Related papers: A Machine Learning Method to Infer Fundamental Ste…

We present a method for the determination of [alpha/Fe] ratios from low-resolution (R = 2000) SDSS/SEGUE stellar spectra. By means of a star-by-star comparison with degraded spectra from the ELODIE spectral library and with a set of…

With the purpose of assessing classic spectroscopic methods on high-resolution and high signal-to-noise ratio spectra in the near-infrared wavelength region, we selected a sample of 65 F-, G-, and K-type stars observed with CARMENES, the…

Using population synthesis tools we create a synthetic Kepler Input Catalogue (KIC) and subject it to the Kepler Stellar Classification Program (SCP) method for determining stellar parameters such as the effective temperature Teff and…

We present fundamental atmospheric parameters (Teff and log g) and metallicities ([M/H]) for 507,513 M dwarf stars using low-resolution spectra (R~1800) from LAMOST DR10. By employing Cycle-StarNet, an innovative domain adaptation approach,…

We implemented non-solar-scaled opacities in a simultaneous derivation of fundamental parameters and abundances. We carried out a high-precision stellar parameters and abundance determination by applying non-solar-scaled opacities and model…

Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) acquired tens of millions of low-resolution stellar spectra. The large amount of the spectra result in the urgency to explore automatic atmospheric parameter estimation…

We present a new library of synthetic spectra based on the stellar atmosphere code PHOENIX. It covers the wavelength range from 500{\AA} to 55000{\AA} with a resolution of R=500000 in the optical and near IR, R=100000 in the IR and…

This paper investigates the problem of estimating three stellar atmospheric physical parameters and thirteen elemental abundances for medium-resolution spectra from Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). Typical…

We present an analysis of UKIRT observations obtained between 2003 and 2007 to investigate the evolved stellar populations within the central square kiloparsec of M33. Point-spread function (PSF) photometry is employed to mitigate the…

Photometric surveys with the Hubble Space Telescope (HST) allow us to study stellar populations with high resolution and deep coverage, with estimates of the physical parameters of the constituent stars being typically obtained by comparing…

The program package SME (Spectroscopy Made Easy), designed to perform an analysis of stellar spectra using spectral fitting techniques, was updated due to adding new functions (isotopic and hyperfine splittins) in VALD and including grids…

We have employed feedforward neural networks trained on synthetic spectra in the range 3800 to 5600 AA with resolutions of 2-3 AA to determine metallicities from spectra of about 1000 main-sequence turn-off, subgiant and red giant stars in…

Detached eclipsing binary stars (dEBs) are a key source of data on fundamental stellar parameters. Within the light curve databases of survey missions such as Kepler and TESS are a wealth of new systems awaiting characterisation. We aim to…

Deep learning (DL) techniques are a promising approach among the set of methods used in the ever-challenging determination of stellar parameters in M dwarfs. In this context, transfer learning could play an important role in mitigating…

The large amounts of astrophysical data being provided by existing and future instrumentation require efficient and fast analysis tools. Transfer learning is a new technique promising higher accuracy in the derived data products, with…

We present basic atmospheric parameters (Teff, logg, vt and [Fe/H]) as well as luminosities, masses, radii and absolute radial velocities for 348 stars, presumably giants, from the ~1000 star sample observed within the Penn State-Torun…

In this paper, we present a deep learning system approach to estimating luminosity, effective temperature, and surface gravity of O-type stars using the optical region of the stellar spectra. In previous work, we compare a set of machine…

Understanding the atmospheric parameters of stars on the top of the RGB is essential to reveal the chemical composition of the Milky Way, as they can be used to probe the farthest parts of our Galaxy. Our goal is to determine the chemical…

The ~ 200,000 stars observed by the Kepler mission have provided unprecedented constraints across astrophysics. With the advent of modern spectroscopic and photometric surveys, new limits in stellar characterizations are within reach. In…

Modern stellar structure and evolution theory experiences a lack of observational calibrations for the interior physics of intermediate- and high-mass stars. This leads to discrepancies between theoretical predictions and observed phenomena…