Inverse source problems with reduced interior data for a coupled reaction-diffusion system

TL;DR

This paper investigates the inverse source problem in a coupled reaction-diffusion system, establishing stability estimates using Carleman techniques and analyzing data reduction possibilities.

Contribution

It provides new stability estimates for inverse source problems in a reaction-diffusion system and explores data reduction while maintaining uniqueness and stability.

Findings

Lipschitz stability from limited data including a snapshot and subdomain observations.

Hölder stability achieved without boundary data in interior subdomains.

Reduced data can still ensure uniqueness and stability under certain conditions.

Abstract

We consider a two-component semilinear reaction-diffusion system in a bounded spatial domain $\Omega$ over a time interval $(0,T)$, which governs the water density $u(x,t)$ and the vegetation biomass density $v(x,t)$ for $x\in\Omega$ and $0<t<T$. In this system, called the Klausmeier-Gray-Scott model, we assume that an unknown source depends only on the spatial variable and appears in the reaction-diffusion equation for $u$. The main subject is the inverse source problem of determining a source term from limited data on $(u,v)$. We establish two kinds of stability estimates by means of Carleman estimates. First, a Carleman estimate with a singular weight yields a Lipschitz stability estimate for the inverse source problem from data consisting of a snapshot $u(\cdot,t_0)$ in $\Omega$ and $(u,v)$ in a subdomain $\omega$ over a time interval. Second, without assuming boundary data, we prove a H\"older stability estimate in any interior subdomain $\Omega_0$ satisfying $\overline{\Omega_0}\subset\Omega$. We further study how much the observation data can be reduced while preserving uniqueness and stability in the inverse problem under suitable additional conditions.