Extreme fluctuations in noisy task-completion landscapes on scale-free networks

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dc.creatorGuclu, H.
dc.creatorKorniss, G.
dc.creatorToroczkai, Z.
dc.date2007-01-13
dc.date.accessioned2026-07-07T08:27:49Z
dc.date.available2026-07-07T08:27:49Z
dc.descriptionWe study the statistics and scaling of extreme fluctuations in noisy task-completion landscapes, such as those emerging in synchronized distributed-computing networks, or generic causally-constrained queuing networks, with scale-free topology. In these networks the average size of the fluctuations becomes finite (synchronized state) and the extreme fluctuations typically diverge only logarithmically in the large system-size limit ensuring synchronization in a practical sense. Provided that local fluctuations in the network are short-tailed, the statistics of the extremes are governed by the Gumbel distribution. We present large-scale simulation results using the exact algorithmic rules, supported by mean-field arguments based on a coarse-grained description.
dc.description16 pages, 6 figures, revtex
dc.identifierhttps://arxiv.org/abs/cond-mat/0701301
dc.identifierhttp://arxiv.org/abs/cond-mat/0701301
dc.identifierChaos 17, 026104 (2007)
dc.identifierdoi:10.1063/1.2735446
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/137400
dc.subjectDisordered Systems and Neural Networks
dc.subjectStatistical Mechanics
dc.titleExtreme fluctuations in noisy task-completion landscapes on scale-free networks
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