量子位·2025-09-13 06:07Core Viewpoint - The collaboration between Google DeepMind, LIGO, and GSSI has led to the development of Deep Loop Shaping technology, significantly enhancing the low-frequency noise reduction capabilities in gravitational wave detection, allowing for more effective observation of cosmic events [1][4][14]. Summary by Sections Gravitational Waves and Detection Challenges - Gravitational waves are minute disturbances in spacetime caused by events like black hole and neutron star collisions, with signals weaker than atomic nuclei [6][7]. - The LIGO detector, spanning 2.5 miles (approximately 4 kilometers), is designed to capture these faint signals by measuring the interference of laser beams in two vacuum tubes [8][10]. - The detection of gravitational waves has been historically limited by noise interference, particularly in the 10-30Hz low-frequency range, which is crucial for observing medium-mass black hole mergers and neutron star collisions [13]. Breakthrough with AI Technology - The Deep Loop Shaping technology utilizes AI to manage noise rather than directly searching for gravitational waves, reconstructing LIGO's feedback control system [16][18]. - By simulating various noise factors and employing reinforcement learning, the AI optimized the detector's feedback loop, achieving a noise reduction in the 10-30Hz range to 1/30 of traditional methods, with some sub-bands reduced to 1/100 [18][20]. - This advancement has expanded LIGO's effective observation range from 130 million light-years to 170 million light-years, increasing the observable cosmic volume by 70% and significantly enhancing the number of detectable gravitational wave events annually [20][21]. Future Implications - The new technology allows for earlier warnings of cosmic collisions, enabling predictions of events such as neutron star mergers, potentially guiding observational efforts in real-time [22][23].