First passage percolation on the Erdos-R\'enyi random graph
Abstract
In this paper we explore first passage percolation (FPP) on the Erdos-R\'enyi random graph Gn(pn), where each edge is given an independent exponential edge weight with rate 1. In the sparse regime, i.e., when npn λ>1, we find refined asymptotics both for the minimal weight of the path between uniformly chosen vertices in the giant component, as well as for the hopcount (i.e., the number of edges) on this minimal weight path. More precisely, we prove a central limit theorem for the hopcount, with asymptotic mean and variance both equal to λ/(λ-1)n. Furthermore, we prove that the minimal weight centered by n/(λ-1) converges in distribution. We also investigate the dense regime, where npn ∞. We find that although the base graph is a ultra small (meaning that graph distances between uniformly chosen vertices are o(n)), attaching random edge weights changes the geometry of the network completely. Indeed, the hopcount Hn satisfies the universality property that whatever be the value of pn, \ Hn/n 1 in probability and, more precisely, (Hn-βnn)/n, where βn=λn/(λn-1), has a limiting standard normal distribution. The constant βn can be replaced by 1 precisely when λn n, a case that has appeared in the literature (under stronger conditions on λn). We also find bounds for the maximal weight and maximal hopcount between vertices in the graph. This paper continues the investigation of FPP initiated by the authors. Compared to the setting on the configuration model studied in BHHS08, the proofs presented here are much simpler due to a direct relation between FPP on the Erdos-R\'enyi random graph and thinned continuous-time branching processes.
Turn this paper into a lesson
ArcXiv compiles a structured reading guide from this paper's metadata: plain-English importance, contributions, prerequisite concepts, which sections to read first, flashcards, and a quiz. Grounded in the abstract, never invented.