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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 Cov⁡μ(πs,πt)=min⁡(s,t),s,t≥0. 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
1.1F1

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.

1.2F2

Let μ and ν be two probabilities with the stated property. By [F2], for every k≥1, every nonnegative rational list q1,…,qk (with repetitions allowed), and Borel sets Ai⊆R, μ⋂i=1k{f:f(qi)∈Ai}=ν⋂i=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.

2.1F3step 1.2construct

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 πq−1(A), while every member is a finite intersection of such sets; now apply [F3].

3.1F4step 1.2step 2.1

Put D={A∈B(C):μ(A)=ν(A)}. It contains C because both measures have total mass one. If A⊆B and A,B∈D, finite additivity gives μ(B∖A)=μ(B)−μ(A)=ν(B)−ν(A)=ν(B∖A). If An↑A with every An∈D, continuity from below gives μ(A)=lim⁡nμ(An)=lim⁡nν(An)=ν(A). Hence D is a lambda-system. Step 1.2 says P⊆D, so [F4] and step 2.1 give B(C)=σ(P)⊆D. Thus μ=ν.

4.1step 1.1step 3.1F2∎

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.

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.

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Sources