Alphabeta Math
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.

✓ 21 results · all verified · 17 also independently AI-judged
Every result on this page is machine-checked by a proof checker and read in full and owner-audited; the judge is an additional, independent cross-model AI review of the proofs. The 4 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

Sparse Restricted Subgraphs and the Rödl–Nikiforov Theorems

1 · Prerequisites

2 · Summary

The input from the regular-pairs page is the whole quantitative engine here: edge density, ϵ-regular pairs, typical-degree estimates, the induced counting lemma, and the theorem producing large self-regular subsets. Those results let the page translate between maximum-degree sparsity and density sparsity without redoing regularity from scratch. The induced-copy number is the bridge from counting information to structure, and the complement dictionary is what lets sparse and dense conclusions be treated in parallel rather than separately.

The page defines c-sparse, c-dense, and c-restricted sets, together with the directional and weak density language used in the literature. It proves the transfer, complement, and trimming lemmas that convert a self-regular set of extreme density into a genuinely restricted set, then proves Nikiforov's few-copies theorem and Rödl's theorem. The closing results compare the density and maximum-degree normalisations, extend Rödl to forbidden families and large induced subgraphs, and show that boundedly many extreme-self-density parts suffice to cover or partition every H-free graph.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

c-sparse, c-dense and c-restricted vertex sets

Definition

Let G be a finite simple graph and let c≥0 be real. A nonempty vertex set X⊆V(G) is c-sparse when

∣NG(x)∩X∣≤c∣X∣

for every x∈X, and it is c-dense when

∣(X∖{x})∖NG(x)∣≤c∣X∣

for every x∈X. Thus c-dense means that every vertex of X has at most c∣X∣ non-neighbours inside X other than itself.

A set is c-restricted when it is c-sparse or c-dense. The condition is internal to the induced subgraph G[X] (Subgraphs, induced subgraphs and spanning subgraphs), and the dense clause is the sparse clause read in the complement.

Remarks

This page keeps the source's maximum-degree normalisation. The edge-density normalisation appears separately in Sparsity of one vertex set to another, and weak sparsity of a pair and is compared to the present one by the lemmas immediately following this definition.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

Sparsity of one vertex set to another, and weak sparsity of a pair

Definition

Let G be a finite simple graph and let c≥0.

  • For disjoint nonempty sets X,Y⊆V(G), X is c-sparse to Y when every x∈X has at most c∣Y∣ neighbours in Y.
  • For nonempty sets X,Y⊆V(G), the ordered pair (X,Y) is weakly c-sparse when eG(X,Y)≤c∣X∣∣Y∣, with the ordered edge count of Edge counts and densities between nonempty vertex sets.
  • Such a pair (X,Y) is weakly c-dense when it is weakly c-sparse in the complement graph.

The directional notion need not be symmetric, while the weak notion is an edge-count and so is symmetric. For nonempty X, taking Y=X makes weak sparsity the self-density condition discussed in Edge counts and densities between nonempty vertex sets.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

For disjoint nonempty vertex sets, weak c-sparsity says exactly that the edge density is at most c

Statement

Let G be a finite simple graph, let c≥0, and let X,Y⊆V(G) be disjoint nonempty sets. Then (X,Y) is weakly c-sparse if and only if dG(X,Y)≤c.

Facts & Assumptions

Given: A finite simple graph G, a real c≥0, and disjoint nonempty sets X,Y⊆V(G).

[L1]

Weak c-sparsity means ∣EG(X,Y)∣≤c∣X∣∣Y∣ (Sparsity of one vertex set to another, and weak sparsity of a pair).

[L2]

The edge density is dG(X,Y)=eG(X,Y)/(∣X∣∣Y∣), where eG(X,Y) counts ordered pairs (x,y)∈X×Y that form an edge (Edge counts and densities between nonempty vertex sets).

[L3]

Because X and Y are disjoint, each edge between them contributes exactly one such ordered pair, so eG(X,Y)=∣EG(X,Y)∣ (Edges between disjoint vertex sets; complete, anticomplete, pure and mixed pairs).

Proof

technique · direct
1.1L1L3

By [L3], the inequality of [L1] is the same as eG(X,Y)≤c∣X∣∣Y∣.

2.1step 1.1L2algebra

Since X and Y are nonempty, dividing by ∣X∣∣Y∣ is legitimate, and [L2] turns the inequality of step 1.1 into dG(X,Y)≤c.

3.1step 2.1∎

Reversing the same algebra shows the converse implication, so the two conditions are equivalent.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

A set is c-sparse exactly when the maximum degree of the graph it induces is at most c times its size

Statement

Let G be a finite simple graph, let c≥0, and let X⊆V(G) be nonempty. Then X is c-sparse in G if and only if every vertex of the induced subgraph G[X] has degree at most c∣X∣. In particular, if X⊆W⊆V(G), then X is c-sparse in G if and only if it is c-sparse in G[W].

Facts & Assumptions

Given: A finite simple graph G, a real c≥0, and a nonempty set X⊆V(G).

[L1]

The set X is c-sparse when ∣NG(x)∩X∣≤c∣X∣ for every x∈X (c-sparse, c-dense and c-restricted vertex sets).

[L2]

In the induced subgraph G[X], the neighbours of a vertex x∈X are exactly the vertices of NG(x)∩X (Subgraphs, induced subgraphs and spanning subgraphs, Adjacency, incidence, open and closed neighbourhoods, vertex degree, minimum degree and maximum degree).

