{"title":"Geometric random intersection graphs with general connection probabilities","authors":"Maria Deijfen, Riccardo Michielan","doi":"10.1017/jpr.2024.18","DOIUrl":null,"url":null,"abstract":"Let <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline1.png\"/> <jats:tex-math> $\\mathcal{V}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> and <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline2.png\"/> <jats:tex-math> $\\mathcal{U}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> be the point sets of two independent homogeneous Poisson processes on <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline3.png\"/> <jats:tex-math> $\\mathbb{R}^d$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>. A graph <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline4.png\"/> <jats:tex-math> $\\mathcal{G}_\\mathcal{V}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> with vertex set <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline5.png\"/> <jats:tex-math> $\\mathcal{V}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> is constructed by first connecting pairs of points (<jats:italic>v</jats:italic>, <jats:italic>u</jats:italic>) with <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline6.png\"/> <jats:tex-math> $v\\in\\mathcal{V}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> and <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline7.png\"/> <jats:tex-math> $u\\in\\mathcal{U}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> independently with probability <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline8.png\"/> <jats:tex-math> $g(v-u)$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>, where <jats:italic>g</jats:italic> is a non-increasing radial function, and then connecting two points <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline9.png\"/> <jats:tex-math> $v_1,v_2\\in\\mathcal{V}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> if and only if they have a joint neighbor <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline10.png\"/> <jats:tex-math> $u\\in\\mathcal{U}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>. This gives rise to a random intersection graph on <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline11.png\"/> <jats:tex-math> $\\mathbb{R}^d$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>. Local properties of the graph, including the degree distribution, are investigated and quantified in terms of the intensities of the underlying Poisson processes and the function <jats:italic>g</jats:italic>. Furthermore, the percolation properties of the graph are characterized and shown to differ depending on whether <jats:italic>g</jats:italic> has bounded or unbounded support.","PeriodicalId":50256,"journal":{"name":"Journal of Applied Probability","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Probability","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1017/jpr.2024.18","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
Let $\mathcal{V}$ and $\mathcal{U}$ be the point sets of two independent homogeneous Poisson processes on $\mathbb{R}^d$ . A graph $\mathcal{G}_\mathcal{V}$ with vertex set $\mathcal{V}$ is constructed by first connecting pairs of points (v, u) with $v\in\mathcal{V}$ and $u\in\mathcal{U}$ independently with probability $g(v-u)$ , where g is a non-increasing radial function, and then connecting two points $v_1,v_2\in\mathcal{V}$ if and only if they have a joint neighbor $u\in\mathcal{U}$ . This gives rise to a random intersection graph on $\mathbb{R}^d$ . Local properties of the graph, including the degree distribution, are investigated and quantified in terms of the intensities of the underlying Poisson processes and the function g. Furthermore, the percolation properties of the graph are characterized and shown to differ depending on whether g has bounded or unbounded support.
期刊介绍:
Journal of Applied Probability is the oldest journal devoted to the publication of research in the field of applied probability. It is an international journal published by the Applied Probability Trust, and it serves as a companion publication to the Advances in Applied Probability. Its wide audience includes leading researchers across the entire spectrum of applied probability, including biosciences applications, operations research, telecommunications, computer science, engineering, epidemiology, financial mathematics, the physical and social sciences, and any field where stochastic modeling is used.
A submission to Applied Probability represents a submission that may, at the Editor-in-Chief’s discretion, appear in either the Journal of Applied Probability or the Advances in Applied Probability. Typically, shorter papers appear in the Journal, with longer contributions appearing in the Advances.