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Tempered Distributions and the Fourier Transform

1 · Prerequisites

2 · Summary

Tempered distributions are the continuous bilinear dual of Schwartz space. The finite-seminorm criterion makes that continuity usable, while restriction to compactly supported tests and extension of compactly supported distributions relate the theory precisely to ordinary distributions. Weak and strong dual topologies are kept distinct throughout.

With the negative-sign, 2π-normalized Fourier convention, transposition extends the Schwartz transform to a topological automorphism of S. The resulting calculus includes derivatives, polynomial and slowly increasing multipliers, elementary transforms, and the unit-lattice Dirac comb. The final results prove smoothness of SS, handle convolution by a compactly supported distribution, and state only the Fourier product and convolution identities for which every operation is defined.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-14Open item page →

Tempered distribution

Definition

Fix an integer n1. A tempered distribution on Rn is a continuous complex-linear functional

u:S(Rn)C,

where Schwartz space and its locally convex topology are those of Schwartz space and its seminorms and Schwartz topology and convergence. The space of all such functionals is denoted S(Rn).

We write u,φ=u(φ). This pairing is bilinear: the test variable is not conjugated. Thus u(aφ+bψ)=au,φ+bu,ψ for a,bC. The zero functional is tempered. Continuity is topological continuity, and, because the Schwartz topology is generated by a countable cofinal family of seminorms, it is equivalently continuity on every convergent sequence. No choice principle is used in this definition.

TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-14Open item page →

Finite seminorm bound characterizes tempered distributions

Statement

Let u:S(Rn)C be complex-linear. Then u is tempered if and only if there are C0 and integers N,M0 such that

u,φCmaxαN, βMsupxRnxαβφ(x)

for every φS(Rn).

Facts & Assumptions

Given: A complex-linear functional u on S(Rn).

[F1]

A basic zero-neighborhood in Schwartz space imposes finitely many strict bounds on its defining seminorms (Tempered distribution).

Proof

technique · direct continuity estimate
1.1

Suppose u is continuous. There is a basic zero-neighborhood U={φ:pαjβj(φ)<εj,1jr} on which u(φ)<1. If r=0, then U=S and linearity forces u=0, so take C=0. Otherwise put Q(φ)=maxjpαjβj(φ)/εj.

F1
2.1

If Q(φ)>0, then φ/(2Q(φ))U, whence u(φ)<2Q(φ). If Q(φ)=0, every scalar multiple of φ lies in U; boundedness of those scalar multiples of u(φ) forces u(φ)=0. Choose N and M dominating the finitely many αj and βj. Then Q(φ) is at most maxjεj1 times the rectangular maximum in the statement, which proves the required estimate.

F1step 1.1
3.1

Conversely, assume the displayed estimate. For every ε>0, the set on which its finite maximum is less than ε/(C+1) is a zero-neighborhood and is carried by u into the disk of radius ε. Thus u is continuous and hence tempered.

F1given
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Weak and strong topologies on tempered distributions

Definition

A set BS(Rn) is bounded when supφBpαβ(φ)< for every pair of multi-indices. The weak topology σ(S,S) on tempered distributions is generated by

pφ(u)=u,φ(φS).

The strong topology β(S,S) is generated by

pB(u)=supφBu,φ

as B ranges over bounded subsets of S. The empty-set supremum is zero. This supremum is finite: continuity of u gives a basic zero-neighborhood U on which u<1, and the finitely many seminorm bounds defining U imply BtU for some finite t>0; hence pB(u)t. The triangle inequality and homogeneity follow pointwise.

Thus a net (ui) converges weakly to u exactly when uiu,φ0 for every φS, and it converges strongly exactly when pB(uiu)0 for every bounded B. Singletons are bounded, so strong convergence implies weak convergence. Both topologies are Hausdorff, since distinct functionals differ on some test. No identification with either topology on D is asserted, and no choice axiom is used.

TheoremStatement: AI-adaptedProof: AI-adaptedaudited 2026-09-14Open item page →

Polynomial growth functions define tempered distributions

Statement

Let f:RnC be locally integrable. If, for some integer N0,

Rnf(x)(1+x)Ndx<,

then the regular functional uf(φ)=fφ is a tempered distribution. Consequently this holds if f has pointwise polynomial growth outside a compact set, and every class in complex Lp(Rn), 1p, has a representative defining a tempered distribution. These are sufficient conditions; pointwise polynomial growth is not asserted to characterize all regular tempered distributions.

Facts & Assumptions

Given: A locally integrable complex function f on Rn.

[F1]
[F2]

One finite rectangular Schwartz-seminorm estimate characterizes tempered functionals (Finite seminorm bound characterizes tempered distributions).

[F3]

Hölder's inequality, including the L1 and L endpoints, applies to the real nonnegative functions f and a weight (Holder's inequality for integrals, including the endpoint cases).

[F4]

Complex Lp classes, their moduli, and their locally integrable representatives use the conventions of Complex Lp classes and Euclidean test-function conventions.

[F5]

A real p-series converges when its exponent exceeds one (The p-series for a real exponent p converges exactly when p is greater than one).

Proof

technique · weighted integral estimate
1.1

For each integer N0, expansion of (1+x1++xn)N gives a finite constant An,N for which the following estimate holds.

algebra

(1+x)Nφ(x)An,NmaxαNpα,0(φ).

