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Wiener measure on continuous path space

Definition

Assume the Axiom of Choice. Let B be a continuous Brownian motion supplied by the existence theorem, and let A be one measurable probability-one event on which all of its sample paths are continuous. Redefine B~t(ω)={Bt(ω),ωA,0,ωA. and set W(ω)(t)=B~t(ω). Then W is a Borel random element of C([0,),R) with its uniform-on-compacts topology. Its law W=PW1 is called Wiener measure. It is a probability measure and its coordinate process has the Brownian finite-dimensional distributions.

Facts & Assumptions

Given: AC, a Brownian motion B, and its common measurable continuity event A as in the Definition.

[F1]

Under AC, a continuous Brownian motion exists together with one measurable probability-one event on which every one of its sample paths is continuous. Existence of continuous Brownian motion Brownian motion The Axiom of Choice

[F2]

The uoc formula is a metric inducing compact convergence, and this path space is Polish and therefore separable. Uniform-on-compacts metric on continuous path space Under countable choice, continuous path space is Polish Separability: the existence of an at most countable dense subset

[F3]

Countable suprema and pointwise limits of measurable real or extended-real functions are measurable; sums, scalar multiples, positive parts, and absolute values preserve measurability. Sequential suprema, infima, limsup, liminf, and pointwise limits of measurable functions are measurable Closure properties of measurable functions used by the integral

[F4]

The rationals are countable, and between any two nonnegative reals lies a nonnegative rational. Thus Q[0,) is dense in [0,) with its relative topology. Q is countably infinite The rationals embed densely in the reals

[F6]

A measurable map into a measurable space is a random element, and its law is a probability measure. Random elements and real random variables The law of a random element is a probability measure

Verification

technique · direct
1.1

By [F1], fix B and A as in the Definition. Every path W(ω) is continuous: on A it is a Brownian path, and off A it is the zero path. For fixed t, B~t is measurable because for each Borel E, its inverse image is (A{BtE}) together with Ac exactly when 0E.

givenF1
2.1

Fix fC([0,),R) and n1. By path continuity and density [F4], Mn,f(ω):=max0tnW(ω)(t)f(t)=supqQ[0,n]B~q(ω)f(q). Enumerate the countable rational set once. Each function under the supremum is measurable by step 1.1 and [F3], so [F3] makes Mn,f measurable and finite.

step 1.1F3F4
3.1

By [F3], every finite partial sum DN,f=n=1N2n(1Mn,f) is measurable; here 1M=1(1M)+. The partial sums converge pointwise to duoc(W,f) by [F2], so [F3] makes that distance measurable. Therefore the inverse image under W of every open metric ball is measurable. By separability in [F2], fix a countable dense D; the balls with centers in D and positive rational radii form a countable basis, by the metric triangle inequality and rational density, and [F5] makes every subfamily countable. Every open set is therefore a countable union of such balls. Since open sets generate the Borel sigma-algebra by [F5], W is Borel measurable and hence a random element by [F6].

step 2.1F2F3F4F5F6
4.1

By [F6], W=PW1 is a probability measure. For any finite times t1,,tk, the vectors (B~tj)j=1k and (Btj)j=1k agree on A, hence almost surely, so their laws coincide. The coordinate vector (πtj)j=1k under W has exactly the former law by the pushforward definition. Thus the coordinate process under Wiener measure has every Brownian finite-dimensional law. Empty tuples have the unit law and π0=0 almost surely.

step 1.1step 3.1F6
5.1

The zero path used on Ac is fixed and canonical. AC is used only through [F1] to obtain the normal-law construction and Brownian process; redefining a given process on its one supplied null event, taking fixed rational suprema, and pushing forward use no further choice.

step 1.1step 4.1F1

Source notes

Durrett and Sousi construct Brownian motion from its finite-dimensional laws. The verification supplies the path-map measurability required before its law on continuous path space may honestly be called Wiener measure.

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