AI is helping astronomers advance our understanding of the universe through a breakthrough innovation called Deep Loop Shaping. This novel artificial intelligence method enhances the stability and precision of one of the most sensitive scientific instruments ever built—LIGO, the Laser Interferometer Gravitational-Wave Observatory. By reducing noise in the observatory’s feedback control systems, Deep Loop Shaping enables more accurate detection of gravitational waves, the faint ripples in spacetime caused by cataclysmic cosmic events like black hole mergers and neutron star collisions. Published in the journal Science, the research details how Deep Loop Shaping cuts control system noise by 30 to 100 times in the most unstable feedback loops at LIGO. This improvement stabilizes the observatory’s ultra-precise mirrors, which are critical for measuring gravitational waves. The method was developed in collaboration with Caltech and the Gran Sasso Science Institute (GSSI), and successfully tested at LIGO’s facility in Livingston, Louisiana. LIGO uses laser beams traveling 4 kilometers between mirrors housed in massive vacuum chambers. When a gravitational wave passes through, it causes tiny distortions in space—so small they are smaller than the width of an atomic nucleus. These changes are detected by measuring shifts in the laser interference pattern. However, even minor disturbances, such as ocean waves 100 miles away, can interfere with measurements. LIGO relies on thousands of real-time control systems to counteract vibrations and maintain alignment. Deep Loop Shaping improves the performance of these systems, especially in the most challenging control loops. By applying the method across all mirror control loops, scientists could detect hundreds more gravitational wave events each year, with greater detail and sensitivity. This advancement is particularly important for studying intermediate-mass black holes—long-theorized objects that may bridge the gap between stellar-mass and supermassive black holes—and could provide new insights into galaxy formation and evolution. The work represents a shift in how we explore the cosmos. As physicist Rana Adhikari of Caltech put it, studying the universe through gravity is like listening instead of looking. Deep Loop Shaping helps tune in to the “bass” of the cosmos—revealing deeper, previously undetectable signals. Beyond astronomy, the method has potential applications in aerospace, robotics, and structural engineering, where vibration suppression and noise cancellation are critical. The research team includes experts from Caltech, GSSI, and Google DeepMind, and was made possible by the dedicated efforts of the LIGO instrument team. This collaboration marks a major step forward in using AI to unlock the mysteries of the universe.