结合机器学习算法提高从头算方法对 hf/hbr/h cl / na 振动能谱的预测性能

HIGHLIGHTS

  • who: xbany from the Xihua University, Chengdu, China have published the paper: u7ed3u5408u673au5668u5b66u4e60u7b97u6cd5u63d0u9ad8u4eceu5934u7b97u65b9u6cd5u5bf9 HF/HBr/H Cl / Na u632fu52a8u80fdu8c31u7684u9884u6d4bu6027u80fd, in the Journal: (JOURNAL)

SUMMARY

    High-precision vibrational energy spectra contain a large amount of quantum information of molecular system and is essential basic data for people to understand and manipulate molecules. At present, ab-initio methods have achieved great results in the calculation of the potential energy surfaces and corresponding vibrational energies of molecules, but they still face challenges in terms of accuracy and computational cost. Data-driven machine_learning methods have demonstrated a . . .

     

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