from classiq import *\n", "from classiq.qmod.builtins.classical_functions import qft_const_adder_phase\n", "\n", "\n", @@ -256,7 +256,7 @@ }, "outputs": [], "source": [ - "from classiq.qmod import QNum, inplace_prepare_int\n", + "from classiq import *\n", "\n", "modulo_num = 15\n", "reg_len = math.ceil(math.log(modulo_num, 2)) + 1\n", @@ -441,7 +441,7 @@ "metadata": {}, "outputs": [], "source": [ - "from classiq.qmod import SWAP, free\n", + "from classiq import *\n", "from classiq.qmod.symbolic import min, mod_inverse\n", "\n", "\n", @@ -535,7 +535,7 @@ "metadata": {}, "outputs": [], "source": [ - "from classiq.qmod import hadamard_transform\n", + "from classiq import *\n", "\n", "modulo_num = 6\n", "reg_len = math.ceil(math.log(modulo_num, 2)) + 1\n", diff --git a/community/QClass_2024/Submissions/HW4/Hisham_Mansour_HW4_qpe_for_molecules.ipynb b/community/QClass_2024/Submissions/HW4/Hisham_Mansour_HW4_qpe_for_molecules.ipynb index df5cc39bf..4108a8bdf 100644 --- a/community/QClass_2024/Submissions/HW4/Hisham_Mansour_HW4_qpe_for_molecules.ipynb +++ b/community/QClass_2024/Submissions/HW4/Hisham_Mansour_HW4_qpe_for_molecules.ipynb @@ -864,28 +864,7 @@ }, "outputs": [], "source": [ - "from classiq import molecule_problem_to_qmod\n", - "from classiq.qmod import (\n", - " CInt,\n", - " Output,\n", - " QArray,\n", - " QBit,\n", - " QCallable,\n", - " QNum,\n", - " allocate,\n", - " allocate_num,\n", - " control,\n", - " invert,\n", - " qfunc,\n", - " repeat,\n", - ")\n", - "from classiq.qmod.builtins import (\n", - " H,\n", - " apply_to_all,\n", - " exponentiation_with_depth_constraint,\n", - " molecule_hartree_fock,\n", - " qft,\n", - ")\n", + "from classiq import *\n", "from classiq.qmod.symbolic import log, pi\n", "\n", "# this constant will be multipled be a linear factor for each qbit of the qpe, so the\n", @@ -1410,19 +1389,6 @@ "plt.show()" ] }, - { - "cell_type": "markdown", - "id": "9797b512-d41f-47c1-8c0f-4134f0500b80", - "metadata": { - "id": "9797b512-d41f-47c1-8c0f-4134f0500b80" - }, - "source": [ - "## References\n", - "\n", - "[1]: [Michael A. Nielsen and Isaac L. Chuang. 2011. Quantum Computation and Quantum Information: 10th Anniversary Edition, Cambridge University Press, New York, NY, USA.\n", - "](http://mmrc.amss.cas.cn/tlb/201702/W020170224608149940643.pdf)\n" - ] - }, { "cell_type": "markdown", "id": "ttDDvHfPDI4y", From 37ec88ca90d370adc8554609ebe597e0e15abdb9 Mon Sep 17 00:00:00 2001 From: Ori Roth Date: Tue, 17 Dec 2024 13:26:45 +0200 Subject: [PATCH 23/32] Update qmods --- algorithms/dqi/dqi_max_xorsat.qmod | 90 +++++++++---------- .../dqi/dqi_max_xorsat.synthesis_options.json | 38 ++++---- .../grover/3_sat_grover/3_sat_grover.qmod | 2 +- .../3_sat_grover.synthesis_options.json | 41 ++++++++- .../3_sat_grover/3_sat_grover_large.qmod | 2 +- .../3_sat_grover_large.synthesis_options.json | 41 ++++++++- .../grover/grover_max_cut/grover_max_cut.qmod | 2 +- .../grover_max_cut.synthesis_options.json | 41 ++++++++- algorithms/hhl/hhl/hhl_exact.qmod | 12 +-- .../hhl/hhl/hhl_exact.synthesis_options.json | 31 +++---- algorithms/hhl/hhl/hhl_trotter.qmod | 8 +- .../hhl/hhl_trotter.synthesis_options.json | 31 +++---- .../portfolio_optimization.qmod | 2 - ...tfolio_optimization.synthesis_options.json | 32 +++---- .../integer_linear_programming.qmod | 2 - ..._linear_programming.synthesis_options.json | 32 +++---- .../optimization/max_clique/max_clique.qmod | 2 - .../max_clique.synthesis_options.json | 30 +++---- .../max_k_vertex_cover.qmod | 2 - .../max_k_vertex_cover.synthesis_options.json | 34 +++---- .../set_partition/set_partition.qmod | 4 +- .../set_partition.synthesis_options.json | 32 +++---- .../ising_model/ising_model.qmod | 2 - .../ising_model.synthesis_options.json | 32 +++---- 24 files changed, 325 insertions(+), 220 deletions(-) diff --git a/algorithms/dqi/dqi_max_xorsat.qmod b/algorithms/dqi/dqi_max_xorsat.qmod index 1db6c3d99..457376614 100644 --- a/algorithms/dqi/dqi_max_xorsat.qmod +++ b/algorithms/dqi/dqi_max_xorsat.qmod @@ -21,22 +21,22 @@ qfunc binary_to_one_hot_expanded___0(input binary: qnum<2, False, 0>, output one inplace_binary_to_one_hot_expanded___0(one_hot); } -qfunc iteration_lambda___0_0_expanded___0(qvar___3_captured__inplace_one_hot_to_unary__5: qbit, qvar___2_captured__inplace_one_hot_to_unary__5: qbit) { - CX(qvar___3_captured__inplace_one_hot_to_unary__5, qvar___2_captured__inplace_one_hot_to_unary__5); +qfunc iteration_0_lambda___0_0_expanded___0(qvar___3_captured__inplace_one_hot_to_unary__4: qbit, qvar___2_captured__inplace_one_hot_to_unary__4: qbit) { + CX(qvar___3_captured__inplace_one_hot_to_unary__4, qvar___2_captured__inplace_one_hot_to_unary__4); } -qfunc iteration_lambda___0_0_expanded___1(qvar___2_captured__inplace_one_hot_to_unary__5: qbit, qvar___1_captured__inplace_one_hot_to_unary__5: qbit) { - CX(qvar___2_captured__inplace_one_hot_to_unary__5, qvar___1_captured__inplace_one_hot_to_unary__5); +qfunc iteration_0_lambda___0_0_expanded___1(qvar___2_captured__inplace_one_hot_to_unary__4: qbit, qvar___1_captured__inplace_one_hot_to_unary__4: qbit) { + CX(qvar___2_captured__inplace_one_hot_to_unary__4, qvar___1_captured__inplace_one_hot_to_unary__4); } -qfunc iteration_lambda___0_0_expanded___2(qvar___1_captured__inplace_one_hot_to_unary__5: qbit, qvar___0_captured__inplace_one_hot_to_unary__5: qbit) { - CX(qvar___1_captured__inplace_one_hot_to_unary__5, qvar___0_captured__inplace_one_hot_to_unary__5); +qfunc iteration_0_lambda___0_0_expanded___2(qvar___1_captured__inplace_one_hot_to_unary__4: qbit, qvar___0_captured__inplace_one_hot_to_unary__4: qbit) { + CX(qvar___1_captured__inplace_one_hot_to_unary__4, qvar___0_captured__inplace_one_hot_to_unary__4); } qfunc inplace_one_hot_to_unary_expanded___0(qvar: qbit[4]) { - iteration_lambda___0_0_expanded___0(qvar[3], qvar[2]); - iteration_lambda___0_0_expanded___1(qvar[2], qvar[1]); - iteration_lambda___0_0_expanded___2(qvar[1], qvar[0]); + iteration_0_lambda___0_0_expanded___0(qvar[3], qvar[2]); + iteration_0_lambda___0_0_expanded___1(qvar[2], qvar[1]); + iteration_0_lambda___0_0_expanded___2(qvar[1], qvar[0]); X(qvar[0]); } @@ -165,37 +165,37 @@ qfunc prepare_dick_state_unary_input_expanded___5(qvar: qbit[6]) { prepare_dick_state_unary_input_expanded___4(qvar[1:6]); } -qfunc iteration_lambda___0_0_expanded___3(y___0_captured__vector_product_phase__3: qbit) { - Z(y___0_captured__vector_product_phase__3); +qfunc iteration_1_lambda___0_0_expanded___0(y___0_captured__vector_product_phase__2: qbit) { + Z(y___0_captured__vector_product_phase__2); } -qfunc iteration_lambda___0_0_expanded___4(y___1_captured__vector_product_phase__3: qbit) { - Z(y___1_captured__vector_product_phase__3); +qfunc iteration_1_lambda___0_0_expanded___1(y___1_captured__vector_product_phase__2: qbit) { + Z(y___1_captured__vector_product_phase__2); } -qfunc iteration_lambda___0_0_expanded___5(y___2_captured__vector_product_phase__3: qbit) { - Z(y___2_captured__vector_product_phase__3); +qfunc iteration_1_lambda___0_0_expanded___2(y___2_captured__vector_product_phase__2: qbit) { + Z(y___2_captured__vector_product_phase__2); } -qfunc iteration_lambda___0_0_expanded___6(y___3_captured__vector_product_phase__3: qbit) { - Z(y___3_captured__vector_product_phase__3); +qfunc iteration_1_lambda___0_0_expanded___3(y___3_captured__vector_product_phase__2: qbit) { + Z(y___3_captured__vector_product_phase__2); } -qfunc iteration_lambda___0_0_expanded___7(y___4_captured__vector_product_phase__3: qbit) { - Z(y___4_captured__vector_product_phase__3); +qfunc iteration_1_lambda___0_0_expanded___4(y___4_captured__vector_product_phase__2: qbit) { + Z(y___4_captured__vector_product_phase__2); } -qfunc iteration_lambda___0_0_expanded___8(y___5_captured__vector_product_phase__3: qbit) { - Z(y___5_captured__vector_product_phase__3); +qfunc iteration_1_lambda___0_0_expanded___5(y___5_captured__vector_product_phase__2: qbit) { + Z(y___5_captured__vector_product_phase__2); } qfunc vector_product_phase_expanded___0(y: qbit[6]) { - iteration_lambda___0_0_expanded___3(y[0]); - iteration_lambda___0_0_expanded___4(y[1]); - iteration_lambda___0_0_expanded___5(y[2]); - iteration_lambda___0_0_expanded___6(y[3]); - iteration_lambda___0_0_expanded___7(y[4]); - iteration_lambda___0_0_expanded___8(y[5]); + iteration_1_lambda___0_0_expanded___0(y[0]); + iteration_1_lambda___0_0_expanded___1(y[1]); + iteration_1_lambda___0_0_expanded___2(y[2]); + iteration_1_lambda___0_0_expanded___3(y[3]); + iteration_1_lambda___0_0_expanded___4(y[4]); + iteration_1_lambda___0_0_expanded___5(y[5]); } qfunc matrix_vector_product_expanded___0(y: qbit[6], output out: qbit[6]) { @@ -277,37 +277,37 @@ qfunc syndrome_decode_lookuptable_expanded___0(syndrome: qnum<6, False, 0>, erro } } -qfunc iteration_lambda___0_0_expanded___9(target___0_captured__apply_to_all__4: qbit) { - H(target___0_captured__apply_to_all__4); +qfunc iteration_2_lambda___0_0_expanded___0(target___0_captured__apply_to_all__3: qbit) { + H(target___0_captured__apply_to_all__3); } -qfunc iteration_lambda___0_0_expanded___10(target___1_captured__apply_to_all__4: qbit) { - H(target___1_captured__apply_to_all__4); +qfunc iteration_2_lambda___0_0_expanded___1(target___1_captured__apply_to_all__3: qbit) { + H(target___1_captured__apply_to_all__3); } -qfunc iteration_lambda___0_0_expanded___11(target___2_captured__apply_to_all__4: qbit) { - H(target___2_captured__apply_to_all__4); +qfunc iteration_2_lambda___0_0_expanded___2(target___2_captured__apply_to_all__3: qbit) { + H(target___2_captured__apply_to_all__3); } -qfunc iteration_lambda___0_0_expanded___12(target___3_captured__apply_to_all__4: qbit) { - H(target___3_captured__apply_to_all__4); +qfunc iteration_2_lambda___0_0_expanded___3(target___3_captured__apply_to_all__3: qbit) { + H(target___3_captured__apply_to_all__3); } -qfunc iteration_lambda___0_0_expanded___13(target___4_captured__apply_to_all__4: qbit) { - H(target___4_captured__apply_to_all__4); +qfunc iteration_2_lambda___0_0_expanded___4(target___4_captured__apply_to_all__3: qbit) { + H(target___4_captured__apply_to_all__3); } -qfunc iteration_lambda___0_0_expanded___14(target___5_captured__apply_to_all__4: qbit) { - H(target___5_captured__apply_to_all__4); +qfunc iteration_2_lambda___0_0_expanded___5(target___5_captured__apply_to_all__3: qbit) { + H(target___5_captured__apply_to_all__3); } qfunc apply_to_all_expanded___0(target: qbit[6]) { - iteration_lambda___0_0_expanded___9(target[0]); - iteration_lambda___0_0_expanded___10(target[1]); - iteration_lambda___0_0_expanded___11(target[2]); - iteration_lambda___0_0_expanded___12(target[3]); - iteration_lambda___0_0_expanded___13(target[4]); - iteration_lambda___0_0_expanded___14(target[5]); + iteration_2_lambda___0_0_expanded___0(target[0]); + iteration_2_lambda___0_0_expanded___1(target[1]); + iteration_2_lambda___0_0_expanded___2(target[2]); + iteration_2_lambda___0_0_expanded___3(target[3]); + iteration_2_lambda___0_0_expanded___4(target[4]); + iteration_2_lambda___0_0_expanded___5(target[5]); } qfunc hadamard_transform_expanded___0(target: qbit[6]) { diff --git a/algorithms/dqi/dqi_max_xorsat.synthesis_options.json b/algorithms/dqi/dqi_max_xorsat.synthesis_options.json index 1918752c6..ac599d9d2 100644 --- a/algorithms/dqi/dqi_max_xorsat.synthesis_options.json +++ b/algorithms/dqi/dqi_max_xorsat.synthesis_options.json @@ -7,39 +7,37 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "z", + "rz", + "cx", + "h", "u1", - "p", - "cy", "r", - "id", - "y", - "sdg", - "x", - "u2", + "sx", "s", - "ry", - "cx", - "rz", - "h", + "rx", + "y", + "cy", "tdg", - "cz", + "ry", + "u2", "u", - "rx", + "x", + "cz", + "z", + "sxdg", + "sdg", "t", - "sx", - "sxdg" + "p", + "id" ], "is_symmetric_connectivity": true }, "debug_mode": true, "synthesize_all_separately": false, - "output_format": [ - "qasm" - ], + "output_format": ["qasm"], "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 3679731798 + "random_seed": -1 } } diff --git a/algorithms/grover/3_sat_grover/3_sat_grover.qmod b/algorithms/grover/3_sat_grover/3_sat_grover.qmod index cabfffd08..17f12c2f3 100644 --- a/algorithms/grover/3_sat_grover/3_sat_grover.qmod +++ b/algorithms/grover/3_sat_grover/3_sat_grover.qmod @@ -3,7 +3,7 @@ qfunc sat_oracle(x: qbit[], res: qbit) { } qfunc main(output x: qbit[3]) { - allocate(3, x); + allocate(x.len, x); grover_search(1, lambda(vars) { phase_oracle(sat_oracle, vars); }, x); diff --git a/algorithms/grover/3_sat_grover/3_sat_grover.synthesis_options.json b/algorithms/grover/3_sat_grover/3_sat_grover.synthesis_options.json index a20de7f23..a5609b34e 100644 --- a/algorithms/grover/3_sat_grover/3_sat_grover.synthesis_options.json +++ b/algorithms/grover/3_sat_grover/3_sat_grover.synthesis_options.json @@ -1,5 +1,44 @@ { "constraints": { - "max_width": 20 + "max_width": 20, + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "rz", + "cx", + "h", + "u1", + "r", + "sx", + "s", + "rx", + "y", + "cy", + "tdg", + "ry", + "u2", + "u", + "x", + "cz", + "z", + "sxdg", + "sdg", + "t", + "p", + "id" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": -1 } } diff --git a/algorithms/grover/3_sat_grover/3_sat_grover_large.qmod b/algorithms/grover/3_sat_grover/3_sat_grover_large.qmod index f6683d0bb..8f4a2dea4 100644 --- a/algorithms/grover/3_sat_grover/3_sat_grover_large.qmod +++ b/algorithms/grover/3_sat_grover/3_sat_grover_large.qmod @@ -3,7 +3,7 @@ qfunc sat_oracle_large(x: qbit[], res: qbit) { } qfunc main(output x: qbit[4]) { - allocate(4, x); + allocate(x.len, x); grover_search(2, lambda(vars) { phase_oracle(sat_oracle_large, vars); }, x); diff --git a/algorithms/grover/3_sat_grover/3_sat_grover_large.synthesis_options.json b/algorithms/grover/3_sat_grover/3_sat_grover_large.synthesis_options.json index b13c22eed..56d16ac17 100644 --- a/algorithms/grover/3_sat_grover/3_sat_grover_large.synthesis_options.json +++ b/algorithms/grover/3_sat_grover/3_sat_grover_large.synthesis_options.json @@ -1,5 +1,44 @@ { "constraints": { - "max_width": 24 + "max_width": 24, + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "rz", + "cx", + "h", + "u1", + "r", + "sx", + "s", + "rx", + "y", + "cy", + "tdg", + "ry", + "u2", + "u", + "x", + "cz", + "z", + "sxdg", + "sdg", + "t", + "p", + "id" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": -1 } } diff --git a/algorithms/grover/grover_max_cut/grover_max_cut.qmod b/algorithms/grover/grover_max_cut/grover_max_cut.qmod index 2285b0d20..a56250d91 100644 --- a/algorithms/grover/grover_max_cut/grover_max_cut.qmod +++ b/algorithms/grover/grover_max_cut/grover_max_cut.qmod @@ -3,7 +3,7 @@ qfunc cut_oracle(cut_size: int, nodes: qbit[], res: qbit) { } qfunc main(output nodes: qbit[5]) { - allocate(5, nodes); + allocate(nodes.len, nodes); grover_search(3, lambda(vars) { phase_oracle(lambda(vars, res) { cut_oracle(4, vars, res); diff --git a/algorithms/grover/grover_max_cut/grover_max_cut.synthesis_options.json b/algorithms/grover/grover_max_cut/grover_max_cut.synthesis_options.json index 589c0f316..bbef76503 100644 --- a/algorithms/grover/grover_max_cut/grover_max_cut.synthesis_options.json +++ b/algorithms/grover/grover_max_cut/grover_max_cut.synthesis_options.json @@ -1,5 +1,44 @@ { "constraints": { - "max_width": 22 + "max_width": 22, + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "rz", + "cx", + "h", + "u1", + "r", + "sx", + "s", + "rx", + "y", + "cy", + "tdg", + "ry", + "u2", + "u", + "x", + "cz", + "z", + "sxdg", + "sdg", + "t", + "p", + "id" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": -1 } } diff --git a/algorithms/hhl/hhl/hhl_exact.qmod b/algorithms/hhl/hhl/hhl_exact.qmod index 4d5d1f8a6..649f4e4a0 100644 --- a/algorithms/hhl/hhl/hhl_exact.qmod +++ b/algorithms/hhl/hhl/hhl_exact.qmod @@ -1,9 +1,3 @@ -qfunc unitary_with_power_logic(pw: int, matrix: real[][], target: qbit[]) { - power (pw) { - unitary(matrix, target); - } -} - qfunc load_b(amplitudes: real[], output state: qbit[], bound: real) { prepare_amplitudes(amplitudes, bound, state); } @@ -30,6 +24,12 @@ qfunc hhl(rhs_vector: real[], bound: real, precision: int, hamiltonian_evolution } } +qfunc unitary_with_power_logic(pw: int, matrix: real[][], target: qbit[]) { + power (pw) { + unitary(matrix, target); + } +} + qfunc main(output res: qnum, output phase: qnum, output indicator: qbit) { hhl([ 0.18257418583505536, diff --git a/algorithms/hhl/hhl/hhl_exact.synthesis_options.json b/algorithms/hhl/hhl/hhl_exact.synthesis_options.json index a89c3c20a..ba1113e93 100644 --- a/algorithms/hhl/hhl/hhl_exact.synthesis_options.json +++ b/algorithms/hhl/hhl/hhl_exact.synthesis_options.json @@ -7,32 +7,33 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "cy", "rz", - "z", - "sdg", - "t", - "s", + "cx", "h", - "u2", - "tdg", - "sx", - "ry", - "cz", "u1", - "y", "r", - "x", + "sx", + "s", "rx", - "sxdg", - "id", + "y", + "cy", + "tdg", + "ry", + "u2", "u", + "x", + "cz", + "z", + "sxdg", + "sdg", + "t", "p", - "cx" + "id" ], "is_symmetric_connectivity": true }, "debug_mode": true, + "synthesize_all_separately": false, "output_format": ["qasm"], "pretty_qasm": true, "transpilation_option": "auto optimize", diff --git a/algorithms/hhl/hhl/hhl_trotter.qmod b/algorithms/hhl/hhl/hhl_trotter.qmod index 0ee09ad5c..2a4387705 100644 --- a/algorithms/hhl/hhl/hhl_trotter.qmod +++ b/algorithms/hhl/hhl/hhl_trotter.qmod @@ -1,7 +1,3 @@ -qfunc suzuki_trotter1_with_power_logic(hamiltonian: PauliTerm[], pw: int, r0: int, reps_scaling_factor: real, evolution_coefficient: real, target: qbit[]) { - suzuki_trotter(hamiltonian, evolution_coefficient * pw, 1, r0 * ceiling(reps_scaling_factor ** log(pw, 2)), target); -} - qfunc load_b(amplitudes: real[], output state: qbit[], bound: real) { prepare_amplitudes(amplitudes, bound, state); } @@ -28,6 +24,10 @@ qfunc hhl(rhs_vector: real[], bound: real, precision: int, hamiltonian_evolution } } +qfunc suzuki_trotter1_with_power_logic(hamiltonian: PauliTerm[], pw: int, r0: int, reps_scaling_factor: real, evolution_coefficient: real, target: qbit[]) { + suzuki_trotter(hamiltonian, evolution_coefficient * pw, 1, r0 * ceiling(reps_scaling_factor ** log(pw, 2)), target); +} + qfunc main(output res: qnum, output phase: qnum, output indicator: qbit) { hhl([ 0.1825741858, diff --git a/algorithms/hhl/hhl/hhl_trotter.synthesis_options.json b/algorithms/hhl/hhl/hhl_trotter.synthesis_options.json index a89c3c20a..ba1113e93 100644 --- a/algorithms/hhl/hhl/hhl_trotter.synthesis_options.json +++ b/algorithms/hhl/hhl/hhl_trotter.synthesis_options.json @@ -7,32 +7,33 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "cy", "rz", - "z", - "sdg", - "t", - "s", + "cx", "h", - "u2", - "tdg", - "sx", - "ry", - "cz", "u1", - "y", "r", - "x", + "sx", + "s", "rx", - "sxdg", - "id", + "y", + "cy", + "tdg", + "ry", + "u2", "u", + "x", + "cz", + "z", + "sxdg", + "sdg", + "t", "p", - "cx" + "id" ], "is_symmetric_connectivity": true }, "debug_mode": true, + "synthesize_all_separately": false, "output_format": ["qasm"], "pretty_qasm": true, "transpilation_option": "auto optimize", diff --git a/applications/finance/portfolio_optimization/portfolio_optimization.qmod b/applications/finance/portfolio_optimization/portfolio_optimization.qmod index 363c48bc6..bf1751dd0 100644 --- a/applications/finance/portfolio_optimization/portfolio_optimization.qmod +++ b/applications/finance/portfolio_optimization/portfolio_optimization.qmod @@ -3,8 +3,6 @@ qstruct QAOAVars { budget_rule_slack_var: qbit[3]; } - - qfunc main(params: real[6], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); diff --git a/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json b/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json index cf711f93e..ba1113e93 100644 --- a/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json +++ b/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "tdg", - "z", - "u2", - "id", - "s", "rz", + "cx", + "h", + "u1", + "r", "sx", - "sdg", + "s", + "rx", + "y", "cy", + "tdg", + "ry", + "u2", + "u", "x", "cz", - "u", - "y", + "z", + "sxdg", + "sdg", "t", - "u1", - "rx", - "h", "p", - "cx", - "r", - "ry", - "sxdg" + "id" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 3453328217 + "random_seed": -1 } } diff --git a/applications/optimization/integer_linear_programming/integer_linear_programming.qmod b/applications/optimization/integer_linear_programming/integer_linear_programming.qmod index 1b153d454..21489c8cf 100644 --- a/applications/optimization/integer_linear_programming/integer_linear_programming.qmod +++ b/applications/optimization/integer_linear_programming/integer_linear_programming.qmod @@ -4,8 +4,6 @@ qstruct QAOAVars { monotone_rule_2_slack_var_0: qbit; } - - qfunc main(params: real[6], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); diff --git a/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json b/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json index 0ae05c835..ba1113e93 100644 --- a/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json +++ b/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "sx", - "tdg", - "z", "rz", - "y", + "cx", "h", - "cy", - "t", - "sdg", "u1", "r", - "id", - "cx", - "cz", + "sx", + "s", "rx", - "u", - "p", + "y", + "cy", + "tdg", "ry", - "sxdg", - "x", "u2", - "s" + "u", + "x", + "cz", + "z", + "sxdg", + "sdg", + "t", + "p", + "id" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 2943844644 + "random_seed": -1 } } diff --git a/applications/optimization/max_clique/max_clique.qmod b/applications/optimization/max_clique/max_clique.qmod index bceade30c..413e3aba9 100644 --- a/applications/optimization/max_clique/max_clique.qmod +++ b/applications/optimization/max_clique/max_clique.qmod @@ -2,8 +2,6 @@ qstruct QAOAVars { x: qbit[7]; } - - qfunc main(params: real[6], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); diff --git a/applications/optimization/max_clique/max_clique.synthesis_options.json b/applications/optimization/max_clique/max_clique.synthesis_options.json index bbb495713..ba1113e93 100644 --- a/applications/optimization/max_clique/max_clique.synthesis_options.json +++ b/applications/optimization/max_clique/max_clique.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "r", - "id", - "u", + "rz", "cx", - "sx", "h", - "y", "u1", + "r", + "sx", "s", - "u2", - "ry", - "rz", - "p", - "t", - "cz", "rx", - "sdg", + "y", "cy", - "x", "tdg", + "ry", + "u2", + "u", + "x", + "cz", + "z", "sxdg", - "z" + "sdg", + "t", + "p", + "id" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 4176492311 + "random_seed": -1 } } diff --git a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod index dcd187633..98196497f 100644 --- a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod +++ b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.qmod @@ -2,8 +2,6 @@ qstruct QAOAVars { x: qbit[10]; } - - qfunc main(params: real[6], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); diff --git a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json index 2d889877c..ba1113e93 100644 --- a/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json +++ b/applications/optimization/max_k_vertex_cover/max_k_vertex_cover.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "id", - "z", + "rz", + "cx", + "h", + "u1", + "r", "sx", - "sdg", "s", - "x", - "t", + "rx", "y", - "u1", - "cx", - "h", - "sxdg", - "cz", "cy", - "p", - "r", - "rz", - "ry", "tdg", - "rx", + "ry", "u2", - "u" + "u", + "x", + "cz", + "z", + "sxdg", + "sdg", + "t", + "p", + "id" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 3857045423 + "random_seed": -1 } } diff --git a/applications/optimization/set_partition/set_partition.qmod b/applications/optimization/set_partition/set_partition.qmod index 703f5e6db..c24de2ab4 100644 --- a/applications/optimization/set_partition/set_partition.qmod +++ b/applications/optimization/set_partition/set_partition.qmod @@ -2,13 +2,11 @@ qstruct QAOAVars { x: qbit[10]; } - - qfunc main(params: real[6], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); repeat (i: 3) { - phase (-((((((((((((16 * v.x[0]) + (16 * v.x[1])) + (16 * v.x[2])) + (10 * v.x[3])) + (10 * v.x[4])) + (12 * v.x[5])) + (10 * v.x[6])) + (12 * v.x[7])) + (16 * v.x[8])) + (22 * v.x[9])) - 70) ** 2), params[i]); + phase (-((((((((((((4 * v.x[0]) + (16 * v.x[1])) + (14 * v.x[2])) + (18 * v.x[3])) + (16 * v.x[4])) + (16 * v.x[5])) + (12 * v.x[6])) + (4 * v.x[7])) + (10 * v.x[8])) + (20 * v.x[9])) - 65) ** 2), params[i]); apply_to_all(lambda(q) { RX(params[3 + i], q); }, v); diff --git a/applications/optimization/set_partition/set_partition.synthesis_options.json b/applications/optimization/set_partition/set_partition.synthesis_options.json index ac5cce353..ba1113e93 100644 --- a/applications/optimization/set_partition/set_partition.synthesis_options.json +++ b/applications/optimization/set_partition/set_partition.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "u", - "u1", + "rz", "cx", - "x", - "u2", - "sdg", - "s", + "h", + "u1", "r", - "cz", - "id", - "cy", - "sxdg", - "ry", + "sx", + "s", "rx", - "rz", "y", - "sx", + "cy", "tdg", - "t", + "ry", + "u2", + "u", + "x", + "cz", "z", + "sxdg", + "sdg", + "t", "p", - "h" + "id" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 1468870560 + "random_seed": -1 } } diff --git a/applications/physical_systems/ising_model/ising_model.qmod b/applications/physical_systems/ising_model/ising_model.qmod index 6108af2c7..b2e4dca01 100644 --- a/applications/physical_systems/ising_model/ising_model.qmod +++ b/applications/physical_systems/ising_model/ising_model.qmod @@ -2,8 +2,6 @@ qstruct QAOAVars { z: qbit[6]; } - - qfunc main(params: real[10], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); diff --git a/applications/physical_systems/ising_model/ising_model.synthesis_options.json b/applications/physical_systems/ising_model/ising_model.synthesis_options.json index 9c23bd269..ba1113e93 100644 --- a/applications/physical_systems/ising_model/ising_model.synthesis_options.json +++ b/applications/physical_systems/ising_model/ising_model.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "u1", + "rz", "cx", - "p", - "cz", "h", - "x", + "u1", + "r", "sx", - "y", - "tdg", - "rz", - "cy", - "id", "s", - "r", - "t", - "z", "rx", - "u", - "sdg", + "y", + "cy", + "tdg", "ry", + "u2", + "u", + "x", + "cz", + "z", "sxdg", - "u2" + "sdg", + "t", + "p", + "id" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 2916469319 + "random_seed": -1 } } From a0f25fc0629b77bed539536d16dfd01f42d26d61 Mon Sep 17 00:00:00 2001 From: Ori Roth Date: Tue, 17 Dec 2024 17:01:20 +0200 Subject: [PATCH 24/32] Update qmods --- .../discrete_poisson_solver.qmod | 8 ++--- .../oblivious_amplitude_amplification.qmod | 34 +++++++++---------- algorithms/simon/simon_example.qmod | 8 ++--- algorithms/simon/simon_shallow_example.qmod | 14 ++++---- algorithms/vqls/lcu_vqls/vqls_with_lcu.qmod | 16 ++++----- .../whitebox_fuzzing/whitebox_fuzzing.qmod | 14 ++++---- .../option_pricing/option_pricing.qmod | 14 ++++---- .../quantum_walk_circle_balanced_coin.qmod | 20 +++++------ .../quantum_walk_hypercube.qmod | 8 ++--- .../hamiltonian_simulation_qubitization.qmod | 30 ++++++++-------- 10 files changed, 83 insertions(+), 83 deletions(-) diff --git a/algorithms/differential_equations/discrete_poisson_solver/discrete_poisson_solver.qmod b/algorithms/differential_equations/discrete_poisson_solver/discrete_poisson_solver.qmod index dbe6fd199..2b8392dd1 100644 --- a/algorithms/differential_equations/discrete_poisson_solver/discrete_poisson_solver.qmod +++ b/algorithms/differential_equations/discrete_poisson_solver/discrete_poisson_solver.qmod @@ -3,10 +3,6 @@ qfunc qsct_2d(xy_variable: qnum[2]) { qct_type2(xy_variable[1]); } -qfunc powered_hamiltonian_evolution(hamiltonian: PauliTerm[], scaling: real, p: int, qba: qbit[]) { - suzuki_trotter(hamiltonian, p * ((-6.28318530718) * scaling), 1, 1, qba); -} - qfunc inverse_amplitude_load(prefactor: real, phase: qnum, ind: qbit) { ind *= prefactor / phase; } @@ -22,6 +18,10 @@ qfunc matrix_inversion_HHL(prefactor: real, my_unitary: qfunc (int, qbit[]), sta } } +qfunc powered_hamiltonian_evolution(hamiltonian: PauliTerm[], scaling: real, p: int, qba: qbit[]) { + suzuki_trotter(hamiltonian, p * ((-6.28318530718) * scaling), 1, 1, qba); +} + qfunc main(output x_variable: qnum<3, False, 0>, output y_variable: qnum<3, False, 0>, output phase: qnum, output indicator: qbit) { xy_variable: qnum<3, False, 0>[2]; prepare_amplitudes([ diff --git a/algorithms/oblivious_amplitude_amplification/oblivious_amplitude_amplification.qmod b/algorithms/oblivious_amplitude_amplification/oblivious_amplitude_amplification.qmod index 154002cdf..a4b791895 100644 --- a/algorithms/oblivious_amplitude_amplification/oblivious_amplitude_amplification.qmod +++ b/algorithms/oblivious_amplitude_amplification/oblivious_amplitude_amplification.qmod @@ -1,3 +1,20 @@ +qfunc check_block(b: qnum, res: qbit) { + res ^= b == 0; +} + +qfunc oblivious_amplitude_amplification(reps: int, block_encoding: qfunc (qnum, qbit[]), block: qnum, data: qbit[]) { + block_encoding(data, block); + repeat (index: reps) { + grover_operator(lambda(b) { + phase_oracle(lambda(x, res) { + check_block(x, res); + }, b); + }, lambda(b) { + block_encoding(data, b); + }, block); + } +} + qfunc apply_pauli_term(pauli_string: Pauli[], x: qbit[]) { repeat (index: x.len) { switch(pauli_string[index], [lambda() { @@ -24,23 +41,6 @@ qfunc block_encode(pauli_list: Pauli[][], data: qbit[], block: qnum) { } } -qfunc check_block(b: qnum, res: qbit) { - res ^= b == 0; -} - -qfunc oblivious_amplitude_amplification(reps: int, block_encoding: qfunc (qnum, qbit[]), block: qnum, data: qbit[]) { - block_encoding(data, block); - repeat (index: reps) { - grover_operator(lambda(b) { - phase_oracle(lambda(x, res) { - check_block(x, res); - }, b); - }, lambda(b) { - block_encoding(data, b); - }, block); - } -} - qfunc main(output data: qnum, output block: qnum) { allocate(2, block); prepare_amplitudes([ diff --git a/algorithms/simon/simon_example.qmod b/algorithms/simon/simon_example.qmod index b14ec214a..81e82fd05 100644 --- a/algorithms/simon/simon_example.qmod +++ b/algorithms/simon/simon_example.qmod @@ -1,7 +1,3 @@ -qfunc simon_qfunc_simple(s: int, x: qnum, output res: qnum) { - res = min(x, x ^ s); -} - qfunc simon_qfunc(f_qfunc: qfunc (qnum, output qnum), x: qnum) { res: qnum; hadamard_transform(x); @@ -9,6 +5,10 @@ qfunc simon_qfunc(f_qfunc: qfunc (qnum, output qnum), x: qnum) { hadamard_transform(x); } +qfunc simon_qfunc_simple(s: int, x: qnum, output res: qnum) { + res = min(x, x ^ s); +} + qfunc main(output x: qnum) { allocate(5, x); simon_qfunc(lambda(x, res) { diff --git a/algorithms/simon/simon_shallow_example.qmod b/algorithms/simon/simon_shallow_example.qmod index 00268be57..903cf0120 100644 --- a/algorithms/simon/simon_shallow_example.qmod +++ b/algorithms/simon/simon_shallow_example.qmod @@ -1,3 +1,10 @@ +qfunc simon_qfunc(f_qfunc: qfunc (qnum, output qnum), x: qnum) { + res: qnum; + hadamard_transform(x); + f_qfunc(x, res); + hadamard_transform(x); +} + qfunc simon_qfunc_with_bipartite_s(partition_index: int, x: qbit[], output res: qbit[]) { allocate(x.len, res); repeat (i: x.len - partition_index) { @@ -9,13 +16,6 @@ qfunc simon_qfunc_with_bipartite_s(partition_index: int, x: qbit[], output res: } } -qfunc simon_qfunc(f_qfunc: qfunc (qnum, output qnum), x: qnum) { - res: qnum; - hadamard_transform(x); - f_qfunc(x, res); - hadamard_transform(x); -} - qfunc main(output x: qnum) { allocate(6, x); simon_qfunc(lambda(x, res) { diff --git a/algorithms/vqls/lcu_vqls/vqls_with_lcu.qmod b/algorithms/vqls/lcu_vqls/vqls_with_lcu.qmod index 8a0bb95f4..f0aeb7869 100644 --- a/algorithms/vqls/lcu_vqls/vqls_with_lcu.qmod +++ b/algorithms/vqls/lcu_vqls/vqls_with_lcu.qmod @@ -1,3 +1,11 @@ +qfunc block_encoding_vqls(ansatz: qfunc (), block_encoding: qfunc (), prepare_b_state: qfunc ()) { + ansatz(); + block_encoding(); + invert { + prepare_b_state(); + } +} + qfunc apply_ry_on_all(params: real[], io: qbit[]) { repeat (index: io.len) { RY(params[index], io[index]); @@ -60,14 +68,6 @@ qfunc prepare_ca(pauli_terms_list: PauliTerm[], system_qubits: qbit[], ancillary } } -qfunc block_encoding_vqls(ansatz: qfunc (), block_encoding: qfunc (), prepare_b_state: qfunc ()) { - ansatz(); - block_encoding(); - invert { - prepare_b_state(); - } -} - qfunc main(params: real[9], output ancillary_qubits: qnum, output system_qubits: qnum) { allocate(2, ancillary_qubits); allocate(3, system_qubits); diff --git a/applications/cybersecurity/whitebox_fuzzing/whitebox_fuzzing.qmod b/applications/cybersecurity/whitebox_fuzzing/whitebox_fuzzing.qmod index 9a950049f..464ad58a1 100644 --- a/applications/cybersecurity/whitebox_fuzzing/whitebox_fuzzing.qmod +++ b/applications/cybersecurity/whitebox_fuzzing/whitebox_fuzzing.qmod @@ -3,8 +3,9 @@ qfunc my_sp(x: qnum, y: qnum) { hadamard_transform(y); } -qfunc my_predicate(x: qnum, y: qnum, res: qbit) { - res ^= ((x + y) < 9) and (((x * y) % 4) == 1); +qfunc my_grover_operator(oracle_operand: qfunc (), diffuser_operand: qfunc ()) { + oracle_operand(); + diffuser_operand(); } qfunc prep_minus(output out: qbit) { @@ -22,6 +23,10 @@ qfunc my_oracle(predicate: qfunc (qbit)) { } } +qfunc my_predicate(x: qnum, y: qnum, res: qbit) { + res ^= ((x + y) < 9) and (((x * y) % 4) == 1); +} + qfunc zero_predicate(x: qnum, y: qnum, res: qbit) { joined: qnum; {x, y} -> joined; @@ -43,11 +48,6 @@ qfunc my_diffuser(sp_operand: qfunc (qnum, qnum), x: qnum, y: qnum) { } } -qfunc my_grover_operator(oracle_operand: qfunc (), diffuser_operand: qfunc ()) { - oracle_operand(); - diffuser_operand(); -} - qfunc main(output x: qnum, output y: qnum) { allocate_num(6, False, 0, x); allocate_num(6, False, 0, y); diff --git a/applications/finance/option_pricing/option_pricing.qmod b/applications/finance/option_pricing/option_pricing.qmod index 64fb81c4b..07dbfcdbd 100644 --- a/applications/finance/option_pricing/option_pricing.qmod +++ b/applications/finance/option_pricing/option_pricing.qmod @@ -3,6 +3,13 @@ qstruct OptionPricingState { ind: qbit; } +qfunc iqae_algorithm(k: int, oracle_operand: qfunc (qbit[]), sp_operand: qfunc (qbit[]), x: qbit[]) { + sp_operand(x); + power (k) { + grover_operator(oracle_operand, sp_operand, x); + } +} + qfunc iqae_oracle(state: OptionPricingState) { Z(state.ind); } @@ -59,13 +66,6 @@ qfunc european_call_state_preparation(state: OptionPricingState) { payoff(state.asset, state.ind); } -qfunc iqae_algorithm(k: int, oracle_operand: qfunc (qbit[]), sp_operand: qfunc (qbit[]), x: qbit[]) { - sp_operand(x); - power (k) { - grover_operator(oracle_operand, sp_operand, x); - } -} - qfunc main(k: int, output ind: qbit) { state: OptionPricingState; asset: qbit[]; diff --git a/tutorials/advanced_tutorials/discrete_quantum_walk/quantum_walk_circle_balanced_coin.qmod b/tutorials/advanced_tutorials/discrete_quantum_walk/quantum_walk_circle_balanced_coin.qmod index 6695b65b9..34d7eb0df 100644 --- a/tutorials/advanced_tutorials/discrete_quantum_walk/quantum_walk_circle_balanced_coin.qmod +++ b/tutorials/advanced_tutorials/discrete_quantum_walk/quantum_walk_circle_balanced_coin.qmod @@ -1,13 +1,3 @@ -qfunc quantum_step_clockwise(x: qbit[]) { - within { - qft(x); - } apply { - repeat (i: x.len) { - PHASE(((2 * pi) * (2 ** i)) / (2 ** x.len), x[i]); - } - } -} - qfunc discrete_quantum_walk(time: int, coin_flip_qfunc: qfunc (qnum), walks_qfuncs: qfunc[] (), coin_state: qnum) { power (time) { coin_flip_qfunc(coin_state); @@ -19,6 +9,16 @@ qfunc discrete_quantum_walk(time: int, coin_flip_qfunc: qfunc (qnum), walks_qfun } } +qfunc quantum_step_clockwise(x: qbit[]) { + within { + qft(x); + } apply { + repeat (i: x.len) { + PHASE(((2 * pi) * (2 ** i)) / (2 ** x.len), x[i]); + } + } +} + qfunc main(t: int, output x: qnum) { coin: qbit; allocate_num(floor(log(128, 2)), True, 0, x); diff --git a/tutorials/advanced_tutorials/discrete_quantum_walk/quantum_walk_hypercube.qmod b/tutorials/advanced_tutorials/discrete_quantum_walk/quantum_walk_hypercube.qmod index a47414f8a..5f78eec55 100644 --- a/tutorials/advanced_tutorials/discrete_quantum_walk/quantum_walk_hypercube.qmod +++ b/tutorials/advanced_tutorials/discrete_quantum_walk/quantum_walk_hypercube.qmod @@ -1,7 +1,3 @@ -qfunc moving_one_hamming_dist(pos: int, x: qbit[]) { - X(x[pos]); -} - qfunc discrete_quantum_walk(time: int, coin_flip_qfunc: qfunc (qnum), walks_qfuncs: qfunc[] (), coin_state: qnum) { power (time) { coin_flip_qfunc(coin_state); @@ -13,6 +9,10 @@ qfunc discrete_quantum_walk(time: int, coin_flip_qfunc: qfunc (qnum), walks_qfun } } +qfunc moving_one_hamming_dist(pos: int, x: qbit[]) { + X(x[pos]); +} + qfunc main(t: int, output x: qbit[]) { allocate(4, x); coin: qbit[]; diff --git a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_with_block_encoding/hamiltonian_simulation_qubitization.qmod b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_with_block_encoding/hamiltonian_simulation_qubitization.qmod index d08a6fbee..08fa45d93 100644 --- a/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_with_block_encoding/hamiltonian_simulation_qubitization.qmod +++ b/tutorials/popular_usage_examples/hamiltonian_simulation/hamiltonian_simulation_with_block_encoding/hamiltonian_simulation_qubitization.qmod @@ -1,3 +1,18 @@ +qfunc lcu_cheb(coef: real[], generalized_signs: int[], walk_operator: qfunc (qnum, qbit[]), walk_block: qnum, walk_data: qbit[], cheb_block: qnum) { + within { + inplace_prepare_state(coef, 0.0, cheb_block); + } apply { + repeat (k: generalized_signs.len) { + control (cheb_block == k) { + U(0, 0, 0, (pi / 2) * generalized_signs[k], walk_data[0]); + power (k) { + walk_operator(walk_block, walk_data); + } + } + } + } +} + qfunc apply_pauli_term(pauli_string: PauliTerm, x: qbit[]) { repeat (index: x.len) { switch(pauli_string.pauli[index], [lambda() { @@ -52,21 +67,6 @@ qfunc my_walk_operator(block: qbit[], data: qbit[]) { RY(2 * pi, block[0]); } -qfunc lcu_cheb(coef: real[], generalized_signs: int[], walk_operator: qfunc (qnum, qbit[]), walk_block: qnum, walk_data: qbit[], cheb_block: qnum) { - within { - inplace_prepare_state(coef, 0.0, cheb_block); - } apply { - repeat (k: generalized_signs.len) { - control (cheb_block == k) { - U(0, 0, 0, (pi / 2) * generalized_signs[k], walk_data[0]); - power (k) { - walk_operator(walk_block, walk_data); - } - } - } - } -} - qfunc main(output ham_block: qnum, output data: qnum, output exp_block: qnum) { allocate(4, exp_block); allocate(2, ham_block); From 2bba551a6b2aa21ad07dc7e90480ff172a7cf12f Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Wed, 18 Dec 2024 11:49:19 +0200 Subject: [PATCH 25/32] added missing timeouts --- tests/resources/timeouts.yaml | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/tests/resources/timeouts.yaml b/tests/resources/timeouts.yaml index a461d6ace..57bea5e43 100644 --- a/tests/resources/timeouts.yaml +++ b/tests/resources/timeouts.yaml @@ -325,3 +325,11 @@ whitebox_fuzzing.qmod: 720 X.qmod: 10 Yasir_Mansour_HW3_VQE.ipynb: 30 Yasir_Mansour_HW4_molecule_eigensolver.ipynb: 600 +classiq_discrete_quantum_walk.ipynb: 100 +qiskit_discrete_quantum_walk.ipynb: 100 +tket_discrete_quantum_walk.ipynb: 100 +classiq_qsvt.ipynb: 100 +pennylane_cat_qsvt_example.ipynb: 100 +qiskit_qsvt.ipynb: 100 +pennylane_catalyst_discrete_quantum_walk.ipynb: 100 +tket_qsvt_example.ipynb: 100 From 6608e756e3a3aca187b7c37c5c181fd515afa973 Mon Sep 17 00:00:00 2001 From: Ori Roth Date: Wed, 18 Dec 2024 14:18:55 +0200 Subject: [PATCH 26/32] Update dqi Qmod --- algorithms/dqi/dqi_max_xorsat.qmod | 104 +++--------------- .../dqi/dqi_max_xorsat.synthesis_options.json | 36 +++--- 2 files changed, 33 insertions(+), 107 deletions(-) diff --git a/algorithms/dqi/dqi_max_xorsat.qmod b/algorithms/dqi/dqi_max_xorsat.qmod index 457376614..10cc1b098 100644 --- a/algorithms/dqi/dqi_max_xorsat.qmod +++ b/algorithms/dqi/dqi_max_xorsat.qmod @@ -21,27 +21,15 @@ qfunc binary_to_one_hot_expanded___0(input binary: qnum<2, False, 0>, output one inplace_binary_to_one_hot_expanded___0(one_hot); } -qfunc iteration_0_lambda___0_0_expanded___0(qvar___3_captured__inplace_one_hot_to_unary__4: qbit, qvar___2_captured__inplace_one_hot_to_unary__4: qbit) { - CX(qvar___3_captured__inplace_one_hot_to_unary__4, qvar___2_captured__inplace_one_hot_to_unary__4); -} - -qfunc iteration_0_lambda___0_0_expanded___1(qvar___2_captured__inplace_one_hot_to_unary__4: qbit, qvar___1_captured__inplace_one_hot_to_unary__4: qbit) { - CX(qvar___2_captured__inplace_one_hot_to_unary__4, qvar___1_captured__inplace_one_hot_to_unary__4); -} - -qfunc iteration_0_lambda___0_0_expanded___2(qvar___1_captured__inplace_one_hot_to_unary__4: qbit, qvar___0_captured__inplace_one_hot_to_unary__4: qbit) { - CX(qvar___1_captured__inplace_one_hot_to_unary__4, qvar___0_captured__inplace_one_hot_to_unary__4); -} - -qfunc inplace_one_hot_to_unary_expanded___0(qvar: qbit[4]) { - iteration_0_lambda___0_0_expanded___0(qvar[3], qvar[2]); - iteration_0_lambda___0_0_expanded___1(qvar[2], qvar[1]); - iteration_0_lambda___0_0_expanded___2(qvar[1], qvar[0]); +qfunc inplace_one_hot_to_unary(qvar: qbit[]) { + repeat (i: qvar.len - 1) { + CX(qvar[(qvar.len - i) - 1], qvar[(qvar.len - i) - 2]); + } X(qvar[0]); } qfunc one_hot_to_unary_expanded___0(input one_hot: qbit[4], output unary: qbit[3]) { - inplace_one_hot_to_unary_expanded___0(one_hot); + inplace_one_hot_to_unary(one_hot); lsb: qbit; one_hot -> {lsb, unary}; free(lsb); @@ -165,37 +153,12 @@ qfunc prepare_dick_state_unary_input_expanded___5(qvar: qbit[6]) { prepare_dick_state_unary_input_expanded___4(qvar[1:6]); } -qfunc iteration_1_lambda___0_0_expanded___0(y___0_captured__vector_product_phase__2: qbit) { - Z(y___0_captured__vector_product_phase__2); -} - -qfunc iteration_1_lambda___0_0_expanded___1(y___1_captured__vector_product_phase__2: qbit) { - Z(y___1_captured__vector_product_phase__2); -} - -qfunc iteration_1_lambda___0_0_expanded___2(y___2_captured__vector_product_phase__2: qbit) { - Z(y___2_captured__vector_product_phase__2); -} - -qfunc iteration_1_lambda___0_0_expanded___3(y___3_captured__vector_product_phase__2: qbit) { - Z(y___3_captured__vector_product_phase__2); -} - -qfunc iteration_1_lambda___0_0_expanded___4(y___4_captured__vector_product_phase__2: qbit) { - Z(y___4_captured__vector_product_phase__2); -} - -qfunc iteration_1_lambda___0_0_expanded___5(y___5_captured__vector_product_phase__2: qbit) { - Z(y___5_captured__vector_product_phase__2); -} - -qfunc vector_product_phase_expanded___0(y: qbit[6]) { - iteration_1_lambda___0_0_expanded___0(y[0]); - iteration_1_lambda___0_0_expanded___1(y[1]); - iteration_1_lambda___0_0_expanded___2(y[2]); - iteration_1_lambda___0_0_expanded___3(y[3]); - iteration_1_lambda___0_0_expanded___4(y[4]); - iteration_1_lambda___0_0_expanded___5(y[5]); +qfunc vector_product_phase(v: int[], y: qbit[]) { + repeat (i: y.len) { + if (v[i] > 0) { + Z(y[i]); + } + } } qfunc matrix_vector_product_expanded___0(y: qbit[6], output out: qbit[6]) { @@ -208,7 +171,7 @@ qfunc matrix_vector_product_expanded___0(y: qbit[6], output out: qbit[6]) { out[5] ^= (0 ^ y[4]) ^ y[5]; } -qfunc syndrome_decode_lookuptable_expanded___0(syndrome: qnum<6, False, 0>, error: qnum<6, False, 0>) { +qfunc syndrome_decode_lookuptable(syndrome: qnum, error: qnum) { control (syndrome == 0) { error ^= 0; } @@ -277,43 +240,6 @@ qfunc syndrome_decode_lookuptable_expanded___0(syndrome: qnum<6, False, 0>, erro } } -qfunc iteration_2_lambda___0_0_expanded___0(target___0_captured__apply_to_all__3: qbit) { - H(target___0_captured__apply_to_all__3); -} - -qfunc iteration_2_lambda___0_0_expanded___1(target___1_captured__apply_to_all__3: qbit) { - H(target___1_captured__apply_to_all__3); -} - -qfunc iteration_2_lambda___0_0_expanded___2(target___2_captured__apply_to_all__3: qbit) { - H(target___2_captured__apply_to_all__3); -} - -qfunc iteration_2_lambda___0_0_expanded___3(target___3_captured__apply_to_all__3: qbit) { - H(target___3_captured__apply_to_all__3); -} - -qfunc iteration_2_lambda___0_0_expanded___4(target___4_captured__apply_to_all__3: qbit) { - H(target___4_captured__apply_to_all__3); -} - -qfunc iteration_2_lambda___0_0_expanded___5(target___5_captured__apply_to_all__3: qbit) { - H(target___5_captured__apply_to_all__3); -} - -qfunc apply_to_all_expanded___0(target: qbit[6]) { - iteration_2_lambda___0_0_expanded___0(target[0]); - iteration_2_lambda___0_0_expanded___1(target[1]); - iteration_2_lambda___0_0_expanded___2(target[2]); - iteration_2_lambda___0_0_expanded___3(target[3]); - iteration_2_lambda___0_0_expanded___4(target[4]); - iteration_2_lambda___0_0_expanded___5(target[5]); -} - -qfunc hadamard_transform_expanded___0(target: qbit[6]) { - apply_to_all_expanded___0(target); -} - qfunc dqi_max_xor_sat_expanded___0(output y: qbit[6], output solution: qbit[6]) { k_num_errors: qnum<2, False, 0>; prepare_amplitudes([ @@ -326,10 +252,10 @@ qfunc dqi_max_xor_sat_expanded___0(output y: qbit[6], output solution: qbit[6]) binary_to_unary_expanded___0(k_num_errors, k_unary); pad_zeros_expanded___0(k_unary, y); prepare_dick_state_unary_input_expanded___5(y); - vector_product_phase_expanded___0(y); + vector_product_phase([1.0, 1.0, 1.0, 1.0, 1.0, 1.0], y); matrix_vector_product_expanded___0(y, solution); - syndrome_decode_lookuptable_expanded___0(solution, y); - hadamard_transform_expanded___0(solution); + syndrome_decode_lookuptable(solution, y); + hadamard_transform(solution); } qfunc main(output y: qbit[6], output solution: qbit[6]) { diff --git a/algorithms/dqi/dqi_max_xorsat.synthesis_options.json b/algorithms/dqi/dqi_max_xorsat.synthesis_options.json index ac599d9d2..f8d613bfd 100644 --- a/algorithms/dqi/dqi_max_xorsat.synthesis_options.json +++ b/algorithms/dqi/dqi_max_xorsat.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "rz", - "cx", - "h", - "u1", - "r", - "sx", - "s", - "rx", - "y", - "cy", - "tdg", - "ry", "u2", - "u", - "x", - "cz", + "cy", + "rx", + "id", "z", + "u", "sxdg", - "sdg", + "x", + "rz", + "sx", + "ry", "t", "p", - "id" + "u1", + "y", + "tdg", + "s", + "h", + "r", + "cx", + "sdg", + "cz" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": -1 + "random_seed": 2676057990 } } From caebe67836ef68ef61a8e9745917b7329c64f0b1 Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Wed, 18 Dec 2024 18:46:30 +0200 Subject: [PATCH 27/32] adjusted integer using notebooks --- .../portfolio_optimization.ipynb | 68 ++++++------ ...tfolio_optimization.synthesis_options.json | 34 +++--- .../integer_linear_programming.ipynb | 105 ++++++++++-------- .../integer_linear_programming.qmod | 6 +- ..._linear_programming.synthesis_options.json | 32 +++--- 5 files changed, 127 insertions(+), 118 deletions(-) diff --git a/applications/finance/portfolio_optimization/portfolio_optimization.ipynb b/applications/finance/portfolio_optimization/portfolio_optimization.ipynb index 5fff5f122..75687a310 100644 --- a/applications/finance/portfolio_optimization/portfolio_optimization.ipynb +++ b/applications/finance/portfolio_optimization/portfolio_optimization.ipynb @@ -121,7 +121,7 @@ "num_assets = len(returns)\n", "\n", "# setting the variables\n", - "portfolio_model.w = pyo.Var(range(num_assets), domain=pyo.Integers, bounds=(0, 6))\n", + "portfolio_model.w = pyo.Var(range(num_assets), domain=pyo.Integers, bounds=(0, 7))\n", "\n", "w_array = list(portfolio_model.w.values())\n", "\n", @@ -202,7 +202,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Opening: https://nightly.platform.classiq.io/circuit/79e25a43-a916-476c-a108-022dfec85da8?version=0.62.0.dev9\n" + "Opening: https://nightly.platform.classiq.io/circuit/83bbd639-d2b0-4fb6-b89b-b9a790a5bd4d?version=0.63.0.dev2\n" ] } ], @@ -253,7 +253,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Optimization Progress: 61it [04:44, 4.67s/it] \n" + "Optimization Progress: 61it [05:10, 5.09s/it] \n" ] } ], @@ -290,7 +290,7 @@ }, { "data": { - "image/png": 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7hMemTJkCjuO8fhYsWOD1uuPHj2POnDnQ6XQoLCzEfffdB7vdHufVEwRBEASRqCRENdaWLVvw8ssvo7KyssdzN910Ex599FHhd51OJ/zb4XBgzpw5KC4uxnfffYe6ujrMmzcParUaTz75ZFzWThAEQRBEYiN7ZKejowNXX301Xn31VeTk5PR4XqfTobi4WPgRl4Z/9tln2LNnD95++22MHz8es2fPxmOPPYalS5fCarXG82MQBEEQBJGgyC52Fi5ciDlz5mD69Ol+n//Xv/6F/Px8jBkzBosWLUJnZ6fw3MaNGzF27FgUFRUJj82cORNGoxG7d+8OuE+LxQKj0ej1QxAEQRBEciJrGmvFihXYunUrtmzZ4vf5X/3qVxg4cCBKSkqwY8cOPPDAA9i/fz8++OADAEB9fb2X0AEg/F5fXx9wv0uWLMHixYuj9CkIgiAIgkhkZBM7NTU1uPPOO7Fu3TqkpaX53ebmm28W/j127Fj069cP06ZNw6FDhzBkyJCI971o0SLcc889wu+s3TRBEARBEMmHbGms6upqNDY24vTTT4dKpYJKpcKGDRvw4osvQqVSweFw9HjNxIkTAQAHDx4EABQXF6OhocFrG/Z7cXFxwH1rtVphNASNiCAIgiCI5EY2sTNt2jTs3LkT27ZtE37OOOMMXH311di2bRuUSmWP12zbtg0A0K9fPwBAVVUVdu7cicbGRmGbdevWwWAwoKKiIi6fgyAIgiCIxEa2NFZmZibGjBnj9VhGRgby8vIwZswYHDp0CMuXL8eFF16IvLw87NixA3fffTfOPfdcoUR9xowZqKiowLXXXounn34a9fX1ePDBB7Fw4UJotVo5PhZBEIRfLHYHVAoFlIrgAwsJgog+sldjBUKj0eDzzz/HjBkzMHLkSPz2t7/F5ZdfjtWrVwvbKJVKrFmzBkqlElVVVbjmmmswb948r748BEEQctNtc+C8p9fjF69slHspBJGScDzP83IvQm6MRiOysrLQ3t6eFP6dE62duOed7bjxnEGYOTqwd4kgiPhwsLED05/bAKWCw8EnZoPjKLpDENFA6vU7ITooE9Hl8z0N+P5oC3RaJYkdgkgAOiyuETYOJw+bg4dGRWKHIOJJwqaxiMhpMbu6R7eaqYs0QSQCZotnXl+XtWelKUEQsYXEThLS0mn1+i9BEPLSIRY7NhI7BBFvSOwkIZ7Ijk3mlRAEAQAd3R6x02m1B9mSIIhYQGInCWFip8Nih9XulHk1BEGYrRTZIQg5IbGThIgjOm2UyiII2TGJIjvdJHYIIu6Q2ElCTomMyeTbIQj5ERuUO8mgTBBxh8ROksHzPFpFAod8OwQhP1SNRRDyQmInyTB22+FwevpEtlJkhyBkx0TVWAQhKyR2kowWn946vr8TBBF/KLJDEPJCYifJ8BU3ZFAmCPmhPjsEIS8kdpIM367JLeTZIQjZ6bB4BA6JHYKIPyR2kgzf6ivy7BCBaOu0Ym+dUe5lpASUxiIIeSGxk2SwNJbCPWeQxA4RiIXLt2L2C//DwcYOuZeS9Ig7KJPYIYj4Q2InyWBprAG5Oq/fCcKXnxpcIudos1nmlSQ/Xn12KI1FEHGHxE6SwSI7Qwv1rt8pskP4ged5QQgbu8nXFUt4nkeHaFxEN0V2CCLukNhJMpjYGVzgEjttZFAm/GDstsPu7sckHmVARJ9OqwO8p/UVGZQJQgZI7CQZLJIzpCADgKuZGQ0DJXwRtygwdpEgjiXiFBZA4yIIQg5I7CQZLDVRnpchmJSp1w7hS4vZIvyb0lixxeQjdiiyQxDxh8ROksGGgObptcjWaQCQb4foyakOz3eC0lixxTeyQ1PPCSL+kNhJImwOp3Dhys3QIEenBkDDQImeeKWxKLITUzoojUUQskNiJ4lgPXUUHJCVrkZuhsbrcYJgiKN9xi6K7MQS1mNH6c4rU58dgog/JHaSCBbBydZpoFRwnjQW9dohfGjpoMhOvDC7y87z3DcflMYiiPhDYieJOOU2nbL0Va5b7JBBmfBFLIDJsxNbWGSnIFMLgNJYBCEHJHaSCBbZYemrnAwW2aE7d8KbU1R6HjfYEFAmdrpsDvDixjsEQcQcEjtJBPNhCGKHGZQpskP44GtQpotv7GDVWPl6rfBYt416XxFEPCGxk0QwH4ZvZIfEDuGLWOzYHDxdfGMIq8ZikR2Aeu0QRLwhsZNEMFGT4/bqMM8ODQMlfPE1rZvIpBwzmNgxpKmhUblOuSR2CCK+kNhJItgFzBPZcaWxqKkgIabL6hAuthql6xRAFVmxgxmU9Vol0tVKAECXlUzhBBFPSOwkEa09PDvuaiwyKAeF53ks+Gc1rnx5I+yO5E/nsKo9jVKBoixXaqWdeu3EDFZ6rk9TicRO8n/PCCKRUMm9ACJ6sBEAzKvDRA8bBspC6IQ3e+qM+HR3PQDgRGsXyvMzZF5RbBFHAA1pagBdFNmJISyNlaFRQadxix1KYxFEXKGrXxLBIjuseZkhTU3DQCXw8c464d+pcNFnYidHEDvUayeWeNJYKqS5IzudlMYiiLhCYidJ4HnecxFzp68Uoi7KrZ3JfxGPBJ7n8d8dIrGTAukc9j3Jy9DAkO4K7lKvndjBSs/1aSqkuyM71EWZIOILiZ0kodPqgMXu8gGw9BXg6bVDIyP8s6fOiKOnOoXfUymyk5uhQaY7spMKn1suTCyNpaU0FkHIBYmdJIFdwDQqhXBCBUDDQEMgjuoAqRHhONXDs0NprFjB87wQ2cn0SmOR2CGIeEJiJ0kQ+3U4jhMe96SxSOz4wvO84NfJ1LrSOalw0WfNJymNFXu6bU443c2pvSI7JHYIIq4kjNh56qmnwHEc7rrrLgBAS0sLbr/9dowYMQLp6ekYMGAA7rjjDrS3t3u9juO4Hj8rVqyQ4RPIyykfvw6DGgsGZnetK4WVplZgxuhiAKmRzhEiO3pxGiv5RZ4cmCyu7xPHATqNuM8OiR2CiCcJUXq+ZcsWvPzyy6isrBQeq62tRW1tLZ599llUVFTg2LFjWLBgAWpra7Fy5Uqv17/xxhuYNWuW8Ht2dna8lp4wtPo0FGTQMNDAsKjO+SMK0S8rDUBqRDiEfkw6jVAWnQqfWw7M7iGgeo0KHMcJaSzy7BBEfJFd7HR0dODqq6/Gq6++iscff1x4fMyYMXj//feF34cMGYInnngC11xzDex2O1Qqz9Kzs7NRXFwc13UnGr7dkxk0DNQ/PM/jv26xM6eyH2rbugCkRoRD/F1RuHsT0LiI2GAWmZMBkEGZIGRC9jTWwoULMWfOHEyfPj3ktu3t7TAYDF5Ch71Hfn4+zjrrLLz++ushJzhbLBYYjUavn76Ob/dkBg0D9c/uWiOOuVNYU0cWCkbdVIhwnOpwdVDO03sMyqkg8uSAecD0aa5zFqWxCEIeZI3srFixAlu3bsWWLVtCbtvc3IzHHnsMN998s9fjjz76KKZOnQqdTofPPvsMt956Kzo6OnDHHXcEfK8lS5Zg8eLFvV5/IuHbY4dBnh3//FeUwtJpVDCkp0YJts3hFIRNboZWmHaeCiJPDnwjO+kU2SEIWZBN7NTU1ODOO+/EunXrkJaWFnRbo9GIOXPmoKKiAo888ojXcw899JDw79NOOw1msxnPPPNMULGzaNEi3HPPPV7vX1ZWFtkHSRBaRKZTMTQMtCfiKqw5lf0AQBTZSe4IBxO9Cg7ISlcLF+NkF3lywTxReq1L5KRTNRZByIJsaazq6mo0Njbi9NNPh0qlgkqlwoYNG/Diiy9CpVLB4XCdDEwmE2bNmoXMzEysWrUKarU66PtOnDgRJ06cgMViCbiNVquFwWDw+unrtLoNyLk6X88ODQP1xTeFBcBTgp3kF30merN1GigVnCDyum1OWO00nDLaeMSOTxqLIjsEEVdki+xMmzYNO3fu9Hrs+uuvx8iRI/HAAw9AqVTCaDRi5syZ0Gq1+Oijj0JGgABg27ZtyMnJgVarjdXSExI2yZpFchg0DLQnLIU1daQrhQUgZTw7rMcO+14wLwngMinn6VPr7ybWBDQoU2SHIOKKbGInMzMTY8aM8XosIyMDeXl5GDNmDIxGI2bMmIHOzk68/fbbXkbigoICKJVKrF69Gg0NDZg0aRLS0tKwbt06PPnkk7j33nvl+EiywmZf5WV4X6zYMFAn7xoGWmgILRiTGfEsrAvH9hMez3Rf9M1WB+wOJ1TK5BSFp3yq9pQKDnqtCh0WO4zddhI7UcY3skOl5wQhD7KXngdi69at2Lx5MwBg6NChXs8dOXIE5eXlUKvVWLp0Ke6++27wPI+hQ4fiueeew0033STHkmXD4eSFqea+kR02DLTFbEVrpy3lxc6uk0Ycb/FOYQEQmusBrgtUtk86MFkQDwFlGNLcYifJo1pyEDCNRZEdgogrCSV21q9fL/x7ypQpIUvIZ82a5dVMMFVp77IJLel9q7Fcj6nRYrbSMFD4T2EBrpli6WolumwOGLuSV+z4RnYAwJCuRm17d0qMyog3Hd2+aSzXfymyQxDxJTlj9SkGEzGZaSqo/aRfaBioC1cjwVoAwJyxJT2eTwWTcqvfyE5qlN3LgdnqHgLK+uxoXH+fNAiUIOILiZ0kQDwE1B80DNTFrpNG1LR0IU2twPkjC3o8nwomZaEfk+i7wi7Eyfy55aLDPS4iQ0OeHYKQExI7SYC/C5gYaizoYo07quObwmKkQmNBVrXnm8YCUmPie7zpcH+XfNNYVrsTDmfwND1BENGDxE4SIDQUDOAzoWGgPo0E/aSwAJdRF0juxoIeg7Kn6kr43Eks8uSCDQLN9BkXAVB0hyDiCYmdJCDQEFAGGwbalsJprJ0n24OmsIDUiOz4+65kpkD6Ti46fPrsaEV9rqgiiyDiB4mdJKA1lNhhkZ0UFjtrd9cDAKaNLPKbwgKS37PjdPKefkx6cRqLRXaSN6IlF76l5woFJ0R3uimyQxBxg8ROEkCendCcaO0CAJw2IDvgNoJRN0kv+sZum+ATydZ5+goxkWdK4oiWHPA8L3RQZmIH8MzHooosgogfJHaSABaxCRzZoWGg7MISKKoDJH8ai/XYydSqoFV5vCPC505ir5IcWOxO2N3iMkPrOd40H4sg4g+JnSSgNZRBmYaBotPKvBPKgNsk++Rzwa+j9/6eZJJBOSawFBbgKT0HaPI5QcgBiZ0k4FSoNJbPMNBUhEV2xNUwviR7U8FTHf4jgMnuVZILoXuyRgmFghMe90R2klNUE0QiQmInCQhlUGbDQIHUrcjqtEhIYyX5Rd/fXCyA+uzECt9KLIYnspOaNx4EIQckdvo43TYHzO6oRSCxw4aBAp7p6KlGp/suWhcsjZXkF33WQdt3fhrrs2Oy2KnRXRQRzMlpPmJHzQzKyfk9I4hEhMROH6fNLV6UCk64aPmD9dpJ1WGgnshOMM9Oco9NENJYPTw7oonvSSr05MC37JxBpecEEX9I7PRxWPv/HJ0GHMcF3C4nxedjMc9OhoRqrGSNcLS4vyu+aSyNSoE0tetUkKx+JTkIJHaY4KZqLIKIHyR2+jit7gqrQENAGTkpPPnc6eSFC0t6kMhOpigylowRjlOCt0vb4zmafB592KgIX89OGvXZIYi4Q2Knj8N657BeOoFI5caC4jvoYJEdrUqZ1BGOQAZlgHrtxIIOi+s7FCiNRZEdgogfJHb6OC0dPadY+yObNRZMwV477A6a4yCImUBkJnGEI1jVHvXaiT4d7shOoDRWN0V2CCJukNjp47S4DcqhxA6L7KRi6TmretGplUF9TUDyTj7neV6UxvIT2Unysns5EPrs+Kax1JTGIoh4Q2KnjxOqezIjlYeBCg0Fg6SwGMk6MqLT6oDF3VDSr9hJ8rJ7OWCl55lpZFAmCLkhsdPHCTUElJHKnh0hshPEnMxI1ggH+55oVQq/x4HSWNGnw+rpoCyGSs8JIv6Q2OnjtITonsxgBua+3FTwxS8O4IY3t8DmCK/zrGcIqASxI0R2kivCcUpkTvaXykv2uWByECiNRVPPCSL+hI7rEwlNa4iJ54ycPh7ZsTuc+MtXB2G1O7G/3oQx/bMkv9YsoaEgI1kbC7YGGALKYHPBTBTZiRqB0lhUjUUQ8YciO30cIY0VwrPT14eBHm42C+sWT5OWAhu46HuH7Y9k9eycCvE9oT470Sf0bCwSOwQRL0js9GF4npcc2fEaBtrV96I7e2qNwr/NYYodFtkJNvGckazpnEDdkxmZSVqFJicBxQ5Fdggi7pDY6cOYLHbYHK6xBqHEjtcw0D7Ya2dvnUjshHlHzO6gpUV2ktOoG6x7MpC8ES05EdJYFNkhCNkhsdOHYT4MnUYp9O4IRl8eBrqnLvLIjqf0PPQxYk0Fk8270uIeApoXyLOTRqXn0SZkZIfEDkHEDRI7fZhQPgxf+uowUJ7ne5XG6gxQAuyPZG0qGKpqLytJI1pyYbE7hKirvkefHdfvlMYiiPhBYqcPwyI7ge7Wfemrw0CbTBZB2AEeD45UqKmgp5lkILGTKeovxPPJN/E93ogHyfrOY2ORHbuTD7uNAkEQkUFipw8jtRKL0VcbC+4WpbAAT6RGKmZqKhgyssM+t5MP3xNF9ERsilcqvPsapWk8p13qtUMQ8YHETh9GakNBRl8dBipOYQERlJ4zg7KkpoLufjMWO5zO5IlwMM9OoO9KmloBtdJ1UU42v5IcsO+obwoLADRKhSCAqIsyQcQHEjt9GJaaCDey09eGgTJzcr7eVUkUdul5OGksd4SD5z3t/vs6FrsDJvcxC1R6znFc0pbdy4EgdvxUAHIcRyZlgogzJHb6MJF6dvraMFBWdn5meQ6ASErPpRuU09RKaFSuP4tkSWWxVgNKhUfQ+IPmY0UPcxCxA9Dkc4KINyR2+jAsHRV2NVYf8ux0Wu040mwGAJxRngugF00FJYgdIPkaC4q9XQpFz7lYDMGcnSQiT048Zef+v3M0+Zwg4guJnT4M64qbmxH4bl1Mbh8cBrqv3gSeBwoytRiYqwMQQWTHJr2pIJB8jQU93q7g3xPqtRM9gqWxAOq1QxDxhsROH4aJlkBdcX3pi5EdlsKq6GeAzn2XHGmfHSnjIgBxY8HkuOifEkRxiJEiSSby5CRkGosiOwQRV0js9GGk3rEz5B4GarE7cMvb1fjLlwckv4ZVYlWUGIQLR2e4YieMqedA8k0+Z9+TvBCiOFNLaaxowYRyoGiijuZjEURcSRix89RTT4HjONx1113CY93d3Vi4cCHy8vKg1+tx+eWXo6Ghwet1x48fx5w5c6DT6VBYWIj77rsPdrv8d+TtXTa88PkBXP/G9zFp0mZzONHeFZ5nR+5hoBsPncInu+rx/OcHJEcPWCXWqH4G4cIRTuk5z/PoDDuNlVyNBaW2KBDK7pMkoiUnoSI7nvlYdKwJIh4khNjZsmULXn75ZVRWVno9fvfdd2P16tV47733sGHDBtTW1uKyyy4Tnnc4HJgzZw6sViu+++47vPXWW3jzzTfxxz/+Md4foQcqBYdlGw7iq/1N2HmyPerv3+ZOYXEchAGfoZB7GOiOE67jYHfy+N9PzSG3dzh57K83AXClsVgnWrPVIVlAWuxOONz9cpLRoLx2dz02HT4VdBvJYictuUSenLBGlqHFDkV2CCIeyC52Ojo6cPXVV+PVV19FTk6O8Hh7eztee+01PPfcc5g6dSomTJiAN954A9999x02bdoEAPjss8+wZ88evP322xg/fjxmz56Nxx57DEuXLoXVKq8vJUOrwgUVxQCAD7fVRv392ciH7HR1jw6twZBzGOiOE23Cv7/c1xhy+2OnzOi0OpCmVmBQfoZQ2eJw8rBITMOJLyY6iZ6dvuJd+anBhN/8sxrXvfF90LVKFTuZSToXTA5CpbEEg7KNxkUQRDyQFtePIQsXLsScOXMwffp0PP7448Lj1dXVsNlsmD59uvDYyJEjMWDAAGzcuBGTJk3Cxo0bMXbsWBQVFQnbzJw5E7fccgt2796N0047ze8+LRYLLBaL8LvRaPS7XW/5+bgSrN5eizU7avH7C0eFJUpCccrdETdHYvdkhivlZY57Y0Ge57GtxhPhWr+/EU4nH7QUmqWwRhQboFRwwgBFwJUmkDLpnd1ha1QKqJTStH1fGRmxZrtLRHfbnFi3uwGXTyj1u90pyWmsxIjsHG7qwOvfHkGn1QGHk4fd4Zoh5XDysDl5OJxOjO2fjQdmjQDHRe9vKpqYg3RQBsTVWCQsCSIeyCp2VqxYga1bt2LLli09nquvr4dGo0F2drbX40VFRaivrxe2EQsd9jx7LhBLlizB4sWLe7n60Jw3vABZ6Wo0GC3YfOQUzh6SH7X3ZpGdXIkpLIZcjQXr2rvR3GGBUuHqHnvKbMX2E204bUBOwNcI5uR+BgAQXttlc6DT6kCehP2GMyqCkSgX/WDwPI//7qwTfl+9ozag2PEYlKWmseS9AD/x3734IkTk79uDp3DVmWUYlJ8Rp1WFR6jSc+qzQxDxRTaxU1NTgzvvvBPr1q1DWlpaXPe9aNEi3HPPPcLvRqMRZWVlUd+PRqXA7DHFWLGlBh9tq42q2Al3LhZDrmGgLIU1oigT5fk6fLyzHl/tawwqdoSy8xKD8FiG1iV2pJqUWU8enYRREQxDH0jn/NTQgUNNZigVHBxOHt8caEaL2er3+yB8V0J02mYizyRjRKut04qvDzQBAO6YNgyGNBXUSgVUSg4qBQeVQoEXvzyAY6c6cbipI4HFTnBTfFofqcZyOHn89auDmDQkD2e6m3oSRF9ENs9OdXU1Ghsbcfrpp0OlUkGlUmHDhg148cUXoVKpUFRUBKvVira2Nq/XNTQ0oLjY5YUpLi7uUZ3Ffmfb+EOr1cJgMHj9xIqfjy8BAHyyqx4We/RObK0Rip1smRoLshTWuLIsnD+iEADw5f7gd+97hB47mcJj7OIhdfJ5ZxgTzxl9IbLz3x2uFNbUkYWo6GeA3cnj0109o5kOJy+kLCV7dmT83Gt318Pm4DGyOBP3XDAcvz5nMOafXY6rJw7EVWcOwOUTSjGmfxYA4HCTWbZ1hkJqNVaij4v44WgL/rzuJzy2Zo/cSyGIXiGb2Jk2bRp27tyJbdu2CT9nnHEGrr76auHfarUaX3zxhfCa/fv34/jx46iqqgIAVFVVYefOnWhs9Fw0161bB4PBgIqKirh/Jn9MHJSHwkwt2rts+FpCBZJUmA8jXM+O3JGdcaXZmDKiEBwH7DppRIOx2+/2pzosaDBawHEuzw6DRWjYnXMouqzh9dgBEr+TsDiFNWdsP1w8ziWoV2/vaYRv77KBDW8P1aLAMy5Cvs+9ervrc7HP5I8h7mjO4eaOuKwpEqSmsRJ96jlLabb2sXl6BOGLbGInMzMTY8aM8frJyMhAXl4exowZg6ysLNx4442455578NVXX6G6uhrXX389qqqqMGnSJADAjBkzUFFRgWuvvRbbt2/H2rVr8eCDD2LhwoXQaqV1FY41SgUnnLg/8nMxihR28gnlw/BFDs+O08ljp7vsvLI0GwWZWlSWZgMAvgrgzdhb5yo5L8/L8Lpg6N0VWVIbC3omnocjduSPcASDpbA0KgWmjSrERZX9AACbjpxCo494ZCNFWDooGOxzWx1OWS7CzR0WfHfIdUPAPpM/BhfoASR2ZKcjhEG5rwwCZd8DKpEn+jqyl54H4//+7/9w0UUX4fLLL8e5556L4uJifPDBB8LzSqUSa9asgVKpRFVVFa655hrMmzcPjz76qIyr7snP3WJn3Z76sEcdBEI83DEcQo2MONnWhXmvf49HPtrduwWKONxshsliR5pageFFrgvVVJbKCiB29tS5xBEzJzPCbSzomXgehmdHNBAzFg0hewtLYZ03vACZaWqU5epw2oBs8Dy8TMuAp2ovTx9a/GdoVELTSTmE3ic76+DkgXGlWRiYF9iLM0iI7CSm2LHanUKHcn2A752uj/TZYWIn0UUZQYQiocTO+vXr8fzzzwu/p6WlYenSpWhpaYHZbMYHH3zQw4szcOBAfPzxx+js7ERTUxOeffZZqFSyV9R7UVmahfI8HbptTny+tyH0CyQQsUE5iGdn6/FWzP3Lt/j6pyb8Y+PRqF3oWQprTEmWUP49daRL7HxzsNmvl4lVYo0S+XUAj2iRKhrDnXgOeNJYTj78oaOxxjeFxbi40n8qK5zviULBCVE0OVJZq3e4PtdFlYFTWAAwuMAldppMFpgSMPom/m4GmnrOSs8TPY3F+ll1Wh1wOhNP+BOEVBJK7CQrHMfh5+P7A4heg8FIDcqBIjsfbjuJX7yyCc0drrSHk3f1b4kGO0QpLMboEgMKM7XotDrw/ZGWHq9haSxxJRbguXhIFSHCxPMwIjtpagXUSleII9F67exvMHmlsBhzKvuB44Ctx9tQ09IpPC61xw5DLnN2fXs3thx1fQ/mBElhAa5BrQWZrkjVkQSM7rCoY5o6cG+n9D6WxgKA7igWWBBEvCGxEydYKuvrn5qiYg5ukVhh4wsTO2wYqNPJ45m1+3Dnim2w2p2YPsrTtyicGVTB2M7MyWVZwmMKBSdUZX2x1zuV1W1z4GCTy3xa0S/L6zld2JEd98TzMCI7HMcl7OiEj93RD5bCYhQZ0jBxkKs0WJzKapXYY4chlzn7vzvrwPPAGQNzUJKdHnJ7IZWVgL6dUOZkQDQuoo9EdgBPlJQg+iIkduLE0EI9Rpe4SoQ/3lUX+gVBaOu0ClGXcMWOId0zDLSuvQu3/KsaS786BAC4ZcoQvHLtBKEBXzT8RVa7E7vdKalxosgOAJzvTmV9tb/RK2V2oKEDDiePHJ0aRQZvr4kw+VziHTHbLlA6IRCJUJnkS6AUFsNfVVa4VXvCqIw4R7TYmoNVYYkZUsDETuJVZLG/m2CDZ9P7SDWWRbS+RPcXEUQwSOzEERbd6W0qa8vRVgAu74LUSd4MpWgY6C9f2YS1uxugUSrw5yvG4YFZI6FQcBFNFw/ETw0mWO1OZKWrMTBP5/Xcz4blQ63kXA3iROkIwZxcYugxDkDnFi1S1+bpsxPecfI0FkycyE6gFBZj9ph+UCo47K414pBbBEjtnszIlCGiVdPSiW01bVBwwOyxgftjiRmc767ISsA0lklKZKevpLFEkZ1OW+IIf4IIFxI7cYTdtW452oLatq6I32eze8r1xEFSBib0hA0DrW3vRl6GBstvmug1aoCJnWhEdlgKq7I0q4dw0WtVwmcQl6ALfp1+PZs96sNuKhh+nx0gMRsLBkphMXIzNPjZUFeX7jXufjXhGtnlSGOtcX+uSYPzUJgprZt6IqexwonsdNkcCVnxxxBHniiNRfRlSOzEkZLsdJxVngueB9bsiDy6s9lt6J00OLL27cVZrgvKyOJM/GfhZJzh0waepXyicde5vaYNgEvs+INVZYl9O55KrJ5iJyMOTQWBxGssGCqFxfD0dDoJnucjMCjHP6LF/hZCVWGJYRVZR5rNCVclxMROpoTIDs97+2ISDYuoSIHSWERfhsROnGHjIyJtMGjstmF3rSvNE2lk5w8XVuB3s0di5S1noyxX1+N5j6Do/YWeVWL5+nUYTOxsOdoCY7err42/mVjC2rTh+YnY1PP0MNNYmQmWxgqVwmLMGF0EjUqBQ01m7Ks3iQzK0ppsxjuNdaipA7trjVApOMwaIy2FBQBluTqoFBy6bA40mPx34ZYLJpCDRnbUHvGdyCJCXIFlpgntRB+GxE6cuXBsP6gUHHad9PgqwqH6aCucPDAwTydEaMKlosSABecNCegp0EcpjdVpteOnBldKalxZtt9tyvMzMDg/A3b3MMsTrV0wWezQKBUY4u6UKybcFFskU8+BxEtjhUphMQxpapw/ogCAS1BLHQLqeX18++ywdNvkoflhme3VSgUGuIV6oqWyzCGGgAKASqmAxl2WnsgVWd1kUCaSBBI7cSY3Q4Nzhrl8FR9FYFTedIT5dWI3gThaBuVdJ41w8kCRQYsiQ2BhxqqyvtzXKFRuDSvS+x1vIJSeS7zLjGRcBJBYk895nscaCSksBktlraw+AavDXbUnsdO2MPk8DiKP53ms3hFeFZaYwQlakcW+m5kBRkUw0tSu73cim5TFvbYoskP0ZUjsyIA4lRWuOXHzYZdf56wIU1hS8ERPencSFg//DMY0t9hZv79RSNH5MycDIoNymJ6dcJoKAokV2dnfYMJhCSksxtSRhdBplGgyuRpEpquVksWep79Q7C9s+xtMONjYAY1SgRmji0K/wAdhRlaCVWQJaawQ3zkm3BO5/Fzc3ZwiO0RfhsSODFxQUYw0tQJHms3YddIo+XVmix07TzK/TuwiO3qhS3HvLnjbmV8nQAqLcUZ5LvRaFZo7rPhg60kA/v06gMdoLDXqZBZKzyMzKCeC2JGawmLoNCqv5pDhpIfiWXLPUljnjSgQjnc4JGpFljnEEFBGX2gsKI7sJHIEiiBCQWJHBvRaFaa5L0b/2XZS8uuqj7XC4eTRPzvdr7E4WkQrjbVDVHYeDI1KIaT2TrpL8kNFdix2J+yO0FUsQul5mP2IPFVJoY/Bqh9PYOb/fY1jp6J/0Q03hcUQp4XyJPp1gPhFtHqbwgKAwcJA0MRKY3k6KAcX2H1h8rlX6TmlsYg+DIkdmZgr6nbrkFg6uzkOfh0gOgblVrMVx065ZjRV9s8OuT3z7TBGBhA7YtNnqPlYdodn+rROHbvIzj83HsP+BlPU5p6JCTeFxTh3eL7gGQkvshOfkvtdJ404dqoTaWqFkMYMF5bGOtHa5XeYrFx0SOizA/SNyedWO5WeE8kBiR2ZmDKiEFnpajSaLNjkbhIYCubXmRhhfx2phDt/yh873Om2QfkZyNKFTlFMcVcQAUBpTjqy0v2/RqPyDOkMtb5O0V2pLuJxEcHFDs/zONjoiiywkvloEm4Ki6FVKTFrtKuUW2rZOeCJaHVaHbBJiJxFCovqTBtVFHYXcEa+XoNMrQo8D0FYJwJmCR2Ugb4x+ZyaChLJAokdmdCoFMJ051U/hk5ldVkdQjfiSPvrSMXTyybyk9uOEM0EfSnMTMM497aBUlie9UnroszuRJUKTijzlYrYqBvMRN5ksghm3j0xEDtfH2gGAEG4hMOd04dhTmU/XD+5XPJrxBfoWEV3nE4e/3WLuItDTDgPBsdxCVmRJWUQKNBH0ljiyA6NiyD6MCR2ZOSS8f0BAJ/uqg95d/fj8VbYHDyKDNoeM6aijZDG6kWO3jMmIlvya/6fe2SFb0rLF6ldlNkdtk6t7DGqIhQswuFw8kENpCyqA7iiC9GaFA+4okbsIj6mvzTRKKY0R4elvzo9rNeqlAqhJ1GsTMo/1rTiZFsX9FoVpoyILIXFSMSKLCnjIgBRGiuBIzviQaCJLMoIIhQkdmTkjIE56J+djg6LHZ/vbQi67Sb3iIiJg/LCvnCHS28NyjzPC5VY48ukX2ivmTQQ3zxwPn5xZlmI9bnviEOlsQRzcngpLMCVYlC6x8MHMykfaPSOKOyvj150p8VshbHbDo5DzAWuGE+vndjcyTNv04yKIiG6ESmJWJHFjltSpLHEg0ApjUX0YUjsyIhCwWGuu+fOf34Mbm4Vhn/G2K8D9N6gXG/sRpPJAqWCQ0U/6WKH4ziU5uhCijmdxHEWniGg4XtCOI7zlGEHMSkf9BE7e9xDTKPBEXe0oiQrvdeiIBxiWXZvdziFFBbrN9UbEi2NZXc4hVlXIcWOhqWxEjM9ZHM4vYonaOo50ZchsSMzl57mSmWt398ozDHypdvmwI9uD0ys/TpA75sKsuGfw4syw+5cLAXP5PPg6+uMsMcOQ4pJ+UCjS9z0c4/uiKZJmaVm2AU9XsRyLti3h07hlNmKvAwNJrsntPeGwfmuNNaRBEljif9mQqWxhD471sQcBOo7oJQiO0RfhsSOzAwrykRFPwPsTs9Ua1+217TBanciX6/FkDhc+DJETQXD7fAMIKIUVjhIbSzYGeHEc4aUCAeL7FzkNtqyie3RgF3AWaomXsQyjfWhu6/UnMp+fseBhEt5viu919ppC3izEE9MFtd3RaNSQKMK/vlYGitRjb++6TXy7BB9GRI7CQCL7nwYoMHg94JfJzfmfh3AEznh+chOcDsiMCeHg15iNVZv0lhA6MaCrWYrmjtcF9iLKl0pmf31Jsl9k0JxpEkmsSMhfRcJ3TYH1u6qBwD8PMJGgr7oNCqUuKNqidBckEV2QqWwgMTvs9NT7CSmKCMIKZDYSQAuHlcCjgO2HG1FTUvPfiGbj8Snvw4jXa0E01Th+nacTh47alyRHall5+HiMVDHOI0VIrJz0O0T6Z+djtElBmhVCnTZHFHrpCxXZIf184l2GuuLvY0wWx3on52O0wfkRO19hYqsBDApd7gjO1LETpo6sauxeqSxElSUEYQUSOwkAMVZaTh7iMuL89F2b6OyzeFE9bFWAPHx6wAuc26GMF08vBPckVNmmCx2pKkVGF6UGYvlCdVVIZsK9jayE+Kiz1JYQwv1UCkVGFns+rx7o2BSdjp5HHGLJuZLiRdCRCvKaayPtrsilz8fXwKFInoRSqEiKwF8O0yAS2mUmJ7gfXZYZEfrTsfZnbxXR2WC6EuQ2EkQ5rp77qz68aSXT2bHiXZ02RzI0akxrDB+F70MiYLCF5bCGl2SFRVPhj/0mnDTWJEalINf9A80eMQOAIxyN0OMhkm5tr0LVrsTaiWH/jnpvX6/cIhFNVZ7lw1f7WsCAKECMVokUkUW+3vJDCONlail52wIqHjcCKWyiL4KiZ0EYdaYYmhVChxs7MBukcmVzcM6a1BuVO+GQxFpr53tMU5hAZ6hniHTWJbopLFMIdJYw2IgdlgKa2BehtDvJ154qtCid2Fbu6seVocTw4v0GFkcvEN2uLA0ViJUZHV0s4aCob9zaQneVJDNG9NrVUIH8kSNQhFEKEjsJAiGNDWmV7gnoYvGRwjzsOKUwmJE2mtnp3sm1rgYmZMBzzTpkE0Fbb1LY3lKsP3v52CDK13lG9mJxtgIufw6gOhzRzGy86E7hcUimNGETT8/eqozaubwSJE6BBRI/DSWxR3Z0aoVCd8TiCBCQWIngWDjIz5yT0K3O5z44Wh8zcmMDImN+3ypb+8GAAyIYcdfyU0FexvZSQ+czumw2FHr/qxM7Izs5/Ls1LV3o62zd2XQzGwb7x47QGivUrg0Grux8ZArQhmtKiwxJdnp0KgUsNqdONnaFfX3DwchjZUWRhorQcUOS6+lqZTCCJFEFWYEEQoSOwnEecMLkK1zTULfeOgUdtcaYbY6YEhTRT30H4pIGwuylI8hjAnd4SK9qWDk4yKA4Bf9Q25zcr5ei2ydRti+LNflr+ltdIdFdgbLENmJdp+dNTvq4OSB0wdkoyw3+iJYqeAwKI+ZlOX17QiRHQnRxPQ+Uo2VplaKIjuJuVaCCAWJnQRCo1JgzlhXc7r/bDsp+HXOLM+Nu29DH4FB2enkYXJvb5BwZxspGRJTbL03KHsmn/vCZmL5msZHFTPfTu8qsthFe1CcK7GA6PfZ+dBdYRiLqA4jUWZkhZXGSnABIa7G0kksCiCIRIXEToLBGgx+uqseG35yVa/EO4UFRGZQdnVcdv2bCYVYIL2DMktj9bapYM+LPis7H1bkI3aiYFK22B044U7HyOPZcf2/67DY4eylB+Zosxnba9qg4IA5lbETO0JFVoJEdqSksVhkx2J39vo4xwIhjaVWCn9ziSrMCCIUJHYSjAkDc1Ca45qE/u1B9/DPOJuTAY/YCedOjkVANEqF0JsjFoSdxopCU0HfsRkHG73NyQzBpNyLsRHHT3WC513ly/l6TegXRBl2oeZ5CJG6SGF9oyYPzUdBprbXawtEolRkmSOI7ACJmcpiaSytWuEROzQfi+ijkNhJMDiOE4zKgOvCProkvn4dQGxQln5yYxGQzDRVTMda6CTO7ur9uAiX2LE5eKHnCEPcUFAM+391sLEDNkdkDdhYc7xBBRlxGQ/iS5paKYjVQGX3UuB5XhiBEosqLDGJlsaS1EFZldhih33n09RKod0DpbGIvgqJnQTkktM84f4JA3OgilFzvmBE0lSQGVpjmcICvGd3BbtI9Dayk6FRglmlxP6VbpsDx91jPXzFTmlOOjK1KlgdThyKsMmdnGXnjGj02tlTZ8ShJjM0KgVmji6K1tL8wgbk1rV3y3pBDkfsKBQc0tSuv+1EnI/VbRd5dliZfAKKMoKQAomdBGRoYSbG9HdFCCYNjn8KC4iszw6L7MTSnAx4z+4K5tvp7WwsjuNElUkesXOk2QwnD2Slq1Gg1/Z4DStBj9S3I9cAUDHR6LXz0TZXCmvayELBBxQrsnUa5Ohc+5AzlWUOY1wEkNgVWRZxZIfSWEQfh8ROgrLk0kpcd3Y5rpk0QJb9R2JQZhfGWF/YxLO7Ap18nU5euIBEmsYCPL6ddlGE44AoheUvzeQxKUdWkZUQkZ1e9tpxOnnBrxPt8RCBSISBoCy6KSWyA3i+m4kc2UlTidNYibdOgpBCbG/BiYgZW5qFsTEcuRAKIbITRkrAk8aK/ddKp1Giw2IPKMa67Q6hMizSyA7gP8JxMEDZOaO3FVmHhR478S87Z/S2186Woy2oa+9GplaFKSMKo7m0gAzOz0D1sVaZIzvhiR0hjZWAkR2h9FytENK55Nkh+iqyRnaWLVuGyspKGAwGGAwGVFVV4ZNPPgEAHD16FBzH+f157733hPfw9/yKFSvk+khJQyRNBQWDsja2kR0gdJpNfAfKUgWR4C/CEagSi1EhqsgKZqD2h7HbhuYOCwCgPD92XahD0dteOyyqM3NMMdJ6cfzDYZDMA0EdomiiXmIqN5EjO0JTQZWCIjtEn0fWyE5paSmeeuopDBs2DDzP46233sLcuXPx448/YuTIkairq/Pa/pVXXsEzzzyD2bNnez3+xhtvYNasWcLv2dnZ8Vh+UsMMyuGksYSGgnGI7GSEOPmy9Fa6WtmrAar+Jp8HqsRijCjOhIIDTpmtaDJZUGhIk7y/o+6oREGmNubpwGBkpvXOoLxuTwOA2DYS9IVFwg7LFNkR/61IGQQKJLpnx9Nnh0l2EjtEX0VWsXPxxRd7/f7EE09g2bJl2LRpE0aPHo3i4mKv51etWoUrr7wSer33RSY7O7vHtkTvYJ6YyAzKsb9Ih2os2GmTPn06GL6RHZvDKaRJhhVl+n1NmlqJQfkZONRkxp46Y1hiJxH8OoBH5EVSet7cYUGjyQKOA84oz4n20gLCKrKONJnB83zcy/bZ34payUGrkva9EyafJ6CI6BYNAlW4jyWlsYi+SsIYlB0OB1asWAGz2Yyqqqoez1dXV2Pbtm248cYbezy3cOFC5Ofn46yzzsLrr78eMnVgsVhgNBq9fghvxJETqd1dPQbl2GtofYi+Hyz9lt4Lvw7QcxjosVOdsDl46DRKlGQFFjGRmpSFAaByi500788dDj/Vuz7zgFxdr8zh4TIgTwcF54owNrlTgfEknLJzRiKXdFvEBmUNpbGIvo3sYmfnzp3Q6/XQarVYsGABVq1ahYqKih7bvfbaaxg1ahTOPvtsr8cfffRRvPvuu1i3bh0uv/xy3HrrrXjppZeC7nPJkiXIysoSfsrKyqL6mZIB8Qlb6ok4Xn12AAgegkBND9mdspSBjMEw+KRzDoaoxGJEalJOmMgO8+xEkMba5xY7IwJEvmKFVqVEaY7L5yRHRVY4c7EY6Qk8+bzbX+l5HCM7VrsTBxtNYfveCMIfsoudESNGYNu2bdi8eTNuueUWzJ8/H3v27PHapqurC8uXL/cb1XnooYcwefJknHbaaXjggQdw//3345lnngm6z0WLFqG9vV34qampiepnSgbSRBUYUlNZ8UxjsUGlnQENyq7Hex/Z8TbqCubkguCVUhXuTsrhTj9PGLGTHnlkZ79b7Iwsjq/YATwzsuSoyAq3EguAYN4OFTE52mzG524fVLzwHgQa/9lYj/93D6Y/9zW+Odgct30SyYvsYkej0WDo0KGYMGEClixZgnHjxuGFF17w2mblypXo7OzEvHnzQr7fxIkTceLECVgsgcPYWq1WqABjP4Q3HMeF3WuHmXjjkcZiYfWOAHeave2ezGDCjUWthMhOUQix447sHG7qEC4aoeB5XrhIs4u2XPh+7nDY1+ASO8NlEDuesRHxr8jqCLPHDuD5foYyKN+x4kf8+h8/YNfJ9sgXGCae2VjypLHY39qBBnmHuxLJgexixxen09lDqLz22mv4+c9/joKCgpCv37ZtG3JycqDVxm7oYKoQbhdlZmaNRxpL8BQFSGP1di4WwzM2wfXZhIaCISI7hZla5GZo4OSBnxqk+XaaOizosNih4ICyXPnKzgFPRKs9zKaCTiePAw1yRnbkaywYURrLHdkJJogdTl5Ih7IxJfHAM/VcIUsaix3PtggbWxKEGFmrsRYtWoTZs2djwIABMJlMWL58OdavX4+1a9cK2xw8eBBff/01Pv744x6vX716NRoaGjBp0iSkpaVh3bp1ePLJJ3HvvffG82MkLWFHdrri59nRh5jd1dtREQxxU0GnkxfmXQWqxGJwHIdR/TLx7cFT2FtnRGVpdsh9sTERpTk6ydU8saLIXUFW29aFbptDcq+cE61d6LQ6oFEqUJ4X/+hU/2zXuhtNMhqUw4hspksQESdbu2BzuHwrzXE0XnvSWB7PTrfNCYeTh7IX7Rykwo5npF28CUKMrGKnsbER8+bNQ11dHbKyslBZWYm1a9figgsuELZ5/fXXUVpaihkzZvR4vVqtxtKlS3H33XeD53kMHToUzz33HG666aZ4foykJZzGgt02B6zuKd9xTWOFaCrY68iOyKB8sq0L3TYnNCoFynLSQ752VLHBLXakRXYSxa8DAP2z05GboUGL2Yp99SaML8uW9Lp99a4IxJBCvSwDbHN0GgBAa6c17vsWPDthfOc8fXacAbc51OxJ4zR3xO9zCU0F1Qqvv6MumyOsVF2ksLRguNFFgvCHrGLntddeC7nNk08+iSeffNLvc7NmzfJqJkhEl1DREzHMyMpx4Z3sI0UfoqmgOUqRHbFBmXkIBudnSLqQh2tSThS/DuCKTFWWZmH9/ibsONEmWezIaU4GRGLHHH+x0xHmEFDAE9kJ1mfniCglF6/IDs/zIrGjRJpaAY4DeN4VhYqH2GHnHRI7RDRIOM8OkTiwuzkp87FYCkuvVfWqY7FUQjUV9JSeR6fPjtXuFMyhgTon+yIuP5dSPuuZiSW/2AGAyv6u2Ww7Tkg3xe53+3VGyCV2Mlxix2x1SDaGR4sOi+uiHE4ay2NQDvw3Jq4sa45Teo4JHcBVjcVxnKcnUBwmnzudPMzuv2ESO0Q0ILFDBCQcg7JgTo7TiAPpTQV7dweq16jA2ulUH28FIF3sDCnQQ63kYOq240RrV8jtPWks+QaAimE+ox0n2iS/hkV25BI7hjSV4Cdp64zvRZJ95/RhdO1mXqhgkZ3DojTWqThFrCyitBpbYzznY4lvsEjsENGAxA4REM98rNAnN2McGwoCnhNvID9RV5TGRSgUHDLd+/rxeBsAYFihtAu5RqXAUPe2oZoLOpw8jp1yi50ESGMBQGWpK7JzsLFDkuC12B1CdCreDQUZHMfJ5tvxdFCW/jcgxbMjRxqr2909WangoHanbKVEoaKFOGJLYoeIBiR2iIBkhBHZESaex8GcDIj8RCH67PRm4jmDCTh20pUa2QGAUf2Y2AluUmYVN1qVAv3CmKUVSwoNaSg2pMHJA7trQ/uODjeZ4XDyyExToV+QURqxJkfn+v8Vb98OM9SGI7AFARHwe2xHbXu38Hu80ljihoIM9rckpWCht5hJ7BBRhsQOERB9GMNAhVERcUpj6UKsjfkKojGbSfyZlAoO5fnSe+BUSBwbwVIVg/Iz4uJ5ksrYUubbaQu5rdicHO8hnGKYb6clzpGdU2aXEGGRJSmkhZh6frS5072d61RttjriMjRUbE5mZMQxjSVuZmm1O+PuvyKSDxI7REDC6bNjFBoKxieyw9Zmc/DCwEIxbOq5rpdpLMD7Mw3MC68HDhM7oSqyEqnsXMy4Uukm5X0y+3UYuTJVZNW1uSIwJdnSo1rpIcYwsO/FqH4GaNxRlniksoSGgqLITjwbC/qecyi6Q/QWEjtEQBLZoCyusvJXHSJEdqKQxsoUfaZQnZN9YRVZx1s6sb2mLeB2iSp2xrpNyjsljCnY7+6xI5dfh5GT4U5jxdGgbOq2weT+O+mXFboHE8PTrM+/2GFjLwbn65HvjljFR+x4RkUw4jkfy/ecQ2KH6C0kdoiAhNNUUOieHCfPjkqpEPwE/iJP7IQcTs+TQIgF3LAQM7F8ycnQ4NLT+gMAfr9qJ+wO/0ZUNt4g0cQOKz8/0mwOecH5yT3DaESxvLPmWBqpJY6RnXq3r8aQpopoXITNwcPm57sh7r2Un+kagXMqDo0FWbRU6xXZcX2ueKTRfGeykdgheguJHSIgOqEaK5w0VnwiO0DwxoLmKE09B7zTWOGYkxm/v3AUDGkq7K414q2Nx/xuk0gNBcXkZGhQluuKVAQbQmnstuFkm6u8Xu7ITm5G/KuxmIk4nKgO4P399OfbEfdeyte7xE48Iztizw5bq5S+W72lR2Qnzm0EiOSDxA4RkFC9bMSY4jjxnBFIjPE8L2oqGOXIjsSyczEFmVr8bvYoAMBzn+1HXbt3z51um0MQConSY0cM67ezPYhJ+Se3X6dfVhqydPETvP6QI7JT5/7/1y8Mvw4AaJQKMD96t49o53leSGMNKshAnlvExaPXjr9qrAwJ3Z6jBXl2iGhDYocISIYwf0pKGiu+nh3Asz5fMWZ1OGF3ujoWRyey4/lMkUZefnFmGSYMzIHZ6sAjH+32eu6ou79OVrpaKJtOJFgqa2cQkzLrnDxc5qgO4PHsxLOpYKSRHY7jRL12vP/OWsxWGLvt4DigPM+TxmqKQ/m5v2qs9DA6qvcW33MOiR2it5DYIQISjkGZpbEy4yl2AqxPfOfZ29lYgMeHVJqTHnEpu0LB4YlLx0Cl4LB2dwM+39MgPHdE5NeRs2Q7EJ5OykHEjswzscTIGdkpiaC/ULrGfzqWpTZLstKRplYKkZ24VmOpe0Z24mFQZqM3GCR2iN5CYocICGuO1mVzwOEMPttJ6LMTp9JzQFwa733yZSdjjVIhdH/tDaP6GcBxQNXgvF69z8hiA248ZxAA4OGPdgsRqUSbieXLmP6uz3+yrSvghTZRys4BeTw79UZ3ZCc7vMgOAKRrXN9R38gOM62zaGJBHA3KnjSWn2qsuDQVdP8Nu9NoJHaI3hLRleDRRx9FZ2dnj8e7urrw6KOP9npRRGIgrioJFbqWI43Fuij7prE6o2hOBoAx/bOw+ffT8NTllb1+rzunDUP/7HScbOvC858fAJC4ZeeMzDS1IMT8pbJ4npd9JpYY1lSwM47DQGt7E9lxp4p8PTuHfb4X8TQoe9JYog7KLAIVh2PKbp76u8UjiR2it0QkdhYvXoyOjo4ej3d2dmLx4sW9XhSRGGhVCqjc7slgqSy7wylMKI6rQVnjv+lhZ5QmnospzEwTBkz2Bp1GhccuGQ0AeO2bI9hTa/SInQSrxBITLJXVaLKgvcsGpYLDkDD7EMWCTK1K+N7Gw7fD8zzq3J6d4iimsTw9dlzfizx9/NJYFiGNJeqgHGK0RTRh5xvWoJHEDtFbIhI7PM/79RZs374dubm5vV4UkRhwHCdpPpZYbMTTsyNUi/mE1T0Tz6MndqLJ1JFFuHBsMRxOHr9ftdNTcZOgkR3AMxTU39gIlsIqz9N5XRzlguM4ZMfRt2PssgtCJVyDMgCkq/2nsTwi2CUgWWSntdMWsF9TtOh2R3a8ZmOx0vM4pLHYOYUiO0S0COs2PCcnBxzHgeM4DB8+3EvwOBwOdHR0YMGCBVFfJCEfeq0K7V22oBVZrKFgulop5NjjAfMQ+EZ2PBPP4xdlCpeHLx6Nr39qxjZRV+XyvD4gdk6297jZYZ2TR8rcTFBMboYazR2WuPh2at2tBHJ06ogEtlCNJYrsOJw8jp1yWQVYZCdHp4GCA5y8S8QVxnBgrN/IjvvvKdAcr2hiFsSOaw4diR2it4R1NXj++efB8zxuuOEGLF68GFlZWcJzGo0G5eXlqKqqivoiCfnwmBIDR3Y8lVjxFRcZAfoACZGdBIgyBKLIkIZ7ZwzHI6v3AACKDWkJLc4q+mVBqeDQZLKg3tjtFcHYX886J8vv12HEsyKL9U2KJKoDiDoTi0TEydYuWB1OaFQKlLijG0oFh9wMDZo7rGjqsMRU7PhtKihMPY99GouN3uifQ5EdIjqEdXadP38+AGDQoEGYPHkyVKrEPTkT0UHKMFA5uicDHg+Bb1i9K4qjImLJtVXl+ODHk9hxoj2hU1iAK4UxrFCPffUm7DjR7i12GlyRnUToscNgYqctDpEd5tcJZwCoGH+Tzw83uwRkeZ7OyyuWr9eiucMa84qsbr/jIuLXVJA8O0S0iSjnkJmZib179wq/f/jhh7jkkkvw+9//HlZrfCcNE7FF6LUTxJTI0lhyRXZ81xbNURGxRKng8OwV4zBhYA7mVQ2UezkhGSeYlNuExxxOHgfcM7ESoccOg1VktZhjf5Fk084jj+z07F8TqEIvXhVZFj+DQIVIqs0Bng/eiqI3OJy8cCxK3Wksq90Zt8o6IjmJSOz85je/wU8//QQAOHz4MK666irodDq89957uP/++6O6QEJeMoSRDIFPNPGeeM4IZJ6ORTVWrBhelIn3bzkbs8f2k3spIRkrmJQ9FVlHT5lhsTuRrlZiQK5OrqX1IFeYfB4/z04klViAR5SLL+aeHjve1W2sIitekZ00PwZlh5MXStNjgfjmpdCgFSJbFN0hekNEYuenn37C+PHjAQDvvfcezjvvPCxfvhxvvvkm3n///Wiuj5AZKdVYRqGhoDxix1eIsTB7pN2OCf8wk/JOt0kZ8MzEGl6khyIKpfnRIq6enbYopbESKLIjNBUURXZ0on/HMpXV4T6fqJUc0tRKoYM5iR2iN0Rceu50upT9559/jgsvvBAAUFZWhubm5uitjpAdKSMjTDIZlAM1Fewraay+xojiTGiUCrR12lDT4opm7BPETuKksACP2IlHZKf3BuXAaSzfrtosstMU6zQWayooiuyolAqh2jKW87HYuYade7LcN1EkdojeEJHYOeOMM/D444/jn//8JzZs2IA5c+YAAI4cOYKioqKoLpCQF0kGZbdnJ95pLBa5CTQbqy+ksfoSWpUSI/u5RA2bgJ5InZPFxGtkhLihYEmEYkfooOyOpnRZHTjp7sjsm8ZikZ2Yp7H8VGMB8Zl8ziqxMnzFThwHuxLJR0Ri5/nnn8fWrVtx22234Q9/+AOGDh0KAFi5ciXOPvvsqC6QkBcpkR1PNVa8IztsbT5NBa2sqSClsaKNOJUFeKadJ1KPHcBjUG6NsUG5tdMmREGKsrQRvYfv1POjp1xRnax0NXJ03jcQBXEzKPesxgJENxhxSGOxv28DRXaIKBDR1aCyshI7d+7s8fgzzzwDpZLuppMJFmIPdnIzyTDxHBCVwroHlTIjI2tnT5Gd6FPZPxvAcWyvaUO3zSFcmIcXyz8mQkxunDw7bCZWvl7jNTQzHNI13ulYZk4elJ/Ro1N9vEZGeGZjeX8m37XGAnZjxdLilMYiokGvbn2rq6uFEvSKigqcfvrpUVkUkThIMigLaSx5Ss8B18mXia1EHxfRl6ksc0V2dp1sx/56E3jelTJiEYdEIdtdjdVlcw0DjdUYC5bCitSvA4gjOy6BccTdY2ewn1lp4jRWoLE90aDbTwdlQOY0FokdohdEdHVqbGzEVVddhQ0bNiA7OxsA0NbWhvPPPx8rVqxAQUFBNNdIyEh4aaz4Rna0KgWUCg4OJw+zxSGIHTaVOYPSWFFnaIEeaWoFzFYHPtlVDwAYUZQZs4tupLBhoHYnj9ZOa6/ESDA85uTIuxnrfAZsHg5gTgY8kR27k0d7l02YARZtugOksdIlRHp7CxmUiVgQkWfn9ttvR0dHB3bv3o2Wlha0tLRg165dMBqNuOOOO6K9RkJGApV3izF1yxPZ4ThOuNMUG6jZaAsdRXaijkqpwJgSV3Tng60nACSeORlwfTc8jQVjl8rydE+OXEylabw9O540Vs/UoFalFNI7zTE0KQdKY7EbiFhOPvf17DCxYySxQ/SCiMTOp59+ir/+9a8YNWqU8FhFRQWWLl2KTz75JGqLI+SHlXdLiuzE2bMDiCafi06+rIRXl+DjIvoqrLlgo8nlG0lEsQNAMPfG0qRc19b7yI5nEKgTPM/jcFPgNBYQe5Oy3eGE3enqo5SmDhDZieHk8w6rf7HTRmKH6AURiR2n0wm1uueFTa1WC/13iOQglGeH53khshNvgzLgETTiyA67Q6bITmxgYyMYiSt2Yl9+Xss8O72I7IjTWK2dNqFJZ3mef7ET68aC3aLuyL6ma51PFCoWsMgOO/dk6yiNRfSeiMTO1KlTceedd6K2tlZ47OTJk7j77rsxbdq0qC2OkB8Wtg7UZ6fT6qqEAuJfeg6I5vWI7jSZMEvkqed9GRbZYSRaQ0FGPHrtRMOzIy49Z1Gdkqy0gAb7WI+MEI+tCFR6Hs9qLCo9J6JBRGLnL3/5C4xGI8rLyzFkyBAMGTIEgwYNgtFoxEsvvRTtNRIywkLJFrsTdkfPqB1LYakUnCziQph87j75iuf2JPrU877KoLwMZLqPbVluuvAdSTRi7dlxOnnUC9VYkYsd5tlx8p6O1L7NBMXEOrLD/n40KkWPESC6eKSxqBqLiAERnaXKysqwdetWfP7559i3bx8AYNSoUZg+fXpUF0fIj1gwmC0OZOm89bEnhaWSpSInw6exoPiOk9JYsUGh4DCmfxY2Hj6FEQka1QHEnp3YiJ1mswU2Bw+OA4oMvY/sAMDuWiOAnjOxxMS6106gSizA8/cW09lYVI1FxICwIjtffvklKioqYDQawXEcLrjgAtx+++24/fbbceaZZ2L06NH43//+F6u1EjKgUSmgVrpEjL95OKxCIt5l5wwhsuM+QbKTsILzf7ImosPPhuUDACYOypN5JYHxeHZic5FkUZ3CTC3Uysi/a2ql529sT62rM3UwseOJ7MQ2jeWvNxETZrGcjRVI7FjtTq8UG0GEQ1h/oc8//zxuuukmGAw9W8NnZWXhN7/5DZ577jnJ77ds2TJUVlbCYDDAYDCgqqrKq5prypQp4DjO62fBggVe73H8+HHMmTMHOp0OhYWFuO+++2C3x+4PMRUJZlL2lJ3LJHZ8DMpm0cTzROv9kkzcfO5gLL9pIq6bXC73UgISa89ObVvvGwoymLDwpLGkiJ3YprF8K7EAsZk6ln12XO+td3t29FqV0B2dojtEpIQldrZv345Zs2YFfH7GjBmorq6W/H6lpaV46qmnUF1djR9++AFTp07F3LlzsXv3bmGbm266CXV1dcLP008/LTzncDgwZ84cWK1WfPfdd3jrrbfw5ptv4o9//GM4H4sIQTCTslGmiecM39Jz9l9KYcUWtVKBs4fk9yqiEWti7dlh5uSS7MhTWAz2fWVCY7CfHjuM/LilsXr+DemEv7cYdlBm1Vju8w7HcUIPLxI7RKSEdaZqaGjwW3LOUKlUaGpqkvx+F198MS688EIMGzYMw4cPxxNPPAG9Xo9NmzYJ2+h0OhQXFws/4qjSZ599hj179uDtt9/G+PHjMXv2bDz22GNYunQprNbYzsRJJQIN3AREaSyZIjs6QYgxzw6VnRMuhDRWzMSOK7JTbOh9ZEfs29EoFeifE/g9Yz353GILEtlRx382FkC+HaL3hCV2+vfvj127dgV8fseOHejXr19EC3E4HFixYgXMZjOqqqqEx//1r38hPz8fY8aMwaJFi9DZ2Sk8t3HjRowdOxZFRUXCYzNnzoTRaPSKDhG9I0Pbs0sxg/UEkaPsHPCszRPZoYnnhIvcGHt22BDQaER2xN/XgXk6IW3jj/xMl9jptDpiIjosdrdnx29kh/29xSayY3c4hR4+4uIIQezE6P8lkfyEdUW48MIL8dBDD2HWrFlIS/P+A+/q6sLDDz+Miy66KKwF7Ny5E1VVVeju7oZer8eqVatQUVEBAPjVr36FgQMHoqSkBDt27MADDzyA/fv344MPPgAA1NfXewkdAMLv9fX1AfdpsVhgsXhCwEajMaw1pxrBPDtGmSaeM3zXxkZF0MRzIkc0DLTL6oj6YNj6KAwBZaSLoijBzMmA67utVSlgsTtxqsMKXW50hX23O7Kj9evZiW0aSzxzi93IANRrh+g9Yf2VPPjgg/jggw8wfPhw3HbbbRgxYgQAYN++fVi6dCkcDgf+8Ic/hLWAESNGYNu2bWhvb8fKlSsxf/58bNiwARUVFbj55puF7caOHYt+/fph2rRpOHToEIYMGRLWfsQsWbIEixcvjvj1qYaQxvJbjZUYBmWzTxqLJp4Teq0KaiUHm8M1DDRdE91hoMLE86hEdjzf10FBzMmAy8OSr9fiZFsXmjosKMvV9Xr/YoRqLD+RHXYTEas0Fosea5QKL88QpbGI3hJWGquoqAjfffedkFK69NJLcemll+L3v/89xowZg2+++aZHpCUUGo0GQ4cOxYQJE7BkyRKMGzcOL7zwgt9tJ06cCAA4ePAgAKC4uBgNDQ1e27Dfi4uLA+5z0aJFaG9vF35qamrCWnOq4VvxJMYks0HZt6kgTTwnGBzHCVPBo21Sdjh51BvdQ0CjEtnxfF+HBDEnMwSTsin6JuVAQ0CB2E89Fyae+5xPSOwQvSXsK8LAgQPx8ccfo7W1FQcPHgTP8xg2bBhycnKisiCn0+mVYhKzbds2ABB8QVVVVXjiiSfQ2NiIwsJCAMC6detgMBiEVJg/tFottFptVNabCgh3c/4MyoJnR+7IjncaiwzKBODy7TSZLGiLstejyWSBw8lDqeBQkNn7c0k4kR1AZFKOgfk6WFNBlsay2p3C548mQiWW1vvvl8QO0Vsivv3NycnBmWee2audL1q0CLNnz8aAAQNgMpmwfPlyrF+/HmvXrsWhQ4ewfPlyXHjhhcjLy8OOHTtw991349xzz0VlZSUAV6l7RUUFrr32Wjz99NOor6/Hgw8+iIULF5KYiSJSIjsG2SI7/tNYOi2JHcLj22mJcq+dWnfZeVGmNioX/HA8O4Co104MIjsez44fg7JIlHVa7VH36nkaCnq/LxM7RhI7RITIGutvbGzEvHnzUFdXh6ysLFRWVmLt2rW44IILUFNTg88//xzPP/88zGYzysrKcPnll+PBBx8UXq9UKrFmzRrccsstqKqqQkZGBubPn49HH31Uxk+VfAQ1KHfJbVD27qDs6bNDaSxC1FgwyhGQurbeTzsXw76vhjQV8txrDkYsR0YI1Vh+DMpalQIKzjXHq9PqiPrfvZDGosgOEWVkvSK89tprAZ8rKyvDhg0bQr4HS6sRsSOoQVnm0nPx2niepz47hBex8uxEY9q5GOaPGVSgl9T5W4jsxCSN5Y7s+DEocxyHDI0KJos9JhVZHd3eoyIYJHaI3pK47U+JhMGTxup5cvOksWRqKuhem5N3naRJ7BBiWK+dtiinsVglVkmUIjvsZmGIBL8O4Om1E5M0VpDIDiAyKfuJ9PYWIY3lcz7Jcg91bSOxQ0QIxfqJkOi1/k9uFrtDuAuUTeyIfAVmq11IY1FTQQIQjYyIskE52pGdy04rRX17N+ZVDZS0fX5GDNNYtsDVWIBoPlYMhnJ2UBqLiBF0RSBCEsizwyongJ6lovFCoeCg0yjRaXXALAqtU1NBAgBy3BGBaHt2PENAoyN2irPS8OjcMZK3Z5GdmFRjCR2U/Ud2YtlY0GyhNBYRGyiNRYQkUDWWSZRfj3YJajiIGwtSGosQE6thoJ7ITnQbFUqFeXbaOm2wOZxRfW8LKz0PEdnpjEEay8Q6oAcQO1a7UyiNJ4hwILFDhEQfILLjGQIqb4BQ3FjQI3YoaEnExrNjczjR6PbKRKN7ciRkp6uFG4xoCzlPU8EAkZ0YTj4PFNkR31BRdIeIBBI7REh0AbqmmmRuKMgQR548pecU2SE8pefR7LPTaLKA5wG1kkN+hjz9vBQKTvhsTVE2KQcbFwHEdvJ5oGosjuOEmyoSO0QkkNghQsJOPFa70ytkbpR5VASDiZ1OrzQWRXYIINvt2em2OdEVpUhEnXvaeXFWGhQypm/zYmRSDjYIFBClsWJReh5gXARAvh2id5DYIUIizp+LU1meNJbMkR1RKSyNiyDEsGGgQPSiO7VRnHbeG9iYilMd0U5jhYjsaGMvdnw9O4BI7ES5so5IDUjsECFRKxXQuCszxCblhExj2WhcBOGB4zjk6KLbRZlFdqJViRUpQmPBmEV2AhmUmWcn+mksdjOV6UfsGCiyQ/QCEjuEJPSiiidGwqSx3CffFrMVPO96jNJYBEMYGRGlyE5dgkR2YpfGCjwIFIhPGitoZIfEDhEBJHYISbAZVB2JmMZynxjFRs30AHelROrBfDvRqlpiZeclMlViMfJjlsaS1lQwpp4dEjtElCGxQ0jCM13cXxpLboOy6+Tb5L7DTVMrZO37QyQW0R4GmiiRHZbGaopRZCfwuIjYpLHsDqeQQiOxQ0QbEjuEJPz12vGksRIrskMpLEKM4NmJkrE12t2TI8Uz+Tx6kR2e54XIjr9BoICnIEBKZGdl9Qm8+vVhSfsWp8iDpbGMJHaICKCrAiEJnTBdXOzZcUd25BY77pOvR+xQCovwEE3PjsXuEDwy0RoCGikFepbGil5khwkdIEhTQYlix+ZwYtEHO2Bz8Lh4XAmKQ4hDk8UlYjQqT0GEGIrsEL2BIjuEJPwNA2V3WLIblN1CjF2ESOwQYrJ10RsZ0dDu+o5pVQph7pZcsDTWKbMVTicflfdkQ0CBYJ4daR2U69q6YXO41lVv7A65bxbZ8VeJBZDYIXoHiR1CEsyzk8il53b3CZ/SWISY3Az3MNAoRHbE0845Tl5fGItYOZx81AQAGwKq4ABVAN+bJ7IT3LNT09op/LtRgtjpcEd2/KWwACBLR2KHiBwSO4Qk/E0+Z54d+Wdjee+fIjuEGE+fnd5fJBPFnAy40j0s2hGt8nMW2UlTKwOKOamRnRMisSPFRG0KMCqCwT5rG4kdIgJI7BCS8DUoO528EOWR36DsLW4oskOIiaZnp5ZFdmQuO2cwk3K0KrJYZCdQCguQPvX8RGuX8O9GY+j1sTRWKLFDkR0iEkjsEJLwdCl2nZBMFrvQwC9RPDsMiuwQYnJEnh2e7523pc5diVWSAJEdQOTbiVJFVqiGgoBI7NgcQY9nTUt4kR2WxvI3FwvwiB2r3SmskyCkQmKHkISvQdnkTmFpVYqgd4HxgMQOEYwcd2THYneiq5cXSebZCVVZFC8KojwyIlRDQcBTmcnz3tVbvoQb2WE3UoE8O3qtSuifRdEdIlxI7BCSEDw7blOisSsxUliAp/ScQWksQkyGRgmN0nWq622vHdZjR+7uyQxPr50opbEkRHbE3cnNQVJZYrEjKbITwrPDcZzgDySxQ4QLiR1CEr4GZRbZkbt7MkCRHSI4HMchh1Vk9bL8nJVQJ4JBGYhFGiv4EFAAUCo4oQdPIJOyxe5Ag8lTgdVskuDZsbIbqMDnFPLtEJFCYoeQhGdchOvkligNBQHvqewATTwnepIThV473TaH8PpE8+xEL43lNigHiewAoSuyatu6IbbzNJksIf1SrBrLt7pSjCB2otQNm0gdSOwQkvAdBJooDQUZ4lSWjoaAEj54RkZELnZY2blOo0yIiCYgrsaKbmQnlA+PpbIC9dph5uTyPB0AwOpwhozGsKhxIIMy4OnpRZEdIlxI7BCS0Pt4djxpLPkjO4B3KksXIOdPpC7RGAZa15Y4DQUZ+VEeGSHFswN4bn66AkR2mF9ncIFeiMY0hkhleSaeBxZalMYiIoXEDiEJX8+OJ42VGMJCHPomzw7hS7a7+25LL9IftQnUUJAhrsbqbVk9IK0aC/BMPjcHFDuuyE5ZTjoKM93T2SWLncA3UCR2iEghsUNIgokdm4OHxe4Q0liJ4NkBvBsLBsv5E6lJNCI7u062AwCGFuqjsqZowNJY3TanpCnkoWCRnUBDQBkZIUZG1LgjO6U5OhS4xU6jKfjICFaN5dskVAyJHSJSSOwQkhB7YswWR8LMxWKI01jpFNkhfBAMyr3w7FQfawUATBiYE5U1RYMMrUrwz0TDpGwR0ljB/4ZCTT4XIju56YLYCRXZCacay0hihwgTEjuEJFRKhXC3Z7bYhblYiWNQpjQWERgW2WmLUOyYLXbsqTMCSCyxA0S3144njRX80pAeohrrhCiyIzmNJUR2qPSciD4kdgjJ6IWREXZPZCdB0ljicnNqKkj4Inh2IhwGur2mDQ4nj5KsNJRkJ45nBxCXn/e+IsuTxgp+w5ARZD5Wt80hCJvSnHRRGkuqZ4fEDhF9SOwQkvH01vBEdhKlBFd8gqTIDuFLbz07QgqrPDdqa4oW0ey1IzQVDFGNlS6aj+ULi+pkalXISlejMNPVbTpYZMfmcApRpaBiR0dih4gMEjuEZMTDQD19dhIjsiMOfZNBmfBF7NmJpGrpByZ2BmRHc1lRIZ+lsUw9hVyn1Y5Xvz6MX76ySTBYB8MiYeo54Pkb81d6zvw6/XPSwXGcpMiOeOwEpbGIWEBXBUIy4mGgiZbGEhuoyaBM+MIiO1b3MNBwUp1OJ4+tx11i54wEjuycMnvERKfVjn9tOo6Xvz4kpLdW/XgSY/pnBX0vKeMiAM/fmL/ZWOJKLACSPDvsfKJVKaBWBr4HJ7FDRAqJHUIyGSLPTsIZlN1rUys5r9ERBAG4UpsapQJWhxMtZmtYYudAYwdM3XboNEqMLM6M4SojI19kUPYnctRKDjYHLymF122X1lRQFzSN5anEAiBEdtq7bOi2OfxGjZhfJ9T5hIkdi90Z8L0A4EizGXf8+0fcOmUIZo/tF/Q9idSArgqEZJigONVhhc3hSgUkTOm5++KVTqMiCD94DwMNLyrww7EWAMD4smyogkQd5CLPHdnZcrQV5z79FZ74eC+aO6wYkKvD0/+vEo/OHQMAOCVB7Fgkjotgf2/+DMonWrwjO1npamHqfCBfEYsQBUthAS4/j1Lh6l4dLLrzr03HsPNkO1ZsqQn6fkTqkBi35USfQO8+wdW1u05mCs47fSQn7CQZ6mRJpC45Og0ajJawe+0wc/IZCVZyzmBpLJYmGpCrw21Th+LS0/pDrVTgi70NAKTNBeuWOAg0PUifHRbZKc1xRXaYb+dkWxeaTBZBBIkxSajEYu9lSFOhtdOG9i4bigxpfrf79tApAKHL3YnUQdbblGXLlqGyshIGgwEGgwFVVVX45JNPAAAtLS24/fbbMWLECKSnp2PAgAG444470N7ubbLjOK7Hz4oVK+T4OEkPExJsIGJmmjphZgSx0nPy6xCBiLTXDhM7pyeo2BnVLxO5GRohkvPFb8/DlWeUCd6XHPfnPiWhNF2qZ0eYjRWkGqtMJGryQ5iUpUZ2gNC+nRazFXvdPZGaojQzjOj7yHobXFpaiqeeegrDhg0Dz/N46623MHfuXPz444/geR61tbV49tlnUVFRgWPHjmHBggWora3FypUrvd7njTfewKxZs4Tfs7Oz4/xJUgNmUGaRnUQpOweA08tyMLI4E3MoP08EQKjICqP8vMlkwbFTneC4xBU72ToNNv9+GlQKzu/NR16G9InvFqmRHbX3rDyG2WIX0mWluZ5+RKFMyqyhYGY4YifAnLON7qgO4BqQ6nDyQuqLSF1kvVpdfPHFXr8/8cQTWLZsGTZt2oQbb7wR77//vvDckCFD8MQTT+Caa66B3W6HSuVZenZ2NoqLi+O27lSFTROvd0d2EqUSC3D13/j0rnPlXgaRwHg8O9LFDovqjCjKTKjvuy/BKphYZKfT6ghq6gXC8OwEmHp+0j0ZPitd7XW8QpWfd4QR2TGEiOx8e6hZ+LeTd4lbtn8idUkYt53D4cCKFStgNptRVVXld5v29nYYDAYvoQMACxcuRH5+Ps466yy8/vrrUZn+S/SEnYhYlUeiVGIRhBRyI5iPVe02JydqVEcKmVoV1EpXZCNUVIt1UNaGGBfBqrF8p577+nUYISM7zLMj4ZwSKo313cFmr99DDSAlUgPZr1Y7d+5EVVUVuru7odfrsWrVKlRUVPTYrrm5GY899hhuvvlmr8cfffRRTJ06FTqdDp999hluvfVWdHR04I477gi4T4vFAovF80dnNBqj94GSGL3PNOJEvtMlCF9yhHSO9GqsHxLcnCwFjuOQo9Og0WRBi9kadNyFMBsrxCDQ9ABNBWuESizvfXiGgfoXHiwdFlYay4/YOdnWhaOnOqHggJLsdJxo7SKTMgEgAcTOiBEjsG3bNrS3t2PlypWYP38+NmzY4CV4jEYj5syZg4qKCjzyyCNer3/ooYeEf5922mkwm8145plngoqdJUuWYPHixVH/LMmOb2fiRCk7JwgpMM+O1DRWt80hdB0+Y2DiNRMMh9wMj9gJRrizsawOJ2wOp5BGE3rs+FRchRoZEU4aK5jYYVGdytJsGNLVJHYIAdnTWBqNBkOHDsWECROwZMkSjBs3Di+88ILwvMlkwqxZs5CZmYlVq1ZBrQ5+gZ04cSJOnDjhFbnxZdGiRWhvbxd+amqoF4MUfMtCKY1F9CVYZEeqQXnnyXbYHDzy9VqhQV5fJVeCSdnucMLudFkApM7GArzLz0NHdgKJHdd7hCo9Bzxix+hP7LjNyZOH5qFAL20AKZEaJNzVyul0CkLFaDRi5syZ0Gq1+Oijj5CW5r+ngpht27YhJycHWm1gQ5pWqw36POEf37suSmMRfQnm2ZFSlQQAPxz1pLASpcVCpEgReiyFBYSO7GiUCqgUHOxOHl1WhyBATrQxz453ZEcQOx0W8Dzf43h2uDuyhyN2fCM7PM/jO7c5+ewh+fjfAde/KbJDADKLnUWLFmH27NkYMGAATCYTli9fjvXr12Pt2rUwGo2YMWMGOjs78fbbb8NoNAremoKCAiiVSqxevRoNDQ2YNGkS0tLSsG7dOjz55JO499575fxYSYuv2KHIDtGXyHZPzG7ttPm94PoiNBMs77t+HUaeBLHTLeqZEyqyw3Ec0jVKmLrtMFs95edCj51cb7HDRlrYHDzaOm2C+GKYWWSnFwblQ01mNBgt0KgUmDAwB/vqTQCo1w7hQtarVWNjI+bNm4e6ujpkZWWhsrISa9euxQUXXID169dj8+bNAIChQ4d6ve7IkSMoLy+HWq3G0qVLcffdd4PneQwdOhTPPfccbrrpJjk+TtLje9dFnh2iLyEeBtppdQT1h/C8Z/hnX67EYkjpMdTtjuxolAooJPSl0bnFDjMpm7ptaHObv/v7pLG0KiWydWq0ddrQaLL0EDumKHh2WFTnjIE5SFMrJQ0gJVIHWcXOa6+9FvC5KVOmhCwhnzVrllczQSK2ZFA1FtGH0WmU0KgUsNpdw0CDXVgPN5vRYrZCo1JgTEnwSeF9gVwpaSyJZecMV8GCRaikYlGdHJ3abzqqMFOLtk4bmkwWjPAZqGqWOC4CcPXUAvyInYMuv87ZQ/IAhPYJEamF7AZlou/gOynaQGksog/BcZxk3w5LYY0rzYImREqnLyBF7HRLbCjISPeZfB4ohcXwNBbsWX7eEY7Y8RPZcTh5bDzsFjtD8732R2KHAEjsEGGgVHBeU8UpjUX0NcS+nWBUu83JE/p4yTlDSjUWGwIayq/DyPDptVPT4r+hICNY+XkkTQUtdqfgM9pTa0R7lw16rQqV/bPc+9MK791p7TmdnUgtSOwQYSEO/VMai+hrsIv+kaaOoNv94O6c3JebCYqRlsaKLLLjm8by7bHDCBRpsdqdsLr9QnpNaLGj16qEWVes/Jz5dSYOyoXK3fNHr1UhzZ2So+gOQWKHCAtxF2WqxiL6GhMHufwcz6zdj/3uah1fWs1WHGoyA0gOczIgjuzY4HT690KyyE6aRM8OGxnBJp/XBBgVwQjU90Y8TNTXF+gPjuOEFHqbW+x8e8g7hcW2o1QWwSCxQ4SFOLJDYofoa9x6/hBUDc6D2erAr/+xxW+kg1VhDS7IEERCX4dVYzmcPIzd/lN4gkE5xKgIBvPwsbJxFtnx7bHDKDT4Fx4shZWmVghRmVCIfTtWuxNbjrgicZOH5nltxwQWiR2CxA4RFkzsZGiUkk9MBJEoqJUK/PXq01GWm46ali7c+q9q2BxOr22SYR6WLxqVQpg7FSiVJczFCjeyY2VpLPeoiADdpj2RHW+DsqmbmZOlp8UFsdNpw4/HW9FlcyAvQ4Phhd5VXoJPiHrtpDx0tSLCglVLZJJfh+ij5GRo8Nr8M5GhUWLT4RY8unqP1/OsEmtCEokdQDwI1b/YEeZiSY3suFNOnVYH2jttgmjpnx1eZIc1JfQdNBwMgyiyw0ZEVA3J69EfSKgAM5LYSXVI7BBhwSI7hnRKYRF9l+FFmXjhF6eB44B/bjqGtzcdA+Ayy26vaQOQPJVYDJaSO9URSOy4IjtS++zo1O40ltUh+HXy9RqvuVliCvSuKIux2+7VrbmjW3olFiPLS+y4zMmTRX4dYZ/k2SHckNghwoJNO6bIDtHXmV5RhHtnjAAAPPLRbmw8dAq7a9thsTuRrVNjSEGGzCuMLqHKz8ON7DAzcZfVHtKvA7hukFjPIrH4ECaeS6jEYjCxU2/sxo/H2wB4mgmKEc/kIlIbEjtEWAiRHTInE0nArVOG4OfjSmB38rj1X9X4cFstAGDCgL4//NMXIbITwrOjDbf03OoQ/DqBKrEAd3WUvqf4YGInnIIHJnY+39MAu5NH/+x0DPDTzJBGRhAMEjtEWHjSWBTZIfo+HMfh6f9XibH9s9DaacOb3x0FAExIguGfvgiRnQBip9sWXlNBj0HZEbJ7MoP5dsQeGnMYc7EYTOwcbna1CJg8NM+vOA3WtZlILUjsEGFxxsAcaJQKoV8JQfR10tRKvDrvDOHCCLgiO8mGZxio/9LzcMdFsNLzTqs9ZPdkhr/IjqcaK3yxwzh7SE+/DuARO80d1oD9hYjUgMQOERbnDi/ArsUz8auJA+ReCkFEjeKsNLxy7QRoVApk69QYV5Yt95KiTp7QRdl/SscSYVPBTlFkJ5hnBxB5aIyeSEs4Q0AZPcWO/5uvfLe4cjj5kPPQiOSGjBdE2CTDYESC8OW0ATlYd/e54MBJjm70JVjpeUuAuWBCNVa4TQWtdrS4K7zKQkR2/PW9CWcIKEMsdoYV6lFoSPO7nVqpQG6GBi1mKxpNFuTptX63I5IfumoRBEG4GZiXgQF5waMTfZXcEJGdSMdFNLRbYHYPAy3JDpHG8tP3JpwhoIwsnUfsBIrqCPukLsoESOwQBEGkBB6DcqBxEeF6dlzbWd0dqAsztSFfW+inFLyjFwZlwHselj+o1w4BkNghCIJICXLdBuUOi13w54hhj0mvxvIWJ6EqsQD/woN5djLDEDt5GVpolApolApMClEs4U9gEakHeXYIgiBSAEO6CkoF5zLrmm0ozvKOwghNBcOM7DBCVWIB3iMjnE4eCgUnVGOFE9lJ1yjx6vwzoFJwXiktf9DICAKgyA5BEERKwHGcqPy8Z2VSuINA09Xhi528DJfwsDt5tHW50mnCbKwwG5WeN7zA74gIX6iLMgGQ2CEIgkgZPOXnPcWOp6mgtMiOQsF5CZ6yEGXngKuSM8cdiWGN/joi6LMTDp7UGTUWTGVI7BAEQaQIORkuodHip+eMp6mg9MuCOJUVqscOQyg/d/t2zBaXyIq92KHITipDYocgCCJFCDYywmNQlt5jSKcVRXZyQ6exAG8PjcXuEKq5wvHshEOhMDKCxE4qQ2KHIAgiRQg2DDTccREAoFO7BArHAf2ypIkdcXUUi+oAMYzs6F2RJFO3XUjVEakHiR2CIIgUgZWf+4vshDsIFPBEdooNaZI7q4vTSsyvk65WQqmIzZR5Q7pKWBulslIXEjsEQRApQm4AgzLP86JqrDAiO27PjhRzMqNAlFYyWVwVWeFWYoUDx3FCF2VKZaUuJHYIgiBShJwAYocJHSA8g3K6O40lpeycIa6OirU5uec+SeykKiR2CIIgUgTBoOxTjcVGRQDhGZQz3GmscMQOq8ZqNFnQwSI78RI71GsnZaEOygRBEClCIIMyq8RScIBaKd07c9nppahp6cTF40okv8bLs+OO7GRoYztlvpAiOykPiR2CIIgUQVx6zvM8OM4lbMSVWOwxKZw3vADnDS8Iaw1M7Ji67Wh2iw+9NvjIh95CjQUJSmMRBEGkCGxchN3Jw+iuhAKA7jCHgPYGQ5pK2M/RU2YAgD7GkR3y7BAkdgiCIFKENLUSGe4KKnH5uSWCHjuRwnGcID6ONLvFTgyrsYCeXZuJ1IPEDkEQRAohVGSJTMosshMPsQN4PDSHm1xiJ1bdkxkU2SFI7BAEQaQQwjDQDpHYiaChYG9g4qO2vQsAkBnHaiye52O6LyIxIbFDEASRQviL7LA0ljZukR1XWonpjlhHdvL1rs9sc/Bo67TFdF9EYkJihyAIIoXw10VZSGPFObLDiHWfHa1KiWydq+KLeu2kJiR2CIIgUgh/87G64xzZ8RU7mTE2KAPwjIwwkthJRWQVO8uWLUNlZSUMBgMMBgOqqqrwySefCM93d3dj4cKFyMvLg16vx+WXX46Ghgav9zh+/DjmzJkDnU6HwsJC3HfffbDb7b67IgiCIOB/ZIQlzpGdQh+xE+s0FiD27VCvnVREVrFTWlqKp556CtXV1fjhhx8wdepUzJ07F7t37wYA3H333Vi9ejXee+89bNiwAbW1tbjsssuE1zscDsyZMwdWqxXfffcd3nrrLbz55pv44x//KNdHIgiCSGjy/KWx4lh6DsQ/jQVQF+VUR9YOyhdffLHX70888QSWLVuGTZs2obS0FK+99hqWL1+OqVOnAgDeeOMNjBo1Cps2bcKkSZPw2WefYc+ePfj8889RVFSE8ePH47HHHsMDDzyARx55BBqNRo6PRRAEkbD4LT2PczUWMygz4iF2qPw8tUkYz47D4cCKFStgNptRVVWF6upq2Gw2TJ8+Xdhm5MiRGDBgADZu3AgA2LhxI8aOHYuioiJhm5kzZ8JoNArRIX9YLBYYjUavH4IgiFTAX2SHTT2PV2QnT6+BeCpFrJsKAh6x00hiJyWRXezs3LkTer0eWq0WCxYswKpVq1BRUYH6+npoNBpkZ2d7bV9UVIT6+noAQH19vZfQYc+z5wKxZMkSZGVlCT9lZWXR/VAEQRAJil/Pjo01FYzPJUGtVAhGaSDOnh0SOymJ7GJnxIgR2LZtGzZv3oxbbrkF8+fPx549e2K6z0WLFqG9vV34qampien+CIIgEgUmMkzddtgcroiOJ40Vn8gO4O3bydDEw7NDIyNSGdmnnms0GgwdOhQAMGHCBGzZsgUvvPACrrrqKlitVrS1tXlFdxoaGlBcXAwAKC4uxvfff+/1fqxai23jD61WC61WG/B5giCIZCUrXQ0FBzh5V/l5oSFNlMaK3/1vQaYW++pN0GmUUCqkT1rvzf4A6rOTqsge2fHF6XTCYrFgwoQJUKvV+OKLL4Tn9u/fj+PHj6OqqgoAUFVVhZ07d6KxsVHYZt26dTAYDKioqIj72gmCIBIdhYITpp8zk3K3Lb6zsQCP+IiHORnw9Nlp67QJpfZE6iBrZGfRokWYPXs2BgwYAJPJhOXLl2P9+vVYu3YtsrKycOONN+Kee+5Bbm4uDAYDbr/9dlRVVWHSpEkAgBkzZqCiogLXXnstnn76adTX1+PBBx/EwoULKXJDEAQRgNwMDU6ZrcJ8LKGpYJyqsYD4i51snRpqJQebg0dzhxX9s9Pjsl8iMZBV7DQ2NmLevHmoq6tDVlYWKisrsXbtWlxwwQUAgP/7v/+DQqHA5ZdfDovFgpkzZ+Kvf/2r8HqlUok1a9bglltuQVVVFTIyMjB//nw8+uijcn0kgiCIhMe3/JxFOuLVQRnweGjiUYkFABzHoUCvRW17N5pMFhI7KYasYue1114L+nxaWhqWLl2KpUuXBtxm4MCB+Pjjj6O9NIIgiKTFd2REvJsKAsDAXB2Anj13YklBpkvsNBqpi3KqIbtBmSAIgogvue4p4KeY2LHHt6kgAJw/shDPXjEOEwflxm2fZFJOXUjsEARBpBi+kR2LDJEdpYLD/5tQGrf9AUABlZ+nLAlXjUUQBEHEltwM/5GdeA0ClQtqLJi6JPc3myAIgugBEzutnd6RnXgalOWARkakLiR2CIIgUgzPyAgbAE81VjybCsoB67UjV2Snrr0L5z+7Hr97f4cs+09lkvubTRAEQfTAMwzUddEXqrHiOC5CDgoN8oqdR1fvwZFmM97fegJWd9dqIj6Q2CEIgkgxWGSn1WwDz/Oe2VipEtnpsIDn+bju+6v9jfhkl2tAtc3B40CjKa77T3WS+5tNEARB9IBVY1kdThi77LA7XRf+ZI/sMM+O1e763PGi2+bAwx/u9npsT60xbvsnSOwQBEGkHOkaJdLdZuTa9i7h8XiWnstBmloJg7tjc1NH/BoLLlt/CMdbOlFsSMMvziwDAOwmsRNXSOwQBEGkIKwiq04kduLZVFAu4l2RdaTZjGUbDgEAHrqoAmeWu5ooUmQnviT/N5sgCILoARM7tW2uCIdGqYBCwcm5pLgQz147PM/j4Y92w2p34pxh+bhwbDEqSgwAgD11Rjid8fUNpTIkdgiCIFKQHJ/ITrKbkxnx7KL8ya56fP1TEzRKBR6dOwYcx2FooR4alQIdFjtqWjtjvgbCRWp8uwmCIAgvWPl5nTuyo01yczKjME6RnQ6LHY+u3gMAWDBlCAblZwAA1EoFRhRlAiDfTjwhsUMQBJGC5LgrsphBOdkbCjLilcZ64fOfUG/sxoBcHW6dMsTrudHuVNbu2vaYroHwkBrfboIgCMKL3Aw1AKCu3RXZSfZKLAbrtRNLg/L+ehNe//YoAGDx3NE9jq3g26HITtwgsUMQBJGC5Ga4LvpM7KRCJRYQ+8gOz/N48D874XDymDW6GOePKOyxjSeyQ2InXqTGt5sgCILwgkV22NiCVInsCCMjOmIjdt7fehJbjrZCp1HijxdX+N1mZLEBHOeKLiXDBPaXNxzCzP/7GsdOmeVeSkBI7BAEQaQgLLLDSBnPjjuN1WK29phPxfM8dp1sx8sbDuF/B5rCfm+e5/HiFwcAAHdMG4aS7HS/22VoVYJhua/7dv7+v8NY8sk+7G8wYfX2WrmXExCV3AsgCIIg4g+L7DBSpRorR6eBSsHB7uRxymxBZpoa3xxowpf7GrF+f5Pg5UlTK7D1oQug00i/TB5qMuN4Syc0SgXmVQ0Mum1FPwMON5mxp86IKX5SXX2Bd7fU4PH/7hV+334icYUbiR2CIIgUhFVjMVIlsqNQcMjXa1Fv7MZN//gB++tNsDk8zf10GiU4AGarA98caMaM0cWS33v9/kYAwMTBuSFF0uiSLKzZUddnfTuf7qrD7z7YAQA4Z1g+/negGdtr2uRdVBBS49tNEARBeJGt04ATNUxO9iGgYorcvp1dJ42wOXgMys/ADZMH4Z83noUf/3gBrjjDNb/qy32NYb3v+v2u1Jc/U7Ivo/twRdY3B5pxx7+3wckDV55RipevnQClgkOjyYL69vjNHAsHiuwQBEGkIEoFh+x0NVo7bQBSp4MyANx1wXCsrD6B0wfkYOrIQsE/w5g2qhBvfncUX+xrhNPJSxqjYbbYsfnIKQDA+SNDix1Wfn6k2YwOix16bd+4HG893oqb//kDrA4nZo8pxpLLKqFUcBhWqMe+ehO2n2hDcZb0aFi8SJ1vN0EQBOEFm48FpI5nB3BFXpb+6nTc+LNBPYQOAJw1KBcZGiWaTBbskmgg/vZgM2wOHgPzdH7f05d8vVaIMO2rkxbdWb75OB5fswcOmWZq7as34vo3tqDT6sA5w/Lx/C/GQ+kWguNKswEAO060ybK2UJDYIQiCSFHEYidVSs+loFUpce7wAgDA53ulpbK+CiOFxRhdkgVAWr+dVrMVf/xwF/7+zRF8e7BZ8j6ixbFTZlz72vdo77Lh9AHZePnaCV4CubLM9Vl2JKhJmcQOQRBEiiI2KadKU0GpTHWnor7c1xByW57nBXPylBEFkvcRztiIj3fVwe6O6Hy1PzwvUW851WHBNa9tRpPJgpHFmXjjurN6GLBZZGd7TRt4PvGmudO3myAIIkXJ01NkJxDnjywEx7lMzKFMt/sbTKhr70aaWoFJg/Mk70MwKUtIY320zdPD5qswjdO95alP9qGmpQsDcnX4xw1nIUun7rHNiOJMaFQKGLvtOHoq8aa5k9ghCIJIUcSRnVQpPZdKvl6L8WXZAEJXZX21z5XCOntIfliisaKfK/XzU30HbA5nwO3q2rvw/dEWAIBKweHoqU4caY5Pt+JtNW14r/oEAOD5X4xHoSHN73ZqpUIQb4no26FvN0EQRIqSqgZlqUwfVQQA+GJv8FQWSyudH0YKCwDKctORmaaC1eHEgYaOgNut2V4HngfOKs/FWYNyAYRfFh8JTiePRz7aDQC47PT+OH1ATtDtPamsxPPtkNghCIJIUbwNynQ58IX5dr452Iwuq8PvNu1dNlQfawWAsDshcxyHin6hfTsfbj8JAPj5+BJhTevj4Nv54MeT2FbThgyNEr+bNTLk9pWlzKTcFuOVhQ99uwmCIFKUHKrGCsrI4kz0z06Hxe7Ed4f8V0B9c6AZDiePoYV6lOXqwt4Hq8gK5Ns51NSBXSeNUCk4XDi2nyCoNh9ugdliD3t/UjF12/CnT/cBAG6fNixg+kpMpTuys6u2HfYgaTk5ILFDEASRouRlUDVWMDiOEyIpXwRIGwlVWMPDS2ExKoSKLP9ihxmTzxmWj9wMDYYUZGBArg5WhzOmJeh/+fIgmkwWDMrPwPWTyyW9ZnB+BjK1KnTbnPgpSFpODujbTRAEkaJ4G5QpsuOPaaPcJeh7G3uUVDudPNb/5O6vI6Frsj+YqXdvrRFOn2aBPM8Lk8R/Pr4EgEuAMW9QrErQDzd14PVvjwAA/nhRhWQ/l0LBYWyCprJI7BAEQaQo3qXndDnwx6TBedBplKg3dveIvuypM6LJZEGGRokzyoObdwMxtFAPjUoBk8WOmlbvku1dJ4043GxGmlqBCyo8IxiYsPpqX1NMeto8tmYPbA4e548oCFvEsVRWok1Ap283QRBEipKuVgrpK6rG8k+aWomfDc0HAHzh002Z9buZPDQ/4uOnViowoigTQM+hoB+5jcnTRhV5zc6aNDgPaWoF6o3d2Ftnimi/gfhyXwO+2t8EtZLDQxdVhP36cRTZIQiCIBIJjuNw+oAcZGpVEZlrUwUhleXTTVkoOY8whcXwVGR5xI7DyeMjlsIaV+K1fZpaiclD8r3WEA0sdgceW7MXAHDDzwZhcIE+7PeodPcm2l9vQrfNfwWbHJDYIQiCSGH+eeNZ+G7RVGSl9+yKS7hgYmb7iXY0Gl3dlFvMVvxY0wYgvBER/hjdv2f5+fdHWtBgtCAzTeX3/acIqazoiZ03vj2KI81mFGRqcfvUYRG9R0lWGvL1GtidvKTO0PFCVrGzZMkSnHnmmcjMzERhYSEuueQS7N+/X3j+6NGj4DjO7897770nbOfv+RUrVsjxkQiCIPoUKqUCmWkkdIJRmJkmpGdYJOV/B5rA867y9H5Z6b16/9F+KrJYVGf2mGK/KTJmUt56vBVtndZe7R8AGo3deOmLAwCA380a6ZU2CweO4zy+HbcYTARkFTsbNmzAwoULsWnTJqxbtw42mw0zZsyA2exqg11WVoa6ujqvn8WLF0Ov12P27Nle7/XGG294bXfJJZfI8IkIgiCIZGSau5sym4LOIirhNhL0x8hiAzgOaDRZ0GSywGp34uOddQCAueP7+31NaY4Ow4v0cPLABndFWG946pN9MFsdOG1ANi49zf8+pcI6KSfSBPTIpFuU+PTTT71+f/PNN1FYWIjq6mqce+65UCqVKC4u9tpm1apVuPLKK6HXe+cSs7Oze2xLEARBENFg6shCPLfuJ3xzoBmdVrsgMMIdEeGPDK0Kg/IycLjZjD11RtgdTrR32VCQqQ06WPT8kYX4qaED6/c3BRRFUni/+gQ++NFlhn7k4tFQKLiI3wsAKstcUbDtCWRSTijPTnu7SwXm5ub6fb66uhrbtm3DjTfe2OO5hQsXIj8/H2eddRZef/31oOV4FosFRqPR64cgCIIgAjG6xIBiQxq6bA78bcNhtHbakJmmwukDIys598XTXLAdH7obCV5U2Q/KIMLj/BGe0REOZ2Ql6DtOtGHRqp0AgDumDcM4t8G4N7DIzuEmM4zdtl6/XzRIGLHjdDpx1113YfLkyRgzZozfbV577TWMGjUKZ599ttfjjz76KN59912sW7cOl19+OW699Va89NJLAfe1ZMkSZGVlCT9lZWVR/SwEQRBEcsFxHKa6q7Je3nAIAHDusAKoldG5jLKxEdVHW7Fuj6vqy7cKy5cJA3OQmaZCa6ctoihKc4cFv/lnNax2J6aPKsRd0yIzJfuSm6FBaY7Lx7QrQVJZCSN2Fi5ciF27dgU0Fnd1dWH58uV+ozoPPfQQJk+ejNNOOw0PPPAA7r//fjzzzDMB97Vo0SK0t7cLPzU1NVH7HARBEERyMt0tdix219yn3lZhiWEm5S/2NaLL5sCAXB3Gh4iyqJUKnOseUxFuVZbN4cSt/9qKuvZuDC7IwHNXje91+krMuARrLpgQYue2227DmjVr8NVXX6G0tNTvNitXrkRnZyfmzZsX8v0mTpyIEydOwGKx+H1eq9XCYDB4/RAEQRBEMM4eku/Vafq8KIodlsZi/HxcCTgutPhgqaxw++08vmYPvj/SAr1WhVeuPQOGKFfksQnoiVKRJavY4Xket912G1atWoUvv/wSgwYNCrjta6+9hp///OcoKAj95dq2bRtycnKg1WqjuVyCIAgihRF3Ux7bPwuFmaEngUslX69FkcFzzZo7PngKi8GiS7tOGoUeQKF474cavLXxGADg/64aj6GF4TcPDAXz/iRKJ2VZq7EWLlyI5cuX48MPP0RmZibq6+sBAFlZWUhP9/QtOHjwIL7++mt8/PHHPd5j9erVaGhowKRJk5CWloZ169bhySefxL333hu3z0EQBEGkBtdMGogv9zXimkkDov7eo0uy0GBsxMjiTAxzj5AIRb5ei3GlWdh+oh3r9zfhyjODe1C317ThD//ZBQC4a/owXFBR1Ot1+2NM/yxwHFDb3o0mkwUFmfIGH2SN7Cxbtgzt7e2YMmUK+vXrJ/y88847Xtu9/vrrKC0txYwZM3q8h1qtxtKlS1FVVYXx48fj5ZdfxnPPPYeHH344Xh+DIAiCSBGmjCjE4SVzcNWZ0Rc70929fK47uzys17EOz1+G8O00mTyG5AsqinBHhF2SpaDXqjDUPW4iEaI7HB+Lkal9DKPRiKysLLS3t5N/hyAIgpAFnufR3GENOwqyvaYNc5d+C71Wha0PXQCNqmccw2p34uq/b8KWo60YUpCB/yycHPPO2b99dzve33oCd0wbhnsuGB6TfUi9fsuaxiIIgiAIwgXHcRGle8b2z0K+XoPmDit+ONqCs4fmo9HUjW3H27D9RBu217Rj+4k2mLrtyNSq8Mq8M+IyImRcWRbe33oiISI7JHYIgiAIog+jUHA4b3gh3t96Ag/+Zxe6bQ7Utvc0KxvSVHjhl6dhSATTzCNBPCOL53lJ1WWxgsQOQRAEQfRxpo1yiZ3Dza7ZkhwHDC/MxPiybIwry8a4siyMKMqEKkpNEKUwql8m1EoOrZ02nGjtQlmuLm779oXEDkEQBEH0cWaOLsbvZo8EAIwvy8aY/lkRTy6PFlqVEqP6GbDjhCuNRmKHIAiCIIiIUSo4LDhviNzL6EFlaRZ2nGjHjhPtuKhSWu+gWJAQHZQJgiAIgkg+xL4dOSGxQxAEQRBETGAzsnadbI94Mns0ILFDEARBEERMGFqoh06jRLZOg0aTtHEWsYA8OwRBEARBxASlgsPGRdOQlR77vj7BoMgOQRAEQRAxQ26hA5DYIQiCIAgiySGxQxAEQRBEUkNihyAIgiCIpIbEDkEQBEEQSQ2JHYIgCIIgkhoSOwRBEARBJDUkdgiCIAiCSGpI7BAEQRAEkdSQ2CEIgiAIIqkhsUMQBEEQRFJDYocgCIIgiKSGxA5BEARBEEkNiR2CIAiCIJIaldwLSAR4ngcAGI1GmVdCEARBEIRU2HWbXccDQWIHgMlkAgCUlZXJvBKCIAiCIMLFZDIhKysr4PMcH0oOpQBOpxO1tbXIzMwEx3FRe1+j0YiysjLU1NTAYDBE7X2TFTpe4UPHLDzoeIUPHbPwoOMVPr05ZjzPw2QyoaSkBApFYGcORXYAKBQKlJaWxuz9DQYDfenDgI5X+NAxCw86XuFDxyw86HiFT6THLFhEh0EGZYIgCIIgkhoSOwRBEARBJDUkdmKIVqvFww8/DK1WK/dS+gR0vMKHjll40PEKHzpm4UHHK3zicczIoEwQBEEQRFJDkR2CIAiCIJIaEjsEQRAEQSQ1JHYIgiAIgkhqSOwQBEEQBJHUkNiJIUuXLkV5eTnS0tIwceJEfP/993IvKSH4+uuvcfHFF6OkpAQcx+E///mP1/M8z+OPf/wj+vXrh/T0dEyfPh0HDhyQZ7EJwJIlS3DmmWciMzMThYWFuOSSS7B//36vbbq7u7Fw4ULk5eVBr9fj8ssvR0NDg0wrlp9ly5ahsrJSaFJWVVWFTz75RHiejldwnnrqKXAch7vuukt4jI6ZN4888gg4jvP6GTlypPA8Ha+enDx5Etdccw3y8vKQnp6OsWPH4ocffhCej+W5n8ROjHjnnXdwzz334OGHH8bWrVsxbtw4zJw5E42NjXIvTXbMZjPGjRuHpUuX+n3+6aefxosvvoi//e1v2Lx5MzIyMjBz5kx0d3fHeaWJwYYNG7Bw4UJs2rQJ69atg81mw4wZM2A2m4Vt7r77bqxevRrvvfceNmzYgNraWlx22WUyrlpeSktL8dRTT6G6uho//PADpk6dirlz52L37t0A6HgFY8uWLXj55ZdRWVnp9Tgds56MHj0adXV1ws8333wjPEfHy5vW1lZMnjwZarUan3zyCfbs2YM///nPyMnJEbaJ6bmfJ2LCWWedxS9cuFD43eFw8CUlJfySJUtkXFXiAYBftWqV8LvT6eSLi4v5Z555Rnisra2N12q1/L///W8ZVph4NDY28gD4DRs28DzvOj5qtZp/7733hG327t3LA+A3btwo1zITjpycHP7vf/87Ha8gmEwmftiwYfy6dev48847j7/zzjt5nqfvmD8efvhhfty4cX6fo+PVkwceeID/2c9+FvD5WJ/7KbITA6xWK6qrqzF9+nThMYVCgenTp2Pjxo0yrizxOXLkCOrr672OXVZWFiZOnEjHzk17ezsAIDc3FwBQXV0Nm83mdcxGjhyJAQMG0DED4HA4sGLFCpjNZlRVVdHxCsLChQsxZ84cr2MD0HcsEAcOHEBJSQkGDx6Mq6++GsePHwdAx8sfH330Ec444wxcccUVKCwsxGmnnYZXX31VeD7W534SOzGgubkZDocDRUVFXo8XFRWhvr5eplX1DdjxoWPnH6fTibvuuguTJ0/GmDFjALiOmUajQXZ2tte2qX7Mdu7cCb1eD61WiwULFmDVqlWoqKig4xWAFStWYOvWrViyZEmP5+iY9WTixIl488038emnn2LZsmU4cuQIzjnnHJhMJjpefjh8+DCWLVuGYcOGYe3atbjllltwxx134K233gIQ+3M/TT0niD7EwoULsWvXLi9vAOGfESNGYNu2bWhvb8fKlSsxf/58bNiwQe5lJSQ1NTW48847sW7dOqSlpcm9nD7B7NmzhX9XVlZi4sSJGDhwIN59912kp6fLuLLExOl04owzzsCTTz4JADjttNOwa9cu/O1vf8P8+fNjvn+K7MSA/Px8KJXKHs77hoYGFBcXy7SqvgE7PnTsenLbbbdhzZo1+Oqrr1BaWio8XlxcDKvVira2Nq/tU/2YaTQaDB06FBMmTMCSJUswbtw4vPDCC3S8/FBdXY3GxkacfvrpUKlUUKlU2LBhA1588UWoVCoUFRXRMQtBdnY2hg8fjoMHD9J3zA/9+vVDRUWF12OjRo0SUn+xPveT2IkBGo0GEyZMwBdffCE85nQ68cUXX6CqqkrGlSU+gwYNQnFxsdexMxqN2Lx5c8oeO57ncdttt2HVqlX48ssvMWjQIK/nJ0yYALVa7XXM9u/fj+PHj6fsMfOH0+mExWKh4+WHadOmYefOndi2bZvwc8YZZ+Dqq68W/k3HLDgdHR04dOgQ+vXrR98xP0yePLlHy4yffvoJAwcOBBCHc3+vLc6EX1asWMFrtVr+zTff5Pfs2cPffPPNfHZ2Nl9fXy/30mTHZDLxP/74I//jjz/yAPjnnnuO//HHH/ljx47xPM/zTz31FJ+dnc1/+OGH/I4dO/i5c+fygwYN4ru6umReuTzccsstfFZWFr9+/Xq+rq5O+Ons7BS2WbBgAT9gwAD+yy+/5H/44Qe+qqqKr6qqknHV8vK73/2O37BhA3/kyBF+x44d/O9+9zue4zj+s88+43mejpcUxNVYPE/HzJff/va3/Pr16/kjR47w3377LT99+nQ+Pz+fb2xs5Hmejpcv33//Pa9SqfgnnniCP3DgAP+vf/2L1+l0/Ntvvy1sE8tzP4mdGPLSSy/xAwYM4DUaDX/WWWfxmzZtkntJCcFXX33FA+jxM3/+fJ7nXSWIDz30EF9UVMRrtVp+2rRp/P79++VdtIz4O1YA+DfeeEPYpquri7/11lv5nJwcXqfT8ZdeeilfV1cn36Jl5oYbbuAHDhzIazQavqCggJ82bZogdHiejpcUfMUOHTNvrrrqKr5fv368RqPh+/fvz1911VX8wYMHhefpePVk9erV/JgxY3itVsuPHDmSf+WVV7yej+W5n+N5nu99fIggCIIgCCIxIc8OQRAEQRBJDYkdgiAIgiCSGhI7BEEQBEEkNSR2CIIgCIJIakjsEARBEASR1JDYIQiCIAgiqSGxQxAEQRBEUkNihyCIlKS8vBzPP/+83MsgCCIOkNghCCLmXHfddbjkkksAAFOmTMFdd90Vt32/+eabyM7O7vH4li1bcPPNN8dtHQRByIdK7gUQBEFEgtVqhUajifj1BQUFUVwNQRCJDEV2CIKIG9dddx02bNiAF154ARzHgeM4HD16FACwa9cuzJ49G3q9HkVFRbj22mvR3NwsvHbKlCm47bbbcNdddyE/Px8zZ84EADz33HMYO3YsMjIyUFZWhltvvRUdHR0AgPXr1+P6669He3u7sL9HHnkEQM801vHjxzF37lzo9XoYDAZceeWVaGhoEJ5/5JFHMH78ePzzn/9EeXk5srKy8Itf/AImk0nYZuXKlRg7dizS09ORl5eH6dOnw2w2x+hoEgQhFRI7BEHEjRdeeAFVVVW46aabUFdXh7q6OpSVlaGtrQ1Tp07Faaedhh9++AGffvopGhoacOWVV3q9/q233oJGo8G3336Lv/3tbwAAhUKBF198Ebt378Zbb72FL7/8Evfffz8A4Oyzz8bzzz8Pg8Eg7O/ee+/tsS6n04m5c+eipaUFGzZswLp163D48GFcddVVXtsdOnQI//nPf7BmzRqsWbMGGzZswFNPPQUAqKurwy9/+UvccMMN2Lt3L9avX4/LLrsMNH6QIOSH0lgEQcSNrKwsaDQa6HQ6FBcXC4//5S9/wWmnnYYnn3xSeOz1119HWVkZfvrpJwwfPhwAMGzYMDz99NNe7yn2/5SXl+Pxxx/HggUL8Ne//hUajQZZWVngOM5rf7588cUX2LlzJ44cOYKysjIAwD/+8Q+MHj0aW7ZswZlnngnAJYrefPNNZGZmAgCuvfZafPHFF3jiiSdQV1cHu92Oyy67DAMHDgQAjB07thdHiyCIaEGRHYIgZGf79u346quvoNfrhZ+RI0cCcEVTGBMmTOjx2s8//xzTpk1D//79kZmZiWuvvRanTp1CZ2en5P3v3bsXZWVlgtABgIqKCmRnZ2Pv3r3CY+Xl5YLQAYB+/fqhsbERADBu3DhMmzYNY8eOxRVXXIFXX30Vra2t0g8CQRAxg8QOQRCy09HRgYsvvhjbtm3z+jlw4ADOPfdcYbuMjAyv1x09ehQXXXQRKisr8f7776O6uhpLly4F4DIwRxu1Wu31O8dxcDqdAAClUol169bhk08+QUVFBV566SWMGDECR44cifo6CIIIDxI7BEHEFY1GA4fD4fXY6aefjt27d6O8vBxDhw71+vEVOGKqq6vhdDrx5z//GZMmTcLw4cNRW1sbcn++jBo1CjU1NaipqREe27NnD9ra2lBRUSH5s3Ech8mTJ2Px4sX48ccfodFosGrVKsmvJwgiNpDYIQgirpSXl2Pz5s04evQompub4XQ6sXDhQrS0tOCXv/wltmzZgkOHDmHt2rW4/vrrgwqVoUOHwmaz4aWXXsLhw4fxz3/+UzAui/fX0dGBL774As3NzX7TW9OnT8fYsWNx9dVXY+vWrfj+++8xb948nHfeeTjjjDMkfa7NmzfjySefxA8//IDjx4/jgw8+QFNTE0aNGhXeASIIIuqQ2CEIIq7ce++9UCqVqKioQEFBAY4fP46SkhJ8++23cDgcmDFjBsaOHYu77roL2dnZUCgCn6bGjRuH5557Dn/6058wZswY/Otf/8KSJUu8tjn77LOxYMECXHXVVSgoKOhhcAZcEZkPP/wQOTk5OPfcczF9+nQMHjwY77zzjuTPZTAY8PXXX+PCCy/E8OHD8eCDD+LPf/4zZs+eLf3gEAQREzie6iIJgiAIgkhiKLJDEARBEERSQ2KHIAiCIIikhsQOQRAEQRBJDYkdgiAIgiCSGhI7BEEQBEEkNSR2CIIgCIJIakjsEARBEASR1JDYIQiCIAgiqSGxQxAEQRBEUkNihyAIgiCIpIbEDkEQBEEQSQ2JHYIgCIIgkpr/D9T+eJvXM3L4AAAAAElFTkSuQmCC", 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", "text/plain": [ "
" ] @@ -370,34 +370,34 @@ " \n", " \n", " \n", - " 1022\n", - " {'w': [1, 2, 0], 'budget_rule_slack_var': [1, ...\n", - " 0.000488\n", - " -4.5\n", + " 180\n", + " {'w': [1, 2, 1], 'budget_rule_slack_var': [0, ...\n", + " 0.000977\n", + " -4.8\n", " \n", " \n", - " 847\n", - " {'w': [2, 2, 2], 'budget_rule_slack_var': [0, ...\n", + " 515\n", + " {'w': [3, 1, 2], 'budget_rule_slack_var': [0, ...\n", " 0.000488\n", - " -4.4\n", + " -4.6\n", " \n", " \n", - " 367\n", - " {'w': [0, 3, 0], 'budget_rule_slack_var': [1, ...\n", - " 0.000977\n", - " -3.9\n", + " 112\n", + " {'w': [2, 2, 2], 'budget_rule_slack_var': [0, ...\n", + " 0.001465\n", + " -4.4\n", " \n", " \n", - " 101\n", - " {'w': [1, 3, 1], 'budget_rule_slack_var': [1, ...\n", - " 0.001465\n", - " -3.7\n", + " 713\n", + " {'w': [2, 1, 2], 'budget_rule_slack_var': [1, ...\n", + " 0.000488\n", + " -4.3\n", " \n", " \n", - " 1023\n", - " {'w': [2, 1, 0], 'budget_rule_slack_var': [0, ...\n", + " 1285\n", + " {'w': [1, 1, 0], 'budget_rule_slack_var': [1, ...\n", " 0.000488\n", - " -3.5\n", + " -4.2\n", " \n", " \n", "\n", @@ -405,11 +405,11 @@ ], "text/plain": [ " solution probability cost\n", - "1022 {'w': [1, 2, 0], 'budget_rule_slack_var': [1, ... 0.000488 -4.5\n", - "847 {'w': [2, 2, 2], 'budget_rule_slack_var': [0, ... 0.000488 -4.4\n", - "367 {'w': [0, 3, 0], 'budget_rule_slack_var': [1, ... 0.000977 -3.9\n", - "101 {'w': [1, 3, 1], 'budget_rule_slack_var': [1, ... 0.001465 -3.7\n", - "1023 {'w': [2, 1, 0], 'budget_rule_slack_var': [0, ... 0.000488 -3.5" + "180 {'w': [1, 2, 1], 'budget_rule_slack_var': [0, ... 0.000977 -4.8\n", + "515 {'w': [3, 1, 2], 'budget_rule_slack_var': [0, ... 0.000488 -4.6\n", + "112 {'w': [2, 2, 2], 'budget_rule_slack_var': [0, ... 0.001465 -4.4\n", + "713 {'w': [2, 1, 2], 'budget_rule_slack_var': [1, ... 0.000488 -4.3\n", + "1285 {'w': [1, 1, 0], 'budget_rule_slack_var': [1, ... 0.000488 -4.2" ] }, "execution_count": 10, @@ -458,7 +458,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -492,7 +492,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 13, "id": "05449034-19e5-4b5d-80ea-7b2ba7ccd877", "metadata": { "tags": [] @@ -502,7 +502,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "x = [3, 1, 2] , cost = -4.6\n" + "x = [1, 2, 1] , cost = -4.8\n" ] } ], @@ -526,7 +526,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 14, "id": "324c9a09", "metadata": { "pycharm": { @@ -544,9 +544,9 @@ " Variables:\n", " w : Size=3, Index=w_index\n", " Key : Lower : Value : Upper : Fixed : Stale : Domain\n", - " 0 : 0 : 2.0 : 6 : False : False : Integers\n", - " 1 : 0 : 1.0 : 6 : False : False : Integers\n", - " 2 : 0 : 1.0 : 6 : False : False : Integers\n", + " 0 : 0 : 2.0 : 7 : False : False : Integers\n", + " 1 : 0 : 1.0 : 7 : False : False : Integers\n", + " 2 : 0 : 1.0 : 7 : False : False : Integers\n", "\n", " Objectives:\n", " cost : Size=1, Index=None, Active=True\n", diff --git a/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json b/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json index ba1113e93..8e4d13d71 100644 --- a/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json +++ b/applications/finance/portfolio_optimization/portfolio_optimization.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "rz", - "cx", + "p", + "cz", "h", + "t", + "rz", "u1", - "r", - "sx", - "s", - "rx", - "y", - "cy", - "tdg", + "z", "ry", + "sxdg", + "cx", + "rx", "u2", + "cy", "u", - "x", - "cz", - "z", - "sxdg", + "y", + "sx", + "r", + "s", + "tdg", + "id", "sdg", - "t", - "p", - "id" + "x" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": -1 + "random_seed": 4243313233 } } diff --git a/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb b/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb index 702813b48..e5dafe97a 100644 --- a/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb +++ b/applications/optimization/integer_linear_programming/integer_linear_programming.ipynb @@ -57,7 +57,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "48889b21-557b-481c-80c5-3c0b5c91adb6", "metadata": { "ExecuteTime": { @@ -101,7 +101,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "6e5295f4-7ba6-4ff6-8782-1c4c2c7f85e4", "metadata": { "ExecuteTime": { @@ -116,12 +116,12 @@ "c = np.array([1, 2, 3])\n", "\n", "# Instantiate the model\n", - "ilp_model = ilp(A, b, c, 4)" + "ilp_model = ilp(A, b, c, 3)" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "345330b2-9c14-41f6-b4ba-e11fb9ca1565", "metadata": { "ExecuteTime": { @@ -146,9 +146,9 @@ "1 Var Declarations\n", " x : Size=3, Index=x_index\n", " Key : Lower : Value : Upper : Fixed : Stale : Domain\n", - " 0 : 0 : None : 4 : False : True : NonNegativeIntegers\n", - " 1 : 0 : None : 4 : False : True : NonNegativeIntegers\n", - " 2 : 0 : None : 4 : False : True : NonNegativeIntegers\n", + " 0 : 0 : None : 3 : False : True : NonNegativeIntegers\n", + " 1 : 0 : None : 3 : False : True : NonNegativeIntegers\n", + " 2 : 0 : None : 3 : False : True : NonNegativeIntegers\n", "\n", "1 Objective Declarations\n", " cost : Size=1, Index=None, Active=True\n", @@ -184,7 +184,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "816b468f-a59f-4f2f-8337-4a9d66548425", "metadata": { "tags": [] @@ -201,7 +201,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "62ec28b3-cb49-411a-8c4a-8004fff6c105", "metadata": {}, "outputs": [], @@ -221,7 +221,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", "metadata": { "pycharm": { @@ -234,7 +234,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Opening: https://nightly.platform.classiq.io/circuit/ef888bc5-02f8-4150-b49f-76cd8bbc7ecf?version=0.62.0.dev9\n" + "Opening: https://nightly.platform.classiq.io/circuit/2d391a9b-4f75-4b90-ba76-fe6eb0cc3dec?version=0.63.0.dev2\n" ] } ], @@ -253,7 +253,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "7d188c69-21d1-4afe-86b1-46229e91a01e", "metadata": {}, "outputs": [], @@ -275,7 +275,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "62d12d20-1c80-4a9e-bb6b-b1fddc6cbe40", "metadata": { "tags": [] @@ -285,7 +285,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Optimization Progress: 72%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌ | 65/90 [03:27<01:19, 3.19s/it]\n" + "Optimization Progress: 76%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎ | 68/90 [02:24<00:46, 2.12s/it]\n" ] } ], @@ -303,7 +303,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "02454398-b229-403c-824a-b1eb539fbc1f", "metadata": { "tags": [] @@ -315,13 +315,13 @@ "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -367,7 +367,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "id": "9638f749-a60b-4176-a4ea-50d7c2bb986f", "metadata": {}, "outputs": [ @@ -399,49 +399,56 @@ " \n", " \n", " \n", - " 32\n", - " {'x': [0, 0, 1]}\n", - " 0.004883\n", + " 18\n", + " {'x': [0, 0, 1], 'monotone_rule_1_slack_var': ...\n", + " 0.011719\n", " -3.000000e+00\n", " \n", " \n", " 0\n", - " {'x': [0, 1, 0]}\n", - " 0.281738\n", + " {'x': [0, 1, 0], 'monotone_rule_1_slack_var': ...\n", + " 0.030762\n", " -2.000000e+00\n", " \n", " \n", - " 8\n", - " {'x': [1, 0, 0]}\n", - " 0.016113\n", - " -1.000000e+00\n", + " 9\n", + " {'x': [0, 0, 0], 'monotone_rule_1_slack_var': ...\n", + " 0.018066\n", + " 1.527468e-150\n", " \n", " \n", - " 73\n", - " {'x': [0, 0, 0]}\n", + " 150\n", + " {'x': [0, 0, 1], 'monotone_rule_1_slack_var': ...\n", " 0.001465\n", - " 1.527468e-150\n", + " 7.000000e+00\n", " \n", " \n", - " 104\n", - " {'x': [0, 0, 1]}\n", - " 0.000977\n", - " 7.000000e+00\n", + " 130\n", + " {'x': [0, 1, 0], 'monotone_rule_1_slack_var': ...\n", + " 0.001953\n", + " 8.000000e+00\n", " \n", " \n", "\n", "" ], "text/plain": [ - " solution probability cost\n", - "32 {'x': [0, 0, 1]} 0.004883 -3.000000e+00\n", - "0 {'x': [0, 1, 0]} 0.281738 -2.000000e+00\n", - "8 {'x': [1, 0, 0]} 0.016113 -1.000000e+00\n", - "73 {'x': [0, 0, 0]} 0.001465 1.527468e-150\n", - "104 {'x': [0, 0, 1]} 0.000977 7.000000e+00" + " solution probability \\\n", + "18 {'x': [0, 0, 1], 'monotone_rule_1_slack_var': ... 0.011719 \n", + "0 {'x': [0, 1, 0], 'monotone_rule_1_slack_var': ... 0.030762 \n", + "9 {'x': [0, 0, 0], 'monotone_rule_1_slack_var': ... 0.018066 \n", + "150 {'x': [0, 0, 1], 'monotone_rule_1_slack_var': ... 0.001465 \n", + "130 {'x': [0, 1, 0], 'monotone_rule_1_slack_var': ... 0.001953 \n", + "\n", + " cost \n", + "18 -3.000000e+00 \n", + "0 -2.000000e+00 \n", + "9 1.527468e-150 \n", + "150 7.000000e+00 \n", + "130 8.000000e+00 " ] }, - "execution_count": 12, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -461,7 +468,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "id": "25277397-d7a5-4466-af4c-fee2e17bc8b9", "metadata": {}, "outputs": [], @@ -479,7 +486,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "id": "77668ce1-64f6-4086-b0fe-597ded8ad0e0", "metadata": { "tags": [] @@ -487,7 +494,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -529,7 +536,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", "metadata": { "tags": [] @@ -538,10 +545,12 @@ { "data": { "text/plain": [ - "{'x': [0, 0, 1]}" + "{'x': [0, 0, 1],\n", + " 'monotone_rule_1_slack_var': [0],\n", + " 'monotone_rule_2_slack_var': [0]}" ] }, - "execution_count": 15, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -569,7 +578,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { "pycharm": { diff --git a/applications/optimization/integer_linear_programming/integer_linear_programming.qmod b/applications/optimization/integer_linear_programming/integer_linear_programming.qmod index 21489c8cf..d447b9a52 100644 --- a/applications/optimization/integer_linear_programming/integer_linear_programming.qmod +++ b/applications/optimization/integer_linear_programming/integer_linear_programming.qmod @@ -1,14 +1,14 @@ qstruct QAOAVars { x: qnum<2, False, 0>[3]; - monotone_rule_1_slack_var_0: qbit; - monotone_rule_2_slack_var_0: qbit; + monotone_rule_1_slack_var: qbit[1]; + monotone_rule_2_slack_var: qbit[1]; } qfunc main(params: real[6], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); repeat (i: 3) { - phase (-(((((((((10 * v.x[0]) * v.x[1]) + ((10 * v.x[0]) * v.x[2])) - v.x[0]) + ((10 * v.x[1]) * v.x[2])) - (2 * v.x[1])) - (3 * v.x[2])) + (10 * (((((v.monotone_rule_1_slack_var_0 + v.x[0]) + v.x[1]) + v.x[2]) - 1.0) ** 2))) + (10 * (((((v.monotone_rule_2_slack_var_0 + v.x[0]) + v.x[1]) + v.x[2]) - 1.0) ** 2))), params[i]); + phase (-(((((((((10 * v.x[0]) * v.x[1]) + ((10 * v.x[0]) * v.x[2])) - v.x[0]) + ((10 * v.x[1]) * v.x[2])) - (2 * v.x[1])) - (3 * v.x[2])) + (10 * (((((v.monotone_rule_1_slack_var[0] + v.x[0]) + v.x[1]) + v.x[2]) - 1.0) ** 2))) + (10 * (((((v.monotone_rule_2_slack_var[0] + v.x[0]) + v.x[1]) + v.x[2]) - 1.0) ** 2))), params[i]); apply_to_all(lambda(q) { RX(params[3 + i], q); }, v); diff --git a/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json b/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json index ba1113e93..0523412fc 100644 --- a/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json +++ b/applications/optimization/integer_linear_programming/integer_linear_programming.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ + "t", "rz", - "cx", - "h", - "u1", - "r", "sx", - "s", - "rx", - "y", "cy", + "rx", + "cz", "tdg", - "ry", - "u2", "u", - "x", - "cz", - "z", - "sxdg", + "ry", + "y", + "u1", + "h", "sdg", - "t", + "cx", + "r", + "sxdg", + "x", + "id", "p", - "id" + "z", + "u2", + "s" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": -1 + "random_seed": 3739250181 } } From 213ed6350315c70550924a63fd9b801e662b7855 Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Thu, 19 Dec 2024 12:00:35 +0200 Subject: [PATCH 28/32] test commit Co-authored-by: Lior Preminger --- algorithms/algebraic/hidden_shift/hidden_shift.ipynb | 12 ++++-------- 1 file changed, 4 insertions(+), 8 deletions(-) diff --git a/algorithms/algebraic/hidden_shift/hidden_shift.ipynb b/algorithms/algebraic/hidden_shift/hidden_shift.ipynb index 5f106413b..c67139271 100644 --- a/algorithms/algebraic/hidden_shift/hidden_shift.ipynb +++ b/algorithms/algebraic/hidden_shift/hidden_shift.ipynb @@ -63,9 +63,7 @@ { "name": "stdout", "output_type": "stream", - "text": [ - "" - ] + "text": [] } ], "source": [ @@ -253,8 +251,7 @@ "output_type": "stream", "text": [ "f_dual: (((((((((x[5]) & (y[0])) ^ ((x[2]) & (y[1]))) ^ ((x[7]) & (y[2]))) ^ ((x[0]) & (y[3]))) ^ ((x[6]) & (y[4]))) ^ ((x[3]) & (y[5]))) ^ ((x[1]) & (y[6]))) ^ ((x[4]) & (y[7]))) ^ ((((((((x[5]) & (x[2])) & (x[7])) & (x[0])) & (x[6])) & (x[3])) & (x[1])) & (x[4]))\n", - "g: (((((((((x[0]) & (y[3])) ^ (((x[1]) ^ 1) & (y[6]))) ^ ((x[2]) & ((y[1]) ^ 1))) ^ (((x[3]) ^ 1) & (y[5]))) ^ ((x[4]) & (y[7]))) ^ ((x[5]) & (y[0]))) ^ ((x[6]) & (y[4]))) ^ ((x[7]) & (y[2]))) ^ ((((((((y[0]) & ((y[1]) ^ 1)) & (y[2])) & (y[3])) & (y[4])) & (y[5])) & (y[6])) & (y[7]))\n", - "" + "g: (((((((((x[0]) & (y[3])) ^ (((x[1]) ^ 1) & (y[6]))) ^ ((x[2]) & ((y[1]) ^ 1))) ^ (((x[3]) ^ 1) & (y[5]))) ^ ((x[4]) & (y[7]))) ^ ((x[5]) & (y[0]))) ^ ((x[6]) & (y[4]))) ^ ((x[7]) & (y[2]))) ^ ((((((((y[0]) & ((y[1]) ^ 1)) & (y[2])) & (y[3])) & (y[4])) & (y[5])) & (y[6])) & (y[7]))\n" ] } ], @@ -389,8 +386,7 @@ "output_type": "stream", "text": [ "f: (((((((((x[0]) & (y[3])) ^ ((x[1]) & (y[6]))) ^ ((x[2]) & (y[1]))) ^ ((x[3]) & (y[5]))) ^ ((x[4]) & (y[7]))) ^ ((x[5]) & (y[0]))) ^ ((x[6]) & (y[4]))) ^ ((x[7]) & (y[2]))) ^ ((((((((y[0]) & (y[1])) & (y[2])) & (y[3])) & (y[4])) & (y[5])) & (y[6])) & (y[7]))\n", - "g: (((((((((x[0]) & (y[3])) ^ (((x[1]) ^ 1) & (y[6]))) ^ ((x[2]) & ((y[1]) ^ 1))) ^ (((x[3]) ^ 1) & (y[5]))) ^ ((x[4]) & (y[7]))) ^ ((x[5]) & (y[0]))) ^ ((x[6]) & (y[4]))) ^ ((x[7]) & (y[2]))) ^ ((((((((y[0]) & ((y[1]) ^ 1)) & (y[2])) & (y[3])) & (y[4])) & (y[5])) & (y[6])) & (y[7]))\n", - "" + "g: (((((((((x[0]) & (y[3])) ^ (((x[1]) ^ 1) & (y[6]))) ^ ((x[2]) & ((y[1]) ^ 1))) ^ (((x[3]) ^ 1) & (y[5]))) ^ ((x[4]) & (y[7]))) ^ ((x[5]) & (y[0]))) ^ ((x[6]) & (y[4]))) ^ ((x[7]) & (y[2]))) ^ ((((((((y[0]) & ((y[1]) ^ 1)) & (y[2])) & (y[3])) & (y[4])) & (y[5])) & (y[6])) & (y[7]))\n" ] } ], @@ -589,7 +585,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.7" + "version": "3.11.4" } }, "nbformat": 4, From e4dc7f30b07d51739e93e2e56f3d45e97c6f44b7 Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Thu, 19 Dec 2024 12:25:23 +0200 Subject: [PATCH 29/32] added galois to test requirements Co-authored-by: Lior Preminger --- requirements_tests.txt | 2 ++ 1 file changed, 2 insertions(+) diff --git a/requirements_tests.txt b/requirements_tests.txt index d69421200..54d71fdd5 100644 --- a/requirements_tests.txt +++ b/requirements_tests.txt @@ -1,5 +1,7 @@ pytest testbook + torch torchvision +galois From ebfc6a5245ed148ce19b1b5fa321df4f515871ab Mon Sep 17 00:00:00 2001 From: Dor Harpaz Date: Thu, 19 Dec 2024 13:50:22 +0200 Subject: [PATCH 30/32] Fix file rename --- .github/workflows/Internal-automatic-deployment.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/Internal-automatic-deployment.yml b/.github/workflows/Internal-automatic-deployment.yml index 936acfa73..a3abce596 100644 --- a/.github/workflows/Internal-automatic-deployment.yml +++ b/.github/workflows/Internal-automatic-deployment.yml @@ -11,14 +11,14 @@ on: jobs: deploy-prod: if: github.event.pull_request.merged == true && github.event.pull_request.base.ref == 'main' - uses: ./.github/workflows/deployment-qmod.yml + uses: ./.github/workflows/Utils-deployment-qmod.yml with: deploy-mode: production secrets: inherit deploy-dev: if: github.event.pull_request.merged == true && github.event.pull_request.base.ref == 'dev' - uses: ./.github/workflows/deployment-qmod.yml + uses: ./.github/workflows/Utils-deployment-qmod.yml with: deploy-mode: staging secrets: inherit From ce1e531d84d07ee04ce184d7194d4e6e73f3d6f5 Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Sun, 8 Dec 2024 14:23:15 +0200 Subject: [PATCH 31/32] with min_graph_coloring, portforlio_opt, set_cover, max_induced_k_colorable, electric_grid, mis, mds --- .../electric_grid_optimization.ipynb | 411 +- .../electric_grid_optimization.qmod | 1798 +--- ...c_grid_optimization.synthesis_options.json | 40 +- .../max_independent_set.ipynb | 474 +- .../max_independent_set.qmod | 326 +- ...max_independent_set.synthesis_options.json | 44 +- .../max_induced_k_color_subgraph.ipynb | 459 +- .../max_induced_k_color_subgraph.qmod | 6742 +------------- ...ed_k_color_subgraph.synthesis_options.json | 44 +- .../min_graph_coloring.ipynb | 490 +- .../min_graph_coloring.qmod | 7927 +---------------- .../min_graph_coloring.synthesis_options.json | 44 +- .../minimum_dominating_set.ipynb | 413 +- .../minimum_dominating_set.qmod | 2752 +----- ...imum_dominating_set.synthesis_options.json | 44 +- .../optimization/set_cover/set_cover.ipynb | 520 +- .../optimization/set_cover/set_cover.qmod | 2463 +---- .../set_cover.synthesis_options.json | 44 +- 18 files changed, 1311 insertions(+), 23724 deletions(-) diff --git a/applications/optimization/electric_grid_optimization/electric_grid_optimization.ipynb b/applications/optimization/electric_grid_optimization/electric_grid_optimization.ipynb index 2bc91a2c9..d1bb92a4a 100644 --- a/applications/optimization/electric_grid_optimization/electric_grid_optimization.ipynb +++ b/applications/optimization/electric_grid_optimization/electric_grid_optimization.ipynb @@ -54,20 +54,13 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 7, "id": "dfdf4e93-c86f-47b0-9ced-7e4c6a2447f1", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:04:04.062042Z", - "iopub.status.busy": "2024-05-07T16:04:04.061832Z", - "iopub.status.idle": "2024-05-07T16:04:05.541487Z", - "shell.execute_reply": "2024-05-07T16:04:05.540719Z" - } - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -148,16 +141,9 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 8, "id": "7cd709da-2feb-43da-b45c-b99c299b4b8b", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:04:05.545686Z", - "iopub.status.busy": "2024-05-07T16:04:05.545230Z", - "iopub.status.idle": "2024-05-07T16:04:05.806453Z", - "shell.execute_reply": "2024-05-07T16:04:05.805663Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "import pyomo.environ as pyo\n", @@ -201,19 +187,71 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 9, "id": "adbe0aaf-b592-41d0-936d-72f60164142e", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:04:05.811678Z", - "iopub.status.busy": "2024-05-07T16:04:05.810510Z", - "iopub.status.idle": "2024-05-07T16:04:05.815184Z", - "shell.execute_reply": "2024-05-07T16:04:05.814524Z" + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "5 Set Declarations\n", + " each_consumer_is_supplied_rule_index : Size=1, Index=None, Ordered=Insertion\n", + " Key : Dimen : Domain : Size : Members\n", + " None : 1 : Any : 4 : {0, 1, 2, 3}\n", + " source_supply_rule_index : Size=1, Index=None, Ordered=Insertion\n", + " Key : Dimen : Domain : Size : Members\n", + " None : 1 : Any : 3 : {0, 1, 2}\n", + " x_index : Size=1, Index=None, Ordered=True\n", + " Key : Dimen : Domain : Size : Members\n", + " None : 2 : x_index_0*x_index_1 : 12 : {(0, 0), (0, 1), (0, 2), (0, 3), (1, 0), (1, 1), (1, 2), (1, 3), (2, 0), (2, 1), (2, 2), (2, 3)}\n", + " x_index_0 : Size=1, Index=None, Ordered=Insertion\n", + " Key : Dimen : Domain : Size : Members\n", + " None : 1 : Any : 3 : {0, 1, 2}\n", + " x_index_1 : Size=1, Index=None, Ordered=Insertion\n", + " Key : Dimen : Domain : Size : Members\n", + " None : 1 : Any : 4 : {0, 1, 2, 3}\n", + "\n", + "1 Var Declarations\n", + " x : Size=12, Index=x_index\n", + " Key : Lower : Value : Upper : Fixed : Stale : Domain\n", + " (0, 0) : 0 : None : 1 : False : True : Binary\n", + " (0, 1) : 0 : None : 1 : False : True : Binary\n", + " (0, 2) : 0 : None : 1 : False : True : Binary\n", + " (0, 3) : 0 : None : 1 : False : True : Binary\n", + " (1, 0) : 0 : None : 1 : False : True : Binary\n", + " (1, 1) : 0 : None : 1 : False : True : Binary\n", + " (1, 2) : 0 : None : 1 : False : True : Binary\n", + " (1, 3) : 0 : None : 1 : False : True : Binary\n", + " (2, 0) : 0 : None : 1 : False : True : Binary\n", + " (2, 1) : 0 : None : 1 : False : True : Binary\n", + " (2, 2) : 0 : None : 1 : False : True : Binary\n", + " (2, 3) : 0 : None : 1 : False : True : Binary\n", + "\n", + "1 Objective Declarations\n", + " cost : Size=1, Index=None, Active=True\n", + " Key : Active : Sense : Expression\n", + " None : True : minimize : 0.5*x[0,0] + x[0,1] + x[0,2] + 2.1*x[0,3] + x[1,0] + 0.6*x[1,1] + 1.4*x[1,2] + x[1,3] + x[2,0] + 1.4*x[2,1] + 0.4*x[2,2] + 2.3*x[2,3]\n", + "\n", + "2 Constraint Declarations\n", + " each_consumer_is_supplied_rule : Size=4, Index=each_consumer_is_supplied_rule_index, Active=True\n", + " Key : Lower : Body : Upper : Active\n", + " 0 : 1.0 : x[0,0] + x[1,0] + x[2,0] : 1.0 : True\n", + " 1 : 1.0 : x[0,1] + x[1,1] + x[2,1] : 1.0 : True\n", + " 2 : 1.0 : x[0,2] + x[1,2] + x[2,2] : 1.0 : True\n", + " 3 : 1.0 : x[0,3] + x[1,3] + x[2,3] : 1.0 : True\n", + " source_supply_rule : Size=3, Index=source_supply_rule_index, Active=True\n", + " Key : Lower : Body : Upper : Active\n", + " 0 : -Inf : x[0,0] + x[0,1] + x[0,2] + x[0,3] : 2.0 : True\n", + " 1 : -Inf : x[1,0] + x[1,1] + x[1,2] + x[1,3] : 2.0 : True\n", + " 2 : -Inf : x[2,0] + x[2,1] + x[2,2] + x[2,3] : 2.0 : True\n", + "\n", + "9 Declarations: x_index_0 x_index_1 x_index x source_supply_rule_index source_supply_rule each_consumer_is_supplied_rule_index each_consumer_is_supplied_rule cost\n" + ] } - }, - "outputs": [], + ], "source": [ - "# opt_model.pprint()" + "opt_model.pprint()" ] }, { @@ -224,164 +262,67 @@ "## Solving with Classiq\n", "We take a specific example: the one outlined above.\n", "\n", - "### First generating parameters for the qauntum circuit" + "### First generating parameters for the quantum circuit" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 10, "id": "65d37686-873e-4f04-a207-8f04dab7fc23", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:04:05.819895Z", - "iopub.status.busy": "2024-05-07T16:04:05.818740Z", - "iopub.status.idle": "2024-05-07T16:04:07.898134Z", - "shell.execute_reply": "2024-05-07T16:04:07.897282Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "qaoa_config = QAOAConfig(num_layers=5, penalty_energy=3.0)\n", - "# the penalty_energy influence the convergence to the right solution." - ] - }, - { - "cell_type": "markdown", - "id": "8b78c9d7-3cac-4f5d-ba57-6bb0b04cac07", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm (`OptimizerConfig`) we define the maximum number of iterations of the hybrid algorithm(`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm:" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "4923e39f-c497-413d-a832-1656594b6ada", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:04:07.901605Z", - "iopub.status.busy": "2024-05-07T16:04:07.900694Z", - "iopub.status.idle": "2024-05-07T16:04:07.904292Z", - "shell.execute_reply": "2024-05-07T16:04:07.903706Z" - } - }, - "outputs": [], - "source": [ - "optimizer_config = OptimizerConfig(\n", - " max_iteration=100,\n", - " alpha_cvar=1,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "ec0491fb-fbe5-4b5e-845a-a4ed48dab919", - "metadata": {}, - "source": [ - "Combining all the parts together using `construct_combinatorial_optimization_model` to get a `SeralizedModel` which include `pyomo.ConcreteModel`, `QAOAConfig`, and `OptimizerConfig`." