Vertex Intrinsic Fitness: How to Produce Arbitrary Scale-Free Networks

Abstract

We study a recent model of random networks based on the presence of an intrinsic character of the vertices called fitness. The vertices fitnesses are drawn from a given probability distribution density. The edges between pair of vertices are drawn according to a linking probability function depending on the fitnesses of the two vertices involved. We study here different choices for the probability distribution densities and the linking functions. We find that, irrespective of the particular choices, the generation of scale-free networks is straightforward. We then derive the general conditions under which scale-free behavior appears. This model could then represent a possible explanation for the ubiquity and robustness of such structures.

4 pages, 3 figures, RevTex

References in corpus (2)

• Mixing patterns in networks
• Class of correlated random networks with hidden variables

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