One-dimensional Gaussian logarithmic Sobolev inequality: for functions
ProvedGaussianMatrix.gaussian_logsobolev_one_dimLet be the standard Gaussian measure on . Let be continuously differentiable, and assume that , and are -integrable (with the convention ). Then
The left-hand side is the entropy of the nonnegative function .
This is Gross's logarithmic Sobolev inequality for the Gaussian measure in dimension one, with the sharp constant . Together with the tensorization of entropy it yields the inequality on (gaussian_logsobolev), which in turn gives the entropy bound for Lipschitz used in Herbst's argument. It is the only analytic input of the whole chain that is not elementary.
Formalization Note. The derivative is deriv g, and is ContDiff ℝ 1 g. The integrability hypotheses guarantee that all Bochner integrals in the statement are the true (finite) integrals; Real.log 0 = 0 matches the convention . The hypotheses on and are in fact consequences of the others (Gaussian Poincaré inequality and the inequality itself) but are included to keep the statement transparent. Constant gives .
import Definitions.Def_GaussianMatrix_basic open MeasureTheory ProbabilityTheory open scoped Matrix
namespace GaussianMatrix
theorem gaussian_logsobolev_one_dim (g : ℝ → ℝ) (hg : ContDiff ℝ 1 g)
(hg2 : Integrable (fun t => g t ^ 2) (gaussianReal 0 1))
(hglog : Integrable (fun t => g t ^ 2 * Real.log (g t ^ 2)) (gaussianReal 0 1))
(hdg : Integrable (fun t => deriv g t ^ 2) (gaussianReal 0 1)) :
∫ t, g t ^ 2 * Real.log (g t ^ 2) ∂(gaussianReal 0 1)
- (∫ t, g t ^ 2 ∂(gaussianReal 0 1)) * Real.log (∫ t, g t ^ 2 ∂(gaussianReal 0 1))
≤ 2 * ∫ t, deriv g t ^ 2 ∂(gaussianReal 0 1) := by
sorry
end GaussianMatrix