Numerical Linear Algebra
where the algebra stops being the arithmetic
Concept

Symmetric eigenproblem — where it appears

Finding the eigenvalues of a symmetric matrix, which are real and whose eigenvectors are orthogonal. It is a fundamentally easier problem than the general one, and its perturbation theory has no condition number in it beyond one.

Named by 3 essays across 2 fields — each of them below, with the objects they name alongside it.

10⁻⁹10⁻⁷10⁻⁵10⁻³10⁻⁸10⁻⁵10⁻²gap between the two eigenvalueshow far it movedthe eigenvectorsthe eigenvaluestheir plane‖E‖ / gapone perturbation, three answerseigenvalue shift, spread over the sweep1plane angle, spread over the sweep1eigenvector angle, spread1.6·10⁵the dashed line is Davis–Kahan's ‖E‖/gaptwo of the three never noticed

The gap decides the eigenvector

A symmetric matrix's eigenvalues move by at most the size of the perturbation, whatever the spectrum looks like. Its eigenvectors are governed by a completely different quantity — the distance to the neighbouring eigenvalue — and at a gap of 10⁻⁹ the same perturbation turns them through 27°.

spectra · Eigen conditioning the invariant planesolid: beforedashed: aftersame perturbation, two questionsthe vectors turned, radians0.029the plane turned, radians7.6·10⁻⁸what left the plane5.6·10⁻⁸drawn in the unperturbed plane's own basisa radius is not determined; the circle is

The plane survives what its vectors do not

At a gap of 10⁻⁹ a perturbation of 10⁻⁶ turns the two eigenvectors through half a radian and turns the plane they span through 7.6·10⁻⁸ — a ratio of six million. Ask for the subspace instead of the vectors and a hopeless computation becomes a well-conditioned one, with no change to the arithmetic.

spectra · Invariant subspace largest eigenvalue erroras given, order 960.043balanced, order 964.4·10⁻⁴symmetrised, order 962.2·10⁻¹²016324864809611210⁻¹⁶10⁻¹³10⁻¹⁰10⁻⁷10⁻⁴10⁻¹order nlargest |computed − exact| eigenvaluean error of one: the integers are no longer told apartas givenbalancedsymmetrisedopen dots: complex pairs returned for a real spectrumevery entry is an integer, stored exactly

Balanced is not symmetric

The Sylvester–Kac matrix is made of small integers, so a double holds it exactly, and its eigenvalues are the integers from −(n − 1) to n − 1 in steps of two. Every digit an eigensolver loses on it is therefore the solver's own, and it loses them at exactly the rate first-order perturbation theory predicts: the median error is half the prediction across 1,568 eigenvalues. Balancing, the preprocessing libraries apply for this kind of matrix, divides every condition number by about sixty and leaves their growth untouched, and at order 112 the unbalanced solver returns eighteen complex eigenvalues for a spectrum of integers.

error · Exact ground truth

Named alongside it

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

Davis kahanEigenvalue gapEigenvector conditioningPerturbationPrincipal anglesCondition numberEigenvalue condition numberExact ground truthFrancis's double shiftInvariant subspaceNon-normalityOrthogonal projection

All concepts