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

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Suresh, Aswin
Karambelkar, Viraj
Kasliwal, Mansi M.
Ashley, Michael C.B.
De, Kishalay
Hankins, Matthew J.
Moore, Anna M.
Soon, Jamie
Soria, Roberto
Travouillon, Tony

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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.

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Publications of the Astronomical Society of the Pacific

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