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Nonnegativity of the Hlawka deficit's Hessian on the cyclic coordinate box

Proved
HlawkaSchatten.DiagonalConstruction.deficitHessian_nonneg

by savarin · Sep 28, 2026 · Mathlib 0df444a (Lean v4.33.1)

convexityhessianhlawka-schattensharp-constant

Write a triple XXX as three columns X0,X1,X2∈R3X_0,X_1,X_2\in\mathbb R^3X0​,X1​,X2​∈R3, with Xj,iX_{j,i}Xj,i​ coordinate iii of column jjj (Lean: X j i). Let pairTriple(X)j\mathrm{pairTriple}(X)_jpairTriple(X)j​ denote the sum of the two columns of XXX other than jjj (so pairTriple(X)0=X1+X2\mathrm{pairTriple}(X)_0=X_1+X_2pairTriple(X)0​=X1​+X2​, pairTriple(X)1=X0+X2\mathrm{pairTriple}(X)_1=X_0+X_2pairTriple(X)1​=X0​+X2​, pairTriple(X)2=X0+X1\mathrm{pairTriple}(X)_2=X_0+X_1pairTriple(X)2​=X0​+X1​), and totalTriple(X)=X0+X1+X2\mathrm{totalTriple}(X)=X_0+X_1+X_2totalTriple(X)=X0​+X1​+X2​. Let cyclicCenter\mathrm{cyclicCenter}cyclicCenter be the triple whose jjj-th column has −1-1−1 in position jjj and 111 elsewhere, and entryBox:={X:∣Xj,i−cyclicCenterj,i∣≤19/100 for all j,i}\mathrm{entryBox}:=\{X:|X_{j,i}-\mathrm{cyclicCenter}_{j,i}|\le19/100\text{ for all }j,i\}entryBox:={X:∣Xj,i​−cyclicCenterj,i​∣≤19/100 for all j,i}.

For v,h∈R3v,h\in\mathbb R^3v,h∈R3, define

normHessianp(v,h):=(p−1)(∑i∣vi∣p)1/p−1∑i∣vi∣p−2(hi−radialCoefficientp(v,h) vi)2,radialCoefficientp(v,h):=∑i∣vi∣p−2vihi∑i∣vi∣p.\begin{gathered} \mathrm{normHessian}_p(v,h):=(p-1)\Bigl(\textstyle\sum_i|v_i|^p\Bigr)^{1/p-1}\sum_i|v_i|^{p-2}\bigl(h_i-\mathrm{radialCoefficient}_p(v,h)\,v_i\bigr)^2, \\ \quad \mathrm{radialCoefficient}_p(v,h):=\frac{\sum_i|v_i|^{p-2}v_ih_i}{\sum_i|v_i|^p}. \end{gathered}normHessianp​(v,h):=(p−1)(∑i​∣vi​∣p)1/p−1∑i​∣vi​∣p−2(hi​−radialCoefficientp​(v,h)vi​)2,radialCoefficientp​(v,h):=∑i​∣vi​∣p∑i​∣vi​∣p−2vi​hi​​.​

For p,K∈Rp,K\in\mathbb Rp,K∈R, define the Hessian of the Hlawka deficit at a triple XXX, in direction ZZZ (another triple), as

deficitHessianp,K(X,Z):=(2K−1)∑jnormHessianp(Xj,Zj)  +  normHessianp(totalTriple(X),totalTriple(Z))  −  K∑jnormHessianp(pairTriple(X)j,pairTriple(Z)j).\begin{gathered} \mathrm{deficitHessian}_{p,K}(X,Z) := (2K-1)\sum_j \mathrm{normHessian}_p(X_j,Z_j) \\ \;+\; \mathrm{normHessian}_p\bigl(\mathrm{totalTriple}(X),\mathrm{totalTriple}(Z)\bigr) \\ \;-\; K\sum_j \mathrm{normHessian}_p\bigl(\mathrm{pairTriple}(X)_j,\mathrm{pairTriple}(Z)_j\bigr). \end{gathered}deficitHessianp,K​(X,Z):=(2K−1)j∑​normHessianp​(Xj​,Zj​)+normHessianp​(totalTriple(X),totalTriple(Z))−Kj∑​normHessianp​(pairTriple(X)j​,pairTriple(Z)j​).​

