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Research Article | Open Access

An efficient spectral-Galerkin method for a new Steklov eigenvalue problem in inverse scattering

Shixian Ren1,2Yu Zhang3Ziqiang Wang2( )
School of Mathematical Sciences, Guizhou Normal University, Guiyang, Guizhou 550025, China
School of Data Science and Information Engineering, Guizhou Minzu University, Guiyang, Guizhou 550025, China
School of Mathematics & Statistics, Guizhou University of Finance and Economics, Guiyang, Guizhou 550025, China
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Abstract

An efficient spectral method is proposed for a new Steklov eigenvalue problem in inverse scattering. Firstly, we establish the weak form and the associated discrete scheme by introducing an appropriate Sobolev space and a corresponding approximation space. Then, according to the Fredholm Alternative, the corresponding operator forms of weak formulation and discrete formulation are derived. After that, the error estimates of approximated eigenvalues and eigenfunctions are proved by using the spectral approximation results of completely continuous operators and the approximation properties of orthogonal projection operators. We also construct an appropriate set of basis functions in the approximation space and derive the matrix form of the discrete scheme based on the tensor product. In addition, we extend the algorithm to the circular domain. Finally, we present plenty of numerical experiments and compare them with some existing numerical methods, which validate that our algorithm is effective and high accuracy.

CLC number: 65N25, 65N35

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AIMS Mathematics
Pages 7528-7551

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Cite this article:
Ren S, Zhang Y, Wang Z. An efficient spectral-Galerkin method for a new Steklov eigenvalue problem in inverse scattering. AIMS Mathematics, 2022, 7(5): 7528-7551. https://doi.org/10.3934/math.2022423

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Received: 13 November 2021
Revised: 22 December 2021
Accepted: 30 December 2021
Published: 15 May 2022
©2022 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)