no code implementations • 20 Dec 2019 • Yusen Wu, Chao-hua Yu, Sujuan Qin, Qiaoyan Wen, Fei Gao
Specifically, the training phase provides a physical quantity to measure the posterior distribution in quantum feature spaces, and this measure is utilized to design the quantum maximum a posterior (QMAP) algorithm and the quantum predictive distribution estimator (QPDE).
no code implementations • 30 Sep 2019 • Yuan-Yuan Zhao, Chao Zhang, Shuming Cheng, Xinhui Li, Yu Guo, Bi-Heng Liu, Huan-Yu Ku, Shin-Liang Chen, Qiaoyan Wen, Yun-Feng Huang, Guo-Yong Xiang, Chuan-Feng Li, Guang-Can Guo
We first establish the DI verification framework, relying on the measurement-device-independent technique and self-testing, and show it is able to verify all EPR-steerable states.
Quantum Physics