Conditional pair distributions in many-body systems: Exact results for Poisson ensembles

Autores
Rohrmann, Rene Daniel; Zurbriggen, Ernesto
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We introduce a conditional pair distribution function (CPDF) which characterizes the probability density of finding an object (e.g., a particle in a fluid) to certain distance of other, with each of these two having a nearest neighbor to a fixed but otherwise arbitrary distance. This function describes special four-body configurations, but also contains contributions due to the so-called mutual nearest neighbor (two-body) and shared neighbor (three-body) configurations. The CPDF is introduced to improve a Helmholtz free energy method based on space partitions. We derive exact expressions of the CPDF and various associated quantities for randomly distributed, non-interacting points at Euclidean spaces of one, two and three dimensions. Results may be of interest in many diverse scientific fields, from fluid physics to social and biological sciences.
Fil: Rohrmann, Rene Daniel. Consejo Nacional de Investigaciones Cienti­ficas y Tecnicas. Centro Cientifico Tecnologico San Juan. Instituto de Ciencias Astronomicas de la Tierra y del Espacio; Argentina
Fil: Zurbriggen, Ernesto. Universidad Nacional de Cordoba. Observatorio Astronomico de Cordoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
Fluids
Statistics
Poisson Ensembles
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:11336/11465
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/11465
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network_name_str CONICET Digital (CONICET)
spelling Conditional pair distributions in many-body systems: Exact results for Poisson ensemblesRohrmann, Rene DanielZurbriggen, ErnestoFluidsStatisticsPoisson Ensembleshttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1We introduce a conditional pair distribution function (CPDF) which characterizes the probability density of finding an object (e.g., a particle in a fluid) to certain distance of other, with each of these two having a nearest neighbor to a fixed but otherwise arbitrary distance. This function describes special four-body configurations, but also contains contributions due to the so-called mutual nearest neighbor (two-body) and shared neighbor (three-body) configurations. The CPDF is introduced to improve a Helmholtz free energy method based on space partitions. We derive exact expressions of the CPDF and various associated quantities for randomly distributed, non-interacting points at Euclidean spaces of one, two and three dimensions. Results may be of interest in many diverse scientific fields, from fluid physics to social and biological sciences.Fil: Rohrmann, Rene Daniel. Consejo Nacional de Investigaciones Cienti­ficas y Tecnicas. Centro Cientifico Tecnologico San Juan. Instituto de Ciencias Astronomicas de la Tierra y del Espacio; ArgentinaFil: Zurbriggen, Ernesto. Universidad Nacional de Cordoba. Observatorio Astronomico de Cordoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaAmerican Physical Society2012-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/11465Rohrmann, Rene Daniel; Zurbriggen, Ernesto; Conditional pair distributions in many-body systems: Exact results for Poisson ensembles; American Physical Society; Physical Review E: Statistical Physics, Plasmas, Fluids And Related Interdisciplinary Topics; 85; 5; 4-2012; 1-131063-651Xenginfo:eu-repo/semantics/altIdentifier/url/http://journals.aps.org/pre/abstract/10.1103/PhysRevE.85.051109info:eu-repo/semantics/altIdentifier/doi/10.1103/PhysRevE.85.051109info:eu-repo/semantics/altIdentifier/url/https://arxiv.org/abs/1109.6664info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:40:49Zoai:ri.conicet.gov.ar:11336/11465instacron: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 09:40:49.661CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Conditional pair distributions in many-body systems: Exact results for Poisson ensembles
title Conditional pair distributions in many-body systems: Exact results for Poisson ensembles
spellingShingle Conditional pair distributions in many-body systems: Exact results for Poisson ensembles
Rohrmann, Rene Daniel
Fluids
Statistics
Poisson Ensembles
title_short Conditional pair distributions in many-body systems: Exact results for Poisson ensembles
title_full Conditional pair distributions in many-body systems: Exact results for Poisson ensembles
title_fullStr Conditional pair distributions in many-body systems: Exact results for Poisson ensembles
title_full_unstemmed Conditional pair distributions in many-body systems: Exact results for Poisson ensembles
title_sort Conditional pair distributions in many-body systems: Exact results for Poisson ensembles
dc.creator.none.fl_str_mv Rohrmann, Rene Daniel
Zurbriggen, Ernesto
author Rohrmann, Rene Daniel
author_facet Rohrmann, Rene Daniel
Zurbriggen, Ernesto
author_role author
author2 Zurbriggen, Ernesto
author2_role author
dc.subject.none.fl_str_mv Fluids
Statistics
Poisson Ensembles
topic Fluids
Statistics
Poisson Ensembles
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 introduce a conditional pair distribution function (CPDF) which characterizes the probability density of finding an object (e.g., a particle in a fluid) to certain distance of other, with each of these two having a nearest neighbor to a fixed but otherwise arbitrary distance. This function describes special four-body configurations, but also contains contributions due to the so-called mutual nearest neighbor (two-body) and shared neighbor (three-body) configurations. The CPDF is introduced to improve a Helmholtz free energy method based on space partitions. We derive exact expressions of the CPDF and various associated quantities for randomly distributed, non-interacting points at Euclidean spaces of one, two and three dimensions. Results may be of interest in many diverse scientific fields, from fluid physics to social and biological sciences.
Fil: Rohrmann, Rene Daniel. Consejo Nacional de Investigaciones Cienti­ficas y Tecnicas. Centro Cientifico Tecnologico San Juan. Instituto de Ciencias Astronomicas de la Tierra y del Espacio; Argentina
Fil: Zurbriggen, Ernesto. Universidad Nacional de Cordoba. Observatorio Astronomico de Cordoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description We introduce a conditional pair distribution function (CPDF) which characterizes the probability density of finding an object (e.g., a particle in a fluid) to certain distance of other, with each of these two having a nearest neighbor to a fixed but otherwise arbitrary distance. This function describes special four-body configurations, but also contains contributions due to the so-called mutual nearest neighbor (two-body) and shared neighbor (three-body) configurations. The CPDF is introduced to improve a Helmholtz free energy method based on space partitions. We derive exact expressions of the CPDF and various associated quantities for randomly distributed, non-interacting points at Euclidean spaces of one, two and three dimensions. Results may be of interest in many diverse scientific fields, from fluid physics to social and biological sciences.
publishDate 2012
dc.date.none.fl_str_mv 2012-04
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/11336/11465
Rohrmann, Rene Daniel; Zurbriggen, Ernesto; Conditional pair distributions in many-body systems: Exact results for Poisson ensembles; American Physical Society; Physical Review E: Statistical Physics, Plasmas, Fluids And Related Interdisciplinary Topics; 85; 5; 4-2012; 1-13
1063-651X
url http://hdl.handle.net/11336/11465
identifier_str_mv Rohrmann, Rene Daniel; Zurbriggen, Ernesto; Conditional pair distributions in many-body systems: Exact results for Poisson ensembles; American Physical Society; Physical Review E: Statistical Physics, Plasmas, Fluids And Related Interdisciplinary Topics; 85; 5; 4-2012; 1-13
1063-651X
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journals.aps.org/pre/abstract/10.1103/PhysRevE.85.051109
info:eu-repo/semantics/altIdentifier/doi/10.1103/PhysRevE.85.051109
info:eu-repo/semantics/altIdentifier/url/https://arxiv.org/abs/1109.6664
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/pdf
dc.publisher.none.fl_str_mv American Physical Society
publisher.none.fl_str_mv American Physical Society
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 13.070432

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