Strong Convergence of Full Discretization for Stochastic Cahn-Hilliard Equation Driven by Additive Noise

In this article, we consider the stochastic Cahn-Hilliard equation driven by additive noise. We discretize the equation by exploiting the spectral Galerkin method in space and a temporal accelerated implicit Euler method. Based on optimal regularity estimates of both exact and numerical solutions, we prove that the proposed numerical method is strongly convergent with a sharp convergence rate in a negative Sobolev space. Utilizing the semigroup theory and interpolation inequality, we deduce the spatial optimal convergence rate and the temporal superconvergence rate of the proposed numerical method in the strong sense.