Deciphering the generating rules and functionalities of complex networks

Abstract Network theory helps us understand, analyze, model, and design various complex systems. Complex networks encode the complex topology and structural interactions of various systems in nature. To mine the multiscale coupling, heterogeneity, and complexity of natural and technological systems,...

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Autores principales:	Xiongye Xiao, Hanlong Chen, Paul Bogdan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/4ba8f88bde9e43ba8a1efd073eb70d67
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spelling	oai:doaj.org-article:4ba8f88bde9e43ba8a1efd073eb70d672021-11-28T12:18:06ZDeciphering the generating rules and functionalities of complex networks10.1038/s41598-021-02203-42045-2322https://doaj.org/article/4ba8f88bde9e43ba8a1efd073eb70d672021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-02203-4https://doaj.org/toc/2045-2322Abstract Network theory helps us understand, analyze, model, and design various complex systems. Complex networks encode the complex topology and structural interactions of various systems in nature. To mine the multiscale coupling, heterogeneity, and complexity of natural and technological systems, we need expressive and rigorous mathematical tools that can help us understand the growth, topology, dynamics, multiscale structures, and functionalities of complex networks and their interrelationships. Towards this end, we construct the node-based fractal dimension (NFD) and the node-based multifractal analysis (NMFA) framework to reveal the generating rules and quantify the scale-dependent topology and multifractal features of a dynamic complex network. We propose novel indicators for measuring the degree of complexity, heterogeneity, and asymmetry of network structures, as well as the structure distance between networks. This formalism provides new insights on learning the energy and phase transitions in the networked systems and can help us understand the multiple generating mechanisms governing the network evolution.Xiongye XiaoHanlong ChenPaul BogdanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiongye Xiao Hanlong Chen Paul Bogdan Deciphering the generating rules and functionalities of complex networks
description	Abstract Network theory helps us understand, analyze, model, and design various complex systems. Complex networks encode the complex topology and structural interactions of various systems in nature. To mine the multiscale coupling, heterogeneity, and complexity of natural and technological systems, we need expressive and rigorous mathematical tools that can help us understand the growth, topology, dynamics, multiscale structures, and functionalities of complex networks and their interrelationships. Towards this end, we construct the node-based fractal dimension (NFD) and the node-based multifractal analysis (NMFA) framework to reveal the generating rules and quantify the scale-dependent topology and multifractal features of a dynamic complex network. We propose novel indicators for measuring the degree of complexity, heterogeneity, and asymmetry of network structures, as well as the structure distance between networks. This formalism provides new insights on learning the energy and phase transitions in the networked systems and can help us understand the multiple generating mechanisms governing the network evolution.
format	article
author	Xiongye Xiao Hanlong Chen Paul Bogdan
author_facet	Xiongye Xiao Hanlong Chen Paul Bogdan
author_sort	Xiongye Xiao
title	Deciphering the generating rules and functionalities of complex networks
title_short	Deciphering the generating rules and functionalities of complex networks
title_full	Deciphering the generating rules and functionalities of complex networks
title_fullStr	Deciphering the generating rules and functionalities of complex networks
title_full_unstemmed	Deciphering the generating rules and functionalities of complex networks
title_sort	deciphering the generating rules and functionalities of complex networks
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/4ba8f88bde9e43ba8a1efd073eb70d67
work_keys_str_mv	AT xiongyexiao decipheringthegeneratingrulesandfunctionalitiesofcomplexnetworks AT hanlongchen decipheringthegeneratingrulesandfunctionalitiesofcomplexnetworks AT paulbogdan decipheringthegeneratingrulesandfunctionalitiesofcomplexnetworks
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Deciphering the generating rules and functionalities of complex networks

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