Systematic KMTNet Planetary Anomaly Search. VII. Complete Sample of q &lt; 10<sup>−4</sup> Planets from the First 4 yr Survey

Zang, Weicheng; Jung, Youn Kil; Yang, Hongjing; Zhang, Xiangyu; Udalski, A.; Yee, Jennifer C.; Gould, Andrew; Mao, Shude; Albrow, M. D.; Chung, Sun-Ju; Han, Cheongho; Hwang, Kyu-Ha; Ryu, Yoon-Hyun; Shin, In-Gu; Shvartzvald, Yossi; Cha, Sang-Mok; Kim, Dong-Jin; Kim, Hyoun-Woo; Kim, S.-L.; Lee, Chung-Uk; Lee, Dong-Joo; Lee, Yongseok; Park, Byeong-Gon; Pogge, Richard W.; Mróz, P.; Skowron, J.; Poleski, R.; Szymański, M. K.; Soszyński, I.; Pietrukowicz, P.; Kozłowski, S.; Ulaczyk, K.; Rybicki, K.; Iwanek, P.; Wrona, Marcin; Gromadzki, M.; Wang, Hanyue; Zhang, Jiyuan; Zhu, Wei

doi:10.3847/1538-3881/acb34b

Cited by 21 publications

(19 citation statements)

References 84 publications

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“…However, in contrast to the majority of published by-eye discoveries (but similar to most of the new AnomalyFinder discoveries reported in Zang et al 2021Zang et al , 2022Zang et al , 2023Gould et al 2022;Hwang et al 2022;Jung et al 2022), most of the planetary events reported in this paper have only upper limits on ρ, and these limits are mostly not very constraining. As discussed by Gould et al (2022), in these cases, θ ast determinations are not likely to be of much use, either now or in the future.…”

Section: Source Propertiescontrasting

confidence: 50%

“…Among these five planets, none is truly exceptional in its own right, although OGLE-2019-BLG-0679 has a relatively large normalized projected separation, s = 2.18. Indeed, among the 53 previously published (or summarized) AnomalyFinder planets from 2018 and 2019 (Gould et al 2022;Jung et al 2022;Zang et al 2022Zang et al , 2023, only one had a larger separation, i.e., OGLE-2018-BLG-0383, with s = 2.45 (Wang et al 2022).…”

Section: Summary Of All 2019 Subprime Anomalyfinder Planetsmentioning

confidence: 98%

“…We present the analysis of all planetary events that were identified by the KMTNet AnomalyFinder algorithm (Zang et al 2021(Zang et al , 2022 and occurred during the 2019 season within the 21 subprime KMTNet fields covering ∼84 deg 2 that lie in the periphery of the richest microlensing region of the Galactic bulge and are observed with cadences Γ = 0.2-1 hr −1 . This work follows the publication of complete samples of the 2018 prime (Gould et al 2022;Hwang et al 2022;Wang et al 2022) and subprime (Jung et al 2022) AnomalyFinder events, the 2019 prime (Zang et al 2021;Hwang et al 2022;Zang et al 2022) events, and a complete sample of all events from 2016 to 2019 with planet-host mass ratios q < 10 −4 (Zang et al 2023). The above references are (ignoring duplicates) Papers I, IV, II, III, V, VI, and VII, in the AnomalyFinder series.…”

Section: Introductionmentioning

confidence: 99%

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Systematic KMTNet Planetary Anomaly Search. VIII. Complete Sample of 2019 Subprime Field Planets

Jung

Zang

Wang

et al. 2023

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We complete the publication of all microlensing planets (and “possible planets”) identified by the uniform approach of the KMT AnomalyFinder system in the 21 KMT subprime fields during the 2019 observing season, namely, KMT-2019-BLG-0298, KMT-2019-BLG-1216, KMT-2019-BLG-2783, OGLE-2019-BLG-0249, and OGLE-2019-BLG-0679 (planets), as well as OGLE-2019-BLG-0344 and KMT-2019-BLG-0304 (possible planets). The five planets have mean log mass ratio measurements of (−2.6, −3.6, −2.5, −2.2, −2.3), median mass estimates of (1.81, 0.094, 1.16, 7.12, 3.34) M Jup, and median distance estimates of (6.7, 2.7, 5.9, 6.4, 5.6) kpc, respectively. The main scientific interest of these planets is that they complete the AnomalyFinder sample for 2019, which has a total of 25 planets that are likely to enter the statistical sample. We find statistical consistency with the previously published 33 planets from the 2018 AnomalyFinder analysis according to an ensemble of five tests. Of the 58 planets from 2018–2019, 23 were newly discovered by AnomalyFinder. Within statistical precision, half of the planets have caustic crossings, while half do not; an equal number of detected planets result from major- and minor-image light-curve perturbations; and an equal number come from KMT prime fields versus subprime fields.

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Section: Source Propertiescontrasting

confidence: 50%

Section: Summary Of All 2019 Subprime Anomalyfinder Planetsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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Systematic KMTNet Planetary Anomaly Search. VIII. Complete Sample of 2019 Subprime Field Planets

Jung

Zang

Wang

et al. 2023

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“…The fourth criterion is that the maximum value of the source brightness must be >5 times larger than the flux error at the time. We note that this criterion is more conservative than the criterion that is used in the analysis by KMTNet (Zang et al 2022(Zang et al , 2023. The fifth criterion is that there are at least three consecutive points with the observed flux deviating from the constant baseline by more than 5σ.…”

Section: Flux Determinationmentioning

confidence: 99%

Prediction of Planet Yields by the PRime-focus Infrared Microlensing Experiment Microlensing Survey