Thus the weighted hypothesis implies uf(φ)An,N(f(1+x)N)maxαNpα,0(φ). [F1, algebra]

2.1

The estimate in step 1.1 makes the integral absolutely convergent for every Schwartz test and proves that uf is tempered. It also shows directly that changing f on a null set changes no pairing.

F1F2step 1.1
3.1

The integer shells mx<m+1 have measure at most (2m+2)n. Hence (1+x)sdx< whenever s>n+1, by comparison with m1mns. If f(x)C(1+x)d off a compact set, choose an integer N>d+n+1. Local integrability handles the compact part, and the shell estimate handles its complement, so step 2.1 applies.

F5step 2.1
4.1

If fL1, take N=0. If 1<p< and q is conjugate to p, choose N with Nq>n+1; Hölder gives f(1+x)Nfp(1+)Nq<. If p=, choose N>n+1 and use any finite essential bound for f. The same estimates on bounded balls give local integrability of the chosen representatives.

F3F4step 3.1
5.1

For n1, as a boundary calculation, define fr(x)=xr for x0 and assign any finite value, say fr(0)=0, when r<0; set f01, and for r>0 use the usual value fr(0)=0. The value at this measure-zero point has no effect on local integrability or the induced distribution. The function fr is locally integrable at the origin exactly when r>n: for r<0, the dyadic annuli 2j1x<2j give a series comparable to j2j(n+r); for r0 there is no singularity, while the reverse bound on a fixed cone gives divergence when rn. At infinity it has polynomial growth. Therefore fr is among the tempered regular examples precisely for the locally meaningful range r>n.

F1step 2.1step 3.1
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Fourier transform of a tempered distribution

Definition

Assume Countable Choice, exactly as required by the published Schwartz Fourier theorem. For φS(Rn) put

φ^(ξ)=Fφ(ξ)=Rnφ(x)e2πixξdx.

For uS(Rn) define its Fourier transform by

Fu,φ=u,Fφ(φS(Rn)).

The published automorphism Fourier transform is a topological automorphism of Schwartz space sends Schwartz tests continuously to Schwartz tests, so composition with the continuous functional of Tempered distribution is again a continuous complex-linear functional. Hence FuS. The pairing is bilinear: there is no conjugation and no inverse transform on the right-hand side. Countable Choice is used only through the cited published Fourier construction; transposition itself uses no additional choice.

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Fourier transform on tempered distributions is well defined and continuous

Statement

Assume Countable Choice. The Fourier transform F:S(Rn)S(Rn) is well-defined and complex-linear. It is continuous for both the weak topology σ(S,S) and the strong topology β(S,S).

Facts & Assumptions

Given: Countable Choice and a tempered distribution u.

[F1]

The distributional transform is the bilinear transpose of the Schwartz transform (Fourier transform of a tempered distribution).

[F2]

The Schwartz transform is a continuous linear automorphism (Fourier transform is a topological automorphism of Schwartz space).

[F3]

Weak dual seminorms use single tests and strong dual seminorms use bounded test sets (Weak and strong topologies on tempered distributions).

Proof

technique · transpose seminorm calculation
1.1

By [F2], Fφ is a Schwartz test and depends continuously and linearly on φ. Thus φu(Fφ) is a continuous complex-linear functional. This proves well-definedness, and linearity in u follows directly from the pairing.

F1F2
1.2

For a single test φ, pφ(Fu)=u(Fφ)=pFφ(u). Every target weak seminorm therefore pulls back to a source weak seminorm, so F is weakly continuous.

F1F3
2.1

If BS is bounded, continuity and linearity of the Schwartz transform imply that F(B) is bounded: each output seminorm is bounded by finitely many input seminorms.

F2step 1.1

pB(Fu)=supφBu(Fφ)=pF(B)(u).

Thus every target strong seminorm pulls back to a strong seminorm and the map is strongly continuous. Countable Choice was used only in [F2], not in these transpose calculations. [F2, F3] ∎

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Fourier transform is a topological automorphism of tempered distributions

Statement

Assume Countable Choice. Fourier transformation is a topological automorphism of S(Rn) for both the weak and strong dual topologies. If

Ru,φ=u,φ(),

then F2u=Ru and F1=RF=FR.

Facts & Assumptions

Given: Countable Choice and uS(Rn).

[F1]

Fourier transformation on S is weakly and strongly continuous (Fourier transform on tempered distributions is well defined and continuous).

[F2]

On Schwartz space, F2=R, R2=I, and F1=RF (Fourier transform is a topological automorphism of Schwartz space).

Proof

technique · transpose the Schwartz identities
1.1

Evaluate the second transform on an arbitrary Schwartz test φ.

F2

F2u,φ=u,F2φ=u,Rφ=Ru,φ.

Thus F2u=Ru. This is a direct test calculation and uses no density assertion about S inside its dual. [F2]

2.1

Reflection on the dual satisfies R2=I. Since step 1.1 gives R=F2 as operators on S, associativity gives the following two-sided inverse calculation.

step 1.1algebra

(RF)F=R2=I,F(RF)=F4=R2=I.

Hence F1=RF; also RF=F3=FR. [step 1.1, algebra]

3.1

The inverse RF=F3 is a composition of weakly continuous maps and also of strongly continuous maps. Therefore F is a topological automorphism for both topologies. Countable Choice is used only through [F1]–[F2].

