Schnack-Petersen Anna Kristina, Koch Henrik, Coriani Sonia, Kjønstad Eirik F
Department of Chemistry, Technical University of Denmark, 2800 Kongens Lyngby, Denmark.
Scuola Normale Superiore, Piazza dei Cavaleri 7, 56126 Pisa, Italy.
J Chem Phys. 2022 Jun 28;156(24):244111. doi: 10.1063/5.0087261.
We present an efficient implementation of ground and excited state coupled cluster singles and doubles (CCSD) gradients based on Cholesky-decomposed electron repulsion integrals. Cholesky decomposition and density fitting are both inner projection methods, and, thus, similar implementation schemes can be applied for both methods. One well-known advantage of inner projection methods, which we exploit in our implementation, is that one can avoid storing large VO and V arrays by instead considering three-index intermediates. Furthermore, our implementation does not require the formation and storage of Cholesky vector derivatives. The new implementation is shown to perform well, with less than 10% of the time spent calculating the gradients in geometry optimizations. Furthermore, the computational time per optimization cycle is significantly lower compared to other implementations based on an inner projection method. We showcase the capabilities of the implementation by optimizing the geometry of the retinal molecule (CHO) at the CCSD/aug-cc-pVDZ level of theory.
我们基于Cholesky分解电子排斥积分，提出了一种基态和激发态耦合簇单双激发（CCSD）梯度的高效实现方法。Cholesky分解和密度拟合都是内投影方法，因此，两种方法可以应用相似的实现方案。我们在实现过程中利用的内投影方法的一个众所周知的优点是，可以通过考虑三指标中间体来避免存储大型的VO和V数组。此外，我们的实现不需要形成和存储Cholesky向量导数。新的实现方法表现良好，在几何优化中计算梯度所花费的时间不到10%。此外，与基于内投影方法的其他实现相比，每个优化周期的计算时间显著更低。我们通过在CCSD/aug-cc-pVDZ理论水平上优化视网膜分子（CHO）的几何结构，展示了该实现方法的能力。
