科研之友
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摘要
Polynomial filtering can provide a highly effective means of computing all eigenvalues of a real symmetric (or complex Hermitian) matrix that are located in a given interval, anywhere in the spectrum. This paper describes a technique for tackling this problem by combining a thick restart version of the Lanczos algorithm with deflation ("locking") and a new type of polynomial filter obtained from a least-squares technique. The resulting algorithm can be utilized in a "spectrum slicing" approach whereby a very large number of eigenvalues and associated eigenvectors of the matrix are computed by extracting eigenpairs located in different subintervals independently from one another.
- 出版日期2016
