An Automated Catalog of Long Period Variables using Infrared Lightcurves from Palomar Gattini-IR

Abstract

Abstract Long Period Variables (LPVs) are stars with periods of several hundred days, representing the late, dust-enshrouded phase of stellar evolution in low to intermediate mass stars. In this paper, we present a catalog of 154,755 LPVs using near-IR lightcurves from the Palomar Gattini-IR (PGIR) survey. PGIR has been surveying the entire accessible northern sky (δ > −28°) in the J-band at a cadence of 2–3 days since 2018 September, and has produced J-band lightcurves for more than 60 million sources. We used a gradient-boosted decision tree classifier trained on a comprehensive feature set extracted from PGIR lightcurves to search for LPVs in this data set. We developed a parallelized and optimized code to extract features at a rate of ∼0.1 s per lightcurve. Our model can successfully distinguish LPVs from other stars with a true positive rate of 95%. Cross-matching with known LPVs, we find 70,369 (∼46%) new LPVs in our catalog.