English

Structural phase transition in evolving networks

Statistical Mechanics 2009-11-10 v1 Disordered Systems and Neural Networks

Abstract

A network as a substrate for dynamic processes may have its own dynamics. We propose a model for networks which evolve together with diffusing particles through a coupled dynamics, and investigate emerging structural property. The model consists of an undirected weighted network of fixed mean degree and randomly diffusing particles of fixed density. The weight ww of an edge increases by the amount of traffics through its connecting nodes or decreases by a constant factor. Edges are removed with the probability Prew.=1/(1+w)P_{rew.}=1/(1+w) and replaced by new ones having w=0w=0 at random locations. We find that the model exhibits a structural phase transition between the homogeneous phase characterized by an exponentially decaying degree distribution and the heterogeneous phase characterized by the presence of hubs. The hubs emerge as a consequence of a positive feedback between the particle and the edge dynamics.

Keywords

Cite

@article{arxiv.0905.1470,
  title  = {Structural phase transition in evolving networks},
  author = {Sang-Woo Kim and Jae Dong Noh},
  journal= {arXiv preprint arXiv:0905.1470},
  year   = {2009}
}

Comments

4 pages, 5figures

R2 v1 2026-06-21T13:00:13.240Z