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DefinitionDefinition: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-14
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d-dimensional Brownian motion

Definition

Assume the Axiom of Choice and let d1 be a finite integer. An Rd-valued process B=(Bt)t0 is a standard d-dimensional Brownian motion if:

  1. B0=0 almost surely;
  2. for every finite list 0=t0<t1<<tn, the vector increments BtjBtj1,1jn, are mutually independent and have laws Nd(0,(tjtj1)Id); and
  3. there is one measurable event A with P(A)=1 such that tBt(ω) is continuous from [0,) to Rd for every ωA.

Equivalently, its d coordinate processes Bα=(Btα)t0 are independent standard one-dimensional Brownian motions. Here independence of the processes means the following precise assertion. Put I=[0,) and equip RI with its cylinder sigma-algebra. The maps Φα:ΩRI,Φα(ω)(t)=Btα(ω),1αd, are independent random elements.

Facts & Assumptions

Given: AC, a finite integer d1, and an Rd-valued process B=(Bt)t0.

[F1]

Standard one-dimensional Brownian motion starts at zero, has independent normal increments on every finite increasing time list, and has one common probability-one continuity event. Brownian motion

[F2]

Under AC, Nd(m,Σ) exists for every positive semidefinite Σ, is realized as m+Σ1/2Z with independent standard-normal coordinates, and is determined by the characteristic function exp(iumuTΣu/2), including when Σ is singular. Multivariate normal law, including singular covariance Characteristic function of a multivariate normal law

[F3]

Scalar normal characteristic functions and characteristic functions of finite independent sums have their usual formulas. Characteristic function of a normal law Characteristic functions under affine maps and independent sums

[F4]

Independence of random elements is characterized by finite rectangle probabilities. Disjoint groups of an independent sigma-algebra family remain independent, and measurable coordinatewise functions preserve independence. Independent random elements Independent random elements are characterized by finite rectangle probabilities Disjoint groups of an independent sigma-algebra family remain independent Measurable coordinatewise functions preserve independence

[F5]

Finite-coordinate cylinders generate the cylinder sigma-algebra and form a pi-system; independent pi-systems containing the whole space generate independent sigma-algebras. Coordinate maps, finite-coordinate cylinders, and the cylinder σ-algebra Finite-coordinate cylinders form a π-system Independent pi-systems generate independent sigma-algebras

[F6]

Continuity of a map into finite-dimensional Euclidean space is equivalent to continuity of all its coordinates. A finite intersection of probability-one events has probability one. A vector-valued function has a limit, or is continuous, if and only if each of its components does; with the algebra of continuous vector-valued functions Basic identities for a probability measure

[F7]

AC supplies the normal-law and Brownian interfaces used above. The Axiom of Choice

Proof

technique · direct proof of the asserted equivalence
1.1

We first record the diagonal-Gaussian fact used in both directions. If XNd(0,hId) for h0, [F2] realizes that law as hZ, where the coordinates of Z are independent standard normals. Equality of vector laws preserves every rectangle probability, so the coordinates of X are independent and each has law N(0,h). This includes h=0, when every coordinate is the constant zero variable.

F2F4
1.2

Conversely, suppose that X1,,Xd are independent and each has law N(0,h). For uRd, [F3] gives EeiuX=α=1dEeiuαXα=exp ⁣(h2α=1duα2). This is the characteristic function of the existing law Nd(0,hId) by [F2], and the uniqueness clause of [F2] identifies the vector laws. Thus XNd(0,hId). For d=1 this says exactly that N1(0,h) is the scalar N(0,h) law; for h=0 both sides are the point mass at zero.

F2F3
1.3

Each Φα in the Definition is a random element: for every finite FI, the finite observation map ω(Btα(ω))tF is measurable because the inverse image of each coordinate generator is measurable. Therefore the inverse images of all finite-coordinate cylinders, and hence of their generated cylinder sigma-algebra, are measurable.

