姬利海副研究员，北京应用物理与计算数学研究所

In this talk, we will introduce a novel overlapping domain decomposition splitting algorithm based on a Crank--Nisolson method is developed for the stochastic NLS equation driven by a multiplicative noise with non-periodic boundary conditions. The proposed algorithm can significantly reduce the computational cost while maintaining the similar conservation laws. Numerical experiments are dedicated to illustrating the capability of the algorithm for different spatial dimensions, as well as the various initial conditions. In particular, we observe that our proposed algorithm has excellent computational efficiency and is highly competitive by comparing with the classical ones. It provides a useful tool for solving stochastic partial differential equations.