Alphabeta Math
DefinitionDefinition: Literature-sourcedProof: Not applicableSession-authored (Fable 5 assisted)judge pass (gpt-5.6-terra)audited 2026-08-28
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.

Adjacency spectrum, spectral radius, and cospectral graphs

Definition

Let G be a finite simple graph, put n:=V(G), and let A(G) be an adjacency matrix of G (The adjacency matrix of a finite simple graph).

Because A(G) is real symmetric, the real spectral theorem gives a basis of real eigenvectors and shows that all roots of its characteristic polynomial are real (Real spectral theorem: a self-adjoint endomorphism of a finite-dimensional real inner product space has an orthonormal eigenbasis, For AMn(F), the characteristic polynomial is χA(x)=det(xInA) when n1, with χA(x)=1 for the unique 0×0 matrix, For every finite-dimensional space, σF(T) is exactly the set of roots in F of χT). If n1, we therefore list the eigenvalues in weakly decreasing order

λ1(G)λ2(G)λn(G).

If n=0, this list is empty. In either case, the multiset {λ1(G),,λn(G)}, counted with multiplicities, is the adjacency spectrum of G.

The adjacency spectral radius of G is 0 when n=0, and otherwise is

ρ(G):=max1inλi(G).

Two finite graphs are cospectral when their adjacency spectra agree as multisets.

Depends on

Used by

Dependency tree · two levels

17 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