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(WIP) Example code for NeurIPS 2022 paper "Differentiable Analog Quantum Computing for Learning and Control"

License: MIT License

C++ 17.40% Python 80.10% CMake 2.50%

diffquantum's Introduction

Differentiable Analog Quantum Computing for Learning and Control

Jiaqi Leng*, Yuxiang Peng*, Yi-Ling Qiao*, Ming C. Lin, Xiaodi Wu

[arXiv] [GitHub]

Setup

We have tested our code on Ubuntu and Mac (some code needs to be modified for Mac) with Python 3.8. Below is an example of how to build this library

git clone [email protected]:YilingQiao/diffquantum.git
cd diffquantum
pip install -r requirements.txt
git submodule init
git submodule update
python setup.py install

Demos

  1. Run QAOA to solve the maxcut problems.
python demo_maxcut.py

TODO. We are still clearning the code for

  1. Run VQE to solve for H2 Ground State and Energy.

  2. Demos for quantum control problems.

  3. Commparisons and draw

Documentation

TODO. We are preparing for more detailed documentation.

Bibtex

@inproceedings{leng2022diffaqc,
  title={Differentiable Analog Quantum Computing for Optimization and Control},
  author={Leng, Jiaqi and Peng, Yuxiang and Qiao, Yi-Ling and Lin, Ming and Wu, Xiaodi},
  booktitle={Conference on Neural Information Processing Systems (NeurIPS)},
  year={2022}
}

diffquantum's People

Contributors

jiaqileng avatar pickspeng avatar qiaoyiling avatar sqrta avatar yilingqiao avatar

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