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "8972cb39-3dd2-4930-9f57-a448eae0e7fe", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:04:07.906974Z", - "iopub.status.busy": "2024-05-07T16:04:07.906415Z", - "iopub.status.idle": "2024-05-07T16:04:16.397515Z", - "shell.execute_reply": "2024-05-07T16:04:16.396886Z" - } - }, - "outputs": [], - "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=opt_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")\n", + "combi = CombinatorialProblem(pyo_model=opt_model, num_layers=6, penalty_factor=8)\n", "\n", - "# defining constraint such as computer and parameters for a quicker and more optimized circuit.\n", - "qmod = set_preferences(qmod, timeout_seconds=3000)" + "qmod = combi.get_model()\n", + "write_qmod(qmod, \"electric_grid_optimization\")" ] }, { "cell_type": "markdown", - "id": "2ad2070e-3d16-4b2c-a9e8-a68506ba6430", + "id": "c1ab3b7a-e81d-4b12-b822-418eef8edb30", "metadata": {}, "source": [ - "Now we can create a quantum circuit using the `synthesize` command and show it" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "1032fb02-17ce-4534-8845-b75d149e8fb4", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:04:16.400635Z", - "iopub.status.busy": "2024-05-07T16:04:16.400418Z", - "iopub.status.idle": "2024-05-07T16:04:16.464566Z", - "shell.execute_reply": "2024-05-07T16:04:16.463936Z" - } - }, - "outputs": [], - "source": [ - "write_qmod(qmod, \"electric_grid_optimization\")" + "We now solve the problem by calling the `optimize` method of the `CombinatorialProblem` object. For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`maxiter`) and the $\\alpha$-parameter (`quantile`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" ] }, { "cell_type": "code", - "execution_count": 8, - "id": "4e057ddc-1f99-464e-99e4-cb31e885a07b", + "execution_count": 14, + "id": "41276b9c-4406-4f8d-bc56-c4ee7497d61f", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:04:16.467538Z", - "iopub.status.busy": "2024-05-07T16:04:16.466919Z", - "iopub.status.idle": "2024-05-07T16:04:25.452696Z", - "shell.execute_reply": "2024-05-07T16:04:25.451931Z" - } + "tags": [] }, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Opening: https://platform.classiq.io/circuit/f21658ea-a358-4aad-a5e8-096d4c16bed7?version=0.41.0.dev39%2B79c8fd0855\n" + "ename": "ClassiqAPIError", + "evalue": "Internal error occurred. Please contact Classiq support.\nError number 122001 occurred:\n\nError identifier: E1F6D3DA2-C8A2-4BC3-9ED6-9F88BB83A16E\nIf you need further assistance, please reach out on our Community Slack channel at: https://short.classiq.io/join-slack", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mClassiqAPIError\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m:2\u001b[0m\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/applications/combinatorial_optimization/combinatorial_problem.py:84\u001b[0m, in \u001b[0;36mCombinatorialProblem.optimize\u001b[0;34m(self, execution_preferences, maxiter, cost_trace, quantile)\u001b[0m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21moptimize\u001b[39m(\n\u001b[1;32m 77\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 78\u001b[0m execution_preferences: Optional[ExecutionPreferences] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 81\u001b[0m quantile: \u001b[38;5;28mfloat\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1.0\u001b[39m,\n\u001b[1;32m 82\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mlist\u001b[39m[\u001b[38;5;28mfloat\u001b[39m]:\n\u001b[1;32m 83\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_ \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m---> 84\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_qprog\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 85\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mes_ \u001b[38;5;241m=\u001b[39m ExecutionSession(\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_, execution_preferences \u001b[38;5;66;03m# type:ignore[assignment,arg-type]\u001b[39;00m\n\u001b[1;32m 87\u001b[0m )\n\u001b[1;32m 89\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mestimate_cost_wrapper\u001b[39m(params: np\u001b[38;5;241m.\u001b[39mndarray) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mfloat\u001b[39m:\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/applications/combinatorial_optimization/combinatorial_problem.py:73\u001b[0m, in \u001b[0;36mCombinatorialProblem.get_qprog\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 71\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel_ \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 72\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_model()\n\u001b[0;32m---> 73\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_ \u001b[38;5;241m=\u001b[39m \u001b[43msynthesize\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel_\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type:ignore[assignment,arg-type]\u001b[39;00m\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/synthesis.py:85\u001b[0m, in \u001b[0;36msynthesize\u001b[0;34m(serialized_model, auto_show)\u001b[0m\n\u001b[1;32m 71\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msynthesize\u001b[39m(\n\u001b[1;32m 72\u001b[0m serialized_model: SerializedModel, auto_show: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 73\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m SerializedQuantumProgram:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 75\u001b[0m \u001b[38;5;124;03m Synthesize a model with the Classiq engine to receive a quantum program.\u001b[39;00m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;124;03m [More details](https://docs.classiq.io/latest/reference-manual/synthesis/)\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 83\u001b[0m \u001b[38;5;124;03m SerializedQuantumProgram: Quantum program serialized as a string. (See: QuantumProgram)\u001b[39;00m\n\u001b[1;32m 84\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 85\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43masync_utils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43msynthesize_async\u001b[49m\u001b[43m(\u001b[49m\u001b[43mserialized_model\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m auto_show:\n\u001b[1;32m 87\u001b[0m show(result)\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/async_utils.py:37\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(coro)\u001b[0m\n\u001b[1;32m 32\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrun\u001b[39m(coro: Awaitable[T]) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m T:\n\u001b[1;32m 33\u001b[0m \u001b[38;5;66;03m# Use this function instead of asyncio.run, since it ALWAYS\u001b[39;00m\n\u001b[1;32m 34\u001b[0m \u001b[38;5;66;03m# creates a new event loop and clears the thread event loop.\u001b[39;00m\n\u001b[1;32m 35\u001b[0m \u001b[38;5;66;03m# Never use asyncio.run in library code.\u001b[39;00m\n\u001b[1;32m 36\u001b[0m loop \u001b[38;5;241m=\u001b[39m get_event_loop()\n\u001b[0;32m---> 37\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mloop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_until_complete\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcoro\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/nest_asyncio.py:98\u001b[0m, in \u001b[0;36m_patch_loop..run_until_complete\u001b[0;34m(self, future)\u001b[0m\n\u001b[1;32m 95\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m f\u001b[38;5;241m.\u001b[39mdone():\n\u001b[1;32m 96\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 97\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mEvent loop stopped before Future completed.\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m---> 98\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresult\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/asyncio/futures.py:203\u001b[0m, in \u001b[0;36mFuture.result\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 201\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__log_traceback \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 202\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 203\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception\u001b[38;5;241m.\u001b[39mwith_traceback(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception_tb)\n\u001b[1;32m 204\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_result\n", + "File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/asyncio/tasks.py:267\u001b[0m, in \u001b[0;36mTask.__step\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 263\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 264\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m exc \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 265\u001b[0m \u001b[38;5;66;03m# We use the `send` method directly, because coroutines\u001b[39;00m\n\u001b[1;32m 266\u001b[0m \u001b[38;5;66;03m# don't have `__iter__` and `__next__` methods.\u001b[39;00m\n\u001b[0;32m--> 267\u001b[0m result \u001b[38;5;241m=\u001b[39m coro\u001b[38;5;241m.\u001b[39msend(\u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 268\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 269\u001b[0m result \u001b[38;5;241m=\u001b[39m coro\u001b[38;5;241m.\u001b[39mthrow(exc)\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/synthesis.py:67\u001b[0m, in \u001b[0;36msynthesize_async\u001b[0;34m(serialized_model)\u001b[0m\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msynthesize_async\u001b[39m(\n\u001b[1;32m 64\u001b[0m serialized_model: SerializedModel,\n\u001b[1;32m 65\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m SerializedQuantumProgram:\n\u001b[1;32m 66\u001b[0m model \u001b[38;5;241m=\u001b[39m Model\u001b[38;5;241m.\u001b[39mmodel_validate_json(serialized_model)\n\u001b[0;32m---> 67\u001b[0m quantum_program \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m ApiWrapper\u001b[38;5;241m.\u001b[39mcall_generation_task(model)\n\u001b[1;32m 68\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m SerializedQuantumProgram(quantum_program\u001b[38;5;241m.\u001b[39mmodel_dump_json(indent\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m))\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/api_wrapper.py:125\u001b[0m, in \u001b[0;36mApiWrapper.call_generation_task\u001b[0;34m(cls, model, http_client)\u001b[0m\n\u001b[1;32m 121\u001b[0m poller \u001b[38;5;241m=\u001b[39m JobPoller(base_url\u001b[38;5;241m=\u001b[39mroutes\u001b[38;5;241m.\u001b[39mTASKS_GENERATE_FULL_PATH)\n\u001b[1;32m 122\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m poller\u001b[38;5;241m.\u001b[39mrun_pydantic(\n\u001b[1;32m 123\u001b[0m model, timeout_sec\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, http_client\u001b[38;5;241m=\u001b[39mhttp_client\n\u001b[1;32m 124\u001b[0m )\n\u001b[0;32m--> 125\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_parse_job_response\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresult\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgenerator_result\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mQuantumProgram\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/api_wrapper.py:61\u001b[0m, in \u001b[0;36m_parse_job_response\u001b[0;34m(job_result, output_type)\u001b[0m\n\u001b[1;32m 59\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m output_type\u001b[38;5;241m.\u001b[39mmodel_validate(job_result\u001b[38;5;241m.\u001b[39mresult)\n\u001b[1;32m 60\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m job_result\u001b[38;5;241m.\u001b[39mfailure_details:\n\u001b[0;32m---> 61\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ClassiqAPIError(job_result\u001b[38;5;241m.\u001b[39mfailure_details)\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ClassiqAPIError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnexpected response from server\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[0;31mClassiqAPIError\u001b[0m: Internal error occurred. Please contact Classiq support.\nError number 122001 occurred:\n\nError identifier: E1F6D3DA2-C8A2-4BC3-9ED6-9F88BB83A16E\nIf you need further assistance, please reach out on our Community Slack channel at: https://short.classiq.io/join-slack" ] } ], "source": [ - "qprog = synthesize(qmod)\n", - "show(qprog)" - ] - }, - { - "cell_type": "markdown", - "id": "6a3f6f40-1b5b-4c48-9508-115096a948f2", - "metadata": {}, - "source": [ - "We now execute the problem iteratively by calling the `execute` function on the quantum program we have generated:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "f0e5e58a-f97c-47bc-b16b-1185e0a17b96", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:04:25.457663Z", - "iopub.status.busy": "2024-05-07T16:04:25.456404Z", - "iopub.status.idle": "2024-05-07T16:07:16.006361Z", - "shell.execute_reply": "2024-05-07T16:07:16.005610Z" - } - }, - "outputs": [], - "source": [ - "result = execute(qprog).result_value()" + "%%time\n", + "cost_values = []\n", + "optimized_params = combi.optimize(maxiter=100, cost_trace=cost_values, quantile=1)" ] }, { @@ -394,32 +335,39 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 15, "id": "af2b4f18-b829-47a8-82ac-c3e0fb4a6894", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:16.011389Z", - "iopub.status.busy": "2024-05-07T16:07:16.010151Z", - "iopub.status.idle": "2024-05-07T16:07:16.042190Z", - "shell.execute_reply": "2024-05-07T16:07:16.041486Z" - } - }, + "metadata": {}, "outputs": [ { "data": { - "image/jpeg": 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", "text/plain": [ - "" + "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 10, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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ABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC7cLS/Pnz1d4eLiqVaumzp07a/369db+iYmJatWqlapVq6Z27dppxYoV5+07ZswYORwOxcfHl3PVAADAXblVWEpISNCECRM0ffp0bdq0Se3bt1dsbKyOHDlSYv+1a9cqLi5OI0eO1Lfffqu+ffuqb9++2rp1a7G+77//vr755huFhoZW9DQAAIAbcauw9Pzzz2vUqFEaPny4WrdurQULFqhGjRp69dVXS+w/b9489ejRQ5MmTVJERIT++te/6tprr9VLL73k0u/gwYMaP3683nrrLXl7e1+KqQAAADfhNmEpLy9PKSkpiomJcbZ5eHgoJiZGycnJJY5JTk526S9JsbGxLv0LCws1ePBgTZo0SW3atKmY4gEAgNvyquwCSisjI0MFBQUKDg52aQ8ODlZqamqJY9LS0krsn5aW5nz97LPPysvLSw888ECpa8nNzVVubq7zdU5OTqnHAgAA9+I2d5YqQkpKiubNm6dFixbJ4XCUetysWbPk7+/vPMLCwiqwSgAAUJncJiwFBgbK09NT6enpLu3p6ekKCQkpcUxISIi1/1dffaUjR46ocePG8vLykpeXl/bt26eJEycqPDz8vLVMmTJF2dnZzuPAgQO/b3IAAKDKcpuw5OPjo8jISCUlJTnbCgsLlZSUpKioqBLHREVFufSXpFWrVjn7Dx48WN9//72+++475xEaGqpJkybp008/PW8tvr6+8vPzczkAAMDlyW32LEnShAkTNHToUHXs2FGdOnVSfHy8Tp48qeHDh0uShgwZooYNG2rWrFmSpAcffFDdunXT3Llzdeutt2rJkiXauHGjFi5cKEmqV6+e6tWr53INb29vhYSE6Oqrr760kwMAAFWSW4WlgQMH6ujRo5o2bZrS0tLUoUMHrVy50rmJe//+/fLw+N/Nsq5du2rx4sWaOnWqHn/8cbVo0UIffPCB2rZtW1lTAAAAbsZhjDGVXYS7y8nJkb+/v7Kzs/lIDgAAN1Ha399us2cJAACgMhCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwcLuwNH/+fIWHh6tatWrq3Lmz1q9fb+2fmJioVq1aqVq1amrXrp1WrFjhPJefn6/HHntM7dq1U82aNRUaGqohQ4bo0KFDFT0NAADgJtwqLCUkJGjChAmaPn26Nm3apPbt2ys2NlZHjhwpsf/atWsVFxenkSNH6ttvv1Xfvn3Vt29fbd26VZJ06tQpbdq0SU8++aQ2bdqk9957Tzt37tTtt99+KacFAACqMIcxxlR2EaXVuXNnXXfddXrppZckSYWFhQoLC9P48eM1efLkYv0HDhyokydPavny5c62Ll26qEOHDlqwYEGJ19iwYYM6deqkffv2qXHjxqWqKycnR/7+/srOzpafn99FzAwAAFxqpf397TZ3lvLy8pSSkqKYmBhnm4eHh2JiYpScnFzimOTkZJf+khQbG3ve/pKUnZ0th8OhgICAcqkbAAC4N6/KLqC0MjIyVFBQoODgYJf24OBgpaamljgmLS2txP5paWkl9j9z5owee+wxxcXFWRNmbm6ucnNzna9zcnJKOw0AAOBm3ObOUkXLz8/XgAEDZIzRK6+8Yu07a9Ys+fv7O4+wsLBLVCUAALjU3CYsBQYGytPTU+np6S7t6enpCgkJKXFMSEhIqfoXBaV9+/Zp1apVF9x3NGXKFGVnZzuPAwcOXMSMAACAO3CbsOTj46PIyEglJSU52woLC5WUlKSoqKgSx0RFRbn0l6RVq1a59C8KSrt27dJnn32mevXqXbAWX19f+fn5uRwAAODy5DZ7liRpwoQJGjp0qDp27KhOnTopPj5eJ0+e1PDhwyVJQ4YMUcOGDTVr1ixJ0oMPPqhu3bpp7ty5uvXWW7VkyRJt3LhRCxculHQuKN15553atGmTli9froKCAud+prp168rHx6dyJgoAAKoMtwpLAwcO1NGjRzVt2jSlpaWpQ4cOWrlypXMT9/79++Xh8b+bZV27dtXixYs1depUPf7442rRooU++OADtW3bVpJ08OBBffTRR5KkDh06uFzr888/10033XRJ5gUAAKout3rOUlXFc5YAAHA/l91zlgAAACoDYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAACLiwpLTz31lE6dOlWs/fTp03rqqad+d1EAAABVhcMYY8o6yNPTU4cPH1b9+vVd2o8dO6b69euroKCg3Ap0Bzk5OfL391d2drb8/PwquxwAAFAKpf39fVF3lowxcjgcxdo3b96sunXrXsxbAgAAVEleZelcp04dORwOORwOtWzZ0iUwFRQU6MSJExozZky5FwkAAFBZyhSW4uPjZYzRiBEjNHPmTPn7+zvP+fj4KDw8XFFRUeVeJAAAQGUpU1gaOnSoJKlp06a6/vrr5eVVpuEAAABu56L2LNWuXVs7duxwvv7www/Vt29fPf7448rLyyu34gAAACrbRYWl++67Tz/88IMk6aefftLAgQNVo0YNJSYm6tFHHy3XAgEAACrTRYWlH374QR06dJAkJSYmqlu3blq8eLEWLVqkd999tzzrAwAAqFQX/eiAwsJCSdJnn32mXr16SZLCwsKUkZFRftWVYP78+QoPD1e1atXUuXNnrV+/3to/MTFRrVq1UrVq1dSuXTutWLHC5bwxRtOmTVODBg1UvXp1xcTEaNeuXRU5BQAA4EYuKix17NhRTz/9tN544w2tWbNGt956qyRpz549Cg4OLtcCfy0hIUETJkzQ9OnTtWnTJrVv316xsbE6cuRIif3Xrl2ruLg4jRw5Ut9++6369u2rvn37auvWrc4+s2fP1gsvvKAFCxZo3bp1qlmzpmJjY3XmzJkKmwcAAHAfF/UE7++//16DBg3S/v37neFFksaPH69jx45p8eLF5V6oJHXu3FnXXXedXnrpJUlSYWGhwsLCNH78eE2ePLlY/4EDB+rkyZNavny5s61Lly7q0KGDFixYIGOMQkNDNXHiRD3yyCOSpOzsbAUHB2vRokW6++67S1UXT/AGAMD9lPb390V99/+aa67Rli1birXPmTNHnp6eF/OWF5SXl6eUlBRNmTLF2ebh4aGYmBglJyeXOCY5OVkTJkxwaYuNjdUHH3wg6dydsLS0NMXExDjP+/v7q3PnzkpOTj5vWMrNzVVubq7zdU5OzsVOCwAAVHG/60FJKSkpzkcItG7dWtdee225FFWSjIwMFRQUFPuYLzg4WKmpqSWOSUtLK7F/Wlqa83xR2/n6lGTWrFmaOXNmmecAAADcz0WFpSNHjmjgwIFas2aNAgICJElZWVm6+eabtWTJEgUFBZVnjVXOlClTXO5Y5eTkKCwsrBIrAgAAFeWiNniPHz9eJ06c0LZt25SZmanMzExt3bpVOTk5euCBB8q7RklSYGCgPD09lZ6e7tKenp6ukJCQEseEhIRY+xf9tyzvKUm+vr7y8/NzOQAAwOXposLSypUr9fLLLysiIsLZ1rp1a82fP1+ffPJJuRX3az4+PoqMjFRSUpKzrbCwUElJSef9e3RRUVEu/SVp1apVzv5NmzZVSEiIS5+cnBytW7eOv3EHAAAkXeTHcIWFhfL29i7W7u3t7Xz+UkWYMGGChg4dqo4dO6pTp06Kj4/XyZMnNXz4cEnSkCFD1LBhQ82aNUuS9OCDD6pbt26aO3eubr31Vi1ZskQbN27UwoULJUkOh0MPPfSQnn76abVo0UJNmzbVk08+qdDQUPXt27fC5gEAANzHRYWlW265RQ8++KDefvtthYaGSpIOHjyohx9+WNHR0eVa4K8NHDhQR48e1bRp05SWlqYOHTpo5cqVzg3a+/fvl4fH/26Wde3aVYsXL9bUqVP1+OOPq0WLFvrggw/Utm1bZ59HH31UJ0+e1OjRo5WVlaU//vGPWrlypapVq1Zh8wAAAO7jop6zdODAAd1+++3atm2bc2PzgQMH1LZtW3300Udq1KhRuRdalfGcJQAA3E+FPmcpLCxMmzZt0meffeb82n5ERITL84oAAAAuB2Xa4L169Wq1bt1aOTk5cjgc+tOf/qTx48dr/Pjxuu6669SmTRt99dVXFVUrAADAJVemsBQfH69Ro0aVeKvK399f9913n55//vlyKw4AAKCylSksbd68WT169Djv+e7duyslJeV3FwUAAFBVlCkspaenl/jIgCJeXl46evTo7y4KAACgqihTWGrYsKG2bt163vPff/+9GjRo8LuLAgAAqCrKFJZ69eqlJ598UmfOnCl27vTp05o+fbp69+5dbsUBAABUtjI9Zyk9PV3XXnutPD09NW7cOF199dWSpNTUVM2fP18FBQXatGmT8yGRVwqeswQAgPupkOcsBQcHa+3atfrLX/6iKVOmqChnORwOxcbGav78+VdcUAIAAJe3Mj+UskmTJlqxYoV++eUX/fjjjzLGqEWLFqpTp05F1AcAAFCpLuoJ3pJUp04dXXfddeVZCwAAQJVTpg3eAAAAVxrCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALBwm7CUmZmpQYMGyc/PTwEBARo5cqROnDhhHXPmzBmNHTtW9erVU61atdS/f3+lp6c7z2/evFlxcXEKCwtT9erVFRERoXnz5lX0VAAAgBtxm7A0aNAgbdu2TatWrdLy5cv15ZdfavTo0dYxDz/8sJYtW6bExEStWbNGhw4dUr9+/ZznU1JSVL9+fb355pvatm2bnnjiCU2ZMkUvvfRSRU8HAAC4CYcxxlR2EReyY8cOtW7dWhs2bFDHjh0lSStXrlSvXr30888/KzQ0tNiY7OxsBQUFafHixbrzzjslSampqYqIiFBycrK6dOlS4rXGjh2rHTt2aPXq1aWuLycnR/7+/srOzpafn99FzBAAAFxqpf397RZ3lpKTkxUQEOAMSpIUExMjDw8PrVu3rsQxKSkpys/PV0xMjLOtVatWaty4sZKTk897rezsbNWtW9daT25urnJyclwOAABweXKLsJSWlqb69eu7tHl5ealu3bpKS0s77xgfHx8FBAS4tAcHB593zNq1a5WQkHDBj/dmzZolf39/5xEWFlb6yQAAALdSqWFp8uTJcjgc1iM1NfWS1LJ161b16dNH06dPV/fu3a19p0yZouzsbOdx4MCBS1IjAAC49Lwq8+ITJ07UsGHDrH2aNWumkJAQHTlyxKX97NmzyszMVEhISInjQkJClJeXp6ysLJe7S+np6cXGbN++XdHR0Ro9erSmTp16wbp9fX3l6+t7wX4AAMD9VWpYCgoKUlBQ0AX7RUVFKSsrSykpKYqMjJQkrV69WoWFhercuXOJYyIjI+Xt7a2kpCT1799fkrRz507t379fUVFRzn7btm3TLbfcoqFDh+qZZ54ph1kBAIDLiVt8G06SevbsqfT0dC1YsED5+fkaPny4OnbsqMWLF0uSDh48qOjoaL3++uvq1KmTJOkvf/mLVqxYoUWLFsnPz0/jx4+XdG5vknTuo7dbbrlFsbGxmjNnjvNanp6epQpxRfg2HAAA7qe0v78r9c5SWbz11lsaN26coqOj5eHhof79++uFF15wns/Pz9fOnTt16tQpZ9s//vEPZ9/c3FzFxsbq5Zdfdp5funSpjh49qjfffFNvvvmms71Jkybau3fvJZkXAACo2tzmzlJVxp0lAADcz2X1nCUAAIDKQlgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMDCbcJSZmamBg0aJD8/PwUEBGjkyJE6ceKEdcyZM2c0duxY1atXT7Vq1VL//v2Vnp5eYt9jx46pUaNGcjgcysrKqoAZAAAAd+Q2YWnQoEHatm2bVq1apeXLl+vLL7/U6NGjrWMefvhhLVu2TImJiVqzZo0OHTqkfv36ldh35MiRuuaaayqidAAA4MYcxhhT2UVcyI4dO9S6dWtt2LBBHTt2lCStXLlSvXr10s8//6zQ0NBiY7KzsxUUFKTFixfrzjvvlCSlpqYqIiJCycnJ6tKli7PvK6+8ooSEBE2bNk3R0dH65ZdfFBAQUOr6cnJy5O/vr+zsbPn5+f2+yQIAgEuitL+/3eLOUnJysgICApxBSZJiYmLk4eGhdevWlTgmJSVF+fn5iomJcba1atVKjRs3VnJysrNt+/bteuqpp/T666/Lw6N0y5Gbm6ucnByXAwAAXJ7cIiylpaWpfv36Lm1eXl6qW7eu0tLSzjvGx8en2B2i4OBg55jc3FzFxcVpzpw5aty4canrmTVrlvz9/Z1HWFhY2SYEAADcRqWGpcmTJ8vhcFiP1NTUCrv+lClTFBERoXvuuafM47Kzs53HgQMHKqhCAABQ2bwq8+ITJ07UsGHDrH2aNWumkJAQHTlyxKX97NmzyszMVEhISInjQkJClJeXp6ysLJe7S+np6c4xq1ev1pYtW7R06VJJUtH2rcDAQD3xxBOaOXNmie/t6+srX1/f0kwRAAC4uUoNS0FBQQoKCrpgv6ioKGVlZSklJUWRkZGSzgWdwsJCde7cucQxkZGR8vb2VlJSkvr37y9J2rlzp/bv36+oqChJ0rvvvqvTp087x2zYsEEjRozQV199pauuuur3Tg8AAFwGKjUslVZERIR69OihUaNGacGCBcrPz9e4ceN09913O78Jd/DgQUVHR+v1119Xp06d5O/vr5EjR2rChAmqW7eu/Pz8NH78eEVFRTm/CffbQJSRkeG8Xlm+DQcAAC5fbhGWJOmtt97SuHHjFB0dLQ8PD/Xv318vvPCC83x+fr527typU6dOOdv+8Y9/OPvm5uYqNjZWL7/8cmWUDwAA3JRbPGepquM5SwAAuJ/L6jlLAAAAlYWwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALDwquwCLgfGGElSTk5OJVcCAABKq+j3dtHv8fMhLJWD48ePS5LCwsIquRIAAFBWx48fl7+//3nPO8yF4hQuqLCwUIcOHVLt2rXlcDgqu5xKlZOTo7CwMB04cEB+fn6VXc5li3W+dFjrS4N1vjRYZ1fGGB0/flyhoaHy8Dj/ziTuLJUDDw8PNWrUqLLLqFL8/Pz4P+IlwDpfOqz1pcE6Xxqs8//Y7igVYYM3AACABWEJAADAgrCEcuXr66vp06fL19e3sku5rLHOlw5rfWmwzpcG63xx2OANAABgwZ0lAAAAC8ISAACABWEJAADAgrAEAABgQVhCmWVmZmrQoEHy8/NTQECARo4cqRMnTljHnDlzRmPHjlW9evVUq1Yt9e/fX+np6SX2PXbsmBo1aiSHw6GsrKwKmIF7qIh13rx5s+Li4hQWFqbq1asrIiJC8+bNq+ipVCnz589XeHi4qlWrps6dO2v9+vXW/omJiWrVqpWqVaumdu3aacWKFS7njTGaNm2aGjRooOrVqysmJka7du2qyCm4hfJc5/z8fD322GNq166datasqdDQUA0ZMkSHDh2q6GlUeeX98/xrY8aMkcPhUHx8fDlX7YYMUEY9evQw7du3N99884356quvTPPmzU1cXJx1zJgxY0xYWJhJSkoyGzduNF26dDFdu3YtsW+fPn1Mz549jSTzyy+/VMAM3ENFrPO///1v88ADD5gvvvjC7N6927zxxhumevXq5sUXX6zo6VQJS5YsMT4+PubVV18127ZtM6NGjTIBAQEmPT29xP5ff/218fT0NLNnzzbbt283U6dONd7e3mbLli3OPn//+9+Nv7+/+eCDD8zmzZvN7bffbpo2bWpOnz59qaZV5ZT3OmdlZZmYmBiTkJBgUlNTTXJysunUqZOJjIy8lNOqciri57nIe++9Z9q3b29CQ0PNP/7xjwqeSdVHWEKZbN++3UgyGzZscLZ98sknxuFwmIMHD5Y4Jisry3h7e5vExERn244dO4wkk5yc7NL35ZdfNt26dTNJSUlXdFiq6HX+tfvvv9/cfPPN5Vd8FdapUyczduxY5+uCggITGhpqZs2aVWL/AQMGmFtvvdWlrXPnzua+++4zxhhTWFhoQkJCzJw5c5zns7KyjK+vr3n77bcrYAbuobzXuSTr1683ksy+ffvKp2g3VFHr/PPPP5uGDRuarVu3miZNmhCWjDF8DIcySU5OVkBAgDp27Ohsi4mJkYeHh9atW1fimJS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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "result.convergence_graph" + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(nrows=1, ncols=1)\n", + "axes.plot(cost_values)\n", + "axes.set_xlabel(\"Iterations\")\n", + "axes.set_ylabel(\"Cost\")\n", + "axes.set_title(\"Cost convergence\")" ] }, { @@ -525,18 +473,8 @@ } ], "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " opt_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=True).head(5)" + "optimization_result = combi.get_results()\n", + "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { @@ -582,95 +520,20 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 16, "id": "a6c01f4d-ca8a-40ca-8ce3-8d969c9aa42a", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:07:24.250484Z", - "iopub.status.busy": "2024-05-07T16:07:24.249969Z", - "iopub.status.idle": "2024-05-07T16:07:24.519581Z", - "shell.execute_reply": "2024-05-07T16:07:24.518880Z" - } - }, + "metadata": {}, "outputs": [ { - "data": { - "text/markdown": [ - "**QAOA SOLUTION**" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "total cost= 3.599999999999998\n" + "ename": "NameError", + "evalue": "name 'optimization_result' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[16], line 82\u001b[0m\n\u001b[1;32m 78\u001b[0m plt\u001b[38;5;241m.\u001b[39maxis(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moff\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 79\u001b[0m plt\u001b[38;5;241m.\u001b[39mshow()\n\u001b[0;32m---> 82\u001b[0m best_solution \u001b[38;5;241m=\u001b[39m \u001b[43moptimization_result\u001b[49m\u001b[38;5;241m.\u001b[39mloc[optimization_result\u001b[38;5;241m.\u001b[39mcost\u001b[38;5;241m.\u001b[39midxmin()]\n\u001b[1;32m 84\u001b[0m plotting_sol([best_solution\u001b[38;5;241m.\u001b[39msolution[\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mx_\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mi\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(best_solution\u001b[38;5;241m.\u001b[39msolution))], \n\u001b[1;32m 85\u001b[0m best_solution\u001b[38;5;241m.\u001b[39mcost, is_classic\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n", + "\u001b[0;31mNameError\u001b[0m: name 'optimization_result' is not defined" ] - }, - { - "data": { - "text/html": [ - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" } ], "source": [ @@ -757,7 +620,11 @@ "\n", "best_solution = optimization_result.loc[optimization_result.cost.idxmin()]\n", "\n", - "plotting_sol(best_solution.solution, best_solution.cost, is_classic=False)" + "plotting_sol(\n", + " [best_solution.solution[f\"x_{i}\"] for i in range(len(best_solution.solution))],\n", + " best_solution.cost,\n", + " is_classic=False,\n", + ")" ] }, { @@ -931,7 +798,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" } }, "nbformat": 4, diff --git a/applications/optimization/electric_grid_optimization/electric_grid_optimization.qmod b/applications/optimization/electric_grid_optimization/electric_grid_optimization.qmod index dd4045987..25d035a05 100644 --- a/applications/optimization/electric_grid_optimization/electric_grid_optimization.qmod +++ b/applications/optimization/electric_grid_optimization/electric_grid_optimization.qmod @@ -1,1771 +1,33 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=41.35 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - 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Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.5 - } -]; - -qfunc main(params_list: real[10], output target: qbit[18]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + x_0,0: qbit; + x_0,1: qbit; + x_0,2: qbit; + x_0,3: qbit; + x_1,0: qbit; + x_1,1: qbit; + x_1,2: qbit; + x_1,3: qbit; + x_2,0: qbit; + x_2,1: qbit; + x_2,2: qbit; + x_2,3: qbit; + source_supply_rule_0_slack_var_0: qbit; + source_supply_rule_0_slack_var_1: qbit; + source_supply_rule_1_slack_var_0: qbit; + source_supply_rule_1_slack_var_1: qbit; + source_supply_rule_2_slack_var_0: qbit; + source_supply_rule_2_slack_var_1: qbit; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=False, -initial_point=[0.0, 0.17455213596692695, 0.04363803399173174, 0.1309141019751952, 0.08727606798346348, 0.08727606798346348, 0.1309141019751952, 0.04363803399173174, 0.17455213596692695, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=100, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=1 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[12], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 6) { + phase (-(((((((((((((((((((0.5 * v.x_0,0) + v.x_0,1) + v.x_0,2) + (2.1 * v.x_0,3)) + v.x_1,0) + (0.6 * v.x_1,1)) + (1.4 * v.x_1,2)) + v.x_1,3) + v.x_2,0) + (1.4 * v.x_2,1)) + (0.4 * v.x_2,2)) + (2.3 * v.x_2,3)) + (16 * ((((v.x_0,0 + v.x_1,0) + v.x_2,0) - 1) ** 2))) + (16 * ((((v.x_0,1 + v.x_1,1) + v.x_2,1) - 1) ** 2))) + (16 * ((((v.x_0,2 + v.x_1,2) + v.x_2,2) - 1) ** 2))) + (16 * ((((v.x_0,3 + v.x_1,3) + v.x_2,3) - 1) ** 2))) + (64.0 * ((((((((0.5 * v.source_supply_rule_0_slack_var_0) + (0.5 * v.source_supply_rule_0_slack_var_1)) + (0.5 * v.x_0,0)) + (0.5 * v.x_0,1)) + (0.5 * v.x_0,2)) + (0.5 * v.x_0,3)) - 1) ** 2))) + (64.0 * ((((((((0.5 * v.source_supply_rule_1_slack_var_0) + (0.5 * v.source_supply_rule_1_slack_var_1)) + (0.5 * v.x_1,0)) + (0.5 * v.x_1,1)) + (0.5 * v.x_1,2)) + (0.5 * v.x_1,3)) - 1) ** 2))) + (64.0 * ((((((((0.5 * v.source_supply_rule_2_slack_var_0) + (0.5 * v.source_supply_rule_2_slack_var_1)) + (0.5 * v.x_2,0)) + (0.5 * v.x_2,1)) + (0.5 * v.x_2,2)) + (0.5 * v.x_2,3)) - 1) ** 2))), params[i]); + apply_to_all(lambda(q) { + RX(params[6 + i], q); + }, v); + } +} diff --git a/applications/optimization/electric_grid_optimization/electric_grid_optimization.synthesis_options.json b/applications/optimization/electric_grid_optimization/electric_grid_optimization.synthesis_options.json index 518f1a763..9eeb8e4eb 100644 --- a/applications/optimization/electric_grid_optimization/electric_grid_optimization.synthesis_options.json +++ b/applications/optimization/electric_grid_optimization/electric_grid_optimization.synthesis_options.json @@ -1,5 +1,43 @@ { + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, "preferences": { - "timeout_seconds": 3000 + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "p", + "y", + "ry", + "u1", + "u", + "t", + "s", + "x", + "id", + "r", + "rx", + "tdg", + "cz", + "sx", + "cy", + "h", + "u2", + "z", + "sxdg", + "cx", + "rz", + "sdg" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 4093170185 } } diff --git a/applications/optimization/max_independent_set/max_independent_set.ipynb b/applications/optimization/max_independent_set/max_independent_set.ipynb index f1191d064..71f750459 100644 --- a/applications/optimization/max_independent_set/max_independent_set.ipynb +++ b/applications/optimization/max_independent_set/max_independent_set.ipynb @@ -39,12 +39,6 @@ "execution_count": 1, "id": "49a9588b-e79e-4813-b7c5-ac068d7b930c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:12.856430Z", - "iopub.status.busy": "2024-05-07T15:52:12.856181Z", - "iopub.status.idle": "2024-05-07T15:52:13.399271Z", - "shell.execute_reply": "2024-05-07T15:52:13.398641Z" - }, "tags": [] }, "outputs": [], @@ -52,7 +46,6 @@ "import networkx as nx\n", "import numpy as np\n", "import pyomo.core as pyo\n", - "from IPython.display import Markdown, display\n", "from matplotlib import pyplot as plt" ] }, @@ -71,12 +64,6 @@ "execution_count": 2, "id": "48889b21-557b-481c-80c5-3c0b5c91adb6", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:13.402476Z", - "iopub.status.busy": "2024-05-07T15:52:13.401869Z", - "iopub.status.idle": "2024-05-07T15:52:13.406304Z", - "shell.execute_reply": "2024-05-07T15:52:13.405679Z" - }, "tags": [] }, "outputs": [], @@ -104,25 +91,18 @@ "- Index set declarations (model.Nodes, model.Arcs).\n", "- Binary variable declaration for each node (model.x) indicating whether that node is chosen to be included in the set.\n", "- Constraint rule - for each edge we require at least one of the corresponding node variables to be 0.\n", - "- Objective rule \u2013 the sum of the variables equals to the set size." + "- Objective rule – the sum of the variables equals to the set size." ] }, { "cell_type": "code", "execution_count": 3, "id": "439b4081-cb00-4a59-bc23-20a21a291f67", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:13.408755Z", - "iopub.status.busy": "2024-05-07T15:52:13.408266Z", - "iopub.status.idle": "2024-05-07T15:52:14.007366Z", - "shell.execute_reply": "2024-05-07T15:52:14.006681Z" - } - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -145,12 +125,7 @@ "execution_count": 4, "id": "345330b2-9c14-41f6-b4ba-e11fb9ca1565", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:14.012596Z", - "iopub.status.busy": "2024-05-07T15:52:14.011279Z", - "iopub.status.idle": "2024-05-07T15:52:14.020876Z", - "shell.execute_reply": "2024-05-07T15:52:14.020169Z" - }, + "scrolled": true, "tags": [] }, "outputs": [ @@ -211,102 +186,81 @@ }, { "cell_type": "markdown", - "id": "17ea14ec-dbb7-487c-b4f1-cabc8d5e3c29", + "id": "dc64fdc1-2b8d-4a5c-a3a5-144b1e9662f0", "metadata": { "tags": [] }, "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):" + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the qaoa algorithm, with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { "cell_type": "code", - "execution_count": 5, - "id": "816b468f-a59f-4f2f-8337-4a9d66548425", + "execution_count": 8, + "id": "a41fe673-a242-41ff-93e9-8b66ddcdfd11", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:14.025670Z", - "iopub.status.busy": "2024-05-07T15:52:14.024439Z", - "iopub.status.idle": "2024-05-07T15:52:16.270258Z", - "shell.execute_reply": "2024-05-07T15:52:16.269600Z" - }, "tags": [] }, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "qaoa_config = QAOAConfig(num_layers=3)" - ] - }, - { - "cell_type": "markdown", - "id": "db34d5ac-6877-4285-8dec-7bf7b37eb783", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" + "combi = CombinatorialProblem(pyo_model=mis_model, num_layers=3, penalty_factor=10)\n", + "\n", + "qmod = combi.get_model()" ] }, { "cell_type": "code", - "execution_count": 6, - "id": "e41d0dd3-4135-4330-9ba3-c1b30c339a74", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:16.273418Z", - "iopub.status.busy": "2024-05-07T15:52:16.272601Z", - "iopub.status.idle": "2024-05-07T15:52:16.276365Z", - "shell.execute_reply": "2024-05-07T15:52:16.275788Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, + "execution_count": 9, + "id": "88895285-cfa6-48d3-9e57-2ebd277536eb", + "metadata": {}, "outputs": [], "source": [ - "optimizer_config = OptimizerConfig(max_iteration=60, alpha_cvar=0.7)" + "write_qmod(qmod, \"max_independent_set\")" ] }, { "cell_type": "markdown", - "id": "214d6051-43b8-4b9d-8454-f9cdb62b4cf0", + "id": "2ddaa221-0fa1-4200-8720-025ed7cd8eda", "metadata": {}, "source": [ - "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:" + "## Synthesizing the QAOA Circuit and Solving the Problem\n", + "\n", + "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "0243019c-6fc3-435f-b6ec-8b4355d6660c", + "execution_count": 10, + "id": "c41a61f7-7d06-48ad-b9fd-5fc54965a932", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:16.278670Z", - "iopub.status.busy": "2024-05-07T15:52:16.278371Z", - "iopub.status.idle": "2024-05-07T15:52:16.422355Z", - "shell.execute_reply": "2024-05-07T15:52:16.421734Z" - }, "pycharm": { "name": "#%%\n" }, + "scrolled": true, "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Opening: https://nightly.platform.classiq.io/circuit/5f349e4d-590e-4d1b-ac4e-d63aaec23f47?version=0.61.0.dev3\n" + ] + } + ], "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=mis_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" + "qprog = combi.get_qprog()\n", + "show(qprog)" ] }, { "cell_type": "markdown", - "id": "1fcc3812-c9d0-421c-84bb-38047297b33f", + "id": "edee52b0-0c97-4cdc-af41-97eb3c216c49", "metadata": {}, "source": [ "We also set the quantum backend we want to execute on:" @@ -314,67 +268,31 @@ }, { "cell_type": "code", - "execution_count": 8, - "id": "53bc041f-065c-44d2-b220-dafd9d0504ac", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:16.425237Z", - "iopub.status.busy": "2024-05-07T15:52:16.424825Z", - "iopub.status.idle": "2024-05-07T15:52:16.435948Z", - "shell.execute_reply": "2024-05-07T15:52:16.435280Z" - }, - "tags": [] - }, + "execution_count": 11, + "id": "7f028868-c80b-438d-b7fe-7d5280d86533", + "metadata": {}, "outputs": [], "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", + "from classiq.execution import *\n", "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", + "execution_preferences = ExecutionPreferences(\n", + " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\"),\n", ")" ] }, - { - "cell_type": "code", - "execution_count": 9, - "id": "6a754e2c-a9e7-40c4-8cee-a9a3f5a86896", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:16.438408Z", - "iopub.status.busy": "2024-05-07T15:52:16.438033Z", - "iopub.status.idle": "2024-05-07T15:52:16.452664Z", - "shell.execute_reply": "2024-05-07T15:52:16.452057Z" - } - }, - "outputs": [], - "source": [ - "write_qmod(qmod, \"max_independent_set\")" - ] - }, { "cell_type": "markdown", - "id": "943291f0-6a9f-4286-a69d-ef13a0a12ef6", + "id": "cec06839-8a83-4d7c-b8ed-c048db3f0f2b", "metadata": {}, "source": [ - "## Synthesizing the QAOA Circuit and Solving the Problem\n", - "\n", - "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" + "We now solve the problem by calling the `optimize` method of the `CombinatorialProblem` object. For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`maxiter`) and the $\\alpha$-parameter (`quantile`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" ] }, { "cell_type": "code", - "execution_count": 10, - "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", + "execution_count": 12, + "id": "9881db5f-7456-43b8-a892-220bc3dace41", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:16.455142Z", - "iopub.status.busy": "2024-05-07T15:52:16.454684Z", - "iopub.status.idle": "2024-05-07T15:52:19.876612Z", - "shell.execute_reply": "2024-05-07T15:52:19.875932Z" - }, - "pycharm": { - "name": "#%%\n" - }, "tags": [] }, "outputs": [ @@ -382,39 +300,17 @@ "name": "stdout", "output_type": "stream", "text": [ - "Opening: https://platform.classiq.io/circuit/7e58acc3-dfdb-4ebf-88c6-c980aa6e5089?version=0.41.0.dev39%2B79c8fd0855\n" + "CPU times: user 4.71 s, sys: 159 ms, total: 4.87 s\n", + "Wall time: 1min 32s\n" ] } ], "source": [ - "qprog = synthesize(qmod)\n", - "show(qprog)" - ] - }, - { - "cell_type": "markdown", - "id": "80238cf9-d7bd-46e5-9d48-b7cf23a6b304", - "metadata": {}, - "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "62d12d20-1c80-4a9e-bb6b-b1fddc6cbe40", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:19.879287Z", - "iopub.status.busy": "2024-05-07T15:52:19.878734Z", - "iopub.status.idle": "2024-05-07T15:52:25.320726Z", - "shell.execute_reply": "2024-05-07T15:52:25.319931Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "result = execute(qprog).result_value()" + "%%time\n", + "cost_values = []\n", + "optimized_params = combi.optimize(\n", + " execution_preferences, maxiter=60, cost_trace=cost_values, quantile=0.7\n", + ")" ] }, { @@ -427,38 +323,46 @@ }, { "cell_type": "code", - "execution_count": 12, - "id": "02454398-b229-403c-824a-b1eb539fbc1f", + "execution_count": 13, + "id": "ee1cbabe-2596-4f5d-9478-47267fb8d50c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:25.325641Z", - "iopub.status.busy": "2024-05-07T15:52:25.324432Z", - "iopub.status.idle": "2024-05-07T15:52:25.356784Z", - "shell.execute_reply": "2024-05-07T15:52:25.356169Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/jpeg": 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", "text/plain": [ - "" + "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "result.convergence_graph" + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(nrows=1, ncols=1)\n", + "axes.plot(cost_values)\n", + "axes.set_xlabel(\"Iterations\")\n", + "axes.set_ylabel(\"Cost\")\n", + "axes.set_title(\"Cost convergence\")" ] }, { "cell_type": "markdown", - "id": "615ed612-b835-4bf0-aa92-92d30ef8006d", + "id": "52919e64-6dfa-48fd-8051-d81d9016f301", "metadata": { "tags": [] }, @@ -468,25 +372,25 @@ }, { "cell_type": "markdown", - "id": "670eddd3-2da7-4a88-b571-7884ef24f60c", + "id": "c37c2ba4-8261-498d-83b6-a45ded0d6a86", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm:" + "We can also examine the statistics of the algorithm. The optimization is always defined as a minimzation problem, so the positive maximization objective was tranlated to a negative minimization one by the pyomo to qmod translator." + ] + }, + { + "cell_type": "markdown", + "id": "d2409631-208b-49cd-8389-92a7f9935919", + "metadata": {}, + "source": [ + "In order to get samples with the optimized parameters, we call the `get_results` method:" ] }, { "cell_type": "code", - "execution_count": 13, - "id": "516d78ba-2951-46eb-b1af-efe877513556", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:25.360585Z", - "iopub.status.busy": "2024-05-07T15:52:25.360332Z", - "iopub.status.idle": "2024-05-07T15:52:25.445578Z", - "shell.execute_reply": "2024-05-07T15:52:25.444791Z" - }, - "tags": [] - }, + "execution_count": 14, + "id": "c4ec53c7-087d-4c4e-a6f0-d8a70acea60c", + "metadata": {}, "outputs": [ { "data": { @@ -509,83 +413,68 @@ " \n", " \n", " \n", + " solution\n", " probability\n", " cost\n", - " solution\n", - " count\n", " \n", " \n", " \n", " \n", - " 35\n", - " 0.009\n", - " 3.0\n", - " [0, 0, 0, 0, 1, 0, 1, 1]\n", - " 9\n", + " 47\n", + " {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.002930\n", + " -3.0\n", " \n", " \n", - " 14\n", - " 0.016\n", - " 3.0\n", - " [0, 0, 0, 0, 1, 1, 0, 1]\n", - " 16\n", + " 59\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'...\n", + " 0.001953\n", + " -3.0\n", " \n", " \n", - " 6\n", - " 0.023\n", - " 3.0\n", - " [0, 1, 0, 0, 0, 0, 1, 1]\n", - " 23\n", + " 95\n", + " {'x_0': 0, 'x_1': 0, 'x_2': 0, 'x_3': 0, 'x_4'...\n", + " 0.000977\n", + " -3.0\n", " \n", " \n", - " 1\n", - " 0.035\n", - " 3.0\n", - " [0, 0, 1, 1, 0, 0, 0, 1]\n", - " 35\n", + " 64\n", + " {'x_0': 0, 'x_1': 0, 'x_2': 1, 'x_3': 1, 'x_4'...\n", + " 0.001465\n", + " -3.0\n", " \n", " \n", - " 92\n", - " 0.003\n", - " 3.0\n", - " [1, 1, 0, 1, 0, 0, 0, 0]\n", - " 3\n", + " 88\n", + " {'x_0': 0, 'x_1': 0, 'x_2': 0, 'x_3': 0, 'x_4'...\n", + " 0.000977\n", + " -3.0\n", " \n", " \n", "\n", "" ], "text/plain": [ - " probability cost solution count\n", - "35 0.009 3.0 [0, 0, 0, 0, 1, 0, 1, 1] 9\n", - "14 0.016 3.0 [0, 0, 0, 0, 1, 1, 0, 1] 16\n", - "6 0.023 3.0 [0, 1, 0, 0, 0, 0, 1, 1] 23\n", - "1 0.035 3.0 [0, 0, 1, 1, 0, 0, 0, 1] 35\n", - "92 0.003 3.0 [1, 1, 0, 1, 0, 0, 0, 0] 3" + " solution probability cost\n", + "47 {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.002930 -3.0\n", + "59 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'... 0.001953 -3.0\n", + "95 {'x_0': 0, 'x_1': 0, 'x_2': 0, 'x_3': 0, 'x_4'... 0.000977 -3.0\n", + "64 {'x_0': 0, 'x_1': 0, 'x_2': 1, 'x_3': 1, 'x_4'... 0.001465 -3.0\n", + "88 {'x_0': 0, 'x_1': 0, 'x_2': 0, 'x_3': 0, 'x_4'... 0.000977 -3.0" ] }, - "execution_count": 13, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " mis_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=False).head(5)" + "optimization_result = combi.get_results()\n", + "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { "cell_type": "markdown", - "id": "687f492b-a4a5-49c6-964c-8959b035bb93", + "id": "6b88a671-363a-4833-af23-2d27f70d4af4", "metadata": {}, "source": [ "And the histogram:" @@ -593,31 +482,13 @@ }, { "cell_type": "code", - "execution_count": 14, - "id": "31a4e74d-b2b8-42e0-826d-de7b51de1fe8", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:25.450643Z", - "iopub.status.busy": "2024-05-07T15:52:25.449435Z", - "iopub.status.idle": "2024-05-07T15:52:25.685563Z", - "shell.execute_reply": "2024-05-07T15:52:25.684857Z" - }, - "tags": [] - }, + "execution_count": 22, + "id": "ce35f016-5cee-4c22-9791-e545306f6b54", + "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array([[]], dtype=object)" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -627,12 +498,17 @@ } ], "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" + "optimization_result[\"cost\"].plot(\n", + " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + ")\n", + "plt.ylabel(\"Probability\", fontsize=16)\n", + "plt.xlabel(\"cost\", fontsize=16)\n", + "plt.tick_params(axis=\"both\", labelsize=14)" ] }, { "cell_type": "markdown", - "id": "a3a890a1-c5d4-409d-b9a3-d7ffd4fdd6c0", + "id": "91ce1000-65a4-4f3d-89fa-cb552ac3069c", "metadata": {}, "source": [ "Let us plot the solution:" @@ -640,66 +516,65 @@ }, { "cell_type": "code", - "execution_count": 15, - "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", + "execution_count": 16, + "id": "6e2a5a15-f8f9-4005-be77-7f406d7e399c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:25.690192Z", - "iopub.status.busy": "2024-05-07T15:52:25.689045Z", - "iopub.status.idle": "2024-05-07T15:52:25.694309Z", - "shell.execute_reply": "2024-05-07T15:52:25.693659Z" - }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'x_0': 1,\n", + " 'x_1': 1,\n", + " 'x_2': 0,\n", + " 'x_3': 1,\n", + " 'x_4': 0,\n", + " 'x_5': 0,\n", + " 'x_6': 0,\n", + " 'x_7': 0}" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "best_solution = optimization_result.solution[optimization_result.cost.idxmax()]" + "best_solution = optimization_result.solution[optimization_result.cost.idxmin()]\n", + "best_solution" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "id": "fed415f4-67ed-4a85-9138-553c75972ac8", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:25.698802Z", - "iopub.status.busy": "2024-05-07T15:52:25.697644Z", - "iopub.status.idle": "2024-05-07T15:52:25.706511Z", - "shell.execute_reply": "2024-05-07T15:52:25.705822Z" - } - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Independent Set: [2, 3, 7]\n", + "Independent Set: [0, 1, 3]\n", "Size of Independent Set: 3\n" ] } ], "source": [ - "independent_set = [node for node in graph.nodes if best_solution[node] == 1]\n", + "independent_set = [node for node in graph.nodes if best_solution[f\"x_{node}\"] == 1]\n", "print(\"Independent Set: \", independent_set)\n", "print(\"Size of Independent Set: \", len(independent_set))" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "id": "9861107b-3b50-4272-a07c-c0c4566b13ca", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:25.711117Z", - "iopub.status.busy": "2024-05-07T15:52:25.709952Z", - "iopub.status.idle": "2024-05-07T15:52:26.053349Z", - "shell.execute_reply": "2024-05-07T15:52:26.052556Z" - } - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -736,15 +611,9 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:26.058419Z", - "iopub.status.busy": "2024-05-07T15:52:26.057188Z", - "iopub.status.idle": "2024-05-07T15:52:26.133076Z", - "shell.execute_reply": "2024-05-07T15:52:26.132477Z" - }, "pycharm": { "name": "#%%\n" }, @@ -761,15 +630,9 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "id": "a7524894-b5c5-42d4-8f92-a019bef5e7da", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:26.137916Z", - "iopub.status.busy": "2024-05-07T15:52:26.136534Z", - "iopub.status.idle": "2024-05-07T15:52:26.144526Z", - "shell.execute_reply": "2024-05-07T15:52:26.143929Z" - }, "tags": [] }, "outputs": [ @@ -792,20 +655,13 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "id": "9bc4df9d-771b-4df5-943b-9b142134e979", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:26.148888Z", - "iopub.status.busy": "2024-05-07T15:52:26.147883Z", - "iopub.status.idle": "2024-05-07T15:52:26.436437Z", - "shell.execute_reply": "2024-05-07T15:52:26.435757Z" - } - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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hwxQWFjJgwAClo5RKrVazbNkybt68aZCjqEII0yUFpRCV2O0FN8uXLzf5BTf38/XXXwMwffp0hZPc27Bhw3jssccIDg7m+PHjSscRQghApryFqJQ2bNjApEmTuHr1KlWrVuXzzz9nwoQJSscyaLVq1SIvL49r164pHeW+EhISqFevHp6enly4cEHpOEIIISOUQlQmtxfcDB069I4FN1JM3ltubi4pKSkGt11QaTw9PRk7diwXL17km2++UTqOEELICKUQlUFaWhqjRo0iJCQElUrF4MGDWbFihdwj+YA+++wzXnnlFdasWWM09yZqtVocHBwoKioiKysLa2trpSMJIUyYjFAKYcT+ueAmJCSkZMHN+vXrpZh8CL/++itqtZonnnhC6SgPzNzcnG+//ZaCggKeeeYZpeMIIUycjFAKYaQ++ugj3nvvPQoKCnB3d2fFihUmvSl5WVhbW+Ph4UFsbKzSUR5ao0aNiI2NJTo6Gl9fX6XjCCFMlIxQCmFkNmzYQI0aNXjzzTexsLBgyZIlJt/hpizCw8MpLCzk8ccfVzrKI9mwYQMAQ4cOVTiJEMKUSUEphJE4efJkyYKba9eu8eqrr8qCGz349ttvAcPfLqg0vr6+DBs2jDNnzrBixQql4wghTJRMeQth4P694GbIkCH8/PPPco+knhjTdkGlKSgooHr16piZmZGdnY25ubnSkYQQJkZGKIUwUBqNhnHjxpUsuGndujUXLlxg3bp1UkzqSU5ODikpKQQEBCgdpUysra1ZsGABN27ckJ7sQghFSEEphAH66KOPqFatGj/99BN16tQhNDSUI0eO4OnpqXS0SuW7774D4LnnnlM4SdlNmzYNT09PfvrpJxISEpSOI4QwMTLlLYQB2bBhA88//zzp6enY29vz+eefM378eKVjVVqtWrXixIkT3Lx5E7Xa+L9fHz16lNatW9OsWTNOnDihdBwhhAkx/k9QISqBkydP0qhRo5IFN6+99hpZWVlSTJazyMhIGjRoUCmKSbhVIPft25eTJ0+WrP4WQoiKUDk+RYUwUmlpaXTr1o3mzZsTGxvL0KFDyczM5OOPP640RY6h2r9/PxqNhoEDByodRa9+//13LCwseO6559DpdErHEUKYCPmJJYQC/rngZu/evbLgRgG3twuaNm2awkn0y87OjnfffZfs7GxmzJihdBwhhImQeyiFqGDz58/n/fffp6CgAE9PT1atWkXHjh2VjmVyXF1dKSgoIDs7W+ko5cLNzY3U1FQuX76Mq6ur0nGEEJWcjFAKUUHWrVuHs7Mzs2bNwtLSkh9//JGLFy9KMamA7OxsUlNTjX67oHtZs2YNOp1OOugIISqEFJRClLOTJ0/i4+PD8OHDycnJKVlwM27cOKWjmazb2wVV5kVPnTt3pkuXLhw8eJCdO3cqHUcIUcnJlLcQ5SQtLY2RI0eyd+9eVCoVQ4cO5aeffpJ7JA1Ay5YtOXnyZKXZLqg0mZmZuLi44OjoSEpKSqV+r0IIZcmnixB6ptFoePbZZ0sW3LRp04YLFy6wdu1aKSYNRFRUFN7e3pW+wHJ0dOTll1/m6tWrvPvuu0rHEUJUYpX701SICjZv3jyqVavGzz//jLu7O/v27ePw4cPS4caAhIWFVcrtgkozf/58nJyc+OijjyrtAiQhhPKkoBRCD24vuHnrrbdkwY2BW7RoEQDTp09XOEnFUKvVrFixAq1Wy/Dhw5WOI4SopOQeSiHK4Pjx4zz55JPExsZiYWHByy+/zLx58yr9VKoxq1mzJhqNhqysLKWjVKg2bdoQERHB/v376dChg9JxhBCVjBSUQjyClJQURo0aRWhoKCqVimHDhvHzzz9ja2urdDRxD9nZ2VSvXp2+ffsSHBysdJwKlZycjLu7O7Vq1SIpKUnpOEKISkaGUYR4CLcX3NSuXZvQ0NCSBTd//PGHFJNGYPHixQBMnDhR4SQVz83NjUmTJnH58mU++eQTpeMIISoZGaEU4gHNmzePDz74gMLCQulwY6SaN29OZGQkGo3GJG9L0Ol0VK9enYKCArKysuRLkBBCb0zvE1VUSjcKtUQnX+NEYhbRyde4UajV27nXrl1bsuDGysqKn376SRbcGKno6GiT2C6oNGq1miVLlqDRaHjyySeVjiOEqETMlQ4gxKOKS73O6sOJhJxNIzEzj38OtasAD0dbuvm4MLqtB941qz70+Y8fP86oUaOIi4vDwsKCN954QxbcGLE9e/Zw8+ZNBg8erHQURY0YMYK5c+eyadMmTp48SbNmzZSOJISoBGTKWxidS5l5zNoQyb5z6ZipVRTpSv8jfPv5Tg2c+XCIP+6O95/ikwU3ldMTTzzB2rVruXz5Mm5ubkrHUVR8fDze3t7Uq1eP+Ph4peMIISoBGWoRRmVNRCI9vwjlwPkMgHsWk/98/sD5DHp+EcqaiMRSj9VoNIwdO7ZkwU3btm25ePGiLLipJEJDQ3FwcDD5YhLAy8uLMWPGcP78eb7//nul4wghKgEZoRRG45uQOD7dEVvm87wS2JD/dfO+47G5c+cyd+7ckgU3q1evlr36KpHMzEycnJzo378/mzdvVjqOQdBoNFSvXp3i4mKys7OxtLRUOpIQwojJCKUwCmsiEvVSTAJ8uiOW3/4eqby94Obtt9/G2tq6ZMGNFJOVy+3uOKa4XVBpLC0t+fLLL8nPz+fZZ59VOo4QwsjJCKUweJcy8+j5RSiFWt1/nss5spGsPUvv+jrHPtOo2qz3XZ+zVEPxlg8499dhLCwseOWVV5g7d64suKmkmjVrRlRUlMluF3QvDRs25Ny5c5w9exZvb+/7v0AIIe5CVnkLgzdrQyTa+9wraeFSDyu3Rnc8ZuXepNTjC29qKWg0gCcaevDTTz/JPZKV3OnTp2nYsKEUk3exfv16/P39GTx4MNHR0UrHEUIYKSkohUGLS73OvnPp9z3O2vMxHHtMeODzqszMsanXnA9nvCjFZCW3e/du2S7oHvz8/BgyZAgbNmxg9erVjB49WulIQggjJF/XhUFbfTgRM7XqgY7VXs9Ap9U88LnN1CpWHSp91beoHG63W5w+fbrCSQzXqlWrsLKyYvLkyWi1+msKIIQwHVJQCoMWcjbtvlsDAVyP2Mjlb8dy6dOhJH4xktzI3fd9TZGumJDYNH3EFAYsLCyM6tWr4+rqqnQUg2Vra8uHH35Ibm4uU6dOVTqOEMIISUEpDFZuoZbEzLx7H2RhhZmdI1X8emAfMALrei0oLswjY8sX3IgOve81EjPy9NqmURiWzMxMrl69Kqv2H8DMmTNxd3dn2bJlJCUlKR1HCGFk5B5KYbASMm5wv7FJ++Z9sW/e947H8i+eJG3NW2Tu+p4qTbrc8/XFwMWMGzRxq1a2sMIgffPNNwBMmjRJ4STGYd26dbRp04bBgwdz9OhRpeMIIYyIjFAKg6W5yzZBD8KmbjPM7Gugy895oHsqH/U6wvCtW7cOMzMz+vXrp3QUo9C6dWsCAwM5duwYmzZtUjqOEMKISEEpDJal+aP/8TSr4gCALi+nXK8jDNvp06fx8fGR7YIewh9//IGFhQXPPvssOp182RJCPBj5lBUGq65TFR5sffd/FV2/1etbbedwz+OKi4tp7+9N8+bNmTx5MkFBQRQUFDziVYUh2blzJ1qtlqFDhyodxajY29sze/ZssrKyePXVV5WOI4QwEtIpRxi0Lp+EkHCPhTma9EtYOrvf8diNmH2kB32MuooD7tNW3fP8FoXZFK59k5SUFG7evFnyuJ2dHXXr1qVVq1b06dOH/v37Y2dnV7Y3IyrUsGHDWL9+Pampqbi4uCgdx+jUrFmTjIwMUlJScHZ2VjqOEMLASUEpDNqcTdGsPJxQ6tZBiV+MRGVmjqVLPdRVqnPzagI3084DUGPYO9h6tyn13GZqFU+39WTOwFsddRITE9mwYQMhISH89ddfJCcno9H8/z2Ytra2eHh40KJFCwIDAxk0aBAODg76e7NCr5ydnSkuLiYjI0PpKEZpz5499OjRg44dO7Jv3z6l4wghDJwUlMKgxaVep9fCsFKfT1v/IQUXjlN88+9papUKM3sXnPpOw6Zus/uef9eMzjRwqVrq8ykpKQQFBbFr1y5OnjxJUlLSHVPi1tbWuLu789hjj9GzZ0+GDBkio2EGID09nRo1ajBo0CA2btyodByj1alTJ/bv38/u3bvp3r270nGEEAZMCkph8J5edpgD5zMeaIPzB2WmVtG+vhMrx7d96NdmZ2cTFBTE9u3bOXHiBImJieTl/f+0vJWVFW5ubjRt2pRu3boxZMgQPDw89JZd3N+cOXN477332LJli6zwLoP09HRcXV1xdnYmJSVF6ThCCAMmBaUweJcy8+j5RSiFetzex8pcza4ZXXB31E8f79zcXLZs2cLWrVs5duwYFy9eJDc3t+R5CwsLXF1d8fPzo2vXrgwbNgwvLy+9XFv8V9OmTYmJiaGwsFBWeJfRyy+/zOeff86cOXN49913lY4jhDBQUlAKo7AmIpE31kfq7XwfD/VnZOvyHTUsKChg69atbN26lYiICM6fP09Ozv9vY2Rubo6LiwuNGzemU6dODBs2jCZNmpRrJlOg0+mwsrKiUaNGREbq78+MqdLpdDg7O5Obm0t6ejr29vZKRxJCGCApKIVRGDt2LBvjCqje5Zkyn+vVQB9e6NZAD6kenlarZefOnQQHB3Po0CHi4+PJzs7m9l9DtVpNjRo1aNSoER06dGDIkCG0aNFCRtkewtatW+nXrx9vv/0277//vtJxKoVNmzYxaNAgAgMD2b59u9JxhBAGSApKYfCmTp3K4sWL8ff3580lfzJn82m0uuKHuqfSTK3CXK3i/YFNyn1k8mHpdDrCwsL4888/OXjwILGxsWRmZpYUmSqVCicnJxo2bEiHDh0YOHAg7du3lyKzFEOGDGHjxo2yXZCetWrVimPHjnHo0CHatn34e4+FEJWbFJTCoL366qt8+umneHt7c/r0aczNzbmUmcesDZHsO5eOmVp1z8KyWFeESm1GpwbOfDjEX2/3TJY3nU5HREQEQUFBhIeHc+bMGdLT00s6l6hUKhwcHGjQoAEBAQEMGDCAbt26YW5urnBy5d3eMzE9PV3hJJVLUlISnp6e1K5dm8TERKXjCCEMjBSUwmDdXqnr6elJbGwslpaWdzwfl3qd1YcTCYlNIzEjj3/+QVYBrlXNORuynk61IGjF9xWavbycPHmSoKAg9u3bx+nTp0lLS6OoqKjk+WrVquHl5UWbNm3o27cvffr0+c//t8osLS2NmjVrMnjwYDZs2KB0nErn+eefZ8mSJXz22WfMnDlT6ThCCAMiBaUwSAsWLOD111+nVq1anDt3Dlvbe48s3ijUcjHjBhqtDktzNXWdqlDF6tail4KCgjsWw1Q2Z8+eZcOGDYSGhhIVFUVKSgparbbkeTs7O+rVq1fS9WfAgAH3/f9prN555x0++OADgoOD6du3r9JxKh2tVkv16tW5efMmmZmZlfbPkRDi4UlBKQzON998w7Rp06hRowbnzp0r06rSF154gUWLFhEaGkrnzp31mNKwJSQksGHDBnbv3k1kZCRXrly5o+tPlSpV7uj6M3DgwErR9cff358zZ87IdkHlaPXq1YwZM4YhQ4awfv16peMIIQyEFJTCoCxfvpznnnsOBwcH4uPjcXR0LNP5bk+B9uzZk507d+oppXFKSUlhw4YN7Nq1i7/++ovLly/f0fXHxsaGOnXq0KxZM3r27MnQoUONqofz7e2CfH19OXXqlNJxKrXGjRsTExNDZGQkfn5+SscRQhgAKSiFwfjtt9948sknsbOzIzY2FldXV72ct169eiQnJ5Ofny+jVv+SmZlJUFAQO3bsKOn6k5+fX/K8lZUVtWvXpmnTpnTv3p1hw4bh5uamYOLSBQcH079/f959913mzJmjdJxKLS4uDh8fHxo0aEBsbKzScYQQBkAKSmEQNm3axODBg7GxsSEmJkavrQrnzp3L22+/zapVqxg9erTezltZ5ebm8ueff7Jt27aSrj83btwoed7CwoJatWqVdP0ZPnw49erVUzDxLYMHDyYoKIirV68a1ciqsXrqqaf49ddfWbJkCRMmTFA6jhBCYVJQCsXt3r2bwMBALC0tOXXqFN7e3no9f0FBAba2trRo0YKjR4/q9dymoqCggC1btrBt2zYiIiK4cOHCf7r+1KxZk8aNG9OlSxeGDh2Kr69vhWZ0cnJCpVLJdkEVRKPR4ODggEqlIisry6R2ExBC/JcUlEJR4eHhdOnSBTMzM44dO1Zu92M99thjREVFkZ+fLz/49ESj0bBr1y62bNnC4cOHS7r+3GZmZlbS9adTp04MHjyYZs2alcttBykpKdSqVUsWilSwxYsXM3XqVJ5++mlWrFihdBwhhIKkoBSKOX78eEnHjYMHD9KqVatyu9ayZcuYMGECH3/8Ma+99lq5XcfU6XQ69u7dy+bNmzl48CBxcXF3dP1Rq9U4OTnh4+ND+/btGThwIAEBAWUuMt9++23mzp3Ljh076NWrlz7einhAXl5eXLhwgbi4OLy8vJSOI4RQiBSUQhHR0dG0aNGCoqIi9u7dS8eOHcv1ejqdDmtrazw9PYmLiyvXa4k76XQ6Dh8+zKZNmwgPD+fs2bP/6fpTvXp1vL29S7r+dOnS5aG6/jRp0oTY2Fhu3rxZXm9DlOLkyZM0b94cf39/WV0vhAmTglJUuPj4ePz8/NBoNGzbtq3CRpS6du1KaGgoGRkZZd6OSJTdyZMn2bhxY0nXn6tXr97R9cfBwaGk60+/fv1K7rP9N51Oh6WlJY0bN5aCRiGDBg1i06ZN/Pbbb4wYMULpOEIIBUhBKSpUUlISjRo1Ii8vj40bNzJw4MAKu/bOnTsJDAxkxowZfP755xV2XfHgYmJi2LhxY0nXn9TU1Du6/lStWpV69erRunVr+vTpQ79+/dizZw+PP/447733Hu+8846C6U1XXl4e1atXx9ramqysLNmeSwgTJAWlqDBpaWl4e3tz/fp1Vq9ezZNPPlnhGezs7KhatSpXrlyp8GuLR3PhwgU2bNjAnj17iIqK+k/XHzMzM4qKinjiiScYOHAgAwcOLFN3JfFobrdLnTJlCosWLVI6jhCigklBKSpEZmYmDRo0ICsri6VLlzJ+/HhFcgwbNoz169dz7tw5WUBgxJKTk9m4cSO7du0iKCio5H7M22xsbHB3d6d58+YlXX/kNofyV6dOHa5cucKlS5cMdgN8IUT5kIJSlLvc3Fzq16/P1atX+eqrr5g2bZpiWaKiovD39+epp55i9erViuUQ+nF7u6Bhw4bx3XffERQUxM6dOzlx4gSXLl26a9efxx57jJ49ezJ48GApevQsPDycjh070rp1a44cOaJ0HCFEBZKCUpSrgoICvLy8SE5OZv78+bzxxhtKR6JGjRpoNBquXbumdBRRRrNmzWL+/Pns2rWLHj16/Of5nJwc/vzzT7Zv386xY8dISEi4o+uPpaVlSdef260lPT09K/ItVDo9evRgz549bNmyhX79+ikdRwhRQaSgFOVGo9HQsGFDEhISeOutt/jggw+UjgTAlClT+O6779i/fz8dOnRQOo4og8aNG3Pu3Lk77qm8n7y8PIKDg+/o+nP9+vWS5293/fHz8yvp+uPj41Me8Sul7OxsatSogb29PVevXpUFOkKYCCkoRbnQarX4+flx9uxZg1tVfXuaNDAwkO3btysdRzyi29sF+fn5cfLkyTKdS6PRsGPHDoKDgzly5EipXX8aN258R9cfcXe3N5p/7bXX+Pjjj5WOI4SoAFJQCr3T6XQ0b96cU6dOMWnSJL777julI/1H3bp1SUlJIS8vT0ZQjFRQUBCDBw/mgw8+4K233tL7+bVaLaGhoXd0/cnKyrqj64+zszM+Pj506NCBgQMH0rZtW/nzxK3PAFdXVzIzM0lLS5MFUUKYACkohV7pdDoCAgI4cuQIo0ePZtWqVUpHuqv33nuPOXPmsGbNGkaOHKl0HPEIBgwYwJYtWyp0o3qdTsfBgwfZtGkTBw4c4OzZs2RkZNzR9cfR0fGOrj9du3Y1ySLz9r6vXbp0Ye/evUrHEUKUMykohV51796dkJAQBg8ezIYNG5SOU6q8vDzs7Oxo2bIlERERSscRj8DR0RFzc3PS0tIUzaHT6Uq6/uzfv5+YmJhSu/60bduW/v37ExgY+FCtJY1VQEAAhw4dIjQ0lM6dOysdRwhRjqSgFHrTv39/goODjebexKZNmxIdHU1+fv5dW/oJw5WcnEzt2rUZPnw4f/zxh9Jx7io6OpqNGzcSFhZGdHT0f7r+2Nvb39H1p3///lhbWyuYWP9SUlKoXbs2NWvWJDk5Wek4QohyZHrzMKJcjBgxguDgYDp27GgUxSTA9OnT0el0fP3110pHEQ/p9u/ZlClTFE5SuiZNmjB79my2b99OUlISN2/e5Pz583z66af069cPBwcHTp8+zdKlSxk+fDg2NjbY2dnh5+fH2LFj+fXXX8nNzVX6bZSJq6sr//vf/7hy5Qrz5s37z/M3CrVEJ1/jRGIW0cnXuFGovctZhBDGQEYoRZmNGzeOn376iZYtW3LkyBGjuV9Mp9NhZWVFvXr1iI2NVTqOeAi+vr7Ex8c/1HZBhiopKYmNGzeye/duTp06xeXLlyksLCx53sbGBg8PD5o3b05gYCCDBg0yqkUuOp0OJycnbty4QWZmJlduFLP6cCIhZ9NIzMzjnz+AVICHoy3dfFwY3dYD75pVlYothHhIUlCKMpk2bRrffPMNTZo04dSpU0ZTTN7WuXNn9u3bR1ZWFg4ODkrHEQ/g9nZB/v7+nDhxQuk45SI9PZ2NGzeyY8cOTp48SVJS0h1df6ytralduzbNmjWjR48eDBkyBFdXVwUT39u6desYNf4FGo5+lxv2HpipVRTpSv/Rc/v5Tg2c+XCIP+6OthWYVgjxKKSgFI/s9ddfZ8GCBTRo0ICYmBijXGSwdetW+vXrx8yZM/nss8+UjiMewIYNGxg6dChz585l9uzZSsepMDk5OSVF5vHjx0lMTLxr15/HHnuMbt26MXToUDw8PBRM/P/WRCTyxh/HKUaFyuzBPyfM1CrM1SreG9iEUa0N470IIe5OCkrxSG5vu+Pu7s65c+eMelFLlSpVqFatmiwaMBK3F3/JqPL/d/0JDg7m6NGjXLx48T9df1xdXUu6/gwbNgxvb+8KzfhNSByf7ij7LSWvBDbkf90qNrsQ4sFJQSke2ieffMJrr72Gq6sr8fHx2Noa93TUkCFD2LhxI+fOncPLy0vpOOI+qlevjqWlJampqUpHMUgajYZt27axdevWkq4//+xbb2ZmhouLS0nXnyFDhtC0adNyybImIpE31kfq7XwfD/VnpIxUCmGQpKAUD2Xx4sVMnToVJycnzp8/j729vdKRyuzUqVM89thjBr0Ru7glKSkJd3d3nnjiCX7//Xel4xgNrVZLSEgImzdv5tChQ5w7d+6uXX8aNWpEhw4dGDRoEK1bty7TPdGXMvPo+UUohVrdf57LjdxFzpEN3MxMhqKboFJjZueIU9/p2NRvUeo5rczV7JrRRe6pFMIASUEpHtjPP//Ms88+i4ODA3FxcTg7OysdSW+cnZ3RarV39G8Whuf2fbshISF07dpV6ThGTafTceDAgZKuP7GxsaSnp5cUmbe7/jRs2JCAgAAef/xxOnfu/MBF5tPLDnPgfMZdF98kffMMRTeysHCui0XNehRdz6Aw8RQUF+M8ZBZVfNrf9ZxmahXt6zuxcnzbR3/jQohyIQWleCBr165lxIgRVKlShbNnz+Lm5qZ0JL16/vnnWbJkCQcOHCAgIEDpOKIUjRo14sKFC3dsqyP0R6fTcfz4cYKCgu7o+vPP1pK3u/60a9eOAQMG0KNHj/8syItLvU6vhWGlXifnxFbsmnRBbfn/I435F46T9ts7mFVzoc6UH++Zc9eMzjRwkS2FhDAkUlCK+woODmbAgAFYW1sTExODp6en0pH07nbnlT59+rB161al44i70Ol0WFhY0KxZM44dO6Z0HJMSFRV1R9eftLS0/3T9qV+/Pq1bt6Z///5E6Ory69HL99wa6G4SPx0KgMcr60s9xkyt4um2nswZ2OTR3owQolwY3z4vokLt2bOHxx9/HEtLS/76669KWUwCuLm54eHhQUhIiNJRRCk2bNiATqfjiSeeUDqKyfHz88PPz++Ox+Lj41m/fj0hISFERUURHR3NyZMnWbJkCW6TfsCi+sPNYuh0OoqLtKitq9zzuCJdMSGxacxBCkohDIlx7UItKtTBgwcJDAzEzMyMI0eOVPh2IxVt7NixFBYWsnbtWqWjiLtYunQpAFOnTlU4iQDw8vLi1VdfJTg4mMTERDQaDZcuXeLThV9j4VDroc+XtWMxFOuw8Wpz32MTM/KkTaMQBkamvMVdnTx5kjZt2lBcXMyBAwdo3bq10pHKXV5eHnZ2drRu3ZrDhw8rHUf8i4ODA9bW1qSkpCgdRdxDdPI1+n+9/6FekxcfwdU/3kNlaUOd6atRm99/X9st0zrSxK3ao8YUQuiZjFCK/4iJiaFdu3YUFRWxe/dukygmAWxtbWncuDHHjh274/4wobzExESuXbtGt27dlI4i7kNzl22C7nl86gWurpsLKjU1n5r/QMXko1xHCFG+pKAUd7hw4QItW7bk5s2bBAcH07lzZ6UjVahp06ZRVFTEN998o3QU8Q9ff/01AC+88ILCScT9WJo/+I8V7bWrXFn5MuiKcB46GyvXBuVyHSFE+ZMpb1EiKSmJRo0akZeXx7p16xgyZIjSkSqcTqfDysoKLy8vzpw5o3Qc8TcfHx8uXrwo2wUZMJ1Ox+bNm1n28ypOej+DSqW69/EFuSQteo5iTR6OfV6garO+D3wtFRA1pzdVrGRdqRCGQr7iCQDS09Np0qQJN27cYOXKlSZZTMKtjiFt27bl7Nmzssm5gdDpdJw7dw5/f3+lo4h/iYqKYurUqTRo0AALCwsGDRrEpvV/oMtJu+frdFoNl5dMpliTR7WOTz1UMQng4WQrxaQQBkYKSkF2djY+Pj7k5OSwZMkSRo8erXQkRb3xxhsAfPjhhwonEXBrU32dTseIESOUjmLy0tPTmTdvHq1atcLGxgZ/f38WL17M5cuXad68OXPnzuXq1auM79MWM3XpI5QpK15BdyMbta0DRblZZGz79o5/7sVMraJbQxd9vzUhRBnJlLeJy83NxcvLi7S0NBYuXMiLL76odCSDYGtrS/Xq1bl8+bLSUUxenz592L59O9euXasUveONiVarZc2aNaxatYojR46QlZUF3BrJr1u3LoGBgUyZMoWmTZve8br7dcpJ/GIExYV5pT7v+cbme+aSTjlCGB4pKE1YQUEBDRo04PLly8ydO5fZs2crHclgDBo0iE2bNnHx4sVKu5m7sXBwcMDGxoYrV64oHcUkhIeH88MPPxASEkJSUlJJb+8aNWrQoUMHnn32WR5//PH79vQe8Ok2Iq9qUKnN9JZNenkLYbhkyttEabVaGjduzOXLl5k1a5YUk//y7rvvAvDOO+8onMS0JSQkyHZB5SwxMZFZs2bh7++PpaUlHTt2ZMWKFWRmZtK+fXsWLlzI9evXSUtLY8OGDQwaNOi+xeTs2bPZPm8cFGkB/Y1ZmKtVfDhE7qUVwhDJXc0mSKfT4e/vz4ULF5g+fTrz5s1TOpLBadGiBY6OjmzatEnpKCbtq6++AmS7IH3Ky8vj559/5rfffuP48eNcv34dAHNzc7y9venfvz9Tp06lXr16j3Turl27EhERgaurK6/2qMunYfobWX5/YBPcHW31dj4hhP5IQWlidDodLVq04MyZM0yYMIEvv/xS6UgGa8iQISxbtozDhw/Ttq1MsSnhzz//xMrKig4dOigdxWjpdDq2b9/Ojz/+yP79+0s6DalUKtzc3Hj88ceZOHEiXbt2LdN1jh49So8ePcjJyaF///5s2rTp1kimdRyf7ogt8/t4NdCHka09ynweIUT5kHsoTYhOp6NDhw4cOnSIJ598kl9++UXpSAYtKSkJd3d3+vbtS3BwsNJxTI5Op8PCwoLmzZtz9OhRpeMYlZiYGBYvXsy2bds4f/48RUVFAFSrVo3WrVvz1FNPMXr0aCwtH6wrzf189NFHzJo1C5VKxTfffMOUKVPueH5NRCLvbopGqyumSPfgP3LM1CrM1SreH9hEikkhDJyMUJqQwMBADh06xKBBg6SYfAB16tTB3d2dkJAQpaOYpD/++AOdTseTTz6pdBSDl52dzQ8//MC6deuIjIwkPz8fACsrK5o2bcqgQYOYNGkSrq6uer2uRqMhMDCQ0NBQHB0d2b9/P76+vv85blRrDzp4OTNrQyT7zqVjplbds7C8/Xz7+k58OMRfprmFMAIyQmkiHn/8cTZv3kzPnj3ZuXOn0nGMxuzZs/nwww9Zv369yW72rpTevXuzY8cOrl+/jp2dndJxDIpWq2XdunWsWLGCQ4cOkZmZCdzazsfT05OePXsyefJkWrRoUW4ZoqOj6dy5M5mZmXTr1o1t27Y90IhnXOp1Vh9OJCQ2jcSMvDuW7BQXF1PXuQrdGrowpp2HbA0khBGRgtIEjBo1it9++4327dsTHh6udByjkpubi729PW3btuXgwYNKxzEp1apVw9bWVrYL+ltERASLFy9mz549JCYmlmzn4+zsTPv27XnmmWcYMmTIfVdg68M333zDiy++SHFxMR9//DGvvvrqI53nRqGWixk30Gh1fDj3fdb99B3JiRf0PpIqhCh/MuVdyU2YMIHffvuN5s2bs2/fPqXjGB07Ozt8fX2JiIhAq9Vibi5/ZSpCQkICOTk5PP7440pHUUxycjKLFy9m06ZNnDlzBo1GA9zadL9du3YMHz6cCRMmVOhm71qtloEDB7J161bs7e0JCQkp0yhoFStzmrhVA2Bwl1asXVLApk2beP755/UVWQhRQWQfykps+vTpLFu2DF9fX44ePVohIxeV0QsvvEBRURGLFy9WOorJuL37wLRp0xROUnEKCgr44Ycf6N69O9WqVaN27drMnTuX6Oho6tWrx4wZM4iNjeXGjRscOHCAmTNnVmgxGR8fT+3atdm6dStt27YlNTVVr1Pq/fv3B2Dv3r16O6cQouLIlHcl9eabb/LRRx9Rv359zp49KyNrZaDVarG2tsbb25uYmBil45gEb29vLl26REFBgdJRyo1Op2P37t0sW7aMsLCwO6b2a9WqRefOnRk/fjw9evRQ/Mvg8uXLmThxIjqdjrfeeov333+/XK5jbW2Nl5cX0dHR5XJ+IUT5kSqjEpo7dy4fffQR7u7uREdHSzFZRubm5rRp04ZDhw6Rk5Mj/aTLmVar5fz587Rs2VLpKHoXFxfH4sWL2bp1K3FxcSXb+djb29OtWzdGjRrFM888g7W1tcJJb9HpdIwYMYJ169