报告题目 | Gaussian Boson Sampling and its applications |
报告人 | 粟待钦 博士 |
报告人单位 | 加拿大初创公司Xanadu |
报告时间 | 2020-01-15 (周三) 10:30 |
报告地点 | 上海研究院4号楼331会议室 |
主办单位 | 中国科学院量子信息与量子科技创新研究院 |
报告介绍 | Gaussian Boson Sampling is a variant of the well known Boson Sampling, for which the input is Gaussian states (squeezed vacuum and/or coherent states) instead of single photons. Same as the Boson Sampling, Gaussian Boson Sampling is proposed to demonstrate quantum supremacy in a near-term quantum device. It is tempting to find potential applications of Gaussian Boson Sampling. In this talk, I will discuss the connection between Gaussian Boson Sampling and graph theory, and its potential applications to graph related problems. In particular, I will discuss in detail how to use a Gaussian Boson Sampling device to solve the graph isomorphism problem and the graph similarity problem. |