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NISQAI

NISQAI is a library for quantum artificial intelligence on near-term quantum computers. For an overview of our project, please watch this short YouTube Video. For more detailed information, please read our project proposal.

NISQAI is currently in development. The examples folder contains instructive notebooks on some of our ideas, such as our one-qubit quantum classifier.

Development Instructions

We're happy to accept your contributions. To do so, follow these instructions:

  1. Fork the development repository rmlarose/nisqai-dev.

  2. CD into the directory with setup.py:

cd nisqai-dev

  1. Install the NISQAI package:

pip install -e .

From here, you can make your contributions on your fork, then submit a pull request. If these are unfamiliar to you, don't worry! We're happy to help. Send an email to Ryan (rlarose@umich.edu) with any questions.

For ideas of what to contribute, see the issues on the development repository.

Developers

  • Ryan LaRose
  • Yousif Almulla
  • Nic Ezzell
  • Joe Iosue
  • Arkin Tikku

Acknowledgements

The development of NISQAI is supported by the unitary.fund. We thank Will Zeng for creating and running this program, as well as John Hering, Jeff Cordova, Nima Alidoust, and PLOS for sponsoring it.

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A Python toolkit for quantum neural networks.

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