Proof

technique · direct
1.1L2

By [L2], for each x∈X the degree of x in G[X] is exactly ∣NG(x)∩X∣.

2.1step 1.1L1

Therefore the inequalities in [L1] are exactly the degree bounds in the induced subgraph.

3.1step 1.1∎

The same identity of neighbourhoods holds in any larger induced subgraph G[W] containing X, so the ambient graph is irrelevant once the vertex set X is fixed.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-26Open item page →

A c-sparse set has self-density at most c, and a c-dense set has self-density at least 1−c−1/∣X∣

Statement

Let G be a finite simple graph, let c≥0, and let X⊆V(G) be nonempty.

  1. If X is c-sparse, then dG(X,X)≤c.
  2. If X is c-dense, then dG(X,X)≥1−c−1/∣X∣.

Facts & Assumptions

Given: A finite simple graph G, a real c≥0, and a nonempty set X⊆V(G).

[L1]

A set is c-sparse exactly when every vertex of the induced graph G[X] has degree at most c∣X∣ (A set is c-sparse exactly when the maximum degree of the graph it induces is at most c times its size, c-sparse, c-dense and c-restricted vertex sets).

[L2]

The self-density is dG(X,X)=eG(X,X)/∣X∣2 (Edge counts and densities between nonempty vertex sets).

Proof

technique · direct
1.1L1L3

If X is c-sparse, then [L1] bounds every summand in [L3] by c∣X∣, so eG(X,X)≤c∣X∣2.

2.1step 1.1L2algebra

Dividing the inequality of step 1.1 by ∣X∣2 and using [L2] gives dG(X,X)≤c.

3.1L3L2givenalgebra∎

If X is c-dense, then every vertex of G[X] has at most c∣X∣ non-neighbours in X∖{x}, so it has at least ∣X∣−1−c∣X∣ neighbours in X. Summing as in [L3] gives eG(X,X)≥(1−c−1/∣X∣)∣X∣2, and [L2] turns this into dG(X,X)≥1−c−1/∣X∣.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

A set of self-density at most c has a subset of at least half its size that is 4c-sparse

Statement

Let G be a finite simple graph, let c≥0, and let X⊆V(G) be nonempty. If dG(X,X)≤c, then there is a subset X′⊆X with ∣X′∣≥∣X∣/2 such that X′ is 4c-sparse.

Facts & Assumptions

Given: A finite simple graph G, a real c≥0, and a nonempty set X⊆V(G) with dG(X,X)≤c.

[L2]

The self-density inequality dG(X,X)≤c is equivalent to eG(X,X)≤c∣X∣2 (Edge counts and densities between nonempty vertex sets).

[L3]

A set is 4c-sparse exactly when every vertex of the induced graph on it has degree at most 4c times its size (A set is c-sparse exactly when the maximum degree of the graph it induces is at most c times its size, c-sparse, c-dense and c-restricted vertex sets).

Proof

technique · direct
1.1L1L2algebra

By [L1] and [L2], the average internal degree of a vertex of X is at most c∣X∣.

2.1step 1.1algebrachoose

Let B:={x∈X:deg⁡G[X](x)>2c∣X∣}. If ∣B∣≥∣X∣/2, then the sum of the nonnegative internal degrees would be strictly larger than ∣B∣ 2c∣X∣≥c∣X∣2, contradicting step 1.1. Hence X′:=X∖B has ∣X′∣>∣X∣/2, and every x∈X′ has deg⁡G[X](x)≤2c∣X∣.

3.1step 2.1L3algebra∎

For x∈X′ one has deg⁡G[X′](x)≤deg⁡G[X](x)≤2c∣X∣≤4c∣X′∣, because ∣X′∣≥∣X∣/2. Thus [L3] makes X′ 4c-sparse.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

A set is c-sparse in G exactly when it is c-dense in G‾, so c-restrictedness is complement-invariant

Statement

Let G be a finite simple graph, let c≥0, and let X⊆V(G) be nonempty. Then X is c-sparse in G if and only if X is c-dense in G‾. Consequently X is c-restricted in G if and only if it is c-restricted in G‾.

Facts & Assumptions

Given: A finite simple graph G, a real c≥0, and a nonempty set X⊆V(G).

[L1]
[L2]

The definitions of c-sparse, c-dense, and c-restricted are those of c-sparse, c-dense and c-restricted vertex sets.

Proof

technique · direct
1.1L1

For x∈X, the set NG‾(x)∩X is exactly (X∖{x})∖NG(x) by [L1].

2.1step 1.1L2

Therefore the inequality defining c-sparsity in G‾ is exactly the inequality defining c-density in G, and vice versa, by [L2].

3.1step 2.1L2∎

Since c-restricted means the disjunction of the sparse and dense conditions, step 2.1 shows that restrictedness is unchanged by complementation.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-26Open item page →

A subset occupying at least a λ fraction of a c-sparse set is (c/λ)-sparse

Statement

Let G be a finite simple graph, let c≥0, let λ>0, and let X′⊆X⊆V(G) be nonempty. If X is c-sparse and ∣X′∣≥λ∣X∣, then X′ is (c/λ)-sparse.

Facts & Assumptions

Given: A finite simple graph G, reals c≥0 and λ>0, and nonempty sets X′⊆X⊆V(G) such that X is c-sparse and ∣X′∣≥λ∣X∣.

Proof

technique · direct
1.1L1

For every x∈X′, the degree of x in G[X′] is at most its degree in G[X].

