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Tempered Distributions and the Fourier Transform
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Approximation and Compactness in C(K)
- Areas of Elementary Plane Figures
- Binary Operations, Monoids, Groups and Subgroups
- Bounded Linear Operators and Quotient Spaces
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Lp Spaces and Test-Function Conventions
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Countability Axioms and Cardinal Functions
- Darboux, L'Hôpital, and Taylor's Theorem
- Density Separability and Convolution in Lᵖ
- Determinants of Matrices over a Commutative Ring
- Distributions Test Functions and Differentiation
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Finite Probability and the Probabilistic Method
- Foundations of the Real Numbers for Analysis
- Fourier Transform Convolution and Approximate Identities
- Fubini and Change of Variables
- Function Space Topologies and the Exponential Law
- Fundamental Trigonometric Identities
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Improper and Parameter-Dependent Multiple Integrals
- Improper Integrals
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Lebesgue Measure on Euclidean Space
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Metric Spaces
- Mixed Partials, Taylor Formulae, and Extrema
- Modes of Convergence Egorov and Lusin
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Normed and Banach Spaces
- Order, Zorn's Lemma, and the Axiom of Choice
- Outer Measure and the Caratheodory Extension Theorem
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Product Measures and the Fubini Tonelli Theorems
- Properties of the Integral and the Working FTC
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Schwartz Space and the Plancherel Theorem
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Simple Field Extensions and the Construction of the Complex Numbers
- Sine, Cosine, and the Definition of Pi
- Stone–Weierstrass in General
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Complex Exponential and Euler's Formula
- The Derivative and the Mean Value Theorems
- The Exponential Function
- The Inverse and Implicit Function Theorems
- The Lebesgue and Riemann Integrals Compared
- The Lebesgue Integral and the Convergence Theorems
- The Logarithm and General Powers
- The Lᵖ Spaces Holder Minkowski and Riesz Fischer
- The Maximal Function and Lebesgue Differentiation
- The Riemann Integral in Rᵐ and Jordan Content
- The Riemann Integral: Definition and Integrability
- The Topology of Euclidean Space
- The Total Derivative in ℝᵐ → ℝⁿ
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Vector Spaces, Linear Subspaces, Span and Direct Sums
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, -normalized Fourier convention, transposition extends the Schwartz transform to a topological automorphism of . The resulting calculus includes derivatives, polynomial and slowly increasing multipliers, elementary transforms, and the unit-lattice Dirac comb. The final results prove smoothness of , 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
Tempered distribution
Definition
Fix an integer . A tempered distribution on is a continuous complex-linear functional
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 .
We write . This pairing is bilinear: the test variable is not conjugated. Thus for . 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.
Finite seminorm bound characterizes tempered distributions
Statement
Let be complex-linear. Then is tempered if and only if there are and integers such that
for every .
Facts & Assumptions
Given: A complex-linear functional on .
A basic zero-neighborhood in Schwartz space imposes finitely many strict bounds on its defining seminorms (Tempered distribution).
Proof
Suppose is continuous. There is a basic zero-neighborhood on which . If , then and linearity forces , so take . Otherwise put .
If , then , whence . If , every scalar multiple of lies in ; boundedness of those scalar multiples of forces . Choose and dominating the finitely many and . Then is at most times the rectangular maximum in the statement, which proves the required estimate.
Conversely, assume the displayed estimate. For every , the set on which its finite maximum is less than is a zero-neighborhood and is carried by into the disk of radius . Thus is continuous and hence tempered.
Weak and strong topologies on tempered distributions
Definition
A set is bounded when for every pair of multi-indices. The weak topology on tempered distributions is generated by
The strong topology is generated by
as ranges over bounded subsets of . The empty-set supremum is zero. This supremum is finite: continuity of gives a basic zero-neighborhood on which , and the finitely many seminorm bounds defining imply for some finite ; hence . The triangle inequality and homogeneity follow pointwise.
