Local-Hybrid Functional With a Composite Local Mixing Function Built From a Neural Network and a Strong-Correlation Model.

ABSTRACT: Due to their position-dependent admixture of the exact-exchange (EXX) energy density, local hybrid functionals (LHs) enable a flexible balance between reduced self-interaction errors and smaller static-correlation errors, allowing an escape from the usual zero-sum game between these two central aspects of the development of density functional approximations. Recent LHs with strong-correlation factors incorporated into their local mixing functions (LMFs) governing the position-dependence of EXX admixtures have been particularly successful in this context. As only few exact constraints for LMFs are known regarding valence-space behavior, some recent efforts have used machine learning in this context, and the recent LH24n functional with a "neural-network LMF" (n-LMF, DOI: 10.1021/acs.jctc.4c

SUBMITTER: Wodynski A 

PROVIDER: S-EPMC12831636 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature