English

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

Disordered Systems and Neural Networks 2015-05-13 v2 Statistical Mechanics Physics and Society

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 paper 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.

Keywords

Cite

@article{arxiv.0907.1514,
  title  = {Entropy measures for complex networks: Toward an information theory of complex topologies},
  author = {Kartik Anand and Ginestra Bianconi},
  journal= {arXiv preprint arXiv:0907.1514},
  year   = {2015}
}

Comments

(4 pages, 1 figure)