Entropy measures for networks: toward an information theory of complex topologies

Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Oct;80(4 Pt 2):045102. doi: 10.1103/PhysRevE.80.045102. Epub 2009 Oct 13.

Abstract

The quantification of the complexity of networks is, today, a fundamental problem in the physics of complex systems. A possible roadmap to solve the problem is via extending key concepts of information theory to networks. In this Rapid Communication we propose how to define the Shannon entropy of a network ensemble and how it relates to the Gibbs and von Neumann entropies of network ensembles. The quantities we introduce here will play a crucial role for the formulation of null models of networks through maximum-entropy arguments and will contribute to inference problems emerging in the field of complex networks.

MeSH terms

  • Computer Simulation
  • Entropy
  • Models, Biological*
  • Nerve Net / physiology*
  • Signal Transduction / physiology*
  • Social Support*