2.1step 1.1L1algebra

Since X is c-sparse, [L1] gives deg⁡G[X](x)≤c∣X∣; and because ∣X′∣≥λ∣X∣, one has ∣X∣≤∣X′∣/λ. Hence deg⁡G[X′](x)≤(c/λ)∣X′∣ for every x∈X′.

3.1step 2.1L1∎

Applying [L1] again shows that X′ is (c/λ)-sparse.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

Sparsity is preserved when the parameter grows, and every nonempty set of at most two vertices is 0-restricted

Statement

Let G be a finite simple graph and let 0≤c≤c′.

  1. If a nonempty set X⊆V(G) is c-sparse, then it is c′-sparse.
  2. If X is nonempty and ∣X∣≤2, then X is 0-restricted.

Facts & Assumptions

Given: A finite simple graph G, reals 0≤c≤c′, and a nonempty set X⊆V(G).

[L1]

A nonempty set Y is c-sparse when every vertex of Y has at most c∣Y∣ neighbours in Y; it is c-dense when every vertex has at most c∣Y∣ non-neighbours in Y other than itself; and it is c-restricted when it is c-sparse or c-dense (c-sparse, c-dense and c-restricted vertex sets).

Proof

technique · direct
1.1L1algebra

If X is c-sparse, then every vertex of X has at most c∣X∣≤c′∣X∣ neighbours in X, so [L1] makes X c′-sparse.

1.2L1

If ∣X∣=1, then its only vertex has no neighbour and no non-neighbour inside X∖{x}, so [L1] makes X both 0-sparse and 0-dense.

2.1L1∎

If ∣X∣=2, then either the two vertices are adjacent or they are not. In the first case X is 0-dense, and in the second it is 0-sparse. So [L1] makes every two-element set 0-restricted.

CorollaryStatement: AI-generatedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

A c-sparse set X satisfies α(G[X])≥∣X∣/(c∣X∣+1), and a c-dense set satisfies ω(G[X])≥∣X∣/(c∣X∣+1)

Statement

Let G be a finite simple graph, let c≥0, and let X⊆V(G) be nonempty.

  1. If X is c-sparse, then α(G[X])≥∣X∣/(c∣X∣+1).
  2. If X is c-dense, then ω(G[X])≥∣X∣/(c∣X∣+1).

Facts & Assumptions

Given: A finite simple graph G, a real c≥0, and a nonempty set X⊆V(G).

[L4]

Proof

technique · direct
1.1L1L2

In the sparse case, [L1] gives Δ(G[X])≤c∣X∣, so [L2] gives χ(G[X])≤c∣X∣+1.

1.2L4

The two published definitions of α and ω agree by [L4], so the complement statement can be read with the same symbols.

2.1step 1.1L3algebra

Applying [L3] to G[X] yields ∣X∣≤χ(G[X])α(G[X]), hence α(G[X])≥∣X∣/(c∣X∣+1).

3.1step 2.1step 1.2L5∎

If X is c-dense, then [L5] makes X c-sparse in G‾, so step 2.1 applied there gives a stable set of size at least ∣X∣/(c∣X∣+1). Reading that set back in G via [L5] gives a clique of the same size.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

An ϵ-regular pair is ϵ′-regular for every ϵ′≥ϵ with ϵ′>0

Statement

Let 0<ϵ≤ϵ′. If (X,Y) is an ϵ-regular pair, then it is an ϵ′-regular pair.

Facts & Assumptions

Given: Reals 0<ϵ≤ϵ′, disjoint nonempty vertex sets X,Y, and an ϵ-regular pair (X,Y).

[L1]

An ϵ-regular pair requires the density deviation bound for all subsets X′⊆X, Y′⊆Y with ∣X′∣≥ϵ∣X∣ and ∣Y′∣≥ϵ∣Y∣ (ϵ-regular pairs and self-regular vertex sets, Edge counts and densities between nonempty vertex sets).

Proof

technique · direct
1.1L1algebra

If ∣X′∣≥ϵ′∣X∣ and ∣Y′∣≥ϵ′∣Y∣, then also ∣X′∣≥ϵ∣X∣ and ∣Y′∣≥ϵ∣Y∣ because ϵ′≥ϵ.

2.1step 1.1L1algebra∎

The ϵ-regularity of (X,Y) therefore gives ∣d(X′,Y′)−d(X,Y)∣≤ϵ≤ϵ′. This is exactly the definition of ϵ′-regularity.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

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

Statement

Let 0<γ<1, let W⊆V(G) be nonempty, and suppose (W,W) is a γ-regular pair of density d. Then there is a subset W′⊆W with ∣W′∣>(1−γ)∣W∣ such that W′ is ((d+γ)/(1−γ))-sparse.

Facts & Assumptions

Given: A finite simple graph G, a real 0<γ<1, a nonempty set W⊆V(G), and a density d=dG(W,W) such that (W,W) is γ-regular.

[L1]

If (X,Y) is a γ-regular pair of density d and a fixed set Y′⊆Y has ∣Y′∣≥γ∣Y∣, then fewer than γ∣X∣ vertices of X have more than (d+γ)∣Y′∣ neighbours in Y′ (In a regular pair, fewer than ϵ∣X∣ vertices have too small a degree into a large subset, and fewer than ϵ∣X∣ have too large a degree, ϵ-regular pairs and self-regular vertex sets).

[L2]

A set is c-sparse exactly when every vertex of the induced graph on it has degree at most c times its size (A set is c-sparse exactly when the maximum degree of the graph it induces is at most c times its size, c-sparse, c-dense and c-restricted vertex sets).

