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Samplinglib mathematical lesson

The radial cutoff vanishes on and beyond the outer sphere

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

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Mathematical statement

Let E be a normed additive commutative group and let R>0. For every x∈E with 2R≤‖x‖, the radius-R cutoff vanishes.

\[R>0,\ 2R\le\|x\|\quad\Longrightarrow\quad\chi_R(x)=0.\]
Lean statement · radialSmoothCutoff_eq_zero_of_two_mul_le_norm

The inequality is non-strict, so the exported zero region includes the boundary sphere of radius 2R. No differentiable structure on E is needed for this value assertion. 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_eq_zero_of_two_mul_le_norm {R : ℝ} (hR : 0 < R) {x : E}
    (hx : 2 * R ≤ ‖x‖) : radialSmoothCutoff R x = 0

Exact module and namespace context

Proof roadmap

  1. 1Put the radial argument outside the scalar support region

    The radial argument is nonnegative. Dividing the assumed inequality by the positive radius shows it is at least two.

  2. 2Apply scalar vanishing

    The scalar cutoff vanishes whenever the argument has absolute value at least two. Applying that fact gives the desired zero value.

Full assumptions and notation

All objects and hypotheses

  • E is a normed additive commutative group.
  • R∈ℝ, R>0, x∈E, and 2R≤‖x‖.

Mathematical proof

1. Put the radial argument outside the scalar support region

The radial argument is nonnegative. Dividing the assumed inequality by the positive radius shows it is at least two.

\[\left|\frac{\|x\|}{R}\right|=\frac{\|x\|}{R}\ge\frac{2R}{R}=2.\]
Corresponding Lean step

rw [abs_of_nonneg (div_nonneg (norm_nonneg x) hR.le)]; calc (2 : ℝ) = 2 * R / R := by field_simp; _ ≤ ‖x‖ / R := div_le_div_of_nonneg_right hx hR.le

2. Apply scalar vanishing

The scalar cutoff vanishes whenever the argument has absolute value at least two. Applying that fact gives the desired zero value.

\[\chi_R(x)=q(\|x\|/R)=0.\]
Corresponding Lean step

apply smoothUnitCutoff_eq_zero_of_two_le_abs

Lean verification

The exact proof begins folded immediately after the mathematical argument; the statement is folded beside the claim above.

Lean proof · radialSmoothCutoff_eq_zero_of_two_mul_le_norm

Actual proof outline: Put the radial argument outside the scalar support region: The proof uses positivity both to remove absolute values and to preserve the inequality on division. `field_simp` verifies cancellation of the nonzero radius. Apply scalar vanishing: This is a radial substitution into the scalar zero-value theorem.

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.

Download module (.lean)
theorem radialSmoothCutoff_eq_zero_of_two_mul_le_norm {R : ℝ} (hR : 0 < R) {x : E}
    (hx : 2 * R ≤ ‖x‖) : radialSmoothCutoff R x = 0 := by
  apply smoothUnitCutoff_eq_zero_of_two_le_abs
  rw [abs_of_nonneg (div_nonneg (norm_nonneg x) hR.le)]
  calc
    (2 : ℝ) = 2 * R / R := by field_simp
    _ ≤ ‖x‖ / R := div_le_div_of_nonneg_right hx hR.le

Exact module and namespace context

Scope and omitted-condition boundaries
  • Zero at a boundary point is not a claim of local constancy there.
Sources, dependencies, and reuse

Source and reuse

Samplinglib parents called

Mathlib API called (external library)

  • div_le_div_of_nonneg_right
  • abs_of_nonneg

Mathematical sources

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