Stellar parametrization from Gaia RVS spectra

Among the myriad of data collected by the ESA Gaia satellite, about 150 million spectra will be delivered by the Radial Velocity Spectrometer (RVS) for stars as faint as G_RVS~16. A specific stellar parametrization will be performed for most of these RVS spectra. Some individual chemical abundances will also be estimated for the brightest targets. We describe the different parametrization codes that have been specifically developed or adapted for RVS spectra within the GSP-spec working group of the analysis consortium. The tested codes are based on optimization (FERRE and GAUGUIN), projection (MATISSE) or pattern recognition methods (Artificial Neural Networks). We present and discuss their expected performances in the recovered stellar atmospheric parameters (Teff, log(g), [M/H]) for B- to K- type stars. The performances for the determinations of [alpha/Fe] ratios are also presented for cool stars. For all the considered stellar types, stars brighter than G_RVS~12.5 will be very efficiently parametrized by the GSP-spec pipeline, including solid estimations of [alpha/Fe]. Typical internal errors for FGK metal-rich and metal-intermediate stars are around 40K in Teff , 0.1dex in log(g), 0.04dex in [M/H], and 0.03dex in [alpha/Fe] at G_RVS=10.3. Similar accuracies in Teff and [M/H] are found for A-type stars, while the log(g) derivation is more accurate. For the faintest stars, with G_RVS>13-14, a spectrophotometric Teff input will allow the improvement of the final GSP-spec parametrization. The reported results show that the contribution of the RVS based stellar parameters will be unique in the brighter part of the Gaia survey allowing crucial age estimations, and accurate chemical abundances. This will constitute a unique and precious sample for which many pieces of the Milky Way history puzzle will be available, with unprecedented precision and statistical relevance.

[1]  Bingqiu Chen,et al.  The LAMOST stellar parameter pipeline at Peking University – lsp3 , 2014, 1412.6627.

[2]  J. H. J. de Bruijne,et al.  Science performance of Gaia, ESA’s space-astrometry mission , 2012, 1201.3238.

[3]  W. M. Wood-Vasey,et al.  SDSS-III: MASSIVE SPECTROSCOPIC SURVEYS OF THE DISTANT UNIVERSE, THE MILKY WAY, AND EXTRA-SOLAR PLANETARY SYSTEMS , 2011, 1101.1529.

[4]  H. Rix,et al.  THE SPATIAL STRUCTURE OF MONO-ABUNDANCE SUB-POPULATIONS OF THE MILKY WAY DISK , 2011, 1111.1724.

[5]  C. Fabricius,et al.  Gaia broad band photometry , 2010, 1008.0815.

[6]  A. Bijaoui,et al.  Parameter estimation from a model grid application to the Gaia RVS spectra , 2012 .

[7]  A. Bijaoui,et al.  Automated derivation of stellar atmospheric parameters and chemical abundances: the MATISSE algorithm , 2006 .

[8]  A. Bijaoui,et al.  The AMBRE Project: Stellar parameterisation of the ESO:FEROS archived spectra , 2012, 1204.1041.

[9]  A. Recio-Blanco,et al.  Chemical tagging with Gaia-ESO Survey and Gaia-RVS data , 2013, Proceedings of the International Astronomical Union.

[10]  A. Bijaoui,et al.  Automatic stellar spectra parameterisation in the IR Ca ii triplet region , 2011, 1109.6237.

[11]  B. Yanny,et al.  A Spectroscopic Study of the Ancient Milky Way: F- and G-Type Stars in the Third Data Release of the Sloan Digital Sky Survey , 2005, astro-ph/0509812.

[12]  To Appear in ApJ Preprint typeset using L ATEX style emulateapj v. 6/22/04 THE EFFECTIVE TEMPERATURE SCALE OF FGK STARS. II. Teff: COLOR: [Fe/H] CALIBRATIONS , 2008 .

[13]  A. Bijaoui,et al.  The Gaia astrophysical parameters inference system (Apsis) - Pre-launch description , 2013, 1309.2157.

[14]  T. Beers,et al.  THE METALLICITY DISTRIBUTION FUNCTIONS OF SEGUE G AND K DWARFS: CONSTRAINTS FOR DISK CHEMICAL EVOLUTION AND FORMATION , 2011, 1112.2214.

[15]  C. Bailer-Jones,et al.  The expected performance of stellar parametrization with Gaia spectrophotometry , 2012, 1207.6005.

[16]  Nikolai Piskunov,et al.  Modelling of Stellar Atmospheres , 2003 .

[17]  L. Koesterke,et al.  Center-to-Limb Variation of Solar Three-dimensional Hydrodynamical Simulations , 2008, 0802.2177.

[18]  N. Grevesse,et al.  Standard Solar Composition , 1998 .

[19]  Carlos Dafonte,et al.  ANNs and Wavelets: A Strategy for Gaia RVS Low S/N Stellar Spectra Parameterization , 2010 .

[20]  U. Munari,et al.  The radial velocity experiment (RAVE): First data release , 2006 .

[21]  Laszlo Sturmann,et al.  STELLAR DIAMETERS AND TEMPERATURES. I. MAIN-SEQUENCE A, F, AND G STARS , 2011, 1112.3316.

[22]  Paul Barklem,et al.  A list of data for the broadening of metallic lines by neutral hydrogen collisions , 2000 .

[23]  U. Munari,et al.  THE RADIAL VELOCITY EXPERIMENT (RAVE): FOURTH DATA RELEASE , 2006, 1309.4284.

[24]  F. Castelli,et al.  Round Table Summary: Problems in Modelling Stellar Atmospheres , 2003 .

[25]  Heidi Jo Newberg,et al.  SEGUE: A SPECTROSCOPIC SURVEY OF 240,000 STARS WITH g = 14–20 , 2009, 0902.1781.

[26]  Sergey E. Koposov,et al.  The Gaia-ESO Survey: the Galactic thick to thin disc transition , 2014, 1403.7568.

[27]  Sergio Ortolani,et al.  The Gaia-ESO Public Spectroscopic Survey , 2012 .

[28]  L. Girardi,et al.  parsec: stellar tracks and isochrones with the PAdova and TRieste Stellar Evolution Code , 2012, 1208.4498.

[29]  A. Recio-Blanco,et al.  The AMBRE project: A new synthetic grid of high-resolution FGKM stellar spectra , 2012, 1205.2270.