Alphabeta Math
Pipeline-generated
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.

Fourier Transform Convolution and Approximate Identities

1 · Prerequisites

2 · Summary

The Fourier transform here uses the phase e2πixξ on complex-valued functions. The opening definition and well-definedness lemma distinguish an L1 class from its bounded continuous transform, which is defined at every frequency. Translation, modulation, reflection and linear changes of variables fix the conventions used throughout the pair.

Convolution becomes multiplication. The Gaussian calculation then supplies a concrete summability kernel, and the radial-majorant lemma proves recovery at specified Lebesgue values. This separates norm convergence from pointwise recovery and leads to inversion when the transform is integrable, the product formula and injectivity. Finite complex measures are treated through their variation and Gaussian smoothing, ending with measure uniqueness and the conversion to probability's characteristic-function convention.

The elementary transform bound and uniform continuity argument require no choice selection. Items that use the Euclidean measure and approximation interfaces state countable choice; the Radon–Nikodym route for measure smoothing and its uniqueness consumer explicitly assume the Axiom of Choice. These assumptions are local to the statements that use them.

The companion computations test the normalization and the hypotheses of inversion. Wiener and interpolation references provide orientation only where identified; they are not substitutes for proved prerequisites. The next A page develops Schwartz topology and the unitary L2 transform.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)Open item page →

Fourier transform on complex L1 classes

Definition

Let n1 and fL1(Rn;C), with the componentwise integral and quotient conventions of Complex Lp classes and Euclidean test-function conventions, The space Lp(μ) as the quotient by null functions and The class L1(μ) of integrable functions. Define f^(ξ)=Ff(ξ):=Rnf(x)exp(2πixξ)dx,ξRn. Here xξ=j=1nxjξj, Lebesgue measure is used, and the exponential is The complex exponential by its power series. Its unit modulus follows from exp(x+iy)=ex(cosy+isiny), exp(x+iy)=ex, and eiπ+1=0. The integral is evaluated using any measurable representative. Absolute convergence and representative independence are the obligations discharged by The integral transform is representative independent . The output is a function defined at every frequency, not merely an almost-everywhere class. At frequency zero the formula reads f^(0)=f. No choice selection of representatives for a family of classes is part of this definition.

LemmaStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

The integral transform is representative independent

Statement

For every fL1(Rn;C), n1, the integral defining f^(ξ) is absolutely convergent for every ξ and unchanged by null-set modifications. Moreover f^(ξ)f1.

Facts & Assumptions

Given: An integrable complex representative f and ξRn, with the formula of Fourier transform on complex L1 classes.

[F1]

The exponential satisfies exp(x+iy)=ex for real x,y (exp(x+iy)=ex(cosy+isiny), exp(x+iy)=ex, and eiπ+1=0).

[F2]

Integrable functions equal almost everywhere have equal integrals on every measurable set (Two integrable functions are equal almost everywhere exactly when all of their indefinite integrals agree).

[F3]

The modulus of an integral is at most the integral of the modulus (The modulus of an integral is bounded by the integral of the modulus).

Proof

1.1

The exponential factor is continuous, hence measurable, and has modulus one. Thus the product is measurable and f(x)e2πixξdx=f<. Its componentwise integral exists, and f^(ξ)f1.

F1F3given
2.1

If g=f outside a measurable null set N, the same modulus equality proves the product with g integrable, and the two products agree outside N. Applying integral invariance on Rn gives identical values at this ξ. Since ξ was arbitrary, this holds at every frequency; no union of frequency-dependent exceptional sets is taken. In particular a zero class has identically zero transform.

F1F2step 1.1
TheoremStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

The L1 transform is bounded and uniformly continuous

Statement

The map F:L1(Rn;C)BUC(Rn;C) is complex-linear and supξf^(ξ)f1. Here n1 and BUC means bounded uniformly continuous functions.

Facts & Assumptions

Given: f,gL1, complex scalars a,b, and real frequency vectors ξ,h.

[F1]

The integral transform exists at every frequency, is representative independent, and satisfies the pointwise norm bound (The integral transform is representative independent).

[F2]

Dominated convergence applies to complex integrands dominated by one integrable function (Dominated convergence).

[F4]

Integration is complex-linear on L1 (The Lebesgue integral is linear on L1(μ)).

[F6]

The real mean value theorem bounds an increment by a bound for the derivative times the interval length (The mean value theorem, as the case g(x)=x of Cauchy's: for f continuous on [a,b] with a<b and differentiable on (a,b) there is c(a,b) with f(b)f(a)=f(c)(ba)), and (sinu)=cosu, (cosu)=sinu (The derivatives of sine and cosine are cosine and minus sine).

Proof

1.1

Reconstruct first the integral interface used here. Augment any finite disjoint display of a nonnegative simple function by the complement with coefficient 0. Intersections of two augmented displays partition the whole space and have equal coefficients on nonempty cells, so finite additivity and 0(+)=0 prove representation independence. Common refinements give simple addition and monotonicity; scalar zero is direct and positive scalars are termwise. Supremum over simple minorants and the sets {ujcs}, 0<c<1, give monotone convergence; increasing simple approximations give nonnegative additivity, and positive/negative plus real/imaginary decompositions give finite complex L1 linearity. Thus the integrable functions f(x)e2πixξ and g(x)e2πixξ have linear combination (af+bg)(x)e2πixξ, and integrating gives af+bg^=af^+bg^. The pointwise estimate in F1, with a right side independent of frequency, gives boundedness and the asserted supremum bound.

F1F4givenconstruct
2.1

The preceding MCT also gives Fatou by applying it to infjmvjlim infjvj. If uju almost everywhere and ujgL1, Fatou applied to 2guju0 gives lim supjuju0; hence L1 convergence, and the local finite linearity gives convergence of integrals. This proves the exact dominated-convergence clause used below without [F2]'s affected foundation. Factoring the exponentials yields f^(ξ+h)f^(ξ)=F(f(e2πixh1))(ξ). F1 therefore gives the bound f^(ξ+h)f^(ξ)I(h), where I(h)=f(x)e2πixh1dx. For real u, F5--F6 and F8 give sinuu, cosu1u, and hence eiu12u; F5 also bounds this modulus by two. Applying the locally proved dominated convergence to the explicit integer-ball tails, dominated by f, choose an integer R1 with x>Rf<ϵ/4. On xR, F7 gives 2πxh2πRh, so the single choice δ=ϵ/(8πR(1+f1)) makes e2πixh1<ϵ/(2(1+f1)) whenever h<δ. The inside integral is below ϵ/2 and the outside integral below ϵ/2, so I(h)<ϵ. Consequently, for every ϵ>0 there is δ>0 such that h<δ implies the difference is below ϵ for every ξ. This is uniform continuity.

F1F2F3F4F5F6F7F8step 1.1
TheoremStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Translation, modulation, linear dilation and reflection laws

Statement

Assume countable choice. For fL1(Rn;C), a,bRn, and invertible real n×n matrix A, put τaf(x)=f(xa) and Mbf(x)=e2πibxf(x). Then, at every frequency, τaf^(ξ)=e2πiaξf^(ξ),Mbf^(ξ)=f^(ξb),fA^(ξ)=detA1f^(ATξ). Also f()^(ξ)=f^(ξ) and f^(ξ)=f^(ξ).

Facts & Assumptions

Given: The stated data and The Axiom of Countable Choice (ACω); translation has the convention of Translation of a function on Rn.

[F1]

The transform is defined on classes at every frequency (The integral transform is representative independent).

[F2]

The complex L1 change-of-variables formula for a C1 diffeomorphism uses the absolute Jacobian determinant, under countable choice (A C^1 diffeomorphism satisfies the change-of-variables formula for L^1 functions).

Proof

1.1

The maps yy+a and xAx are C1 diffeomorphisms of the open set Rn, with determinants 1 and detA0. Applying F2 to f proves τaf1=f1 and fA1=detA1f1; unit modulus gives Mbf1=f1=f1. These operations preserve null equivalence, by the same substitution applied to indicators of null sets (or directly by its null-set proof). Countable choice is precisely the assumption inherited from this Lebesgue substitution interface.

F1F2given
2.1

Substituting x=y+a in the absolutely convergent translation integral gives f(y)e2πi(y+a)ξdy=e2πiaξf^(ξ). Combining exponential factors in the modulation integral gives e2πix(ξb), hence the modulation formula.

F2F3step 1.1
3.1

Substituting y=Ax gives xξ=yATξ and dx=detA1dy, proving the dilation formula. For A=I its determinant has absolute value one, proving reflection even when orientation is reversed. Finally conjugate the componentwise integral for f^(ξ): conjugation commutes with its real and imaginary integrals and sends e2πixξ to e2πixξ. This proves the last identity. All equalities are pointwise because F1 gives absolute convergence at each frequency.

F1F2step 1.1step 2.1
TheoremStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Fourier transform turns L1 convolution into multiplication

Statement

Assume countable choice. If f,gL1(Rn;C), n1, then fg^(ξ)=f^(ξ)g^(ξ) for every ξRn.

Facts & Assumptions

Given: The stated functions and The Axiom of Countable Choice (ACω).

[F1]

The complex convolution interface supplies representative-independent L1 convolution and translation isometries, under countable choice (Complex translation, convolution, approximate identities, and mollification).

[F2]

The product f(xy)g(y) of Borel representatives is jointly Borel measurable (Borel representatives make the convolution integrand Borel measurable).

[F3]

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

[F4]

Fubini equates complex iterated integrals when the product integral of the modulus is finite (Fubini's theorem for L^1 functions on a sigma-finite product).

