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ExampleConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-29
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.

C([0,1],R) is complete, and on it the uniform metric and the supremum metric induce the same topology

Example

Let I:=[0,1] carry the metric d(s,t)=∣s−t∣ inherited from R (The absolute value makes R a metric space: d(x,y)=∣x−y∣ is a metric, its open balls are the intervals (x−r,x+r), and it is unbounded, Isometry, isometric embedding, and the subspace metric on a subset) and let R carry the same metric. Write C(I,R) for the continuous real functions on I, ρˉ for the uniform metric of For a nonempty set X and a metric space (Y,d) the uniform metric ρˉ(f,g)=sup⁡xmin⁡{d(f(x),g(x)),1} is a metric on YX and d∞ for the supremum metric of The supremum metric d∞(f,g)=sup⁡x∣f(x)−g(x)∣ is a metric on the bounded real-valued functions on a nonempty set. Then:

  1. every f∈C(I,R) is bounded, so d∞ is defined on C(I,R);
  2. ρˉ and d∞ are uniformly equivalent on C(I,R), hence induce the same topology there (Topologically, uniformly and Lipschitz equivalent metrics on a set, Lipschitz equivalence implies uniform equivalence implies topological equivalence);
  3. (C(I,R),ρˉ) is a complete metric space (Complete metric space: every Cauchy sequence converges in the space).

Claim 2 is this page's guarantee that no second notion of convergence has been created. For a nonempty set X and a metric space (Y,d) the uniform metric ρˉ(f,g)=sup⁡xmin⁡{d(f(x),g(x)),1} is a metric on YX mints a metric on YX that is not the published supremum metric — it truncates distances at 1 and needs no boundedness hypothesis — and a reader who has met d∞ first is entitled to ask whether "uniform convergence" now means two things. On the set where both are defined it does not: the two metrics take different values but have the same open sets, so they have the same convergent sequences, the same continuous functions and the same closed sets.

Facts & Assumptions

Given: I=[0,1] with d(s,t)=∣s−t∣, the target R with the same metric, C(I,R), the truncated metric dˉ=min⁡{d,1} on R, the uniform metric ρˉ and, once claim 1 is available, the supremum metric d∞(f,g)=sup⁡t∈I∣f(t)−g(t)∣.

[L2]

A continuous real function on a nonempty compact metric space is bounded and attains a greatest and a least value (A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value, Lower bound, bounded below, bounded set).

[L3]

d∞(f,g)=sup⁡{ ∣f(t)−g(t)∣:t∈I } is a metric on the bounded real functions on a nonempty set, and the supremum is an upper bound of its set and the least one (The supremum metric d∞(f,g)=sup⁡x∣f(x)−g(x)∣ is a metric on the bounded real-valued functions on a nonempty set, Complete ordered field (least-upper-bound property), Suprema and infima are unique).

[L5]

Uniform equivalence of two metrics on one set, and the implication uniform ⇒ topological (Topologically, uniformly and Lipschitz equivalent metrics on a set, Lipschitz equivalence implies uniform equivalence implies topological equivalence, claim 2).

Verification

technique · direct
1.1

I is nonempty and compact, and every f∈C(I,R) is continuous on it, hence bounded; so C(I,R) is a subset of the bounded real functions on I and d∞ is defined on it, which is claim 1.

L1L2L3
2.1

For all f,g∈C(I,R) and every t∈I: dˉ(f(t),g(t))≤∣f(t)−g(t)∣≤d∞(f,g), so d∞(f,g) bounds the set whose supremum is ρˉ(f,g) and therefore ρˉ(f,g)≤d∞(f,g).

step 1.1L3L4
3.1

Let ε>0 be real and put δ:=min⁡{ε,1}/2, a real with 0<δ≤1/2<1 and δ<ε; if ρˉ(f,g)<δ then for every t∈I we have dˉ(f(t),g(t))≤ρˉ(f,g)<δ<1, hence ∣f(t)−g(t)∣=dˉ(f(t),g(t))<δ, so δ bounds the set whose supremum is d∞(f,g) and d∞(f,g)≤δ<ε.

step 2.1L3L4
4.1

Steps 2.1 and 3.1 give uniform equivalence: for a real ε>0 the choice δ′:=ε makes d∞(f,g)<δ′ imply ρˉ(f,g)<ε, and the δ of step 3.1 makes ρˉ(f,g)<δ imply d∞(f,g)<ε; hence the two metrics are uniformly equivalent on C(I,R) and therefore topologically equivalent, which is claim 2.

step 2.1step 3.1L5
5.1

(R,d) is complete and I is a nonempty topological space, so C(I,R) with the restriction of ρˉ is a complete metric space, which is claim 3.

step 1.1L1L6∎

Remarks

  • The two metrics really are different functions. Take f constant 0 and g constant 2: then d∞(f,g)=2 while ρˉ(f,g)=1. What claim 2 says is that this difference is invisible to the topology, not that it does not exist. In particular an assertion about the value of the distance — a diameter, a Lipschitz constant, a radius — must name which metric it means.

  • Completeness is inherited from R and from closedness, in that order. R is complete, so all the real functions on I are complete in the uniform metric; the continuous ones form a closed subset by the uniform limit theorem (A uniform limit of continuous functions is continuous, so C(X,Y) is closed in YX under the uniform metric); and a closed subset of a complete space is complete. Completeness in d∞ follows as well, since uniformly equivalent metrics have the same Cauchy sequences and the same convergent sequences, both conditions being expressed with ε and δ alone.

  • Compactness of I is used only for claim 1. Boundedness of every continuous function is what makes d∞ defined at all, and that is the extreme value theorem. On a non-compact domain the supremum metric is unavailable on all of C(X,R), while the uniform metric ρˉ remains defined; that is the whole reason this page mints the truncated metric.

Depends on

Used by

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Dependency tree · two levels

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Sources