加速高阶耦合簇方法的收敛性 II：耦合簇$\Lambda$方程与动态阻尼
Accelerating the Convergence of Higher-Order Coupled Cluster Methods II: Coupled Cluster $Λ$ Equations and Dynamic Damping
AI总结：
本研究将子迭代法拓展至耦合簇$\Lambda$方程，结合提出的动态阻尼法，在无需全DIIS外推高成本的前提下，实现高阶耦合簇方法振幅与$\Lambda$方程的快速收敛，支撑其解析梯度与性质计算。
摘要：
此前应用于高阶耦合簇振幅方程的子迭代方法，被拓展至耦合簇$\Lambda$方程的求解场景。研究发现，$\Lambda$方程的子迭代流程与振幅方程的子迭代流程高度相似，相较于使用DIIS（直接反演迭代子空间）对所有$\hat{T}$或$\hat{\Lambda}$振幅进行外推的方法，其收敛速率提升效果相近。本文还提出了一种动态阻尼方法，经证实可在振幅方程或$\Lambda$方程出现振荡行为时，有效恢复快速收敛特性。这些技术相结合，能够实现高阶耦合簇方法解析梯度与性质计算所需的振幅方程和$\Lambda$方程的收敛，且无需承担全DIIS外推带来的高内存或磁盘I/O开销。
英文摘要：
The method of sub-iteration, which was previously applied to the higher-order coupled cluster amplitude equations, is extended to the case of the coupled cluster $Λ$ equations. The sub-iteration procedure for the $Λ$ equations is found to be highly similar to that for the amplitude equations, and to exhibit a similar improvement in rate of convergence relative to extrapolation of all $\hat{T}$ or $\hatΛ$ amplitudes using DIIS. A method of dynamic damping is also presented which is found to effectively recover rapid convergence in the case of oscillatory behavior in the amplitude or $Λ$ equations. Together, these techniques allow for the convergence of both the amplitude and $Λ$ equations necessary for the calculation of analytic gradients and properties of higher-order coupled cluster methods without the high memory or disk I/O cost of full DIIS extrapolation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
