Exponential Integrators for Stochastic Maxwells Equations Driven by It^o Noise

This article presents explicit exponential integrators for stochastic Maxwells equations driven by both multiplicative and additive noises. By utilizing the regularity estimate of the mild solution, we first prove that the strong order of the numerical approximation is $frac 12$ for general multiplicative noise. Combing a proper decomposition with the stochastic Fubinis theorem, the strong order of the proposed scheme is shown to be $1$ for additive noise. Moreover, for linear stochastic Maxwells equation with additive noise, the proposed time integrator is shown to preserve exactly the symplectic structure, the evolution of the energy as well as the evolution of the divergence in the sense of expectation. Several numerical experiments are presented in order to verify our theoretical findings.