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.

✓ 10 results · all verified · 8 also independently AI-judged
Every result on this page is machine-checked by a proof checker and read in full and owner-audited; the judge is an additional, independent cross-model AI review of the proofs. The 2 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

Nonuniform fast fourier transforms

1 · Prerequisites

2 · Summary

Scope and conventions

For type 1, finitely many weighted points on the period-one torus are mapped to integer Fourier modes. Type 2 is the matching conjugate-transpose map from modes back to the same points. Type 3 uses separately supplied real frequencies and has no implicit wrapping, frequency scaling, or type-1 complexity guarantee. The signs, domains and normalizations are fixed in Type-1, type-2, and type-3 nonuniform Fourier transforms.

The finite-array l1, Euclidean, and maximum norms used for data and certificates are fixed, including their empty-array convention, in Finite complex-array norms used by the NUFFT certificates.

Gaussian gridding

The periodized Gaussian is defined and shown locally uniformly convergent in Periodized Gaussian gridding kernel and Local uniform convergence of the periodized Gaussian. Its Fourier coefficients and uniform Fourier expansion are proved in Fourier series of the periodized Gaussian. The finite image sum has an explicit omitted-image bound, while the source-centered finite spread has its own tail bound; these are distinct truncations with different constants.

The factorization below names the operators used by the type-1 procedure. Here S is the finite-width spread matrix, Q is the grid DFT with coefficient 1/P, and D is the diagonal matrix of positive Gaussian mode multipliers. The type-2 procedure applies the conjugate transposes in reverse order. The diagram records the factorization only; all error estimates are proved algebraically in Exact Gaussian grid alias identity and explicit alias bound and Certified type-1 Gaussian gridding error and type-2 adjoint bound.

\begin{tikzpicture}[>=stealth, node distance=2.1cm]
\node (c) {$c\in\mathbb C^N$};
\node[draw, rounded corners, right of=c] (spread) {$S$\; finite Gaussian spread};
\node[right of=spread] (grid) {$g\in\mathbb C^P$};
\node[draw, rounded corners, right of=grid] (dft) {$Q$\; normalized grid DFT};
\node[right of=dft] (modes) {$Qg$};
\node[draw, rounded corners, right of=modes] (deconv) {$D^{-1}$\; deconvolution};
\node[right of=deconv] (f) {$\widehat F$};
\draw[->] (c) -- (spread);
\draw[->] (spread) -- (grid);
\draw[->] (grid) -- (dft);
\draw[->] (dft) -- (modes);
\draw[->] (modes) -- (deconv);
\draw[->] (deconv) -- (f);
\end{tikzpicture}

The normalized grid transform in the diagram has entries P−1e−2πik⋅ℓ/M, equivalently P−1/2 times the unitary grid transform. Signed mode k is extracted from, or embedded into, the FFT slot κ(k)=(kr mod Mr)r; Mr>2Kr makes the slots distinct. The algorithm returns inconclusive when an interval, range, denominator, FFT, or twiddle check fails, and returns inconclusive with reason requested-tolerance-not-met when every finite candidate has valid bounds above the requested positive tolerance. Only a candidate whose complete outward error bound meets that tolerance is returned as certified. On successful candidates, the theorem separates the infinite-grid alias term, the finite-spread tail, and the finite-arithmetic radius. For fixed dimension and bounded width and image cutoffs, its scalar work is O(Plog⁡P+Nwd) apart from the stated elementary-range evaluator work.

The prerequisite computed-fast-transforms-and-convolution supplies the computed FFT and its rigorous error bound. The published outward-rounded-interval-and-ball-arithmetic supplies the interval, outward-operation and elementary-range interfaces used directly by the certificate; these existing proved suppliers discharge the planned interval-arithmetic interface. The type-1 coordinate radii explicitly add the computed FFT's normwise error after unitary normalization and positive deconvolution, separately from uncertainty in the spread-grid centers.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: AI-adaptedProof: AI-adaptedprecheck passOpen item page →

Finite complex-array norms used by the NUFFT certificates

Definition

For a finite index set E and a complex array z=(ze)e∈E, define ∥z∥1=∑e∈E∣ze∣,∥z∥2=(∑e∈E∣ze∣2)1/2,∥z∥∞=max⁡e∈E∣ze∣. For z,w∈CE, define the counting inner product by ⟨z,w⟩E=∑e∈Ezewe‾. By Conjugation is an involutive real-field automorphism, zz‾=∣z∣2, and modulus is definite, multiplicative, and subadditive, ⟨z,z⟩E=∑e∈E∣ze∣2, so ∥z∥2=⟨z,z⟩E. For E=∅, all three norms and this inner product are defined to be zero. For nonempty finite E, the maximum exists by repeated comparison in the real order. Complex modulus is as in Real intervals, complex rectangles and ball enclosures, conjugation as in Real and imaginary parts, complex conjugation, and modulus, finite sums as in A finite sum in a commutative monoid indexed by an arbitrary finite set, and the square root is the unique nonnegative root.

Facts & Assumptions

Given: A finite set E and a complex array z∈CE.

[F1]

A finite sum in a commutative monoid indexed by an arbitrary finite set: a finite indexed sum is formed from finitely many terms and the empty sum is zero.

[F2]

Real intervals, complex rectangles and ball enclosures: complex modulus is a finite nonnegative real number.

[F3]

Nonnegative real square roots exist uniquely: every nonnegative real has a unique nonnegative square root.

[F4]

Dedekind-complete ordered real field: the real order is total, so any two real numbers are comparable.

[F5]

The principle of mathematical induction: a statement proved at the first finite list length and preserved when one entry is added holds for every finite list length.

Proof

1.1givenF1F2F4F5induction

For E=∅ all three values are stipulated as zero. If E is nonempty finite, enumerate its elements and induct on the number of entries. A one-entry list of real moduli has a maximum; given a maximum for the first n entries, compare it with the (n+1)st modulus using [F2] and [F4] and keep the larger. Induction [F5] constructs the maximum of the finite modulus list. The finite sum formulas in [F1] are well-defined.

2.1F1F2F3step 1.1algebra∎

Every term ∣ze∣2 is nonnegative by [F2], so the finite sum in the Euclidean norm is nonnegative; [F3] supplies its unique nonnegative square root. Thus all three displayed values are defined, including the separately stipulated empty-array case.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-6-luna)Open item page →

Periodized Gaussian gridding kernel

Definition

For a real parameter τ>0, define the period-one Gaussian gridding kernel by the series

ϕτ(x)=∑n∈Zexp⁡ ⁣(−π(x+n)2τ),x∈R.

The series is the formal periodization; Local uniform convergence of the periodized Gaussian ↗ proves that it converges absolutely and locally uniformly, so its value is a continuous one-periodic real function. Its Fourier coefficient at r∈Z is denoted ϕ^τ(r)=∫01ϕτ(x)e−2πirx dx when this integral is used; Fourier series of the periodized Gaussian ↗ computes it exactly. The kernel is nonnegative and satisfies ϕτ(x+1)=ϕτ(x).

LemmaStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Triangle inequality for the finite NUFFT Euclidean norm

Statement

For a finite index set E and arrays x,y∈CE, the Euclidean norm of Finite complex-array norms used by the NUFFT certificates satisfies ∥x+y∥2≤∥x∥2+∥y∥2.

Facts & Assumptions

Given: A finite set E and arrays x,y∈CE with the counting inner product and norms of Finite complex-array norms used by the NUFFT certificates.

[F1]

Finite complex-array norms used by the NUFFT certificates: ⟨x,y⟩E=∑exeye‾ and ∥x∥22=∑e∣xe∣2.

[F3]

Dedekind-complete ordered real field and Squares of nonzero elements are positive: finite sums of nonnegative reals are nonnegative; a nonzero real square is positive, and a positive summand makes such a finite sum positive.

