论文标题
有效实施具有浓缩电子排斥积分的分子CCSD梯度
Efficient implementation of molecular CCSD gradients with Cholesky-decomposed electron repulsion integrals
论文作者
论文摘要
我们提出了基于Cholesky批准的电子排斥积分的地面和激发状态CCSD梯度的有效实现。 Cholesky分解（例如密度拟合）是一种内部投影方法，因此可以针对这两种方法应用类似的实现方案。我们在实施中利用内部投影方法的一个众所周知的优势是，可以避免通过考虑三个索引中间体来避免存储大型V3O和V4阵列。此外，我们的实施不需要形成和存储Cholesky载体衍生物。新实现表明表现良好，只有不到10％的时间来计算几何优化中的梯度。此外，与基于内部投影方法的其他实现相比，发现每个优化周期所花费的计算时间明显降低。我们通过优化在CCSD/AUG-CC-PVDZ理论水平上优化视网膜分子（C20H28O）的几何形状来说明实现的能力。
We present an efficient implementation of ground and excited state CCSD gradients based on Cholesky-decomposed electron repulsion integrals. Cholesky decomposition, like density-fitting, is an inner projection method, 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 V3O and V4 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. The computational time spent per optimization cycle are furthermore found to be significantly lower compared to other implementations based on an inner projection method. We illustrate the capabilities of the implementation by optimizing the geometry of the retinal molecule (C20H28O) at the CCSD/aug-cc-pVDZ level of theory.
