Alphabeta Math
LemmaStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-07
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.

Cheeger indicator and positive part energy

Statement

Let n≥2 and use normalized edge expansion h and algebraic gap γ=1−μ2. Then γ≤2h. Moreover some sign of a nonzero mean-zero μ2 eigenvector has positive part f≠0 supported on at most n/2 vertices and satisfying ⟨f,(I−M)f⟩≤γ∥f∥2.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

For the regular multigraph and spectral conventions in the stated convention, put α=∥M∣1⊥∥. For n≥2 order the eigenvalues 1=μ1≥μ2≥⋯≥μn, counting multiplicity, and put γ=1−μ2. Thus α=max⁡j≥2∣μj∣, which also controls negative eigenvalues. Write cut⁡(S)=∑u∈S,v∉SAuv and ∂VS={v∉S:Auv>0 for some u∈S}. Normalized edge expansion and external vertex expansion are h=min⁡0<∣S∣≤n/2cut⁡(S)d∣S∣,hV=min⁡0<∣S∣≤n/2∣∂VS∣∣S∣. For n=1, put α=0 and leave μ2,γ,h,hV undefined; cut-expansion assertions are vacuous. A bounded-degree family is an expander family when its normalized edge expansion has a positive uniform lower bound for n≥2. Polynomial-time constructibility means a uniform algorithm outputs the adjacency list in time polynomial in n; neighbor computation in time polynomial in log⁡n is a stronger requirement. (Spectral edge and vertex expansion).

[F2]

If T is self-adjoint on a nonzero finite-dimensional real inner product space and its eigenvalues are ordered as λ1≥⋯≥λn, then λ1=max⁡v≠0RT(v)andλn=min⁡v≠0RT(v). (The smallest and largest eigenvalues of a self-adjoint endomorphism are the minimum and maximum Rayleigh quotients).

Proof

1.1F1F2

On the nonzero invariant space 1⊥, the Rayleigh quotient of I−M is at least γ. For 0<∣S∣≤n/2, the centered indicator has norm squared ∣S∣(1−∣S∣/n)/n and energy cut⁡(S)/(nd). Hence γ≤cut⁡(S)/(d∣S∣(1−∣S∣/n))≤2cut⁡(S)/(d∣S∣). Minimize over the finite nonempty collection of such sets.

2.1step 1.1algebra∎

Choose a nonzero mean-zero eigenvector g for μ2. It has both positive and negative entries, so one sign has at most n/2 positive entries. Let f=max⁡(g,0) for this sign. At a positive coordinate, Mf≥Mg since f≥g and M is nonnegative; thus (I−M)f≤(I−M)g=γg there. Multiply by f, sum, and use f=0 elsewhere to obtain the energy bound. This also works when γ=0 and when some coordinates of g vanish.

Depends on

Used by

Dependency tree · two levels

5 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