Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees

Signor, T., et al.

Detalhes bibliográficos
Autores: Signor, Theosamuele, Rodighiero, Giulia, Serrano, Santiago, Euclid Consortium
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/365786
Acesso em linha:http://hdl.handle.net/10261/365786
Access Level:acceso abierto
Palavra-chave:Methods: statistical
Galaxies: active
Galaxies: evolution
Galaxies: high-redshift
Infrared: galaxies
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network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees
title Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees
spellingShingle Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees
Signor, Theosamuele
Methods: statistical
Galaxies: active
Galaxies: evolution
Galaxies: high-redshift
Infrared: galaxies
title_short Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees
title_full Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees
title_fullStr Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees
title_full_unstemmed Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees
title_sort Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees
dc.creator.none.fl_str_mv Signor, Theosamuele
Rodighiero, Giulia
Serrano, Santiago
Euclid Consortium
author Signor, Theosamuele
author_facet Signor, Theosamuele
Rodighiero, Giulia
Serrano, Santiago
Euclid Consortium
author_role author
author2 Rodighiero, Giulia
Serrano, Santiago
Euclid Consortium
author2_role author
author
author
dc.contributor.none.fl_str_mv European Space Agency
Agenzia Spaziale Italiana
Centre National D'Etudes Spatiales (France)
Ministerio de Ciencia, Innovación y Universidades (España)
Fundação para a Ciência e a Tecnologia (Portugal)
Ministerio de Ciencia e Innovación (España)
Agencia Estatal de Investigación (España)
NASA
UK Space Agency
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Methods: statistical
Galaxies: active
Galaxies: evolution
Galaxies: high-redshift
Infrared: galaxies
topic Methods: statistical
Galaxies: active
Galaxies: evolution
Galaxies: high-redshift
Infrared: galaxies
description Signor, T., et al.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/365786
url http://hdl.handle.net/10261/365786
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://doi.org/10.1051/0004-6361/202348737
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv EDP Sciences
publisher.none.fl_str_mv EDP Sciences
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869425076904919040
spelling Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted treesSignor, TheosamueleRodighiero, GiuliaSerrano, SantiagoEuclid ConsortiumMethods: statisticalGalaxies: activeGalaxies: evolutionGalaxies: high-redshiftInfrared: galaxiesSignor, T., et al.[Context] ALMA observations show that dusty, distant, massive (M* ≳ 1011 M⊙) galaxies usually have a remarkable star-formation activity, contributing of the order of 25% of the cosmic star-formation rate density at z ≈ 3–5, and up to 30% at z ∼ 7. Nonetheless, they are elusive in classical optical surveys, and current near-IR surveys are able to detect them only in very small sky areas. Since these objects have low space densities, deep and wide surveys are necessary to obtain statistically relevant results about them. Euclid will potentially be capable of delivering the required information, but, given the lack of spectroscopic features at these distances within its bands, it is still unclear if Euclid will be able to identify and characterise these objects.[Aims] The goal of this work is to assess the capability of Euclid, together with ancillary optical and near-IR data, to identify these distant, dusty, and massive galaxies based on broadband photometry.[Methods] We used a gradient-boosting algorithm to predict both the redshift and spectral type of objects at high z. To perform such an analysis, we made use of simulated photometric observations that mimic the Euclid Deep Survey, derived using the state-of-the-art Spectro-Photometric Realizations of Infrared-selected Targets at all-z (SPRITZ) software.[Results] The gradient-boosting algorithm was found to be accurate in predicting both the redshift and spectral type of objects within the simulated Euclid Deep Survey catalogue at z > 2, while drastically decreasing the runtime with respect to spectral-energy-distribution-fitting methods. In particular, we studied the analogue of HIEROs (i.e. sources selected on the basis of a red H − [4.5]> 2.25), combining Euclid and Spitzer data at the depth of the Deep Fields. These sources include the bulk of obscured and massive galaxies in a broad redshift range, 3 < z < 7. We find that the dusty population at 3 ≲ z ≲ 7 is well identified, with a redshift root mean squared error and catastrophic outlier fraction of only 0.55 and 8.5% (HE ≤ 26), respectively. Our findings suggest that with Euclid we will obtain meaningful insights into the impact of massive and dusty galaxies on the cosmic star-formation rate over time.The Euclid Consortium acknowledges the European Space Agency and a number of agencies and institutes that have supported the development of Euclid, in particular the Academy of Finland, the Agenzia Spaziale Italiana, the Belgian Science Policy, the Canadian Euclid Consortium, the French Centre National d’Etudes Spatiales, the Deutsches Zentrum für Luft- und Raumfahrt, the Danish Space Research Institute, the Fundação para a Ciência e a Tecnologia, the Ministerio de Ciencia e Innovación, the National Aeronautics and Space Administration, the National Astronomical Observatory of Japan, the Netherlandse Onderzoekschool Voor Astronomie, the Norwegian Space Agency, the Romanian Space Agency, the State Secretariat for Education, Research and Innovation (SERI) at the Swiss Space Office (SSO), and the United Kingdom Space Agency. A complete and detailed list is available on the Euclid web site (http://www.euclid-ec.org).Peer reviewedEDP SciencesEuropean Space AgencyAgenzia Spaziale ItalianaCentre National D'Etudes Spatiales (France)Ministerio de Ciencia, Innovación y Universidades (España)Fundação para a Ciência e a Tecnologia (Portugal)Ministerio de Ciencia e Innovación (España)Agencia Estatal de Investigación (España)NASAUK Space AgencyConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202420242024info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/365786reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttps://doi.org/10.1051/0004-6361/202348737Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3657862026-05-22T06:33:51Z
score 15,811543

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