Skip to content

Strawberry Fields is a full-stack Python library for designing, simulating, and optimizing continuous variable (CV) quantum optical circuits.

License

Notifications You must be signed in to change notification settings

XueshiGuo/strawberryfields

 
 

Repository files navigation

Strawberry Fields


Travis Codecov coverage Codacy grade Read the Docs PyPI PyPI - Python Version

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

Features

  • An open-source software architecture for photonic quantum computing
  • A full-stack quantum software platform, implemented in Python specifically targeted to the CV model
  • Quantum circuits are written using the easy-to-use and intuitive Blackbird quantum programming language
  • Includes a suite of CV quantum computer simulators implemented using NumPy and TensorFlow - these built-in quantum compiler tools convert and optimize Blackbird code for classical simulation
  • Future releases will aim to target experimental backends, including photonic quantum computing chips

Installation

Strawberry Fields requires Python version 3.5+. Installation of Strawberry Fields, as well as all dependencies, can be done using pip:

pip install strawberryfields

TensorFlow support

To use Strawberry Fields with TensorFlow, version 1.3 of TensorFlow is required. This can be installed alongside Strawberry Fields as follows:

pip install strawberryfields tensorflow==1.3

Or, to install Strawberry Fields and TensorFlow with GPU and CUDA support:

pip install strawberryfields tensorflow-gpu==1.3

Note that TensorFlow version 1.3 is only supported on Python versions less than 3.7.

Getting started

To see Strawberry Fields in action immediately, try out our Strawberry Fields Interactive web application. Prepare your initial states, drag and drop gates, and watch your simulation run in real time right in your web browser.

For getting started with writing your own Strawberry Fields code, check out our quantum teleportation, boson sampling, and machine learning tutorials.

Our documentation is also a great starting point to familiarize yourself with the framework of continuous-variable quantum computation, and check out some important and interesting continuous-variable quantum algorithms.

Finally, detailed documentation on the Strawberry fields API is provided, for full details on available quantum operations, arguments, and backends.

Contributing to Strawberry Fields

We welcome contributions - simply fork the Strawberry Fields repository, and then make a pull request containing your contribution. All contributors to Strawberry Fields will be listed as authors on the releases.

We also encourage bug reports, suggestions for new features and enhancements, and even links to cool projects or applications built on Strawberry Fields. If your contribution becomes part of Strawberry Fields, or is highlighted in our Gallery, we will send you some exclusive Xanadu Swag™ - including t-shirts, stickers, and more.

See our contributions page for more details, and then check out some of the Strawberry Fields challenges for some inspiration.


Authors

Nathan Killoran, Josh Izaac, Nicolás Quesada, Ville Bergholm, Matthew Amy, and Christian Weedbrook.

If you are doing research using Strawberry Fields, please cite our paper:

Nathan Killoran, Josh Izaac, Nicolás Quesada, Ville Bergholm, Matthew Amy, and Christian Weedbrook. "Strawberry Fields: A Software Platform for Photonic Quantum Computing", Quantum, 3, 129 (2019).

Support

If you are having issues, please let us know by posting the issue on our Github issue tracker.

We also have a Strawberry Fields Slack channel - come join the discussion and chat with our Strawberry Fields team.

License

Strawberry Fields is free and open source, released under the Apache License, Version 2.0.

About

Strawberry Fields is a full-stack Python library for designing, simulating, and optimizing continuous variable (CV) quantum optical circuits.

Resources

License

Code of conduct

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 99.8%
  • Makefile 0.2%