2 papers
physics.comp-ph2026
TorchNEP: Ultra-Efficient and Accurate Training of Neuroevolution Potentials
Yong-Chao Wu, Xiaoya Chang, Tero Mäkinen +5
Neuroevolution Potential (NEP) is one of the most efficient machine-learned interatomic potential frameworks for large-scale atomistic simulations. However, its original training s…
cond-mat.mes-hall2024
Equivalence analysis between Quasi-coarse-grained and Atomistic Simulations
Dong-Dong Jiang, Jian-Li Shao
In recent years, simulation methods based on the scaling of atomic potential functions, such as quasi-coarse-grained dynamics and coarse-grained dynamics, have shown promising resu…