Construction of reactive potential energy surfaces with Gaussian process regression: active data selection

doi:10.1080/00268976.2017.1407460

	Construction of reactive potential energy surfaces with Gaussian process regression: active data selection
	Zhang, Dong H.3; Guan, Yafu 1,2,3; Yang, Shuo 1,2,3
刊名	MOLECULAR PHYSICS
	2018
卷号	116 期号:7-8 页码:823-834
关键词	Potential Energy Surface Gaussian Process Regression Active Learning
ISSN号	0026-8976
DOI	10.1080/00268976.2017.1407460
文献子类	Article
英文摘要	Gaussian process regression (GPR) is an efficient non-parametric method for constructing multi-dimensional potential energy surfaces (PESs) for polyatomic molecules. Since not only the posterior mean but also the posterior variance can be easily calculated, GPR provides a well-established model for active learning, through which PESs can be constructed more efficiently and accurately. We propose a strategy of active data selection for the construction of PESs with emphasis on low energy regions. Through three-dimensional (3D) example of H-3, the validity of this strategy is verified. The PESs for two prototypically reactive systems, namely, H + H2O H-2 + OH reaction and H + CH4 H-2 + CH3 reaction are reconstructed. Only 920 and 4000 points are assembled to reconstruct these two PESs respectively. The accuracy of the GP PESs is not only tested by energy errors but also validated by quantum scattering calculations.
WOS关键词	NEURAL-NETWORK APPROACH ; QUANTUM DYNAMICS ; DISSOCIATIVE CHEMISORPTION ; INTERPOLATION ; SIMULATIONS ; SCATTERING ; CU(111) ; H2O
WOS研究方向	Chemistry ; Physics
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000430050600005
内容类型	期刊论文
源URL	[http://cas-ir.dicp.ac.cn/handle/321008/169062]
专题	大连化学物理研究所_中国科学院大连化学物理研究所
通讯作者	Zhang, Dong H.
作者单位	1.Chinese Acad Sci, Dalian Inst Chem Phys, Ctr Theoret Computat Chem, Dalian 116023, Peoples R China 2.Chinese Acad Sci, Dalian Inst Chem Phys, State Key Lab Mol React Dynam, Dalian 116023, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Dong H.,Guan, Yafu,Yang, Shuo. Construction of reactive potential energy surfaces with Gaussian process regression: active data selection[J]. MOLECULAR PHYSICS,2018,116(7-8):823-834.
APA	Zhang, Dong H.,Guan, Yafu,&Yang, Shuo.(2018).Construction of reactive potential energy surfaces with Gaussian process regression: active data selection.MOLECULAR PHYSICS,116(7-8),823-834.
MLA	Zhang, Dong H.,et al."Construction of reactive potential energy surfaces with Gaussian process regression: active data selection".MOLECULAR PHYSICS 116.7-8(2018):823-834.