Notice: This library is no longer actively maintained. Its spiritual successor is PennyLane <https://github.com/XanaduAI/pennylane>_ ##############################################################################################################################################

Quantum Machine Learning Toolbox (QMLT) ###########################################

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The Quantum Machine Learning Toolbox (QMLT) is a Strawberry Fields <https://github.com/XanaduAI/strawberryfields>_ application that simplifies the optimization of variational quantum circuits. Tasks for the QMLT range from variational eigensolvers and unitary learning to supervised and unsupervised machine learning with models based on a variational circuit.

Features

The Quantum Machine Learning Toolbox supports:

• The training of user-provided variational circuits

• Automatic and numerical differentiation methods to compute gradients of circuit outputs

• Optimization, supervised and unsupervised learning tasks

• Regularization of circuit parameters

• Logging of training results

• Monitoring and visualization of training through matplotlib and TensorBoard

• Saving and restoring trained models

• Parallel computation/GPU usage for TensorFlow-based models

To get started, please see the online documentation <https://qmlt.readthedocs.io>_.

Installation

Installation of the QMLT, as well as all required Python packages mentioned above, can be done using pip: ::

$ python -m pip install qmlt

Tests

To run all tests please run the following line from the main directory: ::

$ python -m unittest discover tests

Code authors

Maria Schuld and Josh Izaac.

If you are doing research using Strawberry Fields, please cite our whitepaper <https://arxiv.org/abs/1804.03159>_ and the QMLT documentation:

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

Maria Schuld and Josh Izaac. Xanadu Quantum Machine Learning Toolbox documentation. https://qmlt.readthedocs.io.

Support

• Source Code: https://github.com/XanaduAI/QMLT
• Issue Tracker: https://github.com/XanaduAI/QMLT/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

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