Representation of coupled adiabatic potential energy surfaces using neural network based quasi-diabatic Hamiltonians: 1,2 A′ states of LiFH

An analytic quasi-diabatic representation of ab initio electronic structure data is key to the accurate quantum mechanical description of non-adiabatic chemical processes. In this work, a general neural network (NN) fitting procedure is proposed to generate coupled quasi-diabatic Hamiltonians ( H d...

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Veröffentlicht in:	Physical chemistry chemical physics : PCCP 2019-07, Vol.21 (26), p.1425-14213
Hauptverfasser:	Guan, Yafu, Zhang, Dong H, Guo, Hua, Yarkony, David R
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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