An efficient Monte Carlo interior penalty discontinuous Galerkin method for the time-harmonic Maxwell's equations with random coefficients
This work addresses the computational challenge of simulating electromagnetic wave propagation in random media, offering a provably convergent method for uncertainty quantification.
The paper develops an efficient Monte Carlo interior penalty discontinuous Galerkin method for time-harmonic Maxwell's equations with random coefficients, achieving optimal convergence order across three approximation levels as validated by numerical experiments.
This paper develops an efficient Monte Carlo interior penalty discontinuous Galerkin method for electromagnetic wave propagation in random media. This method is based on a multi-modes expansion of the solution to the time-harmonic random Maxwell equations. It is shown that each mode function satisfies a Maxwell system with random sources defined recursively. An unconditionally stable IP-DG method is employed to discretize the nearly deterministic Maxwell system and the Monte Carlo method combined with an efficient acceleration strategy is proposed for computing the mode functions and the statistics of the electromagnetic wave. A complete error analysis is established for the proposed multi-modes Monte Carlo IP-DG method. It is proved that the proposed method converges with an optimal order for each of three levels of approximations. Numerical experiments are provided to validate the theoretical results and to gauge the performance of the proposed numerical method and approach.