Thus a net converges weakly to exactly when for every , and it converges strongly exactly when for every bounded . 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 is asserted, and no choice axiom is used.
Polynomial growth functions define tempered distributions
Statement
Let be locally integrable. If, for some integer ,
then the regular functional is a tempered distribution. Consequently this holds if has pointwise polynomial growth outside a compact set, and every class in complex , , 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 on .
A regular functional is defined by bilinear integration (Regular distribution from a locally integrable function, A locally integrable function on ).
One finite rectangular Schwartz-seminorm estimate characterizes tempered functionals (Finite seminorm bound characterizes tempered distributions).
Hölder's inequality, including the and endpoints, applies to the real nonnegative functions and a weight (Holder's inequality for integrals, including the endpoint cases).
Complex classes, their moduli, and their locally integrable representatives use the conventions of Complex Lp classes and Euclidean test-function conventions.
A real -series converges when its exponent exceeds one (The p-series for a real exponent p converges exactly when p is greater than one).
Proof
For each integer , expansion of gives a finite constant for which the following estimate holds.
Thus the weighted hypothesis implies . [F1, algebra]
The estimate in step 1.1 makes the integral absolutely convergent for every Schwartz test and proves that is tempered. It also shows directly that changing on a null set changes no pairing.
The integer shells have measure at most . Hence whenever , by comparison with . If off a compact set, choose an integer . Local integrability handles the compact part, and the shell estimate handles its complement, so step 2.1 applies.
If , take . If and is conjugate to , choose with ; Hölder gives . If , choose and use any finite essential bound for . The same estimates on bounded balls give local integrability of the chosen representatives.
For , as a boundary calculation, define for and assign any finite value, say , when ; set , and for use the usual value . The value at this measure-zero point has no effect on local integrability or the induced distribution. The function is locally integrable at the origin exactly when : for , the dyadic annuli give a series comparable to ; for there is no singularity, while the reverse bound on a fixed cone gives divergence when . At infinity it has polynomial growth. Therefore is among the tempered regular examples precisely for the locally meaningful range .
Fourier transform of a tempered distribution
Definition
Assume Countable Choice, exactly as required by the published Schwartz Fourier theorem. For put
For define its Fourier transform by
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 . 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.
Fourier transform on tempered distributions is well defined and continuous
Statement
Assume Countable Choice. The Fourier transform is well-defined and complex-linear. It is continuous for both the weak topology and the strong topology .
Facts & Assumptions
Given: Countable Choice and a tempered distribution .
The distributional transform is the bilinear transpose of the Schwartz transform (Fourier transform of a tempered distribution).
The Schwartz transform is a continuous linear automorphism (Fourier transform is a topological automorphism of Schwartz space).
Weak dual seminorms use single tests and strong dual seminorms use bounded test sets (Weak and strong topologies on tempered distributions).
Proof
By [F2], is a Schwartz test and depends continuously and linearly on . Thus is a continuous complex-linear functional. This proves well-definedness, and linearity in follows directly from the pairing.
For a single test , . Every target weak seminorm therefore pulls back to a source weak seminorm, so is weakly continuous.
If is bounded, continuity and linearity of the Schwartz transform imply that is bounded: each output seminorm is bounded by finitely many input seminorms.
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] ∎
Fourier transform is a topological automorphism of tempered distributions
Statement
Assume Countable Choice. Fourier transformation is a topological automorphism of for both the weak and strong dual topologies. If
then and .
Facts & Assumptions
Given: Countable Choice and .
Fourier transformation on is weakly and strongly continuous (Fourier transform on tempered distributions is well defined and continuous).
On Schwartz space, , , and (Fourier transform is a topological automorphism of Schwartz space).
Proof
Evaluate the second transform on an arbitrary Schwartz test .
