Systematic KMTNet Planetary Anomaly Search. IV. Complete Sample of 2019 Prime-Field

TL;DR

This paper presents a complete statistical sample of exoplanets detected via microlensing in 2019 by KMTNet, developing an optimized detection algorithm and analyzing planetary properties, revealing a potentially higher occurrence of low-mass planets.

Contribution

The study introduces an optimized anomaly detection algorithm and provides the first homogeneous sample of 14 planets from KMTNet 2019 data, advancing understanding of planetary mass ratios.

Findings

14 planets identified from 2019 KMTNet data.

Planets are mostly cold giants beyond the snow line.

Planet frequency below a certain mass ratio may be higher than previously thought.

Abstract

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 indicates the three planets are all cold giant planets beyond the snow line of their host stars. The 13 planets are basically uniform in $\log q$ over the range $-5.0 < \log q < -1.5$. This result suggests that the planets below $q_{\rm break} = 1.7 \times 10^{-4}$ proposed by the MOA-II survey may be more common than previously believed. This work is an early component of a large project to determine the KMTNet mass-ratio function, and the whole sample of 2016--2019 KMTNet events should contain about 120 planets.