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Masses and radii of stars can be derived by combining eclipsing binary light curves with spectroscopic orbits. In our previous work, we modelled the All-Sky Automated Survey for Supernovae (ASAS-SN) light curves of more than 30 000 detached eclipsing binaries using phoebe. Here, we combine our results with 128 double-lined spectroscopic orbits from Gaia Data Release 3. We also visually inspect ASAS-SN light curves of the Gaia double-lined spectroscopic binaries on the lower main sequence and the giant branch, adding 11 binaries to our sample. We find that only 50 per cent of systems have Gaia periods and eccentricities consistent with the ASAS-SN values. We use emcee and phoebe to determine masses and radii for a total of 122 stars with median fractional uncertainties of 7.9 per cent and 6.3 per cent, respectively.

 

The All-Sky Automated Survey for Supernovae (ASAS-SN) is the first optical survey to monitor the entire sky, currently with a cadence of ≲ 24 h down to g ≲ 18.5 mag. ASAS-SN has routinely operated since 2013, collecting ∼ 2 000 to over 7 500 epochs of V- and g-band observations per field to date. This work illustrates the first analysis of ASAS-SN’s newer, deeper, and higher cadence g-band data. From an input source list of ∼55 million isolated sources with g < 18 mag, we identified 1.5 × 106 variable star candidates using a random forest (RF) classifier trained on features derived from Gaia, 2MASS, and AllWISE. Using ASAS-SN g-band light curves, and an updated RF classifier augmented with data from Citizen ASAS-SN, we classified the candidate variables into eight broad variability types. We present a catalogue of ∼116 000 new variable stars with high-classification probabilities, including ∼111 000 periodic variables and ∼5 000 irregular variables. We also recovered ∼263 000 known variable stars.

 

Detached eclipsing binaries are a fundamental tool for measuring the physical parameters of stars that are effectively evolving in isolation. Starting from more than 40 000 eclipsing binary candidates identified by the All-Sky Automated Survey for Supernovae (ASAS-SN), we use PHOEBE to determine the sum of the fractional radii, the ratio of effective temperatures, the inclinations, and the eccentricities for 35 576 systems. We visually inspect all the light-curve models to verify the model fits and examine the TESS light curves, when available, to select systems with evidence for additional physics, such as spots, mass transfer, and hierarchical triples. We examine the distributions of the eclipsing binary model parameters and the orbital parameters. We identify two groups in the sum of the fractional radii and effective temperature ratio parameter space that may distinguish systems approaching the semidetached limit. Combining Gaia EDR3 with extinction estimates from three-dimensional dust maps, we examine the properties of the systems as a function of their absolute magnitude and evolutionary state. Finally, we present light curves of selected eclipsing binaries that may be of interest for follow-up studies.

 

As part of an All-Sky Automated Survey for SuperNovae (ASAS-SN) search for sources with large flux decrements, we discovered a transient where the quiescent, stellar source ASASSN-V J192114.84+624950.8 rapidly decreased in flux by $\sim 55{{\ \rm per\ cent}}$ (∼0.9 mag) in the g band. The Transiting Exoplanet Survey Satellite light curve revealed that the source is a highly eccentric, eclipsing binary. Fits to the light curve using phoebe find the binary orbit to have e = 0.79, Porb = 18.462 d, and i = 88.6°, and the ratios of the stellar radii and temperatures to be R2/R1 = 0.71 and Te,2/Te,1 = 0.82. Both stars are chromospherically active, allowing us to determine their rotational periods of P1 = 1.52 d and P2 = 1.79 d, respectively. A Large Binocular Telescope/Multi-Object Double Spectrograph spectrum shows that the primary is a late-G- or early-K-type dwarf. Fits to the spectral energy distribution show that the luminosities and temperatures of the two stars are L1 = 0.48 L⊙, $T_1= 5050\, \mathrm{K}$, L2 = 0.12 L⊙, and $T_{2} = 4190\, \mathrm{K}$. We conclude that ASASSN-V J192114.84+624950.8 consists of two chromospherically active, rotational variable stars in a highly elliptical eclipsing orbit.

