Skip to main content

Open source library for continuous-variable quantum computation

Project description

.. image:: doc/_static/strawberry-fields-text.png
:alt: Strawberry Fields
##################################################

.. image:: https://img.shields.io/travis/XanaduAI/strawberryfields/master.svg?style=for-the-badge
:alt: Travis
:target: https://travis-ci.org/XanaduAI/strawberryfields

.. image:: https://img.shields.io/codecov/c/github/xanaduai/strawberryfields/master.svg?style=for-the-badge
:alt: Codecov coverage
:target: https://codecov.io/gh/XanaduAI/strawberryfields

.. image:: https://img.shields.io/codacy/grade/bd14437d17494f16ada064d8026498dd.svg?style=for-the-badge
:alt: Codacy grade
:target: https://app.codacy.com/app/XanaduAI/strawberryfields?utm_source=github.com&utm_medium=referral&utm_content=XanaduAI/strawberryfields&utm_campaign=badger

.. image:: https://img.shields.io/readthedocs/strawberryfields.svg?style=for-the-badge
:alt: Read the Docs
:target: https://strawberryfields.readthedocs.io

.. image:: https://img.shields.io/pypi/v/StrawberryFields.svg?style=for-the-badge
:alt: PyPI
:target: https://pypi.org/project/StrawberryFields

.. image:: https://img.shields.io/pypi/pyversions/StrawberryFields.svg?style=for-the-badge
:alt: PyPI - Python Version
:target: https://pypi.org/project/StrawberryFields

`Strawberry Fields <https://strawberryfields.readthedocs.io>`_ 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 and above. Installation of Strawberry Fields, as well as all dependencies, can be done using pip:
::

$ python -m pip install strawberryfields


Getting started
===============

To see Strawberry Fields in action immediately, try out our `Strawberry Fields Interactive <https://strawberryfields.ai>`_ 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 <https://strawberryfields.readthedocs.io/en/latest/tutorials/tutorial_teleportation.html>`_, `boson sampling <https://strawberryfields.readthedocs.io/en/latest/tutorials/tutorial_boson_sampling.html>`_, and `machine learning <https://strawberryfields.readthedocs.io/en/latest/tutorials/tutorial_machine_learning.html>`_ tutorials.

Our documentation is also a great starting point to familiarize yourself with the framework of `continuous-variable quantum computation <https://strawberryfields.readthedocs.io/en/latest/introduction.html>`_, and check out some important and interesting continuous-variable `quantum algorithms <https://strawberryfields.readthedocs.io/en/latest/quantum_algorithms.html>`_.

Finally, detailed documentation on the `Strawberry fields API <https://strawberryfields.readthedocs.io/en/latest/code/code.html>`_ 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 <https://help.github.com/articles/about-pull-requests/>`_ containing your contribution. All contributers 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.

.. raw:: html

<img src="https://github.com/XanaduAI/strawberryfields/blob/master/doc/_images/shirt.jpg" width="300px" align="left"> <img src="https://github.com/XanaduAI/strawberryfields/blob/master/doc/_images/sticker_crop.jpg" width="300px" align="left">

See `Contributing to Strawberry Fields <https://github.com/XanaduAI/strawberryfields/blob/master/.github/CONTRIBUTING.md>`_
for more details, and then check out some of the Strawberry Fields `challenges <https://github.com/XanaduAI/strawberryfields/blob/master/.github/CHALLENGES.md>`_ 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 whitepaper <https://arxiv.org/abs/1804.03159>`_:

Nathan Killoran, Josh Izaac, Nicolás Quesada, Ville Bergholm, Matthew Amy, and Christian Weedbrook. Strawberry Fields: A Software Platform for Photonic Quantum Computing. *arXiv*, 2018. arXiv:1804.03159


Support
=======

- **Source Code:** https://github.com/XanaduAI/strawberryfields
- **Issue Tracker:** https://github.com/XanaduAI/strawberryfields/issues

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 <https://u.strawberryfields.ai/slack>`_ -
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.


Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

StrawberryFields_gpu-0.7.3-py3-none-any.whl (1.7 MB view details)

Uploaded Python 3

File details

Details for the file StrawberryFields_gpu-0.7.3-py3-none-any.whl.

File metadata

File hashes

Hashes for StrawberryFields_gpu-0.7.3-py3-none-any.whl
Algorithm Hash digest
SHA256 982035c9b91928de7ab646b8233e72c128342be31f2a3fa078c845b632081891
MD5 8c71beaf814ede810951b9af14553553
BLAKE2b-256 256beea94c17807625fa0c68da5b3df4cbf37477570bcc0f29902d20440e87bf

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page