Showing papers by "T. Prusti published in 2014"
TL;DR: In this paper, the Gaia-ESO Survey is obtaining high-quality spectroscopic data for about 10^5 stars using FLAMES at the VLT, which are analyzed in parallel by several state-of-the-art methodologies.
Abstract: The Gaia-ESO Survey is obtaining high-quality spectroscopic data for about 10^5 stars using FLAMES at the VLT. UVES high-resolution spectra are being collected for about 5000 FGK-type stars. These UVES spectra are analyzed in parallel by several state-of-the-art methodologies. Our aim is to present how these analyses were implemented, to discuss their results, and to describe how a final recommended parameter scale is defined. We also discuss the precision (method-to-method dispersion) and accuracy (biases with respect to the reference values) of the final parameters. These results are part of the Gaia-ESO 2nd internal release and will be part of its 1st public release of advanced data products. The final parameter scale is tied to the one defined by the Gaia benchmark stars, a set of stars with fundamental atmospheric parameters. A set of open and globular clusters is used to evaluate the physical soundness of the results. Each methodology is judged against the benchmark stars to define weights in three different regions of the parameter space. The final recommended results are the weighted-medians of those from the individual methods. The recommended results successfully reproduce the benchmark stars atmospheric parameters and the expected Teff-log g relation of the calibrating clusters. Atmospheric parameters and abundances have been determined for 1301 FGK-type stars observed with UVES. The median of the method-to-method dispersion of the atmospheric parameters is 55 K for Teff, 0.13 dex for log g, and 0.07 dex for [Fe/H]. Systematic biases are estimated to be between 50-100 K for Teff, 0.10-0.25 dex for log g, and 0.05-0.10 dex for [Fe/H]. Abundances for 24 elements were derived: C, N, O, Na, Mg, Al, Si, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Y, Zr, Mo, Ba, Nd, and Eu. The typical method-to-method dispersion of the abundances varies between 0.10 and 0.20 dex.
229 citations
European Southern Observatory1, Uppsala University2, Max Planck Society3, INAF4, Université libre de Bruxelles5, Instituto Politécnico Nacional6, Lund University7, University of Concepción8, Pontifical Catholic University of Chile9, Heidelberg University10, Millennium Institute11, University of Porto12, Complutense University of Madrid13, Vilnius University14, Leibniz Institute for Astrophysics Potsdam15, University of Cambridge16, University of La Laguna17, Spanish National Research Council18, Centre national de la recherche scientifique19, Paris Diderot University20, University of Padua21, University of Bologna22, Indiana University23, Massachusetts Institute of Technology24, University of Catania25, University of Liège26, University of Florence27, Australian National University28, University of Hertfordshire29, University of Edinburgh30, Keele University31, University of Alicante32, European Space Research and Technology Centre33, Royal Observatory of Belgium34, Valparaiso University35
TL;DR: In this article, the Gaia-ESO Public Spectroscopic Survey is using FLAMES at the VLT to obtain high-quality medium-resolution Giraffe spectra for about 10(5) stars and high-resolution UVES spectra of about 5000 stars.
Abstract: Context. The ongoing Gaia-ESO Public Spectroscopic Survey is using FLAMES at the VLT to obtain high-quality medium-resolution Giraffe spectra for about 10(5) stars and high-resolution UVES spectra for about 5000 stars. With UVES, the Survey has already observed 1447 FGK-type stars. Aims. These UVES spectra are analyzed in parallel by several state-of-the-art methodologies. Our aim is to present how these analyses were implemented, to discuss their results, and to describe how a final recommended parameter scale is defined. We also discuss the precision (method-to-method dispersion) and accuracy (biases with respect to the reference values) of the final parameters. These results are part of the Gaia-ESO second internal release and will be part of its first public release of advanced data products. Methods. The final parameter scale is tied to the scale defined by the Gaia benchmark stars, a set of stars with fundamental atmospheric parameters. In addition, a set of open and globular clusters is used to evaluate the physical soundness of the results. Each of the implemented methodologies is judged against the benchmark stars to define weights in three different regions of the parameter space. The final recommended results are the weighted medians of those from the individual methods. Results. The recommended results successfully reproduce the atmospheric parameters of the benchmark stars and the expected T-eff-log g relation of the calibrating clusters. Atmospheric parameters and abundances have been determined for 1301 FGK-type stars observed with UVES. The median of the method-to-method dispersion of the atmospheric parameters is 55K for T-eff, 0.13dex for log g and 0.07 dex for [Fe/H]. Systematic biases are estimated to be between 50-100 K for T-eff, 0.10-0.25 dex for log g and 0.05-0.10 dex for [Fe/H]. Abundances for 24 elements were derived: C, N, O, Na, Mg, Al, Si, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Y, Zr, Mo, Ba, Nd, and Eu. The typical method-to-method dispersion of the abundances varies between 0.10 and 0.20 dex. Conclusions. The Gaia-ESO sample of high-resolution spectra of FGK-type stars will be among the largest of its kind analyzed in a homogeneous way. The extensive list of elemental abundances derived in these stars will enable significant advances in the areas of stellar evolution and Milky Way formation and evolution.