[F4]

Squaring is monotone on the nonnegatives: for nonnegative reals, comparison of squares is equivalent to comparison of the numbers.

Proof

1.1givenF1F2F3F4choosealgebra

First prove Cauchy–Schwarz for these arrays. If y=0, its inner product with x is zero. If y≠0, choose e0 with ye0≠0; [F2]–[F3] give ∥y∥22=∑e∣ye∣2>0. Put a=⟨x,y⟩E and c=a/∥y∥22. Expanding the finite sum using [F1] and conjugation laws gives 0≤∥x−cy∥22=∥x∥22−∣a∣2∥y∥22. Multiplying by the positive denominator yields ∣⟨x,y⟩E∣2≤∥x∥22∥y∥22; all quantities are nonnegative, so [F4] gives ∣⟨x,y⟩E∣≤∥x∥2∥y∥2.

2.1F1F2F4step 1.1algebra∎

Expand the squared norm: ∥x+y∥22=∥x∥22+2Re⁡⟨x,y⟩E+∥y∥22≤(∥x∥2+∥y∥2)2, where the inequality follows from step 1.1 and Re⁡z≤∣z∣, itself immediate from ∣a+ib∣2=a2+b2≥a2 and [F4]. Both sides before squaring are nonnegative, so [F4] gives the stated triangle inequality.

DefinitionDefinition: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Type-1, type-2, and type-3 nonuniform Fourier transforms

Definition

Fix an integer dimension d≥1. Let Td=[0,1)d be the chosen representatives for period-one coordinates; all coordinates in a type-1 or type-2 transform are interpreted modulo integer shifts. Here π is the real constant defined in Real elementary functions and their domains. For x∈Rd and k∈Zd, write k⋅x=∑r=1dkrxr. Let N,J≥0 be finite integers, let x0,…,xN−1∈Td, let c=(cj)j<N∈CN, and choose integers Kr≥0. The rectangular mode set is

K=∏r=1d{−Kr,−Kr+1,…,Kr}.

The type-1 nonuniform discrete Fourier transform maps source coefficients to integer-mode samples:

Fk=∑j=0N−1cje−2πik⋅xj,k∈K.

The type-2 nonuniform discrete Fourier transform maps a coefficient array (fk)k∈K to values at the same point list:

gj=∑k∈Kfke+2πik⋅xj,0≤j<N.

For the type-1 matrix A=(e−2πik⋅xj)k∈K, j<N, define its conjugate transpose by (A∗)jk=Akj‾. Use the finite counting inner products from Finite complex-array norms used by the NUFFT certificates; the type-2 matrix is A∗ as proved below.

The type-3 nonuniform discrete Fourier transform takes a finite source list x0,…,xN−1∈Rd, coefficients cj∈C, and a separately specified finite frequency list ξ0,…,ξJ−1∈Rd, and returns

Gℓ=∑j=0N−1cje−2πiξℓ⋅xj,0≤ℓ<J.

Type 3 has no integer-mode restriction or implicit coordinate wrapping. No frequency normalization, axis scaling, or frequency-space product is implicit; any such scaling is separate input data whose cost must be analyzed separately. Each displayed map is a finite sum of defined complex exponentials; the zero-source case has the empty-sum value zero and the zero-output case returns the empty array. No fast algorithm or complexity claim for type 3 is part of this definition.

Facts & Assumptions

Proof

1.1givenF1F2F3algebra

Fix j<N and k∈K, and put t=2πk⋅xj∈R. By [F1]–[F2], e−it=cos⁡(−t)+isin⁡(−t)=cos⁡t−isin⁡t. Applying [F3] gives e−it‾=cos⁡t+isin⁡t=eit. Thus (A∗)jk=Akj‾=e+2πik⋅xj.

2.1F4step 1.1algebra∎

For any c∈CN and f∈CK, expand the finite sums: ⟨Ac,f⟩K=∑k∈K∑j<Ncje−2πik⋅xjfk‾=∑j<Ncj∑k∈Kfke+2πik⋅xj‾=⟨c,A∗f⟩{j<N}. The first equality uses finite distributivity/reordering from [F4]; the second uses step 1.1 and the stated inner-product convention. Thus the type-2 sum is exactly the conjugate-transpose action under matching finite inner products.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Local uniform convergence of the periodized Gaussian

Statement

For every τ>0, the series defining ϕτ(x) converges absolutely and uniformly on each compact interval of x. Its sum is continuous on R and has period one.

Facts & Assumptions

Given: A real parameter τ>0.

[F1]

Periodized Gaussian gridding kernel: ϕτ(x) is the series ∑n∈Zexp⁡(−π(x+n)2/τ), with π the real constant from the real elementary functions.

[F2]

Dedekind completeness implies the Archimedean property: the natural numbers are unbounded above.

[F3]

For ∣r∣<1, ∑k≥0rk=1/(1−r), and for ∣r∣≥1 the series diverges: if 0<q<1, then ∑n≥0qn=1/(1−q) and its tails tend to zero.

[F4]

The exponential function is strictly increasing, The exponential is positive and satisfies exp⁡(−x)=1/exp⁡(x), Continuity and derivative on a real interval, The exponential function is smooth and (exp⁡)′=exp⁡, Sum, product, quotient, and chain rules from difference quotients, and Real elementary functions and their domains: exp⁡ is continuous and strictly increasing, exp⁡(0)=1 by its power series, and exp⁡(x)>0 for every real x; the difference-quotient definition and scalar power, sum and chain rules show each summand x↦exp⁡(−α(x+n)2) is differentiable and hence continuous, so each finite partial sum is continuous.

[F5]

Real elementary functions and their domains: π=4∫01(1+t2)−1 dt, whose integrand is at least 1/2 on [0,1]; hence π≥2>0.

[F6]

Proof

Given: τ>0.

1.1givenF1F2F3F4F5F6choosealgebra

Put α=π/τ>0 using [F5] and τ>0, and set q=exp⁡(−α)∈(0,1) by [F4]. Fix R>0 and choose an integer n0>R+1 by [F2]. For ∣x∣≤R and ∣n∣≥n0, one has ∣x+n∣≥∣n∣−R>1, hence (x+n)2≥(∣n∣−R)2≥∣n∣−R. Since exp⁡ is increasing, the nth nonnegative summand is at most exp⁡(−α(∣n∣−R))=exp⁡(αR)q∣n∣ by [F6]. The two-sided geometric tail is finite and tends to zero uniformly in x∈[−R,R] as its starting index tends to infinity, by [F3]. This proves absolute and uniform convergence on every compact interval.

2.1F1F4step 1.1algebra∎

Each finite partial sum is continuous by [F1] and [F4]. Fix x0∈R and ε>0, choose R>∣x0∣+1, and choose a partial-sum index for which the uniform tail on [−R,R] is below ε/3 by step 1.1. Continuity of that finite partial sum at x0 gives a neighborhood where its change is below ε/3; the two tail values contribute less than 2ε/3. Thus the full sum is continuous at x0. Absolute convergence permits the reindexing m=n+1 in ϕτ(x+1)=∑nexp⁡(−α(x+1+n)2), giving ϕτ(x+1)=ϕτ(x). Since x0 was arbitrary, the sum is continuous and one-periodic.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Explicit tail for the periodized Gaussian image sum

Statement

For τ>0, integer L≥1, and x∈[0,1], put ϕτ,L(x)=∑n=−LLexp⁡ ⁣(−π(x+n)2τ),Rτ,L=2exp⁡(−πL2/τ)1−exp⁡(−πL/τ). Then 0≤ϕτ(x)−ϕτ,L(x)≤Rτ,L, and the denominator defining Rτ,L is positive.

Facts & Assumptions

Given: τ>0, L≥1, and x∈[0,1].

[F1]

Periodized Gaussian gridding kernel and Local uniform convergence of the periodized Gaussian: ϕτ(x) is the convergent sum over all integer images.