F1step 2.1
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Fourier transform agrees with l one and plancherel transforms

Statement

Assume Countable Choice and use the negative-sign 2π normalization. If fL1(Rn;C), then

Fuf=uf^,

where f^ is the integral Fourier transform. If fL2(Rn;C), then

Fuf=uF2f,

where F2 is the Plancherel extension. These equalities are in S(Rn) and therefore depend only on the corresponding almost-everywhere classes.

Facts & Assumptions

Given: Countable Choice and the fixed 2π Fourier convention.

[F1]

Every Lp class, including p=1,2,, defines a regular tempered distribution (Polynomial growth functions define tempered distributions).

[F2]

The transform on S is defined by bilinear transposition (Fourier transform of a tempered distribution).

[F3]

Absolute Fubini applies on the sigma-finite Euclidean product (Fubini's theorem for L^1 functions on a sigma-finite product).

[F4]

Schwartz space is dense in complex L2, and the Plancherel transform is its unitary extension (Schwartz space is dense in L2, Plancherel theorem).

[F5]

The integral and Plancherel transforms agree on L1L2 (Agreement of the integral and L2 transforms).

[F6]

Hölder applied to moduli controls all L2 test pairings (Holder's inequality for integrals, including the endpoint cases).

Proof

technique · Fubini followed by $L^2$ approximation
1.1

Let fL1 and φS. Schwartz decay makes φL1, so  ⁣f(x)φ(ξ)dxdξ<. Absolute Fubini is therefore applicable.

F2F3

Fuf,φ=f(x) ⁣(φ(ξ)e2πixξdξ)dx=f^(ξ)φ(ξ)dξ.

Since f^ is bounded, [F1] makes the last functional tempered. This proves the L1 assertion. [F1, F2, F3]

1.2

Let fL2 and choose fjS with fjf in L2. For a fixed φS, also FφL2, and Hölder gives the first convergence below.

F4F6

(fjf)Fφ0.

Plancherel gives F2fjF2f in L2, so a second Hölder estimate gives (F2fjF2f)φ0. [F4, F6]

2.1

Each fj belongs to L1L2, and the two agreement results give the displayed identity.

F5step 1.1

fjFφ=(F2fj)φ.

Passing to the two limits from step 1.2 yields Fuf,φ=uF2f,φ. Since this holds for every Schwartz test, the L2 assertion follows. [F1, F2, F5, step 1.2] ∎

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Convolution of a tempered distribution with a schwartz function

Definition

For uS(Rn) and φS(Rn), define the scalar function

(uφ)(x)=uy,φ(xy),xRn.

For each fixed x, the function yφ(xy) is the reflection and translation of a Schwartz function, hence remains in S by Basic operations are continuous on Schwartz space. The pairing with u is therefore defined. This definition initially produces only a scalar function; its smoothness, derivative identities, polynomial growth, and regular-tempered interpretation are proved later. If u=0 or φ=0, the convolution is the zero function. No convolution of two arbitrary tempered distributions is defined, and no choice axiom is used.

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Dirac comb

Definition

For n1, the unit-lattice Dirac comb is

IIIZn=kZnδk,IIIZn,φ=kZnφ(k).

This defines a tempered distribution, not merely a formal series. Indeed, choose an integer L>n+1. The shell {kZn:mk<m+1} has at most (2m+3)n points, and the Schwartz-seminorm definition gives a constant An,L such that

φ(k)An,L(1+k)LmaxαLpα,0(φ).

The resulting shell series is bounded by a constant times m1mnL, which converges by The p-series for a real exponent p converges exactly when p is greater than one. Thus the lattice sum is absolutely convergent and obeys one finite seminorm estimate, so Finite seminorm bound characterizes tempered distributions applies. On a compactly supported test only finitely many terms remain, and the restriction agrees with the locally finite sum of the Dirac distributions Dirac delta and its derivatives. The zero test gives zero. The shell decomposition is canonical, so no choice axiom is used.

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Dirac comb is fourier invariant

Statement

Assume Countable Choice. Under f^(ξ)=f(x)e2πixξdx, the unit-lattice Dirac comb satisfies

FIIIZn=IIIZn

in S(Rn).

Facts & Assumptions

Given: Countable Choice and n1.

[F1]

The comb pairs with a Schwartz test by its absolutely convergent lattice sum (Dirac comb).

[F2]

Fourier transformation on S is defined by transposition (Fourier transform of a tempered distribution).

[F3]

Poisson summation at x=0 says kZnφ^(k)=kZnφ(k), with both sums absolutely convergent (Poisson summation for Schwartz functions).

Proof

technique · test against Poisson summation
1.1

Let φS(Rn). Apply the defining transpose and the comb pairing.

F1F2

FIIIZn,φ=IIIZn,φ^=kZnφ^(k).

All terms and sums are defined by [F1]–[F2]. [F1, F2]

2.1

Poisson summation changes the last sum to kφ(k)=IIIZn,φ. Equality on every Schwartz test proves the stated identity. Countable Choice is used only through the published Fourier and Poisson suppliers.

F1F3step 1.1
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Test function inclusion in schwartz space is continuous

Statement

For n1, the inclusion ι:D(Rn)S(Rn) is continuous and has dense image. This holds in ZF.

Facts & Assumptions

Given: The LF test space D(Rn) and Schwartz space S(Rn).

[F1]

A linear map from D is continuous exactly when every restriction to DK is continuous (Test function lf topology universal property).

