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SYMPLECTIC DISCONTINUOUS GALERKIN FULL DISCRETIZATION FOR STOCHASTIC MAXWELL EQUATIONS
被引:7
作者:
Chen, Chuchu
[1
,2
]
机构:
[1] Chinese Acad Sci, Acad Math & Syst Sci, ICMSEC, LSEC, Beijing 100190, Peoples R China
[2] Univ Chinese Acad Sci, Sch Math Sci, Beijing 100149, Peoples R China
基金:
中国国家自然科学基金;
关键词:
stochastic Maxwell equations;
symplectic dG full discretization;
mean-square convergence;
MEAN-SQUARE CONVERGENCE;
SCHEME;
D O I:
10.1137/20M1368537
中图分类号:
O29 [应用数学];
学科分类号:
070104 ;
摘要:
This paper proposes a fully discrete method called the symplectic discontinuous Galerkin (dG) full discretization for stochastic Maxwell equations driven by additive noises, based on a stochastic symplectic method in time and a dG method with the upwind fluxes in space. A priori H-k-regularity (k is an element of {1, 2}) estimates for the solution of stochastic Maxwell equations are presented, which have not been reported before to the best of our knowledge. These H-k-regularities are vital to making the assumptions of the mean-square convergence analysis on the initial fields, the noise, and the medium coefficients, but not on the solution itself. The convergence order of the symplectic dG full discretization is shown to be k/2 in the temporal direction and k-1/2 in the spatial direction. Meanwhile we reveal the small noise asymptotic behaviors of the exact and numerical solutions via the large deviation principle, and show that the fully discrete method preserves the divergence relations in a weak sense.
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页码:2197 / 2217
页数:21
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