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Invariant mass and almost-sure hitting of accessible sets

Statement

Let P have invariant probability π. If a measurable set A has positive probability of being hit from every starting state, then Pr⁡x(τA<∞)=1 for π-almost every x. In addition, if P is ϕ-irreducible and ϕ(A)>0, then π(A)>0 and the positive-hitting hypothesis holds.

Facts & Assumptions

Given: A probability kernel with invariant probability; for the first conclusion, the positive-hitting premise; for the additional conclusion, a ϕ-irreducibility measure and ϕ(A)>0.

[F1]

Phi-irreducibility for a general-state Markov kernel: every ϕ-positive set is reached with positive probability from every state at some finite positive time.

[F2]

Invariant and stationary distribution for a Markov kernel: πPn=π for every n≥0.

[F3]

Canonical Markov chain on path space: under its stated AC convention, iterated kernels define the canonical path law.

[F4]

Discrete strong Markov property: the canonical chain has the strong Markov property at discrete stopping times.

[F5]

Monotone convergence for the integral: increasing countable sums and limits pass through integration.

[F6]

Tonelli's theorem for nonnegative measurable functions on a sigma-finite product: nonnegative sums and kernel integrals may be interchanged.

[F7]

Measurability of integration against a kernel: integrating a bounded measurable function against a probability kernel gives a measurable function of the starting state.

[A1]

Assume The Axiom of Choice as required by the canonical path-law [F3] and strong Markov [F4] suppliers. The countable level-set arguments below need no measurable selection theorem.

Proof

Given: The invariant law and applicable hypotheses, with [F1]–[F7] and [A1].

1.1F1F2F5F6given

For the additional conclusion, let f(x)=∑n≥1Pn(x,A). By [F1], f(x)>0 everywhere. Tonelli and stationarity give ∫f dπ=∑n≥1π(A). If π(A)=0, this integral is zero, contradicting positivity of f under a probability measure. Hence π(A)>0; [F1] also supplies the positive-hitting premise for the first assertion.

1.2F2F3F5F7A1given

It remains to prove the first assertion under its positive-hitting premise. Set q0=1A and recursively qn+1=1A+1AcPqn, where Pqn(x)=∫qn(y)P(x,dy). Then qn(x)=Pr⁡x(τA≤n); induction and [F7] show each qn is measurable, and qn↑q:=Pr⁡x(τA<∞), so q is measurable. If the bad set {q<1} has positive mass, a countable level-set union gives some δ1>0 for which B1={x:q(x)≤1−δ1} has positive π-measure. For each x∈B1, q(x)>0 and x∉A, so some ℓ0≥1 has Pℓ0(x,A)>0. Countable unions over times and rational thresholds then give a common ℓ0≥1, δ2>0, and B2⊆B1 with π(B2)>0 and Pℓ0(x,A)≥δ2 on B2.

2.1F2F4F5F7step 1.2

Let η=#{k≥1:Xkℓ0∈B2}. At each such visit, the conditional probability of avoiding A at the next ℓ0-step time is at most 1−δ2. Induction using [F4] gives Pr⁡x(τA=∞,η≥r)≤(1−δ2)r for each finite r, and hence Pr⁡x(τA=∞,η=∞)=0. Thus for x∈B2, Pr⁡x(τA=∞,η<∞)≥δ1. To select a measurable positive-mass set with a common finite last-visit bound, for each ℓ≥1 forbid A at every time and also forbid B2 at times kℓ0 with k≥ℓ. For a finite horizon N, let Fn(ℓ)=A∪B2 if n=kℓ0 for some k≥ℓ, and Fn(ℓ)=A otherwise. Set gN,N=1(FN(ℓ))c and recursively set gN,n=1(Fn(ℓ))cPgN,n+1 for n=N−1,…,0. Then gℓ,N=gN,0 is the finite-horizon event probability and is measurable by [F7]. As N→∞, these events decrease to {τA=∞,sup⁡{k≥1:Xkℓ0∈B2}<ℓ}, so continuity from above makes their limit gℓ(x) measurable. The events increase with ℓ and their union is {τA=∞,η<∞}, so gℓ(x)↑ a value at least δ1 on B2. A countable rational threshold selection therefore gives ℓ≥1, δ>0, and B⊆B2 with π(B)>0 and Pr⁡x ⁣(τA=∞, sup⁡{k≥1:Xkℓ0∈B2}<ℓ)≥δ(x∈B).

3.1F2F3F4step 2.1algebra∎

Put L=ℓℓ0 and S=sup⁡{k≥1:XkL∈B}, with S=−∞ if no such visit occurs. For 1≤r≤j, consider the event that XrL∈B, there is no later B-visit at a positive multiple of L, and no hit of A at or after rL. It is a subset of {S=r, XjL∉A}. Stationarity and the Markov property at time rL therefore give Pr⁡π(S=r, XjL∉A)≥∫Bπ(dy)Pr⁡y(τA=∞, S=−∞)≥π(B)δ. Indeed the event in step 2.1 rules out every B2-visit at skeleton indices k≥ℓ, hence every later B-visit at a positive multiple of L=ℓℓ0, as well as every future hit of A. The events S=r are disjoint, so stationarity yields π(Ac)≥jπ(B)δ. Taking j>1/(π(B)δ) contradicts π(Ac)≤1. Therefore the bad set is π-null.

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