This research searches for dark matter, which makes up most of the universe’s mass, by detecting ultralight particles using sensitive quantum sensors. By scanning frequencies like a radio and minimizing noise at cryogenic temperatures, the experiment aims to identify faint signals, bringing scientists closer to understanding the fundamental composition of the universe.

This thesis developed a real-time system for detecting, classifying, and locating sound events using only audio data. A network of 16 microphones and deep learning techniques achieved 96% classification accuracy and average localization error of 1.4 meters, demonstrating that sound-based analysis can effectively replace vision in monitoring applications.