Alphabeta Math
CorollaryStatement: AI-adaptedProof: AI-generatedPipeline-generatedprecheck pendingjudge 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.

An elliptic reduced-gradient L2 rate follows under dual approximation

Statement

Assume Countable Choice and the Galerkin and adjoint hypotheses of Conforming elliptic finite-element reduced gradients have an energy-norm error budget. Suppose the adjoint regularity and dual approximation assumptions of The h^(r+s) L² rate under primal and dual approximation hold separately for the state and adjoint equations, giving ∥u−uh∥L2≤Cuhr+s,∥p−ph∥L2≤Cphr+s for 0<h≤1, r≥1, and s∈(0,1]. Assume the parameter derivative operators satisfy ∣ℓθ′[η](v)∣≤Mℓ0∥η∥2∥v∥L2,∣aθ′[η](v,w)∣≤Ma0∥η∥2∥v∥L2∥w∥L2. Assume the discrete derivative maps in Conforming elliptic finite-element reduced gradients have an energy-norm error budget have compatible L2 extensions and constants CJ,Cℓ,Ca independent of h give, for every ∥η∥2≤1, a direct-objective derivative defect at most CJhr+s, an L2-dual load-derivative defect at most Cℓhr+s, and a bilinear derivative defect at most Cahr+s∥v∥L2∥w∥L2. Then the reduced-gradient error is O(hr+s). This rate requires those extra L2-bounded parameter derivative maps; the energy-norm result alone does not imply it.

Facts & Assumptions

Given: The energy-norm reduced-gradient setting, the stated dual regularity bounds for the state and adjoint, Countable Choice, and the displayed L2 derivative bounds.

[F1]

The Aubin–Nitsche estimate gives an hr+s L2 error under its stated primal and dual approximation hypotheses (The h^(r+s) L² rate under primal and dual approximation).

[F2]

The energy-norm reduced-gradient bound separates state error, adjoint error, and derivative-data defects (Conforming elliptic finite-element reduced gradients have an energy-norm error budget).

[A1]

Countable Choice (The Axiom of Countable Choice (ACω)) and the dual regularity and interpolation hypotheses hold separately for the continuous and adjoint Galerkin equations, with the constants displayed in the Statement; derivative-data and direct-objective defects are O(hr+s) in the stated L2 operator norms.

Proof

1.1F1A1given

Apply [F1] to the state equation and to the adjoint equation with the transposed coercive form. Under [A1], this yields the two displayed L2 error bounds. Countable Choice is required by [F1].

2.1givenstep 1.1algebra

The parameter-derivative bounds in the Statement give ∣ℓθ′[η](ph−p)∣≤Mℓ0∥η∥2Cphr+s and, by adding and subtracting aθ′[η](u,ph), ∣aθ′[η](uh,ph)−aθ′[η](u,p)∣≤Ma0∥η∥2(Cuhr+s∥ph∥L2+∥u∥L2Cphr+s). The L2 norms of u and ph are bounded by the stated state bounds and ∥ph∥L2≤∥p∥L2+Cphr+s.

3.1A1F2step 2.1∎

Apply the exact gradient subtraction in [F2]. The direct-objective and derivative-data defects contribute their assumed O(hr+s) bounds; step 2.1 bounds the state- and adjoint-dependent terms by constants times hr+s. Taking the supremum over ∥η∥2≤1 proves the asserted rate. If the L2 derivative bounds or either dual approximation hypothesis fails, this rate has not been proved.

Depends on

Used by

Nothing in the library uses this result yet.

Dependency tree · two levels

22 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