Stability estimates for Interior Penalty D.G. Methods for the Nonlinear Dynamics of the complex Ginzburg Landau equation

TL;DR

This paper compares three Discontinuous Galerkin schemes for the complex Ginzburg Landau equation, demonstrating their stability and efficiency, with SIPG being the most robust and IIPG showing superior stability among the others.

Contribution

It provides a rigorous stability analysis and comparative study of three DG schemes applied to the nonlinear complex Ginzburg Landau equation, highlighting their relative robustness and efficiency.

Findings

All three DG schemes are stable for the complex Ginzburg Landau equation.

SIPG scheme remains bounded and is most robust under nonlinear conditions.

IIPG scheme exhibits superior stability compared to NIPG.

Abstract

This study investigates the complex Landau equation, a reaction diffusion system with applications in nonlinear optics and fluid dynamics. The equation's nonlinear imaginary component introduces rich dynamics and significant computational challenges. We address these challenges using Discontinuous Galerkin (DG) finite element methods. A rigorous stability analysis and a comparative study are performed on three distinct DG schemes : Symmetric Interior Penalty Galerkin (SIPG), Nonsymmetric Interior Penalty Galerkin (NIPG), and Incomplete Interior Penalty Galerkin (IIPG). These methods are compared in terms of their stability and computational efficiency. Our numerical analysis and computational results demonstrate that all three discontinuous Galerkin (DG) schemes are stable. However, the Symmetric Interior Penalty Galerkin (SIPG) scheme proves to be the most robust, as its norm remains bounded even in the presence of nonlinear terms a property not shared by the others. A comparison between the Incomplete Interior Penalty Galerkin (IIPG) and Nonsymmetric Interior Penalty Galerkin (NIPG) schemes shows that IIPG has superior stability properties. For high values of the penalty parameter, all methods exhibit similar stability behavior. Our results highlight the suitability of DG methods for simulating complex nonlinear reaction-diffusion systems and provide a practical framework for selecting the most efficient scheme for a given problem.