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dc.date.accessioned 2020-06-05T19:33:57Z
dc.date.available 2020-06-05T19:33:57Z
dc.date.issued 2017-06
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/97640
dc.description.abstract We present an extension of the ergodic, mixing and Bernoulli levels of the ergodic hierarchy in dynamical systems, the information geometric ergodic hierarchy, making use of statistical models on curved manifolds in the context of information geometry. We discuss the 2×2 Gaussian Orthogonal Ensembles (GOE) within a 2D correlated model. For values of the correlation coefficient vanishingly small, we find that GOE belong to the information geometric (IG) mixing level having a maximum negative value of scalar curvature. Moreover, we propose a measure of distinguishability for the family of distributions of the 2D correlated model that results to be an upper bound of the IG correlation. en
dc.format.extent 1-8 es
dc.language en es
dc.subject Ergodic hierarchy es
dc.subject Goe es
dc.subject Entropic dynamics es
dc.title Ergodic statistical models: Entropic dynamics and chaos en
dc.type Articulo es
sedici.identifier.uri https://ri.conicet.gov.ar/11336/63627 es
sedici.identifier.uri http://aip.scitation.org/doi/abs/10.1063/1.4985374 es
sedici.identifier.other http://dx.doi.org/10.1063/1.4985374 es
sedici.identifier.other hdl:11336/63627 es
sedici.identifier.issn 0094-243X es
sedici.creator.person Gómez, Ignacio Sebastián es
sedici.creator.person Portesi, Mariela Adelina es
sedici.subject.materias Física es
sedici.description.fulltext true es
mods.originInfo.place Instituto de Física La Plata es
mods.originInfo.place Consejo Nacional de Investigaciones Científicas y Técnicas es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/4.0/
sedici.description.peerReview peer-review es
sedici.relation.journalTitle AIP Conference Proceedings es
sedici.relation.journalVolumeAndIssue no. 1853 es


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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)