Kondo

Sumi

Koshimoto

et al. 2023

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The PRime-focus Infrared Microlensing Experiment (PRIME) will be the first to conduct a dedicated near-infrared microlensing survey by using a 1.8 m telescope with a wide field of view of 1.45 deg2 at the South African Astronomical Observatory. The major goals of the PRIME microlensing survey are to measure the microlensing event rate in the inner Galactic bulge to help design the observing strategy for the exoplanet microlensing survey by the Nancy Grace Roman Space Telescope and to make a first statistical measurement of exoplanet demographics in the central bulge fields where optical observations are very difficult owing to the high extinction in these fields. Here we conduct a simulation of the PRIME microlensing survey to estimate its planet yields and determine the optimal survey strategy, using a Galactic model optimized for the inner Galactic bulge. In order to maximize the number of planet detections and the range of planet mass, we compare the planet yields among four observation strategies. Assuming the Cassan et al. mass function as modified by Penny et al., we predict that PRIME will detect planetary signals for 42–52 planets (1–2 planets with M p ≤ 1M ⊕, 22−25 planets with mass 1M ⊕ < M p ≤ 100M ⊕, 19–25 planets 100M ⊕ < M p ≤ 10, 000M ⊕), per year depending on the chosen observation strategy.

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“…We have already done the systematic searches for the 2018 prime field (Wang et al 2022;Hwang et al 2022;Gould et al 2022), 2018 sub-prime fields (Jung et al 2022), 2019 prime fields (Zang et al 2021;Hwang et al 2022;Zang et al 2022a), and 2019 sub-prime fields (Jung et al 2023). In addition, Zang et al (2023) present a complete sample of planets with the mass ratio q < 10 −4 discovered from all candidate events observed from 2016 to 2019. This is the 9th work to build the complete sample, which is conducted for the 2016 prime-fields (i.e., BLG01, BLG41, BLG02, BLG42, BLG03, BLG43).…”

Section: Introductionmentioning

confidence: 99%

Systematic KMTNet Planetary Anomaly Search. VI. Complete Sample of 2018 Sub-prime-field Planets

Jung

Zang

Han

et al. 2022

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We complete the analysis of all 2018 sub-prime-field microlensing planets identified by the KMTNet AnomalyFinder. Among the 9 previously unpublished events with clear planetary solutions, 6 are clearly planetary (OGLE-2018-BLG-0298, KMT-2018-BLG-0087, KMT-2018-BLG-0247, KMT-2018-BLG-0030, OGLE-2018-BLG-1119, and KMT-2018-BLG-2602), while the remaining 3 are ambiguous in nature. The above ordering of these events is made to facilitate grouping of their Bayesian estimates: the first two are lower-mass gas giants while the last four are Jovian-class planets; the first three most likely lie in the bulge, the last in the disk, and the remaining two are equally likely to be in either population. More specifically, these six planets have host masses M host = ( 0.69 − 0.30 + 0.34 , 0.10 − 0.05 + 0.14 , 0.29 − 0.14 + 0.28 , 0.51 − 0.31 + 0.43 , 0.48 − 0.28 + 0.35 , 0.66 − 0.36 + 0.42 ) M ⊙ , planet masses M planet = ( 0.14 − 0.06 + 0.07 , 0.23 − 0.12 + 0.32 , 2.11 − 1.04 + 2.09 , 1.45 − 0.88 + 1.23 , 0.91 − 0.52 + 0.66 , 1.15 − 0.63 + 0.73 ) M Jup , and distances D L = ( 6.54 − 1.23 + 0.95 , 7.02 − 1.15 + 1.03 , 6.76 − 1.24 + 0.99 , 6.48 − 1.96 + 1.28 , 5.76 − 2.48 + 1.43 , 4.31 − 1.84 + 1.97 ) kpc . In addition, there are 8 previously published sub-prime-field planets that were selected by the AnomalyFinder algorithm. Together with a companion paper on 2018 prime-field planets, this work lays the basis for comprehensive statistical studies. We carry out two such studies, one on caustic topologies and the other on the role of Gaia data. From the first, as expected, half (17/33) of the 2018 planets likely to enter the mass-ratio analysis have non-caustic-crossing anomalies. However, only 1 of the 5 noncaustic anomalies with planet-host mass ratio q < 10−3 was discovered by eye (compared to 7 of the 12 with q > 10−3), showing the importance of the semiautomated AnomalyFinder search. From the second, we find that Gaia has played a major role in the interpretation of 16% of the sample and a supplementary role in 6%.

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Systematic KMTNet Planetary Anomaly Search. VII. Complete Sample of q < 10⁻⁴ Planets from the First 4 yr Survey

Cited by 21 publications

References 84 publications

Systematic KMTNet Planetary Anomaly Search. VIII. Complete Sample of 2019 Subprime Field Planets

Systematic KMTNet Planetary Anomaly Search. VIII. Complete Sample of 2019 Subprime Field Planets

Prediction of Planet Yields by the PRime-focus Infrared Microlensing Experiment Microlensing Survey

Systematic KMTNet Planetary Anomaly Search. VI. Complete Sample of 2018 Sub-prime-field Planets

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Systematic KMTNet Planetary Anomaly Search. VII. Complete Sample of q < 10−4 Planets from the First 4 yr Survey

Cited by 21 publications

References 84 publications

Systematic KMTNet Planetary Anomaly Search. VIII. Complete Sample of 2019 Subprime Field Planets

Systematic KMTNet Planetary Anomaly Search. VIII. Complete Sample of 2019 Subprime Field Planets

Prediction of Planet Yields by the PRime-focus Infrared Microlensing Experiment Microlensing Survey

Systematic KMTNet Planetary Anomaly Search. VI. Complete Sample of 2018 Sub-prime-field Planets

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Systematic KMTNet Planetary Anomaly Search. VII. Complete Sample of q < 10⁻⁴ Planets from the First 4 yr Survey