Numerical Linear Algebra
where the algebra stops being the arithmetic
Ladder

Relative accuracy — the ladder

2 distinct arguments against one idea, from the one that introduces it to the one that assumes the rest.
  1. 1234567810⁻¹⁷10⁻¹⁴10⁻¹¹10⁻⁸10⁻⁵10⁻²10¹singular value, largest firstrelative errorone-sided Jacobizero-shift QRshifted QReigenvalues of BᵀBagainst a rational bisectionσ_min, exactly2.1·10⁻³⁰worst, one-sided Jacobi4.4·10⁻¹⁶worst, zero-shift QR2.2·10⁻¹⁶worst, eigenvalues of BᵀB1a relative error is a ratioand the denominator is the answer

    Small compared to what

    This site's own singular value routine has carried a sentence since the month it was written — that one-sided Jacobi computes the small singular values to high relative accuracy and the standard method does not. It has never been measured here, because measuring it needs a σ that is known rather than computed. A bidiagonal matrix and a Sturm count in exact rationals supply one.

    rung 1 · spectra
  2. 1234567810⁻¹⁷10⁻¹⁴10⁻¹¹10⁻⁸10⁻⁵10⁻²10¹singular value, largest firstrelative errorone-sided Jacobizero-shift QRshifted QReigenvalues of BᵀBthe same four routes, reversedσ_min, exactly5.2·10⁻²⁶Jacobi's error on it0.015sweeps, zero shift400sweeps, shifted16a method is not accuratea method on a matrix is

    Accurate is not a property of a method

    A bidiagonal matrix whose every entry is 1 or 4096 has singular values spanning thirty decades. On it, the method recommended for small singular values loses the small one by one and a half per cent, the sweep with the theorem behind it does not converge at all, and the shift the theorem is a warning about gets every value to 5·10⁻¹⁶. Nothing there contradicts the theory.

    rung 2 · spectra

All ladders