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Box-Covariances of Hyperuniform Point Processes

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arxiv 2506.13661 v2 pith:QTD75EKX submitted 2025-06-16 math.PR

classification math.PR
keywords assumptioncovarianceprocessboxeshyperuniformintegrabilitynumberpoint
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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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Cited by 2 Pith papers

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  1. Limit theory for Lipschitz-localized statistics in random geometric models

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    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.

  2. Hyperuniform random measures, transport and rigidity

    math.PR 2025-10 conditional novelty 2.0 of 10

    A lecture-note survey unifying the spectral, transport, and rigidity sides of hyperuniform random measures, with worked proofs for emblematic models such as the Ginibre ensemble, Sine-β processes, and Gaussian analyti...

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