ZRpUoVtm3bRseOHcvteq6uriQmJpbb+YUQ5UcqjUrm888/5+2338bV1ZUzZ84YzA8mY/fGG28waNAg5s+fz/z585WOU6nd3i5o1KhRSkcps5ycHJYuXcratWv566+/yMvLA8DS0pImTZowcOBApkyZgpubm8JJ/yspKYmAgACSkpJo2rQp4eHh5b7avnHjxmzdulXuVxbCCMmUdyXy/fffM3nyZJycnDh37hwODg5KR6pUbG1tcXR0JCkpSekolVqvXr3YtWuXUW4XpNPp2LBhAytWrODAgQOkp6cDt7rSeHh40L17d6ZMmULr1q0VTnpvv//+O2PGjOHmzZvMmDGDzz//vEKuO2/ePN566y127dpFjx49KuSaQgj9kFUalcSqVauYPHky1apV48yZM1JMloPu3btz+fJlmZIrZ4cPH6ZWrVpGU0weP36c559/nvr162NhYcHw4cPZtGkTOp2Ofv36sWbNGjQaDRcvXuTHH3806GJSp9Px7LPPMnLkSMzMzNi2bVuFFZNAyar+bdu2Vdg1hRD6IXMKlcC6det45plnqFKlCqdPn8bZ2VnpSJXSnDlz2LJlC++++y7Lly9XOk6l8M99CC3N1ahy07l+/TqDBw9WOlqp0tLSWLx4MUFBQZw+fZrCwkIAbGxsaNWqFcOGDWPChAk4OjoqnPThpKWl0b59e+Lj4/Hx8eHAgQMV/h6aNm2KSqXi8OHDFXpdIUTZyZS3kdu6dSv9+/fH2tqamJgYPD09lY5Uqd3+AXu7M4l4eCWdUs6mkZh5Z6cUiou5mX2Fga28mPl4a7xrKt8pRaPRsHr1an755RciIiK4du0aAGZmZtSvX58+ffowZcqUu7YcNBbBwcEMHTqUwsJCJk6cyA8//KBYFicnJywtLWVDeyGMjBSURmzv3r306NEDCwsL/vrrL3x8fJSOVOmNGzeOn376iYiICFq1aqV0HKNyKTPvoXs5d2rgrEgv571797JkyRJCQ0NJTk4u6Urj6upKx44dee655+jdu7fi2/now7Rp0/jmm2+wtLTk999/Z9CgQYrmad26NSdOnECr1SqaQwjxcKSgNFKHDx+mY8eOqFQqjhw5QrNmzZSOZBISExPx9PSkf//+bN68Wek4RmNNRCLvbopGqyu+ZyH5b2ZqFeZqFe8NbMKo1h7lli8hIYFvv/2WLVu2EBsbW1LMVK1alRYtWjBy5EjGjh2LrW3FFrblKTs7m44dOxIdHY2npyeHDh0yiJaHU6ZM4bvvvuPixYsy4yKEEZGC0gidOnWKVq1aodPpCA8Pp23btkpHMil16tQhMzOzZAsYcW/fhMTx6Y7YMp/nlcCG/K+btx4S3erRvnz5cn7//XdOnDjBjRs3ALCwsKBRo0YMGDCAyZMn4+FRfkWskvbu3Uu/fv3Iz8/nqaeeYuXKlQYz2rpu3TqGDx/OV199ZVKdkoQwdobxCSIe2NmzZ2nTpg1FRUXs2rVLikkFPP300+Tn5xMUFKR0FIO3JiJRL8UkwKc7Yvkt4tFW2Ot0OjZt2sTQoUOpWbMmVatWZfr06YSHh+Po6MgzzzzD/v370Wg0nDp1ig8//LDSFpNvvvkm3bp14+bNm6xatYrVq1cbTDEJ0LdvXwBCQ0MVTiKEeBgyQmlEEhIS8PX1paCggM2bN9OvXz+lI5mknJwcHBwcaNeuHQcOHFA6jsG6lJlHzy9CKdTq7nts6pq3KLh4Esws8Hx1Q6nHWZmr2TWjywPdUxkVFcWiRYvYsWMHFy5cQKe7laN69eq0adOGMWPGMGrUKJPZQDsvL4/OnTtz7NgxatWqxcGDBw12StnW1hZ3d3fOnj2rdBQhxAMyjU/SSiA5ORk/Pz8KCgr4/fffpZhUkL29PT4+Phw5ckQ6etzDrA2RaB/gfsnC5NhbxeQD0OqKmbUhkpXj/zsyn56ezvfff8+GDRuIjo4u6QNubW1N8+bNGTJkCJMmTTLJbbUOHz5Mz549yc3NZdCgQaxfv96gRiX/zc3NTRoICGFkDPcTRZRIT0+ncePG5Obm8tNPPzF8+HClI5m8qVOnUlRUpOj2KoYsLvU6+86lP9ACnKsbP0RtbYfK6v6jjkW6YvadS+dc2nW0Wi2rVq2iT58+ODo6UqNGDd566y1OnDhB7dq1mTJlCpGRkeTn53P06FFmz55tksXkvHnzCAgIID8/n++//56NGzcadDEJ4OfnR15eXsmXAiGE4TPsTxVBdnY2Pj4+XLt2je+++45nnnlG6UiCWytRzczM+Pbbb5WOYpBWH07ETK2673E5RzdRlJOOY5+HWHxRrKPHpPewtLTk6aefZvv27VhYWDBkyBCCgoK4efMm586dY9GiRfj5+ZXhXRg3jUZDp06deOutt3ByciI6Oprnn39e6VgPpFOnTgDs2rVL4SRCiAclBaUBy8vLo1GjRmRmZvLZZ58xadIkpSOJv5mbm9O6dWtiYmLIzc1VOo7BCTmbdt/RSZ1WQ1bIcsyd3KnSqMODn1ylRufaiA4dOvDVV19x/fp1UlNTWb9+PQMHDjT40beKcOrUKWrWrMn+/fvp2bMnV65cMap9agcOHAjAjh07FE4ihHhQ8slroAoKCvDx8SE1NZUPPviAmTNnKh1J/Mtrr71GcXEx8+fPVzqKQckt1JKYef8tlTI2fw5FN6kxZNZDX8PcoRbbdoUwbdo0o+n5XVG+/PJLmjdvTk5ODp999hk7d+40uvt8vb29UavVREREKB1FCPGApKA0QFqtliZNmpCUlMQbb7zBW2+9pXQkcRdDhgzB2tqalStXKh3FoCRk3OB+d05qMi+Td2Y/Nl6tsXR2f+hrFAMXM248Ur7KSqvV0rt3b1566SWqVq3KsWPHjPqLqJOTE/Hx8UrHEEI8ICkoDYxOp6Np06acP3+eadOmyeiXgevevTuXLl2SFan/oHmAbYKurp8LajOcB71artcxFXFxcbi5ubFjxw7at29PSkqK0XfPatCgARkZGUrHEEI8ICkoDYhOp6NVq1bExMQwbtw4vvrqK6UjifuYM2fOHf82dVqtllMnj9/zmPwLx9GmX8KmQTs0KRcoSIymIDEadDooLqYgMZqbWVfuey1Lc/n4Ali2bBm+vr6kp6fz3nvvER4ejrW1tdKxyqx169bodDrZi1IIIyEbmxuQjh07Eh4ezsiRI1mzZo3SccQDql69Omq12qRGU3Q6HcePH2f79u0cOnSIM2fOkJycTF5eHioLa9xn/oFKdfdV3jlHNpK1Z+k9z2/hUh+350r/QqUCoub0poqVcd0bqE86nY7hw4ezYcMG7Ozs2LFjBwEBAUrH0pvg4GD69+/PggULePXVRx/JFkJUDNP9NDYwvXr1Ijw8nAEDBkgxaWQGDhzIihUrOH78OC1atFA6jt7FxMSwdetWDh48SHR0NElJSVy/fv2OY2xtbXFzc6NRo0a0a9eOTcXmpN4ouuv5rL1aYZ+X/Z/HcyKCQFeEfduhWLreu2e3h5OtSReTiYmJtG/fnsuXL9O8eXPCwsIq3eKknj17ArB//34pKIUwAjJCaQAGDx5MUFAQ3bt3Z/fu3UrHEQ8pISGBunXrMnDgQKPu752YmMjWrVvZt28fUVFRJCYmkp2dzT8/IqytralZsyYNGzakdevW9OrVi44dO/5nFfGcTdGsPJzwQBubl1z/ixEUa2/es/UigJlaxdNtPZkzsMnDvcFK4rfffuPpp5/m5s2bvPrqqyxYsEDpSOXGzs6OmjVryuIcIYyA6X7FNxBPPfUUQUFBtGvXjp07dyodRzwCT09P3NzcjOb3Lz09nW3bthEaGsrJkye5ePEiWVlZFBX9/4iipaUlNWrUoGnTprRo0YLu3bvTvXt3bG3v380GYHRbD346eLFc8hfpihnTzqNczm3IdDodzz77LCtXrsTGxoZt27bRvXt3pWOVK3d3dy5evKh0DCHEA5CCUkETJ07k119/5bHHHiM8PFw2ZDZio0eP5pNPPmHz5s0MGDBA6TgA5Obmsn37dkJDQzl+/Djx8fGkp6ej1WpLjjE3N8fR0ZHWrVvTvHlzunbtSmBgIA4ODmW6tnfNqnRq4MyB8xkPPErpMeP3+x5jplbRvr4TDVyqlimfsUlLSyMgIIDz58/j6+vLgQMHyvx7ZAz8/f05c+YMubm5lW5KX4jKRqa8FTJjxgwWLlxIo0aNiI6OlmLSyGVnZ+Po6Ej79u3Zv39/hV5bo9EQEhLC7t27OXbsGHFxcaSlpVFYWFhyjFqtpnr16nh6etK0aVM6d+5M3759cXV1LbdclzLz6PlFKIV62t6nuLgYlU7LrhldaFCrul7OaQw2bdrEiBEjKCwsZPLkySxevFjpSBVm0aJFvPDCC/zxxx8MHz5c6ThCiHuQglIBs2bNYv78+dSrV48zZ85gaWmpdCShB40aNSI+Pp7CwsJy+YKg0+k4ePAgO3fu5PDhw5w9e5aUlBTy8/NLjlGpVNjb2+Ph4YGfnx/t27enb9++eHl56T3Pg1gTkcgb6yP1dr6M4C8xSzjC3r17jX6fxQcxdepUFi9ejJWVFb///ntJS0JTkZSUhLu7O5MmTeK7775TOo4Q4h5kyruCzZs3j/nz51O7dm1Onz4txWQlMnnyZGbMmMGSJUvK1Hddp9Nx6tQpduzYwcGDBzl9+jSXL1/mxo07O8PY2dnh4eFB48aNCQgIoHfv3vj5+RnUaPeo1h6k5xby6Y7YMp/r1UAftK79mTlzNy1atODDDz/kjTfe0ENKw5OdnU1AQABnzpyhXr16HDp0CBcXF6VjVbg6depgbm7O0aNHlY4ihLgPGaGsQAsXLmTGjBm4uLgQHx8v9wRVMlqtFmtraxo1akRUVNQDvSY+Pp7g4GAOHDhAVFQUly5dIicn546V1TY2NtSqVQsfHx/atm1LYGAgbdu2NajC8X7WRCTy7qZotLrih1r5baZWYa5W8f7AJoxsfWshTnR0NJ07dyYzM5NOnTqxa9euSvXFbM+ePQwYMID8/HyefvppfvrpJ6P6vdY3Nzc3CgsLTWqfVyGMkRSUFeSHH35g0qRJODo6Eh8fbxI31Juitm3bEhERQW5u7h0ropOTk0u25Dl16hQJCQlkZ2ej0/3//YVWVla4uLjQsGFDWrZsSc+ePenSpUulKZYuZeYxa0Mk+86lY6ZW3bOwvP18pwbOfDjEH3fHO1eXa7Va+vTpw+7du3FwcCAkJKRSTIG/9tprfPLJJ5ibm7Nq1SpGjhypdCTFde3albCwMLRarUkX1kIYOikoK8Dq1asZM2YM9vb2xMXFmeTUlan46aefGDduHC1atMDCwoILFy6QmZl5x8pqCwsLnJ2d8fLyokWLFnTt2pVevXqZzIh1XOp1Vh9OJCQ2jcSMPP75AaTi1qbl3Rq6MKadx31Xcy9cuJCXX34ZgI8++shoN8DOzc2lc+fOnDhxgtq1a3PgwAE8PExva6S7ef3111mwYAEnTpyoFF8ahKispKAsZxs2bGDYsGHY2tpy5swZ6tSpo3QkoQd5eXns2rWLvXv3cuzYMc6dO8fVq1e5efNmyTFmZmY4OjpSt25dmjVrRpcuXejduzfOzs4KJjcsNwq1XMy4gUarw9JcTV2nKg/dAScqKoouXbqQmZlJly5d2LFjh1GN6h48eJDAwEByc3MZMmQIa9eulZG4f9i7dy/dunXjgw8+4K233lI6jhCiFFJQlqPt27fTr18/rKysiI6Opl69ekpHEg9Jq9USFhbGrl27iIiIIC4ujtTUVAoKCkqOUavVVKtWDU9PT/z9/Tl+/DjR0dFcvnwZNzc3BdObDo1GQ9++fdmzZw8ODg6EhobStGlTpWPd13vvvcd7772HWq3mu+++Y8KECUpHMjharRYLCwv69OnD1q1blY4jhCiFFJTlJCwsjO7du2NmZsbJkyfx9fVVOpK4B51Ox7Fjx9i+fTuHDh3izJkzXLlyhby8vJJjVCoVVatWpU6dOjRp0oQOHTrQp08ffHx87jjXwYMHad++PRMnTuSHH36o6Ldi0j7//POSae8FCxaUTIcbmoKCArp3787BgwepUaMG4eHheHvfu3+5KbO3t8fR0VG65ghhwKSgLAcRERG0b98elUrFkSNH5L4fAxMdHc327ds5cOBAyUji9evX7zimSpUquLm54evrS7t27ejduzfNmjV74KlIBwcHzM3NSU9PL4+3IO7h1KlTdO3alaysLLp27cr27dsNagr85MmTdO3alWvXrtG7d282b978n17o4k7+/v7ExcXdMTMghDAs8immZ1FRUXTo0IHi4mLCwsKkmFRQQkICwcHB7N+/n6ioKBITE7l27dodW/JYW1vj6upKQEAAbdq0oVevXrRv377MP+AHDhzIypUrOXXqlFFMvVYmTZs2JSUlhT59+hASEoKrqythYWH4+fkpHe2OEdSFCxfy4osvKpzIODz22GNERUWRnZ0tO2QIYaBkhFKP4uLi8Pf35+bNm+zcuZPu3bsrHckkpKWlsW3bNsLCwjh58iQJCQlkZWVRVFRUcoylpSU1atTA29ubVq1a0a1bN7p37461tXW5ZLpw4QL169dn8ODBbNiwoVyuIe7vs88+47XXXgPgk08+YebMmYrk+Oc2R9WrVzeYAtdYLFu2jAkTJrBy5UrGjBmjdBwhxF1IQaknCQkJ+Pr6UlBQwKZNmxgwYIDSkSqdnJwcdu7cyd69ezl+/Djnz58nPT39ji15zM3NcXZ2pl69ejRv3pxu3boRGBiIvb19hed1c3Pj2rVr/+lwIyrWqVOn6NKlC9nZ2XTv3p2tW7dW6BT42bNn6dChAxkZGZVyI/aKkJaWRs2aNXn22WdZvny50nGEEHchBaUeJCcn4+Pjw40bN1izZg0jRoxQOpJRKygoICQkhD179nDs2DHi4uJIS0tDo9GUHKNWq6levTp169aladOmJVvyuLq6Kpj8Ti+//DKff/45wcHB9O3bV+k4Jk2j0RAYGEhoaCiOjo6EhoZWyAjh999/zwsvvIBOp+ODDz5g9uzZ5X7NysrS0pLGjRtz8uRJpaMIIe5CCsoySk9Px9vbm+zsbH766SfGjh2rdCSjodVqOXToEDt27ODIkSPExsaSkpJCfn5+yTEqlYpq1arh7u6Ov78/HTt2pE+fPkaxBVN2djbVq1enU6dOhIWFKR1HcGva+/XXX0elUvHZZ5/x0ksvlct1dDodQ4YMYdOmTVStWpXdu3fTunXrcrmWqXB3d+f69etkZ2crHUUIcRdSUJZBTk4O9evXJyMjg2+//ZapU6cqHckg6XQ6Tp06xbZt2zh06BCnT58mOTn5P1PBVatWpXbt2jRu3Jj27dvTp08fmjRpolBq/WjYsCEXLlygsLBQNqs2ECdPnqRbt25kZ2fTo0cPtm3bptdV1gkJCQQEBHDlyhVatmxJWFjYHW04xaPp1asXu3fvlhaMQhgoWeX9iPLy8vDx8SEjI4MFCxZIMfm3uLg4goODOXjwIFFRUVy6dInr16/fsbLa1taWWrVq4ePjQ9u2benduzetW7eulD8kJk2axCuvvMKPP/4om1YbiGbNmpGamlpSoNSsWZOwsDC9fHlZtWoV48aNQ6vV8uabb/Lhhx/qIbEACAgIYNeuXRw+fJiAgACl4wgh/kVGKB+BRqOhQYMGXLp0iTlz5vDuu+8qHanCJScnExwczL59+4iMjCQhIYHs7Gx0Ol3JMVZWVtSsWZOGDRvSunVrevToQadOnUxqQYJGo8HGxoYmTZpw6tQppeOIf/noo4+YNWsWKpWKzz///JG38dHpdIwZM4Zff/0VW1tbtmzZQteuXfUb1sQdPnyYdu3a8dZbb/HBBx8oHUcI8S9SUD4krVaLr68v586d49VXX2XBggVKRypXmZmZbN++ndDQUE6cOMGFCxfIzMy8Y0seCwsLnJ2dadCgAS1btqRbt2707NlTpvn+1rp1a44dO0Zubq78PzFAx48fp3v37ly7do1evXoRHBz8UFPgKSkptGvXjoSEBPz8/Ni3b5/slVgOdDod5ubmdO/enV27dikdRwjxLyZfUN7IyCblWCTa/ALMbaxxbelPFSeHux6r0+lo2rQp0dHRTJ06lW+//bZiw5ajvLy8ki15jh07xrlz50hPT+fmzZslx5iZmeHk5ES9evVo1qxZycpqR0dHBZMbvt9++41Ro0aZ7Gi2MSgoKKBXr17s378fJycn9u3b90DtUjds2MCoUaPQaDT873//4+uvv66AtKarevXqVKlShaSkJKWjCCH+xSQLyoSwCFIWLKTOob3Uykjmn3fu6YArTm4kteuK62sv4dn51spMnU5HmzZtOHbsmFHvhabRaNi3bx+7du3i6NGjxMbGkpqaSmFhYckxarUaBwcHPD09adq0acnK6jp16iiY3HjpdDpsbW1xdXWVXsQGbv78+cyePRuVSsXChQuZNm1aqcc+//zzLFmyBCsrK9avX0+/fv0qMKlpat68OdHR0XdsISaEMAwmVVAmnzhNxphx+J8+glalxrxYV+qxt5+PbNwGp1XLGfXiZPbt28fw4cP5448/KjD1o9HpdERERLB9+3YOHz7MmTNnSElJIS8vr+QYlUpF1apVcXd3x8/Pjw4dOtCnTx+8vb0VTF459e7dmx07dnDlyhWD2itT/Nc/p8ADAwPZsmXLHVPgmZmZBAQEEBsbi5eXF4cOHcLZ2VnBxKbjueeeY/ny5aSmpuLi4qJ0HCHEP5hMQXlk9sc0XfAO5kXaexaS/6ZVqdGamfNKzQZceKwuW7ZsKceUjyY6Oppt27Zx4MABTp8+TVJSErm5uXccU6VKFWrXro2vry/t2rWjT58+NG3atFKurDZE4eHhdOzYkcmTJ7N48WKl44j7KCgooGfPnoSHh+Ps7ExYWBi+vr7s3LmTgQMHUlBQYNQzFcZq9erVjBkzhiVLlsiuCUIYGJMoKA+On0nAj19QDKge4fW3X3fwuRkELPtcv+EewoULF9i6dSvh4eFERkZy6dIlrl27dseWPDY2Nri6upZsydOzZ0/atWun1332xKOpVq0aFhYWpKenKx1FPKB58+bx9ttvo1Kp6Nq1K3v27MHCwoJffvmF4cOHKx3P5NxuFvDUU0+xevVqpeMIIf6h0heUR2Z/TJsP39Dv+ea+prfz3U1aWhpbt24lNDSUU6dOcfHiRbKysv6zJU+NGjXw9vamVatW9OjRgy5dumBtbV2u2cSjGz16NL/88guRkZEV0vZP6EdYWBjdunVDp9NhZWXFmTNnqFu3rtKxTJa1tTUNGjQgKipK6ShCiH+o1AVl8onTOLZpjpVW85+RySDgBSAV0HJrBLIqMB0obYezYqDQ3JLMIydwa964zPlycnLYsWMHISEhnDhxgvPnz5ORkYFWqy05xtzcHGdnZ7y8vGjevDldu3alV69e2Nvbl/n6omLFx8fToEEDhg4dyrp165SOIx5AeHg4vXv35saNGzg6OpKZmUmNGjXYt28fPj4+SsczSXXr1iUzM5OcnBylowgh/qFSF5SRTdriG3P0rvdMvgd8DfgD7kAusBvIAUYDq0o5p1alJsa3Ff7Rhx84R0FBAXv27CEkJISjR48SFxfH1atX71ipaGZmRvXq1albty7NmjWjU6dO9OnTR248r2Rq1arF9evX/3OPqzA877zzDnPnzkWtVrNs2TLGjh3L3Llzeeedd1CpVHzzzTdMmTJF6Zgmp1+/fmzdupWbN2/KrTxCGJBKW1AmhEXg2aXNQ71GA1Tj1tZBhfc5NmFfBJ4dW93xmFar5cCBA+zcuZOIiAjOnj1LSkoKBQUFJceoVCqqVauGh4cH/v7+JYWjp6fnQ2UVxmnmzJl88cUX7Nixg169eikdR9xFQUEBXbt25fDhw7i4uHDgwAG8vLxKno+IiKBnz57k5OTQt29fNm3aJIVNBZo3bx5vvfUWu3fvpnv37krHEUL8rdIWlIcHjKZl8JqHWtENUBNIB4rucYxWpWZft0Ec6tmaQ4cOERMTQ3JyMjdu3LjjuKpVq1KnTh0aN25M+/bt6d27t176BQvjlZmZiZOTE126dGHv3r1KxxH/cvz4cbp160ZOTg79+vUjKCjorsViQUEB3bp149ChQ7i4uLB//37ZbquCnDp1iscee8wkOpUJYUwqbUF52bk2tTOS73tcGpAFXAa+4ta9lZ7Axfu87oJ9DernXAXA1tYWNzc3GjVqRLt27QgMDKRly5ayJY+4K29vbxISEigoKJA/IwZkwYIFvPHGG6hUKr788kv+97//3fc177//PnPmzEGtVvPtt98yadKkCkgq1Go1nTp1IjQ0VOkoQoi/VcqCMjc9C9sajjzIj+rGQMw/fl0b2AfUu8/rdMDuTVvo1jdQprvEQ1mwYAGvv/46S5cuZfz48UrHMXkajYY+ffoQEhKCo6MjYWFhDzWTcPjwYXr16sX169fvOaop9MfJyQlLS0uuXLmidBQhxN8q5fBI6vGoB35jnwIfAxMBF24Vijfu+Ypb1EB9q6ryg0M8tJdeegm1Ws1XX32ldBSTFxMTg5ubGyEhIXTt2pUrV6489G0pbdu2JSUlhbZt2xIcHEzt2rWJi4srp8QCoH79+rKfqxAGplIWlNr8gvsf9Ld+wGvAD9zaQqgQaMetwlKf1xHiNktLS5o3b05kZOQdrTBFxVq0aBF+fn5kZmYyf/58QkJCsLS0fKRz2dracujQId59912uXr2Kr68vP/zwg54Ti9tatWqFVqslMTFR6ShCiL9VyoLS3ObRN/fuy60Ryu3lfB1h2mbMmEFxcTGffvqp0lFMjk6nY8CAAbzwwgvY2dlx5MgR3nhDP80P5syZw8GDB7GxsWHSpEk8/vjjdzQkEPrRs2dPADZt2qRwEiHEbZXyHsobGdnYOFd/pGp5KLAB+BEYd4/jdEB+ehZVnBwe4SrC1Ol0OmxsbHBzc+PChQtKxzEZFy5coH379qSkpNCmTRtCQkKwtbXV+3Xy8vLo2rUrERER1KxZk/Dw8Du2HhJlk5eXR5UqVRg+fDh//PGH0nGEEFTSEcoqTg5ccXK75zHRd3ksD9j293/3vc81Eqq58Ok3X8oG1eKRqNVqOnfuzMWLF0lLS1M6jklYsWIFDRs2JDU1lVmzZnH48OFyKSbh1hT4kSNHePvtt0lLS8PHx4elS5eWy7VMka2tLTY2NkRGRiodRQjxt0pZUAIkteuKVlX62+sFOALdgLFAT6A6kA8MBFzvcW6tSs3Oai7MmTMHe3t7GjRowJw5c6S4FA/l7bffBuC9995TOEnlptPpGDVqFGPHjsXKyoqwsDDmzZtXIdd+//33CQ8Px8bGhokTJzJo0CCZAtcTNzc3kpKSlI4hhPhbpZzyhvt3ypkOrAayuTV9reJWQTkZeJAfNRdDj3A0LYEvv/ySI0eOlLRRrF+/PqNHj+aVV16Rftvivuzt7bG2tpZRynKSnJxMQEAAiYmJNG3alH379iny9zIvL48uXbpw9OhRXF1dOXDgAPXq3W9zMnEvgwcPJigoiMLCwkdeTCWE0J9KO0Lp2bk1kY3blDpK+RWQwa2OOMXcKiozuH8xqVWpiWzchrqdWzN8+HD27dtHfn4+a9eupXPnziQlJfHBBx9QrVo16tevz+zZs8nOztbjOxOVSf/+/bl69SrR0Xe7CUOUxbp166hbty6JiYm89NJL/PXXX4p9ybO1tSUiIoK33nqL1NRUvL29WbZsmSJZKotOnToBsGvXLoWTCCEAKK7ELh+PLs43tyzWQXGxHv7RQXG+uWXx5ePR97zuxo0bi7t06VJsZWVVzK16tbhu3brFb775ZnFWVlbFvHlhFM6cOVMMFA8fPlzpKJXK+PHji4Fia2vr4m3btikd5w779+8vrlKlSjFQPHjw4OKioiKlIxml2NjYYqB4+vTpSkcRQhQXF1faKe/bjsz+mDYf6mdLkJLzzX3tgY/ftGkTCxcu5MCBAxQWFgLg6enJyJEjef3113F0dNRbNmGcatasyY0bN+QeXD1IT0+nffv2xMXF0bBhQw4ePGiQf8dyc3Pp2rUrx44dkynwMjAzM6Nt27YcOHBA6ShCmLxKO+V9W5t5r3PwuRnAraHCR3H7dYfGz3yoYhJg4MCB7Nmzh4KCArZs2UL37t1JTU1lwYIFODk54enpyWuvvSZdH0zYqFGjuHHjBrt371Y6ilHbunUr7u7uxMXFMWHCBM6ePWuQxSSAnZ0dR48e5c033yQ1NZWGDRuyfPlypWMZHScnJ86dO6d0DCEEVO4p7386POuj4nxzy+KbKvVDTXPfVKmL880tiw/P/liveYKDg4t79uxZbG1tXTIt7u7uXjxz5sziq1ev6vVawrBdvXq1GCju1q2b0lGM1vTp04uBYktLy+L169crHeeh7Nu3r2QKfMiQITIF/hACAgKK1Wq10jGEEMUmMOX9T8knTpMxZhz+p4+gVakxLy59+47bz0c2boPTquW4NW9cbrm2b9/OZ599xv79+8nPzwegTp06PPHEE7zxxhu4uLiU27WFYfDy8uLSpUsUFBSgVlf6iQO9ycnJoWPHjkRGRuLh4cHBgwdxc7v3HrSGKDc3ly5dunD8+HFq1apFeHi4TIE/gBdffJGvvvqK2NhYvL29lY4jhEkzqZ9cbs0b4x99mITQIxzrN4okp9r/6dmtA5KcanOs3ygS9kXgH324XItJgN69e7Njxw7y8vLYtWsXvXv3JiMjgy+++IKaNWtSp04dXnzxRVJSUso1h1DOxIkTuXnzJitXrlQ6itEICwujVq1aREZGMmrUKC5cuGCUxSTcmgI/duwYb7zxBikpKTRs2JCff/5Z6VgGr3fv3oC0YBTCEJjUCOXd3MjIJuVYJNr8AsxtrHFt6W8w7RT37NnDJ598QlhYGHl5ecCtzXyHDRvGrFmzcHW91/brwphoNBpsbGxo2rQpJ06cUDqOwZs9ezbz58/HzMyM5cuXM2bMGKUj6U1YWBj9+vXjxo0bDBs2jN9//11GrUuh0WiwsrJi0KBBbNy4Uek4Qpg0ky8ojcXevXv55JNPCA0N5caNGwDUqlWLIUOGMHv2bKMdmRH/r0WLFvz111/cuHEDa2trpeMYpH/2yK7Mq6Nzc3Pp1KkTJ0+exM3NjQMHDuDp6al0LINkZ2eHq6urLM4RQmHytddIdO3alS1btpCbm8u+ffvo378/OTk5LFq0iNq1a1OrVi2mTp0qrciM2MyZM9HpdHz22WdKRzFIR48epVatWkRERDBw4EAuX75cKYtJuFUknThxgtdee43k5GQaNGjAihUrlI5lkOrUqUNycrLSMYQweTJCaeTCw8NZsGABe/bsKdnH0NXVlUGDBjFr1iw8PDwUTigelE6nw8bGhjp16hAfH690HIPy0UcfMWvWLFQqFd988w1TpkxROlKFCQsLo2/fvuTl5TF8+HB+++03mQL/hyeeeIK1a9dy48YNbG1tlY4jhMmSTyUj16FDB4KCgrh+/ToHDhxg0KBB5Obm8v333+Pp6UnNmjV5/vnnSUhIUDqquA+1Wk3Hjh05f/689Pb+m0ajoWvXrrz55ps4OjoSFRVlUsUkQOfOnbly5QrNmjVj7dq1eHh4kJiYqHQsg9GlSxfg1j6kQgjlSEFZiQQEBLBx40auX7/OoUOHGDx4MPn5+SxZsoS6detSs2ZNJkyYwIULF5SOKkoxe/ZsAD744AOFkygvOjqaWrVqERoaSo8ePUhJScHX11fpWIqwt7fnxIkTvPrqq1y+fBkvLy9Wr16tdCyDMHDgQEB6eguhNJnyNgFHjx5l/vz57Nq1i5ycHABq1KjBgAEDmD17Nl5eXgonFP9UtWpVbG1tSU1NVTqKYr755htefPFFiouL+eSTT3j55ZeVjmQw9u7dS//+/cnLy2PkyJH88ssvJj8FbmFhQbNmzYiIiFA6ihAmSwpKE3P8+HE+/PBDdu7cWVJcOjs7079/f2bPni2bAxuAESNG8Mcff3DmzBl8fHyUjlOhtFotAwcOZOvWrVSrVo29e/fSrFkzpWMZnJycHDp16sSpU6eoU6cO4eHhJn2/dK1atdBoNGRkZCgdRQiTZdpfa01QixYtWLt2LdeuXePEiRM88cQT3Lx5k59//pmGDRvi7OzM2LFjOXv2rNJRTdZ7770HwLvvvqtwkooVHx9P7dq12bp1KwEBAaSkpEgxWQp7e3v++usvZs6cSVJSkslPgTds2JCsrCylYwhh0qSgNGHNmjXj999/Jzs7m7/++ouRI0dSVFTEihUraNSoEU5OTjzzzDPExMQoHdWk+Pr64uLiwpYtW5SOUmGWL1+Oj48PV69e5d133+XAgQOyF+cD+Oyzz9i9ezcWFhaMGTOGJ598Ep2u9JaylVXbtm0pLi7m1KlTSkcRwmRJQSkAaNq0KWvWrCErK4vIyEiefPJJiouLWblyJY0bN8bR0ZHRo0cTHR2tdFSTMGLECHJzc9m7d6/SUcqVTqdj+PDhPPfcc1hbW7Nv3z7mzJmjdCyj0r17d1JSUvD392fNmjXUrVvX5Paj7dOnDwB//vmnwkmEMF1yD6W4p+joaD788EO2bt1aMqVUvXp1+vTpw6xZs/Dz81M4YeWUlpZGzZo16dGjR6VdvZqUlERAQABJSUk0a9aMffv2YWdnp3QsozZz5ky++OILLCws+Pnnn3nyySeVjlQhtFotFhYW9O3bl+DgYKXjCGGSpKAUDywmJob58+ezZcsWMjMzAXBwcKB3797MmjWLpk2bKpywcqlfvz6XL18mPz+/0q3i/f333xkzZgw3b95k5syZ0h1Ij3bv3s3jjz9Ofn4+Tz75JKtWrap0f37uxt7eHkdHRy5evKh0FCFMUuX/lBF64+vry4oVK8jIyODMmTM888wzmJmZ8dtvv/HYY4/h4ODAiBEjOHnypNJRK4Xx48ej0Wj45ZdflI6iNzqdjmeffZaRI0diZmbGrl27pJjUsx49epCcnIyfnx+//vor9erVM4kpcA8PD1JSUpSOIYTJkhFKUWZxcXF8+OGHbN68mfT0dODWaEGvXr2YNWsWLVq0UDihcSooKMDW1pbmzZtz7NgxpeOUWVpaGu3btyc+Pp5GjRoRHh6Oo6Oj0rEqtRkzZrBw4UIsLCxYuXIlI0eOVDpSuRk9ejS//PILWVlZODg4KB1HCJMjI5SizLy9vVm+fDlXr17l3LlzjBs3DisrK9atW0fLli2pVq0aw4YN4+jRo0pHNSrW1tY0bdqUkydPotFolI5TJsHBwXh4eBAfH8+kSZOIiYmRYrICfPHFF+zYsQNzc3NGjRrF6NGjK+0q8G7dugGY1O4IQhgSKSiFXnl5efHjjz+SlpbG+fPnmTBhAtbW1qxfv57WrVtjb2/PkCFDpKPFA5oxYwY6nY7PP/9c6SiPbNq0afTv35/i4mI2btzId999p3Qkk9KrVy+Sk5Np0qQJv/zyC/Xr1yc5OVnpWHp3uwXj7t27FU4ihGmSKW9RIRISEpg3bx5BQUGkpaUBYGdnR48ePXjzzTdp27atwgkNk06nw9raGg8PD86dO6d0nIeSnZ1Nhw4dOH36NHXr1uXgwYO4uroqHcukTZ8+na+//hoLCwt++eUXhg8frnQkvbK0tKRJkyacOHFC6ShCmBwZoRQVwtPTkx9++IHU1FQSEhKYPHkydnZ2BAUF0a5dO+zs7Hj88ccJDw9XOqpBUavVdOjQgfj4+JL7U43B3r17cXNz4/Tp04wePZr4+HgpJg3AV199xY4dOzAzM+OJJ57gmWeeqVRT4C4uLrLKWwiFSEEpKpyHhweLFy/mypUrXLp0iSlTplC1alU2b95Mx44dsbOzY8CAAezfv1/pqAbhrbfeAuCDDz5QOMmDef311+nWrRs3b97kl19+MZlta4xFr169uHLlCr6+vqxcuRIvL69Kszq6UaNGXLt2rVIVyUIYC/mUF4qqU6cOixYtKiku//e//2Fvb8+WLVvo1KkTVapUoV+/foSFhSkdVTE9evSgSpUq/Pbbb0pHuae8vDxatWrFggULcHNzIz4+3mQ21jY2Dg4OnD59mv/9739cvHgRT09P1q5dq3SsMgsICKC4uFju0RZCAVJQCoNRp04dvv76a5KTk7l8+TLTpk3DwcGBrVu30qVLF6pUqULfvn0rfTvCu+nTpw+pqamcPXtW6Sh3dfjwYWrWrMmxY8cYMmQIly5dwsPDQ+lY4j6+/vprtm3bhlqt5oknnmDs2LFGPbrXr18/QFZ6C6EEWZQjDF5KSgoff/wxf/zxB5cvXwbAxsaGTp068dprr9GjRw+FE5a/6Oho/Pz8GDVqFL/++qvSce4wd+5c3nnnHdRqNd999x0TJkxQOpJ4SJmZmXTo0IEzZ85Qr149Dhw4YJT3vOp0OszNzenRowc7d+5UOo4QJkUKSmFU0tLS+Oijj/jjjz9Kun/Y2NjQsWNHXn31VXr16qVwwvLj4uJCQUEBOTk5SkcBQKPR0KNHD/bv30+NGjUIDw/H29tb6ViiDKZOncrixYuxtLRkzZo1DBkyROlID83BwYGqVaty6dIlpaMIYVJkylsYFRcXFz7//HMuXbrE1atXeeWVV3B2dmbnzp0EBgZiY2NDz5492bp1q9JR9W748OFcv37dIBYrnTp1ipo1a7J//34CAwNJTk6WYrISWLRoEcHBwajVaoYOHcq4ceOMbgq8bt26pKamKh1DCJMjBaUwWs7OznzyySckJiZy9epVXn31VVxcXNi9ezf9+vXDxsaGHj16EBwcrHRUvXjnnXcAeP/99xXNsXDhQpo3b05OTg5ffPEF27dvx9zcXNFMQn/69u3L5cuXadSoET/99BPe3t4le8cag+bNm3Pz5k2jyixEZSAFpagUnJ2dWbBgAQkJCWRkZPDGG29Qs2ZN9uzZQ//+/bG2tqZbt25s2rRJ6aiPzNXVlbp16xIaGqrIqJFWqyUwMJAZM2Zgb2/PiRMneOmllyo8hyh/jo6OxMTEMGXKFM6fP4+7uzsbNmxQOtYDuX1P9Z9//qlwEiFMixSUotJxdHRk/vz5XLx4kaysLN58801q1arF3r17GTRoENbW1nTt2pWgoCCloz60cePGodFoKnwLobi4ONzc3Ni5cycdO3YkNTWVpk2bVmgGUfEWLVrEli1bUKlUDB06lOeee07pSPc1YMAAAEJCQhROIoRpkUU5wmRkZ2fzySefsGbNGs6fPw/catXWtm1bXnzxRYYMGWLwG3AXFBRga2tLixYtOHr0aIVcc+nSpUyePBmdTsf7779fstG6MB3p6el06NCB2NhYvLy8OHDgAC4uLkrHKpW1tTXe3t5ERkYqHUUIkyEFpTBJOTk5fPrpp6xevfqO4rJNmza8+OKLDB061GCLy8cee4yoqCjy8/OxtLQst+vodDqGDRvGxo0bsbOzY9euXdJz3cRNnjyZ77//HisrK37//XcGDhyodKS7qlu3LpmZmQazI4IQpsAwf2IKUc7s7e15//33iY+P59q1a7z77rt4eHgQHh7OE088gbW1NR07duS3334zuFWu06dPR6fT8eWXX5bbNRITE3F3d2fjxo20bNmS1NRUKSYF3333Xcm9iYMGDWLixIkKJ7o7X19frl+/jlarVTqKECZDCkph8uzt7ZkzZw5xcXHk5OTw3nvvUbduXQ4cOMCoUaOwtramffv2/PrrrwZRXI4bNw5zc3OWLFlSLuf/9ddf8fLyIjk5mddee42jR49ia2tbLtcSxmfAgAEkJSXh7e3N0qVL8fb2Jj09XelYd+jQoQOAQWyxJYSpkIJSiH+ws7PjnXfeITY2ltzcXD744APq1avHoUOHeOqpp7CysiIgIIBVq1YpVlyq1Wrat29PXFwcmZmZejuvTqdjzJgxPPXUU1hYWLB7924+/vhjvZ1fVB7Ozs7ExsYyceJEzp07R506dQxqB4XbC3Mq4360QhgquYdSiAeQl5fHl19+yc8//0xsbCzFxcWYm5vTokULXnjhBcaMGVOh91xu376dPn36MGPGDD7//HNuFGq5mHEDjVaHpbmauk5VqGL14HtDpqSk0L59ey5cuEDjxo0JDw/HwcGh/N6AqDQ2bdrEiBEjKCwsZOLEifzwww9KRyppwdi5c2f27t2rdBwhTIIUlEI8pLy8PL766it+/vlnzp49W1JcNm/enClTpjB27NgKKS6ruftQtUV/vDo+TmJmHv/8i6wCPBxt6ebjwui2HnjXrFrqeTZt2sQTTzyBRqNh6tSpfPvtt+WeXVQuaWlpdOjQgXPnzuHt7c2BAwdwdnZWNJOTkxNWVlYkJycrmkMIUyEFpRBlUFBQwNdff83y5cs5c+YMxcXFmJmZ0axZM6ZMmcK4ceP0Xlxeysxj1oZI9p1Lp1hXhEptVuqxZmoVRbpiOjVw5sMh/rg73nkv5JQpU/juu++wsrJi7dq1JVOFQjyKCRMmsGzZMoP489SqVSv++usvbt68qVgGIUyJFJRC6ElBQQHffvsty5cv5/Tp03cUl88//zzPPfdcmVsUrolI5N1N0Wh1xRTpHvyvrplahblaxXsDmzCqtQfZ2dkEBARw5swZ6tevz8GDBw16X0FhPIKCghgxYgQajYbJkyezePFiRXLc3uLo0qVL1KlTR5EMQpgSKSiFKAcajYZFixaxbNkyTp8+jU6nw8zMjKZNmzJp0iTGjx//0MXlNyFxfLojtszZhniZ8/30IeTn5zN27Fh+/PFHg91zUxintLQ0AgICOH/+PA0bNiQ8PLzCp8DXrl3LE088wbfffsvUqVMr9NpCmCIpKIUoZxqNhsWLF7Ns2TKio6PR6XSo1WqaNm3K888/z8SJE+9bXK6JSOSN9frr+pG9/Rt+eGMcI0aM0Ns5hfi3f06Br1+/nn79+lXYtXNzc6latSpPPPEEv//+e4VdVwhTJQWlEBVIo9Hwww8/sGTJEqKiokqKSz8/PyZOnMjkyZP/U1xeysyj5xehFGpL36YoNzqErN3L0OVl33rAzAIbr9a4DJ31n2OLi4uxMleze2bX/9xTKYS+bdiwgVGjRqHRaJgyZQqLFi2qsGvb2NhQt25dYmJiKuyaQpgqKSiFUIhWq+WHH37ghx9+IDIysqS4bNKkCRMnTmTSpElYWlry9LLDHDifUeo9k9kHf+da6ApUFtZYez6GysoWbVYyFOuoNfaLu77GTK2ifX0nVo6X7jei/KWkpNChQwfOnz9Po0aNCA8Px9HRsdyv6+XlRWpqKrm5ueV+LSFMnRSUQhgArVbLsmXL+P777zl16hRFRUWo1Wp82nQlr+vM0l+Xk87lxeNQV6lO7ak/olY/3H2Zu2Z0poFL6VsKCaEvOp2O8ePH89NPP2Ftbc369evp27dvuV5z0KBBbNq0icLCwnLtey+EkE45QhgEc3NzJk2axPHjxykoKOD777+nWbNmpFZtSLGuqNTXZe39EYqLcer9P9Rqc7Q3stHpHqx/sZlaxapDifp6C0Lck1qtZvny5axduxadTke/fv2YNm1auV6zY8eOAISEhJTrdYQQMkIphEHr/EkIiZl5pT6f9M0zFOVm4tD1WbLDVsHfxaS5szu1xnyC2trunuf3dLIl9JVues0sxP2kpKQQEBDAxYsXy3UK/OzZszRq1Kiko5QQovzICKUQBiq3UMulexSTAEX51wHI3vsTFk7u2LcZikWNemjTL5H84/1HfxIz8rhR+GAjmkLoi6urK/Hx8YwdO5YzZ85Qu3Zttm/frvfr+Pj4oFarOXLkiN7PLYS4kxSUQhiohIwb3Hf6oPjWym9zZ3fcxn9N9e7P4Tb+a8yd3CnKuUr+heP3fjlwMeOGXvIK8TDUajU//fQTf/zxB0VFRfTp04fp06fr/TpOTk7ExcXp/bxCiDtJQSmEgdLcY5ugEqpbf4WrNrtzcUPV5rd+nXcm/L6nePnV13n55ZdZtGgRe/bsIT09/eHDCvGIhg8fzsWLF/H09OTrr7+mSZMmZGdn6+38Xl5eZGRk6O18Qoi7K1sfOCFEubE0v//3PbWFNbqim1hUd7vjcfPqtQAoysu57zn27NrB9rQL/3ncwsICW1tb7O3tcXZ2xtXVFQ8PD+rWrYuPjw9+fn54eXlJlx1RZm5ubpw/f55nn32WlStXUqtWLTZt2kSvXr3KfO7WrVtz6NAh4uPj8fLy0kNaIcTdSEEphIGq61QFFdxz2tvc0Q1N8lk06YnYeLUqefxm+iUAzOzuvdBBBWRcPENa8iWio6M5e/Ys58+f59KlS6SkpJCens61a9dITU3lxIkTdz2HmZkZ1tbWVK1alerVq1OzZk3c3NyoW7cuDRs2pHHjxjRp0gRbW9lEXZROrVazYsUKBgwYwJgxYwgMDGT69Ol8+eWXZTpvYGAgX3/9NX/++ScvvfSSfsIKIf5DVnkLYcC6fBJCwj0W5tyIDiX9z08ws3ehztQfSx5PWvQcRTlpuD67ECvXBqW+/mFXeWdmZhIVFUVMTAznzp0jISGB5ORk0tLSyM7OJjc3l8LCQnS6/07Xq1QqrKyssLW1xcHBgRo1alCrVi08PDxo0KABjRo1okmTJri5ud3lysKUJCcn0759exISEmjSpAn79+/HwcHhkc5VUFCAjY0NQ4YMYf369foNKoQoIQWlEAZszqZoVh5OKLVLDsDl759Hm5WMWVVnrGr7Ung5hqLr6VjWbkStpz8t9XVmahVPt/VkzsAmes+t0Wg4c+YM0dHRxMbGcvHiRZKSkkhNTSUzM5OcnBzy8/PRau++wtzCwgIbGxvs7e1xcnKiZs2auLu7U69ePXx8fPD19cXHx+e+PdCF8dLpdDzzzDOsXr0aGxsb/vzzT3r06PFI56pSpQq1a9cmNjZWzymFELdJQSmEAYtLvU6vhWH3PEanKSBt7XsUXoq+tepbbXarj/ewt+57fqU75eh0OpKSkoiKiuLMmTNcuHCBxMREkpOTycjIIDs7m7y8PDQaDXf7qFKr1VhbW2NnZ4ejoyM1atSgdu3a1K1bFy8vL3x9ffH398fe3l6Bdyf04bfffuPpp5/m5s2bj7yfpI+PD5cuXSIv797bcAkhHp0UlEIYuPv18n4UxtjLOycnh8jISGJiYoiPj+fixYtcvnyZq1evkpmZSW5uLgUFBaVOt1taWpZMtzs5OeHm5oaHhwf16tWjUaNG+Pn5UadOHVlkZICSkpJo3749ly5dwt/fn7CwsIeaAh8+fDjr1q0j/fIVsqPi0OYXYG5jjWtLf6o4Pfh5hBClk4JSCAN3KTOPnl+EUvgg2wg9ICtzNbtmdMHdsfItlNFqtZw9e5aYmBjOnj3LhQsXuHTpEqmpqWRkZJRMt9+8efOurzc3Ny+Zbnd0dKRmzZrUqVOnZJFRkyZNaNSokfSGrmA6nY6nn36aX375BRsbGzZv3kz37t3v+7qEsAgiX38Lv9Mn8Mi5esdeeTrgipMbSe264vraS3h2bl1u+YWo7KSgFMIIrIlI5I31kXo738dD/RnZ2kNv5zNWycnJREdHc+bMGc6dO8elS5dITk7m6tWrJdPthYWFpU63W1lZYWdnh4ODAy4uLri5ueHp6UmDBg3w9fXFz8+vXFoKmrJff/2VsWPHcvPmTWbOnMlnn3121+OST5wmY8w4/E8fQatSY15c+hey289HNm6D06rluDVvXF7xhai0pKAUwkh8ExLHpzvKvqjg1UAfXuhW+spv8V+5ubnExMRw+vRpYmNjSUhI4PLly6SmppKVlcX169cpKCigqKjorq+/Pd1erVq1kj093d3dqV+/Pj4+PjRp0oR69erJdPsD+vcU+P79+++4T/bI7I9puuAdzIu09ywk/02rUqM1M+fUa+/TZt7r5RFdiEpLCkohjMiaiETe3RSNVlf8UPdUmqlVmKtVvD+wiYxMliOtVsuFCxeIiori7NmzXLx4kcTERFJSUsjIyODatWvk5eWVOt1+e0/Pf063315k1LBhw5J7Pa2trSv4nRkenU7H6NGjWbNmDba2tvz55590796dg+NnEvDjFxRza5/Vh3X7dQefm0HAsodfACSEqZKCUggjcykzj1kbItl3Lh0zteqeheXt5zs1cObDIf6V8p5JY5WWllayuj0+Pr5kT8/09HSysrJK9vS820f07T09q1SpQvXq1Uv29Lw93e7j44O/vz8uLi4KvLOK9euvv/LMM8+g1Wr5tvcTTN3+h97OfWT2x7SZ+5rezidEZSYFpRBGKi71OqsPJxISm0ZiRt4dHXVUgIeTLd0aujCmnYeiWwOJsikoKOD06dOcPn2ac+fOceHCBZKSkkhLSyMjI4Pr16+Tn59f6nT7P1toOjk53THd7u3tjZ+fH97e3kY93Z6YmMiorr3Zc+k8VlrNXUcmc4BewFFuLcapArwFvFHKOYuBQnNLMo+ckHsqhXgAUlAKUQncKNRyMeMGGq0OS3M1dZ2qUMVKNv02JTqdjoSEBCIjI4mLiyM+Pr5kuv12C83b0+13+9j/ZwtNBweHO6bbGzRoUNJC087OToF3d3+RTdriG3O01HsmPYFEoBXgAwQBucC3wNRSzqlVqYnxbYV/9OFySCxE5SIFpRBCmJjbLTRvr26/ePEiV65cIS0t7Y7p9nvt6VmlShUcHBxwdnbGzc0Nd3d3vLy8aNSoEf7+/ri6ulbYqGdCWASeXdqU+vxy4DmgP7D578eygRqANXD9fuffF4Fnx1ZlDypEJSYFpRBCiLvSaDTExsYSHR1dsqfn5cuXSUlJeaAWmubm5tja2lK1atWS6fbatWtTv379kj099dFC8/CA0bQMXlPq6GQbIAK4BNT5x+O9gR3AIaC0Lf61KjXH+o2i7ebVZcooRGUnBaUQQogy0el0JCcnExkZydmzZ4mPjy/Z0/P2dPuNGzceqIVm9erV79jT09vbu2R1e2ndcS4716Z2RnKp+Zy4Nb1d+K/HPwFe49a9lB/c4/0lOdWmTnrSPf8fCGHqpKAUQghRYXJycoiOji5ZZHR7T8/b0+239/S8XwvN23t6eri48kfwZu41uW4N2AKZ/3p8EzAIeAq41/ijDshPz5I2jULcg9y1L4QQosLY29sTEBBAQEDAPY/TarXExcURHR1NXFwc58+f59KlSyXT7ZmZmVy+fBnsku9ZTAIUcfcfdre3Qs+7z+vVQMqxSLwCO93nSCFMlxSUQgghDI65uTm+vr74+vre87izQTthcOA9jzED7naXZ87f/36Q3Vm1+QUPcJQQpst4Nx4TQghh8sxt7t81qApw4y6Pn/373/X1dB0hTJkUlEIIIYyWa0t/7tetuz6gAf69rGbn3/8ecJ/X6/6+jhCidFJQCiGEMFpVnBy44uR2z2Mm/+vfcGu6ey+3Ri9L2zLotmSn2rIgR4j7kIJSCCGEUUtq1xWtqvQfZ+O5tf/kFm7tSTnm71/fBObf59xalZrL7broKakQlZdsGySEEMKo3a9TDtzqjNMLOM7/9/J+E5j9IOeXTjlC3JcUlEIIIYze/Xp5Pwrp5S3Eg5MpbyGEEEbPadVytGbm6GuEpBjQmpnjtGq5ns4oROUmBaUQQgij59a8Madeex+Vns6nAl52bUDXkYNJT0/X01mFqLykoBRCCFEptJn3OgefmwHwyCOVt193aPxMCnsHEBcXR506dQgKCtJLRiEqKykohRBCVBoByz7nyKyPKDS3vOfK77vRqtQUmltyZPbHtFv6GUuXLi0pJAcPHsxzzz131x7jQghZlCOEEKISSj5xmowx4/A/fQStSn3PxTq3n49s3AanVctxa974jufT09Np3749cXFx1K9fn/DwcFxdXcv7LQhhVGSEUgghRKXj1rwx/tGHSQg9wrF+o0hyqv2fjjo6IMmpNsf6jSJhXwT+0Yf/U0wCODs7Exsby+TJkzl//jyenp6sXbu2Qt6HEMZCRiiFEEKYhBsZ2aQci0SbX4C5jTWuLf0fugNOcHAww4YNo6CggNGjR7NixQrUahmbEUIKSiGEEOIhZGZm0rFjR2JiYvDw8CA8PJw6deooHUsIRcnXKiGEEOIhODo6cvr0aaZNm0ZiYiL169fn119/VTqWEIqSEUohhBDiEe3evZvHH3+c/Px8Ro4cyS+//CJT4MIkSUEphBBClEF2djadO3cmMjKS2rVrc+DAATw8PJSOJUSFkq9RQgghRBk4ODhw6tQpXnnlFS5fvoyXlxcrVqxQOpYQFUpGKIUQQgg92bt3LwMGDODGjRsMGTKEtWvXyhS4MAlSUAohhBB6lJubS+fOnTlx4gS1atUiPDycevXqKR1LiHIlX5uEEEIIPbKzs+P48eO8+eabpKSk4O3tzdKlS5WOJUS5khFKIYQQopyEh4fTp08fcnNz6d+/Pxs3bsTc3FzpWELonRSUQgghRDnKy8uja9euRERE4OLiwv79+/H29lY6lhB6JVPeQgghRDmytbXlyJEjvPvuu1y9ehVfX18WLVqkdCwh9EpGKIUQQogKEhERQc+ePcnJySEwMJAtW7bIFLioFKSgFEIIISpQQUEBPXr04MCBAzg5OREaGkqTJk2UjiVEmciUtxBCCFGBrK2tCQ8P58MPPyQzM5OmTZvy5ZdfKh1LiDKREUohhBBCIcePH6dHjx5kZ2fTvXt3tm7diqWlpdKxhHhoUlAKIYQQCtJoNAQGBhIaGkr16tXZu3cvTZs2VTqWEA9FpryFEEIIBVlaWrJ3714+/fRTrl27RvPmzfnkk0+UjiXEQ5ERSiGEEMJAREVF0aVLFzIzM+nUqRO7du2SKXBhFGSEUgghhDAQfn5+XLlyhR49erBv3z5cXFw4fvy40rGEuC8pKIUQQggDYmlpya5du1i4cCHXr1+nVatWzJs3T+lYQtyTTHkLIYQQBiomJobOnTuTnp5Ou3btCAkJwdraWulYQvyHjFAKIYQQBsrX15crV67Qp08fDh06hIuLC4cPH1Y6lhD/IQWlEEIIYcDMzc3ZunUrixYtIi8vj4CAAObMmaN0LCHuIFPeQgghhJGIi4ujY8eOpKWl0apVK0JDQ7G1tVU6lhAyQimEEEIYC29vb65cucLAgQM5evQoLi4uhIeHKx1LCCkohRBCCGOiVqsJCgpi6dKlFBQU0KlTJ958802lYwkTJ1PeQgghhJG6cOECHTp04MqVKzRr1ox9+/ZhZ2endCxhgmSEUgghhDBS9erVIykpiaFDh3Ly5Elq1qzJ3r17lY4lTJAUlEIIIYQRU6vVrFu3jp9//hmNRkO3bt14+eWXlY4lTIxMeQshhBCVRGJiIh06dCApKQk/Pz/27duHg4OD0rGECZARSiGEEKKS8PDwICEhgVGjRhEVFYWbmxs7d+5UOpYwAVJQCiGEEJWIWq3m119/Zc2aNWi1WgIDA5k+fbrSsUQlJ1PeQgghRCWVnJxM+/btSUhIoFGjRoSHh+Po6Kh0LFEJyQilEEIIUUm5ublx/vx5nnnmGc6cOUPt2rUJDg5WOpaohKSgFEIIISoxtVrNzz//zNq1a9HpdPTv35/JkycrHUtUMjLlLYQQQpiIlJQUOnTowPnz5/H29mb//v24uLgoHUtUAjJCKYQQQpgIV1dX4uPjGT9+PHFxcXh4eBAUFKR0LFEJSEEphBBCmJilS5eWFJKDBw9m3Lhx6HQ6hVMJYyZT3kIIIYSJSk9Pp0OHDsTGxlKvXj0OHDiAq6ur0rGEEZIRSiGEEMJEOTs7c/bsWaZMmcKFCxfw9PRk7dq1SscSRkhGKIUQQgjB9u3bGTx4MAUFBYwePZoVK1agVsu4k3gwUlAKIYQQAoDMzEw6derE6dOn8fDwIDw8nDp16igdSxgB+eohhBBCCAAcHR2Jjo5m+vTpJCYmUr9+fX799VelYwkjICOUQgghhPiP3bt38/jjj5Ofn88TTzzBmjVrZApclEoKSiGEEELcVU5ODp06deLUqVPUrl2b8PBwPD09lY4lDJB81RBCCCHEXdnb2/PXX3/x6quvcvnyZRo0aMDPP/+sdCxhgGSEUgghhBD3FRYWRr9+/bhx4waDBw9m3bp1MgUuSkhBKYQQQogHkpubS5cuXTh+/Diurq7s378fLy8vpWMJAyBfLYQQQgjxQOzs7Dh27BizZs0iNTUVHx8fli5dqnQsYQBkhFIIIYQQDy08PJw+ffqQm5tLv379CAoKwtzcXOlYQiFSUAohhBDikeTl5dGtWzeOHDmCi4sLYWFh+Pj4KB1LKECmvIUQQgjxSGxtbTl8+DBz5szh6tWrNG7cmEWLFikdSyhARiiFEEIIUWYRERH07NmTnJwcAgMD2bJli0yBmxApKIUQQgihFwUFBfTs2ZPw8HCcnJwIDQ2lSZMmSscSFUCmvIUQQgihF9bW1uzfv5/58+eTmZlJ06ZNWbhwodKxRAWQEUohhBBC6N3Jkyfp1q0b2dnZdOvWjW3btmFpaal0LFFOpKAUQgghRLnQaDQEBgYSGhpK9erV2bt3L02bNlU6ligHMuUthBBCiHJhaWnJ3r17+fTTT7l27RrNmzdnwYIFSscS5UBGKIUQQghR7qKioujSpQuZmZl07NiRnTt3Ym1trXQsoScyQimEEEKIcufn50dqaio9e/Zk//79uLq6cvToUaVjCT2RglIIIYQQFcLc3JydO3fy1Vdfcf36ddq0acPcuXOVjiX0QKa8hRBCCFHhYmJi6Ny5M+np6bRr147du3dja2urdCzxiGSEUgghhBAVztfXlytXrtC3b18OHTqEq6srhw8fVjqWeERSUAohhBBCEebm5gQHB/Pdd9+Rl5dHQEAA77zzjtKxxCOQKW8hhBBCKC4uLo5OnTqRmppKy5Yt2bt3L3Z2dkrHEg9IRiiFEEIIoThvb2+Sk5MZNGgQx44dw9XVlf379ysdSzwgKSiFEEIIYRDUajUbN25k6dKlFBQU0LlzZ958802lY4kHIFPeQgghhDA4Fy5coEOHDly5coXHHnuMsLAw7O3tlY4lSiEjlEIIIYQwOPXq1SMpKYlhw4bx119/UatWLfbs2aN0LFEKKSiFEEIIYZDUajVr165l5cqVaDQaevTowcyZM5WOJe5CpryFEEIIYfASExPp2LEjly5dokmTJuzfvx8HBwelY4m/yQilEEIIIQyeh4cHFy9e5MknnyQ6Oho3Nzd27typdCzxNykohRBCCGEU1Go1v/zyC2vWrEGr1RIYGMi0adOUjiWQKW8hhBBCGKHk5GTat2/P/7V3d7FV13ccxz/n9AhKVUwhlXVyxK2iCyPbLpgGbCY3JFODsJDMqQmaOS+MWVzmvDAmRi+40WS3i96YIJkYg8EsbJgFEqFVo2SLDgNYCbRZNrpCEGh5SDlnF6JBEWj7L+nh9PW67Pk/fHv3zu//tH///tx6663p7u5OW1vbZI81ZVmhBAAuOx0dHdm7d29Wr16dXbt2paOjI5s2bZrssaYsQQkAXJbK5XJeeeWVbNiwIfV6PXfffXceffTRyR5rSnLJGwC47A0MDGTx4sX57LPP0tnZme7u7rS3t0/2WFOGFUoA4LLX3t6e3t7ePPLII+nt7U21Ws3GjRsne6wpQ1ACAE3j5Zdf/iokV6xYkYceeii1Wm2Sp2p+LnkDAE1ncHAwd9xxR3bv3p158+bl3XffzZw5cyZ7rKZlhRIAaDqzZ8/Orl278thjj2Xfvn2pVqt5/fXXJ3uspmWFEgBoaps3b86KFSty4sSJ3H///Vm7dm3KZWtqE0lQAgBN7/Dhw1myZEk++eSTzJ07Nz09Pbnhhhsme6ymIc8BgKZ33XXXZefOnXniiSfS39+fm266KevWrZvssZqGFUoAYErZsmVL7rnnnhw/fjyrVq3K+vXrx3wJfOjkSPYdHMqpkVqmVcqZN6s1rdMrl2jixicoAYAp58iRI+nq6spHH32Ujo6O9PT05MYbb7zgPp8eOJp17/dl6+6B9B0aztkBVUpSbZuRpbe054Hbqrn5+msu6fyNRlACAFPWU089lRdeeCGVSiUvvfRSHn744XO26T80nKff/DjbegfTUi7ldO386fTl712ds7Nm5cLMbZtxKcdvGIISAJjS3nnnndx1110ZGhrKvffemw0bNnx1Cfy1D/ry7Fs7M1KrXzAkv6mlXEqlXMpzyxfkvkXVSzV6wxCUAMCUd+zYsdx5553ZsWNH5syZk+3bt+evfbW8+Paewsd+ctn8PL705gmYsnF5yhsAmPKuvvrqfPjhh3nmmWdy4MCB/GTV4xMSk0ny4tt7sv6Dvgk5VqOyQgkAcJaNf9+e327+X9JyRUql0jm///tPv8nI4f+cd/85q/+Y6d/5+ork9Eo5f//dz5r2nsqp+3w7AMC3eGP/FalMm5bTtW///drbf5FT/937jb/Wc+yff0tarjgnJpNkpFbP029+nLW/vm3iB24AghIA4IxPDxzNtt7BC25zzY9/fs7fjuz4S5Lkyrk//NZ9Ttfq2dY7mN6Bo+lsb75XCrmHEgDgjHXv96WlfO5l7os5+o9NSZKZi+877zYt5VJefa8576UUlAAAZ2zdPTCm1wMlSe3UiYwM9qc07apcWV1w3u1O1+rZumeg6IgNSVACACQ5dnIkfYeGx7zf5++9kaSeq76/6KLb9h0cztDJkXFM19gEJQBAkv0HhzKeV98M/WtLkmRm1wMX3baeZN/BoXGcpbEJSgCAJKdGzvNY9wWMHDuU00cGUp4xM9PavnvJztPoBCUAQJJplbFn0efb/5wkaf1B1yU9T6Nrvv8IAGAc5s1qzVif7x7e3Z0kuXbJr0a1fenMeZqNoAQASNI6vZLqGL5kc2qwP7XjR1KZeX0qM2aOap/qrBlpnd58rwEXlAAAZyy9pX3U76E8vO3VJEnrj5aNavuWcilL57ePe7ZGJigBAM544LbqqN9DeWLvjiSlXPvTlaPa/nStngdvrxaYrnE135orAMA43Xz9NenqnJ2evQcvGpbV378x6uO2lEtZ/L1ZTfnZxcQKJQDA16xZuTCVcXx+8UIq5VLWrFw4ocdsJIISAOAsc9tm5Lnl5/+E4ng8v3xB5o7hgZ/LjaAEAPiG+xZV8+Sy+RNyrD8suyW/XNSc905+qVSv18fzlSEAgKb32gd9efatnRmp1Uf9sE7yxT2TlXIpzy9f0PQxmQhKAIAL6j80nKff/DjbegfTUi5dMCy//L2rc3bWrFzY1Je5zyYoAQBG4dMDR7Pu/b5s3TOQvoPDOTugSvnipeVL57fnwdurTfs09/kISgCAMRo6OZJ9B4dyaqSWaZVy5s1qbcov4IyWoAQAoBBPeQMAUIigBACgEEEJAEAhghIAgEIEJQAAhQhKAAAKEZQAABQiKAEAKERQAgBQiKAEAKAQQQkAQCGCEgCAQgQlAACFCEoAAAoRlAAAFCIoAQAoRFACAFCIoAQAoBBBCQBAIYISAIBCBCUAAIUISgAAChGUAAAUIigBAChEUAIAUIigBACgEEEJAEAhghIAgEIEJQAAhQhKAAAKEZQAABQiKAEAKERQAgBQiKAEAKAQQQkAQCGCEgCAQgQlAACF/B+HAxeMTmGv9AAAAABJRU5ErkJggg==", + "image/png": 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", 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" ] @@ -861,7 +717,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" }, "vscode": { "interpreter": { diff --git a/applications/optimization/max_independent_set/max_independent_set.qmod b/applications/optimization/max_independent_set/max_independent_set.qmod index 4fbda4cc2..c8b8fc2ca 100644 --- a/applications/optimization/max_independent_set/max_independent_set.qmod +++ b/applications/optimization/max_independent_set/max_independent_set.qmod @@ -1,309 +1,23 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=3.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-1.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=0.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=0.5 - } -]; - -qfunc main(params_list: real[6], output target: qbit[8]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + x_0: qbit; + x_1: qbit; + x_2: qbit; + x_3: qbit; + x_4: qbit; + x_5: qbit; + x_6: qbit; + x_7: qbit; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=True, -initial_point=[0.0, 0.45833333333333337, 0.22916666666666669, 0.22916666666666669, 0.45833333333333337, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=60, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=0.7 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[6], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 3) { + phase (-(((((((((((((((((((((((20 * v.x_0) * v.x_2) + ((20 * v.x_0) * v.x_4)) + ((20 * v.x_0) * v.x_6)) + ((20 * v.x_0) * v.x_7)) - v.x_0) + ((20 * v.x_1) * v.x_2)) + ((20 * v.x_1) * v.x_4)) + ((20 * v.x_1) * v.x_5)) - v.x_1) + ((20 * v.x_2) * v.x_4)) + ((20 * v.x_2) * v.x_5)) + ((20 * v.x_2) * v.x_6)) - v.x_2) + ((20 * v.x_3) * v.x_4)) + ((20 * v.x_3) * v.x_5)) + ((20 * v.x_3) * v.x_6)) - v.x_3) - v.x_4) + ((20 * v.x_5) * v.x_6)) - v.x_5) - v.x_6) - v.x_7), params[i]); + apply_to_all(lambda(q) { + RX(params[3 + i], q); + }, v); + } +} diff --git a/applications/optimization/max_independent_set/max_independent_set.synthesis_options.json b/applications/optimization/max_independent_set/max_independent_set.synthesis_options.json index 0967ef424..547a5148e 100644 --- a/applications/optimization/max_independent_set/max_independent_set.synthesis_options.json +++ b/applications/optimization/max_independent_set/max_independent_set.synthesis_options.json @@ -1 +1,43 @@ -{} +{ + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "x", + "sx", + "p", + "u1", + "cy", + "sxdg", + "rx", + "cx", + "r", + "id", + "y", + "cz", + "s", + "tdg", + "u", + "rz", + "ry", + "u2", + "z", + "sdg", + "h", + "t" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 3080696119 + } +} diff --git a/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.ipynb b/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.ipynb index 8c23cb094..a00d2401b 100644 --- a/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.ipynb +++ b/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.ipynb @@ -44,12 +44,6 @@ "execution_count": 1, "id": "83ddbd07-f7ab-4d80-b357-3890622d395f", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:46.993834Z", - "iopub.status.busy": "2024-05-07T15:59:46.993374Z", - "iopub.status.idle": "2024-05-07T15:59:47.525960Z", - "shell.execute_reply": "2024-05-07T15:59:47.525184Z" - }, "tags": [] }, "outputs": [], @@ -107,18 +101,12 @@ "execution_count": 2, "id": "bc9871c1-224e-4206-b39e-af7e448aca70", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:47.531914Z", - "iopub.status.busy": "2024-05-07T15:59:47.530379Z", - "iopub.status.idle": "2024-05-07T15:59:48.475400Z", - "shell.execute_reply": "2024-05-07T15:59:48.474677Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -149,12 +137,6 @@ "execution_count": 3, "id": "e5ba50c9-5d89-4ebf-9475-830da3ce5539", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:48.480486Z", - "iopub.status.busy": "2024-05-07T15:59:48.479062Z", - "iopub.status.idle": "2024-05-07T15:59:48.490131Z", - "shell.execute_reply": "2024-05-07T15:59:48.489448Z" - }, "tags": [] }, "outputs": [ @@ -220,102 +202,93 @@ }, { "cell_type": "markdown", - "id": "8a108c16-e77f-4dc5-89f1-4cbbed06bff5", + "id": "21405e6b-0997-4c2c-afb0-bb043a09c535", "metadata": { "tags": [] }, "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):" + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the qaoa algorithm, with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { "cell_type": "code", "execution_count": 4, - "id": "6d1db79c-4d99-49a8-9347-5d6ad67353e3", + "id": "71d475f3-dcfd-4b0b-8813-ae0f31681935", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:48.494703Z", - "iopub.status.busy": "2024-05-07T15:59:48.493521Z", - "iopub.status.idle": "2024-05-07T15:59:50.391512Z", - "shell.execute_reply": "2024-05-07T15:59:50.390855Z" - }, "tags": [] }, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "qaoa_config = QAOAConfig(num_layers=8)" - ] - }, - { - "cell_type": "markdown", - "id": "3ed22929-18cf-47e6-9c2a-ad635365a48a", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" + "combi = CombinatorialProblem(pyo_model=coloring_model, num_layers=8, penalty_factor=10)\n", + "\n", + "qmod = combi.get_model()" ] }, { "cell_type": "code", "execution_count": 5, - "id": "13247459-f1c8-48cf-83f0-f13eb66365ca", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:50.394696Z", - "iopub.status.busy": "2024-05-07T15:59:50.394038Z", - "iopub.status.idle": "2024-05-07T15:59:50.398249Z", - "shell.execute_reply": "2024-05-07T15:59:50.397671Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, + "id": "25374090-83b1-477a-b772-aa0c1b13bac6", + "metadata": {}, "outputs": [], "source": [ - "optimizer_config = OptimizerConfig(max_iteration=20, alpha_cvar=0.7)" + "write_qmod(qmod, \"max_induced_k_color_subgraph\")" ] }, { "cell_type": "markdown", - "id": "31c98d00-ed27-4eb9-86c3-580825ac9677", + "id": "36d4ce2e-205a-4486-a004-cd5befbc81c1", "metadata": {}, "source": [ - "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:" + "## Synthesizing the QAOA Circuit and Solving the Problem\n", + "\n", + "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" ] }, { "cell_type": "code", "execution_count": 6, - "id": "46f35710-d7b3-49d0-ae25-5e36f1f6dd95", + "id": "928df7bd-721f-4823-9b2b-74f5325a051d", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:50.400620Z", - "iopub.status.busy": "2024-05-07T15:59:50.400214Z", - "iopub.status.idle": "2024-05-07T15:59:54.059295Z", - "shell.execute_reply": "2024-05-07T15:59:54.058630Z" - }, "pycharm": { "name": "#%%\n" }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "ename": "ClassiqAPIError", + "evalue": "Internal error occurred. Please contact Classiq support.\nError number 122001 occurred:\n\nError identifier: EB84B0C2F-D256-42B9-B70E-F1D25177BDBE\nIf you need further assistance, please reach out on our Community Slack channel at: https://short.classiq.io/join-slack", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mClassiqAPIError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[6], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m qprog \u001b[38;5;241m=\u001b[39m \u001b[43mcombi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_qprog\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m show(qprog)\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/applications/combinatorial_optimization/combinatorial_problem.py:73\u001b[0m, in \u001b[0;36mCombinatorialProblem.get_qprog\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 71\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel_ \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 72\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_model()\n\u001b[0;32m---> 73\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_ \u001b[38;5;241m=\u001b[39m \u001b[43msynthesize\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel_\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type:ignore[assignment,arg-type]\u001b[39;00m\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/synthesis.py:85\u001b[0m, in \u001b[0;36msynthesize\u001b[0;34m(serialized_model, auto_show)\u001b[0m\n\u001b[1;32m 71\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msynthesize\u001b[39m(\n\u001b[1;32m 72\u001b[0m serialized_model: SerializedModel, auto_show: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 73\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m SerializedQuantumProgram:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 75\u001b[0m \u001b[38;5;124;03m Synthesize a model with the Classiq engine to receive a quantum program.\u001b[39;00m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;124;03m [More details](https://docs.classiq.io/latest/reference-manual/synthesis/)\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 83\u001b[0m \u001b[38;5;124;03m SerializedQuantumProgram: Quantum program serialized as a string. (See: QuantumProgram)\u001b[39;00m\n\u001b[1;32m 84\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 85\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43masync_utils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43msynthesize_async\u001b[49m\u001b[43m(\u001b[49m\u001b[43mserialized_model\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m auto_show:\n\u001b[1;32m 87\u001b[0m show(result)\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/async_utils.py:37\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(coro)\u001b[0m\n\u001b[1;32m 32\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrun\u001b[39m(coro: Awaitable[T]) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m T:\n\u001b[1;32m 33\u001b[0m \u001b[38;5;66;03m# Use this function instead of asyncio.run, since it ALWAYS\u001b[39;00m\n\u001b[1;32m 34\u001b[0m \u001b[38;5;66;03m# creates a new event loop and clears the thread event loop.\u001b[39;00m\n\u001b[1;32m 35\u001b[0m \u001b[38;5;66;03m# Never use asyncio.run in library code.\u001b[39;00m\n\u001b[1;32m 36\u001b[0m loop \u001b[38;5;241m=\u001b[39m get_event_loop()\n\u001b[0;32m---> 37\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mloop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_until_complete\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcoro\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/nest_asyncio.py:98\u001b[0m, in \u001b[0;36m_patch_loop..run_until_complete\u001b[0;34m(self, future)\u001b[0m\n\u001b[1;32m 95\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m f\u001b[38;5;241m.\u001b[39mdone():\n\u001b[1;32m 96\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 97\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mEvent loop stopped before Future completed.\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m---> 98\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresult\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/asyncio/futures.py:203\u001b[0m, in \u001b[0;36mFuture.result\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 201\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__log_traceback \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 202\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 203\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception\u001b[38;5;241m.\u001b[39mwith_traceback(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception_tb)\n\u001b[1;32m 204\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_result\n", + "File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/asyncio/tasks.py:267\u001b[0m, in \u001b[0;36mTask.__step\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 263\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 264\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m exc \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 265\u001b[0m \u001b[38;5;66;03m# We use the `send` method directly, because coroutines\u001b[39;00m\n\u001b[1;32m 266\u001b[0m \u001b[38;5;66;03m# don't have `__iter__` and `__next__` methods.\u001b[39;00m\n\u001b[0;32m--> 267\u001b[0m result \u001b[38;5;241m=\u001b[39m coro\u001b[38;5;241m.\u001b[39msend(\u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 268\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 269\u001b[0m result \u001b[38;5;241m=\u001b[39m coro\u001b[38;5;241m.\u001b[39mthrow(exc)\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/synthesis.py:67\u001b[0m, in \u001b[0;36msynthesize_async\u001b[0;34m(serialized_model)\u001b[0m\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msynthesize_async\u001b[39m(\n\u001b[1;32m 64\u001b[0m serialized_model: SerializedModel,\n\u001b[1;32m 65\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m SerializedQuantumProgram:\n\u001b[1;32m 66\u001b[0m model \u001b[38;5;241m=\u001b[39m Model\u001b[38;5;241m.\u001b[39mmodel_validate_json(serialized_model)\n\u001b[0;32m---> 67\u001b[0m quantum_program \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m ApiWrapper\u001b[38;5;241m.\u001b[39mcall_generation_task(model)\n\u001b[1;32m 68\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m SerializedQuantumProgram(quantum_program\u001b[38;5;241m.\u001b[39mmodel_dump_json(indent\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m))\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/api_wrapper.py:125\u001b[0m, in \u001b[0;36mApiWrapper.call_generation_task\u001b[0;34m(cls, model, http_client)\u001b[0m\n\u001b[1;32m 121\u001b[0m poller \u001b[38;5;241m=\u001b[39m JobPoller(base_url\u001b[38;5;241m=\u001b[39mroutes\u001b[38;5;241m.\u001b[39mTASKS_GENERATE_FULL_PATH)\n\u001b[1;32m 122\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m poller\u001b[38;5;241m.\u001b[39mrun_pydantic(\n\u001b[1;32m 123\u001b[0m model, timeout_sec\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, http_client\u001b[38;5;241m=\u001b[39mhttp_client\n\u001b[1;32m 124\u001b[0m )\n\u001b[0;32m--> 125\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_parse_job_response\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresult\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgenerator_result\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mQuantumProgram\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/api_wrapper.py:61\u001b[0m, in \u001b[0;36m_parse_job_response\u001b[0;34m(job_result, output_type)\u001b[0m\n\u001b[1;32m 59\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m output_type\u001b[38;5;241m.\u001b[39mmodel_validate(job_result\u001b[38;5;241m.\u001b[39mresult)\n\u001b[1;32m 60\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m job_result\u001b[38;5;241m.\u001b[39mfailure_details:\n\u001b[0;32m---> 61\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ClassiqAPIError(job_result\u001b[38;5;241m.\u001b[39mfailure_details)\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ClassiqAPIError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnexpected response from server\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[0;31mClassiqAPIError\u001b[0m: Internal error occurred. Please contact Classiq support.\nError number 122001 occurred:\n\nError identifier: EB84B0C2F-D256-42B9-B70E-F1D25177BDBE\nIf you need further assistance, please reach out on our Community Slack channel at: https://short.classiq.io/join-slack" + ] + } + ], "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=coloring_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" + "qprog = combi.get_qprog()\n", + "show(qprog)" ] }, { "cell_type": "markdown", - "id": "011b8c25-00b5-4099-9079-eb46f640343d", + "id": "78e3d55f-1e2f-40b4-981b-323b023b1152", "metadata": {}, "source": [ "We also set the quantum backend we want to execute on:" @@ -323,278 +296,107 @@ }, { "cell_type": "code", - "execution_count": 7, - "id": "c87b4cd7-a780-4d78-8335-f78b38584d80", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:54.062409Z", - "iopub.status.busy": "2024-05-07T15:59:54.062022Z", - "iopub.status.idle": "2024-05-07T15:59:54.196397Z", - "shell.execute_reply": "2024-05-07T15:59:54.195183Z" - }, - "tags": [] - }, + "execution_count": null, + "id": "a8bef9d6-c764-46a0-b166-dd41e45b956f", + "metadata": {}, "outputs": [], "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", + "from classiq.execution import *\n", "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", + "execution_preferences = ExecutionPreferences(\n", + " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\"),\n", ")" ] }, - { - "cell_type": "code", - "execution_count": 8, - "id": "96507f00-8d76-4ca3-b0dd-0b20d44c1e80", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:54.211269Z", - "iopub.status.busy": "2024-05-07T15:59:54.209802Z", - "iopub.status.idle": "2024-05-07T15:59:54.709502Z", - "shell.execute_reply": "2024-05-07T15:59:54.708816Z" - } - }, - "outputs": [], - "source": [ - "write_qmod(qmod, \"max_induced_k_color_subgraph\")" - ] - }, { "cell_type": "markdown", - "id": "e63e8272-cfd5-4a7d-9ce9-73486dab643a", + "id": "9fc3ffd1-d02a-49e3-bd15-422075b940e2", "metadata": {}, "source": [ - "## Synthesizing the QAOA Circuit and Solving the Problem\n", - "\n", - "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" + "We now solve the problem by calling the `optimize` method of the `CombinatorialProblem` object. For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`maxiter`) and the $\\alpha$-parameter (`quantile`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" ] }, { "cell_type": "code", - "execution_count": 9, - "id": "1b3e64a1-eae5-4ffc-9a08-1d5131401422", + "execution_count": null, + "id": "b954a31c-e15f-403f-9adb-a96228dba985", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:54.712426Z", - "iopub.status.busy": "2024-05-07T15:59:54.711967Z", - "iopub.status.idle": "2024-05-07T16:01:10.648412Z", - "shell.execute_reply": "2024-05-07T16:01:10.647712Z" - }, - "pycharm": { - "name": "#%%\n" - }, "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Opening: https://platform.classiq.io/circuit/941213ad-27c1-464a-8fb9-3936559e6168?version=0.41.0.dev39%2B79c8fd0855\n" - ] - } - ], + "outputs": [], "source": [ - "qprog = synthesize(qmod)\n", - "show(qprog)" + "cost_values = []\n", + "optimized_params = combi.optimize(\n", + " execution_preferences, maxiter=20, cost_trace=cost_values, quantile=0.7\n", + ")" ] }, { "cell_type": "markdown", - "id": "e99f6361-a9ac-48d1-a7b1-c77a0f09adfe", + "id": "7b4b1305-3ccf-4d62-ba61-fb13da4975f9", "metadata": {}, "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" + "We can check the convergence of the run:" ] }, { "cell_type": "code", - "execution_count": 10, - "id": "d7520962-de83-42de-928b-34e72cc01caf", + "execution_count": null, + "id": "ff641ee0-c7a3-48ba-864f-7fb06f7248db", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:01:10.651764Z", - "iopub.status.busy": "2024-05-07T16:01:10.651358Z", - "iopub.status.idle": "2024-05-07T16:02:57.582923Z", - "shell.execute_reply": "2024-05-07T16:02:57.582238Z" - }, "tags": [] }, "outputs": [], "source": [ - "result = execute(qprog).result_value()" + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(nrows=1, ncols=1)\n", + "axes.plot(cost_values)\n", + "axes.set_xlabel(\"Iterations\")\n", + "axes.set_ylabel(\"Cost\")\n", + "axes.set_title(\"Cost convergence\")" ] }, { "cell_type": "markdown", - "id": "56a8d4c5-4f22-4107-999f-2eaa147e52d1", - "metadata": {}, - "source": [ - "We can check the convergence of the run:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "58e49053-f2c6-40f9-9865-9f9e79df6eeb", + "id": "ccd880e2-9dd0-44c2-8d9e-1d892ed5faec", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:02:57.586876Z", - "iopub.status.busy": "2024-05-07T16:02:57.586610Z", - "iopub.status.idle": "2024-05-07T16:02:57.617957Z", - "shell.execute_reply": "2024-05-07T16:02:57.617181Z" - }, "tags": [] }, - "outputs": [ - { - "data": { - "image/jpeg": 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- "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], "source": [ - "result.convergence_graph" + "# Optimization Results" ] }, { "cell_type": "markdown", - "id": "ccd880e2-9dd0-44c2-8d9e-1d892ed5faec", - "metadata": { - "tags": [] - }, + "id": "5988f7ea-3236-4887-a939-6394db1998ce", + "metadata": {}, "source": [ - "# Optimization Results" + "We can also examine the statistics of the algorithm. The optimization is always defined as a minimzation problem, so the positive maximization objective was tranlated to a negative minimization one by the pyomo to qmod translator." ] }, { "cell_type": "markdown", - "id": "6716ab8d-ed59-49ce-a866-b0d344c421dd", + "id": "093a4a1b-af74-4ead-939a-47e0eb1482d9", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm:" + "In order to get samples with the optimized parameters, we call the `get_results` method:" ] }, { "cell_type": "code", - "execution_count": 12, - "id": "1631190c-308e-4300-9984-021fef022f2d", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:02:57.622149Z", - "iopub.status.busy": "2024-05-07T16:02:57.621887Z", - "iopub.status.idle": "2024-05-07T16:02:58.754711Z", - "shell.execute_reply": "2024-05-07T16:02:58.753952Z" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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probabilitycostsolutioncount
4010.0015.0[1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0]1
5720.0014.0[1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0]1
3340.0013.0[1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0]1
2220.0013.0[0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1]1
1690.0013.0[0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0]1
\n", - "
