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dc.contributor.authorSantiago, Basilio Xavierpt_BR
dc.contributor.authorBrauer, Dorothéept_BR
dc.contributor.authorAnders, Friedrichpt_BR
dc.contributor.authorChiappini, C.C.M.pt_BR
dc.contributor.authorQueiroz, Anna Bárbara de Andradept_BR
dc.contributor.authorGirardi, Leo Albertopt_BR
dc.contributor.authorRocha-Pinto, H.J.pt_BR
dc.contributor.authorBalbinot, Eduardopt_BR
dc.contributor.authorCosta, Luiz N. dapt_BR
dc.contributor.authorMaia, Marcio Antonio Geimbapt_BR
dc.contributor.authorSchultheis, Mathiaspt_BR
dc.contributor.authorSteinmetz, M.pt_BR
dc.contributor.authorMiglio, Andreapt_BR
dc.contributor.authorMontalbán, Josefinapt_BR
dc.contributor.authorSchneider, D.P.pt_BR
dc.contributor.authorBeers, T.C.pt_BR
dc.contributor.authorFrinchaboy, P.M.pt_BR
dc.contributor.authorLee, Y.S.pt_BR
dc.contributor.authorZasowski, G.pt_BR
dc.date.accessioned2016-12-07T02:26:26Zpt_BR
dc.date.issued2016pt_BR
dc.identifier.issn0004-6361pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/150006pt_BR
dc.description.abstractContext. Determining distances to individual field stars is a necessary step towards mapping Galactic structure and determining spatial variations in the chemo-dynamical properties of stellar populations in the Milky Way. Aims. In order to provide stellar distance estimates for various spectroscopic surveys, we have developed a code that estimates distances to stars using measured spectroscopic and photometric quantities. We employ a Bayesian approach to build the probability distribution function over stellar evolutionary models given these data, delivering estimates of model parameters (including distances) for each star individually. Our method provides several alternative distance estimates for each star in the output, along with their associated uncertainties. This facilitates the use of our method even in the absence of some measurements. Methods. The code was first tested on simulations, successfully recovering input distances to mock stars with .1% bias. We found the uncertainties scale with the uncertainties in the adopted spectro-photometric parameters. The method-intrinsic random distance uncertainties for typical spectroscopic survey measurements amount to around 10% for dwarf stars and 20% for giants, and are most sensitive to the quality of log g measurements. Results. The code was then validated by comparing our distance estimates to parallax measurements from the Hipparcos mission for nearby stars (<300 pc), to asteroseismic distances of CoRoT red giant stars, and to known distances of well-studied open and globular clusters. The photometric data of these reference samples cover both optical and infrared wavelengths. The spectroscopic parameters are also based on spectra taken at various wavelengths, with varying spectral coverage and resolution: the Sloan Digital Sky Survey programs SEGUE and APOGEE, as well as various ESO instruments Conclusions. External comparisons confirm that our distances are subject to very small systematic biases with respect to the fundamental Hipparcos scale (+0:4% for dwarfs, and +1:6% for giants). The typical random distance scatter is 18% for dwarfs, and 26% for giants. For the CoRoT-APOGEE sample, which spans Galactocentric distances of 4􀀀14 kpc, the typical random distance scatter is '15% both for the nearby and farther data. Our distances are systematically larger than the CoRoT distances by about +9%, which can mostly be attributed to the di erent choice of priors. The comparison to known distances of star clusters from SEGUE and APOGEE has led to significant systematic di erences for many cluster stars, but with opposite signs and substantial scatter. Finally, we tested our distances against those previously determined for a high-quality sample of giant stars from the RAVE survey, again finding a small systematic trend of +5% and an rms scatter of 30%. E orts are underway to provide our code to the community by running it on a public server.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofAstronomy and astrophysics. Les Ulis. Vol. 585 (Jan. 2016), A42, 15 p.pt_BR
dc.rightsOpen Accessen
dc.subjectEspectrofotometriapt_BR
dc.subjectStars: distancesen
dc.subjectGalaxy: structureen
dc.subjectModelos estatísticospt_BR
dc.subjectMapeamentos astronômicospt_BR
dc.subjectStars: statisticsen
dc.subjectMethods: statisticalen
dc.subjectSurveysen
dc.titleSpectro-photometric distances to stars : a general purpose Bayesian approachpt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001004677pt_BR
dc.type.originEstrangeiropt_BR


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