[F5]

Translation obeys τyf^(ξ)=e2πiyξf^(ξ) (Translation, modulation, linear dilation and reflection laws).

[F6]

Null-equivalent L1 representatives have the same transform at every frequency (The integral transform is representative independent).

[F7]

Under countable choice, a completion-measurable real function has a base-measurable almost-everywhere equal representative (A function measurable for a completion is almost everywhere equal to one measurable for the original sigma-algebra).

Proof

1.1

Apply [F7] to the real and imaginary components of f and g, changing infinite values on their null sets to zero, to obtain finite Borel representatives. Euclidean Lebesgue spaces are sigma-finite (the boxes [k,k]n have finite volume and cover them). F2 gives product measurability. Translation invariance and Tonelli give f(xy)g(y)dxdy=f1g(y)dy=f1g1<. Thus the exponential-weighted integrand is also absolutely integrable at every fixed frequency, with this same bound.

F1F2F3F7given
2.1

Fubini now permits exchanging the integrals in the transform of the convolution representative. The inner x integral is the translation transform from F5, giving fg^(ξ)=g(y)e2πiyξf^(ξ)dy=f^(ξ)g^(ξ). The convolution is defined arbitrarily on its null exceptional set; F6 makes that choice irrelevant at every frequency. This proves the asserted equality, including when either input is zero.

F1F4F5F6step 1.1
LemmaStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Complex integration by parts on intervals and decaying lines

Statement

Assume countable choice. For complex C1 functions u,v on [a,b], a<b, Lebesgue integration gives abuv=u(b)v(b)u(a)v(a)abuv and abu=u(b)u(a). If instead u,vC1(R;C), uv,uvL1(R) and u(x)v(x)0 as x±, then Ruv=Ruv.

Facts & Assumptions

Given: The stated functions, The Axiom of Countable Choice (ACω), and the componentwise calculus/integration convention of Complex Lp classes and Euclidean test-function conventions.

[F2]

A bounded Riemann integrable real function on a closed interval has the same Lebesgue integral under countable choice (A bounded Riemann integrable function on a closed bounded interval is Lebesgue measurable and has the same integral).

[F4]

Dominated convergence applies to complex integrable functions (Dominated convergence).

Proof

1.1

Write u=r+is, v=p+iq. Apply F1 to the four real pairs (r,p),(s,q),(r,q),(s,p). Subtract the second identity from the first and add i times the sum of the last two. Since uv=(rpsq)+i(rq+sp) and uv=(rpsq)+i(rq+sp), the result is the complex integration-by-parts identity. All integrands are continuous on the compact interval and hence bounded and Riemann integrable; F2 changes each real integral to a Lebesgue integral. Applying F3 to r,s and the same F2 gives the complex FTC. This is the sole countable-choice use here.

F1F2F3given
2.1

For the whole-line assertion apply step 1.1 on [N,N]. The truncated products converge pointwise to uv and uv and have integrable majorants uv and uv. F4 gives convergence of both integrals; the boundary term u(N)v(N)u(N)v(N) tends to zero by the two assumed limits. Passing to the limit proves the assertion. No separate integrability of u or v is required.

F4step 1.1given
LemmaStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Euclidean Gaussian transform with the 2π normalization

Statement

Assume countable choice. For n1, t>0, and ξRn, F(eπtx2)(ξ)=tn/2eπξ2/t. Every polynomial times a positive real Gaussian is absolutely integrable.

Facts & Assumptions

Given: n1, t>0 and The Axiom of Countable Choice (ACω).

[F1]

The real improper Gaussian integral equals π (The Gaussian integral ex2dx=π).

[F2]

Nonnegative convergent improper integrals agree with Lebesgue integrals under countable choice (A nonnegative improper Riemann integral on a half-line agrees with the Lebesgue integral).

[F3]

Exponential growth dominates each nonnegative integer power (The exponential dominates every fixed nonnegative integer power at +).

[F4]

Complex differentiation under the integral is valid under an integrable derivative majorant (Differentiation under the integral sign).

[F5]

Complex integration by parts on the line holds for integrable products and vanishing product boundaries; its finite-interval FTC also holds (Complex integration by parts on intervals and decaying lines).

[F6]

Absolutely integrable product integrals may be exchanged (Fubini's theorem for L^1 functions on a sigma-finite product).

[F7]

The C1 Lebesgue substitution formula uses the absolute determinant (A C^1 diffeomorphism satisfies the change-of-variables formula for L^1 functions).

[F8]

Euler's formula and real trigonometric derivatives give (e2πixξ)ξ=2πixe2πixξ (exp(x+iy)=ex(cosy+isiny), exp(x+iy)=ex, and eiπ+1=0, The derivatives of sine and cosine are cosine and minus sine).

