Particle Physics

Graph Neural Networks (GNNs) are increasingly applied in particle physics to analyze complex data structures, improve event reconstruction, and enhance particle identification. By leveraging the relational nature of particle interactions, GNNs offer a powerful computational approach for advancing experimental and theoretical studies in high-energy physics.