Thus . This is a direct test calculation and uses no density assertion about inside its dual. [F2]
Reflection on the dual satisfies . Since step 1.1 gives as operators on , associativity gives the following two-sided inverse calculation.
Hence ; also . [step 1.1, algebra]
The inverse is a composition of weakly continuous maps and also of strongly continuous maps. Therefore is a topological automorphism for both topologies. Countable Choice is used only through [F1]–[F2].
Fourier transform agrees with l one and plancherel transforms
Statement
Assume Countable Choice and use the negative-sign normalization. If , then
where is the integral Fourier transform. If , then
where is the Plancherel extension. These equalities are in and therefore depend only on the corresponding almost-everywhere classes.
Facts & Assumptions
Given: Countable Choice and the fixed Fourier convention.
Every class, including , defines a regular tempered distribution (Polynomial growth functions define tempered distributions).
The transform on is defined by bilinear transposition (Fourier transform of a tempered distribution).
Absolute Fubini applies on the sigma-finite Euclidean product (Fubini's theorem for L^1 functions on a sigma-finite product).
Schwartz space is dense in complex , and the Plancherel transform is its unitary extension (Schwartz space is dense in L2, Plancherel theorem).
The integral and Plancherel transforms agree on (Agreement of the integral and L2 transforms).
Hölder applied to moduli controls all test pairings (Holder's inequality for integrals, including the endpoint cases).
Proof
Let and . Schwartz decay makes , so . Absolute Fubini is therefore applicable.
Since is bounded, [F1] makes the last functional tempered. This proves the assertion. [F1, F2, F3]
Let and choose with in . For a fixed , also , and Hölder gives the first convergence below.
Plancherel gives in , so a second Hölder estimate gives . [F4, F6]
Each belongs to , and the two agreement results give the displayed identity.
Passing to the two limits from step 1.2 yields . Since this holds for every Schwartz test, the assertion follows. [F1, F2, F5, step 1.2] ∎
Convolution of a tempered distribution with a schwartz function
Definition
For and , define the scalar function
For each fixed , the function is the reflection and translation of a Schwartz function, hence remains in by Basic operations are continuous on Schwartz space. The pairing with 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 or , the convolution is the zero function. No convolution of two arbitrary tempered distributions is defined, and no choice axiom is used.
Dirac comb
Definition
For , the unit-lattice Dirac comb is
This defines a tempered distribution, not merely a formal series. Indeed, choose an integer . The shell has at most points, and the Schwartz-seminorm definition gives a constant such that
The resulting shell series is bounded by a constant times , 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.
Dirac comb is fourier invariant
Statement
Assume Countable Choice. Under , the unit-lattice Dirac comb satisfies
in .
Facts & Assumptions
Given: Countable Choice and .
The comb pairs with a Schwartz test by its absolutely convergent lattice sum (Dirac comb).
Fourier transformation on is defined by transposition (Fourier transform of a tempered distribution).
Poisson summation at says , with both sums absolutely convergent (Poisson summation for Schwartz functions).
Proof
Let . Apply the defining transpose and the comb pairing.
All terms and sums are defined by [F1]–[F2]. [F1, F2]
Poisson summation changes the last sum to . Equality on every Schwartz test proves the stated identity. Countable Choice is used only through the published Fourier and Poisson suppliers.
Test function inclusion in schwartz space is continuous
Statement
For , the inclusion is continuous and has dense image. This holds in ZF.
Facts & Assumptions
Given: The LF test space and Schwartz space .
A linear map from is continuous exactly when every restriction to is continuous (Test function lf topology universal property).
Schwartz space is defined by the seminorms and their locally convex topology (Schwartz space and its seminorms, Schwartz topology and convergence).
Smooth compactly supported cutoffs approximate every Schwartz function in all Schwartz seminorms (Smooth compact supports are dense in Schwartz space).
Proof
Fix compact and . Each Schwartz seminorm has the following fixed-support bound.