Proof

1.1

For c>0 and integer m0, F3 bounds xmecx2/2 on the tails, and it is bounded on a compact middle interval by continuity. Thus xmecx2Cecx2/2. F1, F2 on both half-lines (reflect the negative half), and F7 give integrability of these majorants and eπx2dx=1. In several dimensions bound a polynomial by a finite sum of monomials and factor the Gaussian; successive nonnegative integration gives the product of the finite one-dimensional bounds.

F1F2F3F6F7given
2.1

Put G(ξ)=eπx2e2πixξdx in dimension one. F4 applies on every frequency interval with derivative majorant 2πxeπx2 from step 1.1. Hence G(ξ)=2πixeπx2e2πixξdx. Apply F5 to u=eπx2 and v=e2πixξ: both derivative products are integrable by step 1.1 and uv0 at both ends. Since u=2πxu and v=2πiξv, it follows that xuv=iξG(ξ), and therefore G=2πξG.

F4F5F8step 1.1
3.1

The product rule gives (eπξ2G(ξ))=0. Applying the finite-interval complex FTC to its real and imaginary parts shows this product is constant, equal to G(0)=1. Thus G(ξ)=eπξ2. F6 tensors this formula in n coordinates; absolute integrability is supplied by step 1.1. Finally substitute y=tx using F7; the Jacobian is tn/2 and the frequency becomes ξ/t. This gives exactly the claimed formula. Countable choice is inherited from F2 and F7, and the argument uses neither later Schwartz theory nor a Fourier inversion theorem.

F2F5F6F7step 1.1step 2.1
TheoremStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Riemann–Lebesgue lemma

Statement

Assume countable choice. For fL1(Rn;C), n1, f^C0(Rn;C): it is continuous and tends to zero as ξ. The notation extends The space C0(Rn) of continuous functions vanishing at infinity componentwise.

Facts & Assumptions

[F1]

The transform is linear, uniformly continuous and bounded by the input L1 norm (The L1 transform is bounded and uniformly continuous).

[F2]

Translation multiplies the transform by e2πihξ (Translation, modulation, linear dilation and reflection laws).

[F3]

Complex L1 translations are norm-continuous under countable choice (Complex translation, convolution, approximate identities, and mollification).

Proof

1.1

For ξ0 set h=ξ/(2ξ2). Then hξ=1/2, so τhff^(ξ)=2f^(ξ) by F2 and linearity. The bound in F1 gives 2f^(ξ)τhff1.

F1F2given
2.1

Given ϵ>0, F3 supplies δ>0 with τhff1<2ϵ for h<δ. If ξ>1/(2δ), the explicit h from step 1.1 satisfies that condition, hence f^(ξ)<ϵ. Continuity is already F1. This is the asserted C0 property. Countable choice is inherited from F2 and F3, not from the explicit selection of h.

F1F2F3step 1.1
LemmaStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Gaussian summability kernels

Statement

Assume countable choice. For t>0 put kt(x)=tn/2eπx2/t on Rn, n1. Then kt0, kt=kt1=1, kt^(ξ)=eπtξ2, and (kt)t>0 is an L1 approximate identity as t0. Directly, kt(z)=eπtξ2e2πizξdξ.

Facts & Assumptions

Given: n1, t>0 and The Axiom of Countable Choice (ACω).

[F1]

The Gaussian transform is F(eπsx2)(ξ)=sn/2eπξ2/s for s>0 (Euclidean Gaussian transform with the 2π normalization).

[F2]

The complex Lebesgue substitution formula uses the absolute Jacobian (A C^1 diffeomorphism satisfies the change-of-variables formula for L^1 functions).

[F3]

Dominated convergence passes integrable tails to zero (Dominated convergence).

[F4]

An approximate identity has unit mass, uniformly bounded L1 norm and vanishing absolute tails outside every fixed radius (An L1 approximate identity on Rn).

Proof

1.1

Apply F1 with s=1/t and multiply by tn/2 to obtain kt^(ξ)=eπtξ2. At ξ=0 this gives mass one; positivity gives the same L1 norm. Applying F1 with s=t at frequency z proves the displayed inverse integral without an inversion theorem.

F1given
2.1

Write y=x/t. F2 gives x>δkt(x)dx=y>δ/teπy2dy. This tends to zero: F3 applied to the explicit integer-radius tails with majorant the integrable Gaussian gives their convergence to zero, and monotonicity bounds every sufficiently small t-tail by any fixed integer tail. All three conditions in F4 now hold with norm bound one. Countable choice is inherited from the Gaussian and substitution results.

F1F2F3F4step 1.1
LemmaStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Lebesgue-point convergence for radial-majorized kernels

Statement

Assume countable choice. Let n1 and let K:RnC be measurable, with K=1 and K(y)Φ(y), where Φ:[0,)[0,) is bounded, nonincreasing, and J:=Φ(y)dy<. For fL1(Rn;C) and a point x with specified Lebesgue value aC, meaning A(r):=y<rf(xy)ady=o(rn), one has εnK(y/ε)f(xy)dya(ε0). The integral is absolutely convergent for every ε>0. The value a is the Lebesgue-point value, not an arbitrary changed value of the representative; this is the componentwise version of Lebesgue points and the Lebesgue set of an Lloc1 class.

