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Systematic KMTNet Planetary Anomaly Search. I. OGLE-2019-BLG-1053Lb, a Buried Terrestrial Planet

Zang et al. (2021)

Kyu-Ha Hwang #2 Co-author Sun-Ju Chung #12 Co-author Youn Kil Jung #14 Co-author Yoon-Hyun Ryu #15 Co-author In-Gu Shin #16 Co-author Sang-Mok Cha #18 Co-author Dong-Jin Kim #19 Co-author Hyoun-Woo Kim #20 Co-author Seung-Lee Kim #21 Co-author Chung-Uk Lee #22 Co-author Dong-Joo Lee #23 Co-author Yongseok Lee #24 Co-author Byeong-Gon Park #25 Co-author
THE ASTRONOMICAL JOURNAL IF 5.84 A 등급 International collaboration
KMTNet(외계행성 탐색시스템)

Abstract

In order to exhume the buried signatures of “missing planetary caustics” in Korea Microlensing Telescope Network (KMTNet) data, we conducted a systematic anomaly search of the residuals from point-source point-lens fits, based on a modified version of the KMTNet EventFinder algorithm. This search revealed the lowest-mass ratio planetary caustic to date in the microlensing event OGLE-2019-BLG-1053, for which the planetary signal had not been noticed before. The planetary system has a planet-host mass ratio of q = (1.25 ± 0.13) × 10^-5. A Bayesian analysis yielded estimates of the mass of the host star, M_host = 0.61^+0.29_-0.24 M_Sun, the mass of its planet, M_planet = 2.48^+1.19_-0.98 M_Earth, the projected planet-host separation, a = 3.4^+0.5_-0.5 au, and the lens distance, D_L = 6.8^+0.6_-0.9 kpc. The discovery of this very-low-mass-ratio planet illustrates the utility of our method and opens a new window for a large and homogeneous sample to study the microlensing planet-host mass ratio function down to q ∼ 10^-5.

AI Classification

Maturity Tier

Tier 1 — Classical ML

AI Role

detection / segmentation

supporting

Techniques

classical-ML

Tasks

anomaly-detection

Subfield

exoplanets

time-series

Flags

Develops AI method
· Classification confidence: 90%