Samplinglib
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2.1 · Book p. 48 · PDF p. 60

Overview of the Inequalities

Places Poincaré, log-Sobolev, transport, concentration, and isoperimetric inequalities in one comparison map.

Open this section in the canonical August 9 source ↗
Formal topologyOpen this section in the underlying Lean graph
Why is this valid?

Each inequality needs an explicit function class and finite terms; extension beyond a smooth compactly supported core requires a closure or density argument.

Source assumptions

  • probability reference law
  • regular test functions or densities

Formal assumptions

  • explicit measure
  • probability normalization for the Poincare interface
  • finite entropy/energy terms
  • explicit function class
View Lean formalization
partial · faithful paraphrase

ASTIS separates the probability-law and density prerequisites from the analytic inequality and its semigroup consumers.

AutoSamplingTheory.lsiKlFiSqrtDensityFisherChainIntegralHandoffScalar

compiled Samplinglib leaf · AutoSamplingTheory/Probability.lean:861
theorem lsiKlFiSqrtDensityFisherChainIntegralHandoffScalar
    {α ι : Type*} [MeasurableSpace α] [Fintype ι] (mu : Measure α)
    {r : α → Real} {dirichlet fisher : Real} {dr dSqrt dLog : ι → α → Real}
    (hdirichlet : dirichlet = ∫ x, (∑ i, dSqrt i x ^ 2) ∂mu)
    (hfisher : fisher = ∫ x, (r x * ∑ i, dLog i x ^ 2) ∂mu)
    (hr : ∀ᵐ x ∂mu, 0 < r x)
    (hdSqrt : ∀ᵐ x ∂mu,
      ∀ i, dSqrt i x = (1 / (2 * Real.sqrt (r x))) * dr i x)
    (hdLog : ∀ᵐ x ∂mu, ∀ i, dLog i x = dr i x / r x) :
    dirichlet = (1 / 4) * fisher := by
  rw [hdirichlet, hfisher]
  rw [← integral_const_mul]
  exact lsiKlFiSqrtDensityFisherChainIntegralFiniteSum mu hr hdSqrt hdLog

/-- Scalar rearrangement behind the one-sided use of the cited DV formula.

This is not a proof of Donsker--Varadhan.  It starts after a cited or
eventually formalized entropy-duality theorem has supplied the variational
upper bound for an admissible test.
-/
Imports
  • Mathlib.Data.Real.Basic
  • Mathlib.Algebra.Order.Archimedean.Real.Basic
  • Mathlib.Analysis.Real.Sqrt
  • Mathlib.Analysis.Calculus.ParametricIntegral
  • Mathlib.Analysis.SpecialFunctions.Log.Basic
  • Mathlib.InformationTheory.KullbackLeibler.Basic
  • Mathlib.MeasureTheory.Measure.LogLikelihoodRatio
  • Mathlib.MeasureTheory.Measure.Tilted
  • Mathlib.Probability.Kernel.Condexp
  • Mathlib.Probability.Moments.IntegrableExpMul
  • AutoSamplingTheory.Core
Local dependencies

Downstream consumers

  • semigroup convergence
  • sampling complexity
Official Chapter 2 supplement. Chewi's supp.pdf contains the omitted tensorization, concentration, Gozlan, metric-measure-space, synthetic-Ricci-curvature, and exercise material. See the complete structured supplement map →