Linearized boundary control method for density reconstruction in acoustic wave equations

We develop a linearized boundary control method for the inverse boundary value problem of determining a density in the acoustic wave equation. The objective is to reconstruct an unknown perturbation in a known background density from the linearized Neumann-to-Dirichlet map. A key ingredient in the derivation is a linearized Blagoves̆c̆enskiĭ's identity with a free parameter. When the linearization is at a constant background density, we derive two reconstructive algorithms with stability estimates based on the boundary control method. When the linearization is at a non-constant background density, we establish an increasing stability estimate for the recovery of the density perturbation. The proposed reconstruction algorithms are implemented and validated with several numerical experiments to demonstrate the feasibility.

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Publication Details

Journal
Inverse Problems
Published
2024-11-29
DOI
https://doi.org/10.1088/1361-6420/ad98bc
Citations
1
Primary Topic
Numerical methods in inverse problems
Type
article
Field-Weighted Citation Impact
0.89

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article

Linearized boundary control method for density reconstruction in acoustic wave equations

Lauri Oksanen, Tianyu Yang, Yang Yang
1 citations
Inverse Problems
Numerical methods in inverse problems
0.89
article

Linearized boundary control method for density reconstruction in acoustic wave equations

Lauri Oksanen, Tianyu Yang, Yang Yang
article en
1 citations

Abstract

We develop a linearized boundary control method for the inverse boundary value problem of determining a density in the acoustic wave equation. The objective is to reconstruct an unknown perturbation in a known background density from the linearized Neumann-to-Dirichlet map. A key ingredient in the derivation is a linearized Blagoves̆c̆enskiĭ's identity with a free parameter. When the linearization is at a constant background density, we derive two reconstructive algorithms with stability estimates based on the boundary control method. When the linearization is at a non-constant background density, we establish an increasing stability estimate for the recovery of the density perturbation. The proposed reconstruction algorithms are implemented and validated with several numerical experiments to demonstrate the feasibility.

Inverse ProblemsVol. 40(12)
Statistics Finland (FI), University of Helsinki (FI), Michigan State University (US)
National Science Foundation, European Commission, Academy of Finland, National Institutes of Health, European Research Council, National Institute of Biomedical Imaging and Bioengineering
Openalex Percentile: Top 26%
Numerical methods in inverse problems
0.89
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