论文标题
自动生成显式相关方法的互补辅助基集（CAB）
Automatic generation of complementary auxiliary basis sets (CABS) for explicitly correlated methods
论文作者
论文摘要
明确相关的计算，除了轨道基集之外，通常需要三个辅助基集：JK（Coulomb-Exchange拟合），RI-MP2（识别MP2的分辨率）和CABS（辅助辅助基集）。如果无法使用感兴趣的轨道基集和化学要素，则可以使用现有算法即时自动生成前两个，但不能自动生成。在本文中，我们提出了一种非常简单的算法，名为AutoCabs。 Github提供了根据免费软件许可证的Python实施。对于CC-PVNZ-F12（n = D，T，Q，5）和W4-08热化学基准，我们证明了自动驾驶仪生成的CABS基集的质量可比性与目的优化的OPTRI基集相当，而文献中的质量差异完全可以忽略N nignes n的增加。
Explicitly correlated calculations, aside from the orbital basis set, typically require three auxiliary basis sets: JK (Coulomb-exchange fitting), RI-MP2 (resolution of the identity MP2), and CABS (complementary auxiliary basis set). If unavailable for the orbital basis set and chemical elements of interest, the first two can be auto-generated on the fly using existing algorithms, but not the third. In this paper, we present a quite simple algorithm named autoCABS; a Python implementation under a free software license is offered at Github. For the cc-pVnZ-F12 (n=D,T,Q,5) and the W4-08 thermochemical benchmark, we demonstrate that autoCABS-generated CABS basis sets are comparable in quality to purpose-optimized OptRI basis sets from the literature, and that the quality difference becomes entirely negligible as n increases.
