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Wiener measure on continuous path space
Definition
Assume the Axiom of Choice. Let be a continuous Brownian motion supplied by the existence theorem, and let be one measurable probability-one event on which all of its sample paths are continuous. Redefine and set Then is a Borel random element of with its uniform-on-compacts topology. Its law 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 , and its common measurable continuity event as in the Definition.
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
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
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
The rationals are countable, and between any two nonnegative reals lies a nonnegative rational. Thus is dense in with its relative topology. is countably infinite The rationals embed densely in the reals
Metric balls generate the metric topology, whose Borel sigma-algebra is generated by its open sets. Products and subsets of countable sets are countable. The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement The Borel sigma-algebra of a topological space A product of two at most countable sets is at most countable Every subset of an at most countable set is at most countable
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
By [F1], fix and as in the Definition. Every path is continuous: on it is a Brownian path, and off it is the zero path. For fixed , is measurable because for each Borel , its inverse image is together with exactly when .
Fix and . By path continuity and density [F4], Enumerate the countable rational set once. Each function under the supremum is measurable by step 1.1 and [F3], so [F3] makes measurable and finite.
By [F3], every finite partial sum is measurable; here . The partial sums converge pointwise to by [F2], so [F3] makes that distance measurable. Therefore the inverse image under of every open metric ball is measurable. By separability in [F2], fix a countable dense ; the balls with centers in 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], is Borel measurable and hence a random element by [F6].
By [F6], is a probability measure. For any finite times , the vectors and agree on , hence almost surely, so their laws coincide. The coordinate vector under 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 almost surely.
The zero path used on 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.
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.
Depends on
- Existence of continuous Brownian motion
- Brownian motion
- 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
- Random elements and real random variables
- The law of a random element is a probability measure
- Sequential suprema, infima, limsup, liminf, and pointwise limits of measurable functions are measurable
- Closure properties of measurable functions used by the integral
- $\mathbb{Q}$ is countably infinite
- The rationals embed densely in the reals
- A product of two at most countable sets is at most countable
- Every subset of an at most countable set is at most countable
- The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement
- The Borel sigma-algebra of a topological space
- The Axiom of Choice
Used by
- Existence and scaling of d-dimensional Brownian motion Corollary
- Brownian scaling Theorem
- Uniqueness of Wiener measure Theorem
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Sources
- Rick Durrett, Probability: Theory and Examples, Section 7.1 (standard reference, not scraped)
- Perla Sousi, Advanced Probability, Section 6.2 (standard reference, not scraped)