The multiplier on the right is finite, including the zero value when . Hence every Schwartz seminorm pulls back continuously to . [F2]
Step 1.1 makes every restricted inclusion continuous. The LF universal property therefore makes continuous on all of .
The approximants in [F3] lie in and converge in the Schwartz topology to the prescribed Schwartz function. Thus the image of is dense. This density argument is separate from continuity, and neither uses a choice axiom.
Compactly supported distributions are tempered
Statement
Every compactly supported distribution has a unique extension . Restricting to recovers . No choice axiom is required.
Facts & Assumptions
Given: A distribution with compact support in .
Such a distribution extends uniquely to a continuous linear functional on , with for any fixed cutoff equal to one near the support (Compactly supported distributions extend to smooth functions).
A finite Schwartz-seminorm estimate proves temperateness (Finite seminorm bound characterizes tempered distributions).
The inclusion is continuous with dense image (Test function inclusion in schwartz space is continuous).
Proof
Restrict the extension from [F1] to . Its continuity gives a compact , an integer , and satisfying the following estimate.
Thus the restriction is tempered by [F2]. [F1, F2]
For , the extension property in [F1] gives ; this includes the zero distribution and empty support. Hence really extends .
If is another extension, then vanishes on . This difference is continuous on , and is dense there, so it vanishes on all of . Therefore the extension is unique.
Tempered distributions embed continuously in distributions
Statement
Restriction to compactly supported tests defines an injective complex-linear map
It is continuous from weak to weak topology and from strong to strong topology. No assertion is made that the strong topology on is the subspace topology inherited from .
Facts & Assumptions
Given: The continuous dense inclusion (Test function inclusion in schwartz space is continuous).
Weak and strong topologies on are generated by point tests and bounded Schwartz-test sets (Weak and strong topologies on tempered distributions).
The corresponding topologies on use point tests and bounded LF-test sets (Weak and strong topologies on distributions).
Proof
Define . Since and are continuous complex-linear maps, is a distribution, and is complex-linear. If , then vanishes on the dense image of ; continuity makes on . Thus is injective.
For each , . Hence every weak seminorm on the target pulls back to a weak seminorm on the source, proving weak continuity.
If is bounded, continuity and linearity of imply that is bounded in .
which proves strong continuity. Density was essential only for injectivity; continuity alone would not prove that conclusion. [F1, F2, given] ∎
Smooth polynomially bounded multipliers on schwartz space
Statement
Let and suppose that for every multi-index there are and an integer such that
Then is a continuous complex-linear endomorphism of . Its transpose
is a tempered distribution and depends continuously on 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 with the derivative-by-derivative polynomial bounds in the statement.
Schwartz seminorms and topology are those of Schwartz space and its seminorms and Schwartz topology and convergence, with multi-indices interpreted by maps and multi-index derivative notation in Euclidean space.
Tempered distributions are continuous functionals on , and their weak and strong topologies test singletons and bounded subsets (Tempered distribution, Weak and strong topologies on tempered distributions).
Proof
Fix and apply the multi-index Leibniz formula.
For each of the finitely many , expansion of bounds that summand by a finite linear combination of seminorms with . Hence each output seminorm is bounded by finitely many input seminorms. [F1, algebra]
Step 1.1 proves simultaneously that and that is continuous. A polynomial has only finitely many nonzero derivatives and each grows polynomially. If , each derivative is bounded, so the hypothesis holds with exponent zero.
For , the composition is continuous and linear, hence tempered. For a single test, , proving weak continuity of the transpose.
If is bounded in , the finite estimates of step 1.1 show that is bounded. Thus , proving strong continuity. The derivative hypothesis is essential: for example is smooth but does not map every Schwartz function to a Schwartz function. No choice axiom is used.
Differentiation and polynomial multiplication preserve tempered distributions
Statement
For , a multi-index , and a complex polynomial , define
Both results lie in . For fixed or , these operations are continuous in both the weak and strong dual topologies, and their restrictions to agree with the corresponding operations on .
