Automated classification of eclipsing binary systems in the VVV Survey

Autores
Daza Perilla, Ingrid Vanessa; Gramajo, Luciana Veronica; Lares Harbin Latorre, Marcelo; Palma, Tali; Ferreira Lopes, C. E.; Minniti, D.; Claria Olmedo, Juan Jose
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
With the advent of large-scale photometric surveys of the sky, modern science witnesses the dawn of big data astronomy, where automatic handling and discovery are paramount. In this context, classification tasks are among the key capabilities a data reduction pipeline must possess in order to compile reliable data sets, to accomplish data processing with an efficiency level impossible to achieve by means of detailed processing and human intervention. The VISTA Variables of the Vía Láctea Survey, in the southern part of the Galactic disc, comprises multiepoch photometric data necessary for the potential discovery of variable objects, including eclipsing binary systems (EBs). In this study, we use a recently published catalogue of one hundred EBs, classified by fine-tuning theoretical models according to contact, detached, or semidetached classes belonging to the tile d040 of the VVV. We describe the method implemented to obtain a supervised machine-learning model, capable of classifying EBs using information extracted from the light curves of variable object candidates in the phase space from tile d078. We also discuss the efficiency of the models, the relative importance of the features and the future prospects to construct an extensive data base of EBs in the VVV survey.
Fil: Daza Perilla, Ingrid Vanessa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; Argentina
Fil: Gramajo, Luciana Veronica. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Lares Harbin Latorre, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; Argentina
Fil: Palma, Tali. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Ferreira Lopes, C. E.. Universidad de Atacama.; Chile
Fil: Minniti, D.. Universidad Andrés Bello; Chile
Fil: Claria Olmedo, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; Argentina
Materia
BINARIES: ECLIPSING
INFRARED: STARS
METHODS: DATA ANALYSIS
METHODS: STATISTICAL
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:11336/222684
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Automated classification of eclipsing binary systems in the VVV SurveyDaza Perilla, Ingrid VanessaGramajo, Luciana VeronicaLares Harbin Latorre, MarceloPalma, TaliFerreira Lopes, C. E.Minniti, D.Claria Olmedo, Juan JoseBINARIES: ECLIPSINGINFRARED: STARSMETHODS: DATA ANALYSISMETHODS: STATISTICALhttps://purl.org/becyt/ford/1.7https://purl.org/becyt/ford/1With the advent of large-scale photometric surveys of the sky, modern science witnesses the dawn of big data astronomy, where automatic handling and discovery are paramount. In this context, classification tasks are among the key capabilities a data reduction pipeline must possess in order to compile reliable data sets, to accomplish data processing with an efficiency level impossible to achieve by means of detailed processing and human intervention. The VISTA Variables of the Vía Láctea Survey, in the southern part of the Galactic disc, comprises multiepoch photometric data necessary for the potential discovery of variable objects, including eclipsing binary systems (EBs). In this study, we use a recently published catalogue of one hundred EBs, classified by fine-tuning theoretical models according to contact, detached, or semidetached classes belonging to the tile d040 of the VVV. We describe the method implemented to obtain a supervised machine-learning model, capable of classifying EBs using information extracted from the light curves of variable object candidates in the phase space from tile d078. We also discuss the efficiency of the models, the relative importance of the features and the future prospects to construct an extensive data base of EBs in the VVV survey.Fil: Daza Perilla, Ingrid Vanessa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: Gramajo, Luciana Veronica. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Lares Harbin Latorre, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: Palma, Tali. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Ferreira Lopes, C. E.. Universidad de Atacama.; ChileFil: Minniti, D.. Universidad Andrés Bello; ChileFil: Claria Olmedo, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; ArgentinaWiley Blackwell Publishing, Inc2023-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/222684Daza Perilla, Ingrid Vanessa; Gramajo, Luciana Veronica; Lares Harbin Latorre, Marcelo; Palma, Tali; Ferreira Lopes, C. E.; et al.; Automated classification of eclipsing binary systems in the VVV Survey; Wiley Blackwell Publishing, Inc; Monthly Notices of the Royal Astronomical Society; 520; 1; 3-2023; 828-8380035-8711CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/mnras/article/520/1/828/6988196info:eu-repo/semantics/altIdentifier/doi/10.1093/mnras/stad141info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:09:18Zoai:ri.conicet.gov.ar:11336/222684instacron: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 10:09:18.648CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Automated classification of eclipsing binary systems in the VVV Survey
title Automated classification of eclipsing binary systems in the VVV Survey
spellingShingle Automated classification of eclipsing binary systems in the VVV Survey
Daza Perilla, Ingrid Vanessa
BINARIES: ECLIPSING
INFRARED: STARS
METHODS: DATA ANALYSIS
METHODS: STATISTICAL
title_short Automated classification of eclipsing binary systems in the VVV Survey
title_full Automated classification of eclipsing binary systems in the VVV Survey
title_fullStr Automated classification of eclipsing binary systems in the VVV Survey
title_full_unstemmed Automated classification of eclipsing binary systems in the VVV Survey
title_sort Automated classification of eclipsing binary systems in the VVV Survey
dc.creator.none.fl_str_mv Daza Perilla, Ingrid Vanessa
Gramajo, Luciana Veronica
Lares Harbin Latorre, Marcelo
Palma, Tali
Ferreira Lopes, C. E.
