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Register a new userGaia-ESO Survey: The analysis of high-resolution UVES spectra of FGK-type stars
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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.
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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~20,000) GIRAFFE spectrograph and the high resolution (R~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, performs automatically 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~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 (~0.9 km s^-1) and to the radial velocities of the standard stars (~0.5 kms^-1) retrieved from the literature. This bias will be corrected in the future data releases, when a common zero point for all the setups and instruments used for the survey will be established.
We present a high resolution synthetic spectral library, INTRIGOSS, designed for studying FGK stars. The library is based on atmosphere models computed with specified individual element abundances via ATLAS12 code. Normalized SPectra (NSP) and surface Flux SPectra (FSP), in the 4830-5400 A, wavelength range, were computed with the SPECTRUM code. INTRIGOSS uses the solar composition by Grevesse et al. 2007 and four [alpha/Fe] abundance ratios and consists of 15,232 spectra. The synthetic spectra are computed with astrophysical gf-values derived by comparing synthetic predictions with a very high SNR solar spectrum and the UVES-U580 spectra of five cool giants. The validity of the NSPs is assessed by using the UVES-U580 spectra of 2212 stars observed in the framework of the Gaia-ESO Survey and characterized by homogeneous and accurate atmospheric parameter values and by detailed chemical compositions. The greater accuracy of NSPs with respect to spectra from the AMBRE, GES_Grid, PHOENIX, C14, and B17 synthetic spectral libraries is demonstrated by evaluating the consistency of the predictions of the different libraries for the UVES-U580 sample stars. The validity of the FSPs is checked by comparing their prediction with both observed spectral energy distribution and spectral indices. The comparison of FSPs with SEDs derived from ELODIE, INDO--U.S., and MILES libraries indicates that the former reproduce the observed flux distributions within a few percent and without any systematic trend. The good agreement between observational and synthetic Lick/SDSS indices shows that the predicted blanketing of FSPs well reproduces the observed one, thus confirming the reliability of INTRIGOSS FSPs.
The extensive stellar spectroscopic datasets that are available for studies in Galactic Archeaology thanks to, for example, the Gaia-ESO Survey, now benefit from having a significant number of targets that overlap with asteroseismology projects such as Kepler, K2 and CoRoT. Combining the measurements from spectroscopy and asteroseismology allows us to attain greater accuracy with regard to the stellar parameters needed to characterise the stellar populations of the Milky Way. The aim of this Gaia-ESO Survey special project is to produce a catalogue of self-consistent stellar parameters by combining measurements from high-resolution spectroscopy and precision asteroseismology. We carried out an iterative analysis of 90 K2@Gaia-ESO red giants. The spectroscopic values of Teff were used as input in the seismic analysis to obtain log(g) values. The seismic estimates of log(g) were then used to re-determine the spectroscopic values of Teff and [Fe/H]. Only one iteration was required to obtain parameters that are in good agreement for both methods and thus, to obtain the final stellar parameters. A detailed analysis of outliers was carried out to ensure a robust determination of the parameters. The results were then combined with Gaia DR2 data to compare the seismic log(g) with a parallax-based log(g) and to investigate instances of variations in the velocity and possible binaries within the dataset. This analysis produced a high-quality catalogue of stellar parameters for 90 red giant stars observed by both K2 and Gaia-ESO that were determined through iterations between spectroscopy and asteroseismology. We compared the seismic gravities with those based on Gaia parallaxes to find an offset which is similar to other studies that have used asteroseismology. Our catalogue also includes spectroscopic chemical abundances and radial velocities, as well as indicators for possible binary detections.
This paper describes the analysis of UVES and GIRAFFE spectra acquired by the Gaia-ESO Public Spectroscopic Survey in the fields of young clusters whose population includes pre-main sequence (PMS) stars. Both methods that have been extensively used in the past and new ones developed in the contest of the Gaia-ESO survey enterprise are available and used. The internal precision of these quantities is estimated by inter-comparing the results obtained by such different methods, while the accuracy is estimated by comparison with independent external data, like effective temperature and surface gravity derived from angular diameter measurements, on a sample of benchmarks stars. Specific strategies are implemented to deal with fast rotation, accretion signatures, chromospheric activity, and veiling. The analysis carried out on spectra acquired in young clusters fields during the first 18 months of observations, up to June 2013, is presented in preparation of the first release of advanced data products. Stellar parameters obtained with the higher resolution and larger wavelength coverage from UVES are reproduced with comparable accuracy and precision using the smaller wavelength range and lower resolution of the GIRAFFE setup adopted for young stars, which allows us to provide with confidence stellar parameters for the much larger GIRAFFE sample. Precisions are estimated to be $approx$ 120 K r.m.s. in Teff, $approx$0.3 dex r.m.s. in logg, and $approx$0.15 dex r.m.s. in [Fe/H], for both the UVES and GIRAFFE setups.
With the purpose of assessing classic spectroscopic methods on high-resolution and high signal-to-noise ratio spectra in the near-infrared wavelength region, we selected a sample of 65 F-, G-, and K-type stars observed with CARMENES, the new, ultra-stable, double-channel spectrograph at the 3.5 m Calar Alto telescope. We computed their stellar atmospheric parameters ($T_{rm eff}$, $log{g}$, $xi$, and [Fe/H]) by means of the StePar code, a Python implementation of the equivalent width method that employs the 2017 version of the MOOG code and a grid of MARCS model atmospheres. We compiled four Fe I and Fe II line lists suited to metal-rich dwarfs, metal-poor dwarfs, metal-rich giants, and metal-poor giants that cover the wavelength range from 5300 to 17100 angstroms, thus substantially increasing the number of identified Fe I and Fe II lines up to 653 and 23, respectively. We examined the impact of the near-infrared Fe I and Fe II lines upon our parameter determinations after an exhaustive literature search, placing special emphasis on the 14 $Gaia$ benchmark stars contained in our sample. Even though our parameter determinations remain in good agreement with the literature values, the increase in the number of Fe I and Fe II lines when the near-infrared region is taken into account reveals a deeper $T_{rm eff}$ scale that might stem from a higher sensitivity of the near-infrared lines to $T_{rm eff}$.
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