Researchers demonstrated a new approach to peer deeper into the complex behavior of materials. The team harnessed the power of machine learning to observe coherent excitations, collective swinging of atomic spins within a system. When the team applied their machine learning model to this real-world data, it was able to overcome challenges such as noise and missing data points.

Greg Stewart/SLAC National Accelerator Laboratory