Percolation on correlated random networks

We consider a class of random, weighted networks, obtained through a redefinition of patterns in an Hopfield-like model, and, by performing percolation processes, we get information about topology and resilience properties of the networks themselves. Given the weighted nature of the graphs, differen...

Full description

Saved in:
Bibliographic Details
Published in:Physical review. E, Statistical, nonlinear, and soft matter physics Statistical, nonlinear, and soft matter physics, 2011-09, Vol.84 (3 Pt 1), p.031120-031120, Article 031120
Main Authors: Agliari, E, Cioli, C, Guadagnini, E
Format: Article
Language:English
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c346t-b4c03d1cb126ca07cd5dcf83a5112eb75f7d2e4bcabaaddfdb7ec61baa4205213
cites cdi_FETCH-LOGICAL-c346t-b4c03d1cb126ca07cd5dcf83a5112eb75f7d2e4bcabaaddfdb7ec61baa4205213
container_end_page 031120
container_issue 3 Pt 1
container_start_page 031120
container_title Physical review. E, Statistical, nonlinear, and soft matter physics
container_volume 84
creator Agliari, E
Cioli, C
Guadagnini, E
description We consider a class of random, weighted networks, obtained through a redefinition of patterns in an Hopfield-like model, and, by performing percolation processes, we get information about topology and resilience properties of the networks themselves. Given the weighted nature of the graphs, different kinds of bond percolation can be studied: stochastic (deleting links randomly) and deterministic (deleting links based on rank weights), each mimicking a different physical process. The evolution of the network is accordingly different, as evidenced by the behavior of the largest component size and of the distribution of cluster sizes. In particular, we can derive that weak ties are crucial in order to maintain the graph connected and that, when they are the most prone to failure, the giant component typically shrinks without abruptly breaking apart; these results have been recently evidenced in several kinds of social networks.
doi_str_mv 10.1103/PhysRevE.84.031120
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_928909088</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>928909088</sourcerecordid><originalsourceid>FETCH-LOGICAL-c346t-b4c03d1cb126ca07cd5dcf83a5112eb75f7d2e4bcabaaddfdb7ec61baa4205213</originalsourceid><addsrcrecordid>eNo9kFtLw0AQhRdRbK3-AR-kb-JD6uwt2TxKqRcoWESfl71MsJpk625q6b83pa0wMHPgnMPwEXJNYUIp8PvF5za94e9sosQEOKUMTsiQSgkZ40V-urt5mfFCygG5SOkLgDOuxDkZMAY5cEGH5G6B0YXadMvQjvtxIUbsJfpxNK0PzbjFbhPid7okZ5WpE14d9oh8PM7ep8_Z_PXpZfowzxwXeZdZ4YB76ixluTNQOC-9qxQ3sn8QbSGrwjMU1hlrjPeVtwW6nPZCMJCM8hG53feuYvhZY-p0s0wO69q0GNZJl0yVUIJSvZPtnS6GlCJWehWXjYlbTUHvCOkjIa2E3hPqQzeH-rVt0P9Hjkj4H_WLZB8</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>928909088</pqid></control><display><type>article</type><title>Percolation on correlated random networks</title><source>American Physical Society:Jisc Collections:APS Read and Publish 2023-2025 (reading list)</source><creator>Agliari, E ; Cioli, C ; Guadagnini, E</creator><creatorcontrib>Agliari, E ; Cioli, C ; Guadagnini, E</creatorcontrib><description>We consider a class of random, weighted networks, obtained through a redefinition of patterns in an Hopfield-like model, and, by performing percolation processes, we get information about topology and resilience properties of the networks themselves. Given the weighted nature of the graphs, different kinds of bond percolation can be studied: stochastic (deleting links randomly) and deterministic (deleting links based on rank weights), each mimicking a different physical process. The evolution of the network is accordingly different, as evidenced by the behavior of the largest component size and of the distribution of cluster sizes. In particular, we can derive that weak ties are crucial in order to maintain the graph connected and that, when they are the most prone to failure, the giant component typically shrinks without abruptly breaking apart; these results have been recently evidenced in several kinds of social networks.</description><identifier>ISSN: 1539-3755</identifier><identifier>EISSN: 1550-2376</identifier><identifier>DOI: 10.1103/PhysRevE.84.031120</identifier><identifier>PMID: 22060341</identifier><language>eng</language><publisher>United States</publisher><ispartof>Physical review. E, Statistical, nonlinear, and soft matter physics, 2011-09, Vol.84 (3 Pt 1), p.031120-031120, Article 031120</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c346t-b4c03d1cb126ca07cd5dcf83a5112eb75f7d2e4bcabaaddfdb7ec61baa4205213</citedby><cites>FETCH-LOGICAL-c346t-b4c03d1cb126ca07cd5dcf83a5112eb75f7d2e4bcabaaddfdb7ec61baa4205213</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22060341$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Agliari, E</creatorcontrib><creatorcontrib>Cioli, C</creatorcontrib><creatorcontrib>Guadagnini, E</creatorcontrib><title>Percolation on correlated random networks</title><title>Physical review. E, Statistical, nonlinear, and