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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.

Spatial BV, finite perimeter, and TV conventions

1 · Prerequisites

2 · Logical flowchart

3 · Definitions, theorems and proofs

LemmaStatement: Literature-sourcedProof: AI-adaptedverified 2026-10-22 (gpt-6.1-sol)Open item page →

Uniqueness of a Radon measure representing a distribution

Statement

Let Ω⊆Rn be open. If two finite signed Radon measures on Ω have the same integrals against every function in Cc∞(Ω), then the measures are equal.

Facts & Assumptions

Given: An open set Ω⊆Rn and finite signed Radon measures μ,ν whose integrals agree on every compactly supported smooth test function.

[F1]

Under the repository convention, each finite signed Radon measure has finite total variation on Ω, and that total-variation measure is regular on all Borel sets. This all-Borel approximation follows already from the finite Radon convention: for a finite positive Radon measure ρ, a Borel A, and ϵ>0, choose compact C⊂Ω with ρ(Ω∖C)<ϵ/2, and open G⊃Ω∖A with ρ(G∩A)<ϵ/2. Then K=C∖G is compact in A and ρ(A∖K)<ϵ. For λ=μ−ν, the partition definition gives ∣λ∣≤∣μ∣+∣ν∣, so ∣λ∣ is finite and regular as well: compact inner and open outer approximations for the finite regular sum ∣μ∣+∣ν∣ also approximate ∣λ∣. (Regular complex Borel measures, Radon measure on an LCH space)

[F3]

A smooth bump can equal one on an inner ball and vanish outside a larger ball. (A smooth bump between concentric Euclidean balls)

[F4]

Dominated convergence applies to bounded pointwise-convergent cutoffs against the finite measure ∣λ∣. (Dominated convergence)

Proof

Given: The open set Ω and finite signed Radon measures μ,ν with equal integrals on smooth compactly supported tests.

1.1F1F2F3F4givenchooseconstruct

If Ω=∅, equality is immediate. If n=0 and Ω≠∅, its singleton indicator is a smooth compactly supported test and determines every measure. Assume henceforth n≥1. Set λ:=μ−ν. If K⊂Ω is compact and nonempty, then for every sufficiently large m, rational inner balls with doubled closures in Ω∩{x:dist⁡(x,K)<1/m} cover K; [F2] gives a finite subcover, and ordering finite rational lists by natural-number codes gives a least such cover. Put the fixed bump [F3] on each selected ball and combine them as ηm=1−∏j(1−ψm,j). Then 0≤ηm≤1, it equals one on K, is supported in the 1/m-neighborhood of K, and ηm(x)→1K(x). Since each ηm is a smooth compactly supported test function, ∫ηm dλ=0; dominated convergence [F4] with respect to the finite regular total-variation measure [F1] gives λ(K)=0. The empty compact set has measure zero directly.

2.1F1step 1.1given∎

For any Borel A⊆Ω and ε>0, inner regularity of ∣λ∣ [F1] gives a compact K⊆A with ∣λ∣(A∖K)<ε. Since step 1.1 gives λ(K)=0, we have ∣λ(A)∣≤∣λ∣(A∖K)<ε. Thus λ(A)=0 for every Borel A, so μ=ν.

LemmaStatement: Literature-sourcedProof: AI-adaptedverified 2026-10-22 (gpt-6.1-sol)Open item page →

Variation of a finite vector Radon measure is Radon

Statement

Let Ω⊆Rn be open and let μ=(μ1,…,μm) have finite signed Radon coordinate measures. For Borel A⊆Ω define V(A):=sup⁡{∑j=1∞∣μ(Aj)∣:(Aj)j≥1 is a Borel partition of A}, where the norm is Euclidean. Then V is a finite positive Radon measure and V(Ω)=sup⁡{∫Ωf⋅dμ:f∈Cc(Ω;Rm), ∣f(x)∣≤1}.

Facts & Assumptions

Given: An open set Ω⊆Rn and a finite tuple of finite signed Radon measures μi.

[F1]

For each coordinate, ∣μi∣ is a finite positive Radon measure. Finiteness upgrades its open-set compact approximation to all Borel sets: for a finite positive Radon measure ρ, Borel A and ϵ>0, choose compact C⊂Ω with ρ(Ω∖C)<ϵ/2, and open G⊃Ω∖A with ρ(G∩A)<ϵ/2. Then C∖G is compact in A and misses mass below ϵ. Thus each ∣μi∣ is regular on all Borel sets. The finite sum λ=∑i∣μi∣ is also regular: choose a compact subset of A for each coordinate and take their finite union for inner approximation, and intersect their open supersets for outer approximation, allocating error ϵ/m when m>0. (Radon measure on an LCH space, Regular complex Borel measures, The total variation of a signed or complex measure is a positive measure)

[F2]

Step 3.1 shows that V is a regular Borel measure, with compact inner approximation on all Borel sets. (Regular Borel measure on an LCH space)

Proof

Given: The open set Ω and finite signed Radon coordinate measures μi.

1.1F1givenalgebra

If m=0, the vector measure and V vanish and the zero field gives the asserted supremum. If Ω=∅, the conclusion is immediate. If n=0 and Ω≠∅, then Ω is a singleton, V(Ω)=∣μ(Ω)∣, and the constant field μ(Ω)/∣μ(Ω)∣ attains the supremum when the vector is nonzero (use the zero field otherwise). Assume henceforth n,m≥1. For every Borel A and every countable Borel partition (Aj) of A, the Euclidean norm satisfies ∣μ(Aj)∣≤∑i=1m∣μi(Aj)∣. Summing over j gives V(A)≤λ(A) for λ:=∑i=1m∣μi∣, so V is finite and V(Ω)<∞.

2.1F1step 1.1givenchoose

If A=⨆k≥1Ek is a disjoint Borel union, then intersecting any partition of A with each Ek and using countable additivity of each coordinate shows V(A)≤∑kV(Ek). Conversely, for fixed N and ε>0, choose for each of the finitely many k≤N a partition of Ek whose sum exceeds V(Ek)−ε/N. Their union, together with A∖⋃k≤NEk, is a partition of A, so V(A)≥∑k≤NV(Ek)−ε. Letting ε↓0 and then N→∞ proves countable additivity. Thus V is a finite positive Borel measure.

2.2step 1.1givenchoose

For every f∈Cc(Ω;Rm) with ∣f∣≤1, approximate f uniformly by finite-valued Borel simple functions whose values have norm at most one. The partition definition bounds each simple integral by V(Ω), and finiteness of the coordinate measures lets the uniform errors tend to zero. Hence the displayed supremum is at most V(Ω).

3.1F1step 1.1step 2.1given

Since V≤λ and λ=∑i∣μi∣ is a finite regular Borel measure by [F1], for every Borel A and ε>0 there is compact K⊆A with λ(A∖K)<ε, whence V(A∖K)<ε. There is also an open G⊇A with λ(G∖A)<ε, whence V(G∖A)<ε. Thus V is a regular Borel measure in the sense of Regular Borel measure on an LCH space, and in particular a Radon measure.

4.1F1F2step 3.1chooseconstruct∎

If V(Ω)=0, the zero field proves the reverse inequality. Otherwise fix 0<ε<V(Ω)/4 and choose a countable Borel partition (Aj) with sum greater than V(Ω)−ε; truncate after N≥1 so the tail is below ε. Omit indices with μ(Aj)=0 or V(Aj)≤ε/(4N); the sum of the omitted partition values is at most ε/4. For every retained index, compact inner regularity [F2] gives a nonempty compact Kj⊂Aj with V(Aj∖Kj)<ε/(8N). Since there are finitely many pairwise disjoint compact sets Kj in the metric space Ω, choose pairwise disjoint open neighborhoods Nj with compact closures in Ω. Outer regularity [F2] gives open Gj⊃Kj with V(Gj∖Kj)<ε/(8N). Put Uj=Gj∩Nj. Then Kj⊂Uj, V(Uj∖Kj)<ε/(8N), and the closures of the Uj remain pairwise disjoint compact subsets of Ω. Define ψj(x):=dist⁡(x,Ω∖Uj)dist⁡(x,Ω∖Uj)+dist⁡(x,Kj). This is continuous and compactly supported, equals one on Kj, and vanishes outside Uj. Set ej=μ(Aj)/∣μ(Aj)∣ and f=∑jejψj. The disjoint closures of the Uj imply disjoint supports and ∣f∣≤1. For bounded Borel vector fields, the partition definition and uniform simple-function approximation give ∣∫g⋅dμ∣≤∫∣g∣ dV. Thus replacing ej1Aj by ejψj loses at most V(Aj∖Kj)+V(Uj∖Kj) for each retained j. Summing these errors, the omitted terms, and the tail gives ∫f⋅dμ>V(Ω)−3ε. Letting ε↓0 proves the reverse bound.

LemmaStatement: Literature-sourcedProof: AI-adaptedverified 2026-10-22 (gpt-6.1-sol)Open item page →

Locally finite smooth partitions of unity on Euclidean open sets

Statement

If an open set Ω⊆Rn is covered by a countable family of open sets (Vℓ)ℓ∈I, then there is a countable locally finite family of nonnegative functions (ηj)⊂Cc∞(Ω) summing to one, with each supp⁡ηj contained in one member Vℓ of the cover. Locally finite means that each point has a neighborhood meeting only finitely many supports.

Facts & Assumptions

Given: An open set Ω⊆Rn and a countable open cover of Ω.

[F3]

For n≥1, a smooth cutoff exists between any two concentric balls whose closures are nested. (A smooth bump between concentric Euclidean balls)

Proof

Given: The open set Ω and its countable open cover.

1.1F1givenalgebra

If Ω=∅, the empty family proves the claim. If n=0 and Ω≠∅, then Ω=R0 is a singleton; choose one cover member containing it and the single function η=1, which is smooth and compactly supported. Thus assume n≥1 and Ω≠∅. For m≥1 set Km={x:∣x∣≤m, dist⁡(x,Ωc)≥1/m} when Ω≠Rn, and set Km=B‾(0,m) when Ω=Rn; put Km=∅ for m≤0. Each Km is compact by [F1], the sets are nested, Km⊂int⁡Km+1, and their interiors cover Ω. The compact shells Sm:=Km∖int⁡Km−1 cover Ω and lie in the open sets Um:=int⁡Km+1∖Km−2. The family (Um) is locally finite: any compact subset of Ω lies in some int⁡KN and hence in Km−2 for all sufficiently large m.

