On the Distances Within Cliques in a Soft Random Geometric Graph

Journal of Statistical Physics(2024)

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摘要
We study the distances of vertices within cliques in a soft random geometric graph on a torus, where the vertices are points of a homogeneous Poisson point process, and far-away points are less likely to be connected than nearby points. We obtain the scaling of the maximal distance between any two points within a clique of size k. Moreover, we show that asymptotically in all cliques with large distances, there is only one remote point and all other points are nearby. Furthermore, we prove that a re-scaled version of the maximal k-clique distance converges in distribution to a Fréchet distribution. Thereby, we describe the order of magnitude according to which the largest distance between two points in a clique decreases with the clique size.
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关键词
Random graphs,Cliques,Extreme value theory,Network clustering,Soft random geometric graph,Primary: 05C80,Secondary: 05C69,60G70,05C82,82B21
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