About
PennyLane is a Python library for differentiable quantum computing, enabling seamless integration of quantum circuits as trainable layers within classical machine learning frameworks like PyTorch and JAX. It is designed for developing and optimizing hybrid classical-quantum models, including Quantum Neural Networks (QNNs) and variational algorithms such as VQE. Use it for hardware-agnostic quantum programming, quantum chemistry simulations, and investigating quantum machine learning phenomena.
Quick Install
Claude Code
Recommendednpx skills add tondevrel/scientific-agent-skills -a claude-code/plugin add https://github.com/tondevrel/scientific-agent-skillsgit clone https://github.com/tondevrel/scientific-agent-skills.git ~/.claude/skills/pennylaneCopy and paste this command in Claude Code to install this skill
GitHub Repository
Frequently asked questions
What is the pennylane skill?
pennylane is a Claude Skill by tondevrel. Skills package instructions and resources that Claude loads on demand, so Claude can perform pennylane-related tasks without extra prompting.
How do I install pennylane?
Use the install commands on this page: add pennylane to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does pennylane belong to?
pennylane is in the Testing category, tagged testing and design.
Is pennylane free to use?
Yes. pennylane is listed on AIMCP and free to install. It runs inside Claude, so no separate service account is required to use the skill itself.
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