Davis kahan — where it appears
Also named here as eigenvalue gap, eigenvector conditioning, principal angles, symmetric eigenproblem — the same set of essays touches all of them, so they are one junction rather than several.
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°.
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.
Named alongside it
The objects these essays reach for when they reach for this one.
Eigenvalue gapEigenvector conditioningPerturbationPrincipal anglesSymmetric eigenproblemCondition numberInvariant subspaceOrthogonal projectionWeyl's inequality