On stabilized P1 finite element approximation fortime harmonic Maxwell's equations

TL;DR

This paper develops and analyzes a stabilized finite element method for time harmonic Maxwell's equations, transforming the hyperbolic problem into an elliptic form to ensure stability, convergence, and robustness of the numerical scheme.

Contribution

It introduces a stabilized linear finite element approach for Maxwell's equations in dual form, providing theoretical convergence proofs and adaptive algorithms validated by numerical experiments.

Findings

Proves coercivity and unique solvability of the stabilized scheme.

Establishes optimal convergence rates of O(h) in L2 and residual norms.

Validates robustness through numerical examples.

Abstract

One way of improving the behavior of finite element schemes for classical, time-dependent Maxwell's equations, is to render them from their hyperbolic character to elliptic form. This paper is devoted to the study of the stabilized linear finite element method for the time harmonic Maxwell's equations in a dual form obtained through the Laplace transformation in time. The model problem is for the particular case of the dielectric permittivity function which is assumed to be constant in a boundary neighborhood. For the stabilized model a coercivity relation is derived that guarantee's the existence of a unique solution for the iscrete problem. The convergence is addressed both in a priori and a posteriori settings. In the a priori error estimates we confirm the theoretical convergence of the scheme in a L2-based, gradient dependent, triple norm. The order of convergence is O(h) in weighted Sobolev space and hence optimal. We also derive, similar, optimal a posteriori error estimates controlled by a certain, weighted, norm of the residual of the computed solution. The posteriori approach is used for constructing adaptive algorithms for the computational purposes. Further, assuming a sufficiently regular solution for the dual problem, we reach the same convergence of O(h). Finally, through implementing several numerical examples, we validate the robustness of the proposed scheme.