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.

The transpose is bounded with the same norm

Statement

Let K=R or C. For a bounded linear T:XY between normed spaces, T:YX is bounded linear and T=T.

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 transpose of a bounded operator, with its stated hypotheses: Let K=R or C. Let T:XY be bounded and linear between normed spaces. Its transpose, or Banach adjoint, is T:YX,(Tg)(x)=g(Tx). The duals are def-dual-space-of-a-normed-space. Composition is bounded by lem-composition-operator-norm-inequality, so this has the displayed codomain. It is linear in g over K. No complex conjugation is inserted; a Hilbert adjoint uses a separate inner-product identification.

[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

Composition is linear in g, and (Tg)(x)=g(Tx)gTx. Taking the two unit-ball suprema gives TT.

F1
2.1

If Tx0, choose a unit functional gY with g(Tx)=Tx. Then Tx=(Tg)(x)Tx. If Tx=0 this inequality holds directly. Taking the supremum for x1 gives the reverse norm bound, including T=0 and zero spaces.

F2step 1.1

Depends on

Used by

Dependency tree · two levels

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Sources