 

Low luminosity active galactic nuclei (LLAGN) probe accretion physics in the low Eddington regime can provide additional clues about galaxy evolution. AGN variability is ubiquitous and thus provides a reliable tool for finding AGN. We analyze the All-Sky Automated Survey for SuperNovae light curves of 1218 galaxies withg< 14 mag and Sloan Digital Sky Survey spectra in search of AGN. We find 37 objects that are both variable and have AGN-like structure functions, which is about 3% of the sample. The majority of the variability selected AGN are LLAGN with Eddington ratios ranging from 10⁻⁴to 10⁻². We thus estimate the fraction of LLAGN in the population of galaxies as 2% down to a median Eddington ratio of 2 × 10⁻³. Combining the BPT line ratio AGN diagnostics and the broad-line AGN, up to ∼60% of the AGN candidates are confirmed spectroscopically. The BPT diagnostics also classified 10%–30% of the candidates as star-forming galaxies rather than AGN.

 

Abstract We present the first results from Citizen ASAS-SN, a citizen science project for the All-Sky Automated Survey for Supernovae (ASAS-SN) hosted on the Zooniverse platform. Citizen ASAS-SN utilizes the newer, deeper, higher cadence ASAS-SN g -band data and tasks volunteers to classify periodic variable star candidates based on their phased light curves. We started from 40,640 new variable candidates from an input list of ∼7.4 million stars with δ < −60° and the volunteers identified 10,420 new discoveries which they classified as 4234 pulsating variables, 3132 rotational variables, 2923 eclipsing binaries, and 131 variables flagged as Unknown. They classified known variable stars with an accuracy of 89% for pulsating variables, 81% for eclipsing binaries, and 49% for rotational variables. We examine user performance, agreement between users, and compare the citizen science classifications with our machine learning classifier updated for the g -band light curves. In general, user activity correlates with higher classification accuracy and higher user agreement. We used the user’s “Junk” classifications to develop an effective machine learning classifier to separate real from false variables, and there is a clear path for using this “Junk” training set to significantly improve our primary machine learning classifier. We also illustrate the value of Citizen ASAS-SN for identifying unusual variables with several examples. 

ABSTRACT We present updated results of the Large Binocular Telescope Search for Failed Supernovae. This search monitors luminous stars in 27 nearby galaxies with a current baseline of 11 yr of data. We re-discover the failed supernova (SN) candidate N6946-BH1 as well as a new candidate, M101-OC1. M101-OC1 is a blue supergiant that rapidly disappears in optical wavelengths with no evidence for significant obscuration by warm dust. While we consider other options, a good explanation for the fading of M101-OC1 is a failed SN, but follow-up observations are needed to confirm this. Assuming only one clearly detected failed SN, we find a failed SN fraction $f = 0.16^{+0.23}_{-0.12}$ at 90 per cent confidence. We also report on a collection of stars that show slow (∼decade), large amplitude (ΔL/L > 3) luminosity changes. 

We present the first estimate of the Galactic nova rate based on optical transient surveys covering the entire sky. Using data from the All-Sky Automated Survey for Supernovae (ASAS-SN) and Gaia—the only two all-sky surveys to report classical nova candidates—we find 39 confirmed Galactic novae and 7 additional unconfirmed candidates discovered from 2019 to 2021, yielding a nova discovery rate of ≈14 yr⁻¹. Using accurate Galactic stellar mass models and three-dimensional dust maps and incorporating realistic nova light curves, we have built a sophisticated Galactic nova model to estimate the fraction of Galactic novae discovered by these surveys over this time period. The observing capabilities of each survey are distinct: the high cadence of ASAS-SN makes it sensitive to fast novae, while the broad observing filter and high spatial resolution of Gaia make it more sensitive to highly reddened novae across the entire Galactic plane and bulge. Despite these differences, we find that ASAS-SN and Gaia give consistent Galactic nova rates, with a final joint nova rate of 26 ± 5 yr⁻¹. This inferred nova rate is substantially lower than found by many other recent studies. Critically assessing the systematic uncertainties in the Galactic nova rate, we argue that the role of faint, fast-fading novae has likely been overestimated, but that subtle details in the operation of transient alert pipelines can have large, sometimes unappreciated effects on transient recovery efficiency. Our predicted nova rate can be directly tested with forthcoming red/near-infrared transient surveys in the southern hemisphere.

 

ABSTRACT The majority of non-merging stellar mass black holes are discovered by observing high energy emission from accretion processes. Here, we pursue the large, but still mostly unstudied population of non-interacting black holes and neutron stars by searching for the tidally induced ellipsoidal variability of their stellar companions. We start from a sample of about 200 000 rotational variables, semiregular variables, and eclipsing binary stars from the All-Sky Automated Survey for Supernovae. We use a χ2 ratio test followed by visual inspection to identify 369 candidates for ellipsoidal variability. We also discuss how to combine the amplitude of the variability with mass and radius estimates for observed stars to calculate a minimum companion mass, identifying the most promising candidates for high mass companions.