AI model's insight helps astronomers propose new theory for observing far-off worlds – TechCrunch

Machine learning models are increasingly augmenting human processes, either performing repetitious tasks faster or providing some systematic insight that helps put human knowledge in perspective. Astronomers at UC Berkeley were surprised to find both happen after modeling gravitational microlensing events, leading to a new unified theory for the phenomenon. Gravitational lensing occurs when light from far-off stars and other stellar objects bends around a nearer one directly between it and the observer, briefly giving a brighter -- but distorted -- view of the farther one. Depending on how the light bends (and what we know about the distant object), we can also learn a lot about the star, planet, or system that the light is bending around. For example, a momentary spike in brightness suggests a planetary body transiting the line of sight, and this type of anomaly in the reading, called a "degeneracy" for some reason, has been used to spot thousands of exoplanets.