Citizen ASAS-SN Data Release I: Variable Star Classification Using Citizen Science
arXiv:2111.02415 · doi:10.1088/1538-3873/ac44f0
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 -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 million stars with and the volunteers identified 10,420 new discoveries which they classified as 4,234 pulsating variables, 3,132 rotational variables, 2,923 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 -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.
19 pages, 20 figures, 4 tables. Submitted to MNRAS. The DR1 catalog and light curves are available here: https://drive.google.com/drive/folders/1sLyJuOTAdEfccSOVkBIhb9YlK6JfOFXl?usp=sharing
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- The All-Sky Automated Survey for Supernovae (ASAS-SN) Light Curve Server v1.0
- Eclipsing binary stars with a Scuti component
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Cited by in corpus (7)
- The ASAS-SN Catalog of Variable Stars X: Discovery of 116,000 New Variable Stars Using g-band Photometry
- YSE-PZ: A Transient Survey Management Platform that Empowers the Human-in-the-Loop
- The Value-Added Catalog of ASAS-SN Eclipsing Binaries: Parameters of Thirty Thousand Detached Systems
- Supervised machine learning on Galactic filaments Revealing the filamentary structure of the Galactic interstellar medium
- The Atacama Cosmology Telescope: Systematic Transient Search of 3-Day Maps
- Bursts from Space: MeerKAT - The first citizen science project dedicated to commensal radio transients
- Stellar X-ray activity and habitability revealed by ROSAT sky survey