Chaos and Superconcentration for Poisson Functionals with Applications in Stochastic Geometry

Fuente: arXiv
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Main Authors: Bhattacharjee, Chinmoy, O'Clarey, Rowan
Format: Preprint
Published: 2026
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author Bhattacharjee, Chinmoy
O'Clarey, Rowan
author_facet Bhattacharjee, Chinmoy
O'Clarey, Rowan
contents We consider square-integrable functionals of Poisson point processes for which the variance upper bound provided by the classical Poincaré inequality is suboptimal, a phenomenon known as superconcentration. In this paper, we establish a rigorous mathematical equivalence between superconcentration and the chaotic behaviour of the functional, and certain associated random sets, under perturbations driven by the Ornstein-Uhlenbeck semigroup on the Poisson space. Leveraging the Malliavin-Stein method, we develop general variance identities and bounds for Poisson functionals, providing a unified framework to prove superconcentration, particularly for geometric functionals that can be expressed as a sum of local score functions. We apply our results to rigorously establish superconcentration and the chaotic behaviour in some models of stochastic geometry. Specifically, we analyse horizontal box-crossing indicators in certain critical continuum percolations, as well as the number of vertices with small degrees and the number of isolated $Γ$-components in random geometric graphs in the dense regime.
format Preprint
id arxiv_https___arxiv_org_abs_2603_23053
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Chaos and Superconcentration for Poisson Functionals with Applications in Stochastic Geometry
Bhattacharjee, Chinmoy
O'Clarey, Rowan
Probability
60D05, 60H07
We consider square-integrable functionals of Poisson point processes for which the variance upper bound provided by the classical Poincaré inequality is suboptimal, a phenomenon known as superconcentration. In this paper, we establish a rigorous mathematical equivalence between superconcentration and the chaotic behaviour of the functional, and certain associated random sets, under perturbations driven by the Ornstein-Uhlenbeck semigroup on the Poisson space. Leveraging the Malliavin-Stein method, we develop general variance identities and bounds for Poisson functionals, providing a unified framework to prove superconcentration, particularly for geometric functionals that can be expressed as a sum of local score functions. We apply our results to rigorously establish superconcentration and the chaotic behaviour in some models of stochastic geometry. Specifically, we analyse horizontal box-crossing indicators in certain critical continuum percolations, as well as the number of vertices with small degrees and the number of isolated $Γ$-components in random geometric graphs in the dense regime.
title Chaos and Superconcentration for Poisson Functionals with Applications in Stochastic Geometry
topic Probability
60D05, 60H07
url https://arxiv.org/abs/2603.23053