PennyLane is an open-source software framework built around the concept of quantum differentiable programming. It seamlessly integrates classical machine learning libraries with quantum simulators and hardware, giving users the power to train quantum circuits.

Classical computations, as well as optimization or training of models, are executed using one of the standard scientific computing or machine learning libraries. PennyLane provides an interface to these libraries, making them quantum-aware.

PennyLane’s standard interface is NumPy, but interfaces to powerful machine learning libraries like PyTorch, Tensorflow, and JAX are also available.

The quantum computations are sent to a device for execution. A device can be real quantum hardware or a classical simulator. PennyLane comes with default simulator devices, but is well-integrated with external software and hardware to run quantum circuits—such as Xanadu’s Strawberry Fields, Rigetti’s Forest, IBM’s Qiskit, or Google’s Cirq.