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Title:
ZASPE: A Code to Measure Stellar Atmospheric Parameters and their Covariance from Spectra
Authors:
Brahm, Rafael; Jordán, Andrés; Hartman, Joel; Bakos, Gáspár
Affiliation:
AA(Instituto de Astrofísica, Facultad de Física, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, 7820436 Macul, Santiago, Chile.; Millennium Institute of Astrophysics, Santiago, Chile. ), AB(Instituto de Astrofísica, Facultad de Física, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, 7820436 Macul, Santiago, Chile.; Millennium Institute of Astrophysics, Santiago, Chile.), AC(Departmen of Astrophysical Sciences, Princeton University, NJ 08544, USA.), AD(Departmen of Astrophysical Sciences, Princeton University, NJ 08544, USA.; Alfred P. Sloan Research Fellow; Packard Fellow)
Publication:
Monthly Notices of the Royal Astronomical Society, Volume 467, Issue 1, p.971-984 (MNRAS Homepage)
Publication Date:
05/2017
Origin:
OUP
Astronomy Keywords:
methods: data analysis, techniques: spectroscopic, stars: fundamental parameters, (stars:) planetary systems, planetary systems
Abstract Copyright:
2017 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society
DOI:
10.1093/mnras/stx144
Bibliographic Code:
2017MNRAS.467..971B

Abstract

We describe the Zonal Atmospheric Stellar Parameters Estimator (zaspe), a new algorithm, and its associated code, for determining precise stellar atmospheric parameters and their uncertainties from high-resolution echelle spectra of FGK-type stars. zaspe estimates stellar atmospheric parameters by comparing the observed spectrum against a grid of synthetic spectra only in the most sensitive spectral zones to changes in the atmospheric parameters. Realistic uncertainties in the parameters are computed from the data itself, by taking into account the systematic mismatches between the observed spectrum and the best-fitting synthetic one. The covariances between the parameters are also estimated in the process. zaspe can in principle use any pre-calculated grid of synthetic spectra, but unbiased grids are required to obtain accurate parameters. We tested the performance of two existing libraries, and we concluded that neither is suitable for computing precise atmospheric parameters. We describe a process to synthesize a new library of synthetic spectra that was found to generate consistent results when compared with parameters obtained with different methods (interferometry, asteroseismology, equivalent widths).
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