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A comprehensive collection of interactive Jupyter notebooks covering fundamental quantum algorithms and quantum cryptography protocols. Perfect for students, researchers, and practitioners looking to understand both theoretical foundations and practical implementations.

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Quantum Algorithms & Cryptography Tutorials

A comprehensive collection of interactive Jupyter notebooks covering fundamental quantum algorithms and quantum cryptography protocols. Perfect for students, researchers, and practitioners looking to understand both theoretical foundations and practical implementations.

Repository Contents

This repository contains three major quantum computing tutorials, each as a complete, self-contained Jupyter notebook with detailed explanations, mathematical derivations, and hands-on implementations.

Deutsch-Jozsa Algorithm

The Gateway to Quantum Advantage

Learn the first quantum algorithm to demonstrate exponential speedup over classical computation for a specific problem.

What You'll Learn:

  • Problem formulation: Constant vs. Balanced functions
  • Mathematical derivation with quantum oracle operations
  • Circuit construction and optimization
  • Why quantum parallelism provides exponential advantage
  • Hands-on implementation with multiple examples

Key Features:

  • Interactive quantum circuit visualizations
  • Step-by-step mathematical proofs
  • Multiple oracle types (constant and balanced functions)
  • Educational examples for 1, 2, and 3-qubit systems

Grover's Algorithm

Quantum Search with Quadratic Speedup

Master the most practically relevant quantum algorithm for unstructured database search.

What You'll Learn:

  • Unstructured search problem and quantum speedup
  • Amplitude amplification through quantum interference
  • Optimal iteration calculations and geometric interpretation
  • Oracle construction for arbitrary search targets
  • Diffusion operator (inversion about average) implementation

Key Features:

  • Complete circuit construction from scratch
  • Multiple search scenarios (single/multiple targets)
  • Automatic optimal iteration calculation
  • Success probability analysis and visualization
  • Real-world applications discussion

BB84 Quantum Key Distribution

Quantum Cryptography & Secure Communication

Explore the revolutionary BB84 protocol that enables provably secure key distribution using quantum mechanics.

What You'll Learn:

  • Quantum cryptography principles and unconditional security
  • Complete BB84 protocol implementation (Alice & Bob)
  • Eavesdropping detection using quantum mechanics
  • Practical cryptographic key generation
  • AES encryption with quantum-generated keys

Key Features:

  • Full protocol simulation with basis reconciliation
  • Eavesdropper attack simulation and detection
  • Real AES-256 encryption/decryption demonstrations
  • Security analysis with QBER calculations
  • Production-ready cryptographic integration

Quick Start

Prerequisites

# Python 3.8 or higher
python --version

# Install required packages
pip install qiskit qiskit-aer matplotlib numpy cryptography pylatexenc ipywidgets

Running the Notebooks

  1. Clone the repository:

    git clone https://github.com/Jnan-py/Quantum-Algorithms-Tutorial.git
    cd Quantum-Algorithms-Tutorial
  2. Launch Jupyter:

    jupyter notebook
  3. Open any tutorial and start learning!

    • Deutsz_Josza_Algorithm.ipynb - Start here for quantum algorithm basics
    • Grover_Algorithm.ipynb - Learn quantum search
    • BB84_(QKD)_Protocol.ipynb - Explore quantum cryptography

Repository Structure

Quantum-Algorithms-Tutorial/
│
├── README.md                          # This file
├── requirements.txt                   # Python dependencies
│
├── Deutsz_Josza_Algorithm.ipynb       # Deutsch-Jozsa Algorithm
├── Grover_Algorithm.ipynb    # Grover's Search Algorithm
├── BB84_(QKD)_Protocol.ipynb           # BB84 Quantum Cryptography
│
├── assets/                           # Images and diagrams
│   ├── BB84 Key Shift flowchart.png
│   └── BB84 Protocol.png
│   └── Deutsh Josza Quantum Circuit.png
│   └── Grover Circuit.png

Learning Path

Recommended order for beginners:

