Related papers: A Challenge of Developing a Classifier for Multi-B…

Temporal and spectral information extracted from a stream of photons received from astronomical sources is the foundation on which we build understanding of various objects and processes in the Universe. Typically astronomers fit a number…

The upcoming new generation of optical spectrographs on four-meter-class telescopes will provide invaluable information for reconstructing the history of star formation in individual galaxies up to redshifts of about 0.7. We aim at defining…

The large sky localization regions offered by the gravitational-wave interferometers require efficient follow-up of the many counterpart candidates identified by the wide field-of-view telescopes. Given the restricted telescope time, the…

We describe photometric recalibration of data obtained by the asteroid survey LINEAR. Although LINEAR was designed for astrometric discovery of moving objects, the dataset described here contains over 5 billion photometric measurements for…

Classification is a popular task in the field of Machine Learning (ML) and Artificial Intelligence (AI), and it happens when outputs are categorical variables. There are a wide variety of models that attempts to draw some conclusions from…

Using 172 plates taken with the 40-cm astrograph of the Sternberg Astronomical Institute (Lomonosov Moscow University) in 1976-1994 and digitized with the resolution of 2400 dpi, we discovered and studied 275 new variable stars. We present…

Photometric measurements are prone to systematic errors presenting a challenge to low-amplitude variability detection. In search for a general-purpose variability detection technique able to recover a broad range of variability types…

Context. The Vista Variables in the V\'ia L\'actea (VVV) ESO Public Survey is a variability survey of the Milky Way bulge and an adjacent section of the disk carried out from 2010 on ESO Visible and Infrared Survey Telescope for Astronomy…

The first results are presented of a four-year program dedicated to the CCD observations of Cepheids in the nearby galaxy IC 1613. Since the program was carried out with a relatively small telescope, the Dutch 0.9 m at ESO-La Silla, the…

RV Tauri variable stars are pulsating evolved stars that are identified by a characterizing feature in their light curves: alternating deep and shallow minima. Many RV Tauri variable stars were originally classified decades ago using visual…

{We focus on characterizing the high-energy emission mechanisms of blazars by analyzing the variability in the radio band of the light curves of more than a thousand sources. We are interested in assigning complexity parameters to these…

We present a classification of galaxies in the Pan-STARRS1 (PS1) 3$\pi$ survey based on their recent star formation history and morphology. Specifically, we train and test two Random Forest (RF) classifiers using photometric features…

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…

A search for variable stars is performed using two epochs of Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS) imaging data for a 9.28 square arcminute portion of M31. This data set reveals 254 sources that vary by at least…

VISTA Variables in the Via Lactea (VVV) is an ESO public near-infrared variability survey of the Galactic bulge and an adjacent area of the southern mid-plane. It will produce a deep atlas in the ZYJHKs filters, and a Ks-band time-series…

Microvariability consists in small time scale variations of low amplitude in the photometric light curves of quasars, and represents an important tool to investigate their inner core. Detection of quasar microvariations is challenging for…

New B, V, I photometry was obtained for a sample of 152 variables (125 RR Lyrae's, 4 anomalous Cepheids, 11 classical Cepheids, 11 eclipsing binaries and a delta Scuti star) in two regions near the bar of the Large Magellanic Cloud (LMC).…

Vast amounts of astronomical photometric data are generated from various projects, requiring significant effort to identify variable stars and other object classes. In light of this, a general, widely applicable classification framework…

We present a methodology to discover outliers in catalogs of periodic light-curves. We use cross-correlation as measure of ``similarity'' between two individual light-curves and then classify light-curves with lowest average ``similarity''…

Despite the utility of neural networks (NNs) for astronomical time-series classification, the proliferation of learning architectures applied to diverse datasets has thus far hampered a direct intercomparison of different approaches. Here…