Poster
in
Workshop: NeurIPS 2024 Workshop: Machine Learning and the Physical Sciences
Digital Discovery of interferometric Gravitational Wave Detectors
Mario Krenn · Yehonathan Drori · Rana Adhikari
Gravitational waves, detected a century after they were first theorized, are spacetime distortions caused by some of the most cataclysmic events in the universe, including black hole mergers and supernovae. The successful detection of these waves has been made possible by ingenious detectors designed by human experts. Beyond these successful designs, the vast space of experimental configurations remains largely unexplored, offering an exciting territory potentially rich in innovative and unconventional detection strategies. Here, we demonstrate an intelligent computational strategy to explore this enormous space, discovering unorthodox topologies for gravitational wave (GW) detectors that significantly outperform the currently best-known designs under realistic experimental constraints. This increases the potentially observable volume of the universe by up to 50-fold. Moreover, by analysing the best solutions from our super-human algorithm, we uncover entirely new physics ideas at their core. At a bigger picture, our methodology can readily be extended to AI-driven design of experiments across wide domains of fundamental physics, opening fascinating new windows into the universe.