F5
2.1

Assume first that B satisfies the three vector clauses of the Definition. Fix 0=t0<<tn and put Zj=BtjBtj1. The random vectors Zj are independent, and by step 1.1 the coordinates (Zjα)α=1d within each fixed j are independent N(0,tjtj1) variables. Hence, for arbitrary Borel sets Aj,αR, P ⁣(j=1nα=1d{ZjαAj,α})=j=1nP ⁣(Zjα=1dAj,α)=j=1nα=1dP(ZjαAj,α). The rectangle criterion [F4] therefore makes the whole finite family (Zjα)j,α mutually independent.

step 1.1F4
3.1

For a fixed α, step 2.1 gives independent increments with the required scalar normal laws. The vector condition at time zero gives B0α=0 almost surely. On the vector continuity event every coordinate path is continuous by [F6]. Consequently each Bα is standard one-dimensional Brownian motion by [F1].

F1F6step 2.1
3.2

For each α, let Πα be the pullbacks by Φα of finite-coordinate cylinders. These classes are pi-systems containing Ω by [F5], and σ(Πα)=σ(Φα). To check their independence, choose one cylinder from every member of any finite subfamily of the coordinates and take the sorted union of their finitely many time supports, adjoining time zero. On the probability-one event {B0=0}, each coordinate's finite observation vector equals a measurable affine function of its own block of scalar increments. Thus its cylinder probabilities equal those of that affine function. Step 2.1 makes all scalar increments independent; [F4] first groups them by α and then preserves independence under these measurable affine maps. The chosen cylinder probabilities therefore factor. Thus the pi-systems Πα are independent, and [F5] makes the full random elements Φ1,,Φd independent. This proves the forward implication. Empty-support cylinders give Ω or and obey the same formula.

givenF4F5step 2.1step 1.3
3.3

Conversely, assume that the random elements Φ1,,Φd are independent and that every Bα is a standard one-dimensional Brownian motion. Fix 0=t0<<tn and let Uα=(BtjαBtj1α)j=1n. This is a measurable function of Φα, so [F4] makes U1,,Ud independent. Within each Uα, the scalar Brownian increments are independent and the jth has law N(0,tjtj1) by [F1]. For arbitrary Borel Aj,α, the same two-stage rectangle calculation as in step 2.1, now first over α and then over j, gives P ⁣(α=1dj=1n{Uα,jAj,α})=α=1dj=1nP(Uα,jAj,α). Hence all the scalar variables Uα,j are mutually independent.

F1F4
4.1

Group the independent scalar variables of step 3.3 by their time index j. By [F4], the resulting sigma-algebras are independent. Each vector increment Zj=(U1,j,,Ud,j)=BtjBtj1 is measurable with respect to the jth grouped sigma-algebra, so the vectors Z1,,Zn are independent. For fixed j, its coordinates are independent N(0,tjtj1) variables; step 1.2 therefore gives ZjNd(0,(tjtj1)Id).

F4step 1.2step 3.3
5.1

For every α, let Cα be a probability-one event on which the path Bα is continuous, and let Eα={B0α=0}. Because d is finite, repeated finite subadditivity in [F6] gives P ⁣(α=1d(CαEα))=1. On this one event, B0=0 and the vector path is continuous by the coordinatewise criterion [F6]. Together with step 4.1 this proves the three vector clauses, and hence the reverse implication.

F1F6step 4.1
6.1

The empty increment list is vacuous; a one-increment list is covered by steps 2.1 and 4.1; repeated times and zero-length increments are excluded by the strictly increasing convention, while time zero and the singular zero-variance law are handled in steps 1.1, 1.2, 3.1, and 5.1. The assumption d1 excludes the empty-coordinate process. AC is used through [F1]--[F3] for the normal-law and Brownian interfaces and their law uniqueness; the finite regrouping, cylinder, and continuity arguments add no further choice.

F1F2F3F7step 1.1step 1.2step 2.1step 3.1step 1.3step 3.2step 3.3step 4.1step 5.1

Source notes

Yoshida Definition 6.1.1 gives the vector-increment definition, Lemma 6.1.3 identifies diagonal multivariate-normal increments with the scalar-coordinate increment family, and Proposition 6.1.4 states the coordinate-process equivalence. The proof above supplies the cylinder-sigma-algebra promotion needed for the word “independent” to apply to whole coordinate processes. Sousi Section 6.2 constructs the vector process from independent scalar Brownian motions.

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