Facts & Assumptions
Given: A tempered distribution , a multi-index , and a complex polynomial (Tempered distribution).
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).
Weak and strong dual topologies use point tests and bounded test sets (Weak and strong topologies on tempered distributions).
On , 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
Each displayed functional is the composition of with a continuous Schwartz endomorphism, followed in the derivative case by a scalar sign. It is therefore continuous and complex-linear on , hence belongs to .
For a single test , the absolute value after either operation is a source weak seminorm evaluated at the transformed test. Thus each operation is weakly continuous.
A continuous linear Schwartz endomorphism sends bounded sets to bounded sets. For a bounded , the target strong seminorm is therefore the source strong seminorm on or (the derivative sign disappears under absolute values). This proves strong continuity.
If , then and are again compactly supported tests. Evaluating the two displayed definitions on gives exactly the formulas in [F3]. Hence restriction to commutes with both operations. The cases , constant , , and follow from the same formulas. No choice axiom is used.
Fourier differentiation and multiplication identities on tempered distributions
Statement
Assume Countable Choice. For and every multi-index ,
Every operation and equality is in .
Facts & Assumptions
Given: Countable Choice, , and a multi-index .
Derivatives and polynomial products on use the bilinear transpose conventions (Differentiation and polynomial multiplication preserve tempered distributions).
The distributional Fourier transform is the bilinear transpose of the Schwartz transform (Fourier transform of a tempered distribution).
On Schwartz tests, and (Fourier transform acts continuously on Schwartz space), and all test operations involved are continuous (Basic operations are continuous on Schwartz space).
Proof
Fix a coordinate and a Schwartz test ; transposition gives the following calculation.
The first minus sign is the distributional derivative sign; the second identity is the second formula in [F3]. [F1, F2, F3]
The first formula in [F3] gives , so transposition yields the second calculation.
[F1, F2, F3]
Coordinate derivatives and coordinate multipliers commute among themselves in the relevant families. Iterating steps 1.1 and 1.2 times therefore gives the two multi-index identities. For both reduce to . Countable Choice is used only through the published Schwartz Fourier identity.
Fourier transform of delta constants plane waves and polynomials
Statement
Assume Countable Choice and the negative-sign normalization. For and every multi-index ,
and
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, , and a multi-index .
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).
Constants, plane waves, and polynomials are regular tempered distributions (Polynomial growth functions define tempered distributions).
On , and is injective (Fourier transform is a topological automorphism of tempered distributions).
Fourier differentiation and multiplication have the precise constants and signs (Fourier differentiation and multiplication identities on tempered distributions).
The published translation/modulation laws use the same negative-sign normalization (Translation, modulation, linear dilation and reflection laws).
Proof
Evaluate the transform of on an arbitrary .
Thus is the displayed plane wave; at this gives . The sign agrees with [F5]. [F1, F2, F5]
Apply to . Since , [F3] gives . Similarly step 1.1 with gives , so applying once more gives .
Apply the derivative identity in [F4] to and use to obtain . Apply the multiplication identity to the constant distribution and use to obtain the formula for .
Every polynomial is a finite complex linear combination of monomials, so linearity completes the polynomial assertion. The zero multi-index recovers and . Countable Choice is used only through the published Fourier suppliers.
Constant coefficient differential operators become polynomial multipliers
Statement
Assume Countable Choice. Let be a complex polynomial in variables, with finite, and put . Then, for every ,
in .
Facts & Assumptions
Given: Countable Choice, a finite polynomial , and .
For every multi-index , (Fourier differentiation and multiplication identities on tempered distributions).
Proof
Fourier transformation, distributional differentiation, and finite addition are complex-linear, giving the following finite expansion.
[F1, algebra]
Substitute [F1] into the finite sum from step 1.1 and factor the common distribution to obtain . This includes constant and zero polynomials. The statement is only an algebraic equivalence: it asserts no division by and no existence or regularity theorem for a PDE. Countable Choice is used only through [F1].
