A fundamental invariant-neural network representation of quasi-diabatic Hamiltonians for the two lowest states of H3-Reference-Cited by-同舟云学术

A fundamental invariant-neural network representation of quasi-diabatic Hamiltonians for the two lowest states of H3

Author:

Yin Zhengxi¹²³⁴⁵,Braams Bastiaan J.⁶⁷⁸,Guan Yafu¹²³⁴⁵,Fu Bina¹²³⁴⁵^ORCID,Zhang Dong H.¹²³⁴⁵

Affiliation:

1. State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry

2. Dalian Institute of Chemical Physics

3. Chinese Academy of Sciences

4. Dalian

5. P. R. China

6. Centrum Wiskunde & Informatica (CWI)

7. The Dutch national Center for Mathematics and Computer Science

8. The Netherlands

Abstract

The FI-NN approach is capable of representing highly accurate diabatic PESs with particular and complicated symmetry problems.

Funder

National Natural Science Foundation of China

Chinese Academy of Sciences

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

Reference64 articles.

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