KASI AI Hub KASI AI Hub

Systematic KMTNet planetary anomaly search V. Complete sample of 2018 prime-field

Gould et al. (2022)

Kyu-Ha Hwang #5 Co-author Chung, Sun-Ju #9 Co-author Jung Youn Kil #10 Co-author Yoon-Hyun Ryu #11 Co-author Cha, Sang-Mok #15 Co-author Dong-jin Kim #16 Co-author Kim Hyoun-Woo #17 Co-author Kim Seung-Lee #18 Co-author Lee, Chung-Uk #19 Co-author Dong-Joo Lee #20 Co-author Yongseok LEE #21 Co-author PARK, BYEONG GON #22 Co-author
ASTRONOMY & ASTROPHYSICS IF 5.803 A 등급 International collaboration
KMTNet(외계행성 탐색시스템)

Abstract

We complete the analysis of all 2018 prime-field microlensing planets identified by the Korea Microlensing Telescope Network (KMTNet) AnomalyFinder. Among the ten previously unpublished events with clear planetary solutions, eight are either unambiguously planetary or are very likely to be planetary in nature: OGLE-2018-BLG-1126, KMT-2018-BLG-2004, OGLE-2018-BLG-1647, OGLE-2018-BLG-1367, OGLE-2018-BLG-1544, OGLE-2018-BLG-0932, OGLE-2018-BLG-1212, and KMT-2018-BLG-2718. Combined with the four previously published new AnomalyFinder events and 12 previously published (or in preparation) planets that were discovered by eye, this makes a total of 24 2018 prime-field planets discovered or recovered by AnomalyFinder. Together with a paper in preparation on 2018 subprime planets, this work lays the basis for the first statistical analysis of the planet mass-ratio function based on planets identified in KMTNet data. By systematically applying the heuristic analysis to each event, we identified the small modification in their formalism that is needed to unify the so-called close-wide and inner-outer degeneracies.

AI Classification

Maturity Tier

Tier 3 — Physics-tailored

AI Role

detection / segmentation

supporting

Techniques

classical-ML

Tasks

anomaly-detectionclassification

Subfield

exoplanets

time-series

Flags

Develops AI method
· Classification confidence: 90%