Lattice QCD

Lattice Quantum Chromodynamics (LQCD) uses numerical simulations on a spacetime lattice to study the fundamental theory of strong interactions. Current research heavily employs machine learning, particularly normalizing flows and gauge-equivariant neural networks, to improve sampling efficiency, reduce computational costs, and enhance the accuracy of observable predictions, addressing challenges like critical slowing down and topological freezing. These advancements are crucial for extracting meaningful physical information from LQCD simulations, impacting our understanding of hadron structure and interactions, and enabling more precise calculations in particle and nuclear physics.