2.1F2F3step 1.1chooseconstruct

Fix once a smooth nonnegative cutoff θ equal to one on B‾(0,1) and supported in B(0,2), whose existence is [F3]. In each Um, consider the rational inner balls B(q,r) for which B‾(q,2r)⊂Um∩Vℓ for some cover index ℓ. Indexed by (ℓ,q,r), these balls form a countable cover of Sm: for each point choose a cover member containing it, then density [F2] gives a rational center and radius with the required doubled closure. Compactness of Sm gives a finite subcover. Order all finite lists of eligible indexed balls by natural-number codes and take the first list covering Sm; thus no choice principle is needed. For each selected ball use the fixed rescaled cutoff ψm,j(x):=θ((x−q)/r). The family is locally finite because each shell contributes finitely many cutoffs supported in Um, and each support also lies in its assigned cover member. Its sum s:=∑m,jψm,j is smooth and positive on Ω because the shells cover Ω.

3.1step 2.1algebra∎

Define ηm,j:=ψm,j/s. Then each function is smooth, nonnegative and compactly supported in Ω, the family is locally finite, and ∑m,jηm,j=1. Each support remains in its assigned cover member, and enumeration gives the required countable family.

LemmaStatement: Literature-sourcedProof: AI-adaptedverified 2026-10-22 (gpt-6.1-sol)Open item page →

Smooth compactly supported functions are dense in C0 on an open Euclidean set

Statement

For every open set Ω⊆Rn, the space Cc∞(Ω) is dense in C0(Ω) in the uniform norm.

Facts & Assumptions

Given: An open set Ω⊆Rn and a continuous function on Ω that vanishes at infinity.

[F2]

For n≥1, a smooth bump can be chosen equal to one on an inner ball and supported in a larger ball. (A smooth bump between concentric Euclidean balls)

Proof

Given: The open set Ω and f∈C0(Ω).

1.1F1F2givenchooseconstruct

If Ω=∅, the zero function suffices. If n=0 and Ω≠∅, then its singleton supports every function and every function is smooth, so take the approximant f itself. Assume n≥1. Let f∈C0(Ω) and ε>0. The set K:={x∈Ω:∣f(x)∣≥ε/3} is compact by the definition of vanishing at infinity. If K=∅, the zero function approximates f within ε/3. Otherwise cover K by finitely many inner balls whose doubled closed balls lie in Ω, using compactness [F1]. Choose the corresponding bumps from [F2] and combine them as χ:=1−∏j(1−χj). Then χ∈Cc∞(Ω) and χ=1 on K, so ∥f−χf∥∞≤ε/3.

2.1F1F2step 1.1chooseconstructalgebra∎

Put g=χf and L=supp⁡g⋐Ω. If L=∅, take the zero approximant. Otherwise, for each x∈L, continuity gives rx>0 such that B‾(x,2rx)⊂Ω and ∣g(y)−g(x)∣<ε/3 on B(x,2rx). Finitely many inner balls B(xj,rj) cover L. By [F2], let ψj be nonnegative smooth bumps equal to one on those inner balls and supported in their doubled balls. The sum s=∑jψj is positive on a neighborhood of L. Repeating the finite cutoff construction of step 1.1 inside the open set {s>0} gives ζ∈Cc∞({s>0}) with 0≤ζ≤1 and ζ=1 on L. Define a=ζ s−1∑jg(xj)ψj on {s>0} and extend it by zero. Its compact support lies in Ω, and the extension is smooth because supp⁡ζ⋐{s>0}. Where s>0, the weighted average differs from g(y) by at most ε/3, since each nonzero weight has ∣g(xj)−g(y)∣<ε/3. Also ζg=g everywhere, because ζ=1 on supp⁡g. Therefore ∥a−g∥∞≤ε/3, and step 1.1 gives ∥a−f∥∞≤2ε/3<ε. This uses only finitely many balls, bumps and sampled values, with no integration or infinite selection.

LemmaStatement: Literature-sourcedProof: AI-adaptedverified 2026-10-22 (gpt-6.1-sol)Open item page →

Loomis–Whitney integral inequality

Statement

Assume Countable Choice. Let n≥2. For each i∈{1,…,n} let gi:Rn−1→[0,∞) be Lebesgue-measurable and integrable, with its arguments identified with all coordinates except xi. Then ∫Rn∏i=1ngi(x1,…,xi^,…,xn)1/(n−1) dx≤∏i=1n(∫Rn−1gi)1/(n−1).

Facts & Assumptions

Given: Countable Choice and an integer n≥2 and nonnegative integrable functions gi on the coordinate hyperplanes.

[F1]

Tonelli applies to nonnegative product-measurable functions on sigma-finite measure spaces. Under Countable Choice, Euclidean Lebesgue measure is the completion of each product of its coordinate factors. In particular Borel functions on a Euclidean product are product-measurable and their product integrals equal their Euclidean integrals. (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product, The Euclidean Lebesgue measure is the completion of the product of the factor Lebesgue measures)

[F3]

Under Countable Choice, Lebesgue measure is the completion of its Borel restriction, and every completion-measurable function has a base-measurable representative. Thus each nonnegative finite Lebesgue-measurable gi has a nonnegative finite Borel representative equal almost everywhere. (L(Rn) is exactly the completion of the restriction of λn to the Borel sets, A function measurable for a completion is almost everywhere equal to one measurable for the original sigma-algebra)

[A2]

Countable Choice is used in the Borel-representative and Euclidean-product identification suppliers. No unqualified choice-free Lebesgue product identity is asserted. (The Axiom of Countable Choice (ACω))

[F2]

For nonnegative integrable functions, Hölder's inequality bounds the integral of a product by the product of the corresponding norms. (Holder's inequality for integrals, including the endpoint cases)

[A1]

For the induction step in dimension n≥3, assume the inequality in dimension n−1.

Proof

Given: Countable Choice, the integer n and nonnegative integrable coordinate functions gi.

1.1A2F1F3givenbase

First replace the gi by their Borel representatives from [F3], setting each representative to zero on its Borel set of nonfinite or negative values. The exceptional sets lie in Borel null sets Ni. Their coordinate lifts are null in Rn: intersect Ni×R with slabs Ni×[−k,k], k≥1, and apply the product rectangle formula in [F1], then take their countable union and permute coordinates. Completeness in [F1] therefore makes the original product Lebesgue-measurable with the same integral as the Borel product; the right-hand integrals are unchanged as well. We may henceforth assume all inputs Borel. For n=2, Tonelli [F1] factors the left side as (∫Rg1)(∫Rg2), which is the right side.

2.1A1F1F2step 1.1givenIH

For n≥3, assume [A1]. For i<n define hi(x1,…,xi^,…,xn−1):=∫Rgi(x1,…,xi^,…,xn−1,xn) dxn. Apply Tonelli [F1] using the Borel sigma-algebras: each hi is Borel and integrable, possibly infinite on a Borel null set. Set it to zero there. The lifted exceptional sets in Rn−1 are null by the slab argument of step 1.1. Consequently all the following sectional inequalities hold almost everywhere, and the modified hi are admissible finite inputs for [A1]. Applying Hölder [F2] in xn to the first n−1 factors and then Tonelli gives an upper bound for the left side of ∫Rn−1gn(x′)1/(n−1)∏i<nhi(xi^′)1/(n−1) dx′. Set H(x′):=∏i<nhi(xi^′)1/(n−2). Hölder in x′ with exponents (n−1)/(n−2) and n−1 bounds this by (∫H)(n−2)/(n−1)(∫gn)1/(n−1). The induction hypothesis [A1] bounds ∫H≤∏i<n(∫hi)1/(n−2), while Tonelli gives ∫hi=∫gi. Substitution yields the claimed product bound in dimension n.

3.1step 1.1step 2.1discharge-induction: step 2.1∎

Induction from the base case [step 1.1] through step 2.1 proves the inequality for every integer n≥2.

LemmaStatement: Literature-sourcedProof: AI-adaptedverified 2026-10-22 (gpt-6.1-sol)Open item page →

A zero distributional gradient is constant on a connected domain

Statement

Assume Countable Choice. Let Ω⊆Rn be open and connected. If u∈Lloc1(Ω) satisfies ∂iu=0 as a distribution for every coordinate i, then there is a constant c∈C such that u=c almost everywhere on Ω. If u is real-valued almost everywhere, c may be chosen in R.

Facts & Assumptions

Given: Countable Choice, an open connected Ω⊆Rn, and u∈Lloc1(Ω) with zero distributional gradient.

[A1]

Countable Choice is assumed for the local mollifier approximation. (The Axiom of Countable Choice (ACω))

[F1]

A smooth compactly supported cutoff exists between nested balls. (A smooth bump between concentric Euclidean balls)

[F2]

Zero distributional derivative means ∫u ∂iϕ=0 for every compactly supported smooth test function. (Distributional derivative)

[F3]

Mollification makes a locally integrable function smooth and differentiates by convolution on compactly contained subdomains. (Convolution with a mollifier is smooth, and derivatives pass under the integral sign)

[F5]

A connected space admits no separation into two disjoint nonempty relatively open subsets. (Separation of a topological space, connected and disconnected spaces, clopen sets, and connected subsets)

Proof

Given: The open connected set Ω and u∈Lloc1(Ω) with zero distributional gradient.

1.1A1F1F2F3givenconstruct

If Ω=∅, choose c=0. If n=0 and Ω≠∅, then Ω=R0 is a singleton and its function u is constant. Henceforth assume n≥1 and Ω≠∅. Let B⋐Ω be any open ball and choose concentric balls B⋐B′⋐B′′⋐Ω. By [F1] take χ∈Cc∞(B′′) equal to one on B′, and extend w:=χu by zero to Rn. For sufficiently small ε, every mollifier centered at a point of B is supported in B′. For such a point x, differentiating the convolution gives ∂i(w∗ρε)(x)=−∫B′u(y)∂yiρε(x−y) dy=0 by the distributional identity [F2]. Thus w∗ρε is constant on the convex ball B by the one-dimensional fundamental theorem along each segment.

2.1A1F4step 1.1choosealgebra

Since w=u on B′, the approximate-identity property [F4] gives w∗ρεj→u in L1(B) for a sequence εj↓0. Write each constant from step 1.1 as cj. The L1(B) convergence makes (cj) Cauchy because ∣B∣∣cj−ck∣≤∥cj−u∥L1(B)+∥ck−u∥L1(B). Its limit cB satisfies u=cB almost everywhere on B.

3.1F5F6step 2.1givenconstruct∎

If Ω=∅, any constant satisfies the conclusion. Otherwise fix one ball and let c be its almost-everywhere value. Let S be the set of points of Ω having a neighborhood on which u=c almost everywhere. It is nonempty and open. If x∈S‾∩Ω, choose a ball B⋐Ω containing x and a point of S; step 2.1 makes u almost everywhere constant on B, and its positive-measure intersection with a neighborhood from S forces that constant to be c. Thus x∈S, so S is relatively closed. Connectedness [F5] gives S=Ω. By the countable rational base [F6], choose a countable cover of Ω by rational balls contained in these neighborhoods; the union of their exceptional null sets is null, hence u=c almost everywhere on all of Ω. The constants cj and cB may be complex; completeness of C justifies their limits. When u is real almost everywhere on a nonempty domain, its a.e. constant c is real because each ball has positive measure.

LemmaStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-6-luna)verified 2026-10-22 (gpt-6.1-sol)Open item page →

Sequence compactness in L1 by finite cell averages

Statement

Assume Countable Choice. Let (vk) be a sequence in real L1(Rn), with sup⁡k∥vk∥1<∞, all zero almost everywhere outside one bounded set. If lim⁡r↓0sup⁡k, ∣h∣≤r∥vk(⋅+h)−vk∥1=0, then a subsequence converges in L1(Rn). This assertion does not require Dependent Choice.

Statement references

Facts & Assumptions

Given: The sequence and uniform translation continuity in the Statement; write M=sup⁡k∥vk∥1.

[A1]

Countable Choice allows choosing measurable representatives for a countable sequence of L1 classes. (The Axiom of Countable Choice (ACω))

[F3]

Ordinary recursion on a set with a specified initial value and deterministic successor rule constructs a unique sequence; this uses no dependent-choice instance. (The recursion theorem)

Proof

Given: The hypotheses above.

1.1F1F2givenconstructalgebra

For δ>0, tile Rn by the half-open cubes Q=δ(z+[0,1)n), z∈Zn, and let Aδv equal δ−n∫Qv on Q. The triangle inequality, followed by [F1] and the substitution y=x+h using [F2], gives ∥v−Aδv∥1≤δ−n∑Q∫Q∫Q∣v(x)−v(y)∣ dy dx≤δ−n∫[−δ,δ]n∥v(⋅+h)−v∥1 dh. Thus, writing ω(r)=sup⁡k,∣h∣≤r∥vk(⋅+h)−vk∥1, one has sup⁡k∥vk−Aδvk∥1≤2nω(nδ)→0 as δ↓0.

1.2F3givenconstruct

For each m≥1, only finitely many cubes of side 2−m meet a fixed ball containing the common supports; all other cell averages vanish. Enumerate all these cells at all levels by first increasing m and then lexicographic order of their integer coordinates. Each cell-average coefficient aj(k) is a bounded real sequence, with bound M divided by that cell's volume. Set S0=N and initialize k0=0. Recursively, at stage m≥1, partition the bounded ranges of the first m coefficients into finitely many half-open dyadic bins of width 2−m, adding an endpoint bin if necessary. Among the finitely many vector bins containing infinitely many indices in Sm−1, take the lexicographically first; let Sm be exactly that infinite set of indices. The finite pigeonhole principle guarantees existence and the specified order makes the rule unique. Then let km be the least member of Sm larger than km−1; such a member exists because Sm is infinite. This deterministic successor rule and initial pair (S0,k0) define the sequence recursively by [F3], with no dependent-choice instance. For fixed j and m≥j, all selected indices kq with q≥m lie in Sm, so their jth coefficients differ by at most 2−m. Consequently every coefficient converges and, at each fixed cell level ℓ, (A2−ℓvkm)m is Cauchy in L1, being a finite weighted sum of these coefficients.

2.1step 1.1step 1.2choosealgebra

Given ε>0, choose a cell level ℓ for which 2nω(n2−ℓ)<ε/3, using step 1.1. For sufficiently large a,b, step 1.2 gives ∥A2−ℓvka−A2−ℓvkb∥1<ε/3. The two approximation errors from step 1.1 then show ∥vka−vkb∥1<ε. Thus the subsequence is Cauchy.

3.1A1F1step 2.1constructalgebra∎

For completeness at exactly the stated axiom strength, choose representatives of this countable sequence by [A1]. Select a further subsequence gj with ∥gj+1−gj∥1<2−j, always choosing the least sufficiently late index, which exists by the Cauchy property. By [F1], ∑j∣gj+1−gj∣ is integrable and finite almost everywhere. Hence gj has a measurable almost-everywhere limit g; moreover ∣g∣≤∣g1∣+∑j∣gj+1−gj∣, so g∈L1, and ∥g−gj∥1≤∑i≥j2−i→0. The original Cauchy subsequence also converges to this L1 class by the triangle inequality. This proves the assertion using only [A1].

LemmaStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-6-luna)verified 2026-10-22 (gpt-6.1-sol)Open item page →

Lipschitz graph area and calculus under Countable Choice

Statement

Assume Countable Choice. Let m≥1, let Q⊆Rm be open, and let h:Q→R be locally Lipschitz. Then h is differentiable almost everywhere, its partial derivatives are measurable and are its weak derivatives. On every open region where h is L-Lipschitz, ∣Dh∣≤L almost everywhere. Let Hm denote the repository's unnormalised Hausdorff measure, put cm=Hm((0,1]m), and write σm=cm−1Hm also on Euclidean spaces containing m-dimensional subsets. The graph map F(y)=(y,h(y)) satisfies, for every nonnegative Borel a, ∫F(Q)a(x) dσm(x)=∫Qa(F(y))1+∣Dh(y)∣2 dy. For the epigraph G={(y,z):y∈Q, z>h(y)}, a smooth vector field compactly supported away from the chart sides satisfies ∫Gdiv⁡ϕ dx=∫Qϕ(y,h(y))⋅(Dh(y),−1) dy. Thus its outward normal is (Dh,−1)/1+∣Dh∣2 almost everywhere. The sign reverses for a subgraph. The graph surface measure is locally finite and Radon on F(Q) with its relative topology, and its null sets coincide with graph images of Lebesgue-null subsets of the base.

Facts & Assumptions

Given: Countable Choice and the locally Lipschitz graph in the Statement.

[F1]

A Lipschitz interval function is absolutely continuous and has a derivative almost everywhere; these conclusions assume at most Countable Choice. (C1 implies Lipschitz, Lipschitz implies absolutely continuous, and absolutely continuous implies continuous and bounded variation, Absolutely continuous functions have integrable derivatives)

[F3]

Lebesgue differentiation of locally integrable functions holds under Countable Choice. (Lebesgue differentiation theorem on Rn)

Proof

Given: The graph in the Statement. All local arguments take place in a box compactly contained in a region on which h is Lipschitz.

1.1F1F2givenconstruct

We first need the integral identity for Lipschitz interval functions without invoking the stronger published general absolutely continuous FTC. If b is L-Lipschitz on [a,d], extend it constantly past the endpoints. Its difference quotients are bounded by L and converge to b′ almost everywhere by [F1]. For any a≤s<t≤d, dominated convergence gives ∫stb′(r) dr=lim⁡ϵ↓01ϵ(∫tt+ϵb(r) dr−∫ss+ϵb(r) dr)=b(t)−b(s). Coordinate difference quotients of h are measurable; [F1] and [F2] show their limits gi exist almost everywhere, with ∣gi∣≤L. Define them to be zero on the exceptional sets. Applying the preceding identity and one-dimensional integration by parts on each line, then [F2], gives ∫h∂iη=−∫giη for smooth compactly supported η. The same line identities hold for every coordinate line of h, outside the appropriate line-null exceptional set of derivatives.

2.1F2F3step 1.1algebra

For a cube C of side 2r and a Lipschitz w, join x to y by the m coordinate segments replacing their coordinates in order. Step 1.1 bounds ∣w(x)−w(y)∣ by the sum of the line integrals of ∣∂iw∣. Integrate in x,y∈C. For coordinate i, the unused coordinates contribute (2r)m−1, while the measure of endpoint pairs whose interval contains a fixed coordinate value is at most (2r)2. Thus, after division by ∣C∣, the triangle inequality yields ∫C∣w−wC∣≤2r∑i=1m∫C∣∂iw∣, where wC is its mean. Outside a null set, g=(gi) has strong Lebesgue points: apply [F3] to its coordinates and to ∣g−q∣ for every rational vector q, then approximate g(x) by such q. The countable union of the exceptional null sets is null under Countable Choice. Ball differentiation also gives cube differentiation by the fixed volume comparison. At such a point x, set p=g(x) and w(y)=h(y)−h(x)−p⋅(y−x). The displayed inequality gives ∫C(x,r)∣w−wC∣=o(rm+1). As w(x)=0 and w has a fixed Lipschitz bound, a mean with ∣wC∣≥ϵr would give ∣w−wC∣≥ϵr/2 on a cube of side proportional to r centered at x, contradicting this estimate. Thus wC=o(r). If ∣w(y)∣≥ϵr at some y in the half cube, the Lipschitz bound gives the same contradiction on a cube of side proportional to r centered at y. Hence sup⁡C(x,r/2)∣w∣=o(r), proving differentiability with derivative p. Difference quotients then give ∣p∣≤L. Countably many rational boxes cover Q, so the assertion is global.

3.1step 2.1constructalgebra

We prove the area identity first for bounded Borel base sets within one L-Lipschitz box. On the differentiability set, for any 0<ϵ<1/4, form countably many Borel pieces on each of which Dh lies within ϵ of a fixed rational vector p, the differentiability remainder is at most ϵ∣z−y∣ whenever ∣z−y∣<1/k, and the points lie in one cube of diameter less than 1/k. Such pieces cover the differentiability set: the remainder condition follows from differentiability, can be tested on countably many rational z by continuity, and is measurable; use increasing integers k and a rational-vector enumeration. Subtract earlier pieces to make them disjoint. For two points y,z of a single piece E, set Apv=(v,p⋅v). Then ∣F(z)−F(y)−Ap(z−y)∣≤2ϵ∣z−y∣≤2ϵ∣Ap(z−y)∣. Consequently F∘Ap−1:Ap(E)→F(E) is at most (1+2ϵ)-Lipschitz, and its inverse is at most (1−2ϵ)−1-Lipschitz. The sets F(E) are Borel because F is a homeomorphism from Q onto its graph.

4.1F2F4step 3.1algebra

Choose an orthonormal coordinate system on the range plane of Ap. Its square coordinate matrix has determinant of absolute value Jp=det⁡(ApTAp)=1+∣p∣2. Thus [F4] gives σm(Ap(E))=Jp∣E∣. Apply [F4] to the two maps in step 3.1 to obtain (1−2ϵ)mJp∣E∣≤σm(F(E))≤(1+2ϵ)mJp∣E∣. The function p↦1+∣p∣2 is 1-Lipschitz, so ∣Jp−1+∣Dh(y)∣2∣≤ϵ on E. The excluded base-null set has graph image of zero σm by [F4], since F is Lipschitz. Sum the displayed inequalities over the disjoint pieces, using ∣p∣≤L+ϵ. The difference between σm(F(B)) and ∫B1+∣Dh∣2 is bounded by Cm,Lϵ∣B∣. Letting ϵ↓0 proves equality. Exhaustion and countable localization extend it to arbitrary Borel B⊆Q; indicator functions, simple functions and monotone convergence prove the asserted integral formula.

