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Finite Fisher Information, the Score and the Fisher Information of a Probability Measure

A probability measure with finite second moment has finite Fisher information when the integral of the Laplacian of every test function is bounded by a constant times the L2(mu)−normL^2(mu)-norm of its gradient (the dual form of the classical condition); its score is then the unique element of the tangent space representing minus the integral of the Laplacian against gradients of test functions, and its Fisher information is the squared L2(mu)−normL^2(mu)-norm of the score, which for positive C1C^1 densities is compared with the classical integral of |grad m|^2/m in the density lemma.

Statement

In the setting of Square-Integrable Vector Fields Against a Probability Measure on Euclidean Space, and Test Functions: Standing Notation, let μ∈P2(Rd)\mu\in\mathcal{P}_{2}(\mathbb{R}^{d}), with L2(μ;Rd)L^{2}(\mu;\mathbb{R}^{d}), test functions, gradients and Laplacians and tangent space TμT_{\mu} as fixed there. The symbol I\mathcal{I} always denotes the Fisher information, never the quadratic cost II of The Wasserstein Space and Its Lift to Square-Integrable Random Vectors: Standing Notation (iv).

1. (Finite Fisher information) The measure μ\mu has finite Fisher information if there is a real number C≥0C\ge0 such that

∣∫RdΔψ dμ∣≤C ∥∇ψ∥μfor every ψ∈Cc∞(Rd).\Bigl|\int_{\mathbb{R}^{d}}\Delta\psi\,d\mu\Bigr|\le C\,\lVert\nabla\psi\rVert_{\mu}\qquad\text{for every }\psi\in C_{c}^{\infty}(\mathbb{R}^{d}).

The set of all μ∈P2(Rd)\mu\in\mathcal{P}_{2}(\mathbb{R}^{d}) with finite Fisher information is denoted P2I(Rd)\mathcal{P}_{2}^{\mathcal{I}}(\mathbb{R}^{d}).

2. (Score) Let μ∈P2I(Rd)\mu\in\mathcal{P}_{2}^{\mathcal{I}}(\mathbb{R}^{d}). The score of μ\mu is the unique ξμ∈Tμ\xi_{\mu}\in T_{\mu} such that

⟨ξμ,∇ψ⟩μ=−∫RdΔψ dμfor every ψ∈Cc∞(Rd).\langle\xi_{\mu},\nabla\psi\rangle_{\mu}=-\int_{\mathbb{R}^{d}}\Delta\psi\,d\mu\qquad\text{for every }\psi\in C_{c}^{\infty}(\mathbb{R}^{d}).

It exists and is unique by Basic Properties of the Tangent Space: Closed Subspace, the Identity Map Belongs to It, Second-Moment Limits, and Representation of Bounded Functionals on Gradients (iv), applied to ℓ(ψ)=−∫RdΔψ dμ\ell(\psi)=-\int_{\mathbb{R}^{d}}\Delta\psi\,d\mu: this ℓ\ell is linear in ψ\psi by The Gradient of a Test Function is Bounded and Square-Integrable, and Its Laplacian Bounded and Integrable, Against Every Probability Measure (iii) and the linearity of the integral (claim 2 of Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion), and, for any CC as in clause 1, ∣ℓ(ψ)∣=∣∫RdΔψ dμ∣≤C∥∇ψ∥μ|\ell(\psi)|=\bigl|\int_{\mathbb{R}^{d}}\Delta\psi\,d\mu\bigr|\le C\lVert\nabla\psi\rVert_{\mu} by claim 2 of Properties of the Absolute Value in an Ordered Field.

3. (Fisher information) For μ∈P2I(Rd)\mu\in\mathcal{P}_{2}^{\mathcal{I}}(\mathbb{R}^{d}), the Fisher information of μ\mu is the nonnegative real number

I(μ)=∥ξμ∥μ2.\mathcal{I}(\mu)=\lVert\xi_{\mu}\rVert_{\mu}^{2}.

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