Minniti, D.
Claria Olmedo, Juan Jose
author Daza Perilla, Ingrid Vanessa
author_facet Daza Perilla, Ingrid Vanessa
Gramajo, Luciana Veronica
Lares Harbin Latorre, Marcelo
Palma, Tali
Ferreira Lopes, C. E.
Minniti, D.
Claria Olmedo, Juan Jose
author_role author
author2 Gramajo, Luciana Veronica
Lares Harbin Latorre, Marcelo
Palma, Tali
Ferreira Lopes, C. E.
Minniti, D.
Claria Olmedo, Juan Jose
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv BINARIES: ECLIPSING
INFRARED: STARS
METHODS: DATA ANALYSIS
METHODS: STATISTICAL
topic BINARIES: ECLIPSING
INFRARED: STARS
METHODS: DATA ANALYSIS
METHODS: STATISTICAL
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.7
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv With the advent of large-scale photometric surveys of the sky, modern science witnesses the dawn of big data astronomy, where automatic handling and discovery are paramount. In this context, classification tasks are among the key capabilities a data reduction pipeline must possess in order to compile reliable data sets, to accomplish data processing with an efficiency level impossible to achieve by means of detailed processing and human intervention. The VISTA Variables of the Vía Láctea Survey, in the southern part of the Galactic disc, comprises multiepoch photometric data necessary for the potential discovery of variable objects, including eclipsing binary systems (EBs). In this study, we use a recently published catalogue of one hundred EBs, classified by fine-tuning theoretical models according to contact, detached, or semidetached classes belonging to the tile d040 of the VVV. We describe the method implemented to obtain a supervised machine-learning model, capable of classifying EBs using information extracted from the light curves of variable object candidates in the phase space from tile d078. We also discuss the efficiency of the models, the relative importance of the features and the future prospects to construct an extensive data base of EBs in the VVV survey.
Fil: Daza Perilla, Ingrid Vanessa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; Argentina
Fil: Gramajo, Luciana Veronica. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Lares Harbin Latorre, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; Argentina
Fil: Palma, Tali. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Ferreira Lopes, C. E.. Universidad de Atacama.; Chile
Fil: Minniti, D.. Universidad Andrés Bello; Chile
Fil: Claria Olmedo, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; Argentina
description With the advent of large-scale photometric surveys of the sky, modern science witnesses the dawn of big data astronomy, where automatic handling and discovery are paramount. In this context, classification tasks are among the key capabilities a data reduction pipeline must possess in order to compile reliable data sets, to accomplish data processing with an efficiency level impossible to achieve by means of detailed processing and human intervention. The VISTA Variables of the Vía Láctea Survey, in the southern part of the Galactic disc, comprises multiepoch photometric data necessary for the potential discovery of variable objects, including eclipsing binary systems (EBs). In this study, we use a recently published catalogue of one hundred EBs, classified by fine-tuning theoretical models according to contact, detached, or semidetached classes belonging to the tile d040 of the VVV. We describe the method implemented to obtain a supervised machine-learning model, capable of classifying EBs using information extracted from the light curves of variable object candidates in the phase space from tile d078. We also discuss the efficiency of the models, the relative importance of the features and the future prospects to construct an extensive data base of EBs in the VVV survey.
publishDate 2023
dc.date.none.fl_str_mv 2023-03
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/11336/222684
Daza Perilla, Ingrid Vanessa; Gramajo, Luciana Veronica; Lares Harbin Latorre, Marcelo; Palma, Tali; Ferreira Lopes, C. E.; et al.; Automated classification of eclipsing binary systems in the VVV Survey; Wiley Blackwell Publishing, Inc; Monthly Notices of the Royal Astronomical Society; 520; 1; 3-2023; 828-838
0035-8711
CONICET Digital
CONICET
url http://hdl.handle.net/11336/222684
identifier_str_mv Daza Perilla, Ingrid Vanessa; Gramajo, Luciana Veronica; Lares Harbin Latorre, Marcelo; Palma, Tali; Ferreira Lopes, C. E.; et al.; Automated classification of eclipsing binary systems in the VVV Survey; Wiley Blackwell Publishing, Inc; Monthly Notices of the Royal Astronomical Society; 520; 1; 3-2023; 828-838
0035-8711
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/mnras/article/520/1/828/6988196
info:eu-repo/semantics/altIdentifier/doi/10.1093/mnras/stad141
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
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
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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