Software library for programming quantum computers

PennyLane

PennyLane is the leading tool for programming quantum computers. A cross-platform Python library, it enables a new paradigm — quantum differentiable programming — that enables seamless integration with machine learning tools. Train a quantum computer like you would train a neural network. PennyLane also supports a comprehensive set of features, simulators, hardware, and community-led resources that enable users of all levels to easily build, optimize and deploy quantum-classical applications.

Key Features

• Write once, run anywhere.
  Change your quantum device in a single line to swap between simulators and hardware; no other changes to your program needed.
• Simulators and hardware, all in one place.
  Access the fastest all-purpose simulators and the widest hardware availability. Seamlessly combine high-performance compute and GPUs with quantum hardware from Xanadu, Amazon Braket, Google, IBM, Rigetti and more; move from rapid iteration to hardware testing with ease.
• A global community.
  From our curated collection of tutorials, support forum, demonstrations, and videos, the PennyLane community is the place to go to learn quantum computing and quantum machine learning.
• Built-in automatic differentiation of quantum circuits.
  PennyLane knows how to differentiate through all quantum devices, whether simulators or hardware. And it automatically chooses the best algorithms for the job.
• Machine learning on quantum hardware.
  Connect quantum hardware seamlessly to PyTorch, TensorFlow, JAX, and NumPy to build rich and flexible quantum-classical models.
• Everything included.
  PennyLane's core tenet is flexibility. Build the algorithms you envision — we won't get in your way. But when you need those extra tools, they are there, from quantum optimizers to quantum chemistry algorithms.