Related papers: CoSHA: Code for Stellar properties Heuristic Assig…
Elucidating the connection between the properties of galaxies and the properties of their hosting haloes is a key element in galaxy formation. When the spatial distribution of objects is also taken under consideration, it becomes very…
We have obtained [Mg/Fe] for around 77% of the stars of the MILES library of stellar spectra in order to include this important information into simple stellar population (SSP) models. The abundance ratios, which were carefully calibrated…
Identification of metal-poor stars among field stars is extremely useful for studying the structure and evolution of the Galaxy and of external galaxies. We search for metal-poor stars using the artificial neural network (ANN) and extend…
In this paper we describe Kea a new spectroscopic fitting method to derive stellar parameters from moderate to low signal/noise, high-resolution spectra. We developed this new tool to analyze the massive data set of the Kepler mission…
We present results for the estimation of gravity, effective temperature, and radial velocity of poorly studied chemically peculiar stars recently observed with the spectropolarimeter Echelle SpectroPolarimetric Device for Observations of…
With the coming data deluge from synoptic surveys, there is a growing need for frameworks that can quickly and automatically produce calibrated classification probabilities for newly-observed variables based on a small number of time-series…
Automated method of full spectrum fitting gives reliable estimates of stellar atmospheric parameters (Teff, logg and [Fe/H]) for late A, F, G and early K type stars. Recently, the technique was further improved in the cooler regime and the…
Cosmological hydrodynamical simulations have become an indispensable tool to understand galaxies. However, computational constraints still severely limit their numerical resolution. This not only restricts the sampling of the stellar…
Considering features of stellar spectral radiation and survey explorers, we established a computational model for stellar effective temperatures, detected angular parameters, and gray rates. Using known stellar flux data in some band, we…
It has long been understood that the light curve of a transiting planet constrains the density of its host star. That fact is routinely used to improve measurements of the stellar surface gravity and has been argued to be an independent…
The light emitted from the stellar photosphere serves as a unique signature for the nature of stars. The behaviour of these stellar lines depend upon the surface temperature, mass, evolutionary status and chemical composition of the star.…
The detection and subsequent characterisation of exoplanets are intimately linked to the characteristics of their host star. Therefore, it is necessary to study the star in detail in order to understand the formation history and…
(abridged) Elemental abundances of FGK stars can be derived routinely from high-resolution optical spectra, but this remains considerably more difficult for cooler stars. Machine-learning methods offer a practical route to infer otherwise…
We present a novel approach to deriving stellar labels for stars observed in MUSE fields making use of data-driven machine learning methods. Taking advantage of the comparable spectral properties (resolution, wavelength coverage) of the…
Tools for the spectroscopic determination of fundamental stellar parameters should not only comprise customized solutions for one particular survey or instrument, but, in order to enable cross-survey comparability, they should also be…
Constraining parameters such as the initial mass function high-mass slope and the frequency of type Ia supernovae is of critical importance in the ongoing quest to understand galactic physics and create realistic hydrodynamical simulations.…
In modern astrophysics, the machine learning has increasingly gained more popularity with its incredibly powerful ability to make predictions or calculated suggestions for large amounts of data. We describe an application of the supervised…
A method is developed for fitting theoretically predicted astronomical spectra to an observed spectrum. Using a hierarchical Bayesian principle, the method takes both systematic and statistical measurement errors into account, which has not…
This paper introduces ASTRA (Algorithm for Stochastic Topological RAnking), a new method for classifying galaxies into cosmic web structures -- voids, sheets, filaments, and knots -- specifically designed for large spectroscopic surveys.…
We present equivalent widths, improved model atmosphere parameters, and revised abundances for 14 species of 11 elements derived from high resolution optical spectroscopy of 311 metal-poor stars. All of these stars had their parameters…