Related papers: K2 Variable Catalogue II: Machine Learning Classif…

The original {\it Kepler} mission observed and characterized over 2400 eclipsing binaries in addition to its prolific exoplanet detections. Despite the mechanical malfunction and subsequent non-recovery of two reaction wheels used to…

We present the collection of eclipsing binaries in the Large and Small Magellanic Clouds, based on the OGLE survey. It contains 48605 systems, 40204 belonging to the LMC and 8401 to the SMC. Out of the total number of the presented…

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…

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…

In this work we train three decision-tree based ensemble machine learning algorithms (Random Forest Classifier, Adaptive Boosting and Gradient Boosting Decision Tree respectively) to study quasar selection in the variable source catalog in…

Detached eclipsing binaries are the primary tool used to measure precise masses and radii of stars. In our previous paper estimating the parameters of more than 30,000 detached eclipsing binaries, we identified 766 eclipsing binaries with…

We present optical lightcurves of 428 periodic variable stars coincident with ROSAT X-ray sources, detected using the first run of the SuperWASP photometric survey. Only 68 of these were previously recognised as periodic variables. A…

We report the first results of a study of variable point sources identified using multi-color time-series photometry from Sloan Digital Sky Survey (SDSS) Stripe 82 over a span of nearly 10 years (1998-2007). We construct a light-curve…

We explore the synergy between photometric and spectroscopic surveys by searching for periodic variable stars among the targets observed by the Apache Point Observatory Galactic Evolution Experiment (APOGEE) using photometry from the…

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,…

We have analyzed archival HST/WFPC2 time-series data of the central parts of globular clusters M13, M30 and NGC 6712 in search of variable objects. Among a total of 21 identified variables there are 15 new discoveries. The sample includes…

Mass loss is a key aspect of stellar evolution, particularly in evolved massive stars, yet episodic mass loss remains poorly understood. To investigate this, we need evolved massive stellar populations across various galactic environments.…

This paper explores the application of machine learning methods for classifying astronomical sources using photometric data, including normal and emission line galaxies (ELGs; starforming, starburst, AGN, broad line), quasars, and stars. We…

The feasibility of using data from the NASA STEREO mission for variable star and asteroseismology studies has been examined. A data analysis pipeline has been developed that is able to apply selected algorithms to the entire database of…

The rate of image acquisition in modern synoptic imaging surveys has already begun to outpace the feasibility of keeping astronomers in the real-time discovery and classification loop. Here we present the inner workings of a framework,…

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…

We explore the detection limits of the phase modulation (PM) method of finding binary systems among multi-periodic pulsating stars. The method is an attractive way of finding non-transiting planets in the habitable zones of intermediate…

Large surveys producing tera- and petabyte-scale databases require machine-learning and knowledge discovery methods to deal with the overwhelming quantity of data and the difficulties of extracting concise, meaningful information with…

Periodic variables are always of great scientific interest in astrophysics. Thanks to the rapid advancement of modern large-scale time-domain surveys, the number of reported variable stars has experienced substantial growth for several…

The image subtraction technique applied to study variable stars in globular clusters represented a leap in the number of new detections, with the drawback that many of these new light curves could not be transformed to magnitudes due to the…