5 papers
Regularity Priors for the Linear Atomic Cluster Expansion
James P. Darby, Joe D. Morrow, Albert P. Bartók +3
Machine-learned interatomic potentials enable large systems to be simulated for long time scales at near ab-initio accuracy. This accuracy is achieved by fitting extremely flexible…
The High Cost of Data Augmentation for Learning Equivariant Models
Henri Klintebäck, Christoph Ortner, Lior Silberman
According to Noether's theorem the presence of a continuous symmetry in a Hamiltonian systems is equivalent to the existence of a conserved quantity, yet these symmetries are not a…
Machine learning intermolecular transfer integrals with compact atomic cluster representations
Keerati Keeratikarn, Christoph Ortner, Jarvist Moore Frost
Calculating intermolecular charge transfer integrals in organic semiconductors requires substantial computer resource for each individual calculation. We might alternatively constr…
Equivariant Representation of Configuration-Dependent Friction Tensors in Langevin Heatbaths
Matthias Sachs, Wojciech G. Stark, Reinhard J. Maurer +1
Dynamics of coarse-grained particle systems derived via the Mori-Zwanzig projection formalism commonly take the form of a (generalized) Langevin equation with configuration-depende…
Thermodynamic Limits of Electronic Systems
David Gontier, Jianfeng Lu, Christoph Ortner
We review thermodynamic limits and scaling limits of electronic structure models for condensed matter. We discuss several mathematical ways to implement these limits in three model…