# Eliminating Gibbs Phenomena: A Non-linear Petrov-Galerkin Method for the Convection-Diffusion-Reaction Equation

## TL;DR

This paper introduces a non-linear Petrov-Galerkin method based on residual minimization in dual norms within Banach spaces to effectively eliminate Gibbs phenomena in convection-diffusion-reaction equations, especially in convection-dominated regimes.

## Contribution

It extends the Petrov-Galerkin framework to reflexive Banach spaces with residual minimization in dual norms, reducing oscillations in numerical solutions of convection-diffusion-reaction equations.

## Key findings

- Oscillations diminish as q approaches 1 in the Lq setting.
- The method effectively reduces Gibbs phenomena in numerical experiments.
- Generalizes discontinuous Petrov-Galerkin methods to Banach spaces.

## Abstract

In this article we consider the numerical approximation of the convection-diffusion-reaction equation. One of the main challenges of designing a numerical method for this problem is that boundary layers occurring in the convection-dominated case can lead to non-physical oscillations in the numerical approximation, often referred to as Gibbs phenomena. The idea of this article is to consider the approximation problem as a residual minimization in dual norms in Lq-type Sobolev spaces, with 1 < q < $\infty$. We then apply a non-standard, non-linear PetrovGalerkin discretization, that is applicable to reflexive Banach spaces such that the space itself and its dual are strictly convex. Similar to discontinuous Petrov-Galerkin methods, this method is based on minimizing the residual in a dual norm. Replacing the intractable dual norm by a suitable discrete dual norm gives rise to a non-linear inexact mixed method. This generalizes the Petrov-Galerkin framework developed in the context of discontinuous Petrov-Galerkin methods to more general Banach spaces. For the convection-diffusion-reaction equation, this yields a generalization of a similar approach from the L2-setting to the Lq-setting. A key advantage of considering a more general Banach space setting is that, in certain cases, the oscillations in the numerical approximation vanish as q tends to 1, as we will demonstrate using a few simple numerical examples.