Leibniz Rule For The Closed Weighted Gradient
ProvedFunctionalInequalities.KLS.LogConcave.exists_mem_domain_closedWeightedOperator_toLp_mul_readableThis theorem extends the product rule to every element of the closed weighted-gradient domain.
Let be finite-dimensional with the stated structures, let be an additive Haar measure, let be log-concave with nonempty interior support, and let be continuous linear. For a smooth compactly supported multiplier and any
there exists a proof of domain membership for the class of , and the resulting operator value satisfies, -almost everywhere,
The statement uses toLp for the product class and closedWeightedOperator for the closed operator. No boundedness or differentiability of is assumed.
Original Lean declaration header
Within namespace FunctionalInequalities.KLS.LogConcave. Shown in its original module context. Proof omitted.
theorem exists_mem_domain_closedWeightedOperator_toLp_mul {φ : V → ℝ} (hφ : ContDiff ℝ ∞ φ)
(hφc : HasCompactSupport φ) (x : (hν.closedWeightedOperator m B hi).domain) :
∃ hmem : (memLp_mul_of_contDiff_hasCompactSupport (ν := ν) hφ hφc
(x : Lp ℝ 2 (ν : Measure V))).toLp _ ∈ (hν.closedWeightedOperator m B hi).domain,
((hν.closedWeightedOperator m B hi ⟨_, hmem⟩ : Lp V 2 (ν : Measure V)) : V → V)
=ᵐ[(ν : Measure V)] fun y =>
φ y • ((hν.closedWeightedOperator m B hi x : Lp V 2 (ν : Measure V)) : V → V) y
+ (x : Lp ℝ 2 (ν : Measure V)) y • apply B φ y
Module navigation
Module: KLS/LogConcave/WeightedGradient/Multiplier.
Definition modules: KLS/LogConcave/WeightedGradient/Closure, Probability/LogConcave, Energy/WeightedGradient/Basic.
Supporting theorems: exists_seq_smooth_tendsto_graph.
Previous: exists_seq_smooth_tendsto_graph.
Source excerpt, lines 134–141 · Frozen source 408915f.
import Definitions.Def_KLSModular_FunctionalInequalities_KLS_LogConcave_WeightedGradient_Multiplier
open MeasureTheory Filter Topology
open scoped ContDiff
open FunctionalInequalities.Energy FunctionalInequalities.Energy.WeightedGradient FunctionalInequalities.Analysis.Semigroup
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [CompleteSpace V]
[MeasurableSpace V] [BorelSpace V] [SecondCountableTopology V] [FiniteDimensional ℝ V]
variable {ν : MeasureTheory.ProbabilityMeasure V} (m : MeasureTheory.Measure V) [m.IsAddHaarMeasure] (B : V →L[ℝ] V)
(hν : FunctionalInequalities.KLS.LogConcave ν) (hi : (interior (ν : MeasureTheory.Measure V).support).Nonempty)
theorem FunctionalInequalities.KLS.LogConcave.exists_mem_domain_closedWeightedOperator_toLp_mul_readable {φ : V → ℝ} (hφ : ContDiff ℝ ∞ φ)
(hφc : HasCompactSupport φ) (x : (hν.closedWeightedOperator m B hi).domain) :
∃ hmem : (memLp_mul_of_contDiff_hasCompactSupport (ν := ν) hφ hφc
(x : Lp ℝ 2 (ν : Measure V))).toLp _ ∈ (hν.closedWeightedOperator m B hi).domain,
((hν.closedWeightedOperator m B hi ⟨_, hmem⟩ : Lp V 2 (ν : Measure V)) : V → V)
=ᵐ[(ν : Measure V)] fun y =>
φ y • ((hν.closedWeightedOperator m B hi x : Lp V 2 (ν : Measure V)) : V → V) y
+ (x : Lp ℝ 2 (ν : Measure V)) y • apply B φ y := by sorry