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LemmaStatement: Literature-sourcedProof: AI-generatedPipeline-generatedprecheck passjudge pass (gpt-6-luna)
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  • 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.
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One-point extension of a nonexpansive map in finite dimensions

Statement

Let E=Rn with its Euclidean norm, let D⊆E, and let T:D→E satisfy ∥T(p)−T(p′)∥2≤∥p−p′∥2 for all p,p′∈D. For every y∈E there exists q∈E such that ∥q−T(p)∥2≤∥y−p∥2(p∈D). Equivalently, one value can be added at the new input y without violating the Lipschitz constant 1.

Facts & Assumptions

Given: E,D,T,y as in the Statement.

[A1]

The map T:D→E is 1-Lipschitz and y∈E.

[F3]

Semicontinuous extreme value theorem on compact Euclidean sets: for n≥1, a continuous real function on a nonempty compact subset of Rn attains its minimum.

[F4]

Every point has a unique nearest point in a nonempty closed Euclidean convex set and Metric projection onto a closed convex set satisfies the variational inequality: in Rn for n≥1, a nonempty closed convex subset has a nearest point to any point, and that projection satisfies the variational inequality.

[F5]

A metric space is compact if and only if every family of closed subsets with the finite intersection property has nonempty intersection: a family of closed subsets of a compact space with the finite-intersection property has nonempty total intersection.

Proof

1.1A1givenF1F2F3construct

If n=0, then E={0}. If D is empty choose q=0; if it is nonempty then D={0}, y=p=T(p)=0, and q=0 satisfies the inequality. Hence assume n≥1. If D=∅, any q works. Otherwise consider any finite nonempty list p1,…,pm∈D and set hi(q)=∥q−Tpi∥22−∥y−pi∥22,H(q)=max⁡1≤i≤mhi(q). By [F1], ∣∥u∥2−∥v∥2∣≤∥u−v∥2=d2(u,v), so each hi and their finite maximum H are continuous. Also, when ∥q∥2≥∥Tpi∥2, hi(q)≥(∥q∥2−∥Tpi∥2)2−∥y−pi∥22, which tends to +∞ as ∥q∥2→∞; thus H is coercive. The nonempty sublevel {H≤H(0)} is closed and bounded, hence compact by [F2]; [F3] gives a global minimizer q0 of H.

2.1A1F1F2F4step 1.1contradictionalgebra

Let I={i:hi(q0)=H(q0)} be the nonempty active set. Its gradients' convex hull is the image of the closed bounded simplex {α∈Rm:αi≥0,∑iαi=1} under the continuous affine map α↦∑i∈Iαi 2(q0−Tpi) (with zero weights outside I). The simplex is compact by [F2]; pulling an open cover back to it shows its continuous image is compact, and [F2] then makes that image closed. If 0 were not in the convex hull, project 0 onto it using [F4]. The projection vector v≠0 obeys ⟨v,2(q0−Tpi)⟩≥∥v∥22 for each i∈I, by the variational inequality. For sufficiently small ϵ>0, every active hi(q0−ϵv) decreases strictly; the finitely many inactive terms have a strict gap below H(q0) and remain below it by continuity. This contradicts minimality. Therefore there are weights αi≥0, supported on I, with ∑iαi=1 and q0=∑iαiTpi.

3.1A1F1step 2.1algebra

Put pˉ=∑iαipi. Expanding squares and using q0=∑iαiTpi gives H(q0)=∑iαihi(q0)=12∑i,jαiαj∥Tpi−Tpj∥22−∑iαi∥y−pi∥22. The nonexpansive hypothesis bounds the double sum by 12∑i,jαiαj∥pi−pj∥22=∑iαi∥pi−pˉ∥22. The variance identity also gives ∑iαi∥y−pi∥22=∥y−pˉ∥22+∑iαi∥pi−pˉ∥22. Hence H(q0)≤−∥y−pˉ∥22≤0. Thus every finite family of the closed balls B‾(Tp,∥y−p∥2) has nonempty intersection.

4.1A1F2F5step 3.1choose∎

Choose one p0∈D. The ball C0=B‾(Tp0,∥y−p0∥2) is compact by [F2]. The sets C0∩B‾(Tp,∥y−p∥2) are closed in C0, and every finite intersection is nonempty by step 3.1 applied with p0 included. [F5] therefore supplies a point q in their total intersection, which satisfies every required inequality. The proof used only finite-dimensional compactness and finite convex combinations; no choice principle is invoked.

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