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Scale-Free Networks Emerging from Weighted Random Graphs

Tomer Kalisky·Sameet Sreenivasan·Lidia A. Braunstein·Sergey V. Buldyrev·Shlomo Havlin·H. Eugene Stanley
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Abstract

We study Erdös-Rényi 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 $P(k)\sim k^{-λ}$ with $λ=2.5$. 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 $λ=2.5$. 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.

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Tomer Kalisky, Sameet Sreenivasan, Lidia A. Braunstein, Sergey V. Buldyrev, Shlomo Havlin, H. Eugene Stanley. 2005-03-24. Scale-Free Networks Emerging from Weighted Random Graphs. https://doi.org/10.1103/physreve.73.025103

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