Proof

technique · direct
1.1L1

Apply [L1] to the pair (W,W) with Y′=W. Since ∣W∣≥γ∣W∣, fewer than γ∣W∣ vertices of W have more than (d+γ)∣W∣ neighbours in W.

2.1step 1.1choose

Let W′ be the remaining vertices. Then ∣W′∣>(1−γ)∣W∣.

3.1step 2.1L2algebra∎

For every x∈W′, one has deg⁡G[W′](x)≤deg⁡G[W](x)≤(d+γ)∣W∣<((d+γ)/(1−γ))∣W′∣. Therefore [L2] makes W′ ((d+γ)/(1−γ))-sparse.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

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

Statement

Let 0<γ<1, let W⊆V(G) be nonempty, and suppose (W,W) is a γ-regular pair of density d. Then there is a subset W′⊆W with ∣W′∣>(1−γ)∣W∣ such that W′ is ((1−d+2γ)/(1−γ))-dense.

Facts & Assumptions

Given: A finite simple graph G, a real 0<γ<1, a nonempty set W⊆V(G), and a density d=dG(W,W) such that (W,W) is γ-regular.

[L1]

In a γ-regular pair (X,Y), all but fewer than γ∣X∣ vertices of X have at least (d(X,Y)−γ)∣Y′∣ neighbours in any subset Y′⊆Y of size at least γ∣Y∣ (In a regular pair, fewer than ϵ∣X∣ vertices have too small a degree into a large subset, and fewer than ϵ∣X∣ have too large a degree, ϵ-regular pairs and self-regular vertex sets).

[L2]

A set is c-dense exactly when every vertex has at most c∣X∣ non-neighbours inside it other than itself (c-sparse, c-dense and c-restricted vertex sets).

Proof

technique · direct
1.1L1

Apply [L1] to the pair (W,W) with Y′=W. Fewer than γ∣W∣ vertices of W then have fewer than (d−γ)∣W∣ neighbours in W.

2.1step 1.1choose

Let W′ be the remaining vertices. Then ∣W′∣>(1−γ)∣W∣.

3.1step 2.1algebra

For x∈W′, at most γ∣W∣ of its neighbours lie outside W′, so x has at least (d−2γ)∣W∣ neighbours in W′.

4.1step 3.1L2algebra∎

Hence x has at most ∣W′∣−1−(d−2γ)∣W∣<((1−d+2γ)/(1−γ))∣W′∣ non-neighbours inside W′. By [L2], the set W′ is ((1−d+2γ)/(1−γ))-dense.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-26Open item page →

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

Statement

Fix a graph H with h=∣V(H)∣, a real 0<η<1/2, and constants γ(H,η),c(H,η)>0 and N(H,η) from the induced counting lemma. If 0<γ≤γ(H,η) and W⊆V(G) has ∣W∣≥N(H,η) with (W,W) γ-regular and η≤dG(W,W)≤1−η, then

ind⁡H(G)≥c(H,η)∣W∣h.

Facts & Assumptions

Given: A graph H with h vertices, a real 0<η<1/2, a graph G, a set W⊆V(G) with ∣W∣≥N(H,η), and a real 0<γ≤γ(H,η) such that (W,W) is γ-regular and η≤dG(W,W)≤1−η.

[L1]

If 0<η<1/2, the induced counting lemma supplies γ(H,η),c(H,η)>0 and N(H,η); it applies to h sets Wi of size at least N(H,η), repetitions allowed, when every relevant pair is γ(H,η)-regular and the edge- and nonedge-density bounds hold, and then yields at least c(H,η)∏i∣Wi∣ induced embeddings of H (Induced counting lemma: regular edge and nonedge pairs force many induced copies).

[L2]

If 0<γ≤γ(H,η) and (W,W) is γ-regular, then it is also γ(H,η)-regular: any A,B⊆W with ∣A∣≥γ(H,η)∣W∣ and ∣B∣≥γ(H,η)∣W∣ also satisfy the γ-threshold, so the defining density deviation is at most γ≤γ(H,η) (ϵ-regular pairs and self-regular vertex sets).

[L3]

Proof

technique · direct
1.1L1

Apply [L1] with W1=⋯=Wh=W. The repeated-set case is permitted by the statement of the counting lemma.

2.1step 1.1L2

By [L2], every pair (Wi,Wj) in this application is γ(H,η)-regular.

2.2step 1.1given

If ij is an edge of H, then the required density lower bound is the left inequality η≤dG(W,W). If ij is a non-edge, the required upper bound is the right inequality dG(W,W)≤1−η. So all density hypotheses of [L1] are satisfied.

3.1step 2.1step 2.2L1L3∎

Therefore [L1] produces at least c(H,η)∣W∣h induced embeddings of H in G, and [L3] identifies this number with ind⁡H(G).

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

If G has fewer than (δn)h induced copies of H and ∣W∣≥λn, then G[W] has fewer than ((δ/λ)∣W∣)h

Statement

Let H have h vertices. If G has n vertices, ind⁡H(G)<(δn)h, and W⊆V(G) satisfies ∣W∣≥λn>0, then

ind⁡H(G[W])<((δ/λ)∣W∣)h.

Facts & Assumptions

Given: A graph H with h vertices, a graph G on n vertices, reals δ>0 and λ>0, and a subset W⊆V(G) with ∣W∣≥λn and ind⁡H(G)<(δn)h.

