Alphabeta Math
LemmaStatement: Literature-sourcedProof: AI-adaptedPipeline-generatedverified 2026-10-22 (gpt-6.1-sol)
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Strict smooth approximation in BV

Statement

Assume Countable Choice. For every open Ω⊆Rn and u∈BV(Ω) there is a sequence uk∈C∞(Ω) such that uk→u in L1(Ω) and ∫Ω∣∇uk∣ dx→TV(u;Ω). When Ω=Rn, the approximating functions may be chosen compactly supported.

Facts & Assumptions

Given: Countable Choice, an open set Ω⊆Rn, and u∈BV(Ω).

[A1]

Countable Choice is used by the Lebesgue regularity and approximate-identity suppliers below. (The Axiom of Countable Choice (ACω))

[F1]

Under Countable Choice, Lebesgue measure on Rn is Radon and regular, with finite measure on bounded sets. (Lebesgue measure is a Radon measure on R^n)

[F3]

Convolution of a locally integrable function with a mollifier is smooth and differentiates under the integral sign. (Convolution with a mollifier is smooth, and derivatives pass under the integral sign)

[F4]

For nonnegative product-measurable functions on sigma-finite spaces, product and iterated integrals agree. (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product)

[F5]

The distributional variation equals the test-field supremum and is lower semicontinuous under L1 convergence. (Test-field formula and L1 lower semicontinuity of spatial TV)

[F6]

Every open Euclidean set has a locally finite nonnegative smooth partition of unity with compact supports. (Locally finite smooth partitions of unity on Euclidean open sets)

[F7]

Smooth cutoffs exist on nested balls, including cutoffs equal to one on a smaller ball. (A smooth bump between concentric Euclidean balls)

[F8]

If w∈C(Ω;Rn)∩L1(Ω;Rn), then w dx is a finite vector Radon measure and its partition variation is ∣w∣ dx. The upper bound follows from the triangle inequality. For the reverse bound, partition the unit sphere into finitely many Borel sets of diameter below η, project each vector integral onto a representative direction, and let η↓0. The weighted measure ∣w∣ dx is finite; truncating its density and using Lebesgue regularity gives outer approximation on Borel sets and compact inner approximation on open sets, hence Radon regularity. Finiteness upgrades compact approximation to all Borel sets: for Borel A, choose compact C⊂Ω with ρ(Ω∖C)<ϵ/2 and open G⊃Ω∖A with ρ(G∩A)<ϵ/2, where ρ=∣w∣ dx; then C∖G is compact in A and ρ(A∖(C∖G))<ϵ. (Lebesgue measure is a Radon measure on R^n)

Proof

Given: Countable Choice, Ω, and u as stated.

1.1F6givenchoose

If Ω=∅, take the zero sequence. If n=0 and Ω≠∅, its singleton supports u itself, which is smooth, has zero gradient and variation, and gives the required constant sequence. Assume henceforth n≥1. By [F6], take a countable locally finite nonnegative smooth partition of unity (ηj)j≥1 on Ω, with each ηj compactly supported in Ω.

2.1A1F2F3F6step 1.1chooseconstruct

Fix δ>0. Extend each wj:=ηju by zero to Rn. Fix a nonnegative unit-mass smooth bump ρ and its rescalings ρε. For each j, the approximate-identity property [F2] gives wj∗ρε→wj in L1, and also (u∇ηj)∗ρε→u∇ηj in L1. Choose the least nonnegative integer mj for which εj:=2−mj is small enough that εj<2−j, the convolution supports remain in Ω, and ∥wj∗ρεj−wj∥1+∥(u∇ηj)∗ρεj−u∇ηj∥1<2−jδ. Set uδ:=∑jwj∗ρεj. This sum is locally finite: for a compact C⋐Ω, choose r>0 so its closed r-neighborhood Cr is compactly contained in Ω. For all sufficiently large j, εj<r; if the thickened support of wj meets C, then supp⁡ηj meets Cr, and local finiteness of (ηj) leaves only finitely many such indices. Thus uδ is smooth by [F3]. Summing the first error terms and using ∑jηj=1 gives ∥uδ−u∥L1(Ω)<δ.

3.1F1F4step 2.1algebra

The product rule follows by testing against Cc∞: D(ηju)=ηjDu+u∇ηj dx. Convolution commutes with distributional derivatives by the defining test pairing and Tonelli [F4] applied to positive and negative parts. These interchanges are product-measurable: each localized L1 density depends only on its own integration variable, and all remaining kernel and smooth test factors are Borel on the product. Absolute integrability follows from the compact supports, the L1 density norms and the finite coordinate variations. Thus [F4] applies before making the interchange. Since ∑jηj=1, local finiteness gives ∑ju∇ηj=0. Therefore ∇uδ=∑j(ηjDu)∗ρεj+∑j((u∇ηj)∗ρεj−u∇ηj). For the first sum, ∣(ηjDu)∗ρεj∣≤(ηj∣Du∣)∗ρεj pointwise, so Tonelli and ∑jηj=1 bound its L1 norm by ∣Du∣(Ω). The second sum has L1 norm below δ by the choices in step 2.1. Hence ∫Ω∣∇uδ∣ dx≤TV(u;Ω)+δ.

4.1A1F5F7F8step 2.1step 3.1chooseconstruct∎

Take δk=1/(k+1) for k∈N and set uk=uδk. Step 2.1 gives uk→u in L1, while step 3.1 gives lim sup⁡k∫Ω∣∇uk∣ dx≤TV(u;Ω). For each k, integration by parts against compactly supported smooth tests identifies Duk=∇uk dx. Since ∇uk is continuous and integrable by step 3.1, [F8] gives uk∈BV(Ω) and TV(uk;Ω)=∫Ω∣∇uk∣ dx. The choice-free lower-semicontinuity clause of [F5], now applied to uk,u∈BV(Ω), gives the reverse inequality. Thus the variations converge. For Ω=Rn, choose a smooth cutoff χR equal to one on B(0,R), supported in B(0,2R), and satisfying ∣∇χR∣≤C/R, using [F7]. Since each u1/(2(k+1)) and its gradient are integrable, choose Rk so its L1 tail, gradient tail, and C∥u1/(2(k+1))∥1/Rk are all below 1/(k+1). The products χRku1/(2(k+1)) are compactly supported and smooth, converge to u in L1, and have gradient integrals bounded above by TV(u;Rn)+O(1/(k+1)); [F8] puts them in BV(Rn) and lower semicontinuity gives convergence of their variations as well.

Depends on

Used by

Dependency tree · two levels

56 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.

Sources