For every p≥256p\ge256p≥256, every KKK with 1≤K≤p1\le K\le p1≤K≤p, every X∈entryBoxX\in\mathrm{entryBox}X∈entryBox, and every triple ZZZ,

0  ≤  deficitHessianp,K(X,Z).0 \;\le\; \mathrm{deficitHessian}_{p,K}(X,Z).0≤deficitHessianp,K​(X,Z).

deficitHessian\mathrm{deficitHessian}deficitHessian is built from normHessian\mathrm{normHessian}normHessian with exactly the combinatorial pattern — three singleton terms with coefficient 2K−12K-12K−1, one "total" term with coefficient 111, and three "pair" terms with coefficient −K-K−K — that a Hlawka-type deficit (2K−1)(N(X0)+N(X1)+N(X2))+N(X0+X1+X2)−K(N(X0+X1)+N(X0+X2)+N(X1+X2))(2K-1)\bigl(N(X_0)+N(X_1)+N(X_2)\bigr)+N(X_0+X_1+X_2)-K\bigl(N(X_0+X_1)+N(X_0+X_2)+N(X_1+X_2)\bigr)(2K−1)(N(X0​)+N(X1​)+N(X2​))+N(X0​+X1​+X2​)−K(N(X0​+X1​)+N(X0​+X2​)+N(X1​+X2​)) has in a size functional NNN. Differentiating each of these seven norm-terms twice along the line X+sZX+sZX+sZ — using that normHessianp\mathrm{normHessian}_pnormHessianp​ is exactly the second derivative of the finite coordinate ppp-norm along a line, away from the origin — reproduces deficitHessianp,K(X,Z)\mathrm{deficitHessian}_{p,K}(X,Z)deficitHessianp,K​(X,Z) term by term. So this theorem is a statement about curvature: for every admissible KKK in the stated range, the Hlawka-type deficit built from the finite coordinate ppp-norm has nonnegative second derivative, in every direction ZZZ, at every point of the cyclic coordinate box.

Preamble
import Definitions.Def_HlawkaSchatten_DiagonalConstruction_BoxHessian
import Definitions.Def_HlawkaSchatten_DiagonalConstruction_Localization
import Mathlib.Analysis.Complex.ExponentialBounds
import Mathlib.Analysis.Convex.Deriv
import Mathlib.Analysis.Convex.Function
import Mathlib.Analysis.Convex.Jensen
import Mathlib.Analysis.Convex.SpecificFunctions.Basic
import Mathlib.Analysis.InnerProductSpace.Basic
import Mathlib.Analysis.InnerProductSpace.Dual
import Mathlib.Analysis.InnerProductSpace.NormPow
import Mathlib.Analysis.Normed.Lp.PiLp
import Mathlib.Analysis.SpecialFunctions.Pow.Continuity
import Mathlib.Data.Fin.VecNotation
import Mathlib.Data.Real.Basic
import Mathlib.Data.Sign.Basic
import Mathlib.Tactic.Abel
import Mathlib.Tactic.FieldSimp
import Mathlib.Tactic.Linarith
import Mathlib.Tactic.LinearCombination
import Mathlib.Topology.Instances.Sign
import Mathlib.Topology.Order.Compact

/-
Copyright (c) 2026 Ezzeri Esa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Ezzeri Esa
-/

/-! # Nonnegative second variation on the entire cyclic box -/

open HlawkaSchatten.DiagonalConstruction
Formal statement
theorem HlawkaSchatten.DiagonalConstruction.deficitHessian_nonneg {p K : ℝ} (hp : 256 ≤ p) (hK : 1 ≤ K) (hKp : K ≤ p)
    {X : Triple} (hX : X ∈ entryBox) (Z : Triple) : 0 ≤ deficitHessian p K X Z := by sorry
Source
https://github.com/savarin/hlawka-schatten/blob/79aa498bfcf7b22bd91d771fb32ec278e2d4704b/HlawkaSchatten/DiagonalConstruction/BoxHessian.lean#L40-L88
Human review
  • Endorsed by Shuze Chen · Sep 29, 2026

    Confirmed by the moderator at approval.

  • Endorsed by savarin · Sep 29, 2026

    Confirmed by the mission captain (proposal self-audit).

  • Endorsed by marwahaha · Sep 30, 2026

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