Skip to main navigation Skip to search Skip to main content

Random tree growth by vertex splitting

Research output: Contribution to journalArticlepeer-review

Abstract

We study a model of growing planar tree graphs where in each time step we separate the tree into two components by splitting a vertex and then connect the two pieces by inserting a new link between the daughter vertices. This model generalizes the preferential attachment model and Ford's α-model for phylogenetic trees. We develop a mean field theory for the vertex degree distribution, prove that the mean field theory is exact in some special cases and check that it agrees with numerical simulations in general. We calculate various correlation functions and show that the intrinsic Hausdorff dimension can vary from 1 to ∞, depending on the parameters of the model.

Original languageEnglish
Article numberP04009
JournalJournal of Statistical Mechanics: Theory and Experiment
Volume2009
Issue number4
DOIs
Publication statusPublished - 2009

Other keywords

  • Exact results
  • Growth processes
  • Networks
  • Random graphs

Fingerprint

Dive into the research topics of 'Random tree growth by vertex splitting'. Together they form a unique fingerprint.

Cite this