Effective Theory

Effective theory provides a simplified, yet accurate, description of complex systems by focusing on relevant degrees of freedom. Current research applies this framework to diverse areas, including neural network training dynamics (analyzing architectures like transformers and employing models like Ginzburg-Landau), string theory (using normalizing flows for numerical simulations), and even modeling the evolution of spoken language. These studies aim to improve our understanding of generalization, criticality, and emergent behavior in these systems, offering insights into both fundamental physics and the development of more efficient machine learning algorithms.