"Uncovering Hidden Particles: Machine Learning and the Large Hadron Collider"

Scientists at the U.S. Department of Energy's Argonne National Laboratory used a neural network to analyze data from the Large Hadron Collider, aiming to uncover undiscovered particles not accounted for in the Standard Model of particle physics. The machine learning approach, known as anomaly detection, identified an anomaly in the data that could indicate the existence of an unknown particle. While further investigation is needed, this technique shows promise for uncovering new physics and will be applied to data collected during the LHC Run-3 period.