performant implementation of the atomic cluster expansion pace and application to copper and silicon

• DOI: 10.17863/cam.71941
• Publication Date: 2021-06-28
• Authors: Lysogorskiy, Yury; Oord, Cas Van Der; Bochkarev, Anton; Menon, Sarath; Rinaldi, Matteo; Hammerschmidt, Th...; Mrovec, Matous; Thompson, Aidan; Csányi, Gábor; Ortner, Christoph; Drautz, Ralf
• Keywords: ddc:620; /639/301/1034/1037; Condensed Matter - Materials Science; /639/301/1034/1035; article; Materials Science (cond-mat.mtrl-sci); FOS: Physical sciences; Computational Physics (physics.comp-ph); 01 natural sciences; Article; QA76.75-76.765; 0103 physical sciences; TA401-492; Computer software; Materials of engineering and construction. Mechanics of materials; Physics - Computational Physics

AbstractThe atomic cluster expansion is a general polynomial expansion of the atomic energy in multi-atom basis functions. Here we implement the atomic cluster expansion in the performant C++ code that is suitable for use in large-scale atomistic simulations. We briefly review the atomic cluster expansion and give detailed expressions for energies and forces as well as efficient algorithms for their evaluation. We demonstrate that the atomic cluster expansion as implemented in shifts a previously established Pareto front for machine learning interatomic potentials toward faster and more accurate calculations. Moreover, general purpose parameterizations are presented for copper and silicon and evaluated in detail. We show that the Cu and Si potentials significantly improve on the best available potentials for highly accurate large-scale atomistic simulations.