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Gaussian Fourier summability at Lebesgue points

Statement

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

Facts & Assumptions

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

[F1]

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

[F2]

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

[F3]

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

[F4]

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

[F5]

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

Proof

1.1

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

F1F2F4F5given
2.1

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

F2F3F5step 1.1

Depends on

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Sources