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Scale-free networks emerging from weighted random graphs
- 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.
- Subjects :
- Random graph
Discrete mathematics
Percolation
Random regular graph
Scale-free network
FOS: Physical sciences
Percolation threshold
Disordered Systems and Neural Networks (cond-mat.dis-nn)
Continuum percolation theory
Condensed Matter - Disordered Systems and Neural Networks
Degree distribution
Supernode
Mathematics
Subjects
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