Automatic Differentiation for Explicitly Correlated MP2

显式相关MP2的自动微分

阅读:1

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 results (10(-5)), which is attributed to deficiencies in AD implementations currently. However, it is notable that vibrational frequencies match within 10(-2) cm(-1). The use of AD also allowed the prediction of MP2-F12/3C(FIX)+CABS IR intensities for the first time.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。