Quantum numerical linear algebra
Thursday, May 6, 2021
3:30PM – 5PM
The two "quantum supremacy" experiments (by Google in 2019 and by USTC in 2020, respectively) have brought quantum computation to the public's attention. In this talk, I will discuss how to use a quantum computer to solve linear algebra problems. I will start with a toy linear system Ax=b, where A is merely a 2 x 2 matrix. I will then talk about some recent progress of quantum linear system solvers, eigenvalue problems, and a proposal for the quantum LINPACK benchmark.
Lin Lin received his B.S. degree in Computational Mathematics from Peking University in 2007, and Ph.D. degree in Applied and Computational Mathematics from Princeton University in 2011, advised by Professor Weinan E and Professor Roberto Car. His research focuses on the development of efficient and accurate numerical methods for electronic structure calculations, with broad applications in quantum chemistry, quantum physics and materials science. He is now an associate professor in the Department of Mathematics at UC Berkeley, a faculty scientist at Berkeley Lab’s Mathematics Group within the Computational Research Division, and a mathematician within Berkeley Lab's Center for Advanced Mathematics for Energy Research Applications (CAMERA). He received the Sloan Research Fellowship (2015), the National Science Foundation CAREER award (2017), the Department of Energy Early Career award (2017), the inaugural SIAM Computational Science and Engineering (CSE) early career award (2017), the Presidential Early Career Awards for Scientists and Engineers (PECASE) (2019), and the ACM Gordon Bell Prize (Team, 2020).