Alphabeta Math
DefinitionDefinition: AI-adaptedProof: Not applicablePipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-22
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Spectrum and resolvent of a bounded operator

Definition

Let X be a complex Banach space (Banach space, The Euclidean metric, convergence, Cauchy sequences, and continuity on the complex plane) and let TB(X) be a bounded linear operator (A bounded linear operator between normed spaces, The spaces (\mathcal B(X,Y)) and (\mathcal B(X)) of bounded linear operators). For a scalar λC write λIT for the bounded linear operator xλxTx (Linear map between vector spaces over the same field).

  • The resolvent set of T is ρ(T):={λC:λIT is bijective and its inverse is a bounded operator XX}. For λρ(T) the inverse R(λ,T):=(λIT)1, an element of B(X), is the resolvent operator of T at λ.
  • The spectrum of T is its complement σ(T):=Cρ(T).
  • A scalar λ is an eigenvalue of T when ker(λIT){0}; the nonzero vectors of that kernel are the eigenvectors of T for λ, and Eλ(T):=ker(λIT) is the eigenspace. The set of eigenvalues is the point spectrum of T; plainly the point spectrum is contained in σ(T), since an operator with nonzero kernel is not injective.
  • For λC the generalized eigenspace of T at λ is Gλ(T):=n1ker((TλI)n), an increasing union of linear subspaces (Linear subspace of a vector space); the union is a linear subspace because the union is increasing. If λ is an eigenvalue and Gλ(T) is finite dimensional, dimCGλ(T) (Finite-dimensional vector space, and its dimension dimFV; infinite-dimensional means having no finite basis) is the algebraic multiplicity of the eigenvalue λ.

Every element of Gλ(T){0} produces an eigenvector, and conversely. If (TλI)nx=0 with x0, let k1 be least with (TλI)kx=0; then y:=(TλI)k1x is nonzero and satisfies (TλI)y=0. So Gλ(T){0} exactly when λ is an eigenvalue. In particular λρ(T) implies Gλ(T)={0}. If λ is an eigenvalue and Gλ(T) is finite dimensional, then the algebraic multiplicity is defined and is at least dimCEλ(T), because Eλ(T)Gλ(T).

Conventions. Only complex scalars are treated here; the real case is handled by complexification on a later page, so no spectrum is attached here to a bounded operator on a real Banach space. The definition is purely one of vocabulary; it asserts no nonemptiness of σ(T), no openness of ρ(T) and no continuity of λR(λ,T), all of which are proved separately. Since 0IT=T, the number 0 lies in σ(T) exactly when T is not invertible with bounded inverse.

Depends on

Used by

Dependency tree · two levels

34 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.

Sources