" - ], - "text/plain": [ - " probability cost solution count\n", - "401 0.001 5.0 [1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0] 1\n", - "572 0.001 4.0 [1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0] 1\n", - "334 0.001 3.0 [1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0] 1\n", - "222 0.001 3.0 [0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1] 1\n", - "169 0.001 3.0 [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0] 1" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "id": "194f8264-7268-4bbe-b9bf-746cd5f1f7d9", + "metadata": {}, + "outputs": [], "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " coloring_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=False).head(5)" + "optimization_result = combi.get_results()\n", + "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { "cell_type": "markdown", - "id": "1de0dda7-16f4-40a8-91f6-d65eb9e73565", + "id": "ce1e11a5-6075-4048-8541-fd4a1cf3ec1b", "metadata": {}, "source": [ "And the histogram:" @@ -602,41 +404,19 @@ }, { "cell_type": "code", - "execution_count": 13, - "id": "f57b11fe-d3de-4226-9b1e-f2d82ccb51ef", + "execution_count": null, + "id": "33712444-2c7f-4b42-8f2b-1de7fb52c861", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:02:58.759575Z", - "iopub.status.busy": "2024-05-07T16:02:58.758336Z", - "iopub.status.idle": "2024-05-07T16:02:59.110565Z", - "shell.execute_reply": "2024-05-07T16:02:59.109232Z" - }, "tags": [] }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[]], dtype=object)" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" + "optimization_result[\"cost\"].plot(\n", + " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + ")\n", + "plt.ylabel(\"Probability\", fontsize=16)\n", + "plt.xlabel(\"cost\", fontsize=16)\n", + "plt.tick_params(axis=\"both\", labelsize=14)" ] }, { @@ -649,33 +429,17 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "b8994248-1c5a-4959-8845-e325755833d4", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:02:59.115579Z", - "iopub.status.busy": "2024-05-07T16:02:59.114407Z", - "iopub.status.idle": "2024-05-07T16:02:59.353197Z", - "shell.execute_reply": "2024-05-07T16:02:59.352509Z" - }, "tags": [] }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", - "best_solution = optimization_result.solution[optimization_result.cost.idxmax()]\n", + "best_solution = optimization_result.solution[optimization_result.cost.idxmin()]\n", + "best_solution = [best_solution[f\"x_{v}\"] for v in range(len(best_solution))]\n", "\n", "one_hot_solution = np.array(best_solution).reshape([NUM_COLORS, len(graph.nodes)])\n", "integer_solution = np.argmax(one_hot_solution, axis=0)\n", @@ -706,38 +470,15 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "73d2b211-52e7-4c29-9c46-8153129aba79", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:02:59.358007Z", - "iopub.status.busy": "2024-05-07T16:02:59.356906Z", - "iopub.status.idle": "2024-05-07T16:02:59.537763Z", - "shell.execute_reply": "2024-05-07T16:02:59.537165Z" - }, "pycharm": { "name": "#%%\n" }, "tags": [] }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ERROR: Solver (asl) returned non-zero return code (-6)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ERROR: Solver log: Couenne 0.5.8 -- an Open-Source solver for Mixed Integer\n", - " Nonlinear Optimization Mailing list: couenne@list.coin-or.org\n", - " Instructions: http://www.coin-or.org/Couenne malloc_consolidate(): invalid\n", - " chunk size couenne:\n" - ] - }, { "name": "stdout", "output_type": "stream", @@ -815,15 +556,9 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "c4a11618-40ae-4174-b296-a37afa65adce", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T16:02:59.552664Z", - "iopub.status.busy": "2024-05-07T16:02:59.552129Z", - "iopub.status.idle": "2024-05-07T16:02:59.564143Z", - "shell.execute_reply": "2024-05-07T16:02:59.563341Z" - }, "tags": [] }, "outputs": [], @@ -866,7 +601,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" }, "vscode": { "interpreter": { diff --git a/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.qmod b/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.qmod index dd063f80c..8141bce1e 100644 --- a/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.qmod +++ b/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.qmod @@ -1,6721 +1,27 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=335.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-79.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-79.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-79.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-79.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-79.25 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-79.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-102.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-102.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-102.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-102.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-127.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-127.25 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=16.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=16.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=12.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=12.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - 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], - coefficient=12.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=12.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=12.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=12.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=12.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=12.0 - 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coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=1.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=2.0 - } -]; - -qfunc main(params_list: real[16], output target: qbit[12]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + x_0,0: qbit; + x_0,1: qbit; + x_0,2: qbit; + x_0,3: qbit; + x_0,4: qbit; + x_0,5: qbit; + x_1,0: qbit; + x_1,1: qbit; + x_1,2: qbit; + x_1,3: qbit; + x_1,4: qbit; + x_1,5: qbit; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=True, -initial_point=[0.0, 0.030585312839621178, 0.004369330405660168, 0.026215982433961012, 0.008738660811320336, 0.021846652028300842, 0.013107991216980504, 0.017477321622640672, 0.017477321622640672, 0.013107991216980506, 0.02184665202830084, 0.00873866081132034, 0.02621598243396101, 0.00436933040566017, 0.030585312839621178, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=20, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=0.7 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[16], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 8) { + phase (-(((((((((((((((20 * v.x_0,0) * v.x_1,0) + ((20 * v.x_0,1) * v.x_1,1)) + ((20 * v.x_0,2) * v.x_1,2)) + ((20 * v.x_0,3) * v.x_1,3)) + ((20 * v.x_0,4) * v.x_1,4)) + ((20 * v.x_0,5) * v.x_1,5)) + ((1 - v.x_0,0) * (1 - v.x_1,0))) + ((1 - v.x_0,1) * (1 - v.x_1,1))) + ((1 - v.x_0,2) * (1 - v.x_1,2))) + ((1 - v.x_0,3) * (1 - v.x_1,3))) + ((1 - v.x_0,4) * (1 - v.x_1,4))) + ((1 - v.x_0,5) * (1 - v.x_1,5))) + (20 * (((((((((((((v.x_0,0 * ((v.x_0,1 + v.x_0,2) + v.x_0,4)) + (v.x_0,1 * (((v.x_0,0 + v.x_0,2) + v.x_0,3) + v.x_0,5))) + (v.x_0,2 * ((((v.x_0,0 + v.x_0,1) + v.x_0,3) + v.x_0,4) + v.x_0,5))) + (v.x_0,3 * ((v.x_0,1 + v.x_0,2) + v.x_0,4))) + (v.x_0,4 * (((v.x_0,0 + v.x_0,2) + v.x_0,3) + v.x_0,5))) + (v.x_0,5 * ((v.x_0,1 + v.x_0,2) + v.x_0,4))) + (v.x_1,0 * ((v.x_1,1 + v.x_1,2) + v.x_1,4))) + (v.x_1,1 * (((v.x_1,0 + v.x_1,2) + v.x_1,3) + v.x_1,5))) + (v.x_1,2 * ((((v.x_1,0 + v.x_1,1) + v.x_1,3) + v.x_1,4) + v.x_1,5))) + (v.x_1,3 * ((v.x_1,1 + v.x_1,2) + v.x_1,4))) + (v.x_1,4 * (((v.x_1,0 + v.x_1,2) + v.x_1,3) + v.x_1,5))) + (v.x_1,5 * ((v.x_1,1 + v.x_1,2) + v.x_1,4))) ** 2))) - 6), params[i]); + apply_to_all(lambda(q) { + RX(params[8 + i], q); + }, v); + } +} diff --git a/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.synthesis_options.json b/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.synthesis_options.json index 0967ef424..9d45b874d 100644 --- a/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.synthesis_options.json +++ b/applications/optimization/max_induced_k_color_subgraph/max_induced_k_color_subgraph.synthesis_options.json @@ -1 +1,43 @@ -{} +{ + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "x", + "h", + "t", + "sxdg", + "z", + "cx", + "id", + "r", + "rz", + "sdg", + "sx", + "p", + "s", + "u", + "y", + "cy", + "u1", + "tdg", + "ry", + "rx", + "u2", + "cz" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 979577880 + } +} diff --git a/applications/optimization/min_graph_coloring/min_graph_coloring.ipynb b/applications/optimization/min_graph_coloring/min_graph_coloring.ipynb index 930b0a113..275bf3b39 100644 --- a/applications/optimization/min_graph_coloring/min_graph_coloring.ipynb +++ b/applications/optimization/min_graph_coloring/min_graph_coloring.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "13d83b59-57f7-48ee-8bff-deda7d28edc5", + "id": "0c4b6a3a-5be7-44a0-98bd-d18798a77ce1", "metadata": { "tags": [] }, @@ -13,7 +13,7 @@ }, { "cell_type": "markdown", - "id": "6d56bb6d-9f3b-45db-8e98-b50f27af7505", + "id": "23c657a0-b7cb-4b1b-8ef8-9fd0bebffb77", "metadata": { "jp-MarkdownHeadingCollapsed": true, "lines_to_next_cell": 2, @@ -23,17 +23,17 @@ "\n", "## Background\n", "\n", - "Given a graph $G = (V,E)$, find the minimal number of colors k\u2000required to properly color it.\n", + "Given a graph $G = (V,E)$, find the minimal number of colors k required to properly color it.\n", "A coloring is legal if:\n", "\n", "- each vetrex ${v_i}$ is assigned with a color $k_i \\in \\{0, 1, ..., k-1\\}$\n", "- adajecnt vertex have different colors: for each $v_i, v_j$ such that $(v_i, v_j) \\in E$, $k_i \\neq k_j$.\n", - "A graph which is k-colorable but not (k\u22121)-colorable is said to have chromatic number k. The maximum bound on the chromatic number is $D_G + 1$, where $D_G$ is the maximum vertex degree. The graph coloring problem is known to be in the NP-hard complexity class." + "A graph which is k-colorable but not (k−1)-colorable is said to have chromatic number k. The maximum bound on the chromatic number is $D_G + 1$, where $D_G$ is the maximum vertex degree. The graph coloring problem is known to be in the NP-hard complexity class." ] }, { "cell_type": "markdown", - "id": "0bdc4e6a-199b-44b3-bd3f-fd24722b616b", + "id": "36fef965-da2a-44a7-a58d-e9d3618f8612", "metadata": { "tags": [] }, @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "5eeb0034-b0e0-4aa4-93f5-7172437c5cdd", + "id": "8dc3596d-8ee9-462c-99c6-a3d8e60fc604", "metadata": { "tags": [] }, @@ -54,7 +54,7 @@ }, { "cell_type": "markdown", - "id": "b80625e0-9c9c-4ed2-9109-0493521ac310", + "id": "ff141ef7-5ed2-4821-834d-eee9a88ff33f", "metadata": {}, "source": [ "We encode the graph coloring with a matrix of variables `X` with dimensions $k \\times |V|$ using one-hot encoding, such that a $X_{ki} = 1$ means that vertex i is colored by color k.\n", @@ -64,15 +64,9 @@ }, { "cell_type": "code", - "execution_count": 1, - "id": "83ddbd07-f7ab-4d80-b357-3890622d395f", + "execution_count": 19, + "id": "246653bf-083d-4b5d-a1f3-20c5a203f753", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:30.726956Z", - "iopub.status.busy": "2024-05-07T15:52:30.726492Z", - "iopub.status.idle": "2024-05-07T15:52:31.138614Z", - "shell.execute_reply": "2024-05-07T15:52:31.137980Z" - }, "tags": [] }, "outputs": [], @@ -116,7 +110,7 @@ }, { "cell_type": "markdown", - "id": "3496c5d6-7df6-49fb-b5b9-5ba48d2b7d62", + "id": "a4782f3c-a919-4071-9423-ac9f21ce25e1", "metadata": {}, "source": [ "### Initialize the model with example graph" @@ -124,21 +118,15 @@ }, { "cell_type": "code", - "execution_count": 2, - "id": "bc9871c1-224e-4206-b39e-af7e448aca70", + "execution_count": 20, + "id": "425c830a-2e2e-4a9a-b9c6-e2fd2cd145d0", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:31.141813Z", - "iopub.status.busy": "2024-05-07T15:52:31.141172Z", - "iopub.status.idle": "2024-05-07T15:52:31.697290Z", - "shell.execute_reply": "2024-05-07T15:52:31.696530Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -160,7 +148,7 @@ }, { "cell_type": "markdown", - "id": "958deac9-b057-485e-bea0-52b95664ae6b", + "id": "e18b6a77-a08c-454d-a89a-efb8c2a2dbe7", "metadata": {}, "source": [ "### show the resulting pyomo model" @@ -168,15 +156,10 @@ }, { "cell_type": "code", - "execution_count": 3, - "id": "e5ba50c9-5d89-4ebf-9475-830da3ce5539", + "execution_count": 21, + "id": "4f74ecd0-9096-4050-88e5-da6361e7ff81", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:31.700521Z", - "iopub.status.busy": "2024-05-07T15:52:31.699501Z", - "iopub.status.idle": "2024-05-07T15:52:31.706355Z", - "shell.execute_reply": "2024-05-07T15:52:31.705805Z" - }, + "scrolled": true, "tags": [] }, "outputs": [ @@ -244,149 +227,38 @@ }, { "cell_type": "markdown", - "id": "fed74b17-0343-410f-b061-f4f8e422c3ab", - "metadata": {}, - "source": [ - "### Initialize classiq QAOA solver" - ] - }, - { - "cell_type": "markdown", - "id": "ccba58ac-beef-47cd-8e55-fa84d652eb65", + "id": "d5846ab0-800c-4e81-9a9e-ac8dc7363893", "metadata": { "tags": [] }, "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):" + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the qaoa algorithm, with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { "cell_type": "code", - "execution_count": 4, - "id": "bcf6b25c-d91a-418d-9de7-9bfbe5d8a42a", + "execution_count": 23, + "id": "816b468f-a59f-4f2f-8337-4a9d66548425", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:31.708858Z", - "iopub.status.busy": "2024-05-07T15:52:31.708376Z", - "iopub.status.idle": "2024-05-07T15:52:33.883015Z", - "shell.execute_reply": "2024-05-07T15:52:33.882200Z" - }, "tags": [] }, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "qaoa_config = QAOAConfig(num_layers=6, penalty_energy=10.0)" - ] - }, - { - "cell_type": "markdown", - "id": "e7de6b8d-bb0e-4d01-9259-59340b2f1e83", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "37b4ee2f-3be3-4431-961b-83f7daa619fb", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:33.888302Z", - "iopub.status.busy": "2024-05-07T15:52:33.886923Z", - "iopub.status.idle": "2024-05-07T15:52:33.893699Z", - "shell.execute_reply": "2024-05-07T15:52:33.892867Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "optimizer_config = OptimizerConfig(alpha_cvar=0.3)" - ] - }, - { - "cell_type": "markdown", - "id": "beb4daac-5567-4d30-9f7a-2c7255807f85", - "metadata": {}, - "source": [ - "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "94aa17c5-439d-4dc6-9470-74993d9c9fd5", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:33.898244Z", - "iopub.status.busy": "2024-05-07T15:52:33.897051Z", - "iopub.status.idle": "2024-05-07T15:52:36.640923Z", - "shell.execute_reply": "2024-05-07T15:52:36.639960Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=coloring_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "7433de86-94d3-4ab2-96d8-c6e22f8f7133", - "metadata": {}, - "source": [ - "We also set the quantum backend we want to execute on:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "a7d86d74-2f1c-49c4-af90-878295ceb55b", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:36.645399Z", - "iopub.status.busy": "2024-05-07T15:52:36.645005Z", - "iopub.status.idle": "2024-05-07T15:52:37.189978Z", - "shell.execute_reply": "2024-05-07T15:52:37.189309Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", + "combi = CombinatorialProblem(pyo_model=coloring_model, num_layers=6, penalty_factor=10)\n", "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", - ")" + "qmod = combi.get_model()" ] }, { "cell_type": "code", - "execution_count": 8, - "id": "17ed6f20-f1e7-4305-86ad-91f3e6939e0b", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:37.194561Z", - "iopub.status.busy": "2024-05-07T15:52:37.193386Z", - "iopub.status.idle": "2024-05-07T15:52:37.824276Z", - "shell.execute_reply": "2024-05-07T15:52:37.823525Z" - } - }, + "execution_count": 24, + "id": "62ec28b3-cb49-411a-8c4a-8004fff6c105", + "metadata": {}, "outputs": [], "source": [ "write_qmod(qmod, \"min_graph_coloring\")" @@ -394,7 +266,7 @@ }, { "cell_type": "markdown", - "id": "8f1a08a1-2ed6-46c6-9083-afd3d8b4e268", + "id": "943291f0-6a9f-4286-a69d-ef13a0a12ef6", "metadata": {}, "source": [ "## Synthesizing the QAOA Circuit and Solving the Problem\n", @@ -404,102 +276,90 @@ }, { "cell_type": "code", - "execution_count": 9, - "id": "3a99384f-c835-44a5-811c-bc69b5c60aae", + "execution_count": 25, + "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:37.828100Z", - "iopub.status.busy": "2024-05-07T15:52:37.827841Z", - "iopub.status.idle": "2024-05-07T15:53:53.579236Z", - "shell.execute_reply": "2024-05-07T15:53:53.577934Z" - }, "pycharm": { "name": "#%%\n" }, + "scrolled": true, "tags": [] }, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Opening: https://platform.classiq.io/circuit/8da93adf-8ec5-44a4-838a-7d1f172c55db?version=0.41.0.dev39%2B79c8fd0855\n" + "ename": "ClassiqAPIError", + "evalue": "Internal error occurred. Please contact Classiq support.\nError number 122001 occurred:\n\nError identifier: EE2BDCFA1-76C0-4282-A217-1E566BB5B8CC\nIf you need further assistance, please reach out on our Community Slack channel at: https://short.classiq.io/join-slack", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mClassiqAPIError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[25], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m qprog \u001b[38;5;241m=\u001b[39m \u001b[43mcombi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_qprog\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m show(qprog)\n", + "File \u001b[0;32m~/classiq-library/applications/optimization/min_graph_coloring/combinatorial_problem.py:73\u001b[0m, in \u001b[0;36mCombinatorialProblem.get_qprog\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 71\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel_ \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 72\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcreate_model()\n\u001b[0;32m---> 73\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_ \u001b[38;5;241m=\u001b[39m \u001b[43msynthesize\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel_\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/synthesis.py:85\u001b[0m, in \u001b[0;36msynthesize\u001b[0;34m(serialized_model, auto_show)\u001b[0m\n\u001b[1;32m 71\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msynthesize\u001b[39m(\n\u001b[1;32m 72\u001b[0m serialized_model: SerializedModel, auto_show: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 73\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m SerializedQuantumProgram:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 75\u001b[0m \u001b[38;5;124;03m Synthesize a model with the Classiq engine to receive a quantum program.\u001b[39;00m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;124;03m [More details](https://docs.classiq.io/latest/reference-manual/synthesis/)\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 83\u001b[0m \u001b[38;5;124;03m SerializedQuantumProgram: Quantum program serialized as a string. (See: QuantumProgram)\u001b[39;00m\n\u001b[1;32m 84\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 85\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43masync_utils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43msynthesize_async\u001b[49m\u001b[43m(\u001b[49m\u001b[43mserialized_model\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m auto_show:\n\u001b[1;32m 87\u001b[0m show(result)\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/async_utils.py:37\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(coro)\u001b[0m\n\u001b[1;32m 32\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrun\u001b[39m(coro: Awaitable[T]) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m T:\n\u001b[1;32m 33\u001b[0m \u001b[38;5;66;03m# Use this function instead of asyncio.run, since it ALWAYS\u001b[39;00m\n\u001b[1;32m 34\u001b[0m \u001b[38;5;66;03m# creates a new event loop and clears the thread event loop.\u001b[39;00m\n\u001b[1;32m 35\u001b[0m \u001b[38;5;66;03m# Never use asyncio.run in library code.\u001b[39;00m\n\u001b[1;32m 36\u001b[0m loop \u001b[38;5;241m=\u001b[39m get_event_loop()\n\u001b[0;32m---> 37\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mloop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_until_complete\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcoro\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/nest_asyncio.py:98\u001b[0m, in \u001b[0;36m_patch_loop..run_until_complete\u001b[0;34m(self, future)\u001b[0m\n\u001b[1;32m 95\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m f\u001b[38;5;241m.\u001b[39mdone():\n\u001b[1;32m 96\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 97\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mEvent loop stopped before Future completed.\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m---> 98\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresult\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/asyncio/futures.py:203\u001b[0m, in \u001b[0;36mFuture.result\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 201\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__log_traceback \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 202\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 203\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception\u001b[38;5;241m.\u001b[39mwith_traceback(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception_tb)\n\u001b[1;32m 204\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_result\n", + "File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/asyncio/tasks.py:267\u001b[0m, in \u001b[0;36mTask.__step\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 263\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 264\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m exc \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 265\u001b[0m \u001b[38;5;66;03m# We use the `send` method directly, because coroutines\u001b[39;00m\n\u001b[1;32m 266\u001b[0m \u001b[38;5;66;03m# don't have `__iter__` and `__next__` methods.\u001b[39;00m\n\u001b[0;32m--> 267\u001b[0m result \u001b[38;5;241m=\u001b[39m coro\u001b[38;5;241m.\u001b[39msend(\u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 268\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 269\u001b[0m result \u001b[38;5;241m=\u001b[39m coro\u001b[38;5;241m.\u001b[39mthrow(exc)\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/synthesis.py:67\u001b[0m, in \u001b[0;36msynthesize_async\u001b[0;34m(serialized_model)\u001b[0m\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msynthesize_async\u001b[39m(\n\u001b[1;32m 64\u001b[0m serialized_model: SerializedModel,\n\u001b[1;32m 65\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m SerializedQuantumProgram:\n\u001b[1;32m 66\u001b[0m model \u001b[38;5;241m=\u001b[39m Model\u001b[38;5;241m.\u001b[39mmodel_validate_json(serialized_model)\n\u001b[0;32m---> 67\u001b[0m quantum_program \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m ApiWrapper\u001b[38;5;241m.\u001b[39mcall_generation_task(model)\n\u001b[1;32m 68\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m SerializedQuantumProgram(quantum_program\u001b[38;5;241m.\u001b[39mmodel_dump_json(indent\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m))\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/api_wrapper.py:125\u001b[0m, in \u001b[0;36mApiWrapper.call_generation_task\u001b[0;34m(cls, model, http_client)\u001b[0m\n\u001b[1;32m 121\u001b[0m poller \u001b[38;5;241m=\u001b[39m JobPoller(base_url\u001b[38;5;241m=\u001b[39mroutes\u001b[38;5;241m.\u001b[39mTASKS_GENERATE_FULL_PATH)\n\u001b[1;32m 122\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m poller\u001b[38;5;241m.\u001b[39mrun_pydantic(\n\u001b[1;32m 123\u001b[0m model, timeout_sec\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, http_client\u001b[38;5;241m=\u001b[39mhttp_client\n\u001b[1;32m 124\u001b[0m )\n\u001b[0;32m--> 125\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_parse_job_response\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresult\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgenerator_result\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mQuantumProgram\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/api_wrapper.py:61\u001b[0m, in \u001b[0;36m_parse_job_response\u001b[0;34m(job_result, output_type)\u001b[0m\n\u001b[1;32m 59\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m output_type\u001b[38;5;241m.\u001b[39mmodel_validate(job_result\u001b[38;5;241m.\u001b[39mresult)\n\u001b[1;32m 60\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m job_result\u001b[38;5;241m.\u001b[39mfailure_details:\n\u001b[0;32m---> 61\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ClassiqAPIError(job_result\u001b[38;5;241m.\u001b[39mfailure_details)\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ClassiqAPIError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnexpected response from server\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[0;31mClassiqAPIError\u001b[0m: Internal error occurred. Please contact Classiq support.\nError number 122001 occurred:\n\nError identifier: EE2BDCFA1-76C0-4282-A217-1E566BB5B8CC\nIf you need further assistance, please reach out on our Community Slack channel at: https://short.classiq.io/join-slack" ] } ], "source": [ - "qprog = synthesize(qmod)\n", + "qprog = combi.get_qprog()\n", "show(qprog)" ] }, { "cell_type": "markdown", - "id": "bd7640ce-3bed-4d79-97e8-fce32d29e720", + "id": "b119464b-9d46-4ea0-ba4a-1734f3e0e3e5", "metadata": {}, "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" + "We also set the quantum backend we want to execute on:" ] }, { "cell_type": "code", - "execution_count": 10, - "id": "9c5fc0fc-3f9c-457e-9a7f-97d21290c67b", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:53:53.583996Z", - "iopub.status.busy": "2024-05-07T15:53:53.582796Z", - "iopub.status.idle": "2024-05-07T15:59:25.538607Z", - "shell.execute_reply": "2024-05-07T15:59:25.537830Z" - }, - "tags": [] - }, + "execution_count": null, + "id": "7d188c69-21d1-4afe-86b1-46229e91a01e", + "metadata": {}, "outputs": [], "source": [ - "result = execute(qprog).result_value()" + "from classiq.execution import *\n", + "\n", + "execution_preferences = ExecutionPreferences(\n", + " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\"),\n", + ")" ] }, { "cell_type": "markdown", - "id": "1e7b9756-2703-41ae-a7b6-0ad3ce270330", + "id": "07621d7c-0e54-4adb-9c47-8fd99a346e29", "metadata": {}, "source": [ - "We can check the convergence of the run:" + "We now solve the problem by calling the `optimize` method of the `CombinatorialProblem` object. For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`maxiter`) and the $\\alpha$-parameter (`quantile`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[2](#cvar)]:" ] }, { "cell_type": "code", - "execution_count": 11, - "id": "0d3191c7-ea88-4888-a1b7-aeed6cc65cf2", + "execution_count": 13, + "id": "62d12d20-1c80-4a9e-bb6b-b1fddc6cbe40", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:25.544008Z", - "iopub.status.busy": "2024-05-07T15:59:25.542827Z", - "iopub.status.idle": "2024-05-07T15:59:25.600344Z", - "shell.execute_reply": "2024-05-07T15:59:25.597759Z" - }, "tags": [] }, - "outputs": [ - { - "data": { - "image/jpeg": 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", - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "result.convergence_graph" + "cost_values = []\n", + "optimized_params = combi.optimize(\n", + " execution_preferences, maxiter=70, cost_trace=cost_values, quantile=0.3\n", + ")" ] }, { "cell_type": "markdown", - "id": "8e75fc5d-29fe-4392-a6fb-64a76ca4c0b8", + "id": "615ed612-b835-4bf0-aa92-92d30ef8006d", "metadata": { "tags": [] }, @@ -509,25 +369,17 @@ }, { "cell_type": "markdown", - "id": "6224908a-8b94-4f43-a73f-b647f6bcd56f", + "id": "9de050b9-cded-4990-a86c-e9ed3023555c", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm:" + "We can also examine the statistics of the algorithm. In order to get samples with the optimized parameters, we call the `get_results` method:" ] }, { "cell_type": "code", - "execution_count": 12, - "id": "50ce011c-6ad5-4ef8-b23b-0f009f464bad", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:25.604399Z", - "iopub.status.busy": "2024-05-07T15:59:25.604039Z", - "iopub.status.idle": "2024-05-07T15:59:27.456960Z", - "shell.execute_reply": "2024-05-07T15:59:27.455248Z" - }, - "tags": [] - }, + "execution_count": 9, + "id": "9638f749-a60b-4176-a4ea-50d7c2bb986f", + "metadata": {}, "outputs": [ { "data": { @@ -550,83 +402,106 @@ " \n", " \n", " \n", + " solution\n", " probability\n", " cost\n", - " solution\n", - " count\n", " \n", " \n", " \n", " \n", - " 301\n", - " 0.001\n", - " 3.0\n", - " [1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0]\n", - " 1\n", + " 96\n", + " {'x_0': 1, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'...\n", + " 0.001953\n", + " -4.0\n", " \n", " \n", - " 466\n", - " 0.001\n", - " 3.0\n", - " [0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0]\n", - " 1\n", + " 108\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'...\n", + " 0.000977\n", + " -4.0\n", " \n", " \n", - " 734\n", - " 0.001\n", - " 12.0\n", - " [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1]\n", - " 1\n", + " 52\n", + " {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'...\n", + " 0.007812\n", + " -3.0\n", " \n", " \n", - " 47\n", - " 0.002\n", - " 12.0\n", - " [0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1]\n", - " 2\n", + " 28\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.011230\n", + " -3.0\n", " \n", " \n", - " 533\n", - " 0.001\n", - " 12.0\n", - " [0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]\n", - " 1\n", + " 32\n", + " {'x_0': 0, 'x_1': 0, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.010254\n", + " -3.0\n", " \n", " \n", "\n", "" ], "text/plain": [ - " probability cost solution count\n", - "301 0.001 3.0 [1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0] 1\n", - "466 0.001 3.0 [0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0] 1\n", - "734 0.001 12.0 [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1] 1\n", - "47 0.002 12.0 [0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1] 2\n", - "533 0.001 12.0 [0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0] 1" + " solution probability cost\n", + "96 {'x_0': 1, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'... 0.001953 -4.0\n", + "108 {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'... 0.000977 -4.0\n", + "52 {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'... 0.007812 -3.0\n", + "28 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.011230 -3.0\n", + "32 {'x_0': 0, 'x_1': 0, 'x_2': 0, 'x_3': 1, 'x_4'... 0.010254 -3.0" ] }, - "execution_count": 12, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import pandas as pd\n", + "optimization_result = combi.get_results()\n", + "optimization_result.sort_values(by=\"cost\").head(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "29cef77e-e7a3-419c-a5ba-7d889bf5a6ba", + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-07T15:59:27.762214Z", + "iopub.status.busy": "2024-05-07T15:59:27.761227Z", + "iopub.status.idle": "2024-05-07T15:59:27.912020Z", + "shell.execute_reply": "2024-05-07T15:59:27.911357Z" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", + "best_solution = optimization_result.solution[optimization_result.cost.idxmin()]\n", + "best_solution = [best_solution[f\"x_{v}\"] for v in range(len(best_solution))]\n", "\n", - "solution = get_optimization_solution_from_pyo(\n", - " coloring_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=True).head(5)" + "one_hot_solution = np.array(best_solution).reshape([max_num_colors, len(graph.nodes)])\n", + "integer_solution = np.argmax(one_hot_solution, axis=0)\n", + "nx.draw_kamada_kawai(\n", + " graph, with_labels=True, node_color=integer_solution, cmap=plt.cm.rainbow\n", + ")" ] }, { "cell_type": "markdown", - "id": "dc772380-e47e-4ce7-9ed9-c62879911c09", + "id": "687f492b-a4a5-49c6-964c-8959b035bb93", "metadata": {}, "source": [ "And the histogram:" @@ -634,15 +509,9 @@ }, { "cell_type": "code", - "execution_count": 13, - "id": "9793d479-62f9-4a4b-92bc-439eb1ef9ba5", + "execution_count": 10, + "id": "31a4e74d-b2b8-42e0-826d-de7b51de1fe8", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:27.461831Z", - "iopub.status.busy": "2024-05-07T15:59:27.460621Z", - "iopub.status.idle": "2024-05-07T15:59:27.757270Z", - "shell.execute_reply": "2024-05-07T15:59:27.756515Z" - }, "tags": [] }, "outputs": [ @@ -652,13 +521,13 @@ "array([[]], dtype=object)" ] }, - "execution_count": 13, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -668,57 +537,49 @@ } ], "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" + "optimization_result[\"cost\"].plot(\n", + " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + ")\n", + "plt.ylabel(\"Probability\", fontsize=16)\n", + "plt.xlabel(\"cost\", fontsize=16)\n", + "plt.tick_params(axis=\"both\", labelsize=14)" ] }, { "cell_type": "markdown", - "id": "2ba86406-7487-449d-a790-0c8fcec11b73", + "id": "a3a890a1-c5d4-409d-b9a3-d7ffd4fdd6c0", "metadata": {}, "source": [ - "Let us plot the best solution:" + "Let us plot the solution:" ] }, { "cell_type": "code", - "execution_count": 14, - "id": "da924ee8-2a38-470b-9175-37a05c22f7ed", + "execution_count": 11, + "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:59:27.762214Z", - "iopub.status.busy": "2024-05-07T15:59:27.761227Z", - "iopub.status.idle": "2024-05-07T15:59:27.912020Z", - "shell.execute_reply": "2024-05-07T15:59:27.911357Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/png": 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", "text/plain": [ - "
" + "{'x_0': 1, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4': 0, 'x_5': 0, 'x_6': 0}" ] }, + "execution_count": 11, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "import matplotlib.pyplot as plt\n", - "\n", "best_solution = optimization_result.solution[optimization_result.cost.idxmin()]\n", - "\n", - "one_hot_solution = np.array(best_solution).reshape([max_num_colors, len(graph.nodes)])\n", - "integer_solution = np.argmax(one_hot_solution, axis=0)\n", - "nx.draw_kamada_kawai(\n", - " graph, with_labels=True, node_color=integer_solution, cmap=plt.cm.rainbow\n", - ")" + "best_solution" ] }, { "cell_type": "markdown", - "id": "df8a97c2-e473-4744-965a-f48a6a383a70", + "id": "226afe35-03e1-4a3c-a06d-5fa815a80550", "metadata": {}, "source": [ "## Classical optimizer results" @@ -726,7 +587,7 @@ }, { "cell_type": "markdown", - "id": "e0e5afa5-f3bb-4770-9d33-f24872a531b6", + "id": "ecc3761d-99f6-4b69-907f-80c89a3dc8a7", "metadata": {}, "source": [ "Lastly, we can compare to the classical solution of the problem:" @@ -735,7 +596,7 @@ { "cell_type": "code", "execution_count": 15, - "id": "d964d750-4792-4fa9-b037-089babb25c76", + "id": "8cbac865-3363-4cce-b5a3-6176028060fa", "metadata": { "execution": { "iopub.execute_input": "2024-05-07T15:59:27.914604Z", @@ -845,7 +706,7 @@ { "cell_type": "code", "execution_count": 16, - "id": "c356a469-b506-457d-b442-f368be978d13", + "id": "98c9e5ab-322c-423d-aa66-06ee696c6aab", "metadata": { "execution": { "iopub.execute_input": "2024-05-07T15:59:28.176765Z", @@ -871,6 +732,24 @@ " graph, with_labels=True, node_color=integer_solution, cmap=plt.cm.rainbow\n", " )" ] + }, + { + "cell_type": "markdown", + "id": "e82b5953-122a-4707-8ab6-f741f14f13a5", + "metadata": { + "pycharm": { + "name": "#%% md\n" + }, + "tags": [] + }, + "source": [ + "\n", + "## References\n", + "\n", + "[1]: [Farhi, Edward, Jeffrey Goldstone, and Sam Gutmann. \"A quantum approximate optimization algorithm.\" arXiv preprint arXiv:1411.4028 (2014).](https://arxiv.org/abs/1411.4028)\n", + "\n", + "[2]: [Barkoutsos, Panagiotis Kl, et al. \"Improving variational quantum optimization using CVaR.\" Quantum 4 (2020): 256.](https://arxiv.org/abs/1907.04769)\n" + ] } ], "metadata": { @@ -889,7 +768,12 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" + }, + "vscode": { + "interpreter": { + "hash": "a07aacdcc8a415e7643a2bc993226848ff70704ebef014f87460de9126b773d0" + } } }, "nbformat": 4, diff --git a/applications/optimization/min_graph_coloring/min_graph_coloring.qmod b/applications/optimization/min_graph_coloring/min_graph_coloring.qmod index d6ce5d209..b5fbcc83b 100644 --- a/applications/optimization/min_graph_coloring/min_graph_coloring.qmod +++ b/applications/optimization/min_graph_coloring/min_graph_coloring.qmod @@ -1,7903 +1,30 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - 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Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.9688 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.9688 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.9688 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.9688 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.9688 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=4.9688 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z - ], - coefficient=-0.0312 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-0.0312 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-0.0312 - } -]; - -qfunc main(params_list: real[12], output target: qbit[15]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + x_0,0: qbit; + x_0,1: qbit; + x_0,2: qbit; + x_0,3: qbit; + x_0,4: qbit; + x_1,0: qbit; + x_1,1: qbit; + x_1,2: qbit; + x_1,3: qbit; + x_1,4: qbit; + x_2,0: qbit; + x_2,1: qbit; + x_2,2: qbit; + x_2,3: qbit; + x_2,4: qbit; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=False, -initial_point=[0.0, 0.013392079468735527, 0.002678415893747106, 0.010713663574988423, 0.005356831787494212, 0.008035247681241316, 0.008035247681241317, 0.00535683178749421, 0.010713663574988423, 0.002678415893747105, 0.013392079468735527, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=0, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=0.3 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[12], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 6) { + phase (-((((((((((((((-(1 - v.x_0,0)) * (1 - v.x_0,1)) * (1 - v.x_0,2)) * (1 - v.x_0,3)) * (1 - v.x_0,4)) - (((((1 - v.x_1,0) * (1 - v.x_1,1)) * (1 - v.x_1,2)) * (1 - v.x_1,3)) * (1 - v.x_1,4))) - (((((1 - v.x_2,0) * (1 - v.x_2,1)) * (1 - v.x_2,2)) * (1 - v.x_2,3)) * (1 - v.x_2,4))) + (20 * ((((v.x_0,0 + v.x_1,0) + v.x_2,0) - 1) ** 2))) + (20 * ((((v.x_0,1 + v.x_1,1) + v.x_2,1) - 1) ** 2))) + (20 * ((((v.x_0,2 + v.x_1,2) + v.x_2,2) - 1) ** 2))) + (20 * ((((v.x_0,3 + v.x_1,3) + v.x_2,3) - 1) ** 2))) + (20 * ((((v.x_0,4 + v.x_1,4) + v.x_2,4) - 1) ** 2))) + (20 * ((((((((((((((((v.x_0,0 * v.x_0,4) + (v.x_0,0 * ((v.x_0,1 + v.x_0,3) + v.x_0,4))) + (v.x_0,1 * (v.x_0,0 + v.x_0,3))) + (v.x_0,2 * v.x_0,3)) + (v.x_0,3 * ((v.x_0,0 + v.x_0,1) + v.x_0,2))) + (v.x_1,0 * v.x_1,4)) + (v.x_1,0 * ((v.x_1,1 + v.x_1,3) + v.x_1,4))) + (v.x_1,1 * (v.x_1,0 + v.x_1,3))) + (v.x_1,2 * v.x_1,3)) + (v.x_1,3 * ((v.x_1,0 + v.x_1,1) + v.x_1,2))) + (v.x_2,0 * v.x_2,4)) + (v.x_2,0 * ((v.x_2,1 + v.x_2,3) + v.x_2,4))) + (v.x_2,1 * (v.x_2,0 + v.x_2,3))) + (v.x_2,2 * v.x_2,3)) + (v.x_2,3 * ((v.x_2,0 + v.x_2,1) + v.x_2,2))) ** 2))) + 3), params[i]); + apply_to_all(lambda(q) { + RX(params[6 + i], q); + }, v); + } +} diff --git a/applications/optimization/min_graph_coloring/min_graph_coloring.synthesis_options.json b/applications/optimization/min_graph_coloring/min_graph_coloring.synthesis_options.json index 0967ef424..3bed3abb6 100644 --- a/applications/optimization/min_graph_coloring/min_graph_coloring.synthesis_options.json +++ b/applications/optimization/min_graph_coloring/min_graph_coloring.synthesis_options.json @@ -1 +1,43 @@ -{} +{ + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "u1", + "u2", + "cx", + "sx", + "r", + "sdg", + "sxdg", + "cz", + "ry", + "u", + "h", + "x", + "z", + "rx", + "id", + "s", + "rz", + "y", + "cy", + "tdg", + "t", + "p" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 1581799683 + } +} diff --git a/applications/optimization/minimum_dominating_set/minimum_dominating_set.ipynb b/applications/optimization/minimum_dominating_set/minimum_dominating_set.ipynb index d952401b8..1583175e9 100644 --- a/applications/optimization/minimum_dominating_set/minimum_dominating_set.ipynb +++ b/applications/optimization/minimum_dominating_set/minimum_dominating_set.ipynb @@ -55,12 +55,6 @@ "execution_count": 1, "id": "49a9588b-e79e-4813-b7c5-ac068d7b930c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:25.623073Z", - "iopub.status.busy": "2024-05-07T15:49:25.622600Z", - "iopub.status.idle": "2024-05-07T15:49:26.563429Z", - "shell.execute_reply": "2024-05-07T15:49:26.562633Z" - }, "tags": [] }, "outputs": [], @@ -68,7 +62,6 @@ "import networkx as nx\n", "import numpy as np\n", "import pyomo.core as pyo\n", - "from IPython.display import Markdown, display\n", "from matplotlib import pyplot as plt" ] }, @@ -87,12 +80,6 @@ "execution_count": 2, "id": "48889b21-557b-481c-80c5-3c0b5c91adb6", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:26.569484Z", - "iopub.status.busy": "2024-05-07T15:49:26.567691Z", - "iopub.status.idle": "2024-05-07T15:49:26.575990Z", - "shell.execute_reply": "2024-05-07T15:49:26.575285Z" - }, "tags": [] }, "outputs": [], @@ -120,8 +107,8 @@ "\n", "- Index set declarations (model.Nodes, model.Arcs).\n", "- Binary variable declaration for each node (model.x) indicating whether that node is chosen for the set.\n", - "- Constraint rule \u2013 for each node, it must be a part of the chosen set or be neighbored by one.\n", - "- Objective rule \u2013 the sum of the variables equals the set size." + "- Constraint rule – for each node, it must be a part of the chosen set or be neighbored by one.\n", + "- Objective rule – the sum of the variables equals the set size." ] }, { @@ -129,18 +116,12 @@ "execution_count": 3, "id": "69359e3e-ed85-4b56-9afb-9dd4b9997ada", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:26.580604Z", - "iopub.status.busy": "2024-05-07T15:49:26.579463Z", - "iopub.status.idle": "2024-05-07T15:49:27.071051Z", - "shell.execute_reply": "2024-05-07T15:49:27.070323Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -162,12 +143,7 @@ "execution_count": 4, "id": "4a985b32-0670-42f3-ba50-5c0097eb75f5", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:27.075862Z", - "iopub.status.busy": "2024-05-07T15:49:27.074634Z", - "iopub.status.idle": "2024-05-07T15:49:27.084010Z", - "shell.execute_reply": "2024-05-07T15:49:27.083316Z" - }, + "scrolled": true, "tags": [] }, "outputs": [ @@ -218,102 +194,81 @@ }, { "cell_type": "markdown", - "id": "17ea14ec-dbb7-487c-b4f1-cabc8d5e3c29", + "id": "797d8aeb-6f65-44bf-87df-afb4e8e5c3d5", "metadata": { "tags": [] }, "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):" + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the qaoa algorithm, with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { "cell_type": "code", "execution_count": 5, - "id": "816b468f-a59f-4f2f-8337-4a9d66548425", + "id": "f95687fa-088f-4c63-8a9b-3570c0fb09f8", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:27.088831Z", - "iopub.status.busy": "2024-05-07T15:49:27.087615Z", - "iopub.status.idle": "2024-05-07T15:49:29.115837Z", - "shell.execute_reply": "2024-05-07T15:49:29.115200Z" - }, "tags": [] }, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "qaoa_config = QAOAConfig(num_layers=6, penalty_energy=8)" - ] - }, - { - "cell_type": "markdown", - "id": "db34d5ac-6877-4285-8dec-7bf7b37eb783", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" + "combi = CombinatorialProblem(pyo_model=mds_model, num_layers=6, penalty_factor=10)\n", + "\n", + "qmod = combi.get_model()" ] }, { "cell_type": "code", "execution_count": 6, - "id": "e41d0dd3-4135-4330-9ba3-c1b30c339a74", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:29.118667Z", - "iopub.status.busy": "2024-05-07T15:49:29.118296Z", - "iopub.status.idle": "2024-05-07T15:49:29.121576Z", - "shell.execute_reply": "2024-05-07T15:49:29.120968Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, + "id": "ad47b2ab-1596-4057-b084-4e47be033022", + "metadata": {}, "outputs": [], "source": [ - "optimizer_config = OptimizerConfig(max_iteration=30, alpha_cvar=0.7)" + "write_qmod(qmod, \"minimum_dominating_set\")" ] }, { "cell_type": "markdown", - "id": "214d6051-43b8-4b9d-8454-f9cdb62b4cf0", + "id": "e167d758-1228-4f5c-a68f-92a765a147a9", "metadata": {}, "source": [ - "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:" + "## Synthesizing the QAOA Circuit and Solving the Problem\n", + "\n", + "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" ] }, { "cell_type": "code", "execution_count": 7, - "id": "0243019c-6fc3-435f-b6ec-8b4355d6660c", + "id": "ab44a528-64d9-4da3-9d5a-2a9d4c3b332a", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:29.124125Z", - "iopub.status.busy": "2024-05-07T15:49:29.123766Z", - "iopub.status.idle": "2024-05-07T15:49:31.641160Z", - "shell.execute_reply": "2024-05-07T15:49:31.640352Z" - }, "pycharm": { "name": "#%%\n" }, + "scrolled": true, "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Opening: https://nightly.platform.classiq.io/circuit/aec0282d-a9b2-4d48-846c-192b5c127ea8?version=0.61.0.dev7\n" + ] + } + ], "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=mds_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" + "qprog = combi.get_qprog()\n", + "show(qprog)" ] }, { "cell_type": "markdown", - "id": "1fcc3812-c9d0-421c-84bb-38047297b33f", + "id": "52f58a5b-10c8-4af2-8abf-298b674ae714", "metadata": {}, "source": [ "We also set the quantum backend we want to execute on:" @@ -322,66 +277,30 @@ { "cell_type": "code", "execution_count": 8, - "id": "53bc041f-065c-44d2-b220-dafd9d0504ac", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:31.645316Z", - "iopub.status.busy": "2024-05-07T15:49:31.645031Z", - "iopub.status.idle": "2024-05-07T15:49:31.738219Z", - "shell.execute_reply": "2024-05-07T15:49:31.737432Z" - }, - "tags": [] - }, + "id": "e5232f48-39c7-4c9c-8f0b-ed81d86cfe93", + "metadata": {}, "outputs": [], "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", + "from classiq.execution import *\n", "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", + "execution_preferences = ExecutionPreferences(\n", + " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\"),\n", ")" ] }, - { - "cell_type": "code", - "execution_count": 9, - "id": "da54146e-edaa-45e8-8a6a-86b7e24be2a3", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:31.743816Z", - "iopub.status.busy": "2024-05-07T15:49:31.742506Z", - "iopub.status.idle": "2024-05-07T15:49:31.894435Z", - "shell.execute_reply": "2024-05-07T15:49:31.893596Z" - } - }, - "outputs": [], - "source": [ - "write_qmod(qmod, \"minimum_dominating_set\")" - ] - }, { "cell_type": "markdown", - "id": "943291f0-6a9f-4286-a69d-ef13a0a12ef6", + "id": "b689df0f-e09b-4f79-aee2-92a4626e9227", "metadata": {}, "source": [ - "## Synthesizing the QAOA Circuit and Solving the Problem\n", - "\n", - "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" + "We now solve the problem by calling the `optimize` method of the `CombinatorialProblem` object. For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`maxiter`) and the $\\alpha$-parameter (`quantile`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" ] }, { "cell_type": "code", - "execution_count": 10, - "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", + "execution_count": 9, + "id": "4e536b46-c25d-4037-9529-5fcd666ef749", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:31.899730Z", - "iopub.status.busy": "2024-05-07T15:49:31.898448Z", - "iopub.status.idle": "2024-05-07T15:49:46.574096Z", - "shell.execute_reply": "2024-05-07T15:49:46.572905Z" - }, - "pycharm": { - "name": "#%%\n" - }, "tags": [] }, "outputs": [ @@ -389,39 +308,17 @@ "name": "stdout", "output_type": "stream", "text": [ - "Opening: https://platform.classiq.io/circuit/d5cb21cc-5e64-4e4e-8ea7-414ea1afd2ee?version=0.41.0.dev39%2B79c8fd0855\n" + "CPU times: user 4min 20s, sys: 954 ms, total: 4min 21s\n", + "Wall time: 14min 1s\n" ] } ], "source": [ - "qprog = synthesize(qmod)\n", - "show(qprog)" - ] - }, - { - "cell_type": "markdown", - "id": "80238cf9-d7bd-46e5-9d48-b7cf23a6b304", - "metadata": {}, - "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "62d12d20-1c80-4a9e-bb6b-b1fddc6cbe40", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:49:46.578242Z", - "iopub.status.busy": "2024-05-07T15:49:46.577187Z", - "iopub.status.idle": "2024-05-07T15:52:05.144387Z", - "shell.execute_reply": "2024-05-07T15:52:05.143772Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "result = execute(qprog).result_value()" + "%%time\n", + "cost_values = []\n", + "optimized_params = combi.optimize(\n", + " execution_preferences, maxiter=70, cost_trace=cost_values, quantile=0.7\n", + ")" ] }, { @@ -434,33 +331,41 @@ }, { "cell_type": "code", - "execution_count": 12, - "id": "02454398-b229-403c-824a-b1eb539fbc1f", + "execution_count": 10, + "id": "092496fc-fd32-435a-a935-eab003b4c814", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:05.147275Z", - "iopub.status.busy": "2024-05-07T15:52:05.146690Z", - "iopub.status.idle": "2024-05-07T15:52:05.166931Z", - "shell.execute_reply": "2024-05-07T15:52:05.166315Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/jpeg": 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", "text/plain": [ - "" + "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 12, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "result.convergence_graph" + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(nrows=1, ncols=1)\n", + "axes.plot(cost_values)\n", + "axes.set_xlabel(\"Iterations\")\n", + "axes.set_ylabel(\"Cost\")\n", + "axes.set_title(\"Cost convergence\")" ] }, { @@ -475,25 +380,17 @@ }, { "cell_type": "markdown", - "id": "670eddd3-2da7-4a88-b571-7884ef24f60c", + "id": "f6ecef23-a456-4ee9-8760-d664656a75a4", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm:" + "We can also examine the statistics of the algorithm. In order to get samples with the optimized parameters, we call the `get_results` method:" ] }, { "cell_type": "code", - "execution_count": 13, - "id": "516d78ba-2951-46eb-b1af-efe877513556", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:05.169568Z", - "iopub.status.busy": "2024-05-07T15:52:05.169098Z", - "iopub.status.idle": "2024-05-07T15:52:07.389654Z", - "shell.execute_reply": "2024-05-07T15:52:07.388902Z" - }, - "tags": [] - }, + "execution_count": 11, + "id": "330a9bf3-b6e7-478d-ab6c-5b72ac1f2d9f", + "metadata": {}, "outputs": [ { "data": { @@ -516,83 +413,68 @@ " \n", " \n", " \n", + " solution\n", " probability\n", " cost\n", - " solution\n", - " count\n", " \n", " \n", " \n", " \n", - " 707\n", - " 0.001\n", - " 2.0\n", - " [1, 1, 0, 0, 0, 0]\n", - " 1\n", + " 870\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.000488\n", + " 3.0\n", " \n", " \n", - " 482\n", - " 0.001\n", + " 36\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'...\n", + " 0.001465\n", " 3.0\n", - " [0, 0, 1, 1, 0, 1]\n", - " 1\n", " \n", " \n", - " 158\n", - " 0.001\n", + " 652\n", + " {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'...\n", + " 0.000488\n", " 3.0\n", - " [1, 1, 0, 1, 0, 0]\n", - " 1\n", " \n", " \n", - " 121\n", - " 0.001\n", - " 4.0\n", - " [0, 0, 1, 1, 1, 1]\n", - " 1\n", + " 167\n", + " {'x_0': 0, 'x_1': 0, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.000977\n", + " 3.0\n", " \n", " \n", - " 704\n", - " 0.001\n", + " 30\n", + " {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.001465\n", " 4.0\n", - " [1, 0, 0, 1, 1, 1]\n", - " 1\n", " \n", " \n", "\n", "" ], "text/plain": [ - " probability cost solution count\n", - "707 0.001 2.0 [1, 1, 0, 0, 0, 0] 1\n", - "482 0.001 3.0 [0, 0, 1, 1, 0, 1] 1\n", - "158 0.001 3.0 [1, 1, 0, 1, 0, 0] 1\n", - "121 0.001 4.0 [0, 0, 1, 1, 1, 1] 1\n", - "704 0.001 4.0 [1, 0, 0, 1, 1, 1] 1" + " solution probability cost\n", + "870 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.000488 3.0\n", + "36 {'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'... 0.001465 3.0\n", + "652 {'x_0': 0, 'x_1': 1, 'x_2': 0, 'x_3': 0, 'x_4'... 0.000488 3.0\n", + "167 {'x_0': 0, 'x_1': 0, 'x_2': 0, 'x_3': 1, 'x_4'... 0.000977 3.0\n", + "30 {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.001465 4.0" ] }, - "execution_count": 13, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " mds_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=True).head(5)" + "optimization_result = combi.get_results()\n", + "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { "cell_type": "markdown", - "id": "687f492b-a4a5-49c6-964c-8959b035bb93", + "id": "c9116e3a-b430-4068-91de-4c56c2629664", "metadata": {}, "source": [ "And the histogram:" @@ -600,31 +482,15 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "id": "31a4e74d-b2b8-42e0-826d-de7b51de1fe8", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:07.394330Z", - "iopub.status.busy": "2024-05-07T15:52:07.393146Z", - "iopub.status.idle": "2024-05-07T15:52:07.701342Z", - "shell.execute_reply": "2024-05-07T15:52:07.700622Z" - }, "tags": [] }, "outputs": [ { "data": { - "text/plain": [ - "array([[]], dtype=object)" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -634,7 +500,12 @@ } ], "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" + "optimization_result[\"cost\"].plot(\n", + " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + ")\n", + "plt.ylabel(\"Probability\", fontsize=16)\n", + "plt.xlabel(\"cost\", fontsize=16)\n", + "plt.tick_params(axis=\"both\", labelsize=14)" ] }, { @@ -647,15 +518,9 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:07.705568Z", - "iopub.status.busy": "2024-05-07T15:52:07.704475Z", - "iopub.status.idle": "2024-05-07T15:52:07.709598Z", - "shell.execute_reply": "2024-05-07T15:52:07.708959Z" - }, "tags": [] }, "outputs": [], @@ -665,20 +530,34 @@ }, { "cell_type": "code", - "execution_count": 16, - "id": "3562002f-d425-482d-be71-f9bb36245dc6", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:07.713729Z", - "iopub.status.busy": "2024-05-07T15:52:07.712616Z", - "iopub.status.idle": "2024-05-07T15:52:08.182072Z", - "shell.execute_reply": "2024-05-07T15:52:08.181217Z" + "execution_count": 14, + "id": "c0cf31f2-a245-4a39-999e-5d98e8dbe0ca", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'x_0': 0, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4': 0, 'x_5': 0}" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" } - }, + ], + "source": [ + "best_solution" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "3562002f-d425-482d-be71-f9bb36245dc6", + "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -703,7 +582,7 @@ " )\n", "\n", "\n", - "draw_solution(G, best_solution)" + "draw_solution(G, [best_solution[f\"x_{i}\"] for i in range(len(best_solution))])" ] }, { @@ -716,15 +595,9 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:08.194837Z", - "iopub.status.busy": "2024-05-07T15:52:08.193301Z", - "iopub.status.idle": "2024-05-07T15:52:08.290328Z", - "shell.execute_reply": "2024-05-07T15:52:08.289518Z" - }, "pycharm": { "name": "#%%\n" }, @@ -776,21 +649,15 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "id": "a7524894-b5c5-42d4-8f92-a019bef5e7da", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:52:08.303277Z", - "iopub.status.busy": "2024-05-07T15:52:08.302942Z", - "iopub.status.idle": "2024-05-07T15:52:08.574093Z", - "shell.execute_reply": "2024-05-07T15:52:08.573365Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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urr7oOFQBmvkjGxERabT4+HjMmjULjo6OWLVqFUaPHo3bt29j7969WlEmAWDFihU4dOjQ8919NEGzZuNhZqZAZORO0VGogrhTDhERqY1r167Bx8cH33//PczNzTFt2jRMnz5dI67OVURwcDA8PDywdOlSfP7556LjKI1MVoQffzREamoXTJoUJjoOVQCXvImISOWFhYVh1apVOHbsGBwcHPD111/D29tb457WLo+rV69i7NixGDJkCBYvXiw6jlLp6uojObkBjIwuiY5CFcQlbyIiUkn/Hv1z584d7Nq1C7dv38asWbO0skympaXB3d0djRo1wq5duzTyYSMbmwGoX78A9+9fEB2FKkDz/iQSEZFae9non+DgYMTGxsLT0xP6+tr5sMazbRWzsrIQHByssYW6a9eZKCkBoqI2iY5CFcAlbyIiUgm5ubnw8/PDmjVrEB8fj3fffRfbtm2Dm5ub6GgqYe7cuTh79ixOnjyJBg0aiI5TbezsGiMhwRwlJSdER6EKYKEkIiKhtHn0T3n5+flh06ZN+Oabb9C9e3fRcaqdVNoFtWv/gvz8LBgZmYuOQ+XAp7yJiEiI+Ph4rF27Ftu3b4dCoYC3tzfmzJmj0VffKiMsLAw9e/aEl5cXtm7dKjpOjbh8+QgyM4eiuHgF+vb9VHQcKgcWSiIiqlEvG/0zbdo02Nraio6mcuLj49GhQwe0aNECJ06c0Jr7R+VyOQID9ZGR0RpeXpdFx6Fy4JI3ERHViBdH/9jb22v16J/yyMvLg4eHB4yMjHD48GGtKZMAIJVK8eRJM5iZXRMdhcqJT3kTEVG1eTb6p1u3bv8Y/XPnzh2tHf1THgqFApMmTcKNGzcQHByslVdv69Ubgtq1i3H9+i+io1A5sFASEZHSPRv906ZNG7z33nsoKSnh6J8KWLlyJQICArBnzx60adNGdBwh3Nymo6gIuHRJO+4bVXcslEREpDS5ubnYuHEjmjRpgvHjx8PJyQlnz55FWFgYBg4cqJGDuJXt2LFj+Oyzz7BkyRIMGTJEdBxhzM3t8OCBNYqKzomOQuXAv9lERFRlaWlp+OKLL+Dk5IQ5c+bgzTffRExMzPPlbolEIjqiWrh+/TrGjBkDDw8Pjdqju7IMDXvAwSEdGRmJoqNQGfiUNxERVRpH/yhPeno6OnbsCCMjI0RERPD+UgA3b/6GxMSeyMmZjwEDVomOQ6XgU95ERFRhL47+MTMzw7x58zj6pwpkMhlGjBiBjIwMnDhxgmXyb82a9cDvv+sjNzcIAAulKmOhJCKicuPon+oxb948hIaG4sSJE2jYsKHoOColL681rK0vQy6X8x5cFcbfGSIiKpVCocAPP/zwfPTP7du3OfpHiXbu3IkNGzZgw4YN6Nmzp+g4Kqdhw1GoVUuOS5cCREehUrBQEhHRSz0b/ePi4oIBAwY8H/1z9epVjv5RkoiICHz44YeYPHkyPvroI9FxVFLXrh8gLw+4ds1PdBQqBQslERH9A0f/1IwHDx5g0KBB6NixIzZv3swn4V/B0NAUiYn1IZFEiY5CpeB3BSIiAsDRPzUpPz8fHh4eMDAwwJEjR3i1twwWFv1gb5+DR4/+FB2FXoGFkohIy8XHx2PWrFlwdHTEqlWrMHr0aNy+fRt79+5F69atRcfTOAqFAl5eXrh+/TqCg4NhZ2cnOpLK69JlFqRSICJio+go9Ap8ypuISEtx9I8YPj4+2L9/Pw4ePIjXX39ddBy1YG/vgtBQYxQW/ig6Cr0CCyURkZYJDw/HypUrOfpHgB9++AGffvopFi1ahGHDhomOo1ZksvaoU+cciosLoKdnKDoO/QuXvImItMCLo39cXV05+keAP//8E6NGjcLAgQPxxRdfiI6jdlq0mABTUwUiInxFR6GXYKEkItJgxcXF2LdvH0f/CPbkyRMMHDgQjo6O2Lt3L5+Ur4SOHcchM1OC27f3iY5CL8ElbyIiDZSbm4sdO3Zg9erViI+PxzvvvINvvvkGbm5ufFq7hj3bVjE9PR3R0dEwMzMTHUkt6ejoIiWlIYyM/hAdhV6CPyIREWmQtLQ0LFu2DE5OTpg9eza6deuGP/744/lyN8tkzZs/fz5Onz6NQ4cOoXHjxqLjqDVb24GoX78Ad+9GiI5C/8JCSUSkAV4c/bNy5UqMGjUKt2/ffr7cTWLs3r0b69atw7p169CrVy/RcdSeq+sslJQA0dGbREehf+GSNxGRGrt+/Tp8fHzg7+8PMzMzzJ07F9OnT+foHxUQGRmJ999/H15eXpg2bZroOBrBxsYJCQkWKCk5JToK/QuvUBIRqaHw8HAMHDgQzs7OOHXqFHx8fBAfH49ly5axTKqAhw8fYtCgQejQoQO2bNnCWw2USCrtivr1k5GXlyE6Cr2AhZKISE2UNvpn9uzZHP2jIp5tq6inp4cjR47AwMBAdCSN0qbNBzA0BM6f3yw6Cr2AhZKISMW9bPRPUFAQR/+oIIVCgcmTJ+PatWsICgpC7dq1RUfSOK1bv4fUVB3Exx8UHYVewEJJRKSi8vLysGnTJjRp0gTjxo2Do6Mjzp49i7CwMLi7u3OWoQpavXo1/P39sXPnTrRr1050HI0klUqRkdESFhZ/Qi6Xi45Df+N3IyIiFfNs9I+joyNH/6iRH3/8EQsWLMDChQsxYsQI0XE0mr39ENjaynD9+s+io9DfJAqFQiE6BBERAQkJCVi7di2+++47KBQKeHl5Ye7cuWjQoIHoaFSGv/76C506dUL37t0RFBTEq8fVLDs7FeHhtkhOHoBx446JjkPg2CAiIuE4+ke9ZWRkwN3dHfb29ti3bx/LZA0wM7PBgwe2kErPi45Cf2OhJCISJDw8HKtWrUJISAjs7e3h4+ODyZMn82ltNVJSUoJRo0YhJSUF0dHRMDc3Fx1Jaxgb94KtbQDS0+NhZeUoOo7W449RREQ16NnonzfffBOurq64desWdu7cydE/auqTTz7BiRMncPDgQTRp0kR0HK3Svv006OoC589vEB2FwEJJRFQjno3+adOmDQYMGIDi4uLno38mTJjA0T9qaM+ePVi9ejXWrFmDPn36iI6jdZo2dcOjRwZITuY9lKqAhZKIqBo9G/3TtGlTjBs3Dg4ODjhz5gzCw8M5+keNRUdH4/3338fEiRMxY8YM0XG0Vl6eC2xs7qCkRCY6itbjU95ERNUgLS0NW7ZswaZNm/DkyROMHDkS8+fPh4uLi+hoVEWJiYlo3749GjRogNDQUO6EI9Bvv20AMAtGRrvRqdN40XG0GgslEZESPRv9s337dsjlco7+0TAFBQXo3r07EhMTceHCBdSpU0d0JK1WWJiHkydNkJLSAxMmhIqOo9X4lDcRkRL8e/TPnDlzOPpHwygUCrz//vuIiYnB+fPnWSZVgIGBMR49soe+/gXRUbQeb94hIqqCZ/dCOjs749SpU/Dx8UF8fDyWLVvGMqlh1q5di71792LHjh144403RMehv1lavg17+1wkJl4THUWrsVASEVXQv0f/3Lx5k6N/NNzPP/+M+fPn45NPPsGoUaNEx6EXdO06CwAQHr5eaA5tx0JJRFROrxr9c+3aNY7+0WA3btzAyJEj0b9/fyxfvlx0HPqXevWc8eCBCTIyuK+3SCyURERl4Ogf7ZWZmQl3d3fUrVsX/v7+0NHRER2JXkIu74i6dR+gsDBPdBStxe+CRESvkJaWhmXLlsHJyQmzZ8+Gm5sb/vjjj+fL3RKJRHREqkbPtlVMSkpCSEgILCwsREeiV2jZcgJMTICIiO2io2gtFkoiUhu5hTJcS8zE5fgnuJaYidzC6hlmnJCQgNmzZ8PJyQn/+9//MHLkSNy+fRv79u3jHEktsnDhQvzyyy8ICAhA06ZNRcehUrRvPxoZGVLcueMvOorW4tggIlJpt5Ky4R8Vj9AbyYhPz8OLg3MlABytjNGzuR3GdHJE09pmVToXR//QM/v27YOPjw/Wrl2Lfv36iY5DZdDR0UVqamOYmMSIjqK1ONiciFRSQnoeFgbG4tztVOhIJSiRv/pb1bPXuzWxwYpBreFgZVyhc0VERGDlypUICQlB/fr1MXfuXEyePJlPa2upCxcuoFu3bhg5ciR27tzJWxvUxLFjH8PMbDXq1z+Hpk3dRMfROiyURKRyDlyIx+ch1yCTK0otkv+mI5VAVyrBFwOdMbKDY6nvVSgU+Omnn7By5UqcO3cOLVq0wIIFCzB69Gg+ra3FHj16hPbt28PR0RGhoaEwNDQUHYnKKT09HpcuOSElZQRGjTogOo7W4T2URKRSNofewidHY1Eok1eoTAJAiVyBQpkcnxyNxebQWy99j0wmg7+/P9q0aYN3332Xo3/ouYKCAgwaNAgSiQRHjx5lmVQzVlaOSEiwRF7eadFRtBILJRGpjAMX4rH615tKOdbqX28i4EL88///bPRPkyZNMHbsWNjb23P0Dz2nUCjw4Ycf4sqVKwgMDETdunVFR6JK0NV1g719CrKzU0VH0Tp8KIeIVEJCeh4+D3n51mmFj24iN/YUCuJjIctMgtTIHAb1msPyzXHQs6r/ymMuCbmGVta6CPL3w8aNG/HkyROMGDECwcHBaNOmTXV9KaSG1q9fj927d2Pfvn3o0KGD6DhUSW3bTkFq6nGEhW3G228vFR1Hq/AeSiJSCeP8ohB+N+2ly9wpgStQ+OBPGLdwg55dA5TkPEH2peNQFBWgzvjV0Ldt8NJjShRyFCbE4snRL+Hl5YW5c+eiYcOG1fyVkLr59ddf0b9/f8ybNw+rVq0SHYeqQC6X48gRA2RmtoC3d6zoOFqFhZKIhLuVlI2+68++8vWCB3/CoG4TSHT0nn+sOP0hEv2mwaSFK2zem1fq8QPGv4ZOLZ2Ulpc0x61bt9CxY0d07doVISEh3AlHA/j6usDS8joGDy7irSw1iL/SRCScf1Q8dKSvHs1iaN/yH2USAPSs6kPfxhHFqQmlHltHKsFPt3KUkpM0S2ZmJgYOHIjatWvj+++/Z5nUEI6Ow2FjU4LY2GOio2gVFkoiEi70RnKFn+hWKBQoycuA1Ni81PeVyBUIvZlclXikgUpKSjBmzBg8evSI2ypqGDe3aSgoAP7441vRUbQKCyURCZVTKEN8el6FPy/32m8oyU6DSYtuZb43Pi2v2rZpJPW0aNEi/PTTTwgICECzZs1ExyElMja2xMOHtSGXh4uOolVYKIlIqLi0XFT0Ru7itASkn9gKg/otYNK6d5nvVwC4n5ZbqXykeb7//nusXLkSPj4+eOutt0THoWpgYtILDg6ZSE2NEx1Fa7BQEpFQRTJ5hd5fkvMEyYe+gNTABDYen0IiLd99bxU9D2mmixcvwsvLC+PGjcOcOXNEx6Fq0rHjdOjoAGFh60VH0RoslEQklL5u+b8NyQtykXTwc8gLcmE3/AvomllXy3lIMz1+/BgeHh5wcXHBd999xz26NVijRl3w8KEhUlJCREfRGvwOS0RCNbA2QXn+WVfIipB8eBlkTx7CbtgS6NuUvlf3iyR/n4e0V2FhIQYPHgy5XI7AwEBuq6gFCgtfh63tPZSU8P7pmsBCSURC6UtlsDEsKPU9CnkJUoJWoTDxL9h6fAKD+i0rdA5Ha2OYGHBjMG2lUCgwZcoUXLp0CUFBQahXr57oSFQDmjQZAwsLBaKj94qOohVYKIlIiJiYEPj5dcTx4yZoY/crpCh55XufnPZD/u0oGDV6AyX5Oci5GvqP/5RGRypBz2Z2yo5PamTjxo3YuXMntm/fjo4dO4qOQzWkSxdvZGdL8Ndfu0RH0Qr8kZ2IakxKyj2cPLkQxcXH4OiYCzs7CZKSWuOdZj1wMv7VD9cUJd0FAOTfjkb+7ej/vG76Ws9Xfm6JXIGxncu/PE6a5eTJk5g7dy7mzZuHcePGiY5DNUhPzxBJSQ4wMLgoOopW4NaLRFStiosLcPq0DxISfOHomAAdHeD+fTvY2XmiT59FMDJ6Opi8tL28K0tHKkHXRtbY69VJacck9XH79m107NgRnTp1wvHjx7kTjhY6enQKrKy2oXHjy3BweF10HI3GQklE1SI29jguXFgOS8sLsLKSIzHRACUlfdGz51ewt3f5z/sT0vPQZ90ZFCpxvI+BrhQnZ3eHg5Wx0o5J6iErKwudO3dGSUkJoqKiYGlpKToSCfD48Q1cv94CaWkTMGzYTtFxNBqXvIlIaVJT43Dy5KcoKgqBo2MubG0lSEp6Dfb28zFy5GhIpa++bdvByhhfDHTGJ0djlZZn2UBnlkktJJfLMXbsWDx8+BDR0dEsk1qsTp3m+PVXUxQVnRAdReOxUBJRlchkRTh9+mvEx38HR8d42No+XdLOyvoAfft+/nxJuzxGdnBEak4hVv96s9J5FAoFJBIJPu7XHCM68N5JbbR48WIcP34cP/zwA5o3by46DgmmUHRCvXqnUFCQA0NDU9FxNBaf8iaiSrl27Sfs2NEFISFG0NdfBBOTJCQlvYNmzS7DyysJAweuqVCZfGZaz6ZYObg1DHSl0JFWbPC0jlQCqaIEOae+RXfb0kcRkWY6cOAAVqxYgVWrVqF///6i45AKcHb2grExEB7+regoGo33UBJRuaWnx+PEiYUoKAiGk1MOcnIkePzYGa+9Ng8dO44rdUm7ohLS87AwMBbnbqdCRyop9WGdZ693a2KDz95qhBHv9kFOTg6io6NhbV3+3XRIvV26dAlubm4YMmQI9uzZw51wCMDTWyCCg/WQnt4WXl584ru6sFASUalksiL89tta3L+/DQ4OcdDVBe7ft4WNzRj07fs5jI0tq/X8t5Ky4R8Vj9CbyYhPy8OL37AkeDq0vGczO4zt7IgmdmYAgPv376NDhw5wcXHBzz//DD09vWrNSOIlJSWhffv2qFOnDs6ePQsjIyPRkUiF+Po2h4nJfYwaVSg6isZioSSil7p+/RdERi6DhUUUrK1L8OiRPoqLe6NHj+VwdGwnJFNuoQw/h/2O0WPH4/t9e/C26xuv3AHnzJkz6NOnD6ZMmYKNGzfWcFKqSYWFhejVqxfu3r2Lixcvon79+qIjkYo5fnwBTE19UK9eKJo16yE6jkbiPZRE9NyTJw9w8KAndu82R3Ly26hdOxxPnjSHgYEvRozIx/jxPworkwBgYqCLhpZ6KHp0Ew0t9UrdTrF79+7YtGkTNm3aBF9f3xpMSTVJoVBg6tSpuHjxIgIDA1km6aXc3GaiuBi4eHGz6Cgai095E2m5khIZfvttLe7d2wp7+/uwtgbi4myQkTER/fp9Ue1L2tXpww8/xB9//IGPPvoILVq0gJubm+hIpGSbN2+Gn58fdu3ahc6dO4uOQyrK0rIeEhKsAPwmOorGYqEk0lJ//XUKERFLYW4eAWvrEpia6iM5+S10774cvXu3Fx1PaTZs2IDr169jyJAhuHDhAhwdOUpIU5w6dQqzZ8/G7Nmz4enpKToOqTh9/W6wswtGVlYyzM3tRMfROFzyJtIiGRmJOHhwAnbtssDjx31gZ3ceT540hb7+dgwfno/x43+Gk5PmlEkA0NfXx+HDh2FkZAQPDw/k5eWJjkRKcOfOHQwfPhy9e/eGj4+P6DikBtq1mwJ9feD8+U2io2gkFkoiDVdSIsPp02vg69sYkZH1YWOzG3K5Hp48mYYePdLg7f0nunb1VurIH1Vja2uL4OBg3LhxA5MmTQKfRVRv2dnZcHd3h7W1NQ4cOABdXS62UdlatXoLSUl6SEw8IjqKRuLfQiINdePGaYSHL4WZWThsbEpgZqaHpKS+ePPNL9GrVyfR8WpcmzZtsGfPHgwdOhQuLi5YuHCh6EhUCXK5HOPGjUN8fDyioqJQq1Yt0ZFIjeTkOKNWrVjI5XKN/iFaBBZKIg2SkZGIEycWITf3KBo0yETt2kBiYgvUqTMLw4ZN1vpvoEOGDMGSJUuwaNEitG7dGu+9957oSFRBn3/+OUJCQnDs2DG0bNlSdBxSM05OI6CrewVXrhxFu3ZDRcfRKCyURGqupESGc+c24/btzahf/w6srYHsbCukp09B377LYGZmIzqiSvn8888RGxuLMWPGIDIyEq1atRIdicrp4MGDWL58OVauXIl3331XdBxSQ66uH+G33z5FfLwvC6WSsVASqambN88iPHwJTEzCYGsrg5mZHpKT+6Bbt2Xo1auL6HgqSyqVYs+ePejatSsGDhyI6OhoWFlZiY5FZbh8+TImTJiA0aNHY/78+aLjkJoyMjJHYmId6OhEiI6icbR7/YtIzWRmPsbhw5Oxa5clEhO7w87uDDIzG0FHZwuGDSuAp+cJNGrEMlkWU1NTBAcHIyMjAyNGjIBMJhMdiUqRnJwMd3d3tGrVCr6+vtyjm6rE1LQvHByykJx8R3QUjcJCSaTing4e3wBf36YID68LGxtfKBRSpKd/CDe3JHh730C3bh9p/f2RFdWwYUMcOnQIoaGhmDdvnug49ApFRUUYMmQIioqKEBQUxD26qco6d54BHR0gLGy96CgahUveRCrq1q3zCAtbAmPjc7Czk8HcXBdJSb3g5rYMPXq4io6nEXr27ImNGzdi6tSpaNOmDSZOnCg6Er1AoVBg2rRpiI6Oxm+//QZ7e3vRkUgDODm1x/nzhsjP/wEAZ1IqCwslkQrJykrGiRNLkJUVgIYNM1C7NvDwYVPUqTMDQ4fyKmR1mDJlCv744w98+OGHaN68Obp27So6Ev3tm2++wfbt27Fjxw506cJbOUh5Cgvbwc4uAjJZEXR19UXH0QgslESCyeVynD//DW7e3Ih69W7B2hrIyrJEWtpk9OmzDBYWdURH1GgSiQSbNm3Cn3/+icGDB+PChQtwcHAQHUvrhYaGYubMmZg5cyavHJPSNWs2HjJZOKKidsHV9X3RcTSCRMEtI4iEuHs3AufOLYaR0RnY2cmQkqKL3Fw3uLp+iaZN3UTHU1mXLl3CG2+8gd9//x3t2rVT2nGTk5PRoUMH2Nra4ty5c7xXT6C7d++iY8eOaNu2LX766SfuhENKJ5MV4ccfDZGW1hUTJ54XHUcj8G8pUQ3Kzk7FiROLkZkZACenJ7CzAx4+bAI7u2kYPHgqdHT4V1IUOzs7BAcHw9XVFV5eXvD39+fTxAI821bR0tISAQEBLJNULXR19ZGc7ARDw0uio2gM/k0lqmZyuRxhYd/ixo0NqFfvBqysgKwsC6Sne6Nv3y+5pK1CXn/9dezatQvDhw+Hi4sLPvnkE9GRtIpcLsf48eMRFxeHyMhIzgelamVt/Q5q1foGcXEX4eTUXnQctcc7/Imqyb17Udi9uy8OHTJESclHsLS8jeTk7qhXLxQTJmRg6NDtLJMqaNiwYVi0aBEWLlyI48ePi46jVb744gsEBwfD39+fOxhRtXN1nYOSEiAqik96KwOvUBIpUXZ2Kk6e/BxPnhxAgwbpqF0bePCgEezspmLQoBlc0lYTX3zxBWJjYzF69GhERUVxz+gacPjwYSxbtgwrVqzgHutUI+zsGuPBAzMUF58QHUUj8F83oiqSy+WIiPDFn3+uQ926f6FWLSAz0xxpaRPRt+9yWFrWEx2RKkgqlWLv3r3o0qXL8+0Za9WqJTqWxrpy5Qo8PT0xcuRI3mZANawL6tf/Ffn5WTAyMhcdRq1xyZuoku7fv4Ddu9/CwYOGKC7+AJaWt5Cc3A116pzEhAmZGDZsB8ukGjMzM0NISAjS09O5PWM1SklJgYeHB1q0aAE/Pz8+CEU16rXXvGBkBISHbxMdRe2xUBJVQG5uOoKCZmDHDhvcudMRtWv/ipwcB8jlqzFoUAEmTjyLFi16i45JStKoUSMcOnQIp0+fxvz580XH0ThFRUUYOnQo8vPzERQUBGNjY9GRSMu0bTsUaWk6uH//gOgoao9L3kRlkMvliIzcgevX16Ju3T9haQlkZJgjLc0Tffsux9tvczs4TdarVy+sW7cOM2bMQJs2beDp6Sk6ksaYOXMmIiIiEBoaymHyJIRUKsWTJ01hZnZVdBS1x0JJ9ApxcRdx5sxi6OmdRt26RahVSwfJya7o3Plz9OjRV3Q8qkHTpk1DTEwM3n//fTRv3hydO3cWHUntbd26Fdu2bYOvry9cXbk3PYlTr95gGBuvwJ9/nkDLlvzeXlncKYfoBXl5Gfj118+Rnv49nJxSIZMBCQkN0LDhFHTvPot7vqqA6toppyxFRUXo1asX7ty5g4sXL6J+/fo1dm5Nc+bMGfTp0wdTpkzBxo0bRcchLZeZ+RhRUXWRkjIIY8YcFR1HbfEKJWk9uVyOqKjduHZtDerUuQ5LSwUyM82QmjoOffsux1tvOYqOSCpAX18fR44cQYcOHeDh4YGzZ89ye8ZKuHfvHoYMGYLu3btj7dq1ouMQwcKiDh48sAZwRnQUtcZCSVorIeEKQkMXQk/v1AtL2l3QqNES9Ojxluh4pIJq166NoKAguLm5YfLkydi7dy+fSq6AnJwcuLu7w8LCgtsqkkoxMOgOW9ujyMx8zA0nKol/m0mr5OVl4MSJZUhN3YcGDVJQuzaQkOCE4uIP4O4+l0vaVKZ27dph586dGDlyJNq0aYOPP/5YdCS1IJfL4enpiXv37iEyMhLW1taiIxE91779VDx6dBTnz2/Au+/+T3QctcRCSRpPLpfjwoV9iI39GrVrX4OFhQIZGaZITR2D3r2/wltvOYmOSGpmxIgRiImJwYIFC+Ds7Ix33nlHdCSV9+WXX+Lo0aMICgqCs7Oz6DhE/9C8eS9cvqyPnJxAACyUlcFCSRrrwYMYhIYuhI7OSdSrVwgrKylSUjqhYcPF6NGDBYCq5ssvv0RsbCxGjRqFqKgotGjRQnQklXX06FEsXboUy5cvh7u7u+g4RC+Vm/sarKyuQC6XQyrlmO6K4lPepFHy87Nw8uSXSE7egwYNklFSAsTHO8DR8QP06vUxl7Q1gKinvF8mKysLXbp0gUwmQ2RkJLdnfImYmBh06dIFAwYMwIEDB3jPKamsU6e+ho7OfJiaHkD79iNEx1E7rOCk9uRyOaKj98HX1wUnT1rCzGw19PRykZIyCm3b3oW3dzz69fuMZZKUztzcHCEhIUhJScGoUaNQUlIiOpJKSU1Nhbu7O5o1a4YdO3awTJJKc3Wdgrw84No1X9FR1BKXvEltPXx4FaGhn0Ei+RX16xfA2lqKlJSOaNBgEXr0GCA6HmmJxo0b4+DBg3j77bexYMECrF69WnQklVBcXIxhw4YhNzcXZ86cgYmJiehIRKUyNDRFYmI96OlFio6illgoSa0UFOTgxIllfy9pJ8HO7umSdmGhNwYMmA89PUPREUkL9enTB2vWrMGsWbPg4uKC8ePHi44k3KxZsxAWFobTp0/D0ZGzXEk9mJv3hY3Nbjx+fAN16jQXHUetsFCSypPL5bh0KQBXrqyCnV0MzM0VePLEBMnJI9C791fo16+x6IhEmDFjxj+2Z+zUqZPoSMJ8++23+Oabb/Ddd9/Bzc1NdByicuvSZRbu3NmN8PANGDz4G9Fx1AoLJamsxMRrOH36M0gkv7ywpN0eTk6foUcPPilKqkUikeCbb77BX3/9hUGDBuHixYuoV6+e6Fg17uzZs5g2bRqmTp2KyZMni45DVCEODq/jt9+MUFj4o+goaoeFklRKQUEOTp36Co8f74KT0+O/l7Tro6DAGwMGfMIlbVJpBgYGz7dnHDRoEM6cOQNDQ+35MxsXF4chQ4agW7duWLduneg4RJUik7VH7drnUVxcwH9zKoBPeZNK+P33g/Dza4dffzWHiclK6OtnISVlGNq0uQlv7wd4++2l/ItNaqFOnToICgp6vvytLZPZcnNz4e7uDjMzMxw6dAh6enqiIxFVSosWnjAzUyAycofoKGqFVyhJmEeP/sTp059BofgZ9vb5sLaWICWlHRwcPkWPHkNExyOqtDfeeAM7duzA6NGj0aZNG8ydO1d0pGqlUCgwYcIE3L59GxEREdxWkdRahw7j8OOPk5Gaug/dun0kOo7aYKGkGlVYmIdTp75CYuJOODk9gp0dEBdXD/n589C//ycwMDAWHZFIKUaNGoWYmBjMnz8fzs7OePvtt0VHqjbLly/H4cOHcfToUbRu3Vp0HKIq0dXVR3JyQxgZXRYdRa2wUFKNuHTpMC5f/h9sbC7DwkIBAwMjpKQMQa9eX6FvX45mIM20fPlyxMbGYuTIkYiKikLz5pr3Zz0wMBBLlizBsmXLMGjQINFxiJTCxmYALC034t69KDRsqL0TGyqCWy9StXn8+AZOn/4MJSU/wsEhH5mZEqSmtkXbtp+iXbuhouORmlKlrRfLIysrC507d4ZcLkdUVBQsLCxER1Ka2NhYdOnSBf3798fBgwe5Ew5pjJSUe4iJaYSUlNEYOdJfdBy1wCuUpFRPl7T/h8TEHXBySoSdHXD/fl3k5c3G229/xiVt0jrm5uYIDg5Gx44dMWrUKBw7dgw6OjqiY1XZs20VmzRpgl27drFMkkaxtW2IhARzlJScFh1FbbBQklJcuRKI33//CtbWl2FpKYehoRGSkwehV6+v0KdPS9HxiIRq2rQpAgIC0L9/f3z66afw8fERHalKiouLMXz4cGRnZyM0NJTbKpJGkkq7ok6dn5GXlwFjY0vRcVQexwZRpSUn38H+/cOxd68JMjIGw9b2EtLS2sDU9ADGjs3DmDFHUbcuyyQRAPTr1w+rV6/G119/jX379omOUyVz5szBuXPncOTIETg5OYmOQ1QtXFzeh6EhcP78FtFR1AKvUFKFFBcX4NSplXjwwBeOjg9hawvExdVBbu4M9Ov3GQwNTUVHJFJZs2bNQkxMDLy9vdG8eXN06NBBdKQK2759OzZv3oxt27bhzTffFB2HqNq4uLjj6FEdZGQcBPCZ6Dgqj4WSyuWPP4Jx8eJyWFldQq1achgZGSIlxQM9ey5Hnz7OouMRqQWJRIJt27bhr