TY - JOUR
T1 - An Automated Catalog of Long Period Variables using Infrared Lightcurves from Palomar Gattini-IR
AU - Suresh, Aswin
AU - Karambelkar, Viraj
AU - Kasliwal, Mansi M.
AU - Ashley, Michael C.B.
AU - De, Kishalay
AU - Hankins, Matthew J.
AU - Moore, Anna M.
AU - Soon, Jamie
AU - Soria, Roberto
AU - Travouillon, Tony
AU - Truong, Kayton K.
N1 - Publisher Copyright:
© 2024. The Author(s). Published by IOP Publishing Ltd on behalf of the Astronomical Society of the Pacific (ASP).
PY - 2024/8/20
Y1 - 2024/8/20
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85201766478&partnerID=8YFLogxK
U2 - 10.1088/1538-3873/ad68a4
DO - 10.1088/1538-3873/ad68a4
M3 - Article
AN - SCOPUS:85201766478
SN - 0004-6280
VL - 136
JO - Publications of the Astronomical Society of the Pacific
JF - Publications of the Astronomical Society of the Pacific
IS - 8
M1 - 084203
ER -