Tomasz Śmierzchalski, Łukasz Pawela, Zbigniew Puchała, Tomasz Trzciński and Bartłomiej Gardas
This is the code and data required to reproduce all results presented in the paper Post-Error Correction for Quantum Annealing Processor using Reinforcement Learning published in Proceedings of the 22nd International Conference on Computational Science (ICCS 2022). All training and validation data were generated randomly during the model's training. The "data" folder consists of test datasets for different sizes of Chimera architecture. Further details are presented in the paper.
Quantum Annealing, Quantum Error Correction, Reinforcement Learning, Error Mitigation
This research was supported by the National Science Centre (NCN), Poland, under project number 2020/38/E/ST3/00269.
If you find this research useful, please cite it under:
@InProceedings{10.1007/978-3-031-08760-8_22,
author="{'{S}}mierzchalski, Tomasz
and Pawela, {\L}ukasz
and Pucha{\l}a, Zbigniew
and Trzci{'{n}}ski, Tomasz
and Gardas, Bart{\l}omiej",
editor="Groen, Derek
and de Mulatier, Cl{'e}lia
and Paszynski, Maciej
and Krzhizhanovskaya, Valeria V.
and Dongarra, Jack J.
and Sloot, Peter M. A.",
title="Post-error Correction for Quantum Annealing Processor Using Reinforcement Learning",
booktitle="Computational Science -- ICCS 2022",
year="2022",
publisher="Springer International Publishing",
pages="261--268",
isbn="978-3-031-08760-8"
doi="10.1007/978-3-031-08760-8_22"
}