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.
For large , the Fox–Sudakov choice of leaves a dense-or-sparse set of order at least
Example
Fix a finite graph , let be the constant from Fox–Sudakov: a quantitative density form of Rödl's theorem ‡, and let be an -free graph on vertices. Write , assume , and choose .
Facts & Assumptions
Given: The data in the Example, in particular .
For , the quantitative-density theorem gives every -free -vertex graph a set of order at least such that or its complement has at most edges (Fox–Sudakov: a quantitative density form of Rödl's theorem ‡).
Verification
For the chosen , one has , so .
Therefore .
So the source theorem guarantees a dense-or-sparse set of order at least .
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
3 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
- Matija Bucić, Tung Nguyen, Alex Scott, and Paul Seymour, Induced subgraph density. I. A loglog step towards Erdős-Hajnal, Theorem 1.5 (standard reference, not scraped)