Related papers: J-PLUS: Support Vector Regression to Measure Stell…
Aims. The derivation of spectroscopic parameters for M dwarf stars is very important in the fields of stellar and exoplanet characterization. The goal of this work is the creation of an automatic computational tool, able to derive quickly…
Large scale, deep survey missions such as GAIA will collect enormous amounts of data on a significant fraction of the stellar content of our Galaxy. These missions will require a careful optimisation of their observational systems in order…
Variable stars with well-calibrated period-luminosity relationships provide accurate distance measurements to nearby galaxies and are therefore a vital tool for cosmology and astrophysics. While these measurements typically rely on samples…
We present stellar atmosphere modeling of JWST NIRCam photometry of nine highly magnified individual stars in a single galaxy at redshift z=0.94 known as the Warhol arc, which is strongly lensed by the galaxy cluster MACSJ0416. Seven of…
We develop a data-driven model to map stellar parameters (effective temperature, surface gravity and metallicity) accurately and precisely to broad-band stellar photometry. This model must, and does, simultaneously constrain the…
Traditional artificial-star tests are widely applied to photometry in crowded stellar fields. However, to obtain reliable binary fractions (and their uncertainties) of remote, dense, and rich star clusters, one needs to recover huge numbers…
Stellar population studies in the infrared (IR) wavelength range have two main advantages with respect to the optical regime: they probe different populations, because most of the light in the IR comes from redder and generally older stars,…
Innovation in the ground and space-based instruments has taken us into a new age of spectroscopy, in which a large amount of stellar content is becoming available. So, automatic classification of stellar spectra became subjective in recent…
We used the Javalambre Photometric Local Universe Survey (J-PLUS) DR2 photometry in twelve optical bands over 2176 deg2 to estimate the fraction of white dwarfs with presence of CaII H+K absorption along the cooling sequence. We compared…
In this work, six convolutional neural networks (CNNs) have been trained based on %different feature images and arrays from the database including 15,638 superflare candidates on solar-type stars, which are collected from the three-years…
Upcoming large-area narrow band photometric surveys, such as J-PAS, will enable us to observe a large number of galaxies simultaneously and efficiently. However, it will be challenging to analyse the spatially-resolved stellar populations…
The spectral energy distribution (SED) of observed stars in wide-field images is crucial for chromatic point spread function (PSF) modelling methods, which use unresolved stars as integrated spectral samples of the PSF across the field of…
We report homogeneous spectroscopic determinations of the effective temperature, metallicity, and projected rotational velocity for the host stars of 56 transiting planets. Our analysis is based primarily on the Stellar Parameter…
Recent developments in computational power and machine learning techniques motivate their use in many different astrophysical research areas. Consequently, many machine learning models have been trained to classify exoplanet transit signals…
Context: Massive amounts of spectroscopic data obtained by stellar surveys are feeding an ongoing revolution in our knowledge of stellar and Galactic astrophysics. Analysing these data sets to extract the best possible astrophysical…
The J-PAS survey will observe ~1/3 of the northern sky with a set of 56 narrow-band filters using the dedicated 2.55 m JST telescope at the Javalambre Astrophysical Observatory. Prior to the installation of the main camera, in order to…
The Southern Photometric Local Universe Survey (S-PLUS) is an ongoing survey of $\sim$9300 deg$^2$ in the southern sky in a 12-band photometric system. This paper presents the second data release (DR2) of S-PLUS, consisting of 514 tiles…
Background. Clustering analysis discovers hidden structures in a data set by partitioning them into disjoint clusters. Robust accuracy measures that evaluate the goodness of clustering results are critical for algorithm development and…
It is an active topic to investigate the schemes based on machine learning (ML) methods for detecting pulsars as the data volume growing exponentially in modern surveys. To improve the detection performance, input features into an ML model…
Stellar spectropolarimetry is a relatively new remote sensing tool for exploring stellar atmospheres and circumstellar environments. We present the results of our HiVIS survey and a multi-wavelength ESPaDOnS follow-up campaign showing…