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1. Citizen ASAS-SN Data Release. I. Variable Star Classification Using Citizen Science

   https://doi.org/10.1088/1538-3873/ac44f0  

   Christy, C. T.; Jayasinghe, T.; Stanek, K. Z.; Kochanek, C. S.; Way, Z.; Prieto, J. L.; Shappee, B. J.; Holoien, T. W.-S.; Thompson, T. A.; Schneider, A. (February 2022, Publications of the Astronomical Society of the Pacific)

   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. 

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2. The ASAS-SN bright supernova catalogue – IV. 2017

   https://doi.org/10.1093/mnras/stz073  

   Holoien, T W-S; Brown, J S; Vallely, P J; Stanek, K Z; Kochanek, C S; Shappee, B J; Prieto, J L; Dong, Subo; Brimacombe, J; Bishop, D W; et al (January 2019, Monthly Notices of the Royal Astronomical Society)
3. A Catalog of M-dwarf Flares with ASAS-SN

   https://doi.org/10.3847/1538-4357/ab793a  

   Rodríguez Martínez, Romy; Lopez, Laura A.; Shappee, Benjamin J.; Schmidt, Sarah J.; Jayasinghe, Tharindu; Kochanek, Christopher S.; Auchettl, Katie; Holoien, Thomas W.-S. (April 2020, The Astrophysical Journal)
4. The ASAS-SN bright supernova catalogue – V. 2018–2020

   https://doi.org/10.1093/mnras/stad355  

   Neumann, K. D.; Holoien, T. W-S; Kochanek, C. S.; Stanek, K. Z.; Vallely, P. J.; Shappee, B. J.; Prieto, J. L.; Pessi, T.; Jayasinghe, T.; Brimacombe, J.; et al (February 2023, Monthly Notices of the Royal Astronomical Society)

   ABSTRACT We catalogue the 443 bright supernovae (SNe) discovered by the All-Sky Automated Survey for Supernovae (ASAS-SN) in 2018−2020 along with the 519 SNe recovered by ASAS-SN and 516 additional mpeak ≤ 18 mag SNe missed by ASAS-SN. Our statistical analysis focuses primarily on the 984 SNe discovered or recovered in ASAS-SN g-band observations. The complete sample of 2427 ASAS-SN SNe includes earlier V-band samples and unrecovered SNe. For each SN, we identify the host galaxy, its UV to mid-IR photometry, and the SN’s offset from the centre of the host. Updated peak magnitudes, redshifts, spectral classifications, and host galaxy identifications supersede earlier results. With the increase of the limiting magnitude to g ≤ 18 mag, the ASAS-SN sample is nearly complete up to mpeak = 16.7 mag and is 90 per cent complete for mpeak ≤ 17.0 mag. This is an increase from the V-band sample, where it was roughly complete up to mpeak = 16.2 mag and 70 per cent complete for mpeak ≤ 17.0 mag. 

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5. ASAS-SN follow-up of IceCube high-energy neutrino alerts

   https://doi.org/10.1093/mnras/stac2261  

   Necker, Jannis; de Jaeger, Thomas; Stein, Robert; Franckowiak, Anna; Shappee, Benjamin J.; Kowalski, Marek; Kochanek, Christopher S.; Stanek, Krzysztof Z.; Beacom, John F.; Desai, Dhvanil D.; et al (August 2022, Monthly Notices of the Royal Astronomical Society)

   ABSTRACT We report on the search for optical counterparts to IceCube neutrino alerts released between 2016 April and 2021 August with the All-Sky Automated Survey for SuperNovae (ASAS-SN). Despite the discovery of a diffuse astrophysical high-energy neutrino flux in 2013, the source of those neutrinos remains largely unknown. Since 2016, IceCube has published likely astrophysical neutrinos as public real-time alerts. Through a combination of normal survey and triggered target-of-opportunity observations, ASAS-SN obtained images within 1 h of the neutrino detection for 20 per cent (11) of all observable IceCube alerts and within one day for another 57 per cent (32). For all observable alerts, we obtained images within at least two weeks from the neutrino alert. ASAS-SN provides the only optical follow-up for about 17 per cent of IceCube’s neutrino alerts. We recover the two previously claimed counterparts to neutrino alerts, the flaring-blazar TXS 0506 + 056 and the tidal disruption event AT2019dsg. We investigate the light curves of previously detected transients in the alert footprints, but do not identify any further candidate neutrino sources. We also analysed the optical light curves of Fermi 4FGL sources coincident with high-energy neutrino alerts, but do not identify any contemporaneous flaring activity. Finally, we derive constraints on the luminosity functions of neutrino sources for a range of assumed evolution models. 

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