[F2]

Schwartz space is defined by the seminorms pαβ and their locally convex topology (Schwartz space and its seminorms, Schwartz topology and convergence).

[F3]

Smooth compactly supported cutoffs approximate every Schwartz function in all Schwartz seminorms (Smooth compact supports are dense in Schwartz space).

Proof

technique · fixed-support estimates and cutoff density
1.1

Fix compact KRn and φDK. Each Schwartz seminorm has the following fixed-support bound.

F2

pαβ(φ)(supxKxα)supxKβφ(x).

The multiplier on the right is finite, including the zero value when K=. Hence every Schwartz seminorm pulls back continuously to DK. [F2]

2.1

Step 1.1 makes every restricted inclusion DKS continuous. The LF universal property therefore makes ι continuous on all of D.

F1step 1.1
3.1

The approximants in [F3] lie in D and converge in the Schwartz topology to the prescribed Schwartz function. Thus the image of ι is dense. This density argument is separate from continuity, and neither uses a choice axiom.

F3
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Compactly supported distributions are tempered

Statement

Every compactly supported distribution vD(Rn) has a unique extension v~S(Rn). Restricting v~ to D recovers v. No choice axiom is required.

Facts & Assumptions

Given: A distribution v with compact support in Rn.

[F1]

Such a distribution extends uniquely to a continuous linear functional on C, with v~(f)=v(χf) for any fixed cutoff equal to one near the support (Compactly supported distributions extend to smooth functions).

[F2]

A finite Schwartz-seminorm estimate proves temperateness (Finite seminorm bound characterizes tempered distributions).

[F3]

The inclusion DS is continuous with dense image (Test function inclusion in schwartz space is continuous).

Proof

technique · cutoff extension and density
1.1

Restrict the C extension from [F1] to S. Its continuity gives a compact K, an integer m, and C0 satisfying the following estimate.

F1

v~(φ)CmaxβmsupxKβφ(x)Cmaxβmp0,β(φ).

Thus the restriction is tempered by [F2]. [F1, F2]

1.2

For ψD, the extension property in [F1] gives v~(ψ)=v(ψ); this includes the zero distribution and empty support. Hence v~ really extends v.

F1
2.1

If wS is another extension, then wv~ vanishes on D. This difference is continuous on S, and D is dense there, so it vanishes on all of S. Therefore the extension is unique.

F3step 1.2
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Tempered distributions embed continuously in distributions

Statement

Restriction to compactly supported tests defines an injective complex-linear map

ρ:S(Rn)D(Rn).

It is continuous from weak to weak topology and from strong to strong topology. No assertion is made that the strong topology on S is the subspace topology inherited from D.

Facts & Assumptions

Given: The continuous dense inclusion j:DS (Test function inclusion in schwartz space is continuous).

[F1]

Weak and strong topologies on S are generated by point tests and bounded Schwartz-test sets (Weak and strong topologies on tempered distributions).

[F2]

The corresponding topologies on D use point tests and bounded LF-test sets (Weak and strong topologies on distributions).

Proof

technique · transpose the dense continuous inclusion
1.1

Define ρ(u)(ψ)=u(jψ). Since j and u are continuous complex-linear maps, ρ(u) is a distribution, and ρ is complex-linear. If ρ(u)=0, then u vanishes on the dense image of j; continuity makes u=0 on S. Thus ρ is injective.

given
1.2

For each ψD, pψ(ρu)=pjψ(u). Hence every weak seminorm on the target pulls back to a weak seminorm on the source, proving weak continuity.

F1F2
2.1

If BD is bounded, continuity and linearity of j imply that j(B) is bounded in S.

F1F2step 1.1

pB(ρu)=supψBu(jψ)=pj(B)(u),

which proves strong continuity. Density was essential only for injectivity; continuity alone would not prove that conclusion. [F1, F2, given] ∎

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Smooth polynomially bounded multipliers on schwartz space

Statement

Let aC(Rn;C) and suppose that for every multi-index γ there are Cγ0 and an integer mγ0 such that

γa(x)Cγ(1+x)mγ.

Then Ma:φaφ is a continuous complex-linear endomorphism of S(Rn). Its transpose

au,φ=u,aφ

is a tempered distribution and depends continuously on u for both the weak and strong dual topologies. Polynomials and Schwartz functions satisfy the hypothesis; an arbitrary smooth function need not.

Facts & Assumptions

Given: A smooth function a with the derivative-by-derivative polynomial bounds in the statement.

[F1]

Schwartz seminorms and topology are those of Schwartz space and its seminorms and Schwartz topology and convergence, with multi-indices interpreted by Ck maps and multi-index derivative notation in Euclidean space.

[F2]

Tempered distributions are continuous functionals on S, and their weak and strong topologies test singletons and bounded subsets (Tempered distribution, Weak and strong topologies on tempered distributions).

Proof

technique · Leibniz seminorm estimates and transposition
1.1

Fix α,β and apply the multi-index Leibniz formula.

F1algebra

xαβ(aφ)=γβ(βγ)xα(γa)βγφ.

For each of the finitely many γ, expansion of (1+x1++xn)mγ bounds that summand by a finite linear combination of seminorms pα+δ,βγ(φ) with δmγ. Hence each output seminorm is bounded by finitely many input seminorms. [F1, algebra]

2.1

Step 1.1 proves simultaneously that aφS and that Ma is continuous. A polynomial has only finitely many nonzero derivatives and each grows polynomially. If aS, each derivative is bounded, so the hypothesis holds with exponent zero.

