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TheoremStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-14
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Uniqueness of Wiener measure

Statement

Assume the Axiom of Choice. There is exactly one probability measure μ on B(C([0,),R)) for which the coordinate process πt(f)=f(t) is centered Gaussian with Covμ(πs,πt)=min(s,t),s,t0. That probability is Wiener measure.

Facts & Assumptions

Given: AC, the uoc path space C=C([0,),R), and its coordinate maps πt.

[F1]

Wiener measure exists as a probability on B(C), and its coordinate process has the Brownian finite-dimensional distributions. A Brownian motion is equivalently a centered Gaussian process with covariance min(s,t), in addition to path continuity. Wiener measure on continuous path space Brownian motion The Axiom of Choice

[F2]

Gaussian processes with identical mean and covariance functions have identical finite-dimensional laws, including singular laws and repeated-time lists. Mean and covariance determine Gaussian finite-dimensional laws

[F3]

The Borel sigma-algebra of C is generated by the nonnegative rational coordinate maps. Borel sigma-algebra of continuous path space is generated by coordinates

[F4]

A lambda-system contains the whole space, relative differences of nested members, and increasing countable unions. Measures are continuous from below, and a lambda-system containing a pi-system contains the sigma-algebra generated by that pi-system. Lambda-systems, or Dynkin systems Continuity from below for measures Dynkin's pi-lambda theorem

Proof

technique · direct
1.1

By [F1], Wiener measure is a probability measure on B(C) and its coordinate process is centered Gaussian with covariance min(s,t). Thus at least one probability with the stated property exists. AC is used here through the normal-law and Brownian construction interfaces; the uniqueness argument below makes no further use of it.

F1
1.2

Let μ and ν be two probabilities with the stated property. By [F2], for every k1, every nonnegative rational list q1,,qk (with repetitions allowed), and Borel sets AiR, μi=1k{f:f(qi)Ai}=νi=1k{f:f(qi)Ai}. Indeed this is equality of the two finite-dimensional laws on the Borel rectangle A1××Ak. The same equality is trivial for the empty intersection C.

F2
2.1

Let P be the family of the finite intersections in step 1.2, including the empty intersection C. It is a pi-system because the intersection of two members is obtained by concatenating their two finite lists. Moreover σ(P)=B(C): the family contains every one-coordinate set πq1(A), while every member is a finite intersection of such sets; now apply [F3].

F3step 1.2construct
3.1

Put D={AB(C):μ(A)=ν(A)}. It contains C because both measures have total mass one. If AB and A,BD, finite additivity gives μ(BA)=μ(B)μ(A)=ν(B)ν(A)=ν(BA). If AnA with every AnD, continuity from below gives μ(A)=limnμ(An)=limnν(An)=ν(A). Hence D is a lambda-system. Step 1.2 says PD, so [F4] and step 2.1 give B(C)=σ(P)D. Thus μ=ν.

F4step 1.2step 2.1
4.1

Step 1.1 proves existence and step 3.1 proves uniqueness, so Wiener measure is exactly the asserted probability. The covariance at time zero is zero, singleton laws and singular repeated-time vectors are covered by [F2], and both directions of “exactly one” have been established.

step 1.1step 3.1F2

Source notes

Durrett constructs Wiener measure from Brownian finite-dimensional laws. The local proof supplies the rational-cylinder pi-system and the complete pi-lambda uniqueness argument.

Depends on

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Sources