Continuous Differentiability of the Moment Potential
ProvedFunctionalInequalities.Analysis.contDiff_one_of_map_gradient_readableThis formalizes the regularity statement associated with Klartag's result, cited as Lemma 2.2 in Letwin (arXiv:2607.24164v1), with the reviewed relation recorded as partial.
Let be a nontrivial finite-dimensional real inner-product space with its Borel measurable structure. Let be Lipschitz and convex, and assume:
- .
- is compact, convex, and has nonempty interior.
- is continuous.
- The push-forward of the tilted volume measure by equals the measure with density .
Then
formalized as ContDiff ℝ 1 u.
This is the regularity conclusion used for the moment potential in the finite-dimensional compact-target setting.
Formalization Note The statement proves ContDiff of order on the whole finite-dimensional space; it does not state positive-definite Hessian, a global diffeomorphism, or a pointwise Monge–Ampère equation.
Original Lean declaration header
Within namespace FunctionalInequalities.Analysis. Shown in its original module context. Proof omitted.
theorem contDiff_one_of_map_gradient
[FiniteDimensional ℝ E] [Nontrivial E] [MeasurableSpace E] [BorelSpace E]
{u : E → ℝ} {L : NNReal} (hu : LipschitzWith L u) (hconv : ConvexOn ℝ univ u)
(hnorm : ∫ x, Real.exp (-u x) ∂(volume : Measure E) = 1)
{K : Set E} (hK : IsCompact K) (hKc : Convex ℝ K) (hKint : (interior K).Nonempty)
{V : E → ℝ} (hV : Continuous V)
(hmap : ((volume : Measure E).tilted (-u)).map (gradient u) =
(volume : Measure E).withDensity (K.indicator fun p => ENNReal.ofReal (Real.exp (-V p)))) :
ContDiff ℝ 1 u
Module navigation
Module: Analysis/Convex/Caffarelli.
Selected supporting theorems: contDiff_one_of_convexOn_of_differentiable, convexOn_truncatedConjugate, eq_of_contact_of_sublevel_bounds, exists_inverse_subgradient_volume_bounds, exists_subgradient_slope_le_inner_add.
Previous: strictConvexOn_of_map_gradient.
Source excerpt, lines 2156–2164 · Frozen source 408915f.
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_Convex_Caffarelli
open MeasureTheory Set Metric
variable {E : Type*}
variable [NormedAddCommGroup E] [InnerProductSpace ℝ E]
set_option maxHeartbeats 800000
theorem FunctionalInequalities.Analysis.contDiff_one_of_map_gradient_readable
[FiniteDimensional ℝ E] [Nontrivial E] [MeasurableSpace E] [BorelSpace E]
{u : E → ℝ} {L : NNReal} (hu : LipschitzWith L u) (hconv : ConvexOn ℝ univ u)
(hnorm : ∫ x, Real.exp (-u x) ∂(volume : Measure E) = 1)
{K : Set E} (hK : IsCompact K) (hKc : Convex ℝ K) (hKint : (interior K).Nonempty)
{V : E → ℝ} (hV : Continuous V)
(hmap : ((volume : Measure E).tilted (-u)).map (gradient u) =
(volume : Measure E).withDensity (K.indicator fun p => ENNReal.ofReal (Real.exp (-V p)))) :
ContDiff ℝ 1 u := by sorry