222 citations
Lund University1, Spanish National Research Council2, Universidade Federal do Rio Grande do Sul3, Australian National University4, Uppsala University5, INAF6, University of Edinburgh7, Keele University8, University of Alicante9, European Space Research and Technology Centre10, Max Planck Society11, Sternberg Astronomical Institute12, University of Catania13, Instituto Politécnico Nacional14, University of Nice Sophia Antipolis15, European Southern Observatory16, Vilnius University17
TL;DR: In this article, the relationship between age, metallicity, and alpha enhancement of FGK stars in the Galactic disk was studied based on the analysis of high-resolution UVES spectra from the Gaia-ESO large stellar survey.
Abstract: We study the relationship between age, metallicity, and alpha-enhancement of FGK stars in the Galactic disk. The results are based upon the analysis of high-resolution UVES spectra from the Gaia-ESO large stellar survey. We explore the limitations of the observed dataset, i.e. the accuracy of stellar parameters and the selection effects that are caused by the photometric target preselection. We find that the colour and magnitude cuts in the survey suppress old metal-rich stars and young metal-poor stars. This suppression may be as high as 97% in some regions of the age-metallicity relationship. The dataset consists of 144 stars with a wide range of ages from 0.5 Gyr to 13.5 Gyr, Galactocentric distances from 6 kpc to 9.5 kpc, and vertical distances from the plane 0 9 Gyr is not as small as advocated by some other studies. In agreement with earlier work, we find that radial abundance gradients change as a function of vertical distance from the plane. The [Mg/Fe] gradient steepens and becomes negative. In addition, we show that the inner disk is not only more alpha-rich compared to the outer disk, but also older, as traced independently by the ages and Mg abundances of stars.
218 citations
TL;DR: In this article, the relationship between age, metallicity, and alpha enhancement of FGK stars in the Galactic disk was studied based on the analysis of high-resolution UVES spectra from the Gaia-ESO large stellar survey.
Abstract: We study the relationship between age, metallicity, and alpha-enhancement of FGK stars in the Galactic disk. The results are based upon the analysis of high-resolution UVES spectra from the Gaia-ESO large stellar survey. We explore the limitations of the observed dataset, i.e. the accuracy of stellar parameters and the selection effects that are caused by the photometric target preselection. We find that the colour and magnitude cuts in the survey suppress old metal-rich stars and young metal-poor stars. This suppression may be as high as 97% in some regions of the age-metallicity relationship. The dataset consists of 144 stars with a wide range of ages from 0.5 Gyr to 13.5 Gyr, Galactocentric distances from 6 kpc to 9.5 kpc, and vertical distances from the plane 0 9 Gyr is not as small as advocated by some other studies. In agreement with earlier work, we find that radial abundance gradients change as a function of vertical distance from the plane. The [Mg/Fe] gradient steepens and becomes negative. In addition, we show that the inner disk is not only more alpha-rich compared to the outer disk, but also older, as traced independently by the ages and Mg abundances of stars.
200 citations
INAF1, European Southern Observatory2, University of Cambridge3, Australian National University4, Paris Diderot University5, University of Hertfordshire6, Lund University7, University of Edinburgh8, Keele University9, University of Alicante10, European Space Research and Technology Centre11, Max Planck Society12, Spanish National Research Council13, University of La Laguna14, Royal Observatory of Belgium15, Uppsala University16, University of Catania17, Instituto Politécnico Nacional18, University of Nice Sophia Antipolis19, Université libre de Bruxelles20
TL;DR: In this article, the authors describe the methods and software used for the data reduction, the derivation of the radial velocities, and the quality control of the FLAMES-UVES spectra.
Abstract: The Gaia-ESO Survey is a large public spectroscopic survey that aims to derive radial velocities and fundamental parameters of about 10(5) Milky Way stars in the field and in clusters. Observations are carried out with the multi-object optical spectrograph FLAMES, using simultaneously the medium-resolution (R similar to 20 000) GIRAFFE spectrograph and the high-resolution (R similar to 47 000) UVES spectrograph. In this paper we describe the methods and the software used for the data reduction, the derivation of the radial velocities, and the quality control of the FLAMES-UVES spectra. Data reduction has been performed using a workflow specifically developed for this project. This workflow runs the ESO public pipeline optimizing the data reduction for the Gaia-ESO Survey, automatically performs sky subtraction, barycentric correction and normalisation, and calculates radial velocities and a first guess of the rotational velocities. The quality control is performed using the output parameters from the ESO pipeline, by a visual inspection of the spectra and by the analysis of the signal-to-noise ratio of the spectra. Using the observations of the first 18 months, specifically targets observed multiple times at different epochs, stars observed with both GIRAFFE and UVES, and observations of radial velocity standards, we estimated the precision and the accuracy of the radial velocities. The statistical error on the radial velocities is sigma similar to 0.4 km s(-1) and is mainly due to uncertainties in the zero point of the wavelength calibration. However, we found a systematic bias with respect to the GIRAFFE spectra (similar to 0.9 km s(-1)) and to the radial velocities of the standard stars (similar to 0.5 km s(-1)) retrieved from the literature. This bias will be corrected in the future data releases, when a common zero point for all the set-ups and instruments used for the survey is be established.
86 citations
TL;DR: In this paper, a brief overview of the Gaia Research for European Astronomy Training (GREAT) network activity plan for the period 2015-2020, aiming to support the maximisation of scientific exploitation of the data from Gaia.
Abstract: This paper gives a brief overview of the Gaia Research for European Astronomy Training (GREAT) network activity plan for the period 2015–2020, aiming to support the maximisation of scientific exploitation of the data from Gaia.