Ergodic statistical models: Entropic dynamics and chaos

Autores
Gomez, Ignacio Sebastián; Portesi, Mariela Adelina
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Gomez, Ignacio Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina
Fil: Portesi, Mariela Adelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina
Materia
ERGODIC HIERARCHY
GOE
ENTROPIC DYNAMICS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/63627
Acceder
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spelling Ergodic statistical models: Entropic dynamics and chaosGomez, Ignacio SebastiánPortesi, Mariela AdelinaERGODIC HIERARCHYGOEENTROPIC DYNAMICShttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1We 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.Fil: Gomez, Ignacio Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; ArgentinaFil: Portesi, Mariela Adelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; ArgentinaAmerican Institute of Physics2017-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/zipapplication/pdfhttp://hdl.handle.net/11336/63627Gomez, Ignacio Sebastián; Portesi, Mariela Adelina; Ergodic statistical models: Entropic dynamics and chaos; American Institute of Physics; AIP Conference Proceedings; 1853; 1; 6-2017; 1-80094-243XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://aip.scitation.org/doi/abs/10.1063/1.4985374info:eu-repo/semantics/altIdentifier/doi/10.1063/1.4985374info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:40:37Zoai:ri.conicet.gov.ar:11336/63627instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:40:37.436CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Ergodic statistical models: Entropic dynamics and chaos
title Ergodic statistical models: Entropic dynamics and chaos
spellingShingle Ergodic statistical models: Entropic dynamics and chaos
Gomez, Ignacio Sebastián
ERGODIC HIERARCHY
GOE
ENTROPIC DYNAMICS
title_short Ergodic statistical models: Entropic dynamics and chaos
title_full Ergodic statistical models: Entropic dynamics and chaos
title_fullStr Ergodic statistical models: Entropic dynamics and chaos
title_full_unstemmed Ergodic statistical models: Entropic dynamics and chaos
title_sort Ergodic statistical models: Entropic dynamics and chaos
dc.creator.none.fl_str_mv Gomez, Ignacio Sebastián
Portesi, Mariela Adelina
author Gomez, Ignacio Sebastián
author_facet Gomez, Ignacio Sebastián
Portesi, Mariela Adelina
author_role author
author2 Portesi, Mariela Adelina
author2_role author
dc.subject.none.fl_str_mv ERGODIC HIERARCHY
GOE
ENTROPIC DYNAMICS
topic ERGODIC HIERARCHY
GOE
ENTROPIC DYNAMICS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv 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.
Fil: Gomez, Ignacio Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina
Fil: Portesi, Mariela Adelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina
description 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.
publishDate 2017
dc.date.none.fl_str_mv 2017-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/63627
Gomez, Ignacio Sebastián; Portesi, Mariela Adelina; Ergodic statistical models: Entropic dynamics and chaos; American Institute of Physics; AIP Conference Proceedings; 1853; 1; 6-2017; 1-8
0094-243X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/63627
identifier_str_mv Gomez, Ignacio Sebastián; Portesi, Mariela Adelina; Ergodic statistical models: Entropic dynamics and chaos; American Institute of Physics; AIP Conference Proceedings; 1853; 1; 6-2017; 1-8
0094-243X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://aip.scitation.org/doi/abs/10.1063/1.4985374
info:eu-repo/semantics/altIdentifier/doi/10.1063/1.4985374
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/zip
application/pdf
dc.publisher.none.fl_str_mv American Institute of Physics
publisher.none.fl_str_mv American Institute of Physics
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.069144

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