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LemmaStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-12
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Exponential contraction of projection away from a quasiconvex set

Statement

Let a geodesic space satisfy the product condition with constant κ≥0, and let ρ>κ. A nonempty set Y is K-quasiconvex, K≥0, if every two points of Y admit a geodesic contained in its closed K-neighbourhood. Suppose q:[a,b]→X is a (λ,ε)-quasi-geodesic, a≤b, and supplied points pa,pb∈Y attain the distances of q(a),q(b) to Y. If d(q(t),Y)≥D for all t and D≥15ρ/2+K+ε/2, then d(pa,pb)≤2K+8ρ+max⁡{5κ,42λ(b−a)exp⁡(−(D−K−ε/2)log⁡25ρ)}. No closest-point existence for general Y is assumed. Only the upper quasi-geodesic bound is used.

For a specified geodesic segment Y=H, the sharper estimate holds with the additive 2K+8ρ term omitted and with K=0 in the exponential and distance hypothesis. Closest points on such a segment exist. If p is a closest point of x on H and z∈H, then d(x,p)+d(p,z)≤d(x,z)+4κ; points on [p,x] retain p as a closest point. These additional interfaces are proved below.

Facts & Assumptions

Given: The space, constants, map, set and attained endpoint projections specified above.

[F1]

The quasi-geodesic upper bound and infimum distance convention are those of Hg toolkit local geodesics and hausdorff control.

[F2]

The product condition gives the four-point inequality with opposite-pair gap 2κ by The gromov product inequality implies the four point condition.

Proof

1.1F1givenalgebra

We first justify projections to any specified geodesic segment H=γ([0,ℓ]). The function f(t)=d(x,γ(t)) is 1-Lipschitz. Let m=inf⁡f([0,ℓ]). Bisect the interval, keeping the left half if its infimum is m, and otherwise the right half, whose infimum must be m since the original interval is their union. Iteration gives nested closed intervals of length ℓ/2n, each with infimum m. Their left endpoints have a supremum r belonging to all the intervals, by completeness. Lipschitz control gives 0≤f(r)−m≤ℓ/2n, hence f(r)=m. This includes ℓ=0. Moreover, if p is a closest point of x in H and x′ lies on [p,x], then p is still closest to x′: for z∈H, d(x′,z)≥d(x,z)−d(x,x′)≥d(x,p)−d(x,x′)=d(x′,p).

1.2F2givenalgebra

For a closest point p of x on a segment H and z∈H, put t=(x∣z)p and choose u∈[p,z] at radius t. Write A=d(x,p) and P=d(p,z); from the definition of t we have A+P=d(x,z)+2t. Applying the product inequality at basepoint x with bridge u gives (p∣z)x≥min⁡{(p∣u)x,(u∣z)x}−κ, and the products expand to (p∣z)x=A−t and (p∣u)x=(u∣z)x=(A+d(x,u)−t)/2, since d(p,u)=t. Hence d(x,u)≤d(x,p)−t+2κ. Minimality of p forces t≤2κ, or equivalently d(x,p)+d(p,z)≤d(x,z)+4κ. For projections p,r of x,y to the same segment, put A=d(x,p), B=d(y,r) and s=d(p,r). The just-proved estimate gives d(x,r)+d(y,p)≥A+B+2s−8κ. By the four-point inequality this sum is at most max⁡{A+B,d(x,y)+s}+2κ. If s>5κ, the first entry of the maximum cannot suffice, and consequently s≤d(x,y)−A−B+10κ. Thus always s≤max⁡{5κ,d(x,y)−A−B+10κ}.

