Related papers: Automated classification of variable stars for ASA…
We present the results of an automated variability analysis of the Kepler public data measured in the first quarter (Q1) of the mission. In total, about 150 000 light curves have been analysed to detect stellar variability, and to identify…
With the availability of large-scale surveys like Kepler and TESS, there is a pressing need for automated methods to classify light curves according to known classes of variable stars. We introduce a new algorithm for classifying light…
Large area surveys will dominate the forthcoming decades of astronomy and their success requires characterizing thousands of discoveries through additional observations at higher spatial or spectral resolution, and at complementary cadences…
We identify 3,113 highly variable objects in 7,200 square degrees of the Palomar-QUEST Survey, which each varied by more than 0.4 magnitudes simultaneously in two broadband optical filters on timescales from hours to roughly 3.5 years. The…
(abridged) Ongoing supernova (SN) surveys find hundreds of candidates, that require confirmation for their use. Traditional classification based on followup spectroscopy of all candidates is virtually impossible for these large samples. We…
We present a machine learning package for the classification of periodic variable stars. Our package is intended to be general: it can classify any single band optical light curve comprising at least a few tens of observations covering…
Context: Mode identification has remained a major obstacle in the interpretation of pulsation spectra in rapidly rotating stars. Aims: We would like to test mode identification methods and seismic diagnostics in rapidly rotating stars,…
The Asteroid Terrestrial-impact Last Alert System (ATLAS) carries out its primary planetary defense mission by surveying about 13000 deg^2 at least four times per night. The resulting data set is useful for the discovery of variable stars…
The ESA global astrometry space mission Gaia has been monitoring the position of a billion stars since 2014. The analysis of such a massive dataset is challenging in terms of the data processing involved. In particular, the blind detection…
We report the discovery of six new variable stars identified through an exploratory analysis of several sky fields observed by the author using a small telescope and a CMOS camera. The search employed simultaneous photometry of hundreds of…
We present a catalog of 307 optical counterparts of the bright ROSAT X-ray sources, identified with the ASAS North survey data and showing periodic brightness variations. They all have declination north of -25 deg. Other data available from…
Variable star analysis and classification is an important task in the understanding of stellar features and processes. While historically classifications have been done manually by highly skilled experts, the recent and rapid expansion in…
The number of known periodic variable stars has increased rapidly in recent years. As an all-sky transit survey, the Transiting Exoplanet Survey Satellite (TESS) plays an important role in detecting low-amplitude variable stars. Using…
We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys, which uses a library of >65000 color templates. The method aims for extracting the information content of object colors in a statistically…
We present the first analysis of results from the SuperWASP Variable Stars Zooniverse project, which is aiming to classify 1.6 million phase-folded light curves of candidate stellar variables observed by the SuperWASP all sky survey with…
With the advent of powerful telescopes such as the Square Kilometer Array and the Vera C. Rubin Observatory, we are entering an era of multiwavelength transient astronomy that will lead to a dramatic increase in data volume. Machine…
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).…
Modern astronomical surveys produce millions of light curves of variable sources. These massive data sets challenge the community to create automatic light-curve processing methods for detection, classification, and characterisation of…
In the coming years, next-generation space-based infrared observatories will significantly increase our samples of rare massive stars, representing a tremendous opportunity to leverage modern statistical tools and methods to test massive…
Star-galaxy classification is one of the most fundamental data-processing tasks in survey astronomy, and a critical starting point for the scientific exploitation of survey data. For bright sources this classification can be done with…