Classification of Chandra X-Ray Sources in Cygnus OB2

Autores
Kashyap, Vinay L.; Guarcello, Mario G.; Wright, Nicholas J.; Drake, Jeremy J.; Flaccomio, Ettore; Aldcroft, Tom L.; Albacete Colombo, Juan Facundo; Briggs, Kevin; Damiani, Francesco; Drew, Janet E.; Martin, Eduardo L.; Giusi, Micela; Naylor, Tim; Sciortino, Salvatore
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We have devised a predominantly Naive Bayes−based method to classify X-ray sources detected by Chandra in the Cygnus OB2 association into members, foreground objects, and background objects. We employ a variety of X-ray, optical, and infrared characteristics to construct likelihoods using training sets defined by well-measured sources. Combinations of optical photometry from the Sloan Digital Sky Survey (riz) and Isaac Newton Telescope Photometric Hα Survey (rIiIHα), infrared magnitudes from United Kingdom Infrared Telescope Deep Sky Survey and Two-Micron All Sky Survey (JHK ), X-ray quantiles and hardness ratios, and estimates of extinction Av are used to compute the relative probabilities that a given source belongs to one of the classes. Principal component analysis is used to isolate the best axes for separating the classes for the photometric data, and Gaussian component separation is used for X-ray hardness and extinction. Errors in the measurements are accounted for by modeling as Gaussians and integrating over likelihoods approximated as quartic polynomials. We evaluate the accuracy of the classification by inspection and reclassify a number of sources based on infrared magnitudes, the presence of disks, and spectral hardness induced by flaring. We also consider systematic errors due to extinction. Of the 7924 X-ray detections, 5501 have a total of 5597 optical/infrared matches, including 78 with multiple counterparts. We find that ≈6100 objects are likely association members, ≈1400 are background objects, and ≈500 are foreground objects, with an accuracy of 96%, 93%, and 80%, respectively, with an overall classification accuracy of approximately 95%.
Fil: Kashyap, Vinay L.. Harvard-Smithsonian Center for Astrophysics; Estados Unidos
Fil: Guarcello, Mario G.. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; Italia
Fil: Wright, Nicholas J.. Keele University.; Reino Unido
Fil: Drake, Jeremy J.. Harvard-Smithsonian Center for Astrophysics; Estados Unidos
Fil: Flaccomio, Ettore. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; Italia
Fil: Aldcroft, Tom L.. Harvard-Smithsonian Center for Astrophysics; Estados Unidos
Fil: Albacete Colombo, Juan Facundo. Universidad Nacional de Rio Negro. Sede Atlantica. Departamento de Investigación en Ciencias Exactas, Naturales y de Ingenieria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; Argentina
Fil: Briggs, Kevin. Keele University.; Reino Unido
Fil: Damiani, Francesco. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; Italia
Fil: Drew, Janet E.. Harvard-Smithsonian Center for Astrophysics; Estados Unidos
Fil: Martin, Eduardo L.. No especifíca;
Fil: Giusi, Micela. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; Italia
Fil: Naylor, Tim. University of Exeter; Reino Unido
Fil: Sciortino, Salvatore. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; Italia
Materia
Star forming regions
Catalogs
Astrostatistics
Open star clusters
OB associations
X-ray stars
Standart stars
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:11336/232445
Acceder
id CONICETDig_cea3b5b81e1fdbb7a6ab634b18bf54c7
oai_identifier_str oai:ri.conicet.gov.ar:11336/232445
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Classification of Chandra X-Ray Sources in Cygnus OB2Kashyap, Vinay L.Guarcello, Mario G.Wright, Nicholas J.Drake, Jeremy J.Flaccomio, EttoreAldcroft, Tom L.Albacete Colombo, Juan FacundoBriggs, KevinDamiani, FrancescoDrew, Janet E.Martin, Eduardo L.Giusi, MicelaNaylor, TimSciortino, SalvatoreStar forming regionsCatalogsAstrostatisticsOpen star clustersOB associationsX-ray starsStandart starshttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1We have devised a predominantly Naive Bayes−based method to classify X-ray sources detected by Chandra in the Cygnus OB2 association into members, foreground objects, and background objects. We employ a variety of X-ray, optical, and infrared characteristics to construct likelihoods using training sets defined by well-measured sources. Combinations of optical photometry from the Sloan Digital Sky Survey (riz) and Isaac Newton Telescope Photometric Hα Survey (rIiIHα), infrared