F1step 1.1
3.1

For uS, the composition uMa is continuous and linear, hence tempered. For a single test, pφ(au)=paφ(u), proving weak continuity of the transpose.

F2step 2.1
4.1

If B is bounded in S, the finite estimates of step 1.1 show that Ma(B) is bounded. Thus pB(au)=pMa(B)(u), proving strong continuity. The derivative hypothesis is essential: for example a(x)=ex2 is smooth but does not map every Schwartz function to a Schwartz function. No choice axiom is used.

F2step 1.1
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Differentiation and polynomial multiplication preserve tempered distributions

Statement

For uS(Rn), a multi-index α, and a complex polynomial P, define

αu,φ=(1)αu,αφ,Pu,φ=u,Pφ.

Both results lie in S. For fixed α or P, these operations are continuous in both the weak and strong dual topologies, and their restrictions to D agree with the corresponding operations on D.

Facts & Assumptions

Given: A tempered distribution u, a multi-index α, and a complex polynomial P (Tempered distribution).

[F1]

Differentiation and polynomial multiplication are continuous linear endomorphisms of Schwartz space (Basic operations are continuous on Schwartz space, Smooth polynomially bounded multipliers on schwartz space).

[F2]

Weak and strong dual topologies use point tests and bounded test sets (Weak and strong topologies on tempered distributions).

[F3]

On D, distributional differentiation has the same sign and smooth multiplication has the same transpose formula (Distributional derivative, Multiplication of a distribution by a smooth function).

Proof

technique · transposition and bounded-set transport
1.1

Each displayed functional is the composition of u with a continuous Schwartz endomorphism, followed in the derivative case by a scalar sign. It is therefore continuous and complex-linear on S, hence belongs to S.

F1given
2.1

For a single test φ, the absolute value after either operation is a source weak seminorm evaluated at the transformed test. Thus each operation is weakly continuous.

F2step 1.1
2.2

A continuous linear Schwartz endomorphism sends bounded sets to bounded sets. For a bounded B, the target strong seminorm is therefore the source strong seminorm on αB or PB (the derivative sign disappears under absolute values). This proves strong continuity.

F1F2step 1.1
3.1

If ψD, then αψ and Pψ are again compactly supported tests. Evaluating the two displayed definitions on ψ gives exactly the formulas in [F3]. Hence restriction to D commutes with both operations. The cases α=0, constant P, P=0, and u=0 follow from the same formulas. No choice axiom is used.

F3
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Fourier differentiation and multiplication identities on tempered distributions

Statement

Assume Countable Choice. For uS(Rn) and every multi-index α,

F(αu)=(2πiξ)αFu,F(xαu)=(12πi)αξαFu.

Every operation and equality is in S(Rn).

Facts & Assumptions

Given: Countable Choice, uS(Rn), and a multi-index α.

[F1]

Derivatives and polynomial products on S use the bilinear transpose conventions (Differentiation and polynomial multiplication preserve tempered distributions).

[F2]

The distributional Fourier transform is the bilinear transpose of the Schwartz transform (Fourier transform of a tempered distribution).

[F3]

On Schwartz tests, F(jφ)=2πiξjFφ and jFφ=F(2πixjφ) (Fourier transform acts continuously on Schwartz space), and all test operations involved are continuous (Basic operations are continuous on Schwartz space).

Proof

technique · first-order test calculation and iteration
1.1

Fix a coordinate j and a Schwartz test φ; transposition gives the following calculation.

F1F2F3

F(ju),φ=u,j(Fφ)=2πiu,F(ξjφ)=2πiξjFu,φ.

The first minus sign is the distributional derivative sign; the second identity is the second formula in [F3]. [F1, F2, F3]

1.2

The first formula in [F3] gives xjFφ=(2πi)1F(jφ), so transposition yields the second calculation.

F1F2F3

F(xju),φ=12πiFu,jφ=12πijFu,φ.

[F1, F2, F3]

2.1

Coordinate derivatives and coordinate multipliers commute among themselves in the relevant families. Iterating steps 1.1 and 1.2 α times therefore gives the two multi-index identities. For α=0 both reduce to Fu=Fu. Countable Choice is used only through the published Schwartz Fourier identity.

step 1.1step 1.2
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Fourier transform of delta constants plane waves and polynomials

Statement

Assume Countable Choice and the negative-sign 2π normalization. For a,bRn and every multi-index α,

Fδa(ξ)=e2πiaξ,F1=δ0,F(e2πibx)=δb,

and

F(αδ0)=(2πiξ)α,F(xα)=(12πi)ααδ0.

Functions in these formulas denote their regular tempered distributions. By linearity, the last identity determines the transform of every polynomial.

Facts & Assumptions

Given: Countable Choice, a,bRn, and a multi-index α.

[F1]

Dirac distributions and their derivatives have the bilinear evaluation convention (Dirac delta and its derivatives) and compactly supported distributions are tempered (Compactly supported distributions are tempered).

[F2]

Constants, plane waves, and polynomials are regular tempered distributions (Polynomial growth functions define tempered distributions).

[F3]
[F4]

Fourier differentiation and multiplication have the precise 2π constants and signs (Fourier differentiation and multiplication identities on tempered distributions).

[F5]

The published translation/modulation laws use the same negative-sign normalization (Translation, modulation, linear dilation and reflection laws).

