When studying the ε-pseudospectrum of a matrix, one is often interested in computing the extremal points having maximum real part or modulus. This is a crucial step, for example,when computing the distance to instability of a stable system. Using the property that the pseudospectrum is determined via perturbations by rank-1 matrices, we derive differential equations onthe manifold of normalized rank-1 matrices whose solutions tend to the critical rank-1 perturbationsassociated with the extremal points of (locally) maximum real part and modulus. This approach alsoallows us to track the boundary contour of the pseudospectrum in a neighborhood of the extremalpoints. The technique we propose is related to an idea recently developed by Guglielmi and Overton,who derived discrete dynamical systems instead of the continuous ones we present. The methodturns out to be fast in comparison with those previously proposed in the literature and appears tobe promising in dealing with large sparse problems.
Differential equations for roaming pseudospectra: paths to extremal points and boundary tracking.
GUGLIELMI, NICOLA;
2011-01-01
Abstract
When studying the ε-pseudospectrum of a matrix, one is often interested in computing the extremal points having maximum real part or modulus. This is a crucial step, for example,when computing the distance to instability of a stable system. Using the property that the pseudospectrum is determined via perturbations by rank-1 matrices, we derive differential equations onthe manifold of normalized rank-1 matrices whose solutions tend to the critical rank-1 perturbationsassociated with the extremal points of (locally) maximum real part and modulus. This approach alsoallows us to track the boundary contour of the pseudospectrum in a neighborhood of the extremalpoints. The technique we propose is related to an idea recently developed by Guglielmi and Overton,who derived discrete dynamical systems instead of the continuous ones we present. The methodturns out to be fast in comparison with those previously proposed in the literature and appears tobe promising in dealing with large sparse problems.File | Dimensione | Formato | |
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