High dimensional finite elements for multiscale Maxwell wave equations
This work provides an efficient numerical method for solving multiscale Maxwell equations, which is important for applications in electromagnetics and wave propagation.
The authors develop a sparse tensor product finite element method for multiscale Maxwell wave equations that achieves essentially optimal computational cost, requiring degrees of freedom comparable to solving a macroscopic problem in ℝ^d alone. Numerical correctors are constructed, and for two-scale problems, convergence rates are derived and confirmed by examples.
We develop an essentially optimal numerical method for solving multiscale Maxwell wave equations in a domain $D\subset{\mathbb R}^d$. The problems depend on $n+1$ scales: one macroscopic scale and $n$ microscopic scales. Solving the macroscopic multiscale homogenized problem, we obtain the desired macroscopic and microscopic information. This problem depends on $n+1$ variables in ${\mathbb R}^d$, one for each scale that the original multiscale equation depends on, and is thus posed in a high dimensional tensorized domain. The straightforward full tensor product finite element (FE) method is exceedingly expensive. We develop the sparse tensor product FEs that solve this multiscale homogenized problem with essentially optimal number of degrees of freedom, that is essentially equal to that required for solving a macroscopic problem in a domain in ${\mathbb R}^d$ only, for obtaining a required level of accuracy. Numerical correctors are constructed from the FE solution. For two scale problems, we derive a rate of convergence for the numerical corrector in terms of the microscopic scale and the FE mesh width. Numerical examples confirm our analysis.