耦合团簇计算的收敛性改进
Convergence improvement for coupled cluster calculations
摘要：
讨论了耦合簇迭代的收敛性问题，提出了一种新的迭代格式。而Jacobi方法只反转方程系数的大矩阵的对角部分，我们反转一个矩阵，其中还包括一个相对较小的数量的非对角系数，选择根据激励幅度经历的最大变化的耦合集群迭代。算例表明，新的IPM（inversion of partial matrix）方法比直接的Jacobi型格式或已知的迭代子空间方法中的约化线性方程组或直接求逆等收敛工具具有更好的收敛性.
英文摘要：
Convergence problems in coupled-cluster iterations are discussed, and a new iteration scheme is proposed. Whereas the Jacobi method inverts only the diagonal part of the large matrix of equation coefficients, we invert a matrix which also includes a relatively small number of off-diagonal coefficients, selected according to the excitation amplitudes undergoing the largest change in the coupled cluster iteration. A test case shows that the new IPM (inversion of partial matrix) method gives much better convergence than the straightforward Jacobi-type scheme or such well-known convergence aids as the reduced linear equations or direct inversion in iterative subspace methods.
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