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The Carleman Contraction Mapping Method for a Coefficient Inverse Problem of the Epidemiology: The Carleman contraction mapping method for a coefficient inverse problem of the epidemiology

Bibliographic Details
Title: The Carleman Contraction Mapping Method for a Coefficient Inverse Problem of the Epidemiology: The Carleman contraction mapping method for a coefficient inverse problem of the epidemiology
Authors: Michael V. Klibanov, Trung Truong
Source: SIAM Journal on Applied Mathematics. 85:848-874
Publication Status: Preprint
Publisher Information: Society for Industrial & Applied Mathematics (SIAM), 2025.
Publication Year: 2025
Subject Terms: monitoring epidemics, Inverse problems for PDEs, convexification, 35R30, Reaction-diffusion equations, Epidemiology, numerical studies, FOS: Mathematics, Initial-boundary value problems for second-order parabolic systems, Mathematics - Numerical Analysis, Numerical Analysis (math.NA), coefficient inverse problem, Carleman estimate
Description: It is proposed to monitor spatial and temporal spreads of epidemics via solution of a Coefficient Inverse Problem for a system of three coupled nonlinear parabolic equations. To solve this problem numerically, a version of the so-called Carleman contraction mapping method is developed for this problem. On each iteration, a linear problem with the incomplete lateral Cauchy data is solved by the weighted Quasi-Reversibility Method, where the weight is the Carleman Weight Function. This is the function, which is involved as the weight in the Carleman estimate for the corresponding parabolic operator. Convergence analysis ensures the global convergence of this procedure. Numerical results demonstrate an accurate performance of this technique for noisy data.
26 pages
Document Type: Article
File Description: application/xml
Language: English
ISSN: 1095-712X
0036-1399
DOI: 10.1137/24m1714356
DOI: 10.48550/arxiv.2412.00297
Access URL: http://arxiv.org/abs/2412.00297
Rights: arXiv Non-Exclusive Distribution
Accession Number: edsair.doi.dedup.....e205ad6d2a0740c943d0da04a0bb0ee7
Database: OpenAIRE
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