The ASAS-SN catalogue of variable stars – V. Variables in the Southern hemisphere

Abstract

The All-Sky Automated Survey for Supernovae (ASAS-SN) provides long baseline (∼4 yrs) light curves for sources brighter than V 17 mag across the whole sky. As part of our effort to characterize the variability of all the stellar sources visible in ASAS-SN, we have produced ∼30.1 million V-band light curves for sources in the southern hemisphere using the APASS DR9 catalog as our input source list. We have systematically searched these sources for variability using a pipeline based on random forest classifiers. We have identified ∼220, 000 variables, including ∼88, 300 new discoveries. In particular, we have discovered ∼48, 000 red pulsating variables, ∼23, 000 eclipsing binaries, ∼2, 200 δ-Scuti variables and ∼10, 200 rotational variables. The light curves and characteristics of the variables are all available through the ASAS-SN variable stars database (https://asas-sn.osu.edu/variables). The pre-computed ASAS-SN Vband light curves for all the ∼30.1 million sources are available through the ASAS-SN photometry database (https://asas-sn.osu.edu/photometry). This effort will be extended to provide ASAS-SN light curves for sources in the northern hemisphere and for V 17 mag sources across the whole sky that are not included in APASS DR9.

Cool, Luminous, and Highly Variable Stars in the Magellanic Clouds from ASAS-SN: Implications for Thorne–Żytkow Objects and Super-asymptotic Giant Branch Stars

“…Each ASAS-SN camera has a 4.5 deg 2 field-of-view, 8″ pixels, and typical point-source FWHM of ∼2 pixels. With all-sky coverage, ASAS-SN data have already been used extensively for the analysis of Milky Way variable stars (Jayasinghe et al 2018(Jayasinghe et al , 2019a(Jayasinghe et al , 2019b(Jayasinghe et al , 2020a(Jayasinghe et al , 2020b(Jayasinghe et al , 2020cPawlak et al 2019;Percy 2019;Shields et al 2019;Auge et al 2020).…”

Alert Classification for the ALeRCE Broker System: The Real-time Stamp Classifier

“…We built a training set of ZTF alerts using the labeled set from SnchezSez et al (2020), which is a results of cross-matching with other catalogs, such as the ASAS-SN catalogue of variable stars (Jayasinghe et al 2018(Jayasinghe et al , 2019a(Jayasinghe et al ,b, 2020, the Roma-BZCAT Multi-Frequency Catalog of Blazars (Massaro et al 2015), the Million Quasars Catalog (version June 2019, Flesch 2015, 2019, the New Catalog of Type 1 AGNs (Oh2015; Oh et al 2015), the Catalina Surveys Variable Star Catalogs (Drake et al 2014(Drake et al , 2017, the LINEAR catalog of periodic light curves (Palaversa et al 2013), Gaia Data Release 2 (Mowlavi et al 2018;Rimoldini et al 2019), the SIMBAD database (Wenger et al 2000), and spectroscopically classified SNe from the TNS database. The Active Galactic Nuclei Supernovae asteroid subset was built by selecting the alerts that were near a Solar-system object, requiring that the ssdistnr field in the alert metadata exists.…”

LAMOST Time-Domain Survey: First Results of four $K$2 plates

“…The characters of the templates include light curve period, skewness of the magnitude distribution, median magnitude, standard deviation of the magnitude, the ratio of magnitudes brighter or fainter than the average, the ratio between the Fourier components a 2 and a 4 , 10% and 90% percentile of slopes of a phase-folded light curve. They were concluded as identification parameters that trigger the classification through machine learning method and visual inspection (Paczyński et al 2006;Kim & Bailer-Jones 2016;Jayasinghe et al 2020;Yang et al 2021, submitted). μ=0.32 σ=0.76…”