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Internal-edge mixing bound — Lemma 3.3

PDF p. 19: Lemma 3.3

Statement

Let G=(V,E) be an (n,d∗,α)-expander, and let X⊆V. Then

−αd∗∣X∣≤e(X,X)−(d∗/n)∣X∣2≤αd∗∣X∣.

Here e(X,X) counts ordered adjacency entries, so a non-loop edge internal to X contributes twice and a loop in X contributes once.

Facts & Assumptions

[F1]

The expander has a nonempty finite vertex set of size n, adjacency matrix A, all-ones matrix J, and centered adjacency matrix ΔA=A−(d∗/n)J satisfying ∥ΔA∥≤αd∗ (Adjacency spectral expander — Definition 1.3).

[F2]

The ordered count is e(X,X)=∑x∈X∑y∈XAxy, including diagonal entries (Oriented edge count between sets).

[F3]

The vertex inner product is ⟨f,g⟩=∑x∈Vf(x)‾g(x), with induced norm ∥f∥2 and matrix action by finite row sums (Finite vertex Hilbert space in the article convention). The operator norm is the supremum of ∥Hf∥2/∥f∥2 over nonzero f (Loewner order, Hermitian inner product, and operator norm).

[F4]

Cauchy–Schwarz gives ∣⟨f,g⟩∣≤∥f∥2∥g∥2; the vertex-space convention transfers the cited linear-first version by conjugation (Cauchy–Schwarz: |⟨ u,v⟩|≤‖ u‖‖ v‖, with equality exactly for linearly dependent vectors, Finite vertex Hilbert space in the article convention).

Proof

Given: An (n,d∗,α)-expander G and X⊆V.

Goal: Establish the two displayed inequalities.

Proof technique: direct.

1.1F1F2F3

Let 1X be the indicator function, equal to 1 on X and 0 outside it. The coordinate sums give ⟨1X,A1X⟩=e(X,X), ⟨1X,J1X⟩=∣X∣2, and ∥1X∥22=∣X∣. Hence ⟨1X,ΔA1X⟩=e(X,X)−(d∗/n)∣X∣2.

2.1F1F3F4step 1.1∎

If 1X=0, then ∥ΔA1X∥2=0; otherwise the operator-norm definition gives ∥ΔA1X∥2≤∥ΔA∥∥1X∥2. Thus Cauchy–Schwarz and the expander bound yield ∣⟨1X,ΔA1X⟩∣≤∥ΔA∥∥1X∥22≤αd∗∣X∣. The quantity in step 1.1 is real, so the absolute-value inequality is exactly the two claimed bounds.

Source notes

The statement and indicator-vector method are attributed to Expander graphs are globally synchronizing, Lemma 3.3. The proof above derives the bound from the stated mathematical suppliers.

Depends on

Used by · 3

Dependency tree · 2 levels

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