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Two universal physical principles shape the topological statistics of real-world networks


Lorimer, Tom; Gomez, Florian; Stoop, Ruedi (2015). Two universal physical principles shape the topological statistics of real-world networks. Scientific Reports, 5(12353):online.

Abstract

The study of complex networks has pursued an understanding of macroscopic behaviour by focusing on power-laws in microscopic observables. Here, we uncover two universal fundamental physical principles that are at the basis of complex network generation. These principles together predict the generic emergence of deviations from ideal power laws, which were previously discussed away by reference to the thermodynamic limit. Our approach proposes a paradigm shift in the physics of complex networks, toward the use of power-law deviations to infer meso-scale structure from macroscopic observations.

Abstract

The study of complex networks has pursued an understanding of macroscopic behaviour by focusing on power-laws in microscopic observables. Here, we uncover two universal fundamental physical principles that are at the basis of complex network generation. These principles together predict the generic emergence of deviations from ideal power laws, which were previously discussed away by reference to the thermodynamic limit. Our approach proposes a paradigm shift in the physics of complex networks, toward the use of power-law deviations to infer meso-scale structure from macroscopic observations.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2015
Deposited On:11 Feb 2016 13:19
Last Modified:08 Dec 2017 18:29
Publisher:Nature Publishing Group
Series Name:Scientific Reports
Number of Pages:1
ISSN:2045-2322
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1038/srep12353
Official URL:http://www.nature.com/srep/2015/150723/srep12353/full/srep12353.html
PubMed ID:26202858

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