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Weighted two-sided comparison between the rectangular Bregman and Mazur-distance objectives

Proved
HlawkaSchatten.rectangularBregmanObjective_two_sided

by savarin · Sep 27, 2026 · Mathlib 0df444a (Lean v4.33.1)

bregman-divergencehlawka-schattenoperator-inequalitiesschatten-normsvariational-methods

Let E,FE,FE,F be finite-dimensional complex inner-product spaces and let ppp be any real number (no hypothesis is placed on ppp in this statement). For a complex-linear map T:E→FT:E\to FT:E→F, write T^\widehat TT for its Hermitian dilation, the self-adjoint operator on E⊕FE\oplus FE⊕F given by T^(x,y)=(T∗y, Tx)\widehat T(x,y)=(T^\ast y,\,Tx)T(x,y)=(T∗y,Tx) (hermitianDilation). For a self-adjoint operator CCC on E⊕FE\oplus FE⊕F and h:R→Rh:\mathbb R\to\mathbb Rh:R→R, write h(C)h(C)h(C) for the operator obtained by applying hhh to the eigenvalues of CCC in any orthonormal eigenbasis of CCC; this operator itself does not depend on which eigenbasis is chosen, since it acts as h(μ)h(\mu)h(μ) on every μ\muμ-eigenvector of CCC, not only on the vectors of one particular chosen eigenbasis — which is what lets ψp(S^)∘ψp(T^)\psi_p(\widehat S)\circ\psi_p(\widehat T)ψp​(S)∘ψp​(T) below be a single well-defined operator even though S^\widehat SS and T^\widehat TT generally have different eigenbases. With Fp(x)=∣x∣p/pF_p(x)=|x|^p/pFp​(x)=∣x∣p/p, Gp(x)=∣x∣p−2xG_p(x)=|x|^{p-2}xGp​(x)=∣x∣p−2x, and the scalar Mazur map ψp(x)=sign⁡(x) ∣x∣p/2\psi_p(x)=\operatorname{sign}(x)\,|x|^{p/2}ψp​(x)=sign(x)∣x∣p/2 (powerPotential, powerGradient, scalarMazur; all three are totalized real powers, defined for every real ppp and xxx), set

Bp(S,T)  =  Tr⁡Fp(S^)−Tr⁡Fp(T^)−Re⁡Tr⁡ ⁣(S^∘Gp(T^))+Tr⁡ ⁣(T^∘Gp(T^))B_p(S,T) \;=\; \operatorname{Tr}F_p(\widehat S) - \operatorname{Tr}F_p(\widehat T) - \operatorname{Re}\operatorname{Tr}\!\big(\widehat S\circ G_p(\widehat T)\big) + \operatorname{Tr}\!\big(\widehat T\circ G_p(\widehat T)\big)Bp​(S,T)=TrFp​(S)−TrFp​(T)−ReTr(S∘Gp​(T))+Tr(T∘Gp​(T))

(dilatedBregmanTrace, the trace-level Bregman combination of FpF_pFp​ between S^\widehat SS and T^\widehat TT) and

Dp(S,T)  =  Tr⁡(ψp(S^)2)−2Re⁡Tr⁡(ψp(S^)∘ψp(T^))+Tr⁡(ψp(T^)2)D_p(S,T) \;=\; \operatorname{Tr}\big(\psi_p(\widehat S)^2\big) - 2\operatorname{Re}\operatorname{Tr}\big(\psi_p(\widehat S)\circ\psi_p(\widehat T)\big) + \operatorname{Tr}\big(\psi_p(\widehat T)^2\big)Dp​(S,T)=Tr(ψp​(S)2)−2ReTr(ψp​(S)∘ψp​(T))+Tr(ψp​(T)2)

(dilatedMazurDistanceSq, the squared Hilbert–Schmidt distance Tr⁡((ψp(S^)−ψp(T^))2)\operatorname{Tr}\big((\psi_p(\widehat S)-\psi_p(\widehat T))^2\big)Tr((ψp​(S)−ψp​(T))2) between the Mazur images of the two dilations). Separately, let Ψp(T):E→F\Psi_p(T):E\to FΨp​(T):E→F be the rectangular Mazur map of TTT — the unique complex-linear map whose dilation is ψp(T^)\psi_p(\widehat T)ψp​(T), i.e. Ψp(T)^=ψp(T^)\widehat{\Psi_p(T)}=\psi_p(\widehat T)Ψp​(T)​=ψp​(T) (rectangularMazurMap); it satisfies Dp(S,T)=2 ∥Ψp(S)−Ψp(T)∥22D_p(S,T) = 2\,\|\Psi_p(S)-\Psi_p(T)\|_2^2Dp​(S,T)=2∥Ψp​(S)−Ψp​(T)∥22​, where ∥⋅∥2\|\cdot\|_2∥⋅∥2​ is the Schatten-222 (Hilbert–Schmidt) norm.

