Numerical Linear Algebra
where the algebra stops being the arithmetic
Concept

Non-normal matrices — where it appears

A matrix that does not commute with its transpose, whose eigenvectors are therefore not orthogonal and whose spectrum need not describe it.

Named by 2 essays across 2 fields — each of them below, with the objects they name alongside it.

036912151821242700.250.50.7511.25index kweight appliedonebidiagonalArnoldiis it a function of σmisfit, even fit1.6·10⁻¹²misfit, general fit0.063‖A − Aᵀ‖/‖A‖0.086one method's weights do not notice the operatorand the other's stop being a function of σ

The basis decides what a filter is

The vocabulary of regularisation is spectral — a method keeps a component or discards it, and the weights are a function of the singular value. Row-normalising a symmetric blur so that it preserves a constant makes it 8.6% asymmetric, and that is enough to move GMRES's weights from 7·10⁻¹⁴ off a function of σ to 4.4·10⁻².

regularisation · gmres darker is smaller: 10⁻¹⁰, 10⁻⁶, 10⁻³, 10⁻¹one spectrum, two matricesspectral radius0.8reach of the 10⁻³ level1.3eigenvalues, all at0.8the circle is |z| = 1and every eigenvalue is well inside it

The eigenvalues that are not there

For a normal matrix the resolvent norm is exactly one over the distance to the nearest eigenvalue, so a picture of it carries nothing the spectrum did not. Move one entry above the diagonal and the region a perturbation of 10⁻⁸ can put an eigenvalue into stops being a disc and reaches out past the unit circle, while every eigenvalue stays at 0.8.

spectra · non normality

Named alongside it

The objects these essays reach for when they reach for this one.

Arnoldi iterationEigenvalue condition numberEigenvectorsFilter factorsGMRESIll posed problemKrylov subspaceLsqrNon-normalityPerturbationPseudospectrumThe real Schur form

All concepts