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Network Anatomy Controlling Abrupt-like Percolation Transition

We virtually dissect complex networks in order to understand their internal structure, just as doctors do with the bodies of animals. Our novel method classifies network links into four categories: bone, fat, cartilage, and muscle, based on network connectivity. We derive an efficient percolation st...

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Autores principales: Kawamoto, Hirokazu, Takayasu, Hideki, Takayasu, Misako
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5428047/
https://www.ncbi.nlm.nih.gov/pubmed/28279026
http://dx.doi.org/10.1038/s41598-017-00242-4
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author Kawamoto, Hirokazu
Takayasu, Hideki
Takayasu, Misako
author_facet Kawamoto, Hirokazu
Takayasu, Hideki
Takayasu, Misako
author_sort Kawamoto, Hirokazu
collection PubMed
description We virtually dissect complex networks in order to understand their internal structure, just as doctors do with the bodies of animals. Our novel method classifies network links into four categories: bone, fat, cartilage, and muscle, based on network connectivity. We derive an efficient percolation strategy from this new viewpoint of network anatomy, which enables abrupt-like percolation transition through removal of a small amount of cartilage links, which play a crucial role in network connectivity. Furthermore, we find nontrivial scaling laws in the relationships between four types of links in each cluster and evaluate power exponents, which characterize network structures as seen in the real large-scale network of trading business firms and in the Erdős-Rényi network. Finally, we observe changes in the transition point for random bond percolation process, demonstrating that the addition of muscle links enhances network robustness, while fat links are irrelevant. These findings aid in controlling the percolation transition for an arbitrary network.
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spelling pubmed-54280472017-05-15 Network Anatomy Controlling Abrupt-like Percolation Transition Kawamoto, Hirokazu Takayasu, Hideki Takayasu, Misako Sci Rep Article We virtually dissect complex networks in order to understand their internal structure, just as doctors do with the bodies of animals. Our novel method classifies network links into four categories: bone, fat, cartilage, and muscle, based on network connectivity. We derive an efficient percolation strategy from this new viewpoint of network anatomy, which enables abrupt-like percolation transition through removal of a small amount of cartilage links, which play a crucial role in network connectivity. Furthermore, we find nontrivial scaling laws in the relationships between four types of links in each cluster and evaluate power exponents, which characterize network structures as seen in the real large-scale network of trading business firms and in the Erdős-Rényi network. Finally, we observe changes in the transition point for random bond percolation process, demonstrating that the addition of muscle links enhances network robustness, while fat links are irrelevant. These findings aid in controlling the percolation transition for an arbitrary network. Nature Publishing Group UK 2017-03-13 /pmc/articles/PMC5428047/ /pubmed/28279026 http://dx.doi.org/10.1038/s41598-017-00242-4 Text en © The Author(s) 2017 This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Kawamoto, Hirokazu
Takayasu, Hideki
Takayasu, Misako
Network Anatomy Controlling Abrupt-like Percolation Transition
title Network Anatomy Controlling Abrupt-like Percolation Transition
title_full Network Anatomy Controlling Abrupt-like Percolation Transition
title_fullStr Network Anatomy Controlling Abrupt-like Percolation Transition
title_full_unstemmed Network Anatomy Controlling Abrupt-like Percolation Transition
title_short Network Anatomy Controlling Abrupt-like Percolation Transition
title_sort network anatomy controlling abrupt-like percolation transition
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5428047/
https://www.ncbi.nlm.nih.gov/pubmed/28279026
http://dx.doi.org/10.1038/s41598-017-00242-4
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