[F2]

Real elementary functions and their domains: π=4arctan⁡(1)≥2>0, because (1+t2)−1≥1/2 on [0,1]; the exponential power series gives exp⁡(0)=1.

[F4]

For ∣r∣<1, ∑k≥0rk=1/(1−r), and for ∣r∣≥1 the series diverges: for 0<q<1, ∑h≥0qh=1/(1−q) and ∑h≥1qh=q/(1−q).

Proof

1.1givenF1F2F3F4algebra

Let q=exp⁡(−πL/τ)∈(0,1) by [F2]–[F3]. For positive omitted indices write n=L+h with h≥1. Since 0≤x≤1, (x+n)2≥n2=(L+h)2≥L2+Lh, so their sum is at most exp⁡(−πL2/τ)∑h≥1qh. By [F4] this is at most exp⁡(−πL2/τ)/(1−q).

1.2givenF1F2F3F4algebra

For negative omitted indices write n=−(L+1+h) with h≥0. Then ∣x+n∣=L+1+h−x≥L+h, and (L+h)2≥L2+Lh. Their sum is at most exp⁡(−πL2/τ)∑h≥0qh=exp⁡(−πL2/τ)/(1−q) by [F4].

2.1step 1.1step 1.2F1F3algebra∎

The two omitted tails are nonnegative and exhaust the indices outside [−L,L]. Adding steps 1.1 and 1.2 gives the claimed remainder Rτ,L; [F3] also proves its denominator is positive.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Fourier series of the periodized Gaussian

Statement

Assume Countable Choice. For τ>0, the Fourier coefficient of ϕτ at each integer r is ϕ^τ(r)=τexp⁡(−πτr2), and ϕτ(x)=∑r∈Zτexp⁡(−πτr2)e2πirx. The periodized series on the left converges locally uniformly, and the Fourier series on the right converges absolutely and uniformly.

Facts & Assumptions

Given: Countable Choice and a real parameter τ>0.

[A1]

The Axiom of Countable Choice (ACω): Countable Choice, as required by the Schwartz Poisson-summation and Euclidean Gaussian-transform suppliers.

[F1]

Poisson summation for Schwartz functions: for a Schwartz function h on R, ∑n∈Zh(x+n)=∑r∈Zh^(r)e2πirx, with the left side locally uniform and the right side absolutely uniformly convergent.

[F2]

Euclidean Gaussian transform with the 2π normalization: under Countable Choice, (exp⁡(−πtu2))^(r)=t−1/2exp⁡(−πr2/t) for t>0 and r∈R.

[F3]

Schwartz space and its seminorms: h∈S(R) when it is smooth and every seminorm sup⁡u∣umh(q)(u)∣ is finite.

[F4]

The exponential function is smooth and (exp⁡)′=exp⁡ and Sum, product, quotient, and chain rules from difference quotients: exp⁡′=exp⁡, and derivatives of products and compositions obey the product and chain rules.

[F5]

The exponential dominates every fixed nonnegative integer power at +∞: for every fixed nonnegative integer m and a>0, xm/exp⁡(ax)→0 as x→+∞.

[F6]

Local uniform convergence of the periodized Gaussian: the defining kernel series is locally uniformly convergent and equals ϕτ.

[F7]

Real elementary functions and their domains: arctan⁡(1)=∫01(1+t2)−1 dt≥1/2, so π=4arctan⁡(1)≥2>0; the real exponential is defined on all of R.

Proof

1.1A1F3F4F5F7giveninduction

Let hτ(u)=exp⁡(−πu2/τ). By [F4], induction on derivative order gives hτ(q)(u)=Pq(u)exp⁡(−πu2/τ) for a polynomial Pq. For every m,q, the quantity ∣u∣m∣Pq(u)∣exp⁡(−πu2/τ) tends to zero as ∣u∣→∞: bound the polynomial by a finite sum of powers, set z=u2, and apply [F5] with a=π/τ>0 by [F7]. On a compact interval it is bounded by continuity. Thus every seminorm in [F3] is finite and hτ∈S(R).

2.1A1F1F2F6step 1.1∎

Apply [F1] to hτ from step 1.1. By [F2] with t=1/τ, its Fourier transform at integer r is τexp⁡(−πτr2). The left periodization is ϕτ by [F6], so [F1] gives the displayed Fourier series, its coefficient formula, and both convergence assertions.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passOpen item page →

Explicit periodized Gaussian spread-tail bound

Statement

Let d≥1, τr>0, and integers Mr,wr≥1 satisfy Mr≥2wr+1. Define ar=π/(τrMr2) and Sr=21−exp⁡(−ar),Tr=2exp⁡(−arwr2)(1+12arwr). For x=(xr)r=1d∈[0,1)d, let Wr(xr)={ℓ∈{0,…,Mr−1}:min⁡n∈Z∣ℓ/Mr−xr−n∣≤wr/Mr},W(x)=∏r=1dWr(xr). With Φτ(z)=∏r=1dϕτr(zr), the omitted spreading mass obeys ∑ℓ∈∏r{0,…,Mr−1}∖W(x)Φτ(ℓ1/M1−x1,…,ℓd/Md−xd)≤Td,Td:=∑r=1dTr∏s≠rSs. Also ∑ℓr=0Mr−1ϕτr(ℓr/Mr−xr)≤Sr for every coordinate and point.

Facts & Assumptions

Given: The stated finite dimension, positive τr, integers Mr,wr, and point x.

[F1]

Local uniform convergence of the periodized Gaussian: each periodized Gaussian is nonnegative, one-periodic, and its defining integer series converges absolutely and locally uniformly.

[F2]

For ∣r∣<1, ∑k≥0rk=1/(1−r), and for ∣r∣≥1 the series diverges: for 0<q<1, the geometric series converges and its finite tails have the usual explicit sum.

[F3]

Continuity and derivative on a real interval, The exponential function is smooth and (exp⁡)′=exp⁡, and Sum, product, quotient, and chain rules from difference quotients: the power and product rules give (t2)′=2t, and the constant function has zero derivative by its difference quotient; hence (t↦−at2)′=−2at. Combining this with (exp⁡)′=exp⁡ and the scalar chain rule shows that fa(t)=exp⁡(−at2) is differentiable with derivative fa′(t)=−2atexp⁡(−at2) for a>0.

[F4]

The second fundamental theorem: if G is differentiable on [a,b] with G′=f and f is integrable, then ∫abf=G(b)−G(a): if G′=g on a compact interval and g is integrable, then ∫uvg=G(v)−G(u).

[F6]

Real elementary functions and their domains, The exponential function is strictly increasing, and The exponential is positive and satisfies exp⁡(−x)=1/exp⁡(x): π=4∫01(1+t2)−1 dt≥2>0, exp⁡(0)=1, and the exponential is positive and strictly increasing; hence ar>0 and 0<exp⁡(−ar)<1.

Proof

1.1F1F2F6constructalgebra

Fix one coordinate, write M=Mr, τ=τr, w=wr, a=π/(τM2)>0 by [F6], and y=Mxr. Reindexing the finite grid index and period index by m=ℓ+nM gives ∑ℓ=0M−1ϕτ(ℓ/M−xr)=∑m∈Zexp⁡(−a(m−y)2). For every integer s≥0, at most two integers satisfy s≤∣m−y∣<s+1. Their terms are at most exp⁡(−as2); for s≥1, s2≥s. Thus the sum is at most 2∑s=0∞exp⁡(−as)=2/(1−exp⁡(−a))=Sr by [F2].

1.2F1F3F4F5algebra

If ℓ∉Wr(xr), then every m=ℓ+nM satisfies ∣m−y∣>w. On either side of y, the lattice distances form a unit-spaced sequence d+n with d>w. The first term is at most exp⁡(−aw2). For each later term, monotonicity of fa gives fa(d+n)≤∫d+n−1d+nfa(t) dt. For R>w, [F3]–[F4] give ∫wRfa(t) dt≤1w∫wRtfa(t) dt=exp⁡(−aw2)−exp⁡(−aR2)2aw≤exp⁡(−aw2)2aw. By [F5], the last subtracted term tends to zero as R→∞. Taking limits of the finite tail sums, which converge by [F1], bounds each side by exp⁡(−aw2)(1+1/(2aw)). Both sides together yield ∑ℓ∉Wr(xr)ϕτ(ℓ/M−xr)≤Tr.

