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dc.contributor.authorSmart, Richard L.
dc.contributor.authorSarro, L. M.
dc.contributor.authorRybizki, J.
dc.contributor.authorReylé, Céline
dc.contributor.authorRobin, A. C.
dc.contributor.authorHambly, N. C.
dc.contributor.authorAbbas, U.
dc.contributor.authorBarstow, Martin Adrian
dc.contributor.authorDe Bruijne, Jos H.J.
dc.contributor.authorBucciarelli, B.
dc.contributor.authorCarrasco, J. M.
dc.contributor.authorCooper, W. J.
dc.contributor.authorHodgkin, S. T.
dc.contributor.authorMasana, E.
dc.contributor.authorMichalik, D.
dc.contributor.authorSahlmann, J.
dc.contributor.authorSozzetti, A.
dc.contributor.authorBrown, Anthony G.A.
dc.contributor.authorVallenari, Antonella
dc.contributor.authorCarballo Fidalgo, Ruth 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2022-01-14T16:33:23Z
dc.date.available2022-01-14T16:33:23Z
dc.date.issued2021
dc.identifier.issn0004-6361
dc.identifier.issn1432-0746
dc.identifier.otherESP2016-80079-C2-1-Res_ES
dc.identifier.otherESP2016-80079-C2-2-Res_ES
dc.identifier.otherRTI2018-095076-B-C21es_ES
dc.identifier.otherRTI2018-095076-B-C22es_ES
dc.identifier.otherBES-2016-078499es_ES
dc.identifier.otherBES-2017-083126es_ES
dc.identifier.otherAYA2017-89841Pes_ES
dc.identifier.otherTIN2015-65316-Pes_ES
dc.identifier.urihttp://hdl.handle.net/10902/23738
dc.description.abstractABSTRACT: Aims. We produce a clean and well-characterised catalogue of objects within 100 pc of the Sun from the Gaia Early Data Release 3. We characterise the catalogue through comparisons to the full data release, external catalogues, and simulations. We carry out a first analysis of the science that is possible with this sample to demonstrate its potential and best practices for its use. Methods. Theselection of objects within 100 pc from the full catalogue used selected training sets, machine-learning procedures, astrometric quantities, and solution quality indicators to determine a probability that the astrometric solution is reliable. The training set construction exploited the astrometric data, quality flags, and external photometry. For all candidates we calculated distance posterior probability densities using Bayesian procedures and mock catalogues to define priors. Any object with reliable astrometry and a non-zero probability of being within 100 pc is included in the catalogue. Results. We have produced a catalogue of 331 312 objects that we estimate contains at least 92% of stars of stellar type M9 within 100 pc of the Sun. We estimate that 9% of the stars in this catalogue probably lie outside 100 pc, but when the distance probability function is used, a correct treatment of this contamination is possible. We produced luminosity functions with a high signal-to-noise ratio for the main-sequence stars, giants, and white dwarfs. We examined in detail the Hyades cluster, the white dwarf population, and wide-binary systems and produced candidate lists for all three samples. We detected local manifestations of several streams, superclusters, and halo objects, in which we identified 12 members of Gaia Enceladus. We present the first direct parallaxes of five objects in multiple systems within 10 pc of the Sun. Conclusions. We provide the community with a large, well-characterised catalogue of objects in the solar neighbourhood. This is a primary benchmark for measuring and understanding fundamental parameters and descriptive functions in astronomy.es_ES
dc.description.sponsorshipThe Gaia mission and data processing have financially been supported by, in alphabetical order by the Spanish Ministry of Economy (MINECO/FEDER,UE) through grants ESP2016-80079-C2-1-R, ESP2016-80079-C2-2-R, RTI2018-095076-B-C21, RTI2018-095076-B-C22, BES-2016-078499, and BES-2017-083126 and the Juan de la Cierva formación 2015 grant FJCI-2015-2671, theSpanish Ministry of Education, Culture, and Sports through grant FPU16/03827, the Spanish Ministry of Science and Innovation (MICINN) through grant AYA2017-89841P for project “Estudio de las propiedades de los fósiles estelares en el entorno del Grupo Local” and through grant TIN2015-65316-P forproject “Computación de Altas Prestaciones VII”es_ES
dc.format.extent44 p.es_ES
dc.language.isoenges_ES
dc.publisherEDP Scienceses_ES
dc.rights© ESO 2021es_ES
dc.sourceAstronomy & Astrophysics 2021, 649, A6es_ES
dc.subject.otherCatalogses_ES
dc.subject.otherAstrometryes_ES
dc.subject.otherStars: luminosity function, mass functiones_ES
dc.subject.otherHertzsprung-Russell and C-M diagramses_ES
dc.subject.otherStars: low-masses_ES
dc.subject.otherSolar neighborhoodes_ES
dc.titleGaia Early Data Release 3: The Gaia Catalogue of Nearby Starses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1051/0004-6361/202039498es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1051/0004-6361/202039498
dc.type.versionpublishedVersiones_ES


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