For T:E→FT:E\to FT:E→F with singular values sv⁡k(T)\operatorname{sv}_k(T)svk​(T), the Schatten ppp-power sphere is {T∣∑k: sv⁡k(T)≠0sv⁡k(T)p=1}\{T\mid\sum_{k:\,\operatorname{sv}_k(T)\ne0}\operatorname{sv}_k(T)^p=1\}{T∣∑k:svk​(T)=0​svk​(T)p=1} (schattenPowerSphere; the sum runs over the nonzero singular values, which for p>0p>0p>0 is the same as summing over all of them). Let ι\iotaι be a finite index type, let a:ι→Ra:\iota\to\mathbb Ra:ι→R with ai≥0a_i\ge0ai​≥0 for every iii, let (ui)i∈ι(u_i)_{i\in\iota}(ui​)i∈ι​ be a family on the Schatten ppp-power sphere, and let vvv be a further point on that sphere. Define the rectangular Bregman objective and rectangular Mazur-distance objective

rectangularBregmanObjective(p,a,u,v)=∑iai⋅Bp(ui,v)2,rectangularMazurDistanceObjective(p,a,u,v)=∑iai ∥Ψp(ui)−Ψp(v)∥22\begin{aligned} &\mathrm{rectangularBregmanObjective}(p,a,u,v)\\ &\quad= \sum_i a_i\cdot\frac{B_p(u_i,v)}{2},\\ &\mathrm{rectangularMazurDistanceObjective}(p,a,u,v)\\ &\quad= \sum_i a_i\,\big\|\Psi_p(u_i)-\Psi_p(v)\big\|_2^2 \end{aligned}​rectangularBregmanObjective(p,a,u,v)=i∑​ai​⋅2Bp​(ui​,v)​,rectangularMazurDistanceObjective(p,a,u,v)=i∑​ai​​Ψp​(ui​)−Ψp​(v)​22​​

(the second equals ∑iai Dp(ui,v)/2\sum_i a_i\,D_p(u_i,v)/2∑i​ai​Dp​(ui​,v)/2 as well, since Dp(S,T)=2∥Ψp(S)−Ψp(T)∥22D_p(S,T)=2\|\Psi_p(S)-\Psi_p(T)\|_2^2Dp​(S,T)=2∥Ψp​(S)−Ψp​(T)∥22​). Assume real numbers m,Mm,Mm,M satisfy the pointwise two-sided bound

m Dp(S,T)  ≤  Bp(S,T)  ≤  M Dp(S,T)m\,D_p(S,T) \;\le\; B_p(S,T) \;\le\; M\,D_p(S,T)mDp​(S,T)≤Bp​(S,T)≤MDp​(S,T)

for every pair of complex-linear maps S,T:E→FS,T:E\to FS,T:E→F. Then the theorem states

m⋅rectangularMazurDistanceObjective(p,a,u,v)≤rectangularBregmanObjective(p,a,u,v)≤M⋅rectangularMazurDistanceObjective(p,a,u,v).\begin{aligned} &m\cdot\mathrm{rectangularMazurDistanceObjective}(p,a,u,v)\\ &\quad\le\mathrm{rectangularBregmanObjective}(p,a,u,v)\\ &\quad\le M\cdot\mathrm{rectangularMazurDistanceObjective}(p,a,u,v). \end{aligned}​m⋅rectangularMazurDistanceObjective(p,a,u,v)≤rectangularBregmanObjective(p,a,u,v)≤M⋅rectangularMazurDistanceObjective(p,a,u,v).​

This lifts a pairwise two-sided bound between BpB_pBp​ and DpD_pDp​, assumed uniformly over rectangular operators, to the weighted finite-family objectives that the variational argument minimizes over the Schatten power sphere, with the same constants m,Mm,Mm,M.

Formalization Note Both named objectives already carry the same 12\tfrac1221​ normalization relative to BpB_pBp​ and DpD_pDp​ respectively (one directly, the other through the identity Dp(S,T)=2∥Ψp(S)−Ψp(T)∥22D_p(S,T)=2\|\Psi_p(S)-\Psi_p(T)\|_2^2Dp​(S,T)=2∥Ψp​(S)−Ψp​(T)∥22​), so the displayed two-sided bound needs no extra factor on either side. No convexity of FpF_pFp​ is claimed or needed here, since ppp ranges over all of R\mathbb RR; BpB_pBp​ and DpD_pDp​ are used purely as totalized algebraic quantities, and the two-sided bound between them is assumed as a hypothesis on this page, not derived from convexity.

Preamble
import Definitions.Def_HlawkaSchatten_HermitianDilation
import Definitions.Def_HlawkaSchatten_SchattenNorm
import Definitions.Def_HlawkaSchatten_Variational
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
-/

/-!
# Variational minima for the Bregman--Mazur argument

This file proves two reusable parts of the variational layer.  First, a
pointwise two-sided comparison transports to attained global minima, even
when the two objectives are indexed by different but equivalent spheres.
Second, the weighted squared-distance objective on a Hilbert unit sphere has
the exact minimum used in the Schatten argument.
-/


open scoped InnerProductSpace ComplexConjugate







variable {𝕜 H ι : Type*} [RCLike 𝕜] [Fintype ι]
  [NormedAddCommGroup H] [InnerProductSpace 𝕜 H]











section RectangularMazur

variable {E F κ : Type*} [Fintype κ]
  [NormedAddCommGroup E] [InnerProductSpace ℂ E] [FiniteDimensional ℂ E]
  [NormedAddCommGroup F] [InnerProductSpace ℂ F] [FiniteDimensional ℂ F]

open HlawkaSchatten
Formal statement
theorem HlawkaSchatten.rectangularBregmanObjective_two_sided
    (p m M : ℝ) (a : ι → ℝ) (ha : ∀ i, 0 ≤ a i)
    (u : ι → schattenPowerSphere (𝕜 := ℂ) (E := E) (F := F) p)
    (v : schattenPowerSphere (𝕜 := ℂ) (E := E) (F := F) p)
    (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) :
    m * rectangularMazurDistanceObjective p a u v ≤
        rectangularBregmanObjective p a u v ∧
      rectangularBregmanObjective p a u v ≤
        M * rectangularMazurDistanceObjective p a u v := by sorry
Source
https://github.com/savarin/hlawka-schatten/blob/79aa498bfcf7b22bd91d771fb32ec278e2d4704b/HlawkaSchatten/Variational.lean#L312-L359

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