arXiv · 2305.06605
Probable brown dwarf companions detected in binary microlensing events during the 2018-2020 seasons of the KMTNet survey
Abstract
We inspect the microlensing data of the KMTNet survey collected during the 2018--2020 seasons in order to find lensing events produced by binaries with brown-dwarf companions. In order to pick out binary-lens events with candidate BD lens companions, we conduct systematic analyses of all anomalous lensing events observed during the seasons. By applying the selection criterion with mass ratio between the lens components of $0.03\lesssim q\lesssim 0.1$, we identify four binary-lens events with candidate BD companions, including KMT-2018-BLG-0321, KMT-2018-BLG-0885, KMT-2019-BLG-0297, and KMT-2019-BLG-0335. For the individual events, we present the interpretations of the lens systems and measure the observables that can constrain the physical lens parameters. The masses of the lens companions estimated from the Bayesian analyses based on the measured observables indicate that the probabilities for the lens companions to be in the brown-dwarf mass regime are high: 59\%, 68\%, 66\%, and 66\% for the four events respectively.
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Cheongho Han, Youn Kil Jung, Doeon Kim, Andrew Gould, Valerio Bozza, Ian A. Bond, Sun-Ju Chung, Michael D. Albrow, Kyu-Ha Hwang, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Hongjing Yang, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Hyoun-Woo Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Jennifer C. Yee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge, Fumio Abe, Richard Barry, David P. Bennett, Aparna Bhattacharya, Hirosame Fujii, Akihiko Fukui, Yuki Hirao, Stela Ishitani Silva, Rintaro Kirikawa, Iona Kondo, Naoki Koshimoto, Yutaka Matsubara, Sho Matsumoto, Shota Miyazaki, Yasushi Muraki, Arisa Okamura, Greg Olmschenk, Clément Ranc, Nicholas J. Rattenbury, Yuki Satoh, Takahiro Sumi, Daisuke Suzuki, Taiga Toda, Paul J. Tristram, Aikaterini Vandorou, Hibiki Yama, Yoshitaka Itow. 2023-05-11. Probable brown dwarf companions detected in binary microlensing events during the 2018-2020 seasons of the KMTNet survey. https://doi.org/10.1051/0004-6361%2F202245455
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