Related papers: A machine learned classifier for RR Lyrae in the V…

Acquiring near-infrared K-band (2.2 um) photometry for RR Lyrae variables in globular clusters and nearby galaxies is advantageous since the resulting distances are less impacted by reddening and metallicity. However, K-band photometry for…

Vista Variables in The Via Lactea (VVV) is an ESO variability survey that is performing observations in near infrared bands (ZYJHKs) towards the Galactic bulge and part of the disk with the completeness limits at least 3 mag deeper than…

Context: It is not known how many globular clusters may have been left undetected towards the Galactic bulge. Aims: One of the aims of the VISTA Variables in the Via Lactea (VVV) Survey is to accurately measure the physical parameters of…

Many studies have shown that RR Lyrae variable stars (RRL) are powerful stellar tracers of Galactic halo structure and satellite galaxies. The Dark Energy Survey (DES), with its deep and wide coverage (g ~ 23.5 mag) in a single exposure;…

Context. A number of RR Lyrae stars show variable mean magnitudes in the OGLE survey light curves of the Galactic bulge. Hitherto this phenomenon was not studied, as it was generally assumed to be related to problems with the photometry.…

VISTA variables in the Via Lactea is an ESO Public survey dedicated to scan the bulge and an adjacent portion of the Galactic disk in the fourth quadrant using the VISTA telescope and the near-infrared camera VIRCAM. One of the leading…

We have analyzed the data on 16,836 RR Lyrae (RR Lyr) variables observed toward the Galactic bulge during the third phase of the Optical Gravitational Lensing Experiment (OGLE-III), which took place in 2001-2009. Using these standard…

We present the first results of a project aiming to trace the spatial structure of the Milky Way using detached eclipsing binaries (DEBs) as distance indicators. A sample of DEBs from the OGLE-II catalogue was selected and their near…

We investigate the properties of known RR Lyrae in the Vera C. Rubin Observatory Data Preview 1 (DP1) fields and compare those with the predictions based on stellar pulsation models tailored to the Legacy Survey of Space and Time (LSST)…

The Vista Variables in the V\'ia L\'actea survey (VVV) is a near-IR ESO public survey devoted to study the Galactic bulge and southern inner disk covering 560 deg$^2$ on the sky. This multi-epoch and multi-wavelength survey has helped to…

We present results for the QUEST RR Lyrae Survey at low galactic latitude, conducted entirely with observations obtained with the QUEST mosaic camera and the 1.0/1.5m J\"urgen Stock Schmidt telescope at the National Observatory of…

RR Lyrae stars (RRLs) are tracers of the Milky Way's fossil record, holding valuable information on its formation and early evolution. Owing to the high interstellar extinction endemic to the Galactic plane, distant RRLs lying at low…

We present the results of various automated classification methods, based on machine learning (ML), of objects from data releases 6 and 7 (DR6 and DR7) of the Sloan Digital Sky Survey (SDSS), primarily distinguishing stars from quasars. We…

The census of the globular clusters (GCs) in the Milky Way (MW) is still a work in progress. We explore the nature of 19 new GC candidates in the Galactic bulge, based on the analysis of their colour-magnitude diagrams (CMDs) in the…

Machine-learning (ML) algorithms will play a crucial role in studying the large datasets delivered by new facilities over the next decade and beyond. Here, we investigate the capabilities and limits of such methods in finding galaxies with…

The properties of the Milky Way's nuclear stellar disc give crucial information on the epoch of bar formation. Mira variables are promising bright candidates to study the nuclear stellar disc, and through their period-age relation dissect…

We present the first results of an near-ultraviolet (NUV) survey of RR Lyrae stars from the Ultraviolet Optical Telescope (UVOT) aboard the Swift Gamma-Ray Burst Mission. It is well-established that RR Lyrae have large amplitudes in the…

Over the last two decades, machine learning models have been widely applied and have proven effective in classifying variable stars, particularly with the adoption of deep learning architectures such as convolutional neural networks,…

We present a machine learning method to estimate the physical parameters of classical pulsating stars such as RR Lyrae and Cepheid variables based on an automated comparison of their theoretical and observed light curve parameters at…

Purpose: RR Lyrae stars are important distance indicators. They are usually present in globular clusters where they were first discovered. The study of their properties and distribution in our Galaxy and external galaxies constitutes a…