Mollified Log-Determinant Lower Bound
ProvedFunctionalInequalities.Analysis.posDef_and_convolution_le_log_det_hessianMatrix_readableThis is the mollified log-det lower bound from the weak Letwin route.
Let , with convex and continuous. Assume that, almost everywhere in , there exist a Hermitian positive-definite matrix and a vector such that
- ;
- for every , has at the quadratic expansion represented by
quadraticAt B x g (u x), with error bounded by near .
For every compactly supported bump normalized with respect to volume, and every , the convolution has positive-definite Hessian and
This is the formalized mollified determinant inequality and can be reused as the regularized convexity input in moment-map arguments.
Original Lean declaration header
Within namespace FunctionalInequalities.Analysis. Shown in its original module context. Proof omitted.
theorem posDef_and_convolution_le_log_det_hessianMatrix {n : ℕ}
{u F : EuclideanSpace ℝ (Fin n) → ℝ} (hconv : ConvexOn ℝ univ u) (hF : Continuous F)
(hae : ∀ᵐ x ∂(volume : Measure (EuclideanSpace ℝ (Fin n))),
∃ B : Matrix (Fin n) (Fin n) ℝ, B.IsHermitian ∧ B.PosDef ∧ F x ≤ Real.log B.det ∧
∃ g : EuclideanSpace ℝ (Fin n),
∀ ε > 0, ∀ᶠ y in 𝓝 x, |u y - quadraticAt B x g (u x) y| ≤ ε * ‖y - x‖ ^ 2)
(φ : ContDiffBump (0 : EuclideanSpace ℝ (Fin n))) (x : EuclideanSpace ℝ (Fin n)) :
(hessianMatrix (convolution (φ.normed volume) u (ContinuousLinearMap.lsmul ℝ ℝ) volume) x).PosDef ∧
convolution (φ.normed volume) F (ContinuousLinearMap.lsmul ℝ ℝ) volume x ≤
Real.log (hessianMatrix
(convolution (φ.normed volume) u (ContinuousLinearMap.lsmul ℝ ℝ) volume) x).det
Module navigation
Module: Analysis/Convex/Viscosity.
Definition modules: Analysis/BakryEmery/HessianOperator, Analysis/Convex/Alexandrov.
Supporting theorems: forall_posDef_add_log_det_le_trace_iff, posSemidef_hessianMatrix_of_upper_touch, convolution_hessian_integral, trace_integral_bound.
Previous: trace_integral_bound · Next: ae_exists_quadraticAt_expansion.
Source excerpt, lines 1327–1337 · Frozen source 408915f.
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_Convex_Viscosity open FunctionalInequalities.Probability.Stein open MeasureTheory Set Metric Filter open scoped RealInnerProductSpace ENNReal Topology
theorem FunctionalInequalities.Analysis.posDef_and_convolution_le_log_det_hessianMatrix_readable {n : ℕ}
{u F : EuclideanSpace ℝ (Fin n) → ℝ} (hconv : ConvexOn ℝ univ u) (hF : Continuous F)
(hae : ∀ᵐ x ∂(volume : Measure (EuclideanSpace ℝ (Fin n))),
∃ B : Matrix (Fin n) (Fin n) ℝ, B.IsHermitian ∧ B.PosDef ∧ F x ≤ Real.log B.det ∧
∃ g : EuclideanSpace ℝ (Fin n),
∀ ε > 0, ∀ᶠ y in 𝓝 x, |u y - quadraticAt B x g (u x) y| ≤ ε * ‖y - x‖ ^ 2)
(φ : ContDiffBump (0 : EuclideanSpace ℝ (Fin n))) (x : EuclideanSpace ℝ (Fin n)) :
(hessianMatrix (convolution (φ.normed volume) u (ContinuousLinearMap.lsmul ℝ ℝ) volume) x).PosDef ∧
convolution (φ.normed volume) F (ContinuousLinearMap.lsmul ℝ ℝ) volume x ≤
Real.log (hessianMatrix
(convolution (φ.normed volume) u (ContinuousLinearMap.lsmul ℝ ℝ) volume) x).det := by sorry