5.1F2step 1.1step 2.1step 4.1algebra∎

For a compactly supported smooth scalar b in the chart, vertical integration gives ∫G∂zb=−∫Qb(y,h(y)) dy. For a horizontal coordinate put Bi(y)=∫h(y)∞b(y,z) dz. This is Lipschitz and compactly supported in Q; step 2.1 and ordinary differentiation of the smooth integral give ∂iBi=∫h(y)∞∂ib dz−b(y,h(y))gi almost everywhere. Its weak derivative integrates to zero by step 1.1 and [F2]. Apply these identities to the components of ϕ and sum. Step 4.1 converts the resulting flux into the unit-normal formula. The graph measure is a graph pushforward of the locally bounded measurable density 1+∣Dh∣2 dy; compact and open approximation in the base show it is locally Radon on the graph with its relative topology. The density is between 1 and 1+L2 on every local box, which also proves the null-set assertion.

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Spatial BV and distributional total variation

Definition

Let Ω⊆Rn be open and let u∈L1(Ω;R), where elements of L1 are almost-everywhere equivalence classes. For each i∈{1,…,n}, its distributional derivative Diu acts on φ∈Cc∞(Ω) by ⟨Diu,φ⟩:=−∫Ωu ∂iφ dx. The function u is in BV(Ω) when each Diu is represented by a finite signed Radon measure and the resulting vector-valued measure Du=(D1u,…,Dnu) has finite total variation. Here a finite vector-valued Radon measure means that its partition variation is a finite Radon measure. For a Borel set A⊆Ω, define ∣Du∣(A):=sup⁡{∑j=1∞∣Du(Aj)∣: (Aj)j≥1 is a Borel partition of A}, using the Euclidean norm on each vector value. Define the spatial total variation by TV(u;Ω):=∣Du∣(Ω). A Lebesgue-measurable set E⊆Ω of finite measure has finite perimeter relative to Ω when χE∈BV(Ω); its relative perimeter is P(E;Ω):=TV(χE;Ω).

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A unit vector density has scalar variation measure

Statement

Let X be a locally compact second-countable metric space, let λ be a finite positive Radon measure on X, and let ν:X→Rm be continuous with ∣ν(x)∣=1 for every x. Define the vector measure μ(A):=∫Aν dλ on Borel sets. Its partition variation satisfies ∣μ∣=λ.

Facts & Assumptions

Given: A locally compact second-countable metric space X, a finite positive Radon measure λ, and a continuous unit-vector field ν.

[F1]

Here partition variation means V(A):=sup⁡{∑j∣μ(Aj)∣:(Aj)j≥1 is a Borel partition of A}, with empty parts allowed. This is the formula used in the Euclidean vector-Radon lemma; we prove the equality directly on X, without applying that lemma's Euclidean regularity conclusion to a general metric space. (Variation of a finite vector Radon measure is Radon)

[F2]

Each coordinate formula μi(A):=∫Aνi dλ defines a finite signed Borel measure. Countable additivity follows by dominated convergence for disjoint Borel unions, since ∣νi∣≤1 and λ(X)<∞. (Dominated convergence)

Proof

Given: The space X, the finite Radon measure λ, and the continuous unit field ν.

1.1F1F2givenalgebra

The coordinate measures are well-defined by [F2]. For every countable Borel partition (Aj) of a Borel set A, the triangle inequality for vector integrals gives ∑j∣μ(Aj)∣≤∑j∫Aj∣ν∣ dλ=λ(A). Taking the supremum in the definition [F1] gives V(A)≤λ(A).

2.1F1step 1.1chooseconstructalgebra

Fix a Borel A and 0<ε<1. Partition the unit sphere in Rm into finitely many Borel pieces Cj of diameter below ε, by intersecting it with a sufficiently fine finite grid of half-open boxes in [−1,1]m (including the outer faces). Choose a unit vector ej in each nonempty piece, requiring only finite choice. The sets Aj=A∩ν−1(Cj) are a finite Borel partition of A, since ν is continuous. For x∈Aj, ej⋅ν(x)=1−12∣ej−ν(x)∣2≥1−ε2/2. Thus ∣μ(Aj)∣≥ej⋅μ(Aj)≥(1−ε2/2)λ(Aj). Adding empty parts gives an admissible countable partition in [F1], so V(A)≥(1−ε2/2)λ(A). Letting ε↓0 and using step 1.1 proves V(A)=λ(A) for every Borel A, including zero-mass sets.

3.1step 2.1∎

Consequently the partition set function is the positive Radon measure λ itself. This proves ∣μ∣=λ on the stated space without any Euclidean-domain assumption or restriction of A to an open set.

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Euclidean real Radon representation under Countable Choice

Statement

Assume Countable Choice. For every open U⊆Rd, every bounded real linear functional on C0(U;R) is integration against a unique finite signed Radon measure. No Dependent Choice assumption is required.

Facts & Assumptions

Given: Countable Choice, an open Euclidean set U, and a bounded real functional L on C0(U).

[A1]

Countable Choice permits simultaneous selection from a countable family of nonempty sets. (The Axiom of Countable Choice (ACω))

[F1]

A bounded real functional is a difference of two bounded positive functionals, by a positive-cone supremum construction using no choice axiom. (A bounded real C_0(X) functional is a difference of positive functionals)

[F2]

Every metric outer measure measures all Borel sets; its Caratheodory restriction is a countably additive measure. (Every Borel set is Carathéodory measurable for a metric outer measure, Carathéodory's theorem: measurable sets form a sigma-algebra carrying a complete measure)

[F3]

Smooth compactly supported functions are uniformly dense in C0(U), and finite signed Radon measures agreeing on these tests are equal. (Smooth compactly supported functions are dense in C0 on an open Euclidean set, Uniqueness of a Radon measure representing a distribution)

Proof

Given: The objects in the Statement.

1.1givenconstruct

First let P be bounded and positive. For relatively open G⊆U put p(G)=sup⁡{P(f):f∈Cc(U), 0≤f≤1, supp⁡f⊆G}. Then 0≤p(G)≤∥P∥, p(∅)=0, and p is monotone. If a compact K is covered by open sets Gj, finitely many suffice, and there are continuous nonnegative compactly supported functions b1,…,bN, each supported in one of these sets, whose sum is positive on K. Indeed cover K by finitely many balls with doubled closures compactly contained in the relevant Gj and use distance cutoffs on these balls. On a neighborhood of K normalize the bi by their sum. Thus any f supported on K with 0≤f≤1 decomposes into finitely many fi≥0 with ∑fi=f and each fi≤1 compactly supported in its assigned Gj; combine terms assigned to the same j. Consequently p(⋃jGj)≤∑jp(Gj). For pairwise disjoint opens, adding finitely many admissible functions gives the reverse inequality for every finite partial sum, so p is countably additive on disjoint open unions. These compact partitions use only finite choices.

2.1A1F2step 1.1construct

Define μ∗(A)=inf⁡{p(G):A⊆G⊆U, G open}. For a sequence (Aj) and ε>0, [A1] selects open Gj⊇Aj with p(Gj)<μ∗(Aj)+ε2−j; step 1.1 proves countable subadditivity. Zero and monotonicity are immediate, so μ∗ is an outer measure, and μ∗(G)=p(G) for open G. If dist⁡(A,B)>0, they have disjoint open neighborhoods V,W in U. Every open G⊇A∪B satisfies p(G)≥p(G∩V)+p(G∩W)≥μ∗(A)+μ∗(B), by step 1.1. Taking the infimum and using subadditivity proves the metric condition. By [F2], restriction to Borel sets is a finite measure μ with μ(U)≤∥P∥.

3.1step 2.1choose

For an admissible f in the definition of p(G), let K=supp⁡f. Every open V⊇K admits f, hence μ(K)=inf⁡V⊇Kp(V)≥P(f). Taking the supremum over f proves μ(G)=sup⁡K⊆G compactμ(K). Outer regularity on every Borel set is the definition of μ∗. Finiteness gives compact inner regularity on every Borel set as well: given Borel A and ε>0, choose compact H⊆U with μ(U∖H)<ε and open V⊇U∖A with μ(V∖(U∖A))<ε. Then H∖V⊆A is compact and misses at most 2ε of μ(A). Thus μ is finite Radon, including regularity on all Borel sets.

4.1step 1.1step 3.1algebra

If 0≤g∈Cc(U) and g≤1K for compact K, the argument in step 3.1 gives P(g)≤μ(K). If instead g≥1K, then for 0<η<1, the open set Gη={g>1−η} contains K and every admissible f for p(Gη) satisfies f≤g/(1−η) on all of U. Positivity yields μ(K)≤p(Gη)≤P(g)/(1−η). Letting η↓0 gives μ(K)≤P(g).

5.1F3step 4.1algebra

Fix 0≤f∈Cc(U) and ε>0, take N with Nε≥∥f∥∞, and put fj=min⁡(ε,(f−(j−1)ε)+), K0=supp⁡f, Kj={f≥jε} for 1≤j≤N. The sum of the fj is f, and ε1Kj≤fj≤ε1Kj−1. Step 4.1 gives the same lower and upper bounds εμ(Kj) and εμ(Kj−1) for P(fj) as for ∫fj dμ. Summing and telescoping gives ∣P(f)−∫f dμ∣≤εμ(K0). Hence equality holds for f≥0, then for every real f∈Cc(U) by positive and negative parts. Uniform density [F3], boundedness of P, and finiteness of μ extend the identity to C0(U).

6.1F1F3step 3.1step 5.1construct∎

Apply [F1] to L=P−Q and the preceding construction to P,Q, obtaining finite positive Radon measures α,β. Their difference σ=α−β represents L. Its total variation is dominated by α+β, hence is regular by compact and open approximation with that finite positive Radon measure. Uniqueness follows from [F3]. All countable selections were the open near-minimizers in step 2.1; all other constructions were explicit or involved finitely many choices.

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Test-field formula and L1 lower semicontinuity of spatial TV

Statement

For every open Ω⊆Rn and real-valued u∈BV(Ω), TV(u;Ω)=sup⁡{∫Ωu div⁡φ dx:φ∈Cc∞(Ω;Rn), ∣φ(x)∣≤1}. If uk,u∈BV(Ω) are real-valued and uk→u in L1(Ω), then TV(u;Ω)≤lim inf⁡kTV(uk;Ω). In addition, assuming Countable Choice, for any real-valued u∈L1(Ω) the displayed supremum is finite if and only if u∈BV(Ω), with equality to TV(u;Ω); under the same assumption, an L1 limit of real-valued BV functions with bounded liminf total variation belongs to BV(Ω) and satisfies the same lower-semicontinuity inequality.