[L1]

An induced embedding of H into G[W] is, by definition, an induced embedding of H into G whose image lies in W (Induced embeddings and induced copies of a graph, Subgraphs, induced subgraphs and spanning subgraphs).

[L2]

The induced-copy number counts induced embeddings (The induced-embedding count ind⁡H(G)).

Proof

technique · direct
1.1L1

By [L1], every induced embedding counted by ind⁡H(G[W]) is also counted by ind⁡H(G).

2.1step 1.1L2

Therefore ind⁡H(G[W])≤ind⁡H(G)<(δn)h by [L2].

3.1step 2.1algebra∎

Since ∣W∣≥λn, one has n≤∣W∣/λ. Substituting this into step 2.1 yields ind⁡H(G[W])<((δ/λ)∣W∣)h.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-26Open item page →

Nikiforov: for every H and every ϵ∈(0,12) 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)∣

Statement

Fix a graph H with h=∣V(H)∣ and a real ϵ∈(0,12). Then there exists δ>0 such that every nonempty finite simple graph G with

ind⁡H(G)<(δ∣V(G)∣)h

has an ϵ-restricted vertex set of size at least δ∣V(G)∣.

Facts & Assumptions

Given: A graph H with h vertices and a real ϵ∈(0,12).

[L1]

For each 0<γ<1, the self-regular-subset theorem gives a constant δ1(γ)>0 such that every nonempty graph on n vertices has a subset W with ∣W∣≥δ1(γ)n and (W,W) γ-regular (Every finite graph has a linearly large ϵ-self-regular vertex subset, ϵ-regular pairs and self-regular vertex sets).

[L2]

The induced counting constants include N=N(H,η), and if 0<γ≤γ(H,η), ∣W∣≥N, (W,W) is γ-regular, and its self-density lies between η and 1−η, then ind⁡H(G)≥c(H,η)∣W∣h (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).

[L4]

Every nonempty set of at most two vertices is 0-restricted, hence ϵ-restricted (Sparsity is preserved when the parameter grows, and every nonempty set of at most two vertices is 0-restricted).

Proof

technique · direct
1.1L2L3algebra

Set η:=ϵ/4 and choose γ>0 so small that γ≤ϵ/8 and γ≤γ(H,η) from [L2]. Then (η+γ)/(1−γ)≤ϵ, and the dense trimming parameter from [L3] is also at most ϵ, because η=ϵ/4, γ≤ϵ/8, and ϵ<1/2.

2.1step 1.1L1L2choose

If h=0, the induced-copy hypothesis is never satisfied: both sides of its displayed inequality are 1. Thus suppose h≥1. Let δ1:=δ1(γ) be the constant of [L1], let c:=c(H,η) and N:=N(H,η) be the constants of [L2], put N′:=max⁡{N,1}, and set δ:=min⁡{δ1c1/h, (1−γ)δ1, δ1/N′, 1}. Then δ>0 and depends only on H and ϵ.

3.1step 2.1L1L4choosealgebra

Now let G be a nonempty graph on n vertices with ind⁡H(G)<(δn)h. If n<N′/δ1, then any singleton X is 0-restricted by [L4] and satisfies ∣X∣=1>δn, because δ≤δ1/N′. Hence suppose n≥N′/δ1. By [L1] choose W⊆V(G) with ∣W∣≥δ1n≥N′≥N such that (W,W) is γ-regular.

4.1step 1.1step 2.1step 3.1L2algebra

If η≤dG(W,W)≤1−η, then [L2] gives ind⁡H(G)≥c∣W∣h≥cδ1hnh≥(δn)h, contrary to the hypothesis on G. Therefore either dG(W,W)<η or dG(W,W)>1−η.

5.1step 1.1step 2.1step 3.1step 4.1L3

In the first case, the low-density trimming lemma in [L3] yields a subset W′⊆W with ∣W′∣>(1−γ)∣W∣≥δn that is ϵ-sparse by step 1.1. In the second case, the high-density trimming lemma in [L3] yields a subset W′⊆W with the same size bound that is ϵ-dense. In either case W′ is ϵ-restricted.

6.1step 3.1step 4.1step 5.1∎

Step 3.1 handles small n, and steps 4.1 and 5.1 handle all remaining cases, so every graph satisfying the induced-copy bound has an ϵ-restricted set of size at least δ∣V(G)∣.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

Rödl: for every H and every ϵ∈(0,12) there is δ>0 such that every nonempty H-free graph has an ϵ-restricted vertex set of size at least δ∣V(G)∣

Statement

For every graph H and every ϵ∈(0,12) there exists δ>0 such that every nonempty H-free finite simple graph G has an ϵ-restricted vertex set of size at least δ∣V(G)∣.

Facts & Assumptions

Given: A graph H and a real ϵ∈(0,12).

[L2]

For every graph H and ϵ∈(0,1/2) there is δ>0 such that every nonempty graph G satisfying ind⁡H(G)<(δ∣V(G)∣)∣V(H)∣ has an ϵ-restricted set of size at least δ∣V(G)∣ (Nikiforov: for every H and every ϵ∈(0,12) 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)∣).

Proof

technique · direct
1.1L2choose

Let δ be the constant supplied by [L2] for the given H and ϵ.

1.2L1algebra

If G is nonempty and H-free, then [L1] gives ind⁡H(G)=0<(δ∣V(G)∣)∣V(H)∣.

