One- and multi-dimensional stochastic Maxwell equations with additive noise are considered in this paper. It is known that such system can be written in the multi-symplectic structure, and the stochastic energy increases linearly in time. High order discontinuous Galerkin methods are designed for the stochastic Maxwell equations with additive noise, and we show that the proposed methods satisfy the discrete form of the stochastic energy linear growth property and preserve the multi-symplectic structure on the discrete level. Optimal error estimate of the semi-discrete DG method is also analyzed. The fully discrete methods are obtained by coupling with symplectic temporal discretizations. One- and two-dimensional numerical results are provided to demonstrate the performance of the proposed methods, and optimal error estimates and linear growth of the discrete energy can be observed for all cases.
翻译:本文考虑了含有添加噪声的单维和多维随机Maxwell方程式。众所周知,这种系统可以写在多中位结构中,而随机能量则在时间上线性地增加。高有序不连续的Galerkin方法是为具有添加噪声的随机Maxwell方程式设计的,我们表明,建议的方法满足了随机能量线性增长特性的离散形式,并维护了离散水平上的多中位结构。还分析了半分位DG方法的最佳误差估计。完全离散的方法是通过与随机时间分解的混合获得的。提供了一维和二维的数字结果,以证明拟议方法的性能,并且对所有情况都可以看到最佳误差估计和离散能量的线性增长。