qiskit-learning-journey

This repository documents my hands-on practice with quantum computing fundamentals using IBM Qiskit, completed as part of the Coursera + Packt course “Practical Quantum Computing with IBM Qiskit for Beginners.” It includes my code implementations, experiments, and visualizations of essential quantum gates, circuits, and algorithms.

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Motivation

• Build an applied understanding of qubits, gates, and circuits
• Learn how to represent states with statevectors and Bloch spheres
• Explore key quantum operations through code
• Create a personal reference that I (and others) can reuse and build upon
• Part of my learning journey to deepen my knowledge of quantum technologies and prepare to contribute to research and innovation

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Repository Contents

1. CNOT & Controlled Gates

   • Implements CNOT, Controlled-Y, and Controlled-Z gates
   • Demonstrates entanglement and Bell states
   • Includes Bloch sphere visualizations

2. Hadamard Gate & Measurement

   • Introduces the Hadamard transformation
   • Demonstrates measurement results with simulators and histograms

3. Pauli Gates, Bloch Sphere & Histogram

   • Visualizes Pauli-X, Pauli-Y, and Pauli-Z gates
   • Simulates initial states, transitions, and measurement results

4. U, R(Φ), S & T Gates

   • U-gate with Euler rotations
   • R(Φ) rotation gates (Rx, Ry, Rz)
   • S and S† phase gates
   • T and T† phase gates
   • Custom initial states and normalization
   • Bloch sphere visualizations
   • Statevector representation (including LaTeX formatting)

5. Swap Gate

   • Demonstrates the SWAP gate
   • Includes decomposition into a CNOT-based implementation

6. Toffoli Gate (CCX and CCZ)

   • X- and Z-controlled Toffoli gates
   • Implementation with standard gates
   • Simulation results and histogram plots

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Requirements

Mandatory:

pip install qiskit qiskit-aer matplotlib numpy

Optional (for visualizations and LaTeX formatting):

pip install qiskit-textbook

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Getting Started

1. Clone the repository

   git clone https://github.com/yourusername/quantum-qiskit-course.git
   cd quantum-qiskit-course

2. Launch Jupyter Notebook

   jupyter notebook

3. Run the examples

   • Open any notebook or Python file (e.g., CNOT_Controlled_Gates.ipynb) and execute cells sequentially.
   • Bloch spheres and histograms will be displayed inline.
   • Statevector LaTeX outputs (if available) may require the optional qiskit-textbook package.

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Course Reference

• Course: Beginner’s Guide to Practical Quantum Computing with IBM Qiskit (Coursera)
• Provider: Packt Publishing & IBM Quantum

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Acknowledgments

• IBM Qiskit team – for the open-source framework
• NumPy & Matplotlib – for math and visualization tools

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