Facts & Assumptions

Given: An open set Ω⊆Rn, a real-valued u∈BV(Ω), and, for the lower-semicontinuity clause, real-valued uk∈BV(Ω) with uk→u in L1(Ω).

[A1]

Countable Choice is assumed only for the finite-test-supremum characterization of arbitrary L1 functions. (The Axiom of Countable Choice (ACω))

[F1]

The distributional derivative acts on a compactly supported smooth test function by the negative-transpose formula. (Spatial BV and distributional total variation)

[F2]

The partition variation of a finite vector of signed Radon measures is a finite positive Radon measure and equals the supremum over compactly supported continuous vector fields of norm at most one. (Variation of a finite vector Radon measure is Radon)

[F3]

C0(Ω) is the space of continuous functions vanishing at infinity; compactly supported smooth functions are dense in it in the uniform norm. (Compact support, Cc(X), and C0(X), Smooth compactly supported functions are dense in C0 on an open Euclidean set)

[F4]

Under Countable Choice, every bounded real linear functional on C0(Ω;R) is integration against a unique finite signed Radon measure. This specialized Euclidean construction uses explicit cutoffs and no Dependent Choice. (Euclidean real Radon representation under Countable Choice)

Proof

Given: The hypotheses listed above.

1.1F1F2F3givenchoose

Suppose u∈BV(Ω) and write μ=Du. The distributional derivative identity gives ∫Ωu div⁡φ dx=−∫Ωφ⋅dμ. The continuous-field dual formula [F2] bounds the supremum over smooth fields by ∣μ∣(Ω). Conversely, for any f∈Cc(Ω;Rn) with ∣f∣≤1, for every ε>0, density [F3] gives one smooth compactly supported g with ∥g−f∥∞<ε; replacing g by g/max⁡(1,∥g∥∞) keeps the unit bound and changes this error by at most another ε. Finiteness of the coordinate measures bounds the integral error by a fixed constant times ε. Letting ε↓0 (without selecting a sequence of approximants) shows that the smooth supremum is at least the continuous-field supremum ∣μ∣(Ω). Thus V(u)=TV(u;Ω).

1.2A1F2F3F4givenconstruct

Assume [A1], let real-valued u∈L1(Ω), and suppose M:=V(u)<∞. For each coordinate i, define Li(ψ):=−∫Ωu ∂iψ dx on real Cc∞(Ω). Taking the test vector with only its ith component equal to ψ and also its negative shows ∣Li(ψ)∣≤M∥ψ∥∞. By density [F3], Li extends uniquely to a bounded real linear functional on real C0(Ω). Apply [F4] directly to this real functional to obtain a finite signed Radon measure μi representing Diu. Applying [F2] to μ=(μ1,…,μn) and using [F3] to pass between continuous and smooth unit fields gives ∣μ∣(Ω)=M. Hence u∈BV(Ω) and TV(u;Ω)=M.

2.1givenstep 1.1

If the L1 limit u is already in BV(Ω), boundedness of div⁡φ gives ∫u div⁡φ=lim⁡k∫uk div⁡φ for each admissible φ. Each approximating integral is at most TV(uk;Ω) by step 1.1, so taking the supremum gives TV(u;Ω)≤lim inf⁡kTV(uk;Ω); this branch uses no choice axiom.

3.1A1givenstep 1.2choose∎

If only L:=lim inf⁡kTV(uk;Ω)<∞ is known, choose a subsequence whose variations converge to L. The same test-integral limit gives V(u)≤L. Under [A1], step 1.2 implies u∈BV(Ω) and TV(u;Ω)=V(u)≤L. If L=+∞, the extended inequality is automatic.

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Full-space, Dirichlet, and Neumann TV conventions

Definition

Let Ω⊂Rn be a bounded Lipschitz domain, meaning a bounded open set whose boundary has a finite cover by coordinate neighborhoods in which it is the graph of a Lipschitz function and Ω lies on one side of that graph. For u∈BV(Ω) define the Neumann total variation by TVN(u;Ω):=∣Du∣(Ω). Define its zero extension u~∈L1(Rn) by u~=u almost everywhere on Ω and u~=0 almost everywhere on Rn∖Ω. Define the Dirichlet total variation by TVD(u;Ω):=TV(u~;Rn) when u~∈BV(Rn) and by TVD(u;Ω):=+∞ otherwise. For v∈BV(Rn) define the full-space total variation by TVF(v):=TV(v;Rn). Thus Neumann variation counts only the distributional derivative inside Ω, while Dirichlet variation also counts any jump created by zero extension across ∂Ω.

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Coarea identity for smooth scalar functions

Statement

Assume Countable Choice. Let Ω⊆Rn be open and let u∈C∞(Ω;R)∩L1(Ω) satisfy ∫Ω∣∇u∣ dx<∞. For t>0 set Et+:={x∈Ω:u(x)>t} and for t<0 set Et−:={x∈Ω:u(x)<t}. Then the level sets have finite perimeter relative to Ω for almost every applicable t, and ∫Ω∣∇u∣ dx=∫0∞P(Et+;Ω) dt+∫−∞0P(Et−;Ω) dt.

Facts & Assumptions

Given: Countable Choice, an open Ω⊆Rn, and a smooth real function u∈L1(Ω) with ∇u∈L1(Ω;Rn).

[A1]

Countable Choice is assumed for the countable chart and surface-measure constructions. (The Axiom of Countable Choice (ACω))

[F1]

The critical values of a smooth scalar function on an open Euclidean set have Lebesgue measure zero. (Morse-Sard for Euclidean maps)

[F2]

A C1 map with nonsingular derivative has a local C1 inverse, and an injective such map on an open set obeys the compactly supported change-of-variables formula. (The Euclidean inverse function theorem, A compactly supported Riemann integrand admits the global change-of-variables formula from a diffeomorphism near the relevant compact preimage)

[F3]

On an m-dimensional graph, Hausdorff measure divided by the repository normalization constant cm has density 1+∣Dh∣2; for C1 graphs this agrees with the chart surface integral. Graph surface measures are Radon in their relative topology, and pushforward to the open ambient domain is Radon when the graph is relatively closed and the total measure finite. (Lipschitz graph area and calculus under Countable Choice, Chart and partition independence of surface measure)

[F4]

For a C1 graph boundary and a compactly supported C1 vector field, integrating its divergence over the subgraph gives the graph flux formula. (The local graph flux calculation)

[F5]

Rational points are dense in Euclidean space and form a countable family, so rational balls give a countable base. (The rationals embed densely in the reals, Q is countably infinite, A product of two at most countable sets is at most countable)

[F6]

A countable open cover of an open Euclidean set admits a locally finite smooth partition of unity subordinate to that cover. (Locally finite smooth partitions of unity on Euclidean open sets)

[F7]

A continuous unit-vector density against a finite Radon surface measure has partition variation equal to that surface measure. (A unit vector density has scalar variation measure)

[F8]

Tonelli permits summing nonnegative chart integrals and interchanging the level and spatial integrations. (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product)

Proof

Given: The hypotheses listed above.

1.1A1F2F3F5F6givenconstruct

Put G:={x∈Ω:∇u(x)≠0}. The balls with rational centers and radii whose closures lie in Ω and on which some ∂iu never vanishes form a countable open cover of G by density and countability [F5]; assign each ball the least such coordinate i. Each ball is convex. The map Ti(x)=(x1,…,xi−1,u(x),xi+1,…,xn) has nonzero Jacobian there; it is injective because along each line parallel to the ith axis, u is strictly monotone. Thus [F2] makes it a C1 diffeomorphism onto its open image. By [F6], choose a locally finite smooth partition of unity (ηj) on G subordinate to these chart balls. On a ball assigned coordinate i, write y=xi^ and t=u(x); the inverse chart has graph form xi=h(y,t), with ∣det⁡DTi∣=∣∂iu∣ and 1+∣Dyh∣2=∣∇u∣∣∂iu∣ by implicit differentiation. Change of variables [F2] and the surface density [F3], applied to the compactly supported nonnegative weight ηj, give ∫Gηj∣∇u∣ dx=∫R∫G∩{u=t}ηj dHn−1 dt.

2.1F1F8step 1.1given

Sum the chart identities of step 1.1 over j. Since ∑jηj=1 on G, Tonelli [F8] gives ∫Ω∣∇u∣ dx=∫RHn−1(G∩{u=t}) dt, because ∇u=0 on Ω∖G. Sard's theorem [F1] says that outside a null set every point of a level is regular, so the integrand agrees almost everywhere in t with Hn−1(Ω∩{u=t}). This also establishes measurability of the level-area function as a countable sum of the chart integrals in step 1.1.

3.1A1F3F4F7step 2.1given∎

Fix a nonzero regular value t for which the area in step 2.1 is finite; throughout the proof Hn−1 denotes the normalized graph measure from [F3], with counting measure if n=1. In that case every graph chart is a single point at fixed level, its empty-coordinate Jacobian is one, and the same substitution identity in step 1.1 is the ordinary one-dimensional substitution formula. Then Γt:=Ω∩{u=t} is a smooth hypersurface. For a compactly supported smooth test field ϕ, its intersection with Γt is compact; local finiteness gives a neighborhood meeting only finitely many chart supports, whose partition sum is one there. Decompose ϕ into the finite chart-supported sum and a remainder vanishing near Γt. The remainder has zero divergence integral over either level set because its restriction to that open set extends as a compactly supported smooth field. Each chart term obeys the graph flux formula [F4]. Summing shows that DχEt+=+(∇u/∣∇u∣)Hn−1∣Γt and DχEt−=−(∇u/∣∇u∣)Hn−1∣Γt. The level Γt is relatively closed in Ω; hence this measure is finite and Radon by the graph area construction [F3], and [F7] gives its partition variation as exactly Hn−1∣Γt. Hence the indicator is BV and its perimeter equals that area. For t>0 and t<0, respectively, Markov's inequality gives ∣Et+∣≤t−1∥u∥1 and ∣Et−∣≤∣t∣−1∥u∥1, so the indicators are in L1. The area integral is finite, so almost every applicable nonzero level is regular and has finite area by step 2.1; the required perimeter equality and almost-everywhere finiteness follow.

