Powerful AI finds 100+ hidden planets in NASA data including rare and extreme worlds
Powerful AI finds 100+ hidden planets in NASA data including rare and extreme worlds
http://www.sciencedaily.com/releases/2026/05/260502233926.htm
Publish Date: 2026-05-03 00:58:00
Source Domain: www.sciencedaily.com
Astronomers at the University of Warwick have confirmed more than 100 exoplanets, including 31 newly identified worlds, using a new artificial intelligence system. The team applied this tool to data from NASA’s Transiting Exoplanet Survey Satellite (TESS), a mission that scans the sky for slight dips in starlight that occur when a planet crosses in front of its host star.
Their findings, published in MNRAS, are based on a detailed analysis of observations from more than 2.2 million stars gathered during TESS’s first four years. The researchers focused on planets that orbit very close to their stars, completing a full orbit in less than 16 days. This approach has produced one of the most precise measurements yet of how common these short-period planets are.
“Using our newly developed RAVEN pipeline, we were able to validate 118 new planets, and over 2,000 high-quality planet candidates, nearly 1,000 of them entirely new,” said first author Dr. Marina Lafarga Magro, Postdoctoral Researcher at the University of Warwick. “This represents one of the best characterized samples of close in planets and will help us identify the most promising systems for future study.”
Rare and Extreme Planet Types Identified
The newly confirmed planets include several especially interesting categories. Some are ultra-short-period planets that circle their stars in under 24 hours. Others belong to the so-called ‘Neptunian desert,’ a region where few planets are expected to exist based on current theories. The study also revealed tightly packed multi-planet systems, including previously unknown pairs of planets orbiting the same star.
How RAVEN Improves Planet Detection
Modern planet-hunting missions often flag thousands of possible planets, but determining which signals are genuine remains difficult. Many false signals can mimic planets, including eclipsing binary stars.
“The challenge lies in identifying if the dimming is indeed caused by a planet in orbit around the star or by…
