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TheoremStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-12
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Morse stability with explicit parameter dependence

Statement

Assume AC for the projection-family proof below. For λ≥1, ε≥0 and δ≥0, the image of every possibly discontinuous (λ,ε)-quasi-geodesic map of a nonempty compact real interval into a geodesic δ-slim space has Hausdorff distance at most M=92λ2(ε+3δ) from every geodesic with the same endpoints. No properness is assumed.

Facts & Assumptions

Given: Such a map q:[a,b]→X, a≤b, and a specified endpoint geodesic. Put κ=3δ.

[F1]

Quasi-geodesics, nonempty interval domains, infimum distances and both Hausdorff inclusions have the conventions of Hg toolkit local geodesics and hausdorff control. The product inequality holds with κ=3δ by Slim triangles imply the gromov product inequality; it is equivalent to the four-point condition by The gromov product inequality implies the four point condition.

[F2]

In a geodesic product-κ space all chosen triangles are 4κ-slim by The four point condition implies slim triangles.

[F3]

For d(q(a),q(b))≥2ε, Hg toolkit polygonal interpolation of quasi geodesics supplies a 2λ-Lipschitz (λ,4ε)-quasi-geodesic with the same endpoints and Hausdorff error at most 2ε. Its short-endpoint bound is 3λ2ε+ε from q(a).

[F4]

Closest points on a specified segment exist, remain projections along their radial segments and satisfy d(x,p)+d(p,z)≤d(x,z)+4κ for z on the target. Both the geodesic-target and quasiconvex-target exponential contraction estimates are supplied by Exponential contraction of projection away from a quasiconvex set.

[F5]

AC permits the families of closest points and radial geodesics used below (The Axiom of Choice). No closest-point assertion for arbitrary closed sets is assumed.

Proof

1.1F1algebra

We first derive auxiliary metric estimates using only the product constant κ. For a specified segment [u,v] and a point z, choose its point m at distance (z∣v)u from u. This parameter lies between zero and d(u,v). Put P=(u∣v)z. Expanding products shows that d(u,z)+d(v,m)=d(v,z)+d(u,m)=d(u,v)+P. The four-point inequality therefore gives d(z,m)≤P+2κ. Every point w on [u,v] satisfies P≤d(z,w), by adding the two triangle inequalities through w. Also, for any w∈[u,v], d(z,w)≤max⁡{d(z,u),d(z,v)}+κ: if w is within κ of an endpoint this follows by the triangle inequality; otherwise the four-point inequality gives d(z,w)≤max⁡{d(z,u)−d(w,u),d(z,v)−d(w,v)}+2κ, which gives the claim since both sublengths exceed κ.

1.2F1F4algebra

Let Y be nonempty and Q-quasiconvex as in F4, and suppose p,r∈Y are closest points of x,y respectively. For any z∈Y, choose its quasiconvexity segment [p,z] and its point u at parameter t=(x∣z)p. 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. Points of Y occur arbitrarily close to distance Q from u, hence closest-point minimality implies t≤Q+2κ. Thus d(x,p)+d(p,z)≤d(x,z)+2Q+4κ. With A=d(x,p), B=d(y,r) and s=d(p,r), adding the estimates for z=r and z=p gives d(x,r)+d(y,p)≥A+B+2s−4Q−8κ. The four-point inequality bounds this by max⁡{A+B,d(x,y)+s}+2κ. If s>2Q+5κ, the first maximum entry cannot suffice; therefore s≤max⁡{2Q+5κ,d(x,y)−A−B+4Q+10κ}. The first radial estimate with z=r also gives s≤d(x,r)−A+2Q+4κ, since B≤d(y,p)≤d(x,y)+A. If B≤A then d(x,r)≤d(x,y)+B≤d(x,y)+A; if B>A then the same radial estimate with the roles of x,p and y,r interchanged gives s≤d(y,p)−B+2Q+4κ≤d(x,y)+A−B+2Q+4κ. Hence in every case the prime projection bound s≤d(x,y)+2Q+4κ holds.

