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Exact Ornstein–Uhlenbeck momentum transition and covariance

Statement

For the O subproblem dPt=−γPt dt+2γβ−1M1/2dWt over a step h>0, with P0 measurable at the start of the step and Brownian increments independent of the starting sigma algebra, Ph=e−γhP0+β−1(1−e−2γh) M1/2ξ, where ξ∼Nd(0,Id) is independent of the starting sigma algebra. In particular, conditionally on P0, the transition is Gaussian with mean e−γhP0 and covariance β−1(1−e−2γh)M.

Facts & Assumptions

Given: The model data in Underdamped Langevin equation and canonical Gibbs density, a deterministic step h>0, and the O subproblem.

[F1]

Underdamped Langevin equation and canonical Gibbs density: M is symmetric positive definite and the O subproblem has friction γ and noise covariance 2γβ−1M.

[F2]

Deterministic Ito integrals are Gaussian: a finite vector of deterministic It^o integrals against Brownian increments is jointly centered Gaussian, with covariance entries given by the integrals of products of their deterministic integrands; future increments are independent of the starting sigma algebra.

[F3]

Multidimensional Ito formula for Brownian-driven processes: the It^o product rule applies to a continuously differentiable deterministic scalar factor times a Brownian It^o process.

[F4]

A non-negative operator has a unique non-negative square root: M has a unique symmetric positive square root.

[A1]

The Axiom of Choice: AC is inherited from the deterministic It^o integral and Gaussian-law interfaces [F2]; no further choice is used.

Proof

Given: The assumptions above.

1.1F1F2F3A1givenalgebra

Put S=2γβ−1M1/2. Multiplying the O equation by the deterministic integrating factor eγt and applying [F3] componentwise gives d(eγtPt)=eγtS dWt. Integrating from 0 to h and multiplying by e−γh yields [F1, F2, F3, A1, given, algebra] Ph=e−γhP0+∫0he−γ(h−s)S dWs. The integrand is deterministic and square-integrable. By [F2] the integral is centered Gaussian, independent of the starting sigma algebra, with covariance ∫0he−2γ(h−s)SST ds=2γβ−1M∫0he−2γ(h−s)ds=β−1(1−e−2γh)M.

2.1F1F2F4step 1.1givenalgebra∎

By [F4], the displayed covariance has square root β−1(1−e−2γh)M1/2. A centered Gaussian vector with this covariance has the same law as that matrix times ξ∼Nd(0,Id); [F2] gives independence from the starting sigma algebra. This proves the exact transition and conditional moments.

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