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使用张量分解的振动耦合簇响应理论计算振动激发能。

Calculating vibrational excitation energies using tensor-decomposed vibrational coupled-cluster response theory.

作者信息

Madsen Niels Kristian, Jensen Rasmus Berg, Christiansen Ove

机构信息

Department of Chemistry, University of Aarhus, Langelandsgade 140, DK-8000 Aarhus C, Denmark.

出版信息

J Chem Phys. 2021 Feb 7;154(5):054113. doi: 10.1063/5.0037240.

DOI:10.1063/5.0037240
PMID:33557569
Abstract

The first implementation of tensor-decomposed vibrational coupled cluster (CP-VCC) response theory for calculating vibrational excitation energies is presented. The CP-VCC algorithm, which has previously been applied to solving the vibrational coupled cluster (VCC) ground-state equations without explicitly constructing any tensors of order three or higher, has been generalized to allow transformations with the Jacobian matrix necessary for computation of response excitation energies by iterative algorithms. A new eigenvalue solver for computing CP-VCC excitation energies is introduced, and the different numerical thresholds used for controlling the accuracy of the obtained eigenvalues are discussed. Numerical results are presented for calculations of the 20 lowest eigenvalues on a set of 10 four-atomic molecules, as well as for a number of polycyclic aromatic hydrocarbons (PAHs) of increasing size, up to PAH8 with 120 modes. It is shown that the errors introduced by the tensor decomposition can be controlled by the choice of numerical thresholds. Furthermore, all thresholds can be defined relative to the requested convergence threshold of the equation solver, which allows black-box calculations with minimal user input to be performed. Eigenstates of PAHs were efficiently computed without any explicitly constructed tensors, showing improvements in both memory and central processing unit time compared to the existing full-tensor versions.

摘要

本文提出了用于计算振动激发能的张量分解振动耦合簇(CP-VCC)响应理论的首次实现。CP-VCC算法此前已应用于求解振动耦合簇(VCC)基态方程,无需显式构建任何三阶或更高阶张量,现已推广到允许通过迭代算法与计算响应激发能所需的雅可比矩阵进行变换。引入了一种用于计算CP-VCC激发能的新特征值求解器,并讨论了用于控制所得特征值精度的不同数值阈值。给出了在一组10个四原子分子上计算20个最低特征值的数值结果,以及对于一些尺寸不断增加的多环芳烃(PAH),直至具有120个模式的PAH8的数值结果。结果表明,张量分解引入的误差可以通过数值阈值的选择来控制。此外,所有阈值都可以相对于方程求解器所需的收敛阈值来定义,这使得能够在用户输入最少的情况下进行黑箱计算。与现有的全张量版本相比,无需任何显式构建的张量即可高效计算PAH的本征态,在内存和中央处理器时间方面均有改进。

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