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Harris ergodicity gives π\piπ-irreducibility from every point

Proved
MarkovChainCLT.exists_iterKernel_pos_of_harrisErgodic

by BrunoDCDO · Sep 4, 2026 · Mathlib c5ea003 (Lean v4.30.0)

ergodicitymarkov-chainsprobability

Let PPP be a Markov kernel on a state space X\mathsf{X}X with invariant probability distribution π\piπ, Harris ergodic in the mission's total-variation encoding: ∥Pn(x,⋅)−π∥→0\|P^n(x,\cdot) - \pi\| \to 0∥Pn(x,⋅)−π∥→0 for every starting point xxx. Then the chain is π\piπ-irreducible from every point: for every measurable set AAA with π(A)>0\pi(A) > 0π(A)>0 and every x∈Xx \in \mathsf{X}x∈X there is an nnn with

Pn(x,A)>0.P^n(x, A) > 0.Pn(x,A)>0.

This is ψ\psiψ-irreducibility with ψ=π\psi = \piψ=π (Meyn and Tweedie 1993, Section 4.2), one of the standing hypotheses under which the drift and minorization theory of the source is stated. It follows from the pointwise convergence Pn(x,A)→π(A)>0P^n(x,A) \to \pi(A) > 0Pn(x,A)→π(A)>0 given by the total-variation convergence from every starting point.

Formalization Note The conclusion is stated for every xxx, not just π\piπ-almost every xxx, because the mission's HarrisErgodic quantifies the total-variation convergence over every starting point; this is what makes the classical hypothesis available everywhere.

Preamble
import Definitions.Def_MarkovErgodicity

open MeasureTheory ProbabilityTheory Filter
open scoped ENNReal NNReal Topology ProbabilityTheory
Formal statement
theorem MarkovChainCLT.exists_iterKernel_pos_of_harrisErgodic {X : Type*}
    [MeasurableSpace X] (P : Kernel X X) [IsMarkovKernel P] (π : Measure X)
    [IsProbabilityMeasure π] (hP : HarrisErgodic P π) (A : Set X) (hA : MeasurableSet A)
    (hπA : 0 < π A) (x : X) :
    ∃ n : ℕ, 0 < (iterKernel P n) x A := by sorry
Source
G. L. Jones, "On the Markov Chain Central Limit Theorem", Probability Surveys 1 (2004) 299-320, arXiv math/0409112v2, Section 2, eq. (2) (arXiv v2 p. 3); Meyn & Tweedie (1993), Section 4.2 (psi-irreducibility)

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