Asaf Ferber, Matthew Kwan, Bhargav P. Narayanan, A. Sah, Mehtaab Sawhney
{"title":"Friendly bisections of random graphs","authors":"Asaf Ferber, Matthew Kwan, Bhargav P. Narayanan, A. Sah, Mehtaab Sawhney","doi":"10.1090/cams/13","DOIUrl":null,"url":null,"abstract":"Resolving a conjecture of Füredi from 1988, we prove that with high probability, the random graph \n\n \n \n \n G\n \n (\n n\n ,\n 1\n \n /\n \n 2\n )\n \n \\mathbb {G}(n,1/2)\n \n\n admits a friendly bisection of its vertex set, i.e., a partition of its vertex set into two parts whose sizes differ by at most one in which \n\n \n \n n\n −\n o\n (\n n\n )\n \n n-o(n)\n \n\n vertices have more neighbours in their own part as across. Our proof is constructive, and in the process, we develop a new method to study stochastic processes driven by degree information in random graphs; this involves combining enumeration techniques with an abstract second moment argument.","PeriodicalId":285678,"journal":{"name":"Communications of the American Mathematical Society","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications of the American Mathematical Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1090/cams/13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Resolving a conjecture of Füredi from 1988, we prove that with high probability, the random graph
G
(
n
,
1
/
2
)
\mathbb {G}(n,1/2)
admits a friendly bisection of its vertex set, i.e., a partition of its vertex set into two parts whose sizes differ by at most one in which
n
−
o
(
n
)
n-o(n)
vertices have more neighbours in their own part as across. Our proof is constructive, and in the process, we develop a new method to study stochastic processes driven by degree information in random graphs; this involves combining enumeration techniques with an abstract second moment argument.