Spectral density of dense random networks and the breakdown of the Wigner semicircle law

Detalhes bibliográficos
Autor(a) principal: Metz, Fernando Lucas
Data de Publicação: 2020
Outros Autores: Silva, Jeferson Dias da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/218523
Resumo: Although the spectra of random networks have been studied for a long time, the influence of network topology on the dense limit of network spectra remains poorly understood. By considering the configuration model of networks with four distinct degree distributions, we show that the spectral density of the adjacency matrices of dense random networks is determined by the strength of the degree fluctuations. In particular, the eigenvalue distribution of dense networks with an exponential degree distribution is governed by a simple equation, from which we uncover a logarithmic singularity in the spectral density. We also derive a relation between the fourth moment of the eigenvalue distribution and the variance of the degree distribution, which leads to a sufficient condition for the breakdown of the Wigner semicircle law for dense random networks. Based on the same relation, we propose a classification scheme of the distinct universal behaviors of the spectral density in the dense limit. Our theoretical findings should lead to important insights on the mean-field behavior of models defined on graphs.
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spelling Metz, Fernando LucasSilva, Jeferson Dias da2021-03-10T04:21:07Z20202643-1564http://hdl.handle.net/10183/218523001122370Although the spectra of random networks have been studied for a long time, the influence of network topology on the dense limit of network spectra remains poorly understood. By considering the configuration model of networks with four distinct degree distributions, we show that the spectral density of the adjacency matrices of dense random networks is determined by the strength of the degree fluctuations. In particular, the eigenvalue distribution of dense networks with an exponential degree distribution is governed by a simple equation, from which we uncover a logarithmic singularity in the spectral density. We also derive a relation between the fourth moment of the eigenvalue distribution and the variance of the degree distribution, which leads to a sufficient condition for the breakdown of the Wigner semicircle law for dense random networks. Based on the same relation, we propose a classification scheme of the distinct universal behaviors of the spectral density in the dense limit. Our theoretical findings should lead to important insights on the mean-field behavior of models defined on graphs.application/pdfengPhysical Review Research. College Park. Vol. 2, no. 4 (Oct./Dec. 2020), 043116, 12 p.Lei do semicírculo de WignerSistemas dinâmicosMatrizes aleatóriasSpectral density of dense random networks and the breakdown of the Wigner semicircle lawEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001122370.pdf.txt001122370.pdf.txtExtracted Texttext/plain64335http://www.lume.ufrgs.br/bitstream/10183/218523/2/001122370.pdf.txt01f62aee10a813d1c81fceabc9076883MD52ORIGINAL001122370.pdfTexto completo (inglês)application/pdf694800http://www.lume.ufrgs.br/bitstream/10183/218523/1/001122370.pdf63dbb24a8c537c07af380cad54622db5MD5110183/2185232023-05-21 03:27:28.168959oai:www.lume.ufrgs.br:10183/218523Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-05-21T06:27:28Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Spectral density of dense random networks and the breakdown of the Wigner semicircle law
title Spectral density of dense random networks and the breakdown of the Wigner semicircle law
spellingShingle Spectral density of dense random networks and the breakdown of the Wigner semicircle law
Metz, Fernando Lucas
Lei do semicírculo de Wigner
Sistemas dinâmicos
Matrizes aleatórias
title_short Spectral density of dense random networks and the breakdown of the Wigner semicircle law
title_full Spectral density of dense random networks and the breakdown of the Wigner semicircle law
title_fullStr Spectral density of dense random networks and the breakdown of the Wigner semicircle law
title_full_unstemmed Spectral density of dense random networks and the breakdown of the Wigner semicircle law
title_sort Spectral density of dense random networks and the breakdown of the Wigner semicircle law
author Metz, Fernando Lucas
author_facet Metz, Fernando Lucas
Silva, Jeferson Dias da
author_role author
author2 Silva, Jeferson Dias da
author2_role author
dc.contributor.author.fl_str_mv Metz, Fernando Lucas
Silva, Jeferson Dias da
dc.subject.por.fl_str_mv Lei do semicírculo de Wigner
Sistemas dinâmicos
Matrizes aleatórias
topic Lei do semicírculo de Wigner
Sistemas dinâmicos
Matrizes aleatórias
description Although the spectra of random networks have been studied for a long time, the influence of network topology on the dense limit of network spectra remains poorly understood. By considering the configuration model of networks with four distinct degree distributions, we show that the spectral density of the adjacency matrices of dense random networks is determined by the strength of the degree fluctuations. In particular, the eigenvalue distribution of dense networks with an exponential degree distribution is governed by a simple equation, from which we uncover a logarithmic singularity in the spectral density. We also derive a relation between the fourth moment of the eigenvalue distribution and the variance of the degree distribution, which leads to a sufficient condition for the breakdown of the Wigner semicircle law for dense random networks. Based on the same relation, we propose a classification scheme of the distinct universal behaviors of the spectral density in the dense limit. Our theoretical findings should lead to important insights on the mean-field behavior of models defined on graphs.
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dc.date.issued.fl_str_mv 2020
dc.date.accessioned.fl_str_mv 2021-03-10T04:21:07Z
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dc.relation.ispartof.pt_BR.fl_str_mv Physical Review Research. College Park. Vol. 2, no. 4 (Oct./Dec. 2020), 043116, 12 p.
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