Automatic Differentiation for Explicitly Correlated MP2.

ABSTRACT: Automatic differentiation (AD) offers a route to achieve arbitrary-order derivatives of challenging wave function methods without the use of analytic gradients or response theory. Currently, AD has been predominantly used in methods where first- and/or second-order derivatives are available, but it has not been applied to methods lacking available derivatives. The most robust approximation of explicitly correlated MP2, MP2-F12/3C(FIX)+CABS, is one such method. By comparing the results of MP2-F12 computed with AD versus finite-differences, it is shown that (a) optimized geometries match to about 10^-3 Å for bond lengths and a 10^-6 degree for angles, and (b) dipole moments match to about 10^-6 D. Hessians were observed to have poorer agreement with numerical re

SUBMITTER: Mitchell EC 

PROVIDER: S-EPMC11465469 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature