Crank-Nicolson finite element approximations for a linear stochastic fourth order equation with additive space-time white noise
For researchers in numerical analysis of stochastic PDEs, this provides an alternative time-stepping scheme with equivalent convergence rates, though the result is incremental as it matches existing methods.
The paper develops and analyzes a Crank-Nicolson finite element method for a linear stochastic fourth-order parabolic equation with additive space-time white noise, proving strong error estimates that match the convergence order of the Backward Euler method from prior work.
We consider a model initial- and Dirichlet boundary- value problem for a fourth-order linear stochastic parabolic equation, in one space dimension, forced by an additive space-time white noise. First, we approximate its solution by the solution of an auxiliary fourth-order stochastic parabolic problem with additive, finite dimensional, spectral-type stochastic load. Then, fully-discrete approximations of the solution to the approximate problem are constructed by using, for the discretization in space, a standard Galerkin finite element method based on $H^2$-piecewise polynomials, and, for time-stepping, the Crank-Nicolson method. Analyzing the convergence of the proposed discretization approach, we derive strong error estimates which show that the order of strong convergence of the Crank-Nicolson finite element method is equal to that reported in [Kosioris and Zouraris MMAN 44 (2010)] for the Backward Euler finite element method.