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Smooth cutoff functions for operator-core arguments

Definition
KLSModular_FunctionalInequalities_KLS_LogConcave_HeatSemigroup_OperatorCore

by Lazyfill · Oct 25, 2026 · Mathlib 0df444a (Lean v4.33.1)

functional-inequalitiesklskls-conjecturekls-modularlog-concavemodule-context

The private definition profile is a fixed smooth bump equal to one on the ball of radius 555 and supported in the ball of radius 888. For r∈Rr\in\mathbb Rr∈R, cutoff is the rescaled function χr(y)=profile⁡(r−1y)\chi_r(y)=\operatorname{profile}(r^{-1}y)χr​(y)=profile(r−1y); contDiff_cutoff gives smoothness, while cutoff_eq_zero, tsupport_cutoff_subset, and hasCompactSupport_cutoff give its support properties for r>0r>0r>0. These are technical cutoff facts used in operator-core estimates.

Original module imports

import FunctionalInequalities.KLS.LogConcave.HeatSemigroup.Generator
import FunctionalInequalities.KLS.LogConcave.WeightedGradient.Multiplier
import Mathlib.Analysis.Calculus.BumpFunction.InnerProduct

Original declaration excerpt

Shown in the original module context.

private def profile : ContDiffBump (0 : V) := ⟨5, 8, by norm_num, by norm_num⟩

Module navigation

Direct project imports: KLS/LogConcave/HeatSemigroup/Generator, KLS/LogConcave/WeightedGradient/Multiplier.

Theorems in source order:

  • norm_toLp_mul_cutoff_le
  • eq_zero_of_localRegularity
  • exists_seq_smooth_tendsto_adjointComp_of_localRegularity

Project result: The KLS conjecture.

Original module · FunctionalInequalities.KLS.LogConcave.HeatSemigroup.OperatorCore · Frozen source 408915f.

Definition code
import Definitions.Def_KLSModular_FunctionalInequalities_KLS_LogConcave_HeatSemigroup_Generator
import Definitions.Def_KLSModular_FunctionalInequalities_KLS_LogConcave_WeightedGradient_Multiplier
import Mathlib.Analysis.Calculus.BumpFunction.InnerProduct

noncomputable section
open MeasureTheory Filter Topology Metric Set InnerProductSpace
open FunctionalInequalities.Analysis.Semigroup FunctionalInequalities.Analysis.BakryEmery
open scoped ContDiff RealInnerProductSpace
namespace FunctionalInequalities
namespace KLS
namespace LogConcave
open Energy Energy.WeightedGradient
section Cutoff
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [FiniteDimensional ℝ V]
/-- One fixed smooth profile, equal to one on the ball of radius five and supported in the ball
of radius eight. -/
 def profile : ContDiffBump (0 : V) := ⟨5, 8, by norm_num, by norm_num⟩
/-- The scaled cutoff `χ_r (y) = profile (r⁻¹ • y)`: one on `closedBall 0 (5 r)`, zero off
`ball 0 (8 r)`, with gradient of size `O(1/r)`. -/
 def cutoff (r : ℝ) (y : V) : ℝ := (FunctionalInequalities.KLS.LogConcave.profile (V := V)) (r⁻¹ • y)
 theorem contDiff_cutoff (r : ℝ) : ContDiff ℝ ∞ (FunctionalInequalities.KLS.LogConcave.cutoff (V := V) r) :=
  (FunctionalInequalities.KLS.LogConcave.profile (V := V)).contDiff.comp (contDiff_id.const_smul _)
 theorem cutoff_eq_zero {r : ℝ} (hr : 0 < r) {y : V} (hy : 8 * r ≤ ‖y‖) :
    FunctionalInequalities.KLS.LogConcave.cutoff (V := V) r y = 0 := by
  apply (FunctionalInequalities.KLS.LogConcave.profile (V := V)).zero_of_le_dist
  rw [dist_zero_right, norm_smul, Real.norm_eq_abs, abs_of_pos (inv_pos.2 hr),
    ← div_eq_inv_mul, le_div_iff₀ hr]
  exact hy
 theorem tsupport_cutoff_subset {r : ℝ} (hr : 0 < r) :
    tsupport (FunctionalInequalities.KLS.LogConcave.cutoff (V := V) r) ⊆ closedBall (0 : V) (8 * r) := by
  refine closure_minimal (fun y hy => ?_) isClosed_closedBall
  rw [mem_closedBall, dist_zero_right]
  by_contra h
  exact hy (FunctionalInequalities.KLS.LogConcave.cutoff_eq_zero hr (le_of_lt (not_le.1 h)))
 theorem hasCompactSupport_cutoff {r : ℝ} (hr : 0 < r) :
    HasCompactSupport (FunctionalInequalities.KLS.LogConcave.cutoff (V := V) r) :=
  HasCompactSupport.of_support_subset_isCompact (isCompact_closedBall (0 : V) (8 * r))
    ((subset_tsupport _).trans (FunctionalInequalities.KLS.LogConcave.tsupport_cutoff_subset hr))
end Cutoff
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [CompleteSpace V]
  [MeasurableSpace V] [BorelSpace V] [SecondCountableTopology V] [FiniteDimensional ℝ V]
end LogConcave
end KLS
end FunctionalInequalities
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/KLS/LogConcave/HeatSemigroup/OperatorCore.lean#L86-L130 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.KLS.LogConcave.HeatSemigroup.OperatorCore`, definition bundle `KLSModular_FunctionalInequalities_KLS_LogConcave_HeatSemigroup_OperatorCore`; the repository is private at upload time).

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