Related papers: Automated classification of Hipparcos unsolved var…
In this work, we present a framework for estimating and evaluating uncertainty in deep-attention-based classifiers for light curves for variable stars. We implemented three techniques, Deep Ensembles (DEs), Monte Carlo Dropout (MCD) and…
The Hubble Catalog of Variables (HCV) project aims to identify the variable sources in the Hubble Source Catalog (HSC), which includes about 92 million objects with over 300 million measurements detected by the WFPC2, ACS and WFC3 cameras…
A large number of unidentified sources found by astronomical surveys and other observations necessitate the use of an automated classification technique based on machine learning methods. The aim of this paper is to find a suitable…
The All Sky Automated Survey (ASAS) monitors bright stars (8 mag < V < 14 mag) south of declination +28 deg. The ASAS Catalogue of Variable Stars (ACVS) presently contains 50,099 objects; among them are 2212 objects classified as RR Lyrae…
We present the results of our search for variable stars using the long-term Las Cumbres Observatory (LCO) monitoring of white dwarf ZTF J0139+5245 with the two 1.0-m telescope nodes located at McDonald Observatory using the Sinistro imaging…
We report the detection of 1143 variable stars towards the Galactic bulge, including 320 previously uncatalogued variables, using time-series photometry extracted from data obtained with the VIMOS imager at the Very Large Telescope.…
Variable stars, or particularly eclipsing binaries, are very essential astronomical occurrence. Surveys are the backbone of astronomy, and many discoveries of variable stars are the results of surveys. All-Sky Automated Survey (ASAS) is one…
A search for RR Lyrae stars has been conducted in the publicly available data of the Northern Sky Variability Survey (NSVS). Candidates have been selected by the statistical properties of their variation; the standard deviation, skewness…
We describe an ongoing variable star search program and present the first reduced results of a search in a 19 square degree (4.4\circle x 4.4\circle) field centered on J2000 {\alpha} = 22:03:24, {\delta} = +18:54:32. The search was carried…
By digitizing astronomical photographic plates one may extract full information stored on them, something that could not be practically achieved with classical analogue methods. We are developing algorithms for variable objects search using…
This work presents the first large-scale photometric variability survey of the intermediate age (~200 Myr) open cluster M11. Thirteen nights of data over two observing seasons were analyzed (using crowded field and ensemble photometry…
We conduct a systematic search for periodic variables in the hot subdwarf catalogue using data from the Zwicky Transient Facility. We present the classification of 67 HW Vir binaries, 496 reflection effect, pulsation or rotation sinusoids,…
In a previous paper, we studied two statistical methods used to analyse the variability of active galactic nuclei (AGNs): the C and F statistics. Applying them to observed differential light-curves of 39 AGNs, we found that, even though the…
Astronomy light curves are sparse, gappy, and heteroscedastic. As a result standard time series methods regularly used for financial and similar datasets are of little help and astronomers are usually left to their own instruments and…
We present an automated morphological classification in 4 types (E,S0,Sab,Scd) of ~700.000 galaxies from the SDSS DR7 spectroscopic sample based on support vector machines. The main new property of the classification is that we associate to…
The Hubble Catalog of Variables (HCV) is a 3 year ESA funded project that aims to develop a set of algorithms to identify variables among the sources included in the Hubble Source Catalog (HSC) and produce the HCV. We will process all HSC…
We proposed a machine learning approach to identify and distinguish dusty stellar sources employing supervised and unsupervised methods and categorizing point sources, mainly evolved stars, using photometric and spectroscopic data collected…
Periodic variables illuminate the physical processes of stars throughout their lifetime. Wide-field surveys continue to increase our discovery rates of periodic variable stars. Automated approaches are essential to identify interesting…
We present an image classification algorithm using deep learning convolutional neural network architecture, which classifies the morphologies of eclipsing binary systems based on their light curves. The algorithm trains the machine with…
In the last couple of decades, tremendous progress has been achieved in developing robotic telescopes and, as a result, sky surveys (both terrestrial and space) have become the source of a substantial amount of new observational data. These…