1.3F1F2F4algebra

For a specified segment H, put VR={x:d(x,H)≤R}, R≥0. Closest points on H exist by F4. If p projects x onto H and d(x,H)≥R, the radius-R point q on [p,x] projects x onto VR: the triangle inequality gives d(x,y)≥d(x,H)−R for y∈VR, and q attains equality. The same argument and F4 show that q projects every later point of [p,x] onto VR. Moreover VR is 8κ-quasiconvex. Join two points of VR to closest points on H by radial segments of length at most R. The radial segments and intervening part of H lie in VR. Splitting the resulting quadrilateral by a diagonal and applying F2 twice puts every point of any fourth side within 8κ of these three segments, with arbitrarily small witness errors. Hence that side lies in the closed 8κ-neighbourhood of VR. This includes R=0, where the sharper quasiconvexity constant zero is available.

1.4F1F6algebra

The following elementary real facts justify the extrema and numerical steps. A Lipschitz function on a compact interval is bounded by its value at one endpoint plus or minus its Lipschitz constant times the interval length, and attains its infimum: bisect, keep the left half when it has the same infimum and otherwise the right half; nested left endpoints have a supremum, and the Lipschitz bound times the interval length tends to zero, forcing attainment there. Infima exist by the real completeness convention in F1. A continuous real function with opposite weak signs at the ends has a zero by the same interval bisection retaining opposite endpoint signs; continuity at the limiting point proves its value is zero. Finally F6's positive series terms give exp⁡(t)≥1+t for t≥0. Put q0=693/1000. Exact rational arithmetic gives ∑j=06q0jj!+q077!11−q0/8<2,∑j=016((459/50)q0)jj!>579. In the first inequality the omitted exponential tail has successive ratios at most q0/8 and is bounded by the displayed geometric tail. Thus exp⁡(q0)<2, so log⁡2>q0. Monotonicity and the second inequality yield (log⁡2)exp⁡((459/50)log⁡2)>q0⋅579=401247/1000>400, and consequently 3200exp⁡(−(459/50)log⁡2)log⁡2<8. All these are rational finite-sum comparisons and geometric tail bounds, not rounded numerical estimates.

2.1step 1.2F1algebra

Fix ρ>κ. Here is the required small-gap assertion. Suppose f:[u,v]→X is continuous, p(t) is any supplied closest-point selection in a Q-quasiconvex set, and 4ρ+2Q≤h≤d(p(u),p(v)). There is w∈[u,v] with h−4ρ−2Q≤d(p(u),p(w))≤h and with d(p(u),p(t))≤h for every t∈[u,w]. Write J(t)=d(p(u),p(t)). If J≤h everywhere, use w=v. Otherwise let t0=inf⁡{t:J(t)>h}. The prime projection bound of step 1.2 and continuity of f at u make J(t)<h on some initial interval, because 4κ+2Q<h; hence t0>u. All t<t0 have J(t)≤h. By continuity at t0, choose w<t0 and t′≥t0 with J(t′)>h, both close enough to t0 that 2d(f(w),f(t′))<4(ρ−κ). Such bad t′ occur arbitrarily close to the infimum. The prime projection bound of step 1.2 gives d(p(w),p(t′))≤d(f(w),f(t′))+2Q+4κ<2(ρ−κ)+2Q+4κ=2ρ+2Q+2κ≤4ρ+2Q, so J(w)>h−4ρ−2Q. This proves the assertion without continuity of p. Reversing the real parameter gives the corresponding assertion from the right endpoint.

2.2step 1.4F1F6algebra

We now prove the continuous estimate, assuming more precisely that f:[a,b]→X is Lipschitz and is a (λ,C)-quasi-geodesic, C≥0. Fix z∈[a,b] and ρ>κ. Set L=18ρ, D=55ρ, α=3/25, and β=αlog⁡25(4+(L+2ρ)/D)ρλ,A∗=42λexp⁡(−(1−α)Dlog⁡25ρ),B∗=L+4ρL−13ρA∗β. All denominators and these constants are positive. Put T∗=λ2(D+3L/2+ρ+11C/2)−2ρ and h0=ρ/(4λ). We shall prove, by induction on a nonnegative integer n, for every a≤u≤z≤v≤b with v−u≤nh0, that (f(u)∣f(v))f(z)≤T∗+B∗(1−exp⁡(−β(v−u))). For n=0, u=v=z and the left side is zero, whereas T∗≥81ρ≥0. The constants are independent of u,v,n.

