TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations

arXiv:2402.17660v1 Announce Type: new
Abstract: Achieving a balance between computational speed, prediction accuracy, and universal applicability in molecular simulations has been a persistent challenge. This paper presents substantial advancements in the TorchMD-Net software, a pivotal step forward in the shift from conventional force fields to neural network-based potentials. The evolution of TorchMD-Net into a more comprehensive and versatile framework is highlighted, incorporating cutting-edge architectures such as TensorNet. This transformation is achieved through a modular design approach, encouraging customized applications within …

arxiv cs.lg network neural network physics.bio-ph physics.chem-ph physics.comp-ph simulations type