2.1step 1.1step 1.2L2∎

Applying [L2] to step 1.2 yields the desired ϵ-restricted set.

CorollaryStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

Rödl's theorem for a nonempty family of forbidden induced subgraphs

Statement

Let F be a nonempty family of graphs and let ϵ∈(0,12). Then there exists δ>0 such that every F-free nonempty finite simple graph G has an ϵ-restricted vertex set of size at least δ∣V(G)∣.

Facts & Assumptions

Given: A nonempty family F of graphs and a real ϵ∈(0,12).

[L1]

A graph that is F-free is H-free for every H∈F (H-free and F-free graphs under the induced-subgraph convention).

[L2]

For every graph H and ϵ∈(0,1/2) there is δ>0 such that every nonempty H-free graph G has an ϵ-restricted set of size at least δ∣V(G)∣ (Rödl: for every H and every ϵ∈(0,12) there is δ>0 such that every nonempty H-free graph has an ϵ-restricted vertex set of size at least δ∣V(G)∣).

Proof

technique · direct
1.1givenchoose

Choose any graph H∈F.

2.1step 1.1L2choose

By [L2], there is a constant δ>0 such that every nonempty H-free graph has an ϵ-restricted set of size at least δ∣V(G)∣.

3.1step 1.1step 2.1L1∎

If G is nonempty and F-free, then [L1] makes it H-free, so step 2.1 applies to G.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

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

Statement

For every graph H and every ϵ∈(0,12) there exists δ>0 such that every nonempty H-free finite simple graph G contains a set X⊆V(G) with ∣X∣≥δ∣V(G)∣ and either dG(X,X)≤ϵ or dG(X,X)≥1−ϵ.

Facts & Assumptions

Given: A graph H and a real ϵ∈(0,12).

[L1]

Rödl's theorem supplies a constant δ0>0 such that every nonempty H-free graph G has an (ϵ/2)-restricted set of size at least δ0∣V(G)∣ (Rödl: for every H and every ϵ∈(0,12) there is δ>0 such that every nonempty H-free graph has an ϵ-restricted vertex set of size at least δ∣V(G)∣).

[L2]

A (ϵ/2)-sparse set has self-density at most ϵ/2, while a (ϵ/2)-dense set has self-density at least 1−ϵ/2−1/∣X∣ (A c-sparse set has self-density at most c, and a c-dense set has self-density at least 1−c−1/∣X∣).

Proof

technique · direct
1.1L1choose

Let δ0 be the constant from [L1] for the parameter ϵ/2, and set δ:=min⁡{δ0,ϵδ0/2}.

2.1step 1.1L1

If G is nonempty and H-free, then [L1] gives a set X with ∣X∣≥δ0∣V(G)∣ that is (ϵ/2)-restricted.

3.1step 2.1L2

If X is (ϵ/2)-sparse, then [L2] gives dG(X,X)≤ϵ/2≤ϵ.

3.2step 1.1step 2.1L2algebracases

If X is (ϵ/2)-dense and ∣X∣≥2/ϵ, then [L2] gives dG(X,X)≥1−ϵ. If instead ∣X∣<2/ϵ, then ∣V(G)∣<2/(ϵδ0) by step 2.1, and the single-vertex set {v} has self-density 0≤ϵ and size 1>δ∣V(G)∣ by the choice of δ in step 1.1.

4.1step 3.1step 3.2algebra∎

In every case there is a set of size at least δ∣V(G)∣ whose self-density is at most ϵ or at least 1−ϵ.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

The edge-density form of Rödl's theorem implies the maximum-degree form, with ϵ and δ each shrunk by a constant factor

Statement

Assume the edge-density form of Rödl's theorem holds at parameter ϵ/4 with constant δ0. Then the maximum-degree form holds at parameter ϵ with constant δ0/2.

Facts & Assumptions

Given: A graph H, a real ϵ∈(0,12), and the edge-density form of Rödl's theorem at parameter ϵ/4 with constant δ0.

[L1]

The edge-density form supplies, in every nonempty H-free graph G, a set X of size at least δ0∣V(G)∣ with dG(X,X)≤ϵ/4 or dG(X,X)≥1−ϵ/4 (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).

[L2]

If dG(X,X)≤c, then some subset X′⊆X with ∣X′∣≥∣X∣/2 is 4c-sparse (A set of self-density at most c has a subset of at least half its size that is 4c-sparse).

Proof

technique · direct
1.1L1choose

Let G be a nonempty H-free graph. By [L1], choose X⊆V(G) with ∣X∣≥δ0∣V(G)∣ and either dG(X,X)≤ϵ/4 or dG(X,X)≥1−ϵ/4.

2.1step 1.1L2

In the sparse branch, [L2] applied with c=ϵ/4 gives a subset X′⊆X with ∣X′∣≥∣X∣/2 that is ϵ-sparse, hence ϵ-restricted.

2.2step 1.1L2L3algebra

In the dense branch, the diagonal convention gives dG‾(X,X)=1−1/∣X∣−dG(X,X)≤ϵ/4; applying [L2] to G‾ yields a subset X′⊆X with ∣X′∣≥∣X∣/2 that is ϵ-sparse in G‾, and [L3] turns this into ϵ-dense, hence ϵ-restricted, in G.

3.1step 2.1step 2.2∎

In either branch ∣X′∣≥(δ0/2)∣V(G)∣, so the maximum-degree form holds with constant δ0/2.

