Hunting for open clusters in Gaia DR2: 582 new OCs in the Galactic disc

Abstract Context. Open clusters are key targets for studies of Galaxy structure and evolution, and stellar physics. Since the Gaia data release 2 (DR2), the discovery of undetected clusters has shown that previous surveys were incomplete. Aims. Our aim is to exploit the Big Data capabilities of mach...

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Authors: Castro Ginard, Alfred, Jordi i Nebot, Carme, Luri Carrascoso, Xavier, Álvarez Cid-Fuentes, J., Casamiquela, Laia, Anders, Friedrich, Cantat Gaudin, Tristan, Monguió i Montells, Maria, Balaguer Núñez, María de los Dolores, Solà, S., Badia, Rosa M.
Format: article
Status:Published version
Publication Date:2020
Country:España
Institution:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repository:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/161894
Online Access:https://hdl.handle.net/2445/161894
Access Level:Open access
Keyword:Astrometria
Cúmuls d'estels
Astrometry
Clusters of stars
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spelling Hunting for open clusters in Gaia DR2: 582 new OCs in the Galactic discCastro Ginard, AlfredJordi i Nebot, CarmeLuri Carrascoso, XavierÁlvarez Cid-Fuentes, J.Casamiquela, LaiaAnders, FriedrichCantat Gaudin, TristanMonguió i Montells, MariaBalaguer Núñez, María de los DoloresSolà, S.Badia, Rosa M.AstrometriaCúmuls d'estelsAstrometryClusters of starsAbstract Context. Open clusters are key targets for studies of Galaxy structure and evolution, and stellar physics. Since the Gaia data release 2 (DR2), the discovery of undetected clusters has shown that previous surveys were incomplete. Aims. Our aim is to exploit the Big Data capabilities of machine learning to detect new open clusters in Gaia DR2, and to complete the open cluster sample to enable further studies of the Galactic disc. Methods. We use a machine-learning based methodology to systematically search the Galactic disc for overdensities in the astrometric space and identify the open clusters using photometric information. First, we used an unsupervised clustering algorithm, DBSCAN, to blindly search for these overdensities in Gaia DR2 (l, b, ϖ, μα*, μδ), and then we used a deep learning artificial neural network trained on colour-magnitude diagrams to identify isochrone patterns in these overdensities, and to confirm them as open clusters. Results. We find 582 new open clusters distributed along the Galactic disc in the region |b| < 20°. We detect substructure in complex regions, and identify the tidal tails of a disrupting cluster UBC 274 of ∼3 Gyr located at ∼2 kpc. Conclusions. Adapting the mentioned methodology to a Big Data environment allows us to target the search using the physical properties of open clusters instead of being driven by computational limitations. This blind search for open clusters in the Galactic disc increases the number of known open clusters by 45%.EDP Sciences2020202020202020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion11 p.application/pdfapplication/pdfhttps://hdl.handle.net/2445/161894Articles publicats en revistes (Física Quàntica i Astrofísica)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.1051/0004-6361/201937386Astronomy & Astrophysics, 2020, vol. 635, num. A45https://doi.org/10.1051/0004-6361/201937386(c) The European Southern Observatory (ESO), 2020info:eu-repo/semantics/openAccessoai:recercat.cat:2445/1618942026-05-29T05:05:01Z
dc.title.none.fl_str_mv Hunting for open clusters in Gaia DR2: 582 new OCs in the Galactic disc
title Hunting for open clusters in Gaia DR2: 582 new OCs in the Galactic disc
spellingShingle Hunting for open clusters in Gaia DR2: 582 new OCs in the Galactic disc
Castro Ginard, Alfred
Astrometria
Cúmuls d'estels
Astrometry
Clusters of stars
title_short Hunting for open clusters in Gaia DR2: 582 new OCs in the Galactic disc
title_full Hunting for open clusters in Gaia DR2: 582 new OCs in the Galactic disc
title_fullStr Hunting for open clusters in Gaia DR2: 582 new OCs in the Galactic disc
title_full_unstemmed Hunting for open clusters in Gaia DR2: 582 new OCs in the Galactic disc
title_sort Hunting for open clusters in Gaia DR2: 582 new OCs in the Galactic disc
dc.creator.none.fl_str_mv Castro Ginard, Alfred
Jordi i Nebot, Carme
Luri Carrascoso, Xavier
Álvarez Cid-Fuentes, J.
Casamiquela, Laia
Anders, Friedrich
Cantat Gaudin, Tristan
Monguió i Montells, Maria
Balaguer Núñez, María de los Dolores
Solà, S.
Badia, Rosa M.
author Castro Ginard, Alfred
author_facet Castro Ginard, Alfred
Jordi i Nebot, Carme
Luri Carrascoso, Xavier
Álvarez Cid-Fuentes, J.
Casamiquela, Laia
Anders, Friedrich
Cantat Gaudin, Tristan
Monguió i Montells, Maria
Balaguer Núñez, María de los Dolores
Solà, S.
Badia, Rosa M.
author_role author
author2 Jordi i Nebot, Carme
Luri Carrascoso, Xavier
Álvarez Cid-Fuentes, J.
Casamiquela, Laia
Anders, Friedrich
Cantat Gaudin, Tristan
Monguió i Montells, Maria
Balaguer Núñez, María de los Dolores
Solà, S.
Badia, Rosa M.
author2_role author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Astrometria
Cúmuls d'estels
Astrometry
Clusters of stars
topic Astrometria
Cúmuls d'estels
Astrometry
Clusters of stars
description Abstract Context. Open clusters are key targets for studies of Galaxy structure and evolution, and stellar physics. Since the Gaia data release 2 (DR2), the discovery of undetected clusters has shown that previous surveys were incomplete. Aims. Our aim is to exploit the Big Data capabilities of machine learning to detect new open clusters in Gaia DR2, and to complete the open cluster sample to enable further studies of the Galactic disc. Methods. We use a machine-learning based methodology to systematically search the Galactic disc for overdensities in the astrometric space and identify the open clusters using photometric information. First, we used an unsupervised clustering algorithm, DBSCAN, to blindly search for these overdensities in Gaia DR2 (l, b, ϖ, μα*, μδ), and then we used a deep learning artificial neural network trained on colour-magnitude diagrams to identify isochrone patterns in these overdensities, and to confirm them as open clusters. Results. We find 582 new open clusters distributed along the Galactic disc in the region |b| < 20°. We detect substructure in complex regions, and identify the tidal tails of a disrupting cluster UBC 274 of ∼3 Gyr located at ∼2 kpc. Conclusions. Adapting the mentioned methodology to a Big Data environment allows us to target the search using the physical properties of open clusters instead of being driven by computational limitations. This blind search for open clusters in the Galactic disc increases the number of known open clusters by 45%.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/161894
url https://hdl.handle.net/2445/161894
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1051/0004-6361/201937386
Astronomy & Astrophysics, 2020, vol. 635, num. A45
https://doi.org/10.1051/0004-6361/201937386
dc.rights.none.fl_str_mv (c) The European Southern Observatory (ESO), 2020
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) The European Southern Observatory (ESO), 2020
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 11 p.
application/pdf
application/pdf
dc.publisher.none.fl_str_mv EDP Sciences
publisher.none.fl_str_mv EDP Sciences
dc.source.none.fl_str_mv Articles publicats en revistes (Física Quàntica i Astrofísica)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869408846162690048
score 15,811543

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