AIBullisharXiv – CS AI · 8h ago6/10
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From Evaluation to Design: Using Potential Energy Surface Smoothness Metrics to Guide Machine Learning Interatomic Potential Architectures
Researchers introduce the Bond Smoothness Characterization Test (BSCT), a new evaluation metric for Machine Learning Interatomic Potentials that efficiently detects physical inaccuracies in quantum potential energy surfaces. By combining BSCT with architectural refinements like differentiable k-nearest neighbors and temperature-controlled attention, the team demonstrates how systematic model design can achieve both low regression errors and stable molecular dynamics simulations.