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 and use normalized edge expansion and algebraic gap . Then . Moreover some sign of a nonzero mean-zero eigenvector has positive part supported on at most vertices and satisfying .
Facts & Assumptions
Given: the objects and hypotheses in the statement above.
For the regular multigraph and spectral conventions in the stated convention, put . For order the eigenvalues , counting multiplicity, and put . Thus , which also controls negative eigenvalues. Write and . Normalized edge expansion and external vertex expansion are For , put and leave 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 . Polynomial-time constructibility means a uniform algorithm outputs the adjacency list in time polynomial in ; neighbor computation in time polynomial in is a stronger requirement. (Spectral edge and vertex expansion).
If is self-adjoint on a nonzero finite-dimensional real inner product space and its eigenvalues are ordered as then (The smallest and largest eigenvalues of a self-adjoint endomorphism are the minimum and maximum Rayleigh quotients).
Proof
On the nonzero invariant space , the Rayleigh quotient of is at least . For , the centered indicator has norm squared and energy . Hence . Minimize over the finite nonempty collection of such sets.
Choose a nonzero mean-zero eigenvector for . It has both positive and negative entries, so one sign has at most positive entries. Let for this sign. At a positive coordinate, since and is nonnegative; thus there. Multiply by , sum, and use elsewhere to obtain the energy bound. This also works when and when some coordinates of 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
- Hoory–Linial–Wigderson, Expander Graphs and Their Applications, May 2006 draft; §4.5.1 and beginning §4.5.2, pp40–42. (standard reference, not scraped)