Single Transit Detection In Kepler With Machine Learning And Onboard Spacecraft Diagnostics

ABSTRACT Exoplanet discovery at long orbital periods requires reliably detecting individual transits without additional information about the system. Techniques like phase-folding of light curves and periodogram analysis of radial velocity data are more sensitive to planets with shorter orbital periods, leaving a dearth of planet discoveries at long periods. We present a novel technique using an ensemble of Convolutional Neural Networks incorporating the onboard spacecraft diagnostics of Kepler to classify transits within a light curve. We create a pipeline to recover the location of individual transits, and the period of the orbiting planet, which maintains > 80% transit recovery sensitivity out to an 800-day orbital period. Our neural network pipeline has the potential to discover additional planets in the Kepler dataset, and crucially, within the η-Earth regime. We report our first candidate from this pipeline, KOI 1271.02. KOI 1271.01 is known to exhibit strong Transit Timing Variations (TTVs), and so we jointly model the TTVs and transits of both transiting planets to constrain the orbital configuration and planetary parameters and conclude with a series of potential parameters for KOI 1271.02, as there is not enough data currently to uniquely constrain the system. We conclude that KOI 1271.02 has a radius of 5.32 0.20 R INTRODUCTION studies to measure masses and potentially detect their atmospheric composition. Since the discovery of the first exoplanets, there has Thousands of confirmed planets and thousands of been a rapid increase in the number of exoplanets discovered more planet candidate signals have been found within (Wolszczan & Frail 1992; Mayor & Queloz 1995; the Kepler field of view (Borucki et al. 2011; Batalha Charbonneau et al. 2000). With the discovery of more et al. 2013; Thompson et al. 2018; Morton et al. 2016) exoplanets, it became possible to perform demographic as well as within the current TESS sample Guerrero studies of exoplanets and dissect the population along et al. (2021). These discoveries have enabled statistical other axes (such as stellar metallicity, for example). Of particular interest is the occurrence observed roughly 150,000 stars photometrically during rate of Earth-like planets around Sun-like stars (i.e. - its main mission Borucki et al. (2010). Kepler continued η-Earth) (Fressin et al. 2013; Catanzarite & Shao 2011; to observe the sky after two of its reaction wheels broke Petigura et al. 2013; Foreman-Mackey et al. 2014; Farr as the K2 mission Howell et al. (2014). Kepler was a statistical et al. 2014; Silburt et al. 2015; Burke et al. 2015; Traub mission aimed at finding the frequency of Earthlike 2015; Garrett et al. 2018; Mulders et al. 2018; Hsu et al. planets around Sun-like stars, η-Earth.