Renaming for descriptiveness

Project.toml

@@ -1,7 +1,7 @@
 name = "SpinGlassEngine"
 uuid = "0563570f-ea1b-4080-8a64-041ac6565a4e"
 authors = ["Anna Maria Dziubyna <[email protected]>", "Tomasz Śmierzchalski <[email protected]>", "Bartłomiej Gardas <[email protected]>", "Konrad Jałowiecki <[email protected]>", "Łukasz Pawela <[email protected]>", "Marek M. Rams <[email protected]>"]
-version = "1.3.0"
+version = "1.4.0"
 
 [deps]
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"

docs/src/params.md

@@ -15,7 +15,6 @@ SearchParameters
 In the boundary MPS-MPO approach we apply Matrix Product Operator (MPO) to appropriate sites of Matrix Product State (MPS). In this context, the absorption of a MPO into a MPS leads to an exponential growth of the bond dimension. Hence, a truncation scheme is necessary to mitigate this issue and to keep the bond dimension in a reasonable size. 
 Our package offers users the flexibility to choose between three distinct methods for optimizing the boundary MPS used in contracting the tensor network: 
 * `Zipper`
-* `MPSAnnealing`
 * `SVDTruncate`.
 `Zipper` method combines randomized truncated Singular Value Decomposition (SVD) and a variational scheme.
 ```@raw html
@@ -25,10 +24,6 @@ With the `SVDTruncate` method, the Matrix Product State (MPS) is systematically
 ```@raw html
 <img src="../images/svd_truncate.png" width="50%" class="center"/>
 ```
-On the other hand, the `MPSAnnealing` method tailors the construction of MPS based on variational compression.
-```@raw html
-<img src="../images/annealing.png" width="50%" class="center"/>
-```
 
 # Sparsity 
 Our software package acknowledges the importance of two fundamental methodologies in tensor processing

examples/pegasus.jl

@@ -17,16 +17,15 @@ function bench(instance::String, β::Real, bond_dim::Integer, num_states::Intege
 
     dE = 3.0
     δp = exp(-β * dE)
-    all_betas = [β / 8, β / 4, β / 2, β]
 
     potts_h = potts_hamiltonian(
         ising_graph(instance),
         spectrum = my_brute_force,
         cluster_assignment_rule = pegasus_lattice((m, n, t)),
     )
 
-    params = MpsParameters{Float64}(; bd = bond_dim, ϵ = 1E-8, sw = 4, ts = 1E-16)
-    search_params = SearchParameters(; max_states = num_states, cut_off_prob = δp)
+    params = MpsParameters{Float64}(; bond_dim = bond_dim, var_tol = 1E-8, num_sweeps = 4, tol_SVD = 1E-16)
+    search_params = SearchParameters(; max_states = num_states, cutoff_prob = δp)
     Strategy = Zipper
     Sparsity = Sparse
     Layout = GaugesEnergy
@@ -36,8 +35,8 @@ function bench(instance::String, β::Real, bond_dim::Integer, num_states::Intege
     ctr = MpsContractor{Strategy,Gauge,Float64}(
         net,
         params;
-        βs = all_betas,
-        graduate_truncation = :graduate_truncate,
+        beta = β,
+        graduate_truncation = true,
         onGPU = onGPU,
     )
 

examples/truncation_BP.jl

@@ -27,7 +27,6 @@ Dcut = 8
 tolV = 1E-16
 tolS = 1E-16
 max_sweeps = 0
-indβ = 1
 ITERS_SVD = 2
 ITERS_VAR = 1
 DTEMP_MULT = 2
@@ -43,7 +42,7 @@ params =
     MpsParameters(Dcut, tolV, max_sweeps, tolS, ITERS_SVD, ITERS_VAR, DTEMP_MULT, METHOD)
 search_params = SearchParameters(MAX_STATES, δp)
 
-Strategy = Zipper  # MPSAnnealing SVDTruncate
+Strategy = Zipper  # SVDTruncate
 Layout = GaugesEnergy
 Gauge = NoUpdate
 cl_states = [2^10]