Alphabeta Math
TheoremStatement: Literature-sourcedProof: AI-adaptedPipeline-generatedprecheck passjudge pass (gpt-6-luna)
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.

Matérn interpolation and its power function converge at rate h^ν

Statement

Assume full AC conservatively for the Hilbert projection and weighted-L2 suppliers. Fix arbitrary d≥1, ν>0, a>0, s=ν+d/2, the normalized Matérn kernel k of The normalized Matérn kernel in the 2π Fourier convention, and an admitted uniform-cone domain Ω. There are constants C,h0>0, depending only on d,ν,a and the domain's cone constants, such that for every finite nonempty distinct site set X⊂Ω with fill distance hX≤h0 and every f∈Hs(Ω), ∥f−sXf∥L∞(Ω)≤ChXν∥f∥Hs(Ω),sup⁡x∈ΩPX(x)≤ChXν. Here sXf and PX are the native interpolant and power function of Native Matérn interpolation is an orthogonal projection with power function. The rate requires no mesh-ratio bound. The constants are uniform over site sets satisfying the fill-distance condition.

Facts & Assumptions

Given: Full AC, the fixed kernel and domain, a finite distinct set X, its fill distance hX≤h0, and f∈Hs(Ω).

[F1]

The restricted native norm and restriction-quotient Sobolev norm satisfy c∥u∥Hs(Ω)≤∥u∥Hk(Ω)≤C∥u∥Hs(Ω). (The restricted Matérn native space is the Sobolev quotient space)

[F2]

A Sobolev function vanishing on X obeys ∥u∥∞≤ChXν∥u∥Hs(Ω) on the uniform-cone domain, without a separation assumption. (A Sobolev function vanishing on scattered sites has an h^ν bound)

[F3]

Native interpolation is an orthogonal projection, its residual vanishes on X, and its pointwise error is bounded by PX(x) times the native norm. (Native Matérn interpolation is an orthogonal projection with power function)

[F4]

The Cauchy-sequence reals have the least-upper-bound property and are a complete ordered field; hence the Archimedean theorem supplies an integer m>ν for the fixed real ν. (The Cauchy-sequence reals have the least-upper-bound property, Every complete ordered field is Archimedean)

[A1]

Full AC is carried conservatively for the inherited Hilbert-space suppliers; the estimate makes no additional choice from an indexed family. (The Axiom of Choice, The Axiom of Countable Choice (ACω))

Proof technique: apply the zeros estimate to the native projection residual.

Proof

technique · apply the zeros estimate to the native projection residual

Given: The hypotheses above.

1.1F1F2F3F4A1algebra

By [F4] choose an integer m>ν and apply the zeros estimate [F2] with this fixed m. Regard f as an element of the same set of continuous restrictions Hs(Ω)=Hk(Ω) using [F1], and let e=f−sXf. By [F3], e∣X=0 and ∥e∥Hk(Ω)≤∥f∥Hk(Ω). Therefore [F1] and [F2] give ∥e∥L∞(Ω)≤C0hXν∥e∥Hs(Ω)≤C0c−1hXν∥e∥Hk(Ω)≤C0c−1C1hXν∥f∥Hs(Ω). This is the first estimate.

2.1F1F2F3step 1.1algebra∎

Fix x∈Ω and set rx=(I−ΠX)k(⋅−x), so PX(x)=∥rx∥. Self-adjointness and reproduction in [F3] give f(x)−sXf(x)=⟨f,rx⟩. The bound in [F3] shows that this residual evaluation functional has norm at most PX(x). If rx=0, it is the zero functional and its norm is PX(x)=0. If rx≠0, the unit vector fx=rx/∥rx∥ satisfies fx(x)−sXfx(x)=⟨fx,rx⟩=∥rx∥=PX(x), so the functional norm is exactly PX(x). Applying step 1.1 to every f of native norm at most one therefore gives PX(x)≤C2hXν, uniformly in x; taking the supremum proves the second estimate. The constant does not depend on X except through the upper bound on hX, and no mesh ratio entered either [F2] or this argument.

Depends on

Used by

Dependency tree · two levels

43 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