Alphabeta Math
TheoremStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-13
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Convolution with a test function is smooth

Statement

Let u∈D′(Ω) and φ∈D(Rn). On the open safe domain V={x:x−supp⁡φ⊆Ω}, the convolution u∗φ is smooth and ∂α(u∗φ)=(∂αu)∗φ=u∗(∂αφ). The last expression is restricted to V if its own safe domain is larger. For Ω=Rn the domain is all of Rn. This holds in ZF.

Facts & Assumptions

[F1]

The convolution is u∗φ(x)=u(φ(x−⋅)) on its open safe domain (Convolution of a distribution with a test function).

[F2]

A smooth parameter family with locally common compact test support pairs smoothly with a distribution, and parameter derivatives pass through the pairing (Distribution pairing with smooth parameter families).

[F3]

Distribution derivatives act by signed test differentiation (Distributional derivative).

Proof

Given: u,φ,V as in the statement.

1.1givenF1F2

Put S=supp⁡φ. For compact H⊆V, all y-supports of F(x,y)=φ(x−y), x∈H, lie in H−S. This is compact as the continuous image of the compact product H×S, and it lies in Ω by the definition of V. The function F is jointly smooth, so F2 gives smoothness of u∗φ and ∂xα(u∗φ)(x)=u((∂αφ)(x−⋅)).

2.1step 1.1F1F3algebra

Differentiating the reflected test in y gives ∂yαφ(x−y)=(−1)∣α∣(∂αφ)(x−y). F3 therefore gives (∂αu)∗φ(x)=(−1)∣α∣u(∂yαφ(x−⋅))=u((∂αφ)(x−⋅)), since the two signs multiply to one. Together with step 1.1 this proves both equalities.

3.1step 2.1F1

The support of ∂αφ is contained in S, so its safe domain contains V, justifying the stated restriction. If φ=0, the safe domain is all of Rn and each expression is zero. If V is empty the smoothness and equalities are vacuous on that open set; α=0 gives the defining convolution identity. No choice is used. □

Depends on

Used by

Dependency tree · two levels

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Sources