{ "id": "0808.4067", "version": "v3", "published": "2008-08-29T10:26:48.000Z", "updated": "2010-09-06T17:09:22.000Z", "title": "The diameter of sparse random graphs", "authors": [ "Oliver Riordan", "Nicholas Wormald" ], "comment": "92 pages; expanded slightly with minor corrections; to appear in Combinatorics, Probability and Computing", "journal": "Combinatorics, Probability and Computing 19 (2010), 835--926", "doi": "10.1017/S0963548310000325", "categories": [ "math.PR", "math.CO" ], "abstract": "In this paper we study the diameter of the random graph $G(n,p)$, i.e., the the largest finite distance between two vertices, for a wide range of functions $p=p(n)$. For $p=\\la/n$ with $\\la>1$ constant, we give a simple proof of an essentially best possible result, with an $O_p(1)$ additive correction term. Using similar techniques, we establish 2-point concentration in the case that $np\\to\\infty$. For $p=(1+\\epsilon)/n$ with $\\epsilon\\to 0$, we obtain a corresponding result that applies all the way down to the scaling window of the phase transition, with an $O_p(1/\\epsilon)$ additive correction term whose (appropriately scaled) limiting distribution we describe. Combined with earlier results, our new results complete the determination of the diameter of the random graph $G(n,p)$ to an accuracy of the order of its standard deviation (or better), for all functions $p=p(n)$. Throughout we use branching process methods, rather than the more common approach of separate analysis of the 2-core and the trees attached to it.", "revisions": [ { "version": "v3", "updated": "2010-09-06T17:09:22.000Z" } ], "analyses": { "subjects": [ "05C80", "60C05" ], "keywords": [ "sparse random graphs", "additive correction term", "largest finite distance", "separate analysis", "wide range" ], "tags": [ "journal article" ], "note": { "typesetting": "TeX", "pages": 92, "language": "en", "license": "arXiv", "status": "editable", "adsabs": "2008arXiv0808.4067R" } } }