Random Euclidean coverage from within

preprint2022arXivOpen access

Abstract

Let X1,X2,…X_1,X_2, \ldots be independent random uniform points in a bounded domain A⊂RdA \subset \mathbb{R}^d with smooth boundary. Define the coverage threshold RnR_n to be the smallest rr such that AA is covered by the balls of radius rr centred on X1,…,XnX_1,\ldots,X_n. We obtain the limiting distribution of RnR_n and also a strong law of large numbers for RnR_n in the large-nn limit. For example, if AA has volume 1 and perimeter ∣∂A∣|\partial A|, if d=3d=3 then Pr⁡[nπRn3−log⁡n−2log⁡(log⁡n)≤x]\Pr[nπR_n^3 - \log n - 2 \log (\log n) \leq x] converges to exp⁡(−2−4π5/3∣∂A∣e−2x/3)\exp(-2^{-4}π^{5/3} |\partial A| e^{-2 x/3}) and (nπRn3)/(log⁡n)→1(n πR_n^3)/(\log n) \to 1 almost surely, and if d=2d=2 then Pr⁡[nπRn2−log⁡n−log⁡(log⁡n)≤x]\Pr[n πR_n^2 - \log n - \log (\log n) \leq x] converges to exp⁡(−e−x−∣∂A∣π−1/2e−x/2)\exp(- e^{-x}- |\partial A|π^{-1/2} e^{-x/2}). We give similar results for general dd, and also for the case where AA is a polytope. We also generalize to allow for multiple coverage. The analysis relies on classical results by Hall and by Janson, along with a careful treatment of boundary effects. For the strong laws of large numbers, we can relax the requirement that the underlying density on AA be uniform.

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