3.1step 1.1step 2.2F1F4F5algebra

Assume the induction bound for n, and let v−u≤(n+1)h0. Write Z=f(z), U=f(u), V=f(v), P=(U∣V)Z. If P≤L, the bound holds since T∗≥81ρ>L and the exponential contribution is nonnegative. Suppose P>L. Choose any segment [U,V] and its point m at parameter (Z∣V)U, as in step 1.1. Then P≤d(Z,m)≤P+2κ<P+2ρ. On a specified segment H=[Z,m], let π have distance P from Z; thus d(π,m)≤2ρ. Using F4 and AC, select closest points p(t)∈H for all t∈[a,b]. In particular p(z)=Z. Closest-point minimality gives d(U,Z)≤d(U,p(u))+d(p(u),Z)≤d(U,m)+d(p(u),Z); since d(U,Z)−d(U,m)=P, we have d(p(u),Z)≥P. Thus p(u) lies between π and m. The same computation holds for p(v).

4.1step 2.1step 1.4step 3.1F1algebra

Apply step 2.1 on [u,z] with Q=0 and threshold L+d(π,p(u)). It is at least 4ρ and is less than d(p(u),Z) since L<P. Obtain y−∈[u,z] with L+d(π,p(u))−4ρ≤d(p(u),p(y−))≤L+d(π,p(u)), and this upper bound holds on all of [u,y−]. From the right endpoint similarly obtain y+∈[z,v]. Measure coordinates on H from m. The initial projections have coordinates in [0,d(m,π)], and the upper bounds imply that all projections in these two outer intervals have coordinates in [0,L+d(m,π)]. Hence their pairwise distance is at most L+2ρ, and their individual distances from π are at most L (since d(m,π)≤2ρ<L). The function t↦d(f(t),H) is Lipschitz, by the triangle inequality and Lipschitzness of f. Step 1.4 gives minima d−,d+ attained at c−∈[u,y−], c+∈[y+,v].

5.1step 4.1F1F4algebra

For r∈[u,y−] and s∈[y+,v], the lower quasi-geodesic inequality and the route through their projections give s−r≤λ(d(f(r),H)+d(f(s),H)+L+2ρ+C). We also have the product recurrence P≤(f(r)∣f(s))Z+L+4ρ. Indeed F4 gives (f(r)∣p(r))Z≥d(Z,p(r))−2κ≥P−L−2κ, and the same holds on the right. The product of p(r),p(s) at Z is the smaller of their radial distances, at least P−L. Applying the product inequality twice through these two projections gives (f(r)∣f(s))Z≥P−L−4κ≥P−L−4ρ.

6.1step 5.1step 2.2F1algebra

If both d−,d+≤D+4C, put s0=d(f(c−),f(c+)). The sum of the two upper quasi-geodesic bounds via z gives 2(f(c−)∣f(c+))Z≤λ(c+−c−)+2C−s0. If s0≥12ρ, step 5.1 gives c+−c−≤λ(2D+L+2ρ+9C), hence (f(c−)∣f(c+))Z≤λ2(D+L/2+ρ+11C/2)−6ρ. If s0≤12ρ, the direct lower quasi-geodesic bound gives c+−c−≤λ(12ρ+C), so the same product is at most λ2(6ρ+3C/2), which is bounded by that preceding expression because D=55ρ, L=18ρ and λ≥1. Adding the recurrence loss L+4ρ≤λ2L+4ρ in step 5.1 proves P≤T∗ and thus the required induction bound.

7.1step 1.3step 4.1step 6.1F4F5algebra

In the remaining case one of d−,d+ is at least D+4C and is the larger. First suppose d=d−≥D+4C and d+≤d. By AC choose, for each parameter t, a radial segment from p(t) to f(t). For integers k≥0 define Rk=(2k−1)d, Vk=VRk from step 1.3, and let qk(t) be the point at radius min⁡{Rk,d(f(t),H)} on that radial segment. Set Q0=0 and Qk=8ρ for k≥1. Step 1.3 makes Vk Qk-quasiconvex; when d(f(t),H)≥Rk, qk(t) is a closest point to Vk. We use the following finite stopping construction. At stage k there is x∈[u,y−] such that d(f(t),H)≥(2k+1−1)d(u≤t≤x),d(qk(u),qk(x))≥L−4ρ+7Qk. The initial stage k=0 uses x=y− by its projection lower bound in step 4.1 and the definition of the minimum d.

