Alphabeta Math
CorollaryStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02
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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.

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A finite family has an SDR if and only if every subfamily has a union at least as large as its index set

Statement

Let (Ax)x∈X have finite index set X and finite union U:=⋃x∈XAx. It has an SDR if and only if ∣⋃x∈SAx∣≥∣S∣(S⊆X).

Facts & Assumptions

Given: A family (Ax)x∈X with finite X and finite union U, and its tagged incidence graph with parts XL,UR.

[F1]

The tagged incidence graph is finite and bipartite, its left-neighbourhood of SL is the tagged copy of ⋃x∈SAx, and an SDR is an injection choosing one adjacent right tag for each left tag (Bipartite neighbourhoods, Hall's condition and systems of distinct representatives).

[L1]

A finite bipartite graph has a matching saturating its left part exactly when Hall's condition holds (Hall's marriage theorem for a finite bipartite graph).

Proof

technique · direct
1.1

The displayed union inequality is exactly Hall's condition for the finite tagged incidence graph.

F1
1.2

By [F1] the tagged incidence graph is finite, so [L1] makes that condition equivalent to a matching that saturates XL.

F1L1
1.3

Such a matching assigns each x the underlying element of its unique matched right tag, and conversely an SDR gives those pairwise disjoint tagged matching edges.

F1
2.1

Combining steps 1.1--1.3 proves the stated equivalence.

step 1.1step 1.2step 1.3∎

Depends on

Used by

Dependency tree · two levels

9 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