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TheoremStatement: Literature-sourcedProof: AI-adaptedSession-authored (Fable 5 assisted)precheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-16
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Counting lemma: regular dense pairs contain many part-respecting copies of every fixed graph

Statement

Let H be a finite simple graph on labelled vertices [h], and let 0<η<1. There are constants γ=γ(H,η)>0, c=c(H,η)>0, and N=N(H,η) such that the following holds for every finite simple graph G. Let W1,,WhV(G) be nonempty, not necessarily distinct, with WiN. Whenever ijE(H), require WiWj and require (Wi,Wj) to be γ-regular in G of density at least η. Then at least ci=1hWi maps ϕ:[h]V(G) with ϕ(i)Wi carry every edge of H to an edge of G. At least half this many such maps are injective, after increasing N if necessary.

Facts & Assumptions

Given: H,η, a host graph G, and host sets WiV(G) satisfying the Statement.

[L1]

If (X,Y) is ϵ-regular of density d and YY satisfies YϵY, then fewer than ϵX vertices xX have N(x)Y<(dϵ)Y, and separately fewer than ϵX have N(x)Y>(d+ϵ)Y (In a regular pair, fewer than ϵX vertices have too small a degree into a large subset, and fewer than ϵX have too large a degree).

[L2]

Restricting a regular pair to sufficiently large subsets preserves regularity, with a controlled new parameter and density loss (Slicing lemma: large subpairs remain regular and their density shifts by at most ϵ).

[L3]

A finite simple graph has finitely many vertices, no loops, and unordered edges between distinct vertices (A finite simple graph is a finite vertex set together with a set of two-element vertex subsets).

Proof

technique · direct
1.1

If h=0 there is exactly one map ϕ:V(G), it is injective and carries every edge of H to an edge of G vacuously, and i=10Wi=1, so γ=c=1/2 and N=1 give both assertions; assume h1 from here. Put e=E(H). Choose γ>0 with γ(η/2)h/(2h); since h1 and 0<η<1 this also gives γ(η/2)h and γη/2. Set c=2h(η/2)e>0.

givenL3choose
2.1

Embed the vertices in the order 1,,h. After choosing images for 1,,r, maintain for each j>r the candidate set obtained by intersecting Wj with the neighbourhoods of the already embedded neighbours of j. The invariant is Cj(η/2)dr(j)Wj, where dr(j) is the number of neighbours of j among [r].

step 1.1induction
3.1

Suppose the invariant holds before embedding r+1, and let j>r+1 be a neighbour of r+1. The invariant and step 1.1 give Cj(η/2)hWjγWj, so Cj meets the size threshold [L1] asks of a subset of Wj inside the original γ-regular pair (Wr+1,Wj); no reslicing of that pair is needed for this bound, and [L2] confirms that the restricted pairs carried along remain regular. Write d for the density of (Wr+1,Wj), so dη. Applying [L1] to this one subset Cj, fewer than γWr+1 vertices of Wr+1 have fewer than (dγ)Cj neighbours in Cj, and (dγ)Cj(ηγ)Cj(η/2)Cj because γη/2. This is a bound for the single subset Cj, giving one exceptional set for each neighbour of r+1.

step 1.1step 2.1L1L2
4.1

The union of the at most h exceptional sets of step 3.1 has size at most hγWr+112(η/2)hWr+112Cr+1, so at least half of Cr+1 survives; note that the exceptional sets are measured against Wr+1, not against Cr+1. Every remaining choice preserves the invariant after replacing each future-neighbour candidate set by its neighbourhood. Vertex v is therefore chosen from a set of size at least 12(η/2)dv1(v)Wv, and vdv1(v)=e because each edge is counted once, at its later endpoint. Thus the greedy induction supplies at least 2h(η/2)eiWi=ciWi edge-preserving maps.

step 1.1step 2.1step 3.1inductionalgebra
5.1

A noninjective map identifies at least one pair i<j and hence there are at most (h2)N1iWi collision choices. Choose N so that this is at most (c/2)iWi whenever all WiN.

step 4.1L3algebrachoose
6.1

Removing these collision maps leaves at least (c/2)iWi injective part-respecting copies of H.

step 4.1step 5.1

Depends on

Used by

Dependency tree · next 3 levels

Direct dependencies and their dependencies through the next three levels: 13 results over 10 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.

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