STEPARSYN: A Bayesian code to infer stellar atmospheric parameters using spectral synthesis



Downloads per month over past year

Tabernero, H. M. and Gómez Marfil, Emilio and Montes Gutiérrez, David and González Hernández, J. I. (2022) STEPARSYN: A Bayesian code to infer stellar atmospheric parameters using spectral synthesis. Astronomy & Astrophysics, 657 . ISSN 0004-6361

[thumbnail of gomezmarfil05libre.pdf]

Official URL:


Context. STEPARSYN is an automatic code written in Python 3.X designed to infer the stellar atmospheric parameters T-eff, log g, and [Fe/H] of FGKM-type stars following the spectral synthesis method. Aims. We present a description of the STEPARSYN code and test its performance against a sample of late-type stars that were observed with the HERMES spectrograph mounted at the 1.2-m Mercator Telescope. This sample contains 35 late-type targets with well-known stellar parameters determined independently from spectroscopy. The code is available to the astronomical community in a GitHub repository. Methods. STEPARSYN uses a Markov chain Monte Carlo sampler to explore the parameter space by comparing synthetic model spectra generated on the fly to the observations. The synthetic spectra are generated with an spectral emulator. Results. We computed T-eff, log g, and [Fe/H] for our sample stars and discussed the performance of the code. We calculated an internal scatter for these targets of -12 +/- 117 K in T-eff, 0.04 +/- 0.14 dex in log g, and 0.05 +/- 0.09 dex in [Fe/H]. In addition, we find that the log g values obtained with STEPARSYN are consistent with the trigonometric surface gravities to the 0.1 dex level. Finally, STEPARSYN can compute stellar parameters that are accurate down to 50 K, 0.1 dex, and 0.05 dex for T-eff, log g, and [Fe/H] for stars with v sin i <= 30 km s(-1).

Item Type:Article
Additional Information:

© ESO 2022. We would like to thank the anonymous referee for his/her comments and suggestions that helped to improve the paper. We acknowledge financial support from the Agencia Estatal de Investigación of the Ministerio de Ciencia, Innovación y Universidades through projects PID2019-109522GB-C51,54/AEI/10.13039/501100011033. HMT and JIGH acknowledge financial support from the Centre of Excellence "Severo Ochoa" and "María de Maeztu" awards to the Instituto de Astrofísica de Canarias (SEV-2015-0548) and Centro de Astrobiología (MDM-2017-0737). JIGH also acknowledges financial support from the Spanish Ministry of Science and Innovation (MICINN) project AYA2017-86389-P, and also from the Spanish MICINN under 2013 Ramón y Cajal program RYC-2013-14875. E. M. acknowledges financial support from the Spanish Ministerio de Universidades through fellowship FPU15/01476. This work is based on observations obtained with the HERMES spectrograph, which is supported by the Research Foundation - Flanders (FWO), Belgium, the Research Council of KU Leuven, Belgium, the Fonds National de la Recherche Scientifique (F.R.S.-FNRS), Belgium, the Royal Observatory of Belgium, the Observatoire de Geneve, Switzerland and the Thuringer Landessternwarte Tautenburg, Germany. This research has made use of the SIMBAD database, operated at CDS, Strasbourg, France. This work has made use of data from the European Space Agency (ESA) mission Gaia , processed by the Gaia Data Processing and Analysis Consortium (DPAC,). Funding for the DPAC has been provided by national institutions, in particular the institution participating in the Gaia Multilateral Agreement. This research made use of Astropy, a community-developed core Python package for Astronomy.

Uncontrolled Keywords:To-limb variation; Radial-velocities; Spectroscopic parameters; Galah survey; M dwarfs; Stars; Planet; Metallicities; Abundance; Search
Subjects:Sciences > Physics > Astrophysics
ID Code:73038
Deposited On:23 Jun 2022 07:57
Last Modified:27 Jun 2022 12:11

Origin of downloads

Repository Staff Only: item control page