TheoremBase

On Integrals of Cylindrical Functions the Gaussian Score Drift is the Noise Ornstein-Uhlenbeck Functional, and the Score-Drift Hamilton-Jacobi Operator Takes Its Pointwise Form

On integrals of bounded C2C^2 cylindrical functions, the score drift of the Gaussian entropy pair equals beta times the noise Ornstein-Uhlenbeck functional, so the Hamilton-Jacobi operator with Gaussian score drift takes an explicit pointwise form.

Statement

In the setting of A Diagonal Gaussian Reference Measure on the Noise Wasserstein Space, Rescaled Heads and Gaussian Tails: Standing Notation, so that the reference measure is ρ=γc\rho=\gamma_{c}, let β\beta and κ\kappa be positive real numbers with ck≤κ akc_{k}\le\kappa\,a_{k} for every k∈Nk\in\mathbb{N}, and let (D,DΣ,E,Σ)(\mathcal{D},\mathcal{D}_{\Sigma},\mathcal{E},\Sigma) be the Gaussian entropy pair with temperature β\beta, whose hypothesis holds with this κ\kappa. Let n∈Nn\in\mathbb{N}, let f∈Cb2(Rn)f\in C^{2}_{b}(\mathbb{R}^{n}), the set of Bounded Twice Continuously Differentiable Functions with Bounded First and Second Partial Derivatives on Euclidean Space §bounded with q=nq=n, with partial derivatives ∂kf\partial_{k}f and ∂k∂kf\partial_{k}\partial_{k}f as in Differential Calculus and Convexity on Euclidean Open Sets: Standing Notation §derivatives, let φ=f∘pn\varphi=f\circ p_{n}, and let UφU_{\varphi}, ∇aφ\nabla_{a}\varphi and ∇Uφ\nabla U_{\varphi} be as in Integrals of Bounded C^2 Cylindrical Functions are Noise Intrinsic Test Functions with the Noise Gradient as Gradient. Here DΣ⊆D⊆Pρa\mathcal{D}_{\Sigma}\subseteq\mathcal{D}\subseteq\mathcal{P}^{a}_{\rho} and D⊆P2(X)\mathcal{D}\subseteq\mathcal{P}_{2}(X) by The Gaussian Entropy Pair on the Noise Wasserstein Space: Relative Entropy and the Noise Score Field §penalty-domain and The Gaussian Entropy Pair on the Noise Wasserstein Space: Relative Entropy and the Noise Score Field §score-domain, so that for μ∈D\mu\in\mathcal{D} the noise Ornstein-Uhlenbeck functional Lμa(f)L^{a}_{\mu}(f) of μ\mu at ff is defined. ⟨⋅,⋅⟩μ\langle\cdot,\cdot\rangle_{\mu} is the inner product of L2(μ;Xa)L^{2}(\mu;X^{a}).

1. (Test function) UφU_{\varphi} is a noise intrinsic test function on D\mathcal{D}, and ∇Uφ(μ)=∇aφ\nabla U_{\varphi}(\mu)=\nabla_{a}\varphi for every μ∈D\mu\in\mathcal{D}, by Integrals of Bounded C^2 Cylindrical Functions are Noise Intrinsic Test Functions with the Noise Gradient as Gradient §test and Integrals of Bounded C^2 Cylindrical Functions are Noise Intrinsic Test Functions with the Noise Gradient as Gradient §gradient.

2. (The score drift is the Ornstein-Uhlenbeck generator) For every μ∈DΣ\mu\in\mathcal{D}_{\Sigma},

⟨Σ(μ),∇Uφ(μ)⟩μ=β Lμa(f)=β∑k=1nak∫X(xkck ∂kf(pn(x))−∂k∂kf(pn(x)))μ(dx).\langle\Sigma(\mu),\nabla U_{\varphi}(\mu)\rangle_{\mu}=\beta\,L^{a}_{\mu}(f)=\beta\sum_{k=1}^{n}a_{k}\int_{X}\Bigl(\frac{x_{k}}{c_{k}}\,\partial_{k}f(p_{n}(x))-\partial_{k}\partial_{k}f(p_{n}(x))\Bigr)\mu(dx).

3. (The Gaussian-score-drift operator on integrals) Let λ0,θ∈R\lambda_{0},\theta\in\mathbb{R} be positive, let g:D→Rg:\mathcal{D}\to\mathbb{R}, and let FF be the Hamilton-Jacobi operator with Gaussian score drift relative to γc\gamma_{c} with temperature β\beta, discount λ0\lambda_{0}, control cost θ\theta and running cost gg. Then for every μ∈DΣ\mu\in\mathcal{D}_{\Sigma} and r∈Rr\in\mathbb{R} the pair (μ,∇Uφ(μ))(\mu,\nabla U_{\varphi}(\mu)) belongs to the bundle Va(DΣ)\mathcal{V}^{a}(\mathcal{D}_{\Sigma}) of noise fields over DΣ\mathcal{D}_{\Sigma}, on which FF is defined, and

F(μ,r,∇Uφ(μ))=λ0 r+θ2∑k=1nak∫X∂kf(pn(x))2 μ(dx)+β Lμa(f)−g(μ).F\bigl(\mu,r,\nabla U_{\varphi}(\mu)\bigr)=\lambda_{0}\,r+\frac{\theta}{2}\sum_{k=1}^{n}a_{k}\int_{X}\partial_{k}f(p_{n}(x))^{2}\,\mu(dx)+\beta\,L^{a}_{\mu}(f)-g(\mu).

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