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Lemma 1, p. 12 — ‖PJ‖_D ≤ ‖J‖_D for every J ∈ L₂(S, D)

Proved
TDApprox.Conv.lemma_1

by mikedeng1 · Oct 6, 2026 · Mathlib 0df444a (Lean v4.33.1)

invariant-distributionmarkov-chainnonexpansivep2o-batch-pfp2ap2o-gran-per-chapterp2o-plan-paperp2o-v1weighted-norm

Let P=(pij)P = (p_{ij})P=(pij​) be the transition matrix of a Markov chain on a countable state space SSS, and suppose that the chain has a unique invariant distribution π\piπ with π(i)>0\pi(i) > 0π(i)>0 for every iii (Assumption 1(a)). Write ∥J∥D2=∑iπ(i)J(i)2\|J\|_D^2 = \sum_i \pi(i)J(i)^2∥J∥D2​=∑i​π(i)J(i)2, so that L2(S,D)={J:∥J∥D<∞}L_2(S,D) = \{J : \|J\|_D < \infty\}L2​(S,D)={J:∥J∥D​<∞}, and (PJ)(i)=∑jpijJ(j)(PJ)(i) = \sum_j p_{ij}J(j)(PJ)(i)=∑j​pij​J(j).

For every J∈L2(S,D)J \in L_2(S,D)J∈L2​(S,D), the vector PJPJPJ is well defined (each series ∑jpijJ(j)\sum_j p_{ij}J(j)∑j​pij​J(j) converges absolutely), lies in L2(S,D)L_2(S,D)L2​(S,D), and

∥PJ∥D≤∥J∥D.\|PJ\|_D \le \|J\|_D.∥PJ∥D​≤∥J∥D​.

So PPP is a nonexpansion of the steady-state weighted norm. Every contraction estimate of the paper (Lemmas 2–5) rests on this inequality.

Formalization Note. (PJ)(i)(PJ)(i)(PJ)(i) is the integral of JJJ against the row P(i)P(i)P(i). The well-definedness of PJPJPJ and its membership in L2(S,D)L_2(S,D)L2​(S,D) are added as conjuncts; the page uses both implicitly when it writes ∥PJ∥D\|PJ\|_D∥PJ∥D​.

Preamble
import Mathlib
import Definitions.Def_TDApprox_Conv_Model
open MeasureTheory ProbabilityTheory Filter Topology Finset Matrix
Formal statement
namespace TDApprox.Conv

/-- **Lemma 1** (Tsitsiklis & Van Roy, LIDS-P-2322 (1996), p. 12). Under Assumption 1(a), for any
`J ∈ L₂(S, D)` we have `‖PJ‖_D ≤ ‖J‖_D`, where `(PJ)(i) = Σ_j p_ij J(j) = ∫ J d(P i)`.
The conclusion also records that `PJ` is well defined (`J` is integrable under every row `P i`)
and lies in `L₂(S, D)`; both are implicit in the page's `‖PJ‖_D`. -/
theorem lemma_1 {S : Type*} [MeasurableSpace S] [DiscreteMeasurableSpace S] [Countable S]
    (P : Kernel S S) [IsMarkovKernel P] (π : Measure S) [IsProbabilityMeasure π]
    (h1a : Assumption1a P π) (J : S → ℝ) (hJ : MemL2D π J) :
    (∀ i, Integrable J (P i)) ∧ MemL2D π (Pop P J) ∧ normD π (Pop P J) ≤ normD π J := by sorry

end TDApprox.Conv
Source
Tsitsiklis & Van Roy, LIDS-P-2322 (1996), Lemma 1, p. 12
Human review
  • Endorsed by Shuze Chen · Oct 6, 2026

    Confirmed by the moderator at approval.

  • Endorsed by mikedeng1 · Oct 6, 2026

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

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