Entropy measures for networks: Toward an information theory of complex topologies
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.
- Publication:
-
Physical Review E
- Pub Date:
- October 2009
- DOI:
- arXiv:
- arXiv:0907.1514
- Bibcode:
- 2009PhRvE..80d5102A
- Keywords:
-
- 89.75.Hc;
- 89.75.Fb;
- 89.75.Da;
- Networks and genealogical trees;
- Structures and organization in complex systems;
- Systems obeying scaling laws;
- Condensed Matter - Disordered Systems and Neural Networks;
- Condensed Matter - Statistical Mechanics;
- Physics - Physics and Society
- E-Print:
- (4 pages, 1 figure)