Schwartz parameter pairing and integral interchange
Statement
For , the map
is as a map from to Schwartz space, with . This clause holds in ZF.
Assume Countable Choice for the following integral clause. Let and let be continuous in every Schwartz seminorm. Suppose each is jointly measurable and, for every , there is such that
for almost every . Then belongs to , derivatives pass under the integral, and every satisfies
All integrals in this clause are Lebesgue integrals.
Facts & Assumptions
Given: A Schwartz function ; for the second clause also Countable Choice, a family with the stated seminorm majorants, and .
Fixed translations, reflection, and derivatives preserve Schwartz space continuously (Basic operations are continuous on Schwartz space).
The functional obeys one finite Schwartz-seminorm estimate (Finite seminorm bound characterizes tempered distributions).
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
Fix a compact set of parameters . The inequality transfers every polynomial weight in to one in , uniformly for . Apply the one-variable integral Taylor remainder along each coordinate.
The same estimate applied to every derivative gives continuity of all iterated derivatives. [F1, algebra]
Iterating step 1.1 proves that is in the Schwartz topology and gives the displayed derivative formula. When every derivative is zero. No integration on parameter space and no choice principle occurred. [step 1.1]
For the integral clause, differentiate under the integral and apply the integral triangle inequality pointwise in .
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 . Thus . [F3]
Let . Subdivide it into the canonical equal mesh and form lower-corner finite sums for . Uniform continuity in each seminorm and [F3] make these sums converge to in that seminorm. Continuity of may therefore be passed through this explicit limit.
The last equality is the same scalar step-function approximation. [F2, F3]
The finite estimate [F2] involves only finitely many seminorms. Their majorants show both in those seminorms and as . 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.
Tempered convolution is smooth with polynomial growth
Statement
For and , the function is smooth and every derivative has polynomial growth. For each multi-index ,
Consequently , interpreted as a regular distribution, belongs to .
Facts & Assumptions
Given: and , with convolution as in Convolution of a tempered distribution with a schwartz function.
There are giving a finite rectangular seminorm estimate for (Finite seminorm bound characterizes tempered distributions).
Translation, reflection, and differentiation are continuous on Schwartz space (Basic operations are continuous on Schwartz space).
Smooth pointwise-polynomial-growth functions define regular tempered distributions (Polynomial growth functions define tempered distributions).
Proof
For every and coordinate , Taylor's integral remainder and show that the -difference quotients of converge in every Schwartz seminorm to . Continuity of permits differentiation of the scalar pairing, and iteration gives every multi-index derivative.
[F1, F2, given]
Apply the definition of distributional differentiation to the translated test.
Together with step 1.1 this proves both derivative identities, including . [F2, step 1.1]
Apply [F1] to the translated test in step 1.1. Write and expand .
Hence . [F1, algebra]
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 or , all formulas reduce to zero. No parameter integral or choice axiom is used.
Fourier transform of a compactly supported distribution is a smooth polynomially bounded multiplier
Statement
Assume Countable Choice. Let have compact support, let be its canonical extension, and let equal one on a neighborhood of . Then is the regular tempered distribution represented by
The function is independent of , is smooth, and for every multi-index there are with . Consequently multiplication by is continuous on and, by transpose, on in both dual topologies.
Facts & Assumptions
Given: Countable Choice, a compactly supported distribution , and a cutoff as in the statement.
The extension 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).
Compactly supported distribution pairings with smooth parameter families differentiate in the parameter (Distribution pairing with smooth parameter families).
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).
A smooth function whose derivatives grow polynomially is a continuous Schwartz multiplier, as is its transpose (Smooth polynomially bounded multipliers on schwartz space).
Proof
If and are both one near , then vanishes near that support, so [F1] makes its pairing with zero. Thus is cutoff-independent.
