Eigenvalues for a class of non-Hermitian tetradiagonal Toeplitz matrices

We study a family of non-Hermitian tetradiagonal Toeplitz matrices having a limiting set consisting of one analytic arc only. We derive individual asymptotic expansions for all eigenvalues as the matrix size grows to infinity. Additionally, we provide specific expansions for the extreme eigenvalues, which are those approaching the endpoints of the limiting set. Although this family does not belong to the simple-loop class, we managed to extend the existing theory to this case. Our results reveal the intricate details of the eigenvalue structure and allow a high accuracy direct calculation.

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Publication Details

Journal
Journal of Spectral Theory
Published
2024-12-11
DOI
https://doi.org/10.4171/jst/538
Citations
3
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
1.08
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article

Eigenvalues for a class of non-Hermitian tetradiagonal Toeplitz matrices

Sergei M. Grudsky, Juanita Gasca, Manuel Bogoya
3 citations
Journal of Spectral Theory
Matrix Theory and Algorithms
1.08
article

Eigenvalues for a class of non-Hermitian tetradiagonal Toeplitz matrices

Sergei M. Grudsky, Juanita Gasca, Manuel Bogoya
article en
3 citations

Abstract

We study a family of non-Hermitian tetradiagonal Toeplitz matrices having a limiting set consisting of one analytic arc only. We derive individual asymptotic expansions for all eigenvalues as the matrix size grows to infinity. Additionally, we provide specific expansions for the extreme eigenvalues, which are those approaching the endpoints of the limiting set. Although this family does not belong to the simple-loop class, we managed to extend the existing theory to this case. Our results reveal the intricate details of the eigenvalue structure and allow a high accuracy direct calculation.

Journal of Spectral TheoryVol. 15(1)
Southern Federal University (RU), Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (MX), Universidad del Valle (CO)
Openalex Percentile: Top 19%
Matrix Theory and Algorithms
1.08
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