Triple-deficit upper bound for the Schatten -norm via the radial Mazur map
ProvedHlawkaSchatten.tripleGap_radial_leLet be finite-dimensional complex inner-product spaces, let , let with , and let be any three complex-linear maps, possibly zero. Write for the Schatten -norm (schattenPNorm). The rectangular Mazur map (rectangularMazurMap) is obtained by applying to the eigenvalues of the Hermitian dilation on , then taking the lower-left block. It carries the Schatten- power sphere onto the Schatten- power sphere. It is generally nonlinear; at it is the identity. Define the radial rectangular image (radialRectangularMazurMap) by
Record by its values on a fixed orthonormal basis of , obtaining the vector in the Hilbert space of column tuples with its norm (radialMazurHilbertMap). Then and for every . Define the triple deficit and its mapped counterpart by
For any two complex-linear maps , write (dilatedBregmanTrace) and (dilatedMazurDistanceSq) for the trace-level Bregman divergence and squared Mazur distance between and , built respectively from the scalar potential and the odd map . Assume the uniform two-sided bound
holds for every pair . Then
This is the three-operator specialization of the family-level deficit estimate, extended to include vanishing inputs. Only the upper bound needed in the final transfer is stated. When and , it combines with the three pair lower bounds and the classical Hilbert-space Hlawka inequality for the mapped vectors to give a Hlawka constant . If the same comparison constants work in every dimension, the resulting constant is dimension independent.
import Definitions.Def_HlawkaSchatten_Final
import Definitions.Def_HlawkaSchatten_GapComparison
import Definitions.Def_HlawkaSchatten_HermitianDilation
import Definitions.Def_HlawkaSchatten_MazurGapComparison
import Definitions.Def_HlawkaSchatten_SchattenNorm
import Mathlib.Analysis.Calculus.LHopital
import Mathlib.Analysis.Convex.Deriv
import Mathlib.Analysis.Convex.SpecificFunctions.Basic
import Mathlib.Analysis.InnerProductSpace.Adjoint
import Mathlib.Analysis.InnerProductSpace.Basic
import Mathlib.Analysis.InnerProductSpace.Dual
import Mathlib.Analysis.InnerProductSpace.NormPow
import Mathlib.Analysis.InnerProductSpace.PiL2
import Mathlib.Analysis.InnerProductSpace.ProdL2
import Mathlib.Analysis.InnerProductSpace.SingularValues
import Mathlib.Analysis.InnerProductSpace.Trace
import Mathlib.Data.Sign.Basic
import Mathlib.LinearAlgebra.Matrix.Charpoly.Basic
import Mathlib.Topology.Compactification.OnePoint.Basic
import Mathlib.Topology.Instances.Sign
/-
Copyright (c) 2026 Ezzeri Esa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Ezzeri Esa
-/
/-!
# Dimension-independent Hlawka constants for Schatten norms
This file removes the unit-sphere normalization from the variational
comparison and performs the final Hilbert-space Hlawka transfer.
-/
open scoped InnerProductSpace
variable {E F : Type*}
[NormedAddCommGroup E] [InnerProductSpace ℂ E] [FiniteDimensional ℂ E]
[NormedAddCommGroup F] [InnerProductSpace ℂ F] [FiniteDimensional ℂ F]
open HlawkaSchatten
theorem HlawkaSchatten.tripleGap_radial_le
{p m M : ℝ} (hp : 1 < p) (hm : 0 ≤ m)
(x y z : E →ₗ[ℂ] F)
(hbound : ∀ S T : E →ₗ[ℂ] F,
m * dilatedMazurDistanceSq p S T ≤ dilatedBregmanTrace p S T ∧
dilatedBregmanTrace p S T ≤ M * dilatedMazurDistanceSq p S T) :
tripleGap (schattenPNorm p) x y z ≤
2 * M * mappedTripleGap (schattenPNorm p) (radialMazurHilbertMap p) x y z := by sorry