Weak approximation of stochastic partial differential equations: the non linear case

Details Weak approximation of stochastic partial differential equations: the non linear case Weak approximation of stochastic partial differential equations: the non linear case

2008-04-08

arxiv.org/abs/0804.1304v1

Mathematics

Numerical Analysis

Scientific paper

We study the error of the Euler scheme applied to a stochastic partial differential equation. We prove that as it is often the case, the weak order of convergence is twice the strong order. A key ingredient in our proof is Malliavin calculus which enables us to get rid of the irregular terms of the error. We apply our method to the case a semilinear stochastic heat equation driven by a space-time white noise.

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