Related papers: CoSHA: Code for Stellar properties Heuristic Assig…
We calculate the fundamental stellar parameters effective temperature, surface gravity and iron abundance - T$_{\rm eff}$, log g, [Fe/H] - for the final release of the Mapping Nearby Galaxies at APO (MaNGA) Stellar Library (MaStar),…
The MaNGA Stellar Library (MaStar) is a large collection of high-quality empirical stellar spectra designed to cover all spectral types and ideal for use in the stellar population analysis of galaxies observed in the Mapping Nearby Galaxies…
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…
We present an homogeneous set of stellar atmospheric parameters (Teff, log g, [Fe/H]) for a sample of about 700 field and cluster stars which constitute a new stellar library in the near-infrared developed for stellar population synthesis…
We report the stellar atmospheric parameters for 7503 spectra contained in the first release of the MaNGA stellar library (MaStar) in SDSS DR15. The first release of MaStar contains 8646 spectra measured from 3321 unique stars, each…
The increasing number of spectra gathered by spectroscopic sky surveys and transiting exoplanet follow-up has pushed the community to develop automated tools for atmospheric stellar parameters determination. Here we present a novel approach…
We present the first release of the MaNGA Stellar Library (MaStar), which is a large, well-calibrated, high-quality empirical library covering the wavelength range of 3,622-10,354A at a resolving power of R~1800. The spectra were obtained…
We introduce the ongoing MaStar project, which is going to construct a large, well-calibrated, high quality empirical stellar library with more than 8000 stars covering the wavelength range from 3622 to 10,354A at a resolution of R~2000,…
In this paper, we developed a spectral emulator based on the Mapping Nearby Galaxies at Apache Point Observatory Stellar Library (MaStar) and a grouping optimization strategy to estimate effective temperature (T_eff), surface gravity (log…
The large amount of spectra obtained during the epoch of extensive spectroscopic surveys of Galactic stars needs the development of automatic procedures to derive their atmospheric parameters and individual element abundances. Starting from…
Context: Empirical libraries of stellar spectra play an important role in different fields. For example, they are used as reference for the automatic determination of atmospheric parameters, or for building synthetic stellar populations to…
Modern large-scale photometric surveys have provided us with multi-band photometries of billions of stars. Determining the stellar atmospheric parameters, such as the effective temperature (\teff) and metallicities (\feh), absolute…
Stellar parameters for large samples of stars play a crucial role in constraining the nature of stars and stellar populations in the Galaxy. An increasing number of medium-band photometric surveys are presently used in estimating stellar…
Accurate determination of stellar atmospheric parameters and elemental abundances is crucial for Galactic archeology via large-scale spectroscopic surveys. In this paper, we estimate stellar atmospheric parameters -- effective temperature…
Temperature, surface gravity, and metallicitity are basic stellar atmospheric parameters necessary to characterize a star. We aim to improve the description of the spectroscopic temperatures especially for the cooler stars where the…
Aims: We developed a new method of estimating the stellar parameters Teff, log g, [M/H], and elemental abundances. This method was implemented in a new code, SP_Ace (Stellar Parameters And Chemical abundances Estimator). This is a highly…
We introduce the public version of the BAyesian STellar Algorithm (BASTA), an open-source code written in {\tt Python} to determine stellar properties based on a set of astrophysical observables. BASTA has been specifically designed to…
In the era of vast spectroscopic surveys focusing on Galactic stellar populations, astronomers want to exploit the large quantity and good quality of data to derive their atmospheric parameters without losing precision from automatic…
Context: StePar is an automatic code written in Python 3.X designed to compute the stellar atmospheric parameters Teff, log(g), [Fe/H], and of FGK-type stars by means of the EW method. This code has already been extensively tested in…
We present a homogeneous set of stellar atmospheric parameters Teff, log g, [Fe/H] for MILES, a new spectral stellar library covering the range 3525 - 7500 angstrom at 2.3 angstrom (FWHM) spectral resolution. The library consists of 985…