Proof

technique · evaluate delta and use reflection/calculus identities
1.1

Evaluate the transform of δa on an arbitrary φS.

F1F2

Fδa,φ=φ^(a)=e2πiaξφ(ξ)dξ.

Thus Fδa is the displayed plane wave; at a=0 this gives Fδ0=1. The sign agrees with [F5]. [F1, F2, F5]

2.1

Apply F to Fδ0=1. Since Rδ0=δ0, [F3] gives F1=δ0. Similarly step 1.1 with a=b gives Fδb=e2πibx, so applying F once more gives F(e2πibx)=Rδb=δb.

F3step 1.1
3.1

Apply the derivative identity in [F4] to δ0 and use Fδ0=1 to obtain F(αδ0)=(2πiξ)α. Apply the multiplication identity to the constant distribution and use F1=δ0 to obtain the formula for xα.

F4step 2.1
4.1

Every polynomial is a finite complex linear combination of monomials, so linearity completes the polynomial assertion. The zero multi-index recovers Fδ0=1 and F1=δ0. Countable Choice is used only through the published Fourier suppliers.

step 3.1algebra
TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-14Open item page →

Constant coefficient differential operators become polynomial multipliers

Statement

Assume Countable Choice. Let P(z)=αAaαzα be a complex polynomial in n variables, with A finite, and put P()=αAaαα. Then, for every uS(Rn),

F(P()u)=P(2πiξ)Fu

in S(Rn).

Facts & Assumptions

Given: Countable Choice, a finite polynomial P, and uS(Rn).

[F1]

For every multi-index α, F(αu)=(2πiξ)αFu (Fourier differentiation and multiplication identities on tempered distributions).

Proof

technique · finite linearity
1.1

Fourier transformation, distributional differentiation, and finite addition are complex-linear, giving the following finite expansion.

F1algebra

F(P()u)=αAaαF(αu).

[F1, algebra]

2.1

Substitute [F1] into the finite sum from step 1.1 and factor the common distribution Fu to obtain αaα(2πiξ)αFu=P(2πiξ)Fu. This includes constant and zero polynomials. The statement is only an algebraic equivalence: it asserts no division by P(2πiξ) and no existence or regularity theorem for a PDE. Countable Choice is used only through [F1].

F1step 1.1
LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-14Open item page →

Schwartz parameter pairing and integral interchange

Statement

For φS(Rn), the map

xTxφ,(Txφ)(y)=φ(xy),

is C as a map from Rn to Schwartz space, with xγTxφ=Tx(γφ). This clause holds in ZF.

Assume Countable Choice for the following integral clause. Let r1 and let H:RrS(Rn) be continuous in every Schwartz seminorm. Suppose each yβH(t,y) is jointly measurable and, for every α,β, there is gαβL1(Rr) such that

pαβ(H(t))gαβ(t)

for almost every t. Then G(y)=RrH(t,y)dt belongs to S, derivatives pass under the integral, and every uS satisfies

u,H(t)dt=u,H(t)dt.

All integrals in this clause are Lebesgue integrals.

Facts & Assumptions

Given: A Schwartz function φ; for the second clause also Countable Choice, a family H with the stated seminorm majorants, and uS.

[F1]

Fixed translations, reflection, and derivatives preserve Schwartz space continuously (Basic operations are continuous on Schwartz space).

[F2]

The functional u obeys one finite Schwartz-seminorm estimate (Finite seminorm bound characterizes tempered distributions).

[F3]

Dominated convergence and the complex integral triangle inequality hold for the stated Lebesgue integrals (Dominated convergence, The modulus of an integral is bounded by the integral of the modulus).

Proof

technique · weighted Taylor remainders and explicit finite sums
1.1

Fix a compact set of parameters K. The inequality 1+y(1+supxKx)(1+xy) transfers every polynomial weight in y to one in xy, uniformly for xK. Apply the one-variable integral Taylor remainder along each coordinate.

F1algebra

pαβ ⁣(Tx+hejφTxφhTx(jφ))0.

The same estimate applied to every derivative gives continuity of all iterated derivatives. [F1, algebra]

Iterating step 1.1 proves that xTxφ is C in the Schwartz topology and gives the displayed derivative formula. When φ=0 every derivative is zero. No integration on parameter space and no choice principle occurred. [step 1.1]

1.2

For the integral clause, differentiate under the integral and apply the integral triangle inequality pointwise in y.

F3

yβG(y)=yβH(t,y)dt,pαβ(G)gαβ(t)dt.

The derivative statement follows successively from difference quotients and dominated convergence; the seminorm estimate follows from the integral triangle inequality before taking the supremum in y. Thus GS. [F3]

1.3

Let QR=[R,R]r. Subdivide it into the canonical equal mesh and form lower-corner finite sums SR,m for H. Uniform continuity in each seminorm and [F3] make these sums converge to GR(y)=QRH(t,y)dt in that seminorm. Continuity of u may therefore be passed through this explicit limit.

F2F3

u(GR)=limmu(SR,m)=limmQQu(H(tQ))=QRu(H(t))dt.

The last equality is the same scalar step-function approximation. [F2, F3]

2.1

The finite estimate [F2] involves only finitely many seminorms. Their L1 majorants show both GRG in those seminorms and QRu(H(t))dtRru(H(t))dt as R. Passing to the limit in step 1.3 proves the interchange formula. Countable Choice is used exactly through [F3]'s Lebesgue interface; the finite-sum and continuity argument adds no stronger choice.