  1. Start with Deutsch-Jozsa

    • Fundamental quantum concepts
    • Oracle-based algorithms
    • Quantum vs. classical complexity
  2. Progress to Grover's Algorithm

    • Advanced quantum techniques
    • Practical quantum advantage
    • Amplitude amplification
  3. Master BB84 Cryptography

    • Real-world quantum applications
    • Quantum security principles
    • Integration with classical systems

Technical Requirements

Software Dependencies

  • Python: 3.8+
  • Qiskit: Latest version
  • Jupyter: Notebook environment
  • Additional packages: Listed in requirements.txt

Hardware Requirements

  • RAM: 4GB minimum, 8GB recommended
  • CPU: Any modern processor (quantum simulation is CPU-intensive)
  • Storage: ~100MB for notebooks and dependencies

Optional Quantum Hardware

  • IBM Quantum Experience account (for real quantum device access)
  • Compatible with any Qiskit-supported quantum backend

Use Cases & Applications

Educational

  • University courses in quantum computing
  • Self-study for quantum algorithm mastery
  • Research preparation for advanced quantum topics
  • Workshop material for quantum computing bootcamps

Professional Development

  • Quantum software engineering skill building
  • Cryptography and security expertise development
  • Research and development in quantum technologies
  • Patent research and competitive analysis

Research Applications

  • Algorithm benchmarking and performance analysis
  • Quantum advantage demonstration for specific problems
  • Security protocol development and testing
  • Educational material creation for publications

Contributing

We welcome contributions! Here's how you can help:

Types of Contributions

  • Bug fixes in code or explanations
  • Documentation improvements and clarifications
  • New features and algorithm extensions
  • Visualization enhancements and better diagrams
  • Additional examples and use cases

Contribution Process

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Make your changes with clear commit messages
  4. Add tests if applicable
  5. Submit a pull request with detailed description

Code Style

  • Follow PEP 8 for Python code
  • Use descriptive variable names and functions
  • Include docstrings for all functions
  • Add comments for complex quantum operations
  • Maintain educational clarity in explanations

Acknowledgments

Quantum Computing Pioneers

  • Charles Bennett & Gilles Brassard - BB84 Protocol inventors
  • Lov Grover - Grover's Algorithm creator
  • David Deutsch & Richard Jozsa - Deutsch-Jozsa Algorithm developers

Tools & Frameworks

  • IBM Qiskit - Quantum computing framework
  • Jupyter Project - Interactive computing environment
  • Python Community - Programming language ecosystem

Educational Resources

  • IBM Quantum Experience - Quantum computing platform
  • Microsoft Quantum Development Kit - Quantum programming tools
  • Quantum Computing Community - Open source contributors

Support & Contact

Getting Help

  • Documentation: Check individual notebook markdown cells
  • Issues: Use GitHub Issues for bug reports
  • Discussions: Start a GitHub Discussion for questions
  • Direct Contact: jnanyalla@gmail.com

Stay Updated

  • Star this repository to stay notified of updates
  • Watch for new algorithm additions
  • Fork to customize for your needs

Future Enhancements

Planned Additions

  • Shor's Algorithm - Quantum factoring and cryptography breaking
  • Variational Quantum Eigensolver (VQE) - Quantum chemistry applications
  • QAOA - Quantum optimization algorithms
  • Simon's Algorithm - Hidden subgroup problem solution
  • Quantum Error Correction - Fault-tolerant quantum computing

Advanced Features

  • Interactive widgets for parameter exploration
  • 3D visualizations of quantum state evolution
  • Performance benchmarking against classical algorithms
  • Real quantum hardware integration tutorials
  • Quantum machine learning applications

Star History

If you find these tutorials helpful, please consider starring the repository!

Your support helps us continue creating high-quality educational content for the quantum computing community.


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A comprehensive collection of interactive Jupyter notebooks covering fundamental quantum algorithms and quantum cryptography protocols. Perfect for students, researchers, and practitioners looking to understand both theoretical foundations and practical implementations.

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