8.1step 2.1step 7.1algebra

Given a stage, apply step 2.1 to Vk on [u,x] with threshold 9ρ+4Qk. This lies between 4ρ+2Qk and L−4ρ+7Qk. Obtain w∈[u,x] with 5ρ+2Qk≤d(qk(u),qk(w))≤9ρ+4Qk, and the upper bound holds for every parameter in [u,w]. If some t∈[u,w] satisfies d(f(t),H)≤(2k+2−1)d, choose such a t and call it r. This is the stopping case, handled next. Otherwise every parameter in [u,w] has distance strictly greater than that threshold; the next-stage construction below applies with x=w.

9.1step 5.1step 7.1step 8.1step 2.2algebra

In the stopping case u≤r≤w≤x≤y−. For t∈[r,x], step 7.1 and radial projection give d(f(t),Vk)≥2kd. Step 5.1 and d(f(r),H)≤(4⋅2k−1)d give c+−r≤λ2k(4+(L+2ρ)/D)d. Here L+C+2ρ≤((L+2ρ)/D)d, since d≥D+4C and 4(L+2ρ)≥D, and d+≤d. Also 2kd−C/2−Qk≥(1−α)D+α2kd. For k=0 this is (1−α)(d−D)≥C/2, which follows from d−D≥4C. For k≥1, (1−α)(2kd−D)≥(1−α)(D+8C)≥8ρ+C/2, proving the other case.

10.1step 7.1step 8.1step 9.1step 2.2F4F6algebra

The stage lower bound and the projection cap up to w imply d(qk(r),qk(x))≥L−13ρ+3Qk. Apply F4's exponential contraction to f∣[r,x] and Vk, with lower distance 2kd. Its hypothesis 2kd≥15ρ/2+Qk+C/2 follows from d≥55ρ+4C. For k=0, use F4's sharper segment-target estimate, with no additive term. For k≥1, its additive term is 2Qk+8ρ=3Qk. Thus, in both cases, L−13ρ≤max⁡{5κ,42λ(x−r)exp⁡(−(2kd−C/2−Qk)log⁡25ρ)}. Since L−13ρ=5ρ>5κ, the exponential entry is at least L−13ρ. Step 9.1 splits its exponent and yields L−13ρ≤A∗(x−r)exp⁡(−α2kdlog⁡25ρ). The exponentials before splitting are at most one, and 42≤20, so also x−r≥ρ/(4λ)=h0.

11.1step 1.4step 2.2step 5.1step 9.1step 10.1F6algebra

The first bound in step 9.1 gives exp⁡(−α2kdlog⁡2/(5ρ))≤exp⁡(−β(c+−r)). Use t≤exp⁡(t)−1 for t=β(x−r)≥0 from step 1.4 and exponential addition to obtain β(x−r)exp⁡(−α2kdlog⁡25ρ)≤exp⁡(−β(c+−x))−exp⁡(−β(c+−r))≤exp⁡(−β(c+−x))−exp⁡(−β(v−u)). Combining this with step 10.1 and the definition of B∗ yields L+4ρ≤B∗(exp⁡(−β(c+−x))−exp⁡(−β(v−u))). Moreover c+−x+h0≤c+−r≤v−u≤(n+1)h0, so c+−x≤nh0. The outer induction hypothesis applies to [x,c+], which contains z. Adding its bound to the recurrence in step 5.1 cancels the two intermediate exponentials exactly and gives P≤T∗+B∗(1−exp⁡(−β(v−u))). This proves the required induction step whenever the stopping case occurs.

12.1step 1.2step 1.3step 7.1step 8.1step 11.1algebra

If there is no stopping point in step 8.1, every t∈[u,w] has d(f(t),H)>(2k+2−1)d. Both qk+1(u) and qk+1(w) therefore exist at their prescribed radii; their distances to qk(u),qk(w) respectively equal 2kd, and step 1.3 makes those earlier radial points their closest points in Vk. Apply the contraction inequality of step 1.2 to these two new points. Because the old projection gap is at least 5ρ+2Qk>5κ+2Qk, its second maximum entry must apply. Hence d(qk+1(u),qk+1(w))≥2k+1d−5ρ−2Qk≥L−4ρ+7Qk+1. For the last inequality it suffices to use 2k+1d≥2D=110ρ, Qk≤8ρ, Qk+1=8ρ and L=18ρ: the left side is at least 89ρ and the required right side is 70ρ. Thus x=w gives the next stage. Choose in advance a finite integer k0 with (2k0+1−1)d>d(f(u),H), possible since d>0. Stage k0 is impossible at t=u. Only finitely many stages and selections are therefore required, and a stopping case must have occurred. Step 11.1 proves the desired bound in this large-left-minimum case.

