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Random graphs with arbitrary clustering and their applications
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dc.contributor.author | Mann, Peter Stephen | |
dc.contributor.author | Smith, V Anne | |
dc.contributor.author | Mitchell, John B. O. | |
dc.contributor.author | Dobson, Simon Andrew | |
dc.date.accessioned | 2021-02-04T16:30:14Z | |
dc.date.available | 2021-02-04T16:30:14Z | |
dc.date.issued | 2021-01-22 | |
dc.identifier.citation | Mann , P S , Smith , V A , Mitchell , J B O & Dobson , S A 2021 , ' Random graphs with arbitrary clustering and their applications ' , Physical Review. E, Statistical, nonlinear, and soft matter physics , vol. 103 , no. 1 , 012309 . https://doi.org/10.1103/PhysRevE.103.012309 | en |
dc.identifier.issn | 1539-3755 | |
dc.identifier.other | PURE: 271506372 | |
dc.identifier.other | PURE UUID: bce5e5b0-36b3-4eb3-9c3d-8f85876a236e | |
dc.identifier.other | ORCID: /0000-0002-0379-6097/work/88267130 | |
dc.identifier.other | ORCID: /0000-0002-0487-2469/work/88267307 | |
dc.identifier.other | ORCID: /0000-0001-9633-2103/work/88268306 | |
dc.identifier.other | Scopus: 85099791332 | |
dc.identifier.other | WOS: 000610780300004 | |
dc.identifier.uri | https://hdl.handle.net/10023/21376 | |
dc.description.abstract | The structure of many real networks is not locally treelike and, hence, network analysis fails to characterize their bond percolation properties. In a recent paper [P. Mann, V. A. Smith, J. B. O. Mitchell, and S. Dobson, arXiv:2006.06744], we developed analytical solutions to the percolation properties of random networks with homogeneous clustering (clusters whose nodes are degree equivalent). In this paper, we extend this model to investigate networks that contain clusters whose nodes are not degree equivalent, including multilayer networks. Through numerical examples, we show how this method can be used to investigate the properties of random complex networks with arbitrary clustering, extending the applicability of the configuration model and generating function formulation. | |
dc.format.extent | 10 | |
dc.language.iso | eng | |
dc.relation.ispartof | Physical Review. E, Statistical, nonlinear, and soft matter physics | en |
dc.rights | Copyright © 2021 American Physical Society. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the final published version of the work, which was originally published at https://doi.org/10.1103/PhysRevE.103.012309. | en |
dc.subject | Complex networks | en |
dc.subject | Random graphs | en |
dc.subject | Clustered networks | en |
dc.subject | QA Mathematics | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | QC Physics | en |
dc.subject | T-NDAS | en |
dc.subject.lcc | QA | en |
dc.subject.lcc | QA75 | en |
dc.subject.lcc | QC | en |
dc.title | Random graphs with arbitrary clustering and their applications | en |
dc.type | Journal article | en |
dc.description.version | Publisher PDF | en |
dc.contributor.institution | University of St Andrews. School of Chemistry | en |
dc.contributor.institution | University of St Andrews. Office of the Principal | en |
dc.contributor.institution | University of St Andrews. St Andrews Centre for Exoplanet Science | en |
dc.contributor.institution | University of St Andrews. Centre for Biological Diversity | en |
dc.contributor.institution | University of St Andrews. Scottish Oceans Institute | en |
dc.contributor.institution | University of St Andrews. Institute of Behavioural and Neural Sciences | en |
dc.contributor.institution | University of St Andrews. School of Biology | en |
dc.contributor.institution | University of St Andrews. St Andrews Bioinformatics Unit | en |
dc.contributor.institution | University of St Andrews. EaSTCHEM | en |
dc.contributor.institution | University of St Andrews. Biomedical Sciences Research Complex | en |
dc.contributor.institution | University of St Andrews. School of Computer Science | en |
dc.contributor.institution | University of St Andrews. Sir James Mackenzie Institute for Early Diagnosis | en |
dc.identifier.doi | https://doi.org/10.1103/PhysRevE.103.012309 | |
dc.description.status | Peer reviewed | en |
dc.identifier.url | http://arxiv.org/abs/2006.08427 | en |
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