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Welcome to MentPy’s documentation

Note

MentPy is in its alpha version and is under active development.

The mentpy library is an open-source Python package for creating and training quantum machine learning (QML) models in the measurement-based quantum computing (MBQC) framework. This library contains functions to automatically calculate the causal flow or generalized flow of a graph and tools to analyze the expressivity of the MBQC ansatzes.

Features

  • Manipulation of graph states.

  • Automatically calculate the causal flow or generalized flow of a graph.

  • Simulate MBQC circuits.

  • Optimize measurement angles in MBQC ansatzes used for QML.

  • Create data and noisy data for training QML models.

  • Determine the lie algebra of an MBQC ansatz.

Roadmap

  • Improve current simulators for MBQC circuits.

  • Increase code coverage.

  • Add autodiff support for MBQC circuits.

  • Add support for more general MBQC states.

  • Integrate with pyzx to optimize resources in MBQC circuits.

Contributing

If you would like to contribute to this project, please feel free to open an issue or pull request 😄.

Acknowledgements

This library was first developed by Luis Mantilla for his master’s thesis at the University of British Columbia. Luis would like to thank his M.Sc. supervisors, Dr. Dmytro Bondarenko, Dr. Polina Feldmann, and Dr. Robert Raussendorf.

Citation

If you find MentPy useful in your research, please consider citing us 🙂

@software{Mantilla_Mentpy_2023,
   title = {{MentPy: A python package for simulating and training QML models in the MBQC framework.}},
   author = {Mantilla, Luis},
   year = {2023},
   url = {https://github.com/mentpy/mentpy},
}
L. Mantilla, MentPy: A python package for simulating and training QML models in the MBQC framework, (2023). https://github.com/mentpy/mentpy
Mantilla, L. (2023). MentPy: A python package for simulating and training QML models in the MBQC framework. Retrieved from https://github.com/mentpy/mentpy
Mantilla, Luis. MentPy: A python package for simulating and training QML models in the MBQC framework. 2023. Web. https://github.com/mentpy/mentpy