magnitudes from United Kingdom Infrared Telescope Deep Sky Survey and Two-Micron All Sky Survey (JHK ), X-ray quantiles and hardness ratios, and estimates of extinction Av are used to compute the relative probabilities that a given source belongs to one of the classes. Principal component analysis is used to isolate the best axes for separating the classes for the photometric data, and Gaussian component separation is used for X-ray hardness and extinction. Errors in the measurements are accounted for by modeling as Gaussians and integrating over likelihoods approximated as quartic polynomials. We evaluate the accuracy of the classification by inspection and reclassify a number of sources based on infrared magnitudes, the presence of disks, and spectral hardness induced by flaring. We also consider systematic errors due to extinction. Of the 7924 X-ray detections, 5501 have a total of 5597 optical/infrared matches, including 78 with multiple counterparts. We find that ≈6100 objects are likely association members, ≈1400 are background objects, and ≈500 are foreground objects, with an accuracy of 96%, 93%, and 80%, respectively, with an overall classification accuracy of approximately 95%.Fil: Kashyap, Vinay L.. Harvard-Smithsonian Center for Astrophysics; Estados UnidosFil: Guarcello, Mario G.. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; ItaliaFil: Wright, Nicholas J.. Keele University.; Reino UnidoFil: Drake, Jeremy J.. Harvard-Smithsonian Center for Astrophysics; Estados UnidosFil: Flaccomio, Ettore. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; ItaliaFil: Aldcroft, Tom L.. Harvard-Smithsonian Center for Astrophysics; Estados UnidosFil: Albacete Colombo, Juan Facundo. Universidad Nacional de Rio Negro. Sede Atlantica. Departamento de Investigación en Ciencias Exactas, Naturales y de Ingenieria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; ArgentinaFil: Briggs, Kevin. Keele University.; Reino UnidoFil: Damiani, Francesco. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; ItaliaFil: Drew, Janet E.. Harvard-Smithsonian Center for Astrophysics; Estados UnidosFil: Martin, Eduardo L.. No especifíca;Fil: Giusi, Micela. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; ItaliaFil: Naylor, Tim. University of Exeter; Reino UnidoFil: Sciortino, Salvatore. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; ItaliaIOP Publishing2023-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/232445Kashyap, Vinay L.; Guarcello, Mario G.; Wright, Nicholas J.; Drake, Jeremy J.; Flaccomio, Ettore; et al.; Classification of Chandra X-Ray Sources in Cygnus OB2; IOP Publishing; Astrophysical Journal Supplement Series; 269; 1; 10-2023; 1-220067-0049CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://doi.org/10.3847/1538-4365/acdd68info:eu-repo/semantics/altIdentifier/doi/10.3847/1538-4365/acdd68info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T12:11:00Zoai:ri.conicet.gov.ar:11336/232445instacron: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:34982025-10-22 12:11:00.615CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Classification of Chandra X-Ray Sources in Cygnus OB2
title Classification of Chandra X-Ray Sources in Cygnus OB2
spellingShingle Classification of Chandra X-Ray Sources in Cygnus OB2
Kashyap, Vinay L.
Star forming regions
Catalogs
Astrostatistics
Open star clusters
OB associations
X-ray stars
Standart stars
title_short Classification of Chandra X-Ray Sources in Cygnus OB2
title_full Classification of Chandra X-Ray Sources in Cygnus OB2
title_fullStr Classification of Chandra X-Ray Sources in Cygnus OB2
title_full_unstemmed Classification of Chandra X-Ray Sources in Cygnus OB2
title_sort Classification of Chandra X-Ray Sources in Cygnus OB2
dc.creator.none.fl_str_mv Kashyap, Vinay L.
Guarcello, Mario G.
Wright, Nicholas J.
Drake, Jeremy J.
Flaccomio, Ettore
Aldcroft, Tom L.
Albacete Colombo, Juan Facundo
Briggs, Kevin
Damiani, Francesco
Drew, Janet E.
Martin, Eduardo L.
Giusi, Micela
Naylor, Tim
Sciortino, Salvatore
author Kashyap, Vinay L.
author_facet Kashyap, Vinay L.
Guarcello, Mario G.
Wright, Nicholas J.
Drake, Jeremy J.
Flaccomio, Ettore
Aldcroft, Tom L.
Albacete Colombo, Juan Facundo
Briggs, Kevin
Damiani, Francesco
Drew, Janet E.
Martin, Eduardo L.
Giusi, Micela
Naylor, Tim
Sciortino, Salvatore
author_role author
author2 Guarcello, Mario G.
Wright, Nicholas J.
Drake, Jeremy J.
Flaccomio, Ettore
Aldcroft, Tom L.
Albacete Colombo, Juan Facundo
Briggs, Kevin
Damiani, Francesco
Drew, Janet E.
Martin, Eduardo L.
