Lower bound on the smallest eigenvalue of matrices

Abstract M-matrix is widely used in physics. We establish two new inequalities of l(S*G) for S, G ∈ μ n by utilizing the Gerschgorin theorem and Brauer theorem. New results are more useful in practical applications since they depend on the matrix’s own elements. Example shows that the new estimating equations are more accurate than some already known conclusions in some circumstances.

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Publication Details

Journal
Journal of Physics Conference Series
Published
2025-02-01
DOI
https://doi.org/10.1088/1742-6596/2964/1/012053
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
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article

Lower bound on the smallest eigenvalue of matrices

Fubin Chen
Journal of Physics Conference Series
Matrix Theory and Algorithms
article

Lower bound on the smallest eigenvalue of matrices

Fubin Chen
article en

Abstract

Abstract M-matrix is widely used in physics. We establish two new inequalities of l(S*G) for S, G ∈ μ n by utilizing the Gerschgorin theorem and Brauer theorem. New results are more useful in practical applications since they depend on the matrix’s own elements. Example shows that the new estimating equations are more accurate than some already known conclusions in some circumstances.

Journal of Physics Conference SeriesVol. 2964(1)
Kunming University of Science and Technology (CN), Kunming University (CN)
Openalex Percentile: Top 95%
Matrix Theory and Algorithms
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Lower bound on the smallest eigenvalue of matrices — Fubin Chen · Journal of Physics Conference Series (2025) | TGRS Research Map | TGRS