Differentiable Quantum Computing for Large-scale Linear Control (NeurIPS 2024)

Connor Clayton*, Jiaqi Leng*, Gengzhi Yang*, Yi-Ling Qiao, Ming C. Lin, Xiaodi Wu

[NeurIPS] [GitHub]

Demos

1. To optimize the control policy K. Just run

python lqr2.py

2. We can switch between the classical method and ours by setting name = 'classical' or name = 'quantum' in lqr2.py. Logs are stored in ./logs

3. To run the scaling comparison, run

python scale_comparison.py

BibTex

@inproceedings{
clayton2024differentiable,
title={Differentiable Quantum Computing for Large-scale Linear Control},
author={Clayton, Connor and Leng, Jiaqi and Yang, Gengzhi and Qiao, Yi-Ling and Lin, Ming and Wu, Xiaodi},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
}