Facts & Assumptions

[F1]

Open subsets of Euclidean space are Lebesgue measurable under countable choice (Assuming countable choice, every Borel subset of Rn is Lebesgue measurable).

[F2]

Measurable balls have positive finite measure by the cube bounds in Euclidean balls have positive finite Lebesgue measure.

[F4]

Tonelli gives countable nonnegative summation under the integral (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product).

[F5]

Complex Lebesgue substitution holds for C1 diffeomorphisms, including translations, reflections and positive dilations (A C^1 diffeomorphism satisfies the change-of-variables formula for L^1 functions).

Proof

1.1

Balls are open by the triangle inequality, so F1 establishes measurability before the cube bounds F2 are used. Put vn=B(0,1)(0,). F3 gives B(0,r)=vnrn and B(0,r)B(0,r/2)=vn(12n)rn. On that annulus Φ(y)Φ(r); hence rnΦ(r)Jr/[vn(12n)]0 as r, where Jr is the integral over yr/2. Integrability implies these tails tend to zero, by countable additivity on explicit integer annuli. Also disjoint annuli 2j1y<2j, j0, give j02jnΦ(2j)J/[vn(12n)].

F1F2F3F4given
1.2

Write H(y)=f(xy)a. Boundedness of Φ makes the integral with f absolutely convergent: it is at most εnΦ(0)f1 by reflection and translation of Lebesgue measure. Scaling the defining integral of K gives εnK(y/ε)dy=1. Fact F5 applies to these affine diffeomorphisms and supplies both substitutions. Thus the absolute error is at most εnΦ(y/ε)H(y)dy.

F5given
2.1

Given η>0, fix δ>0 such that A(r)ηrn for 0<r<δ. For ε<δ/2, the central ball contributes at most Φ(0)εnA(ε)ηΦ(0). Each dyadic shell 2jεy<2j+1ε whose lower radius is below δ/2 contributes at most εnΦ(2j)A(2j+1ε)η2n2jnΦ(2j). Their sum is bounded by ηC, where C=Φ(0)+2nJ/[vn(12n)], independently of ε. These regions cover y<δ/2.

F4step 1.1step 1.2given
3.1

On yδ/2, the contribution from f(xy) is at most εnΦ(δ/(2ε))f10 by step 1.1. The contribution from a is at most azδ/(2ε)Φ(z)dz0 by integrability and scaling. The total error therefore has limit superior at most ηC. Letting η0 proves convergence. The proof uses the stated countable-choice Euclidean measure interfaces and explicit shells, with no full AC or choice of witnesses at different points.

F5step 1.1step 1.2step 2.1
TheoremStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Gaussian Fourier summability at Lebesgue points

Statement

Assume countable choice. For fL1(Rn;C) and t>0, Stf(x):=f^(ξ)eπtξ2e2πixξdξ=(fkt)(x) for every x, where kt(x)=tn/2eπx2/t. As t0, Stff in L1 and at every Lebesgue point with value a one has Stf(x)a.

Facts & Assumptions

Given: n1, fL1, t>0 and The Axiom of Countable Choice (ACω).

[F1]

f^ is bounded by f1 (The L1 transform is bounded and uniformly continuous).

[F2]

The Gaussian kernels have mass one, form an approximate identity, and equal the inverse Gaussian integral (Gaussian summability kernels).

[F3]

A bounded integrable decreasing radial majorant gives convergence at every specified Lebesgue value (Lebesgue-point convergence for radial-majorized kernels).

[F4]

Complex Fubini holds for absolutely integrable product integrands (Fubini's theorem for L^1 functions on a sigma-finite product).

[F5]

Complex approximate identities converge in each finite Lp norm under countable choice (Complex translation, convolution, approximate identities, and mollification).

Proof

1.1

By F1 and Gaussian integrability, the defining integral for Stf(x) is absolutely convergent. Inserting the definition of f^, the product integrand has modulus f(y)eπtξ2, whose double integral is f1tn/2<. Use a Borel representative of f as supplied in F5's convolution construction; the resulting integrand is product measurable. F4 therefore gives Stf(x)=f(y)[eπtξ2e2πi(xy)ξdξ]dy=f(y)kt(xy)dy by F2. This last integral exists at every x since k_t is bounded; substitution yxy gives the stated convolution convention.

F1F2F4F5given
2.1

F2 and F5 now give Stff10. For pointwise recovery, take K(y)=eπy2, Φ(r)=eπr2 and ε=t in F3. This profile is bounded, nonnegative and decreasing, its radial integral is one, and the dilated kernel is exactly k_t. Thus at every specified Lebesgue value a, Stf(x)a. The two assertions use different estimates; norm convergence alone has not been used to infer pointwise convergence.

