An Improved Arc Algorithm for Detecting Definite Hermitian Pairs

A 25-year-old and somewhat neglected algorithm of Crawford and Moon attempts to determine whether a given Hermitian matrix pair (A, B) is definite by exploring the range of the function ..., which is a subset of the unit circle. The researchers revisit the algorithm and show that with suitable modif...

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Published inSIAM journal on matrix analysis and applications Vol. 31; no. 3; pp. 1131 - 1151
Main Authors Guo, Chun-Hua, Higham, Nicholas J., Tisseur, Françoise
Format Journal Article
LanguageEnglish
Published Philadelphia, PA Society for Industrial and Applied Mathematics 01.01.2009
Subjects
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ISSN0895-4798
1095-7162
DOI10.1137/08074218X

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Abstract A 25-year-old and somewhat neglected algorithm of Crawford and Moon attempts to determine whether a given Hermitian matrix pair (A, B) is definite by exploring the range of the function ..., which is a subset of the unit circle. The researchers revisit the algorithm and show that with suitable modifications and careful attention to implementation details it provides a reliable and efficient means of testing definiteness. A clearer derivation of the basic algorithm is given that emphasizes an arc expansion viewpoint and makes no assumptions about the definiteness of the pair. Convergence of the algorithm is proved for all (A, B), definite or not. It is shown that proper handling of three details of the algorithm is crucial to the efficiency and reliability: how the midpoint of an arc is computed, whether shrinkage of an arc is permitted, and how directions of negative curvature are computed.(ProQuest: ... denotes formulae/symbols omitted.)
AbstractList A 25-year-old and somewhat neglected algorithm of Crawford and Moon attempts to determine whether a given Hermitian matrix pair (A, B) is definite by exploring the range of the function ..., which is a subset of the unit circle. The researchers revisit the algorithm and show that with suitable modifications and careful attention to implementation details it provides a reliable and efficient means of testing definiteness. A clearer derivation of the basic algorithm is given that emphasizes an arc expansion viewpoint and makes no assumptions about the definiteness of the pair. Convergence of the algorithm is proved for all (A, B), definite or not. It is shown that proper handling of three details of the algorithm is crucial to the efficiency and reliability: how the midpoint of an arc is computed, whether shrinkage of an arc is permitted, and how directions of negative curvature are computed.(ProQuest: ... denotes formulae/symbols omitted.)
Author Tisseur, Françoise
Guo, Chun-Hua
Higham, Nicholas J.
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Issue 3
Keywords Saddle point method
Modification
Costs
Hermitian generalized eigenvalue problem
Linear form
Unit circle
Shrinkage estimator
Hermitian matrix
hyperbolic quadratic eigenvalue problem
Polynomial method
Computing
saddle point linear system
Partial differential equation
Implementation
Convergence
15A18
Statistical test
Efficiency
Cholesky method
65F30
Crawford number
65F15
Eigenvalue problem
Mathematical expansion
Expansion
Conjugate gradient method
definite pair
direction of negative curvature
Polynomial matrix
pencil
Algorithm
Factorization
Saddle point
Numerical analysis
Linear system
Linear algebra
Hyperbolic equation
Matrix method
Matrix polynomial
Reliability
Curvature
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Snippet A 25-year-old and somewhat neglected algorithm of Crawford and Moon attempts to determine whether a given Hermitian matrix pair (A, B) is definite by exploring...
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StartPage 1131
SubjectTerms Algebra
Algorithms
Applications
Computational efficiency
Convergence
Curvature
Derivation
Exact sciences and technology
Linear and multilinear algebra, matrix theory
Mathematical analysis
Mathematics
Moon
Numerical analysis
Numerical analysis. Scientific computation
Numerical linear algebra
Probability and statistics
Probability theory and stochastic processes
Reliability, life testing, quality control
Sciences and techniques of general use
Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications)
Statistics
Symbols
Title An Improved Arc Algorithm for Detecting Definite Hermitian Pairs
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