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One-sided BV traces and Green identity on a Lipschitz graph

Statement

Assume Countable Choice. In a Lipschitz graph chart let G be the side z>h(y), and let u∈BV(G) locally, with finite L1 norm and variation on each smaller bounded graph collar under consideration. On every smaller base box B there is a unique local L1(B) trace τu such that u(y,h(y)+t)⟶τu(y)in L1(B) as t↓0 through almost every t. The trace is linear and satisfies a bound ∥τu∥L1(B)≤C(a−1∥u∥L1(C2a)+∣Du∣(C2a)), where C2a is a fixed larger graph collar with positive margins at the chart sides and a>0 is sufficiently small. For every smooth vector field ϕ compactly supported away from those sides, ∫Gudiv⁡ϕ=−∫Gϕ⋅dDu+∫τu(y)ϕ(y,h(y))⋅(Dh(y),−1) dy. The corresponding assertions hold for the subgraph with the normal reversed. For an interval endpoint in dimension one, the same assertions mean the one-sided scalar limit, the usual endpoint sign, and counting measure on the boundary.

Facts & Assumptions

Given: Countable Choice and a smaller graph collar with closure, except its graph face, contained in the larger chart. Write Cb={(y,z):y∈B′, 0<z−h(y)<b} for a larger base box B′⊃B‾ and sufficiently small b.

[F2]

Completed Euclidean Fubini and Tonelli hold under Countable Choice. Vertical translation in each fixed base slice therefore preserves volume for (y,t)↦(y,h(y)+t). (Tonelli and Fubini for the completed product, with only almost-everywhere section measurability, The Euclidean Lebesgue measure is the completion of the product of the factor Lebesgue measures)

[F3]

A Lipschitz function is differentiable almost everywhere, its ordinary and weak derivatives agree, and graph area and normal have the formulas in the preceding lemma. (Lipschitz graph area and calculus under Countable Choice)

[F4]

Finite signed Radon measures are determined by compactly supported smooth tests, and smooth cutoffs exist on nested balls. (Uniqueness of a Radon measure representing a distribution, A smooth bump between concentric Euclidean balls)

Proof

Given: The chart and u in the Statement.

1.1F1F2givenconstruct

Fix a>0 with C2a inside the larger chart. On every compact subset of G, mollify u using a nonnegative unit-mass bump, writing uϵ=u∗ρϵ where the convolution ball stays in G. The distributional derivative identity and [F2] give ∂zuϵ=(Dzu)∗ρϵ there. For 0<s<t<a, ordinary line integration gives ∫B∣uϵ(y,h(y)+t)−uϵ(y,h(y)+s)∣ dy≤∫{y∈B, s<z−h(y)<t}∣∂zuϵ∣ dx. For sufficiently small ϵ, the ϵ-neighborhood of this last strip lies in C2a: its lower height is positive since s>0, its upper height is below 2a, and its lateral projection lies in B′. The convolution bound and [F2] make the right side at most ∣Dzu∣(C2a), since each kernel integrates to at most one.

2.1F1F2step 1.1construct

On each compact-height collar y∈B, 1/j<z−h(y)<a−1/j, [F1] gives L1 convergence of uϵ to u. Choose a sequence ϵℓ↓0 whose L1 errors on the first ℓ such collars are below 2−ℓ, always using the least sufficiently large dyadic exponent. By [F2], for a full-measure set of heights the slice functions converge in L1(B). Applying step 1.1 at two such heights proves ∥ut−us∥L1(B)≤∣Dzu∣(C2a),ut(y)=u(y,h(y)+t),0<s,t<a. Repeat this construction for a countable sequence of smaller a tending to zero and intersect the full-measure height sets. The collars C2a decrease to the empty set inside G, so finiteness of ∣Dzu∣ implies their measures tend to zero. Thus ut is Cauchy in L1(B) as t↓0 outside one null set.

3.1F2step 2.1chooseconstructalgebra

Choose one height from each interval (2−j−1a,2−ja) outside that null set by Countable Choice. The corresponding Cauchy sequence has an L1 limit: choose measurable representatives, then a subsequence whose successive L1 differences are below 2−j; [F2] makes the sum of the absolute differences integrable and gives its almost-everywhere and L1 limit. The Cauchy estimate in step 2.1 makes this limit independent of heights and gives the asserted convergence along all good heights. This also proves uniqueness and linearity. Averaging the bound ∥τu∥1≤∥ut∥1+∣Dzu∣(C2a) over 0<t<a using [F2] gives ∥τu∥1≤a−1∥u∥L1(Ca)+∣Dzu∣(C2a). Since ∣Dzu∣≤∣Du∣, this is the stated bound. Traces obtained on nested base boxes coincide by the same slice convergence.

4.1F1F2F3step 3.1constructalgebra

The distributional identity extends from smooth to compactly supported Lipschitz vector fields ψ inside G. Indeed mollification converges uniformly to ψ, while its derivatives are uniformly bounded and converge almost everywhere to the weak derivatives, by [F3] and Lebesgue differentiation: if g is a bounded weak derivative at a strong Lebesgue point x, then ∣g∗ρϵ(x)−g(x)∣≤Cϵ−n∫B(x,ϵ)∣g(y)−g(x)∣ dy→0. Consequently ∫ψϵ⋅dDu→∫ψ⋅dDu by uniform convergence and finiteness, and ∫udiv⁡ψϵ→∫udiv⁡ψ by dominated convergence. Set r=z−h(y) and let θ be the continuous function zero on (−∞,0], linear from zero to one on [0,1], and one on [1,∞). For fixed ϵ>0 use ψ=ϕθ((r−ϵ)/ϵ), whose support is a compact subset of G. Its almost-everywhere gradient uses the ordinary chain rule from [F3], and its transition term is ϵ−1∫ϵ2ϵ∫ut(y)ϕ(y,h(y)+t)⋅(−Dh(y),1) dy dt. By step 3.1, the uniform bound on Dh, and uniform continuity of ϕ, this converges to ∫τu ϕ(y,h(y))⋅(−Dh,1) dy. The other terms converge to ∫Gudiv⁡ϕ and −∫Gϕ⋅dDu, since the cutoff tends pointwise to one in G. Rearrangement proves the Green formula.

5.1F3F4step 3.1step 4.1algebra∎

These formulas also show independence of the direction of a valid graph chart. On an overlap, [F3] applied to u=1 first identifies the outward vector surface measures by [F4]. Their variations are their scalar graph measures: for a unit measurable density n against a finite positive measure μ, variation is at most μ by the triangle inequality, and is at least (1−η)μ by partitioning the unit sphere into finitely many Borel sets of diameter below η and projecting each vector integral onto a representative direction. Let η↓0. Thus the outward normals agree almost everywhere. Subtract the two Green formulas for general u; [F4] makes (τ1u−τ2u)nμ zero, and the same variation argument gives τ1u=τ2u almost everywhere. Reflection gives the subgraph formulas. In dimension one, omit the base integral: the convolution and line estimate in steps 1.1–2.1 make u(t) Cauchy through almost every t approaching an endpoint, and step 4.1 gives the endpoint boundary term. All arguments and bounds remain valid, with scalar absolute value and counting measure.

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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.

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Trace formula and bounded zero extension on Lipschitz domains

Statement

Assume Countable Choice. Here Hm on a boundary denotes normalized Hausdorff measure: the repository's unnormalised m-dimensional Hausdorff measure divided by cm=Hm((0,1]m) for m≥1, and counting measure for m=0. Let n≥2 and let Ω⊂Rn be a bounded Lipschitz domain, meaning a bounded open set whose boundary has a finite cover by coordinate neighborhoods in which it is the graph of a Lipschitz function and Ω lies on one side of the graph. There is a unique bounded linear trace operator T:BV(Ω)→L1(∂Ω,Hn−1) such that for every u∈BV(Ω) and ϕ∈Cc1(Rn;Rn), ∫Ωu div⁡ϕ dx=−∫Ωϕ⋅dDu+∫∂ΩTu ϕ⋅ν dHn−1, where ν is the outward unit normal defined almost everywhere on ∂Ω. The zero extension u~ belongs to BV(Rn) and satisfies TV(u~;Rn)=TV(u;Ω)+∥Tu∥L1(∂Ω)≤CΩ(∥u∥L1(Ω)+TV(u;Ω)) for a finite constant CΩ depending only on the domain. The same conclusions hold in dimension one for a bounded open set with a finite one-sided graph cover, with the two one-sided endpoint traces and counting measure on its finite boundary.

Facts & Assumptions

Given: Countable Choice, a bounded Lipschitz domain Ω⊂Rn, and u∈BV(Ω).

[F1]

Every smaller Lipschitz graph chart has a linear one-sided L1 trace, its local norm estimate, and the local BV Green formula. Traces agree on overlapping charts. The same result supplies the endpoint case in dimension one. (One-sided BV traces and Green identity on a Lipschitz graph)

[F2]

Normalized Hausdorff measure on a Lipschitz graph has density 1+∣Dh∣2, with its almost-everywhere unit outward normal. (Lipschitz graph area and calculus under Countable Choice)

[F3]

Compact sets admit finite smooth cutoff covers, and finite signed Radon measures are determined by smooth compactly supported tests. (A smooth bump between concentric Euclidean balls, Uniqueness of a Radon measure representing a distribution)

[F4]

A finite vector of signed Radon measures has finite Radon partition variation. (Variation of a finite vector Radon measure is Radon)

[F5]

Since Ω is bounded, Ω‾ and ∂Ω are closed bounded subsets of Rn, hence compact. A finite subcover by smaller graph charts still covers ∂Ω; the graph area formula in [F2] gives finite Radon surface measure there. In dimension one the finite chart cover makes the boundary finite. (Heine-Borel in Rn: with the Euclidean metric a subset of Rn is compact if and only if it is closed and bounded, and the proof by bisection uses no choice principle; the same holds on the real line)

[F6]

If μ is a finite positive Radon measure and f∈L1(μ;R), then the signed measure fμ is finite Radon. For ρ:=∣f∣μ, truncate f so the L1 tail is arbitrarily small. For the bounded truncation, compact inner approximation of open sets and open outer approximation of Borel sets for μ control the weighted errors by the uniform bound. Taking the tail and regularity errors to zero gives compact inner regularity on open sets and outer regularity on Borel sets for ρ. Finiteness upgrades compact approximation to all Borel sets: for Borel A, choose compact C⊂X with ρ(X∖C)<ϵ/2 and open G⊃X∖A with ρ(G∩A)<ϵ/2; then C∖G is compact in A and ρ(A∖(C∖G))<ϵ. Finally, the partition of A into A∩{f≥0} and A∩{f<0} gives ∣fμ∣=∣f∣μ=ρ, so the signed measure has regular total variation.

[F7]

A compactly supported C1 vector field can be approximated together with its first derivatives uniformly by smooth compactly supported mollifications. Normalize a nonnegative bump from [F3] to mass one; uniform continuity of the field and its derivatives gives uniform convergence, and differentiation of the convolution follows by integration by parts.

Proof

Given: Countable Choice and the bounded Lipschitz domain in the Statement.

