arXiv · 2405.08137
LATTE: an atomic environment descriptor based on Cartesian tensor contractions
Abstract
We propose a new descriptor for local atomic environments, to be used in combination with machine learning models for the construction of interatomic potentials. The Local Atomic Tensors Trainable Expansion (LATTE) allows for the efficient construction of a variable number of many-body terms with learnable parameters, resulting in a descriptor that is efficient, expressive, and can be scaled to suit different accuracy and computational cost requirements. We compare this new descriptor to existing ones on several systems, showing it to be competitive with very fast potentials at one end of the spectrum, and extensible to an accuracy close to the state of the art.
Explore related subjects
Keep this discovery
Franco Pellegrini, Stefano de Gironcoli, Emine Küçükbenli. 2024-05-13. LATTE: an atomic environment descriptor based on Cartesian tensor contractions. https://arxiv.org/abs/2405.08137
Cite the original work for its findings. Save a collection to share your selection of sources.