An averaged space–time discretization of the stochastic p-Laplace system

Abstract

AbstractWe study the stochastic p-Laplace system in a bounded domain. We propose two new space–time discretizations based on the approximation of time-averaged values. We establish linear convergence in space and 1/2 convergence in time. Additionally, we provide a sampling algorithm to construct the necessary random input in an efficient way. The theoretical error analysis is complemented by numerical experiments.