2.1step 1.1step 1.2algebra∎

The complement of the product set W(x) is the union of the d sets where at least one coordinate index is outside its Wr(xr). Since all kernel terms are nonnegative, the total omitted product mass is at most the sum of the d coordinate-tail product sums. Each such finite product factors into the one-coordinate tail in step 1.2 and the full-coordinate masses in step 1.1; hence it is at most Tr∏s≠rSs. Summing over r gives Td.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Exact Gaussian grid alias identity and explicit alias bound

Statement

Assume Countable Choice. Let d≥1, N≥0, cj∈C, xj∈[0,1)d, integers Kr≥0, positive integers Mr>2Kr, and τr>0. Write P=∏r=1dMr, define Φτ(z)=∏r=1dϕτr(zr), and let gℓ=∑j=0N−1cjΦτ(ℓ1/M1−xj,1,…,ℓd/Md−xj,d),0≤ℓr<Mr. For k∈K=∏r{−Kr,…,Kr} define the normalized grid DFT g~k=1P∑ℓ1=0M1−1⋯∑ℓd=0Md−1gℓexp⁡ ⁣(−2πi∑r=1dkrℓr/Mr). Put Φ^(m)=∏rτrexp⁡(−πτrmr2). Then g~k=∑q∈ZdΦ^(k+q⊙M)∑j=0N−1cjexp⁡(−2πi(k+q⊙M)⋅xj), where (q⊙M)r=qrMr. In particular, Φ^(k)>0 and g~kΦ^(k)=Fk+∑q≠0[∏r=1dexp⁡ ⁣(−πτr((kr+qrMr)2−kr2))]∑j=0N−1cjexp⁡(−2πi(k+q⊙M)⋅xj). For sr=exp⁡(−πτrMr(Mr−2Kr))∈(0,1) and A=∏r=1d(1+2sr1−sr)−1, the alias error satisfies ∣g~kΦ^(k)−Fk∣≤A∑j=0N−1∣cj∣.

Facts & Assumptions

Given: The finite data above and Countable Choice.

[A1]

The Axiom of Countable Choice (ACω): Countable Choice, inherited through the periodized-Gaussian Fourier-series supplier.

[F1]

Fourier series of the periodized Gaussian: ϕτ(x)=∑m∈Zτ e−πτm2e2πimx, absolutely and uniformly.

[F2]

Type-1, type-2, and type-3 nonuniform Fourier transforms: Fk=∑jcje−2πik⋅xj for k∈K.

[F6]
[F7]

Conjugation is an involutive real-field automorphism, zz‾=∣z∣2, and modulus is definite, multiplicative, and subadditive: ∣zw∣=∣z∣∣w∣ and ∣z+w∣≤∣z∣+∣w∣ for complex numbers.

Proof

1.1A1F1F3givenconstructalgebra

Substitute [F1] into each factor of Φτ and then into g~k. Absolute uniform convergence in [F1] permits interchanging the finite grid/source sums with the absolutely convergent Fourier series. For an integer mr, the coordinate root sum is 1Mr∑ℓr=0Mr−1e2πi(mr−kr)ℓr/Mr={1,mr−kr∈MrZ,0,mr−kr∉MrZ. Indeed, in the first case every term is 1; in the second, z=e2πi(mr−kr)/Mr≠1 by [F3] while zMr=1, so the finite geometric sum is (1−zMr)/(1−z)=0. Thus only mr=kr+qrMr remain in each coordinate, giving the displayed exact alias identity.

2.1F1F2F6step 1.1algebra

The q=0 term of that identity is Φ^(k)Fk by [F1]–[F2]. Each factor τrexp⁡(−πτrkr2) is positive by [F6], so division by Φ^(k) is valid. For each q, its coefficient ratio is Φ^(k+q⊙M)Φ^(k)=∏rexp⁡ ⁣(−πτr((kr+qrMr)2−kr2)). Separating q=0 proves the deconvolution identity.

3.1givenF4F5F6F7step 1.1step 2.1algebra∎

Since Mr>2Kr, τr>0 and π>0 by [F6], the exponent parameter λr=πτrMr(Mr−2Kr) is positive. Positivity and strict monotonicity of exp⁡ in [F6] imply 0<sr=e−λr<1. Fix one coordinate r. If qr=±h with integer h≥1 and ∣kr∣≤Kr, then (kr+qrMr)2−kr2=qr2Mr2+2qrMrkr≥h2Mr2−2hMrKr≥hMr(Mr−2Kr)>0. Hence the absolute alias multiplier for that coordinate is at most srh. By [F5] its sum over nonzero qr is at most 2sr/(1−sr), so the sum over all coordinate multi-indices other than zero is at most the product of the coordinate sums including their unit terms, minus the all-zero term, namely A. The unit-modulus fact [F4], multiplicativity, and the triangle inequality in [F7] bound each source phase sum by ∑j∣cj∣. This gives the asserted alias bound.

AlgorithmAlgorithm: Literature-sourcedProof: Not applicablejudge pass (gpt-6-luna)Open item page →

Certified Gaussian gridding for type 1 and type 2

Definition

Fix a dimension d≥1, finite mode bounds Kr≥0, a finite type-1 source list (xj,cj)j<N or type-2 data (xj)j<N,(fk)k∈K as in Type-1, type-2, and type-3 nonuniform Fourier transforms, and a nonempty finite ordered list of candidate tuples C=((τr,Mr,wr,Lr)r=1d)ν=1C, an interval-arithmetic format (p,emin⁡,emax⁡) with integers p≥2 and emin⁡≤emax⁡, and one operationwise arithmetic model from Operationwise real and complex floating point arithmetic with rounded square roots and fused multiply-add with the same binary precision p and normal exponent limits jmin⁡=emin⁡ and jmax⁡=emax⁡. Let u be a valid unit-roundoff bound for this selected model instance; it is not a separate free control, and require u≤1/16. Use this same model instance for every computed FFT operation. Let J≥1 be the finite elementary-series truncation index, 0≤ϵtw≤1/4 an exact rational maximum allowed twiddle certificate, 0<δϕ≤1/4 an exact rational phase-evaluation tolerance, integers 2≤pϕ,0≤pϕ,max⁡ giving the initial and maximum phase precisions, and a finite recursion-depth cap dFFT≥0. The phase evaluator uses exponent limits emin⁡,emax⁡ and truncation index J. Also supply an exact positive dyadic requested absolute tolerance εreq>0. Source coordinates and coefficients are finite dyadics interpreted as exact real and complex inputs. Each candidate must have rational τr>0, a power-of-two grid length Mr=2qr with integer qr≥0, Mr>2Kr, integer width wr≥1 with Mr≥2wr+1, and integer image cutoff Lr≥1. A malformed global control or structurally invalid candidate returns invalid-input before arithmetic. Type 3 is not an input mode for this algorithm.

After validating the global controls and candidate shapes, if N=0 return status certified immediately: type 1 returns the exact zero output array and zero radii, and type 2 returns the empty output array and zero radius. For N>0, process the candidates in supplied order; the first candidate that produces a complete interval certificate meeting εreq is returned.

