Open Access
2017 Distances in scale free networks at criticality
Steffen Dereich, Christian Mönch, Peter Mörters
Electron. J. Probab. 22: 1-38 (2017). DOI: 10.1214/17-EJP92

Abstract

Scale-free networks with moderate edge dependence experience a phase transition between ultrasmall and small world behaviour when the power law exponent passes the critical value of three. Moreover, there are laws of large numbers for the graph distance of two randomly chosen vertices in the giant component. When the degree distribution follows a pure power law these show the same asymptotic distances of $\frac{\log N} {\log \log N}$ at the critical value three, but in the ultrasmall regime reveal a difference of a factor two between the most-studied rank-one and preferential attachment model classes. In this paper we identify the critical window where this factor emerges. We look at models from both classes when the asymptotic proportion of vertices with degree at least $k$ scales like $k^{-2} (\log k)^{2\alpha + o(1)}$ and show that for preferential attachment networks the typical distance is $\big (\frac{1} {1+\alpha }+o(1)\big )\frac{\log N} {\log \log N}$ in probability as the number $N$ of vertices goes to infinity. By contrast the typical distance in a rank one model with the same asymptotic degree sequence is $\big (\frac{1} {1+2\alpha }+o(1)\big )\frac{\log N} {\log \log N}.$ As $\alpha \to \infty $ we see the emergence of a factor two between the length of shortest paths as we approach the ultrasmall regime.

Citation

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Steffen Dereich. Christian Mönch. Peter Mörters. "Distances in scale free networks at criticality." Electron. J. Probab. 22 1 - 38, 2017. https://doi.org/10.1214/17-EJP92

Information

Received: 30 August 2016; Accepted: 10 August 2017; Published: 2017
First available in Project Euclid: 2 October 2017

zbMATH: 1372.05208
MathSciNet: MR3710797
Digital Object Identifier: 10.1214/17-EJP92

Subjects:
Primary: 05C82
Secondary: 05C80 , 60C05 , 90B15

Keywords: Barabási-Albert model , Critical phenomena , diameter , dynamical random graph , Giant component , graph distance , inhomogeneous random graph , power law , preferential attachment , Scale-free network , small world

Vol.22 • 2017
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