**Zu Chongzhi Mathematics Research Seminar**

**Date and Time (China standard time): **Friday, November 1, 2:00 pm – 3:00 pm

**Location: **WDR 1007

**Zoom**: 977 7589 0705, **Passcode**: dkumath

**Title**: Sharp error estimate of Euler type methods for SDEs via relative entropy

**Speaker**: Lei Li

**Abstract**: We establish sharp error estimates of the laws for Euler type discretization of some stochastic differential equations. In particular, we consider the discretization of Langevin diffusion with random batch approximation, and the equations with multiplicative noise. Our approach is to use the relative entropy, together with some integrability estimates of the derivatives of the logarithmic numerical density.

**Bio**: Lei Li is currently a tenure-track associate professor in the Institute of Natural Sciences and the School of Mathematical Sciences at Shanghai Jiao Tong University (SJTU). He obtained his B.S. from Tsinghua University in 2010 and Ph.D. from the University of Wisconsin-Madison in 2015. Then, he was an assistant research professor at Duke University, and joined SJTU in 2018. His main research interest is in applied mathematics, especially designing and analyzing numerical methods for stochastic models arising from physics and data sciences. Currently, he is focusing the interacting particle systems and stochastic differential equations.