  1. For each coordinate compute outward enclosures for ar=πτrMr2,sr=exp⁡ ⁣(−πτrMr(Mr−2Kr)),dr=τrexp⁡(−πτrKr2), Sr=21−exp⁡(−ar),Tr=2exp⁡(−arwr2)(1+12arwr),Rr=2exp⁡(−πLr2/τr)1−exp⁡(−πLr/τr). Use Certified range evaluation for elementary real and complex functions for every real exponential and square-root node in the procedure, including the finite norms, normalization and complex moduli; use format (p,emin⁡,emax⁡) and truncation index N=J on every such call. Form every Machin enclosure of π with this same format and index. Use the outward interval operations for the rational DAGs. Set A=∏r=1d(1+2sr1−sr)−1,Td=∑r=1dTr∏s≠rSs,dmin⁡=∏r=1ddr. Store outward upper bounds A+,Td+ and Rr+, where Rr+ bounds the exact image-tail constant Rr, and a lower bound dmin⁡−. If any required enclosure is non-finite, if a required denominator interval in A,Sr,Tr,Rr contains zero, if some sr enclosure is not strictly below 1, or if dmin⁡−≤0, reject this candidate as inconclusive; no division by an unverified multiplier is performed.

  2. For every source define and construct its periodic nearest-point set by the following finite rule. For each coordinate put aj,r=Mrxj,r, enumerate the integers from ⌈aj,r−wr⌉ through ⌊aj,r+wr⌋, and take their least nonnegative residues modulo Mr as Wj,r; then set Wj=∏rWj,r. This equals the displayed set because its membership condition is equivalent to some integer m≡ℓr(modMr) satisfying ∣m−aj,r∣≤wr. Compute the endpoints by exact rational comparisons. At most 2wr+1 consecutive integers are enumerated, and Mr≥2wr+1 makes their residues distinct. Wj=∏r=1d{ℓr∈{0,…,Mr−1}:min⁡n∈Z∣ℓr/Mr−xj,r−n∣≤wr/Mr}, using the selected candidate. For type 1 only, for each ℓ∈Wj reduce each exact dyadic displacement ℓr/Mr−xj,r modulo one to zr∈[0,1). Enclose the one-dimensional kernel by evaluating the finite image sum ∑n=−LrLrexp⁡ ⁣(−π(zr+n)2/τr) with Certified range evaluation for elementary real and complex functions using N=J, then add the symmetric interval [−Rr+,Rr+] from step 1. All kernel and coefficient products and sums use outward interval arithmetic. For each grid cell ℓ, this gives a complex rectangle enclosing its exact truncated-spread value gℓ. Choose its lower-left corner uℓ as a dyadic center and an upward dyadic radius eℓ large enough to enclose gℓ−uℓ. Let Eeval be an outward upper bound for (∑ℓeℓ2)1/2 and let U be an outward upper bound for ∥u∥2=(∑ℓ∣uℓ∣2)1/2. Before a type-1 FFT call, require every real and imaginary coordinate of every uℓ to belong to the representable set F of the selected operationwise model; otherwise reject this candidate with a range-failure status before calling the FFT. Type 2 skips this spreading-grid construction; its source-window intervals are evaluated in step 4 using the sets Wj just defined.

  3. For each mode k∈K, define its grid slot by κ(k)=(kr mod Mr)r=1d, using least nonnegative residues; Mr>2Kr makes this map injective. Put η=10u+ϵtw, ρr=(1+η)qr−1 for each axis, and ρ=∏r(1+ρr)−1. For type 1, run Computed unitary radix-two FFT with certified twiddle phases on each length-Mr grid line along axes 1,…,d in a fixed lexicographic line order, with direction forward, the selected operationwise model, phase tolerance δϕ, exponent limits emin⁡,emax⁡, phase precisions pϕ,0,pϕ,max⁡, series cap J, and recursion cap dFFT. The supplier passes the exact rational phase argument q=−2m/Mr for its twiddle indexed by m and returns a certificate ϵℓ for each twiddle it uses. Reject this candidate with the returned status if an FFT call is non-finite or inconclusive; otherwise verify for every returned twiddle certificate that ϵℓ≤ϵtw. If any certificate exceeds ϵtw, reject this candidate with status twiddle-bound-not-met and do not use that FFT output. This check applies literally when ϵtw=0, so every used twiddle must then have certificate zero. After all checks pass, extract the unitary Fourier coordinates at slots κ(k) for k∈K and scale by P−1/2, where P=∏rMr. Use the range evaluator with format (p,emin⁡,emax⁡) and N=J for every real elementary node, including this scaling and the mode multipliers; use the same J Machin enclosure of π. For each required mode evaluate the multiplier interval dk=∏rτrexp⁡(−πτrkr2); if its lower endpoint is ≤0, reject this candidate as inconclusive before division. Otherwise divide by that certified positive interval. Use outward complex-rectangle arithmetic. For each k∈K, choose the lower-left corner zk of this computed scaling/deconvolution rectangle and an upward dyadic radius bk containing that rectangle about zk. This rectangle alone concerns the computed FFT output, not the exact unitary transform. Separately form a certified outward upper bound RFFT for ρUP dmin⁡−. Here U is the certified norm bound of the actual dyadic input grid from step 2, and ρ uses the same selected model's valid bound u and checked twiddle limit ϵtw as the successful FFT calls. Evaluate this nonnegative radius DAG with outward interval operations: integer powers use finite products, and the normalization square root uses the same range format and index J. As with the existing model and rational constants, use certified enclosing constants throughout; in particular enclose the selected model's valid unit-roundoff bound. If that model supplies no tighter certified enclosure for u, use the already verified enclosure [0,1/16], converted outward to the selected format; thus no additional oracle or input for u is required. Reject the candidate as inconclusive if any radius enclosure is non-finite or the normalization denominator enclosure is not strictly positive before division. Define the returned coordinate radius by the upward dyadic sum rk=ru⁡(bk+RFFT); if this sum overflows, reject the candidate with its range status. Thus every returned radius includes both the scaling/deconvolution rectangle and the separately bounded error of its computed FFT relative to the exact transform of the dyadic center grid. Set ϵana=A++Td+P dmin⁡−,Bround=max⁡k∈Krk+EevalP dmin⁡−. The returned error certificate is ϵana and Bround.

  4. For type 2, form the conjugate-transpose finite gridding factorization. For each input mode k, evaluate its multiplier interval using the same format and truncation setting N=J; if its lower endpoint is ≤0, reject the candidate as inconclusive before division. Otherwise divide by that certified positive interval. For the resulting mode rectangles choose lower-left dyadic centers vk and radii ek enclosing their deviations. Set Ef to an outward upper bound for (∑kek2)1/2 and V to an outward upper bound for ∥v∥2. Require every real and imaginary coordinate of the vk to belong to F; otherwise reject this candidate with a range-failure status before calling the FFT. Embed each vk at grid slot κ(k), zero-fill all unused grid modes with zero centers and zero radii, and apply Computed unitary radix-two FFT with certified twiddle phases in direction inverse on the same axes and in the same lexicographic line order, passing the same operationwise model and phase controls as in type 1. Reject a non-finite or inconclusive FFT call; for a finite return verify every returned twiddle certificate ϵℓ≤ϵtw, with the same literal zero-bound rule. Enlarge the unitary-grid output by radius Ef+ρV and scale by P−1/2. For each source xj, use exactly the grid cells ℓ∈Wj from step 2; reduce each coordinate displacement ℓr/Mr−xj,r modulo one to zr∈[0,1), enclose ∑n=−LrLrexp⁡(−π(zr+n)2/τr) by range-evaluator calls with format (p,emin⁡,emax⁡) and N=J, and add [−Rr+,Rr+]. Multiply the coordinate window intervals, conjugate the resulting real window (which leaves it unchanged), and multiply and sum against the scaled grid rectangles using outward complex-rectangle arithmetic at every operation. Return the lower-left corner zj and an outward radius rj containing each resulting rectangle; the type-2 rounding certificate is Bround∗=max⁡jrj. Its analytic certificate is the same ϵana from step 3.