F2F3step 1.3
TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-14Open item page →

Tempered convolution is smooth with polynomial growth

Statement

For uS(Rn) and φS(Rn), the function uφ is smooth and every derivative has polynomial growth. For each multi-index γ,

γ(uφ)=(γu)φ=u(γφ).

Consequently uφ, interpreted as a regular distribution, belongs to S(Rn).

Facts & Assumptions

Given: uS and φS, with convolution as in Convolution of a tempered distribution with a schwartz function.

[F1]

There are C,N,M giving a finite rectangular seminorm estimate for u (Finite seminorm bound characterizes tempered distributions).

[F2]

Translation, reflection, and differentiation are continuous on Schwartz space (Basic operations are continuous on Schwartz space).

[F3]

Smooth pointwise-polynomial-growth functions define regular tempered distributions (Polynomial growth functions define tempered distributions).

Proof

technique · differentiate translated tests in Schwartz seminorms
1.1

For every x and coordinate j, Taylor's integral remainder and 1+y(1+x)(1+xy) show that the xj-difference quotients of yφ(xy) converge in every Schwartz seminorm to yjφ(xy). Continuity of u permits differentiation of the scalar pairing, and iteration gives every multi-index derivative.

F1F2given

γ(uφ)(x)=uy,γφ(xy).

[F1, F2, given]

1.2

Apply the definition of distributional differentiation to the translated test.

F2

γuy,φ(xy)=(1)γuy,yγφ(xy)=uy,γφ(xy).

Together with step 1.1 this proves both derivative identities, including γ=0. [F2, step 1.1]

2.1

Apply [F1] to the translated test in step 1.1. Write z=xy and expand yα=(xz)α.

F1step 1.1algebra

supyyαyβγφ(xy)Cφ,N,M,γ(1+x)N.

Hence γ(uφ)(x)Cγ(1+x)N. [F1, algebra]

3.1

Step 1.1 gives smoothness, and step 2.1 gives pointwise polynomial growth for every derivative. In particular the function is locally integrable and [F3] makes its regular distribution tempered. If u=0 or φ=0, all formulas reduce to zero. No parameter integral or choice axiom is used.

F3step 1.1step 2.1
TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-14Open item page →

Fourier transform of a compactly supported distribution is a smooth polynomially bounded multiplier

Statement

Assume Countable Choice. Let vD(Rn) have compact support, let v~S be its canonical extension, and let χD equal one on a neighborhood of suppv. Then Fv~ is the regular tempered distribution represented by

V(ξ)=vx,χ(x)e2πixξ.

The function V is independent of χ, is smooth, and for every multi-index α there are Cα,mα with αV(ξ)Cα(1+ξ)mα. Consequently multiplication by V is continuous on S and, by transpose, on S in both dual topologies.

Facts & Assumptions

Given: Countable Choice, a compactly supported distribution v, and a cutoff χ as in the statement.

[F1]

The extension v~ is tempered and its pairing with a smooth function is computed using any cutoff equal to one near the support (Compactly supported distributions are tempered, Compactly supported distributions extend to smooth functions).

[F2]

Compactly supported distribution pairings with smooth parameter families differentiate in the parameter (Distribution pairing with smooth parameter families).

[F3]

The Fourier transform is defined by bilinear transposition (Fourier transform of a tempered distribution), and the local Schwartz integral lemma permits a seminorm-dominated integral to cross a tempered pairing (Schwartz parameter pairing and integral interchange).

[F4]

A smooth function whose derivatives grow polynomially is a continuous Schwartz multiplier, as is its transpose (Smooth polynomially bounded multipliers on schwartz space).

Proof

technique · compact finite-order estimate and pairing interchange
1.1

If χ1 and χ2 are both one near suppv, then (χ1χ2)e2πixξ vanishes near that support, so [F1] makes its pairing with v zero. Thus V is cutoff-independent.

F1
1.2

Apply smooth parameter differentiation from [F2].

F2

ξαV(ξ)=vx,χ(x)(2πix)αe2πixξ.

On one fixed compact containing suppχ, the finite-order estimate for v differentiates the displayed test in x only finitely many times. Each resulting term is bounded by a constant times (1+ξ)m. Hence V is smooth and every derivative has the claimed polynomial bound. [F1, F2, algebra]

1.3

Let φS and set H(ξ,x)=χ(x)e2πixξφ(ξ). As an x-Schwartz family, H(ξ,) is continuous in ξ, and every x-Schwartz seminorm has an integrable majorant C(1+ξ)qφ(ξ). Thus [F3] applies.

F3

Fv~,φ=v~,Fφ=vx,χ(x)e2πixξφ(ξ)dξ=V(ξ)φ(ξ)dξ.

[F1, F3]

2.1

Equality in step 1.3 identifies Fv~ with the regular distribution uV. The derivative bounds from step 1.2 satisfy [F4], which proves both multiplier assertions. For v=0, V=0; empty support causes no exception. Countable Choice enters only through the published Fourier and Lebesgue-interchange clauses.

F4step 1.2step 1.3
LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-14Open item page →

Compact distribution convolution preserves schwartz and tempered spaces

Statement

Let vD(Rn) have compact support. Then

Cv:SS,(Cvφ)(x)=(vφ)(x)=vy,φ(xy),

is continuous and complex-linear. If uS, define uvS by

uv,ψ=ux,vy,ψ(x+y).

