Network Anatomy Controlling Abrupt-like Percolation Transition

Abstract 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 perco...

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Autores principales:	Hirokazu Kawamoto, Hideki Takayasu, Misako Takayasu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/80469ed3957b45d794ea889c3f9154f2
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spelling	oai:doaj.org-article:80469ed3957b45d794ea889c3f9154f22021-12-02T11:53:05ZNetwork Anatomy Controlling Abrupt-like Percolation Transition10.1038/s41598-017-00242-42045-2322https://doaj.org/article/80469ed3957b45d794ea889c3f9154f22017-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-00242-4https://doaj.org/toc/2045-2322Abstract 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.Hirokazu KawamotoHideki TakayasuMisako TakayasuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-8 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Hirokazu Kawamoto Hideki Takayasu Misako Takayasu Network Anatomy Controlling Abrupt-like Percolation Transition
description	Abstract 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.
format	article
author	Hirokazu Kawamoto Hideki Takayasu Misako Takayasu
author_facet	Hirokazu Kawamoto Hideki Takayasu Misako Takayasu
author_sort	Hirokazu Kawamoto
title	Network Anatomy Controlling Abrupt-like Percolation Transition
title_short	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_sort	network anatomy controlling abrupt-like percolation transition
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/80469ed3957b45d794ea889c3f9154f2
work_keys_str_mv	AT hirokazukawamoto networkanatomycontrollingabruptlikepercolationtransition AT hidekitakayasu networkanatomycontrollingabruptlikepercolationtransition AT misakotakayasu networkanatomycontrollingabruptlikepercolationtransition
_version_	1718394875365294080

Network Anatomy Controlling Abrupt-like Percolation Transition

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