7/+goeHBy5evIi6deuKjlVu58+fx9SpUzFlyhR88MEHouMQVSupVIqMjOYwN78OuVwOqZSLuqXhrw690tMl7ZHYs8cUT554wNb2d6SltYap6fcYNSoXY8YEol49lkmiijAwMMDRo0chkUgwaNAgFBQUiI5ULvHx8Rg8eDBcXV2xYcMG0XGIakT9+kNgZyfDn3/+IjqKymOhpH8oLi7AL78sg6+vI65caQI7uwAUF5shJ2c++vXLgrf3FbRvP4o/qRFVQd26dREYGIgrV67gww8/VPntGZ9tq2hiYsJtFUmruLnNQGEhcPnyNtFRVB6XvAkAEBt7HBcufIlatS6iVi05jI0NkJw8ED17foXevV8THY9I43To0AF+fn4YO3Ys2rRpg9mzZ4uO9FIKhQITJ07ErVu3EB4eDhsbG9GRiGqMmZkNHjywhVR6TnQUlcdCqcVSUu7h1KnPUFQUAkfHXNjaSpCU9Brs7Rdg5EhehSSqbmPGjEFMTAzmzZuHVq1a4a233hId6T9WrFiBQ4cO4ciRI3BxcREdh6jGGRv3gK3tITx58gC1atmLjqOy2Bi0jExWhF9//Qq+vo64fLkRbG33o7jYBNnZ89CnTwa8vWPQocMYlkmiGrJixQq8/fbbGDlyJG7duiU6zj+EhIRg0aJFWLp0KQYPHiw6DpEQb7wxDbq6wPnzG0VHUWncelFLXL36I6Kjv4SlZTSsrORITDRASUkf9Oy5Avb2vOpA6kPdtl4sj8zMTHTq1AkSiQSRkZEqsT3jtWvX0LlzZ7z11ls4ePAgf8gkrbZ/vwFyc53g7X1TdBSVxSVvDZaaGodTpz5DYWEwHB1zni9p168/DyNHjuU/EEQqwsLCAiEhIejYsSPGjBmD4OBgodszpqWlYeDAgWjUqBF27drF7xWk9fLyXGBtfQklJTLo6LA6vQy/S2gYmawIJ078D76+DfD77w1gY+OP4mIjZGbOfr6k3anTeP4DQaRimjVrhoCAAPz000/47DNxQ5RlMhlGjBiBzMxMBAUFwdSUmxUQNW48BrVqyfH77wdER1FZbBUa4vr1X7BjhyuCg42hp7cQJiaPkJz8Dpo1uwwvr2S4u6+FkZG56JhEVIq33noLPj4+WLVqFb7//nshGebOnYszZ87g8OHDaNiwoZAMRKqmS5f3kZsLXL++U3QUlcXrtmosPT0eJ04sQkFBEJycsmFnJ8Hjx61Qr95cjBjhyauQRGpozpw5iImJgZeXF5o1a4b27dvX2Ln9/PywceNGfPPNN+jRo0eNnZdI1RkYGOPRo/rQ148SHUVlsVCqmZISGX77bS3u3dsKe/v7sLEB7t+3RWamF/r2/RzGxpaiIxJRFUgkEnz77be4cePG8+0Z69SpU+3nDQsLe76l4pQpU6r9fETqxtLybVhZ+eHRoz9Rt25L0XFUDi9hqYm//jqFnTvdEBRkCB2dBTAxSURy8tto0uTC30va61gmiTSEoaEhjh49CrlcjsGDB6OwsLBaz5eQkIDBgwejc+fO2LiRo1GIXqZLl1mQSoHw8HWio6gkXqFUYU+ePMCJE4uQlxeIBg2yYGcHPHrUCvXqzcGIERO5pE2kwerVq4egoCC8+eabmDJlCvz8/CCRSJR+nry8PHh4eMDIyAhHjhyBvr6+0s9BpAnq138Np06ZoKjoZ9FRVBILpYopKZHhzJkNuHt3C+zt7/29pG2NjIzp6Nt3KUxMrERHJKIa0rFjR2zfvh3jx49HmzZtMHPmTKUeX6FQYNKkSfjrr78QHh4OW1tbpR6fSNPI5e1Rt+4ZFBcXQE/PUHQclcJCqSJu3DiN8PClMDMLh41NCUxN9ZCU1A/duy9Hr14dRMcjIkHGjRuHmJgYzJkzB61atULfvn2VduyVK1ciICAAhw4dQps2bZR2XCJN1aLFRBQUnEF4+HZ07z5ddByVovU75eSmZeDx77GQ5RdA18gQdd5oDRNryxo5d0ZGIk6cWITc3KNo0CATubnAo0ct0LLlbHTp4s0lbaKX0MSdcspSUlKCAQMGICoqCtHR0WjSpEmVj3ns2DG4u7tj8eLF+OKLL5SQkkjzlZTIcOyYAdLT22OE+y/C+oMq0spCGXf2Ah77rId95G+om5b4jyeT5AAeWdfDg849UGf+LDi9qdyrgyUlMpw9uxF37myBvf1d6OsD9+9boVatkejT5wuYmdko9XxEmkYbCyUAZGRkoFOnTtDR0UFkZCTMzSs/V/b69evo3Lkz+vTpg8OHD/OHV6Jyijt7Adc++RCt/0pA/ScpNdofVJ1WFcrEy9eRNnYiWl+Phkwiha5C/sr3Pns9tlVHWO/biXptW1Xp3Ddv/obw8KUwMQmDra0MSUl6KCjogTff/BING3aq0rGJtIm2FkoAuHHjBjp16oRu3bohKCioUtszpqeno2PHjjAyMkJERAR3wiEqB5H9QV1ozY+l0Z+tglXHtmj550UAKPUPw4uvt/zzIqw6tkX0Z6sqfM7MzMc4fNgbu3ZZIjGxJ+zsziAzszF0dL7BsGEF8PT8lWWSiMqtefPm2L9/P3744QcsXry4wp//bFvFJ0+eIDg4mGWSqBxE9Ad1pBUP5UR4zUGXHeugAFDRoRu6Cjl0ZEXouOITRDxOQhe/taW+v6REhnPntuD27c2oX/82rKyA7OxaSE+fgr59l3FJm4iqpH///li1ahXmz58PFxcXjBw5styf+/HHHyM0NBQnTpxAo0aNqjElkWaoyf6g7jS+UEZ/tgpddjwdQlrZCW7PPq/LjnWIrlsHHZfP/897bt06j7CwxTAxOQ9bWxnMzXWRnNwbrq5foFcv10qemYjov+bNm4eYmBhMmjQJzZo1K9fS/86dO7F+/Xps3rwZPXv2rIGUROqtpvqDptDoeygTL1+HVce2MJAV/ecPwzUASwH8DuAxAGMArQB8DOC9VxxPAaBQVx/p0ZdRr20rZGUl48SJRcjKOoSGDTOQlwckJjZD8+Yz4er6IW90J6oG2nwP5Yvy8/PRvXt3PHr0CBcvXkTt2rVf+d6IiAj06NEDnp6e+Pbbb6tlQDqRJimtPwBAIYAlAPYCeALABcByAK8a6vXv/qCJNLrxpI2dCN0S2Uv/MMQByAbgCWADgGd3Iw0E8N0rjicBoFsiw+MRo+Dr2wznz9eGtfV2ABKkpX0AN7ckeHvfQLduH7FMElG1MjIyQmBgIEpKSkrdnvHBgwcYNGgQOnbsiM2bN7NMEpVDaf0BACYAWAtgDJ52CB0A7wA4/4r3P+sPaWMnKjuqytDYK5RxZy/AqXvHCn1OCYA3ABQA+KuM9/r/rx6K6zSHq+syNG3qVsmURFRRvEL5T5GRkejevTvGjRuH7du3/6Mw5ufno1u3bkhOTsbFixdhZ2cnMCmReiirP0QD6ATgawDz/v5YAYDXANgBCC/r+OcuwMmtvRKSqhaNvYz22Gc9ZJKKfXk6ABwAZJTxPplEisbne2DChNMsk0QkVOfOnfHdd9/Bz88Pmzdvfv5xhUIBLy8vXL9+HSEhISyTROVUVn84jKd94f0XPmYIwAtABICEUo4tk0jxeOU6ZcRUORr7UI595G9lPtoPALkA8gFkAggB8BOAEWV8jq5CDvvIM1XOSESkDJ6enoiJicHs2bPRqlUr9O7dGz4+Pti/fz8CAgLw+uuvi45IpDbK6g+XATQD8O+tBZ5d07yCpxenXkZXIUd9De0PGnmFMif1CeqmJZbrvXMB2AJogqeXrgcB2FzqZzxVL+0hctMyKhuRiEipVq1ahd69e2PYsGHw9fXFp59+is8++wzDhw8XHY1IbZSnPzwCUPclH3/2sbLah6b2B428Qpl06Soal/O9swAMxdM/AAfx9D7KonJ8nhRA2KFtqPXGq34OIaLqcO/ePTRtCty+/SNKSv4UHUelfPrpECxceAlffz0ZQ4a0wXvvtcCFC/6iYxGpjSe/J6BfGe/JB2Dwko8bvvB6aaQAHv8ei8b9ulU0nkrTyEIpyy8o93tb/P0fABgPoB+ejg2KQtlzpwqyvkFubml3SxCRstnZAd99BwCLkZsrOo3qWbHi2f/6A/n540RGIVI7BVllXyQywtOxQf/53BdeL0tFeoq60MhCqWtkWPabXmEogA8A3ATQvIz3Gpp/BBMTXqEkqkn37t3DokWLsXz5l2jYsKHoOCqjpKQEX3+9Gvfu3cPIkSPg5+cHd3d3DBs2THQ0IrVRZJ4A4NNS31MXwMOXfPzR3/9drxznqUpPUVUaWSjrvNEaclTuBtFnl6ozy3ifHIDrsA9hYm1ZibMQUWXp6FzCrVuL0aTJOxwb9IK5c+ciOPg6fvnlF/Tu3RsKRVN88sknaN9+NO+jJCqn3EYZkE/5tNT+8DqAUABZ+OeDOVEvvF4aOZ72FE2jkQ/lmFhb4pF16T8jJL/kY8UA9uDp5eqy5tgnWtdnmSQilbB7926sXbsW69atQ+/evQEA8+fPx+jRozFhwgRcvnxZcEIi9VCe/jAUT5+3eHETlEIAO/F0PmVZ65aa2h80slACwIPOPUqdI/UBgN4AvgDgi6dbJrkAuPT3/zYt5dgyiRTXWtbCrl09cevWq+biExFVv8jISLz//vvw8vLCtGnTnn9cIpHA19cXrVq1gru7O5KSkgSmJFIfZfWHTgCG4enC+Hw8LZa9ANwH4FPGsWUSKR527q6coCpGYwtlnfmzSp0jNQJPv/itAKbg6RZK9gCCAcwp49i6Cjnie+rDzu43PHzYDTt31sKRI+8jK+tl1z2JiKrHw4cPMWjQILRv3x5btmz5z7aKRkZGCAoKQlFREYYMGYKiovLMsCDSbmX1B+DpauYsPN3LewaernAeB/BmGcfWVchR55PZSkipejR260UAiHXuhJZ/XizXgPPykkmk+LNle7S+FoWsrGScOLEEWVkH0bDhE+TlAYmJTdGs2Qy4uXE/b6LqwK0Xn8rPz0f37t3x6NEjXLx4EbVr137leyMiItCjRw94enri22+/5X7eRGWo7v6giTS68Vjv2wmZji6U1ZgVAGQ6urDetxMAYG5uhyFDtmHixHTUr38Oyck9YWFxD3L5dBw+bIBdu3rj9u0wJZ2diOgphUKByZMn4+rVqwgODi61TAJAly5dsG3bNmzfvh3ffPNNDaUkUl/V3R80kUYXynptWyFm/rIy50mWlwRAzIIvUa/tfx/ZadrUDRMmnMbgwfmQSDYiK6shatc+jQcP3LBzpxWOHp2C7OxUJSUhIm22evVq+Pv7Y+fOneW+Sjtx4kTMmjULM2fOxOnTp6s5IZF6q8n+oCk0esn7mQivOeiyYx0UKHtY+cs8+7xIrzno7Lum3J+XmfkYJ04sRnb2YTRsmPH3kngzNG8+E66uH3JJnKgStH3J+6effsK7776LTz75BCv+f4p5uchkMrzzzjv4/fffceHCBTRq1KiaUhJpBlH9QR1pRaEEgOjPVsHFZwl0S2QVuidCJpFCpqOLmAVfouPy+ZU+/82bZxEe/jlMTM7D1laGpCQ9FBR0R7duy9CoUZdKH5dI22hzofzrr7/QqVMndO/eHUFBQZX6oTQ9PR0dO3aEkZERwsPDYWZmVg1JiTSH6P6gLrSmUAJA4uXrSBs7Ea2vR0MmkZb6B+PZ67GtOsJ6306lXaYuKZHh3LnNuH17M+zt70BfH7h/3wqWliPQt+8ymJnZKOU8RJpKWwtlRkYGOnXqBF1dXURERMDc3LzsT3qF69evo3PnzujduzeOHDnC1RKiMqhCf1B1WvVdpF7bVmh9LQpxZ6Lx+zsj8cC6Pv79R0IO4IF1ffz+zkjEnbuA1teilPqHQUdHFz16zIK392107vwQ6elekEpLYGW1FWfP2sLXtyXOn/8WcrnyniwjIvVWUlKCUaNGISUlBcHBwVUqkwDQqlUrfP/99wgODsYXX3yhpJREmutZf7j7WwROu7VCfC27Gu8Pqk6rrlC+TG5aBh7/HgtZfgF0jQxR543WQibY37hxGuHhX8DMLAw2NiV/L4n3QPfuX6FBgw41nodIVWnjFcqPP/4Ya9euxc8//4y+ffsq7bj/+9//sHDhQhw8eJB7fhOVQ2TkbhQUTIBEshHtXxunEv1BVWh9oVQ1JSUynD27EXfubIG9/d2/l8StUavWKPTr9wVMTKxERyQSStsK5d69ezF+/HisX78eM2fOVOqxFQoFRo8ejZCQEISFheH1119X6vGJNM2uXT1ga3sG/frlQ0/PUHQclaJVS97qQEdHFz17zoG39x106pSAtLQJkEqLUavWZvz2mzV8fVshPNyXS+JEWiA6OhqTJ0/GxIkTMWPGDKUfXyKRwM/PDy1atIC7uzuSk7nbF1FppNKLePTIgWXyJVgoVVitWvYYNmwnJkzIRJ06J5Gc7IZatW6iqGgyDh40wp49byMu7qLomERUDRITE+Hh4YF27dph69at1ba7jbGxMYKCglBYWIihQ4dye0aiV3j48CocHXNRq9bboqOoJBZKNdGiRW9MnHgOHh4FKCnxQU5OfdjZ/YLbtztgxw5bBAXNRF5ehuiYRKQEBQUFGDRoEHR0dHD06FEYGBhU6/kcHBxw5MgRREZGVsuVUCJNEBGxHnI50LWrZu7FXVUslGpGR0cXvXt/DG/vu38viY+Hjk4hLC034vRpK/j6OiMiwo9L4kRqSqFQ4P3330dMTAyCgoJQp06dGjmvq6srtm7dim+//RZbt26tkXMSqZOMjJ/x4IEJ6tZtKTqKSmKhVGO1atlj+PDd8PTMQu3avyIlpStq1bqBwkJvBAQYYc+edxAff0l0TCKqgLVr12Lv3r3YsWMH3njjjRo9t5eXF2bMmIEZM2bgt99+q9FzE6mywsI81K37EHJ5J9FRVBYLpYZo2bIvJk48D3f3PMhk/0Nubl3Urv0Tbt16A35+dggOns0lcSIV98svv2D+/PlYsGABRo0aJSTDmjVr0L17dwwdOhT37t0TkoFI1UREfAcTE6BVq4mio6gsjg3SYOnp8ThxYhEKCgLh5JSD7GwJkpKc8dpr89Cx4zjujkFqSVPHBt28eRMdO3aEm5sbgoODoaOjIyxLWloaOnbsCBMTE4SHh8PU1FRYFiJV4OfXAVZWlzBwYCF0dHRFx1FJbBQazMrKESNG7IGnZzZsbX9ESkpnWFldR0HBBAQEGGPv3neRkHBFdEwirZeZmYmBAweibt268Pf3F1omAcDa2hohISG4d+8ePD09eU82aT1j4xikpTVmmSwFC6WWcHbuj0mTwjFwYD6Ki1cgN7c2atf+ETdvtoWfX22EhMxFfn6W6JhEWufZtopJSUkICQmBhYWF6EgAAGdnZ/j7+yMwMBBffvml6DhEwty8eRZ16xahdm0P0VFUGgulltHV1Uffvp/C2zsO7drdR0rKaOjp5cHcfC1OnrSEr68LoqP38YoEUQ1ZuHAhfvnlFwQEBKBp06ai4/zDwIED8eWXX2Lp0qU4cuSI6DhEQvz++2YUFwNubhypVRoWSi1mY+OEkSP9MX58NmxsfkBKSkdYW19DXt44HDhgjL1738ODBzGiYxJpLH9/f/j4+GD16tXo16+f6DgvtXDhQgwfPhzjx49HTAy/H5D2ycv7DQ8e1EKtWvaio6g0FkoCALz22juYNCkSAwbkoqjoS+Tl2aF27eO4caMN/Pzq4Nix+SgoyBEdk0hjXLhwAV5eXvD09MSsWbNEx3kliUSCHTt2oHnz5nB3d0dqaqroSEQ1Jjs7Ffb2KdDT6yY6ispjoaR/0NMzRL9+i+DtHY+2be8iOXkk9PRyYGb2NX791Ry+vm1w4YI/l8SJquDRo0fw8PDA66+/jm3btlXbtorKYmJigqCgIOTl5WHo0KEoLi4WHYmoRpw/vxEGBkDbth+KjqLyWCjplWxtG2LUqP0YPz4HVlbBSElpD2vrq8jNHYv9+02wb58HEhOviY5JpFYKCgowePBgAEBgYCAMDQ0FJyofR0dHHDlyBOHh4Zg5c6boOEQ14uHDI0hO1kXLlm+JjqLyWCipXFxcBsLLKxoDBuSioGAp8vNtYGcXjOvXX4OfX10cP76AS+JEZVAoFJgyZQouX76MoKAg1K1bV3SkCnFzc8OWLVueb9FIpMnkcjksLW8gK6sV5zaXA3+FqEL09Azx9tufw9s7Aa+/fhspKSOgr58FU1Mf/PqrOfz82uLixQDRMYlU0vr167Fr1y74+fmhQ4cOouNUyuTJkzFt2jRMmzYNZ8+eFR2HqNrExATDxqYEjo7DRUdRC9wph5TiypVA/P77ClhbX4KlpRwPHxoCeBu9eq1A3botRccjDaKuO+X8+uuv6N+/P+bOnQsfHx/RcaqkuLgYb731FmJjY3HhwgU0aNBAdCQipduzpz/s7H7Gm28+gbGxpeg4Ko+FkpSquLgAJ0+uwMOHO+Dk9BASCXD/fl3UrTsBffosgoGBseiIpObUsVDeunULHTt2RJcuXXDs2DHhO+EoQ1paGjp06AAzMzOEh4fDxMREdCQipdq1ywIlJcbw8nokOopa4JI3KZWeniH6918Gb+8HcHG5ieTkoTAwyISJyf/w88+m8PNrh0uXDouOSVRjMjMz4e7ujtq1a2P//v0aUSaBp9szBgcH486dO5gwYQJ4bYI0SUrKPTg4ZMHEpJfoKGqDhZKqTe3aTTF69CGMG5cLc/NDSE1tB2vrK8jKGoZ9+4zh7z8Ejx/fEB2TqNqUlJRgzJgxSExMVKltFZWldevW2LdvHw4fPozly5eLjkOkNGFh66GjA3TqxN1xyouFkmpEu3ZD4eV1Ef375yAvbxEKCmrBzu4oYmNbwNe3Hn78cTEKC/NExyRSqkWLFuGnn37CgQMH0KxZM9FxqoWHhweWLVuGJUuWIDAwUHQcIqVITT2Ohw8N0bBhJ9FR1AYLJdUoAwNjvPPOl/D2fojWrf9CcvJgGBpmwNh4OX76yRR+fu1x+TL3DCb1t3//fqxcuRI+Pj54++23RcepVosWLcLQoUMxbtw4xMbGio5DVCUyWRHs7O6hsLCt6ChqhQ/lkEr4/feDuHJlFWxsLsPCQoGEBGPo6LyD3r1XoHbtpqLjkQpRh4dyLl68iG7dumHYsGHYvXu3yu+Eowy5ublwdXVFVlYWoqOjYWNjIzoSUaVERPihsNAbOjpb0K3bR6LjqA1eoSSV8MYbw+Hl9TveeisLubmforDQAnZ2hxET0wy+vvb46aclKC4uEB2TqEyPHz+Gh4cHXFxc8N1332lFmQSebs8YHByMnJwcDB8+nNszktr666/dyM6WoHPnSaKjqBUWSlIphoamePfdFfD2ToSz83UkJ3vAyCgNRkZf4ocfTODn1wF//BEsOibRSxUWFmLw4MGQy+Vqta2isjg5OeHIkSM4d+4cZs+eLToOUaXo6l5EUpIj9PS06+9vVbFQksqqW7clxowJxJgx+TA1PYC0NBfY2v6OJ088sHevCfbvH47k5DuiYxIB+P9tFS9duoTAwEDUq1dPdCQhunXrhs2bN2PLli3Yvn276DhEFZKQcAUODvmwsnpHdBS1w0JJaqF9+xHw8rqMfv2ykJMzH0VF5rCzO4QrV5rA19cBP//8BZfESaiNGzdi586d2L59Ozp10u4nQz/44AN89NFHmDp1Ks6fPy86DlG5RUSsh1wOuLryCntF8aEcUlsPH15FaOgiSCS/oH79Ajx5IsWTJ+3Rvv1ncHEZKDoeVRNVfCjn5MmTePvttzFr1iysXr1adByVUFxcjH79+uHatWu4ePEiHB0dRUciKpOvb33o6WXB0zNbdBS1wyuUpLbq138NY8cGYdSoXJiY7ENa2muwtb2A9HR37Nljiv37RyEl5Z7omKThbt++jeHDh6NPnz5YtWqV6DgqQ09PD4cOHYKJiQnc3d2Rm5srOhJRqQoKclCvXiKAzqKjqCUWSlJ7UqkUHTqMgbf3H+jTJwPZ2R+juNgEdnYHcPlyI/j6OuLXX5dDJisSHZU0TFZWFtzd3WFra4sDBw5ozLaKymJjY4Pg4GDcunULEydO5PaMpNLCwrbC2BhwdvYWHUUtsVCSRjEyMsd77/nAyysJzZv/gaSkATA2Toa+/mKEhBhhx47OuHr1R9ExSQPI5XKMHTsWDx48QEhICCwtLUVHUkkuLi7Ys2cPDh06hBUrVoiOQ/RK9+8fQHq6FO3aDRMdRS2xUJLGsrd3wbhxxzByZB6MjfciPd0ZtrbRSE19F3v2mOHAgTFITY0THZPU1OLFi3H8+HHs378fzZs3Fx1HpQ0ePBhLly7FokWLEBzMsV+kmkxMriI9vSmkUlajyuCvGmk8qVSKjh3Hwts7Bn36ZCAraw6Ki41ha/s9Ll1qAF9fJ/z661dcEqdyCwgIwIoVK7Bq1Sq88w7Hi5TH4sWLMWTIEIwdOxZXr14VHYfoH27cOI06dYpQt+4g0VHUFp/yJq2VkHAFv/32GXR1T6Fu3UKkp0uRkdEJnTothrNzf9Hx6BVEP+V96dIluLm5YciQIdizZ4/W7ISjDDk5OXB1dUVOTg6io6NhbW0tOhIRAMDffwhsbY+iU6dHsLCoIzqOWuIVStJaDg6vY9y4HzBiRB4MDXchPb0V7OwikZLyDnbvNkNAwFikp8eLjkkqJCkpCe7u7nB2dtaqbRWVxdTUFMHBwcjKyuL2jKRSCgvP4MEDK5bJKmChJK0nlUrRubMnvL1j0atXOjIzZ0EmM4KNjT8uXHCCr28DnDy5kkviWq6wsBBDhgyBTCZDUFAQjIyMREdSSw0aNMDhw4dx9uxZzJ07V3QcImRmPoa9fRoMDLqLjqLWWCiJXmBsbAl393Xw8kpG06a/IympP0xMHkFX91MEBxtjxw5X/PnnCdExqYYpFApMnToVFy5cQGBgIOrXry86klrr3r07Nm7ciE2bNsHPz090HNJyYWGboK8PtGs3RXQUtaYrOgCRqnJ0bIfx43+EXC5HVNROPHmyFnXrhiMpqR+io81gZDQIfft+hVq17EVHpWq2efNm+Pn5YdeuXejcmUOPlWHKlCmIiYnBlClT0KJFC7i6uoqORFoqMfEozMz00KNHX9FR1BqvUBKVQSqVoksXL3h7X0OPHmnIyJiBkhIDWFvvQVSUA3x9G+HUqa9RUiITHZWqwalTpzB79mzMnj0bnp6eouNolA0bNqBLly4YPHgw4uN5vzLVPLlcjlq1biEn5zXRUdQeCyVRBZiYWMHDYwMmTUpBkyYXkJz8FkxNH0JHZz6Cggyxc2c3/PXXKdExSUnu3r2L4cOHo1evXvDx8REdR+Po6+vj8OHDMDIygoeHB/Ly8kRHIi1z+fJhWFuXoEGDkaKjqD0WSqJKcnJqj/Hjf8bw4fnQ19+OJ0+aws7uPB4/7oNduyxw6NBEZGQkio5JlZSdnY2BAwfCysoKAQEB0NXlHULVwdbWFsHBwbhx4wYmTZrE7RmpRl296of8fKBr1w9FR1F7LJREVSSVStG1qze8vf9Ejx5pePJkGuRyPVhb70JkZH34+jbG6dNruCSuRuRyOcaNG4f4+HiEhISgVq1aoiNptDZt2mDPnj0ICAjAypUrRcchrRKBhw/rwsjIXHQQtcdCSaREJiZWGDRoEyZNSkXDhpFISuoLM7MESKXzEBhoiJ07u+Pmzd9Ex6QyfP755wgJCcH+/fvRsmVL0XG0wpAhQ7BkyRJ89tlnOHbsmOg4pAWSkm7B3j4b5uZ8GEcZWCiJqknDhp3g6fkrhg0rgK7uNmRkNEXt2meRmNgTu3ZZ4vBhb2RmPhYdk/7l0KFDWL58OVasWIF3331XdByt8vnnn8PDwwNjxozB9evXRcchDRcevh46OkDnzjNFR9EI3HqRqAZlZ6fixIklyMgIQIMG6SgsBB4+bIwmTaahW7dp0NHhfXplqc6tFy9fvgxXV1d4eHjA39+fO+EIkJOTgy5duiA/Px/R0dGwsrISHYk0lK9vQxgaJmHsWD4Mpgy8QklUg8zMbDB48DeYNCkNDRqEIzm5D8zM4gHMxtGjRti1qwdu3jwrOqZWSk5Ohru7O1q1agU/Pz+WSUFMTU0REhKCjIwMjBgxAjIZ7z0m5ZPJimBnF4fiYuX+UKrNWCiJBGnUqAs8PU9g2LAC6OhsQWZmI9jZnUFiYnfs3FkLhw9P5pJ4DSkqKsKQIUNQVFTEbRVVQMOGDXHo0CGEhoZi3rx5ouOQBoqM3AlzcwWaNRsvOorGYKEkEkwqlaJbt4/g7X0Dbm5JSE//EIAENja+CA+vC1/fpjhzZhPkcrnoqBpJoVBg+vTpiI6ORmBgIOztufORKujZsyc2bNiADRs2YOfOnaLjkIa5eXMPsrIk6NRpgugoGoOFkkiFmJvbYfDgrZg4MR329ueRlNQL5ub3oVDMwOHDBti1qxdu3TovOqZG2bp1K7777jts27YNXbp0ER2HXvDRRx9h8uTJ+PDDDxERESE6DmkQA4NLSE5uAF1dfdFRNAYLJZGKatLEFRMmnMLQoYWQSDYiK6shatcOxcOH3bBzpxWOHPkQWVnJomOqtdDQUMyYMQMzZ87ExIkTRcehf5FIJNi8eTM6duyIQYMG4cGDB6IjkQaIi7uI+vULYG3NKQ7KxKe8idRIZuZjnDy5BFlZh9CwYQby8oDExKZo1mwG3Nw+glSq+T8jKusp73v37qFDhw5o27YtfvrpJ+6Eo8KSk5PRoUMH2Nra4ty5c7zHlaokIGA8bGz2onXr27Czayw6jsbQ/H99iDSIhUUdDBnyHSZOfIJ69c4gObkHLCzuQS6fjsOHDbB7dx/cvculwbI821bR0tKS2yqqATs7OwQHB+P69evw8vLi9oxUJTk5J5CQYM4yqWQslERqqlmzNzFhQigGD84HsB5ZWQ1gZ3cK9+93xc6dVjh6dAqys1NFx1Q5crkc48ePR1xcHEJCQjjnUE28/vrr2L17N/bv3w8fHx/RcUhN5ednoV69x5BKeb+0srFQEqk5HR1d9OgxE97et9C16yOkp3tBIpHDymobzp2zha9vC5w7t5VPif/tiy++QHBwMPz9/dGqVSvRcagChg0bhkWLFuHTTz/FDz/8IDoOqaGwsG9gZAS89pq36Cgah/dQEmmomzd/Q1jY5zAzC4ONTQmSkvRQUNAdb765HA0bdhIdr9Kqcg/lkSNHMHToUHz11VdYuHBhNSWk6iSXyzF48GCcPn0aUVFR3GudKsTPry0sLWMxaFCRVtxzXpP4q0mkoZo164GJE89g0KACKBRrkJ3tgNq1T+Levc7YscMagYFTtWpJ/I8//sD48eMxYsQIfPrpp6LjUCVJpVLs3bsXjo6OGDhwIJ48eSI6EqkRU9NrePKkGctkNeCvKJGG09HRRc+ec+DtfQedOz9EWtoESKUy1Kr1Dc6etYWvb0uEhX2n0UviKSkpcHd3R4sWLbBjxw5uq6jmzMzMEBwcjPT0dG7PSOV2/fovqF27GPXqDREdRSOxUBJpEUvLehg2bCcmTMhEnTonkZzcDZaWt1Bc/AEOHjTE7t1v4f79C6JjKlVRURGGDh2K/Px8BAUFwdjYWHQkUoLGjRvj0KFDOH36NObPny86DqmBS5e2oqgIcHObLjqKRmKhJNJSLVr0xsSJZzFoUAFKSnyQk2OP2rV/xZ07HbFjhw2CgmYgNzdddMwqmzlzJiIiInD06FE4ODiIjkNK1KtXL6xbtw7r1q3D7t27RcchFVdUdA4PHljD3NxOdBSNxEJJpOV0dHTRu/fH8Pa+i06dEpCW5gmptBiWlpvw22/W8PVthfBwX7VcEt+6dSu2bduGrVu3wtXVVXQcqgbTpk2Dl5cX3n//fURGRoqOQyoqIyMRDg7pMDTsITqKxuJT3kT0Un/+eQKRkV/A3DwS1tYlePRIH8XFvdC9+5dwcmovLFd5n/I+c+YM+vTpgylTpmDjxo01mJBqWmFhIXr37o07d+7g4sWLqF+/vuhIpGKOH18AU1Mf1KsXimbNeoiOo5F4hZKIXqply76YOPE83N3zUFKyCrm5dVG79s+4fbsDduywRVDQTOTlZdRoptxCGe5lFEO/bjPcyyhGbuHLH8a4f/8+hg4dijfffBNr1qyp0YxU8wwMDHDkyBHo6enBw8MD+fn5oiORinn8OAiPHumzTFYjXqEkonJLT4/HiROLUFAQBCenbOTkSPD4cSs4O89Fp06e1TKK41ZSNvyj4hF6Ixnx6Xl48RuWBICjlTF6NrfDmE6OaFrbDDk5OXB1dUVOTg6io6NhbW2t9Eykmi5dugQ3NzcMHjwYe/fu5dP8BODp7NLgYD2kp7eFl9dF0XE0FgslEVXKtWs/ISrqS1haRsHKSv73knhv9Oy5Ag4Or1f5+AnpeVgYGItzt1OhI5WgRP7qb1XPXndrYo3ME9vw2w9HEBkZCWdn5yrnIPUSEBCAkSNHwsfHBx9//LHoOKQCLl7cj5yc0ZDLV6NXr7mi42gsFkoiqhKZrAihoWsQF/ctHBzioKsL3L9vCxubsejbdwmMjS0rfMwDF+Lxecg1yOSKUovkv0mgQElxEUY318XKyQMrfF7SDJ999hn+97//4fjx43jnnXdExyHBdu/uA1vbU+jVKxuGhqai42gsFkoiUprU1DicPLkQRUUhcHTMQXa2BElJzmjd+mN06DC2XEvim0NvYfWvN6uQQgFAgnn9mmFaz6ZVOA6pK7lcDg8PD5w5cwZRUVFo0aKF6Egk0J49ZigqsoC39wPRUTQaCyURVYurV39EdPSXsLSMhpWVHImJBigp6YOePVfA3t7lpZ9z4EI8Pjkaq7QMqwa3xogOjko7HqmPrKwsdOnSBTKZDFFRUbC0tBQdiQR4/PgGrl9vgbS0CRg2bKfoOBqNhZKIqpVMVoTTp30QH/8dHB0ToKMD3L9vBzu78ejTZzGMjMwBPL1nss+6MyiUlT3vMjM8ABln90LPxhH1vL955fsMdKU4Obs7HKy4O442un37Njp27IhOnTrh+PHj0NHRER2JatjRo1NgZbUNTZr88cofZEk5ODaIiKqVrq4++vVbBG/veLRtexcpKaOgp5cLM7PVOHnSEr6+LoiO3odPA2MgK8f9krKsVGRGHIREz7Ds98oVWBiovCuepF6aNGmCgwcP4sSJE/jkk09ExyEB0tN/REKCMctkDWChJKIaY2vbECNHfo/x43NgZRWMlJQOsLa+hlvJC3H+dlq5HsB5EuoHg3rNoV+nSZnvLZErcO52Km4nZysjPqmhPn36YM2aNVi9ejX27NkjOg7VoOLiAtSpkwCZTNxGDNqEhZKIhHBxGYhJk6IwYEAuTt7/AhKUlPk5BfFXkfdXGGr1fr/c59GRSrAvMr4qUUnNzZgxAxMnTsT777+P6Oho0XGohkRE+MLUVIEWLSaIjqIVWCiJSCg9PUPczW8ABUq/v00hL0H6iW0wbdMP+nYNyn38ErkCoTeTq5iS1JlEIsHWrVvRrl07eHh4IDExUXQkqgG3b/sjM1OCjh3HiY6iFVgoiUionEIZ4tPzyn7f5Z8gy0qB5ZsV/8chPi3vlds0knYwMDDA0aNHoaOjg0GDBqGgoEB0JKpmBgZXkJLSEDo6uqKjaAUWSiISKi4tF2XdOVmSn4WMc/6w7DoCOsYWFT6HAsD9tNxK5SPNUadOHQQFBSEmJgbvv/8+OOREc929G4H69Qtga8sNDmoKCyURCVVUjjFBGWf3QmpkCrP271XreUjzvfHGG9ixYwf27t2LtWvXio5D1SQ6ehNKSgBX11mio2gNXgcmIqH0dUv/ubY4/SFyrvyCWr0noyQ7/fnHFSXFUMhLIMtIgsTAGDpGZlU6D2mPUaNGISYmBvPnz4ezszPefvtt0ZFIyXJzT6OgwAK9ezuJjqI1WCiJSKgG1iaQAK9c9i7JTgMUcjw5+S2enPz2P68/3OYFs/YDYdXn1U9+S/4+D9Ezy5cvR2xsLEaOHImoqCg0b95cdCRSkry8DNSvn4Tk5P6io2gVFkoiEsrEQBeOVsaIe8WDOXq2TrAd/Nl/Pp5xdi/kRfmw6vM+dC3rlnoOR2tjmBjw2x39Px0dHfj7+6Nz585wd3dHVFQULCwqfn8uqZ7z5zfD0BBo0+YD0VG0CteAiEi4ns3toCOVvPQ1HWMLGDfr8p//SI3MIdU3gnGzLqWOEZJAgU4OptWUnNSZhYUFQkJCkJSUhFGjRqGkpOxZqKT64uMPIjVVB61bV/6ea6o4FkoiEm5MJ8dy7ZJTGQpI8M3sUZg6dSru3btXLecg9dW0aVMEBATgl19+wcKFC0XHoSqSy+WwsPgTGRktIZWy4tQk/moTkXBNa5uhWxObV16lfJk6Y1ainvc3pb5HRypBZycLfPLRBBw8eBBNmzbF6NGj8ccff1Q1MmmQfv36YfXq1fDx8cG+fftEx6EquH79Z9jaymBvP0R0FK3DQklEKmHFoNbQrUChLA9dqQRfD2+HRYsWIS4uDuvXr0dERARef/119O/fH2fOnOEsQgIAzJo1C56envD29saFCxdEx6FKunx5KwoLAVfXaaKjaB0WSiJSCQ5WxvhioLNSj7lsoDMcrIwBAMbGxpg2bRpu3boFf39/PHz4ED169ECXLl0QFBQEuZxzKrWZRCLBtm3b0LZtW3h4eODRo0eiI1ElyGTn8eCBLczMbERH0ToslESkMkZ2cMS8fs2UcqyP+zXHiA6O//m4rq7u82XvH3/8EQYGBhg0aBCcnZ2xc+dOFBUVKeX8pH4MDQ1x9OhRSCQSbs+ohtLT4+HgkAFj416io2glFkoiUinTejbFysGtYaArrdA9lcDTeyYNdKVYNbg1pvZsUup7JRLJ82Xv8PBwNG/eHJMmTUKjRo2wdu1aZGdnV+XLIDVVt25dBAYG4sqVK/jwww95S4QaCQvbBF1doH17LneLIFHwbwsRqaCE9DwsDIzFudup0JFKSn0K/Nnr3ZrYYMWg1s+XuSvq+vXr+Prrr7Fv3z6Ymppi2rRpmD59Ouzs7Cr7ZZCa8vf3x9ixY7F27VrMnj1bdBwqB1/fZjAxiceoUbyyLAILJRGptFtJ2fCPikfozWTEp+X9Y0cdCZ4OLe/ZzA5jOzuiiV3p2y+WV0JCAtatW4fvvvsOJSUl8PLywty5c9GwYUOlHJ/Uw4IFC7B69Wr89NNP6Nevn+g4VIqSEhmOHTNAWtob8PKKFh1HK7FQEpHayC2U4X5aLopkcujrStHA2qRad8BJT0/Hli1bsHHjRjx58gQjRozA/Pnz0aZNm2o7J6mOkpISDBw4EOHh4YiOjkbTpk1FR6JXiIrag/x8TwDr0aPHTNFxtBILJRFRGfLy8rBjxw6sXr0acXFx6N+/PxYsWIA333wTEolyRx2RasnMzESnTp0gkUgQGRnJ7RlV1K5dvWBrG4o+fXJhYFC5W16oavhQDhFRGV4cObRv3z48ePAAPXr0QNeuXTlySMM9257x0aNHGDNmDLdnVFFSaTQePbJnmRSIhZKIqJz09PQwZswY/PHHH/jhhx+gr6/PkUNaoFmzZggICMBPP/2ERYsWiY5D/5KYeA329rmwtHxbdBStxkJJRFRBEokE77zzDkcOaZG33noLPj4+WLlyJb7//nvRcegF4eHrAQBdu84SmkPb8R5KIiIleNnIoRkzZsDW1lZ0NFIShUIBT09PHDp0COfOnUP79u1FRyIAvr4O0Nd/gvHjc0RH0WoslERESsSRQ5qtoKAA3bt3x8OHD3Hx4kXUqVNHdCStVliYh5MnTZCS0gMTJoSKjqPVuORNRKREDg4OWLt2LeLj47Fw4UIEBASgadOmGDNmDGJiYkTHoyoyNDREYGAg5HI5Bg8ejMLCQtGRtFpExHaYmAAtW04UHUXrsVASEVUDKysrLF68GHFxcVi/fj3CwsLQpk2b5/decnFIfdWrVw9BQUG4dOkSpkyZwt9Lge7c8UdGhhTt248WHUXrsVASEVUjjhzSTB07dsT27duxc+dObNy4UXQcrWVsHIPU1MbQ0am+DQ6ofFgoiYhqAEcOaZ5x48Zh3rx5mDt3Lk6ePCk6jta5des86tYthJ3de6KjEPhQDhGRMBEREVi1ahWCg4NRv359zJkzB5MnT4aZmXL2JKfqV1JSggEDBiAqKgrR0dFo0qSJ6EhaY//+kbC1DUC7dnGwsnIUHUfrsVASEQn24sghMzMzTJ06lSOH1EhGRgY6deoEHR0dREZGwtzcXHQkreDnZweptBgTJz4RHYXAJW8iIuFatWqFnTt34u7du5gwYQLWrVsHJycnTJs2Dffu3RMdj8pgaWmJkJAQPHz4EGPHjuV9sTUgOzsV9vYp0NV1Ex2F/sZCSUSkIl4cOfTpp59y5JAaad68OQ4cOIDjx49j8eLFouNovLCwzTAwANq2nSI6Cv2NhZKISMWUNnLo7NmzHFOjovr3749Vq1ZhxYoVOHDggOg4Gu3BgyNISdFFq1bcv1tVsFASEamol40c6t69O0cOqbB58+Zh7NixmDRpEi5duiQ6jkaSy+WwtPwTmZktIZWyxqgK/k4QEam4f48c0tPTez5yaNeuXRw5pEIkEgm+++47ODs7w93dHUlJSaIjaZzY2GOwsSmBo+Nw0VHoBSyURERqQiKRPF/2DgsLQ7NmzTBx4kQ0btwYa9euRXZ2tuiIBMDIyAhBQUGQyWTcnrEa/PHHtygoANzcpomOQi9goSQiUkNdu3ZFcHAwrl27hj59+mDBggVwcnLC4sWLkZKSIjqe1qtfvz4CAwNx8eJFTJ06lfe9KpFcHo6HD+1gbGwpOgq9gIWSiEiNvThyyNPTkyOHVEjnzp3x3Xffwc/PD5s3bxYdRyOkpsbBwSETJia9RUehf+FgcyIiDZKeno4tW7Zgw4YNyMjIwIgRI7BgwQK4uLiIjqa15syZg40bN+KXX35B794sQlURHDwbFhbr4egYjkaNuoiOQy9goSQi0kB5eXnYsWMHVq9ejbi4OPTv3x+ffPIJunXrBolEIjqeVpHJZHj33Xdx8eJFREdHo3HjxqIjqS1f38YwMkrEmDH5oqPQv3DJm4hIA/175FBCQsLzkUPBwcEcOVSDdHV1ceDAAVhbW8Pd3Z0PT1VSSYkMtrb3UFjYRnQUegkWSiIiDfZs5FBMTMzzkUMeHh547bXXOHKoBtWqVQvBwcGIj4/HuHHjWOgrITp6LywsFGjSZKzoKPQSLJRERFrg3yOHmjZt+nzk0Lp165CTkyM6osZr2bIl9u/fj5CQEHz++eei46idv/7ahexsCbp08RYdhV6ChZKISMu8OHKod+/emD9/PhwdHbFkyRKOHKpm7777Lv73v/9h+fLlOHjwoOg4akVX9yKSkhygp2coOgq9BB/KISLScgkJCVi7di22b98OuVwOLy8vzJ07Fw0aNBAdTSMpFAqMHTsWgYGBCAsLQ9u2bUVHUnkJCVdw505bpKd/iMGDt4qOQy/BQklERACAtLQ0bNmyBRs3bkRGRgZGjhyJ+fPnc+RQNcjPz0e3bt2QnJyMixcvws7OTnQklXbo0CRYW+9Ey5bXUbduS9Fx6CW45E1ERAAAa2trLFmyBHFxcVi3bh3Onz+PNm3a4N1338XZs2e524sSPduesaioCEOGDOHDUWXIzPwVDx6YskyqMBZKIiL6BxMTE0yfPh23bt3C3r17ER8fz5FD1cDe3h6BgYGIjo7GtGnTWNhfoaAgB/XqPYRC0Ul0FCoFCyUREb2Unp4exo4dy5FD1ahLly7Ytm0btm/fjm+++UZ0HJUUHv4tjI0BZ2cv0VGoFCyURERUKo4cql4TJ07EzJkzMXPmTISGhoqOo3Lu3duPJ0+kaNduhOgoVAo+lENERBV2/fp1+Pj4wN/fH2ZmZpg2bRqmT58OW1tb0dHUkkwmQ//+/XH58mVER0ejUaNGoiOpjP37DZCb2wDe3jdER6FS8AolERFVWKtWrbBr1y7cuXMHnp6eWLt2LZycnDB9+nTcv39fdDy1o6uri4CAAFhaWnJ7xhfcvPkb6tYtQp06HqKjUBlYKImIqNIcHR2xbt06xMXF4ZNPPsH+/fvRpEmT5/deUvlZWVkhJCQEcXFxGD9+PB9+AnDx4mYUFwNubjNFR6EysFASEVGVceSQcrRq1Qr+/v4IDg7GF198ITqOcAUFvyEhwQqWlvVER6EysFASEZHSvGrkkKurK0cOldN7772Hr776CsuWLcPhw4dFxxEmKysZ9vZp0NfvJjoKlQMLJRERKd2LI4eOHz8OXV1djhyqgE8++QQjR46Ep6cnrly5IjqOEOfPb4K+PtCu3RTRUagc+JQ3ERHViPDwcKxatQohISGwt7fHnDlzMHnyZJiamoqOppLy8vLQrVs3pKWl4cKFC1r3BL2vbyuYmd3GiBH84UMd8AolERHViGc77Vy9ehW9e/fG/Pnz4ejoiCVLliAlJUV0PJVjbGyMoKAg5OfnY+jQoVp1VVcul6NWrZvIyXEWHYXKiYWSiIhqlLOz8z9GDq1Zs4Yjh17BwcEBR48eRUREBGbO1J4nnf/4IxDW1iVwdBwuOgqVEwslEREJ8WzkUHx8PEcOlcLV1RVbt27Ftm3bsHXrVtFxakRs7Hbk5wNublNFR6FyYqEkIiKh/j1y6Ny5c89HDp07d44jhwB4eXlh+vTpmDFjBs6cOSM6TrWTyyOQmFgHRkbmoqNQObFQEhGRSng2cuj27dvPRw69+eabHDn0t7Vr16J79+4YMmQI7t27JzpOtUlOvgMHhyyYmvYVHYUqgIWSiIhUyr9HDuno6HDkEP5/e0YLCwu4u7sjJydHdKRqER6+ATo6QKdO00VHoQpgoSQiIpUkkUieL3uHhYWhadOmmDhxIho3box169ZpbKEqjbW1NUJCQnDv3j14enpq5FXb1NTjePjQEA0adBAdhSqAhZKIiFQeRw79P2dnZ+zbtw9Hjx7Fl19+KTqOUslkRbCzu4/Cwnaio1AFsVASEZHa4Mihp9zd3bF8+XIsXboUR48eFR1HaaKidsHcXIFmzcaLjkIVxJ1yiIhIbaWlpWHLli3YuHEjMjIyMHLkSCxYsACtW7cWHa3aKRQKjBw5EsePH0dERARcXFxER6qynTvdYGMTjv79C6Crqy86DlUAr1ASEZHaetnIIRcXF60YOSSRSLBjxw40a9YM7u7uSE1NFR2pyvT0LiEpyZFlUg2xUBIRkdorbeRQSEiIRj68Ajz9uoODg5Gbm4thw4ahuLhYdKRKi4+/BHv7fFhbvys6ClUCCyUREWmMl40ccnd3R+vWrbF7926NHDnk6OiIo0ePIiwsDLNmzRIdp9IiIzegpARwdZ0jOgpVAgslERFpnBdHDp0/fx6NGzfGhAkT0LhxY6xfv17jRg65ublhy5Yt+Oabb/Dtt9+KjlMpWVkn8OCBGezsGouOQpXAQklERBrt2bL31atX0atXL3z88cdwdHTE559/rhH3HT4zefJkTJ06FdOmTcPZs2dFx6mQ/Pws1Kv3CEBn0VGokviUNxERaZX4+HisXbsW27dvh0KhgLe3N+bOnQsnJyfR0aqsuLgYb731FmJjY3Hx4kW1+ZpOnfKBjs4CmJkF4I03houOQ5XAQklERFopLS0NmzdvxqZNm5CRkYFRo0Zh/vz5aj9yKC0tDR06dIC5uTnCwsJgYmIiOlKZ/PzawdIyBoMGFUEq5eKpOuLvGhERaSVra2t8/vnnz0cOnT17Fi4uLhgwYIBajxyytrZGcHAwbt++jQkTJqjF12FqehVPnjRlmVRj/J0jIiKt9uLIoT179iAuLg5vvvkm3Nzc1HbkUOvWrbF3714cPnwYy5cvFx2nVH/+eQK1axejXr3BoqNQFbBQEhER4enIoXHjxj0fOSSVStV65NCgQYOwbNkyLFmyBIGBgaLjvNKlS1tRVAS4uk4XHYWqgIWSiIjoBa8aOdSkSRO1Gzm0aNEiDB06FOPGjUNsbKzoOC9VWHgGDx5Yw8KijugoVAUslERERK/w4sihnj174uOPP4aTk5PajBySSCTYtWsXmjRpopLbM2ZmPoa9fToMDLqLjkJVxEJJRERUBmdnZ+zevRt37tzBuHHjsHr1ajg6OmLGjBmIi4sTHa9Uz7ZnzM7OxvDhw1Vqe8bz5zdAXx94442PREehKmKhJCIiKidHR0esX78e8fHxWLBgAb7//ns0btxYpZeUAcDJyQlHjhzBuXPnMGeO6mxt+OhREB4/1kOLFr1FR6EqYqEkIiKqoBdHDq1du/YfI4fOnz8vOt5Lvfnmm9i8eTM2b96M7du3i44DuVwOK6ubyM1V77mf9BQLJRERUSWZmJhgxowZz0cO3b9/H926dXt+76WqjRz64IMPMGXKFEydOlV48b106RCsrORo0GCk0BykHCyUREREVfTiyKFjx479Z+SQKt23uGHDBnTt2hWDBw9GfHy8sBzXrvkiLw9wdZ0iLAMpDwslERGRkkil0uc77bw4cqhx48YqM3JIT08Phw4dgomJCdzd3ZGbmysoSRQSE+vC0NBU0PlJmVgoiYiIqsGzZe/Y2FiVGzlka2uL4OBg3Lp1CxMnTqzx7RmTkm7B3j4b5ub9avS8VH1YKImIiKrRa6+9ppIjh1xcXLBnzx4cOnQIK1asqNFzh4Wtg44O0KXLrBo9L1UfFkoiIqIa8O+RQ/7+/sJHDg0ePBhLly7FokWLEBISUmPnTU//EQkJRnBweL3GzknVi4WSiIioBj0bORQfH4+1a9fizJkzQkcOLV68GEOGDMGYMWNw7dq1aj9fcXEBateOh0zWvtrPRTWHhZKIiEiAZyOH7ty585+RQ8eOHauxkUNSqRS7du1Co0aNMHDgQKSlpVXr+SIjd8LMTIHmzcdX63moZrFQEhERCfTvkUMSiQQDBw6s0ZFDpqamCAoKQmZmJkaMGAGZTFZt57p1ay+ysiTo2JGFUpOwUBIREamAZyOHzp8/j3PnzqFRo0bPRw5t2LCh2sf7NGzYEIcPH8aZM2cwd+7cajuPgcFlJCc3hK6ufrWdg2oeCyUREZGKcXNzw7FjxxAbG4sePXpg3rx5cHR0rPaRQz169MDGjRuxceNG+Pn5Kf349+5FoX79AtjYDFD6sUksiaKmh08RERFRhTzbM9zX1xcKhQLe3t6YO3cunJycquV8H374IXbs2IHQ0FC4uroq7bgBAWNhY+MPF5e7sLVtqLTjkngslERERGoiNTUVmzdvxqZNm5CZmYlRo0Zh/vz5aN26tVLPU1RUhD59+uDGjRu4ePEiHBwclHJcP7+60NHJw4QJmUo5HqkOLnkTERGpCRsbGyxdurTaRw7p6+vjyJEjMDIygoeHB/Ly8qp8zLy8DNSv/xhSaVclJCRVw0JJRESkZl4cObR79+5qGTn0bHvGv/76C5MmTary9oznz2+BoSHg4vJ+lbOR6mGhJCIiUlN6enoYP378S0cO7dmzp8ojh9q0aYPdu3cjICAAK1eurNKx4uMPIjVVBy4u7lU6DqkmFkoiIiI197KRQ56enkoZOTR06FAsXrwYn332GY4dO1apY8jlcpibX0dGRnNIpawemogP5RAREWmgq1evwsfHB99//z0sLCwwffp0TJs2DTY2NhU+llwux5AhQ3Dq1ClERkaiVatWFfr8a9d+QkrKO8jPX4z+/ZdV+Pyk+lgoiYiINNiLI4cAwNvbG3PmzKnwyKGcnBx06dIF+fn5iI6OhpWV1Svfm1sow/20XBTJ5NDXlSLyxCTY1zmKrl1TYGZW8UJLqo+FkoiISAv8e+TQ6NGjMX/+fLz22mvlPsbdu3fRoUMHtGvXDj/99BN0dXWfv3YrKRv+UfEIvZGM+PQ8/LNcKFBLNxnuHTphTCdHNK1tprSvi1QDCyUREZEWyc3Nha+vL9asWYOEhAQMGDAACxYsgJubW7k+PzQ0FH379sX06dOxbt06JKTnYWFgLM7dToWOVIIS+atrxbPXuzWxwYpBreFgZaysL4sEY6EkIiLSQsXFxdi/fz98fHxw7do1uLq6YsGCBXj33XfLfHBmy5YtmDZtGqat+x6/pllCJleUWiT/TUcqga5Ugi8GOmNkB8eqfimkAlgoiYiItJhcLscPP/yAVatWISwsDM7Ozpg/fz5GjRoFPT29l36OQqFA31lrcNu4ZZXPP69fM0zr2bTKxyGx+Ow+ERGRFpNKpXjvvfeejxxq2LBhmSOHAi4mKKVMAsDqX28i4EK8Uo5F4vAKJREREf1DaSOHEtLz0GfdGRTK/rsbT0FcDJL2L3zpMeuMWw2D+i1e+pqBrhQnZ3fnPZVqjIWSiIiIXurZyKHt27dDIpHA29sbD5sNwuXEvJfeM/msUJq98R706zb7x2tGjdpBx9jipefRkUrQtZE19np1qpavg6ofCyURERGV6tnIoS17j8Bk+Ku3YHxWKG08PoFJi/I9Nf6ik7PfRBM7jhRSR7yHkoiIiEplY2ODpUuX4v2v90KC8l2HkhfmQSEvKfc5dKQS7IvkvZTqSrfstxAREREB5+88gQKSMt+X9uMGKIryAYkUBg7OqNVzEgzqlv4kd4lcgdCbyVgKZ2XFpRrEQklERERlyimUIT49r/Q36ejBuHlXGDVqD6mxBYpT45EVHYgk/wWoM/Zr6NdpXOqnx6flIbdQBhMD1hN1w98xIiIiKlNcWm6Zi92G9i1haP/COKGmnWDcwhWP/KbjyZndqD1iWamfrwBwPy0XzvVe/vAOqS7eQ0lERERlKnrJmKDy0KtVD0ZNO6EgPqZc91RW9jwkFgslERERlUlft/KVQdfcBiiRQVFcWK3nIXH4u0ZERERlamBtUo7HcV5OlvEYEl19SPQNS32f5O/zkPphoSQiIqIymRjowrGMnWxK8jL/87GipLvIuxUNwwZtIZGUXjscrY35QI6a4u8aERERlUvP5nbYGxX30l1yACAlaBWkevowqN/y76e8E5Dzx8+Q6BmgVo8JpR5bRypBz2Z21ZCaagILJREREZXLmE6O2BVx/5WvGzfrjNxrvyErOgjyojzoGFvAuFlXWLiNgl6teqUeu0SuwNjOjkpOTDWFWy8SERFRuY3zi0L43bRXXqWsDO7lrf54DyURERGV24pBraErrezjOS+nK5VgxaDWSj0m1SwWSiIiIio3BytjfDFQudsjLhvoDIcyHvgh1cZCSURERBUysoMj5vVrppRjfdyvOUZ04L2T6o73UBIREVGlHLgQj89DrkEmV1TonkodqQS6UgmWDXRmmdQQLJRERERUaQnpeVgYGItzt1OhI5WUWiyfvd6tiQ1WDGrNZW4NwkJJREREVXYrKRv+UfEIvZmM+LQ8vFguJHg6tLxnMzuM7eyIJnZmomJSNWGhJCIiIqXKLZThflouimRy6OtK0cDahDvgaDgWSiIiIiKqEj7lTURERERVwkJJRERERFXCQklEREREVcJCSURERERVwkJJRERERFXCQklEREREVcJCSURERERVwkJJRERERFXCQklEREREVcJCSURERERVwkJJRERERFXCQklEREREVcJCSURERERVwkJJRERERFXCQklEREREVcJCSURERERVwkJJRERERFXCQklEREREVcJCSURERERVwkJJRERERFXCQklEREREVcJCSURERERVwkJJRERERFXCQklEREREVcJCSURERERVwkJJRERERFXCQklEREREVcJCSURERERVwkJJRERERFXCQklEREREVcJCSURERERVwkJJRERERFXCQklEREREVcJCSURERERVwkJJRERERFXCQklEREREVcJCSURERERV8n/wszsJSAZJowAAAABJRU5ErkJggg==", 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" ] @@ -840,7 +707,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" }, "vscode": { "interpreter": { diff --git a/applications/optimization/minimum_dominating_set/minimum_dominating_set.qmod b/applications/optimization/minimum_dominating_set/minimum_dominating_set.qmod index e59e6d282..dfb902b30 100644 --- a/applications/optimization/minimum_dominating_set/minimum_dominating_set.qmod +++ b/applications/optimization/minimum_dominating_set/minimum_dominating_set.qmod @@ -1,2723 +1,35 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=131.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=19.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=19.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=15.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - 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Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-4.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-8.0 - } -]; - -qfunc main(params_list: real[12], output target: qbit[20]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + x_0: qbit; + x_1: qbit; + x_2: qbit; + x_3: qbit; + x_4: qbit; + x_5: qbit; + dominating_rule_0_slack_var_0: qbit; + dominating_rule_0_slack_var_1: qbit; + dominating_rule_1_slack_var_0: qbit; + dominating_rule_1_slack_var_1: qbit; + dominating_rule_2_slack_var_0: qbit; + dominating_rule_2_slack_var_1: qbit; + dominating_rule_2_slack_var_2: qbit; + dominating_rule_3_slack_var_0: qbit; + dominating_rule_3_slack_var_1: qbit; + dominating_rule_4_slack_var_0: qbit; + dominating_rule_4_slack_var_1: qbit; + dominating_rule_4_slack_var_2: qbit; + dominating_rule_5_slack_var_0: qbit; + dominating_rule_5_slack_var_1: qbit; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=False, -initial_point=[0.0, 0.049907578558225495, 0.0099815157116451, 0.0399260628465804, 0.0199630314232902, 0.029944547134935294, 0.0299445471349353, 0.019963031423290194, 0.0399260628465804, 0.009981515711645097, 0.049907578558225495, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=30, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=0.7 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[12], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 6) { + phase (-(((((((((((v.x_0 + v.x_1) + v.x_2) + v.x_3) + v.x_4) + v.x_5) + (80 * ((((((((v.dominating_rule_0_slack_var_0 / 2) + v.dominating_rule_0_slack_var_1) - (v.x_0 / 2)) - (v.x_1 / 2)) - (v.x_3 / 2)) - (v.x_5 / 2)) + 0.5) ** 2))) + (80 * ((((((((v.dominating_rule_1_slack_var_0 / 2) + v.dominating_rule_1_slack_var_1) - (v.x_0 / 2)) - (v.x_1 / 2)) - (v.x_2 / 2)) - (v.x_4 / 2)) + 0.5) ** 2))) + (80 * ((((((((v.dominating_rule_3_slack_var_0 / 2) + v.dominating_rule_3_slack_var_1) - (v.x_0 / 2)) - (v.x_2 / 2)) - (v.x_3 / 2)) - (v.x_4 / 2)) + 0.5) ** 2))) + (80 * ((((((((v.dominating_rule_5_slack_var_0 / 2) + v.dominating_rule_5_slack_var_1) - (v.x_0 / 2)) - (v.x_2 / 2)) - (v.x_4 / 2)) - (v.x_5 / 2)) + 0.5) ** 2))) + (80 * ((((((((((v.dominating_rule_2_slack_var_0 / 2) + v.dominating_rule_2_slack_var_1) + (v.dominating_rule_2_slack_var_2 / 2)) - (v.x_1 / 2)) - (v.x_2 / 2)) - (v.x_3 / 2)) - (v.x_4 / 2)) - (v.x_5 / 2)) + 0.5) ** 2))) + (80 * ((((((((((v.dominating_rule_4_slack_var_0 / 2) + v.dominating_rule_4_slack_var_1) + (v.dominating_rule_4_slack_var_2 / 2)) - (v.x_1 / 2)) - (v.x_2 / 2)) - (v.x_3 / 2)) - (v.x_4 / 2)) - (v.x_5 / 2)) + 0.5) ** 2))), params[i]); + apply_to_all(lambda(q) { + RX(params[6 + i], q); + }, v); + } +} diff --git a/applications/optimization/minimum_dominating_set/minimum_dominating_set.synthesis_options.json b/applications/optimization/minimum_dominating_set/minimum_dominating_set.synthesis_options.json index 0967ef424..67f14d055 100644 --- a/applications/optimization/minimum_dominating_set/minimum_dominating_set.synthesis_options.json +++ b/applications/optimization/minimum_dominating_set/minimum_dominating_set.synthesis_options.json @@ -1 +1,43 @@ -{} +{ + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "rz", + "z", + "ry", + "sxdg", + "id", + "y", + "cy", + "sdg", + "sx", + "t", + "cz", + "u2", + "cx", + "p", + "h", + "u1", + "r", + "u", + "s", + "rx", + "x", + "tdg" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 3580858457 + } +} diff --git a/applications/optimization/set_cover/set_cover.ipynb b/applications/optimization/set_cover/set_cover.ipynb index fdf65e2f6..6506704b4 100644 --- a/applications/optimization/set_cover/set_cover.ipynb +++ b/applications/optimization/set_cover/set_cover.ipynb @@ -2,8 +2,9 @@ "cells": [ { "cell_type": "markdown", - "id": "11d8810e-c1b2-458c-bf28-ecab44a01cc2", + "id": "acdcdf8c-96e0-40c3-80de-edbb55839e13", "metadata": { + "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ @@ -13,7 +14,7 @@ }, { "cell_type": "markdown", - "id": "877ae3cf-10cc-4e51-a428-eb57687d8d18", + "id": "c01e205c-4ff3-4ffd-94ce-e600917fa226", "metadata": {}, "source": [ "## Introduction\n", @@ -29,49 +30,21 @@ "We go through the steps of solving the problem with the Classiq platform, using QAOA algorithm [[2](#QAOA)]. The solution is based on defining a pyomo model for the optimization problem we would like to solve." ] }, - { - "cell_type": "code", - "execution_count": 1, - "id": "49a9588b-e79e-4813-b7c5-ac068d7b930c", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:36:44.114329Z", - "iopub.status.busy": "2024-05-07T15:36:44.114069Z", - "iopub.status.idle": "2024-05-07T15:36:45.009877Z", - "shell.execute_reply": "2024-05-07T15:36:45.009179Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "import networkx as nx\n", - "import numpy as np\n", - "import pyomo.core as pyo\n", - "from IPython.display import Markdown, display\n", - "from matplotlib import pyplot as plt" - ] - }, { "cell_type": "markdown", "id": "8517ef73-faf6-4fd8-9db8-4088551398e0", "metadata": {}, "source": [ - "## Building the Pyomo model from a graph input\n", + "## Building the Pyomo model from an input\n", "\n", "We proceed by defining the pyomo model that will be used on the Classiq platform, using the mathematical formulation defined above:" ] }, { "cell_type": "code", - "execution_count": 2, - "id": "48889b21-557b-481c-80c5-3c0b5c91adb6", + "execution_count": 1, + "id": "4c9dd3a1-1f62-42af-9fee-d10972468138", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:36:45.021711Z", - "iopub.status.busy": "2024-05-07T15:36:45.014097Z", - "iopub.status.idle": "2024-05-07T15:36:45.033939Z", - "shell.execute_reply": "2024-05-07T15:36:45.033189Z" - }, "tags": [] }, "outputs": [], @@ -79,6 +52,8 @@ "import itertools\n", "from typing import List\n", "\n", + "import pyomo.core as pyo\n", + "\n", "\n", "def set_cover(sub_sets: List[List[int]]) -> pyo.ConcreteModel:\n", " entire_set = set(itertools.chain(*sub_sets))\n", @@ -102,27 +77,21 @@ }, { "cell_type": "markdown", - "id": "ffd32c78-9492-4ced-a5a0-9ba61d1b43b7", + "id": "58060aae-2336-4c01-bd4f-4529ff6d658a", "metadata": {}, "source": [ "The model contains:\n", "\n", "- Binary variable for each subset (model.x) indicating if it is included in the sub-collection.\n", - "- Objective rule \u2013 the size of the sub-collection.\n", - "- Constraint \u2013 the sub-collection covers the original set." + "- Objective rule – the size of the sub-collection.\n", + "- Constraint – the sub-collection covers the original set." ] }, { "cell_type": "code", - "execution_count": 3, - "id": "69359e3e-ed85-4b56-9afb-9dd4b9997ada", + "execution_count": 2, + "id": "f01725a9-40d9-40ef-9915-19363e9a31da", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:36:45.038822Z", - "iopub.status.busy": "2024-05-07T15:36:45.037683Z", - "iopub.status.idle": "2024-05-07T15:36:45.054023Z", - "shell.execute_reply": "2024-05-07T15:36:45.053234Z" - }, "tags": [] }, "outputs": [], @@ -143,15 +112,9 @@ }, { "cell_type": "code", - "execution_count": 4, - "id": "4a985b32-0670-42f3-ba50-5c0097eb75f5", + "execution_count": 3, + "id": "a972ae72-1232-4398-8914-91b025b86587", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:36:45.059024Z", - "iopub.status.busy": "2024-05-07T15:36:45.057842Z", - "iopub.status.idle": "2024-05-07T15:36:45.067477Z", - "shell.execute_reply": "2024-05-07T15:36:45.066797Z" - }, "tags": [] }, "outputs": [ @@ -215,95 +178,73 @@ "source": [ "## Setting Up the Classiq Problem Instance\n", "\n", - "In order to solve the Pyomo model defined above, we use the Classiq combinatorial optimization engine. For the quantum part of the QAOA algorithm (`QAOAConfig`) - define the number of repetitions (`num_layers`):" + "In order to solve the Pyomo model defined above, we use the `CombinatorialProblem` quantum object. Under the hood it tranlates the pyomo model to a quantum model of the qaoa algorithm, with cost hamiltonian translated from the pyomo model. We can choose the number of layers for the qaoa ansatz using the argument `num_layers`, and the `penalty_factor`, which will be the coefficient of the constraints term in the cost hamiltonian." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "816b468f-a59f-4f2f-8337-4a9d66548425", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:36:45.072198Z", - "iopub.status.busy": "2024-05-07T15:36:45.071028Z", - "iopub.status.idle": "2024-05-07T15:36:47.002020Z", - "shell.execute_reply": "2024-05-07T15:36:47.001218Z" - }, "tags": [] }, "outputs": [], "source": [ "from classiq import *\n", - "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n", + "from classiq.applications.combinatorial_optimization import CombinatorialProblem\n", "\n", - "qaoa_config = QAOAConfig(num_layers=3, penalty_energy=10)" - ] - }, - { - "cell_type": "markdown", - "id": "db34d5ac-6877-4285-8dec-7bf7b37eb783", - "metadata": {}, - "source": [ - "For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`max_iteration`) and the $\\alpha$-parameter (`alpha_cvar`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" + "combi = CombinatorialProblem(pyo_model=set_cover_model, num_layers=3, penalty_factor=10)\n", + "\n", + "qmod = combi.get_model()" ] }, { "cell_type": "code", - "execution_count": 6, - "id": "e41d0dd3-4135-4330-9ba3-c1b30c339a74", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:36:47.007469Z", - "iopub.status.busy": "2024-05-07T15:36:47.006012Z", - "iopub.status.idle": "2024-05-07T15:36:47.011287Z", - "shell.execute_reply": "2024-05-07T15:36:47.010661Z" - }, - "pycharm": { - "name": "#%%\n" - }, - "tags": [] - }, + "execution_count": 5, + "id": "62ec28b3-cb49-411a-8c4a-8004fff6c105", + "metadata": {}, "outputs": [], "source": [ - "optimizer_config = OptimizerConfig(max_iteration=60, alpha_cvar=0.7)" + "write_qmod(qmod, \"set_cover\")" ] }, { "cell_type": "markdown", - "id": "214d6051-43b8-4b9d-8454-f9cdb62b4cf0", + "id": "943291f0-6a9f-4286-a69d-ef13a0a12ef6", "metadata": {}, "source": [ - "Lastly, we load the model, based on the problem and algorithm parameters, which we can use to solve the problem:" + "## Synthesizing the QAOA Circuit and Solving the Problem\n", + "\n", + "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "0243019c-6fc3-435f-b6ec-8b4355d6660c", + "execution_count": 6, + "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:36:47.015793Z", - "iopub.status.busy": "2024-05-07T15:36:47.014626Z", - "iopub.status.idle": "2024-05-07T15:36:49.435098Z", - "shell.execute_reply": "2024-05-07T15:36:49.434274Z" - }, "pycharm": { "name": "#%%\n" }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Opening: https://nightly.platform.classiq.io/circuit/d637438d-d18b-453c-81e6-1a142f3f6bb7?version=0.61.0.dev7\n" + ] + } + ], "source": [ - "qmod = construct_combinatorial_optimization_model(\n", - " pyo_model=set_cover_model,\n", - " qaoa_config=qaoa_config,\n", - " optimizer_config=optimizer_config,\n", - ")" + "qprog = combi.get_qprog()\n", + "show(qprog)" ] }, { "cell_type": "markdown", - "id": "1fcc3812-c9d0-421c-84bb-38047297b33f", + "id": "b119464b-9d46-4ea0-ba4a-1734f3e0e3e5", "metadata": {}, "source": [ "We also set the quantum backend we want to execute on:" @@ -311,67 +252,31 @@ }, { "cell_type": "code", - "execution_count": 8, - "id": "53bc041f-065c-44d2-b220-dafd9d0504ac", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:36:49.440751Z", - "iopub.status.busy": "2024-05-07T15:36:49.439278Z", - "iopub.status.idle": "2024-05-07T15:36:49.569569Z", - "shell.execute_reply": "2024-05-07T15:36:49.568764Z" - }, - "tags": [] - }, + "execution_count": 7, + "id": "7d188c69-21d1-4afe-86b1-46229e91a01e", + "metadata": {}, "outputs": [], "source": [ - "from classiq.execution import ClassiqBackendPreferences\n", + "from classiq.execution import *\n", "\n", - "qmod = set_execution_preferences(\n", - " qmod, backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\")\n", + "execution_preferences = ExecutionPreferences(\n", + " backend_preferences=ClassiqBackendPreferences(backend_name=\"simulator\"),\n", ")" ] }, - { - "cell_type": "code", - "execution_count": 9, - "id": "4f2734e8-3b97-4298-8afe-640044685896", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:36:49.574677Z", - "iopub.status.busy": "2024-05-07T15:36:49.573452Z", - "iopub.status.idle": "2024-05-07T15:36:49.710082Z", - "shell.execute_reply": "2024-05-07T15:36:49.709369Z" - } - }, - "outputs": [], - "source": [ - "write_qmod(qmod, \"set_cover\")" - ] - }, { "cell_type": "markdown", - "id": "943291f0-6a9f-4286-a69d-ef13a0a12ef6", + "id": "07621d7c-0e54-4adb-9c47-8fd99a346e29", "metadata": {}, "source": [ - "## Synthesizing the QAOA Circuit and Solving the Problem\n", - "\n", - "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" + "We now solve the problem by calling the `optimize` method of the `CombinatorialProblem` object. For the classical optimization part of the QAOA algorithm we define the maximum number of classical iterations (`maxiter`) and the $\\alpha$-parameter (`quantile`) for running CVaR-QAOA, an improved variation of the QAOA algorithm [[3](#cvar)]:" ] }, { "cell_type": "code", - "execution_count": 10, - "id": "1d71e29a-5d53-49c4-84b2-45f59be4da31", + "execution_count": 8, + "id": "62d12d20-1c80-4a9e-bb6b-b1fddc6cbe40", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:36:49.714846Z", - "iopub.status.busy": "2024-05-07T15:36:49.713781Z", - "iopub.status.idle": "2024-05-07T15:36:57.571614Z", - "shell.execute_reply": "2024-05-07T15:36:57.570935Z" - }, - "pycharm": { - "name": "#%%\n" - }, "tags": [] }, "outputs": [ @@ -379,39 +284,17 @@ "name": "stdout", "output_type": "stream", "text": [ - "Opening: https://platform.classiq.io/circuit/11fd03ea-49d7-4ea9-a772-fca49f53953e?version=0.41.0.dev39%2B79c8fd0855\n" + "CPU times: user 4min 42s, sys: 1.05 s, total: 4min 43s\n", + "Wall time: 19min 24s\n" ] } ], "source": [ - "qprog = synthesize(qmod)\n", - "show(qprog)" - ] - }, - { - "cell_type": "markdown", - "id": "80238cf9-d7bd-46e5-9d48-b7cf23a6b304", - "metadata": {}, - "source": [ - "We now solve the problem by calling the `execute` function on the quantum program we have generated:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "62d12d20-1c80-4a9e-bb6b-b1fddc6cbe40", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:36:57.574164Z", - "iopub.status.busy": "2024-05-07T15:36:57.573795Z", - "iopub.status.idle": "2024-05-07T15:47:48.605861Z", - "shell.execute_reply": "2024-05-07T15:47:48.605172Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "result = execute(qprog).result_value()" + "%%time\n", + "cost_values = []\n", + "optimized_params = combi.optimize(\n", + " execution_preferences, maxiter=60, cost_trace=cost_values, quantile=0.7\n", + ")" ] }, { @@ -424,33 +307,41 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 9, "id": "02454398-b229-403c-824a-b1eb539fbc1f", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:47:48.614337Z", - "iopub.status.busy": "2024-05-07T15:47:48.613888Z", - "iopub.status.idle": "2024-05-07T15:47:48.663145Z", - "shell.execute_reply": "2024-05-07T15:47:48.662502Z" - }, "tags": [] }, "outputs": [ { "data": { - "image/jpeg": 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//u//vu9970vXh9wMJV4HJM2j17/+9dA8FgIs0rwU+jG8SoB685vfTDWJTG6WxK+OQG8ikE6F6E3hXCpHYLsIwHYwEO07CVGSuMUIjPWY9tpCeHrixAkCaa9RKNFxiWYUaE08VwgDqoAbnv/855MKYoAM8EBXXOEbriQnT0ZwiW9KNpo0rA/9kC3MRyA5MKsImiE+jpjw3Mte9jKMt9yiApIhrI8/owrKglyRB1KByOlAkAmOOGRLNHJGfsLJ2RISDq8TmblX0A+KKXWkXhQHDxGfCLCaiUFWcDPVZxwXqzU5oMpjaUcRp2gM9RAtjs4KXAuMAIgwpOUWxZfk+PHAgoRzNds+HElWOMCkdAZ6EQNpudJTwVEokakvIhFOzgTavC1C4FHSUnGQxzIBAcPr9hJR95/4xCfyFLSpEQjbvG5CGLCHd6kgOQAIrGwCgwMdjixDPO4cgd5EwAm4N9+LS3WZCFirba28sSYqF203TECjTKMPQ0A/5G6cB+tYSVCLkTTtOIGwLAl/4Ad+gEnUGGZp38nTKOTLv/zLYQ4ikyEx8cBSlGsMR/5wM/O2LH8yJx+u5A9/PPe5z2XAmClLDAxDwKh9qKc8zcQwYe75lZoiGM6yQjzrN1gfArX7d37nd6A6yBKD8Hd913chgFEmkjPuix5PRSB1I2CWMjPySlbMlCYaC5+sywLf0xsgnNpxvUgtqCzcCU8z9w0wAQceJbl1DsiTgmBfMgEQisbhJwmgZdlSHSuIVMQnB3RxhpbR0ekwIS2dHnoP6NP2ui1D8nHnCPQmAk7AvfleXKrLRIAGmsbdrJdGxpaRURFNv90aleKnjYaE0L1o8U21gkdp3KEK4sA3EA80wFPCYQL0LZ7CHPAERAsrkwkF4bHJ0gxAwtAEGgcwgxdWQB6kgrdwGGAhP27RcU0VNpG4IjwOkbDWogVioKY3YHTFU4qGjeAeOhCEY6Rl7hLxCUdfhHGR1nRKpIWNTDa7IjMlkglXnsK4TDpjkJjOAfZzRnl5RH3RpHlKfak1j8iTWpM/T4GIq8FIODUiGl0QHGSM9s9THGAiEuZrqoCHp0iCY2gcHEAMVZhoyENdkI3q4EFjpiDyRBirhb0LQmBTpssBJqnIzV4WIiEeMVGCra9ANKsp8Ioc6qgL8Tt3/u0I9BwCPgbcc6/EBbonCBjN0KyTCa08DTd+YykIgxDCoQGab/gSP9TFUzjPWnxC4BiIlslZ3/qt38oSF8ZB4QY4hqbcqM4I6e677yYydmDafRp6NEuMzxTx7//+71Y6bMEUZUJ4Sky4hCuOCcwMu7761a8m7eMe9zijDXuEJBRNcor7oR/6IaRl0i9XAmFW4uChIPRmBGZGMSFWX+Yekw96LT0DiqNDQOko7kRGbGpk9TVJCGQiNBTLJCYGYhk3ZeIxQMFn5PYd3/EdaKuf+9znyBzipLJIBQhkQhXwULRJAg3jITkWbAZ6MfxyC4szFg4vEpkkkOsznvEMyPu3fuu3eGpJqAtPqSNXU82JxiNqhwxEowirL7Vg9BcCZsQaP/ERhtdBpfAgKq+PWpCcVNa3wGPcj8fZFxDc9TICrgH38ttx2baNABxjVEFK2IjrBz7wAcyktN3cojjSKN90001QC2ZVWnxUUuMwWnz8tPIMdlrDzaLSj3/84/e73/2Yb4yuSfx3v/vdMBCTp8iNOMSHqNDe8FMutME6GeYtM6zLDGr4j+W2aKsQHgVBkDArfMYjSmECEewL/UAeRCBDrkgLYUMw0CGaHMuQyBBNF4GpFEmYdP0TP/ETMDeGcaZcYVVmV69bbrkFOmdAF0usCQZnw2eIR4YIhnhkiAB4soKYm81oNGtnYV/omZhQGql+7dd+jXlPPMVajlqJmZo6MkWZXgtxUMdhUzLhFnWZ+NToVa96FRZ1ZEMGCkJmJIGJ8VNThCf8N37jNwATZEAeAMmQ+WUAi6jwNzGRjfy5RU7goiCgIPCXf/mXiYxVnIlm9kIZtCY3xvXpyjC5mkyYLoeGzXsECroUGNVZXQa2ZOjOEehpBPhf584RuJoQoAWnOjTfrJ01jYpGn/+EUIW18sxDJgJaGg06cWDKrPpEg5ayWziDidDYTglH1YMGmLvEU7S9v//7vydz5gxbZNN08WPaZV0NSdjcg6cwGToc4RCt6eLERHUjQ0ZDLdDCTW8jJiRkeaJk//Zv/zb5QC0wGcuIMUpDfjylN4DWi5maGsHxrDmGC+FaHkGQrLJFVEK4BQ24EKXZ1g4RggBc0VNJC0sxIG0CZOV++tOffsELXmAj5Vy/5mu+5o/+6I9IQgQ0USwH8D23sCZXHLVADaWmECfMhwLNAmU6LlaQSQXO5AOt4lgT9aIXvYhekaWlFsxkJhPNTMzXTMNm4hW9JQthnheLo0hFH4XSmf5NN8ge0Q9gBTYLhakI3QhoGFWbmVn2NMvTbv3qCPQaArKpOm2BO0fg6kAALsHRUqMyWo34hUNg0BsEDI3BIjTWxOEWCiEaHlgKPy04pIWfCKQ1trb/sVALIZAfyUmC4xYKMZaioSfE+MbSMpZptA1hMMKKjkh8IqDdkuGjHvUoCnrTm96EEknOmTCIRzRuiWNFcNvtkM0EMNlME8V4bmouMQkhw6z0LNyKzrIiH1O4DRxLRRyAspyzmN0JgQgJGbqGMiF14LIQqk9CysIGYHVhDjY2fCztPCIrrjzCXMwVZ8URTuZWTYM3K5QI9IqAjoTIyVMTgyu3CA+MxKFQnFWBtIRTOo8sH255uiHnrAj3OAK9gICPAffCW3AZdgwB2BQKpFlHEbTWn1YYnmDEkUBIwggSD605dEJ8/DTr0Am6F7oylltIyHiIVp5oNPEmH7fwB6283cK+5ic56hpNP2VBMzw19kVLJhxllGg4KIFHTMtipi5Th1CgiU+I5Y8k+InGFdogED90i7OElE44EiKbhZPcrLJGUSSkpjhKJ7LFp3Y2zs1TUpklmZyJZsXRNTGWQn5y5hFV5kpCImd8ZmCSBPYlHLjwm2AAS87WeyAtej9IssCaCDzCARp+XoF5KI6ERpz47RageGWEUzQhsC9J8FNHijYxgAhHHBxx7BFdAWIiLZF5Efhx5ieO3frVEehNBFwD7s334lJdJgIwAa0wjb6lp6W2RplwArlCYNb0E8E8MBDcwC2ttileUBd+o2rimB5m+cA9NrZKHHIjDk+JY5HZAoJ5W7a5ByORr33ta9mSAhsv+ZMhQ7bsofEv//Iv6L6YeTHSEgij2NX4MpMtE88qwpW6QDlGKvAc1TE/IkFs5JPFJENkM47MAk1nzW7xQFpcratBhkZyGWIWE6ngRR4ZpIyUQ/kkxCzM2C21piCW6mKy/sqv/EpM39jVMcLziIFk9GAywVxvAwFUjYRcQZIrGVIdImBOh2675TcQDF4igDBiEAGP4UwgAnPN+gf4ux21IAKpNoDQHcf9jsDeI8Bv3Z0jcDUhQMtrw59UCj9uQ+2gIvS/LA5PuaW5xwN1cYXSNiThlnygZ6Pb7rQ2dmuloGuyMpUVSvAElmGODTDtEyaAEhg/5j88ZmemDhFCnlYoj84vjkcwH/IQk0JNsO5okBkRCIHXLRwmMzGM56gFzgS2CFYcA6gbysVkbREohfhkgrNCTU57SrbcbpCEWwRg1y36E9QOwmME18ZokccSbnpFBnKD0e0pft6LCWYhAEsFgdpksIqA5wYBiIz2zBWZic/V4lsmfnUEehkB14D3vg/kEuw4AvyXM+2qO2d4DkJiEhBNOeoX7TgaJO212U5hFwJpu/FYCBF4Sg6oWd36GSHE4anpjuhzmSaH5kcphBhbkBtMDG1DxohEKvIx/c+SEEImJq1dkRAxCCRat/CZH45B7EwRhJ+ITJIsQuaxzLmFX6m1qcvZU2QjLVWjIBwCE9KtUJKcJBsqTnJTgqk+j6DezFbMbVYi0WBf0IBQwdDs5AQSgWp2l2LyUDTsa6YFQkiVVZBHJjnIYL1AVItguJGhvSzLJ8uNVOdL3h3H/Y5ALyDgBNwLb8Fl2DEEIBWaacsOLsw83e2+UR2PrKG3aLTsGQXCBFkcy4GGHorCD/FkdEIcQqBSY6MsCVRB62/jnURAaUPrtbRodXAh/sxZWm6NuS2crLjlioN+cPATvAXrdHcsUNyNfiA5YkJaEA8ZkomQqnJVFocciKBZJuSTkSVpM0akUMufaJacrIhgPMcjAukBUDW7mrSWg8lvlIwM5JB1C7oJ1ZIgJ/GBlKzooAA4dSQQB3RWd2NQg51wqzvZkgOl21umUjamgAwZExPHQCDPrBZWrl8dgZ5CwAm4p16HC7MzCBgZkBcNN62wZWrNOi2yNPO67pZH8BMtO4FGhHY1nZX4OB7husUiEEah3TcOszgZjWWEB0lAIRQE7REIK2SUnBVKtmQCUcFtMA0eBCAJCU1s/DzCdQtAIM74iXCKJjJpKSJjJsJtbJtAS56xIKRlI6Mmv9EVOWyoJjlQCvKAj5VO5vgp10S1q9UXEIhjOdD/IH8ypDNEeKbXWiZcERhprYJZIB4yJPPuytrr6K4CqZAhQ3tDBIozZLoz6S7C/Y5ATyFwlROwNFRdTZX9T7YGiP+6tB02+4Y45zcHPfWeXBhHwBFwBByBiyOwoad78ci98HRfEDDkioN96TgzHkZHm145hkQ67FAvigJPrQvfC6/EZXAEHAFHwBHoRoDW20w+NNT4abF5ip/5d+zmhk6FeYY5B5akjxSqq5yAeVW8DOxROAxuWOGYDsNOfmwmwKPsBWMb5Gl26x5HwBFwBByB3kGAZhx9iWYcyyVSmUIFAbPknaO+2TPVRLUBkd4R+5KSrK0dvGTU/ooAvyrtpheENzJmdIqtZdkskCkbOF4Yw1GM+VmXqr/q6NI6Ao6AI7AfEMiUWjzUl+YaD7bMY8eO2Tx8A4HGHE82RaD3kblqNeDshWXvgLeFmQIN2OZ6oA3zFuFn3hk9qfNnoGQJ3eMIOAKOgCPQawhgtmTHU1YZ0NrTtmfT/fqIgPfRVm3QrbEsBIwdg1ub0smvChrutd+Wy+MIOAKOgCNgCGQjhqYBE4jWREvOGDAr3xgeNva1tj1bVtf76F21BAy/bnhz3EK0rAlB5eV1mrGCEN5ZFrn3X5hL6Ag4Ao7AfkMg05EyjyEA7zKSiN/GhmnVM4buC4iuWgLO0O/uOvFusDxjoKDHlIVnMd3TTwisTaHrJ6ldVkfAEdgpBGjDWXSO8ZkMadKNg+26U0Xsdj5XMwFjowA+tFvrE5niSwi3ONN68ZgqvNtAe/6XhwA8K1RrdJveMAuj80lDJELmvbyCPJUj4Aj0MgLWnqMB02gjpy0ixYNR0x7BwTzKtrvp5bpksl21s6CzGrrnakPAyJhaZZ6rrYZeH0fAEdgXCDgB74vX3L+VTGfHXXKSXBhcMkr/guCSOwKOwFWJwNVsgr4qX5hXyhFwBBwBR+DqQMA14KvjPV69tcDOHMZB0t1T7PZrxbvjuCJ89f4WvGaOwFWGwHlt2VVWP69OXyMgo7ywr16hYXNQbPZJQ+yRzsySyO4cAUfAEegDBFwD7oOXtH9FFN3XyLXTUwzXTb2SDVSMcY2kQUo04E7k/Quc19wRcAT6AAFvqvrgJe17EWFXtUIr+0LILC/jg0doVziYn3F6t++xcgAcAUegbxDYMwK2lVvghIe9qAwwW1LN+YB2a0uq2Tcjg5ONxywJV05Q4JqltcgcrsBSMAskxEphyS9Ltgn0zTdArN9cwiY3yFyr15qtlHqXaolxcK0lHNxo6klWEk0Y2Z0j4Ag4An2BwJ4RcLZfCeupcWxQZWuooczh4WF22YZ3LQ7h5oGex8fHicDtysoKxyoAMdtonDlzBo9tbsUuoNm+kvjJmUdkRSbE5Cgkbt31GQIYmsOgVC6H+YCe2ic/c+e/v+FN5+brzSQgRFVhfH1WJxfXEXAEHIE9I2DYEZZlH23eAZT5rne961u+5VvgV3j07/7u7yBLIrDFCU9RiAl83vOeNzg4+Ad/8AdwKpuh4Cf8iU98Io8e+chHPutZz4KebZtQuJzkxtP2gjl0wZh4ZmbGX3mfISBmZ/TayCzPy7Xggx+/5U1ve+cXTpysxmJ3hoBbfDHuG/la4D57ty6uI7DPEdgzAoY+4UU7yhHDMqz5Dd/wDX/1V3/F+0C1hUoxFy8vL3M9dOjQv/zLv8DQ97vf/YiGvktCoj3pSU+68847P/KRj/zRH/3R29/+9h/+4R/GyAyXW1rjaXu7Rsw8RQ/e5++7H6vPb4DuFG9O7Mv5YG5hZWGlemZ61tiXwMRmXXH8hm4+2o91dJkdAUdgHyKwZ7Og0VyBm4YVykTxhU2npqY42gKyRPGFnjFEm8X4c5/73Hd913e9//3vf/rTn47lmQMgSfjWt771fe9736233nr06NGHPOQhf/EXf/GN3/iNL3nJS2BrlGPLGcY1xZdSCEEttrT43fUNAkkYRDk+vEI+hXxQD8Ly8MRyPQ5yqQYccrSGnHQVJXEcypiDO0fAEXAE+gCBPdOA7QwplBs41XA6ePAgZmdCUIhhX6ZTEc7TF7zgBfDrwx/+cKgajZkBXfRgZmBBrmRCNEIe//jHo93+z//8D+xrxmeemgWbTPCTllRnz57tg3fiInYjIPybC0L5oaLy8llZbbSCsN6GmWVIGFbO5W2NcJRghXbnCDgCjkCfILBnGjBEi86CHszhFVCmsSZXtF4zFMOXEOerXvWqu+66iyFeHkHMaLHYn0l4xx13QNgHDhwAZ8aSuR4/fvy2227DwwFVo6OjBJqlmrFhSBrdmrQU2ifvxcXsRiDitUG9dl2q1hrNVq3eFLMGOrEuRGolLEVKhKrdOQKOgCPQJwjsmQYMiWIiBiV0U4gWBxOj+KLyormi1GKXvuWWW37v934PUzOBRIBQYWUScgutwrIMEuMnHLo1gzNcS0LyNPxRlF/2spfd5z73IQ4Oe3WfvBcX0xDgPcqnu99UDYr1wvBqvQbZMhfAupCNFt02ONqdI+AIOAJ9g8CeETAIoZLCl6i2+OFXrvAr3AmbYovm9r/+67/OnTuHToymy+Du3Xff/cIXvhA2RW9mNJcBYB7B1lAv5MoQ8jXXXGOWbQthtRKM/ku/9Evo0FA1CvSJEyfI1l0/IRCLVVlIuB0wts+vZC4ZWC0fwKzBT6QYB1yJUSxIHy6Iu5m6n2rpsjoCjsA+RGDPTNBwJARsfAnvYhzmFjaFj1FlCOH2+c9//tOe9jR4FO5E033Ri1500003fe/3fi/0zKAv4czM+pIv+RJSvf71ryeHL/3SL2Wh0eTkpM3wgstxtMt23Ydv96qpMgScC1qwbxTkq0mxrmdyc5uLm7koF+siJZ0kfdXU2CviCDgCVz8Ce0bA8CLqLwQMcZrN+QMf+ABMibLLFGiMz4zp4sxofN/73pdXcfvtt3/7t387i5Hws1TpYQ972P/3//1/f//3f3/y5Mmf/dmfffKTn4wGzCMyxEzNFS7HY87epBGz+f3aHwiI+VnmWPFSdRQ4UFtz0mg1CcxLoDtHwBFwBPoSgT0zQWdaKTTJiO+b3/zm7/u+72NLjenp6ec85zlf8RVf8dKXvpQRXAaGcRm0THImIUkYAEb9hZhJwgLiRzziEf/2b/+2sLAAqcO4WXxoGIeuTKtNKpuulT11Tx8hEHYWGDHUy6fZkJELfgzrqtD16teF+40j4Ag4Ar2HwJ5pwEABI3LFFo0ezDpglvNef/31BpEZqDO4GMFluJfxYByBaM82yfnP//zPYWIoFtLFTM30K54yPwvztTnLwazQcHA3N2eZu6fXERAdmHW+Iia/mCZdqSSuNloy3qvLk/iWM5PW+l0S050j4Ag4Aj2OwHoF4goKm1GsDQNTMlZlKx9ChT7xs6DISBr2hVYJMYplA0vi4GBfo1WLBk8zeIzGDOMSmUeWofFupnNboF/7AwFoVhePGb3yRlvtBLqt6xR6HhLCdc9+x/0BokvpCDgCvYjAnmnARrFwJPZhqBEHE+NnmNYMxcy0YvEumFkgtIqHVDy1DSwxOJOKHKBhW31EZJ5Cw2a1hpWhXhxxiMlTOLsXX4LLdFEE9K0J/7LlJBowOz+j/Mq6o/NT8X5dDz4fFg9xBByBnkRgzzQHNGDRYZOEFUSwIzSJhysMCvXijIYBzXRfxoltCpVdIVd4l1VGpgTDuPAukckEdZls8ROTDPEY++KxcDzu+gMB7S/Jr6QjLj4GHGBi9GDTfXmSPe3E8m9HwBFwBPoAgT0jYHRZ2NFsxUbAoMUtDGqwZR7Tg6FkCzc2tYRZCIHwrt1y3WCCzsLd048IsBV0R62NmHrFWt8wV1iprsoMAmVfCDhnP+TOwdL9WE2X2RFwBPYbAntGwPsNaK/v5SAg64/E0szPFJa1m1h04JCtoCHgTPdVj8R05wg4Ao5AvyDgBNwvb2r/yplZoIWD20yElinRjAC3O6zb0Y8h6oyR9y9cXnNHwBHoFwScgPvlTe1fOUMZ7RXHADAzsGSntDBqxwl+e7BGwAz5OwUbWH51BByBnkfACbjnX5EL2JmDhfGZpeOsAg7Zg1J2VpFlwebSKL4RRwcQ/3YEHIHeR8AJuPff0X6XcM0EHYecQSjLj6IcK5HaLbFCr9N4nYD3+4/F6+8I9BMCTsD99Lb2raym4MLEaL1cmT+PBiwm6M68K43A9Og1a/S+xcor7gg4Av2CgBNwv7yp/Son1MrOV6EM97Yjztjg5KNmLmk1g3yDUeFYDiiEddeId823XxHzejsCjkCfIOAE3Ccvan+KCcHGrTAv+7W1dOPnufnF8cFc0KwGxaHTC0GpwLCwHlMoPG1LlvYnUl5rR8AR6D8EnID7753tL4nhYFkNLPQqC3+TJIKSg7gZFmuMB8sS4WTtR9w5m2F/QeS1dQQcgf5EYK3t6k/5XeqrHYGuYV1RcdUxBoxrNJgODQMLP3Mrq5TcOQKOgCPQPwg4AffPu9q3knZUXFGC27oMWFl5tV4DEqFeWFh+yJFPwtq3vxGvuCPQjwg4AffjW9tPMkfCr6bbbiBgjsDiEdtitcVE7c4RcAQcgT5DwAm4z17Y/hMXvTbddRIbc6PNMYSxGKDDHGc/GzHHseyVxTYdAk5HXd5/QHmNHQFHoM8QcALusxe2b8UVik1k4a/Nd2b4lxMqQSPmkOBsOfC+Rccr7gg4An2IgBNwH760fSSy/T7X1vYyCzqWjThY/RtwJLAhQaB4RPf137NB4ldHwBHoAwS8weqDl7SvRWTvK5lpFTSToBgF586d4+BndF8M0RwCzTPMz+VSnmHgKJfzidD7+qfilXcE+g0B2eLAnSPQowig+uokLMRDyeWD+stmlHyCMGq12BC644i5pid3Av3bEXAEHIEeRsA14B5+OS4aCOgqI4hWv2UMmNOQDJhGoyG0G0a6Dlj26EgjOW6OgCPgCPQDAk7A/fCW9rOMEK9RrILAOmCINhcVuKvW2Q06dar9rl06wf7tCDgCjkDvIuAE3LvvxiUTBDrLiuyXKmbnJCmXy6xDYh2wWZ1NI5aZWJ3IDp0j4Ag4Ar2PgBNw778jlzAd3sXU3Gg1wygaGBrkfKSudcCyKXRqmHa0HAFHwBHoEwScgPvkRe1vMU3TBYNWk8nP+cHBQfyddcDpNh37GyGvvSPgCPQfAj4Luv/emUqMyqcWV84g0HulKHapkEU7zEVKgnxTwxkszdhLA/rtopOv6CfyYci3EQf5oD1YlHXATd2CUrqQHJFELX0SVr+9W5fXEdjnCLgG3Gc/gNTQyt6Lsv2isC9Ey6cONcG+zeUgXgmSerVRZ6PkZT3CTzZplJP8Oh8hrE42ursUG0xlnx6DQ5g3abaKSbuo1VxsxIWkeXikFCXBwiL1k+5FKScbc+Ry/d3T6DHkXRxHwBHYdQScgHcd4l0pAAZdI1Hh1iK7VAjFtvQT54slCJhD7HUbiy0uz4HRVbHeFYkvO9OI+VZB0oRiddsNzj1ql/Pyu213dPvIxE47FZddkCd0BBwBR+CKIuAEfEXh3r3ChDkhqlyeRTvwEben5pR9syLhJ1RE1RKF0tR1ArJIPekRAk7Z1ZYhVSoVBGUzLBM3rU4nTk/WwYVyBBwBR2AjAk7AGxHp03s5paAVB2EhCPPNOIdR+q3//f63vPe2lLiUcPuVofSwX3svtgyJ3Si5hYx1xLtP35iL7Qg4AvsdASfgq+EXIMotFmgdCQ2CQj3OnZprvfHt73nt616fUhQErK96Uw42PbhHteH1EhsBDw8P89rgX7ocOLbq4JoNbEuQO0fAEXAEeh4BJ+Cef0WbCiiMg0ttsHaTQMIoi2EuVy4t1lvztfbU/EpDj/CzCB3Ds931x3UDrULAWJ6HhkqEiwbsKnB/vEaX0hFwBDZBwJchbQJK3wSx+TGypmTMsQX4ogarc4rBSjMpj04UkrjRlpHgTpRuX3/UEqIVBbejBxvl6hCwjAF3RoGlLhqzPyrlUjoCjoAjAAJOwP30M8DUjM6L1UKNrt3Du8pQPEhC+BfGPTe3XG1GjZiNK2xKVr+aOlQDXus/QLmEFGQraGHcDi/300t0WR0BR8ARMAT6tV329ycIhGKCtleI9tti1VGQlCsDbFix2mjFhVIcFWbn6vminJvbZK2vkBaX8xyB9jnvyZ4HcOivCJ3LISA1XV6Wtb/lMp8yj+bm5LbVlprLecDuHAFHwBHoHwScgPvnXamk8NC6gV8NRENUJVGeEAGH5ZnNsCAu4901FVKfXlBz7FUaVqnlYpJDyrAv/nU26CySexwBR8AR6AcEnID74S1tIqO+OCVbyJUb+bABZWe0l4MK2mHYDiMOzTVWZSgVfuYMA02kOaYPelf9RcpsybJhYIyLrltQMzRzss6PYzH96gg4Ao5AjyPgBNzjL2ijeJCoMGim0iYxr5A7yFcJWP2YaldXwzCHjlir1y0LYzIzQUPGXTy8sYhevrdJWJBvsVikdusIeHPzei/XxmVzBByBfY2AE3A/vX5jXzE0p065GOrllhnRQqtyIi7fqzpWKgRcq4mSuBW3phpvJfaVikOtOsxKxY1xIeBSqYQ23GzKkRNRyM7Q1LU3K3ClgPJyHAFHoN8QcALutzeW6q5y/I9qsULHYnuGfoSB2BBL9NvV1VUbLObMvnb7KmEmqpFqwGGqAUPAVNteoRNw//2UXWJHYH8j4ATcZ++/i0vhWXUWJIuPYF8GecUoXa+umlbIGDCaIizdiX2B+nble4EYex9MLdIxYLb76owBZ7ybefZeUJfAEXAEHIEtIODrgLcAUs9EgVntoxKpEpzqwQRAwEwODlqhbARd504145asm9XomhYjbkgkgmTfSvRm7YEJOUPemT+N3xNfWKBtq0nV6JncXYhbZY4gjOIwbjeSXDOUraKlt9ET4roQjoAj4AhsFQFtc7ca2ePtMQIQJcfipp0mBj5ZisP2k0afnNDH7oxJiTlXfE5NLaAj5qNoZnqxVJSTckmFcpzDWp20wtAOAA7aSm+SQ5rPHldwQ/FwaqNJFfOm+S7Wg2KJXbDqQ0FwYCAsF6Kzi3XrbTDFLCcIyOord46AI+AI9AUCTsB98ZoyIcXILB9VeMUki88IGG02FEJlyhWfJjpuDCuxMZYqwEZLaVqeqzVXB5HxdTirF38MSSgD3Kady3hvEhaidsk04CSGndl1RMwCqRM83DkCjoAj0BcIrDVdfSGuC3kRBIRvhYzFMVnJhkubbE2p3CzUZGquRupE1Ng9fElrpF+66DfI58UEgH6Pbb2zDEkrIHb1fqlWDyPuojkCjsCVQsAJ+EohfUXKMf4RJVhPDaLMaq3GNdVxRRnmja+99N7nq24CZs0RpAsBI7atA2YWNB2LtBaq6l8RmL0QR8ARcAR2AIG1tngHMvMs9hYBJSs4NiNgNOJard5K6VfYSwSUy2bvHR7rPUKmThmxNhpSBZv/nBEwtek9qff2d+ClOwKOQH8gsFlD3B+Su5SbIwAhYXRe04AbQsAE2qc7zbp3LyTWiwOo3QScacDIykYcZoJeEzoj6u5Kut8RcAQcgV5FYF0j3KtCulzbQEAImDOA2X0DF+bqjRYEDEvxkS06ZJcOe+l98+qph9WfmuBsDJgrfvoZ6TOpXebdBlwe1RFwBByBvUKgb1rhvQKoH8uFiZiBZYTUiGUjLKhJP7ZmKa1TRsVr93q+Ya9VOWNWq5TNNMvp4YMa0mvyujyOgCPgCGwJASfgLcHUL5EwPrO/xt1310ZGRtARG63m6bPnSiyjZUFti0N1Q13BZHpwf9QJs3OeBb5tFlgF7GtNpTA+I/rQ0BCec+fOlcR4Lib3kNnR6P7uHAFHwBHoEwScgPvkRW1HTDHMJgnTlDg0l60pISXTgKHhtYVKF7LX9qQSbLW3hVVUittMA14HTDpnel2Y3zgCjoAj0JsIOAH35nu5R1JxAAMEjI4oXJVERsCiGovLpVtO2l1nQNi25uiE9dB3N6XaSQxGvdk64At1JHqoDi6KI+AIOAKbIeAEvBkqfRtmdFWtVlEWR0dH87liHITVps5vZiNKqxdDxLLtM9ysxyhpYM/SmKq7orkjJpo9184ypJBOhq0DtmrJtZuu10Ld5wg4Ao5ALyLgBNyLb+UeysRZhJDT+Ph4mM8xF2ulJiZo3nR6KJJMhO4b102pRsA2C5qBYCPgdV2H7th9U0UX1BFwBPYpAk7AV8uL10U4RkBrGnA+zxjwalWmXkFULVOBbbnOOuLqXRCokfYbUg2YMeyOBiwEDCWnaj01sHr1blVcMkfAEXAE1iHgBLwOjqvjJhsDZrgUVqo2ODFInDAZrt+ICqJVuVMTtI0BM+XZCLjzsP/qZZXyqyPgCOxbBJyA++7VM6qr+mx6yb5SVZCvlbjQDAoDhaQU1JMg32QBkp1jGLOXo5yYJLs3mh268702Gav38BAC5uxF2WIzRPh8wPGEQSWkUs0mU8xYVJXKrAj08Czu3oPWJXIEHIG9RMAJeC/Rv5yylTizYdyImVXwTxxxJD1zq+K2bAR9aiVqFoaHkuqxStiO87VGPt8OSkmrUmwHcTUo5OtRmEBUYYuzgXX+swrCzKwOlV2OYLuTpt5CemqZr8fBYrteD5pjlcGBIDg2GISN5aVas0qXQrRfCJneRO9VYHdg8VwdAUfgKkDACbivXyIjoNkR9BiYmXElHLrcjhpRfrgYjBag66jeTkR/TOocEwzdQleoiqotolnanYJgBCwTpHvHcaax7h2CRKEcciwacCgacIFPxPYcOQ4Jpi6d9c1ard4R3yVxBBwBR+DCCPRUa3thMf3JZghsYBvI1wiYHaMg3sHKwODgIOkYEpbJWcasa/OEz3v1xOHTY67DrCJW9zpgbm02Fltl4SQalXfnCDgCjkD/IHBeK9w/orukKQIpa8qr1A2Sg0a9FiVxZaBcKuaTIKrWa2Ky5gMHKwF38ayk2kDkPQVsNwF3rwOmCkbAWKVxRMvmavWU/C6MI+AIOAIXQsAJ+ELI9Gw4et6FGFN2voKZUHmRvlxMKWpltZaqtmyV3MW93TW8UI7dcfbEL8zaGZpm2w1ksHXA1MM2hTYCTvfr2BMRvVBHwBFwBC4LASfgy4JtrxN1TTYyRl17j/Bzo1YNkvZgJRANmHXA9Ybwa8hUJmZsrcU8rxLKwj02i1gmVnVsy2jA8DGKLwFUm82uqUJDZnaLy6LpnV8cAUfAEeh1BC7SHPe66C7f2tohXYoDu0JLHIjUqK0yoXm4EgwPDLARR42toY2m04XAgtwmL97i9BisELCdwYBc3WPACGuqMFqxj/322EtzcRwBR2BLCGzSDm8pnUfqDQS6uIeZznLHfsmYaqOwXS4F5YroiM2UwaJYeFgmRKeO27WbTmAPf3efhoSYtiOHsTK3rgH38Ktz0RwBR2ATBPaMgG1CDU0qU3aRC08DYyJsoeN8+M0zPT1tUhOStbBstUjg0tKSPSItbnl52W65Zo1yFnIVeTAUn0ebqrzm9MCj2iorjZrFPIf/BkzDCqPc4tKKVL8dR5UK/GyKrl0l/LzMJLBnXDtp53NyoDHVWVxc5DdQqVRkynMQDAwMwMErKyv8iJvNdo7NsXq8Mj2DqgviCDgCvYDAnhGwzW5l1lC5XDZytSG9zk6/RTMwHjhwAJhoeXlKEpiVGUY0wYTQ/vJoYWGBTDh+gNP3uCUrmNgy7wV8d1uG2GzJovxCSbLet92UEwdLhRxrgA3MVlsGUZMoJ8PAG2Zhddg3/V6j5d0WfJv5q2B0s0gmM83Umcc6W/vnjW8TOI/uCDgCvYvAnhEwjSmsaWou5GrmRNNiTSemSc2UWrgWZjX2Ze4rqaBbksC+w8PDoAslz83NEZ9sjYl7F/LdkSxOYjgYpq3X0XGTcrGIPjhQLsphDE02pJSVOlKyXXdHht3ItZtZjWt57zYrK+1e6BmF3dF2QwzP0xFwBByBHUeAVnpvHAquNaBWPIZEPJkWC5MQgVuszZCracNEMJ4mIRowV468JZDIFm7J4XUeZXqS5X+1XHWicmcZEmt8s0N+w5D9noWGGpj04wTq5dWWigXGeVeqQsASgU2llICFilOdtxsYy7w7ZO/97LEpQmjnYdN1wGI+EbVYY+y9vC6BI+AIOAJbRWDPNGBTWWZmZkyt+cAHPvCUpzzl2muvRcF997vfDelColibf+InfuLRj340OzodPHjwGc94BnxMg0vliHbnnXc+73nPGxkZgWuf/exnc/wtCjERUJdJu1UAro54wj68SjlaoVpdwQ5dKZUJMxxWWZWUEe4lNOBNaHnPEUK5NxmMgOmNmQZsYxb8SLR7IVHEAuDOEXAEHIE+QWDPCBiyBKLJyUkaTVgTd9NNN7385S+Hj1FheYoxGa49ffr0k570pFtvvfWf//mfz50794QnPMEGAiHgX/7lX37b29723ve+941vfOOHPvQh+BuFGObeV60wSvCGXxoGfBBg/jMEXCrITlir1VrKSyxR2kDA/UBY9sapZrcGzK0RMOMRaSWcfTf8FPzWEXAEehuBPTNBm/UYcFBocI973OO+7uu+jglZ3/3d33399dfzFPZlfPdf//VfMS9DyY961KNe9rKXffmXf/ldd9113XXX3X777a95zWtuvvnm+9znPg960INomp/4xCfefffdELCR+lU7KHgBytRJWKIIoxGyD2W5WIKZ6aYQYjYDtEhW1Ea5jYTd279PkS7rUdE547VmY8D8bHhq0wjSaAKAO0fAEXAE+gOBvWyOszlWLCiCKmBfiJYWFq2XR+g3MAetLQoQVmXszGjAtLnHjh0j8vve977Dhw8/7GEPw8pKE/zN3/zNJPzoRz8K+wK8qUr98Qa2JyVbTfJhuNcszrrwSHOQkwiDHCu6VjlAKIgH8jJsym6U+EED9uWxMhknF8oj3ZrDBlgTGT2WTOzJXv4ktCprF6TKcdQiVZNjF2UhVZDkdLBbKl7gUMWo0EhyTD/DEblrg7C1TNznCDgCjkBvIrBnra3NZAYUplPZTGZ414gWwmA6FdOyzMYI9aLVQcMvfvGLn/a0pzEeTAQ4G2UX0sXiCgdD1QwSowFjyiZPQohvM7MImZ+fJwc8s7OzvfkatigV9uRWUGhzJn3YCpMWA91CxUqehbDAkiRmsp1crLEIeGJQTNAHR1m5VW+3WotJwMh5rlRsrC6QBEaDj9vC5Zo4acFzZC4595hj5VmxIL0JDi5eWYrb9Wh4NGTGFTuMHBwbWW1GU9rjWK3WN1lk1WN1cXEcAUfAEehGYM8IGI5EIYOGoUmzIsKghMCpkCXGRogWD7LCxMT5ju/4DvTjP/3TPyUyejAmaFN2iQb7QtVkSCpYmfVIsK/Ngj516tTv/M7vPOABD0C9ht3vfe97d1e+7/xogabLosEKgeqWyFqLdJNnWLbKOG8SlHOsPxKVNs8GFpgElHHxhBGqL+uUZEWt6o16eoMcKkyAuAtYuO3hXlwRTH4WQsCi/oY56zaIBsxyqyjf0Krxs0lF77kK7AVoXqYj4Aj0AwJ7RsCAA19yhUHhTjzQKs0o2i22ZRgXhRVTM7OxuD7zmc/88Ic//KlPfYqxYYv88Ic//OMf/zjxUYXVshqcPHnS+JV50RCwkTf26p/5mZ/55Cc/iU0bXfnMmTP98FIuS0adggT7WMUBTZRjNQaAks4cl1vrlxAiN33lpMeg/TN6FEjPp8AOWZ3hhn6sUV/B78I6Ao7AziOwlwQM4xqbQo0QJKotjiqaoRgKgUu4/sAP/MAnPvEJ5lsRGTM1gURjxhZUDSWj8hLnzW9+M9Ry//vf39RlcjbzNbnhGRsbg+aJZlS98yheqRztbW3yzoRPRfXjz4zwqPsmVKUo87B0u08JMLN8P9GVka2q/mrYCGRHLyXgYgkCTncwtY6F1FCgcOcIOAKOQB8gsGdjfjSmMCjsiGEZtsAPxaK8spyXec7ou0eOHDl06BArfV/72te+853vJAIxeUpCqPTo0aNMnH7605/+d3/3dwz9/tAP/dD3fM/3XHPNNZA0DE22qNfQMG8A0iWt+W1jyz54LdsS0SinswgHlEhNh8PywPYeLjP+LVO0JCQn18xea3F6+irnJ0oNWULFq4RotQYisvWxbI53wOxuLO/tUMzu7hwBR8AR6AcE9oyAbYYzEMG+NKys5X3uc5+LgkvIT/7kTzIJ6/GPf/xLXvKSv/zLv4Q70XeJY7tlffCDH7zxxhuxRbMMiZhMhGZV0k033fQnf/InsC/0TEw0PFKpwhThh4TIFho+ceJEP7yUS8godHTeSCejuIRhpzUCBlWi8aGzQnRsDJCy5KvGZ8mhrxzdB4axebM5GFiHramCEXC9KRuzyE5Y52HSV1V0YR0BR2DfIbBnBAwpwsFYnqFJFF9W8X72s5+16dCM+8Kv9ipgTaymZlg2HrVwFFxa4v+tjpFd1GXCaaC5Eg0bNamkqVaHVZZAKPmGG26wkP69blDwjHQyQuXWxoCxyxPIh04JXRBVE1OduM/qrj0GXizTxni/9KdQ4akXOBRysv+kDVvgkbAwnUrWZ3V0cR0BR2BfIrChPb9yGNBu0p6i6cK+eLLFSPiNfe20QYgW9sWgCoMatSAi+hz8asOc5GPsC1XDNMSB0YkD+5LWFGLS8ohAy/PKVfJKlQTviuKvGnCjzQolmdFmr9YGfYFiTRbtpqzd9oEvQmT9iG0DAu6uWsJL7oMquIiOgCPgCGxEYM80YDSzTBZaVWjYbo0p8Zs2jJnRLI2EmDUVD4TK1cKzfKAcApmTxTXTfc0DDVu2WebE6VNnyl+38NCPqIOFwiprhPOyrrrZbB06FLA+h+FSgKVrQs+jnRwQzZGzg/IF2blCdcbufHrTn/DudPB6cbHNrKskiXnNiYwntA5OTrSbzcWlearSZhVzEocdm0dv1sWlcgQcAUegG4E904C7hXD/ZSLQOQsJDoZSmWUlSjAKYcRqWTnBXsJ0zhJ0lRZhY8B9wr6s8xWNV+ZhpeMLsgpYHV2rrHdFAMZoaixdEY1scfzqCDgCjkAvI+AE3MtvZ6Ns8CYvDAvzphOOYFxWccG1kC4GaOYFE9HMBowBK/OSWLi3X/gXQaFgrkiNFR0rO3YOAQE9uNPDkHDDSWP2T902vly/dwQcgf2GgBNw379xo+MWeyYzOt4QosI4nw2Uci4hNWQaWkq6UFlfjQEzapBWsNWCgHXtL3zMbpQRYw54qC/avdkAsFf3/ev0CjgCjsC+QcAJ+Cp51ZATRMUaYEzQA+VK9l5tULybgNfM0f1R9Zx1GBCbqpXyBapGJ4JPMc9EaCXgzgwzRoH7o04upSPgCDgCatF0GPoYAbO+it6ntuWVlSZKoS0CJgyuMgJm3nhGTaiM/VVhJrMjcIsTJOIkm5FHSD4nk71hZfZPMxyoe39VzaV1BByB/YxApintZxD6qe5ikN3McbIgllh24WBqErPEiWWH9BljZSu4SCqztPrI2cERunO4jQEju+4GLSc3QcAEQsBpp8JnQffRm3VRHYF9j4ATcJ/9BOQcX/nwJ5OsGOvFl5NZwDIOuoKWGOUH8jIebExdzMW5pGlar542mI8TmUnMhyTiyFEOGLKb3rvKCmA5qqnFIiOOQ9IfLKdAMdUbWTnrKUxYCaxnJWU16r1KuESOgCPgCJyPgLZn5wd7SE8iIHotuiAX4VBZdYRCnNNPxPnHQXB6iQNzS4dGomEeM3M4CCaGigNh69z0FPrxCpslB4XBweGYjbIlPQ7qFS/LaMmbY+97jIjjoM2BHDmEn1tcHSgUBgt5KhUH+VjF50jLUi5aqgYsVlLF3uZj9eTLc6EcAUfAEViPgBPwejx6/Q67sn14cfru4GT9mGm62g5bYb6ca7PLCY95wqmEuaDJ+Cm8xVEFXAlMJxZrZbltBxG8jq1X1xXj7SmHgCI2nQ504QJnIaU1FiELshY4bnZOO9YnEu7OEXAEHIHeR8AJuPff0RYktGnBnY2gsy3DeLulUpH0tmHyFjLqvSii64vDip6NAVsIVxvhbjRY/2yuxxT4jlj+7Qg4Ao7A+Qg4AZ+PSZ+EbMY16VFIlYqal6UiumtnoIcxrI3z9tNsYZ3YTF3bTdYBtwtFrOXirPaVchkber0uc7x9BrQC4xdHwBHoGwScgPvmVZmgwjSbiWycmp1FSBQxNctpjzKJCQJWI7OkZFltfxFwSymXdcBUpFQoYj/PQCiXi9RFD1vsueHrzd6ShzkCjoAjsIaAE/AaFn3kEw42TXC90LLhBucfVypZhLIcBywaMMOo5vpqIyz0W061kqpigmYBldicpW7i+LZjOWyRlQZz8Z+0weNXR8AR6HUEvLXq9Td0CflgHP3AUei41XqN+NkYME+Uf2WDaNbqcNuPrs1RiyxDki/ZC5oq8KvlQ33hYzocDazTm3dI+rG6LrMj4AjsFwScgPvpTcOgxj0bhBb6UXa1bSaNpcJYDgaywWB0x3WKb1+Nl8K71Nf2D+GQCZvvTQg1ZitKPH23t9eG1+e3joAjsD8RcALus/cO4QjnCCWZT6gXXVD3pgjmFxawypZLoveySQXrc1gYe+DAAVbrnDsnM5VaLDnqq3fODtDFUg77OcPbhXwkBz1RjUT6G9SDTTfbrYaNfIsWbEcHKzZ+cQQcAUegxxHoq8a4x7Hca/EgIHRBVhxhmLX3alwLaWGnNTWxr1TfdYB2NGBZlkR1eIYnLzuA6fDwurh+4wg4Ao5AHyDgBNwHL+niIqr6m6rETLaqNeqDg4MkYe4SyiIEVSgUYCxbCtx/BBzKuiPrW2RjwDr+K3td2zpgqkY1qRoh7hwBR8AR6BcEnID75U1dWk7stPVWk2HgoaEihBRjblYrNTZpCJi1OlC1aoyXzqp3YpiyS3U4DYnTBulMZCxLdWQWdMg6YNmIIwvvHeFdEkfAEXAELoKAE/BFwOmDR4yFQjxQEa7OjoztNow1UEklF71QJ0UTyFodXc6jj9bNyEoj9+YXVnRjVjoWtgyJGgWczpDEXISAg8DWARPeP9XqTbBdKkfAEbiiCDgBX1G4d7WwlZU6+WOVtaVHhZys2MGtacBG1EJU/aEuptSrO2/ITlhB22zOVi8qQdUi6VtULWavHSVhcvrVEXAEHIFNEXAC3hSW3g7cjD3h1uXVFeZbCScxAEwc1R3RC7Mx4Owg4H4hYHsNJjbKPWIX8p0DCVGM20GpKMPbttFmb78zl84RcAQcgY0IOAFvRKS37/V9yUTgVJllUSwrfblvBdFKgyMIk8G83LL1BtZnaJhjkQpR0ogKq0mRaUs86mi/WHHXzNeSpPecWJtxnEkolzBiIw4OPyJE5pLl0HdZB0xgS6zR4qLNuib6xC+OgCPgCPQcAr3Z8PYcTD0iEPzCOl6h0ZSaRK4wFsvrKhpwMtCoVo+OFKN2UCkkq7Um21Rgjj42PrCYlD83XasUg3p1FfJiOa1SuOiWPc5ZSbtZLgTY1peqjXIhLIRCtc2E84CjUoFqRu3GKoPfzMIChEif9sjLcjEcAUfAEbg4Ak7AF8en557Cl6btybeRZyKzndlwo9rORXG7nIvzCXzUSlAOGRIWDbjdDEtowERLpzRBVpJWcurkhrcHXWwCIyQavaj76a4jcrYxgboOWM4DTmshmnDq7cHKuEiOgCPgCHQjkM7T6Q5yf58iYJOBbcoVVWA8mCtUy8QlBkptHbAcYN9frrNy2caA2WWTCthiKjxFHwPur7fp0joCjkAXAv3WHHeJ7t4NCNiOjBWOQlLSyqiWsxlsGRLx+5SA6UZAwCxDYkJZVmt0ePbczKqWhbvHEXAEHIG+QMAJuC9e05aEXFlZIR7bYBkBowBDUVBXtgyJp0bA/TULGrGpBeuAEbtYXLPZYGvWZcDpOuAtYeSRHAFHwBHoGQScgHvmVdxjQdCAoSjOJxAC1rU7RsDna8D9Q8ByHrCcsgABN1mGxDpg8cPHmNd1HbBMSKvVZQG0xuKJ/6QFIneOgCPQ+wh4a9X772irEtq59Oi7kkAXGyknpWPALJYVPlbrdP8QsFRl/TpgYV9+tVyZcVVSfdiGtyWqO0fAEXAE+gcBJ+D+eVeXkjQ7DJgjGLop1mZjySSmTg7dTzthvfvN8mWszciMY2Db2BdxmeSNHkyXQoaHUw24d2vhkjkCjoAjsAEBJ+ANgPTrLeS6vLwM1zIJiw02wnx+dbUJP2G/nZwchaIwUPOyIelms81c4n6pJ90Ghn1ZZEXtmIFV0W2uOQMYxZhwak0gbqkWsBjJzwPul9fqcjoCjgAIOAFfPT8Dm6aUkatZm1mxI+cZsF0Ue2OpvmjhfVRttFuUYKqA5Kb+WhXMFt3R74PEf8t99FJdVEfAEXACvpp+A9k6YKuUTXiGlVB3YSwIGAbGk7PdlPul5noesJiY+bFGnLygHoZ/090nZYSboDoqMTPPMiO7xHLnCDgCjkBPI+BaQ0+/nm0JZ+uAZRa0TFFiI4705bJ0FupiplJDjs2Fg0Wb3FbOexUZKY1x222s6kEuitgJSylYKyKcG5TKRXRj5kFTWz8Naa/elJfrCDgCl4GAE/BlgNaLSaAiI+DBwaJRlK0DRlY5j6FQYBi40Uipt18IGOGluyBD1yI53Yh0dxGpofQh+GORFY+q1abVmkB3joAj4Aj0BQJOwH3xmrYkpK0DZpqSUBEnNCh1YbtlKpaxFEowm0ltKa+eiSQDwLINlggE/ZpC3C2dLbuyJViECy27cwQcAUegHxBwAu6Ht7Q1GTtjwBI76WzEYaOnNlDKKHDfETB1acXpUmAh4POgQLlHA2aVc5/1LM6riAc4Ao7AfkPACXiv33iqsjFByj56xpEEyvJXvsVrXwmqrYxydt5ZlM77NSNtEDRaSS5pldPHcmgBh/bF7TYacDEfRmHSaEcc5KcV5nRdzLti0O3k1ov8ZZXlECSWMDPQmwtj6iIunQ0twhepWAhJCxicRng+Q1sKvzoCjoAj0GsIdJrfXpNr/8iTcizzo2ocdCu6HuZW+EbWtco5e0KM/KVfLO21mUYR5/GRhiu0Q4qTq0GhPDxWCEflzOAgzFfqq9VSGIwUZC7WaCUs5pOT07WoXGglcRQlbTmsUM7PzUtZLSY5KRcTt6d+ElS2RQWaSVBrtYfKBWY815qsOCrouchy2GIxSsJCsd6OUZRzEZ2YXuxJ7J+fs9fUEXAEto5AT7W2Wxf7aonZUW2VNphohPpLkDmoF07pdsrDEkfYMvtAwPg5lB71rxKFpuESkkNzDFpyhq5owGiJcb0V6lgqaSWJ+SUj+dOiUCPltqecqLZ64m+UU50ftV2BkNOOqVqeLkkQNVoxE6S1Ij0lvAvjCDgCjsAFEXACviA0V+jBms1UDh5QTklLZtdF5ZotCcI6HIZCmWxFbMuyM2NYklu4zVSyXSy2lGkvRErQ0oWAdQWzWKBtInQ2G4vhbRkDbrXpYshaJXeOgCPgCPQJAk7APfCihDV4EXzyQi98o652m4K3QCurq1IRFgFn9bEtouzWwqvVKrddK2mzuD3s0bo3m+wyiQac546JWKalGypF6XOETECTn/IWgOrhqrpojoAjsL8QkFbL3Z4hAGGscQa+HCocw7otCZQZv/ZQ+Cb1XfB9ra4yhCwEnKViJw4xaCtZEY6aaAuF96yyl1swNeAkJzRg22VTkIjbma2cZUhUzWaAX24Jns4RcAQcgT1A4IIN+h7Isq+L5EVETCxiR0V2lGAqkUx5Tq2tMu1KbasXe1nZNliGYnr0UWdEuVsDJkJKy30AuMCCmKwywkCfL+QgY3CBcTM9viwacIeABaaLodQHNXYRHQFHYN8g4K1Vb7xq0VPztg6Jw+V1y0hZR2R8Aq3oFCmI5oLvy8Z3bayXvKCo7op1jwF3h/eFn+FeVjBnY8Aic4yZIF2Rla0DJnhdnfuibi6kI+AI7GMELtig72NM9qLquoqVaclowHxsMQ3nGJkohKsGfDHB7FD67CiklIA7NGzh0Fg/UhSdj3YsJmhx52FgQ92ttq7XOu+pBzgCjoAj0LMI7BgBr6ysWCXZcxgPCtn8/PyGakMAhG9QzjbE2W+3MGu9VpNlQUke4GZqwR/89RvefvPnFYd0uhGsKZjCxxfmT47LBfnR0VEoim0rCoUcWMswsNpqOSSYPbAw5JJLnKA7nk9kWmDvXViszNRnhnjrjebY2Bi/12ajTe2SuGW/XTTgYqksPy0wCmWatDtHwBFwBPoCgR0j4MHBQSpMQ4lGsrCwgM2T5hJWoNGHGIx00cMIR40xe2lfAHQFhBT1VBYgBbU4+MLJlY/+z+fe9YEPC9V26BYVsOOFkjd/ZTAQKbpnPncvQ8o0YOKAf/+MASOv1L3JIiN1Jn92xWNVJkL/dCqQ2p0j4Ag4Aqx72SG3tLTEfFQca12Gh4e5wrVDQ0NZ9jAxbaU1l7SlWbh7ZAdFdohk76swmF6unluuFs+cUwJm4pGMdOKXMWC++FwAOevTgD8RDd1uAuZdEG5x+kj9zX4bdC/4zeR1K2g9ZVGwAAk+xXyO7h2/Lv9NZXC5xxFwBPoCgc3VqcsQHdKVE2cbDaydNIhcuwmADDEVYgUlDk/tbIDLKOVqTMKxRWJqZocrvhtJlB8ciUqDMIzOfpavLg1YOXgzFGwWNLCvPWRJcWcM2MLpFUm2/eOQ1urOz0YIGFOBqLzrfrTW55B1wDpVrb8q2D+vwiV1BByBnUdgXVt2T7JHR2GtC8w6MzODmssAsG37QNOJBys0DSgcDCsTck8KuvrSRozUMvGqKXOv5lfqtXa4VG0I6zIwLFtGdjRg8V3wfdkYvA0EpEqy8HpqbNblwemBwZph3/CUCdpoqAacZ+Nq2X6SWdCqActDlHu6dNV67QKmAaK4cwQcAUegFxHYMRM0tGoKCqowejADwFSXQEgXh8eMz1xF4XOnCECwcdKSiVJJARaGXVdbcS1JFlaqMuuqM/V5K2wp2q0aHgCXD8PusowJAlaw2SBLWEriXNCI3cvvpN5ssDFJLldIoaB7khPLM0aDYhnrelSrNajoVoDq5Wq6bI6AI7CvELigRrVdFDByoubOzs6iBGMVfO5zn/v2t78d6l1cXMTybBwMMZPtBtP0dgu6yuJnM9SoF/zBXKJ8qSzHFXHDn1LKmglaQjd3thVUucz5QOKEnPRLrqImyrV/577ZGLD14aQmCf0TUBFXLAoTu1nF0PCrI+AI9BECO0bANJG0jxMTEwxGvulNb7rrrru++Zu/+YEPfOA//uM/fv7zsqgGDk5ZgbazfxZtCg9m79NuOvdqIBYbsX264mUJLuFhpW8hXwkjZkEHdTXM1xs1VgnFSY6uSsIgrqh1MaQqlgr8vC7VaC3fjjdPUgzXrNgp5ySmJFICJgQvtwMRZwPHjXaLeV6qW+dS+koFZBqYLeBZH3wJ8Xf9MZJz5hFXjoXi0EE7hkG6IzJpnHOAYypbZKSbsfO+XOG86wB6AY6AI9DLCOwYAVNJOJgrNPzVX/3Vb3jDG+68887v+77ve8UrXvHgBz/4yU9+8mtf+1qbi8sipX5RgmFWTvnjI5xrNCvNv35kbpQ84ghfU8ckOH20zTfOyG7YLg9KxrX56aDFcbdDd80FTYiXha3N+gDdF9ieXIWSmawVczoQTmZOxxhnC4tBMLXcTKLc0dFgkP5NE5MDhBpxQC4MRjZjcTASxau5cLol22xFoSjKuuWl5NOWQ4FtMEIyl6AecfQgOL1YCDhXbcrMPqRcpfL5Cgu3ONGYahwaC6r1dq0hI+hQtTtHwBFwBPoFgR0jYAaAsaZi5IRlmY2FHsymEC984Qs//elP/9Zv/dZ//Md/PPvZzybkx3/8x7maLbofMIKNuggJhsTZVcL1bN4Ns5S3VauMsEOxCfAyYgwJciRDVOc0YMtKODGGIVmQlO49QcFKNZFos5KQyc2tJI8mXQzRZJs5O/aXWcGqBxO3mMjB9a0gXDXxpQqks56DFJPWyUrsnav0BmQhVisOVQOWnyuGATbNVut8Qi8DZDglqZ1EWO9xzsG98/ZcEkfAEbg4Aqb3XDzOlp7CqRAw1MvmGyz/xXPixIm//du//cu//MuzZ8/+4A/+4FOf+lQi/PRP//RjH/vYt73tbVvKtFciQQPaU6F1X89Uel6vPLJ2HyvwPWEAMqlx7g+21YRdqzqV78xZO69wiWAz2oiMzZk+kBlpzzcwkIcs/arJ7ljhjr3zjoS7/80QLzW1ekW6GljqLtq6bNCRK+Tpaoj9pbD7ongJjoAj4AjsEAI71hjTvksTHwSw7//9v//3la985Yc//OHjx4+j/j784Q/Hwxgwa5MwRD/iEY+w2dE7VIXdzcaGRo1f05LSG8iuDTPjjIYlmL91UfXxRS5Mf9blv51JU7ZSCGUOm2o9CUq2QxYl6Jiubpe1PjcjYGiVCMUSm1LI44yA7SkhEDD226S6yK6XYqTuK0evxghYehiMceiqaasBtaaO/LTqzJOmy1KQDtK23kBfIeHCOgKOwFWFgCp2O1EjZuHaUlQmWD3nOc+5173uxSzo973vfV//9V9/ww032JpgVijd//73/7Ef+zFazJ0oc9fzUD7F3EurblTbad21jecCfHw0mirHRNyms9nKloh8VquoqEzr5YT5RpqZlkWE9FV1J5Ci5XGNKVhhiPG/012QQCISqMwtZwvbXhyrqzp6bOX1xVWrj32Futg6t7RuOi5PDegH0fOjmvXMZtAX9XIhHQFHYN8jsGMasG1IRENJa/ixj33s2muv7VZzR0ZGpqamDh48COAvetGLbKi4z8CHh2n7OxSrRxUxPGm0qPS8iYJ66SoKn2qelrFsaBVhUA2rdfYMM243Vr1gVjAqvR8jYIkkxCvfLDFm0bURMAG8IPy6WmlQCtU4Eq/Hnei4THJe2wkLea1S5uGpTbBvNDojBT1eIxfPEXAEHAFFIFWrdgQN2NdaxkOHDjHci9bL6O/tt9/OUmDyn5ycNA96jE2H3pFCdz8TmnXhVziLL86hlaNoU9LM2Fd3ksy05O3IlPEgpEi21UYzCXMQOyZVMXAbLWeROkUIg3Ycs7DMQmt2hURPo+o8TLmKDMCct9OPS4GBwSpopnXqQreCj9Qxlr3B+EVJ1VrSY3HnCDgCjkC/ILBjGjCWZ3RfW+CLssViJDiYEDxmfwYR7NLPetazXvziF/cLOsK5HQqEBmzSsBCAVkC2rmIIN1WCicdwLg+216fZoIwCGlmgAXO8D1lvRU8lB1JBTkAtaWNZt4PL1ES9S08NsvwtpI+uVAoVPxvblqrZO9A6UHG6LPbb66NKuaiOgCOwzxHYMQJG/YV3rYn867/+6xe84AXPf/7zmW/FKUmf+9znmAv9i7/4i0zC+vmf/3nM0QwDo4oxU7obfVpV2lAGkomAJZZWFaWtewskiJwQKwK/sTs5kBV+GmjYxUioO9t75IdVhYBp75NqoxWUZC9i6I3Gv0OzcLCOqhIkc6CFNNce6s3FL7phJCkkPxLXG6162CwXSgtLyyzlbbeYcySPMCa34rYdB6S3QbOF5gdVx8VccO7cOaCz7T/xmGw6Y8nkERGADnDExK31kaC+cGHIwuUW08LbLebWA3O91houF6g5c+AwplAJVH9+e3Nzc/G1lUvY6/uiyi6kI+AI7A8EdoyAbYgRLoQFIeDXvOY1X/M1X0OgwcheHC972ctuvvnm66677od+6IegZ9gXxjU+IBrcAINyhX1JglHR9GlsjzZ7CCY2D0/ZyoPFxHgoC4I34uEWbsbKTbSdm+QFl8GvIlqhFDDLh6Uui9VgoiKhtPU2EqwsDdUZ8SHIZTgZ6dSFvww1y+5PrXSGNbl26XqdjLMgJCPMtkC5eK1tBpPF7GTTD99aVXoV1NT6XlJl6RXJaxEP70C7L3RQ+qE+LqMj4Ag4AikC94Qz1oEI89EyQqW497///YcPHzZrJxSL4suelLfccgtLhGFlGlMeQdWQK6f34EiI4osObUnIlzg4GlYjXZ7CHzbRmjjGvnAJhG3sS1pSkQ/8DQ/ZYPM6+S77BuOmMKKwI6rYp++cedPb3/3xz52hsRftkgfpCUUgSYAxw+UUBtHUW+wFnbChVTsIOf9H8iLXDScgKePKk65XB5ikA3kN73qgmJg0aMB4iGm3fXQV8PU8YCNaMwlkSNMNsp5H//Ut+ugduKiOgCOwCwisa6zvSf4s/7Xk0Cos+J//+Z8wK+opmi4ciU7MYiTisD8lITClGZMzxiUyKi8sYgxBU2utLa0q/G1ZQTB4IF1TnSmIEm3mF00wWeF4RKCp0fekOmtphfBCyJDCFlvBZ2+7801ve+f7P/wxCLhDtmCoatrlacCWFPM7a5BqTLRms8mczYJGBnuIRwY9RRIhfXNGwLYMyUbZzaRvuInRvCMf8UlpXRkzOXRIvJNXz3/zlqk+nTCwLrAQOHWph7dPXZm2xnUNoE4k/3YEHAFHoDcR2DETNO0+jTutJA39n/7pn37Hd3wH1yc84Qk0jm984xvvuOMOrii17373u9kgmshwhlECuJiyawBBq3AzZJzlZjoua4iJwGHDzKYmDmRjrENMS4h+DD3jZ0CUadgWuANXWnS4Tm3NpXxQHBqZWVyeX64S3NXWy2bOlCUseXlFMpU5F1SrMnMKDJNYDrhF5xbtl2Iglq58GSpHpK4A2b6DhNYHwlBrzKucvSaN0TMx14L6xEdNOwQslZapZtTQMNFKFuREQonTJxVyMR0BR8AREAR2jIDRPmnioQEU1qc85SlMvPrDP/xDuJAW/3u+53ue9rSnPeABD6A8doeGfVFzzV5KfJtOBQej7MKmsAgsS1Y4e0XEgVyNrWFfYhrpEmLbXp45cwaLN+yLpZpsd5J9kYBpyWEByoMLocKJQ0eSXHF+edVoscMEMh2alTEEZuqwCb/Vq6qr1Wqdo5DY/aqdhKu1hlC6OD2akOAOuQM1a4V5wAwsBkbxGAFb/yOzTWu3RlIZHwMXfuu1SK7940CVLlcUleSACXNZ50JwC/k9yIFITsAdePzbEXAE+gIBab53xGEZnp6epomHOB/1qEfBhb/zO7/zF3/xF//yL//C/s+wL2RJQbAvDSU6rtEJzEF8TIvveMc7vv3bv53tO9CY3/rWt8IWZouGen/5l3/5IQ95CPGf+MQnfvSjHyUHE/gzn/nMz/3czxHOuDK8zkYfMJANBDJLa0cqJZmgcMVy+hB0yGdgZAhCPnX6rOlgopiKVibXlJL1btsXJWCrsiED5XT2ehK1WEowIkX309vuIiwhhwF3osjDDdFsDBg8uxP2i99ea+fNS9fDJBdjgE7Z42px+qVGLqcj4Ag4AjtGwBDGgQMH4F3Ukc9+9rM25xY/3GC6LKot6hcEQCCRjY9NaUOlgzLZMvp3f/d3aUbNlGrv5uUvf/mrX/3qX/mVXyFPWBkOJjKlwOK/+qu/+pa3vIUJX3/zN3/DqcOseiIJmZODzdLaibfLcX6cTiSkj8rJHKeJkSAamFjQY4nWY8fzjoq69YI7hNkII8aYG5zWKwpsM0rqSYudrHRetBQjauwmBIwKHEQYXhttjuZrDOTW5muhSHds5DEmaVRHVmTHYa7ejoSyRFMnX62BDiNbL0IerOUhd3vtkF2EbGETYAxYhVZRWXKdU7xlzVU5oo7tZiwLljqI7rXgXr4j4Ag4ApdCQJvgS0XaynM0VzjVdNBnPvOZnIOECZSEKF7wpeUAK2MihobxwLLQMGQJJaM9f+u3fitLhLFU40ctJi0JZ2dn/+mf/gntFt698cYb0afh6X//93+nlNtuu+3v1T3oQQ965CMfySMWPlEQ5msyJ2dKNFUST6Y0mxjbuwonBmyyzDyf4SA4kgtaA0dmk+GTM7HsZ500gqhV1xUwEVtYUei2cuc4H5b6ctxgsYx9YLXOeYL5gahajBcWZ+fgG9RVZi3TB9ABZ1n5ynlGxWLFCoHwW0HEoC6HAVeC+kSxRS8AV2u2EEOqL3SUFMI4aQaTYwNLtdxyM89babXZzguml61EKJ2KkFDO3uWkpO1VQMvbtQviY23nVArM/vxOJkfluKOkWUPwOKQnkYeTkfzocDHfrs4sVumLWPdi1yTyjB0BR8AR2DEErMXegewweGajtvAfM7D+67/+i+W/0KEN3MK7v/3bv828aJtORRx4EbolAsWT3DzQRsaXtLkovszkgq2JgF6LKRubNmPMH/nIR1C4H/rQh0L86MQc+UBCOPj7v//7yY1ArkbAJCSCZW7EvI3awkZq74WnMO+yGUY1yJeHJpfqyfziXDI5wshjEJaSnMx7sulTokFuncOEIDFsi/rLp9XmJMJoqBjEKw0WtTIJi2d8xEkB8pVTjrQSrIIkZLg4H7QHImg1rThxVWOWnbzCMOacQtWAC7VWDoqC0bt6XqItc4syTQH8bV18EWz3na6I5kchp/9Kl4NeSyi7n6jYorCXwkaO0whjmQgnILlzBBwBR6AfENgxAoYM2IpoYmKCWmMW/vIv/3KYjyFbuNM4EhaEbo19sUvDiNwaRKbyEhPGJRoJaW7xs5wXjRnLM9GMbGB0lGP05k984hO25JdH5EMgc6+wP3OLGDwijo16QrqwPpmQ5+XM04GAdXzXKItG/8Dk2Nz87Lmpmeb1w0z+ERoQ5jKN87Laf51iTT41XaSLfr+8MIv8psxp3pK/OboneLBOyzRotXkTzepl9eWpYZUmEPlDjiksFoWbLWZOdOr+cNSSOWf8JPi9iMRUx+DuiE8E62+BWCfMvx0BR8AR6AMEdoyA4VTY15YJfehDH2JCFhoqbAoG2nrms/YRZoUpCeQpfGAUa5wBhYimo0on4adOnSIc1dnUZa5MsSacPNGq4V2bBc0tWfHUIo+Pj3NrbIQR+4//+I+ZDmbTsozLL+O1iEKpyWC/wwfGPvf5xtTcYhwVWL7b4UEj4G3mbZlqIrwgg3dsZHTmzEmOFmDxsTJsV57IYQSsY6D2AIgBH9yY5mwh+PEopLocWA8UYh8OwonZdzSl4wmyOVoKhJjWpVeUOSPgy+ldZVm4xxFwBByBK47ABv3q8su3EV940WZXwb4f/vCHWfVLOE0nfMzVWBAGhQmgT5zprFmpMBB6MCosPAGh2kHCLDGibYW/ScgjmJWsjh8/zoivKc3E5BHqMnEsQ/K3lTn0CX72Z3/27rvvRgwEYy/MrKytepQDtUsgXQma/cMTIwxDzswvCT+qEs/TdFruRsLcWiEdNlmt1zAZT4yPs9kTB/ChAvN6KLEz51dzO68IolnnI123hf1Aycn6NKSxV4N1AFhAsoHNuq8cBGx9uExq66LJbWeeAV4n4Awf9zgCjkBfILBjBEybiPpLnSFFjiD8ru/6Lk5ieNzjHsciXSzAf/AHf8CSIQZxrelEtTV04GDaTQtE00VDhVaPHDkCj6LW3Pve9+YApd///d/HKgvvsrb4ve9977Of/Wy4ljlZkDoLlqBeYv7DP/wD7PuN3/iNZIgHQiIHYyCuMBBXMrnvfe97eW/FCNjkPDo5HMUtNGAlstSWq6o+DN2ll22xJE3BayAjNt9AoR4fGbVa6F6Uqaa3NrdIRclYmHCKpspUsKIqotHtGmd3LAoMi9NxUVPBFiXrlWjM1UMUhM8E4kUY0LYMiXdNiBNwho97HAFHoC8Q2DECZgaWLf7hDOBXvOIVt956K+ZfWkb0TsZ973//+//bv/0biKDacj127Bg8YbOjUctwNKDvete7GNmFS6DnT33qU1/4whfwP/3pT3/lK1/5ute9jnHl3/zN34TdWWRMZNYsfdM3fdOLXvQilOy3ve1tPPq2b/s2hoGhXlJRLu21URH0nO1MyVrhbb+VVPmVdJAcNHlkvFzMJWemZ5lzyxxdwtkbEZHw2FWibtMZndQ4Uz5JhgeHWGEjKr+yLgXAyikBU4jqfNiYJQlm/FjO/7UehvUFOpKYCVrkMByYUw2v40/7CtuUcA+j02mgdITnugFhuzVuBjB5B+4cAUfAEegTBNa0insoMGyKikkmWIz/6q/+6gMf+ABkCbMyIoth+TGPeQw7UJqtmHFcdpfkEXyWFfqmN72J3SvRlWlnOS6JR0996lNf+9rXstgXHfcHf/AHSUUm73nPe3hkTP+qV72Ktb/f8i3fAqmziQergaF8bM4wLm2xETClUITd4rFdLbNCt+SBWeFXI0Al4IlBpt3Gs0u1lUAWJhmCUhcM0XHcmVi2pby7I4FFs91CsytziDK7TwdxW/kE2hH+yZxpwHoL/VAiZXbTEn6yklgddO0pd6DRbuv64uxZlm0PeyBgqVTXryUT1qpm3AwQWbh7HAFHwBHofQR2jIBhX2yAqJ7UGaKlrYcIoUbGfTEpY4iGEQnhqTWXeGzZkgV+wzd8w6ZHGNHscpAw7nwoDx48yCrh7nCbg02IqURZk200TDiCdcffkl8p3Fa3JKwNivLXjJJRvRaUZmvBkTI8Kds4i31U5udu36KgA7ZM4GV50ezSAuO3A+XKYLmyXEmmZoL7HgtifSQWauHUMMipZg+Vxqx+ku0xz52rUV+0f+VrkQEPU4Zrq7VypUDvo1gq2QJZOi4Lc7MyEj86tqW690Ak6sJwPhWkHyYYw8RJHAGCrNqSzgq9k+HhIUgaW0uny9EDcrsIjoAj4AhcCoHtE8YFcqRlNPZlnhRDv2xNRYOI7dd0lBe/+MUE2ixfLNKbcu0FMt7rYLMta9POEiA4gEnYo0PFejucXRHd1BQva/ozyt+G0Oht7EWl87BkfwyOdOTo4YJsKlln00vUVlGtOyZo1QI3lIJ+T3HW58CTPc08JgxZ0fXhdZhFdxsS7mlUxDaE1zo3HVW4802fQ2rtGvCevigv3BFwBLaNwI5pwJQMrcK4mHl/4zd+46abbvr4xz/OtCxGZ9/85jejen7yk59EibnrrrvY8DkblN22vHuUgCYeFsSxBROziQ+Pj921vHRmLoknQ9HJMnMvnGDxtiwnu0nSCbJ+EEuPSF0pRwPlMuO+TASPgoIwEPkTQ5YlSb7GrNmVbg1+W3bVXWzKWEpTZEsG9JCQtu8mK20cA7ZJ3oKDmtrZfKQgmBDNbdDdPwD3OwKOQI8jYC3/DghJCwitGhlAsZ/+9Kcf/ehHP+MZz8D4zAguS5KwD8PQPOorTQX1VCi20+bDgG3M6Icmh5Nc6fQMK5FSOrxsBI0m87oXR61RbyXxQCmolMqw+kqtKtkq6Qqtqy6+geBJbnPZsm3IbKcOoqemfiVg2bhDtwWlLjYPTnLuE7dBxc+kTglYOhZieKeTt26wPIvnHkfAEXAEehKBndSAOfSXlbvwK00hdPvDP/zDqFwM4MENaCfwgSm+LDey6Vo9Cch5QikBCw3zhElPSSsfFQ5NjIX5lbOzi0kwEuY6nRghSIm1PaeztmzqFjthtZO4XAzMBL1aq4bBCFmi+sLQKQF3cldiRa5Axj71ECqJok9lDZLs9YxgWLGFwGV+Ui7AAgEB20BAJ5s++ObnhNhmY8cjdeOqZ0jo0cjsNy6VRbMXFbjzNvqgYi6iI+AI7G8EdpKAYV8jWmY+M5/5Xe96ly37QeVi+g96DAoxRmn26KAZhTP6C3mdY5twrgHznw5PTgTRmbPT83FwTVYLrVR2tz2PcSdA0X3hdPmBkpigV6sQsJAqy3By9qKEYI1k0/yJQBcHMG2TL3tGJqIHZxRtw6i5CDM1QlIK+2Mpf21PyL2Kfb4GLEYUXXQlno4GTDS5cwLeq/fk5ToCjsA2EdgxApZGPwylcU8S9sfgQCRMo+jBDAmfOHGCiVfoMd/5nd8J+9JQZjOGtint3kSnRmnBLJ2SdUfJ5MRYqx1Pz87xgKfKBRoFzuvE3aqsqsxZZMaA8bDVJqoqHsC0cDmY0NQ+rl0O/Y+xYdNou8eAESmN18lciUrmpfPIFMo+6gBtHANWzA0GezUMClAdFoArHXcB5F5HwBFwBHoYgR3TF7AB0ghibca8/IIXvAD7MwTMZlWf+cxnsA2i+LL6Bd61JSWmuPQwLF2iMbs2aEOxOWFWThFinVUyPFRpx42llWU0rrid52geCI8jeWW+FGf1bMuBBetcmWJFvq027M7SoRI7fQT5RlsW20jWcYdQuZHpWKbmsQ+1nP+zwlkFYaGSS0o8ECExl7dFWpVJ9eCI2c+wVDlq5IJmLclx/DA5K0mbtHQsduyXgAQ75RAOWNox6nyrEOkhzJo15yZmRSA3vUhwo/MiGGYP3OMIOAKOQG8jsJPNLguQrLInT56EgE2Bg3QtHHqGa2ypkg5P9jYwKh2tOStooxynBOqGGzGrbwuNdv3a6yZzYa1WXapyDmA+D/MmbJcYMlYLCxilbb127ItdaITBUi2Im3ElCssM/A5hQK7MLbVl/W67OVSOAuZHy1pjiFKU7Nrqco6ThMPiUhBM1yJ2sLxmqDAExbJnVitks+wcCmHMscBs6JFnAtZQsVCKg+OjYaXUPDGzwuQuna/EumY5109YS2268Nwas229BrsWE7lWmV3faOaT+mRFJoQXiuWgGYe6LSXrgPNFaiyLuCaGS2Fp8MzCttHfNdk9Y0fAEXAELoHAjhEwqq0N9FLgk570pFtuuQXjM9tXYT+0uVewL7xrxufMuHoJ6fb6MVwKB/CRWUzqk5BIlNByCT2zUYU1CdeFvMKV6zet2rr4sGCDoxeSoBixIUdQ0kN7m+0c4ZSIOsveWJqbvC/Uv5xcZHsudL5VUXejSpSUmJkkshJHxEwiIkSWAwFowJWwEXGORJJLTdtSNRG/4xh3xpG2VxyiqPxY9uOCnHasTse2U7/WFsQ4kRkzQF3fUq9I73I4Ao6AI3BRBGi7dsbZMhibL/NVX/VVP/ZjP8Y64Ac96EEovgxP2lKZJz/5yUbABO5MqbufC8qtEmy6EFiGe3Whz+jA0PxCg02lggHlLKkRzNdFZ1uUrQNFA21Xl+qSi9kJ6KbgV8t2OqFKDwGWaGZCoEjKs95MNgacYRsp+0psdZSTjQF3wvrgmzrajyrbQK2DRfYtHvtd+YnAffBGXURHwBHoILBjBEyGrC8yYuDgI2b6/PZv/7adPwg3GEkwZYY1M8zXNYLpyNC73/CfqJKZgDoCGwV5tEnmYc3Nnjo3Pd8+NiZrhHT2le6UoYmyJBf3JESW/NHzmHFlnRUyK1dkPLdWw/4qgZKHXNYEydiIIGDnWXbUcUroOv0q7T3wuJ2E+dCWIfWL+QGpzRkBG8UKWrIrSroniUUAG/oWAMUhlng76fzbEXAEHIGeRmA7bHHRitBKwgHGtcy6gmvN/oyHabrYn+EJwokDeeC5aGY99JAeinAff11Q4T0yMZG0W+emp+BOnE7HFTOo3m3nooQJj8oeJoksQCJzmwVdW10jYInVlXm22wYJMf5THhaIlHpNBKF1GNuu6OhiWN4wuXo7Uu5ZXGpDZ47ijYAVZ4UbCu6ADWJGwH30u9ozQL1gR8AR6BkEuljlnslE+8ja36/7uq9Du6XFhHF/4Rd+geOJ2P2KW84W5NgiHlkDmmoz96zEK5CaFp7BVxl/xacfLsyPArWjBycZTz07Mws5tCM0TKjOIm1Hrk4KUttqonK5SFilVOSYBQtBsWMdcEY2wqg4OXEh9dKzIc7AQNGeyLWzHCeLYyF0j8C/vzRg0KBvh9jrfjPcdwjY9vLkKSA4Aa/9BtznCDgCPY/AjhEwehiLfTmal/2wUEe4ffWrX01bzwwsblF83/KWt5ixFExoK3semVRAo0jU3HQKkLCerAY+PDqcj9vziwsQMGF0OAhXDXibkCayIgg6MfKgj0LmZqKv18W2DFi6DphI60DTEqVoI1R2g8JJN0C/hKC6nEXmRRBuCmXXw173ZuuAqZLVy64Gh/mNgPuuar0OvcvnCDgCu4nANtniwqJgAoUJGAM28uAwYDiYBUhcoRbbexIaNgKwRvPCmfXcE2n6TSjW9aiqO1Iu55J4pd6AgPno9FvU0svHE5qhX5LXjS2LeRY+sf4oXRS0KVxZYGeItAu0DvtmccxjI8cUtI6cu9L1ptd6Dza9wCTM6pUJzFPQM6rOAt3jCDgCjkAvI3D5hHF+rbBw0sRDvabpMgNrcnKSwMzyTBKUMJw1qefn0IshrOVhM0idJ8VKXyVi2WT5XsdGw2bzxN2n0F+rzaAk2yxzCu+2J7WxDAg6hHYx4AML6FHW8CBTq4Nmi2U1VmAo2m+eYyEEITMwAzVPa3Wx0NKzkcNyRVuWK+OltlKWL9mlg/wHykzVOnZsmCLoFfURAYMGPyfExr5CzSJ2zW402NNL9ubgmUAni7VY84b6yxQ/CXLnCDgCjkA/ILCTBMysK8gALQQ+wM/BRxyFBE8QyEiwnBifJNAMt31jgoaplKy4aGvPRbRSPmOVoFLMrdTUTFyQxbOXZ1bPUjVanEsYF3J5VjrJNOu4lXQfr3ceZ9raY+Ynid6sG1Ns+nvT4Wt5AmPZkQ+Q2XmZbZq0JwKB2vTdi/xmiGP6sWvAPfHOXAhHwBHYGgLb1tgukq1ZmJ/znOfQGtLKc/TvS1/6UggYDYY2FEqGhrFFX4QtLpL5nj2CWtl0SozMOC7yTbdltByMVkp3L61OrQQHB+WRHFoIFWzTwYWaczqUyyQsCLhUYIequMXOHhScnjYvWrIw/3q3uloHYZvevP5Jekcio1s4usB0MrXTamdi0+i9GEiPDbHWfjZigBCXoQ0qPgZsmPjVEXAE+giBtC275xLDr1ibn/e853FFEcEk+KxnPQuDKpOw0H2PHz/OLVtlWTOKHnzPS7wiOSjjsl9USpMwl5AXqDHneGJkmA0i5UgkJTkZWd2makl0WIQrWYihNUyX8xbRgMMY4rGdJYhDqdifM8rJ6k6fhu6O7YKSBW7wiMbLnliRyExk3g77ZvaLg1w3EnAHhc63dEsY16Bv4bOg++W1upyOgCMAAjumAcO4ZPeHf/iHNPHd1kJmZhklcx4DEVhag7pGCP7+cEKrMvYqNCsXGRKGgPkcmJzIneWUifn28QkZahU6VQ7mumUnWSsH28A5VgSSogQzcN5YXW6xQWVRtvBk3Dcj4Ix4iAkBowFv5XxlUiEXHSCOa67VgmBoyyLudUSb27y5Biwj6IKgEbBNCN9reb18R8ARcAS2hMCOacCUxuweyADjs5Vs7SYtI7eEHzx4kBA83NpMaYvWF1faeD4pAavESSvgVOCokJ+en1daliN7LsOJQq2usw5YDiIEI/Y0wWMqnXAnuyGvreq1FCIStgQgvYgGTBw5RFE3jyIZyNM90r2z0kx6/ItOQ0cDVkmtG4JS39kLy0aIXQPu8ffo4jkCjsD5CFwWaZyfjYaYEkyDaC0mV/gDPsbmiWpCu4+jobTwC+TRo8FKsciW9i1QdnNhMD4+Crudm57FoCunFKHIKktvqw5Zkqy/Ylo0qjClSKCMA4sBedP8WeWFfnwRi0KbQwtVIOsXQcDEr9X6xwaN0V8RsBlkKbYZaql5Qnp4/LoMw23h75EdAUfAEdgrBHaMgCFaWkCuYuTUxp6GnuaeW8JN5bX2ETK2272q8zbKZV0v216FAdooA6ht+RbFFJWSOU2DlTLnHy0srigBi2bfxQtbKgRqFOMySh77aeiRR5yGJPmjAeOLkmoSscSJGGx8xQN5Jn9yJTrrj2uNJB+0WZK87kXKVl3yx7TqxIiXVG09EIlzlKJSlfldaTZanvq1EE2U3u79F/0Zeh/NJMwlbdmgZM11nQgcJ0DPUYWYIJqJLM1y5wg4Ao5AXyCwrt2+JxJDtyS3q/FrppYRCAfz1AY4tzJgeU8k2cm01AnNK4wHgvpw0GoGg7VgkFvjgsPHDg+UKrffejfcDFXUGK/lwTqeuJQsLB2WswWDahDM1sU0MK4YQfJDpZA9MG+bWqgxTI8qXIujXBxGLRgVLBsNhIGbg4Vq0lxeuO7AYPoiQ2Rg+nTEMcAIAjdXcvlGvUZAsSjnNh0aGqpHg2eqEZtx67EGFILjMGNZm6QnIl5K5iv4HJE4OXFptVVKGgN0eigaeelSoO+qGHGzTU+IvcSuPTRWawYzq8yKc+cIOAKOQH8gsGME3B/VvQwpVQMO4jrH/4o2JjmgZcmJukNDA2wq1aq30V8JyuWs+7GtMphbJXQuObKPZcJJwGh7cgAwS4agyHqcI3NIBQOraYN2LKIYG1RvbrTg7xa7cOiLJAwZRefloy4mG+n9yAyxmNF4aL0d5GqJnBNMf0kGh8Wx2bQsOu419rKKQKrsulEIW2s/VrX2d+qYsCdoPozbYdSIpZ7uHAFHwBHoCwTW2rS+EHfvhBRDNByY4iX23WByEm2szaGBVT3gft0g5TYFhTYYL4cpy2jT6rAicJutq9mwxNionlQ2d/oi64DJTCKbIRoC1rld9XrfnEaF/IwBA8XaLGi1phhKdrWnXG3yQfcj9zsCjoAj0LMIOAFv5dWAUkq+fJlD/arkglKxwI4ZiysyiJs96kTZxjdUyixoWFZXIUnCchE7dJyuq8GurJZi6QCEKHmJTSZHBiZhQTwXt+oLdenoNKUYVduM623It3dRkZmpA9RRZ9NTDzWco6zzoOPoYfgypA4Y/u0IOAJ9g4AT8NZeVcj4o01rSg21tpfF+OhwLgpn55ZTOkjUsru1LNNYytskhxShGSFgNa3ClNwaUwrZYHTt7CBpc9xITrDtfsyGJxcqE8ZCdbckxLcFS6Y3XyhJT4UjM3rtOgKWmhO85lCJfRnSGhzucwQcgT5BwAn4ki8KPoTCAEomDAteOs4IBXB7cHKCk4tOn50iGO61NamXzLErgmQLmZBWCDiKIGBuyXmgzDTosFFblZw1iAVFltCW5eAneGVlBc/goNK4PV5/NZE611QD7iMCpjamATOJDJf2JKgPle84Km+T7X0jjg4k/u0IOAJ9gIAT8BZfEvOiOgQsKey0oeDQ5Bjzcc+cmxL2hUsvbzMOTdtoNGH5kqirUoCOASc2Bmxkw5InmY3UoXmKI9xU5MxwLSnXO2OqTGm2MeBsaHl93F68o5o2BmxD7J2eRBcBKzp5DnD0MeBefIEukyPgCFwQASfgC0KTPlBNC+aDFgGLaVdmI4Z3uR0dLDPBaX5hMVVOL5XZps8txzW9VmkWQiFyFohSLHtgqsvIB+qxaUcM8l7IZZGJQHwGjwlZy/ZCyXop3HoPelByKlZ3pSzIej79Va9ewthlcQQcgT1AwAn4UqCrwRkFl48s6ZFvcZAhE6/uc8O1q0sLs4srQqIEqTZmEbZ8jUg4PSfG4bGRUfIp6JSpsfGRZr1aW5WcmX/UqDPhq8JkLGZg2TJr+JkjLSBUhj87q4A3KRPbbL1RL5TL0Fghwlg9SKQLHYaRMvwm2exZ0GJVkMG0QB9DoeCgqIRbmwqNp81mYXKCsnRWuF1mm2udUm60bZR8PmHvWX28YEfAEXAEOgg4AXeQuNi3rJqFnEQL7WjARAe7seHBXJgsLq+mtCxsTZztOGZXweqQuawkTuc6y6CmmFTXNODzlt5IfM5KglogYLm5sJOMOs7GStGbpbfQUak7D2XsudecrZ8Sxt1UMuqmteMpcYjSWW+1aWwPdAQcAUeghxBwAt7SyzACFnLlEAZxsgsV2B06gGU0mZ1f0JXAW8rq/EiQBwPAhJtqaxFkDDhJD2Ngqw7ZAEof4M1yqLH5Vhxf5CQGi2nMZP4NY8CiGtony7THPLoPtJDrWrWNce2+i4BltZXM2JIKSPyubkeP1cnFcQQcAUdAEHACvvTvQJVF4z+jK0li7f9YOSgVckvLK3XocY0iLp3nWgxy1ynQXMXWqg9QhCulIntBZ9N60e5UDIai01fGLZOZMbEODw9rHppys0umWPPQdgOVGdcib6o+yjkPverQ8pHSqtBt4E9F7iJgswQYYhrcu5XqVbBdLkfAEbiiCDgBXwpuXfyTasDiF0WUaVIZUw4PDTZa8eKy8C8HP10qu/OeK3mu1msoo7L2t/NcyTis2cGBLHkKg9Z51lV24UADHhkZ6STa/NuUZjiJx3LIUmd5cRq7h9kXCTONdkPdkDpdF62vgrqZ/QACBpNupX9DQr91BBwBR6BHEHAC3sqLEJSEeLl0FuNyQyjt/oEDE8wQOjfdwm8TfyTilp3lJ8Zk1v6W5DBg6J2syuUCTFmvc0yDLjxOYPc0U8Jha4gbAkYDZheOi2jAGlEks8SVithpbfFSml3X10Xy6Yp1Rb06Wp2OjndrwAiR3rIttsptGjArrHgL1tvIBE1ByO7d4wg4Ao5ADyDgBLyll9BhJmgsZTJLBlMeOXQ4XyycPH0WfuweqdxSvsIiQsG2MFfGfTvJSgUmXad7QRvTtORkwXXvy7S9i48Bp30C9sNSTVe3gpbiGixharc2MNMGhuvIspffNo15U42206lI+z2dMeDmhkrtpfRetiPgCDgCF0ZgXYN+4Wj7+ElYgCBRG2UjppSgZFK00K1qwBNjIwxRMg+LaHi2hxR2VKXcJitoknw535YJzVHQZm9FzamW5JlURLHEiuI2YUzGCtmUMhQZVuIcm3dU8jGyaTZIRBSxyep7lW5DIvt6cIYhY8iykqcUsZ9IjJK43AhWGjldRsxRSKJ1k0S0Y5LoVS+aVmy98rFa87QTQZ6uxd0FHwVxtCKrl+3Qxk65Uhfqy94oKgAasMw+L4RxLombcdtuTZzOxHW5I4597JGm3V35OwX5tyPgCDgCmyCgDfUm4R4kCDDWCwFAPJiGSxxFGMshQklYYiY0wMEBKGHXHD+CJnpmeppnraCgu2hsA718IYRip+dq+VzpULnFCQywL+bsyeGg3Yxn6sUZDhyEGJvVoTKkHMODEA58SapPnlqoHDgyVmiOKfEip5SeRMbTxo7wapskzTzC5eOgnASP+NIH1NvxG997OqlwwkGuUZ3juOA6vAxL60JjSKlDVGyC2YyDZluGYjlmmI8cyKispdb4zqD4Niq8nagUNLvabCS5ifFRAC/yxzQ4hEQjToIyvRXZfDvi7GMEHhsslaOkVm+GxXy1Idt3IqnYJOivxLLsitzsY48ko12Wfzt19biOgCOw7xBwAr7YK6e9poHHibIl7CvNvQUSAM/BwUMDZWyeCyurhPCYp5fhGm2IM1+KWlCt5cOLYepvIyzVuMeFDSUMK0AKgQuraMBBrpJPYCLVgNPSoSPV/MiKmDHHRQS2j1QSTw4EX3zDtfDXhz51K0unOM+4WCmjAteQnYKsLC3QSupokGjAov5vjJLG3K0vimvGEQf9AjXIyI8VhR4Nn3lliCMMKkVLJXUDE95RE7aVaKQgNJU3GxLW6PJEXfq0c+vfjoAj4AhcUQScgLcFdwoXbMeHGz7joyPww+zs7LYyWouszClTh8J164AhEBY4EY11OOJsrrIVrAFcbAx4sDKQvUU52KHLaXQJSnKiT6McE/PBNx6u5HK33vq5pXawVIeF8/B0LtE8bB9qzUHlwkflIHCuYqNeX35XSbvmbcdNCqXH0JFnk5Ks0uVCkVnogqRILZQMRRtDQ8AXSb5Jjh7kCDgCjsDuI5A13btfVB+WYJTTEdyw6nAchlAIKQlGx0rMv52fn4co19NfJ92lvsmnWmugRts6YMuEwM66Gs02YxDxiBaOYx0wc6yG2IZRGEcdD9c7OUBYCZhds5AYSr9hMjg2MVpvrNx2Z60dFRPZ+7JQQmUknn601pRghXAnHNz5pN0OsXXDyELKacnri92xu7jJWYTp+ceig2fOAOnAghBDgwPtdmt1RfaiNAU4m42V8e958GTZuccRcAQcgSuNwO62nle6NrtTnmCUttx8rSHGTT4KhsrBUGWAhT3zKyllbUsKse121gUNljkNGMfelFJMCRU4ZC8ONf7KWCZRCV4TgLMImSQ8NjxiJaYycpP6LLJcGVfODwjFNlcD6PrhD7hvq11970duLpSL9ZizjoWwWq2mnsTEADR9CWVfBEk/nD0h5G0fKw6xuwnRAnf8aqdNdO8l0uFcKwq1HvO9uJGhAUbHF5eXkGoNCnkCbtaZkJsuR6z1EbueudcRcAQcgd1GYK013+2S+j5/U/hscBUqYjoxBIzdmDORhkeiMH92apE6bpeTbC2NLcwVDVjU1NSVi0zJYsmQLeI1LtTsmS+l36YBsxPWpkxiUZV9pJB0MDuSCWWP/JL7Mjfrwx/78CpMG8nap6QZNFs6BUsi8tHUouAy9srpEJh0xaoro8sdCcmTj8brSLzT3wiWHvckHQDtiOjxyVKoBHANsQHQLeBudHiIvcMWFpeNbLmGzPuGrgFLSdt/6wqZXxwBR6BXEPBG6RJvYj1A3FnDL7yEz2YGDY8MYi4+NzVrTf8lclz/GHYgFSOXBMs6YPgiEJWOT2dha2pJRddjMa9YfW28VseAmd87yCyslF67s+6IaqxqTNkOioWgHAf3uzb4ouuPnZub+dSJKWY1ox9Cq+VKRdkU9bejAZu2bRzL1T4UoiFYobc75btbvi36L7IO2F6FdVng4KHBCjbxxRU9mUo7B6nl2XorptOvlWoYr927zxFwBByBK4wAzZC7SyCQUq6wkXyMjwiMghbrgrhlf8dCqTy/lOpel8iu6zFpbR0ws5EJXmdohYBz8C0KHquOeBolFlWTm1cONZLTkDqS0SeQbMRJzvINn6Oqw9ASUq035asWDIbBgx94Y5gPP/Y/n4f5m7rSifgrjZWMZpMgjyKMPZoUa84yWrvfdV8ct+hxGJWmTLq+TO3ACBeXi3nmmDXqKPIicyqpvLz0Beor60rMPZ9Ob6brgXsdAUfAEbgSCDgBXwLltPGWWHJ4gU47khuAS9rQk6zJveHaa+fm5haWU91LHm/ZCQUEwXJVdnWemJhYrVZNt4ZFDh8+jP43Mz3NWmF05FxBeBQHHVH6mTnIN+F8X/bW2MCSWeESX6cPWy0qg7LPB0owZvMve/ADSvnC295zMwQcFYPFRTRhDh4mQrsdN8wMTdCZ+bgBq5HeBCUS+12z16MQvFI8IbvpVlfoEwQgg1aeR8+l+gzp6seKZY0SaNRbweTIaD6XOzt1jlpXOcJBJFXAeGuXsUe35e5XR8ARcAR2DQEn4ItBSyMOQHykIRfWk3m/2qjTvscRA6dBmxHUsbGxMBfNL65AEtt1sAPODK1owDkd7LRMmOGVPZJ9MlKl1h6mg6OFnMQiD/mYZPqc1bLYh2XrShFbpU1rIY+LcXDdobFKId9KincsBKts0DEg3BwlUdJu5yJ27GAHkgBuHhyLPvipmXfffAfLkRkFlmJwKgsXu9Og3brQySBrak9ZNjQN+Qvzcy88LMLgBYUKA+itZrMte3OInV6sCzxBaBV083lY0nlx5wg4Ao7AniAgrbO7rSIg7bo02IoaY7Jx0KqjsB46OBmFudNT0zT6QhfbcWQJnTQb8F2E/pmPYGDJBmUPfRT6adp5QLqwRgvXxzIADP3H5TLaLCGqjG7kEuFgScLGlkHMR+TSOFyODAXXHj6K4njzLSdkr4+iVCqXhFAYktTiZL4ZsEb4tpnglf/w2lf/879OrwbYgiW55CAyMsHJAiTbXXOY2bE/r+uYdCDWXgvD1zGbWmMGGB5il7Am8QVKWwfciam7c6Yi6rvbNXE9Y0fAEXAEtoyAN0dbhkoYShRK5TFS6SQkNcaOjzOSGJ49N731vLpjcpZwvdmAZopFJl7JG0Gzg+ZKhSIDvzY/q5tCTGleXl1FmuFBxnNVI83IpitrRDWtEcJc0491d2ixQj/0S1Zq8fs/+imGsoXMZY+pXKE8COvnomIzF2D8ffN7brl9auHO6fkzS23R94V91bXZknqdzt15sMPfQsAgrRtxUMUO+FJK0qJyCla7CWrDZaKFrVa8xNxuCbaNsNIp0BKUDriLT9HyH79A4c4RcAT2CgFvgy6BfMY4Go+7DmJYOvHKPCkmYaGtlhaXV7DZbsaDFysCRkFlE5rJiQbMIDOxyZhPkdFa2+6KL9bbaOYwMx4+LAImmDFgrjILmueU3VW8xYej8AgPK1vJBOuQyE2y/uqHfQl8+5nbTyxyMhLR2C9Z0yyv1IlLT+DTJ4O3f+ijubHJ4uTh0wuLKMRESzm4TVTFpqtEytlxF4tGHqcasJZl/Q8KSic54+P4BdHhAxZSt+L2wlIKAzH1yUWEAg53joAj4AjsDQLeAF0ad+WZtE1f4zjzhTKJllMBWIzbbLTnli6d24YYZMNZB7KYNSdnLqiD46TMzk5YnDAvbJM+1C9GPzkMGAYyAl7TbrsjKR1DpUJb5MDH/AzvJq2k1j42Flx37b0Xqs1P3bbI9lEpnyXYewsrbeHa17/9v28/M1XNFeYb7bNLS8K+5GCCcC4DFnjNc32ZO3ynFuV15wEL8CoDiFmV5LAk7bKMjA5xFtLiMoPaKhoTwGXzTW6Q3Z0j4Ag4Ar2FgBPwpd6H0FfHyaBnxzHAKtN9mAUtpwFOTk6yN8fp03Odx1v9hlxtim42zIkFWKcQ2ZxkziHigNuu3NRPKjaCJpS9O9JnXXHw2gceQkRxQpaiIgtjoiuH7VJBRpUf+tAvKQ0M/vf730d8oSqYLYkqlcFSLvjMyeanPn/H4evvffi6ezVz+dnVGqooPAZBSw5owFaGZr97FwZ66RmkPLqhGJsVHceFfAHZqRqz4UBveVV2o+R2rdMiXRh3joAj4Aj0FgJdjNJbgvWMNGL6Vd5SiVC1bJkQc6RkYhNH/MUxG0hOjpTjXOn0fFVbei5bavEtHkuJWShTCFnUhAdC10FPsha+j1DpdNUvu1Lq+Uuq/LE0qNYOOf6Wmb8EqKFVX6U+5QK5Zh8J44/n+lR8QqLR8nLw0C8aP1jJfeajH+ehbCiV5IOoshrkYbD/ePNbavNTN1575Ivude9yZbher0K46kTxhedkDpaWmQbvwhclNmXwGlVXLA0IaAWu4YsMMhWaadvSxxgsl1rI39TIsRil9UXk2lI3jdEZBtbXs5aNPHXnCDgCjsCVRWCXW9ArW5ldKM3aaGmu5U90vrgkE4BZopOvRSNBOFDM5YeD4NqRXG7kwBdmRU0M2FS5jYVW9GNLJ5tpWGq9ZnISyNqeL9x5dqAUHRobgB/F+JwrSFlBcHBinJszUwuqEctq11zMsbw1nrIw986p1bBRvdfhsSYMlCtjtuYjbMwnaYYJJwCLnCUh1qaM6NJb0MMYkqDSDgaXm8n4UPAVx4PD9akDQXD7iVVGgmejYDEMFoPgQ2eCN77j3fcfLzz/KY88PjQataOlGdkzCx5jTTJaeVgqtXNBlQ0tud01Bz5ztaQWFA5OjLIIuhhJ34RTnXCg0WQOd1CIcxW6BsRkH6wDIwPN/MBd0yvIOUQ3A8tzo5GgP5ewEwAGyPBSsp06yMjekTxx5wg4Ao7AFUbACfhSgNO0r3NiegU1Gm/ZhkN2g45p3YeLYTPOLQo5Qg60/fCS+jXt2nShdVlJDLJvJZwG2OK0eVXTJD1/pC/oGGczjmEJ7LCaIV4IVyYtV9GAg9agqXbKJF1kQsby4SF7dUmZpBZul6W8VijnH+FH8q9+0BdX5+fe/76bqQ6cusTSqiB49T/+xxfd58aH3feGg7ng3sdHGtXa8tIC8clGHecT5olmWaVhu/BF/qAK3jm225BVvwTwSZ2iKqcF28pgCLbMyuawyC4cgmCifSAMCoKwJhFTPnfpl2K/llsnV/92BBwBR+AKISAtlbttItDValvLDgEPDzNayaGEkpWd3QcLoLDpfCGoQhnQeHBjaWweQRCrfo3ebAYWfgkJWVcD0ynzCXHAGikJZmPADEZfyOkT4800FRwMK3Nj9ww/f8VXfWWt1f7oJz4BqTOqTD/gfR+au/vEnaVi/jGPftTIYDA2LNtgTs/MkZtkiBjC3eKyfOx2N67ZGLBCuFaCGKYBlfOPtD/EA+o1MDCAh+lpa/Eu4fPf/yUA8seOgCOwewh4A3T52AqpikYlfDw5Psq5CBDwGjnLwiGGSi9Mj1oyj9dOYhBKkwwsTbGYh3XSE+YlUJe0GnMqzfAUyhEaUq1503ep9IRyyEM+SCQCCwczE4uScsH19zo0fuDA/Gr99ELAjhwU/Y63v7VSiO77RTdcf3ycOEMVppeF84tL0k1Am4S0OWVIBqdV0dTA3btks6AFbQVTYZcCMS1ruSnCPB8elkXMi0tyIqHWV5/bJY3VFaIAdN+73xFwBByBK4nApo32lRSgj8tizyooMInFrstmxUnSXlxkIBVHgH22VLt6o4ERtVSSwweVAdNUpRKHI3URsNCPZMsXSvHyqqwDHhoa0s2eNytIpiKJ64hkPjXkYvQW+pXsKsXgi+77gNVm+70fuQN7+jvec9f0uVPMKv72J3+N1WFykD0t240GJz9I7wCRjLl0dppksqvOCNg24uguSMGQGVjowFZPKjQ6Okqc9C1Y10ev0nXgsVa5OxP3OwKOgCOwhwikbfQeStDrRYu5tcvKq2yG/dPac7jIdNzxMTnvvl6rNtgUQ4aJxQk9q7tIHYkpGnAS2apfottILaWyyyR7IIsGrBmmW18oi0CEnXXA8gb524RcVJsWhdocJaUf+KgdcZCusj0R7vegBy7Xmu/9wIfg9Xe84x1n7j7x5G983EE9ZAldGZ15fHiAidaLatnV1bcMcuuypU7eu/edacBShLJppgGb7cECTYDRoWHg41QMKsrkcXlxuDXhZJFVZsPfBLG1mO5zBBwBR2DXEZDm291lIJA26yHqr4zKDg3IsUOs2WXjpqa2/Up2MLVwgOYPH6RsqI9SNoQMjWP0JCKxWWfRCkWhcHJcW8VKUarvEcnGgCtlGfs0vRkxul6ndBrsI6Xik4d8pVZoPIw5C0kFwY033mt0fOzk2XOvf/udZ86cPnrkwLd87RevNCVn0rRrweHJcXZknl2srsp4tO2zLBOr15coWe24AxxA6F4HTMUol49WSlCVWw0cGCgD4ApHSxEKkkwr00jdJLxeQsnGnSPgCDgCe4JAV4u9J+X3eqEXxsfGUGGwmO0dZSI064Ro/TnJr8XSXSG6TNeikkp0fAsRbnQtuIIFQjrnWbbLwOnSX+zAcI8sYdJUEkmZhzs+MBNUlNfFNdjBuwSFYrvuukuzlJp/uy5nDIqgnHs4GVx33TWc8/RP//RP1dXl7/6u7yD9REGpPQ5GB4JKKYehd2EVYzkafloL4uQ6+3xILrvjtEcC/2qNuohUvGIEBxQhYHuCFYGgOluXSIiSq0Gh1ewWULPTS3eo+x0BR8ARuIIIeBu0VbA3tOE2BYmjEkhvM6cOHToAX959ci4HXSlJ1RttO16QceJUXesaOLU4sMTszDxHGx2/9hp4I5fPx+1WxNIamA/tlr0ukmR+UTRVHqXaZxAsrMgJhgwAsxkUr1BZSjzdjiTm1gzoFKasRD65UqHZapexm6PjtoOv+rJHJM366NDAfa6//hEPvTf9CUakWebEpOiojQl6MCqWbr3jxMiAbG4hRzWJ+sskb5YBZ+V0yrusb6pj6agLfY4sjypm/Xp9ZGRQ+graR8EEjVdGBviSLgjSyORtAg6OcqBFcRlXY6KYmAbylTJD19a30X6J1D/FICvDPY6AI+AI7AUCGxrtvRCh58tcT73pnY1EyiE9CiFt+kCpzJDtarUON0MmwiG6XEcmEIkCZxxMqGhs3a4Zt9c0YH2ASm1Tq0wtNnKyEhM9lQFDNxoe3APJkJsel7tGWlnmBElZa+WpD6n4TtCt5YBBWH04Fxw7OD5SjJanz9z06K8eUbO20FrSTNrNgSjgIVOeV9UWjrm7AwgzuTYpNCv9nnuEYVWRTec7d3LsdCl4LgJQCypktRRLfhSxH4rO0U7ni3UEtvT6wjpZ+bcj4Ag4AnuFgFow96rwfi43pQQhMzhADJ0jw4NUaF4OLTgiY78yTclI4YL1JCWfFsfqJWEhX9KZyRiTRdkzukWfq6+uyiwtdlsUrmfnSfIOVmUfaJk43V2AKqMZu3Q/UXaSTE1SksJMUS4nRMa+UNi673vdwDd87Vcuzc096pH3I1a7FQ9y3i+KN0ft5gqTo8NxmFtcFfsznQU9MlErRQSpflaoBl7WBeNBli7zCz5MMsehqfMcYNZiURdNEQpFI4F9KoMDc4scx1BNhiuaRurYnSgrRVNQgjtHwBFwBPYGASfgLeF+PsmIgojrqIA08RNjo5hP5zkMT2cp8XCD3ibxO2yQNfwEcBgwT+DalCeEf6BhYY5yubQUBLVaDQWbtDasSeRVnQ3FImDTgDXfjTKS3FwnWx0bthu5QsBC/2EjKJaD8Xzw5Md+JfOuh+VIRGi5ISZc6D7HfltBqRjBu/M6DVpMxMyKEirkLyskLWtnvyBcJWDV9Mka3Vt1WsFBRKdGUin6OZgcrP/Bjijh1BRvITlU1ppIIuLzkXp1y4ufIPpO8sCdI+AIOAJXGoEd0F2utMh7Xl7WiOORj6iJCDU2NgJbLCwsGKbyJOzeBJHmnrCMedNqcF/XDaRRZyWhcAzRlBqEgMvQcbValSewiBCQUD+jnBAhZxFuzh1doSoMhWi5hEOdwp5RXdYei9bIOfbsEs2g7xE2vSrIZsmMwA4UCGRxFKkSNmEeLBdIMruwqAIihZrRZYtMEXVnHfUyDRgP48KtGN07srlmUv/znfaBtMZSx5GRERRm2RGlA4LW3JIxTY4aKyTn5+MhjoAj4AhcWQS8MbosvCFCtC5Ru1CshBhp7cdGRtkUYnZeWIpGnw+B7bZwBlQixWxGH4TJQqMwKJT1XXRxDI8YVyadasCSG9GkpCBYWZFdOCoVDiBQp0ypZdq9lp16TRahIUgUOfBxzTFtSWNFmKA550A/QT2W2yioyOQxzj3A0i0JD06yzUg4v7CMSKoB62RtRE3LTUu6J18Z6WaZSEFyiCL6NkcUa7CUKCBqFyUbUxdkMjc4PBTlCnOLCyR3rs1gcY8j4Aj0IAJugr78l6ItvDb+qoSJ8TMMbRsmYQl1SgOyjnVT9iUKMeucniQ7P6cJZPTYvGqXxpsu/tFACB/6NEpeOwzYEmx2VcOsEC4FwaV2tYgwcLsRlxjRTXXZpIjZOTXnkqTFxGvpZYTBkUMVuH9pdYVQakQm8tfNe5sVfQ/DKAcC5ppjCFjLwn/JMjHLowFjIbDSU1HvoSie3BFwBByBXUAg1aB2IeerKktg0qaf8UIdS1RDMGfxSWiYiyMUyGCkGBaC1kpN6BQVjfU6UGouVBWYucYyIzqlDyJzYx/8KHkc9WNHMSjF5NFzeYrWl8uHMB/WYpgPJ8PC6moYipOgnJNdnSWMgVrhJhLhuIr6yr3pjZ1wfdi5aTUTFO8ierBUgTJU2VVNnfQtplkjc8RWILm4URstQeBxow4hUmfttFFqqmKqOirnMzEzW4TBHC8WeYkgdZNTiXRamQWYEObnqo5cWyHROGxRBbCnnPbECmtZ6cTGmSl2PJEZaikPp3BKOeaQfCDfkrfQDOtqaaf/gQldcLFIkiRdM62Z+ABwCp1/OQKOwJVHQJqmXnOsujEND8EYUuX6cz/3c9ddd92BAweuv/76l7zkJYToxGBRBF/84hezD/O111774Ac/+Atf+AKPZmZmLIKt4YHeLDKBqrzxvT1HI25MJk12CC2RHFqMkzakhcpYWWkKAT/gOkzDc2cX63NxUA6DPIfyNpaK6JBIK+0/bf06tKEcqIzP9PR02KoeHRduCfMcN1xoJ7LAB+vz2Mgw23rMrTYgMYqIQs4MFHdqeikoVY6Midos+UP95JSwZtiIRjiSY4DlJGBxiK+TstXHDbErhbBcUF1bKhUF5UoQsfUGM60polUsFNtBqREOtguDUUlyPzBQGYiKt5+OuUES0Y31ON5Vtt5EtU6qQcynNbvQZrwaXISdWdcsBxgjQ8yRiyttNinBQbfyh58PsXQiFXEAqcEJvhgLeMq5jgzXLi4zRbwxNlxkLS/BYYFpY52RZwHTIMVqbrWWeh4tNYcLzTvmGvxupLh2oxLGbM9h5yUTQBDvTr46ir8G+sURcAQcgSuNgGozV7rQi5UHp2JZNe48ceIEvPtrv/Zr//iP//g3f/M32Hgh1+/8zu9kz/2f/MmfZCuoP//zP//7v//7V73qVZOTk3ge//jHf+hDH8JPNK4QOflgkMxMtdsnYHhAlC9IivaeZpurrAYKOWuW5h7ClFFVmdmDuZjJSoWoHuSXW0GI/pvAKCRnDFMS8jEW72RDCiF0oQIYMUyytT1ZZHItqO2VvS2FS8QpYcFwbZ0jzWn0wnSdaUjysLsgWFvy0Ks8orjNnTzQOshj42zyLxjrIzafiaHhucXmwnK9yQAxIWACCauiLhi16noIY35oNFjSvFggxVlOOkisVUy3k7TKSXFWcUomN+VglV7UZenNIA5VhncpgVXOCCcoUlEdK9aoWh97QnxxLFYKxitRXF9ZaTG5W3JgW5MgpEZy0AW3UpYgJBU2AbJqyxN3joAj4AhcQQR6rv3J64RX23oClRco3vCGNzzucY97zGMe88AHPhCKffSjH/3ud7+bcGK+9KUvfeYzn/nUpz71pptu+s3f/M1Tp069/vWv5xHsy5VMbJtl/OjBzCW2/ZO53RFn84bIyszScBLTkuH4teNoZeg3JYvNShTjrW7tKHVh0ysz5qYZco4DvMF+0MTR/bayHAg3C4FOnBYukb9N3OW/XIhvQ36YGUBxbm6uacTFYwaMWaakFCmEie7cjuHPj/zPyns+Mr2EFkzvLh385ivMh53BbYut17QUaDbDSbfhJJyAVktmYNGFWksJ1hd1kxMTzRprp1fTyhv+nW22NiS9fIA2ZOS3joAj4AhsH4Gea4JobKkFBEMbauerP+UpT3nrW996yy23oMi+733ve8973vOjP/qjcO1nP/tZjLff+73fS3xoD4Z4xCMecfPNN3ML0RJCVmjAZtDGz5zhw4cPbx8iCCfjnCy1CClTg3R8UUUWI+/o8BDbYLFaR9hEVNNN2SJV/iwvlvgiKvs3bbBFQDxkYrp7XdYBr1Ei4ctK8vA9Kl1ahhS5k446U0nJXGoZjI8OMxY7tzAvSq85qZ0woxyrlEPPzlebMv79uje95W//+f+eXeIUBdKiKUs0UrCsWL7ISylWHqb5EEztRafWyKLV8iGi7HetL1ESdrmL1JWfAbPK+fGk78wI2K5dOaQydYW41xFwBByBK4zAhmb/Cpe+SXE0uNCq6b40oyh/L3zhC8+cOfOYxzwG9YunjAE/9rGPJeXHPvYxWMooCs/Zs2ePHz8OMfOIVGiHpkzTiMPBaMBLS0u33nrrJkVeMsja+5Qu1mLrBpPCs7AQzT1cODY2lkyfW1iqJ9g8MTBLkg3ckSa3+NysCgHLDsZCpVqEcY8SVUrApu+SBEEwgHOVZUhRODQwSA7cioCYZ80UnpbA1+ZFrz2/sE/3cRTxNQu5jAwNJu3W0tKKZSq9C0LFHB80GdtldBabc6m4GASfP3l6amrq5OzitQcnxH6sEYkm8VMJqQrGc7HeSxhxhNX1dAtFgIlX7P+B/Rkq3UjAhpEm3PQyNgyMsnIaE7Q4jW/rpSyg+6qldQe43xFwBByBK4cADV9vObjT2Be+hJagtFe+8pWve93rXv7yl99xxx1/9md/9opXvEIO7alWYVzYl4FhqwDaLYcTkBy6ItCszbOzs7/+679+5MgRVOGDBw9+0zd902XWVodZlSWU7dJcaMDlqCJjFxh0dGQYDXh+cVmpRannPN1rgwC1mhzdky/IIKU4jW8sQ7h1L6q1mlBsx5H58uoKd1gIkMA+KhbE1nH3iFuokPww0pyFG4OJ0aEobs6ywYWWwPQqGXJNRAOGZTV+HnqdXg6qsOnw8InpaSiwGeXbOvAqNmBSZtWQBcTpbGSeYLhuMlYtk71wMnAOmEyghoBhU94dpaTTy1JC1YibXdjNpFwstRrNlIG1A5B2lYjfBUuXd7OMPMwRcAQcgV1GQNrZHnRoeKbCwqNMwvqpn/qp7/7u72YK9HOe85znP//5v/Irv4I9+Uu/9Euh4c997nMmP5ruhz/84fvf//5YdE1zIhyD5C/8wi+cPHmSfCDjd77znTtUWcUNMoAv5UQgcRgTRoYGmPOzsqp82UW98M4mQHPkEdbyRhOB4RjjJtmyIx2AjSH9Ykk4iV4FT/UTySocMdEzxNo1uUzCZC4UkoiCLAJRIF8mmjzeltNChDl1SrJkwnkM1HZ2fsEecb4EyqX4mawlBzHyYWZacMfphRVOYywPnpxbwG4utBvp2VD4iG2JRZQUNwJIBVU3IhRiZCYfUEkhbbEBZjp7S9JY70R9F7yQBb8NDB66VQn5kSEWckHFnSPgCDgCPYXAJrywt/LZufSMbqL+wqnQMGRs48GotqjFNK/wLlblQ4cOwa8Yom1bKPZe+PznP3+/+92PCDaqahUhQ0LIDf2Y1Ur3pHYww0ZHSQw2d+jOhK+xwFbiWXBXis32jaIisugXDtvoJI8848zMB0at7nLcgAwBNnAMPWpi6LcTbYfYhkU/alwX9hoZquSSFqccQJaaPT2BtDegPQ3UYJTdYHpxqcbU43xxdlU22ERKCJj4MKLUQFJaTbmVD39E40OHQqpEj0H6NPKIb1JBwDh5sgVHPD78Zoi7NnGNQjK9uZOTCcG1E7CF3D2KI+AIOAI7ioA1RDua5T3LDEIiA1iNK4O4jCY+73nPY7Ev05sZG37Tm970q7/6q8x8tgb9BS94AUuE3/jGN376059+7nOfy/Kkpz3taSQ0IrSsuEW/5IrLQux2a1ckEWE2ujBiti0KVj4fNTj3V8nkyKGDpXLl9jtOSGSYU67Swq9r6IVdUke+03PzhVIJqzuhYi5lXZOcNSgRuB0ZKbabsK3MZ1qpy3nBjIwyAQuFnjqOD0BaDTLXkjYRczO5O2Vf6FvSCJNrWvlWE3tw9BCLeetMwqIsDlDC2SmKeOSNSeyoGgS33XlyYHS8Hgenp+cI4wmSo+TLjh+ao6QUlsW+3GCJFmGw7zmWEEdKwHbskRqsWUJdrTc5DZjXShwx6CuYwvyay6YXMjxy+HDSas9MLckvieJl5XBX4Z1kF8mkE2UHvq13uGlG/IbtZ8yvHSPHZf04N83YAx0BR6A/EOi5SVhGvVxxTMBh4JZZ0DTBP/ADPwABsxLpR37kR37pl34JJZjGC/My6tEznvEMKOoJT3jCm9/8ZlRnFGUbOt2NN0D7DvsYnyOeFRHJtF42rQoGKyUkqQlTEglsZblwl1tLLcFozux5gQYsJ/uKqVm4mis0AwO2Y1YGMzULHGidpdB8aqaWXapCksi7EyuwUBPP+XRzSmZ07Q7UArZwSaWWbhCLmgtkDR0OlIoIC8sOyuM4jEQAKZ8SdKiV24UVat9qh/n5xRXZjkPFysuKYHMqJHc8IDSKZpaaf/V/3/buD3/sV3/pZ+91IKiYKUCnl4NpCzWYGVpZ6jSTi31RENYOYgBadzwK3hPHD9LK5YfBL5bfDI53SqcQjz2igjIGoZ3OPRHSC3UEHIE9QaDnCNh4hbbJJuDQNrG46MYbb/zpn/5pA4hwlD8cWiCNLMrxz/zMz3B7+vTpo0ePonBkTd4OAWpNd6pDW57COpCONKBiL4X/8MEadBTqrfZSVfaI0u0hNxDwJhI1m+xVGebTnaBJlcjqJrS8NrZbxoDFDGuzoBlqRRSKXl5lbnDeDK3GTtKQ84APrsN1erP9i3QLOuPIkLpuJEIu7O01OlieXqrOLgQHhyVbSkMewQFspCeR5HPh1MzMSrUZFfIzc/MQMI76yXYixGbjMJYOB1GzHRdYryRVjoaHoztOz8ystj/5helrDhyQrUk4HZn4GKUT9uDEBC1ElTIVFJWqwZr1ZhdSDpYrwMKwBQvCJYqssE6xyVJIAVfQod1Csfy2YVlks5KNce2Wp8Qxhr6CcnlRjoAjsJcIpC3bXoqwvuyseaLVhV+hW55zxhxrkCwic6nMDwOh69CK0XLhYF8i0IShaqzPcnfuaEk7vIDMtKlAOT5WwT66tFqtitQ4nQFkXmNH89tVWaFar1GFcnkgfdKGcsgJahPDqY5mBjLmrfkTQkmMdtNe2yJpjUlk+6yxr7JjSthpzlv/kkFtdYyeqthc6KlNjI20kmRmvmmbdhGYfogOASdi6p2dmW+34kKuUKsyHZ3gdLhafOzSwUkPrFwS24As1m624morODO/PHLw2s/ceQrMyCGGgHGY4tlfqy1TsKhsKpDqiCl9SaTNnU2MZ7pAGrPzmjaPvfuh/Dj5MdsPm6vxLj9Uwk0tNhGopsXZfYm8BEfAEegJBDpNbU8II0LQMOHw0B5BsaYQczs+Pi6Pg4DlRvhpuWhhuaUVw+BsSbil8c2SSOwddfANkqVXyCBt2UXzA0c+LIlCF6/WGhzgSzSctbbrpbAnaRjarRKwHDsIYcgRuBTSsUZiTAUHdH2b1kVKdMSFpWUadFuDpBtRSUJ1gtt6d5nvt5ORVDcTd5w1tgGLrBasOJ7R0xHWtPsopJuwulwdKA0MVobQW1fl/YgKneZGfyCU/aElQ1R77VzA1yenFmar8YmpBXIjZhZdIrfT3VQEGfmXySI5b+qo8OjwCDqv7SIu0EQUfOmEm+a2I4EZs/Ki6VPy08XDG+SHyiPqm1XZCXhHAPdMHIF+QeAyG+jdqx4NE80TtGpFWJNEC5XptaiDOBovuJZAPETGWSsGK2d68+4JmebMAKw27OhoUANejvQdGByuNxsrorKuuU7zvwkRoClmBEyCrC0WW7TsBS0jmtSOLZjJxJiOOtJwM7V7rYDd8lErYU+Tf3xsBLv63ILwKto7DwiXx4iFXhtFU1Myk+ggM8rGDxRzhdmZWapg20i22eSZQfIw4VgJ6UyoYSPKRxx5NDh2IFcemppfsWVLoWyqRdaYaoOGqMBrY6UZAXfwlIjnu3UasP6QQPj8aFc4xH6ivE26aBnRGg0jXi9IeIUB8eIcAUeg5wiYV2IaAw2WtUpwEn6I1szREA/OHolq2GwSHyUYP2lpfK2Nu3KvVriXYWBOrxUmYrETpliRS6mJqUpIIpN9L+DoLrB0GJnteYeASSBsS2Ib61XCSomQVVmMaxbLpjRLNGH/CxdxgZK3ECxVkmrgKGZseAQPBx5z1U0nJdycnRbBMDyq59FDhw8fPJRPwqkzZ0nFiyMOPSgb2S0WxHDAG5WNnpPg1tvuaLTjpWpjbmlloSH6dA7lmE2yFMxGs8UkLFiqU86WvsU2kI4BC5EjOnWwz5bS72ikzgsVUw0/VMubQQQmK3STbrd/R8v3zBwBR6B3Edhe03YF6mGaLm0ubShtFiWaloAnU4LxG93S1KJPWBsHK1sgtscdbc6AKEUJOsGXXlHQMAeLHohipxGwl7I7VZnzZ9vVVix7Z+hoLo2uDMaSjNnTbPak+z3JnWqPNc4QDPJMcRLakaCUMBgpJW+UwVI+bkYBC3vAgiyZ2ltrBaWkNRxxWi6O+cfq5EsDVC4Lu9yrbESl+YnAyE6+iDdYwh+h3CMJA7UEEs1icrow66Om5ziEt3B4pHBwJM9qYE5mhP4GQ6mFrCjmhEYOB24qgJXhoDjIhOrT07OFArOTosVqa7GqC5wAVnhT52M1a/mglY/Er2uS5RsnnQ28iex/qRPBNVTlhO3LUl7EMmTovCmD10SRdWJ8DHOe6lImhUsCd9HJb0TZX7ZY0UHuk9PLN3/yC6fn63OrMmouP5O0e3CRftouSuhZOwKOwF4hcCXaoG3VzRQmkmS8i99MdlBslpUtNLLwTEMyZZGpyBaeRb4HHjQ6WnmabuE5oxyuwgN2DhD2UpkELN2FYkHiHR4d4JzdO8/M0ORDUqwdimtLZVm+y1hpvhFGtjhGyCBuks/USpzkB46VC+MENFqMny5xqBDZcvptGAyj0xfjei6arrUZPaW9XmCiE6r+4ukbJ+T8Bk4KVnkwAXNQsSxIyhzhcoZudr9FDypv2EYfVxbjkGDBnFvU7cmR0sDw+Ofvnqb8XGmA84AJLwWtMGkWC2WK/uyJJSY43zDavuFQuFio3F3LczgwG1gGy7VCrsSG0cxvHsrLcYNNiDyIlsPgrrmFYq7VbqyElZEPfapZQGhBileqsDaXkvrsofFBpe08pWJMsA6BcLC8EBzYIhEjyJKErB/0RQOrteqZueVVIM1X2KpaFnRpH0JylxMkI7i5KwfNZhcuUgTzzuRfjfkM3FLuF6brv/fX//5rf/qaYDAnXYSYee/82plzBh9zdecIOAL7BQFrwvZLbS+rnkpkmhIys08nH3u0hiG+sWEGgpP51bqNaBKzgLrV0X4gDz7SyPInVMJKG0Jycmg8lmih2Aijq6iXwuaivhUjWT1aMyVQW/B6ixPmG0M5IVfWH3d4aI19rRT0qm2zL0VKGhKy9Qd8ELWU5CijELRHhyq1Rmu5keptTE1mqyy6GaxV5p90DpbajVZ8bKIyOVSoheH0aoPVw6ynYhyXCHrAg3jUL6o89DO7vNpqVg9PjsQsHV6qSeGyDkrMzvjbjSozsfJhU9ZFyUeep3BzK3c4qsvWILqFZxIUw4SuA8mbiWwMglSKpOj0SGuYW2bpi9AsdvWS/T4Qhp7CzGq8FJRn67klRaBzSKP8GNw5Ao7AvkIgaxz2Va13sbI6Wzuem5+htaWhF5aQDSs6huJ1JQv4jAFjbrUxYGiDELtmEe0R0dQ0K8G2LNjsARsiZ6nugSf9SWzYbwpWnByfwMiv62sl+3whrxwmo7QobgzBU+u41bj2+DWHDhwI42R2alqOM8YOr6uc2XKkWyq7YXMVDlm68T73CuPmubOnQazdQD0WGcic6WyYFqhjOgqsc6lS2u3Oq8tfZEZ6KDPXGLBgLjquk9heR1fU3fciKlt0Ap2AIJMEZBL42bm5RpAsNxpnZqWO+iPhiwhE2vR3svuCegmOgCOwFwikre1eFH11ljk2Moy+u7ywiMqVtq0d5gRrWmT7SOVldDCQk46SthjPaaVlXyv29Fh7KUQ2Yzuki98cU3igJWZ7cZstke083JHvNQG6sxsfH2K4ndlD0AaMizwMWuq4pRBwtR4sLMwVcrkjB3OjjPBG4fzcDDFF89Q6J6jC3dmp1XhufpENRh7ygPu266tnT58kPpO1oC2A4NNqovzLWp2UgEmuows8upADbKQfrAxAwMvLEksJuLtGKtSF0u90uFQZxV3sGfp2w+D07Gw7V6yH4amZmvXSEkCUsWLR/Xe6fM/PEXAEeheB7oapd6XsI8k4ECmM20tLCyArdCqtfQqy0lB3Eytzs2wdsKmzkAst8RoBK8/YI44/ytpmCJhMme9NcjQmsf/uoFMzb3d+SG9FD5akN4AuvlwXAqZ0mSmVMGgcMR1qfjlo1lfHhmWgvpQPRsqlxsrKwopQZlbn7NdmUCy2A2zaw4Ol+3/xUC5ozk5Psy9HHrM1qqAW2k7SvRu7NWAeXbzCJKZ3gl2B04sln04HSF5EB0S+tV7yenbXyY9AqotFAbqlvLOzc0EZKEtnZmYZuCZQz9rg3aME764snrsj4Aj0FAJZk9hTUvWrMKA5OlJgoNF2gZC2lSZV6KTT8Gc1kzZZVCIWLEEVJT12EGNrWwZYlRU6tFEqVSBl04CNLmx//6GhCrdkQ/Is1x3wiKT8IbOVlmUpNDI+MooSzKHAtrmG8m+B4nk2PbuQxI2jB8eJhuF5YnQwCpPTU/Mo6dYDKdoGWJoSlY9oZ6bQDFGXB44PBxNDlUZ95eRZmdqMM3M1caFP0YBNiq3VlMjDw4OkoKcCmmpL76ymknzSzCzL3b0KNHy0W6UEDOOemp1t5Qt88DAKTgg7Q0s3BcGIv6Mvc3dr57k7Ao7APUPgCjZG90zQfkk9MYayEy/MzyKwNKfYHnVyLrdgbR+pi7SzMoZa41AgGQOWMFzKbHaj17Ux4E7jzD4k0BKapvGRJNkaM3XlulUvtKDMIGVDFROTY+zTbFuBUgMZ29RTjRnaPDMzxYTfo4cnIVBqc2BouFIonJyaQa8TzmW2WA7TAFQkNWdbDsJOnVsMC+WhMlOogxuOHcRqfcfdJ5WQZFYVEeoy+7lrHfAWqsnqcfJnP3Aszyu1qiqXaWXJ8IqyrxUr4shrjxPpb8G4Z+cWG5wc1U5OTc9ZbyvkF2Lqr0R25wg4AvsFASfgHX7TYxzoEzD6uExbKnqezKoBZK5qiOzwmRl6oQRd65yYcsiuF6bOplZlbY7zOegsMl4xWW1DEiY2bYGPtlu7tR6Cip0lRxVNWE+EaRdiYx6WkpkOXKLDcWpCEsyxQWbQnBgZoKosGh4uFyuF/NySnB/cFE1WIGAYWAGwkeNgdmE5yhVKOVkZfXxypFLInZkSpVBpWirPZtF0NXCZHOa5IE8BXCxHNzKmTiqGgTv2BBlU7nb6ShDGPt1Pdtov1Rb5kYSq8VlcWa1zwEYznl9aBhzCdcI7/RQVZ6fL9/wcAUegZxFwAt7JV0NDC1sOlEqjQ0Pn5qRt1UZVG3/YEj7WtTh40fBoludXRROGJybHRIxmo1EqsByJzZVlSo5QFrkNDMB52LThOZTL6UWZ4gu7sGSWM3Zxsr/SeRQlDy7fddNw2n1AUDaxsgHp+fl5RnnNwa30MRijvePOOzFB3/v6Y4Qj5w2HD7XrtZnFxVVuTVBswdQWg3w7weKO9467T7Eb1n3vfT2g3Xiv48tLcydPnUMDBpw8y4l0ijjq/tjYGH5RwNlUiwMMYllTdCFXyBeqjeCG66+LW8277zpFyXSDcLwI/Ra/4rohTMJ3y6lSrpOhg49/ZqZUGSgPDoW5/LnpGURCmFQw/7+4Wy/A83UEehQB/0+/wy8GQDk3F/pcXa2h79G2CpFCkNLKxqiR1voTAD3LblmynkffAvGEdDY6278QRdlIlqOesDmz/9fGeDt6f54c1EQ2kxodHoL72Ywa4YnDB6ngNjS5+ZWlXNiaHB1AMuozOTKUtBqzizJlGrVPHARsezEyOKwFrNTieiMeHx6AgI9OMA+rzYaUkrOuFpZsRYOlQKu65XLRK+CGKM1yJAbxzFSgEgrqZKh81/Ul3t13urbIIOVXkc8XD0we4rWyF2dqSUAEkVwB3X1xvARHwBHoEQScgHfyRYAmrejYyACW5PmFJdpcGn1teXmCF/ZVTibQeIsjFtiE0g4dJK0SjRpr16RKx4DrYlnFccYfBIxavBZjR32qpqa/Cr6sRlKCcubk5CRV40TI7MhHpEI1X24F0wsz+UJ85OCwpTo+OZ40GyenpqyfYfST5kPdlQxnF5erzdaxQwdQp689wk5i8dTc4mK6DFhwg4A37gV9STpmY88w1dTRnkXwtbcg5esrMo8YrM23q1eZJ64vj8IwHjAZ7dpj13JgVKvemJ/vlMysM+LYO+6E+bcj4Ahc3QikTe3VXckrWTvURE4NQtOlqdUNoLoLNy4QrZGWlptqTQ6cqFQYM5VbU3bTBErG+Mtl1vWE2Trg1VU594kDkq9gWw1xiOT8VibGxygdAqYCEspiJPWs1IPFpaVSMceJhUQDhENjIZtZn52ZQ/1NtX7ykGyU83RHydkF0Y+P6Lytg0PBQKXEUcrTCxpL46LCYn7fAMsl9WGMvcPDclyHrddSoORC4esHtuV+dx3F8mESN6P7WvbizBzblh49eOjA+AQnUsyenVfx6MTIYcnMxJL47hwBR2B/IOAEvJPv2drbybFxSAICtnFSOAbSErISBhIKsiJRDVfrHFcAAUOx6oR0Yat1bTBLb4lTqzUIJTFrkDBHQ8BpEsmS4J10InAm5VrGIhXFUhwD0mZLlpqgMjMveimot+PRkQG6EsSj4mNDQamYn1+GmoWPZVKzxDYEJBMWEy9Vq6XK4ORImaFdEh6cHGPS1dkZoWibvcwkLCVg+ZWm1bwk/bI7ZoSpXIoyUzm5CfASsAdOZjfn0sLBYZ4jGlvxgZGRaw8fxTN99lz6P5DhBwi4E3MPBPUiHQFH4Ioj4AS8w5DT1o6PjYZRAgHjN9JhQwmhAEyRSsAM9XLPVKNavckWxqkGLK102lJ3yyQ7Yek6YHvMDGQI2I683SR2d8rt+zfLEEm1Ehy5EAsBc1qGzPHWqKal8/jM2Rl2rDpy6ABlQsB8GNfl+EIYdKoqo93a++jAoWln5tvVemNsYpLRWo48gpyOHz3ChOATp06b4GSrI9+sA15XE+kIXMTJflLM1pYYyKmib4i9WS03RNmhW0pCAOrOC0cqJJ+bnglb8aFxTO7H2D8MAk6rE/ETkZ7HlRNuh+ro2TgCjsBlI+AEfNnQbZ4Qshhh/pGqicSwJjVV24SGjYMlLXNjWQSMJxsDxk9jvaYBa2OcrQOWp7LlMmtYZAz4EjxE7J10SC6bY4wOirTL1VWGonH8epCRmVInTt4dFfJHjx6h+sI0SVDKMRY+wjLoM1NLxBSTMxITW0mbC4uJUXMZVJaMlJ+uOXoM9f+uk6eIhRZLkc2YqWesA5YYqQYs3os6PceQIXLiMwYspofNokuW8jp23XHusQlAYXiEgJPgyMHg8IEBQEEhzsTD08YQ7c4RcAT2DQLatu2b2u52RaEYrK+D5VwTEzQH0ioVwUlsXpGuQFLaZJmRNLvCMEzQSWyMU3VK9CRO+eU5z8QcSdp8LmpziKGSBXFq7ZDdkssFWR2M7kh+urLJrN2Sqaa1im775YqYXcOkdqsBrHTKM3d5BNW2kKw0Q4Z24QqL0GizC8c8i40OjI0iFafu2WqrgWHWRJdmZldFDrRgvuSDzTpohtHyymouboyJ0RonE4XHx6TjMjUtGzRqdcknLCUxxxfiZBa4VoiYwCJli+OLunPeYLrNJKcqER0FuJjU2djSdtBO4woFkoVMkFan2VmvSAq0Mu3aiZJ9k6l9spAteKTcFm+T2kfMeK+3g6XlBabIH6oEExX2YWkvryyyhwn1ZQSYaOF522VvoRCP4gg4Av2KgLZB/Sp8z8kNMTCce3Cs0iwP3TFbp8UegI1qrTBsYBjlDByWHLEWpxG0V5N4sBCszszno1y5LFOaxdDaaMC++WSVs/8kPobLpkwPXo3DaRlLlTW0J6YWByeOVaK4nFBWzLnBcJCu82GwEf0ZorsAhWwJLRRGOYiQn4X+MoQK9VBC9mcuVIohXHhsOBcPH/m8am7EQf0tF4NP3X5Xrjh4/cFDxVZM9VhXhRADMg48evL0EoxXjKh40C602rl2NUzaheD2kydH8s17HxwGpVZQgJwe8uBr46Rx6tTdhFANmb3VaBUWF24YFSjaHI8c5tEac0kzlwirKf9DtyWWHeVsoBkoIjlxeSIIrp8sLIeVO+ZFEpJpdWS5FB/yV6ezngBN1GT9SFz5EGQfu+1cNVEncZrHxb9YPB1hC5BTHTn8+fYzC9jTJ4YG2fnrvtcFYbNx4u676SJUySQqhnFE5Ey4i2fsTx0BR+AqQMDapaugIj1RBdBEHRsdrNRiVuYkrNXJcdivaHeyxTMfSMPYhX0JUQVjVY/SWb60/KRPWpFSIHcYo0W5I3GUg8xJyHPVgKNyPpSmGrpNdMoSGcvQJy41uW6LJjRhdiFbCldHLlou9+yYQQGDIVtc5etBYbYKRYk89Bt4utpo1hocGDzMEiD0VtFQUUNHGTEush2k3DYkPqo8p88THxacXVzKt6qHx8SWjhIPTbE7B3uYNNqN2RWlQckJym/D+qiHUKhMUyI2twKGZChfIgYQS/WlCL2iVg/kYg4dWtI9Lwk2kSwJMckmdRKkleQ+rThZCqprjjg4u66Fbs1HKp1/RpXnqvUkF44MVyDggSjAQ6VmVkRm+W1Q5OUVsTVBPJYj4Aj0GgLWaveaVP0tz9jYILOHGKxlSyZZgZOXxp9v1dIEcFQ5tkbmEefdcmsnMUid0fAgEtmZMIIUGPvkI2tYdFdFbJU41iPZGLDc7LajtyAdBnEykVttv6Ojo60knluYl1BEZjR3JWjW6vQmWFqTBml9Dx+YZEcNJqMZTzbZ2FkdOjt5TU0x3Tk+cugwYViewYedtrBCt5v10+fmiUBs+hfMgqaINb60LC58BV/gQ2hZKh3m9DykNDaZ8JSr5JZRneS+IXti2bjzhmIQSkDYnqOzID0GcVOzC60of3BygtdMF+HQgclmmDs3s7BW/Jpve4V4bEfAEehHBGhr3O0kArTQ2JYL6Hlxe2VVhvc2ONu6kZaWmNUG1sd4sFKRhhdK4Es+eqfDlQweQwVMPGa7Sh1TDrpnQVvOtO+76kSaDiNRFBtD0iEQWlWRqcXUDN2IeKBcZpss4TjV9GHBQwcn2q3mzMyMsGtezl40x28OWKZmZlFrD0yuUR0+5lFzbv3dJ0+TB5OXYGjMA4SbDJ0MLvFtkYeHR5FzYQGExQmp6gfB+GgfQB+IXz/m6aLmzuMd+KZEStejKUqHDx7AJs8HAm4HhbvPgYPYOdw5Ao7AfkOAZsHdTiJgVuWRoWFUt9mlztYKujZGi0kBp80VAq4zmVioi0cpj4rKLASBwonyCQEznlrKF9qtpFoTjmYGMuo1aqjktivciwAd16F2hGasmjt4EQKmaouLi8jP1DCuZ6dmCvn8oYOTad3E3C6kdmB8oM1ulLOzMoMsTzdCttzEi2NEm00ZB4rFobLEzDPVWat9/NhhNP6Tp85QFiu02hwhlMsbAW9UUzWfDRcTXeCTuegjQZSfm1+QSsgOoGIYt49IIdZmrR5pMK6LfT37aPoduahAFEPWUOypqYVmWDiiJzby5OihCW7vPjuHX2TWyOl1R0r3TBwBR6C3EaBlcLeTCMiyGbiH+cD5/LnZJZksBE3GEIDwiDb50hzT4EJTDJ3S9g9WZF6uLLORpGkzjI8PHMEEX9mLI8pVG3JI7soyS2ti1gFT0E7K3Z2XnjCYBpjEepOwKGi9Bsw+Xoh05uxUPoyuv+a4xTLBqSBzsBgSXq2xaEmekBa+lmpypMR8m10mJ8ZGGPoV7lGdGM+1LGSKgrtPn0ZFZnI1PCkasEbY2kX4nYJIMjg8BORzi0sdmISD+WzCvsQA+U68TQq6yKNNYm8Mkhcr5ULA8+2ogOIbNYN8Ozh8aJLvk5zaITJLBHeOgCOwrxDYTuO2r4C53MqyaoimdGJsHJXxzLSc7SPTlIVZYQVpyHkqDb4sQQqqMgYcs2MUt8pM0DFRhKeVp4SASSlLgaOw0RQCrjXqaMCckHS5Am41XUYIlCRyK0MIrY4Oo0/Ozy0QxGGLiHSaDZ/bzWNHD6Oziv1cGZOYw/mgUi5Sr6XVYEWmgMvGGpw9SM6nz2GXjg5OjDODWTJn6plaZY8enGDY+ORZwY150WKu1w6NlL81x7m7FE1ZOgYcLq9U04oIsKr4ZrqvlMzyKko2MMUD3nSV9GO17pRKXBF0m04KlVdpZzKdnZuPo/zhA4WBHHPEgkMTo+0wf3pmljgSQSPrD2CbpXh0R8AR6E8ErOnpT9l7T2qaaABttoLhygDSzS1xsoC2qHriK0+NDKwxZ7lPS3TKuJRu9WTBQgNWM7lXOikUc/AQhlxoiSN0oDQYeXccnQQRwLiguwjUX0gCbmPjTFTwpdUViaMroBaXqpiax0YGbfTXxjOJiWF9qIzokRicmY8mVCSJ+OMYBozLo0ODOuuMOeJN84wM8bg9vyg6MwTM4HHSUfRBYwuOacWoucKVemhjrtYAM+7N+kDJ9pEgsQpLeDq5OnvQKSV9C51b/bas1wVd+saYFTkW6YaEBTYzKYZBMcZCMAg1LyzXVcRL5+MxHAFH4CpDYLNW5iqr4hWvDrOeR4dHUGkgHZkCBMZNjj1Cr8rJMcAaICynS3EgjIGKDI7mimGjWg9yKIg081ERRiKqLmCFfYul8tLy6sKqKJHsRVXJs2aY1pxDDdNjCneslulypiw/4TPEYz+qXJSDKo4ckrlRjOyKuqux7j51Lm61brj2IAuCmfytYksSGPfaa44h8O0nzg6OyNabxTy8I2uQZuaxvscHx0dZNk0XhCFkKYLMR4FugMVLnz/NSRVBscz4eJmCcFaW+kJZ4HUh127A/e1WcOzocUqcmpmxudeSRPEMmvUGWbNfiJ4IudqQbaf50LOxLBmcFo8QMkJ1OZm7vX2XcDYiPZP8HafnomIJvVw6HU2xclx/vAiSi6vVM/M1Ikg3TCR05wg4AvsFgfVNzH6p9e7Wk4Z6YmSUtnVhdRGikEaVk+S72lbjEprzhgyhJkVZaCMOpRCyY+oVj1KDpFpoUebQHTm5b7Uq2dhht7s3BtwlqYrVGTqFKZFTVFtmjYU51DnkXGwEdfT4iJFsiZwrlFTVZZZvCw14QlTaYH65KvVco1BsAyvMkBofGSY3XUgs3IYfxR67NNtCTc2x4JllWq0oUvu85L3mLlz3JB9hgm7RB6KbgrEAu71kTVclV2il+2dGxYFBAiHmJTo8RZlcxifszNNOl2Wvldbt08y6Ay7up8q6Zpll3AvLVeqCAZ//cvKCY5lex8FZBC6uQMD6A9H4F8/SnzoCjsBVg4AT8A6/SmGZODh64FDcbM0sztOyiwInzEpLzDYU0s7CsUSjEa632B8pLrMAVh0zftu6A6XcEUNoQbSwgXKpnYSr1frSqqS205NSElLulkJ3yl0oLyUyHlITJhgzEXphgWlSwewcJve4UiwNFURkNN9UO02autJmgq7D2ZlZBryxAODYAZsanZlaCKMC04DRBqln0kIrluRkfsN1x4lz+92nIeBmm3Wzso/nRtexS28M517M521Ie2Cg2ODE+xqbaOGwNmOGaMp+1jnkihaqIqZtPEUtuhVq69+kOZNY0ithpkHb+dKySbDaDs4tVHllR2RtNE6InK29jh48QOCZuZV0sRShnSQSy50j4Ahc1Qg4Ae/86wXTifEcK3dnF2UNTNq4y8ZNSlGdKxpYtcEGk6wDTif6hhEbKzKHSyZhyZ840Rtt2JWtplarcnrSkJ31Y88vQkUW4bKuwg+pM+5JGcj0cp2DncMKjWxTc6Jjjo6wnih1zbSmcsDRgclRTNBT03PozsBiO05RszNnp6N84eCEEjBzuqhFZ6XWtdceh61vO3E3NMwAMHRIKSkYnSLE9r6p0wlWSbPKY0Cin4OFGe1T+kBo3IWisq9MHGslORuex0/mfKghV/Clo9Cm7Au6LmwuGKfrAbVgFnwuOD2zgGX88OSo/JeTgXZ5xccOTSSt5qnp+TTTixTblaV7HQFH4OpAQBoCdzuKgGw7PFQRrl1hza5lLQ28sA/f0saqBgwx1+r1MGEMWANpkdmzWOKTgb4XScUCYKypHC8fYo+tM6UoCe0swlQDtvx37iplruXW5WUVFVQi0gfDoyOMaE/PzuCfmltgidThwwepr+m+WjmewLmtsZFhTPHT8wvckxQA0GdXmsH8wlK+WB4ZlqFfKVC0XLFvU97RI4cS5gafm1muYWwvmj6qxUrUVALxXsAlrQS9mV5LQeZh1RtNBtbhU7o1+RIWbjnvgJeSHwhXg+CDn56aWkzHfq0I24LyAthmUlyg6E2Dk1hU/xACXmo168x8llj0TTB9tIMjB8aZv3ZyaoEfA7F0x9JNc/FAR8ARuAoR0AbwKqzXXlaJAV+MyjBHrdXEtCjNNu26cpc0sh1Hm1vF9BrGsjc/Tp8R2Zp5ia4+holFA07Car25Wq/BQKYBm9aILtidZyfvnftGpxQxTCirRGCrkNGA4UsWAdO1uO74NcLPGo05R+LkgPn2xFiRIdWFxRXriNiao7m5uN5qDw2NsCdyao+FtLUE6jIxMVoolueXVqdn4zAXpQSclq85S+YXqjQSyabRRCHngaFhqJfhZkqnaAwMqJ4YzKVbEQZve9cX/vV1r//YLZ8gNh8JlBcl30KZaYn38D8IuUnVeddn5xaZSX70wJiM+5uLg+OHJuhinZ6Zt5liGtkE6cTxb0fAEbh6EbiH7cvVC8xl1ywRJa+Ul3WoDGHON1SZFROr8YI27Nq40yg3dHvkYtdL0Cdd94wBRx0TdK22zIpaW+EqHCRm28sWc9sJZRFySnzpGPD8EiGnWLPbio8ePYo/R8110q9UUkRro+/J+cHLq6uoocqCBE9Pz0a5PGo0KKEHypRl2FrX+8Ldo0NBZXAAhj53brrVlK0oyWg7FZX9w4yfBwcHSbuyUlUNGC/ARiHbiql07/7AzZ/9wh3vfu/7WSKFo347T30CgnA6Iw1Ts4sscT5ysJJ1HqjZ0UNDBLIdND8GoX66IZLEnSPgCOwLBLra+n1R312vJAoWZZSiYLgYc6zR8rIqPKJ7iWmWOUcy7Uh4SkiF0waZEAvrkKa74eVWcoF6WP0TBaP5diGpLzfjuSYG6VZZZy4xcIpBF0bhFQrfMPda9DZoXjaNNBVOJzzxbNtO8iURuWEWlwHLnJhxmaUcy3mLBwpxOW4t1ALW60wtVJnrNDkyQC1Y3mrVkE0lQniuMCI7Y4crrSqnEikwERVYWF4tFvLDFSwFOAiYpVhwMRjJEQXkX2b7jiCam1upc16y1M9qKN9BQixC7LOeMkVAqi9HF+NDFrgfC3+rtsrJu61250CqnEyJwjJxx5nZaOTgB289OwU9Er+NHGTA0YHqpC7yElIopWK8wrRci3LpK5mEEQuaUXBXl6uFMBodlq3NVCWO8YyPMhUr4pH0xihN1yVfOluP4Qg4AlcFAtIYuNspBGik41yB63AYXDOaL4eDszPtGloNlIBlNmzlmisF5j7HMG+wvMR2SAOjFXZjECJh0i+0l0vSs/wgaqiEhUm8obH24liuOZsU76ol5VIyVpEVqbJ9A5zVJhajp7JxstRC7uAzmUtNEXzIfOvOJCG+UDj0I8oa1YmYmRQUh5GmEjZGkuDhR0rFlelTC8lsENw2tVxrth5472G4M8fsKURrrkb5djUYbLLQJg7uNVnJDRVvO9eEb8iO7UfuODmbD2vHDpepGnPKJGcO+0XgpcVisEQ+1113hJVCN3/ks6XShCzB0gnDVFlmSOUQjd2uZK4zIebIVupJdwHwQCBfYuiXzI8cPEBPaPbuz5dzrWKOWgSzK0J1RPnU7Y1aWLprJTc38dDXvPdOMqgEy+TBscXQM0IqR7ZFYnGISWl5duYizjYchIpZoBgszgftlZWD4weHeGNIEMrLoUeAeBMjE/WFhWmgpAuDUqzzs7ZRhEd1BByBvkXACXgnXx2NtLECKthQUVYdMQMIeqTpbzGuaM160qQZJxoNMWtWC7rXsdEJ9lgI2Np8QoRRdRXscD4pxmjAwXyddK0yLXWnIDykogTiq94rj4x1LU+TR0O3dCFV6pARSpNZ2ZYfRSJakk+aB0pJ1K4vtXKn2ZwrlM0l2FES4pSxU1KJDtlGq+RrEPUd9kvqsyvowOLgaMZ3YUOOaiB3yqDnIRmjWxfodLCNRuvgwXG2GeGs5HaMAUAGZM1JHUWEzr14ka5TRQmH5BGEwx2k71CWEyRa7XqVOKoAMzYv23pgcv7Ypz+/Wm8cu+E+Z1eTT5+YImmkhms8uTwrm7UI6eeoT15Xd7FrAlzcR27afQkWFpgaFo8DlJKsWD9C6ianAh8YZmVwuLhI74I37v8fL46oP3UErioE/D/8Dr9OU2Bo/ZmpxISppaWljD+kJLEbGzuwq7MQDxre+e9gQ0i6DIkx4OVlCMvWAadxhGjg4KyQtaQEZaHbrySUo+qsWstJLlOqGLGWHKOhsXF4ZaVau+sUVBJPToyhu4uz8lSkLGB8fBwcmDINwwghhcGZc+fCJDl6+BDR250pSfJdLKOckvO9rr+hWZctr3EcxWhZSfad+mQee0S2650Y7ok7XClGSWuBXUDCUgjB0iEQK7m4j37yM2yS+dhHftlEJbrrjls/f2opyQ0R3m6JBYLhWDFa6AaiqSFaU13ehZqdnpplGt2BiREqk74x6olZIQgOHxynICKgFLtzBByBfYXAWnu9r6q9S5UFzQ5HyLF9lDI7M0+IqlHcoeoI4DAwnFGFGJKIcUqCuNU3ASN34hKv4+Q0JJYh1es13ctpZAjFMjNVkv15BNRJeA++TYw0Z274NEXNpuRoeLTA+lxMz7ffAf+2OOBWx4wtidZDcUAyPgcmJqDDubk5kkJFZMH2kKwUOjw5KREUEAJ5RJWoJvlfcw0bebaZvMRiJwhYiswyJCodA2Jt7iKdwQy3ydDxgWEZA55ZYbW1SMU4NnKSdD4ITpydHRuqPObLR7/iQfepLc198BOfq2JpT9pYiInKPqDQIdtDKvuKaGoMkO/Lc6en50Hs2ORY2ptg7ECGvGVCAIFslHZqau7ycvZUjoAj0L8ISMPkbgcREFLR7CYmZBMo1uoAMayRUgbUAc3oXRXztG7rSIT06Xo5SIVrxnocYZKwbZbs/5zEI8ODhMubsxgSSxzG37WM1j+yCFu5Ion+JlT91VzhVTKTjz5jiFlsp0PD1UbzjhMn0BmPHzmoSdayl1Fv5VTCx8fHIFEW/lJ1qIw6Lywv5cJkfFAKyuvOX2KCVm5stGV09OBAMFAp0Uth/JSDKMjXanMe7xrld8olE3EcYCET1LibGK5EcXN6pcFkMdZKMUQcN1aI8ckvBAs1mTh2bTl45EPuXckl77vlf2R+eRAxwa3dbJBWzOiSGVVR23mauUTalhNlmjVIM/P5YunIgWGs2jKjO2RCQEHt0MHhySF2QEMDvtwStiWOR3YEHIEeQmBDy9lDkvWvKMYWqQas20VRFwLhY2E3WW4iCuVKtQpNVUq6Ctg4mavwRMdpRkSvVAa51mvNjgYs9lVhIyIoKWnEnW3AEdA+HWEgS9kyEwYR9X14fIJTDO4+jQ26fezQZCqzyEEFRBKRjtskwEBtGjB3UNn0omxdOTxQYetKAUKnNWHrxeIL4bVD2SYZRI5NjkfCvHGxsxUlRcgqJylCsjVTwcY6671Md1Y3IRbn9sxyCwJWuGIUYjK4+RNfCAoDN95wrBIE9z82MDlU+vxdU2dqxCE9Y8ZEF2GEeKUKVuTGoqyIS15t+hYaMEuaUXY5CZj8eO/SQwHSdnB0YhQ9/+S5WUVDCnTnCDgC+wSBtdZ+n1T4ClTT2tBsDJgSLUTaXD6qEhHCzlbQj221KEqxRVJCtYgmKgEM+kLe1WqVMeAwbrNzFhHkzdFmW6rNanXZr1a4LZt/JKqjFCKy5vIol/ghJwiYEAzLTF8+BMVKzaxiaOEQpViW5RMGk2NyLsX03DwLkJD37rOcsBgdGBsZINuWzFVu6+CnlcJgLSEYZq85fJCzhuOknZOzGNZqKciICBdxzBqTSVPkM1rhaIbmQk1mhCm9xVGxuNwI/ufWO4sDA1/20AdAwPc6GFx39EA9yX3gltPCuCxeUp2b+MrjfGvSixR40Ue8WPI5PTWNln94fKDMxDw1xRPImx3IB8cPjnCCMhEoXZd6XTQ7f+gIOAJXEQI0U+52GAFTmRjcJV8GbrtyB+2UHmjUmyxNZe2JTg6CUnS2k1CLEI465WKdqlMUSmk0mvUquxzLmlnhIeJkUXWucpqs64vn233BGr9DOULDqWMVL8JBpQRBHsx85rZaZT5zPDJg88hEeFN/LQ08TG4DA3kSLS4ts86VhBxKn+TyE0MowIzzEhC0YyE+fLawCr2XqUkHRyoF2VSyKichay3ISvoofLqksoI2XHUgWbAZKIQ5OUUqYtqzZE5xYTQ7Xzt1bprD/+53wzhvaDQIrj88UawMffyzt63KttFJ4fzDlulO6Fj1hoIueQtWti/XwsJSELdGB8pF7U9QWTnIQus1McypSPHiIpPcZeB5DfFL5u4RHAFHoM8R2G773OfV3X3xARTiqdaa1x4ZgH1XcdqmclG7aRwVSpAIt4wBc0je/9/eewDIUVz5/z15dmbzalergISEciAJBRCIJILBgDHB2AZjbOO7w2ebO/vubN/vHM722fwd8PmcccKH8REtMIicBUhCQgklJFDWKq027+SZ/+fV6+kd7a6ytLuSujXqra6u8OpV9fvWe5XKykpRDUEwARo2U/Z4gDitFcE6YuXQgGVjS9RNQJ3R0zJm8IAmoAogw3QmDWewqUv5TBJdfA/BQ44sNhd5gpH9+/eH4CDHNyViw4YKPfKe/wKmXtb8kLGslpJzGjgXodjj9+3YzQHJ1s6WtpzXP6i2H2puUHRlYFFW/fCT+c4Gs/k7ccRQT7oNZTTgk7VQ6WQuIUf2ERrukP8+ypUN+OzVuoP6++LtbWznwTokmfPkC8QSmRVr1hcXFVWUREuDrHHOAPaXzzyP0fWFby+VExB9ePjYgQvCpERy8Vd/8gf/g7qo623NsiVIOOCXgxiySaoLHZ4Vv6ajlo4E2fwrir3k3XWt2uU6qPTdwC4HXA4cuxzIC5ljtwR9jHJkKzzV441QE0EpZi53wIU5lxChzC9pzi5AFcNOa8Q6oUQNtm3RBeUiAMOooDWG6GB+VrAZabUDmXFZGyRsL0mzI9uCxPbjNHHyrUKwz76gULFHvdghMpfNcrpAVVkpQ7Y2LFEqc0EtIIkngQE++MCZEk1tbaDzzsZWehnlxexIgfYvGK1GZkIKW0AmIqatmqg/6El5srHiMGuMMQt7GAwmRE6WK9nl6iDOztb8gUdqgiBrH0PsgXQuS8ZCGswPhd/fVNfe0nDWxNEQgBGce3nEGjKwhjlfS999LynDsowLCP38pAQyQM3iKCmOXUzxP6CLWBhApMTZDHYCSRDWQLepcSEzm0UlriyNYG9vbImhAQud7uVywOXAicGB7oXYiVH2o1JKVUdVzJaVlZFHc3MCAzKCVWRrHjZxMwYM2nZZByyhJCA/47QN0QE/i1uBFpkebJDATolT/ESiH8lLuhBmCw6TqORj5yhUCTkASXlxNAjK5rID+1eBogZTxDxtxrmJIhZbJxZLgdPZ3O6GFpBzA3tHW54B/fqBaQESYiGWn+6KKM68pShEZHh4xIAQwO7LJlCC8eEne0KTrrJSwuovX3Ay04spWMZGDfOIhfKNjaC9VYhJ5fxtOQaA12da6y+eMkRjgOmlAQs8ZsuO1xcsZf6VrA4z/QZBaIrLdGVJyU497zigv5AYz7LsqonJ2P0ry00cg78mRWkqomlzJEM/Tya1bWd9fqz6gBJ3A7kccDlwrHPAkSzHekH6Cv2Kl2bg0gKAgczGxkaFSBtazXgtsrfNLEPCOKkAJlLfKL+OAqdJ4U8l+f0cK8TClVxpVDaQkp9WHRsqCbjIRZodl53ZHn4db/fvsjNxAoIWZAO08gJHdUV5EUcF+rwD7RPmJT9BK6XKhNECEbhfvypWBtXvboSazTt2sf1X/5oaWW/EM1tt0LEQAMaULut0AWbmRvULyWba6VhTMOBJ6WYdAr2mOHuOAdsFdQjl+ArDR4LySqogk25rkdeA3Xs7rC31Lf2i/lH9DKgaJpLp1AmjglZ6xbsbtsUsOcfYjEObwyH97MiRV7qVAEODBNn/BQFQU7ez3pdNDqouNxGEQZRRmInL8GtwTYWVjG/ZvgOPzsUxcdybywGXA8clB/Ly8rgsXG8USo3PmjPSH62QsVvlsrGMsgeUyFjkbywmZwuyyUaeTCBOTNCME3ayQhMdRVnOBcrmSkvYZ1qHD008kxpqXD6RPf4eQu2SkKJcfusJo7EZ6JVMjLEbhCorKRKLcCbZn30kuHKivEmPIZ8lTnvOFGhdXc2e1rsaGsDc3S3t/nBRFccUkhp0y2AxWy8DwEyOFjgScEolmB7F3Kja6nJM3JSaHLVPY1jUfWENGQJp/MMNapIdBzd5Msl4mwwzMwK9YOX6ZM438ZRBUVMFWMHJjcTHnRSoKS1qiKWXrZdeAmR4cjEry6SsgolRAv97z1qy73yZIlrbdjUAwAOryyCJid2wRaenSW3L1tZWbVUJW3sSDIIPLoPOGbrPLgdcDhxLHMjLy2OJ5mOAVtACactSYAVgpdhgJYqe/rXaZR2wNxwUk3Je7hqn/d4upqCaDGcKAAPYxcURPFQnlFgisAuEtglsxzysP9ow7OR4MLN3QSBmEGE5Z5dHkDKdSyX711SRv1ifuTS4ugXGQDexZVdVVUH8jp31jXHswJ5oSSkrqRSqxaRs7LBgsJkHbqZxMeqazV524fSrr7h00IAapnpJ2gAXGYNde/KnSymFEv4D6VRBSVkFu1HGW5uIKgC84n1vKHr26WN9ZttlAmhIjN6njh5mBYoWLl/XruzMJuhV6Fvuxo8bzoO4CM2PgvuziYHVFTAmbdb/Sg2mpSgo5QQY0K8y7M3sqm/Q8AeRgRvU5YDLgWOZAy4AH+HaU+ktU6aM/ZPUm5ubuYvwFnzyKlbh1BVKqLbyVqPh2sslOzKaMeBoGOwy4UlCEpQLaCoYp1S/w7zTMIA6g6EmJVudFTqzMnGpzIqEQ9FgsLY/+1KCs/JCLcR0MExpQBMuIbGMM369vm07d9XtsHyhcCQaNUfymfc+X0aOhmLkljXBBp1ARdApm5o0ZsCF08ZUFEt5Oy5RG7X8HX62Sxli8lYfPBgDttKJWEsjeNyUsNZu3sk09EnjR0U8GagkK35owNTB9MlneMORxave291i4JYzM3KyLpeIWhJJkxJqIe0s9/OH6MTdtavek03XcDaymdFFHNgl/DXoCwH9q8LRcLCpqbltP+m5r10OuBw4rjjgAvCRrE6BALObPw44Gy3CHJpuSdgbQcjYJQcFpgWbEbuxnD/l4TAkmV1kVwMvjMgGiAA8Sc38eMusXLRq9EX2lmDM2EYZeY1TLLf6swtj0hGzrfkdVAlNVI3hDC5LOnaOko9Y2Us9Vm04WxvN1HKireilEo9tOgiKJRr1MiXIxXlPcrJfecgKsSdzU3J7QzLqs8qCst2VTjImMXP+gRfm2HwQhPOmmpqwQpfoWqacnBjMpOs8O+COkgkh+Mm944JQg+Okxo/VP7lsqj0Rx0S+u91qa2n0pGL9K3xyTpLmyBowE3LsyP4s76qrq2tsFV3Z8rDdiayS4i0dDpIyLIAnmh1IzNRq84Mwwx3J2WEULmY4Gwt2c1srs8xK2YSDgtF/ENqFahx0AvixKQl0tsTiTe3KNebHZzmqAzL4GT7afQW7mJqNaU4FWYqTdqW/DkrsOIV/hP16abDCe/6Npt4RMu/fE38L6Sl090Tex2MehTwsdO+1rHsEclqCOvYayX1xCBwQ4557HTEO5BDW3mRr3FccprXWVqEctq9ramsGsdDGaNZpzhfkOFs5/XdbazoTLqmuLEPXEiNrOiPQ5vX4fH4CZnNpM0Mo4/Fg/fWVlYQ9DQnW/VQW+QUwAhZnIRSDLt5QOpMJqJFWi4GYl+9HdDUBENyKVgdQSAIqvEhYRZo8vhnI81p+mTHGf8ZQf/G1G0kbwvkxQYwC+AIcNuhjO0n86TAIqIra7x9TJcXfnYsufXdrJNE2oiLMwly2vOKXS2eDwSi7YYV9RtMlJjiVCwQ4wsFMhxaSDBDKrLM9ywJpSq1dPv0j1LH+yEbNYNBfUVVet3s3Oc5b+m5ZIDFtwnggSlCtPY4K7/dkMnDQH46nLUzTL78+7415b4+79swAhxhn0t5kLEzJyYY7WqusTjJ5srZMBquNVZy0ghFooU6ZV8ecOiqIkQYr3hIoKmvNWC1tLYOKI6UlshQZGmEK0AvGsrSaWgr5LIaaa2r6bWrfvW5bfNhw5gRgEqANaIdNWhRZkrHmLT0uScJUsVST+WEdMVttUzS9CMwbqQm9lDnilkrRUjgp2WE0JbkTgJS4c0mNOwGOgkNzkSwcYtWra14E6ihHQXgnZP5tYQJHlXgn577jOEh+wvQ81zoqQEpj0pEqsfuXwm++Agl8orFU2HGULpeVR5axohgFRUbKVRzOeD1sBBFHoIr0FN1EDJu6riWbY1PkBFjBq8ILeM7LDxGCnB1Mm5fVv0x49uSQ13adeWUgGHzmIm3JU78W5LaIbvNoE1KY/H7cpCWfmP4Rl+3Mu0QtxhuMYdwUGJbeAO/s3MEizLbs9iXzoIyCJ4cLIcKLgsHmRHbd1l1FVrqWLSINyBDaBCRNzh0yCKf5CVT5fWiQ9CGMJUBy5xJ6SM/5iYf47XGRlHgSCMKKQn46BU2JTLNlLV29xptqPW30EF7BoHCAic8pK9nOkQ/sk4UhYuaMKYnW5sVLl7FeivVIaVYoszkI1QankwlmUzNpSiaNcQXDydb2bBtHKPlwpxJZzsxoj7PhhhQoEYcHXs7QQDdubKJkXuaCseZKSRKtFx7KHDYoxCmDwUWRYoK1NbdAc5AdsK0MBgASC+sOIqYsUtLOFeoIRykRP97TKrgrmYZWc+uIaN7w2OHTESrv0sSce967R/46lCuB+yCzS9XvSZ+YUtyroyV0y09pfw6L92AorZUfb81dXHu8Fg/3OmwOIOnc64hyAPtrkKVBKZ8VqCjxhzyJeMt2wRMy8WBQbBNTco41rt5Aers/FSsKGn1N3tpkpNlKkU03RNmSLwMn91CI7aBbcbCpBXf5OGz1T9LDp/PVnV/nMIf9DH0IOYgxuYkThyqmxgHWoAnCDW9FVWVy5+6t2+rKrVxtbX9ylqlcEhQ1kJW7BeTidCTCIVBoorOwCVJgHGPAbIHZ0CqnIC1f/V7U7zt9wkiCQLMv5M3FGQ8wmaGJ+q1htVZ5afH27dvf35AsHiZHT/j5JwcjyuYcTNGiKxRPJHPpTChS5KuopsAtHOHA9h5SJ4w1m2SxG2M89oZYQEx9b93Jzl+Byn72gVHMAKDQokgY8szEcaGzqqo6k9tav2VX5dhqNiAR6qUMhrOQS076peLmwp9L/LHNG8OA8dCbRuIuoRxOakQJoZHFRdGlkXW8Mp5y43KCOQ71P+L3zuk7z9q09L5nrvjZF2zKO7v8tQcLuvgf5x6dGeI8742fhQ3Abgv80ZZj89BJ4zjnXc8Xz+XskeU5AhFNpygtC2fYYrAi6A/F2AvRbs/ISm3XRoKkEt50sihgLIwd/VQ5E5fXaoFEDiKGiSPnMSCtPZ7iCGqnXArApGcW76hfL9yhTQojarfmLh0H+X5lnhGfr984rJr+/QNFoVgylsmkqvtVEiA/pIu9UyWDiWYnYpI6BAFqokMSOjiqM5RUlJemsv5dLYkN263mtlT/mn41JRY2f7UReIJhKxjIxuN0g/gS+E2edGYkEl7w9kIoQEFPYVkIhHOhaDZYxCGFbRl6QsFwVNz1aWsnM+nCViJgbTbDxnSNkgmZ4x6JhjgnmRpiXfP2+gbAu7Kqv6lyqWtohDDwVIiV4W25qmtqqcktm7cZT1CfUWPs1EybNvylB6DxCYqlAGuzrNwyBzsQ35TaJGPf8JCftrWCF8aDRqh5mkZp2hkhpQK5SwjJib+m4Ukz7pUL+rVkTvm0UEpeAUlQa35dClsQxnVKe+jKz658oWnJj9pXR5d71yiuz+FwIP8pHk4abtxCDuQQrd5kRuzN4QC/2niyqLlVhvVE6noqzHCwH0zOpFiAFA4AwLyxxQefiZw3ZMQfckU+GfEyii9IBgCzabDWmaMBF2a+h5uYR/lS4UdJCy4hWMQ2642EfvkRoKyyws9+kiz1zWXKoqIoy3/Bifyk6XwSwonDoJxcudjZMZDJosJWlhWlPN6GeO61BVt9RZHRI0biGbZARpkFLQbknDebBs7kSmSs86ZPTcTaV65cySOlo9aaUpmGZKaFSXNUBNHY3MrMjcr4xafesuauz933+MsvLVjDq6wHxT4BmrXG2wFQou9oaMl5w6WV/bBRyyUdJtDUTL4C8Aza4V1VU2N5g5t27EqGoM8vI8OMAvuzVgDjOMPFzA9IMaONOX4YFYhPXvqTNAvYhZMfTDfIaQzUYol1fqahdYTHH4THtM7IiJlQZgM+iTJRjp+q4ZLJUbq0qetdiTd3oVyYs+fdFEQ+kc6/jgJqSe2GZzhxlAjvo8keFD8LGN7RiJy2gsNpZjhozNxJ372OIAfUsHUEEzzRk0K0gwGISVoqzOXg+t0tqR2N1uBi2XkxTDv3iImR7YGRppywKycQOJf0PVHeRHpy95CQUUlIKsLqo1yGbZlKWFdjPgNkjDiAESDPvhuvnr0JnXaOtmoFsuLpl3FcEaBQSMehKBoBabHlRiOYb40KaHadJCqzzkQJxsarmhnJUeDC+wGXiHgMQZsly2kfY+1WhAVQeLSncq/PfztaVDJ+jAAwSi8SPMMYLzQyAasoBCByFfuskcOCbNvR0FC/4v3GkwaWV1FhbPdlpI/WCzGaYgm0eaZVv7o89tKcuRvfX9u8c8vq5aUTR39hYAlj4iYx1F8jsLbXN3qMBqxNwvCEzEiMVHMM8OtDNbtzBYM7WloaAGNz8EUukOXgRbNei8CEyrNZui4S3X52GGW4pJ42rhNJQnZc+kDG0kuSV/BBDyw2YSQTXvJT6O2I2IOuPMFioyh0Q5t57HZkV0sqd2Nh6EFy+3xWhTwsdDv8NByTqre/Oapfwwk78+4+X8xjlcBC8X+slqHv0A1iYoGWSVOYoqVJWxgvveH0zlbGCktQt2R6LhKcsUM0Kn+yxB9gAo6ArAoX/splF8ix6uIRCYbYhoOjkFgwyqMCLp+KOPhIjHIsrt64OiaNieyWIUn+iCQXQGUmtkBxaXGUg3GZ/c0elpz/wws4kclkhSEUWCmX/sfhXkySAtBZd8v2y14rUiKzu7ypnK+1ub2yMjLylAFkLQt8MhlfIMSJzAEIRS1nY2pzTC9TsadOPgMN+L777z/91HFnTTp98KByIdVIIlReypLzhd5Z1/zY83OefXVBuLRs6OCTivyedZvWPvb0yzddPbOCud1ZhgwiKsV27Njl8fn79eunVS/Fo7cBpiuQGBglZHk5B04UNcVa62JWrojpV/CH+V8p8Nx8oqxoUh5JBClC4bUn32iA/PKszIc1fTvYS17chetSO1os9SNFTcjGMHzzkQszO/LuzhlJI8BPSBSHPBZcOjBhw/Ce72CN+NtU6zvlWkH849/ZwQItqzBi7/x0+GG6vyp8lIMmTp6bTjDXcUQ54ALwkWQnXzsKFg0evQKBi6PM54kw16etiUWt2HCYlcOF8oS1EwEj22sYH9WacEpco7+I4BANWD4AxCUmSV8mxcTnoKkxW/HVuPu4H33xo187ZOezsgskRIl4T/vNEbhlxeGw38NRfJWlUUCOQPyyTAMHpUEjpGo+viSYR+R9lGxvr4SvXCCq2JkFvVj3BbvKS0qj4Vx1RJhJxhyFQVWxK1mAhVXpJIcQ4t8es4JF1rVXXbninSVMxXr2ha1PP/c0m3UPPWXUpClTR48f0S9svbVyyzNPPbtkxbspX3jMsCFnn3v+5MnDqZT/+sZ/P/vS65PPOP3UEf3IXNYSJTNs4N3MNGjLV1qqOGpIy7JQy3AJGk1HhaJHGY3w+5oy2ba2TDLE/DAJCQab0V4Q3WzcJX5y0SikFFySQsdlIsm8LNtLLQpw2vAWzvAjhkYyPT8YLfWQT2fP5DoSPlou8svTarLgWUhVP2NEEsoM9Yq7EsqU0vgZuC2g2XZKm9JIJtET6AYDDpqfdFmEb6YZKFdNA8OLNqYcddIkUD7ICcTVo1pUF4CPKHtpsEkmOyfCDP+CIxlrfHXt+0vX+5rS6DRoMwy0sWQXBGrZybLg0vIAw33mkp4nzVuEC8LZbvGm+fMZELGyJJqOtZZEQxVR+TDkCENzsYSGv53Hg3vwKxGK7ct8ntBsOhCMKoqBV+iTeb+nDIl6krFgLldZWqzlTGVyJWEWArHjI1tKA4ER7XnkUzN/bQjZw2/fDxlABgYlY/SAfCy7tvxVFaVNDYwHZyeOH0vWeFrxGBOlkslsgHOYyVVWVotkqSiSHtKoQaE//OxbcxetW/LOkhUrVrS0ta5cvWrpqlU+f4iBgGRTuyeTHVw7aNKkSefOOLu2SlAtlrMuuOCi555+6n8feuo//u0WDnym+qOgb4xVTm2+orKacqHajCdg0+YlD9lka2uQk5LpXZkB5v5VVS27djas3Tx16tB0UgaCCZRoS/k4Dlp4iqHBrBQHmJIJD545Kx5PhIuI3d3F2HY8zt5eRGUlXKg41JpC6ZdlVFJowJhGlsqEUPwVg2GcmA5ofNJ5kcFx3pvm2l3qnf2kR2iuDgNO5yAH9Syp5VIpts72s7RLKJReFMYSqOYdK/KkD4PGnkrK1t/5FQEHlceJFNjUDgzkr3Rv8/wULps6z6RgrxmSYRFdnN3q1MimgoTvSa9kPBUM76W95cO4fw+KAy4AHxS79heY9k1r1TaaZNSP4cUIf1e/t2HC6Sez+rVfVNCUWTztjAAHS5mXlE/RmJJNB1ZFDP7IxlySA2oRvCyKTRT7cyGvmLf71GXoERFod74VfRXU4AZrZ72esMdbFrLYQqS5taW6PGokp8wxIgqoQtxCqY03HOjYQeIgS4soluhIbZYPZTKcZQTgh9JtuVTsrHHDgD48vQJpDDrLjij8Vfs/9UZEvgfIA1PPOWPY2WcMy1kf2rgrMW/h228tXLCdGVIxT1Vl/2lnTbrovEm1FRKStb/UeFnAuuoDE194/qWdjfGHH194y4cmtbRbCLFtW3dguohETXcMvIBZ5MiPmDlvkHM4GAPOpTknEXtJ/8qSdZlk3ea6xOlDwUgBREjzGHmHBdpEkWlgpMMWJ+1JL/OxaWmkVtAmcGqNSMGY4y1TtpCsTOVi8xZGdgWqcHPRMwqE6CpIt6ClubGkpNjIZYAXmlhxLghHZ7EgbRPtKNygoeCCRvvyBMTck83mEsmED2NCQBoFVcMFguCWldXsWpNhupvMObejSZGkoPbjifene35K90UMA4z7xBOJYKjIa6xv6ayXESFGSdJppqZQ5zlBX/icSTF4ZBpDhhYiC+I9HsbBzFdy4vL2iLcmF4CPJEtZUxIzCMT85kzAjzpVMuzkTGXV/M2bXvruPeyJGMrGyM8XKYv5o+/uTA4eOkEFSiciVIyCIGY+US4asGqKIwMrStGg+QJEkeoBudiJpu4e+RAhJP85ii4FaVoijnoKeVJejjTw5tioq4y5RWFPY13DkEE1UgSYINFYJCyrhUSDV+TO5yLW9z0FSf7Nfv6aTr4kL4l6fZiCxw6prm9sTCTiZ50spLIFd1HYn4snvBGZsWVQR9LkFR8DMaEfN3tpAK6I9sH9QkMvO/uGy87e2WbVba0/aUBVxG8VB8XITPhIWPAswSBuwLrmqitnPTF77sKlF58/aQgHDGLnaIsHPJ6aijL6WaTJTy5FDxAEzTsVRyEGY0GMUSfVzs0l23zp5qDFkZNQws9bLJPyiAjTAFIgVJaFM3LBu/aEFWGvDk3UJGw71Qtwkme2JQ8EPU0YJALW4lVbouFo/+py7CjM/NbK8nkCReXVWmpSJRbxsnRdmDtHSuK1/4sulKME7z/0AYUwGbMNHDudFDELXPiJRi5kmyXU9FG4fLKznDebTHQ2Ah1QFidSIGnq/KQnxwZwNCraLbu/0UC4CQz4A5xdHTSb2CcT8SLRDQjFPEH+shwuKV+sDH0UNLgTiX9HqawuAB9hxqLl0Ehp6tKj9AWi/mz/iuiWxqZwgG2dsv5UOhGPoYT4w5nh/aqG9mNr5MKro3HjMgfVAyjpdHs23dpUhv7L6GFh8D7g7vRF8sny4woWgcYo7zQwdrNCcPoHlkXbyopOHlgrkhX0kbLKxy2hHfXFPO9RRiOHJcyBXYw0S0CZi+VNp9hs2+9PNtWvW3H22WcDmfmLHbvFug2MGbkkpBCNfLmrAwVRJp4buU8ZcAyMWtUjq9ChCQZkMpNasNHEZLQ5m7Y+dMkpK1cOW/LOsof/9uLnPnFRe8ra3hxnOsDAqhJN0w7tAUZz7CpqdjfjTQ4sQQjWlBWnE61zFi+I1EQGDxpSUVZWEpU5eqUBrIKynzZ6tOxamjAWFkhGIFJMswmlSZkbA8DmQmymsx5YTLdGVgzL3qUrt7Q+/Len6rftGj9u3NlTp4wdXUvHDmDDUMMfehUUgZKiddL1kZhivZBtxYQjB3AVmjEOIPjeglAC2CpZplHeUfb9wmZ+kGqAQt5BVFtSJkZwKKZ0tYJYAgiCt3OJZaXw2Xlxgjny/PR6kkmWwmHSp+UKP2kVVC+OdmM+oGHrmnSad9obZNKBzE4kFL0w0oC9YDCdONl01r2OGAdcAD5irCQh5HARnXEBnRQ7CbN/xqVjBp/3tVtRe5EFNGMwoL016fEEdrcmmzOhkwbKeHCni2BcstITmZOIWWEsjZFJE0/qP/JjUVnGZC4VLXuRjIVyZy9BNJXDvZO4gKWTn8dee4Nfa2usPJDxZ9utWLtVUl0W8P/jbdciFCvDdhSzeSZftxa3I40OmkjdSbnDdz8uIgmq+hk49GRSaWTwxGEDd5w67LJzTwM16dUHi5iPnfWwi7aR6QggLimFRGT+MG4pBdunFLGfhnnVHs8G/V62ysI21xYXxRVoEx2U0OwtKmKJqXYiy6667LxVqxYvWrrkjdWTzxxdsnT99nQ6PbCyTIx4ZmYZaiJMkPEGGXhG8pGELB6ma1VdHOpfU76paet9Tz8RjyfxCbLnRzAysKZ/eSQyZeKp504ajp6dYt1QQs7kkGl+SrchvuAmLBW9kBOm6ECApH5BrzcXLln+3vqIx//ya2/MX7h4wsRxM2acd9r4/syqRy+KE4dgREhbQTn5A8sEFkhZK1eQcs85sZj6AyHIZidRdF9TqVKK+narLCJALBuJZqxWrABBKwhISGvRyuwgEj/3sjngoZdSBAOZ/snMCOUnjH30qUWBosiEcaOH1EhAlGBasj/AYSpmbWA2Jz1a2CstvndawvFdgy5Pj3D9etEg5Bgb1vkmrTb25s8WRWTjCUQ5zT7I2Tu5mK/IU45VBwVLtmXongAmxIh5lnlcJNXe7A1XIiiprb0E7z6RnvClYAKTYjJWp0rBkmKGvBMyExklONHm80er0FIwJxqabPszEhMVL38RXeNKeod0kRYGhjBzuwxsBENiurzs3FNPHzeiqjKSwopG9h4fqpU3QF+oQ0kiRzGB21qULJ0qN+grNrpstiJso21ra3tlcYRytra0oPBxNrOZ6oWHp8hrNcZzk0aXXfPBS/7wf4/e/9jsEf/6kW3tAG6utqpUjh+GOJhhDLX5YprKT6a8gUCx3zNmqO/Dl1+6I9m0pX7blrodDY2tLa2x+t1tjQ0bwz7f/HlLmpuv+/DFE4qkB+Nlyy05U0qBZy+8AtzhLj/6f+/vtOYuWmb5wn/3D3esfXfN4qVL3lywZNHyd4HhC8+fcdqYStHpIZCuBPXJ3qDCCkPmXsZTTTnA6Y7q2wsV+/fuJglWjqXSQCzVl4QYo6ht3W3NXbBo/qJlEyZMmHHOmYMqTA+EOXUZWWHfTSL7z/n4DNENK2QhgHQARZqYviBVu35b8o2Fy2a/8ub6LdtCQf+506ZeetH5p4+MMJ7SnOTIMsFclrCncgyEYfg3erA23OOTbb1TKheAjyTfEbPtYvjylDJngd2Aw5x550+wgbABKSCV05E4KAljn5dRYqantmajMim4m4v9/X1yaAPQzaKWECKm1NTVHqEVqQo+uEOGrm4oOBAv8tMfgY0s5kk/0rYkqldMQEIG69Ct0gEs0kZno18ha5m5ZP8N4xDsPjJXKCA9dhgnsgbNMptms7HB5XTr6fgL4gp5/iBbglAd2Pd1sXVekzTkS4nE8o/OQCeCLTVZLiU9Bo9VHPFl23Z5i8IlJWE0RDltEbsterOMt3rC3qTXil59xdQX31q0cv2mB+e1b08xjOqtKS+DJklBSmkbVGECdcshzxaHVfqx0ntpGx+YPjIdF64UFYvyym9Xu7Vuk7V1+7Z7//DbF196PZDLXXrBxAo/86fQUcTEL5Kx64WoNYuNKSx8QImc/fQLddt3n3POuWdMqDxrwtTzL5o6d8GqF195+YXX3ly4bOXwIYM/eNnMMScPGFwmnTyxSpAwkVMpsfMWNLBOWQHDRwSDOyXLIyv0MJgyBs9EMFgM+j7zwssvvjKnoTW+uW4Hi8QuOu/siSPLIQ19nTLK2CYP0m9wr244QDWJ7pvn57q6xLMvvvLiGwtz5QPGT52RisfeXLr6jbcWjRk17MqLLzhv0oCGuFVBH1U+a28qyygJzPWmMylQ2b2OIAdcAD6CzBQBS/tMenyJHDOWUSrYk1LSl8ZrfiIQ4zGZyo8lkfVI6E0iNWz0UlK0hSNhxQyNEEIRSKZQl1HekEQEP+Crp74VKYKZliqdChsQwhwEaMBJSEaF4Rwns9MFAdIY5813LJojXBBRL+jtxMVxyBfHK8POtngCCR6QUXRwjeQ5eiobCPjb2uPBItFn4SvvumcQ2ds1gk4sgkeWZ1AXnCDozYK+QmgmlfFks0yk9mIIploYqI9H2UkjlfIFAjfdcO2Pfvfgc88+zUKjSn+mpIRTn6VApIoeopd8eMwBExUWKnLtHKwULmIrLkYzCYfptykhCDg4atWOttpH1obSH31k1iOPPvpoKOi7aMY4Ri6MLDWj0bg5NooEzXYuZmK5Xy0LLZz9UWztarZeePWV4oqa66++gOT5DSu3Tpo55uwpY+YuWPHG/Pmr17238/4dl10w45LzJg9gNrSHXhNUQRscMP0kBhfMWDJFpUXzA3jJkEwpCHdC670TAHbPYVPXQi+xSH+Pi3MVpY8i8xnpnplM126NPfbk04uWLWMP7yuuvmbu/LeeefHl7Tt3tn/gktPGDWCvFbImCoYBmbiLU9LEw9AiZEpZpBzCWrlwOITxXt2mx6FvnJcm9D5vheRLVvZVmEPeT/5CG8zTt3wXHYTxjqQ0hTw9EkHTt1PmofC5Iz8S5Kf8lDQlpvGRvzI1Ulgaz+T8QQ81uGZTy0N/nbVk+SpPMPKZW244dUy0JWXNnr107tx5772/8deb7n9kVsl1V18x9pTBJ1VKhkyS5k5VSLraxZGspY+r5Egm/DcZi0NCCz3qVEeeWNs/T+Qe9UIYssiH1HjH+f2Iz108XH7Rp46zOb5ZKLJr1y62EMqwboSpnB5Pa2sr/kjYhoaGiooKzamtrS0ajRIrFovpSUH4J5PJYDDIfFeksDnwHj0GEZlub28vLy9vbm4mpPpzOs0RnD9Jw6NRciERzPcsLbawmeb9aYUglkFfEz7/tUhz1Mu0Qv1c8eDJL/M/7ZTzgfrCX4diQ6ZTWCjG4FogbnwqWFU22KXroN982h2Ph/sROkSZjEgXSmxud3qljx3BCmhwouTFDLUGlhPDVF9BSIA0JtBbFDPVXZ+x/vTAS08+/9qgAf0zTXV/+tk3wTx6Hawr47BjwxkVXSZBI66oX8VmW3CZukYLhZ8E4s7vgcfnzHryGdTy6z5y0/nnDicdSOnHq+aGck9ADiL2oVeLnV26NWzEmbHiAWtH2rrrNw+tXLv+wnMu/ocbzqxIyHJfWh9TARkpgeD3Gq1lq1c9OuvxlqamU0eN/sfPfAIMhmAs0kG6HClWVANxgWaOaPRbrZb1/NKWx599YVPdjvGjR82YMnnSmOjgsExuoE9ALTrsxQGFecbaDq19OJdvBllR1SUofBHWKMxDGLPQecR0tK3R+u299y5+552hJw+/6aO3nDq8eHOD9cTjL7/5xpxoMDjzwhmXz5w2oFQaGj28sEcol+lkMoeCAWzsFB5s1Kz5o7cEJxkzpjdIpymekJ4tdijDDGqHwqXpsZlyYwAnjmjhiB0IkZ6ilkS2U82q6DCWeqwg9sVyKfY5NydzY15J0TPLx6F8LHgTW4XXk7JSLTKuRH3JL5jzBDgNWszChiPkRX1DBGYjPOiq5sRyoieLmA6sUCMlY7od64dgUTIVJ8EgbYv6pqeek5EE6V1KijJBjVJjjOIOqfwWrNj48KzHVqxaeerpZ37iphsmDiwjO20J21qshSu2cyT2O8tXRyPh2qqy2z724SmjijG2FPtyYHeioT5UVmamoftjyXSM08jDTNeS7iyqBOnQG2P8LQA0A9meDBNRmfTFpAUs4DIaIqyixjMw0SNz/73Msst6GJ/xYPeGCUWm+kwwCdrpAgg6lD6fKgAARL5JREFUCW0keVlZ2dGT550IOBqPfQ6AwVFQFgTFAXMps0Ks3nncsGHD0KFDAelUKsXJBPg0NTWBwXwtIHQ4HKae2L2okFkOEvOKYMd0hRWWy3X3BgcQZfy4EITqQNIhU/1It1YA2sjJ+ct3/N/Dj23etK6y2P/TH/8n4wwIcASm6IuYbcXyTfT8pdLXRiVNM//KqG7IuBjWEJ/12NMLnnz+leZE7lN/97lTZTjYKmaTFpJFBCbbLRa5FTP7zBdjj5FMxBfytXqtJ95Y8/BzL7TH49/65zvHV1tRRB3izutjlnQ66IsBdZa1PWmtXb/j0b8+1rirPuT133nHHaOGssJJwCwKmYx5s3dn2Fq92/rz315dvmH7jsbWjMcfDQWDuXTUm5l48sALp006Y3QFO2EDAfQE4IhelJoE5G6KiwMkQ8KKQ/AB4d1ulCpMyL60x4/Nnh1E4SRcgNJNO7P/8c1vYoqv7t//85//3OAKiQJaYKV/+eVVs2c/1djYOG7smOs/fO3EYbJzCeDDT9a+ZRL0dTB/sLt2SXkV83cZ16QCSHnxmtRfH5+9atWqc6ZOuuryi0YOFmRmiIKXDbvrKyoqYaCqjLDdlF6IAR7IWoY3ICCeYmk3oJZMJFLpdCAQoLufL7H9V0FXTfTOeWWiz0McvMh62B41wyo5nww0kEuSCKzMNjwho0wsURQSfZ6G0tLSEg4WhUAsDvpojnPAGivrbQ7CK2MkIFeoJSIpUG5sK0xfwEcWkJtuHKXneu61VX+b/WRdXd0Zk878+Mc/dkqlVUVF5DDnBOA2LYEO1obd1o763GN/e7Ju0/pkW9PtN99w1YxRJEtjYDlDomFXqLykvSUeKYOrVl1DsrxCMBgWtbZZnO3GCj0qgo092IwdKxivuGAaVKWo62w2KMI5G48lsBXBapaK8J5gDJTAU9OpMHG63FwA7sKSo+MBstLxBClpvijB1dXVa9eu/c///M9Zs2YBsdOnT//9738/bNgwAgDS3/72t++9915UW3Ym+p//+Z+xY8fu2LGjpqaG2iI6YaBRPwMcvOrfv78LwEen3k6QVBE1/LgQm+pAtqC4ogx52hCwjJl6rHbLeuzJBS+9+PyoYQO+8LlbIwZ1aIv8xHSNQLLjmpQMACOBeZA3cmnKOMQognjiB3ggIn9171NvLV3FRi433/qpGWeWpVNW/4BVIkSlrHQLoJALFWV9Je3sWxoQMv7lO/e+u27NJ2+56YYLJpQgRoVqDlYSvZC1wQwjkyw/hOmmHel7fvd7II0e7c033zzz3LEQg0wnBo4X5rz7xFMMJO8qipRecOHMSy4Z/+abG15/Y87WrRuJXRwNDR48YNig2uuuuKQ46EXGUhhggJ4GWiVuKVvBRZrAEGdRhL1IfjAINQhhLWu7eKA02J8XLH7vF7+8p3bA4OLi0n+68xMYxaMMfhseSnGZ171o3f0PPhKLp5LZ3Gc+89mqqqraGk+xjAbLD5qR5hFAK2GhvtcnrZffXjPrxVfe314fLa/ioOjWhl2BZPuVM6Z98toZNaBbm8UuqZlU0hsMZDxydjeUQFyMndpy1vr1sUEDirAtsF4Lozcps1FXgOOqcgAqtIi5J5PzpjG0+EM+nzeezrEHq5LBPZMWLdTjC7ebM7KUfviBg1yoxK2bW/pXldSaLUtJ3MMgBHXOUvQAQwJwMNvc2pDJZcrLy9Ckk4ykhEpySeGSFZVabrWsjXFrd5P1yosvsXaN/X+ixaUVFVX9+lWXl3GIuFUSsP76+Or58+bV79xxxaWX3XL9RPiDdlyDJp2MMeEkK5P7pSUIPcw2b7OeembenFdfjrW1fuLmj11y/tjGBouJb6x792TjbK6TakeZCVEfu+JWc8Z6c8ma9du3UdmnThg3bnh5MZ2JjEW/kxXHdDWlCWHyExbISE4ylSyGl/hy0bIpBdRoO5MvxPh3ubkA3IUlR8dj586dgC5p19fX81GBwVOmTDnnnHO+9KUv8dkAxoMGDQJo6Xh+//vfv+uuu/785z/X1tZ+97vfZQ/9l156CYhF5UUJdipMyQTXSXDAgAEuAB+dejtBUkVa6IUDmcFdxCxiBZMlwkRtpzg27sy+/faCk2orp542QkUKPX+mQct8FhE9RDRJyTsdCSMdGzmMMDJv8TKDbSQIJKCJIifv+fMLL7z6Riha+pnPfGbyuCjJ5lrSpZ5YGBMex1Bg5gyWxj1Wo2XNW9b+y9/8milo/3PXFyuMlRgZaBZMkRd2QTasFrGIMbM1ZgXMTpzf/8m9G+rq2JZw0MlDPvvZG8k0HrdmPfjsO2+/nWppGX/KqNs+/vGBNX4WJUMS+L2twXrx9TeefumFXc3N/ftVt+5uDAMOkWhpaSnDPXy/XFiqdNCHDjGfLXNuURkZHcJMm/Oxd6sMhguwgl5mtJLir1i29g+/+yMGusmTptx5xzXJhEU5UZRKfFbL7p2lldXwG9pYw/rLex59Y9Gitng2WlpeUYWqzCc+YMiQISedVN6/wir3WUsW754zf/6y997bvLshFwqdMnbcmAnjp049+YlZcxfPn5dpaxtcWXHNJZdccv6ISH6WPh0pJunFGC7dmJkz/+23l7yD0CiJhK698rIrzhsGw1nigKqXjbUVYW4FLBm6l1Fz0EMmvGuz4I4lO81eUyxURtkzBFMp9Slr1y5r27ambVs3b9qwfuvmjY31O3OJ1oljRsw875xpZ04oLzK9NPpJQC9b75AQ+8YxvoCNW9Axl0hnA/4wHGBeVV2jNX/ltjcWvbNyU11bKpED97xM42ecwYTOZJlCyOappaFIKtbuzWQ+e+utM6dXMCCCxYDeTLEQLW2Y0QtBR+6QbUzi5PXg43MZbm+Npy648KJbPjKdIhSlrTI/Vsm43xcKhzwsdl+4ou7pV1995a23I5VVnlAIpag4FJ04dszU084cMbhqRK1whA39qFu1S8Im0mlqTBcF/CXYcLgooPyysuCdlQW87u5y5LkzbkiluCbo7lh1GH6M1BJbNVdlNLj7xhtvvPnmm/grshJGA4C1X/jCF7785S8Dtxhq+Ob/8pe/3HTTTYSktkBcLNLq5q7jB+jWLgDDDfc6NA4gKMAwE5c7T3qTCTVodEY+irkY+Ycb8RTmDEpjf0bkMadaNGUkkMTLJyJwLAN1Ji1ZF8yVF0EaxlaCm2NZNhDk82hOW7/9w2Nr1m3c1dD8d5//p7PGRUrMEvMIkIFx1hNutnzNHmuXZX3hX34fDvhuufL8y6adXOXDdtqYCyNCPWGZOyyHDkquEEp+xlDZhrYXsJ6cs+xnv//d4OHDo1U1p065cNZfn2jfsW1waeTGKy659qIJ/oSJjDJeJLFaOJ3YqNrzV25+6U2WGu9oT/n4TvkAAR69MEFJoWQnZ25SOL2nfRjJ/Umz5yHEoBAH2KyGXy7TULfptJEjz5185rVXjMZ+AFTEWq1+xVa2cXe4JJhuT/pLyhmhBoBRLecs3DBr9vOtiUxLLNmeSAgPfMycQ6VjjXAp4iLZ1lDiz0yeOOLS86aNHVaJJRlI4ICupe+3PPrU84tXbdgdy44af8Z1V1143gix0G/eEeO8jYVLV6zduLUtmfX6gwxyZdPJ9qb608aOvPkj1408STogbAMCYVpZgitsc0qPxogajhrVxkB94bW1yXp76erlaza9v72lJZ6Kt7Yl4q3YQoI+2V+WEfvq8uL1a1b2Ky2+8bqrL79oGujI4DiGcU+MvVzAQw7mCGABp7B0C1B556ypW7lh0/JV69idLdYQD6S9VUUV0arS0y+eGmMHGnbvbGvnIJDm3Q2tu3enWtuysdjAfpW33HD9mFNKy5jRmbMa661+7GRuFnFBvNF7qSbahBQlnfUxM8sX9jz20vL7Hnki4S2aOGnq331i6klmmBYtmd+mJuvBRx5bsmxZW3N8wtiJw4ad4vOGlq1ctWbD+lwg4IsWse3QwMqSMSNHTDlz0qhhkVKzCAL7PvyXror5wb32WDwSZnM300jE25AjJO1xuQC8BzuO6oPOoiILrGGnnXbaLbfcsnHjxmeeeaaysvKLX/ziZz/7WfpZLEUYPnz4mjVrRowYoUbms84664ILLvjhD38IxALGhRQSAKFAaujKLgAXcsZ1HxQHREiIzDXQqEO56iVKS44BLcQu43libVNJZsIjVHTxFUIGBTjLQmQmpYjklnQcnYkYKn5UpudBWuQRyZJPC+AXErsomsqfH3h+9nOvtFtFMy+/6MpLJo8o99HigS52S8MgudOyHnpj+x//8OdpE8bc9cUrwuylFWa6Dxu7RJiDztEUYQgBqchfSDCT2FEuGT2NWrtz1nt1Ld/6wf+X9kUbWr39qwcMqy6/+cNXnjbYy+orYDfX3u5hpFfi+Vrakyl/mNFMYKbNSHFyb2ixGhv5JXfV78ag1djcwqQN6RMnMxiM+RL5wOkfYy2I+cJpeMHu06jTzG/KsVwtxW9QRenVl82cObkGSY1JlrvAAvZ1TNSJNivMOc/e5kQmGA3SAwCewKSmmLWT8ctdDZu21DFThGtLQ1Obr7i6pvbCs0694tyRo8tlH7EIK+KYrwWityW9pWFofvi1DU++tmBTY3sq3nbBuJN9yTbs8Fu21rW2x2oHDmTt1umnnzZiiPXinE2vvfzKu2tWRcKhaz90zeWXn8pQLLTxo77gouGIcIVrd5u1bVfD6vfWL3/3/XWb65raYjkfin9047bdRZHi6oqyQQNrhw8ZNJzDLAcUs8ksu5I9/fTbs2fPzqRTCLFLZ15YUynDrkWc2mXwKJG2UuyX4rMWrW95dfHi5+fP293anklmBlZWnzVy3LSxE047uaZff6vJmLihh0jalnDAvZYmq7LYirdka8q9LG9kjJaJ8m0trV5UFPR+DyMnqNb8aGiUB/2Z4YlIo2xhZ721NvH9//ltfXvmjPFjv/qZS1BbGdl74pVVz7304tbtW+lVfvS6Gy47/1QGgMmRaW6sGVu1fsvcxYuXv7vKnMbCYr1cwOurLK0cMfzkCWNGDx886OTBVrLNKotKGWPxeMCXirJjqtAMF02BhY49LheA92DHUXrgs8RIReIM66LmYqrCeIXnbbfd9vnPf37+/Plf/epXv/nNb95xxx3PP//85Zdfvnr16lNOOYXwW7du/cY3vsGX89BDD/HoQDjpgNbgMZ1xZIFrgj5KFXeCJNsZgKXYNgLnZNIq+wWFsbYxKQqJrCud2mLJEhk9FLmSSXMEMntUZdjDWDlGZELqnSCIMC5CmteCjeYSkZREsfOCbcniEhQYa2t9as7cRS/OW75xR11F/6IPXnzuZWedWc1KZfAvZy1vsb5x1z015f0+OH3qTecMLAHq2rcXRaNxAIhzKKCN3faxNgntRt4ZmYv0Q71GCd7NJlNp6ze/e6ClITN92vSrLx5KFHoPiEuMpSVyukQ6yaFSLGwpKiVB0fb4g95PgqZrYRI14G4ox0Br3ki5JE9zx015bUYYT71p8RlfBY9bmnaXl0XNqirhqJyWbHlb2KesWPbJiptM0ca4eI0PnBeNUeYcAynWplYOw7AqPVaJjJayL44JlGC5PivUmITs3dGWDpT5m5lk/syiv81+jh1Ik+2xSChwxvhRl8w4+/TxVdjQiASr2GKnMW49NvuNF+bM27a7ZfS4CRdfcO7FZ9Uw0km+LVkQ19qyo3nt+k3rNm7ZsGkzcsyTSba1tiTbW0pLikacPGTI4JMuvfRs9g9nMNspuLKFIkDtW4t2/OXhWaQwacq0a6+7cuJgmWGXarM8UdE4d1vW488vf2HOG1t2bKssrzh3ylmXzZjGRCoZOU9YpWj7UNKVm4bDsDSZbMP4L/kwSxxrflu7FS1lmZr0CWUYOyWTA9jslAnkVKQ3mM74M4FQmxkIX7XD+v19s1e9t2HoySedN/2cpW+/vWbFEg7yHD18yCc/dsPwgXK0SmGJGNGAwSy3fHHu+nVb6latXbtl584YFRMMZrB2p1PlJZHaipIPzZwxffTQiBhTsswFY5mKP1Imrby7ywXg7rhyFPxgNAor6IsJGvMRI0njx48HejFbgcS33347fVvGerkuvfRSZvQxMKym5muuuYYhAaZoEVcBGDz+0Y9+9LOf/QwHAEyC0OtqwEeh0k6UJBU8jJRD0lNqaVGCJir1BXwQH2I0BgmQQYRsjyUjRbIdCehLs4zI5GWEokQkWD6+OoghUVQC2blIaGaQZhDoAjDsT5rKhsOSBXiw7L3G5+a8/ubKBUzbmTRs5FUzP3DGhGrMw797fuX9jz561ujRd33x+n4sJicbfwwlKp7BJi1i2MwaQuYbErixOofLG8DISbJsFMY7ssvFLWcDVCSsIY9uBifnoBrRwaAf4WOAlnUlIdbs8JpJSSy2EW5IcqLvk5W6JQNxyTRw1vOQJd8jf8VkrIElhOZh+MMrzMy8E0I4yyTLUiNvOX8IAxGgrMNAWVdvLJwFrBOW0p/AnEvZxD+eLoJeiWZQmlyZ6ekRiwIZYH7f3mT97bV3Bg8dMX5EeGBEehtE1DuxW+NZH5utWNbry3bNeubldzfUMZB97hnj2Ppld0Pj+xu3NLYlAiEs/L6mluaAL1BaWjLspIETx42eMGbokFpZqSW6sjEsK5FCvCkFucNtfiS+4N3kQ48/vXTV+2MmnHrFJRddPF5oAAVfnrf1iReeX7dhfU2/qpHDhtz+0asqi6wyKsAka6omm03GhAfCH+U8hTUV4ckm2to4khI2ysYvZCUDIUwbY4+rMnpRILAx2ZiKM/FpCUwWZDMgQu82Mw82NVh3/+qBlXW7w0VRfzJRGfJ94sNXXzSlHwlpw6A4FAE3vTP1pHQ0JwrFj7la63ckVq5du2z16i1bNzXu3NWvLHLd5TOvvnByCXxm4ajYhGgJjJYre6QtFF4uABdy4yi6FXd1Zj8Ci0VHIOvPf/5zHcTVac9MxWIhAcD8DgsEhw5FS+aTvuCCC84888y7775bqwrwBrNJDZMXDjwxQTM7wwXgo1h5x3vSSBkuwQvklDwg7fRy3hjURQs2gdSXEOZJBKB92W9Nl9B4G53ZFpwqgewoHVmINwmQpSajgrsuZr20/L2X35i3YcV7FaGyqWdMGn/mxLv/+KtgyPPPn/rkuSOrS5F/qI4+QErGEs1YGykh7EiAxJwioMcIxvPTXBCmojLyAGYZPc+8smmGGsQ8YWSbBucnk8EJZUqAVJcyaGmkx2Bylbu6RW9izpgAMOwygXGYbotDhpkVJBTy32xJLNH10kSUS+SBg/llBkiITXAqCKINmSQuIURTR78josYCrKDfdAK4M9EpsMMMsoKUgBWQyd2HUohtFiJ9wWQukMC8gY0hYz3z8trZL7zaGGNKORvepbzpZCTgGVJbNXbEyUMHDRg3djjGXfapJi9+5MudBCsAGxLs4DkFl3lbQBcoSzAAb/V265En2SZyNVtQ3Xbbrex9sHTJotdeeNafaZt+5sQrZkybPuEkkrKH8AEtUzUkynQqP4O6pCIsNyzlrqwxBJg2BiGGOcJEqg8GAOLCYeGDXgKBwiWeScy5xyzry3f/devOhumnn3rjVWcNLLKwZmOHFx7KRSGIBG+1ZyRVqaukNF15l7/WvhtLJdpLisNDBrGcWza28XpTfrY9E3KF+q6XC8BdeXLkfVhopDZnFFa1RX/605+eO3fu8uXLd+/ezRgwc7IWLlz48MMPE2zUqFGYpoFk6Ni2bRuDwb/+9a+vuOIK3aYD6CURXjk1B/Qe67PmjjzH3RQPhgMqRFR8i2jimZ9RZwuSMRIkHyjvb4yw+QdFAJOa4JmBGd6h7klclUD5BFR8aUx9Y+SckYwtrTlvsaeBrX3brBeeXbxo7qJEY1NR1Lulfv2Hr7rktms+UM3cHRYtBf1pM9uVZSEiUElaBDcGY3nmP3ZIkzuylPOVJC+7TCKUmY4r3goVKpGVGryJwE9AnZ8mK2lyCakmJXGol3m03XhKXLx4R0Qu5HYePzWk3vWleS9RbBaYGHozAUiFn6FOaDZRxY+uhwF1Ya3or+jUTrKwBKwVBqCscfeG2s25FOCAapbCMwVgyZ7hzkA842WCNNk0Ja1Nu3IPPfNqZc0ARnNPHhStKWPDCnvEmjl32BkglbwIDDRBJHAeESyPG1KVdu15BDNZr+ygZ8zmYHBdm/Xci6ueef31Nq+/nRXe7a1jBlV/aMY5F545qrbI8jOaL50XOlSCvqZcbHEFmmZDDOJSEIOg0qchnGEpoWFGp4uoplHgbfNEwyh/8CW+cttwWDoHLYx9NFsMA1cGRdOlEyDj6Wygiv5K0SSOEGR+GkkSlx+JarpmVRK+7IWCHi5bv5EAc8mzyQAHntgZimenyxHjjmA/DuR5n9uIw2G6shu9lrlXjPgCtB/96EeXLVv2qU996ic/+cmtt96KXvvjH//4pz/96a9+9StgFTszII1CjKLMjGjs0mjA2KJVCVYkZjyY2YyuBuww2XUcFgcQKEhAR1x1TUtEkCP3kEFIIiPV8iFNVAlgVBP17dht1xFg5oWTjgYzSZn4YjQ2M2MR9KvXW689/+riBa8N6B/50uc+ObqmwseRw2Je9rXLyX6yuZUQTNLMvPZi4ZVZNwaGASjRExn9E1DElwwlWKsMMAJ8ssUSp1xwl4sgKJvq4K7EoYACkFy8MYhuHvJveTD02p78IRMQUfNRX8lQMpMUuAvKyA8mE0rylBdckgHQZRy2F+5OyZtwrJQyV7c4RF6kIXcnqqavceSuJWNglHlzWjjDeRMAXsIaflxOPE1TiDc/mdyE1ZcfGCcD7TCQICZZdG692G8rmfGEIjmPdJaoLlLe2Wy9snjpr//6UHm/qgsmnjlz0plj+hWXkI1GIg1q0OyDalgjlnpjAGAjE+lKGP6Dj0ItMZQ8pQ0focXxla6W2gYMsw1JhOdHKcSiTRux52fhUSQJGjt3e7IlEmQ6PSMbrCVTZZ9Kod/BHiPSaOjc+NOUnb5B0LQsWyFGWddLeSEzGrRZQh85KK35MM5fF4AdVhx1B0iJgks2OpTLVhvMbcbmzP4bd955J8sf1UANxH7ta1+77777GBvGHP3LX/6S9cHgq+6QxVvAWEeOQWKwHGBGOXYB+KjX3wmSgYpCCiswjPAQQeaIbOGBiBJQxnbJW4UN48XNJGBkscRViWgDhhMnH5a/GrLAgxjMrkpmG9lc24za4sGBifVb25PNdeecfkoA9EV0Mi+MbSl9nDJn9uvSfGRdqVhTSVTThXSRnaY0QrUEYx+NZhnTRS7mkLCcSMyPgOYyQhoTr4ZF83JSKCCxK9EdLxXAlEGaaF7oCx9F+itXTDENPejism7Y8BnyCI7EJ2w+dt52Sh4aVYvmZKnhnEcN5jyCBx52E4NZgpSElfFIMtdEctgLcuw+wTN+aWaUy5aK0XLZBI2dbukb6FQxbMDpdDREQFoF5mtGyFkGqz0NJgqXGgw2qUqvIk+CgCYatnAzlfN62R/KK9D+zvbN8XRm9IAhZWx+QSSswFw4UByNfd0kJH6maFDBIl6S5YkfLBSHNEN9UNwljv6U3XsHYGGIQC+lgOdmyh5L6zAUc+AYi8Zk0xJprrlY0hPkcDfc5CgTzOgUKgCH6Hnogma0XQ+LvmXDONLirdJHZYLTsm0ZJHFBkpJrngpvLgAXcuNouYFJIFM3ngRBcevQryIxu0Bjl0a7JXtw1FlrhDYMJBMXTVcV30L6tOYwXADAR3Uv6MJMXffxyQEVE1q2QklR6O+UXEQb0kYFIqFFGjov8w5HCpMEakkHAOcD2H8LctMoxl+EuCiKiDxZxWtWWJJEEb5sbNDcFGKpBwfagMJ+hinl5D6hx9CCkqTEScaGMu72gC6p8mNokmW/UgQjylmwKrpPvgj5OIzzEYIfL8gab73y4fLPNh/sRzU2m9N+JX2jq1EQZL6E4yK6Kqa2uoaXEMokLzafQprzbChQAAYyRa+TuNy5NBGjW5G+6lrmlb42YUggTy3BU7JVpcwE5h1dEdCXIU6bRXhBTyaZBnGYTyLBRGvzx5O5jJfJxV7DWBAalCIpNuBgbBgiNXmlljSAVfYiE8aYFwWaPV5sQ0F4swZEEsHCYNsiyJux+QC7cmtyoCGIRf3aRSU9Of2ZDoKgm7GmCPPMDC0xbPBatiOjXPw0ljKB9gkumjd4c+l7HBLf1LoxLJtyaUyaBIHodnHnqBnKGIAjMiGPmV2ouqTTEVdyU8CVJPG3q0waFsUTD2058sa8o91KC+3uOi4BeK9fe3cc6Ak/EJdsMBRzh+PssMEEZlATSAZinTMYQFnQ1xkMUNgGX4kIYDOQDEg7bzVNsFmxvCeK4eZxonFARSOlVtHWufgql1TKGUHUOYD9TDLdJ2D87UwEfjQpI7TY6D/GAlkfw2nAAr94a7KE+T9sy1xcRrqtySSHUxEjyzJg2SxaiREyEHaapmAXopq7ZA9CI5rNBFqzeaWdL3+cfIVeuyAqMe0w4t/1UnM1/mSdp1xyVOwGh4zYlcQF1XhjBzKJSmSDWuYJ3dQMG2ruaPFcBoOFcHOZ4LYbzd24SM9Qq09613AmASdD28ZujPYahffE1OnKTHuW4EQHA2UxlzdcJIDKEposG+hm6AWZbSaIIDo0DOXOT7olaBZ2x8cmjWSpR1VPOayBeeQIPZI2qEyJ6JOw+IndKFnNE+TISzbAAoLZzUXgFNzSIBpD/KDMTH4yk6K0aoQOQ34+SyWBu3CA/1AoNc+lEXDsCQmQbN5I/4aL9SlssMWMM2NOl/XkJAP6Bqg2dHyo0otEqEUqhx4cnIIIOm5Kina8TC70GMSaYeagCXLTbemcfz7B4/XvntzuA6UEOzEXy4qLDHt5ywwJnYoF9LInJaCLJ4v61VP1XYBWCeetIrGqyKQA9HI5SMzbPlBEl4TjigOdmhRSRi77Dy4aJ9LbkW/mLe+N9FMZaKShiSKeohkUpmk3bhNPUzF9VJzyJsaSJE7ZASxzKVbpoZ8Fvb4oc4FkN0V2LvZxS4LNhpAQg8CcUSNZocaarYdAPs1M75CtlNvKJC9F0VJ4Nq/SMmlXBKVekEE6GCWNSpSfRZV/K3+NwFUPLYrmZNz0JLKMNGmxjJpocucm8l7wmB/ZmQ6BpOFPyrxskVpKqep3PNqcUSCXkM6FImuwRmg2lIsQUEqgmXekRm6ixrHOWVCCn5OgQQ4e29pa/UVFbLQi1HNohJclVBgc0j5PXM5QQhJxuBI/YZUcoMvxzuShRdU7FQGRzF42ycsrJ4DEIgWTKYPNbGSFfKNWgVurtIwMmdpMrEq/WYfGkjTAPhBmETP2CEnNcEiqFDj3BWSFkQE/J30cBCGoQL5GydsxeMVFDEkH9d2my/iqt0eMxgTjRwJ+xrAZojZzt7RccYCX41JZhWwSsZMiuKje0klB6zeepoWg2YuFnxVQMrEc+yY7kmJXCQmB0G/wSBmkJBzv9z4HwGAn1mZVVcFO+A8ecwc72VRWfXATgO01ODdJ3wKxwC3+PGp0AuDW8KZtS026ACxccK+jyQFEuhpO85kgfLhULnHXRxV45o2qswgzVeaMX+GNCMi+fLTCN7hZKWA2tRedhtk7Kk7lxDcrxMaU+Mj80oicsoc5ujlUytkEYiFFEHNXpUZSlNwLSOKzM5+e/Ur+CA35S23Q0lGwfVQSE8KofHjmX+RjFP61GaTFMsin0cnUcUhxSI5n7ooK3OUCIxHVhNUseI1DxITenURMUHlBGk6ywiJGkQ1eiScSX3lg9GR8sKXbSqQkaLJQSrDJ0VFgKlYqiU5nznsC7LxoCnAxl0H9TTOkzjlF7LJCMDYZM6Rr5qRj0rZpNm+UfMmFi8BciRTbmGXYlDHoi0C4DsAJl00XhnRx+JislU6WBFnXzVgvfuinHNWq2GZSISeSM42QPIiOh176RinBx2C6QqO+Vyrs8oqXsLWje8ZrEuS0K8oMB9mWnP4GQdjuUwtDUIkhGRAW0iRDH/oxf51L3NAE1fhjyWfA2sSmmRKO45DUUO2EP94dfQ6AYbgqvo65WM8WVCjV6tDTgvWuPg7EOtFxgMpOIhrMvbscOFwOiIzZ4+rioZJLw9iiKR9GHwui2y+M8md7S5h8+A6vTj7mhYQUAOGdTJ2WMUs7AkoQko79ltgrUcU3odjw0JgBTSBDCRH5FcpHO755a+Qq70XL7FDheaWIoEE1HXPP4zkPxCq4zFvn2Xmn4Lfny3wohyEkqukqlbZp2EnDie347JE3vvqC2GJKxfyOnqZIo6/wJIRJxhQT5ijSQImJ6lAipHl9Xjb3JjFoygeTAIwAi43BWAr0lTyZS3LOAzAedpoduUogLSEbZ8l4qh3GVjy0gLI+1sRkQrvZzcrGPBPYUEgSGpRgJqSmY0fnIU+wIVu98bMdNlXyBx+HP/IWP9LmrlAhKq15LDeznuXBPBLU6bNJIiZF+52GsCvQzlFS1bQkEE9OAfT5RLn3RQA+UXjvlvOE4IAjcfZd2n0Fc6RZ1yTsV7b9suA9L8w7birfzaPkYkdxwnZ+1hd5eoAlEycfSv3zbzVs/l13T+qn9z1j7Se0E9hxSAS7LBp33/dCqsQNKhQkVfiWl/poCtsli4JYJkcNWxCsI0CXV/sisRMJ3Qa1w3QEtfPq8CggvmsKhcGU4DzZHTQXxDKehVwy70gkH8sO2+mxIIU8J/PQLq+UiA5Sus16jzROnAeXFydOXbsldTngcsDlgMuBPsQBF4D7UGW4pLgccDngcsDlwInDAReAT5y6dkvqcsDlgMsBlwN9iAMuAPehynBJcTngcsDlgMuBE4cDLgCfOHXtltTlgMsBlwMuB/oQB1wA7kOV4ZLicsDlgMsBlwMnDgeOWwBmSbsuAsbhrBLWxcQc1cBmHbp/Fg4qe98bdLA5lzYIDcY+XIVRNJ3CAOruO3eX/l6si8Km5TSVbhuSU029SG3XrI91+ruWSH20Ljj0RT9nNpPHn70v9ha+r/mfgPQjxnW3JZXnuue/inTlBhuEOZ9YX6uvvdFz3AKwA7pIEBUiVB4X/jyyiYcGCHNqtjnXYW8MIopubMlpxFq7GqWwpjV9UnAce0ut5/1d+nue54U5Ok3CcfC2U0OiaeFJM6OyCuP2BbdDtuM4tujfGw/5/PXINf2c2e2Hw110W729RelT/icg/bRAvQorAh+V5KAv+3fqToiqVhUG67Pu43YjDmfnLBzIO7RhpJvW1vz580eNGsWH19TUxK5bfHu4+fy6rSQOgaisrCQu1cyd/aipXQ6HoL51q0sVpo627eTbbWo97+nS3/M8L8yRJue0DfxpRfjQeUdYcMoIzY9NzlWYEgwk1mNIClPoXfexTv/euMdGthwiDsP5YPn2qQV2kt+xY4fi8d5i9R3/E41+FeO0Rhx8KfoR6W6dVBk+CrqIaIwZehxt36msfVFCSY7viyrhoozUkKLs4MGDHY7otpfah3I8Cx3OhtJ4qiTt16+fE8CBWxyO23nbFxwu/b1eC4Vto7CRaEPSRgWRvKKyep3argQc6/R3LRE+qi0p3ILE3Ybpy54nMv2FHxF8WLBgAcYMB8U4E89x930Hh2TpHp19ubEdGdooKT2m9evXo2SgwkYiEaoN/RUdUY3M3WajJy8RBfwmOuJy5cqVU6ZM2b59O+CNxCQFUgbCaRa4CxtHtwn2sKdLfw8zvFN22ja4a9ugndCKaEv9+/fHEjN27Fh6h7Qi2hLtELNKX9PAjnX6O1WH84iyO3z4cKQB3XHcaMB82vCf8jph+rLjBKSfquHS7qC6uaNTqUKF4sunhFTvy7XWlbbjFoC1qroWGB/qiS8NOYg01Aqj8lQV7hqe+sbag5maBImCg7jEamhoQFaqyqKylZCE6ZpC7/q49Pcu/8ldGwZtQw0ttCJ6RUh8+n/032l7tCLC4GBqQt9sQlDFdYzS320DoA/E96tVoF8xo0vYJChmt+H7mqdLv9YI0hhW8B2piOY7wp9qPVaQuC+avI5IWzcSwxYZhQnSY2KwR+1+yEHqj8rj0porDKlu/SBV9BAL+wZ4DOLy1omCQ91675pIL/q49Pci852sCxuGumlC9OFA3MLxKiqrMKQTvdcdhVQdi/R3ZSDzP5ADSGo+ap3SAfpSKfqldw3f13xc+rVGUJwc3YkuLNVHd+pYQV+KcNzOgtbqUfjhzqelbr466gkQJQBdYIVSDdztHX0FKckrvlXuiEu1V5OaJohnobvbRHrR06W/F5nvZF3YQhw3DUnRV5sWzYzKcqL0KYdDM1Q57mOI/q7M5NvXuVegL0KALjjLwI4V9KU4JzL9TguED6i/+tXwEcETwBi1qmt191mf4xaA+Za4tLfO3XFTExgrFFPVzZ23e6shvky0ZC56VSA3A3U4/t//+3+ITrpaNAUiYtMmi765jhP66W0o/ZBKx5myQz9FVrmPJ6VQRu2NCb3oD/2wFwJgO6XAAf3//u//zl0th9QIZeGVdqp6kdRus8Zkgr+2QBzIC8hG6/rqV7+q/XQCqIP2Q2G7TaR3PeEt9FMLsBpKIB7mf/vb3wa3uPBB8FGu3iVyb7k7rUIrglI43+kPf/hDRlKJyIfARX9CP+e9JdUr/nujH/nz3e9+l4n0UKXiy+m9UUaqjHshUPUK8WTqsBRHYSPhK/jBD36gs2Khf+fOnarYdKXTaWbOK1ojlz6CuCoH9CPC03E44fuyoy8OW/YpfvG5qsShQeOANho6Laa+vh6blbYDvm1EJ2KIrwXZ1Kfop/lCMM2UJl5dXa20FdKJIVQ7E3welMJp2X2qFEoMUlK/LkilCvikFZ61Xuge0fntgzNalWwqArFI589hLPP4EDrM78Oft4WvnDC97qBt0zycBgOpsJ3mBLeVYP0ueEQOUoo+2Idwmg3kwU9aDt1Q2gllgVraDF8u/nQvKNexQj8tB4JpPDR+mE+hoJwC4ihsM06RCz170q1SBTJwqGyEWiSSTmstbEgUh4rQb7mQQtobV6dyFQY4pt0uAO+/+vRD1eZOaHrNNTU1Gg3xREuicfRZGepIHxw0d6QkXYeqqiqKA9bS3FWMIpJ429d6DzCZb5XPj24Qs5aU5yo9ceOPBoA/nzfdC+YVa4C+dtdpB1BFFcBteA6e0WAYDVFP7VU4Dayv0e/QQy1AP4KeStGPguak2AwME6yr9HTi9q4DgqFQm3ohJQ7ZOPiWMUcXvu077r3RrxQq7lIjCCI+6kKsolz46NW7xdHP1unlOx8FVGkT4nOGzq5E4s9VWKiuYY5dHxeAD6ju+ACQNTRxum+ISx4VwPSLpVUVduUOKMUeDKTdT+3ma7boXoVwRaFUNhV+FT1I4AFlpUx2JJGjkxHZgS7wuK/JUG05DofBsE6mNkQk8oXW5ZTigNjRU4GgCtlHzwz+44BOB7SUBCwofBFdsa2nCNxPPmy1wUY6BNKKwKENCQe6L266QXzXiH6Ktp+0euP1vunXj5r2A/3btm2rra2lmHSDeOSrh17FLaqst/pG2n6gU8FV+wrKSHVzh36Vq4A01aEhHWbzFncnT+ftse7Yw15xrBfmaNDPx0mytA/u9P2RnrRpGjSKF0JHxzCQqrzlke/5aNBwOGnyQarcJBHKop8l6Is2BrVaOnoP6o82fzh5HY24fMB8gdwhkvSRkvAZ4oEERD8+GCT0FV9vX0NfJZg74k/bBsRTI/jQomA+3QheKaSpHsyrPnXRJGA1NHMpRNHaoRn6aTPQrx+CSsk+RbkSA/pqI4d4+meUgtZC++EtqKAl0qIRjJVIfa0Ie6MfmqFfa4GWT12AvhBPicAqqkMblRZHv+5eKZq2H80aarVDQBPC3uC4aU5q+dfxo05t6XiFXuWJC8D7aZYqN2lGdDAJitDH2olI4ltVwYQnHwmSiOalSLCfFHv2tYoY7nyltHJHyiDuoRYfpBJNnI+BEvEl9Cx1+88NzkOeloLuDvQjehSr1CjNcICWog+O/lI82g/iBvrhMHJQSUU4gsS4leGE4RXFpC72z5GeDQGp8BzEgufQSRXAZ0YxoJ8SQT/iEn8VmkjVnqXugHKDSJ0ZS/+MiuA71fbjNCT9bKkO3ZvsgBLtwUDd0q9fhNYC5aIuVBlQumhLxOKuj50grQdpt7RJQwmtyKEHNYaJBTQqOtY6EANJ6PrcuyXVidiTlPdMXi4A74fPAABNBxGj2tUvfvGLyy67jC/2kksueeaZZ4Be/bYB4z6IvpQN4mnlOJCbNO677rrrAx/4AB/ngAED/uM//gN/ykXvAUffpP+JJ5647rrrTjvtND7Cxx9/HCmJrKFQEPzKK6/cdNNNarM655xzEEBqiuBV37l+9rOfXXrppRBPR+GWW25ZsmQJUh7+Q+HWrVvhOdBLKfChOWkb6zvEQwmE0eavueYaZvAh7i+//PJZs2Yxh4BRjM997nOTJk2iCDNmzPjHf/xHdohDqvYp4iEGlKXBaNumefzTP/3TyJEjP/nJT/IKDKPT+cUvfpGeHBV0ww03bNq06RiiH1LfffddyB46dChF4BN4+OGH6WcrhlFqB8y0vfVK0WjSCM/vfOc7VAHNBj5D2CmnnEKzpzkhXf/6178iUVHfR48efcEFF/QKkb2YaV8c9uhFdnTNGg0AoY8/X/JDDz30ve997+677542bdof/vCHD33oQxs2bECwqu5L26LFc++aSC/6QDwXpYDIH//4xz/60Y/uu+++M844g30Q/+Ef/oFXX//61+k9QCHfQy/SubeskZITJ0786Ec/iqA5+eST+W5BX0hds2bNRz7ykdtuu+3555/n6129ejXq16BBg/aWTm/5I1++9KUvjRgxAibfcccdtJlly5ahAVCKgQMHAgn33nuvtplCDaa3qO023yFDhrBuDZ6PGTPmpz/96bXXXrtixQqkKujFSh6AGbMQbQn6f/3rXyNSu02ktzxpP3SRFYMXL1788ssv0x896aST+FTpd37/+99/4IEH6OSBE5///OdpY3Pnzu0tUrvNd2/0ExiJ9JWvfGXdunWPPfYYOj3o+/GPf/ydd94BbnWegZpVaF29CMC0E+iklzxu3LgXXniB4qD4ogxAG+5XX3319ttv//KXv4xo4vulV0e5+qAU7bZqjownpXWvfXOAD5UAtJiLL774E5/4hAbmq0Yw/fd//7d2ObGf4I9U3XdSvfgWufPhD3/4C1/4AkgMGUDy9ddff+utt+JQqihgL5K3j6z5hnkLgKF7qRvcQpu88cYb8aciuHDoq32k0yuvtHlAMLmDWHy0wAAEK7cR93Tg8Ae3HnnkEURVrxC5j0y1eRRyGPUFoNUo+CvbH3zwQTAMJN5HUr3yCpYqq5HvdCDmzZt36qmnIvEhhg8BZHr00Uf1A1+6dCm18NJLL/GqsCKI3otNax/0g2Q0nl/+8pdaO9AJsP3+97+HfvVxCuJ84/j0/EURvvGNb9CNVq5CttIA/y+88EK6p/pIBanDCeCI017k/9Fml2uC3n8/Rqca0jujBwdiIVI1DuY4hCZ9TxoW0of2RJ9u/8n1bAi1P9OMoJNO6P3338+sJVo2ujtd5g9+8IMoB1CE+sJH27OkHVBufHuo6YhIlZJ055EmCEokPmdKXnXVVWzFfu655z799NP4UxEHlGgPBtIhLgjevHkzQ6c6+og2qfWCyoLEJAyPgAFXD5J2QFkh1gmnhFERf/nLX957772LLroITxo8Ply4N27cqF/BASXas4FoM5D6qU99CkM6pghmINKoIGHOnDm0Gb5iPnA+ar4OFEfsE7wlvBacD4foWsaepbojt27phzy6pKjymLL4nAmNKk8/7/zzz8etBFM6Kk4L25Fcz7rIHRoYm8BaTjvH/k9F0AeFCkQQ3R2scXy/lPHTn/70U089BcMpF5QTAE/u+PQu/6Hh6F0uAO+HtzRu2jp3WgMtg6FTGhNYhQzF+MYrQJc7b2ln+iXsJ8WefY3oh1rI4/7tb38bgw8jRhDPUTB//OMfEUmQw0dC0bj6oBVUP0LtJeCG23yQjJ7C89/+9rdnnXUWJmhgDCRmSLgPdoCgVuehYB7H2j958mTGusAqZD0jkYzboQQgX7iAAQrVs61j/7kpS5GVMJ+BRqTnwoULsf1QBKjVeqGA2KIZEu6DHSC+SqoAcKLfyQZqTNpwvlOMt4zHMzZJs0d3xJ+xDIaBKTKeWjSQGB6Rwv45dXRC7I1+WE2nDRMuk0ORSGAbAAae8V1DiBKvzYmvWx+PDoH7SRVOInkYPPrTn/6EjYHxOzQZRo5oUaAshDG6wRwIhpCY53HllVdytiApaqeBsuPug41qP2U+mNd9TmM7GOJ7IiySkWyQPjhQwhhi4Qg5ZCWtH7lDG6Kt0MgIw3erHbeeIOtg8oBagnNHawS0GDFCa6Snz4QUbIZ33nmn0s/nqvrZwaR91MPCdrgK/yESVuPms6Qi6Osw9wfTFhTw6f7tb39DOTv99NML1zcfdeIOIAMIVusIU96YZoV80erA8okGhlqADGJePcxH1lMo+kYHkGrPBcEeSKsAn+rq6kAspkHQ6WEMGHOug80MbWDXZTy1D7Z/rA60FiYB0fK1ndOKoBxPysXIEc0J9IKhfAv4gLXUCJeyWKGX2lEw6Dm+53PaG/2UhYtxa5CMLhHkMUWR2UxgMJ086Ae3lObeolxLQKumwTOPkrYN2xm/4CPFDvH666/TjYOx6ADM4KM6sEX/+c9/phTQny+9/CVM4ePx5qaFude+OUAPjgBqeX722Wdxqw+tn2l7GpdONE1t3+n01luoVdrA3f/6r/+iQSslbEc8depU5A5vob+3yDvAfBE3s2fPdkYZ0SCR+MRF0ED/1772NTDgAJPq+WD0chBDyCCypuvGnekz9CqQJqiVyH3MD7jR43uetv3mSEeTMJg3YTWO6dOno0oiMXGDygjQK664AlSjXE7T2m+aPRkAma5Sm/avfAZxgSiwiu4OA/AQwzdC6bBCs0Exj5ROy6JV1rvl6pZ+SrRlyxbu9IogEoIpAksz6FUrtV1HUnuS505eykDI0yFe7vTS6DojPPmWoZ+BMAgmGATzmTCz0hGkGldbnZPgceZwTdD6be7rjnDhNbbcmTNn8jEgifhuae5MhGbaJK9oUliBcNA49pVQb7yjjw+1UAht9Kbpe6rchxa6xvign9HQoZ+PxBne7g1Ku89TreJUARdCE1UManEzdETHH6HPBTYvX74cAO4+id72xUL+f//3fxjZlFrgFkhjXvf777+PUQ7d/c0334T5qGh0j3qb2G7yp6+DL+1fdSka0qJFi7gjMZkRjc2WmRAIVsrVBzVgvlM+W5oHrMb2g80Wsz9AtWrVKsYCkPWYJagXvpG1a9ei2fOWwlJSPhPKqFp+N0zpKa+90Y8Fi0+D3humdYjk06AIXHzC+oHjA41gG4/ce4rezvkoA2ketCK+XO6UCDsQFhTcDAGweg0KCUbfCDDGvugkwUeBu3c1eIeYo+WgkbnXPjhAc3He3nPPPbT4//3f/0WYonJRJXQ/+Ya1c0ewvtlZQ0RqEW6++WYa/ZNPPsk8GsQ9k5jocgJmvOW77ZvEIzuYZsL4LosIf/7znyN3mO8DwcwmA3eZFgcY/OpXv6IugLHCytIi9/qdaedIGQwngC6mZgbAECvatdep0VCIP+jFgqVep7YrAVD7L//yL+AWpk7kJvOHEZSAGUXAlnj22WfTDaJoBMOza/Re96H9aKvQj5TWzqD7v/3bv4Fb0EbtMDv3ueeeYzo6ZcEgpJ8DsXirX4SjkPVKWfZGP8TQe2ZslVXmzGnii9beW2ErcsrSi5+20v+tb32LARe6OHzI7EOAFEL9hSq+aL5ctBro/+Y3v4kyQCuiLSmrHSW+VzjfM5mK0uZe++YAH7DzEdLKMWRhTqSnxgCeapZEV5G673R68S2dZUhFBtFvYB4Z2gz0I4bo+zvEE8Bp+r1Iaqes+WL5RFluwZ2L7vBnP/tZFamsAcOfj3b8+PEoN50i9pFHaEYvUcq5M6RNN05pg+HUi8p6XgED6u4jlDtkoKwj6KGQAbzzzjuPgQBEJ10ffFCzuNBguPOITu/E6jsOuKqfp+IQAMyqZciD+XwRzF2iFVEvFJOZ6uqvH4ICQK9/FN3Sr2VBj2dlOVoB9DOXmGmV0O/IIqeH1+t1gaWQ75R2QncH8wPGc+jXIrCynHkb9Oro/bBKG1I7KQMUX3sSvV6Ko0GAmFn4ctzL5YDLAZcDLgdcDrgc6EkOuGPAPcltNy+XAy4HXA64HHA5YHPABWC3KbgccDngcsDlgMuBXuCAC8C9wHQ3S5cDLgdcDrgccDngArDbBlwOuBxwOeBywOVAL3DABeBeYLqbpcsBlwMuB1wOuBxwAdhtAy4HXA64HHA54HKgFzjgAnAvMN3N0uWAywGXAy4HXA64AOy2AZcDvcABTvTj+CDNmK0GcLDtA3f2GOFeuDpft8xlyxT82VqBu16F+4Y6sYjIrgUagI0+2KNK3eyBwLHz6uZOGPaXcB41Oo96YjERdesDfBxK2N6BR145Pk501+FywOXAoXHABeBD45sby+XAYXGA3aF//OMfs8Ma20v94he/AH3ZjZLNBfWsJOBWcRSUZZ8j9gxi8zLy00212L8JN9ticyckUKqx2NoJoGWHTk5e4qRYdg1jgyECa2qcYkR4xVqAnFc8sq8nd6Jrmuyaqb0BEiEpsF+7BaTMbr1AL2k6AE9E93I54HLgcDjgHkd4ONxz47ocOEQOsP2hqpJolqAaFwmx3zUqJljIvn08AnuKsrqjPciHA0+gGphk90dO2uCAW0ICk0AmgXFwcbQGG47iL9vz58831JBgLaivbjLiSDiCgdBEIX0SIVngmSwgDOznrZMLbsgjQRRrpRAf93I54HLgkDngasCHzDo3osuBQ+cAO+KyIzHnpHJUxh133AFeonGCnSAxR31wJg+PnPh0++23c34D2YB8EyZM4ATJr3/966AmGxeD3+yjO2zYMFBzypQpHGyOugxwcigFxwW+9dZbpMDj7373OxAU3OUQDoV8DrTggCAyAkRvueUWcBfQBdHZFZmj0f/1X/+VQ905NYszGEBi1GvQGh0dlZpguDkwzkXfQ694N6bLgQIOuABcwAzX6XKgpzgA4IGpABsI+qMf/YgznVArgUz2qb/88suBZ47rYdQW/+9+97toqOAlATjrBgjE/4c//CGqMMoopmx25OckmVmzZn3ve9+DfPa7//u//3vu27ZtIzUglihovWrE3rp166233lpdXc35PxxQAxizUT7maMCVLB544AEwm+MWOGuZ09H/9Kc/8YowDFdz9IWe/Y4pm9R6ik9uPi4HjmcOuCbo47l23bL1WQ6AqbW1tRiN0UoBY/RLdE3Q7itf+cqVV17J8W2qDQO0HHfDI9jMoTEoppyg5yigKMQUEEvy9ddfz0lEwDOPnFykAQjP4LFOniKjuro68uIUIzTsefPmcSQcgdGVb7zxRlB54MCBPKJJf+lLX8IcDcr+5S9/AaRvu+02gBwFmqN/oQGq0IzpOhDYvVwOuBw4TA64AHyYDHSjuxw4FA4wvIptGcTFAgxGooCioWLyZVYUWi9QBzwDyaWlpRiWuYBVNGCOMQdceQQ+UVg5wJyZXJw2DyIyu4pEIAU3mjGKLBhPmiROeNRlIhKA81axbxOdYKTAIbhgMwfRQw/wTBgi6qtBgwZx0CwUgsqcXY8affXVV3McISZoEPpQyuzGcTngcmBPDrgm6D354T65HOgRDgCuOrUKJRWURQnmAhdRN1FnUUk5CBltlRNSVT3VGVIoyuigQCaxFixYgPWY89jRUxcuXIilGrjFn4ukCAYM4wZBCa/YjCd4zJgxAbSU2KKBZwCVYPig6YLKXGSHDw48gWSQ+MEHH2SOGBr5+eefjy26R5jkZuJy4DjngKsBH+cV7Bavb3IA9EXNhTZADo0TpAQXQcdJkyZhTGZOFpf6g6PopgRGAwZHFRR5xTQr1GJGf4FVMJLJXKi8mizYiUKMGxwlCwJzkQjBmMl1zz33MIhLGO7PPvssDvLCTQBNHJs2kAxJJEh0DnvnLcPSXN/5zneA+XfeeWfo0KF9k7EuVS4HjiEOuBrwMVRZLqnHDwewNoOslIcpx8xbBuGYSwXUsYQXE/Sdd97JMC026scff/yf//mfgU9CEh5Y1VhAKQuZ1q9f/9hjjxHx/vvv/+Mf/4imSzB0a8zXaNKoxbrMV2GViOAxBmTGhjEmr1y5EtWZMWDcTKvmLWmiGQPD6MHQA+RjheaR6V2/+c1vlixZwmwsHOjBhD9+asIticuB3uOAC8C9x3s35xOYA4y5qln4Bz/4AQolVmjmLYN2Y8eOffTRR5knhboJ/vF28ODB4CJgjFaKjRr3zp074RxLmMBm5kZ97GMf++1vf8u8ZeAZf8JgxL744ot5xZjx3XffTRQdUQbg0V8feeQRshs3btxVV101efLkn/zkJ8RiDyz0b6CazTcIBh4Ta/PmzcAweAzMT58+fdq0acRlRhikEsW9XA64HDhMDnj45g8zCTe6ywGXAwfLAVRMEE6HYwE8ouucKb5HNU3jA6ACfsxexkTMI0oz4KoZ6WdLSJRjVXD1LXfSQcfFH4B3AqAQg8EaF9sy1mngVvNVgzOv8FELNrSRJkkxJwu36twaV0nSFNTHvbsccDlwyBxwAfiQWedGdDlwuBwA8xSGcQDGJAfsAX5AI/5cADCeOmNLB4AJSQBwkbFbJ3sdBuaVYqrO2FKw1OgEZrIVeIzuy4xogJzUCEBIfLjzCPoC24q4CuoALT6kqXeSIgp4DPwT3snddbgccDlwaBxwv6JD45sby+XAEeAA2AaeobOCviAfKQKNgCXIhw8XE7LwxMEdUASSFSwJA+iCi+zXwSuGb7mTgmrG3EkB8AYv8VccZYQYrOUVd4VPUsNNANIEfXGQBfQo+vKIJ48Ehk6y4yJNUNxFX5jjXi4HDp8DrgZ8+Dx0U3A5cNAcAPPQa3XalEYG3hRHde9lsBOcA3rRa8E8sJBZ0NiECazW5sIsSc1Rl1UPxoe4JKI6tD46KjIOfHgF1qoJWhVfJ01Fbo2LxszwMzTwllzoLvDohHQdLgdcDhwyB1wN+JBZ50Z0OXDoHAAdQV+AEEgjFUAO9AX2eGTLC0AO8CMMj4RR9RTYUwUX9Rd/AFvj4iAk4dF0SQptlSiqpOKJG08C6OwqTYEozMYCdMFykuWRWATTwIQhIhcaNp5AL5cq6DwSXuEZt3u5HHA5cDgccDXgw+GeG9flgMsBlwMuB1wOHCIHXA34EBnnRnM54HLA5YDLAZcDh8MBF4APh3tuXJcDLgdcDrgccDlwiBxwAfgQGedGczngcsDlgMsBlwOHwwEXgA+He25clwMuB1wOuBxwOXCIHHAB+BAZ50ZzOeBywOWAywGXA4fDAReAD4d7blyXAy4HXA64HHA5cIgccAH4EBnnRnM54HLA5YDLAZcDh8OB/x+8gzH3aID39AAAAABJRU5ErkJggg==", "text/plain": [ - "" + "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 12, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "result.convergence_graph" + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(nrows=1, ncols=1)\n", + "axes.plot(cost_values)\n", + "axes.set_xlabel(\"Iterations\")\n", + "axes.set_ylabel(\"Cost\")\n", + "axes.set_title(\"Cost convergence\")" ] }, { @@ -468,22 +359,14 @@ "id": "670eddd3-2da7-4a88-b571-7884ef24f60c", "metadata": {}, "source": [ - "We can also examine the statistics of the algorithm:" + "We can also examine the statistics of the algorithm. In order to get samples with the optimized parameters, we call the `get_results` method:" ] }, { "cell_type": "code", - "execution_count": 13, - "id": "516d78ba-2951-46eb-b1af-efe877513556", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:47:48.667430Z", - "iopub.status.busy": "2024-05-07T15:47:48.666357Z", - "iopub.status.idle": "2024-05-07T15:47:50.023109Z", - "shell.execute_reply": "2024-05-07T15:47:50.022422Z" - }, - "tags": [] - }, + "execution_count": 10, + "id": "9638f749-a60b-4176-a4ea-50d7c2bb986f", + "metadata": {}, "outputs": [ { "data": { @@ -506,78 +389,63 @@ " \n", " \n", " \n", + " solution\n", " probability\n", " cost\n", - " solution\n", - " count\n", " \n", " \n", " \n", " \n", - " 118\n", - " 0.001\n", - " 4.0\n", - " [0, 0, 0, 0, 1, 1, 1, 1]\n", - " 1\n", + " 1726\n", + " {'x_0': 1, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'...\n", + " 0.000488\n", + " 5.0\n", " \n", " \n", - " 986\n", - " 0.001\n", - " 14.0\n", - " [0, 0, 0, 0, 1, 1, 1, 1]\n", - " 1\n", + " 581\n", + " {'x_0': 1, 'x_1': 0, 'x_2': 1, 'x_3': 1, 'x_4'...\n", + " 0.000488\n", + " 5.0\n", " \n", " \n", - " 524\n", - " 0.001\n", - " 14.0\n", - " [0, 0, 0, 0, 1, 1, 1, 1]\n", - " 1\n", + " 5\n", + " {'x_0': 1, 'x_1': 0, 'x_2': 1, 'x_3': 1, 'x_4'...\n", + " 0.000977\n", + " 5.0\n", " \n", " \n", - " 142\n", - " 0.001\n", - " 15.0\n", - " [0, 0, 0, 1, 1, 1, 1, 1]\n", - " 1\n", + " 1878\n", + " {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'...\n", + " 0.000488\n", + " 5.0\n", " \n", " \n", - " 37\n", - " 0.001\n", - " 15.0\n", - " [1, 1, 1, 1, 1, 0, 0, 0]\n", - " 1\n", + " 1454\n", + " {'x_0': 1, 'x_1': 0, 'x_2': 0, 'x_3': 0, 'x_4'...\n", + " 0.000488\n", + " 5.0\n", " \n", " \n", "\n", "" ], "text/plain": [ - " probability cost solution count\n", - "118 0.001 4.0 [0, 0, 0, 0, 1, 1, 1, 1] 1\n", - "986 0.001 14.0 [0, 0, 0, 0, 1, 1, 1, 1] 1\n", - "524 0.001 14.0 [0, 0, 0, 0, 1, 1, 1, 1] 1\n", - "142 0.001 15.0 [0, 0, 0, 1, 1, 1, 1, 1] 1\n", - "37 0.001 15.0 [1, 1, 1, 1, 1, 0, 0, 0] 1" + " solution probability cost\n", + "1726 {'x_0': 1, 'x_1': 1, 'x_2': 1, 'x_3': 1, 'x_4'... 0.000488 5.0\n", + "581 {'x_0': 1, 'x_1': 0, 'x_2': 1, 'x_3': 1, 'x_4'... 0.000488 5.0\n", + "5 {'x_0': 1, 'x_1': 0, 'x_2': 1, 'x_3': 1, 'x_4'... 0.000977 5.0\n", + "1878 {'x_0': 1, 'x_1': 1, 'x_2': 0, 'x_3': 1, 'x_4'... 0.000488 5.0\n", + "1454 {'x_0': 1, 'x_1': 0, 'x_2': 0, 'x_3': 0, 'x_4'... 0.000488 5.0" ] }, - "execution_count": 13, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import pandas as pd\n", - "\n", - "from classiq.applications.combinatorial_optimization import (\n", - " get_optimization_solution_from_pyo,\n", - ")\n", - "\n", - "solution = get_optimization_solution_from_pyo(\n", - " set_cover_model, vqe_result=result, penalty_energy=qaoa_config.penalty_energy\n", - ")\n", - "optimization_result = pd.DataFrame.from_records(solution)\n", - "optimization_result.sort_values(by=\"cost\", ascending=True).head(5)" + "optimization_result = combi.get_results()\n", + "optimization_result.sort_values(by=\"cost\").head(5)" ] }, { @@ -590,31 +458,15 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 11, "id": "31a4e74d-b2b8-42e0-826d-de7b51de1fe8", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:47:50.025530Z", - "iopub.status.busy": "2024-05-07T15:47:50.025337Z", - "iopub.status.idle": "2024-05-07T15:47:50.337003Z", - "shell.execute_reply": "2024-05-07T15:47:50.336242Z" - }, "tags": [] }, "outputs": [ { "data": { - "text/plain": [ - "array([[]], dtype=object)" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -624,7 +476,12 @@ } ], "source": [ - "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])" + "optimization_result[\"cost\"].plot(\n", + " kind=\"hist\", bins=30, edgecolor=\"black\", weights=optimization_result[\"probability\"]\n", + ")\n", + "plt.ylabel(\"Probability\", fontsize=16)\n", + "plt.xlabel(\"cost\", fontsize=16)\n", + "plt.tick_params(axis=\"both\", labelsize=14)" ] }, { @@ -637,40 +494,38 @@ }, { "cell_type": "code", - "execution_count": 15, - "id": "4326e84b-26f6-4ea9-a53b-090fb3658b8c", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:47:50.339966Z", - "iopub.status.busy": "2024-05-07T15:47:50.339479Z", - "iopub.status.idle": "2024-05-07T15:47:50.343195Z", - "shell.execute_reply": "2024-05-07T15:47:50.342571Z" - }, - "tags": [] - }, - "outputs": [], + "execution_count": 12, + "id": "187d0102-25db-499f-876d-63283db642a8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[1, 0, 1, 1, 0, 1, 0, 1]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "best_solution = optimization_result.solution[optimization_result.cost.idxmin()]" + "best_solution = optimization_result.solution[optimization_result.cost.idxmin()]\n", + "best_solution = [best_solution[f\"x_{i}\"] for i in range(len(best_solution))]\n", + "best_solution" ] }, { "cell_type": "code", - "execution_count": 16, - "id": "0d941c26-bbc6-403d-90d7-c061458e099f", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:47:50.345381Z", - "iopub.status.busy": "2024-05-07T15:47:50.345195Z", - "iopub.status.idle": "2024-05-07T15:47:50.348809Z", - "shell.execute_reply": "2024-05-07T15:47:50.348140Z" - } - }, + "execution_count": 13, + "id": "ea2eab42-51c7-4163-a79e-27051beaf19d", + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Quantum Solution: num_sets=4, sets=[[1, 6, 8], [3, 7, 9], [4, 7, 10], [2, 5, 8]]\n" + "Quantum Solution: num_sets=5, sets=[[1, 2, 3, 4], [6, 7], [8, 9, 10], [3, 7, 9], [2, 5, 8]]\n" ] } ], @@ -680,6 +535,14 @@ ")" ] }, + { + "cell_type": "markdown", + "id": "149932e1-bfa8-4c27-b5f9-037e74eba400", + "metadata": {}, + "source": [ + "## Comparison to a classical solver" + ] + }, { "cell_type": "markdown", "id": "dde1905d-aeff-4297-a9d3-ad14910e6161", @@ -690,15 +553,9 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 14, "id": "5a7ca4b6-25a0-46dd-b5cc-de6a639a6f57", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:47:50.352085Z", - "iopub.status.busy": "2024-05-07T15:47:50.351904Z", - "iopub.status.idle": "2024-05-07T15:47:50.430503Z", - "shell.execute_reply": "2024-05-07T15:47:50.429853Z" - }, "pycharm": { "name": "#%%\n" }, @@ -709,38 +566,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Model unknown\n", - "\n", - " Variables:\n", - " x : Size=8, Index=x_index\n", - " Key : Lower : Value : Upper : Fixed : Stale : Domain\n", - " 0 : 0 : 1.0 : 1 : False : False : Binary\n", - " 1 : 0 : 1.0 : 1 : False : False : Binary\n", - " 2 : 0 : 1.0 : 1 : False : False : Binary\n", - " 3 : 0 : 1.0 : 1 : False : False : Binary\n", - " 4 : 0 : 0.0 : 1 : False : False : Binary\n", - " 5 : 0 : 0.0 : 1 : False : False : Binary\n", - " 6 : 0 : 0.0 : 1 : False : False : Binary\n", - " 7 : 0 : 0.0 : 1 : False : False : Binary\n", - "\n", - " Objectives:\n", - " cost : Size=1, Index=None, Active=True\n", - " Key : Active : Value\n", - " None : True : 4.0\n", - "\n", - " Constraints:\n", - " independent_rule : Size=10\n", - " Key : Lower : Body : Upper\n", - " 1 : 1.0 : 1.0 : None\n", - " 2 : 1.0 : 2.0 : None\n", - " 3 : 1.0 : 2.0 : None\n", - " 4 : 1.0 : 2.0 : None\n", - " 5 : 1.0 : 1.0 : None\n", - " 6 : 1.0 : 1.0 : None\n", - " 7 : 1.0 : 1.0 : None\n", - " 8 : 1.0 : 1.0 : None\n", - " 9 : 1.0 : 1.0 : None\n", - " 10 : 1.0 : 1.0 : None\n" + "Classical solution: [1, 1, 1, 1, 0, 0, 0, 0]\n" ] } ], @@ -749,41 +575,17 @@ "\n", "solver = SolverFactory(\"couenne\")\n", "solver.solve(set_cover_model)\n", - "\n", - "set_cover_model.display()" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "2e5c1b07-6060-455d-81ed-e48a2207c81b", - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:47:50.435103Z", - "iopub.status.busy": "2024-05-07T15:47:50.433926Z", - "iopub.status.idle": "2024-05-07T15:47:50.439457Z", - "shell.execute_reply": "2024-05-07T15:47:50.438759Z" - }, - "tags": [] - }, - "outputs": [], - "source": [ "classical_solution = [\n", - " pyo.value(set_cover_model.x[i]) for i in range(len(set_cover_model.x))\n", - "]" + " int(pyo.value(set_cover_model.x[i])) for i in range(len(set_cover_model.x))\n", + "]\n", + "print(\"Classical solution:\", classical_solution)" ] }, { "cell_type": "code", - "execution_count": 19, - "id": "a7524894-b5c5-42d4-8f92-a019bef5e7da", + "execution_count": 15, + "id": "ac9b02a1-4293-4759-b41b-3a5d6d4101c1", "metadata": { - "execution": { - "iopub.execute_input": "2024-05-07T15:47:50.444336Z", - "iopub.status.busy": "2024-05-07T15:47:50.443142Z", - "iopub.status.idle": "2024-05-07T15:47:50.449865Z", - "shell.execute_reply": "2024-05-07T15:47:50.449249Z" - }, "tags": [] }, "outputs": [ @@ -814,7 +616,7 @@ "\n", "## References\n", "\n", - "[1]: [Set Cover Problem (Wikipedia)](https://en.wikipedia.org/wiki/Set_cover_problem)\n", + "[1]: [Integer Programming (Wikipedia).](https://en.wikipedia.org/wiki/Integer_programming)\n", "\n", "[2]: [Farhi, Edward, Jeffrey Goldstone, and Sam Gutmann. \"A quantum approximate optimization algorithm.\" arXiv preprint arXiv:1411.4028 (2014).](https://arxiv.org/abs/1411.4028)\n", "\n", @@ -838,7 +640,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" }, "vscode": { "interpreter": { diff --git a/applications/optimization/set_cover/set_cover.qmod b/applications/optimization/set_cover/set_cover.qmod index 963c97f44..423f9987e 100644 --- a/applications/optimization/set_cover/set_cover.qmod +++ b/applications/optimization/set_cover/set_cover.qmod @@ -1,2431 +1,38 @@ -hamiltonian: PauliTerm[] = [ - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=129.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=9.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=14.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=14.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=14.5 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - 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Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - }, - PauliTerm { - pauli=[ - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::Z, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I, - Pauli::I - ], - coefficient=-5.0 - } -]; - -qfunc main(params_list: real[6], output target: qbit[23]) { - allocate(target.len, target); - qaoa_penalty(target.len, params_list, hamiltonian, target); +qstruct QAOAVars { + x_0: qbit; + x_1: qbit; + x_2: qbit; + x_3: qbit; + x_4: qbit; + x_5: qbit; + x_6: qbit; + x_7: qbit; + independent_rule_1_slack_var_0: qbit; + independent_rule_2_slack_var_0: qbit; + independent_rule_2_slack_var_1: qbit; + independent_rule_3_slack_var_0: qbit; + independent_rule_3_slack_var_1: qbit; + independent_rule_4_slack_var_0: qbit; + independent_rule_4_slack_var_1: qbit; + independent_rule_5_slack_var_0: qbit; + independent_rule_6_slack_var_0: qbit; + independent_rule_7_slack_var_0: qbit; + independent_rule_7_slack_var_1: qbit; + independent_rule_8_slack_var_0: qbit; + independent_rule_8_slack_var_1: qbit; + independent_rule_9_slack_var_0: qbit; + independent_rule_10_slack_var_0: qbit; } -cscope ``` -vqe_result = vqe( -hamiltonian=hamiltonian, -maximize=False, -initial_point=[0.0, 0.06913183279742764, 0.03456591639871382, 0.03456591639871382, 0.06913183279742764, 0.0], -optimizer=Optimizer.COBYLA, -max_iteration=60, -tolerance=0.0, -step_size=0.0, -skip_compute_variance=False, -alpha_cvar=0.7 -) -save({"vqe_result": vqe_result, "hamiltonian": hamiltonian}) -``` + +qfunc main(params: real[6], output v: QAOAVars) { + allocate(v.size, v); + hadamard_transform(v); + repeat (i: 3) { + phase (-(((((((((((((((((v.x_0 + v.x_1) + v.x_2) + v.x_3) + v.x_4) + v.x_5) + v.x_6) + v.x_7) + (20 * ((((v.independent_rule_10_slack_var_0 - v.x_3) - v.x_6) + 1.0) ** 2))) + (20 * ((((v.independent_rule_1_slack_var_0 - v.x_0) - v.x_4) + 1.0) ** 2))) + (20 * ((((v.independent_rule_5_slack_var_0 - v.x_1) - v.x_7) + 1.0) ** 2))) + (20 * ((((v.independent_rule_6_slack_var_0 - v.x_2) - v.x_4) + 1.0) ** 2))) + (20 * ((((v.independent_rule_9_slack_var_0 - v.x_3) - v.x_5) + 1.0) ** 2))) + (20 * ((((((v.independent_rule_2_slack_var_0 + v.independent_rule_2_slack_var_1) - v.x_0) - v.x_1) - v.x_7) + 1.0) ** 2))) + (20 * ((((((v.independent_rule_3_slack_var_0 + v.independent_rule_3_slack_var_1) - v.x_0) - v.x_1) - v.x_5) + 1.0) ** 2))) + (20 * ((((((v.independent_rule_4_slack_var_0 + v.independent_rule_4_slack_var_1) - v.x_0) - v.x_1) - v.x_6) + 1.0) ** 2))) + (20 * ((((((v.independent_rule_7_slack_var_0 + v.independent_rule_7_slack_var_1) - v.x_2) - v.x_5) - v.x_6) + 1.0) ** 2))) + (20 * ((((((v.independent_rule_8_slack_var_0 + v.independent_rule_8_slack_var_1) - v.x_3) - v.x_4) - v.x_7) + 1.0) ** 2))), params[i]); + apply_to_all(lambda(q) { + RX(params[3 + i], q); + }, v); + } +} diff --git a/applications/optimization/set_cover/set_cover.synthesis_options.json b/applications/optimization/set_cover/set_cover.synthesis_options.json index 0967ef424..33a270955 100644 --- a/applications/optimization/set_cover/set_cover.synthesis_options.json +++ b/applications/optimization/set_cover/set_cover.synthesis_options.json @@ -1 +1,43 @@ -{} +{ + "constraints": { + "max_gate_count": {}, + "optimization_parameter": "no_opt" + }, + "preferences": { + "machine_precision": 8, + "custom_hardware_settings": { + "basis_gates": [ + "h", + "u2", + "sx", + "y", + "s", + "u", + "p", + "id", + "tdg", + "rx", + "cy", + "ry", + "rz", + "cx", + "z", + "sxdg", + "sdg", + "cz", + "x", + "u1", + "r", + "t" + ], + "is_symmetric_connectivity": true + }, + "debug_mode": true, + "synthesize_all_separately": false, + "output_format": ["qasm"], + "pretty_qasm": true, + "transpilation_option": "auto optimize", + "timeout_seconds": 300, + "random_seed": 4217730586 + } +} From d682c844485032cbbf7f0db5e501f65f9653dec6 Mon Sep 17 00:00:00 2001 From: Or Samimi Golan Date: Thu, 19 Dec 2024 17:44:07 +0200 Subject: [PATCH 32/32] partialy updated electric_grid_opt --- .../electric_grid_optimization.ipynb | 87 +++++++++++-------- .../electric_grid_optimization.qmod | 26 ++---- ...c_grid_optimization.synthesis_options.json | 34 ++++---- 3 files changed, 74 insertions(+), 73 deletions(-) diff --git a/applications/optimization/electric_grid_optimization/electric_grid_optimization.ipynb b/applications/optimization/electric_grid_optimization/electric_grid_optimization.ipynb index d1bb92a4a..ab736a5ab 100644 --- a/applications/optimization/electric_grid_optimization/electric_grid_optimization.ipynb +++ b/applications/optimization/electric_grid_optimization/electric_grid_optimization.ipynb @@ -54,13 +54,13 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 1, "id": "dfdf4e93-c86f-47b0-9ced-7e4c6a2447f1", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -141,7 +141,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 2, "id": "7cd709da-2feb-43da-b45c-b99c299b4b8b", "metadata": {}, "outputs": [], @@ -187,7 +187,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 3, "id": "adbe0aaf-b592-41d0-936d-72f60164142e", "metadata": {}, "outputs": [ @@ -267,7 +267,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 4, "id": "65d37686-873e-4f04-a207-8f04dab7fc23", "metadata": {}, "outputs": [], @@ -281,6 +281,40 @@ "write_qmod(qmod, \"electric_grid_optimization\")" ] }, + { + "cell_type": "markdown", + "id": "714e2dfb-9509-4a7b-9940-1fabfe889ee4", + "metadata": {}, + "source": [ + "### Synthesizing the QAOA Circuit and Solving the Problem\n", + "\n", + "We can now synthesize and view the QAOA circuit (ansatz) used to solve the optimization problem:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "ee471ef8-26a2-4f18-aa78-9ba425124b4e", + "metadata": { + "pycharm": { + "name": "#%%\n" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Opening: https://nightly.platform.classiq.io/circuit/f84291c6-fe4a-4747-bd18-755ff29e4ed9?version=0.63.0.dev5\n" + ] + } + ], + "source": [ + "qprog = combi.get_qprog()\n", + "show(qprog)" + ] + }, { "cell_type": "markdown", "id": "c1ab3b7a-e81d-4b12-b822-418eef8edb30", @@ -291,38 +325,22 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 6, "id": "41276b9c-4406-4f8d-bc56-c4ee7497d61f", "metadata": { "tags": [] }, "outputs": [ { - "ename": "ClassiqAPIError", - "evalue": "Internal error occurred. Please contact Classiq support.\nError number 122001 occurred:\n\nError identifier: E1F6D3DA2-C8A2-4BC3-9ED6-9F88BB83A16E\nIf you need further assistance, please reach out on our Community Slack channel at: https://short.classiq.io/join-slack", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mClassiqAPIError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m:2\u001b[0m\n", - "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/applications/combinatorial_optimization/combinatorial_problem.py:84\u001b[0m, in \u001b[0;36mCombinatorialProblem.optimize\u001b[0;34m(self, execution_preferences, maxiter, cost_trace, quantile)\u001b[0m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21moptimize\u001b[39m(\n\u001b[1;32m 77\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 78\u001b[0m execution_preferences: Optional[ExecutionPreferences] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 81\u001b[0m quantile: \u001b[38;5;28mfloat\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1.0\u001b[39m,\n\u001b[1;32m 82\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mlist\u001b[39m[\u001b[38;5;28mfloat\u001b[39m]:\n\u001b[1;32m 83\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_ \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m---> 84\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_qprog\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 85\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mes_ \u001b[38;5;241m=\u001b[39m ExecutionSession(\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_, execution_preferences \u001b[38;5;66;03m# type:ignore[assignment,arg-type]\u001b[39;00m\n\u001b[1;32m 87\u001b[0m )\n\u001b[1;32m 89\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mestimate_cost_wrapper\u001b[39m(params: np\u001b[38;5;241m.\u001b[39mndarray) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mfloat\u001b[39m:\n", - "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/applications/combinatorial_optimization/combinatorial_problem.py:73\u001b[0m, in \u001b[0;36mCombinatorialProblem.get_qprog\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 71\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel_ \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 72\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_model()\n\u001b[0;32m---> 73\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_ \u001b[38;5;241m=\u001b[39m \u001b[43msynthesize\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel_\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type:ignore[assignment,arg-type]\u001b[39;00m\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mqprog_\n", - "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/synthesis.py:85\u001b[0m, in \u001b[0;36msynthesize\u001b[0;34m(serialized_model, auto_show)\u001b[0m\n\u001b[1;32m 71\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msynthesize\u001b[39m(\n\u001b[1;32m 72\u001b[0m serialized_model: SerializedModel, auto_show: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 73\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m SerializedQuantumProgram:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 75\u001b[0m \u001b[38;5;124;03m Synthesize a model with the Classiq engine to receive a quantum program.\u001b[39;00m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;124;03m [More details](https://docs.classiq.io/latest/reference-manual/synthesis/)\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 83\u001b[0m \u001b[38;5;124;03m SerializedQuantumProgram: Quantum program serialized as a string. (See: QuantumProgram)\u001b[39;00m\n\u001b[1;32m 84\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 85\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43masync_utils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43msynthesize_async\u001b[49m\u001b[43m(\u001b[49m\u001b[43mserialized_model\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m auto_show:\n\u001b[1;32m 87\u001b[0m show(result)\n", - "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/async_utils.py:37\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(coro)\u001b[0m\n\u001b[1;32m 32\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrun\u001b[39m(coro: Awaitable[T]) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m T:\n\u001b[1;32m 33\u001b[0m \u001b[38;5;66;03m# Use this function instead of asyncio.run, since it ALWAYS\u001b[39;00m\n\u001b[1;32m 34\u001b[0m \u001b[38;5;66;03m# creates a new event loop and clears the thread event loop.\u001b[39;00m\n\u001b[1;32m 35\u001b[0m \u001b[38;5;66;03m# Never use asyncio.run in library code.\u001b[39;00m\n\u001b[1;32m 36\u001b[0m loop \u001b[38;5;241m=\u001b[39m get_event_loop()\n\u001b[0;32m---> 37\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mloop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_until_complete\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcoro\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/night/lib/python3.11/site-packages/nest_asyncio.py:98\u001b[0m, in \u001b[0;36m_patch_loop..run_until_complete\u001b[0;34m(self, future)\u001b[0m\n\u001b[1;32m 95\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m f\u001b[38;5;241m.\u001b[39mdone():\n\u001b[1;32m 96\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 97\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mEvent loop stopped before Future completed.\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m---> 98\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresult\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/asyncio/futures.py:203\u001b[0m, in \u001b[0;36mFuture.result\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 201\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__log_traceback \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 202\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 203\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception\u001b[38;5;241m.\u001b[39mwith_traceback(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception_tb)\n\u001b[1;32m 204\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_result\n", - "File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/asyncio/tasks.py:267\u001b[0m, in \u001b[0;36mTask.__step\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 263\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 264\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m exc \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 265\u001b[0m \u001b[38;5;66;03m# We use the `send` method directly, because coroutines\u001b[39;00m\n\u001b[1;32m 266\u001b[0m \u001b[38;5;66;03m# don't have `__iter__` and `__next__` methods.\u001b[39;00m\n\u001b[0;32m--> 267\u001b[0m result \u001b[38;5;241m=\u001b[39m coro\u001b[38;5;241m.\u001b[39msend(\u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 268\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 269\u001b[0m result \u001b[38;5;241m=\u001b[39m coro\u001b[38;5;241m.\u001b[39mthrow(exc)\n", - "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/synthesis.py:67\u001b[0m, in \u001b[0;36msynthesize_async\u001b[0;34m(serialized_model)\u001b[0m\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msynthesize_async\u001b[39m(\n\u001b[1;32m 64\u001b[0m serialized_model: SerializedModel,\n\u001b[1;32m 65\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m SerializedQuantumProgram:\n\u001b[1;32m 66\u001b[0m model \u001b[38;5;241m=\u001b[39m Model\u001b[38;5;241m.\u001b[39mmodel_validate_json(serialized_model)\n\u001b[0;32m---> 67\u001b[0m quantum_program \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m ApiWrapper\u001b[38;5;241m.\u001b[39mcall_generation_task(model)\n\u001b[1;32m 68\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m SerializedQuantumProgram(quantum_program\u001b[38;5;241m.\u001b[39mmodel_dump_json(indent\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m))\n", - "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/api_wrapper.py:125\u001b[0m, in \u001b[0;36mApiWrapper.call_generation_task\u001b[0;34m(cls, model, http_client)\u001b[0m\n\u001b[1;32m 121\u001b[0m poller \u001b[38;5;241m=\u001b[39m JobPoller(base_url\u001b[38;5;241m=\u001b[39mroutes\u001b[38;5;241m.\u001b[39mTASKS_GENERATE_FULL_PATH)\n\u001b[1;32m 122\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m poller\u001b[38;5;241m.\u001b[39mrun_pydantic(\n\u001b[1;32m 123\u001b[0m model, timeout_sec\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, http_client\u001b[38;5;241m=\u001b[39mhttp_client\n\u001b[1;32m 124\u001b[0m )\n\u001b[0;32m--> 125\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_parse_job_response\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresult\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgenerator_result\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mQuantumProgram\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/night/lib/python3.11/site-packages/classiq/_internals/api_wrapper.py:61\u001b[0m, in \u001b[0;36m_parse_job_response\u001b[0;34m(job_result, output_type)\u001b[0m\n\u001b[1;32m 59\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m output_type\u001b[38;5;241m.\u001b[39mmodel_validate(job_result\u001b[38;5;241m.\u001b[39mresult)\n\u001b[1;32m 60\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m job_result\u001b[38;5;241m.\u001b[39mfailure_details:\n\u001b[0;32m---> 61\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ClassiqAPIError(job_result\u001b[38;5;241m.\u001b[39mfailure_details)\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ClassiqAPIError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnexpected response from server\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[0;31mClassiqAPIError\u001b[0m: Internal error occurred. Please contact Classiq support.\nError number 122001 occurred:\n\nError identifier: E1F6D3DA2-C8A2-4BC3-9ED6-9F88BB83A16E\nIf you need further assistance, please reach out on our Community Slack channel at: https://short.classiq.io/join-slack" + "name": "stderr", + "output_type": "stream", + "text": [ + "Optimization Progress: 101it [20:53, 12.41s/it] \n" ] } ], "source": [ - "%%time\n", - "cost_values = []\n", - "optimized_params = combi.optimize(maxiter=100, cost_trace=cost_values, quantile=1)" + "optimized_params = combi.optimize(maxiter=100, quantile=1)" ] }, { @@ -335,7 +353,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 7, "id": "af2b4f18-b829-47a8-82ac-c3e0fb4a6894", "metadata": {}, "outputs": [ @@ -345,13 +363,13 @@ "Text(0.5, 1.0, 'Cost convergence')" ] }, - "execution_count": 15, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -363,11 +381,10 @@ "source": [ "import matplotlib.pyplot as plt\n", "\n", - "fig, axes = plt.subplots(nrows=1, ncols=1)\n", - "axes.plot(cost_values)\n", - "axes.set_xlabel(\"Iterations\")\n", - "axes.set_ylabel(\"Cost\")\n", - "axes.set_title(\"Cost convergence\")" + "plt.plot(combi.cost_trace)\n", + "plt.xlabel(\"Iterations\")\n", + "plt.ylabel(\"Cost\")\n", + "plt.title(\"Cost convergence\")" ] }, { diff --git a/applications/optimization/electric_grid_optimization/electric_grid_optimization.qmod b/applications/optimization/electric_grid_optimization/electric_grid_optimization.qmod index 25d035a05..2cc70ac10 100644 --- a/applications/optimization/electric_grid_optimization/electric_grid_optimization.qmod +++ b/applications/optimization/electric_grid_optimization/electric_grid_optimization.qmod @@ -1,31 +1,15 @@ qstruct QAOAVars { - x_0,0: qbit; - x_0,1: qbit; - x_0,2: qbit; - x_0,3: qbit; - x_1,0: qbit; - x_1,1: qbit; - x_1,2: qbit; - x_1,3: qbit; - x_2,0: qbit; - x_2,1: qbit; - x_2,2: qbit; - x_2,3: qbit; - source_supply_rule_0_slack_var_0: qbit; - source_supply_rule_0_slack_var_1: qbit; - source_supply_rule_1_slack_var_0: qbit; - source_supply_rule_1_slack_var_1: qbit; - source_supply_rule_2_slack_var_0: qbit; - source_supply_rule_2_slack_var_1: qbit; + x: qbit[4][3]; + source_supply_rule_0_slack_var: qbit[2]; + source_supply_rule_1_slack_var: qbit[2]; + source_supply_rule_2_slack_var: qbit[2]; } - - qfunc main(params: real[12], output v: QAOAVars) { allocate(v.size, v); hadamard_transform(v); repeat (i: 6) { - phase (-(((((((((((((((((((0.5 * v.x_0,0) + v.x_0,1) + v.x_0,2) + (2.1 * v.x_0,3)) + v.x_1,0) + (0.6 * v.x_1,1)) + (1.4 * v.x_1,2)) + v.x_1,3) + v.x_2,0) + (1.4 * v.x_2,1)) + (0.4 * v.x_2,2)) + (2.3 * v.x_2,3)) + (16 * ((((v.x_0,0 + v.x_1,0) + v.x_2,0) - 1) ** 2))) + (16 * ((((v.x_0,1 + v.x_1,1) + v.x_2,1) - 1) ** 2))) + (16 * ((((v.x_0,2 + v.x_1,2) + v.x_2,2) - 1) ** 2))) + (16 * ((((v.x_0,3 + v.x_1,3) + v.x_2,3) - 1) ** 2))) + (64.0 * ((((((((0.5 * v.source_supply_rule_0_slack_var_0) + (0.5 * v.source_supply_rule_0_slack_var_1)) + (0.5 * v.x_0,0)) + (0.5 * v.x_0,1)) + (0.5 * v.x_0,2)) + (0.5 * v.x_0,3)) - 1) ** 2))) + (64.0 * ((((((((0.5 * v.source_supply_rule_1_slack_var_0) + (0.5 * v.source_supply_rule_1_slack_var_1)) + (0.5 * v.x_1,0)) + (0.5 * v.x_1,1)) + (0.5 * v.x_1,2)) + (0.5 * v.x_1,3)) - 1) ** 2))) + (64.0 * ((((((((0.5 * v.source_supply_rule_2_slack_var_0) + (0.5 * v.source_supply_rule_2_slack_var_1)) + (0.5 * v.x_2,0)) + (0.5 * v.x_2,1)) + (0.5 * v.x_2,2)) + (0.5 * v.x_2,3)) - 1) ** 2))), params[i]); + phase (-(((((((((((((((((((0.5 * v.x[0][0]) + v.x[0][1]) + v.x[0][2]) + (2.1 * v.x[0][3])) + v.x[1][0]) + (0.6 * v.x[1][1])) + (1.4 * v.x[1][2])) + v.x[1][3]) + v.x[2][0]) + (1.4 * v.x[2][1])) + (0.4 * v.x[2][2])) + (2.3 * v.x[2][3])) + (16 * ((((v.x[0][0] + v.x[1][0]) + v.x[2][0]) - 1) ** 2))) + (16 * ((((v.x[0][1] + v.x[1][1]) + v.x[2][1]) - 1) ** 2))) + (16 * ((((v.x[0][2] + v.x[1][2]) + v.x[2][2]) - 1) ** 2))) + (16 * ((((v.x[0][3] + v.x[1][3]) + v.x[2][3]) - 1) ** 2))) + (64.0 * ((((((((0.5 * v.source_supply_rule_0_slack_var[0]) + (0.5 * v.source_supply_rule_0_slack_var[1])) + (0.5 * v.x[0][0])) + (0.5 * v.x[0][1])) + (0.5 * v.x[0][2])) + (0.5 * v.x[0][3])) - 1) ** 2))) + (64.0 * ((((((((0.5 * v.source_supply_rule_1_slack_var[0]) + (0.5 * v.source_supply_rule_1_slack_var[1])) + (0.5 * v.x[1][0])) + (0.5 * v.x[1][1])) + (0.5 * v.x[1][2])) + (0.5 * v.x[1][3])) - 1) ** 2))) + (64.0 * ((((((((0.5 * v.source_supply_rule_2_slack_var[0]) + (0.5 * v.source_supply_rule_2_slack_var[1])) + (0.5 * v.x[2][0])) + (0.5 * v.x[2][1])) + (0.5 * v.x[2][2])) + (0.5 * v.x[2][3])) - 1) ** 2))), params[i]); apply_to_all(lambda(q) { RX(params[6 + i], q); }, v); diff --git a/applications/optimization/electric_grid_optimization/electric_grid_optimization.synthesis_options.json b/applications/optimization/electric_grid_optimization/electric_grid_optimization.synthesis_options.json index 9eeb8e4eb..d76cede2d 100644 --- a/applications/optimization/electric_grid_optimization/electric_grid_optimization.synthesis_options.json +++ b/applications/optimization/electric_grid_optimization/electric_grid_optimization.synthesis_options.json @@ -7,28 +7,28 @@ "machine_precision": 8, "custom_hardware_settings": { "basis_gates": [ - "p", "y", + "u2", + "rx", "ry", - "u1", - "u", + "rz", + "tdg", + "cy", "t", - "s", - "x", + "p", + "cx", + "sx", "id", "r", - "rx", - "tdg", - "cz", - "sx", - "cy", - "h", - "u2", - "z", + "s", "sxdg", - "cx", - "rz", - "sdg" + "u", + "x", + "sdg", + "u1", + "z", + "cz", + "h" ], "is_symmetric_connectivity": true }, @@ -38,6 +38,6 @@ "pretty_qasm": true, "transpilation_option": "auto optimize", "timeout_seconds": 300, - "random_seed": 4093170185 + "random_seed": 654633485 } }