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Systematic reanalysis of KMTNet microlensing events, paper I: Updates of the photometry pipeline and a new planet candidate

Yang et al. (2024)

Kyu-Ha Hwang #3 Co-author Chung, Sun-Ju #12 Co-author Kim Seung-Lee #13 Co-author PARK, BYEONG GON #14 Co-author Jung Youn Kil #16 Co-author Yoon-Hyun Ryu #17 Co-author Cha, Sang-Mok #20 Co-author Dong-jin Kim #21 Co-author Lee, Chung-Uk #23 Co-author Dong-Joo Lee #24 Co-author Yongseok LEE #25 Co-author
Monthly Notices Of The Royal Astronomical Society IF 4.8 A 등급 International collaboration
KMTNet(외계행성 탐색시스템)

Abstract

In this work, we update and develop algorithms for KMTNet tender-love care (TLC) photometry in order to create a new, mostly automated, TLC pipeline. We then start a project to systematically apply the new TLC pipeline to the historic KMTNet microlensing events, and search for buried planetary signals. We report the discovery of such a planet candidate in the microlensing event MOA-2019-BLG-421/KMT-2019-BLG-2991. The anomalous signal can be explained by either a planet around the lens star or the orbital motion of the source star. For the planetary interpretation, despite many degenerate solutions, the planet is most likely to be a Jovian planet orbiting an M or K dwarf, which is a typical microlensing planet. The discovery proves that the project can indeed increase the sensitivity of historic events and find previously undiscovered signals.

AI Classification

Maturity Tier

Tier 1 — Classical ML

AI Role

data-reduction / preprocessing

supporting

Techniques

classical-ML

Tasks

denoising/reconstructiondetection/segmentation

Subfield

exoplanets

time-series

Flags

Develops AI method
· Classification confidence: 80%