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Robustness in the Poisson Boolean model with convex grains

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arxiv 2410.13366 v1 pith:Q7FW3URM submitted 2024-10-17 math.PR

classification math.PR
keywords grainsdistributiongrainpoissonrobustnessbooleanconvexcriteria
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abstract

We study the Poisson Boolean model where the grains are random convex bodies with a rotation-invariant distribution. We say that a grain distribution is dense if the union of the grains covers the entire space and robust if the union of the grains has an unbounded connected component irrespective of the intensity of the underlying Poisson process. If the grains are balls of random radius, then density and robustness are equivalent, but in general this is not the case. We show that in any dimension $d\ge2$ there are grain distributions that are robust but not dense, and give general criteria for density, robustness and non-robustness of a grain distribution. We give examples which show that our criteria are sharp in many instances.

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  1. Nonamenable Poisson zoo

    math.PR 2025-05 reject novelty 8.0 of 10

    For worms on any nonamenable unimodular transitive graph and for arbitrary animals on nonamenable free products, infinite second moment forces infinite clusters at every positive intensity.

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