Large deviations for macroscopic observables of heavy-tailed matrices

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Bordenave, Charles, Guionnet, Alice, Male, Camille
Natura: Preprint
Pubblicazione: 2024
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866914954490150912
author Bordenave, Charles
Guionnet, Alice
Male, Camille
author_facet Bordenave, Charles
Guionnet, Alice
Male, Camille
contents We consider a finite collection of independent Hermitian heavy-tailed random matrices of growing dimension. Our model includes the Lévy matrices proposed by Bouchaud and Cizeau, as well as sparse random matrices with O(1) non-zero entries per row. By representing these matrices as weighted graphs, we derive a large deviations principle for key macroscopic observables. Specifically, we focus on the empirical distribution of eigenvalues, the joint neighborhood distribution, and the joint traffic distribution. As an application, we define a notion of microstates entropy for traffic distributions which is additive for free traffic convolution.
format Preprint
id arxiv_https___arxiv_org_abs_2409_14027
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Large deviations for macroscopic observables of heavy-tailed matrices
Bordenave, Charles
Guionnet, Alice
Male, Camille
Probability
We consider a finite collection of independent Hermitian heavy-tailed random matrices of growing dimension. Our model includes the Lévy matrices proposed by Bouchaud and Cizeau, as well as sparse random matrices with O(1) non-zero entries per row. By representing these matrices as weighted graphs, we derive a large deviations principle for key macroscopic observables. Specifically, we focus on the empirical distribution of eigenvalues, the joint neighborhood distribution, and the joint traffic distribution. As an application, we define a notion of microstates entropy for traffic distributions which is additive for free traffic convolution.
title Large deviations for macroscopic observables of heavy-tailed matrices
topic Probability
url https://arxiv.org/abs/2409.14027