Alphabeta Math
LemmaStatement: AI-adaptedProof: 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.

Weak graph limits preserve zero tangential H(curl)

Statement

Assume Countable Choice. Let Ω⊂R3 be a bounded open set. Suppose un∈H0(curl⁡;Ω), un→u strongly in L2(Ω;R3), and sup⁡n∥curl⁡un∥2<∞. Then a subsequence of the curls converges weakly in L2 to curl⁡u, the limit u belongs to H(curl⁡;Ω), and in fact u∈H0(curl⁡;Ω).

Facts & Assumptions

Given: Countable Choice; the bounded open set Ω; the distributional graph-space definition; and the sequence in the statement.

[A1]

Countable Choice is the stated hypothesis of the weak-subsequence supplier. (The Axiom of Countable Choice (ACω))

[F1]

L2(Ω;R3) is a separable real Hilbert space: the scalar L2 space on a bounded measurable set is separable and Hilbert, and a finite product of separable Hilbert spaces is separable and Hilbert. (L2 controls on a bounded spatial region form a separable Hilbert space, L2 with the integral pairing is a Hilbert space)

[F2]

Every bounded sequence in a separable real Hilbert space has a weakly convergent subsequence. (A bounded sequence in a separable Hilbert space has a weakly convergent subsequence)

[F3]

The distributional curl is characterized by ∫Ωcurl⁡v⋅φ dx=∫Ωv⋅curl⁡φ dx for every compactly supported smooth test vector field φ. (The real H(curl) graph space on a polyhedron)

[F4]

H0(curl⁡) is a norm-closed linear subspace of the H(curl⁡) graph Hilbert space, by its closure definition; a closed subspace of a Hilbert space is the orthogonal complement of its orthogonal complement. (Zero tangential trace H(curl) space, Orthogonal decomposition by a closed subspace)

Proof

Given: The sequence and assumptions in the statement.

1.1F1F3givenalgebra

The graph of distributional curl is closed in L2(Ω;R3)×L2(Ω;R3): if vj→v and curl⁡vj→w in L2, [F3] gives ∫Ωw⋅φ dx=∫Ωv⋅curl⁡φ dx for each test φ, so curl⁡v=w. By [F1] the product is Hilbert, hence its closed graph is Hilbert with the graph inner product. Thus H(curl⁡;Ω) is a Hilbert space.

1.2A1F1F2F3step 1.1choose

The curls are bounded in the separable Hilbert space of [F1]. By [F2] choose a subsequence, still indexed by n, with curl⁡un⇀w weakly in L2. For every test φ, strong convergence of un and [F3] give ∫Ωw⋅φ dx=lim⁡n∫Ωcurl⁡un⋅φ dx=lim⁡n∫Ωun⋅curl⁡φ dx=∫Ωu⋅curl⁡φ dx. Therefore curl⁡u=w distributionally and u∈H(curl⁡).

2.1F4step 1.2algebra∎

The strong convergence of un and weak convergence of their curls show that un⇀u in the graph Hilbert space: for every v∈H(curl⁡), ⟨un,v⟩H(curl⁡)=(un,v)L2+(curl⁡un,curl⁡v)L2⟶(u,v)L2+(w,curl⁡v)L2=⟨u,v⟩H(curl⁡). For every y∈H0(curl⁡)⊥, each ⟨un,y⟩H(curl⁡)=0; weak convergence gives ⟨u,y⟩H(curl⁡)=0. By [F4], u∈(H0(curl⁡)⊥)⊥=H0(curl⁡).

Depends on

Used by

Dependency tree · two levels

39 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