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FASMA 2.0: A Python package for stellar parameters and chemical abundances

M. Tsantaki, D. T. Andreasen, G. D. C. Teixeira

Effective temperature (Teff), surface gravity (logg), and metallicity ([M/H]) are basic stellaratmospheric parameters necessary to characterize a star. Once these parameters are obtained,we can in turn, infer their chemical abundances of various elements and in conjunction withevolutionary models to estimate their evolution, i.e., mass and radius. In this work, we usespectroscopy as a powerful tool to extract this information from stellar atmospheres applied tostars with spectral type FGK both dwarfs and giants. The growing number of spectroscopicsurveys dedicated to the study of the Galactic stellar populations has inflated the number ofhigh quality spectra to several hundreds of thousands. This amount is expected to multiplywith the forthcoming surveys, such as WEAVE (de Jong et al., 2019) and 4MOST (Daltonet al., 2014). The success of these surveys highly depends on the analysis tools to exploitsufficiently all spectral information. Moreover, it is a well-known axiom in exoplanetary studiesthat one can only determine the planetary properties once the ones of the host star are known.The planetary properties such as mass, radius, composition, are directly linked to their hostsand therefore, robust tools for the derivation of these parameters are necessary.

Python; chemical abundances; astronomy; spectroscopy; stellar parameters

The Journal of Open Source Software
Volume 5, Number 50
2020 June

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Faculdade de Ciências da Universidade de Lisboa Universidade do Porto Faculdade de Ciências e Tecnologia da Universidade de Coimbra
Fundação para a Ciência e a Tecnologia COMPETE 2020 PORTUGAL 2020 União Europeia