Inexact rational Krylov subspace method for eigenvalue problems

Inexact rational Krylov subspace method for eigenvalue problems
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求解特征值问题的非精确有理 Krylov 子空间方法

DOI:
10.1002/nla.2437
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发表时间:
2022
影响因子:
4.3
通讯作者:
Xue, Fei
Xue, Fei
中科院分区:
数学3区
文献类型:
--
作者:
Xu, Shengjie;Xue, Fei

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研究了求解大规模非对称特征值问题的非精确有理Krylov子空间方法。有理Krylov子空间方法的每次迭代(外部步骤)都需要求解一个移位线性系统以扩大子空间,由大规模问题的迭代线性求解器执行。如果用迭代方法(内步)近似求解这些线性方程组,则在每个外步引入误差,并且误差在有理Krylov子空间中累积。在这篇文章中,我们推导出一个上限的误差在每一个外部步骤,以保持相同的收敛性的精确有理Krylov子空间方法逼近不变的子空间。由于该界与目标不变子空间的当前特征残差范数成反比,因此随着外部迭代的进行,在每个外部步骤处的迭代线性解的容限可以被放宽。一个重新启动的变种的不精确的合理Krylov子空间方法也被提出。数值实验表明,放宽内公差可以有效地节省计算量。
An inexact rational Krylov subspace method is studied to solve large‐scale nonsymmetric eigenvalue problems. Each iteration (outer step) of the rational Krylov subspace method requires solution to a shifted linear system to enlarge the subspace, performed by an iterative linear solver for large‐scale problems. Errors are introduced at each outer step if these linear systems are solved approximately by iterative methods (inner step), and they accumulate in the rational Krylov subspace. In this article, we derive an upper bound on the errors introduced at each outer step to maintain the same convergence as exact rational Krylov subspace method for approximating an invariant subspace. Since this bound is inversely proportional to the current eigenresidual norm of the target invariant subspace, the tolerance of iterative linear solves at each outer step can be relaxed with the outer iteration progress. A restarted variant of the inexact rational Krylov subspace method is also proposed. Numerical experiments show the effectiveness of relaxing the inner tolerance to save computational cost.
DOI: 10.1007/978-1-4613-9353-5_10
发表时间: 1994
期刊: --
影响因子: --
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通讯作者: Axel Ruhe
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发表时间: 2009-08
期刊: SIAM J. Matrix Anal. Appl.
影响因子: --
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