AI exoplanet validation: RAVEN pipeline confirms 118 new TESS planets at 91% accuracy
AnalysisA University of Warwick-led team released RAVEN (a Bayesian classifier built on gradient-boosted decision trees and Gaussian processes) and used it to validate 118 new exoplanets in NASA's TESS data, the satellite scanning 2.2 million stars for orbital dips. The pipeline hit 91% accuracy and 97% precision on a 1,361-candidate test set, with uncertainties on close-in planet abundance cut by roughly a factor of ten. Candidate-vetting that used to fill PhD dissertations for two or three years now runs as a single classifier pass. The work landed as an arXiv preprint with two companion papers in MNRAS.