Alphabeta Math
LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26
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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.
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The induced copies of H1 in G are counted by summing, over the induced embeddings of H1−v, the number of vertices that extend them at v

Statement

Let H1 be a finite simple graph with h1=∣V(H1)∣≥1, let v∈V(H1), write H1−v for the induced subgraph H1[V(H1)∖{v}], and let G be a finite simple graph with n=∣V(G)∣. For an induced embedding φ of H1−v into G define its extension set

Xφ:={ u∈V(G)∖φ[V(H1)∖{v}]:the map extending φ by v↦u is an induced embedding of H1 into G }.

Then, writing Ψ for the set of induced embeddings of H1−v into G,

ind⁡H1(G)=∑φ∈Ψ∣Xφ∣,∣Ψ∣≤n h1−1.

Facts & Assumptions

Given: A finite simple graph H1 with h1=∣V(H1)∣≥1, a vertex v∈V(H1), and a finite simple graph G with n=∣V(G)∣; the sets Φ of induced embeddings of H1 into G and Ψ of induced embeddings of H1−v into G.

[F1]

An induced embedding of H in G is an injection φ:V(H)→V(G) such that, for all distinct x,y∈V(H), xy∈E(H) if and only if φ(x)φ(y)∈E(G) (Induced embeddings and induced copies of a graph).

[F2]

ind⁡H(G) is the number of induced embeddings of H into G (The induced-embedding count ind⁡H(G)).

[F3]

H1[W]=(W, E(H1)∩[W]2), so two vertices of W are adjacent in H1[W] exactly when they are adjacent in H1 (Subgraphs, induced subgraphs and spanning subgraphs).

[L1]

For finite sets X,Y and a relation R⊆X×Y with row fibres Rx and column fibres Ry, one has ∑x∈X∣Rx∣=∣R∣=∑y∈Y∣Ry∣ (Double counting: ∑x∈X∣Rx∣=∣R∣=∑y∈Y∣Ry∣ for a relation between finite sets, A relation R⊆X×Y between finite sets, its row fibres Rx and its column fibres Ry).

[F4]

For a finite index set S and a constant c, ∑i∈Sc=∣S∣⋅c (The sum ∑i∈Sai over a finite index set, and its product form).

[L2]

For finite sets A and B, the set AB of functions B→A is finite with ∣AB∣=∣A∣∣B∣ (The set AB of functions B→A between finite sets is finite, with ∣AB∣=∣A∣∣B∣).

Proof

technique · direct
1.1F1F3

If ψ∈Φ then its restriction ψ′ to V(H1)∖{v} is injective, and for distinct x,y∈V(H1)∖{v} the condition xy∈E(H1−v) is the condition xy∈E(H1), which holds exactly when ψ(x)ψ(y)∈E(G); so ψ′∈Ψ, and it is the only member of Ψ that ψ restricts to.

1.2F1L2L3

Let R⊆Ψ×Φ consist of the pairs (φ,ψ) whose second entry restricts to the first. Both Φ and Ψ are sets of functions between finite sets, hence finite.

2.1step 1.1step 1.2F4

The column fibre of R at ψ∈Φ has exactly one element by step 1.1, so ∑ψ∈Φ∣Rψ∣=∣Φ∣.

2.2step 1.2F1given

The row fibre of R at φ∈Ψ is carried bijectively onto Xφ by ψ↦ψ(v): the map is injective because ψ is determined by φ together with ψ(v), and its image is exactly Xφ, because a vertex u arises as some ψ(v) precisely when extending φ by v↦u gives an induced embedding of H1, and injectivity of that extension is exactly the requirement u∉φ[V(H1)∖{v}].

3.1step 2.1step 2.2L1F2

Double counting R therefore gives ∑φ∈Ψ∣Xφ∣=∣R∣=∣Φ∣=ind⁡H1(G).

4.1step 3.1F1L2L3∎

Every member of Ψ is a function from V(H1)∖{v}, a set of h1−1 elements, to V(G), so Ψ is a subset of a set of size n h1−1 and ∣Ψ∣≤n h1−1.

Depends on

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Dependency tree · two levels

33 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