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Fast, Stable, Computation of the Eigenvalues of Unitary-plus-rank-one Matrices, including Companion Matrices Watkins, David
Description
We consider upper Hessenberg unitary-plus-rank-one matrices, that is, matrices of the form $A = \tilde{U} + \tilde{x}\tilde{y}^{T}$, where $\tilde{U}$ is unitary, and $A$ is upper Hessenberg. This includes the class of Frobenius companion matrices, so methods for this type of matrix can be applied to the problem of finding the zeros of a polynomial. The unitary-plus-rank-one structure is preserved by any method that performs unitary similarity transformations, including Francis's implicitly-shifted $QR$ algorithm. We present a new implementation of Francis's algorithm that acts on a data structure that stores the matrix in $O(n)$ space and performs each iteration in $O(n)$ time. This is joint work with Jared Aurentz, Thomas Mach, and Raf Vandebril. Ours is not the first fast algorithm that has been proposed for this problem, but it is the first that has been shown to be backward stable, and it is faster than other fast algorithms that have been proposed previously.
Item Metadata
Title |
Fast, Stable, Computation of the Eigenvalues of Unitary-plus-rank-one Matrices, including Companion Matrices
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Creator | |
Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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Date Issued |
2017-07-08T14:01
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Description |
We consider upper Hessenberg unitary-plus-rank-one matrices,
that is, matrices of the form
$A = \tilde{U} + \tilde{x}\tilde{y}^{T}$, where $\tilde{U}$ is unitary, and $A$ is upper Hessenberg. This includes
the class of Frobenius companion matrices, so methods for this type of
matrix can be applied to the problem of finding the zeros of a polynomial.
The unitary-plus-rank-one structure is preserved by any method that performs
unitary similarity transformations, including Francis's implicitly-shifted
$QR$ algorithm. We present a new implementation of Francis's algorithm
that acts on a data structure that stores the matrix in $O(n)$ space and
performs each iteration in $O(n)$ time. This is joint work with Jared Aurentz, Thomas Mach, and Raf Vandebril.
Ours is not the first fast algorithm that has been proposed for this problem, but it is the first that has been shown to
be backward stable, and it is faster than other fast algorithms that have been proposed previously.
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Extent |
28 minutes
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Subject | |
Type | |
File Format |
video/mp4
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Language |
eng
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Notes |
Author affiliation: Washington State University
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Series | |
Date Available |
2018-01-04
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0362589
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URI | |
Affiliation | |
Peer Review Status |
Unreviewed
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Scholarly Level |
Faculty
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International