Structure preserving integration and model order reduction of skew-gradient reaction-diffusion systems
B\"ulent Karas\"ozen, Tu\u{g}ba K\"u\c{c}\"ukseyhan, Murat Uzunca

TL;DR
This paper develops a structure-preserving numerical framework for skew-gradient reaction-diffusion systems, combining discretization, energy preservation, and model order reduction to efficiently simulate complex patterns.
Contribution
It introduces a novel combination of SIPG, AVF, and POD-DEIM methods for energy-preserving discretization and reduction of skew-gradient reaction-diffusion equations.
Findings
Energy of the discrete system satisfies mini-maximizer property.
Numerical simulations show accurate reproduction of patterns.
Reduced models significantly improve computational efficiency.
Abstract
Activator-inhibitor FitzHugh-Nagumo (FHN) equation is an example for reaction-diffusion equations with skew-gradient structure. We discretize the FHN equation using symmetric interior penalty discontinuous Galerkin (SIPG) method in space and average vector field (AVF) method in time. The AVF method is a geometric integrator, i.e. it preserves the energy of the Hamiltonian systems and energy dissipation of the gradient systems. In this work, we show that the fully discrete energy of the FHN equation satisfies the mini-maximizer property of the continuous energy for the skew-gradient systems. We present numerical results with traveling fronts and pulses for one dimensional, two coupled FHN equations and three coupled FHN equations with one activator and two inhibitors in skew-gradient form. Turing patterns are computed for fully discretized two dimensional FHN equation in the form of…
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