Gradient-based Quantum Neural Network Using Quantum Computing Chips

Gradient-based Quantum Neural Network Using Quantum Computing Chips

CLEO 2023

10.1364/CLEO_AT.2023.JTh2A.22

https://doi.org/10.1364/cleo_at.2023.jth2a.22

Y. C. Zhan, H. Zhang, H. Cai, D. P. Poenar, L. C. Kwek, A. Q. Liu

27 July 2023

Zhan, Y. C., Zhang, H., Cai, H., Poenar, D. P., Kwek, L. C., & Liu, A. Q. (2023). Gradient-based Quantum Neural Network Using Quantum Computing Chips. CLEO 2023, JTh2A.22. https://doi.org/10.1364/cleo_at.2023.jth2a.22

An analytic gradient algorithm for training neural networks in an 8-mode quantum photonic chip is proposed. The algorithm shows 4x faster-training speed and 3% accuracy rate enhancement than existing approaches in solving two classification tasks.

Publisher Copyright

This research / project is supported by the Singapore Ministry of Education - Academic Research Fund Tier 3
Grant Reference no. : MOE2017-T3-1-001; PUB-1804-0082

This research / project is supported by the PUB, Singapore’s National Water Agency - N.A.
Grant Reference no. : PUB-1804-0082

https://oar.a-star.edu.sg/communities-collections/articles/21562

2160-8989

Institute of Microelectronics