F2F3F5step 1.1
TheoremStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

L1 Fourier inversion with an integrable transform

Statement

Assume countable choice. If fL1(Rn;C) and f^L1, then g(x)=f^(ξ)e2πixξdξ is bounded and continuous, equals f almost everywhere, and equals the specified value at every Lebesgue point of f.

Facts & Assumptions

Given: n1, f,f^L1 and The Axiom of Countable Choice (ACω).

[F1]

Gaussian Fourier means recover each Lebesgue value (Gaussian Fourier summability at Lebesgue points).

[F2]

An L1 transform is bounded and uniformly continuous (The L1 transform is bounded and uniformly continuous).

[F3]

Dominated convergence permits passage under an integral with a single integrable majorant (Dominated convergence).

[F4]

Almost every point of a locally integrable function is a Lebesgue point under countable choice (Almost every point is a Lebesgue point of a locally integrable function).

Proof

1.1

Since f^L1, F2 applied to it shows that g(x)=F(f^)(x) is bounded and uniformly continuous. For fixed x and the explicit sequence tm=1/(m+1), mN, the damped integrands converge pointwise to f^(ξ)e2πixξ and have majorant f^. F3 therefore gives Stmf(x)g(x).

F2F3given
2.1

At any Lebesgue point with value a, F1 gives the same sequence limit a, so g(x)=a. Since fL1 is locally integrable, F4 gives such points with a=f(x) outside a null set (for complex inputs apply the real conclusion to both components and bound the complex oscillation by their sum). Hence g=f almost everywhere. In particular g represents the original L1 class. Countable choice is precisely inherited from F1 and F4; no statement about all values of an arbitrary representative follows.

F1F4step 1.1
TheoremStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Fourier transform of a product with one integrable transform

Statement

Assume countable choice. For f,gL1(Rn;C) with f^L1, use the continuous representative fc(x)=f^(η)e2πixηdη. Then fcgL1 and, for every ξ, fg^(ξ)=f^(η)g^(ξη)dη. The product class is unchanged by other representatives; the symmetric variant holds when g^L1 instead.

Facts & Assumptions

Given: The stated inputs and The Axiom of Countable Choice (ACω).

[F1]

Inversion gives the continuous representative from an integrable transform (L1 Fourier inversion with an integrable transform).

[F2]

The transform bound is suph^h1 (The L1 transform is bounded and uniformly continuous).

[F3]

Fubini permits exchanging absolutely integrable complex product integrals (Fubini's theorem for L^1 functions on a sigma-finite product).

Proof

1.1

F1 and the bound F2 applied to f^ give fc(x)f^1, hence fcg1f^1g1<. Changing either input on a null set changes its product only on the union of those two sets, so the integrable product class is well-defined. Also the convolution integral in the conclusion is absolutely convergent at every frequency, bounded by f^1g1 using F2.

F1F2given
2.1

Insert the inverse integral for fc into fc(x)g(x)e2πixξdx. The product integrand has modulus f^(η)g(x) with double integral f^1g1; measurability follows from coordinate pullbacks and the continuous exponential. F3 exchanges the integrals, giving f^(η)[g(x)e2πix(ξη)dx]dη, the required expression. Exchanging the roles of f and g proves the symmetric variant under its stated hypothesis. Countable choice is inherited from F1. No assertion that arbitrary products of two integrable functions are integrable is used.

F1F3step 1.1
CorollaryStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Uniqueness of the L1 Fourier transform

Statement

Assume countable choice. If f,gL1(Rn;C) and f^=g^, then f=g almost everywhere. Equality of the transforms almost everywhere already suffices.

Facts & Assumptions

Given: n1, the stated inputs and The Axiom of Countable Choice (ACω).

[F1]

The transform is linear and continuous as a function of frequency (The L1 transform is bounded and uniformly continuous).

[F2]

A function and its integrable transform obey inversion almost everywhere (L1 Fourier inversion with an integrable transform).

Proof

1.1

Set h=fg. By linearity, h^=0. If equality was given only almost everywhere, continuity still implies this everywhere: a nonzero value would remain bounded away from zero on an open ball, which contains a positive-volume box and cannot be null. Thus the transform of h is the zero integrable function.

F1given
2.1

F2 applies to h, since both h and its zero transform are integrable. It gives h(x)=0dξ=0 almost everywhere, so f=g as classes. Countable choice is inherited from inversion (and the Euclidean measure interface in the optional almost-everywhere hypothesis).

F2step 1.1
CorollaryStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Fourier multipliers of approximate identities

Statement

Assume countable choice. For any complex L1 approximate identity (Kε), K^ε(ξ)1 at each frequency. For fL1, fKε^=f^K^εf^ uniformly. Also fKεf in every finite Lp norm for which fLp.

