Tag: configurational integral
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AI Tensor Networks Solve Century-Old Physics Puzzle with THOR AI
New Computational Framework Tackles a Century-Old Challenge Researchers from The University of New Mexico (UNM) and Los Alamos National Laboratory (LANL) have unveiled a pioneering computational framework that dramatically improves how scientists compute the configurational integral—a central and notoriously difficult part of statistical physics. The team’s system, called THOR (Tensors for High-dimensional Object Representation) AI,…
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THOR AI Solves Century-Old Physics Puzzle with Tensors
THOR AI: A Tensor Network Breakthrough for Statistical Physics Researchers from the University of New Mexico (UNM) and Los Alamos National Laboratory (LANL) have unveiled a novel computational framework that tackles a long-standing challenge in statistical physics: the configurational integral at the heart of predicting a material’s thermodynamic and mechanical properties. The approach, called Tensors…
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AI Tensor Network Solves Century-Old Physics Puzzle
A Breakthrough in Statistical Physics Researchers from The University of New Mexico (UNM) and Los Alamos National Laboratory (LANL) have unveiled a novel computational framework that tackles a long-standing obstacle in statistical physics. The THOR (Tensors for High-dimensional Object Representation) AI framework applies tensor network algorithms to compress and evaluate the sprawling configurational integrals and…