IBM Qiskit Tutorials

A collection of Jupyter notebooks exploring quantum computing concepts using IBM Qiskit.

Episodes

• Episode 2: Installation - Setting up Qiskit and the development environment
• Episode 3: Hello World - Introduction to quantum circuits and basic operations
• Episode 4: Primitives - Working with Qiskit primitives for quantum computations
• Episode 5: Dynamic Circuits - Exploring dynamic quantum circuits and conditional operations
• Episode 6: Contributing - Guidelines for contributing to quantum computing projects

Setup Instructions

1. Create Python Environment

conda create -n qiskit-env-py310 python=3.10
conda activate qiskit-env-py310

2. Install Required Packages

pip install qiskit qiskit-ibm-runtime qiskit_aer 'qiskit[visualization]' 'qiskit[machine-learning]'

3. Configure IBM Quantum Credentials

1. Copy the template configuration file:

   cp config_template.py config.py

2. Get your IBM Quantum token:

   • Visit IBM Quantum Platform
   • Sign up or log in to your account
   • Navigate to your account settings
   • Copy your API token

3. Edit config.py and replace YOUR_IBM_QUANTUM_TOKEN_HERE with your actual token

4. Launch Jupyter Notebook

jupyter notebook

Then open any of the episode notebooks to start learning!

Security Note

⚠️ Important: The config.py file contains your sensitive IBM Quantum credentials and is excluded from version control via .gitignore. Never commit this file to GitHub or share it publicly.

Requirements

• Python 3.8+
• Qiskit
• Jupyter Notebook
• IBM Quantum account (free at quantum.ibm.com)

License

This project is for educational purposes.