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.
is complete in the supremum metric for every nonempty compact metric space
Statement
Let be a nonempty compact metric space. Every member of is bounded, so the supremum metric
is defined on . With this metric, is complete.
Facts & Assumptions
Given: A nonempty compact metric space and the set of continuous real-valued functions on it.
Every continuous real-valued function on a nonempty compact metric space has a bounded range (A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value).
If is nonempty, the formula defines a metric on the set of bounded functions (The supremum metric is a metric on the bounded real-valued functions on a nonempty set).
A sequence is Cauchy in a metric when, for every positive error, all pairwise distances sufficiently far out are below that error; it converges to when its distances to tend to zero (Cauchy sequence in a metric space, Convergence of a sequence in a metric space: iff in ).
A sequence of real-valued functions converges uniformly if and only if it is uniformly Cauchy (A sequence of real-valued functions converges uniformly if and only if it is uniformly Cauchy).
A uniform limit of continuous real-valued functions on a metric space is continuous (The uniform limit of continuous real-valued functions on a metric space is continuous).
A metric space is complete when every Cauchy sequence in it converges to one of its points (Complete metric space: every Cauchy sequence converges in the space).
Proof
By [L1], every is bounded. Thus is a subset of the bounded functions on , and the restriction of the metric in [L2] is a metric on .
Let be a Cauchy sequence in this supremum metric.
Given a real , choose such that for all . Then for all such and every , so is uniformly Cauchy.
By [L4] there is a function such that uniformly on .
The function is continuous by [L5], hence belongs to and is bounded by [L1].
Let . Uniform convergence gives such that for every and ; hence , so in the supremum metric.
Every Cauchy sequence in therefore converges in the supremum metric to a member of , so the metric space is complete.
Depends on
- The space $C(K,\mathbb{R})$ of continuous real-valued functions on a nonempty compact metric space
- The supremum metric $d_\infty(f,g) = \sup_x |f(x) - g(x)|$ is a metric on the bounded real-valued functions on a nonempty set
- A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value
- A sequence of real-valued functions converges uniformly if and only if it is uniformly Cauchy
- The uniform limit of continuous real-valued functions on a metric space is continuous
- Complete metric space: every Cauchy sequence converges in the space
- Convergence of a sequence in a metric space: $x_k \to x$ iff $d(x_k, x) \to 0$ in $\mathbb{R}$
- Cauchy sequence in a metric space
Used by
- The uniform closure of a unital real function algebra is closed under absolute value, maximum, and minimum Lemma
- Arzelà--Ascoli for real C(K) under Countable Choice and Dependent Choice: compact closure iff equicontinuous and pointwise bounded Theorem
- Under Dependent Choice, continuous nowhere differentiable functions form a dense subset of C([0,1],ℝ) Theorem
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 97 results over 15 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.
Sources
- MIT OpenCourseWare 18.100B, Real Analysis, Lectures 20–21 (standard reference, not scraped)
- W. Trench, Introduction to Real Analysis (standard reference, not scraped)