Extreme eigenvalues of Laplacian random matrices with Gaussian entries

A Laplacian matrix is a real symmetric matrix whose row and column sums are zero. We investigate the limiting distribution of the largest eigenvalues of a Laplacian random matrix with Gaussian entries. Unlike many classical matrix ensembles, this random matrix model contains dependent entries. Our main results show that the extreme eigenvalues of this model exhibit Poisson statistics. In particular, after properly shifting and scaling, we show that the largest eigenvalue converges to the Gumbel distribution as the dimension of the matrix tends to infinity. While the largest diagonal entry is also shown to have Gumbel fluctuations, there is a rather surprising difference between its deterministic centering term and the centering term required for the largest eigenvalues.

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Publication Details

Journal
Electronic Journal of Probability
Published
2025-01-01
DOI
https://doi.org/10.1214/25-ejp1366
Primary Topic
Random Matrices and Applications
Type
article
Field-Weighted Citation Impact
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article

Extreme eigenvalues of Laplacian random matrices with Gaussian entries

Kyle Luh, Andrew D. Campbell, Santiago Arenas-Velilla, Víctor Pérez‐Abreu et al.
Electronic Journal of Probability
Random Matrices and Applications
article

Extreme eigenvalues of Laplacian random matrices with Gaussian entries

Kyle Luh, Andrew D. Campbell, Santiago Arenas-Velilla, Víctor Pérez‐Abreu, Sean O’Rourke
article en

Abstract

A Laplacian matrix is a real symmetric matrix whose row and column sums are zero. We investigate the limiting distribution of the largest eigenvalues of a Laplacian random matrix with Gaussian entries. Unlike many classical matrix ensembles, this random matrix model contains dependent entries. Our main results show that the extreme eigenvalues of this model exhibit Poisson statistics. In particular, after properly shifting and scaling, we show that the largest eigenvalue converges to the Gumbel distribution as the dimension of the matrix tends to infinity. While the largest diagonal entry is also shown to have Gumbel fluctuations, there is a rather surprising difference between its deterministic centering term and the centering term required for the largest eigenvalues.

Electronic Journal of ProbabilityVol. 30(none)
Institute of Science and Technology Austria (AT), University of Colorado Boulder (US)
Openalex Percentile: Top 85%
Random Matrices and Applications
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