AI Breakthrough Finally Cracks Century-Old Physics Problem
An AI framework now computes once-impossible physics equations within seconds. The breakthrough redefines how scientists study the behavior of materials. Researchers at the University of New Mexico and Los Alamos National Laboratory have created an advanced computational framework that solves a major problem that has challenged statistical physicists for decades. Known as the Tensors for High-dimensional Object Representation (THOR) AI framework, the system uses tensor network algorithms to efficiently compress and analyze vast configurational integrals and partial differential equations. These equations are fundamental for determining how materials behave under different thermodynamic and mechanical conditions. By combining tensor networks with machine learning potentials, which represent interatomic forces and atomic motion, the researchers achieved accurate, scalable simulations of materials across a wide range of physical environments. “The configurational integral — which c...
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