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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/38178
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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:UNLP2025-09-29T10:57:04Zoai: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:13292025-09-29 10:57:04.356SEDICI (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 |
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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) |
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openAccess |
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http://creativecommons.org/licenses/by/3.0/ Creative Commons Attribution 3.0 Unported (CC BY 3.0) |
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application/pdf 1055-1075 |
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