1.1F1F2F5givenconstruct

If Ω=∅, its BV space and boundary L1 space are both the zero space, the zero trace is unique, and every formula and estimate holds with both sides zero. Assume henceforth Ω≠∅. By [F5], ∂Ω is compact; choose finitely many smaller graph charts with positive margins inside the original charts that still cover it. Each smaller graph base is bounded and its Lipschitz constant finite, so [F2] gives finite Radon surface measure on that patch and Hn−1(∂Ω)<∞. In each chart [F1] defines a local trace and bounds its surface L1 norm, using [F2], by a chart constant times ∥u∥1+∣Du∣(Ω). On overlaps these local traces agree by [F1]. Consequently they define one class Tu∈L1(∂Ω,Hn−1) with ∥Tu∥1≤C(∥u∥1+TV(u;Ω)). Linearity follows locally from [F1], hence globally.

2.1F1F2F3F5F7step 1.1constructalgebra

Construct a finite smooth partition equal to one on a neighborhood of Ω‾, subordinate to the boundary charts and the interior open set Ω: by [F5] this compact set is covered by finitely many balls with doubled closures in those open sets; take the bumps in [F3], and divide them by their positive sum near Ω‾. Multiply by one further smooth cutoff supported where the sum is positive and equal to one near Ω‾. First take ϕ∈Cc∞(Rn;Rn) and apply the local Green identity [F1] to each chart-supported field ηjϕ. For the interior-supported field the defining distributional identity applies. Sum the identities. Since ∑jηj=1 and ∑j∇ηj=0 near Ω‾, the interior and boundary sums are exactly ∫Ωudiv⁡ϕ=−∫Ωϕ⋅dDu+∫∂ΩTu ϕ⋅ν dHn−1. For an arbitrary ϕ∈Cc1, use [F7] to approximate ϕ and its first derivatives uniformly by compactly supported smooth fields; finite variation and Tu∈L1 pass every term to the limit.

3.1F2F4F6step 1.1step 2.1construct

Extend each coordinate of Du by zero from Ω to Rn. It is a finite signed Radon measure: compact inner approximation can be performed inside Ω, and outer approximation in the ambient space follows by applying that inner approximation to the complement and using finiteness. For each coordinate i, the boundary density fi:=Tu νi is integrable because Tu∈L1 and ∣νi∣≤1. By [F6], fiHn−1∣∂Ω is a finite signed Radon measure; this verifies the required weighted-measure regularity, not just its finiteness. Thus their difference μ=i#Du−Tu νHn−1∣∂Ω is a finite Radon vector measure by [F4]. The formula in step 2.1 says exactly that Du~=μ, so u~∈BV(Rn).

4.1F3step 1.1step 3.1algebra

The two summands defining μ in step 3.1 are supported on the disjoint Borel sets Ω and ∂Ω. The partition definition of variation therefore gives the sum of their variations. For a unit measurable vector density ν and scalar density Tu, the boundary variation is ∣Tu∣Hn−1: the triangle inequality gives the upper bound, and a finite partition of the unit sphere into pieces of diameter below ϵ, applied to the direction sgn⁡(Tu)ν, gives the lower bound (1−ϵ)∣Tu∣Hn−1 by projection; let ϵ↓0. Hence TV(u~)=TV(u;Ω)+∥Tu∥1. Step 1.1 gives the asserted bound. If another trace satisfied the Green identity, their difference times νHn−1 would integrate to zero on all smooth tests, hence be zero by [F3]; the same variation calculation gives equality of the trace classes.

5.1F1F3step 2.1step 3.1step 4.1construct∎

In dimension one, each smaller graph neighborhood contains one boundary point, so the finite graph cover makes the boundary finite. A bounded open set with finite boundary is a finite disjoint union of bounded intervals. Use the one-sided endpoint construction in [F1] on each of their finitely many endpoints. The partition argument of step 2.1 and the disjoint interior/boundary measure calculation in steps 3.1–4.1 apply verbatim with H0 counting measure and outward signs −1 at a left endpoint and +1 at a right endpoint. This proves the stated dimension-one companion.

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Coarea formula for spatial BV

Statement

Assume Countable Choice. Let Ω⊆Rn be open, let u∈BV(Ω), and for t>0 set Et+:={x∈Ω:u(x)>t} while for t<0 set Et−:={x∈Ω:u(x)<t}. Then for almost every applicable t these sets have finite perimeter relative to Ω, and TV(u;Ω)=∫0∞P(Et+;Ω) dt+∫−∞0P(Et−;Ω) dt.

Facts & Assumptions

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

[A1]

Countable Choice is the assigned axiom strength for this item. (The Axiom of Countable Choice (ACω))

[F1]

Strict smooth approximation and the smooth-level coarea calculation are available under Countable Choice. (Strict smooth approximation in BV, Coarea identity for smooth scalar functions)

[F2]

Under Countable Choice, finite distributional test variation of an arbitrary real L1 function is equivalent to membership in BV, with equality to its total variation. In particular this implication and lower semicontinuity apply to limits of level indicators. (Test-field formula and L1 lower semicontinuity of spatial TV)

Proof

Given: The hypotheses in the Statement.

1.1A1F2F3givenconstruct

For any real f∈L1(Ω), define its extended test variation V(f) as the supremum of ∫fdiv⁡φ over smooth compactly supported vector fields with ∣φ∣≤1. It is a lower semicontinuous extended nonnegative function on L1: each test integral is a continuous linear functional and {f:V(f)>a} is the union of its open superlevel sets. By [F2], V(f)<∞ is equivalent to f∈BV, in which case V(f)=TV(f;Ω). For t>0 the indicator χ{f>t} lies in L1, since its norm is at most ∥f∥1/t, and it is right continuous as an L1-valued function of t: if tj↓t>0, its indicators increase to χ{f>t} and their errors tend to zero by monotone convergence. Dyadic right-step approximations therefore make this map Borel measurable. For t<0, t↦χ{f<t} is similarly left continuous and Borel. Composition with the lower semicontinuous V shows that both extended level-variation functions are measurable.

2.1A1F1F2F3step 1.1choosealgebra

By [F1], take smooth strict approximants uj with ∥uj−u∥1<2−j and ∫∣∇uj∣→TV(u;Ω), passing to a subsequence by least indices if needed. For real numbers a,b, the total length of the positive and negative levels at which their signed superlevel or sublevel indicators differ is ∣a−b∣. Hence [F3] gives ∫0∞∥χ{uj>t}−χ{u>t}∥1 dt+∫−∞0∥χ{uj<t}−χ{u<t}∥1 dt=∥uj−u∥1. Sum over j and apply [F3]: for almost every applicable nonzero level, the indicator errors are summable, and in particular the level indicators converge in L1. The lower semicontinuity from step 1.1 gives V(χEt±)≤lim inf⁡jV(χ{uj≷t}) at those levels. Fatou and the smooth coarea identity [F1] consequently give ∫0∞V(χEt+) dt+∫−∞0V(χEt−) dt≤lim inf⁡j∫Ω∣∇uj∣ dx=TV(u;Ω). The integral is finite, so its integrands are finite almost everywhere; [F2] then proves the stated almost-everywhere finite-perimeter assertion.

3.1F2F3step 1.1step 2.1algebra∎

For any admissible smooth test field φ, signed layer cake gives u(x)=∫0∞χEt+(x) dt−∫−∞0χEt−(x) dt almost everywhere. The absolute integral against div⁡φ is bounded by ∥div⁡φ∥∞∥u∥1, so iterated integration is valid. Each level test integral in absolute value is at most its extended variation, using also −φ in step 1.1. Therefore ∫udiv⁡φ is at most the sum of the two perimeter integrals. Take the supremum over φ and apply [F2] to u to obtain the reverse of the inequality in step 2.1. Equality follows. Changing the representative of u changes each level set only by a spatial null set, so all conclusions concern the given L1 class.

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BV Sobolev inequality in full space

Statement

Assume Countable Choice and let n≥2. Every u∈BV(Rn) satisfies ∥u∥Ln/(n−1)(Rn)≤TV(u;Rn).

Facts & Assumptions

Given: Countable Choice, an integer n≥2, and u∈BV(Rn).

[A1]

Countable Choice is needed for the strict smooth approximation used below. (The Axiom of Countable Choice (ACω))

[F1]

Every full-space BV function has a compactly supported smooth strict approximation converging in L1 and in gradient integral. (Strict smooth approximation in BV)

[F2]

The Loomis–Whitney integral inequality bounds the coordinate-product integral by the product of its (n−1)-dimensional integrals. (Loomis–Whitney integral inequality)

[F3]

For a smooth function with continuous derivative, the one-dimensional fundamental theorem gives its value from the integral of its derivative along each coordinate line. (Fundamental theorem of calculus for Banach-valued continuous curves)

[F4]

Tonelli allows the coordinate-line integrals to be assembled into the full-space integrals below. (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product)

Proof

Given: The hypotheses listed above.

1.1F3F4givenalgebra

First let f∈Cc∞(Rn). For each i, put gi(xi^):=∫R∣∂if(x1,…,xi−1,s,xi+1,…,xn)∣ ds. Tonelli [F4] shows gi is nonnegative measurable and integrable. By [F3], integrating from a point to the left of the compact support up to xi gives ∣f(x)∣≤gi(xi^) for every coordinate i. Multiplication and raising to the power 1/(n−1) yield ∣f(x)∣n/(n−1)≤∏i=1ngi(xi^)1/(n−1).

2.1F2step 1.1algebra

Integrating this inequality and applying [F2] gives ∥f∥Ln/(n−1)≤∏i=1n∥∂if∥11/n≤1n∑i=1n∥∂if∥1≤1n∫Rn∣∇f∣ dx. The middle inequality is arithmetic-geometric mean; the last follows pointwise from ∑i∣∂if∣≤n∣∇f∣. Thus the desired inequality holds for smooth compactly supported f, with the stronger constant 1/n.

3.1A1F1F4step 2.1choose∎

By [A1] and [F1], choose fk∈Cc∞(Rn) with fk→u in L1 and ∫∣∇fk∣→TV(u;Rn). Select a subsequence with ∥fkj−u∥1<2−2j; Tonelli [F4] gives ∫∑j∣fkj−u∣<∞, hence fkj→u almost everywhere. Fatou and step 2.1 imply ∫∣u∣n/(n−1) dx≤lim inf⁡j∫∣fkj∣n/(n−1) dx≤TV(u;Rn)n/(n−1). Taking the (n−1)/n power proves the stated inequality and at the same time shows u∈Ln/(n−1).

