Math 2.0

Measure and integration Definition

Abstract Wiener space

Builds on Hilbert spaceBanach spaceSeparable spaceContinuous linear mapProbability measurePushforward measureNormal distributionGaussian measureCylinder set measureClassical Wiener space

Definition

Let HH be a real separable Hilbert space with inner product ⟨⋅,⋅⟩\ip{\cdot}{\cdot} and norm ∥⋅∥H\norm{\cdot}_H. Let EE be a real separable Banach space with dual space E∗E^*. Let i ⁣:H→Ei \colon H \to E be an injective continuous linear map with dense image. For ℓ∈E∗\ell \in E^*, let i∗ℓ∈Hi^* \ell \in H be the vector with ⟨i∗ℓ,h⟩=ℓ(ih)\ip{i^* \ell}{h} = \ell(i h) for all h∈Hh \in H. The triple (i,H,E)(i, H, E) is an abstract Wiener space if there is a Borel probability measure μ\mu on EE with the following property. For every ℓ∈E∗\ell \in E^*, the pushforward ℓ∗μ\ell_* \mu is the centered normal distribution with variance ∥i∗ℓ∥H2\norm{i^* \ell}_H^2.

Remarks

The measure μ\mu is unique, and it is called the abstract Wiener measure; it is a centered Gaussian measure. Equivalently, the image under ii of the canonical Gaussian cylinder set measure of HH extends to a countably additive measure on EE. Conversely, every centered Gaussian measure on a separable Banach space arises in this way, with HH its Cameron–Martin space.

Example: let E=C0([0,1])E = C_0([0, 1]) be the classical Wiener space with the sup norm. Let HH be the space of absolutely continuous h∈Eh \in E with h′∈L2h' \in L^2, with ⟨h,k⟩=∫01h′k′ dt\ip{h}{k} = \int_0^1 h' k' \, dt, and let ii be the inclusion. With μ\mu the Wiener measure, take ℓ(ω)=ω(t)\ell(\omega) = \omega(t). Then i∗ℓi^* \ell is s↦min⁡(s,t)s \mapsto \min(s, t), whose norm squared is tt, and indeed ω(t)\omega(t) has law N(0,t)N(0, t).

Non-example: let E=HE = H be infinite-dimensional and ii the identity. For an orthonormal sequence (ek)(e_k), the readings ⟨x,ek⟩\ip{x}{e_k} would be independent standard normal variables under μ\mu. Then ∑k⟨x,ek⟩2=∞\sum_k \ip{x}{e_k}^2 = \infty almost surely, which is impossible for x∈Hx \in H, so no such μ\mu exists.

Reading path

To understand this page from the ground up, read these 11 pages in order. The foundations come first.

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Each page uses the pages above it. The colour of the bar on a box shows how strong the evidence is, and the box also gives it as text. The list has the same pages.
  • no evidence level
  1. Banach space concept
  2. Classical Wiener space object
  3. Continuous linear map concept
  4. Cylinder set measure concept
  5. Gaussian measure concept
  6. Hilbert space concept
  7. Normal distribution concept
  8. Probability measure concept
  9. Pushforward measure concept
  10. Separable space concept
  11. Abstract Wiener space definition

Further reading

  1. Web https://en.wikipedia.org/wiki/Abstract_Wiener_space
About this page
TagZ4ZM26BJHN
URIm2://Z4ZM26BJHN
Kinddefinition
WritingW0 stub
MSC28C20, 60B11, 46G12
DefinesAbstract Wiener space
UsesHilbert space, Banach space, Separable space, Continuous linear map, Probability measure, Pushforward measure, Normal distribution, Gaussian measure, Cylinder set measure, Classical Wiener space
Changed2 November 2026

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