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Research Article | Open Access

Fast matrix exponential-based quasi-boundary value methods for inverse space-dependent source problems

Fermín S. V. Bazán1Luciano Bedin1Koung Hee Leem2Jun Liu2( )George Pelekanos1
Department of Mathematics, Federal University of Santa Catarina, Florianopolis SC, Santa Catarina, Brazil
Department of Mathematics and Statistics, Southern Illinois University Edwardsville, Edwardsville, IL 62026, USA
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Abstract

In this paper, we study the well-established quasi-boundary value methods for regularizing inverse state-dependent source problems, where the convergence analysis of three typical cases is presented in the framework of filtering regularization method under suitable source conditions. Interestingly, the quasi-boundary value methods can be interpreted as certain Lavrentiev-type regularization, which was not known in literature. As another major contribution, efficient numerical implementation based on matrix exponential in time is developed, which shows much improved computational efficiency than MATLAB's backslash solver based on the all-at-once space-time discretization scheme. Numerical examples are reported to illustrate the promising computational performance of our proposed algorithms based on matrix exponential techniques.

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Networks and Heterogeneous Media
Pages 601-621

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Cite this article:
Bazán FSV, Bedin L, Leem KH, et al. Fast matrix exponential-based quasi-boundary value methods for inverse space-dependent source problems. Networks and Heterogeneous Media, 2023, 18(2): 601-621. https://doi.org/10.3934/nhm.2023026

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Received: 26 October 2022
Revised: 26 December 2022
Accepted: 22 January 2023
Published: 15 June 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)