A comprehensive collection of quantum computing examples, tutorials, and educational resources using Qiskit. This repository serves as a complete learning path from basic quantum concepts to advanced quantum algorithms and applications.
This repository provides:
- Comprehensive Coverage: 100+ tutorials from fundamentals to cutting-edge research
- Interactive Learning: Jupyter notebooks with executable code and visualizations
- Real-World Applications: Cryptography, optimization, simulation, and more
- Progressive Learning: Structured path from beginner to expert level
- Modern Framework: Latest Qiskit with best practices and optimizations
- Theory + Practice: Mathematical foundations with practical implementations
- Research Connections: Links to current quantum computing research
- Quantum Basics
- Qubits and Quantum States
- Quantum Gates and Circuits
- Measurement and Observables
- Quantum Entanglement
- Algorithm Overview
- Deutsch-Jozsa Algorithm
- Grover's Search Algorithm
- Shor's Factoring Algorithm
- Quantum Fourier Transform
- Phase Estimation
- VQA Overview
- Variational Quantum Eigensolver (VQE)
- Quantum Approximate Optimization (QAOA)
- Quantum Neural Networks
- QML Overview
- Quantum Feature Maps
- Quantum Kernels
- Quantum Classifiers
- Hybrid Classical-Quantum Models
- Advanced Overview
- Quantum Error Correction
- Fault-Tolerant Computing
- Quantum Complexity Theory
- Quantum Information Theory
- Python 3.8 or higher
- Basic understanding of linear algebra
- Familiarity with Python programming
- Clone the repository:
git clone https://github.com/bayrameker/quantum-examples.git
cd quantum-examples- Create a virtual environment:
python -m venv quantum-env
source quantum-env/bin/activate # On Windows: quantum-env\Scripts\activate- Install dependencies:
pip install -r requirements.txt- Launch Jupyter Lab:
jupyter lab- Fundamentals: Quantum Basics - Qubits, gates, measurement
- First Algorithm: Deutsch-Jozsa - Simple quantum advantage
- Entanglement: Bell States - Quantum correlations
- Search Algorithm: Grover's Algorithm - Quadratic speedup
- Variational Methods: VQE - Near-term algorithms
- Machine Learning: Quantum Kernels - QML basics
- Cryptography: Shor's Algorithm - Breaking RSA
- Error Correction: Stabilizer Codes - Fault tolerance
- Applications: Quantum Simulation - Real-world problems
- Hardware: NISQ Devices - Near-term limitations
- Complexity: Quantum Advantage - Theoretical foundations
- Information: Quantum Channels - Information theory
quantum-examples/
├── tutorials/ # Main tutorial content
│ ├── 01-fundamentals/ # Basic quantum concepts
│ │ ├── 01-qubits-and-states/
│ │ ├── 02-gates-and-circuits/
│ │ ├── 03-measurement/
│ │ └── 04-entanglement/
│ ├── 02-algorithms/ # Quantum algorithms
│ │ ├── 01-deutsch-jozsa/
│ │ ├── 02-grovers/
│ │ ├── 03-shors/
│ │ ├── 04-qft/
│ │ └── 05-phase-estimation/
│ ├── 03-variational/ # VQAs and optimization
│ │ ├── 01-vqe/
│ │ ├── 02-qaoa/
│ │ └── 03-qnn/
│ ├── 04-machine-learning/ # Quantum ML
│ │ ├── 01-feature-maps/
│ │ ├── 02-quantum-kernels/
│ │ ├── 03-classifiers/
│ │ └── 04-hybrid-models/
│ ├── 05-applications/ # Real-world applications
│ │ ├── 01-cryptography/
│ │ ├── 02-optimization/
│ │ └── 03-simulation/
│ ├── 06-hardware/ # Quantum hardware
│ │ ├── 01-overview/
│ │ └── 05-nisq/
│ └── 07-advanced-topics/ # Advanced topics
│ ├── 01-error-correction/
│ ├── 02-fault-tolerance/
│ ├── 03-complexity/
│ └── 04-information/
├── examples/ # Standalone examples
├── utils/ # Utility functions
├── tests/ # Unit tests
├── docs/ # Additional documentation
└── requirements.txt # Python dependencies
We welcome contributions! Please see our Contributing Guide for details.
This project is licensed under the MIT License - see the LICENSE file for details.
- Qiskit - IBM's quantum computing framework
- Quantum Computing Community
- Quantum Open Source Foundation
- IBM Quantum
- Microsoft Quantum
- Google Quantum AI
Happy Quantum Computing! 🚀