Sałek Paweł, Høst Stinne, Thøgersen Lea, Jørgensen Poul, Manninen Pekka, Olsen Jeppe, Jansík Branislav, Reine Simen, Pawłowski Filip, Tellgren Erik, Helgaker Trygve, Coriani Sonia
Department of Theoretical Chemistry, The Royal Institute of Technology, SE-10691 Stockholm, Sweden.
J Chem Phys. 2007 Mar 21;126(11):114110. doi: 10.1063/1.2464111.
A linear-scaling implementation of Hartree-Fock and Kohn-Sham self-consistent field (SCF) theories is presented and illustrated with applications to molecules consisting of more than 1000 atoms. The diagonalization bottleneck of traditional SCF methods is avoided by carrying out a minimization of the Roothaan-Hall (RH) energy function and solving the Newton equations using the preconditioned conjugate-gradient (PCG) method. For rapid PCG convergence, the Lowdin orthogonal atomic orbital basis is used. The resulting linear-scaling trust-region Roothaan-Hall (LS-TRRH) method works by the introduction of a level-shift parameter in the RH Newton equations. A great advantage of the LS-TRRH method is that the optimal level shift can be determined at no extra cost, ensuring fast and robust convergence of both the SCF iterations and the level-shifted Newton equations. For density averaging, the authors use the trust-region density-subspace minimization (TRDSM) method, which, unlike the traditional direct inversion in the iterative subspace (DIIS) scheme, is firmly based on the principle of energy minimization. When combined with a linear-scaling evaluation of the Fock/Kohn-Sham matrix (including a boxed fitting of the electron density), LS-TRRH and TRDSM methods constitute the linear-scaling trust-region SCF (LS-TRSCF) method. The LS-TRSCF method compares favorably with the traditional SCF/DIIS scheme, converging smoothly and reliably in cases where the latter method fails. In one case where the LS-TRSCF method converges smoothly to a minimum, the SCF/DIIS method converges to a saddle point.
本文提出了哈特里 - 福克(Hartree - Fock)和科恩 - 沙姆(Kohn - Sham)自洽场(SCF)理论的线性缩放实现方法,并通过应用于由1000多个原子组成的分子进行了说明。通过对鲁特汉 - 霍尔(Roothaan - Hall,RH)能量函数进行最小化,并使用预处理共轭梯度(PCG)方法求解牛顿方程,避免了传统SCF方法的对角化瓶颈。为了实现PCG的快速收敛,使用了洛丁(Lowdin)正交原子轨道基。由此产生的线性缩放信赖域鲁特汉 - 霍尔(LS - TRRH)方法通过在RH牛顿方程中引入能级移动参数来工作。LS - TRRH方法的一个很大优点是可以在不增加额外成本的情况下确定最佳能级移动,确保SCF迭代和能级移动牛顿方程都能快速且稳健地收敛。对于密度平均,作者使用信赖域密度子空间最小化(TRDSM)方法,与传统的迭代子空间直接反演(DIIS)方案不同,该方法严格基于能量最小化原理。当与福克/科恩 - 沙姆矩阵的线性缩放评估(包括电子密度的盒式拟合)相结合时,LS - TRRH和TRDSM方法构成了线性缩放信赖域SCF(LS - TRSCF)方法。LS - TRSCF方法与传统的SCF/DIIS方案相比具有优势,在后者方法失败的情况下能够平稳可靠地收敛。在一个案例中,LS - TRSCF方法平稳收敛到最小值,而SCF/DIIS方法收敛到一个鞍点。