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computational-physics

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papersTODAY 04:00 UTC

arXiv Paper Addresses Machine Learning of Metastable Dynamics

A new preprint on arXiv examines how machine learning can be used to identify and model metastable behavior in physical systems. Metastability describes systems that linger in quasi-stable states and then shift abruptly under rare perturbations, a pattern seen across many areas of physics. The work targets the challenge of detecting and representing these transitions computationally.

research/arxiv/physics/dynamical-systems