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学科主题: 物理化学
题名: Communication: Separable potential energy surfaces from multiplicative artificial neural networks
作者: Koch, Werner1;  Zhang, Dong H.
通讯作者: KochWerner
刊名: JOURNAL OF CHEMICAL PHYSICS
发表日期: 2014-07-01
DOI: 10.1063/1.4887508
卷: 141, 期:2, 页:021101
收录类别: SCI
文章类型: Article
WOS标题词: Science & Technology ;  Physical Sciences
类目[WOS]: Physics, Atomic, Molecular & Chemical
研究领域[WOS]: Physics
英文摘要: We present a potential energy surface fitting scheme based on multiplicative artificial neural networks. It has the sum of products form required for efficient computation of the dynamics of multidimensional quantum systems with the multi configuration time dependent Hartree method. Moreover, it results in analytic potential energy matrix elements when combined with quantum dynamics methods using Gaussian basis functions, eliminating the need for a local harmonic approximation. Scaling behavior with respect to the complexity of the potential as well as the requested accuracy is discussed. (C) 2014 AIP Publishing LLC.
关键词[WOS]: CONFIGURATION GAUSSIAN WAVEPACKETS ;  QUANTUM DYNAMICS ;  FEEDFORWARD NETWORKS ;  AB-INITIO ;  INTERPOLATION ;  ALGORITHM
语种: 英语
WOS记录号: WOS:000340269200001
Citation statistics: 
内容类型: 期刊论文
URI标识: http://cas-ir.dicp.ac.cn/handle/321008/144298
Appears in Collections:中国科学院大连化学物理研究所_期刊论文

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作者单位: 1.Chinese Acad Sci, Dalian Inst Chem Phys, State Key Lab Mol React Dynam, Dalian, Peoples R China
2.Chinese Acad Sci, Dalian Inst Chem Phys, Ctr Theoret Computat Chem, Dalian, Peoples R China

Recommended Citation:
Koch, Werner,Zhang, Dong H.. Communication: Separable potential energy surfaces from multiplicative artificial neural networks[J]. JOURNAL OF CHEMICAL PHYSICS,2014,141(2):021101.
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