POST PROCESSING FOR STOCHASTIC PARABOLIC PARTIAL DIFFERENTIAL EQUATIONS

Abstract. We investigate the strong approximation of stochastic parabolic partial dierential equations with additive noise. We introduce post-processing in the context of a standard Galerkin approximation, although other spatial discretisations are possible. In time, we follow [18] and use an exponential integrator. We prove strong error estimates and discuss the best number of post-processing terms to take. Numerically, we evaluate the eciency of the methods and observe rates of convergence. Some experiments with the implicit Euler{Maruyama method are described. Key words. Stochastic exponential integrator, post-processing, numerical solution of stochastic PDEs. AMS subject classications. 60H15,65M12,65M15,65M60 1. Introduction. W