arXiv:0907.1514 [cond-mat.dis-nn]AbstractReferencesReviewsResources
Entropy measures for complex networks: Toward an information theory of complex topologies
Kartik Anand, Ginestra Bianconi
Published 2009-07-09, updated 2009-10-16Version 2
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.
Comments: (4 pages, 1 figure)
Journal: Phys. Rev. E 80, 045102(R) (2009)
Keywords: complex networks, information theory, entropy measures, complex topologies, von neumann entropies
Tags: journal article
Related articles: Most relevant | Search more
arXiv:1402.4426 [cond-mat.dis-nn] (Published 2014-02-18)
Fluctuations analysis in complex networks modeled by hidden variable models. Necessity of a large cut-off in hidden-variable models
arXiv:1012.0203 [cond-mat.dis-nn] (Published 2010-12-01)
Enhancing synchronization by directionality in complex networks
arXiv:cond-mat/0409095 (Published 2004-09-04)
Geographical Coarsegraining of Complex Networks