Related papers: J-PLUS: Support Vector Regression to Measure Stell…
Stellar spectroscopic classification has been successfully automated by a number of groups. Automated classification and parameterization work best when applied to a homogeneous data set, and thus these techniques primarily have been…
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…
The asteroseismic and planetary studies, like all research related to stars, need precise and accurate stellar atmospheric parameters as input. We aim at deriving the effective temperature (Teff), the surface gravity (log g), the…
We present the white dwarf catalog derived from the third data release of the Javalambre Photometric Local Universe Survey (J-PLUS DR3), which covers 3284 deg2 using 12 optical filters. A particular focus is given to the classification of…
We have developed a method for fast and accurate stellar population parameters determination in order to apply it to high resolution galaxy spectra. The method is based on an optimization technique that combines active learning with an…
The study of stellar parameters of planet-hosting stars, such as metallicity and chemical abundances, help us to understand the theory of planet formation and stellar evolution. Here, we present a catalogue of accurate stellar atmospheric…
Analyses of stellar spectra often begin with the determination of a number of parameters that define a model atmosphere. This work presents a prototype for an automated spectral classification system that uses a 15 nm-wide region around…
Time-domain astronomy is progressing rapidly with the ongoing and upcoming large-scale photometric sky surveys led by the Vera C. Rubin Observatory project (LSST). Billions of variable sources call for better automatic classification…
Extreme precision radial velocity (EPRV) surveys usually require extensive observational baselines to confirm planetary candidates, making them resource-intensive. Traditionally, periodograms are used to identify promising candidate signals…
Star formation rates (SFRs) are a crucial observational tracer of galaxy formation and evolution. Spectroscopy, which is expensive, is traditionally used to estimate SFRs. This study tests the possibility of inferring SFRs of large samples…
Kernel phase is a method to interpret stellar point source images by considering their formation as the analytical result of an interferometric process. Using Fourier formalism, this method allows for observing planetary companions around…
A scheme for estimating atmospheric parameters T$_{eff}$, log$~g$, and [Fe/H] is proposed on the basis of Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Haar wavelet. The proposed scheme consists of three processes. A…
Machine learning (ML) has become a key tool in astronomy, driving advancements in the analysis and interpretation of complex datasets from observations. This article reviews the application of ML techniques in the identification and…
We present a new approach to constrain galaxy physical parameters from the combined interpretation of stellar and nebular emission in wide ranges of observations. This approach relies on the Bayesian analysis of any type of galaxy spectral…
Astrometry plays a crucial role in understanding the structure, dynamics, and evolution of celestial objects by providing precise measurements of their positions and motions. We propose a new approach to wide-field, relative astrometry,…
(abridged) Mass loss is a key parameter in the evolution of massive stars, with discrepancies between theory and observations and with unknown importance of the episodic mass loss. To address this we need increased numbers of classified…
The research focuses on determining the metallicity ([Fe/H]) predicted in the solar twin stars by using various regression modeling techniques which are, Random Forest, Linear Regression, Decision Tree, Support Vector, and Gradient…
The Javalambre-Physics of the Accelerated Universe Astrophysical Survey (J-PAS) is a narrow band, very wide field Cosmological Survey to be carried out from the Javalambre Observatory in Spain with a purpose-built, dedicated 2.5m telescope…
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…
This paper investigates the problem of prediction of stellar parameters, based on the star's electromagnetic spectrum. The knowledge of these parameters permits to infer on the evolutionary state of the star. From a statistical point of…