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.
Edge counts and densities between nonempty vertex sets
Definition
Let be a finite simple graph (A finite simple graph is a finite vertex set together with a set of two-element vertex subsets) and let . Define the ordered cross-edge count When and are nonempty, their edge density is We omit the subscript when the graph is clear. If and are disjoint, this agrees with the edges between sets in Edges between disjoint vertex sets; complete, anticomplete, pure and mixed pairs. If they overlap, an edge with both endpoints in contributes in both orientations, while diagonal pairs never contribute.
For a nonempty graph, write . By convention the density of the null graph is .
Depends on
Used by
- An H-free graph has a linearly large induced subgraph whose graph or complement has bounded maximum degree Corollary
- Few induced copies force a linearly large induced subgraph with bounded maximum degree Corollary
- The edge-density form of Rödl's theorem implies the maximum-degree form, with ε and δ each shrunk by a constant factor Corollary
- The edge-density form of Rödl's theorem: every nonempty H-free graph has a linearly large set of self-density at most ε or at least 1-ε Corollary
- A star has tiny self-density, yet no restricted subset containing its centre has more than two vertices Counterexample
- Three pair densities equal to 1/2 need not produce a single transversal triangle Counterexample
- Induced copy density and homogeneous restriction parameter Definition
- Sparsity of one vertex set to another, and weak sparsity of a pair Definition
- The mean-square density, or energy, of a vertex partition Definition
- ε-regular pairs and self-regular vertex sets Definition
- A clique of size s has self-density 1-1/s Example
- The triangle counting lemma is exact for three complete cross-pairs Example
- Two complete pairs and one anticomplete pair produce exactly |X₁||X₂||X₃| induced copies of P₃ Example
- A c-sparse set has self-density at most c, and a c-dense set has self-density at least 1-c-1/|X| Lemma
- A large γ-self-regular set whose density lies between η and 1-η forces at least c|W|^|V(H)| induced copies of H Lemma
- A set of self-density at most c has a subset of at least half its size that is 4c-sparse Lemma
- An ε-regular pair is ε'-regular for every ε'≥ε with ε'>0 Lemma
- Deleting the high-degree vertices of a γ-self-regular set of density d leaves more than (1-γ) of it, and that remainder is ((d+γ)/(1-γ))-sparse Lemma
- Deleting the low-degree vertices of a γ-self-regular set of density d leaves more than (1-γ) of it, and that remainder is ((1-d+2γ)/(1-γ))-dense Lemma
- For disjoint nonempty vertex sets, weak c-sparsity says exactly that the edge density is at most c Lemma
- Bounded degree against bounded density: the two statements of Rödl's theorem, and which one is stronger Remark
- Why the self-density bound for a dense set carries a 1/|X| slack Remark
- Every H-free graph has a homogeneous set of size at least 2^c√log₂ n Theorem
- Every H-free graph has a homogeneous set of size at least 2^c√log₂ n log₂ log₂ n Theorem
- Every H-free graph partitions into boundedly many vertex sets of self-density at most ε or at least 1-ε Theorem
- Nikiforov: for every H and every ε∈(0,1/2) there is δ>0 such that every graph G with ind_H(G)<(δ|V(G)|)^|V(H)| has an ε-restricted vertex set of size at least δ|V(G)| Theorem
Dependency tree · two levels
4 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
- Y. Zhao, Graph Theory and Additive Combinatorics, Definition 2.1.1 (standard reference, not scraped)
- D. Conlon and J. Fox, Graph removal lemmas, sec. 2.1 (standard reference, not scraped)