期刊
ASTRONOMY & ASTROPHYSICS
卷 564, 期 -, 页码 -出版社
EDP SCIENCES S A
DOI: 10.1051/0004-6361/201322430
关键词
methods: data analysis; techniques: spectroscopic; stars: fundamental parameters; stars: abundances
资金
- German Research Foundation (DFG) [Sonderforschungsbereich SFB 881]
- Conseil Scientifique de l'Observatoire de Paris
- Programme National de Cosmologie et Galaxies of the Institut National des Sciences de l'Univers of CNRS
Context. The current and planned high-resolution, high-multiplexity stellar spectroscopic surveys, as well as the swelling amount of underutilized data present in public archives, have led to an increasing number of efforts to automate the crucial but slow process of retrieving stellar parameters and chemical abundances from spectra. Aims. We present MyGIsFOS(1), a code designed to derive atmospheric parameters and detailed stellar abundances from medium-to high-resolution spectra of cool (FGK) stars. We describe the general structure and workings of the code, present analyses of a number of well-studied stars representative of the parameter space MyGIsFOS is designed to cover, and give examples of the exploitation of MyGIsFOS very fast analysis to assess uncertainties through Monte Carlo tests. Methods. MyGIsFOS aims to reproduce a traditional manual analysis by fitting spectral features for different elements against a precomputed grid of synthetic spectra. The lines of Fe I and Fe II can be employed to determine temperature, gravity, microturbulence, and metallicity by iteratively minimizing the dependence of Fe I abundance from line lower energy and equivalent width, and imposing Fe I-Fe II ionization equilibrium. Once parameters are retrieved, detailed chemical abundances are measured from lines of other elements. Results. MyGIsFOS replicates closely the results obtained in similar analyses on a set of well-known stars. It is also quite fast, performing a full parameter determination and detailed abundance analysis in about two minutes per star on a mainstream desktop computer. Currently, its preferred field of application are high-resolution and/or large spectral coverage data (e.g., UVES, X-shooter, HARPS, Sophie).
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据