PennyLane is a cross-platform Python library for differentiable programming of quantum computers.
The main repository for demos is PennyLaneAI/qml. All the demos here can be found at pennylane.ai.
This repository contains some PennyLane demos in Jupyter notebook format.
The notebooks folder contains the demos on Intro to QAOA, Variational Classifier, and Intro to VQE.
The images for these demos are contained in the static/demonstration_assets folder.
🚀 Install PennyLane to run these demos locally, or create a qBraid account to run them online.
🚀 Click on the "Launch on qBraid" button to access the notebooks in your qBraid account.
🚀 If you're running on qBraid please follow these steps:
- Add an environment with the latest PennyLane version available.
- In the Environments section on the right-hand side click on add,
- Search for PennyLane,
- Choose the latest PennyLane version available (v0.41.0 at the moment),
- Click on Install.
- Double-click on the notebooks folder and then double-click on the demo you want to run.
- On the top-right of the notebook choose the PennyLane kernel. See an example in the qBraid docs.
This repository is not actively maintained. If you have any issues with these demos please visit one of the pages below:
- Built demos: https://pennylane.ai
- Source Code: https://github.com/PennyLaneAI/QML
- Questions and issues: https://discuss.pennylane.ai/c/demos
If you have any issues with the qBraid environment please contact qBraid directly. You can find more information at https://github.com/qBraid/ .
The materials and demos in this repository are free and open source, released under the Apache License, Version 2.0.