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LightPFP: A Lightweight Route to Ab Initio Accuracy at Scale
Machine learning interatomic potentials (MLIPs) bridge the gap between quantum-mechanical accuracy and scalable molecular simulations. However, a fundamental trade-off persists: universal MLIPs (u-MLIPs) offer broad transferability but are computationally expensive, whereas task-specific MLIPs (ts-M
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