2.1step 1.1step 1.2F2algebra

Here is the halving estimate. Suppose projections p,r of x,y lie on a segment H, d(x,y)≤10ρ+c, c≥0, and A,B≥M+5ρ+c/2, with M≥15ρ/2. Step 1.2 gives s=d(p,r)≤5κ≤5ρ. Let x′,y′ be the radius-M points on [p,x],[r,y]. Step 1.1 preserves their projections. At basepoint p, all three products (x′∣x)p,(x∣y)p,(y∣y′)p are at least M: the first is exactly M; the second follows from d(p,y)≥B and A+B−d(x,y)≥2M; the third follows from d(p,y′)≥M, d(p,y)≥B and d(y,y′)=B−M. Two product inequalities give (x′∣y′)p≥M−2ρ. The same argument at r gives the analogous bound. Writing v=d(x′,y′), we obtain d(p,y′)≥M−4ρ+v and d(r,x′)≥M−4ρ+v. Four-point control now yields 2M−10ρ+2v≤max⁡{s+v,2M}. Since s≤5ρ≤2M−10ρ, if the first entry is maximal this forces v=0; otherwise it gives v≤5ρ. In either case d(x′,y′)≤5ρ.

2.2step 1.1step 1.2F1givenalgebra

For the original Y, choose its quasiconvexity segment H=[pa,pb], and choose closest points ra,rb of q(a),q(b) on H using step 1.1. For any h∈H and any e>0, there exists y∈Y with d(h,y)<K+e. Consequently D≤d(q(t),y)≤d(q(t),h)+K+e. Letting e tend to zero and taking the infimum over h shows d(q(t),H)≥D−K. At h=ra, minimality of pa in Y similarly gives d(q(a),pa)≤d(q(a),ra)+K. Step 1.2 on H, with x=q(a),p=ra,z=pa, then gives d(ra,pa)≤K+4κ≤K+4ρ. The same estimate holds at b.

3.1step 1.1step 1.2step 2.1

By finite induction, a chain z0,…,z2j with projections ri to H, adjacent gaps at most 10ρ+c, and projection distances at least 5ρj+15ρ/2+c/2, satisfies d(r0,r2j)≤5κ. For j=0 this is step 1.2. For j+1, move each point along its projection segment to radius M=5ρj+15ρ/2. Step 2.1 makes adjacent new gaps at most 5ρ. Discard odd-indexed points: adjacent retained gaps are at most 10ρ, their projections are unchanged by step 1.1, and all their distances to H equal M. The induction hypothesis with c=0 applies to this chain of 2j gaps and proves the claim. This is an induction over finite chains, not a selection over all path parameters.

4.1step 1.1step 3.1F1algebra

First consider a geodesic target H with the whole image at distance at least D0≥15ρ/2+ε/2. Set j=⌊(D0−ε/2−15ρ/2)/(5ρ)⌋≥0 and T=λ(b−a). If T≤10ρ2j, sample q at 2j+1 equally spaced parameters and project to H, retaining the supplied endpoint projections. Step 1.1 supplies the finitely many other projections. Each adjacent gap is at most 10ρ+ε, and step 3.1 gives the bound 5κ. Even when a=b, the two endpoint projections may be supplied differently; the finite chain argument still applies.

4.2step 1.1step 3.1F1algebra

If T>10ρ2j, take the least integer N with T≤10ρ2N. Then N>j and 2N<T/(5ρ), by minimality. Sample at 2N+1 equally spaced parameters, with finite projections as before. Each block of 2j gaps satisfies step 3.1. Adding over the 2N−j blocks gives d(ra,rb)≤5κ2N−j≤5ρ2N−j≤T2−j.

5.1step 4.1step 4.2F3algebra

The floor defining j gives j>(D0−ε/2)/(5ρ)−5/2. Using F3, 2−j≤42exp⁡(−(D0−ε/2)log⁡2/(5ρ)). Here log⁡2>0 because exp⁡ is increasing and exp⁡(0)=1; addition gives exp⁡(−jlog⁡2)=2−j and exp⁡((5/2)log⁡2)=42 (the latter is positive and its square is 32). Thus steps 4.1–4.2 give the asserted maximum bound for a segment target, without the 2K+8ρ term.

6.1step 5.1step 2.2algebra∎

Apply step 5.1 with D0=D−K, whose required lower bound is exactly the stated hypothesis. The triangle inequality through ra,rb adds at most 2K+8ρ by step 2.2, yielding the displayed result. The proof uses finite choices and uniquely specified bisections only; it never assumes projections of arbitrary points onto Y. The auxiliary positive ρ also permits κ=0 without division by zero.

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