Structured backward error — the series
-
A nearby problem of the wrong kind
A good algorithm returns the exact answer to a nearby problem. A hundred and eighteen essays have measured the distance and not one has asked what the nearby problem looks like. On a Toeplitz system it is a rank-one matrix that is constant along none of its diagonals — and the smallest one that is Toeplitz is two and a half million times larger.
-
The condition number of the model
Describe a 40×40 Toeplitz matrix by its 1,600 entries and its condition number is 78,800. Describe it by the one number it actually contains and the condition number is 61.9. The three decades in between are not an approximation or a bound — they are what κ has been over-stating, and the drop is not where the linear algebra is.
-
A perturbation that keeps the symmetry
The smallest perturbation that makes a computed answer exact is the backward error. Ask for the smallest one that also keeps the problem's structure and the number can only go up — and measured on a palindromic quadratic it goes up by 1.17, while the structure the computed spectrum has lost is not in either number.
-
The number that cannot rank them
Levinson and Gaussian elimination are indistinguishable on the backward error a library reports — every one of ninety-six measurements between 1.16·10⁻¹⁷ and 5.73·10⁻¹⁷. The structured backward error separates them by up to a hundredfold, in whichever direction the point happens to give. Only the forward error ranks them, and only because this family's exact answer is known.