Lipschitz stability for Backward Heat Equation with application to Fluorescence Microscopy

TL;DR

This paper establishes Lipschitz stability for reconstructing initial temperature in the backward heat equation, with applications to fluorescence microscopy, correcting previous errors and providing numerical analysis of stability constants.

Contribution

It offers a corrected Lipschitz stability analysis for the backward heat problem with new applications to fluorescence microscopy and numerical stability assessment.

Findings

Lipschitz stability results for backward heat problem with exterior observations.

Application of stability results to inverse problems in fluorescence microscopy.

Numerical analysis linking stability constants to condition numbers.

Abstract

This second version of the manuscript includes, in the appendices, an erratum that points out an error on the published version and offers alternative results for the Lipschitz stability analysis of the backward heat propagation problem and its applications to light sheet fluorescence microscopy. Abstract of the first version: In this work, we study a Lipschitz stability result in the reconstruction of a compactly supported initial temperature for the heat equation in $\mathbb{R}^n$, from measurements along a positive time interval and over an open set containing its support. We take advantage of the explicit dependency of solutions to the heat equation with respect to the initial condition. By means of Carleman estimates we obtain an analogous result for the case when the observation is made along an exterior region $\omega\times(\tau,T)$, such that the unobserved part $\mathbb{R}^n\backslash\omega$ is bounded. In the latter setting, the method of Carleman estimates gives a general conditional logarithmic stability result when initial temperatures belong to a certain admissible set, and without the assumption of compactness of support. Furthermore, we apply these results to deduce a similar result for the heat equation in $\mathbb{R}$ for measurements available on a curve contained in $\mathbb{R}\times [0,\infty)$, from where a stability estimate for an inverse problem arising in 2D Fluorescence Microscopy is deduced as well. In order to further understand this Lipschitz stability, in particular, the magnitude of its stability constant with respect to the noise level of the measurements, a numerical reconstruction is presented based on the construction of a linear system for the inverse problem in Fluorescence Microscopy. We investigate the stability constant with the condition number of the corresponding matrix.