Title: Higher order energy stable ETD based methods for gradient flows

Keynote Speaker: Wang Xiaoming

Abstract:

Many natural and engineering problems follow gradient flow structures in the sense that systems evolve to decrease certain energy. The dynamics of most of these gradient systems are complicated and hence numerical methods are called for. There are at least two desirable features for numerical algorithms for gradient flows with long evolution process: efficient higher oder in time, and long-time stability. We present a class of efficient higher-order energy stable methods for a class of gradient flows based on the exponential time differencing (ETD) method combined with multi-step methods and interpolation. As a specific example, we present a third order ETD based scheme for thin film epitaxial growth model together with numerical results establishing the convergence and stability of the scheme, and the ability of the scheme to capture long-time scaling properties of the system.

Introduction to the Speaker:

Professor Wang Xiaoming, graduated from Fudan University with bachelor and master degrees, received his Ph.D. degree from Indiana University Bloomington, and mainly studies the application of partial differential equations and numerical methods. He has published more than 90 papers in such journals as CPAM, JFM, and SINUM, and is a high-level overseas talent introduced by the country. He previously worked at Courant Institute of Mathematical Sciences, Institute of Advanced Study, Iowa State University, and Fudan University. Before returning to China, he was appointed as Full Professor and Dean of the Department of Mathematics at Florida State University. He is currently the Dean and Chair Professor of the Department of Mathematics at Southern University of Science and Technology.

Inviter:

Rui Hongxing  Professor in the School of Mathematics

Time:

10:00 on September 9 (Wednesday)

Location:

Zoom Conference, ID: 233 862 5719, password: 12345678

Sponsored by: School of Mathematics, Shandong University