Semidefinite Hessian at an Upper Touch
ProvedFunctionalInequalities.Analysis.posSemidef_hessianMatrix_of_upper_touch_readablefunctional-inequalitieskls-conjecturekls-modularkls-readablelog-concave
Let , with convex. If at , , and in a neighborhood of , then the coordinate Hessian of at is positive semidefinite:
This is a pointwise viscosity touching principle for convex functions.
Original Lean declaration header
Within namespace FunctionalInequalities.Analysis. Shown in its original module context. Proof omitted.
theorem posSemidef_hessianMatrix_of_upper_touch {n : ℕ} {u ψ : EuclideanSpace ℝ (Fin n) → ℝ}
(hconv : ConvexOn ℝ univ u) {x₀ : EuclideanSpace ℝ (Fin n)} (hψ : ContDiffAt ℝ 2 ψ x₀)
(hcontact : u x₀ = ψ x₀) (htouch : ∀ᶠ x in 𝓝 x₀, u x ≤ ψ x) :
(hessianMatrix ψ x₀).PosSemidef
Module navigation
Module: Analysis/Convex/Viscosity.
Definition modules: Analysis/BakryEmery/HessianOperator.
Supporting theorems: directional_second_deriv_nonneg.
Previous: directional_second_deriv_nonneg · Next: hessianMatrix_quadratic.
Source excerpt, lines 149–152 · Frozen source 408915f.
Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_Convex_Viscosity open Set Metric Filter open scoped RealInnerProductSpace Topology open FunctionalInequalities.Probability.Stein
Formal statement
theorem FunctionalInequalities.Analysis.posSemidef_hessianMatrix_of_upper_touch_readable {n : ℕ} {u ψ : EuclideanSpace ℝ (Fin n) → ℝ}
(hconv : ConvexOn ℝ univ u) {x₀ : EuclideanSpace ℝ (Fin n)} (hψ : ContDiffAt ℝ 2 ψ x₀)
(hcontact : u x₀ = ψ x₀) (htouch : ∀ᶠ x in 𝓝 x₀, u x ≤ ψ x) :
(hessianMatrix ψ x₀).PosSemidef := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Analysis/Convex/Viscosity.lean#L147-L181 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Analysis.Convex.Viscosity`, declaration `FunctionalInequalities.Analysis.posSemidef_hessianMatrix_of_upper_touch`; the repository is private at upload time).