Alphabeta Math
AlgorithmAlgorithm: Literature-sourcedProof: Not applicablePipeline-generated
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.

Random and systematic Gibbs scan schemes

Definition

Inputs: A common finite-product measurable state space (S,S) with target probability π, an integer m≥1, and for each j=1,…,m a nonempty block Bj with its supplied proper full conditional kernel for π. Invoke Exact Gibbs block update for each block to obtain its exact update kernel Pj:S→S. Select random scan, systematic scan, or both; if random scan is selected, also supply fixed weights wj≥0 with ∑j=1mwj=1.

Admissible conditions: Every Pj acts on this same (S,S) and is an exact block-update kernel for this same target π. The weights are required only for the random-scan branch; systematic scan takes no weights.

Outputs: For each selected mode, its one-update random-scan kernel Prand:S→S or full-sweep systematic kernel Psweep:S→S; for systematic scan, also the phase-indexed single-update kernels P1,…,Pm.

Random-scan instructions: At each update, independently draw j∈{1,…,m} with probabilities w1,…,wm and apply Pj to the current state. The one-update kernel is Prand(x,A)=∑j=1mwjPj(x,A). Uniform random scan is the special case wj=1/m.

Systematic-scan instructions: Starting from the current state, apply P1, then P2, through Pm in that fixed order; repeat the same order for each subsequent sweep. For kernels, P1⋯Pm means chronological composition: apply P1 first and Pm last, as in Composition of probability kernels. Return the full-sweep kernel Psweep=P1⋯Pm. Observing after each single update gives the phase-indexed sequence P1,…,Pm,P1,… and is generally time-inhomogeneous; observing only at full-sweep boundaries gives a homogeneous chain with kernel Psweep. The scan kernels are well-defined by Random and systematic scan kernels are well-defined ↗.

Depends on

Used by

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Sources