Alphabeta Math
LemmaStatement: AI-generatedProof: AI-generated
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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.

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  • 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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Finite coupling makes connectivity probability monotone

Statement

For fixed integer n≥1 and 0≤p≤q≤1, the connectivity probabilities satisfy P(G(n,p) is connected)≤P(G(n,q) is connected). This statement concerns graph connectivity only.

Facts & Assumptions

Given: The objects and hypotheses of the Statement.

Goal: Prove the Statement.

[F1]

Finite product spaces assign to a coordinate tuple the product of its coordinate weights (The finite product of finite probability spaces).

[F2]

Event probabilities in a finite space are sums of nonnegative outcome weights (Finite probability spaces, outcome weights, events, and event probabilities).

[F3]

The law G(n,p) has independent edge coordinates of inclusion probability p (The Erdős-Rényi finite random graph G(n,p)).

[F4]

Connectivity means that every pair of vertices is joined by a finite path (Connected graphs and connected components defined by the existence of vertex paths).

Proof

technique · direct
1.1F1F2F3construct

Give each possible edge a coordinate with three outcomes 0,1,2 of respective weights 1−q,q−p,p, and use their finite product. These weights are nonnegative and sum to one. Include an edge in Hp if its coordinate is 2, and in Hq if its coordinate is 1 or 2. Summing coordinate weights shows the marginals are respectively p and q; summing product weights over each prescribed coordinate block factors, so the graph marginals are G(n,p) and G(n,q).

2.1step 1.1F2F4algebra∎

On every outcome the two graphs have the same nonempty vertex set [n], and every edge of Hp is an edge of Hq. Each path of Hp therefore remains a path of Hq, so the event A that Hp is connected is contained in the event B that Hq is connected. For the product outcome weights w, nonnegativity gives P(B)−P(A)=∑ω∈B∖Aw(ω)≥0. By the graph marginals in step 1.1 this is the desired inequality, including all endpoint cases.

Depends on

Used by · 1

Dependency tree · 2 levels

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