Alphabeta Math
ExampleConstruction: AI-adaptedVerification: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-14
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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.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Absorbing gambler's-ruin chain

Statement

Assume Choice. Fix N1 and p[0,1], put q=1p, and take S={0,1,,N}. The gambler's-ruin transition matrix is P(0,0)=P(N,N)=1,P(x,x+1)=p,P(x,x1)=q(0<x<N), with all other entries zero. It is an absorbed kernel on D={0,N}, and first entrance into D is a hitting time. After a finite hit, the chain restarts at—and remains at—the boundary point hit.

Facts & Assumptions

Given: N,p,q,S,D as displayed and a chain with this transition matrix.

[F1]

Absorption on D replaces every row at xD by δx and leaves the rows on Dc unchanged. (Killed and absorbed transition kernels)

[F2]

The absorbed construction is a probability kernel. (Killed and absorbed kernels are probability kernels)

[F3]

At a measurable hitting time, the conditional future path law is the canonical chain law started from the hit state. (The post-hitting chain restarts from the hit state)

Verification

1.1

For 0<x<N, the only row masses are p and q, which are nonnegative and [F1, F2] sum to one. At 0 and N the rows are the corresponding Dirac masses. Thus these rows are exactly [F1] applied to any base kernel having the displayed interior transitions, and [F2] verifies the kernel. When N=1 there are no interior rows; when p=0 or p=1 the interior motion is deterministic.

F1F2
1.2

Define [given] τD=inf{n0:Xn{0,N}}. Then {τDn}=k=0n{XkD}Fn, so it is a hitting time. If X0D, then τD=0; otherwise it may be infinite in the general eventwise formulation.

given
2.1

By [F3], on {τD<} the conditional future is the chain started [F3, step 1.1, step 1.2] from XτD. Step 1.1 gives P(XτD,XτD)=1, so every subsequent coordinate equals the same boundary state. Constants zero and one give respectively zero and the finite-hit event in the eventwise formula. Choice is used only through [F3].

F3step 1.1step 1.2

Depends on

Used by

Nothing in the library uses this result yet.

Dependency tree · two levels

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Sources