论文标题
关于双原子分子光谱常数的通用性
On the universality of spectroscopic constants of diatomic molecules
论文作者
论文摘要
我们通过机器学习方法表明，平衡距离，谐波振动频率和双原子分子的结合能是普遍相关的。特别是，光谱常数之间的关系与分子键独立于有效。但是，它们在很大程度上取决于成分原子的群体和时期。结果，我们表明，通过在分子内使用原子和周期，可以预测光谱常数的精度为$ \ lyssim 5 \％$。最后，当采用了{\ it i i i i}和密度功能理论（DFT）电子结构方法的光谱常数时，满足了相同的普遍关系。
We show, through a machine learning approach, that the equilibrium distance, harmonic vibrational frequency, and binding energy of diatomic molecules are universally related. In particular, the relationships between spectroscopic constants are valid independently of the molecular bond. However, they depend strongly on the group and period of the constituent atoms. As a result, we show that by employing the group and period of atoms within a molecule, the spectroscopic constants are predicted with an accuracy of $\lesssim 5\%$. Finally, the same universal relationships are satisfied when spectroscopic constants from {\it ab initio} and density functional theory (DFT) electronic structure methods are employed.
