{"paper":{"title":"Systematic KMTNet Planetary Anomaly Search. IV. Complete Sample of 2019 Prime-Field","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["astro-ph.GA"],"primary_cat":"astro-ph.EP","authors_text":"Andrew Gould, Andrzej Udalski, Byeong-Gon Park, Cheongho Han, Chung-Uk Lee, Dong-Jin Kim, Dong-Joo Lee, Hongjing Yang, Hyoun-Woo Kim, Igor Soszy\\'nski, In-Gu Shin, Jan Skowron, Jennifer C. Yee, Krzysztof A. Rybicki, Krzysztof Ulaczyk, Kyu-Ha Hwang, Marcin Wrona, Mariusz Gromadzki, Michael D. Albrow, Micha{\\l} K. Szyma\\'nski, Patryk Iwanek, Pawe{\\l} Pietrukowicz, Przemek Mr\\'oz, Radoslaw Poleski, Sang-Mok Cha, Seung-Lee Kim, Shude Mao, Sun-Ju Chung, Szymon Koz{\\l}owski, Weicheng Zang, Wei Zhu, Xiangyu Zhang, Yongseok Lee, Yoon-Hyun Ryu, Yossi Shvartzvald, Youn Kil Jung","submitted_at":"2022-04-05T06:39:05Z","abstract_excerpt":"We report the complete statistical planetary sample from the prime fields ($\\Gamma \\geq 2~{\\rm hr}^{-1}$) of the 2019 Korea Microlensing Telescope Network (KMTNet) microlensing survey. We develop the optimized KMTNet AnomalyFinder algorithm and apply it to the 2019 KMTNet prime fields. We find a total of 14 homogeneously selected planets and report the analysis of three planetary events, KMT-2019-BLG-(1042,1552,2974). The planet-host mass ratios, $q$, for the three planetary events are $6.34 \\times 10^{-4}, 4.89 \\times 10^{-3}$ and $6.18 \\times 10^{-4}$, respectively. A Bayesian analysis indic"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.02017","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2204.02017/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}