AI Discovers 1,300 Hidden Anomalies in Hubble Archive
TL;DR
ESA researchers used a neural-network tool called AnomalyMatch to scan nearly 100 million tiny image snippets from the 35-year Hubble archive, identifying over 1,300 anomalies—more than 800 of which were not previously documented—mostly related to galactic mergers, jellyfish galaxies, edge-on planet-forming disks, and gravitational lenses; the work demonstrates AI’s power to boost discoveries from archival space data.
Topics:sciencespace#anomalies#artificial-intelligence#astronomy#galactic-mergers#hubble-space-telescope#space
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- Hundreds of new 'anomalies' in Hubble data defy explanation Live Science
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