Evidence for 3 new multi-planet systems from TESS using a Bayesian N-body retrieval and machine learning

Abstract

Transiting exoplanets in multi-planet systems exhibit non-Keplerian orbits as a result of the gravitational influence from companions which can cause the times and durations of transits to vary. The amplitude and periodicity of the transit time variations (TTV) are characteristic of the perturbing planet s mass and orbit. The objects of interest (TOI) from the Transiting Exoplanet Survey Satellite are analyzed in a uniform way to search for TTVs with sectors 1-3 of data. Based on an analysis of 74 planet-hosting stars from the TOI catalog an average photometric precision of ~1000 ppm is measured for stars with magnitudes between ~9--11. Due to the volume of targets in the TESS candidate list, artificial intelligence is used to expedite the search for planets by vetting non-transit signals prior to characterizing the light curve time series. The significance of a perturbing planet is assessed by comparing the Bayesian evidence between a linear and non-linear ephemeris, which is based on an N-body simulation. Nested sampling is used to derive posterior distributions for the N-body ephemeris and in order to expedite convergence custom priors are designed using machine learning. A dual input convolutional neural network is designed to predict the parameters of a perturbing body given the known parameters (M*, M1, P1) and measured perturbation (O-C). There is evidence for 3 new multi-planet systems with non-transiting companions using the 2-minute cadence observations from TESS. Two previously known exoplanets were looked at; WASP-18 b and WASP-126 b and there is evidence for WASP-18 c at a period of 2.155+/-0.006 day with a mass of 55.2+/-12.3 M_Earth and WASP-126 c a 64.0+/-26.9 M_Earth planet at an orbital period of 7.65+/-0.27 day. The third system with a significant TTV is TOI 193.01 with a candidate planet, TOI 193.02, at a period of 1.516+/-0.021 day and mass of 39.4+/-9.5 M_Earth.