Experimental quantum natural gradient optimization in photonics

no code implementations • 11 Oct 2023 • Yizhi Wang, Shichuan Xue, Yaxuan Wang, Jiangfang Ding, Weixu Shi, Dongyang Wang, Yong liu, Yingwen Liu, Xiang Fu, Guangyao Huang, Anqi Huang, Mingtang Deng, Junjie Wu

Our work opens up a vista of utilizing QNG in photonics to implement practical near-term quantum applications.

Quantum generative adversarial learning in photonics

no code implementations • 1 Oct 2023 • Yizhi Wang, Shichuan Xue, Yaxuan Wang, Yong liu, Jiangfang Ding, Weixu Shi, Dongyang Wang, Yingwen Liu, Xiang Fu, Guangyao Huang, Anqi Huang, Mingtang Deng, Junjie Wu

Quantum Generative Adversarial Networks (QGANs), an intersection of quantum computing and machine learning, have attracted widespread attention due to their potential advantages over classical analogs.

Variational Quantum Circuits for Quantum State Tomography

1 code implementation • 16 Dec 2019 • Yong Liu, Dongyang Wang, Shichuan Xue, Anqi Huang, Xiang Fu, Xiaogang Qiang, Ping Xu, He-Liang Huang, Mingtang Deng, Chu Guo, Xuejun Yang, Junjie Wu

We demonstrate our method by performing numerical simulations for the tomography of the ground state of a one-dimensional quantum spin chain, using a variational quantum circuit simulator.

Quantum Machine Learning Quantum State Tomography