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	Communication: fitting potential energy surfaces with fundamental invariant neural network
	Shao, Kejie; Chen, Jun; Zhao, Zhiqiang; Zhang, Dong H.1
刊名	Journal of chemical physics
	2016-08-21
卷号	145期号:7页码:5
ISSN号	0021-9606
DOI	10.1063/1.4961454
通讯作者	Zhang, dong h.(zhangdh@dicp.ac.cn)
英文摘要	A more flexible neural network (nn) method using the fundamental invariants (fis) as the input vector is proposed in the construction of potential energy surfaces for molecular systems involving identical atoms. mathematically, fis finitely generate the permutation invariant polynomial (pip) ring. in combination with nn, fundamental invariant neural network (fi-nn) can approximate any function to arbitrary accuracy. because fi-nn minimizes the size of input permutation invariant polynomials, it can efficiently reduce the evaluation time of potential energy, in particular for polyatomic systems. in this work, we provide the fis for all possible molecular systems up to five atoms. potential energy surfaces for oh3 and ch4 were constructed with fi-nn, with the accuracy confirmed by full-dimensional quantum dynamic scattering and bound state calculations. published by aip publishing.
WOS关键词	FINITE-GROUPS
WOS研究方向	Chemistry ; Physics
WOS类目	Chemistry, Physical ; Physics, Atomic, Molecular & Chemical
语种	英语
出版者	AMER INST PHYSICS
WOS记录号	WOS:000381680700001
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2374407
专题	中国科学院大学
通讯作者	Zhang, Dong H.
作者单位	1.Chinese Acad Sci, State Key Lab Mol React Dynam, Dalian Inst Chem Phys, Dalian 116023, Peoples R China 2.Chinese Acad Sci, Ctr Theoret Computat Chem, Dalian Inst Chem Phys, Dalian 116023, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Shao, Kejie,Chen, Jun,Zhao, Zhiqiang,et al. Communication: fitting potential energy surfaces with fundamental invariant neural network[J]. Journal of chemical physics,2016,145(7):5.
APA	Shao, Kejie,Chen, Jun,Zhao, Zhiqiang,&Zhang, Dong H..(2016).Communication: fitting potential energy surfaces with fundamental invariant neural network.Journal of chemical physics,145(7),5.
MLA	Shao, Kejie,et al."Communication: fitting potential energy surfaces with fundamental invariant neural network".Journal of chemical physics 145.7(2016):5.

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