Special Session 92: Numerical Methods for SPDEs: Bridging Theory and Applications
Strong convergence rates for stochastic Burgers equations
Martin Hutzenthaler
University of Duisburg-Essen Germany
Co-Author(s): Arnulf Jentzen, Felix Lindner, Robert Link, Primoz Pusnik
Abstract:
Subject of this talk are strong convergence rates on the whole probability space for explicit full-discrete approximations of stochastic Burgers equations with multiplicative trace-class noise. The nonlinearity of this benchmark SPDE is not globally monotone. Many classical approximation methods do not converge in the strong sense. In this talk we discuss methods which do converge in the strong sense. The key step in the convergence proof are uniform exponential moment estimates for the numerical approximations.