%0 Journal Article
%A Tabernero Guzmán, Hugo Martín
%A Marfil, E.
%A Montes Gutiérrez, David
%A González Hernández, J.I.
%T STEPAR: an automatic code to infer stellar atmospheric parameters
%D 2019
%@ 1432-0746
%U https://hdl.handle.net/20.500.14352/13694
%X Context. StePar is an automatic code written in Python 3.X designed to compute the stellar atmospheric parameters T_(eff), log g, [Fe/H], and ξ of FGK-type stars by means of the equivalent width (EW) method. This code has already been extensively tested in different spectroscopic studies of FGK-type stars with several spectrographs and against thousands of Gaia-ESO Survey UVES U580 spectra of late-type, low-mass stars as one of its 13 pipelines. Aims. We describe the code that we tested against a library of well characterised Gaia benchmark stars. We also release the code to the community and provide the link for download.Methods. We carried out the required EW determination of Fe i and Fe ii spectral lines using the automatic tool TAME. StePar implements a grid of MARCS model atmospheres and the MOOG radiative transfer code to compute stellar atmospheric parameters by means of a Downhill Simplex minimisation algorithm.Results. We show the results of the benchmark star test and also discuss the limitations of the EW method, and hence the code. In addition, we find a small internal scatter for the benchmark stars of 9 ± 32 K in T_(eff), 0.00 ± 0.07 dex in log g, and 0.00 ± 0.03 dex in [Fe/H]. Finally, we advise against using StePar on double-lined spectroscopic binaries or spectra with R < 30 000, S/N < 20, or v sin i > 15 km s^(−1) , and on stars later than K4 or earlier than F6.
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