Open source library for continuous-variable quantum computation
Project description
PennyLane Strawberry Fields Plugin
##################################
.. image:: https://img.shields.io/travis/com/XanaduAI/pennylane-sf/master.svg?style=for-the-badge
:alt: Travis
:target: https://travis-ci.org/XanaduAI/pennylane-sf
.. image:: https://img.shields.io/codecov/c/github/xanaduai/pennylane-sf/master.svg?style=for-the-badge
:alt: Codecov coverage
:target: https://codecov.io/gh/XanaduAI/pennylane-sf
.. image:: https://img.shields.io/codacy/grade/33d12f7d2d0644968087e33966ed904e.svg?style=for-the-badge
:alt: Codacy grade
:target: https://app.codacy.com/app/XanaduAI/pennylane-sf?utm_source=github.com&utm_medium=referral&utm_content=XanaduAI/pennylane-sf&utm_campaign=badger
.. image:: https://img.shields.io/readthedocs/pennylane-sf.svg?style=for-the-badge
:alt: Read the Docs
:target: https://pennylane-sf.readthedocs.io
.. image:: https://img.shields.io/pypi/v/PennyLane-SF.svg?style=for-the-badge
:alt: PyPI
:target: https://pypi.org/project/PennyLane-SF
.. image:: https://img.shields.io/pypi/pyversions/PennyLane-SF.svg?style=for-the-badge
:alt: PyPI - Python Version
:target: https://pypi.org/project/PennyLane-SF
This PennyLane plugin allows the Strawberry Fields simulators to be used as PennyLane devices.
`Strawberry Fields <https://strawberryfields.readthedocs.io>`_ is a full-stack Python library for designing, simulating, and optimizing continuous variable (CV) quantum optical circuits.
`PennyLane <https://pennylane.readthedocs.io>`_ is a machine learning library for optimization and automatic differentiation of hybrid quantum-classical computations.
Features
========
* Provides two devices to be used with PennyLane: ``strawberryfields.fock`` and ``strawberryfields.gaussian``. These provide access to the Strawberry Fields Fock and Gaussian backends respectively.
* Supports all core PennyLane operations and expectation values across the two devices.
* Combine Strawberry Fields optimized simulator suite with PennyLane's automatic differentiation and optimization.
Installation
============
PennyLane-SF requires both PennyLane and Strawberry Fields. It can be installed via ``pip``:
.. code-block:: bash
$ python -m pip install pennylane-sf
Getting started
===============
Once the PennyLane-SF plugin is installed, the two provided Strawberry Fields devices can be accessed straight away in PennyLane.
You can instantiate these devices for PennyLane as follows:
.. code-block:: python
import pennylane as qml
dev_fock = qml.device('strawberryfields.fock', wires=2, cutoff_dim=10)
dev_gaussian = qml.device('strawberryfields.gaussian', wires=2)
These devices can then be used just like other devices for the definition and evaluation of QNodes within PennyLane. For more details, see the `plugin usage guide <https://pennylane-sf.readthedocs.io/en/latest/usage.html>`_ and refer to the PennyLane documentation.
Contributing
============
We welcome contributions - simply fork the PennyLane-SF repository, and then make a
`pull request <https://help.github.com/articles/about-pull-requests/>`_ containing your contribution. All contributers to PennyLane-SF 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 PennyLane and Strawberry Fields.
Authors
=======
Josh Izaac, Ville Bergholm, Maria Schuld, Nathan Killoran and Christian Gogolin
If you are doing research using PennyLane, please cite our whitepaper:
.. todo:: insert PennyLane whitepaper citation.
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/pennylane-sf
- **Issue Tracker:** https://github.com/XanaduAI/pennylane-sf/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
=======
PennyLane-SF is **free** and **open source**, released under the Apache License, Version 2.0.
##################################
.. image:: https://img.shields.io/travis/com/XanaduAI/pennylane-sf/master.svg?style=for-the-badge
:alt: Travis
:target: https://travis-ci.org/XanaduAI/pennylane-sf
.. image:: https://img.shields.io/codecov/c/github/xanaduai/pennylane-sf/master.svg?style=for-the-badge
:alt: Codecov coverage
:target: https://codecov.io/gh/XanaduAI/pennylane-sf
.. image:: https://img.shields.io/codacy/grade/33d12f7d2d0644968087e33966ed904e.svg?style=for-the-badge
:alt: Codacy grade
:target: https://app.codacy.com/app/XanaduAI/pennylane-sf?utm_source=github.com&utm_medium=referral&utm_content=XanaduAI/pennylane-sf&utm_campaign=badger
.. image:: https://img.shields.io/readthedocs/pennylane-sf.svg?style=for-the-badge
:alt: Read the Docs
:target: https://pennylane-sf.readthedocs.io
.. image:: https://img.shields.io/pypi/v/PennyLane-SF.svg?style=for-the-badge
:alt: PyPI
:target: https://pypi.org/project/PennyLane-SF
.. image:: https://img.shields.io/pypi/pyversions/PennyLane-SF.svg?style=for-the-badge
:alt: PyPI - Python Version
:target: https://pypi.org/project/PennyLane-SF
This PennyLane plugin allows the Strawberry Fields simulators to be used as PennyLane devices.
`Strawberry Fields <https://strawberryfields.readthedocs.io>`_ is a full-stack Python library for designing, simulating, and optimizing continuous variable (CV) quantum optical circuits.
`PennyLane <https://pennylane.readthedocs.io>`_ is a machine learning library for optimization and automatic differentiation of hybrid quantum-classical computations.
Features
========
* Provides two devices to be used with PennyLane: ``strawberryfields.fock`` and ``strawberryfields.gaussian``. These provide access to the Strawberry Fields Fock and Gaussian backends respectively.
* Supports all core PennyLane operations and expectation values across the two devices.
* Combine Strawberry Fields optimized simulator suite with PennyLane's automatic differentiation and optimization.
Installation
============
PennyLane-SF requires both PennyLane and Strawberry Fields. It can be installed via ``pip``:
.. code-block:: bash
$ python -m pip install pennylane-sf
Getting started
===============
Once the PennyLane-SF plugin is installed, the two provided Strawberry Fields devices can be accessed straight away in PennyLane.
You can instantiate these devices for PennyLane as follows:
.. code-block:: python
import pennylane as qml
dev_fock = qml.device('strawberryfields.fock', wires=2, cutoff_dim=10)
dev_gaussian = qml.device('strawberryfields.gaussian', wires=2)
These devices can then be used just like other devices for the definition and evaluation of QNodes within PennyLane. For more details, see the `plugin usage guide <https://pennylane-sf.readthedocs.io/en/latest/usage.html>`_ and refer to the PennyLane documentation.
Contributing
============
We welcome contributions - simply fork the PennyLane-SF repository, and then make a
`pull request <https://help.github.com/articles/about-pull-requests/>`_ containing your contribution. All contributers to PennyLane-SF 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 PennyLane and Strawberry Fields.
Authors
=======
Josh Izaac, Ville Bergholm, Maria Schuld, Nathan Killoran and Christian Gogolin
If you are doing research using PennyLane, please cite our whitepaper:
.. todo:: insert PennyLane whitepaper citation.
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/pennylane-sf
- **Issue Tracker:** https://github.com/XanaduAI/pennylane-sf/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
=======
PennyLane-SF is **free** and **open source**, released under the Apache License, Version 2.0.
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