Alphabeta Math
LemmaStatement: Literature-sourcedProof: AI-adaptedPipeline-generatedjudge pass (gpt-6.1-sol)
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.

The Euler–Poisson–Darboux equation for spherical means

Statement

Assume the Axiom of Countable Choice, let n≥1, let f∈C2(Rn) and let M=Mf be the spherical mean of Spherical means and the weighted ball integral of space-dependent data. Then for every x∈Rn and r>0 ΔxM(x,r)=Mrr(x,r)+n−1rMr(x,r). The right-hand side extends continuously to r=0 with value Δf(x): with M(x,0):=f(x) one has Mr(x,r)→0 and (Mrr+n−1rMr)(x,r)→Δf(x) as r↓0. If u∈C2(Rn×I) is a classical solution of □cu=0 on an interval I, then its space-time mean (x,r,t)↦Mu(x,r,t):=ωn−1−1∫Sn−1u(x+rω,t) dσ(ω) satisfies ∂t2Mu=c2(Mrr+n−1rMr). No equation for f is needed for the identity itself.

Facts & Assumptions

Given: Countable Choice, n≥1, f∈C2(Rn), the spherical mean M=Mf with M(x,0)=f(x), and, when stated, a C2 solution u of □cu=0 on Rn×I.

[F1]

For k≥1 and h∈Ck(Rn), (x,r)↦Mh(x,r) is Ck on Rn×(0,∞) with all derivatives obtained by differentiating h under the sphere integral; it extends continuously to r=0 with Mh(x,0)=h(x), and its radial derivative tends to 0 uniformly on compacta (Smoothness, parity and zero-radius limits of spherical means).

[F2]

If g∈C2(Rn) and r>0, then ∂rMg(x,r)=rnAΔg(x,r), where AΔg(x,r)=∣Br(x)∣−1∫Br(x)Δg is the ball average (Radial derivative of a spherical average, The average of a locally integrable function over a Euclidean ball).

[F3]

For h∈C0(Rn) one has Mh(x,r)=Ah(x,r)+rn∂rAh(x,r) for all r>0 (Ball means and sphere means are related by a radial derivative).

Proof

1.1F1algebra

The spatial Laplacian passes under the sphere integral: by [F1] the map (x,r)↦M(x,r) is C2, and differentiating the defining integral twice in x, ΔxM(x,r)=ωn−1−1∫Sn−1Δf(x+rω) dσ(ω)=MΔf(x,r) for every r>0.

1.2F2F3algebra

Radial identities. Put A(x,r):=AΔf(x,r). Applying [F2] only to f gives Mr(x,r)=rnA(x,r). Since Δf is continuous, [F3] applied to Δf gives MΔf(x,r)=A(x,r)+rn∂rA(x,r). Differentiating the first identity in r gives Mrr(x,r)=1nA(x,r)+rn∂rA(x,r); therefore Mrr+n−1rMr=1nA+rn∂rA+n−1nA=A+rn∂rA=MΔf(x,r)=ΔxM(x,r). The radial-derivative formula is used only with the C2 function f; no differentiability of Δf is assumed.

1.3F4algebra

The limits at r↓0. For 0<r≤1 the bound ∣AΔf(x,r)∣≤sup⁡B1(x)∣Δf∣<∞ holds, the supremum being finite by [F4]; hence Mr(x,r)=rnAΔf(x,r)→0. Moreover the identity just proved gives Mrr(x,r)+n−1rMr(x,r)=MΔf(x,r)=ΔxM(x,r). Since Δf is continuous at x, ∣MΔf(x,r)−Δf(x)∣≤sup⁡ω∈Sn−1∣Δf(x+rω)−Δf(x)∣→0 as r↓0.

1.4F1algebra

The space-time version. If u∈C2 solves □cu=0, applying the differentiation-under-the-sphere-integral computation of [F1] to the C2 function (x,t)↦u(x,t) yields ΔxMu(x,r,t)=MΔxu(x,r,t) and ∂t2Mu(x,r,t)=Mutt(x,r,t) for all r>0 and t∈I. Since utt=c2Δu, this gives ∂t2Mu=c2MΔu=c2ΔxMu; and the identity of the first two steps applied to the C2 spatial function u(⋅,t) gives ΔxMu(x,r,t)=Mrr(x,r,t)+n−1rMr(x,r,t). Substituting, ∂t2Mu=c2(Mrr+n−1rMr).

2.1given∎

Collecting: the Euler–Poisson–Darboux identity holds for every C2 datum, its right-hand side has the stated continuous extension at r=0 with value Δf(x), and the space-time means of solutions satisfy the same radial equation with two time derivatives on the left.

Depends on

Used by

Dependency tree · two levels

65 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.

Sources