  This paper proposes and analyzes a new operator splitting method for
stochastic Maxwell equations driven by additive noise, which not only
decomposes the original multi-dimensional system into some local
one-dimensional subsystems, but also separates the deterministic and stochastic
parts. This method is numerically efficient, and preserves the symplecticity,
the multi-symplecticity as well as the growth rate of the averaged energy. A
detailed $H^2$-regularity analysis of stochastic Maxwell equations is obtained,
which is a crucial prerequisite of the error analysis. Under the regularity
assumptions of the initial data and the noise, the convergence order one in
mean square sense of the operator splitting method is established.
