LOCALIZED ORTHOGONAL DECOMPOSITION FOR A MULTISCALE PARABOLIC STOCHASTIC PARTIAL DIFFERENTIAL EQUATION.

A multiscale method is proposed for a parabolic stochastic partial differential equation with additive noise and highly oscillatory diffusion. The framework is based on the localized orthogonal decomposition (LOD) method and computes a coarse-scale representation of the elliptic operator, enriched by fine-scale information on the diffusion. Optimal order strong convergence is derived. The LOD technique is combined with a (multilevel) Monte Carlo estimator and the weak error is analyzed. Numerical examples that confirm the theoretical findings are provided, and the computational efficiency of the method is highlighted. [ABSTRACT FROM AUTHOR]