324 citations · 438 across the 9 of their papers we have counts for
Showing 2025Show all
2 papers · 1 filter
physics.comp-ph2025
TorchSim: An efficient atomistic simulation engine in PyTorch
Orion Cohen, Janosh Riebesell, Rhys Goodall +6
We introduce TorchSim, an open-source atomistic simulation engine tailored for the Machine Learned Interatomic Potential (MLIP) era. By rewriting core atomistic simulation primitiv…
physics.chem-ph2025
Beyond Force Metrics: Pre-Training MLFFs for Stable MD Simulations
Shagun Maheshwari, Zhengxian Tang, Janghoon Ock +3
Machine-learning force fields (MLFFs) have emerged as a promising solution for speeding up ab initio molecular dynamics (MD) simulations, where accurate force predictions are criti…