Density of near-extreme events

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dc.creatorSabhapandit, Sanjib
dc.creatorMajumdar, Satya N.
dc.date2007-01-16
dc.date2007-03-27
dc.date.accessioned2026-07-07T07:55:36Z
dc.date.available2026-07-07T07:55:36Z
dc.descriptionWe provide a quantitative analysis of the phenomenon of crowding of near-extreme events by computing exactly the density of states (DOS) near the maximum of a set of independent and identically distributed random variables. We show that the mean DOS converges to three different limiting forms depending on whether the tail of the distribution of the random variables decays slower than, faster than, or as a pure exponential function. We argue that some of these results would remain valid even for certain {\em correlated} cases and verify it for power-law correlated stationary Gaussian sequences. Satisfactory agreement is found between the near-maximum crowding in the summer temperature reconstruction data of western Siberia and the theoretical prediction.
dc.description4 pages, 3 figures, revtex4. Minor corrections, references updated. This is slightly extended version of the Published one (Phys. Rev. Lett.)
dc.identifierhttps://arxiv.org/abs/cond-mat/0701375
dc.identifierhttp://arxiv.org/abs/cond-mat/0701375
dc.identifierPhys. Rev. Lett. vol. 98, pp. 140201 (2007)
dc.identifierdoi:10.1103/PhysRevLett.98.140201
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/127026
dc.subjectStatistical Mechanics
dc.subjectDisordered Systems and Neural Networks
dc.titleDensity of near-extreme events
dc.typetext

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