aromatic solvation 1atomistic simulations 1binary alloys 1CCSD(T) accuracy 1configurational entropy 1hydrophobic effects 1machine learning potentials 1phase diagrams 1pi-hydrogen bonding 1vibrational entropy 1
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physics.comp-ph2026
Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks
Anton Bochkarev, Yury Lysogorskiy, Ralf Drautz
We present an algorithm for evaluating contracted Clebsch--Gordan tensor products in -equivariant machine learning potentials at fixed Canonical P…
physics.comp-ph2025
Conservative adaptive-precision interatomic potentials
David Immel, Ralf Drautz, Godehard Sutmann
Adaptive precision molecular dynamics simulations have developed along energy- and force-coupling approaches, which allow for a continuous transition between different particle des…
physics.comp-ph2024
Adaptive-precision potentials for large-scale atomistic simulations
David Immel, Ralf Drautz, Godehard Sutmann
Large-scale atomistic simulations rely on interatomic potentials providing an efficient representation of atomic energies and forces. Modern machine-learning (ML) potentials provid…