Citizen ASAS-SN Data Release II: Variable Star Classification Using Citizen Science

TL;DR

This paper reports on the second data release from Citizen ASAS-SN, a citizen science project that classifies variable stars from light curves, resulting in thousands of new variable star identifications and insights into user classification accuracy.

Contribution

It introduces a large-scale citizen science approach to classify variable stars, providing new variable star data and analyzing user classification performance.

Findings

Identified 4432 new variable stars from 94975 candidates.

Achieved up to 77% user agreement for certain variable types.

Provided a dataset of interesting or unusual variable stars.

Abstract

We present the second 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 tasks users with classifying variable stars based on their light curves. We started with 94975 new variable candidates and identified 4432 new variable stars. The users classified the new variables as 841 pulsating variables, 2995 rotational variables, 350 eclipsing binaries, and 246 unknown variables. We found 68% user agreement for user-classified pulsating variables, 51% for rotational variables, and 77% for eclipsing binaries. We investigate user statistics and compare new variables to known variables. We present a sample of variables flagged as interesting or unusual.