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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/142789
Ver los metadatos del registro completo
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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) |
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openAccess |
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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 |
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