Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/9185
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dc.contributor.authorHoppe, K-
dc.contributor.authorRodgers, GJ-
dc.date.accessioned2014-10-16T14:07:12Z-
dc.date.available2014-10-16T14:07:12Z-
dc.date.issued2014-
dc.identifier.citationPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics, 90(1): 012815, Jul 2014en_US
dc.identifier.issn1539-3755-
dc.identifier.urihttp://journals.aps.org/pre/abstract/10.1103/PhysRevE.90.012815en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/9185-
dc.descriptionCopyright @ 2014 American Physical Societyen_US
dc.description.abstractThe ability to understand the impact of adversarial processes on networks is crucial to various disciplines. The objects of study in this article are fitness-driven networks. Fitness-dependent networks are fully described by a probability distribution of fitness and an attachment kernel. Every node in the network is endowed with a fitness value and the attachment kernel translates the fitness of two nodes into the probability that these two nodes share an edge. This concept is also known as mutual attractiveness. In the present article, fitness does not only serve as a measure of attractiveness, but also as a measure of a node's robustness against failure. The probability that a node fails increases with the number of failures in its direct neighborhood and decreases with higher fitness. Both static and dynamic network models are considered. Analytical results for the percolation threshold and the occupied fraction are derived. One of the results is that the distinction between the dynamic and the static model has a profound impact on the way failures spread over the network. Additionally, we find that the introduction of mutual attractiveness stabilizes the network compared to a pure random attachment. © 2014 American Physical Society.en_US
dc.languageeng-
dc.language.isoenen_US
dc.publisherAmerican Physical Societyen_US
dc.subjectFitness-driven networksen_US
dc.subjectMutual attractivenessen_US
dc.subjectPercolationen_US
dc.titlePercolation on fitness-dependent networks with heterogeneous resilienceen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1103/PhysRevE.90.012815-
pubs.organisational-data/Brunel-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Mathematics-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Mathematics/Mathematical Sciences-
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pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute for Ageing Studies-
Appears in Collections:Mathematical Physics
Dept of Mathematics Research Papers

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