English

Hybrid Percolation Transition in Cluster Merging Processes: Continuously Varying Exponents

Statistical Mechanics 2016-01-20 v2

Abstract

Consider growing a network, in which every new connection is made between two disconnected nodes. At least one node is chosen randomly from a subset consisting of gg fraction of the entire population in the smallest clusters. Here we show that this simple strategy for improving connection exhibits a phase transition barely studied before, namely a hybrid percolation transition exhibiting the properties of both first-order and second-order phase transitions. The cluster size distribution of finite clusters at a transition point exhibits power-law behavior with a continuously varying exponent τ\tau in the range 2<τ(g)2.52 < \tau(g) \le 2.5. This pattern reveals a necessary condition for a hybrid transition in cluster aggregation processes, which is comparable to the power-law behavior of the avalanche size distribution arising in models with link-deleting processes in interdependent networks.

Keywords

Cite

@article{arxiv.1512.04624,
  title  = {Hybrid Percolation Transition in Cluster Merging Processes: Continuously Varying Exponents},
  author = {Y. S. Cho and J. S. Lee and H. J. Herrmann and B. Kahng},
  journal= {arXiv preprint arXiv:1512.04624},
  year   = {2016}
}

Comments

5 pages, 3 figures

R2 v1 2026-06-22T12:09:51.407Z