Outliers for deformed inhomogeneous random matrices

Fuente: arXiv
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Hauptverfasser: Geng, Ruohan, Liu, Dang-Zheng, Zou, Guangyi
Format: Preprint
Veröffentlicht: 2024
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author Geng, Ruohan
Liu, Dang-Zheng
Zou, Guangyi
author_facet Geng, Ruohan
Liu, Dang-Zheng
Zou, Guangyi
contents Inhomogeneous random matrices with non-trivial variance profiles determined by symmetric stochastic matrices and with independent sub-Gaussian entries up to Hermitian symmetry, encompass a wide range of important models, including sparse Wigner matrices and random band matrices. In these models, the maximum entry variance-a natural proxy for sparsity-serves both as a key structural feature and a primary analytical obstacle. In this paper, we consider low-rank additive perturbations of such matrices and establish a sharp BBP phase transition for extreme eigenvalues at the level of the law of large numbers. Furthermore, in the Gaussian setting, we derive the fluctuations of spectral outliers under suitable conditions on the variance profile and perturbation. These fluctuations exhibit strong non-universality, depending on the eigenvectors, sparsity levels, and the underlying geometric structure. Our proof strategies rely on ribbon graph expansions, upper bounds for diagram functions, large-moment estimates, and the enumeration of typical diagrams.
format Preprint
id arxiv_https___arxiv_org_abs_2407_12182
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Outliers for deformed inhomogeneous random matrices
Geng, Ruohan
Liu, Dang-Zheng
Zou, Guangyi
Probability
Mathematical Physics
60B20
Inhomogeneous random matrices with non-trivial variance profiles determined by symmetric stochastic matrices and with independent sub-Gaussian entries up to Hermitian symmetry, encompass a wide range of important models, including sparse Wigner matrices and random band matrices. In these models, the maximum entry variance-a natural proxy for sparsity-serves both as a key structural feature and a primary analytical obstacle. In this paper, we consider low-rank additive perturbations of such matrices and establish a sharp BBP phase transition for extreme eigenvalues at the level of the law of large numbers. Furthermore, in the Gaussian setting, we derive the fluctuations of spectral outliers under suitable conditions on the variance profile and perturbation. These fluctuations exhibit strong non-universality, depending on the eigenvectors, sparsity levels, and the underlying geometric structure. Our proof strategies rely on ribbon graph expansions, upper bounds for diagram functions, large-moment estimates, and the enumeration of typical diagrams.
title Outliers for deformed inhomogeneous random matrices
topic Probability
Mathematical Physics
60B20
url https://arxiv.org/abs/2407.12182