Math 2.0

Probability theory and stochastic processes Brownian motion Object

Classical Wiener space

Description

Let T>0T > 0 and n≥1n \ge 1. The classical Wiener space is the set C0([0,T];ℝn)={w ⁣:[0,T]→ℝn:w continuous, w(0)=0},C_0([0, T]; \R^n) = \set{w \colon [0, T] \to \R^n : w \text{ continuous}, \ w(0) = 0}, with the norm ∥w∥=sup⁡0≤t≤T∣w(t)∣\norm{w} = \sup_{0 \le t \le T} \abs{w(t)} and the Wiener measure μ\mu. The Wiener measure is the unique Borel probability measure on this space under which the coordinate process Wt(w)=w(t)W_t(w) = w(t) is an nn-dimensional Wiener process on [0,T][0, T].

Check that C0([0,T];ℝn)C_0([0, T]; \R^n) is a Banach space:

  1. It is a vector space, and ∥⋅∥\norm{\cdot} is a norm on it, since a continuous function on a compact interval is bounded.
  2. A Cauchy sequence for ∥⋅∥\norm{\cdot} converges uniformly to a function ww; a uniform limit of continuous functions is continuous, and w(0)=0w(0) = 0.

It is also separable: piecewise linear paths with rational vertices are dense.

Remarks

The Wiener measure is the law of Brownian motion, seen as a random element of the path space. The Cameron–Martin space is the subspace of absolutely continuous paths hh with h(0)=0h(0) = 0 and ∫0T∣h′(t)∣2 dt<∞\int_0^T \abs{h'(t)}^2 \, dt < \infty. Translations of μ\mu by elements of the Cameron–Martin space give measures equivalent to μ\mu, but the Cameron–Martin space itself has μ\mu-measure zero. The space is the standard setting of Malliavin calculus.

Where this leads

4 pages build on this one.

Further reading

  1. Web https://en.wikipedia.org/wiki/Classical_Wiener_space
About this page
Tag5Z00K7K1HY
URIm2://5Z00K7K1HY
Kindobject
WritingW0 stub
MSC60J65, 28C20
Instance ofBanach space
Same as
Changed2 November 2026

Markdown · JSON · Edit on GitHub

What this page needs for W1

  • an inventory row: the row of the inventory that the node accounts for (0 of 1)
  • a source with a locator (0 of 1)

The writing levels say how complete the text of a page is. They do not measure its truth.

What links here

Used by

Results about this