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BV extension and translation bounds

Statement

Assume Countable Choice. Let Ω⊂Rn be a bounded Lipschitz domain, meaning a bounded open set whose boundary has a finite cover by Lipschitz graph neighborhoods with Ω on one side of each graph. The zero-extension map is bounded from BV(Ω) to BV(Rn), with support in Ω‾, and there is a finite CΩ such that ∥u~∥L1(Rn)+TV(u~;Rn)≤CΩ(∥u∥L1(Ω)+TV(u;Ω)) for every u∈BV(Ω). For every v∈BV(Rn) and h∈Rn, ∥v(⋅+h)−v∥L1(Rn)≤∣h∣TV(v;Rn).

Facts & Assumptions

Given: Countable Choice, a bounded Lipschitz domain Ω, u∈BV(Ω), v∈BV(Rn), and h∈Rn.

[F1]

The trace result gives a zero extension in BV(Rn) with variation bounded by CΩ(∥u∥1+TV(u;Ω)). (Trace formula and bounded zero extension on Lipschitz domains)

[F2]

Under Countable Choice, full-space BV functions admit compactly supported smooth strict approximations. (Strict smooth approximation in BV)

[F4]

A differentiable function with continuous derivative satisfies the one-dimensional fundamental theorem of calculus along compact intervals. (Fundamental theorem of calculus for Banach-valued continuous curves)

[F5]

Nonnegative integrands may be integrated by iterated integration. (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product)

[A1]

Countable Choice is assumed for full-space strict approximation. (The Axiom of Countable Choice (ACω))

Proof

Given: Countable Choice, u∈BV(Ω), v∈BV(Rn), and h∈Rn.

1.1F1given

The zero extension is in BV(Rn) by [F1]. Its L1 norm equals ∥u∥L1(Ω), and [F1] bounds its full-space variation by CΩ(∥u∥1+TV(u;Ω)); its support is contained in Ω‾ by definition.

1.2F3F4F5givenalgebra

Let first v∈Cc∞(Rn). The fundamental theorem [F4] along the segment from x to x+h gives v(x+h)−v(x)=∫01h⋅∇v(x+th) dt. Integrate the absolute value in x, apply Tonelli [F5], and use translation invariance [F3] to obtain ∥v(⋅+h)−v∥1≤∫01∣h∣∫Rn∣∇v(x+th)∣ dx dt=∣h∣∫Rn∣∇v∣ dx.

2.1A1F2F3step 1.2choose∎

For general v∈BV(Rn), choose vk∈Cc∞ with vk→v in L1 and ∫∣∇vk∣→TV(v) by [F2] under [A1]. Translation is an L1 isometry [F3], so vk(⋅+h)−vk→v(⋅+h)−v in L1. Passing to the limit in step 1.2 proves the translation inequality.

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Compactness and lower semicontinuity for bounded-domain BV

Statement

Assume Countable Choice. Let Ω⊆Rn be a bounded Lipschitz domain, meaning a bounded open set whose boundary has a finite cover by Lipschitz graph neighborhoods with Ω on one side of each graph. Total variation is lower semicontinuous under L1(Ω) convergence of BV functions. Every sequence (uk)⊂BV(Ω) satisfying sup⁡k(∥uk∥L1(Ω)+TV(uk;Ω))<∞ has a subsequence converging in L1(Ω) to a function in BV(Ω).

Facts & Assumptions

Given: Countable Choice, a bounded Lipschitz domain Ω, and a sequence bounded in the BV norm.

[F1]

Zero extensions have common bounded support and uniformly bounded BV norms, and translations obey the linear BV estimate. The extension theorem includes the endpoint case in dimension one. (BV extension and translation bounds)

[F2]

Under Countable Choice, an L1-bounded sequence with common bounded support and uniform translation continuity has an L1-convergent subsequence. This is proved by finite cell averages and a deterministic diagonal selection, without the metric compactness/sequential-compactness equivalence. (Sequence compactness in L1 by finite cell averages)

[F3]

Under Countable Choice, an L1 limit with bounded liminf variation belongs to BV and satisfies lower semicontinuity; if the limit is already BV, the inequality uses no choice axiom. (Test-field formula and L1 lower semicontinuity of spatial TV)

Proof

Given: The hypotheses in the Statement; let M bound the displayed BV norms.

1.1F3givenalgebra

For uk→u in L1(Ω) with all functions in BV(Ω), each compactly supported smooth unit test field has ∫udiv⁡ϕ=lim⁡k∫ukdiv⁡ϕ≤lim inf⁡kTV(uk;Ω). Taking the supremum using [F3] proves the lower-semicontinuity assertion. If only u∈L1 is initially known and that liminf is finite, the Countable Choice characterization in [F3] also proves u∈BV.

2.1F1F2F3step 1.1construct∎

Extend every uk by zero. By [F1], the functions vk=u~k have support in the bounded set Ω‾, satisfy sup⁡k∥vk∥1≤M, and have TV(vk;Rn)≤CΩM. Their translation differences are at most ∣h∣CΩM, uniformly in k. Hence [F2] gives a subsequence vkj→v in L1(Rn). Restriction yields ukj→u=v∣Ω in L1(Ω). The variations in Ω are bounded by M, so step 1.1 and [F3] prove u∈BV(Ω) and TV(u;Ω)≤lim inf⁡jTV(ukj;Ω). This proves the full compactness conclusion.

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BV extension, translation, and coarea

Statement

Assume Countable Choice. For every bounded Lipschitz domain Ω⊆Rn (a bounded open set with a finite Lipschitz graph cover of its boundary, with the domain on one side of each graph), zero extension is a bounded map BV(Ω)→BV(Rn) with support in Ω‾ and satisfies ∥v~∥L1(Rn)+TV(v~;Rn)≤CΩ(∥v∥L1(Ω)+TV(v;Ω)); translations satisfy ∥w(⋅+h)−w∥L1(Rn)≤∣h∣TV(w;Rn) for w∈BV(Rn); and, for every open U⊆Rn and every u∈BV(U), if Et+:={x∈U:u(x)>t} for t>0 and Et−:={x∈U:u(x)<t} for t<0, then these sets have finite perimeter for almost every applicable t and TV(u;U)=∫0∞P(Et+;U) dt+∫−∞0P(Et−;U) dt.

Facts & Assumptions

Given: Countable Choice, bounded Lipschitz domains, and BV functions on the stated domains.

[F1]

Bounded zero extension and the full-space translation estimate hold under Countable Choice, including dimension one. (BV extension and translation bounds)

[F2]

The signed-level coarea identity and almost-everywhere finite perimeter hold under Countable Choice on arbitrary open sets. (Coarea formula for spatial BV)

Proof

Given: The hypotheses in the Statement.

1.1F1given

Apply [F1] to each bounded Lipschitz domain and to the stated full-space BV functions. This proves the support, norm and translation assertions.

2.1F2givenstep 1.1∎

Apply [F2] on the arbitrary open set U to u∈BV(U). It gives exactly the two signed level families, their almost-everywhere finite perimeters, and the displayed equality. All suppliers assume only Countable Choice.

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Relative isoperimetric inequality on bounded connected Lipschitz domains

Statement

Assume Countable Choice, let n≥2, and let Ω⊆Rn be a bounded connected Lipschitz domain (a bounded open set with a finite Lipschitz graph cover of its boundary, with the domain on one side of each graph, and not separable into two disjoint nonempty relatively open subsets). There is a constant CΩ<∞ such that every measurable E⊆Ω with χE∈BV(Ω) satisfies min⁡{∣E∣,∣Ω∖E∣}(n−1)/n≤CΩP(E;Ω).

Facts & Assumptions

Given: Countable Choice, n≥2, a bounded connected Lipschitz domain Ω, and a finite-perimeter set E⊆Ω.

[F1]

Zero extension has a BV bound controlled by interior variation and the L1 norm. (BV extension and translation bounds)

[F2]

Under Countable Choice, a bounded BV sequence on Ω has an L1-convergent subsequence with a BV limit and lower semicontinuity. (Compactness and lower semicontinuity for bounded-domain BV)

[F3]

Zero distributional gradient on a connected open domain forces an almost-everywhere constant under Countable Choice. (A zero distributional gradient is constant on a connected domain)

[F4]

The full-space BV Sobolev inequality holds under Countable Choice. (BV Sobolev inequality in full space)

[F5]

Under Countable Choice, Lebesgue measure is finite on bounded sets. Every nonempty open subset of Rn contains an open box with positive side lengths, whose measure is their positive product; hence bounded nonempty openness gives 0<∣Ω∣<∞. (Lebesgue measure is a Radon measure on R^n, A box in Rn with parameters ai≤bi is Lebesgue measurable of measure ∏i<n(bi−ai), whichever of its faces are included)

Proof

Given: The hypotheses in the Statement. Put a=(n−1)/n.

1.1F1F4F5givenconstructalgebra

The empty domain gives the inequality with both sides zero, so assume Ω≠∅. Its openness and nonemptiness give an open box with positive side lengths contained in Ω, and its boundedness puts Ω inside a bounded box; [F5] therefore gives 0<∣Ω∣<∞. For m=min⁡(∣E∣,∣Ω∖E∣), take A to be the smaller side. Its indicator is BV: the distributional derivative of the constant function 1 in Ω is zero, so DχΩ∖E=−DχE and both sides have the same relative perimeter P. Its zero extension has Ln/(n−1) norm ma. By [F1] and [F4], ma≤C(m+P) for a fixed C≥1 depending only on Ω. If 0<m≤δ=(2C)−n, then Cm≤ma/2, so ma≤2CP. For m=0 the conclusion is immediate.

2.1F2F3step 1.1choosealgebra

Among sets with δ≤∣E∣≤∣Ω∣−δ, the relative perimeters have a positive lower bound, unless that family is empty. Otherwise, if the infimum were zero, Countable Choice would select a sequence Ej in this family with P(Ej;Ω)<1/j. Its indicators are uniformly BV-bounded. By [F2], a subsequence converges in L1(Ω) to v∈BV(Ω) with TV(v;Ω)=0. The distance from v(x) to {0,1} is bounded by ∣v(x)−χEj(x)∣ for every j, so its integral is zero by L1 convergence; hence v is an indicator almost everywhere. Its volume lies in [δ,∣Ω∣−δ] by L1 convergence. But its zero variation makes every coordinate distributional derivative zero, so [F3] makes v constant almost everywhere. An indicator constant must be zero or one, contradicting the volume bounds. This proves a positive lower bound bΩ whenever the family is nonempty.

3.1step 1.1step 2.1algebra∎

In the remaining case m≥δ, both side volumes meet the bounds in step 2.1, so P≥bΩ and ma≤(∣Ω∣/2)a≤(∣Ω∣/2)abΩ−1P. Combine this constant with 2C from step 1.1. If the intermediate-volume family is empty, step 1.1 already covers every set. Thus a finite domain constant gives the asserted inequality for every finite-perimeter E.

4 · Examples, counterexamples and false statements

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