On the Distances Within Cliques in a Soft Random Geometric Graph

Ercan Sönmez, Clara Stegehuis*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

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.

Original languageEnglish
Article number38
JournalJournal of statistical physics
Volume191
Issue number3
DOIs
Publication statusPublished - Mar 2024

Keywords

  • UT-Hybrid-D
  • 60G70
  • 82B21
  • Cliques
  • Extreme value theory
  • Network clustering
  • Primary: 05C80
  • Random graphs
  • Secondary: 05C69
  • Soft random geometric graph
  • 05C82

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