Samplinglib
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ASTIS mathematical exposition

The totalized derivative vanishes throughout the outer zero region

AutoSamplingTheory.TechnicalLemmas.Analysis.Calculus.Cutoff.radialSmoothCutoff_fderiv_eq_zero_of_two_mul_le_norm · theorem · Teaching coverage

Statement

Let E be a real normed vector space, let R>0, and let x∈E satisfy 2R≤‖x‖. Then Mathlib's totalized Fréchet derivative of χ_R at x is the zero continuous linear map. This includes the outer boundary sphere and does not assume an inner-product norm or differentiability of χ_R.

\[R>0,\ 2R\le\|x\|\quad\Longrightarrow\quad D_{\mathrm{tot}}\chi_R(x)=0.\]

All objects and hypotheses

  • E is a normed additive commutative group equipped with a real normed-vector-space structure.
  • R>0, x∈E, and 2R≤‖x‖.
  • No differentiability or inner-product-space hypothesis is assumed; `fderiv` is totalized.

Mathematical proof

1. Recognize a global, hence local, minimum

The outer value theorem gives χ_R(x)=0. The range theorem gives χ_R(y)≥0 for every y∈E. Thus x is a global minimum, and in particular a local minimum.

\[\chi_R(x)=0\le\chi_R(y)\quad(\forall y\in E).\]
Corresponding Lean step

rw [radialSmoothCutoff_eq_zero_of_two_mul_le_norm hR hx]; exact Filter.Eventually.of_forall fun y => (radialSmoothCutoff_mem_Icc R y).1

2. Apply the totalized form of Fermat's rule

At a differentiable local minimum the derivative is zero. Mathlib's theorem states this for totalized fderiv: if differentiability fails, fderiv is zero by definition instead. Consequently the same conclusion holds without an explicit differentiability assumption.

\[x\text{ a local minimum of }\chi_R\quad\Longrightarrow\quad D_{\mathrm{tot}}\chi_R(x)=0.\]
Corresponding Lean step

apply IsLocalMin.fderiv_eq_zero

Lean statement · radialSmoothCutoff_fderiv_eq_zero_of_two_mul_le_norm

The right-hand zero is the zero continuous linear map, not just a zero real value. At ‖x‖=2R the proof uses a minimum, not an unjustified locally-constant neighborhood. The source's surrounding Radial section contributes the implicit type E and its NormedAddCommGroup instance; further structures appear explicitly in the declaration.

Braces mark parameters Lean can infer; square brackets request structures such as a measurable space or probability measure. Named hypotheses are mathematical premises, not facts established by this declaration. Section parameters are described in the mathematical hypotheses above; the module link retains their exact source context.

theorem radialSmoothCutoff_fderiv_eq_zero_of_two_mul_le_norm [NormedSpace ℝ E]
    {R : ℝ} (hR : 0 < R) {x : E} (hx : 2 * R ≤ ‖x‖) :
    fderiv ℝ (radialSmoothCutoff R : E → ℝ) x = 0

Exact module and namespace context

Lean proof · radialSmoothCutoff_fderiv_eq_zero_of_two_mul_le_norm

Actual proof outline: Recognize a global, hence local, minimum: `Filter.Eventually.of_forall` turns the inequality at all points into the neighborhood inequality defining a local minimum. Apply the totalized form of Fermat's rule: This exact library theorem handles both differentiability cases. The ASTIS proof supplies the local-minimum premise.

Braces mark parameters Lean can infer; square brackets request structures such as a measurable space or probability measure. Named hypotheses are mathematical premises, not facts established by this declaration. Section parameters are described in the mathematical hypotheses above; the module link retains their exact source context.

theorem radialSmoothCutoff_fderiv_eq_zero_of_two_mul_le_norm [NormedSpace ℝ E]
    {R : ℝ} (hR : 0 < R) {x : E} (hx : 2 * R ≤ ‖x‖) :
    fderiv ℝ (radialSmoothCutoff R : E → ℝ) x = 0 := by
  apply IsLocalMin.fderiv_eq_zero
  change ∀ᶠ y in 𝓝 x, radialSmoothCutoff R x ≤ radialSmoothCutoff R y
  rw [radialSmoothCutoff_eq_zero_of_two_mul_le_norm hR hx]
  exact Filter.Eventually.of_forall fun y => (radialSmoothCutoff_mem_Icc R y).1

/-- The support of the radial cutoff lies in the closed ball of radius `2 * R`. -/

Exact module and namespace context

Scope and omitted-condition boundaries

  • On a general normed space this statement does not itself establish differentiability.
  • No strict inequality or omission of the boundary sphere should be substituted for the existing statement.

Source and reuse

ASTIS parents called

Mathlib API called (external library)

  • IsLocalMin.fderiv_eq_zero
  • Filter.Eventually.of_forall
  • fderiv_zero_of_not_differentiableAt

Mathematical sources

ASTIS prose is not a quotation or a source-equivalence certificate. Definitions and aliases are explained as constructions, not counted as new mathematical proofs.