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

arXiv:2403.03427v1 Announce Type: cross
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 \emph{Kepler} to classify transits within a light curve. We …

abstract analysis arxiv astro-ph.ep astro-ph.im cs.lg data detection diagnostics discovery exoplanet information light machine machine learning spacecraft transit type