PennyLane-Strawberry Fields Plugin

Release

0.9.0

_images/puzzle_sf.png

The PennyLane-SF plugin integrates the StrawberryFields photonic quantum computing framework with PennyLane’s quantum machine learning capabilities.

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

Strawberry Fields is a full-stack Python library for designing, simulating, and optimizing photonic quantum circuits.

Once the PennyLane-SF plugin is installed, the two provided Strawberry Fields devices can be accessed straight away in PennyLane, without the need to import any additional packages.

Tutorials

To see the PennyLane-SF plugin in action, you can use any of the continuous-variable based demos from the PennyLane documentation, for example the tutorial on Gaussian transformations, and simply replace 'default.gaussian' with any of the available Strawberry Fields devices, such as 'strawberryfields.gaussian':

dev = qml.device('strawberryfields.gaussian', wires=XXX)

The 'strawberryfields.fock' device is explicitly used in the quantum neural net tutorial.

To filter tutorials that use a StrawberryFields device, use the “Strawberry Fields” filter on the right panel of the demos.