论文标题
经验功能的密度灵敏度
Density sensitivity of empirical functionals
论文作者
论文摘要
参数在近似密度函数中的经验拟合很常见。这种拟合将自一致密度的误差与能量功能中的误差混合在一起，但是密度校正的DFT（DC-DFT）将这两个分开。我们用在不同的债券长度上应用于$ h_2^+$的玩具功能的灾难性故障说明，其中标准拟合过程错过了确切的功能； Grimme的D3适合非共价相互作用，该相互作用可能会被诸如Water27和B30数据集中的大密度误差所污染；和接受自洽密度训练的双杂交型，在密度驱动错误的系统上的性能较差。在这些情况下，通过使用Hartree-Fock（HF）密度而不是自洽密度，可以找到更准确的结果。对于小水群的结合能，误差大大减少。在大距离处具有100 \％HF的范围分离杂种，因此这种效果的影响少得多。
Empirical fitting of parameters in approximate density functionals is common. Such fits conflate errors in the self-consistent density with errors in the energy functional, but density-corrected DFT (DC-DFT) separates these two. We illustrate with catastrophic failures of a toy functional applied to $H_2^+$ at varying bond lengths, where the standard fitting procedure misses the exact functional; Grimme's D3 fit to noncovalent interactions, which can be contaminated by large density errors such as in the WATER27 and B30 datasets; and double-hybrids trained on self-consistent densities, which can perform poorly on systems with density-driven errors. In these cases, more accurate results are found at no additional cost, by using Hartree-Fock (HF) densities instead of self-consistent densities. For binding energies of small water clusters, errors are greatly reduced. Range-separated hybrids with 100\% HF at large distances suffer much less from this effect.
