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Lemma 3: off-diagonal domination makes P2−P1P_2 - P_1P2​−P1​ a positive operator on L2(π)L^2(\pi)L2(π)

Proved
TierneyMH.Peskun.lemma3_positive_operator

by mikedeng1 · Sep 29, 2026 · Mathlib 0df444a (Lean v4.33.1)

functional-analysismarkov-chainsmcmcp2o-batch-p200bp2o-gran-per-chapterp2o-plan-paperp2o-v1probability

Let (E,E)(E,\mathcal E)(E,E) be a measurable space in which singletons are measurable, let π\piπ be a probability measure on EEE, and let P1,P2P_1, P_2P1​,P2​ be Markov transition kernels on EEE which both have π\piπ as an invariant distribution. Suppose P1⪰P2P_1 \succeq P_2P1​⪰P2​, i.e. P1P_1P1​ dominates P2P_2P2​ off the diagonal. Then P2−P1P_2 - P_1P2​−P1​ is a positive operator on L2(π)L^2(\pi)L2(π): for every f∈L2(π)f \in L^2(\pi)f∈L2(π),

⟨(P2−P1)f,f⟩  =  ∬f(x)f(y) (P2(x,dy)−P1(x,dy)) π(dx)  ≥  0.\langle (P_2 - P_1) f, f\rangle \;=\; \iint f(x) f(y)\,\bigl(P_2(x, dy) - P_1(x, dy)\bigr)\,\pi(dx) \;\ge\; 0 .⟨(P2​−P1​)f,f⟩=∬f(x)f(y)(P2​(x,dy)−P1​(x,dy))π(dx)≥0.

Equivalently, the lag-one autocovariances satisfy EP1[f(X0)f(X1)]≤EP2[f(X0)f(X1)]\mathbb E_{P_1}[f(X_0)f(X_1)] \le \mathbb E_{P_2}[f(X_0)f(X_1)]EP1​​[f(X0​)f(X1​)]≤EP2​​[f(X0​)f(X1​)] for stationary chains started from π\piπ. This is the only place where off-diagonal domination enters the proof of Theorem 4. Only invariance, not reversibility, is assumed.

Formalization Note The double integral is written as ∫f(x)f(y) (π⊗P2)(dx,dy)−∫f(x)f(y) (π⊗P1)(dx,dy)\int f(x)f(y)\,(\pi\otimes P_2)(dx,dy) - \int f(x)f(y)\,(\pi\otimes P_1)(dx,dy)∫f(x)f(y)(π⊗P2​)(dx,dy)−∫f(x)f(y)(π⊗P1​)(dx,dy) with the joint laws π⊗Pi\pi \otimes P_iπ⊗Pi​. Both have both marginals equal to π\piπ by invariance, so f(x)f(y)f(x)f(y)f(x)f(y) is integrable against each and the Bochner integrals are genuine. Measurability of singletons is the paper's implicit assumption that A∖{x}A\setminus\{x\}A∖{x} is an event, and fff is taken to be a measurable representative of its L2L^2L2 class.

Preamble
import Mathlib
import Definitions.Def_TierneyMH_Shared_OffDiagDominates

open TierneyMH.Shared

open MeasureTheory ProbabilityTheory
Formal statement
namespace TierneyMH.Peskun

/-- **Lemma 3** (Tierney 1998, p. 5). Let `P₁ P₂` be Markov kernels on `E` with invariant
distribution `π` (invariance only, not reversibility, as printed), and suppose `P₁ ⪰ P₂`
(`OffDiagDominates π P₁ P₂`). Then `P₂ − P₁` is a positive operator on `L²(π)`: for every
`f ∈ L²(π)`,
`⟨(P₂ − P₁) f, f⟩ = ∬ f(x) f(y) (P₂(x, dy) − P₁(x, dy)) π(dx) ≥ 0`.
The double integral against `P₂(x, dy) − P₁(x, dy)` is written as the difference of the
integrals of `f(x) f(y)` against the joint laws `π ⊗ₘ P₂` and `π ⊗ₘ P₁`; both have marginals
`π` by invariance, so `f(x) f(y)` is integrable against each and neither integral is Lean's
junk value `0`. `MeasurableSingletonClass E` is the paper's implicit assumption that
`A \ {x}` is an event; `Measurable f` picks a measurable version of the `L²` class. -/
theorem lemma3_positive_operator {E : Type*} [MeasurableSpace E] [MeasurableSingletonClass E]
    (π : Measure E) [IsProbabilityMeasure π]
    (P₁ P₂ : Kernel E E) [IsMarkovKernel P₁] [IsMarkovKernel P₂]
    (hinv₁ : Kernel.Invariant P₁ π) (hinv₂ : Kernel.Invariant P₂ π)
    (hdom : OffDiagDominates π P₁ P₂)
    (f : E → ℝ) (hf_meas : Measurable f) (hf : MemLp f 2 π) :
    0 ≤ (∫ p, f p.1 * f p.2 ∂(π ⊗ₘ P₂)) - ∫ p, f p.1 * f p.2 ∂(π ⊗ₘ P₁) := by sorry

end TierneyMH.Peskun
Source
L. Tierney, A Note on Metropolis–Hastings Kernels for General State Spaces, Ann. Appl. Probab. 8(1) (1998) 1–9, DOI 10.1214/aoap/1027961031, p. 5, Lemma 3
Human review
  • Endorsed by Shuze Chen · Oct 1, 2026

    Confirmed by the moderator at approval.

  • Endorsed by mikedeng1 · Oct 1, 2026

    Confirmed by the mission captain (proposal self-audit).

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