| Entropy measures for networks: toward an information theory of complex topologies. | |
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MedLine Citation:
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PMID: 19905379 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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. |
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Authors:
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Kartik Anand; Ginestra Bianconi |
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Publication Detail:
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Type: Journal Article Date: 2009-10-13 |
Journal Detail:
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Title: Physical review. E, Statistical, nonlinear, and soft matter physics Volume: 80 ISSN: 1550-2376 ISO Abbreviation: Phys Rev E Stat Nonlin Soft Matter Phys Publication Date: 2009 Oct |
Date Detail:
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Created Date: 2009-11-12 Completed Date: 2010-01-20 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101136452 Medline TA: Phys Rev E Stat Nonlin Soft Matter Phys Country: United States |
Other Details:
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Languages: eng Pagination: 045102 Citation Subset: IM |
Affiliation:
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The Abdus Salam International Center for Theoretical Physics, Trieste, Italy. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Computer Simulation Entropy Models, Biological* Nerve Net / physiology* Signal Transduction / physiology* Social Support* |
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