Abstract:

The variational method is a versatile tool for classical simulation of a variety of quantum systems. Great efforts have recently been devoted to its extension to quantum computing for efficiently solving static many-body problems and simulating real and imaginary time dynamics. In this talk, we first review the conventional variational methods for solving static energy spectra and simulating real time dynamics. Then we introduce variational quantum simulation of mixed states under general stochastic evolution. We also present variational algorithms for simulating the generalised time evolution with a non-Hermitian Hamiltonian and matrix multiplication. We apply these methods to give an alternative algorithm of variational simulation of stochastic master equations. 

Short Bio:

Dr. Xiao Yuan received his Bachelor in theoretical physics (major) and computer science (minor) from Peking University in 2012. He received his Ph.D. degree in Physics from Tsinghua University in 2017. From 2017, Xiao conducted research as a postdoctoral fellow at University of Oxford. Xiao’s research interests span the wide spectrum of quantum information science, from fundamental quantum information to algorithms for near-term quantum computers. He predominantly worked on theoretical aspects of quantum information, specifically, measuring and quantifying ‘quantumness’, random number generation and self-testing quantum information. His current research is focused on pragmatic approaches to quantum computing, among which algorithms for simulation and machine learning on near-future quantum computers in particular. Xiao’s research explored the interconnectedness of these seemingly disparate topics, and ways to realize them experimentally.