  5. Enclose ∥c∥1 or ∥f∥1 from above by outward modulus and addition intervals. For each candidate whose operations succeed, compare the outward upper bound ϵana∥c∥1+Bround (type 1), or ϵana∥f∥1+Bround∗ (type 2), exactly with εreq. If it is at most εreq, return the centers and their certificates with status certified. Otherwise record this candidate's first non-success reason as requested-tolerance-not-met together with its finite bound, then continue to the next candidate. For any candidate rejected by a range, interval, denominator, mode-positivity, FFT, or twiddle check, record its first failure status and location, then continue to the next candidate. If the finite candidate list is exhausted without a certified return, return status inconclusive with the first recorded non-success record in candidate order. In particular, if every candidate had finite valid bounds above εreq, return inconclusive(requested-tolerance-not-met) with the first such bound; no approximation is returned as certified on this branch.

The analytic term consists only of the exact infinite-grid alias contribution and the omitted finite-spread tail. The reported rounding radius contains the finite image-series enclosure, outward arithmetic, and computed FFT error. The signed-mode slot map κ is used for both type-1 extraction and type-2 embedding. The transform and FFT axes are fixed; a different normalization or sign convention is a different procedure.

Remarks

The unitary radix-two FFT error theorem is used only on successful axes with the stated u and twiddle bounds; range, interval, or denominator failures return inconclusive. The global lower bound dmin⁡−>0 does not replace checking each separately evaluated mode interval before division. The finite candidate list is part of the input; if none meets the requested tolerance the returned status is inconclusive. This procedure handles types 1 and 2 only. Type 3 requires its own frequency-space scale/product and complexity analysis.

LemmaStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Certified Gaussian gridding terminates with a defined status

Statement

For finite exact dyadic data and finite encoded controls, the procedure Certified Gaussian gridding for type 1 and type 2 terminates with a defined status. Malformed global controls or structurally invalid candidates return invalid-input as specified. On admissible controls, the empty-source branch returns its exact zero or empty output; otherwise the procedure returns the first candidate whose complete finite outward bound meets the exact positive requested tolerance with status certified, or returns inconclusive with the first recorded non-success reason in candidate order after the finite list is exhausted. This includes requested-tolerance-not-met when all candidates have finite valid bounds exceeding the requested tolerance.

Every performed interval division has its prescribed nonzero divisor guard, FFT inputs and twiddle certificates pass the declared checks before use, and every returned finite interval contains the exact value of its evaluated DAG. A candidate with a range failure or unresolved interval, denominator, phase, FFT, radius or tolerance check is not itself returned as certified; a later candidate may still succeed. These are termination and well-defined-status assertions for the specified procedure; its complete transform-error estimates are separate mathematical claims.

Facts & Assumptions

Given: Finite exact dyadic type-1 or type-2 data, a finite nonempty candidate list satisfying the displayed integer/rational hypotheses, the selected operationwise model and its valid unit-roundoff bound u, positive requested tolerance εreq, phase controls δϕ,pϕ,0,pϕ,max⁡,dFFT,ϵtw, common range truncation index J, and the interval and FFT routines named in the Definition.

[F1]

Type-1, type-2, and type-3 nonuniform Fourier transforms: the source, mode and output lists are finite, and the type-1/type-2 formulas use the stated mode set.

[F2]

Certified range evaluation for elementary real and complex functions: each elementary range call uses a finite truncation index N and format, and returns either a finite enclosure or a named failure status; the Definition fixes these to N=J and (p,emin⁡,emax⁡).

[F3]

Computed unitary radix-two FFT with certified twiddle phases and Operationwise real and complex floating point arithmetic with rounded square roots and fused multiply-add: each FFT call requires input coordinates in its selected model's representable set, uses a positive phase tolerance, finite phase-precision range and recursion cap, and returns a certificate for every used twiddle or a failure status; u is a valid bound for that same model instance.

[F4]

Outward-rounded operations are inclusion-isotone and enclose DAG evaluations: every finite interval operation encloses its exact range; invalid or unbounded operations return a non-finite status.

[F5]

Finite complex-array norms used by the NUFFT certificates: the finite ℓ2 norms used for grid and mode error radii are defined by finite sums, with value zero on an empty array.

[F6]

Computed unitary radix-two FFT has the multiplicative stage error bound: a successful unitary FFT with the selected model's u≤1/16 and all used twiddle certificates at most ϵtw≤1/4 has Euclidean error factor (1+10u+ϵtw)q−1 at length 2q, in either direction. The type-1 radius construction uses the actual center-grid bound U and these checked factors; its scaling by P−1/2 and positive mode divisions are included explicitly.

[F7]

Certified Gaussian gridding for type 1 and type 2: step 2 constructs each coordinate support list Wj,r from the finite integer interval [⌈Mrxj,r−wr⌉,⌊Mrxj,r+wr⌋] and reduces those integers modulo Mr.

Proof

1.1givenF2F3F4inductionalgebra

The elementary evaluator in [F2] visits a finite typed DAG in topological order. Its series have the fixed finite index J; its exponential scaling uses a finite integer number of squarings; logarithm bins are a finite integer range determined by positive finite endpoints; and trigonometric reduction examines a finite cell list determined by finite endpoints and a positive certified pi lower bound, returning a named failure if that bound or a branch is unresolved. Square-root endpoint bisection starts with finite integer indices and strictly decreases their positive gap until it is at most one (Exact dyadic bisection for square-root endpoints). Thus these child calls terminate. The phase routine examines only the integer precisions from pϕ,0 to pϕ,max⁡ and calls those finite evaluators (Certified dyadic enclosures for unit-circle phases). Each FFT recursion either returns at length one, returns when its depth cap is zero, or makes two calls with the cap reduced by one and a finite twiddle loop. Induction on the finite depth cap therefore proves termination of every forward call; inverse mode adds only finite conjugations. A failed child call propagates its named status. Consequently no child in [F2]–[F3] is an unbounded evaluation oracle.

1.2givenF1F2F3F5F7algebra

Every loop in a candidate is finite: the dimension, source and mode lists, grid-cell lists, image ranges [−Lr,Lr], expression DAGs, range truncation index J, phase precision interval [pϕ,0,pϕ,max⁡], and recursion cap dFFT are finite by [F1]–[F3]. Each coordinate support list Wj,r is generated by the finite integer interval in [F7]. Every FFT length is a finite power of two by [F3]. The finite norm sums used in the radius construction are defined by [F5]. Thus a candidate either returns a result or reaches one of its explicitly named failure branches after finitely many operations.

1.3givenF2F3F4F6algebra

Every division in step 1 is preceded by the denominator, sr<1, and dmin⁡−>0 checks; every type-1 or type-2 mode division is preceded by its own positive-lower-endpoint test in steps 3–4. Hence all performed divisions have divisor intervals excluding zero. The FFT is called only on inputs in its model's representable set; its statuses are checked and no FFT output is used unless every returned twiddle certificate is at most ϵtw. The type-1 FFT-error radius uses the same checked call bounds [F6]; its normalization divisor is checked to have a strictly positive enclosure before division, and its finite upward radius sum is checked for overflow. A failed interval, range, FFT, denominator, mode-positivity, radius or twiddle check rejects the candidate. Sound containment of every returned finite interval follows from [F2] and [F4].

2.1givenF1step 1.2step 1.3algebra∎

The ordered candidate list is finite, and processing terminates for each candidate by step 1.2. The procedure returns the first successful candidate whose outward absolute-error bound meets εreq; if none does so, it returns inconclusive with the first recorded non-success reason, including requested-tolerance-not-met when all computed bounds exceed tolerance. Therefore every certified return has passed its finite checks, and the inconclusive branch returns no approximation certified to the requested tolerance.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Certified type-1 Gaussian gridding error and type-2 adjoint bound

Statement

Assume Countable Choice and the input hypotheses of Certified Gaussian gridding for type 1 and type 2. If N=0, the type-1 output is exactly zero and the type-2 output is empty, so their coordinatewise errors are zero. For N>0, fix a successful candidate with P=∏rMr, exact multipliers dk=∏rτrexp⁡(−πτrkr2), dmin⁡=∏rτrexp⁡(−πτrKr2)>0, sr=exp⁡(−πτrMr(Mr−2Kr)), and the exact spread-tail quantity Td of Explicit periodized Gaussian spread-tail bound. Put α=∏r=1d(1+2sr1−sr)−1,ϵ0=α+TdPdmin⁡. The algorithm returns an outward upper bound ϵana≥ϵ0.