Facts & Assumptions

Given: n1, The Axiom of Countable Choice (ACω), and the unit-mass, bounded-norm and absolute-tail conditions of An L1 approximate identity on Rn.

[F1]

Complex approximate identities converge in finite Lp norms (Complex translation, convolution, approximate identities, and mollification).

[F2]

The convolution transform equals the product of transforms (Fourier transform turns L1 convolution into multiplication).

[F3]

The supremum norm of a transform is bounded by the input L1 norm (The L1 transform is bounded and uniformly continuous).

Proof

1.1

Put M=supεKε1. Unit mass gives K^ε(ξ)1=Kε(y)(e2πiyξ1)dy. For fixed ξ, its modulus is bounded by Msupy<δe2πiyξ1+2yδKε(y)dy. The latter tail tends to zero (bound it by the defining tail outside δ/2), and the first term tends to zero with δ. This proves the pointwise multiplier limit.

given
2.1

F1 applies to every stated finite p and gives norm convergence, including p=1. By F2 and F3, f^K^εf^=F(fKεf)fKεf10. Thus uniform transform convergence follows from norm approximation, not merely the pointwise multiplier limit. Countable choice is inherited from F1 and F2.

F1F2F3step 1.1
TheoremStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Fourier transform of a finite complex Borel measure

Statement

Assume countable choice. Let μ be a complex Borel measure on Rn, n1, with finite total variation. Then μ^(ξ):=e2πixξdμ(x) is a bounded uniformly continuous function and supμ^μ(Rn).

Facts & Assumptions

Proof

1.1

First repair the positive integral used to construct the complex-measure integral. Augment every finite disjoint nonnegative-simple display by its complement with coefficient 0. Pairwise intersections of two augmented displays partition the space and carry equal coefficients on nonempty cells, so finite additivity and 0(+)=0 prove representation independence. Common refinements give simple addition and monotonicity; scalar zero is direct and positive scalars are termwise. Supremum over simple minorants and the sets {ujcs}, 0<c<1, give monotone convergence; increasing simple approximations give nonnegative additivity and finite L1 linearity after positive/negative and real/imaginary decomposition. Fatou follows by applying MCT to infjmvj; applying Fatou to 2guju proves dominated convergence when ujgL1. For a canonical nonzero-level complex simple function, the triangle inequality and the definition of variation give sdμsdμ. Passing to L1(μ) simple limits using this bound constructs the complex integral, makes it independent of the approximants, and preserves the same variation bound and finite linearity. Each exponential is bounded Borel with modulus one, so it is integrable against μ. The locally reconstructed complex integral exists and gives μ^(ξ)μ(Rn); no Radon–Nikodym representation is needed.

F1F3givenconstruct
2.1

By the addition law and the locally proved variation bound, μ^(ξ+h)μ^(ξ)e2πixh1dμ(x), independently of ξ. Under the stated countable choice the sequential Euclidean limit criterion applies; the locally proved dominated convergence, with majorant 2 on this finite measure space, makes this bound tend to zero as h tends to zero. Hence the transform is uniformly continuous. Countable choice also covers the near-maximizing partition selections in the total-variation additivity proof. Finite variation was assumed; no general finiteness theorem, RN or Hahn decomposition is used.

F1F2F3step 1.1
LemmaStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Gaussian smoothing of finite measures

Statement

Assume AC. Let μ be a finite complex Borel measure of finite variation on Rn, n1. For t>0 define ht(x)=kt(xy)dμ(y) using the Gaussian kernel. Then htL1, ht1μ(Rn), and h^t=k^tμ^. For every complex φCc(Rn), φ(x)ht(x)dxφdμ.

Facts & Assumptions

[F1]

Under AC a finite complex measure absolutely continuous with respect to a sigma-finite positive measure has an integrable density (A finite complex measure absolutely continuous with respect to a sigma-finite positive measure has an integrable complex density).

[F3]
[F5]

Gaussian kernels have mass and norm one and the stated Gaussian transform (Gaussian summability kernels).

[F6]

Gaussian approximate identities converge uniformly on complex C0 (Complex translation, convolution, approximate identities, and mollification).

[F7]

Translation has transform multiplier e2πiyξ (Translation, modulation, linear dilation and reflection laws).

Proof

1.1

Put v=μ. The inequality μ(E)v(E) gives μv; v is finite, hence sigma-finite. F1 gives μ=uv with uL1(v), and F2 gives v(E)=Eudv, in particular udv=v(Rn). For any bounded measurable H, Hdμ=Hudv: first verify this for simple H using the density formula on sets, then approximate bounded H uniformly by quantizing its real and imaginary values. F3 bounds the error on the left by v(Rn)HHm, and the right error by u1HHm. AC enters F1 through the signed RN/Hahn/Jordan existence selections; it also covers the existence assumption omitted in the older F2 proof.

