Information Geometry of Random Matrix Models

dc.creatorShiber, Dan
dc.date2006-09-13
dc.date2007-04-19
dc.date.accessioned2026-07-07T07:57:14Z
dc.date.available2026-07-07T07:57:14Z
dc.descriptionIn this paper we develop the theory of information geometry for single random matrix models, with two goals: proving a Cramer-Rao theorem for estimators on random matrices, and calculating the Legendre transform of pressure and entropy with respect to a metric duality. Consequently, in the large n limit we recover several quantities from free probability: Voiculescu's conjugate variable is the tangent vector to the GUE perturbation model, giving rise to a metric which turns out to be the free Fisher information measure; Hiai's Legendre transform of free pressure agrees with our Legendre transform of pressure; and Speicher's covariance of fluctuations naturally arises as the metric on the random matrix model obtained from the fluctuation functions.
dc.description29 pages, no figures; corrected typos, a few sections revised
dc.identifierhttps://arxiv.org/abs/math/0609372
dc.identifierhttp://arxiv.org/abs/math/0609372
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/127571
dc.subjectOperator Algebras
dc.subjectProbability
dc.subject15A52 Random matrices
dc.titleInformation Geometry of Random Matrix Models
dc.typetext

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