Alphabeta Math
TheoremStatement: 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.

The canonical bidual map is an isometry

Statement

Let K=R or C. For every normed X, the map JX:XX is linear and JXx=x for every xX. In particular it is injective.

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 The canonical evaluation map into the bidual, with its stated hypotheses: Let K=R or C. For a normed X, define JX:XX,(JXx)(f)=f(x)(fX). With the dual norm from def-dual-space-of-a-normed-space, evaluation is linear in f and (JXx)(f)xf, so JXx is a bounded functional on X. The map is canonical and uses no chosen basis or conjugation.

[F2]

From Every nonzero vector has a norming functional, with its stated hypotheses: Let X be a normed space over R or C, and let xX be nonzero. Then there exists fX such that f=1andf(x)=x.

Proof

1.1

For a,bK, evaluation gives JX(ax+by)(f)=af(x)+bf(y) for every f. Also f(x)fx gives JXxx.

F1
2.1

If x0, a norming f satisfies f=1 and f(x)=x, so JXxx. For x=0 both norms are zero. Equality of norms now forces JXx=0 only for x=0, including when X is the zero space.

F2step 1.1

Depends on

Used by

Dependency tree · two levels

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Sources