Distances in probability space and the statistical complexity setup

Autores
Kowalski, Andrés; Martín, María Teresa; Plastino, Ángel Luis; Rosso, Osvaldo A.; Casas, Montserrat
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Statistical complexity measures (SCM) are the composition of two ingredients: (i) entropies and (ii) distances in probability-space. In consequence, SCMs provide a simultaneous quantification of the randomness and the correlational structures present in the system under study. We address in this review important topics underlying the SCM structure, viz., (a) a good choice of probability metric space and (b) how to assess the best distance-choice, which in this context is called a "disequilibrium" and is denoted with the letter Q. Q, indeed the crucial SCM ingredient, is cast in terms of an associated distance D. Since out input data consists of time-series, we also discuss the best way of extracting from the time series a probability distribution P. As an illustration, we show just how these issues affect the description of the classical limit of quantum mechanics.
Facultad de Ciencias Exactas
Materia
Ciencias Exactas
Física
disequilibrium
generalized statistical complexity
information theory
quantum chaos
selection of the probability distribution
semiclassical theories
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/38178
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/38178
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Distances in probability space and the statistical complexity setupKowalski, AndrésMartín, María TeresaPlastino, Ángel LuisRosso, Osvaldo A.Casas, MontserratCiencias ExactasFísicadisequilibriumgeneralized statistical complexityinformation theoryquantum chaosselection of the probability distributionsemiclassical theoriesStatistical complexity measures (SCM) are the composition of two ingredients: (i) entropies and (ii) distances in probability-space. In consequence, SCMs provide a simultaneous quantification of the randomness and the correlational structures present in the system under study. We address in this review important topics underlying the SCM structure, viz., (a) a good choice of probability metric space and (b) how to assess the best distance-choice, which in this context is called a "disequilibrium" and is denoted with the letter Q. Q, indeed the crucial SCM ingredient, is cast in terms of an associated distance D. Since out input data consists of time-series, we also discuss the best way of extracting from the time series a probability distribution P. As an illustration, we show just how these issues affect the description of the classical limit of quantum mechanics.Facultad de Ciencias Exactas2011-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf1055-1075http://sedici.unlp.edu.ar/handle/10915/38178enginfo:eu-repo/semantics/altIdentifier/url/http://www.mdpi.com/1099-4300/13/6/1055info:eu-repo/semantics/altIdentifier/issn/1099-4300info:eu-repo/semantics/altIdentifier/doi/10.3390/e13061055info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/Creative Commons Attribution 3.0 Unported (CC BY 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T10:49:40Zoai:sedici.unlp.edu.ar:10915/38178Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 10:49:41.205SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Distances in probability space and the statistical complexity setup
title Distances in probability space and the statistical complexity setup
spellingShingle Distances in probability space and the statistical complexity setup
Kowalski, Andrés
Ciencias Exactas
Física
disequilibrium
generalized statistical complexity
information theory
quantum chaos
selection of the probability distribution
semiclassical theories
title_short Distances in probability space and the statistical complexity setup
title_full Distances in probability space and the statistical complexity setup
title_fullStr Distances in probability space and the statistical complexity setup
title_full_unstemmed Distances in probability space and the statistical complexity setup
title_sort Distances in probability space and the statistical complexity setup
dc.creator.none.fl_str_mv Kowalski, Andrés
Martín, María Teresa
Plastino, Ángel Luis
Rosso, Osvaldo A.
Casas, Montserrat
author Kowalski, Andrés
author_facet Kowalski, Andrés
Martín, María Teresa
Plastino, Ángel Luis
Rosso, Osvaldo A.
Casas, Montserrat
author_role author
author2 Martín, María Teresa
Plastino, Ángel Luis
Rosso, Osvaldo A.
Casas, Montserrat
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Exactas
Física
disequilibrium
generalized statistical complexity
information theory
quantum chaos
selection of the probability distribution
semiclassical theories
topic Ciencias Exactas
Física
disequilibrium
generalized statistical complexity
information theory
quantum chaos
selection of the probability distribution
semiclassical theories
dc.description.none.fl_txt_mv Statistical complexity measures (SCM) are the composition of two ingredients: (i) entropies and (ii) distances in probability-space. In consequence, SCMs provide a simultaneous quantification of the randomness and the correlational structures present in the system under study. We address in this review important topics underlying the SCM structure, viz., (a) a good choice of probability metric space and (b) how to assess the best distance-choice, which in this context is called a "disequilibrium" and is denoted with the letter Q. Q, indeed the crucial SCM ingredient, is cast in terms of an associated distance D. Since out input data consists of time-series, we also discuss the best way of extracting from the time series a probability distribution P. As an illustration, we show just how these issues affect the description of the classical limit of quantum mechanics.
Facultad de Ciencias Exactas
description Statistical complexity measures (SCM) are the composition of two ingredients: (i) entropies and (ii) distances in probability-space. In consequence, SCMs provide a simultaneous quantification of the randomness and the correlational structures present in the system under study. We address in this review important topics underlying the SCM structure, viz., (a) a good choice of probability metric space and (b) how to assess the best distance-choice, which in this context is called a "disequilibrium" and is denoted with the letter Q. Q, indeed the crucial SCM ingredient, is cast in terms of an associated distance D. Since out input data consists of time-series, we also discuss the best way of extracting from the time series a probability distribution P. As an illustration, we show just how these issues affect the description of the classical limit of quantum mechanics.
publishDate 2011
dc.date.none.fl_str_mv 2011-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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://sedici.unlp.edu.ar/handle/10915/38178
url http://sedici.unlp.edu.ar/handle/10915/38178
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.mdpi.com/1099-4300/13/6/1055
info:eu-repo/semantics/altIdentifier/issn/1099-4300
info:eu-repo/semantics/altIdentifier/doi/10.3390/e13061055
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
dc.format.none.fl_str_mv application/pdf
1055-1075
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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