Alphabeta Math
CorollaryStatement: AI-adaptedProof: AI-adaptedPipeline-generatedverified 2026-09-24 (gpt-6-sol)
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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.

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Distance to a closed subspace via unit annihilators

Statement

Assume the Axiom of Choice. Let K=R or C. For a closed linear subspace M of a normed X and x∈X, dist⁡(x,M)=sup⁡{∣f(x)∣:f∈M⊥, ∥f∥≤1}.

Facts & Assumptions

Given: The Axiom of Choice, 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.

[A1]

AC is used through bidual norm equality [F2] in step 1.1.

[F1]

From The dual of a quotient is its annihilator, with its stated hypotheses: Let K=R or C. Let X be normed and M≤X closed. With quotient norm ∥x+M∥=inf⁡m∈M∥x+m∥ and q(x)=x+M, the map Q:(X/M)∗⟶M⊥,Qh=h∘q is a linear isometric bijection.

[F2]

From The canonical bidual map is an isometry, with its stated hypotheses: Let K=R or C. For every normed X, the map JX:X→X∗∗ is linear and ∥JXx∥=∥x∥ for every x∈X. In particular it is injective.

Proof

1.1F2

In the normed quotient Z=X/M, the bidual isometry gives ∥x+M∥=sup⁡h∈Z∗,∥h∥≤1∣h(x+M)∣. The quotient norm on the left is dist⁡(x,M).

2.1F1step 1.1∎

The quotient-dual isometry sends its unit ball onto the unit ball of M⊥, with f(x)=h(x+M). Substitution proves the formula. The unit balls always contain zero; if x∈M or M=X both sides are zero, and M=0 recovers the dual norm formula.

Depends on

Used by

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Dependency tree · two levels

9 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