Alphabeta Math
LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26
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.

Sparsity is preserved when the parameter grows, and every nonempty set of at most two vertices is 0-restricted

Statement

Let G be a finite simple graph and let 0≤c≤c′.

  1. If a nonempty set X⊆V(G) is c-sparse, then it is c′-sparse.
  2. If X is nonempty and ∣X∣≤2, then X is 0-restricted.

Facts & Assumptions

Given: A finite simple graph G, reals 0≤c≤c′, and a nonempty set X⊆V(G).

[L1]

A nonempty set Y is c-sparse when every vertex of Y has at most c∣Y∣ neighbours in Y; it is c-dense when every vertex has at most c∣Y∣ non-neighbours in Y other than itself; and it is c-restricted when it is c-sparse or c-dense (c-sparse, c-dense and c-restricted vertex sets).

Proof

technique · direct
1.1L1algebra

If X is c-sparse, then every vertex of X has at most c∣X∣≤c′∣X∣ neighbours in X, so [L1] makes X c′-sparse.

1.2L1

If ∣X∣=1, then its only vertex has no neighbour and no non-neighbour inside X∖{x}, so [L1] makes X both 0-sparse and 0-dense.

2.1L1∎

If ∣X∣=2, then either the two vertices are adjacent or they are not. In the first case X is 0-dense, and in the second it is 0-sparse. So [L1] makes every two-element set 0-restricted.

Depends on

Used by

Dependency tree · two levels

6 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