Giusi, Micela
Naylor, Tim
Sciortino, Salvatore
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Star forming regions
Catalogs
Astrostatistics
Open star clusters
OB associations
X-ray stars
Standart stars
topic Star forming regions
Catalogs
Astrostatistics
Open star clusters
OB associations
X-ray stars
Standart stars
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 have devised a predominantly Naive Bayes−based method to classify X-ray sources detected by Chandra in the Cygnus OB2 association into members, foreground objects, and background objects. We employ a variety of X-ray, optical, and infrared characteristics to construct likelihoods using training sets defined by well-measured sources. Combinations of optical photometry from the Sloan Digital Sky Survey (riz) and Isaac Newton Telescope Photometric Hα Survey (rIiIHα), infrared magnitudes from United Kingdom Infrared Telescope Deep Sky Survey and Two-Micron All Sky Survey (JHK ), X-ray quantiles and hardness ratios, and estimates of extinction Av are used to compute the relative probabilities that a given source belongs to one of the classes. Principal component analysis is used to isolate the best axes for separating the classes for the photometric data, and Gaussian component separation is used for X-ray hardness and extinction. Errors in the measurements are accounted for by modeling as Gaussians and integrating over likelihoods approximated as quartic polynomials. We evaluate the accuracy of the classification by inspection and reclassify a number of sources based on infrared magnitudes, the presence of disks, and spectral hardness induced by flaring. We also consider systematic errors due to extinction. Of the 7924 X-ray detections, 5501 have a total of 5597 optical/infrared matches, including 78 with multiple counterparts. We find that ≈6100 objects are likely association members, ≈1400 are background objects, and ≈500 are foreground objects, with an accuracy of 96%, 93%, and 80%, respectively, with an overall classification accuracy of approximately 95%.
Fil: Kashyap, Vinay L.. Harvard-Smithsonian Center for Astrophysics; Estados Unidos
Fil: Guarcello, Mario G.. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; Italia
Fil: Wright, Nicholas J.. Keele University.; Reino Unido
Fil: Drake, Jeremy J.. Harvard-Smithsonian Center for Astrophysics; Estados Unidos
Fil: Flaccomio, Ettore. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; Italia
Fil: Aldcroft, Tom L.. Harvard-Smithsonian Center for Astrophysics; Estados Unidos
Fil: Albacete Colombo, Juan Facundo. Universidad Nacional de Rio Negro. Sede Atlantica. Departamento de Investigación en Ciencias Exactas, Naturales y de Ingenieria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; Argentina
Fil: Briggs, Kevin. Keele University.; Reino Unido
Fil: Damiani, Francesco. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; Italia
Fil: Drew, Janet E.. Harvard-Smithsonian Center for Astrophysics; Estados Unidos
Fil: Martin, Eduardo L.. No especifíca;
Fil: Giusi, Micela. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; Italia
Fil: Naylor, Tim. University of Exeter; Reino Unido
Fil: Sciortino, Salvatore. Istituto Nazionale di Astrofísica. Osservatorio Astronómico di Palermo; Italia
description We have devised a predominantly Naive Bayes−based method to classify X-ray sources detected by Chandra in the Cygnus OB2 association into members, foreground objects, and background objects. We employ a variety of X-ray, optical, and infrared characteristics to construct likelihoods using training sets defined by well-measured sources. Combinations of optical photometry from the Sloan Digital Sky Survey (riz) and Isaac Newton Telescope Photometric Hα Survey (rIiIHα), infrared magnitudes from United Kingdom Infrared Telescope Deep Sky Survey and Two-Micron All Sky Survey (JHK ), X-ray quantiles and hardness ratios, and estimates of extinction Av are used to compute the relative probabilities that a given source belongs to one of the classes. Principal component analysis is used to isolate the best axes for separating the classes for the photometric data, and Gaussian component separation is used for X-ray hardness and extinction. Errors in the measurements are accounted for by modeling as Gaussians and integrating over likelihoods approximated as quartic polynomials. We evaluate the accuracy of the classification by inspection and reclassify a number of sources based on infrared magnitudes, the presence of disks, and spectral hardness induced by flaring. We also consider systematic errors due to extinction. Of the 7924 X-ray detections, 5501 have a total of 5597 optical/infrared matches, including 78 with multiple counterparts. We find that ≈6100 objects are likely association members, ≈1400 are background objects, and ≈500 are foreground objects, with an accuracy of 96%, 93%, and 80%, respectively, with an overall classification accuracy of approximately 95%.
publishDate 2023
dc.date.none.fl_str_mv 2023-10
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/11336/232445
Kashyap, Vinay L.; Guarcello, Mario G.; Wright, Nicholas J.; Drake, Jeremy J.; Flaccomio, Ettore; et al.; Classification of Chandra X-Ray Sources in Cygnus OB2; IOP Publishing; Astrophysical Journal Supplement Series; 269; 1; 10-2023; 1-22
0067-0049
CONICET Digital
CONICET
url http://hdl.handle.net/11336/232445
identifier_str_mv Kashyap, Vinay L.; Guarcello, Mario G.; Wright, Nicholas J.; Drake, Jeremy J.; Flaccomio, Ettore; et al.; Classification of Chandra X-Ray Sources in Cygnus OB2; IOP Publishing; Astrophysical Journal Supplement Series; 269; 1; 10-2023; 1-22
0067-0049
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://doi.org/10.3847/1538-4365/acdd68
info:eu-repo/semantics/altIdentifier/doi/10.3847/1538-4365/acdd68
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 IOP Publishing
publisher.none.fl_str_mv IOP Publishing
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_ 1846782499466772480
score 12.982451

Publicaciones similares