Quantum Numerical Analysis
Abstract
Recent developments in quantum computers have inspired rapid progress in developing quantum algorithms for scientific computing, including examples in numerical linear algebra, partial differential equations, and machine learning. However, the noise of quantum devices and quantum measurements pose new questions in the area of numerical analysis of quantum algorithms. In this talk, the speaker will discuss two of his recent works in this direction: (1) new low-depth algorithms for quantum phase estimation for early fault-tolerant quantum devices and (2) a new robust algorithm for computing phase factors in forming general functions of quantum operators.
About the Speaker
Prof. Ying Lexing received his BS in Computer Science and Applied Mathematics from Shanghai Jiao Tong University in 1998. He then received his MS and PhD from the Courant Institute of Mathematical Sciences at New York University in 2000 and 2004 respectively. Before joining Stanford University in 2012, he was a Postdoctoral Scholar at the California Institute of Technology and a Professor at the University of Texas at Austin. He is currently a Professor of Mathematics at Stanford University, where he is also a member of the Institute for Computational and Mathematical Engineering.
Prof. Ying specializes in scientific computing and numerical analysis. In particular, his research concerns about the design of numerical algorithms for problems in scientific computing. The awards he has received include a Sloan Research Fellowship in 2007, an US National Science Foundation Career Award in 2009, the James H. Wilkinson Prize in Numerical Analysis and Scientific Computing in 2013 and a Morningside Silver Medal of Applied Mathematics in 2016. He was an invited speaker of the 2022 International Congress of Mathematicians.
For Attendees' Attention
This talk will be held online via Zoom. To attend, please join the Zoom meeting at https://hkust.zoom.us/j/93414564699 (Meeting ID: 934 1456 4699 / Passcode: iasip2023).
About the Program
For more information, please refer to the program website at https://iasprogram.hkust.edu.hk/inverseproblems/.
