Equation-of-motion orbital-optimized coupled-cluster doubles method with the density-fitting approximation: An efficient implementation

IF 3.4 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Aslı Ünal, Uğur Bozkaya
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Abstract

Orbital-optimized coupled-cluster methods are very helpful for theoretical predictions of the molecular properties of challenging chemical systems, such as excited states. In this research, an efficient implementation of the equation-of-motion orbital-optimized coupled-cluster doubles method with the density-fitting (DF) approach, denoted by DF-EOM-OCCD, is presented. The computational cost of the DF-EOM-OCCD method for excitation energies is compared with that of the conventional EOM-OCCD method. Our results demonstrate that DF-EOM-OCCD excitation energies are dramatically accelerated compared to EOM-OCCD. There are almost 17-fold reductions for the C 5 H 12 molecule in an aug-cc-pVTZ basis set with the RHF reference. This dramatic performance improvement comes from the reduced cost of integral transformation with the DF approach and the efficient evaluation of the particle-particle ladder (PPL) term, which is the most expensive term to evaluate. Further, our results show that the DF-EOM-OCCD approach is very helpful for the computation of excitation energies in open-shell molecular systems. Overall, we conclude that our new DF-EOM-OCCD implementation is very promising for the study of excited states in large-sized challenging chemical systems.

Abstract Image

Abstract Image

采用密度拟合近似的运动方程轨道优化耦合簇双倍法:高效实施。
轨道优化耦合簇方法非常有助于对激发态等高难度化学体系的分子性质进行理论预测。在这项研究中,提出了一种采用密度拟合(DF)方法的运动轨道方程优化耦合簇双倍法的高效实现方法,简称为 DF-EOM-OCCD。我们比较了 DF-EOM-OCCD 方法与传统 EOM-OCCD 方法在激发能量方面的计算成本。结果表明,与 EOM-OCCD 相比,DF-EOM-OCCD 激发能量大大加快。C 5 H 12 $$ {\mathrm{C}}_5{m\mathrm{H}}_{12} 的激发能量几乎降低了 17 倍。$$ 分子在增强-cc-pVTZ 基集中的性能与 RHF 参照相比降低了近 17 倍。这种性能的显著提高源于 DF 方法降低了积分变换的成本,并有效地评估了粒子-粒子阶梯(PPL)项,这是最昂贵的评估项。此外,我们的结果表明,DF-EOM-OCCD 方法非常有助于计算开壳分子系统的激发能量。总之,我们的结论是,我们新的 DF-EOM-OCCD 实现对于研究大型高难度化学体系中的激发态非常有前途。
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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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