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 MX, NX, both MX and NX 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 MX, NX, define M={fX:f(m)=0 for all mM},N={xX:f(x)=0 for all fN}. Here X is def-dual-space-of-a-normed-space. The first notation agrees with def-continuous-annihilator-of-a-subspace on spanM, 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 fX 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: fX:=f=sup{f(x):x1}.

Proof

1.1

For fixed xX, evaluation Ex(f)=f(x) is linear and satisfies Ex(f)xf, hence has a norm-closed linear kernel. Each fX likewise has a closed linear kernel in X.

F2
2.1

By definition M=xMkerEx and N=fNkerf. 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}.

F1step 1.1
3.1

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

F1step 2.1

Depends on

Used by

Dependency tree · two levels

7 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