{"title":"Abelian groups from random hypergraphs","authors":"Andrew Newman","doi":"10.1017/s0963548323000056","DOIUrl":null,"url":null,"abstract":"Abstract For a $k$ -uniform hypergraph $\\mathcal{H}$ on vertex set $\\{1, \\ldots, n\\}$ we associate a particular signed incidence matrix $M(\\mathcal{H})$ over the integers. For $\\mathcal{H} \\sim \\mathcal{H}_k(n, p)$ an Erdős–Rényi random $k$ -uniform hypergraph, ${\\mathrm{coker}}(M(\\mathcal{H}))$ is then a model for random abelian groups. Motivated by conjectures from the study of random simplicial complexes we show that for $p = \\omega (1/n^{k - 1})$ , ${\\mathrm{coker}}(M(\\mathcal{H}))$ is torsion-free.","PeriodicalId":10513,"journal":{"name":"Combinatorics, Probability & Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.9000,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Combinatorics, Probability & Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/s0963548323000056","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract For a $k$ -uniform hypergraph $\mathcal{H}$ on vertex set $\{1, \ldots, n\}$ we associate a particular signed incidence matrix $M(\mathcal{H})$ over the integers. For $\mathcal{H} \sim \mathcal{H}_k(n, p)$ an Erdős–Rényi random $k$ -uniform hypergraph, ${\mathrm{coker}}(M(\mathcal{H}))$ is then a model for random abelian groups. Motivated by conjectures from the study of random simplicial complexes we show that for $p = \omega (1/n^{k - 1})$ , ${\mathrm{coker}}(M(\mathcal{H}))$ is torsion-free.
期刊介绍:
Published bimonthly, Combinatorics, Probability & Computing is devoted to the three areas of combinatorics, probability theory and theoretical computer science. Topics covered include classical and algebraic graph theory, extremal set theory, matroid theory, probabilistic methods and random combinatorial structures; combinatorial probability and limit theorems for random combinatorial structures; the theory of algorithms (including complexity theory), randomised algorithms, probabilistic analysis of algorithms, computational learning theory and optimisation.