soft matter physics</title><addtitle>Phys Rev E Stat Nonlin Soft Matter Phys</addtitle><description>We consider a class of random, weighted networks, obtained through a redefinition of patterns in an Hopfield-like model, and, by performing percolation processes, we get information about topology and resilience properties of the networks themselves. Given the weighted nature of the graphs, different kinds of bond percolation can be studied: stochastic (deleting links randomly) and deterministic (deleting links based on rank weights), each mimicking a different physical process. The evolution of the network is accordingly different, as evidenced by the behavior of the largest component size and of the distribution of cluster sizes. In particular, we can derive that weak ties are crucial in order to maintain the graph connected and that, when they are the most prone to failure, the giant component typically shrinks without abruptly breaking apart; these results have been recently evidenced in several kinds of social networks.</description><issn>1539-3755</issn><issn>1550-2376</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNo9kFtLw0AQhRdRbK3-AR-kb-JD6uwt2TxKqRcoWESfl71MsJpk625q6b83pa0wMHPgnMPwEXJNYUIp8PvF5za94e9sosQEOKUMTsiQSgkZ40V-urt5mfFCygG5SOkLgDOuxDkZMAY5cEGH5G6B0YXadMvQjvtxIUbsJfpxNK0PzbjFbhPid7okZ5WpE14d9oh8PM7ep8_Z_PXpZfowzxwXeZdZ4YB76ixluTNQOC-9qxQ3sn8QbSGrwjMU1hlrjPeVtwW6nPZCMJCM8hG53feuYvhZY-p0s0wO69q0GNZJl0yVUIJSvZPtnS6GlCJWehWXjYlbTUHvCOkjIa2E3hPqQzeH-rVt0P9Hjkj4H_WLZB8</recordid><startdate>201109</startdate><enddate>201109</enddate><creator>Agliari, E</creator><creator>Cioli, C</creator><creator>Guadagnini, E</creator><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>201109</creationdate><title>Percolation on correlated random networks</title><author>Agliari, E ; Cioli, C ; Guadagnini, E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c346t-b4c03d1cb126ca07cd5dcf83a5112eb75f7d2e4bcabaaddfdb7ec61baa4205213</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Agliari, E</creatorcontrib><creatorcontrib>Cioli, C</creatorcontrib><creatorcontrib>Guadagnini, E</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Physical review. E, Statistical, nonlinear, and soft matter physics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Agliari, E</au><au>Cioli, C</au><au>Guadagnini, E</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Percolation on correlated random networks</atitle><jtitle>Physical review. E, Statistical, nonlinear, and soft matter physics</jtitle><addtitle>Phys Rev E Stat Nonlin Soft Matter Phys</addtitle><date>2011-09</date><risdate>2011</risdate><volume>84</volume><issue>3 Pt 1</issue><spage>031120</spage><epage>031120</epage><pages>031120-031120</pages><artnum>031120</artnum><issn>1539-3755</issn><eissn>1550-2376</eissn><abstract>We consider a class of random, weighted networks, obtained through a redefinition of patterns in an Hopfield-like model, and, by performing percolation processes, we get information about topology and resilience properties of the networks themselves. Given the weighted nature of the graphs, different kinds of bond percolation can be studied: stochastic (deleting links randomly) and deterministic (deleting links based on rank weights), each mimicking a different physical process. The evolution of the network is accordingly different, as evidenced by the behavior of the largest component size and of the distribution of cluster sizes. In particular, we can derive that weak ties are crucial in order to maintain the graph connected and that, when they are the most prone to failure, the giant component typically shrinks without abruptly breaking apart; these results have been recently evidenced in several kinds of social networks.</abstract><cop>United States</cop><pmid>22060341</pmid><doi>10.1103/PhysRevE.84.031120</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1539-3755
ispartof Physical review. E, Statistical, nonlinear, and soft matter physics, 2011-09, Vol.84 (3 Pt 1), p.031120-031120, Article 031120
issn 1539-3755
1550-2376
language eng
recordid cdi_proquest_miscellaneous_928909088
source American Physical Society:Jisc Collections:APS Read and Publish 2023-2025 (reading list)
title Percolation on correlated random networks
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T09%3A13%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Percolation%20on%20correlated%20random%20networks&rft.jtitle=Physical%20review.%20E,%20Statistical,%20nonlinear,%20and%20soft%20matter%20physics&rft.au=Agliari,%20E&rft.date=2011-09&rft.volume=84&rft.issue=3%20Pt%201&rft.spage=031120&rft.epage=031120&rft.pages=031120-031120&rft.artnum=031120&rft.issn=1539-3755&rft.eissn=1550-2376&rft_id=info:doi/10.1103/PhysRevE.84.031120&rft_dat=%3Cproquest_cross%3E928909088%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c346t-b4c03d1cb126ca07cd5dcf83a5112eb75f7d2e4bcabaaddfdb7ec61baa4205213%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=928909088&rft_id=info:pmid/22060341&rfr_iscdi=true