My first quantum computing notebook with IBM Qiskit, using Statevector simulations.
- Updated
May 3, 2025 - Jupyter Notebook
My first quantum computing notebook with IBM Qiskit, using Statevector simulations.
Jupyter notebooks created for the RPI undergraduate research: Quantum Computing in Design Optimization.
A hands-on workshop repository featuring Qiskit-based quantum computing exercises tailored for the LHCb physics community. Includes beginner-friendly notebooks on Qiskit fundamentals, Deutsch-Jozsa, QML, QAOA for Max-Cut, and Grover’s algorithm, with step-by-step explanations and simulations. Ideal for physicists exploring quantum algorithms.
Add a description, image, and links to the quantum-computing-algorithms topic page so that developers can more easily learn about it.
To associate your repository with the quantum-computing-algorithms topic, visit your repo's landing page and select "manage topics."