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Growth, collapse, and self-organized criticality in complex networks

Network growth is ubiquitous in nature (e.g., biological networks) and technological systems (e.g., modern infrastructures). To understand how certain dynamical behaviors can or cannot persist as the underlying network grows is a problem of increasing importance in complex dynamical systems as well...

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Autores principales: Wang, Yafeng, Fan, Huawei, Lin, Weijie, Lai, Ying-Cheng, Wang, Xingang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4832202/
https://www.ncbi.nlm.nih.gov/pubmed/27079515
http://dx.doi.org/10.1038/srep24445
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author Wang, Yafeng
Fan, Huawei
Lin, Weijie
Lai, Ying-Cheng
Wang, Xingang
author_facet Wang, Yafeng
Fan, Huawei
Lin, Weijie
Lai, Ying-Cheng
Wang, Xingang
author_sort Wang, Yafeng
collection PubMed
description Network growth is ubiquitous in nature (e.g., biological networks) and technological systems (e.g., modern infrastructures). To understand how certain dynamical behaviors can or cannot persist as the underlying network grows is a problem of increasing importance in complex dynamical systems as well as sustainability science and engineering. We address the question of whether a complex network of nonlinear oscillators can maintain its synchronization stability as it expands. We find that a large scale avalanche over the entire network can be triggered in the sense that the individual nodal dynamics diverges from the synchronous state in a cascading manner within a relatively short time period. In particular, after an initial stage of linear growth, the network typically evolves into a critical state where the addition of a single new node can cause a group of nodes to lose synchronization, leading to synchronization collapse for the entire network. A statistical analysis reveals that the collapse size is approximately algebraically distributed, indicating the emergence of self-organized criticality. We demonstrate the generality of the phenomenon of synchronization collapse using a variety of complex network models, and uncover the underlying dynamical mechanism through an eigenvector analysis.
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spelling pubmed-48322022016-04-20 Growth, collapse, and self-organized criticality in complex networks Wang, Yafeng Fan, Huawei Lin, Weijie Lai, Ying-Cheng Wang, Xingang Sci Rep Article Network growth is ubiquitous in nature (e.g., biological networks) and technological systems (e.g., modern infrastructures). To understand how certain dynamical behaviors can or cannot persist as the underlying network grows is a problem of increasing importance in complex dynamical systems as well as sustainability science and engineering. We address the question of whether a complex network of nonlinear oscillators can maintain its synchronization stability as it expands. We find that a large scale avalanche over the entire network can be triggered in the sense that the individual nodal dynamics diverges from the synchronous state in a cascading manner within a relatively short time period. In particular, after an initial stage of linear growth, the network typically evolves into a critical state where the addition of a single new node can cause a group of nodes to lose synchronization, leading to synchronization collapse for the entire network. A statistical analysis reveals that the collapse size is approximately algebraically distributed, indicating the emergence of self-organized criticality. We demonstrate the generality of the phenomenon of synchronization collapse using a variety of complex network models, and uncover the underlying dynamical mechanism through an eigenvector analysis. Nature Publishing Group 2016-04-15 /pmc/articles/PMC4832202/ /pubmed/27079515 http://dx.doi.org/10.1038/srep24445 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ 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
Wang, Yafeng
Fan, Huawei
Lin, Weijie
Lai, Ying-Cheng
Wang, Xingang
Growth, collapse, and self-organized criticality in complex networks
title Growth, collapse, and self-organized criticality in complex networks
title_full Growth, collapse, and self-organized criticality in complex networks
title_fullStr Growth, collapse, and self-organized criticality in complex networks
title_full_unstemmed Growth, collapse, and self-organized criticality in complex networks
title_short Growth, collapse, and self-organized criticality in complex networks
title_sort growth, collapse, and self-organized criticality in complex networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4832202/
https://www.ncbi.nlm.nih.gov/pubmed/27079515
http://dx.doi.org/10.1038/srep24445
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