CorollaryStatement: AI-generatedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

A linearly large induced subgraph of a graph with few induced copies again has a linearly large restricted set

Statement

Fix a graph H, a real ϵ∈(0,12), and a fraction λ>0. Then there exists δ>0 such that whenever G is a nonempty graph on n vertices with ind⁡H(G)<(δn)∣V(H)∣ and W⊆V(G) satisfies ∣W∣≥λn, the induced subgraph G[W] contains an ϵ-restricted set of size at least δ∣W∣.

Facts & Assumptions

Given: A graph H, a real ϵ∈(0,12), and a real λ>0.

[L1]

If G has n vertices, h=∣V(H)∣, ind⁡H(G)<(δn)h, and ∣W∣≥λn>0, then ind⁡H(G[W])<((δ/λ)∣W∣)h (If G has fewer than (δn)h induced copies of H and ∣W∣≥λn, then G[W] has fewer than ((δ/λ)∣W∣)h).

[L2]

There is δ0>0 such that every nonempty graph J with ind⁡H(J)<(δ0∣V(J)∣)∣V(H)∣ has an ϵ-restricted set of size at least δ0∣V(J)∣ (Nikiforov: for every H and every ϵ∈(0,12) 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)∣).

Proof

technique · direct
1.1L2choosealgebra

Let δ0 be the constant of [L2] for H and ϵ, and set δ:=min⁡{δ0,λδ0}. Then δ>0, δ≤δ0, and δ/λ≤δ0.

2.1step 1.1L1algebra

If ind⁡H(G)<(δn)∣V(H)∣ and ∣W∣≥λn, then [L1] gives ind⁡H(G[W])<((δ/λ)∣W∣)∣V(H)∣≤(δ0∣W∣)∣V(H)∣.

3.1step 1.1step 2.1L2algebra∎

Applying [L2] inside G[W] yields an ϵ-restricted set of size at least δ0∣W∣. Since δ0∣W∣≥δ∣W∣ by step 1.1, this is the required set.

CorollaryStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

For every λ>0 a bounded number of disjoint ϵ-restricted sets covers all but λ∣V(G)∣ vertices of an H-free graph

Statement

Fix a graph H, a real ϵ∈(0,12), and λ>0. Then there is an integer t=t(H,ϵ,λ) such that every nonempty H-free finite simple graph G contains pairwise disjoint ϵ-restricted sets X1,…,Xs for some s≤t, whose union misses fewer than λ∣V(G)∣ vertices.

Facts & Assumptions

Given: A graph H, reals ϵ∈(0,12) and λ>0.

[L2]

Rödl's theorem provides a constant δ>0 such that every nonempty H-free graph contains an ϵ-restricted set of size at least δ times its order (Rödl: for every H and every ϵ∈(0,12) there is δ>0 such that every nonempty H-free graph has an ϵ-restricted vertex set of size at least δ∣V(G)∣).

[L3]

Sparsity is internal to induced subgraphs, so a set that is ϵ-restricted in an induced subgraph is also ϵ-restricted in the ambient graph (A set is c-sparse exactly when the maximum degree of the graph it induces is at most c times its size, c-sparse, c-dense and c-restricted vertex sets).

Proof

technique · direct
1.1L2choose

Let δ be the constant from [L2]. Choose t minimal with (1−δ)t<λ.

1.2L1L2choose

Starting from G, repeatedly apply [L2] to the induced subgraph on the current remainder while that remainder has at least λ∣V(G)∣ vertices. By [L1] each remainder is still H-free, so this produces pairwise disjoint ϵ-restricted sets X1,X2,….

2.1step 1.1step 1.2algebra

After each extraction, at least a δ fraction of the current remainder is removed. Hence after k steps the remainder has size at most (1−δ)k∣V(G)∣. In particular, after t steps it has size strictly below λ∣V(G)∣ by the choice of t.

3.1step 1.2step 2.1L3∎

The process therefore stops after some number s≤t of extractions, and [L3] makes every extracted set ϵ-restricted in the original graph.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

Every H-free graph partitions into boundedly many vertex sets of self-density at most ϵ or at least 1−ϵ

Statement

Fix a graph H and a real ϵ∈(0,12). Then there exists an integer B=B(H,ϵ) such that every H-free finite simple graph G admits a partition

V(G)=X1⊔⋯⊔Xm,m≤B,

in which every part satisfies dG(Xi,Xi)≤ϵ or dG(Xi,Xi)≥1−ϵ.

Facts & Assumptions

Given: A graph H and a real ϵ∈(0,12).

[L1]

The edge-density form of Rödl's theorem supplies a constant δ0>0 such that every nonempty H-free finite simple graph J contains a set X⊆V(J) with ∣X∣≥δ0∣V(J)∣ and either dJ(X,X)≤ϵ/2 or dJ(X,X)≥1−ϵ/2 (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).

[F1]

If W⊆V(G) then G[W] has the same adjacencies on every subset X⊆W as G does, so dG[W](X,X)=dG(X,X) (Subgraphs, induced subgraphs and spanning subgraphs, Edge counts and densities between nonempty vertex sets).

Proof

technique · direct
1.1L1algebrachoose

Let δ0>0 be the constant from [L1], set ρ:=min⁡{δ0,12}, and note that 0<ρ≤12. Then every nonempty H-free graph J contains a set X⊆V(J) with ∣X∣≥ρ∣V(J)∣ and either dJ(X,X)≤ϵ/2 or dJ(X,X)≥1−ϵ/2.

