Artificial Intelligence uncovers more than 100 new worlds in NASA data – Astronomy Now
An artist’s impression of a planet so close it to its star that it completes an orbit in 10.5 hours. Credit: NASA, ESA, and A. Schaller (for STScI).
An artificial intelligence tool developed at the University of Warwick has uncovered a rich haul of previously hidden exoplanets in data from NASA’s Transiting Exoplanet Survey Satellite (TESS), validating more than 100 worlds and identifying thousands more candidates.
The new system, called RAVEN (RAnking and Validation of ExoplaNets), was applied to observations of more than 2.2 million stars collected during the first four years of the TESS mission. By combining automated detection, machine learning and statistical validation into a single pipeline, the team has produced one of the most comprehensive catalogues of close orbiting planets to...



