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Scale-free networks emerging from weighted random graphs

Authors :
Lidia A. Braunstein
H. Eugene Stanley
Tomer Kalisky
Sameet Sreenivasan
Shlomo Havlin
Sergey V. Buldyrev
Source :
Physical review. E, Statistical, nonlinear, and soft matter physics. 73(2 Pt 2)
Publication Year :
2005

Abstract

We study Erd\"{o}s-R\'enyi random graphs with random weights associated with each link. We generate a new ``Supernode network'' by merging all nodes connected by links having weights below the percolation threshold (percolation clusters) into a single node. We show that this network is scale-free, i.e., the degree distribution is $P(k)\sim k^{-\lambda}$ with $\lambda=2.5$. Our results imply that the minimum spanning tree (MST) in random graphs is composed of percolation clusters, which are interconnected by a set of links that create a scale-free tree with $\lambda=2.5$. We show that optimization causes the percolation threshold to emerge spontaneously, thus creating naturally a scale-free ``supernode network''. We discuss the possibility that this phenomenon is related to the evolution of several real world scale-free networks.

Details

ISSN :
15393755
Volume :
73
Issue :
2 Pt 2
Database :
OpenAIRE
Journal :
Physical review. E, Statistical, nonlinear, and soft matter physics
Accession number :
edsair.doi.dedup.....f6651c25f903c92d23c16d9a22654347