AI RESEARCH
ATOM: A Pretrained Neural Operator for Multitask Molecular Dynamics
arXiv CS.LG
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ArXi:2510.05482v2 Announce Type: replace Molecular dynamics (MD) simulations underpin modern computational drug discovery, materials science, and biochemistry. Recent machine learning models provide high-fidelity MD predictions without the need to repeatedly solve quantum mechanical forces, enabling significant speedups over conventional pipelines. Yet many such methods typically enforce strict equivariance and rely on sequential rollouts, thus limiting their flexibility and simulation efficiency.