Constructive existence proofs and stability of stationary solutions to parabolic PDEs using Gegenbauer polynomials

TL;DR

This paper introduces a computer-assisted framework using Gegenbauer polynomials for constructive existence proofs and stability analysis of stationary solutions to one-dimensional parabolic PDEs.

Contribution

It develops a general approach for boundary value problems, providing explicit estimates and a Newton-Kantorovich method for rigorous existence and stability verification.

Findings

Successfully verified existence of stationary solutions near numerical approximations.

Accurately enclosed the spectrum of the linearization to determine stability.

Demonstrated effectiveness on multiple applications capturing stable and unstable states.

Abstract

In this paper, we present a computer-assisted framework for constructive proofs of existence for stationary solutions to one-dimensional parabolic PDEs and the rigorous determination of their linear stability. By expanding solutions in Gegenbauer polynomials, we first develop a general approach for boundary value problems (BVPs), corresponding to the stationary part of the PDE. This yields a computationally efficient sparse structure for both differential and multiplication operators. By deriving sharp, explicit and quantitative estimates for the inverse of differential operators, we implement a Newton-Kantorovich approach. Specifically, given a numerical approximation $\bar{u}$, we prove the existence of a true stationary solution $\tilde{u}$ within a small, rigorously quantified neighborhood of $\bar{u}$. A key advantage of this approach is that the sharp control over the defect $\tilde{u}-\bar{u}$, integrated with the spectral properties of the Gegenbauer basis, enables an accurate enclosure of the linearization's spectrum around $\tilde{u}$. This allows for a definitive conclusion regarding the (in)stability of the verified solution, which is the main contribution of the paper. We demonstrate the efficacy of this method through several applications, capturing both stable and unstable equilibrium states.