F1F2F3given
2.1

Consequently ht(x)=kt(xy)u(y)dv(y), absolutely at every x because k_t is bounded and u integrable. The joint function is Borel measurable. By F4, F5 and translation invariance, its double absolute integral is u(y)[kt(xy)dx]dv(y)=v(Rn). Fubini therefore supplies a measurable integrable h_t and its stated norm bound. With the additional modulus-one Fourier factor the same double bound applies. F4 and F7 give h^t(ξ)=k^t(ξ)e2πiyξu(y)dv(y)=k^t(ξ)μ^(ξ) by step 1.1.

F4F5F7step 1.1
3.1

For a compactly supported continuous φ, the double absolute integral after multiplication by φ(x) is at most φv(Rn). F4 exchanges the integrals. Since k_t is even, the inner test integral is (ktφ)(y), and F6 gives uniform convergence to φ(y). Thus the difference from φudv has modulus at most ktφφuL1(v)0. Step 1.1 identifies the limit with φdμ.

F4F5F6step 1.1step 2.1
CorollaryStatement: Literature-sourcedProof: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Uniqueness of finite Borel measures from their Fourier transforms

Statement

Assume AC. Finite complex Borel measures μ,ν on Rn with μ^=ν^ are equal. Here finite means finite total variation, and n1.

Facts & Assumptions

Given: The stated measures and The Axiom of Choice.

[F1]

Gaussian smoothing has transform k^tσ^ and converges against all compactly supported continuous tests (Gaussian smoothing of finite measures).

[F2]

The integral Fourier transform is injective on L1 (Uniqueness of the L1 Fourier transform).

[F3]

A compact-finite Borel measure on a second-countable LCH space is regular (Locally finite Borel measures on second-countable LCH spaces are regular).

[F4]

Positive Radon measures agreeing on every compactly supported continuous test are equal (Uniqueness of the RMK representing measure among Radon measures).

Proof

1.1

Set σ=μν. It is a complex measure and its partition sums are bounded by μ+ν, so it has finite variation. Linearity of the bounded-test integrals gives σ^=0. For every t>0, F1 gives a density htL1 with zero transform; F2 gives ht=0 almost everywhere. Passing to the F1 testing limit yields φdσ=0 for every complex φCc.

F1F2given
2.1

Euclidean space is Hausdorff (disjoint small balls separate points) and locally compact by compact closed balls from F6. Balls with rational centers and positive rational radii form a countable base: for an open neighborhood of x choose a sufficiently small contained ball, then a rational center sufficiently near x and rational radius between the resulting strict bounds. Thus F3 applies to the finite positive measure v=σ and makes it regular. Under AC, F5 gives Jordan parts r+,r of r=Reσ and s+,s of s=Imσ. On their respective Hahn sets, for example r+(E)=r(EP)σ(EP)v(E); the same argument bounds each other part by v.

F3F5F6step 1.1
3.1

If 0ρv is one of these parts and E is Borel, regularity of finite v gives compact KE and open UE with v(EK)<ϵ and v(UE)<ϵ. The corresponding rho errors are at most these, so rho is both inner and outer regular and finite on compact sets, hence Radon. For real φCc, step 1.1 gives φdr+=φdr and the analogous equality for s. These component integral identities follow for simple tests and then by their bounded-test approximation. F4 gives r+=r and s+=s, so σ=0. AC is used in smoothing and the Hahn/Jordan decompositions, and covers the regularity construction.

F4F5step 1.1step 2.1
RemarkRemark: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)Open item page →

Characteristic-function normalization

Convention

For a positive Borel probability measure μ on Rn, define φμ(t)=eitxdμ(x). This integral exists because the integrand is Borel of modulus one and μ(Rn)=1; use Integrable real and complex functions, and their integrals and exp(x+iy)=ex(cosy+isiny), exp(x+iy)=ex, and eiπ+1=0. With the negative 2π Fourier convention, the same integral is φμ(t)=μ^(t/(2π)), because 2πix(t/(2π))=itx. In particular φμ(0)=1. This is a sign-and-scale dictionary for a supplied positive probability measure; no measure construction, uniqueness theorem or choice principle is used.

RemarkRemark: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)Open item page →

The interpolation input belongs to measure theory

Interpolation input

The bound f^f1 in The L1 transform is bounded and uniformly continuous supplies the Fourier L1L endpoint. Interpolation requires a theorem that actually permits an infinite target exponent. A theorem stated only with finite target endpoint exponents cannot supply that step.

The published page complex-riesz-thorin-endpoint-interpolation is the designated endpoint-capable supplier; it lies outside this pair's current prerequisite closure. Its role here is orientation. Intermediate-exponent Fourier bounds are not asserted or used in this page, and no second Riesz–Thorin theorem is introduced. The later Plancherel pair supplies the other Fourier endpoint and common-domain agreement needed for that route.

5 · Examples, counterexamples and false statements

None yet.

Sources