Sensitivity of the Lanczos recurrence to Gaussian quadrature data: How malignant can small weights be?

Dedicated to Professor William Gragg on the occasion of his 70th birthday.
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Abstract

Stability of passing from Gaussian quadrature data to the Lanczos recurrence coefficients is considered. Special attention is paid to estimates explicitly expressed in terms of quadrature data and not having weights in denominators. It has been shown that the recent approach, exploiting integral representation of Hankel determinants, implies quantitative improvement of D. Laurie’s constructive estimate.

It has also been demonstrated that a particular implementation on the Hankel determinant approach gives an estimate being unimprovable up to a coefficient; the corresponding example involves quadrature data with a small but not too small weight. It follows that polynomial increase of a general case upper bound in terms of the dimension is unavoidable.

MSC

65F18

Keywords

Lanczos recurrence
Jacobi inverse eigenvalue problem
Stability estimates
Orthogonal polynomials
Gaussian quadrature formula
Small weights

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