For a type-1 output center array F^ and its returned finite-arithmetic radius Bround, ∥F^−F∥∞≤ϵana∥c∥1+Bround. For the type-2 output center array g^ and its returned radius Bround∗, ∥g^−A∗f∥∞≤ϵana∥f∥1+Bround∗, where Ak,j=e−2πik⋅xj is the exact type-1 matrix and A∗ is its conjugate transpose. When N=0, the type-2 output is empty and its coordinatewise assertion is vacuous; the procedure returns zero radius for this empty-output branch.

For fixed d, widths wr≤w, image cutoffs Lr≤L, and fixed interval-series controls, one candidate's scalar grid/FFT/deconvolution work is O ⁣(Plog⁡P+N∏r=1d(2wr+1)∑r=1d(2Lr+1)+∣K∣). Thus for bounded w,L it is O(Plog⁡P+Nwd), apart from the explicitly counted finite elementary-range evaluation work. No type-3 fast-cost claim follows.

Facts & Assumptions

Given: Countable Choice; finite dyadic input data; a successful type-1 or type-2 algorithm output for an exact positive requested tolerance; the selected operationwise model and its valid unit-roundoff bound u≤1/16; positive interval-certified Gaussian deconvolution multipliers; all FFT twiddle certificates verified at ϵtw≤1/4 using the stated positive phase tolerance, phase precision range and finite recursion cap; no FFT, interval, or range failures; and the same τr,Mr,wr,Lr used by the procedure.

[A1]

The Axiom of Countable Choice (ACω): Countable Choice is inherited through the Schwartz Poisson-summation supplier used by the alias identity.

[F1]

Type-1, type-2, and type-3 nonuniform Fourier transforms: the exact type-1 matrix is Ak,j=e−2πik⋅xj and type 2 is A∗f.

[F2]

Exact Gaussian grid alias identity and explicit alias bound: the full periodized-grid factorization has entrywise alias error at most α=∏r(1+2sr/(1−sr))−1.

[F3]

Explicit periodized Gaussian spread-tail bound: for each source column, deleting grid cells outside its product neighborhood removes at most Td of nonnegative kernel mass.

[F4]

Explicit tail for the periodized Gaussian image sum, Certified real elementary-function evaluations enclose their ranges, and Outward-rounded operations are inclusion-isotone and enclose DAG evaluations: each finite image sum plus its symmetric remainder interval encloses the exact periodized kernel, and every finite interval operation preserves that enclosure.

[F5]

Computed unitary radix-two FFT has the multiplicative stage error bound: for a successful length-2q unitary FFT in the selected operationwise model, with u≤1/16 and every returned twiddle certificate checked to be at most ϵtw≤1/4, its normwise error factor is ρq=(1+10u+ϵtw)q−1; inverse mode has the same bound.

[F6]

Finite Parseval and Plancherel identity for the unitary DFT: every exact unitary finite DFT preserves the Euclidean ℓ2 norm; coordinate restriction cannot increase that norm.

[F7]

Certified Gaussian gridding for type 1 and type 2: the type-1 centers are extracted at signed-mode slots κ(k)=(kr mod Mr)r after the checked computed FFT, and their returned coordinate radii are upward sums rk=ru⁡(bk+RFFT), where bk encloses the computed scaling/deconvolution rectangle and RFFT≥ρU/(P dmin⁡−). These radii enclose the exact deconvolution of that dyadic center grid; the separate grid-center contribution is bounded by Eeval/(P dmin⁡−).

[F8]

The radix-two FFT uses O(Nlog⁡2N) complex arithmetic operations: one radix-two transform of length Mr=2qr uses O(Mrlog⁡2Mr) arithmetic operations.

[F9]

Certified Gaussian gridding for type 1 and type 2, Outward-rounded operations are inclusion-isotone and enclose DAG evaluations, and Certified real elementary-function evaluations enclose their ranges: on a successful candidate the reported ϵana is an outward upper bound for A+Td/(Pdmin⁡), and the type-1 Bround adds the finite interval/FFT radius to Eeval/(Pdmin⁡−).

[F10]

Type-1, type-2, and type-3 nonuniform Fourier transforms: every k∈K satisfies ∣kr∣≤Kr.

[F11]

Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm: the natural logarithm is strictly increasing and log⁡1=0.

[F12]

Finite complex-array norms used by the NUFFT certificates: the finite-array norms are the displayed sums and maximum, with value zero on the empty index set.

[F13]

Certified Gaussian gridding for type 1 and type 2: type 2 embeds each signed mode k into the unique slot κ(k), applies the checked inverse unitary FFT, and its output intervals enclose the exact finite conjugate-transpose factorization; the returned radius is the maximum coordinate radius.

[F14]

Real elementary functions and their domains: π=4∫01(1+t2)−1 dt≥2>0.

[F15]

The exponential function is strictly increasing, The exponential is positive and satisfies exp⁡(−x)=1/exp⁡(x), and Nonnegative real square roots exist uniquely: for τr>0 the factors τr and e−πτrKr2 are positive, and kr2≤Kr2 implies e−πτrkr2≥e−πτrKr2; hence dk≥dmin⁡>0.

[F16]

The logarithm to a positive base other than one: log⁡2x=log⁡x/log⁡2 for x>0.

[F17]

Certified Gaussian gridding for type 1 and type 2: the empty-source branch returns exact zero type-1 output, empty type-2 output, and zero radii.

[F18]

Triangle inequality for the finite NUFFT Euclidean norm: the counting Euclidean norm satisfies the triangle inequality.

[F19]

Rectangular matrix multiplication and the identity matrix In, including zero-sized shapes: products of finite matrices have entries given by finite sums over their shared index set.

[F20]

Periodized Gaussian gridding kernel: every exact spread matrix entry is real, because the Gaussian kernel is a product of sums of real nonnegative exponential terms.

[F21]

Conjugation is an involutive real-field automorphism, zz‾=∣z∣2, and modulus is definite, multiplicative, and subadditive: complex modulus is nonnegative and is multiplicative and satisfies the triangle inequality.

[F22]

exp⁡(x+iy)=ex(cos⁡y+isin⁡y), ∣exp⁡(x+iy)∣=ex, and eiπ+1=0: every grid Fourier phase has modulus one, hence ∣Qkℓ∣=P−1.

[F23]

Squaring is monotone on the nonnegatives: for nonnegative reals a,b, a2≤b2 implies a≤b.

[F24]

Certified Gaussian gridding for type 1 and type 2: step 2 generates each Wj,r by enumerating the finite integer interval [⌈Mrxj,r−wr⌉,⌊Mrxj,r+wr⌋] and reducing its entries modulo Mr.

