Qiskit Quantum Code Snippets

Welcome to the Qiskit Quantum Code Snippets repository! I’m thrilled to share this collection of code snippets designed to illustrate various quantum computing concepts and techniques using Qiskit. This repository aims to offer practical examples and resources for both beginners and experienced quantum enthusiasts.

Uniqueness

This project provides a comprehensive repository of Qiskit code snippets for common quantum operations, addressing several key areas in quantum computing:

• Diverse Snippets: Includes a wide range of examples from basic quantum gates and algorithms to advanced topics like error correction, quantum chemistry simulations, and machine learning with quantum algorithms.
• Educational Resource: Offers practical, well-documented examples for beginners and experienced users alike, facilitating learning and experimentation with Qiskit.
• Enhanced Visualization: Features scripts for visualizing quantum circuits, Bloch spheres, and density matrices, making it easier to understand and interpret quantum computations.
• Community-Driven: Designed to be a community resource, encouraging contributions and expansions. The repository is structured to allow easy additions and updates from the community.

This project stands out by combining practical code examples with educational value, bridging gaps in existing resources and fostering collaboration within the quantum computing community.

Contribution to Open Source

This repo I made strives to contribute to the Qiskit open source community by creating a comprehensive repository of practical code snippets that cover a wide range of quantum computing topics. By providing clear and accessible examples of quantum operations, algorithms, and visualization techniques, it serves as a valuable resource for both beginners and experienced practitioners. The repository not only facilitates learning and experimentation with Qiskit but also invites community collaboration by being well-structured for easy expansion and contributions. This initiative enriches the available educational materials, supports the growth of the quantum computing ecosystem, and fosters a collaborative environment within the Qiskit community.

Repository Structure

Here’s a quick overview of what you’ll find in this repository:

• Basics

  • hello_quantum.py: A simple quantum circuit demonstrating the basics of quantum computing.
  • basic_gates.py: Examples of basic quantum gates and their operations.

• Algorithms

  • deutsch_jozsa.py: Implementation of the Deutsch-Josza algorithm.
  • grover.py: Implementation of Grover's search algorithm.

• Error Correction

  • bit_flip_code.py: Example of bit-flip error correction.
  • phase_flip_code.py: Example of phase-flip error correction.
  • shor_code.py: Implementation of Shor’s nine-qubit error correction code.

• Machine Learning

  • qsvm.py: Quantum Support Vector Machine (QSVM) example.
  • quantum_neural_network.py: Basic quantum neural network example.

• Quantum Chemistry

  • molecule_simulation.py: Simulate the energy levels of a simple molecule (H2).

• Visualization

  • circuit_visualization.py: Visualize a quantum circuit.
  • bloch_sphere.py: Visualize qubit states on a Bloch sphere.
  • density_matrix_visualization.py: Visualize density matrices for mixed states.

• Utilities

  • custom_gates.py: Create and use custom gates in Qiskit.
  • circuit_optimization.py: Examples of circuit optimization techniques.

• Tests

  • test_snippets.py: Unit tests for the code snippets to ensure they work correctly.

Getting Started

To get started with this repository, follow these steps:

1. Clone the Repository

First, clone the repository to your local machine:

bash git clone https://github.com/urname/qiskit-quantum-code-snippets.git cd qiskit-quantum-code-snippets

2. Set Up Your Environment

Ensure you have Python and Qiskit installed. Create a virtual environment and install the required dependencies with: python -m venv venv source venv/bin/activate # On Windows use venv\Scripts\activate pip install qiskit matplotlib

3. Run the Code Snippets

You can run any of the code snippets directly. For example, to execute the bit_flip_code.py snippet: python snippets/error_correction/bit_flip_code.py

4. Run the Tests

python -m unittest discover -s tests python -m unittest discover -s tests

5. Contributing

Contributions are welcome! If you have suggestions for improvements or additional snippets, please follow these steps:

Fork the Repository: Click on the "Fork" button on the top right of this repository page.

Create a New Branch:

To ensure everything is working correctly, run the unit tests: git checkout -b feature-branch

Make Your Changes: Add or modify code snippets as needed.

Commit Your Changes:

git add . git commit -m "Add new feature or fix"

Push to Your Fork:

git push origin feature-branch

Create a Pull Request: Go to the original repository and create a pull request from your feature branch.

Acknowledgements

Huge thanks to open source around qiskit and ongoing contributions, this is a small contribution to qiskit from my side