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.
A compact set inside an open set has a uniform neighborhood radius
Statement
Let be compact in Euclidean and let be open with . There is such that for every , if , then . If , any positive works.
Facts & Assumptions
Given: Compactness and openness in the Euclidean metric (Open cover, subcover, compact metric space, and compact subset of a metric space, The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement, as the set of functions , and , , are metrics on it); compactness is intrinsic to the subspace metric (A subset of a metric space is open in the subspace metric exactly when it is the trace of an open set of the ambient space, and it is compact as a metric space in its own right exactly when every family of open subsets of the ambient space covering it, indexed or not, has finitely many members covering it).
Every open cover of compact has a finite subcover (Open cover, subcover, compact metric space, and compact subset of a metric space, A subset of a metric space is open in the subspace metric exactly when it is the trace of an open set of the ambient space, and it is compact as a metric space in its own right exactly when every family of open subsets of the ambient space covering it, indexed or not, has finitely many members covering it).
A nonempty finite set of real numbers has a minimum that belongs to the set (Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set).
Proof
If , take . Otherwise form the family of all balls with , , and . Each such ball is open: if , then and by the triangle inequality. By [F1] this family covers ; [F2] supplies a finite subcover , .
Since , the finite subcover has at least one ball. The minimum belongs to the nonempty finite set of positive radii, so by [F3]. Given and , choose a covering ball containing . Then for its index , , so .
Depends on
- Open cover, subcover, compact metric space, and compact subset of a metric space
- The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement
- Open ball, closed ball and sphere in a metric space
- Metric space: $d(x,y) = 0$ iff $x = y$, symmetry, and the triangle inequality; pseudometric and ultrametric
- The Euclidean inner product $\langle x,y\rangle = \sum_{k<n} x_k y_k$ on $\mathbb{R}^n$
- $\mathbb{R}^n$ as the set of functions $n \to \mathbb{R}$, and $d_1$, $d_2$, $d_\infty$ are metrics on it
- Cauchy-Schwarz $\lvert\langle x,y\rangle\rvert \le \lVert x\rVert_2\lVert y\rVert_2$ with its equality case, the triangle inequality for $\lVert\cdot\rVert_2$, the parallelogram law and polarisation
- A subset of a metric space is open in the subspace metric exactly when it is the trace of an open set of the ambient space, and it is compact as a metric space in its own right exactly when every family of open subsets of the ambient space covering it, indexed or not, has finitely many members covering it
- Every nonempty finite set of reals has a maximum and a minimum
- Maximum and minimum of a set
Used by
Dependency tree · two levels
41 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- A. R. Conn, K. Scheinberg, and L. N. Vicente, Introduction to Derivative-Free Optimization, §§2.1–2.2 and ch. 8 (standard reference, not scraped)
- Tamara G. Kolda, Robert Michael Lewis, and Virginia Torczon, Optimization by Direct Search, §§3.1–3.6 and Nelder–Mead discussion (standard reference, not scraped)