Eigentheory & Diagonalization

generalized eigenspace

When an operator is defective, its ordinary eigenspaces are too small to fill the space. The generalized eigenspace is the repair: instead of stopping at vectors killed by (A - lambda I), you also gather vectors killed by some power (A - lambda I)^k. These extra vectors plug exactly the holes the missing eigenvectors left behind.

Formally, the generalized eigenspace of lambda is G_lambda = ker(A - lambda I)^k for k large enough that the kernel stops growing (k equal to the algebraic multiplicity always suffices). Its dimension equals the algebraic multiplicity of lambda — not merely the geometric multiplicity — so generalized eigenspaces are always 'big enough'. They contain the ordinary eigenspace as the k = 1 layer.

The decisive theorem: over C the whole space is the direct sum of the generalized eigenspaces, V = G_lambda_1 (+) ... (+) G_lambda_m. This always works, even when A is defective and cannot be diagonalized. Choosing a smart basis (Jordan chains) inside each generalized eigenspace yields the Jordan canonical form, the universal normal form for any complex matrix.

G_lambda = ker (A - lambda I)^k , dim G_lambda = algebraic multiplicity of lambda

Generalized eigenspaces grow until their dimension matches the algebraic multiplicity, filling the defect.

The smallest k for which ker(A - lambda I)^k stabilizes is the size of the largest Jordan block for lambda (the index of the eigenvalue). For a diagonalizable matrix k = 1 everywhere, and generalized eigenspaces collapse back to ordinary eigenspaces.

Also called
generalized eigenspaceroot subspace