报告时间：2019年9月19日 上午10:30

报告地点：近代物理系210会议室

报告人：曾蓓 香港科技大学教授

报告题目：Determining system Hamiltonian from eigenstate measurements without correlation functions  

报告摘要：Local Hamiltonians arise naturally in physical systems. Despite its seemingly `simple' local structure, exotic features such as nonlocal correlations and topological orders exhibit in eigenstates of these systems. Previous studies for recovering local Hamiltonians from measurements on an eigenstate [Math Processing Error] require information of nonlocal correlation functions. In this work, we develop an algorithm to determine local Hamiltonians from only local measurements on [Math Processing Error], by reformulating the task as an unconstrained optimization problem of certain target function of Hamiltonian parameters, with only polynomial number of parameters in terms of system size. We also develop a machine learning-based-method to solve the first-order gradient used in the algorithm. Our method is tested numerically for randomly generated local Hamiltonians and returns promising reconstruction in the desired accuracy. Our result shed light on the fundamental question on how a single eigenstate can encode the full system Hamiltonian, indicating a somewhat surprising answer that only local measurements are enough without additional assumptions, for generic cases.

https://arxiv.org/abs/1903.06569

报告人简介：Bei Zeng received the B.Sc. degree in physics and mathematics and M.Sc. degree in physics from Tsinghua University, in 2002 and 2004, respectively.  She received the Ph.D. degree in physics from Massachusetts Institute of Technology (MIT) in 2009. From 2009 to 2010, she was a postdoctoral fellow at the Institute for Quantum Computing (IQC) and the Department of Combinatorics & Optimization, University of Waterloo. In 2010, she joined the Department of Mathematics & Statistics, University of Guelph, as an assistant professor, and promoted to Tenured Associate Professor in 2014 and Professor in 2018. In 2019, she joined the Department of Physics, The Hong Kong University of Science and Technology, as a Professor.