AI Discovers 100+ Hidden Exoplanets in NASA Data Including Rare Extreme Worlds

TITLE: AI Discovers 100+ Hidden Exoplanets in NASA Data Including Rare Extreme Worlds INTRO: Astronomers have unleashed a powerful new AI tool called RAVEN to analyze NASA's TESS mission data, confirming over 100 exoplanets including 31 brand-new worlds and identifying thousands more candidates, revealing rare extreme planets that orbit their stars in less than a day. KEY HIGHLIGHTS: - RAVEN AI system confirmed 100+ exoplanets from NASA TESS data with 31 new discoveries - Identified rare ultra-short period planets orbiting stars in less than 24 hours - Found planets in Neptunian desert region where such worlds were thought to be scarce - Thousands more planet candidates identified for follow-up observation - Demonstrates AI transformative impact on astronomical discovery and data analysis WHAT HAPPENED: A team of astronomers from the University of Warwick deployed an advanced AI system called RAVEN to analyze data from NASA's Transiting Exoplanet Survey Satellite, resulting in one of the largest single-batch exoplanet confirmations to date. The system processed light curves from millions of stars, identifying characteristic dips in brightness that indicate planets. The AI confirmed over 100 exoplanets with 31 being entirely new discoveries. Among the most exciting finds are ultra-short period planets that complete full orbits in less than 24 hours and planets in the Neptunian desert where Neptune-sized planets were thought to be rare. WHY IT MATTERS: For astronomers and data scientists, this demonstrates the transformative power of AI in handling massive datasets generated by modern telescopes. TESS alone has observed hundreds of thousands of stars producing terabytes of data that would take human researchers years to analyze. For the broader scientific community, discovery of planets in unexpected regions challenges existing theories of planetary formation. These extreme worlds provide natural laboratories for studying atmospheric physics and gravitational dynamics. For the general public, each new exoplanet brings us closer to answering whether we are alone in the universe. WHAT'S NEXT: The RAVEN team plans to expand analysis to additional TESS data releases and potentially other exoplanet survey missions. With thousands more candidates identified, follow-up observations using ground-based telescopes and space observatories like James Webb will be critical. Future AI systems will likely incorporate more sophisticated models capable of detecting smaller Earth-sized planets. The success of RAVEN suggests AI will play increasingly central roles in other areas of astronomy from detecting gravitational waves to classifying galaxy formations. SOURCE: https://www.sciencedaily.com/releases/2026/05/260502233926.htm