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Auteurs principaux: Ghandehari, Mahya, Medvedev, Georgi S.
Format: Preprint
Publié: 2024
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Accès en ligne:https://arxiv.org/abs/2405.04417
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author Ghandehari, Mahya
Medvedev, Georgi S.
author_facet Ghandehari, Mahya
Medvedev, Georgi S.
contents The $W$-random graphs provide a flexible framework for modeling large random networks. Using the Large Deviation Principle (LDP) for $W$-random graphs from [9], we prove the LDP for the corresponding class of random symmetric Hilbert-Schmidt integral operators. Our main result describes how the eigenvalues and the eigenspaces of the integral operator are affected by the large deviations in the underlying random graphon. To prove the LDP, we demonstrate continuous dependence of the spectral measures associated with integral operators on the underlying graphons and use the Contraction Principle. To illustrate our results, we obtain leading order asymptotics of the eigenvalues of the integral operators corresponding to certain random graph sequences. These examples suggest several representative scenarios of how the eigenvalues and the eigenspaces of the integral operators are affected by large deviations. Potential implications of these observations for bifurcation analysis of Dynamical Systems and Graph Signal Processing are indicated.
format Preprint
id arxiv_https___arxiv_org_abs_2405_04417
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle The Large Deviation Principle for $W$-random spectral measures
Ghandehari, Mahya
Medvedev, Georgi S.
Probability
Mathematical Physics
Combinatorics
The $W$-random graphs provide a flexible framework for modeling large random networks. Using the Large Deviation Principle (LDP) for $W$-random graphs from [9], we prove the LDP for the corresponding class of random symmetric Hilbert-Schmidt integral operators. Our main result describes how the eigenvalues and the eigenspaces of the integral operator are affected by the large deviations in the underlying random graphon. To prove the LDP, we demonstrate continuous dependence of the spectral measures associated with integral operators on the underlying graphons and use the Contraction Principle. To illustrate our results, we obtain leading order asymptotics of the eigenvalues of the integral operators corresponding to certain random graph sequences. These examples suggest several representative scenarios of how the eigenvalues and the eigenspaces of the integral operators are affected by large deviations. Potential implications of these observations for bifurcation analysis of Dynamical Systems and Graph Signal Processing are indicated.
title The Large Deviation Principle for $W$-random spectral measures
topic Probability
Mathematical Physics
Combinatorics
url https://arxiv.org/abs/2405.04417