Magnus-type integrator for non-autonomous SPDEs driven by multiplicative noise

Abstract

<p style='text-indent:20px;'>This paper aims to investigate numerical approximation of a general second order non-autonomous semilinear parabolic stochastic partial differential equation (SPDE) driven by multiplicative noise. Numerical approximations of autonomous SPDEs are thoroughly investigated in the literature, while the non-autonomous case is not yet understood. We discretize the non-autonomous SPDE by the finite element method in space and the Magnus-type integrator in time. We provide a strong convergence proof of the fully discrete scheme toward the mild solution in the root-mean-square <inline-formula><tex-math id="M1">\begin{document}$ L^2 $\end{document}</tex-math></inline-formula> norm. The result reveals how the convergence orders in both space and time depend on the regularity of the noise and the initial data. In particular, for multiplicative trace class noise we achieve convergence order <inline-formula><tex-math id="M2">\begin{document}$ \mathcal{O}\left(h^2\left(1+\max(0, \ln\left(t_m/h^2\right)\right)\right. \left.+\Delta t^{\frac{1}{2}}\right) $\end{document}</tex-math></inline-formula>. Numerical simulations to illustrate our theoretical finding are provided.