Communication: Fitting potential energy surfaces with fundamental invariant neural network
文献类型：期刊论文
| 作者 | Shao, Kejie; Chen, Jun; Zhao, Zhiqiang; Zhang, Dong H.1 |
| 刊名 | JOURNAL OF CHEMICAL PHYSICS
 |
| 出版日期 | 2016-08-21 |
| 卷号 | 145期号:7 |
| ISSN号 | 0021-9606 |
| DOI | 10.1063/1.4961454 |
| 文献子类 | Article |
| 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 |
| 语种 | 英语 |
| WOS记录号 | WOS:000381680700001 |
| 出版者 | AMER INST PHYSICS |
| 源URL | [http://cas-ir.dicp.ac.cn/handle/321008/170298]  |
| 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, 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). |
| 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). |
| MLA | Shao, Kejie,et al."Communication: Fitting potential energy surfaces with fundamental invariant neural network".JOURNAL OF CHEMICAL PHYSICS 145.7(2016). |
入库方式： OAI收割
来源：大连化学物理研究所
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