Preconditioned Locally Harmonic Residual Method for Computing Interior Eigenpairs of Certain Classes of Hermitian Matrices

Preconditioned Locally Harmonic Residual Method for Computing Interior Eigenpairs of Certain Classes of Hermitian Matrices
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计算某类埃尔米特矩阵内部特征对的预条件局部调和残差法

DOI:
10.1137/14098048x
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发表时间:
2014
期刊:
SIAM J. Sci. Comput.
影响因子:
--
通讯作者:
A. Knyazev
A. Knyazev
中科院分区:
--
文献类型:
--
作者:
E. Vecharynski;A. Knyazev

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我们提出了一种预置的局部调和残差(PLHR)方法来计算广义厄米特特征值问题的几个内部特征对,而不需要传统的谱变换、矩阵分解或反转。PLHR基于短期递归,易于扩展为块形式,同时计算特征对。PLHR可以利用厄米正定预处理,例如,基于移位矩阵绝对值的近似逆,在[E]中介绍。维查连斯基和A. V. Knyazev, SIAM J. Sci。第一版。生态学报,35 (2013),pp. A696—A718]。我们的数值实验表明,PLHR对于某些涉及拉普拉斯算子和哈密顿算子的大规模内特征值问题是有效和鲁棒的,特别是在内存要求很紧的情况下。
We propose a preconditioned locally harmonic residual (PLHR) method for computing several interior eigenpairs of a generalized Hermitian eigenvalue problem, without traditional spectral transformations, matrix factorizations, or inversions. PLHR is based on a short-term recurrence, easily extended to a block form, computing eigenpairs simultaneously. PLHR can take advantage of Hermitian positive definite preconditioning, e.g., based on an approximate inverse of an absolute value of a shifted matrix, introduced in [E. Vecharynski and A. V. Knyazev, SIAM J. Sci. Comput., 35 (2013), pp. A696--A718]. Our numerical experiments demonstrate that PLHR is efficient and robust for certain classes of large-scale interior eigenvalue problems, involving Laplacian and Hamiltonian operators, especially if memory requirements are tight.
DOI: --
发表时间: 2010-08
期刊: --
影响因子: --
作者:
Carson Chow;Julian Cole Lectureship
通讯作者: Carson Chow;Julian Cole Lectureship
DOI: 10.1137/1.9780898718003
发表时间: 2003-05
期刊: --
影响因子: --
作者:
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通讯作者: Y. Saad