This PennyLane plugin allows the Rigetti Forest and pyQuil simulators to be used as PennyLane devices.

pyQuil is a Python library for quantum programming using the quantum instruction language (Quil) - resulting quantum programs can be executed using the Rigetti Forest platform.

PennyLane is a machine learning library for optimization and automatic differentiation of hybrid quantum-classical computations.


  • Provides four devices to be used with PennyLane: forest.numpy_wavefunction, forest.wavefunction, forest.qvm, and forest.qpu. These provide access to the pyQVM Numpy wavefunction simulator, Forest wavefunction simulator, quantum virtual machine (QVM), and quantum processing unit (QPU) respectively.
  • All provided devices support all core qubit PennyLane operations and expectation values.
  • Provides custom PennyLane operations to cover additional pyQuil operations: T, S, ISWAP, CCNOT, PSWAP, and many more. Every custom operation supports analytic differentiation.
  • Leverage PennyLane’s automatic differentiation and optimization together with Rigetti’s Forest SDK and Quantum Cloud Services.

To get started with the PennyLane Strawberry Fields plugin, follow the installation steps, then see the usage page.