Automatic Molecule Fragmentation for Density Matrix Embedding Theory.

ABSTRACT: In quantum chemical calculations, the computational cost of highly accurate ground-state energy calculations for large-scale molecules is exceedingly high. To reduce the computational cost while sustaining high accuracy, quantum embedding methods, such as the density matrix embedding theory (DMET) and bootstrap embedding (BE), have been developed. In DMET, we need to manually determine how to fragment a target molecule, and both the accuracy and computational cost strongly depend on it. This issue hinders the easy application of DMET to practical molecules. On the other hand, BE can be easily applied to any molecules because it automatically constructs fragments based on the structure of a target molecule. In this work, we propose a graph-based automatic molecule fragmentation (GAF) techni

SUBMITTER: Imamura S 

PROVIDER: S-EPMC12516714 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature