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✓ 3 results · all verified · 1 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 2 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

Iterative Restriction and Comb-Extraction Lemmas

1 · Prerequisites

2 · Summary

This page isolates the reusable Section 2 lemmas that sit between the earlier P5 blockade machinery and the later six-vertex structure pages. It keeps the graph-class-free parts of the iteration visible: the nearly covered sparse-pair extraction, the leaf-reducible reduction, the multiplicative sparsity-drop lemma, and the comb-producing alternative.

The proofs are written in the normalization the later route actually uses. In particular, the generalized nearly covered sparse-pair lemma removes the unused P5‾-free hypothesis from Claim 5.2.1, and the leaf-reducible lemma keeps only the graph-level consequence needed for later pages.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-01Open item page →

Leaf-reducible finite graph families

Definition

Let F be a finite family of finite graphs. We say that F is leaf-reducible if there exist a graph H∈F and a leaf v∈V(H) such that the modified family

F′:={H∖{v}}∪(F∖{H})

has the Erdős-Hajnal property in the family sense (The Erdős–Hajnal property and an Erdős–Hajnal constant for a hereditary graph class, H-free and F-free graphs under the induced-subgraph convention).

Thus a leaf-reducible family is one for which deleting one leaf from one member produces a new forbidden family already known to have the Erdős-Hajnal property.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-01Open item page →

A sparse graph without a large sparse pair has a large nearly covered sparse pair

Statement

Let x,y>0 with x≤y≤2−8, and let G be a y3-sparse graph with ∣V(G)∣≥y−4. Suppose that G is not 2y4-sparse, and that there do not exist disjoint sets X,Y⊆V(G) such that

∣X∣≥y4∣V(G)∣,∣Y∣≥(1−4y)∣V(G)∣,

and Y is x-sparse to X. Then there exist a vertex v∈V(G) and disjoint sets A,B⊆V(G)∖{v} such that:

  1. A⊆V(G)∖NG[v] and B⊆NG(v);
  2. ∣A∣≥(1−3y)∣V(G)∣ and ∣B∣≥y4∣V(G)∣;
  3. A is y2-sparse to B; and
  4. every vertex of B has at least x2∣A∣ neighbours in A.

Facts & Assumptions

Given: Parameters x,y and a graph G satisfying the displayed hypotheses.

[L2]

The assertion that Y is x-sparse to X means that every vertex of Y has at most x∣X∣ neighbours in X (Sparsity of one vertex set to another, and weak sparsity of a pair).

Proof

technique · direct
1.1givenchooseL1

Because G is not 2y4-sparse, some vertex v has degree at least 2y4∣V(G)∣. Let N:=NG(v). Then ∣N∣≥2y4∣V(G)∣.

2.1step 1.1L1choosealgebra

Let A′ be the set of vertices in V(G)∖(N∪{v}) with at least 12y2∣N∣ neighbours in N. Averaging over the edges between A′ and N, some vertex of N has at least 12y2∣A′∣ neighbours in A′. Since every vertex has degree at most y3∣V(G)∣ by [L1], we obtain 12y2∣A′∣≤y3∣V(G)∣, so ∣A′∣≤2y∣V(G)∣.

3.1step 2.1L1algebra

Define A:=V(G)∖(N∪A′∪{v}). Since G is y3-sparse, [L1] gives ∣N∣≤y3∣V(G)∣, and because ∣V(G)∣≥y−4 we have 1≤y∣V(G)∣. Therefore ∣A∣≥∣V(G)∣−(y3∣V(G)∣+2y∣V(G)∣+1)≥(1−3y)∣V(G)∣. Also, every vertex of A has fewer than 12y2∣N∣ neighbours in N by definition of A′.

4.1step 3.1L2algebra

Let N′⊆N be the set of vertices with at most x2∣A∣ neighbours in A, and put B:=N∖N′. The number of edges between A and N′ is at most x2∣A∣∣N′∣, so at most x∣A∣ vertices of A have more than x∣N′∣ neighbours in N′. Hence at least ∣A∣−x∣A∣≥(1−3y−x)∣V(G)∣≥(1−4y)∣V(G)∣ vertices of A have at most x∣N′∣ neighbours in N′.

5.1step 4.1L2assume-contradischarge-contradiction

If ∣N′∣≥y4∣V(G)∣, then step 4.1 gives a set Y⊆A with ∣Y∣≥(1−4y)∣V(G)∣ such that every vertex of Y has at most x∣N′∣ neighbours in N′. By [L2], the pair (X,Y):=(N′,Y) is then a forbidden large sparse pair, contradicting the hypothesis. Therefore ∣N′∣<y4∣V(G)∣.

6.1step 1.1step 3.1step 5.1L2algebra

Since ∣N∣≥2y4∣V(G)∣ by step 1.1 and ∣N′∣<y4∣V(G)∣ by step 5.1, we have ∣B∣=∣N∣−∣N′∣≥y4∣V(G)∣. By definition of B, every vertex of B has more than x2∣A∣ neighbours in A. Also step 3.1 gives at most 12y2∣N∣ neighbours in N for each vertex of A, while step 5.1 implies ∣B∣>∣N∣/2; hence 12y2∣N∣<y2∣B∣, so every vertex of A has at most y2∣B∣ neighbours in B. Therefore A is y2-sparse to B.

7.1step 1.1step 3.1step 6.1∎

Step 3.1 gives A⊆V(G)∖NG[v], step 1.1 gives B⊆NG(v), and steps 3.1 and 6.1 give the size, sparsity, and neighbourhood clauses. These are exactly the four clauses of the statement.

LemmaStatement: AI-adaptedProof: AI-adaptedverified 2026-09-24 (gpt-6-sol)Open item page →

Leaf-reducible families yield a large anticomplete pair or a deeper restricted induced subgraph

Statement

Let F be a leaf-reducible finite family of graphs. Then there exist constants d>0 and h≥1 such that for every y∈(0,12), every b>1, and every y-sparse F-free graph G, at least one of the following holds:

  1. there are disjoint sets X,Y⊆V(G) with ∣X∣≥ybd+1∣V(G)∣,∣Y∣≥(1−hy)∣V(G)∣, and Y anticomplete to X; or
  2. G has a yb-restricted induced subgraph with at least ybd+1∣V(G)∣ vertices.

Facts & Assumptions

Given: A leaf-reducible family F, b>1, y∈(0,1/2), and a nonempty y-sparse F-free graph G on n vertices.

[L1]

Leaf-reducibility gives H∈F and a leaf v such that F′={H−v}∪(F∖{H}) has the Erdős-Hajnal property (Leaf-reducible finite graph families).

[L2]
[L3]

The leaf-extension counting lemma gives, in a y-sparse host, many H copies, few H−v copies in a set of size at least yn, or a pair A,B with ∣A∣≥yan, ∣B∣≥(1−∣H∣y)n, and B x-sparse to A (A sparse host has many leaf extensions, few smaller copies, or a sparse pair).

Proof

technique · direct
1.1L1L2given

Fix H,v from [L1], put r=∣H∣, and choose a viral exponent D≥1 for F′ by [L2]. If r=2, then H is an edge, so the H-free graph G is stable and its whole vertex set is 0-sparse. Taking d=h=1 gives outcome 2 for all y,b. Hence assume r≥3 and set d=D(r−1)+2 and h=2r. These constants depend only on F.

2.1step 1.1L3givenalgebra

If y≥(2r)−1, then (1−hy)n≤0. Taking X=V(G) and Y=∅ gives outcome 1, since ybd+1≤1. Hence assume y<(2r)−1. Put x=min⁡{y/2,(2n)−1}>0 and a=bD(r−1)+3. Then x≤y, a≥2, and [L3] applies. Its many-H outcome is impossible because G is F-free.

3.1step 1.1step 2.1L2L3algebra

Suppose the few-H−v outcome of [L3] holds. It gives S⊆V(G) with ∣S∣≥yn and ind⁡H−v(G[S])≤ya−2∣S∣r−1<ybD(r−1)∣S∣r−1, since a−2=bD(r−1)+1 and y<1. Every unchanged member of F′ belongs to F, so it has zero copies in G[S]. The viral premise for F′ therefore holds at ϵ=yb. Virality yields a yb-restricted induced subgraph with at least ybD∣S∣≥ybD+1n≥ybd+1n vertices. This is outcome 2.

3.2step 1.1step 2.1L3algebra

Otherwise [L3] gives disjoint A,B with ∣A∣≥yan, ∣B∣≥(1−ry)n≥(1−hy)n, and B x-sparse to A. Since x∣A∣≤xn≤1/2, every vertex of B has integer degree zero into A, so B is anticomplete to A. Also bd+1=bD(r−1)+2b+1≥a because b>1. Thus ∣A∣≥ybd+1n, and X=A,Y=B give outcome 1.

4.1step 2.1step 3.1step 3.2∎

Step 2.1 handles the large-y case, while steps 3.1 and 3.2 exhaust the two remaining alternatives of [L3]. Thus one of the stated outcomes always holds.

LemmaStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-09-01Open item page →

Iterated sparse restriction reaches the target sparsity threshold

Statement

Let c∈(0,1), b1>1, b2,b3>0, and assume b1b2≥b2+b3. Suppose that x∈(0,c) and that a graph G satisfies:

  1. G has a c-sparse induced subgraph with at least cb2∣V(G)∣ vertices; and
  2. for every λ∈[x,c] and every λ-sparse induced subgraph F of G with ∣V(F)∣≥λb2∣V(G)∣, there is a λb1-sparse induced subgraph of F with at least λb3∣V(F)∣ vertices.

Then G contains an x-sparse induced subgraph with at least xb1b2∣V(G)∣ vertices.

Facts & Assumptions

Given: The parameters and hypotheses in the statement.

[L1]

A λ-sparse vertex set is nonempty, and every vertex has degree at most λ times the size of that set inside the induced subgraph (c-sparse, c-dense and c-restricted vertex sets).

Proof

technique · direct
1.1givenL1

Hypothesis 1 supplies a nonempty c-sparse vertex set, because c-sparse sets are nonempty by [L1]. Hence ∣V(G)∣>0.

1.2givenchooseL1algebra

For each nonempty induced subgraph E of G, let μ(E) be its maximum degree divided by ∣V(E)∣; by [L1], the graph E is λ-sparse exactly when μ(E)≤λ. Define λ(E):=max⁡(xb1,μ(E)). Hypothesis 1 gives a c-sparse induced subgraph E0 with at least cb2∣V(G)∣ vertices, so λ(E0)≤c and ∣V(E0)∣≥λ(E0)b2∣V(G)∣. Because G has only finitely many induced subgraphs, the set of values λ(E) with λ(E)≤c and ∣V(E)∣≥λ(E)b2∣V(G)∣ has a minimum. Choose an induced subgraph F for which that minimum is attained, and write λ:=λ(F).

2.1step 1.2givenalgebraassume-contradischarge-contradiction

Suppose that λ≥x. Then hypothesis 2 applies to F and produces a λb1-sparse induced subgraph F′⊆F with at least λb3∣V(F)∣≥λb2+b3∣V(G)∣≥λb1b2∣V(G)∣ vertices, where the last inequality uses b1b2≥b2+b3. Since F′ is λb1-sparse, we have μ(F′)≤λb1 and therefore λ(F′)=max⁡(xb1,μ(F′))≤λb1<λ. Also ∣V(F′)∣≥λ(F′)b2∣V(G)∣. This contradicts the minimal choice of λ. Therefore λ<x.

3.1step 1.2step 2.1algebra

Since λ=λ(F), step 1.2 gives xb1≤λ, and step 2.1 gives λ<x. Because F is λ-sparse, it is also x-sparse. Moreover ∣V(F)∣≥λb2∣V(G)∣≥(xb1)b2∣V(G)∣=xb1b2∣V(G)∣.

4.1step 3.1∎

The induced subgraph F from step 3.1 is the required x-sparse induced subgraph.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-09-01Open item page →

A sparse graph either sparsifies further or yields a comb or a large sparse pair

Statement

Let 0<x≤y≤2−8, and let G be a y3-sparse graph with ∣V(G)∣≥y−4. Then at least one of the following holds:

  1. there are disjoint sets X,Y⊆V(G) such that ∣X∣≥y4∣V(G)∣,∣Y∣≥(1−4y)∣V(G)∣, and Y is x-sparse to X;
  2. G is 2y4-sparse; or
  3. for some integer ℓ∈[y−1,⌈x−2⌉], there is an (ℓ,y4∣V(G)∣/ℓ2)-comb ((ai,Bi):i∈[ℓ]) in G, and there is a vertex v∈V(G)∖({ai:i∈[ℓ]}∪⋃i=1ℓBi) that is complete to ⋃i=1ℓBi and anticomplete to {ai:i∈[ℓ]}.

Facts & Assumptions

Given: Parameters x,y and a graph G satisfying the displayed hypotheses.

[L1]

If outcomes 1 and 2 fail, then there exist a vertex v∈V(G) and disjoint sets A,B⊆V(G)∖{v} with A⊆V(G)∖NG[v], B⊆NG(v), ∣A∣≥(1−3y)∣V(G)∣, ∣B∣≥y4∣V(G)∣, A y2-sparse to B, and every vertex of B having at least x2∣A∣ neighbours in A (A sparse graph without a large sparse pair has a large nearly covered sparse pair).

[L2]

If every vertex of a nonempty set B has at least ξ∣A∣ neighbours in a nonempty set A, then some set S⊆A with ∣S∣≤⌈1/ξ⌉ meets the neighbourhood in A of at least half of the vertices of B (A dense bipartite side has a small hitting set).

[L3]

In a bipartite graph (A,B) where every vertex of B has a neighbour in A and every vertex of A has at most Δ neighbours in B, either there is a (t,Γt−2)-comb for some integer t≥1, or ∣B∣≤33/23/2−3/2Γ1/2Δ1/2 (A bipartite graph with bounded A-degree has a large comb or a small B-side).

[L4]

An (ℓ,w)-comb in a graph is a sequence of distinct teeth ai and pairwise disjoint blocks Bi such that ai is complete to Bi and anticomplete to every other block (Combs in a graph).

Proof

technique · cases
1.1givencases

[assume-case pair] If outcome 1 already holds, there is nothing to prove.

1.2givencases

[assume-case sparser] If outcome 2 already holds, there is nothing to prove.

1.3L1given

[assume-case comb] Assume now that outcomes 1 and 2 both fail. Then [L1] gives a vertex v∈V(G) and disjoint sets A,B⊆V(G)∖{v} with A⊆V(G)∖NG[v], B⊆NG(v), and the displayed nearly covered sparse pair properties. In particular A and B are nonempty.

2.1step 1.3L2choosealgebra

Apply [L2] with ξ=x2 to the sets A,B. We obtain a set S⊆A with ∣S∣≤⌈x−2⌉ such that at least half of the vertices of B have a neighbour in S. Let B′⊆B be the set of vertices with a neighbour in S; then ∣B′∣≥∣B∣/2≥12y4∣V(G)∣.

3.1step 1.3step 2.1L3algebra

Consider the bipartite graph between S and B′. Every vertex of B′ has a neighbour in S by definition. Since A is y2-sparse to B and S⊆A, every vertex of S has at most y2∣B∣ neighbours in B′. Apply [L3] with d:=1/2, Δ:=y2∣B∣, and Γ:=∣B∣.

4.1step 2.1step 3.1L3algebra

The second alternative of [L3] is impossible for these parameters, because it would give ∣B′∣≤33/23/2−3/2 ∣B∣1/2(y2∣B∣)1/2=33/23/2−3/2 y∣B∣. The constant in front of y∣B∣ is less than 20, while ∣B′∣≥∣B∣/2>20y∣B∣ since y≤2−8<1/40. Hence [L3] yields a (ℓ,∣B∣/ℓ2)-comb ((ai,Bi):i∈[ℓ]) with each ai∈S and each Bi⊆B′.

5.1step 1.3step 2.1step 4.1L4algebra

Because the teeth ai are distinct members of S, we have ℓ≤∣S∣≤⌈x−2⌉. Also [L4] gives ∣Bi∣≥∣B∣/ℓ2 for each tooth block, while every ai∈S⊆A has at most y2∣B∣ neighbours in B. Since ai is complete to Bi by [L4], this forces ∣B∣/ℓ2≤∣Bi∣≤y2∣B∣, and therefore ℓ≥y−1. Finally ∣B∣≥y4∣V(G)∣ from step 1.3, so each block has size at least y4∣V(G)∣/ℓ2.

6.1step 1.3step 5.1

By step 1.3, we already have a vertex v with B⊆NG(v) and A⊆V(G)∖NG[v]. Since each ai∈A and each Bi⊆B, the vertex v is complete to ⋃iBi and anticomplete to {ai:i∈[ℓ]}. Together with step 5.1, this is exactly outcome 3.

7.1step 1.1step 1.2step 6.1cases-exhaustive∎

The three cases 1.1, 1.2, and 1.3 exhaust the possibilities, so one of the stated outcomes always holds.

5 · Examples, counterexamples and false statements

None yet.

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