After restricting u and uv to D, this agrees with the ordinary distribution convolution in which one factor has compact support. All assertions hold in ZF.

Facts & Assumptions

Given: A compactly supported distribution v, a Schwartz function φ, and a tempered distribution u (Tempered distribution).

[F1]

Compactly supported distributions act continuously on all smooth functions and obey a fixed compact finite-order estimate (Compactly supported distributions extend to smooth functions).

[F2]

The Schwartz seminorms/topology are those of Schwartz space and its seminorms and Schwartz topology and convergence.

[F3]

The smooth-parameter clause for compact distribution pairings holds in ZF (Distribution pairing with smooth parameter families).

[F4]

Distribution convolution with one compactly supported factor is well-defined by the addition-map pairing and is commutative (Convolution of distributions when one has compact support, Convolution of distributions is well defined under the support hypothesis).

[F5]

Restriction embeds S into D (Tempered distributions embed continuously in distributions).

Proof

technique · uniform compact-support estimates and transposition
1.1

Choose a compact neighborhood K of suppv and an order m for the estimate in [F1]. Differentiate by [F3] and expand xα=((xy)+y)α.

F1F3algebra

pαβ(Cvφ)Cv,K,α,βmaxγm, δαpδ,β+γ(φ).

Only finitely many terms occur because y stays in K. [F1, F2, F3, algebra]

2.1

The estimates in step 1.1 show that Cvφ is Schwartz and that Cv is continuous. Replacing y by y proves the same statement for Tvψ(x)=vy,ψ(x+y); equivalently Tv=Cvˇ for the reflected compact distribution vˇ.

F2step 1.1
3.1

The displayed candidate for uv is uTv. By step 2.1 this is a continuous complex-linear functional on S, hence tempered.

givenstep 2.1
4.1

For ψD, the inner function Tvψ is precisely the iterated-pairing test used by the addition-map definition in [F4].

F4step 3.1

uv,ψ=ρ(u)v,(x,y)ψ(x+y)

with the cutoff interpretation prescribed there. This proves agreement after the embedding [F5]. The cases u=0, v=0, or empty support give zero. Only the ZF smooth-parameter clause of [F3] was used; no integral-interchange clause or choice axiom entered. [F3, F4, F5, step 3.1] ∎

TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-14Open item page →

Fourier transform converts allowed tempered convolutions to products

Statement

Assume Countable Choice. Let uS(Rn) and φS(Rn). Then

F(uφ)=(Fu)(Fφ),F(φu)=(Fφ)(Fu).

In the second formula the convolution means (Fu)(Fφ) under the distribution-first convention. If vD(Rn) has compact support, then

F(uv)=(Fu)(Fv).

Here Fv is the smooth polynomially bounded function representing the transform of the canonical tempered extension of v. No product of two arbitrary distributions and no convolution of two arbitrary tempered distributions occurs.

Facts & Assumptions

Given: Countable Choice, uS, φS, and, for the last formula, compactly supported v.

[F1]

The convolution uφ is a regular tempered distribution (Tempered convolution is smooth with polynomial growth).

[F3]

Seminorm-dominated Schwartz integrals commute with tempered pairings (Schwartz parameter pairing and integral interchange).

[F4]

Compact-distribution convolution preserves S and agrees with the support-conditioned distribution convolution (Compact distribution convolution preserves schwartz and tempered spaces).

[F5]

Fourier transformation or inversion is available on S, with F2=R (Fourier transform is a topological automorphism of tempered distributions).

[F6]

Products and convolutions of two Schwartz functions satisfy the same 2π-normalized transform laws (Schwartz convolution and product laws).

Proof

technique · test-pairing interchange
1.1

Let ψS. The family x[yφ(xy)ψ^(x)] is dominated in every y-Schwartz seminorm by an integrable polynomial weight times ψ^(x). Therefore [F3] applies.

F3

F(uφ),ψ=uy,φ(xy)ψ^(x)dx.

[F1, F3]

1.2

Absolute scalar interchange, or equivalently [F6] on Schwartz functions, identifies the inner integral.

F6

F(φ^ψ)(y).

Indeed, inserting ψ^(x)=ψ(ξ)e2πixξdξ and translating xy produces φ^(ξ)e2πiyξ. Hence step 1.1 equals Fu,φ^ψ, which is (Fu)(Fφ),ψ. [F2, F3, F6, step 1.1]

1.3

Put V=Fv. Evaluate the compact-factor convolution on an arbitrary ψS.

F4

F(uv),ψ=ux,vy,ψ^(x+y).

The compact support of v and [F3] permit its pairing to cross the rapidly convergent Fourier integral, giving

vy,ψ^(x+y)=V(ξ)ψ(ξ)e2πixξdξ=F(Vψ)(x).

Thus the outer pairing is Fu,Vψ=(Fu)(Fv),ψ. [F2, F3, F4]

2.1

Apply the first identity to Fu and the Schwartz function Fφ, then use Fourier squaring.

F5step 1.2

F((Fu)(Fφ))=(F2u)(F2φ)=(Ru)(Rφ)=R(φu).

Since F1R=F, inversion gives (Fu)(Fφ)=F(φu). Zero factors are included. Countable Choice is used only through the published Fourier/Lebesgue suppliers. [F5, step 1.2] ∎

5 · Examples, counterexamples and false statements

None yet.

Sources