期刊
ASTRONOMY & ASTROPHYSICS
卷 614, 期 -, 页码 -出版社
EDP SCIENCES S A
DOI: 10.1051/0004-6361/201732327
关键词
methods: data analysis; methods: statistical; techniques: photometric; dust, extinction; stars: fundamental parameters
资金
- Centre National detudes Spatiales (CNES)
- National Aeronautics and Space Administration
- National Science Foundation
- Alfred P. Sloan Foundation
- U.S. Department of Energy Office of Science
- Center for High-Performance Computing at the University of Utah
- National Development and Reform Commission
- Brazilian Participation Group
- Carnegie Institution for Science
- Carnegie Mellon University
- Chilean Participation Group
- French Participation Group
- Harvard-Smithsonian Center for Astrophysics
- Instituto de Astrofisica de Canarias
- Johns Hopkins University
- Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo
- Lawrence Berkeley National Laboratory
- Leibniz Institut fur Astrophysik Potsdam (AIP)
- Max-Planck-Institut fur Astronomie (MPIA Heidelberg)
- Max-Planck-Institut fur Astrophysik (MPA Garching)
- Max-Planck-Institut fur Extraterrestrische Physik (MPE)
- National Astronomical Observatories of China, New Mexico State University
- New York University
- University of Notre Dame
- Observatario Nacional/MCTI
- Ohio State University
- Pennsylvania State University
- Shanghai Astronomical Observatory
- United Kingdom Participation Group
- Universidad Nacional Autonoma de Mexico
- University of Arizona
- University of Colorado Boulder
- University of Oxford
- University of Portsmouth
- University of Utah
- University of Virginia
- University of Washington
- University of Wisconsin
- Vanderbilt University
- Yale University
Context. The first Gaia data release unlocked the access to photometric information for 1.1 billion sources in the G-band. Yet, given the high level of degeneracy between extinction and spectral energy distribution for large passbands such as the Gaia G-band, a correction for the interstellar reddening is needed in order to exploit Gaia data. Aims. The purpose of this manuscript is to provide the empirical estimation of the Gaia G-band extinction coefficient k(G) for both the red giants and main sequence stars in order to be able to exploit the first data release DR1. Methods. We selected two samples of single stars: one for the red giants and one for the main sequence. Both samples are the result of a cross-match between Gaia DR1 and 2MASS catalogues; they consist of high-quality photometry in the G-, J- and KS-bands. These samples were complemented by temperature and metallicity information retrieved from APOGEE DR13 and LAMOST DR2 surveys, respectively. We implemented a Markov chain Monte Carlo method where we used (G - K-S)(0) versus T-eff and (J - K-S)(0) versus (G - K-S)(0) calibration relations to estimate the extinction coefficient kG and we quantify its corresponding confidence interval via bootstrap resampling. We tested our method on samples of red giants and main sequence stars, finding consistent solutions. Results. We present here the determination of the Gaia extinction coefficient through a completely empirical method. Furthermore we provide the scientific community with a formula for measuring the extinction coefficient as a function of stellar effective temperature, the intrinsic colour (G - K-S)(0), and absorption.
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