Apply smooth parameter differentiation from [F2].
On one fixed compact containing , the finite-order estimate for differentiates the displayed test in only finitely many times. Each resulting term is bounded by a constant times . Hence is smooth and every derivative has the claimed polynomial bound. [F1, F2, algebra]
Let and set . As an -Schwartz family, is continuous in , and every -Schwartz seminorm has an integrable majorant . Thus [F3] applies.
[F1, F3]
Equality in step 1.3 identifies with the regular distribution . The derivative bounds from step 1.2 satisfy [F4], which proves both multiplier assertions. For , ; empty support causes no exception. Countable Choice enters only through the published Fourier and Lebesgue-interchange clauses.
Compact distribution convolution preserves schwartz and tempered spaces
Statement
Let have compact support. Then
is continuous and complex-linear. If , define by
After restricting and to , 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 , a Schwartz function , and a tempered distribution (Tempered distribution).
Compactly supported distributions act continuously on all smooth functions and obey a fixed compact finite-order estimate (Compactly supported distributions extend to smooth functions).
The Schwartz seminorms/topology are those of Schwartz space and its seminorms and Schwartz topology and convergence.
The smooth-parameter clause for compact distribution pairings holds in ZF (Distribution pairing with smooth parameter families).
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).
Restriction embeds into (Tempered distributions embed continuously in distributions).
Proof
Choose a compact neighborhood of and an order for the estimate in [F1]. Differentiate by [F3] and expand .
Only finitely many terms occur because stays in . [F1, F2, F3, algebra]
The estimates in step 1.1 show that is Schwartz and that is continuous. Replacing by proves the same statement for ; equivalently for the reflected compact distribution .
The displayed candidate for is . By step 2.1 this is a continuous complex-linear functional on , hence tempered.
For , the inner function is precisely the iterated-pairing test used by the addition-map definition in [F4].
with the cutoff interpretation prescribed there. This proves agreement after the embedding [F5]. The cases , , 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] ∎
Fourier transform converts allowed tempered convolutions to products
Statement
Assume Countable Choice. Let and . Then
In the second formula the convolution means under the distribution-first convention. If has compact support, then
Here is the smooth polynomially bounded function representing the transform of the canonical tempered extension of . No product of two arbitrary distributions and no convolution of two arbitrary tempered distributions occurs.
Facts & Assumptions
Given: Countable Choice, , , and, for the last formula, compactly supported .
The convolution is a regular tempered distribution (Tempered convolution is smooth with polynomial growth).
Schwartz multipliers act on , and is a smooth polynomially bounded multiplier (Smooth polynomially bounded multipliers on schwartz space, Fourier transform of a compactly supported distribution is a smooth polynomially bounded multiplier).
Seminorm-dominated Schwartz integrals commute with tempered pairings (Schwartz parameter pairing and integral interchange).
Compact-distribution convolution preserves and agrees with the support-conditioned distribution convolution (Compact distribution convolution preserves schwartz and tempered spaces).
Fourier transformation or inversion is available on , with (Fourier transform is a topological automorphism of tempered distributions).
Products and convolutions of two Schwartz functions satisfy the same -normalized transform laws (Schwartz convolution and product laws).
Proof
Let . The family is dominated in every -Schwartz seminorm by an integrable polynomial weight times . Therefore [F3] applies.
[F1, F3]
Absolute scalar interchange, or equivalently [F6] on Schwartz functions, identifies the inner integral.
Indeed, inserting and translating produces . Hence step 1.1 equals , which is . [F2, F3, F6, step 1.1]
Put . Evaluate the compact-factor convolution on an arbitrary .
The compact support of and [F3] permit its pairing to cross the rapidly convergent Fourier integral, giving
Thus the outer pairing is . [F2, F3, F4]
Apply the first identity to and the Schwartz function , then use Fourier squaring.
Since , inversion gives . 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.