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dc.creatorV'yugin, Vladimir
dc.creatorMaslov, Victor
dc.date2007-08-01
dc.date.accessioned2019-05-03T12:36:46Z
dc.date.available2019-05-03T12:36:46Z
dc.identifierhttp://revistas.ufro.cl/ojs/index.php/cubo/article/view/1590
dc.identifier.urihttp://revistaschilenas.uchile.cl/handle/2250/84318
dc.descriptionWe apply the algorithmic complexity theory to statistical mechanics; in particular, we consider the maximum entropy principle and the entropy concentration theorem for non-ordered data in a non-probabilistic setting. The main goal of this paper is to deduce asymptotic relations for the frequencies of energy levels in a non-ordered collection ωN = [ω1, ..., ωN] from the assumption of maximality of the Kolmogorov complexity K(ωN) given a constraint , where E is a number and f is a numerical function; f(ωi) is an energy level. We also consider a combinatorial model of the securities market and give some applications of the entropy concentration theorem to finance. en-US
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dc.languageeng
dc.publisherUniversidad de La Frontera. Temuco, Chile.en-US
dc.relationhttp://revistas.ufro.cl/ojs/index.php/cubo/article/view/1590/1443
dc.sourceCUBO, A Mathematical Journal; Vol. 9 Núm. 2 (2007): CUBO, A Mathematical Journal; 15-36es-ES
dc.sourceCUBO, A Mathematical Journal; Vol 9 No 2 (2007): CUBO, A Mathematical Journal; 15-36en-US
dc.source0719-0646
dc.source0716-7776
dc.titleAlgorithmic complexity and statistical mechanicsen-US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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