Title
Subspace Acceleration for the Crawford Number and Related Eigenvalue Optimization Problems.
Abstract
This paper is concerned with subspace acceleration techniques for computing the Crawford number, that is, the distance between zero and the numerical range of a matrix A. Our approach is based on an eigenvalue optimization characterization of the Crawford number. We establish local convergence of order 1 + root 2 approximate to 2:4 for an existing subspace method applied to such and other eigenvalue optimization problems involving a Hermitian matrix that depends analytically on one parameter. For the particular case of the Crawford number, we show that the relevant part of the objective function is strongly concave. In turn, this enables us to develop a subspace method that only uses three-dimensional subspaces but still achieves global convergence and a local convergence that is at least quadratic. A number of numerical experiments confirm our theoretical results and reveal that the established convergence orders appear to be tight.
Year
DOI
Venue
2018
10.1137/17M1127545
SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS
Keywords
Field
DocType
subspace acceleration,eigenvalue optimization,Crawford number,coercivity constant,convergence analysis,complex approximation
Convergence (routing),Mathematical optimization,Subspace topology,Mathematical analysis,Matrix (mathematics),Quadratic equation,Linear subspace,Local convergence,Numerical range,Hermitian matrix,Mathematics
Journal
Volume
Issue
ISSN
39
2
0895-4798
Citations 
PageRank 
References 
0
0.34
3
Authors
3
Name
Order
Citations
PageRank
Daniel Kressner144948.01
Ding Lu231.41
Bart Vandereycken319910.21