Alphabeta Math
LemmaStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-07
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.

Annihilators and preannihilators are norm closed

Statement

Let K=R or C. For any normed X and arbitrary M⊆X, N⊆X∗, both M⊥⊆X∗ and ⊥N⊆X are norm-closed linear subspaces. Moreover N‾∥⋅∥⊆(⊥N)⊥.

Facts & Assumptions

Given: The spaces, maps, scalar field, and hypotheses in the statement above. All duals consist of linear functionals over the ambient field; evaluation has no conjugation.

[F1]

From Annihilator notation and the preannihilator, with its stated hypotheses: Let K=R or C. For a normed X and arbitrary subsets M⊆X, N⊆X∗, define M⊥={f∈X∗:f(m)=0 for all m∈M},⊥N={x∈X:f(x)=0 for all f∈N}. Here X∗ is def-dual-space-of-a-normed-space. The first notation agrees with def-continuous-annihilator-of-a-subspace on span⁡M, since linearity makes vanishing on M equivalent to vanishing on its span. The preannihilator lies in X, not in X∗∗. Empty sets impose no conditions: ∅⊥=X∗ and ⊥∅=X.

[F2]

From The dual space X^* of a normed space and its dual norm, with its stated hypotheses: Let X be a normed space over the scalar field K, where K=R in the literal definition and K=C by the convention of rem-real-and-complex-normed-space-convention. The dual space of X is X∗:=B(X,K), the space of bounded linear functionals on X (def-space-of-bounded-linear-operators). Each f∈X∗ is in particular a linear functional in the algebraic sense, so X∗ is a subspace of the algebraic dual from def-algebraic-dual-and-linear-functional. The dual norm on X∗ is the operator norm: ∥f∥X∗:=∥f∥=sup⁡{∣f(x)∣:∥x∥≤1}.

Proof

1.1F2

For fixed x∈X, evaluation Ex(f)=f(x) is linear and satisfies ∣Ex(f)∣≤∥x∥∥f∥, hence has a norm-closed linear kernel. Each f∈X∗ likewise has a closed linear kernel in X.

2.1F1step 1.1

By definition M⊥=⋂x∈Mker⁡Ex and ⊥N=⋂f∈Nker⁡f. Intersections of closed sets are closed and these equations preserve zero, addition, and scalar multiplication. The empty intersection is the whole ambient space, including when X={0}.

3.1F1step 2.1∎

Every g∈N vanishes on ⊥N. Thus N⊆(⊥N)⊥; the latter is norm closed by step 2.1, so it contains the norm closure of N.

Depends on

Used by

Dependency tree · two levels

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Sources