Alphabeta Math
LemmaStatement: Literature-sourcedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-12
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.

Gaussian smoothing of finite measures

Statement

Assume AC. Let μ be a finite complex Borel measure of finite variation on Rn, n≥1. For t>0 define ht(x)=∫kt(x−y) dμ(y) using the Gaussian kernel. Then ht∈L1, ∥ht∥1≤∣μ∣(Rn), and h^t=k^t μ^. For every complex φ∈Cc(Rn), ∫φ(x)ht(x) dx⟶∫φ dμ.

Facts & Assumptions

[F1]

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

[F3]
[F5]

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

[F6]

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

[F7]

Translation has transform multiplier e−2πiy⋅ξ (Translation, modulation, linear dilation and reflection laws).

Proof

1.1F1F2F3given

Put v=∣μ∣. The inequality ∣μ(E)∣≤v(E) gives μ≪v; v is finite, hence sigma-finite. F1 gives μ=uv with u∈L1(v), and F2 gives v(E)=∫E∣u∣ dv, in particular ∫∣u∣ dv=v(Rn). For any bounded measurable H, ∫H dμ=∫Hu dv: first verify this for simple H using the density formula on sets, then approximate bounded H uniformly by quantizing its real and imaginary values. F3 bounds the error on the left by v(Rn)∥H−Hm∥∞, and the right error by ∥u∥1∥H−Hm∥∞. AC enters F1 through the signed RN/Hahn/Jordan existence selections; it also covers the existence assumption omitted in the older F2 proof.

2.1F4F5F7step 1.1

Consequently ht(x)=∫kt(x−y)u(y) dv(y), absolutely at every x because k_t is bounded and u integrable. The joint function is Borel measurable. By F4, F5 and translation invariance, its double absolute integral is ∫∣u(y)∣[∫kt(x−y) dx]dv(y)=v(Rn). Fubini therefore supplies a measurable integrable h_t and its stated norm bound. With the additional modulus-one Fourier factor the same double bound applies. F4 and F7 give h^t(ξ)=k^t(ξ)∫e−2πiy⋅ξu(y) dv(y)=k^t(ξ)μ^(ξ) by step 1.1.

3.1F4F5F6step 1.1step 2.1∎

For a compactly supported continuous φ, the double absolute integral after multiplication by φ(x) is at most ∥φ∥∞v(Rn). F4 exchanges the integrals. Since k_t is even, the inner test integral is (kt∗φ)(y), and F6 gives uniform convergence to φ(y). Thus the difference from ∫φu dv has modulus at most ∥kt∗φ−φ∥∞∥u∥L1(v)→0. Step 1.1 identifies the limit with ∫φ dμ.

Depends on

Dependency tree · 2 levels

Sources