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Eigenvalue computations based on IDR

by H. Gutknecht and J.-P. Zemke

(Report number 2010-13)

Abstract
The Induced Dimension Reduction (IDR) method, which has been introduced as a transpose-free Krylov space method for solving nonsymmetric linear systems, can also be used to determine approximate eigenvalues of a matrix or operator. The IDR residual polynomials are the products of a residual polynomial constructed by successively appending linear smoothing factors and the residual polynomials of a two-sided (block) Lanczos process with one right-hand side and several left-hand sides. The Hessenberg matrix of the OrthoRes version of this Lanczos process is explicitly obtained in terms of the scalars defining IDR by deflating the smoothing factors. The eigenvalues of this Hessenberg matrix are approximations of eigenvalues of the given matrix or operator.

Keywords: Krylov space method; iterative method; induced dimension reduction; large nonsymmetric eigenvalue problem

@Techreport{GZ10_54,
  author = {H. Gutknecht and J.-P. Zemke},
  title = {Eigenvalue computations based on IDR},
  institution = {Seminar for Applied Mathematics, ETH Z{\"u}rich},
  number = {2010-13},
  address = {Switzerland},
  url = {https://www.sam.math.ethz.ch/sam_reports/reports_final/reports2010/2010-13.pdf },
  year = {2010}
}

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