Exploring the Variable Sky with LINEAR. III. Classification of Periodic Light Curves

TL;DR

This paper presents a large, reliable catalog of approximately 7,000 faint periodic variable stars from the LINEAR survey, including classifications and analysis useful for galactic and stellar studies.

Contribution

It introduces a new, extensive sample of classified periodic variables from LINEAR, utilizing SDSS calibration and machine learning for validation, expanding the known variable star population.

Findings

Dominance of RR Lyrae and eclipsing binary stars in the sample

Identification of rare stellar populations like AGB and SX Phoenicis stars

Discovery of a strong correlation between period and color in eclipsing binaries

Abstract

We describe the construction of a highly reliable sample of approximately 7,000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 sq.deg of northern sky. Majority of these variables have not been cataloged yet. The sample flux limit is several magnitudes fainter than for most other wide-angle surveys; the photometric errors range from ~0.03 mag at $r=15$ to ~0.20 mag at r=18. Light curves include on average 250 data points, collected over about a decade. Using SDSS-based photometric recalibration of the LINEAR data for about 25 million objects, we selected ~200,000 most probable candidate variables and visually confirmed and classified approximately 7,000 periodic variables using phased light curves. The reliability and uniformity of visual classification across eight human classifiers was calibrated and tested using a SDSS Stripe 82 region variable star catalog, and verified using an unsupervised machine learning approach. The resulting sample of periodic LINEAR variables is dominated by 3,900 RR Lyrae stars and 2,700 eclipsing binary stars of all subtypes, and includes small fractions of relatively rare populations such as asymptotic giant branch stars and SX Phoenicis stars. We discuss the distribution of these mostly uncataloged variables in various diagrams constructed with optical-to-infrared SDSS, 2MASS and WISE photometry, and with LINEAR light curve features. An interesting side result is a robust and precise quantitative description of a strong correlation between the light-curve period and color/spectral type for close and contact eclipsing binary stars. These large samples of robustly classified variable stars will enable detailed statistical studies of the Galactic structure and physics of binary and other stars, and we make them publicly available.