SuperWASP Variable Stars: Classifying Light Curves Using Citizen Science

TL;DR

This paper reports on classifying over a million variable star light curves from the SuperWASP survey using citizen science, revealing new stellar variables and demonstrating the project's scientific value.

Contribution

It introduces a large-scale citizen science classification effort for stellar light curves, providing a new dataset and preliminary findings on rare and unknown variables.

Findings

89% accuracy for eclipsing binary classifications

Identification of 301 new stellar variables

Discovery of extreme and unusual variable stars

Abstract

We present the first analysis of results from the SuperWASP Variable Stars Zooniverse project, which is aiming to classify 1.6 million phase-folded light curves of candidate stellar variables observed by the SuperWASP all sky survey with periods detected in the SuperWASP periodicity catalogue. The resultant data set currently contains $>$1 million classifications corresponding to $>$500,000 object-period combinations, provided by citizen scientist volunteers. Volunteer-classified light curves have $\sim$89 per cent accuracy for detached and semi-detached eclipsing binaries, but only $\sim$9 per cent accuracy for rotationally modulated variables, based on known objects. We demonstrate that this Zooniverse project will be valuable for both population studies of individual variable types and the identification of stellar variables for follow up. We present preliminary findings on various unique and extreme variables in this analysis, including long period contact binaries and binaries near the short-period cutoff, and we identify 301 previously unknown binaries and pulsators. We are now in the process of developing a web portal to enable other researchers to access the outputs of the SuperWASP Variable Stars project.