Imports
/- Copyright (c) 2026 Lazar Milikic. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Lazar Milikic -/ module public import Physlib.SpaceAndTime.Space.Norm.Basic

Iterated Laplacians of norm distributions

i. Overview

This file proves the distributional identity corresponding to the classical odd-dimensional formula that, in dimension 2 * m + 1, applying the Laplacian m + 1 times to the norm gives a nonzero constant multiple of the Dirac delta at the origin.

ii. Key results

    iterated_distLaplacian_norm_zpow_odd_eq_smul_diracDelta : The (m + 1)-fold Laplacian of the norm in dimension 2 * m + 1 is a nonzero multiple of the Dirac delta.

iii. Table of contents

    A. The odd-dimensional iterated Laplacian of the norm

iv. References

@[expose] public section

A. The odd-dimensional iterated Laplacian of the norm

m:k:hk:k < mh:1 - 2 * k - 2 + (2 * m + 1) 0(1 - 2 * k - 2 + (2 * m + 1)) 0 All goals completed! 🐙

The scalar factor in the odd-dimensional iterated Laplacian of the norm is nonzero.

m:h:1 - 2 * m 01 - 2 * m 0 All goals completed! 🐙 m:2 * m + 1 0 exact_mod_cast (m:2 * m + 1 0 All goals completed! 🐙 : (2 * m + 1 : ) 0) m:volume.real (Metric.ball 0 1) 0 All goals completed! 🐙
distDiv (distOfFunction (fun x => (1 * x ^ (1 - 2)) basis.repr x) ) = ((1 - 2 * 0) * (2 * 0 + 1) * volume.real (Metric.ball 0 1)) diracDelta 0 distDiv (distOfFunction (fun x => x ^ (1 - 2) basis.repr x) ) = ((1 - 2 * 0) * (2 * 0 + 1) * volume.real (Metric.ball 0 1)) diracDelta 0 ((1 - 2 * 0) * (2 * 0 + 1) * volume.real (Metric.ball 0 1)) diracDelta 0 = (1 * volume.real (Metric.ball 0 1)) diracDelta 0 ((1 - 2 * 0) * (2 * 0 + 1) * volume.real (Metric.ball 0 1)) diracDelta 0 = (1 * volume.real (Metric.ball 0 1)) diracDelta 0 x:𝓢(Space (2 * 0 + 1), )(((1 - 2 * 0) * (2 * 0 + 1) * volume.real (Metric.ball 0 1)) diracDelta 0) x = ((1 * volume.real (Metric.ball 0 1)) diracDelta 0) x All goals completed! 🐙 m:Δᵈ (distOfFunction (fun x => x ^ (1 - 2 * (m + 1))) ) = ((1 - 2 * (m + 1)) * (2 * (m + 1) + 1) * volume.real (Metric.ball 0 1)) diracDelta 0 m:x✝:Space (2 * (m + 1) + 1)x✝ ^ (1 - 2 * (m + 1)) = x✝ ^ (-((2 * m.succ + 1) - 2))m:1 - 2 * (m + 1) = -((2 * m.succ + 1) - 2)m:2 * (m + 1) + 1 = (2 * m.succ + 1) m:x✝:Space (2 * (m + 1) + 1)x✝ ^ (1 - 2 * (m + 1)) = x✝ ^ (-((2 * m.succ + 1) - 2)) m:x✝:Space (2 * (m + 1) + 1)x✝ ^ (1 - 2 * (m + 1)) = x✝ ^ (2 - (2 * (m + 1) + 1)); All goals completed! 🐙 m:1 - 2 * (m + 1) = -((2 * m.succ + 1) - 2) m:1 - 2 * (m + 1) = 2 - (2 * (m + 1) + 1); All goals completed! 🐙 m:2 * (m + 1) + 1 = (2 * m.succ + 1) All goals completed! 🐙m:k:ih: (hk : k m), (⇑Δᵈ)^[k] (distOfFunction (fun x => x ^ 1) ) = (∏ j Finset.range k, (1 - 2 * j) * (1 - 2 * j - 2 + (2 * m + 1))) distOfFunction (fun x => x ^ (1 - 2 * k)) hk:k + 1 mhk_le:k mhdist:distOfFunction (fun x => x ^ (1 - 2 * k - 2)) = distOfFunction (fun x => x ^ (1 - 2 * (k + 1))) ((∏ j Finset.range k, (1 - 2 * j) * (1 - 2 * j - 2 + (2 * m + 1))) * ((1 - 2 * k) * (1 - 2 * k - 2 + (2 * m + 1)))) distOfFunction (fun x => x ^ (1 - 2 * (k + 1))) = ((∏ x Finset.range k, (1 - 2 * x) * (1 - 2 * x - 2 + (2 * m + 1))) * ((1 - 2 * k) * (1 - 2 * k - 2 + (2 * m + 1)))) distOfFunction (fun x => x ^ (1 - 2 * (k + 1))) All goals completed! 🐙

In dimension 2 * m + 1, the (m + 1)-fold distributional Laplacian of the distribution induced by the norm is a nonzero multiple of the Dirac delta at the origin.

m:((∏ j Finset.range m, (1 - 2 * j) * (1 - 2 * j - 2 + (2 * m + 1))) * ((1 - 2 * m) * (2 * m + 1) * volume.real (Metric.ball 0 1))) diracDelta 0 = oddNormIteratedLaplacianCoeff m diracDelta 0 m:((∏ j Finset.range m, (1 - 2 * j) * (1 - 2 * j - 2 + (2 * m + 1))) * ((1 - 2 * m) * (2 * m + 1) * volume.real (Metric.ball 0 1))) diracDelta 0 = ((∏ k Finset.range m, (1 - 2 * k) * (1 - 2 * k - 2 + (2 * m + 1))) * ((1 - 2 * m) * (2 * m + 1) * volume.real (Metric.ball 0 1))) diracDelta 0 All goals completed! 🐙