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Euler's identity for the power potential FpF_pFp​ and its gradient GpG_pGp​

Proved
HlawkaSchatten.powerGradient_mul_self

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

hlawka-schattenhomogeneitypower-potentialscalar-comparison

Let p∈Rp \in \mathbb Rp∈R with p>0p>0p>0, and let x∈Rx \in \mathbb Rx∈R. Write Fp(x)=∣x∣p/pF_p(x) = |x|^p/pFp​(x)=∣x∣p/p (powerPotential) and Gp(x)=∣x∣p−2xG_p(x) = |x|^{p-2}xGp​(x)=∣x∣p−2x (powerGradient). Then

Gp(x)⋅x=p⋅Fp(x).G_p(x)\cdot x = p \cdot F_p(x).Gp​(x)⋅x=p⋅Fp​(x).

Equivalently, since p⋅Fp(x)=∣x∣pp\cdot F_p(x) = |x|^pp⋅Fp​(x)=∣x∣p, the gradient times xxx recovers ∣x∣p|x|^p∣x∣p exactly. This is the Euler identity for the potential FpF_pFp​, which is positively homogeneous of degree ppp: multiplying its gradient by xxx recovers ppp times the potential itself. It is an algebraic bookkeeping fact used to simplify expressions that mix the power gradient and the power potential at the same point, arising when the Bregman divergence's defining formula is expanded and rearranged.

Formalization Note. The identity holds for every p>0p>0p>0 and every real xxx, including x=0x=0x=0 (both sides vanish) and the range 0<p≤10<p\le10<p≤1, where Gp(⋅)G_p(\cdot)Gp​(⋅) is a totalized algebraic convention rather than an actual derivative of FpF_pFp​ at the origin: FpF_pFp​ itself is not differentiable at 000 when p≤1p\le1p≤1.

Preamble
import Definitions.Def_HlawkaSchatten_ScalarBregman
import Mathlib.Analysis.Convex.Deriv
import Mathlib.Analysis.Convex.SpecificFunctions.Basic
import Mathlib.Analysis.InnerProductSpace.Basic
import Mathlib.Analysis.InnerProductSpace.Dual
import Mathlib.Analysis.InnerProductSpace.NormPow
import Mathlib.Data.Sign.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
-/

/-!
# Scalar power Bregman data

These are the scalar objects used in the first layer of the audited
Bregman--Mazur proof. The normalization of `powerPotential` is important:
its derivative is the signed `(p - 1)`-power with no extra factor of `p`.
-/


open Filter
open scoped Topology

open HlawkaSchatten
Formal statement
theorem HlawkaSchatten.powerGradient_mul_self {p : ℝ} (hp : 0 < p) (x : ℝ) :
    powerGradient p x * x = p * powerPotential p x := by sorry
Source
https://github.com/savarin/hlawka-schatten/blob/79aa498bfcf7b22bd91d771fb32ec278e2d4704b/HlawkaSchatten/ScalarBregman.lean#L354-L368

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