Multivariate CLT for critical points

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Azaïs, Jean-Marc, Dalmao, Federico, Delmas, Céline
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866907851585224704
author Azaïs, Jean-Marc
Dalmao, Federico
Delmas, Céline
author_facet Azaïs, Jean-Marc
Dalmao, Federico
Delmas, Céline
contents We prove a multivariate central limit theorem for the numbers of critical points above a level with all possible indexes of a non-necessarily isotropic Gaussian random field. In particular, we discuss the non-degeneracy of the limit variance-covariance matrix. We extend, to the non-isotropic framework, known results by Estrade \& Le{ó}n and Nicolaescu for the Euler characteristic of an excursion set and for the total number of critical points of Gaussian random fields. Furthermore, we deduce the almost sure convergence of the normalized (by its mean) number of critical points above a level with any given index and, in particular, of the Euler characteristic of an excursion set. Though we use the classical tools of Hermite expansions and Fourth Moment Theorem, our proof of the non-degeneracy of the limit variance-covariance matrix is completely new since we need to consider all chaotic terms.
format Preprint
id arxiv_https___arxiv_org_abs_2401_09117
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Multivariate CLT for critical points
Azaïs, Jean-Marc
Dalmao, Federico
Delmas, Céline
Probability
We prove a multivariate central limit theorem for the numbers of critical points above a level with all possible indexes of a non-necessarily isotropic Gaussian random field. In particular, we discuss the non-degeneracy of the limit variance-covariance matrix. We extend, to the non-isotropic framework, known results by Estrade \& Le{ó}n and Nicolaescu for the Euler characteristic of an excursion set and for the total number of critical points of Gaussian random fields. Furthermore, we deduce the almost sure convergence of the normalized (by its mean) number of critical points above a level with any given index and, in particular, of the Euler characteristic of an excursion set. Though we use the classical tools of Hermite expansions and Fourth Moment Theorem, our proof of the non-degeneracy of the limit variance-covariance matrix is completely new since we need to consider all chaotic terms.
title Multivariate CLT for critical points
topic Probability
url https://arxiv.org/abs/2401.09117