Convergence Of Haar Pairings For Scalar Functions
ProvedFunctionalInequalities.KLS.LogConcave.tendsto_integral_mul_of_tendsto_readableThis theorem transfers scalar convergence to convergence of Haar integrals against compactly supported weights.
Let be a finite-dimensional real vector space with the stated Borel and topological structures, let be an additive Haar measure, let be a probability measure, and let be continuous with . Suppose and the classes of converge to . For every continuous compactly supported ,
This is a technical localization lemma used to pass limits through Haar integrals. No global integrability of the functions with respect to is required beyond what follows from the tilted-law and compact-support hypotheses.
Original Lean declaration header
Within namespace FunctionalInequalities.KLS.LogConcave. Shown in its original module context. Proof omitted.
theorem tendsto_integral_mul_of_tendsto (hνU : (ν : Measure V) = m.tilted (-U))
(hU : Continuous U) {g : ℕ → V → ℝ} (hg : ∀ n, MemLp (g n) 2 (ν : Measure V))
{f : Lp ℝ 2 (ν : Measure V)} (hlim : Tendsto (fun n => (hg n).toLp (g n)) atTop (𝓝 f))
{ψ : V → ℝ} (hψ : Continuous ψ) (hψc : HasCompactSupport ψ) :
Tendsto (fun n => ∫ x, g n x * ψ x ∂m) atTop (𝓝 (∫ x, f x * ψ x ∂m))
Module navigation
Module: KLS/LogConcave/WeightedGradient/Kernel.
Supporting theorems: integrable_exp_neg_of_eq_tilted, integral_eq_integral_mul_exp.
Previous: restrict_le_smul_of_eq_tilted · Next: tendsto_integral_mul_inner_of_tendsto.
Source excerpt, lines 148–152 · Frozen source 408915f.
import Definitions.Def_KLSModular_FunctionalInequalities_KLS_LogConcave_WeightedGradient_Kernel
open MeasureTheory Filter Topology InnerProductSpace
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V]
[MeasurableSpace V] [BorelSpace V] [SecondCountableTopology V] [FiniteDimensional ℝ V]
{ν : MeasureTheory.ProbabilityMeasure V} (m : MeasureTheory.Measure V) [m.IsAddHaarMeasure] {U : V → ℝ}
theorem FunctionalInequalities.KLS.LogConcave.tendsto_integral_mul_of_tendsto_readable (hνU : (ν : Measure V) = m.tilted (-U))
(hU : Continuous U) {g : ℕ → V → ℝ} (hg : ∀ n, MemLp (g n) 2 (ν : Measure V))
{f : Lp ℝ 2 (ν : Measure V)} (hlim : Tendsto (fun n => (hg n).toLp (g n)) atTop (𝓝 f))
{ψ : V → ℝ} (hψ : Continuous ψ) (hψc : HasCompactSupport ψ) :
Tendsto (fun n => ∫ x, g n x * ψ x ∂m) atTop (𝓝 (∫ x, f x * ψ x ∂m)) := by sorry