13.1step 2.2step 3.1step 6.1step 7.1step 11.1step 12.1F1algebra

If instead d+≥D+4C and d−≤d+, reverse the real parameter by replacing f(t) with f(−t) on [−b,−a], and replace u,z,v by −v,−z,−u. Lipschitz and quasi-geodesic constants, products and interval lengths are unchanged; the large-right minimum becomes the large-left minimum. Steps 7.1–12.1 then shorten to an interval containing −z by at least h0. The same outer induction hypothesis applies because it concerns all intervals containing the fixed point and uses only their length and products; equivalently undo the reversal on the resulting shorter interval before applying it. This yields the identical bound for the original interval. Together with steps 3.1 and 6.1, all cases of the induction step are proved. Every finite b−a is at most nh0 for some integer n, so the induction applies to [a,b].

14.1step 1.1step 1.4step 2.2step 13.1F6algebra

For any specified geodesic G=[f(a),f(b)], step 1.1 and the resulting product bound give d(f(z),G)≤λ2(D+3L/2+ρ+11C/2)+B∗. Substituting the constants in step 2.2 and combining exponentials gives B∗=λ2ρ3200exp⁡(−(459/50)log⁡2)log⁡2<8λ2ρ. Indeed 4+(L+2ρ)/D=48/11, (1−α)D/(5ρ)=242/25, and the 2 factor changes the exponential exponent to −459/50. Step 1.4 proves the strict numerical bound. Since D+3L/2+ρ=83ρ, we obtain d(f(z),G)≤λ2(11C/2+91ρ). This holds for every ρ>κ, so real order gives d(f(z),G)≤D0:=λ2(11C/2+91κ) by letting ρ decrease to κ. No limiting choice of projections is required, because the resulting inequality concerns the same fixed distance.

15.1step 1.1step 1.4step 14.1F1F4algebra

Fix x∈G and split that specified segment into G− from f(a) to x and G+ from x to f(b). The two functions t↦d(f(t),G±) are continuous, and their minimum is at most D0 by step 14.1 and the union G=G−∪G+. Their difference is nonpositive at a and nonnegative at b, so step 1.4 gives a parameter t where they are equal and thus both at most D0. F4 gives closest points x−∈G−, x+∈G+ to f(t), each within D0. The subsegment [x−,x+] of G contains x. Step 1.1 gives d(x,f(t))≤max⁡{d(x−,f(t)),d(x+,f(t))}+κ≤D0+κ. Together with step 14.1 and λ≥1, both Hausdorff inclusions give dH(f([a,b]),G)≤λ2(11C/2+92κ). This includes constant G, a one-point interval and κ=0.

16.1step 3.1step 7.1step 15.1F1F3F5givenalgebra∎

Return to the possibly discontinuous q. If its endpoint distance is at least 2ε, apply F3 to obtain the Lipschitz map f with C=4ε. Step 15.1 and the two inclusions in F3 give, by adding approximate point-to-set witnesses, dH(q([a,b]),G)≤2ε+λ2(22ε+92κ)≤λ2(24ε+92κ)≤92λ2(ε+κ). For precision, each point-to-set bound is composed with witnesses whose errors are arbitrarily small, and then the errors tend to zero; no nearest point on q([a,b]) is asserted. If the endpoint distance is less than 2ε, F3 places every image point within 3λ2ε+ε≤4λ2ε of q(a)∈G, while every point of G is within 2ε of q(a)∈q([a,b]). The same desired bound follows directly. When ε=0, F3 uses f=q, and the zero-κ limit above remains valid. Finally κ=3δ yields the exact stated 92λ2(ε+3δ). AC was spent in the explicitly supplied closest-point and radial-segment families in steps 3.1 and 7.1; interval minima, the finite stopping construction and all boundary cases were justified locally.

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