Semicircularity, Gaussianity and Monotonicity of Entropy

dc.creatorSchultz, Hanne
dc.date2005-12-21
dc.date2006-03-10
dc.date.accessioned2026-07-07T06:55:37Z
dc.date.available2026-07-07T06:55:37Z
dc.descriptionS. Artstein, K. Ball, F. Barthe, and A. Naor have shown that if (X_j) are i.i.d. random variables, then the entropy of n^{-1/2}(X_1+....+X_n) increases as n increases. The free analogue was recently proven by D. Shlyakhtenko. That is, if (x_j) are freely independent, identically distributed, self-adjoint elements in a noncommutative probability space, then the free entropy of n^{-1/2}(x_1+....+x_n) increases as n increases. In this paper we prove that if X_1 (x_1, resp.) has finite entropy (free entropy, resp.), and if the entropy (the free entropy, resp.) is not a strictly increasing function of n, then X_1 (x_1, resp.) must be Gaussian (semicircular, resp.).
dc.descriptionAs pointed out to us by Oliver Johnson, the Levy and the Cauchy distributions are both stable and have finite entropy. In the proof of Corollary 3.4 of the previous version we made a mistake by assuming that the distribution has finite variance. Corollary 3.4 has now been removed. Corollary 2.5 still holds
dc.identifierhttps://arxiv.org/abs/math/0512492
dc.identifierhttp://arxiv.org/abs/math/0512492
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/106336
dc.subjectOperator Algebras
dc.subjectProbability
dc.subject46L54; 62E10
dc.titleSemicircularity, Gaussianity and Monotonicity of Entropy
dc.typetext

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