Reconstruction and well-posedness of an inverse coefficient problem for a diffusion equation
Abstract
In this work, we investigate the inverse coefficient problem of determining an unknown coefficient in a diffusion equation from a single boundary flux measurement. More precisely, assuming that the domain is cylindrical, we develop a unified theoretical and numerical framework for the stable reconstruction of a space-time-dependent coefficient, by reformulating the inverse problem as a nonlinear equation. The inherent nonlinearity of the problem is transferred to an auxiliary nonlinear equation, enabling the application of techniques and concepts from nonlinear analysis. By combining representation formulas with regularity properties of solutions to diffusion equations, we extend to nonlinear inverse problems an approach that has so far been restricted to linear ones. The theoretical reconstruction procedure is complemented by a numerical analysis of the proposed method, including convergence and error estimates, as well as numerical experiments. The proposed reconstruction algorithm is directly inspired by the theoretical framework.
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BibTeX
@misc{cen2026reconstruction,
title = {{Reconstruction and well-posedness of an inverse coefficient problem for a diffusion equation}},
author = {Siyu Cen and Bangti Jin and Yavar Kian and Zhi Zhou},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2611.06112},
eprint = {2611.06112},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2611.06112},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Reconstruction and well-posedness of an inverse coefficient problem for a diffusion equation
AU - Siyu Cen
AU - Bangti Jin
AU - Yavar Kian
AU - Zhi Zhou
PY - 2026
DA - 2026/11/04
PB - arXiv
DO - 10.48550/arxiv.2611.06112
UR - https://arxiv.org/abs/2611.06112
AB - In this work, we investigate the inverse coefficient problem of determining an unknown coefficient in a diffusion equation from a single boundary flux measurement. More precisely, assuming that the domain is cylindrical, we develop a unified theoretical and numerical framework for the stable reconstruction of a space-time-dependent coefficient, by reformulating the inverse problem as a nonlinear equation. The inherent nonlinearity of the problem is transferred to an auxiliary nonlinear equation, enabling the application of techniques and concepts from nonlinear analysis. By combining representation formulas with regularity properties of solutions to diffusion equations, we extend to nonlinear inverse problems an approach that has so far been restricted to linear ones. The theoretical reconstruction procedure is complemented by a numerical analysis of the proposed method, including convergence and error estimates, as well as numerical experiments. The proposed reconstruction algorithm is directly inspired by the theoretical framework.
ER -