Samplinglib
Lean gate not recorded for this source state main · 0e31a3cda412
Markov Chain Monte Carlo · Extended E1 · attached to Chapter 1

General-state convergence: drift, minorisation and coupling

Stable source-facing chapter environment inside the shared Samplinglib reader.

scaffoldsource mapFull source closure not claimed
Planned route

Source → theorem map → reusable Lean nodes

01

Source audit

Definitions, theorems, assumptions, proof route, and exact anchors.

02

Upstream alignment

Use one canonical shared node where types match. Formal/source audit is still required.

03

Frontier Cells

Only genuinely missing mathematical edges become theorem-sized tasks.

04

Graph placement

Dependencies, consumers, cross-library bridges, and reusable shared interfaces.

Primary source ↗

This page establishes a stable source route and truth boundary; it does not claim a completed formalization.

ASTIS extended material, not a chapter of Fearnhead–Nemeth–Oates–Sherlock. No Lean closure asserted.

Why this extension?

Stationarity is only the starting point. Determine from which states the law converges, and whether the rate is qualitative, geometric or uniform.

Primary §1.3; Roberts–Rosenthal §§2–4 (PDF pp.4–32).

\[PV\le aV+b\mathbf1_C,\qquad P^m(x,\cdot)\ge\epsilon\nu(\cdot)\ (x\in C)\]

Proposed proof / reuse route

  1. Audit the measurable state and reference measure.
  2. Keep invariance separate from irreducibility and aperiodicity.
  3. Build the small-set coupling from the exact minorisation.
  4. Combine drift and returns to obtain the source-specific bound.

Truth boundary

Do not infer mixing from detailed balance alone. Preserve exceptional null starting sets, small-set conditions and theorem quantifiers; the displayed conditions are a blueprint, not a complete theorem.

Planned consumers: mcmc, discrete-sampling, log-concave-sampling. Planned sharing is not a compiled dependency or a priority claim.

Sources and exact scope

General state space Markov chains and MCMC algorithms ↗
Gareth O. Roberts, Jeffrey S. Rosenthal · math/0404033v4
§2 construction; §§3–4 convergence/drift/coupling; §5 CLT; §6 scaling. Probability Surveys 1 (2004), 20–71; arXiv v4 (2007).
version-and-sha256-pinned

Convergence Bounds for Monte Carlo Markov Chains ↗
Qian Qin · 2409.14656v1
Handbook contribution on quantitative convergence; theorem-level anchor required for each bound
version-pinned; theorem-level audit pending

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