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CorollaryStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-10
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Birkhoff strong law for iid coordinate shifts

Statement

Assume AC. On the canonical countable product of an integrable real probability law, the left shift is measure preserving and ergodic. Its coordinate averages converge almost surely and in L1 to the common mean by the ergodic theorem.

Facts & Assumptions

[F1]

The Axiom of Choice: The Axiom of Choice (AC) is the following statement.

Every family of nonempty sets has a choice function (def-choice-function).

Written out: for every set F all of whose members are nonempty, there exists a function g with domain F satisfying g(S)S for all SF.

An equivalent formulation is that a product of nonempty sets is nonempty: if Xi for every iI, then iIXi. Here iIXi is the set of functions f with domain I such that f(i)Xi for every iI; when a family of nonempty sets is indexed by itself, such an f is precisely a choice function for it.

[F2]

The Axiom of Countable Choice (ACω): The Axiom of Countable Choice, written ACω, is the following statement.

For every family (Xn)nN of nonempty sets indexed by N there is a function f with domain N such that f(n)Xn for every nN.

Equivalently, in the vocabulary of def-choice-function: every at most countable family of nonempty sets (def-countable) has a choice function.

[F3]

The recursion theorem: Let (N,0,σ) be a Peano system (def-peano-system), in particular the natural numbers N (def-natural-numbers). For any set A, any element aA, and any function f:AA, there is a unique function g:NA such that g(0)=a and g(σ(n))=f(g(n)) for all nN.

[F4]

The axiom of dependent choice: a relation in which every element is related to something admits an N-indexed chain: Let X be a set and let RX×X be a binary relation on X. Call R entire on X when

for every xX there is yX with xRy.

The Axiom of Dependent Choice, written DC, is the following statement.

For every nonempty set X, every relation R entire on X, and every aX, there is a function x:NX (def-function, def-natural-numbers) with x0=aandxnRxn+1  for every nN.

Here a sequence in X means a function from N to X, not necessarily a real-valued sequence. As everywhere in this library N contains 0, and the sequence is indexed from 0; the term x0 is the prescribed starting point a and every later term is related to its predecessor.

What DC adds to what came before. def-choice-function and def-axiom-of-choice select one element from each member of a family that is fixed in advance, and def-countable-choice does the same for a family indexed by N. In both, the family is given before any selection is made. DC is the principle needed when the n-th set to select from is not known until the first n selections have been made: here the admissible values of xn+1 are exactly the R-successors of xn, so the family being chosen from is built along the choosing. That is precisely the situation ACω does not cover, and it is why a construction "pick xn+1 depending on xn, for every n at once" is not licensed by countable choice.

The starting point may be dropped. The formally weaker statement obtained by deleting the clause x0=a — for every nonempty X and every entire R there is a sequence with xnRxn+1 for all n — is an immediate consequence of the form above, since X is nonempty and any of its elements may be taken as a. The reverse derivation is standard and is not needed anywhere in this library, so it is not carried out; every use below prescribes x0.

R need not be an order and the terms need not be distinct. What DC delivers is a sequence, that is a function NX, not a chain in the order-theoretic sense (def-chain). The relation may be symmetric, and the sequence may repeat a value or be constant; all that is asserted is xnRxn+1 at every index.

[F5]

Assuming countable and dependent choice, countable products of arbitrary probability spaces: Assume countable choice and dependent choice. For probability spaces (En,En,μn)nN there is a unique probability measure on the canonical countable-product sigma-algebra having the prescribed finite product marginals.

[F6]

Coordinate random elements of a countable product are independent: Under the measure of F5, the coordinate maps Xn(x)=xn have laws μn and are independent.

[F7]

Measure preservation can be checked on a generating pi-system: Let T:XX be measurable on (X,A,μ). Let P be a π-system generating A, with an increasing sequence PnP covering X and satisfying μ(Pn)<. If μ(T1P)=μ(P) for every PP, then T preserves μ. For finite μ, a generating π-system can be enlarged by X to meet the exhaustion condition.

[F8]

Kolmogorov zero-one law: Let (Xn)nN be an independent sequence of random elements, and let T(Xn:nN) be its tail σ-algebra. Then every event AT(Xn:nN) satisfies P(A){0,1}.

[F9]

Ergodicity relative to an invariant measure: A measure-preserving system is ergodic for μ if each EI has μ(E)=0 or μ(XE)=0, with I as in def-strict-and-mod-null-invariant-σ-algebras. For a probability system this means μ(E){0,1}. The definition is relative to the invariant measure; no probability assumption is implicit in the general null/conull formulation.

[F10]

Birkhoff's theorem for an ergodic probability system: If T is an ergodic measure-preserving transformation of a probability space and f is an integrable real-valued measurable function, then Anf=n1j=0n1fTjc=fdP almost surely and in L1. Invertibility is not required.

Proof

Given: The objects, hypotheses and definitions in the statement. Its conclusions are to be established below.

1.1

AC (F1) selects a member of each set in any prescribed countable nonempty family, giving F2. For an entire relation R on a nonempty A, AC selects s(a){b:aRb} for every a. F3 iterates s from any prescribed a0, yielding an+1=s(an) and thus F4. Hence F5 has its CC and DC hypotheses satisfied and constructs the canonical countable product; F6 gives its coordinate maps their common law and independence.

F1F2F3F4F5F6
1.2

Write T(x0,x1,)=(x1,x2,). Pullbacks of finite coordinate cylinders are cylinders with shifted indices, so T is measurable. The product of the marginal probabilities of any such cylinder is unchanged on shifting all indices. F7 therefore extends equality of cylinder probabilities to all product-measurable sets, proving measure preservation.

F6F7
1.3

If a measurable E is strictly invariant, E=TnE for every n. For each n, the class of sets B whose TnB belongs to σ(Xn,Xn+1,) is a σ-algebra containing the cylinders, hence contains E. Thus E belongs to the coordinate tail σ-algebra. F8 gives P(E) in {0,1}, which is precisely F9.

F8F9
2.1

The zeroth coordinate f(x)=x0 is integrable with integral equal to the common mean. Step 1.2 and step 1.3 verify the system hypotheses of F10. Its averages are exactly Anf=(x0++xn1)/n for n1, so both asserted modes of convergence follow without using the IID strong-law proof.

F10step 1.3

Depends on

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Sources