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The rectangular Mazur-distance objective attains its minimum on the Schatten power sphere

Proved
HlawkaSchatten.rectangularMazurDistanceObjective_isGlobalMinimumValue

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

convex-optimizationhilbert-spacehlawka-schattenschatten-normsvariational-methods

Let E,FE,FE,F be finite-dimensional complex inner-product spaces, let κ\kappaκ be a finite index type and eee an orthonormal basis of EEE indexed by κ\kappaκ, let p∈Rp\in\mathbb Rp∈R with p>0p>0p>0, and let ι\iotaι be a nonempty finite index type. For a complex-linear map 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∣∑ksv⁡k(T)p=1}\{T\mid\sum_k\operatorname{sv}_k(T)^p=1\}{T∣∑k​svk​(T)p=1} (schattenPowerSphere). For 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 with T^(x,y)=(T∗y, Tx)\widehat T(x,y)=(T^\ast y,\,Tx)T(x,y)=(T∗y,Tx) (hermitianDilation), and let ψp(x)=sign⁡(x) ∣x∣p/2\psi_p(x)=\operatorname{sign}(x)\,|x|^{p/2}ψp​(x)=sign(x)∣x∣p/2 be the scalar Mazur map (scalarMazur). Applying ψp\psi_pψp​ to the eigenvalues of T^\widehat TT in an orthonormal eigenbasis gives a self-adjoint operator that is again the dilation of a unique complex-linear map E→FE\to FE→F; that map is the rectangular Mazur map Ψp(T)\Psi_p(T)Ψp​(T) (rectangularMazurMap), so Ψp(T)^=ψp(T^)\widehat{\Psi_p(T)}=\psi_p(\widehat T)Ψp​(T)​=ψp​(T). It satisfies ∑ksv⁡k(Ψp(T))2=∑ksv⁡k(T)p\sum_k\operatorname{sv}_k(\Psi_p(T))^2=\sum_k\operatorname{sv}_k(T)^p∑k​svk​(Ψp​(T))2=∑k​svk​(T)p, so it sends the Schatten ppp-power sphere into the ordinary Schatten-222 (Hilbert–Schmidt) unit sphere.

Fix real weights a:ι→Ra:\iota\to\mathbb Ra:ι→R (no sign condition on the aia_iai​) and a family (ui)i∈ι(u_i)_{i\in\iota}(ui​)i∈ι​ on the Schatten ppp-power sphere. For vvv ranging over the same sphere, consider the weighted objective

f(v)  =  ∑i∈ιai ∥Ψp(ui)−Ψp(v)∥22(rectangularMazurDistanceObjective),f(v) \;=\; \sum_{i\in\iota} a_i\,\big\|\Psi_p(u_i)-\Psi_p(v)\big\|_2^2 \qquad (\texttt{rectangularMazurDistanceObjective}),f(v)=i∈ι∑​ai​​Ψp​(ui​)−Ψp​(v)​22​(rectangularMazurDistanceObjective),

with ∥⋅∥2\|\cdot\|_2∥⋅∥2​ the Schatten-222 norm, and let w=∑i∈ιai Ψp(ui)w=\sum_{i\in\iota}a_i\,\Psi_p(u_i)w=∑i∈ι​ai​Ψp​(ui​) be the weighted barycenter of the Mazur images (rectangularMazurBarycenter). Then the theorem states that fff attains the global minimum value

2(∑i∈ιai−∥w∥2)2\Big(\sum_{i\in\iota}a_i - \|w\|_2\Big)2(i∈ι∑​ai​−∥w∥2​)

over the Schatten ppp-power sphere: this value lower-bounds f(v)f(v)f(v) for every vvv on the sphere, and equals f(v)f(v)f(v) for some vvv on the sphere.

This is the Hilbert-side half of the variational comparison: it computes, in closed form, the minimum of the weighted squared-distance objective on the actual Schatten power sphere of rectangular operators — with no enlargement to an ambient coordinate space — matching the identity min⁡∥v∥=1∑iai∥ui−v∥2=2(∑iai−∥∑iaiui∥)\min_{\|v\|=1}\sum_ia_i\|u_i-v\|^2=2\big(\sum_ia_i-\|\sum_ia_iu_i\|\big)min∥v∥=1​∑i​ai​∥ui​−v∥2=2(∑i​ai​−∥∑i​ai​ui​∥) for unit vectors uiu_iui​ in an ordinary Hilbert space.

Formalization Note The statement is additionally parametrized by an orthonormal basis eee of EEE indexed by κ\kappaκ, used only to identify Hilbert–Schmidt coordinates on EEE in the proof; neither the objective, the barycenter, nor the minimum value depends on the choice of eee.

Preamble
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.rectangularMazurDistanceObjective_isGlobalMinimumValue
    (e : OrthonormalBasis κ ℂ E) [Nonempty ι]
    {p : ℝ} (hp : 0 < p) (a : ι → ℝ)
    (u : ι → schattenPowerSphere (𝕜 := ℂ) (E := E) (F := F) p) :
    IsGlobalMinimumValue (rectangularMazurDistanceObjective p a u)
      (2 * (∑ i, a i - schattenPNorm 2
        (rectangularMazurBarycenter p a u))) := by sorry
Source
https://github.com/savarin/hlawka-schatten/blob/79aa498bfcf7b22bd91d771fb32ec278e2d4704b/HlawkaSchatten/Variational.lean#L419-L457

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