Existence, uniqueness, and numerical approximations for stochastic Burgers equations

Abstract

In this paper we propose an all-in-one statement which includes existence, uniqueness, regularity, and numerical approximations of mild solutions for a class of stochastic partial differential equations (SPDEs) with non-globally monotone nonlinearities. The proof of this result exploits the properties of an existent fully explicit space-time discrete approximation scheme and, in particular, the fact that it satisfies suitable a priori estimates. As a byproduct we obtain almost sure and strong convergence of the approximation scheme to the mild solutions of the considered SPDEs. We conclude by applying the main result of the paper to the stochastic Burgers equations with space-time white noise.

Strong convergence rates for full-discrete approximations of stochastic Burgers equations with multiplicative noise

“…To overcome this issue, tamed Euler approximations were introduced in [26,23]. Subsequently further tamed Euler approximations were introduced and analyzed; see, e.g., [10,31,40,41,43,44,47] for stochastic ordinary differential equtaions and, e.g., [2,3,21,29,38,39,42] for SEEs. Strong convergence rates for explicit time discrete and explicit space-time discrete numerical methods for SEEs with a non-globally Lipschitz continuous but globally monotone nonlinearity have been derived in, e.g., [2,3,7,38,45].…”