Gaia FGK benchmark stars: opening the black box of stellar element abundance determination

¹ Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK
e-mail: pjofre@ast.cam.ac.uk
² Núcleo de Astronomía, Facultad de Ingeniería, Universidad Diego Portales, Av. Ejército 441, Santiago, Chile
³ Department of Physics and Astronomy, Uppsala University, Box 516, 75120 Uppsala, Sweden
⁴ Observatoire de Genève, Université de Genève, 1290 Versoix, Switzerland
⁵ Laboratoire d’Astrophysique de Bordeaux, Univ. Bordeaux, CNRS, UMR 5804, 33615 Pessac, France
⁶ Department of Astronomy, Columbia University, 550 W 120th St, New York, NY 10027, USA
⁷ Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto, CAUP, Rua das Estrelas, 4150-762 Porto, Portugal
⁸ Max-Planck Institute for Astronomy, 69117 Heidelberg, Germany
⁹ Departament d’Astronomia i Meteorologia, Universitat de Barcelona, ICC/IEEC, 08007 Barcelona, Spain
¹⁰ Dpto. Astrofísica, Facultad de CC. Físicas, Universidad Complutense de Madrid, 28040 Madrid, Spain

Received: 3 October 2016
Accepted: 15 December 2016

Abstract

Gaia and its complementary spectroscopic surveys combined will yield the most comprehensive database of kinematic and chemical information of stars in the Milky Way. The Gaia FGK benchmark stars play a central role in this matter as they are calibration pillars for the atmospheric parameters and chemical abundances for various surveys. The spectroscopic analyses of the benchmark stars are done by combining different methods, and the results will be affected by the systematic uncertainties inherent in each method. In this paper, we explore some of these systematic uncertainties. We determined line abundances of Ca, Cr, Mn and Co for four benchmark stars using six different methods. We changed the default input parameters of the different codes in a systematic way and found, in some cases, significant differences between the results. Since there is no consensus on the correct values for many of these default parameters, we urge the community to raise discussions towards standard input parameters that could alleviate the difference in abundances obtained by different methods. In this work, we provide quantitative estimates of uncertainties in elemental abundances due to the effect of differing technical assumptions in spectrum modelling.