Discover new ideas faster.
The definitive open-source Python framework for quantum programming. Built by researchers, for research.
NEW RELEASE¶
PennyLane v0.41 and Catalyst v0.11 are out, with features including resource-efficient decompositions, end-to-end sparse execution, Qualtran integration, and more!
Minimize time-to-research.
PennyLane is unopinionated where it matters. With a functional interface, seamless integration with the scientific ecosystem, and modular building blocks, we get out of the way to help you easily build cutting-edge quantum algorithms.
Accelerated performance.
Scale up your research. Use the high-performance Lightning simulator — backed by NVIDIA cuQuantum — on GPUs and the cloud. But it goes beyond; PennyLane will automatically use the best computational methods for your workflow.
Get up to speed quickly.
Quantum computing can be complex — PennyLane simplifies it. Explore our extensive library of demonstrations and in-depth documentation to advance your expertise in quantum computing, quantum machine learning, and quantum chemistry. Discover how PennyLane can enhance your research and integrate seamlessly into your projects.
Our partners
Community-first software development.
PennyLane is community-driven, built to support your research. With open development on GitHub and direct access to our team, your feedback shapes the roadmap. Join us and help shape the future of quantum research with PennyLane.
Everything differentiable.
PennyLane pioneers a new paradigm — quantum differentiable programming. Everything is trainable, even when using quantum hardware. Don’t just train parameters; train the entire structure of your quantum model.
Don't know where to start?
Here are a few beginner-friendly resources to help you get started
