OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale

Autores
Perren, Gabriel Ignacio; Vazquez, Ruben Angel; Piatti, Andres Eduardo; Moitihno, Andre
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Star clusters are among the fundamental astrophysical objects used in setting the local distance scale. Despite its crucial importance, the accurate determination of the distances to the Magellanic Clouds (SMC/LMC) remains a fuzzy step in the cosmological distance ladder. The exquisite astrometry of the recently launched ESA Gaia mission is expected to deliver extremely accurate statistical parallaxes, and thus distances, to the SMC/LMC. However, an independent SMC/LMC distance determination via main sequence fitting of star clusters provides an important validation check point for the Gaia distances. This has been a valuable lesson learnt from the famous Hipparcos Pleiades distance discrepancy problem. Current observations will allow hundreds of LMC/SMC clusters to be analyzed in this light. Today, the most common approach for star cluster main sequence fitting is still by eye. The process is intrinsically subjective and affected by large uncertainties, especially when applied to poorly populated clusters. It is also, clearly, not an efficient route for addressing the analysis of hundreds, or thousands, of star clusters. These concerns, together with a new attitude towards advanced statistical techniques in astronomy and the availability of powerful computers, have led to the emergence of software packages designed for analyzing star cluster photometry. With a few rare exceptions, those packages are not publicly available. Here we present OCAAT (Open Cluster Automated Analysis Tool), a suite of publicly available open source tools that fully automatises cluster isochrone fitting. The code will be applied to a large set of hundreds of open clusters observed in the Washington system, located in the Milky Way and the Magellanic Clouds. This will allow us to generate an objective and homogeneous catalog of distances up to ~ 60 kpc along with its associated reddening, ages and metallicities and uncertainty estimates.
Fil: Perren, Gabriel Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica la Plata; Argentina
Fil: Vazquez, Ruben Angel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica la Plata; Argentina
Fil: Piatti, Andres Eduardo. Universidad Nacional de Cordoba. Observatorio Astronomico de Cordoba; Argentina
Fil: Moitihno, Andre. Universidade de Lisboa. Lisboa; Portugal
Materia
Cluster
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:11336/34266
Acceder
id CONICETDig_a5edf8266ba7343c2a9f6079e0e6c668
oai_identifier_str oai:ri.conicet.gov.ar:11336/34266
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scalePerren, Gabriel IgnacioVazquez, Ruben AngelPiatti, Andres EduardoMoitihno, AndreClusterhttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1Star clusters are among the fundamental astrophysical objects used in setting the local distance scale. Despite its crucial importance, the accurate determination of the distances to the Magellanic Clouds (SMC/LMC) remains a fuzzy step in the cosmological distance ladder. The exquisite astrometry of the recently launched ESA Gaia mission is expected to deliver extremely accurate statistical parallaxes, and thus distances, to the SMC/LMC. However, an independent SMC/LMC distance determination via main sequence fitting of star clusters provides an important validation check point for the Gaia distances. This has been a valuable lesson learnt from the famous Hipparcos Pleiades distance discrepancy problem. Current observations will allow hundreds of LMC/SMC clusters to be analyzed in this light. Today, the most common approach for star cluster main sequence fitting is still by eye. The process is intrinsically subjective and affected by large uncertainties, especially when applied to poorly populated clusters. It is also, clearly, not an efficient route for addressing the analysis of hundreds, or thousands, of star clusters. These concerns, together with a new attitude towards advanced statistical techniques in astronomy and the availability of powerful computers, have led to the emergence of software packages designed for analyzing star cluster photometry. With a few rare exceptions, those packages are not publicly available. Here we present OCAAT (Open Cluster Automated Analysis Tool), a suite of publicly available open source tools that fully automatises cluster isochrone fitting. The code will be applied to a large set of hundreds of open clusters observed in the Washington system, located in the Milky Way and the Magellanic Clouds. This will allow us to generate an objective and homogeneous catalog of distances up to ~ 60 kpc along with its associated reddening, ages and metallicities and uncertainty estimates.Fil: Perren, Gabriel Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica la Plata; ArgentinaFil: Vazquez, Ruben Angel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica la Plata; ArgentinaFil: Piatti, Andres Eduardo. Universidad Nacional de Cordoba. Observatorio Astronomico de Cordoba; ArgentinaFil: Moitihno, Andre. Universidade de Lisboa. Lisboa; PortugalCambridge University Press2014-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/34266Perren, Gabriel Ignacio; Vazquez, Ruben Angel; Piatti, Andres Eduardo; Moitihno, Andre; OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale; Cambridge University Press; Proceedings of the International Astronomical Union; 10; S306; 5-2014; 298-3001743-9213CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1017/S1743921314011077info:eu-repo/semantics/altIdentifier/url/https://www.cambridge.org/core/journals/proceedings-of-the-international-astronomical-union/article/ocaat-automated-analysis-of-star-cluster-colourmagnitude-diagrams-for-gauging-the-local-distance-scale/B8EA12B662CF8F6BA9793BAC0B9E0755info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:19:23Zoai:ri.conicet.gov.ar:11336/34266instacron: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 10:19:24.0CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale
title OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale
spellingShingle OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale
Perren, Gabriel Ignacio
Cluster
title_short OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale
title_full OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale
title_fullStr OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale
title_full_unstemmed OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale
title_sort OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale
dc.creator.none.fl_str_mv Perren, Gabriel Ignacio
Vazquez, Ruben Angel
Piatti, Andres Eduardo
Moitihno, Andre
author Perren, Gabriel Ignacio
author_facet Perren, Gabriel Ignacio
Vazquez, Ruben Angel
Piatti, Andres Eduardo
Moitihno, Andre
author_role author
author2 Vazquez, Ruben Angel
Piatti, Andres Eduardo
Moitihno, Andre
author2_role author
author
author
dc.subject.none.fl_str_mv Cluster
topic Cluster
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Star clusters are among the fundamental astrophysical objects used in setting the local distance scale. Despite its crucial importance, the accurate determination of the distances to the Magellanic Clouds (SMC/LMC) remains a fuzzy step in the cosmological distance ladder. The exquisite astrometry of the recently launched ESA Gaia mission is expected to deliver extremely accurate statistical parallaxes, and thus distances, to the SMC/LMC. However, an independent SMC/LMC distance determination via main sequence fitting of star clusters provides an important validation check point for the Gaia distances. This has been a valuable lesson learnt from the famous Hipparcos Pleiades distance discrepancy problem. Current observations will allow hundreds of LMC/SMC clusters to be analyzed in this light. Today, the most common approach for star cluster main sequence fitting is still by eye. The process is intrinsically subjective and affected by large uncertainties, especially when applied to poorly populated clusters. It is also, clearly, not an efficient route for addressing the analysis of hundreds, or thousands, of star clusters. These concerns, together with a new attitude towards advanced statistical techniques in astronomy and the availability of powerful computers, have led to the emergence of software packages designed for analyzing star cluster photometry. With a few rare exceptions, those packages are not publicly available. Here we present OCAAT (Open Cluster Automated Analysis Tool), a suite of publicly available open source tools that fully automatises cluster isochrone fitting. The code will be applied to a large set of hundreds of open clusters observed in the Washington system, located in the Milky Way and the Magellanic Clouds. This will allow us to generate an objective and homogeneous catalog of distances up to ~ 60 kpc along with its associated reddening, ages and metallicities and uncertainty estimates.
Fil: Perren, Gabriel Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica la Plata; Argentina
Fil: Vazquez, Ruben Angel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica la Plata; Argentina
Fil: Piatti, Andres Eduardo. Universidad Nacional de Cordoba. Observatorio Astronomico de Cordoba; Argentina
Fil: Moitihno, Andre. Universidade de Lisboa. Lisboa; Portugal
description Star clusters are among the fundamental astrophysical objects used in setting the local distance scale. Despite its crucial importance, the accurate determination of the distances to the Magellanic Clouds (SMC/LMC) remains a fuzzy step in the cosmological distance ladder. The exquisite astrometry of the recently launched ESA Gaia mission is expected to deliver extremely accurate statistical parallaxes, and thus distances, to the SMC/LMC. However, an independent SMC/LMC distance determination via main sequence fitting of star clusters provides an important validation check point for the Gaia distances. This has been a valuable lesson learnt from the famous Hipparcos Pleiades distance discrepancy problem. Current observations will allow hundreds of LMC/SMC clusters to be analyzed in this light. Today, the most common approach for star cluster main sequence fitting is still by eye. The process is intrinsically subjective and affected by large uncertainties, especially when applied to poorly populated clusters. It is also, clearly, not an efficient route for addressing the analysis of hundreds, or thousands, of star clusters. These concerns, together with a new attitude towards advanced statistical techniques in astronomy and the availability of powerful computers, have led to the emergence of software packages designed for analyzing star cluster photometry. With a few rare exceptions, those packages are not publicly available. Here we present OCAAT (Open Cluster Automated Analysis Tool), a suite of publicly available open source tools that fully automatises cluster isochrone fitting. The code will be applied to a large set of hundreds of open clusters observed in the Washington system, located in the Milky Way and the Magellanic Clouds. This will allow us to generate an objective and homogeneous catalog of distances up to ~ 60 kpc along with its associated reddening, ages and metallicities and uncertainty estimates.
publishDate 2014
dc.date.none.fl_str_mv 2014-05
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/11336/34266
Perren, Gabriel Ignacio; Vazquez, Ruben Angel; Piatti, Andres Eduardo; Moitihno, Andre; OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale; Cambridge University Press; Proceedings of the International Astronomical Union; 10; S306; 5-2014; 298-300
1743-9213
CONICET Digital
CONICET
url http://hdl.handle.net/11336/34266
identifier_str_mv Perren, Gabriel Ignacio; Vazquez, Ruben Angel; Piatti, Andres Eduardo; Moitihno, Andre; OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale; Cambridge University Press; Proceedings of the International Astronomical Union; 10; S306; 5-2014; 298-300
1743-9213
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1017/S1743921314011077
info:eu-repo/semantics/altIdentifier/url/https://www.cambridge.org/core/journals/proceedings-of-the-international-astronomical-union/article/ocaat-automated-analysis-of-star-cluster-colourmagnitude-diagrams-for-gauging-the-local-distance-scale/B8EA12B662CF8F6BA9793BAC0B9E0755
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 Cambridge University Press
publisher.none.fl_str_mv Cambridge University Press
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
_version_ 1844614164845166592
score 13.070432

Publicaciones similares