Strong convergence rates of a fully discrete scheme for the stochastic Cahn-Hilliard equation with additive noise

The first aim of this paper is to examine existence, uniqueness and regularity for the stochastic Cahn–Hilliard equation with additive noise in space dimension $d\leq 3$. By applying a spectral Galerkin method to the infinite dimensional equation, we elaborate the well-posedness and regularity of the finite dimensional approximate problem. The key idea lies in transforming the stochastic problem with additive noise into an equivalent random equation. The regularity of the solution to the equivalent random equation is obtained, in one dimension, with the aid of the Gagliardo–Nirenberg inequality and is done in two and three dimensions, by the energy argument. Further, the approximate solution is shown to be strongly convergent to the unique mild solution of the original stochastic equation, whose spatio-temporal regularity can be attained by similar arguments. In addition, a fully discrete approximation of such problem is investigated, performed by the spectral Galerkin method in space and the backward Euler method in time. The previously obtained regularity results help us to identify strong convergence rates of the fully discrete scheme. Numerical examples are finally included to confirm the theoretical findings.