2.1step 1.1L3choose

Since 0<1−ρ<1, [L3] applied to r=1−ρ yields a natural number t≥1 with (1−ρ)t<ρϵ/16.

2.2step 1.1L2F1choose

Let G be an H-free finite simple graph. If V(G)=∅, the empty partition works, so assume n:=∣V(G)∣>0. Put R0:=V(G). For each i=1,…,t, if Ri−1=∅ stop; otherwise the induced subgraph G[Ri−1] is H-free by [L2], so step 1.1 and [F1] give a nonempty set Xi⊆Ri−1 with ∣Xi∣≥ρ∣Ri−1∣ and either dG(Xi,Xi)≤ϵ/2 or dG(Xi,Xi)≥1−ϵ/2. Define Ri:=Ri−1∖Xi.

3.1step 2.2algebra

If the process stops at some stage i≤t because Ri−1=∅, then the nonempty extracted sets X1,…,Xi−1 partition V(G) and each already has self-density at most ϵ/2 or at least 1−ϵ/2, hence in particular at most ϵ or at least 1−ϵ.

3.2step 2.1step 2.2algebra

Assume now that the process does not stop before stage t. Then X1,…,Xt are pairwise disjoint nonempty sets, and an induction on i using step 2.2 gives ∣Ri∣≤(1−ρ)∣Ri−1∣ for every i≤t. Hence ∣Rt∣≤(1−ρ)tn<(ρϵ/16)n by step 2.1, while ∣X1∣≥ρn by step 2.2.

4.1step 3.2algebra

Put Y1:=X1∪Rt and Yi:=Xi for 2≤i≤t. Then Y1,…,Yt partition V(G). Writing x:=∣X1∣, r:=∣Rt∣, y:=∣Y1∣=x+r and α:=r/x, step 3.2 gives α<ϵ/16.

5.1step 4.1algebra

If dG(X1,X1)≤ϵ/2, then eG(Y1,Y1)≤eG(X1,X1)+2ry because the new ordered edges are those incident with at least one vertex of Rt. Therefore dG(Y1,Y1)≤(ϵ/2)(x/y)2+2r/y≤ϵ/2+2α<ϵ.

5.2step 4.1algebra

If instead dG(X1,X1)≥1−ϵ/2, then dG(Y1,Y1)≥dG(X1,X1)(x/y)2≥(1−ϵ/2)/(1+α)2. Since α<ϵ/16 and ϵ<1/2, one has (1+α)2<(1+ϵ/16)2≤1+ϵ/2, so dG(Y1,Y1)>(1−ϵ/2)/(1+ϵ/2)>1−ϵ.

6.1step 2.2step 4.1step 5.1step 5.2

In the situation of steps 3.2 and 4.1, step 5.1 or 5.2 handles Y1, while each Yi=Xi for i≥2 already has self-density at most ϵ/2 or at least 1−ϵ/2. Therefore every part of the partition has self-density at most ϵ or at least 1−ϵ.

7.1step 2.1step 3.1step 6.1∎

Step 3.1 settles the case where the extraction stops early, and step 6.1 settles the case where it reaches stage t. So B:=t works for every H and ϵ.

RemarkRemark: AI-adaptedProof: Not applicablejudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

Bounded degree against bounded density: the two statements of Rödl's theorem, and which one is stronger

The maximum-degree form is stronger than the density form. If every vertex of X has at most ϵ∣X∣ neighbours, then the self-density is at most ϵ by A c-sparse set has self-density at most c, and a c-dense set has self-density at least 1−c−1/∣X∣. The converse fails: small average degree does not control exceptional vertices, and a large star is the basic witness.

What this page proves is the stronger form Rödl: for every H and every ϵ∈(0,12) there is δ>0 such that every nonempty H-free graph has an ϵ-restricted vertex set of size at least δ∣V(G)∣, then derives the density form 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, and finally shows by The edge-density form of Rödl's theorem implies the maximum-degree form, with ϵ and δ each shrunk by a constant factor that the weaker statement implies the stronger one after shrinking the constants by a fixed factor.

RemarkRemark: AI-adaptedProof: Not applicablejudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

Why the self-density bound for a dense set carries a 1/∣X∣ slack

The self-density dG(X,X) counts ordered adjacent pairs of distinct vertices and divides by ∣X∣2, so the diagonal pairs never contribute. A clique on s vertices therefore has self-density s(s−1)/s2=1−1/s, not 1. That is why the dense conclusion in A c-sparse set has self-density at most c, and a c-dense set has self-density at least 1−c−1/∣X∣ carries the reciprocal-size term. The density form of Rödl's theorem absorbs this term by changing its constants and states the cleaner threshold 1−ϵ.

RemarkRemark: AI-adaptedProof: Not applicablejudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26Open item page →

What this proof gives for δ, and why the regularity route is expensive

The proof of Rödl: for every H and every ϵ∈(0,12) there is δ>0 such that every nonempty H-free graph has an ϵ-restricted vertex set of size at least δ∣V(G)∣ runs through the self-regular subset theorem and hence through Szemerédi regularity. Its constant δ is therefore extremely small: it is assembled from the regularity output, the counting-lemma constant, and the trimming loss in Nikiforov: for every H and every ϵ∈(0,12) 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)∣. Nothing on this page claims that this bound is close to optimal.

The significance of the theorem is structural, not quantitative: every H-free graph contains a linearly large region that is sparse or dense in a strong sense. Later work improves the constants by avoiding the full regularity machinery; this page does not.

5 · Examples, counterexamples and false statements

None yet.

Sources