期刊
MOLECULAR PHYSICS
卷 113, 期 13-14, 页码 1823-1833出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00268976.2015.1015642
关键词
potential energy surface; neural network; methane; permutation invariant; moving least squares; spectroscopy
资金
- Hundred-Talent Foundation of Chongqing University
- US Department of Energy [DE-FG02-05ER15694, DE-SC0010616]
- Ministry of Education of Singapore [AcRF] [R-265-000-430-133, R-265-000-494-112]
- Canadian Space Agency
- U.S. Department of Energy (DOE) [DE-SC0010616] Funding Source: U.S. Department of Energy (DOE)
A data-set of nearly 100,000 symmetry unique multi-configurational ab initio points for methane were generated at the (AE)-MRCI-F12(Q)/CVQZ-F12 level, including energies beyond 30,000 cm(-1) above the minimum and fit into potential energy surfaces (PESs) by several permutation invariant schemes. A multi-expansion interpolative fit combining interpolating moving least squares (IMLS) fitting and permutation invariant polynomials (PIP) was able to fit the complete data-set to a root-mean-square deviation of 1.0 cm(-1) and thus was used to benchmark the other fitting methods. The other fitting methods include a single PIP expansion and two neural network (NN) based approaches, one of which combines NN with PIP. Full-dimensional variational vibrational calculations using a contracted-iterative method (and a Lanczos eigensolver) were used to assess the spectroscopic accuracy of the electronic structure method. The results show that the NN-based fitting approaches are able to fit the data-set remarkably accurately with the PIP-NN method producing levels in remarkably close agreement with the PIP-IMLS benchmark. The (AE)-MRCI-F12(Q)/CVQZ-F12 electronic structure method produces vibrational levels of near spectroscopic accuracy and a superb equilibrium geometry. The levels are systematically slightly too high, beginning at similar to 1-2 cm(-1) above the fundamentals and becoming correspondingly higher for overtones. The PES is therefore suitable for small ab initio or empirical corrections and since it is based on a multi-reference method, can be extended to represent dynamically relevant dissociation channels.
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