Critical behavior in inhomogeneous random graphs
Remco van der Hofstad

TL;DR
This paper investigates the critical phenomena of inhomogeneous random graphs with power-law degree distributions, revealing how the asymptotic degree and weight distributions influence the size of the largest critical component.
Contribution
It provides a detailed analysis of the critical behavior in inhomogeneous random graphs, especially in the power-law case, showing how degree distribution tail properties affect component sizes.
Findings
For au>4, the largest critical component scales as n^{2/3}.
For au in (3,4), the largest critical component scales as n^{( au-2)/( au-1)}.
The critical behavior is sensitive to the tail properties of the weight distribution W.
Abstract
We study the critical behavior of inhomogeneous random graphs where edges are present independently but with unequal edge occupation probabilities. The edge probabilities are moderated by vertex weights, and are such that the degree of vertex i is close in distribution to a Poisson random variable with parameter w_i, where w_i denotes the weight of vertex i. We choose the weights such that the weight of a uniformly chosen vertex converges in distribution to a limiting random variable W, in which case the proportion of vertices with degree k is close to the probability that a Poisson random variable with random parameter W takes the value k. We pay special attention to the power-law case, in which P(W\geq k) is proportional to k^{-(\tau-1)} for some power-law exponent \tau>3, a property which is then inherited by the asymptotic degree distribution. We show that the critical behavior…
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