Partition function based analysis of cosmic microwave background maps

Autores
Diego, Jose M.; Martínez-González, E.; Sanz, J. L.; Mollerach, Silvia; Martínez, Vicent J.
Año de publicación
1999
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We present an alternative method to analyse cosmic microwave background (CMB) maps. We base our analysis on the study of the partition function. This function is used to examine the CMB maps, making use of the different information embedded at different scales and moments. Using the partition function in a likelihood analysis in two dimensions (Qrms-PS, n), we find the best-fitting model to the best data available at present (the COBE–DMR 4 years data set). By means of this analysis we find a maximum in the likelihood function for n=1.8-0.65+0.35 and Qrms-PS = 10-2.5+3μ K (95 per cent confidence level) in agreement with the results of other similar analyses [Smoot et al. (1 yr), Bennet et al. (4 yr)]. Also making use of the partition function we perform a multifractal analysis and study the possible fractal nature of the CMB sky. We find that the measure used in the analysis is not a fractal. Finally, we use the partition function for testing the statistical distribution of the COBE—DMR data set. We conclude that no evidence of non-Gaussianity can be found by means of this method.
Facultad de Ciencias Exactas
Materia
Física
Methods: data analysis
Cosmic microwave background
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/142789

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network_name_str SEDICI (UNLP)
spelling Partition function based analysis of cosmic microwave background mapsDiego, Jose M.Martínez-González, E.Sanz, J. L.Mollerach, SilviaMartínez, Vicent J.FísicaMethods: data analysisCosmic microwave backgroundWe present an alternative method to analyse cosmic microwave background (CMB) maps. We base our analysis on the study of the partition function. This function is used to examine the CMB maps, making use of the different information embedded at different scales and moments. Using the partition function in a likelihood analysis in two dimensions (Qrms-PS, n), we find the best-fitting model to the best data available at present (the COBE–DMR 4 years data set). By means of this analysis we find a maximum in the likelihood function for n=1.8-0.65+0.35 and Qrms-PS = 10-2.5+3μ K (95 per cent confidence level) in agreement with the results of other similar analyses [Smoot et al. (1 yr), Bennet et al. (4 yr)]. Also making use of the partition function we perform a multifractal analysis and study the possible fractal nature of the CMB sky. We find that the measure used in the analysis is not a fractal. Finally, we use the partition function for testing the statistical distribution of the COBE—DMR data set. We conclude that no evidence of non-Gaussianity can be found by means of this method.Facultad de Ciencias Exactas1999-06-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf427-436http://sedici.unlp.edu.ar/handle/10915/142789enginfo:eu-repo/semantics/altIdentifier/issn/0035-8711info:eu-repo/semantics/altIdentifier/issn/1365-2966info:eu-repo/semantics/altIdentifier/doi/10.1046/j.1365-8711.1999.02523.xinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:24:24Zoai:sedici.unlp.edu.ar:10915/142789Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:24:25.083SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Partition function based analysis of cosmic microwave background maps
title Partition function based analysis of cosmic microwave background maps
spellingShingle Partition function based analysis of cosmic microwave background maps
Diego, Jose M.
Física
Methods: data analysis
Cosmic microwave background
title_short Partition function based analysis of cosmic microwave background maps
title_full Partition function based analysis of cosmic microwave background maps
title_fullStr Partition function based analysis of cosmic microwave background maps
title_full_unstemmed Partition function based analysis of cosmic microwave background maps
title_sort Partition function based analysis of cosmic microwave background maps
dc.creator.none.fl_str_mv Diego, Jose M.
Martínez-González, E.
Sanz, J. L.
Mollerach, Silvia
Martínez, Vicent J.
author Diego, Jose M.
author_facet Diego, Jose M.
Martínez-González, E.
Sanz, J. L.
Mollerach, Silvia
Martínez, Vicent J.
author_role author
author2 Martínez-González, E.
Sanz, J. L.
Mollerach, Silvia
Martínez, Vicent J.
author2_role author
author
author
author
dc.subject.none.fl_str_mv Física
Methods: data analysis
Cosmic microwave background
topic Física
Methods: data analysis
Cosmic microwave background
dc.description.none.fl_txt_mv We present an alternative method to analyse cosmic microwave background (CMB) maps. We base our analysis on the study of the partition function. This function is used to examine the CMB maps, making use of the different information embedded at different scales and moments. Using the partition function in a likelihood analysis in two dimensions (Qrms-PS, n), we find the best-fitting model to the best data available at present (the COBE–DMR 4 years data set). By means of this analysis we find a maximum in the likelihood function for n=1.8-0.65+0.35 and Qrms-PS = 10-2.5+3μ K (95 per cent confidence level) in agreement with the results of other similar analyses [Smoot et al. (1 yr), Bennet et al. (4 yr)]. Also making use of the partition function we perform a multifractal analysis and study the possible fractal nature of the CMB sky. We find that the measure used in the analysis is not a fractal. Finally, we use the partition function for testing the statistical distribution of the COBE—DMR data set. We conclude that no evidence of non-Gaussianity can be found by means of this method.
Facultad de Ciencias Exactas
description We present an alternative method to analyse cosmic microwave background (CMB) maps. We base our analysis on the study of the partition function. This function is used to examine the CMB maps, making use of the different information embedded at different scales and moments. Using the partition function in a likelihood analysis in two dimensions (Qrms-PS, n), we find the best-fitting model to the best data available at present (the COBE–DMR 4 years data set). By means of this analysis we find a maximum in the likelihood function for n=1.8-0.65+0.35 and Qrms-PS = 10-2.5+3μ K (95 per cent confidence level) in agreement with the results of other similar analyses [Smoot et al. (1 yr), Bennet et al. (4 yr)]. Also making use of the partition function we perform a multifractal analysis and study the possible fractal nature of the CMB sky. We find that the measure used in the analysis is not a fractal. Finally, we use the partition function for testing the statistical distribution of the COBE—DMR data set. We conclude that no evidence of non-Gaussianity can be found by means of this method.
publishDate 1999
dc.date.none.fl_str_mv 1999-06-21
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/10915/142789
url http://sedici.unlp.edu.ar/handle/10915/142789
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/0035-8711
info:eu-repo/semantics/altIdentifier/issn/1365-2966
info:eu-repo/semantics/altIdentifier/doi/10.1046/j.1365-8711.1999.02523.x
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
427-436
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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