Proof

1.1A1F1F2F3F9F10F12F14F15F17F19F21F22algebra

If N=0, [F17] and the finite sums in [F1] give exact zero type-1 output and an empty type-2 output; [F12] assigns zero to empty norms, so both error assertions hold with zero radii. For the remaining proof assume N>0. Let S∞ be the full spread matrix with entries (S∞)ℓj=Φτ(ℓ1/M1−xj,1,…,ℓd/Md−xj,d), and let S keep only the entries in each source's product neighborhood. Define the mode-by-grid matrix Qkℓ=P−1e−2πi∑rkrℓr/Mr and the diagonal mode matrix Dkk=dk, with Dkk−1=1/dk by the positive-multiplier premise. The products below use the finite matrix multiplication of [F19]. The normalized grid sum in [F2], applied to the unit source vector ej, says that every entry of D−1QS∞−A has modulus at most α. For each column j, [F3] bounds the sum of the nonnegative deleted entries by Td; since ∣Qkℓ∣=P−1, it follows that ∣(Q(S∞−S))kj∣≤Td/P. By [F10], ∣kr∣≤Kr, and [F14]–[F15], dk≥dmin⁡>0, so ∣(D−1Q(S∞−S))kj∣≤Td/(Pdmin⁡). Adding the two matrix differences gives ∣(D−1QS−A)kj∣≤ϵ0 for every k,j. For each row, multiplication by c and the complex modulus laws [F21] give ∣((D−1QS−A)c)k∣≤ϵ0∑j∣cj∣, hence ∥(D−1QS−A)c∥∞≤ϵ0∥c∥1 by [F12]. Finally [F9] gives ϵ0≤ϵana for the returned outward bound.

2.1F4F5F6F7F9F10F12F14F15F18F21F23step 1.1algebra

Let g=Sc be the exact truncated spread and u the dyadic center grid computed by the algorithm. The finite image sums and symmetric remainder intervals enclose every exact kernel by [F4]; isotonicity of the outward DAG operations then gives ∥g−u∥2≤Eeval, with norms as in [F12]. By [F18], the counting Euclidean norm has the triangle inequality. For coordinate axis r, regard its P/Mr length-Mr FFTs as one block-diagonal operator. Squaring and summing the linewise supplier bound [F5] gives a normwise error at most ρr times the block input norm; the exact block transform is unitary by [F6]. If xr and yr are the computed and exact outputs after axes 1,…,r, the triangle inequality [F18], the local error bound and unitarity give ∥xr∥2≤(1+ρr)∥xr−1∥2 and ∥xr−yr∥2≤∥xr−1−yr−1∥2+ρr∥xr−1∥2. Starting with x0=y0=u and iterating gives ∥xd−yd∥2≤U∑r=1dρr∏s<r(1+ρs)=U(∏r(1+ρr)−1)=ρU. For each extracted coordinate, the FFT discrepancy has modulus at most ρU, since a coordinate modulus is bounded by the Euclidean norm. The exact scaling by P−1/2 and exact division by the mode multiplier therefore make its deconvolved discrepancy at most ρU/(P dk)≤ρU/(P dmin⁡−), using [F15] and 0<dmin⁡−≤dmin⁡≤dk. By [F4], the computed scaling/deconvolution rectangle encloses the exact scaling/deconvolution of the computed FFT coordinate, so its distance from the returned lower-left center is at most bk. The algorithm forms RFFT outward from the actual input norm bound and the verified call factors; [F7] and the complex triangle inequality [F21] then give distance at most bk+RFFT≤rk from that center to the exact deconvolution of the dyadic center grid. This justifies the full containment claimed in [F7], including the previously omitted computed FFT error. To transfer the grid-center enclosure, define UP as the exact unitary DFT on the full rectangular grid and Rκ as restriction to the slots κ(k). Since Mr>2Kr, two modes in [−Kr,Kr] with the same residue differ by a multiple of Mr of magnitude less than Mr, hence are equal; coordinatewise, κ is injective. The grid transform in step 1.1 is Q=P−1/2RκUP. For any finite array z, each ∣zk∣2 is a nonnegative summand of ∑ℓ∣zℓ∣2, so [F12] and [F23] give ∥z∥∞≤∥z∥2. Parseval and contraction under coordinate restriction in [F6] then yield ∥Q(u−g)∥∞≤∥Q(u−g)∥2≤Eeval/P. By [F10], [F14] and [F15], each dk≥dmin⁡. Thus the additional deconvolution error is at most Eeval/(Pdmin⁡). The algorithm defines Bround=max⁡krk+Eeval/(Pdmin⁡−); using dmin⁡−≤dmin⁡, taking the maximum returned rk and adding its grid-center term gives the asserted radius.

3.1F1F9F19F21step 1.1step 2.1algebra

By [F19], the finite gridding matrix is A~=D−1QS. Step 1.1 bounds its analytic discrepancy by ϵana∥c∥1, and step 2.1 bounds the finite-arithmetic discrepancy from A~c by Bround. The coordinatewise complex triangle inequality [F21], followed by taking the finite maximum, gives ∥F^−Ac∥∞≤ϵana∥c∥1+Bround, and [F1] identifies Ac=F.

3.2F1F4F5F6F12F13F14F15F18F19F20F21step 1.1step 2.1algebra

The type-2 exact finite matrix computed by the algorithm is A~∗. By [F19], (A~)kj=dk−1∑ℓQkℓSℓj. Since dk and Sℓj are real by [F14]–[F15] and [F20], conjugating this entry gives dk−1∑ℓQkℓ‾Sℓj; this is exactly the (j,k) entry of S∗Q∗D−1 by the same finite-product formula. In the slot notation of step 2.1, Q∗=P−1/2UP∗Rκ∗, where Rκ∗ embeds a mode vector into the grid slots κ(k) and zero-fills every other slot; this is the inverse-FFT construction in step 4. Thus A~∗=S∗Q∗D−1. Step 1.1 gives ∣(A~−A)kj∣≤ϵ0 for each entry, so the complex modulus laws [F21] give ∣((A~∗−A∗)f)j∣≤∑k∈K∣(A~−A)kj∣ ∣fk∣≤ϵ0∥f∥1. It remains to bound the finite-arithmetic discrepancy. Let v=D−1f be the exact deconvolved mode vector and vc the dyadic centers of the component rectangles computed in step 4 of the algorithm. That step defines Ef,V with ∥v−vc∥2≤Ef and ∥vc∥2≤V by [F12]–[F13]. The positive-sign computed unitary FFT has axis error factors ρr and total ρ=∏r(1+ρr)−1; its bound is the same as the type-1 calculation in step 2.1 because [F5] gives the same factor for the conjugated inverse routine. Thus its computed center differs from the exact transform of the embedded vc by at most ρV, since zero-fill embedding preserves the Euclidean norm. The exact unitary transform preserves the embedded input uncertainty norm by [F6], so [F18] bounds the computed FFT center's distance from the exact transform of embedded v by Ef+ρV. After scaling by P−1/2, each used grid coordinate is therefore within (Ef+ρV)/P of the exact Q∗v coordinate. The algorithm encloses this discrepancy, evaluates every real spread-window coefficient with a finite image interval containing its exact value by [F4] and [F20], and applies only sound outward rectangle operations. Hence the final rectangle at source j contains (S∗Q∗D−1f)j=(A~∗f)j; its center has error at most its radius rj. Taking the maximum over the finite output set gives ∥g^−A~∗f∥∞≤Bround∗. Combining this finite bound with the displayed analytic entry estimate proves the type-2 claim, using [F12] for the finite norms.

4.1givenF8F11F16F24algebra∎

There are P/Mr length-Mr transforms on axis r, so [F8] gives O(Plog⁡2Mr) work on that axis. Since 1≤Mr≤P and 2>1, [F11] gives log⁡2>log⁡1=0. Formula [F16] therefore shows that log⁡2 is increasing on positive arguments, hence log⁡2Mr≤log⁡2P; fixed d gives O(Plog⁡P) over all axes. By [F24], forming the coordinate neighborhoods takes O(∑r(2wr+1)) index operations per source and produces at most ∏r(2wr+1) retained product cells. For fixed d and Lr≥1, the support-generation cost is bounded by the displayed per-source grid term. Evaluating its coordinatewise image sums costs at most a constant multiple of ∑r(2Lr+1) per retained product cell, and the mode deconvolution pass costs O(∣K∣); interval-series evaluator internals are excluded as stated. These counts yield the displayed bound. This analysis covers types 1 and 2 only; the type-3 frequency ranges require separate scaling and work estimates.

5 · Examples, counterexamples and false statements

None yet.

Sources