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Refactor folders structure and rename old lectures #16

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37 changes: 24 additions & 13 deletions README.md
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Expand Up @@ -5,19 +5,30 @@ Feel free to explore all the lectures provided by our special teacher: the Qibo
![qibo_teaching](https://github.com/user-attachments/assets/3a6e2b31-5a4b-4e0c-8f05-ce15d68ea971)


#### List lectures

| Lecture | Topic |
|-------------|---------------------------------|
| Lecture 1 | Introduction to `Qibo` |
| Lecture 2 | The phase kickback trick |
| Lecture 3 | The Deutsch-Josza algorithm |
| Lecture 4 | The Grover search algorithm |
| Lecture 5 | Opening the Grover black-box |
| Lecture 6 | Simulating quantum noise |
| Lecture 7 | Mitigating the noise |
| Lecture 8 | Variational Quantum Eigensolver |
| Bell inequalities | Exploring multiple Bell-like inequalities |
#### Lectures description

The lectures are divided into macro-groups, corresponding to similar or related topics.
In the following table, we give a brief description of the `Qiboedu` contents.

| Lecture | Topic |
|-------------------------|---------------------------------|
| **Introduction** | |
| 1_qibo_basics | First steps with Qibo |
| **Query algorithms** | |
| 1_phase_kickback | The phase kickback trick |
| 2_deutsch_josza | The Deutsch-Josza algorithm |
| 3_grover | The Grover search algorithm |
| 4_grover_details | Opening the Grover black-box |
| **Entanglement tests** | |
| 1_Bell-Wigner | Simulate Bell-Wigner inequality |
| 2_Bell64 | Simulate Bell 1964 inequality |
| 2_CHSH | Simulate CHSH inequality |
| **Quantum noise** | |
| 1_simulating_noise | Simulating quantum noise |
| 2_error_mitigation | Mitigating the noise |
| **Quantum Machine Learning** | |
| 1_vqe | Variational Quantum Eigensolver |



## Setup
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"source": [
"# Lecture 1: introduction to `qibo`\n",
"\n",
"<center><img src=\"../figures/qibo_mascotte/qibo.png\" alt=\"drawing\" width=\"400\"/></center>\n",
"<center><strong>Fig. 1:</strong> Qibo the mangoose learning Qibo 0.0.1 [DALL-E].</center>\n",
"<center><img src=\"../../figures/qibo_mascotte/qibo.png\" alt=\"drawing\" width=\"400\"/></center>\n",
"<center>Qibo the mangoose learning Qibo 0.0.1 [DALL-E].</center>\n",
"\n",
"### Introduction\n",
"\n",
"During this course we are going to use `Qibo`, an open source framework for quantum computing. It provides us with an high level language which can be used to implement algorithms with both circuit-based and adiabatic computation approaches and, once the code is set up, it can be easily executed on various engines, including both classical and quantum hardware. \n",
"\n",
"<center><img src=\"../figures/qibo_ecosystem.svg\" alt=\"drawing\" width=\"800\"/></center>\n",
"<center><img src=\"../../figures/qibo_ecosystem.svg\" alt=\"drawing\" width=\"800\"/></center>\n",
"\n",
"For more info about the whole framework one can have a look to the [`qibo` webpage](https://qibo.science/).\n",
"\n",
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"source": [
"A crucial step is the backend choice. In qibo four backends are provided, and can be used for different kind of applications.\n",
"\n",
"<center><img src=\"../figures/backends.svg\" alt=\"drawing\" width=\"800\"/></center>\n",
"<center><img src=\"../../figures/backends.svg\" alt=\"drawing\" width=\"800\"/></center>\n",
"\n",
"The blue backends correspond to classical hardware, while the red one can be selected if we want to execute our algorithm directly on a quantum computer.\n",
"\n",
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"source": [
"# Lecture 8: ground state approximation via VQE\n",
"\n",
"<center><img src=\"../figures/qibo_mascotte/qibo_vqe.png\" alt=\"drawing\" width=\"400\"/></center>\n",
"<center><strong>Fig. 8:</strong> Qibo the mangoose learning a VQE [DALL-E].</center>"
"<center><img src=\"../../figures/qibo_mascotte/qibo_vqe.png\" alt=\"drawing\" width=\"400\"/></center>\n",
"<center> Qibo the mangoose learning a VQE [DALL-E].</center>"
]
},
{
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"source": [
"# Lecture 6: simulating quantum noise\n",
"\n",
"<center><img src=\"../figures/qibo_mascotte/qibo_noise.png\" alt=\"drawing\" width=\"400\"/></center>\n",
"<center><strong>Fig. 6:</strong> Qibo the mangoose suffering noise [DALL-E].</center>\n",
"<center><img src=\"../../figures/qibo_mascotte/qibo_noise.png\" alt=\"drawing\" width=\"400\"/></center>\n",
"<center>Qibo the mangoose suffering noise [DALL-E].</center>\n",
"\n",
"## Introduction\n",
"\n",
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"source": [
"# Lecture 7: mitigating the noise\n",
"\n",
"<center><img src=\"../figures/qibo_mascotte/qibo_mit.png\" alt=\"drawing\" width=\"400\"/></center>\n",
"<center><strong>Fig. 7:</strong> Qibo the mangoose mitigating noise [DALL-E].</center>\n",
"<center><img src=\"../../figures/qibo_mascotte/qibo_mit.png\" alt=\"drawing\" width=\"400\"/></center>\n",
"<center>Qibo the mangoose mitigating noise [DALL-E].</center>\n",
"\n",
"## Introduction\n",
"\n",
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"source": [
"# Lecture 4: Grover search algorithm\n",
"\n",
"<center><img src=\"../figures/qibo_mascotte/qibo_coffee.png\" alt=\"drawing\" width=\"400\"/></center>\n",
"<center><strong>Fig. 4:</strong> Who put sugar in Qibo's coffee? [DALL-E].</center>\n",
"<center><img src=\"../../figures/qibo_mascotte/qibo_coffee.png\" alt=\"drawing\" width=\"400\"/></center>\n",
"<center>Who put sugar in Qibo's coffee? [DALL-E].</center>\n",
"\n",
"## Introduction\n",
"\n",
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"\n",
"Now the problem is set up and we can focus on the Grover implementation. \n",
"\n",
"<center><img src=\"../figures/grover-circ.png\" alt=\"drawing\" width=\"800\"/></center>\n",
"<center><img src=\"../../figures/grover-circ.png\" alt=\"drawing\" width=\"800\"/></center>\n",
"We need to follow some steps:\n",
"\n",
"1. we prepare a system of $N+1$ qubits into the $|0\\rangle^{\\otimes N} |1\\rangle$ state. The ancilla gate is the one prepared as usual into $|1\\rangle$;\n",
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