PennyLane-Strawberry Fields Plugin

Release

0.29.1

Warning

This plugin will not be supported in newer versions of PennyLane. It is compatible with versions of PennyLane up to and including 0.29. Please use Strawberry Fields instead.

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 provided Strawberry Fields devices can be accessed straight away in PennyLane, without the need to import any additional packages.

Devices

PennyLane-SF provides various Strawberry Fields devices for PennyLane:

'strawberryfields.fock'

Full simulator that supports all continuous-variable operations.

'strawberryfields.gaussian'

Optimized simulator that supports only Gaussian operations and photon number resolving measurements.

'strawberryfields.remote'

Remote backends including access to continuous-variable hardware.

'strawberryfields.gbs'

Specialized simulator giving access to analytic gradients in Gaussian boson sampling.

'strawberryfields.tf'

TensorFlow simulator that supports backpropagation and all continuous-variable operations.

Note

The Strawberry Fields plugin only supports continuous-variable (CV) operations, such as Squeezing, or NumberOperator.

Tutorials

Check out these demos to see the PennyLane-SF plugin in action:

Plugins and Hybrid computation

Function fitting with a photonic quantum neural network

Quantum advantage with Gaussian Boson Sampling

You can also 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)

index

 

Download Python script

 

Download Notebook

 

View on GitHub