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Sequential cores and recovery sequences

Definition
KLSModular_FunctionalInequalities_Energy_Form_Core

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

functional-inequalitiesklskls-conjecturekls-modularlog-concavemodule-context

PreEnergy.HasRecoverySequenceAt energy x means that some approximating sequence converges to x and its finite energies converge to the prescribed ENNReal value energy x. PreEnergy.AgreesOnTests energy means that the ambient functional equals the finite pre-energy on every realized concrete test, while SequentiallyGenerates means equality with the sequential relaxation. IsSequentialCoreFor packages the latter two exact equalities and does not itself assert density, closability, or a graph-norm core property.

Original module imports

import FunctionalInequalities.Energy.Relaxation.Basic
import Mathlib.Topology.Instances.ENNReal.Lemmas

Original declaration excerpt

Shown in the original module context.

def HasRecoverySequenceAt (energy : Functional X) (x : X) : Prop :=
  ∃ f : P.ApproximatingSequence x,
    Tendsto (fun n ↦ (P.energy (f.1 n) : ENNReal)) atTop (𝓝 (energy x))

Module navigation

Direct project imports: Energy/Relaxation/Basic.

Project result: The KLS conjecture.

Original module · FunctionalInequalities.Energy.Form.Core · Frozen source 408915f.

Definition code
import Definitions.Def_KLSModular_FunctionalInequalities_Energy_Relaxation_Basic
import Mathlib.Topology.Instances.ENNReal.Lemmas

noncomputable section
open Filter Topology
namespace FunctionalInequalities
namespace Energy
namespace PreEnergy
universe u v
variable {X : Type u} [TopologicalSpace X] (P : PreEnergy X)
/-- A recovery sequence at `x` converges to `x` in the ambient topology and has energies
converging to the prescribed extended value. -/
def HasRecoverySequenceAt (energy : Functional X) (x : X) : Prop :=
  ∃ f : P.ApproximatingSequence x,
    Tendsto (fun n ↦ (P.energy (f.1 n) : ENNReal)) atTop (𝓝 (energy x))
/-- A concrete test has the same energy before and after realization in the ambient space. -/
def AgreesOnTests (energy : Functional X) : Prop :=
  ∀ f : P.Test, energy (P.toAmbient f) = (P.energy f : ENNReal)
/-- The pre-energy sequentially generates an extended ambient energy. -/
def SequentiallyGenerates (energy : Functional X) : Prop :=
  P.sequentialRelaxation = energy
/-- A sequential form core both restricts the ambient energy correctly and generates it by
relaxation.

This project-specific name records the two exact equalities above. Identifying it with another
literature notion of graph-norm core is a theorem to be proved in the relevant analytic setting.
-/
structure IsSequentialCoreFor (energy : Functional X) : Prop where
  /-- The finite test energy is the restriction of the ambient energy. -/
  agreesOnTests : P.AgreesOnTests energy
  /-- Relaxing the test energy recovers the entire extended functional. -/
  sequentiallyGenerates : P.SequentiallyGenerates energy
end PreEnergy
end Energy
end FunctionalInequalities
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Energy/Form/Core.lean#L29-L61 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Energy.Form.Core`, definition bundle `KLSModular_FunctionalInequalities_Energy_Form_Core`; the repository is private at upload time).

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