https://github.com/carlolepelaars/skq

Scientific Toolkit for Quantum Computing
https://github.com/carlolepelaars/skq

numpy python quantum quantum-computing quantum-machine-learning

Last synced: 1 day ago
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Scientific Toolkit for Quantum Computing

• Host: GitHub
• URL: https://github.com/carlolepelaars/skq
• Owner: CarloLepelaars
• License: apache-2.0
• Created: 2024-07-12T13:11:02.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2025-01-25T15:24:46.000Z (1 day ago)
• Last Synced: 2025-01-25T15:26:14.496Z (1 day ago)
• Topics: numpy, python, quantum, quantum-computing, quantum-machine-learning
• Language: Python
• Homepage: https://carlo.ai
• Size: 882 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# skq

Scientific Toolkit for Quantum Computing

This library is used in the [q4p (Quantum Computing for Programmers)](https://github.com/CarloLepelaars/q4p) course.

NOTE: This library is developed for educational purposes. While we strive for correctness of everything, the code is provided as is and not guaranteed to be bug-free. For sensitive applications make to check computations. 

## Why SKQ?

- Exploration: Play with fundamental quantum building blocks (NumPy).

- Education: Learn quantum computing concepts and algorithms.

- Integration: Combine classical components with quantum components.

- Democratize quantum for Python programmers and data scientists: Develop quantum algorithms in your favorite environment and easily export to your favorite quantum computing platform for running on real quantum hardware.

## Install

```bash

pip install skq

```