Variational learning the SDC quantum protocol with gradient-based optimization

被引:2
作者
Situ, Haozhen [1 ,2 ]
Huang, Zhiming [3 ]
Zou, Xiangfu [2 ,5 ]
Zheng, Shenggen [2 ,4 ]
机构
[1] South China Agr Univ, Coll Math & Informat, Guangzhou 510642, Guangdong, Peoples R China
[2] Ctr Quantum Comp, Peng Cheng Lab, Shenzhen 518055, Peoples R China
[3] Wuyi Univ, Sch Econ & Management, Jiangmen 529020, Peoples R China
[4] Southern Univ Sci & Technol, Inst Quantum Sci & Engn, Shenzhen 518055, Peoples R China
[5] Wuyi Univ, Sch Math & Computat Sci, Jiangmen 529020, Peoples R China
基金
中国国家自然科学基金;
关键词
Quantum machine learning; Quantum protocol; Simultaneous dense coding;
D O I
10.1007/s11128-019-2348-9
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Recently, a variational learning approach is adopted to discover quantum communication protocols (Wan et al. in npj Quantum Inf 3:36, 2017). Because designing quantum protocols manually is a delicate and difficult work, this variational learning approach is well worth further study. In this paper, we use the same approach to learn the simultaneous dense coding (SDC) protocols with two or three receivers. The gradient-based optimization is used to learn the parameters of the locking operator of the SDC protocol. Two different designs of the loss function are considered. Numerical experiment results show the effectiveness of this variational learning approach.
引用
收藏
页数:10
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