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.
FALSE: every connected subset of is polygonally connected
Statement
False claim: every connected subset of is polygonally connected.
The unit circle is connected but is not polygonally connected.
Facts & Assumptions
Given: The unit circle and the points .
Every connected subset of Euclidean space is polygonally connected.
is path-connected and connected (For , the sphere is path-connected and connected).
A polygonal path is a finite concatenation of straight segments (Polygonal paths and polygonally connected subsets of ).
If distinct unit vectors are joined by a segment, its midpoint has squared Euclidean norm (The Euclidean inner product on , A norm on a real vector space, the induced metric, and the dictionary with the metric axioms).
Refutation
Suppose the claim [A1] holds. Since is connected by [L1], there is a polygonal path in from to .
In its finite vertex list some adjacent vertices are distinct, since its endpoints are distinct. The straight segment from to lies in by [L2].
But the midpoint of this segment has norm strictly less than by [L3], so it does not lie in . This contradicts step 2.1.
Depends on
- For $n\ge2$, the sphere $S^{n-1}$ is path-connected and connected
- Polygonal paths and polygonally connected subsets of $\mathbb{R}^n$
- A norm on a real vector space, the induced metric, and the dictionary with the metric axioms
- The Euclidean inner product $\langle x,y\rangle = \sum_{k<n} x_k y_k$ on $\mathbb{R}^n$
Used by
Nothing in the library uses this result yet.
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 115 results over 22 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
- Sphere (standard reference, not scraped)
- Convex set (standard reference, not scraped)