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Maximal Positive-Volume Simplex in a Compact Set

Proved
FunctionalInequalities.Analysis.exists_max_simplexEdgeMatrix_det_readable

by Lazyfill · Oct 26, 2026 · Mathlib 0df444a (Lean v4.33.1)

functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This establishes existence of a maximal-volume simplex in a compact set with nonempty interior.

Let K⊆RnK\subseteq\mathbb R^nK⊆Rn be compact and assume int⁡(K)≠∅\operatorname{int}(K)\ne\varnothingint(K)=∅. Then there exists a map v:Fin⁡(n+1)→Rnv:\operatorname{Fin}(n+1)\to\mathbb R^nv:Fin(n+1)→Rn such that:

  1. Every vertex viv_ivi​ belongs to KKK.
  2. The simplex edge matrix has positive determinant magnitude:
∣det⁡(simplexEdgeMatrix⁡(v))∣>0.|\det(\operatorname{simplexEdgeMatrix}(v))|>0.∣det(simplexEdgeMatrix(v))∣>0.
  1. Every other (n+1)(n+1)(n+1)-tuple www of points in KKK has no larger determinant magnitude:
∣det⁡(simplexEdgeMatrix⁡(w))∣≤∣det⁡(simplexEdgeMatrix⁡(v))∣.|\det(\operatorname{simplexEdgeMatrix}(w))|\le|\det(\operatorname{simplexEdgeMatrix}(v))|.∣det(simplexEdgeMatrix(w))∣≤∣det(simplexEdgeMatrix(v))∣.

The declaration is exists_max_simplexEdgeMatrix_det_readable. It is the compactness and normalization step for selecting a nondegenerate maximal simplex.

Original Lean declaration header

Within namespace FunctionalInequalities.Analysis. Shown in its original module context. Proof omitted.

theorem exists_max_simplexEdgeMatrix_det {n : ℕ} {K : Set (EuclideanSpace ℝ (Fin n))}
    (hK : IsCompact K) (hint : (interior K).Nonempty) :
    ∃ v : Fin (n + 1) → EuclideanSpace ℝ (Fin n), (∀ i, v i ∈ K) ∧
      0 < |(simplexEdgeMatrix v).det| ∧
      ∀ w : Fin (n + 1) → EuclideanSpace ℝ (Fin n), (∀ i, w i ∈ K) →
        |(simplexEdgeMatrix w).det| ≤ |(simplexEdgeMatrix v).det|

Module navigation

Module: Analysis/Convex/Normalization.

Next: abs_simplexCoord_le_one_of_max.

Source excerpt, lines 31–36 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_Convex_Normalization

Formal statement

theorem FunctionalInequalities.Analysis.exists_max_simplexEdgeMatrix_det_readable {n : ℕ} {K : Set (EuclideanSpace ℝ (Fin n))}
    (hK : IsCompact K) (hint : (interior K).Nonempty) :
    ∃ v : Fin (n + 1) → EuclideanSpace ℝ (Fin n), (∀ i, v i ∈ K) ∧
      0 < |(simplexEdgeMatrix v).det| ∧
      ∀ w : Fin (n + 1) → EuclideanSpace ℝ (Fin n), (∀ i, w i ∈ K) →
        |(simplexEdgeMatrix w).det| ≤ |(simplexEdgeMatrix v).det| := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Analysis/Convex/Normalization.lean#L29-L121 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Analysis.Convex.Normalization`, declaration `FunctionalInequalities.Analysis.exists_max_simplexEdgeMatrix_det`; the repository is private at upload time).

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