What is PennyLane?


PennyLane is a cross-platform Python library for programming quantum computers. Its differentiable programming paradigm enables the execution and training of quantum programs on various backends.

PennyLane connects quantum computing with powerful machine learning frameworks like NumPy’s autograd, JAX, PyTorch, and TensorFlow, making them quantum-aware.

Its central job is to manage the execution of quantum computations, including the evaluation of circuits and the computation of their gradients. This information is forwarded to the classical framework, creating seamless quantum-classical pipelines for applications.


PennyLane’s design principle states that circuits can be run on various kinds of simulators or hardware devices without making any changes – the complex job of optimising communication with the devices, compiling circuits to suit the backend, and choosing the best gradient strategies is taken care of.

The library comes with default simulator devices, but is well-integrated with external software and hardware to run quantum circuits—such as IBM’s Qiskit, or Google’s Cirq, Rigetti’s Forest, or Xanadu’s Strawberry Fields.