Develops a CLT framework for locally dependent scores on marked Euclidean point processes via geometric mixing and bounded-Lipschitz localization, with applications to spin systems and interacting particles.
Box-Covariances of Hyperuniform Point Processes
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abstract
In this work, we present a complete characterization of the covariance structure of number statistics in boxes for hyperuniform point processes. Under a standard integrability assumption, the covariance depends solely on the overlap of the faces of the box. Beyond this assumption, a novel interpolating covariance structure emerges. This enables us to identify a limiting Gaussian ``coarse-grained'' process, counting the number of points in large boxes as a function of the box position. Depending on the integrability assumption, this process may be continuous or discontinuous, e.g.~in $d=1$ it is given by an increment process of a fractional Brownian motion.
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math.PR 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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Limit theory for Lipschitz-localized statistics in random geometric models
Develops a CLT framework for locally dependent scores on marked Euclidean point processes via geometric mixing and bounded-Lipschitz localization, with applications to spin systems and interacting particles.