Alphabeta Math
AlgorithmAlgorithm: Literature-sourcedProof: Not applicablePipeline-generatedprecheck pending
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.

Finite-budget single shooting for a nonlinear two-point BVP

Definition

Let U⊆Rd be the open trial-initial-state set. Let DB⊆Rd×Rd be the open domain of the C1 boundary map B, where C1 means total differentiability with continuous derivative entries. Inputs are a certified evaluator from Certified differentiable IVP approximation interface for shooting, an initial trial s0∈U, residual tolerance τ≥0, and a correction budget M∈N0. The evaluator may return failure on a queried trial. Every successful response must supply the approximate trajectory, the endpoint Φ~(s) and the exact derivative DΦ~(s) of the declared C1 numerical endpoint map, with the interface's stated uniform trajectory-error bound. Success on every queried trial is not an input assumption.

For k=0,1,…,M, in this order:

  1. Query the evaluator at sk. If it fails, return the last accepted trial with status evaluator-failure and no residual certificate. Before evaluating B, check (sk,Φ~(sk))∈DB; if this fails or cannot be established, return the last accepted trial with status invalid-endpoint-pair and no residual certificate. On success form R~(sk)=B(sk,Φ~(sk)) and DR~(sk)=D1B(sk,Φ~(sk))+D2B(sk,Φ~(sk))DΦ~(sk) using Derivative of the nonlinear shooting residual. A failure to evaluate these quantities returns evaluator-failure without a residual certificate.
  2. If ∥R~(sk)∥2≤τ, return sk, its approximate trajectory, and status root-tolerance-met. This status asserts only the displayed residual tolerance.
  3. If k=M, return the last trial and status iteration-budget-exhausted.
  4. Call Newton correction for a square vector residual with A=DR~(sk) and r=R~(sk). If it reports singular-jacobian, stop with that status. Otherwise let uk be its returned correction.
  5. If the proposed trial sk+uk is outside U or its membership cannot be established, return the last accepted trial with status invalid-trial; otherwise accept sk+1=sk+uk. Initially the last accepted trial is s0; accepting a trial supplies no boundary residual certificate until step 1 succeeds there.

On a sequence of successful evaluations with endpoint pairs in DB, this has the same residual, singularity, trial-domain and budget checks as Finite-budget Newton for a square vector residual. It makes no global-start, exact-root, or discretization-error claim. The numerical residual is C1 on the open subset of U where (s,Φ~(s))∈DB; no boundary value is evaluated outside that subset.

Depends on

Used by

Dependency tree · two levels

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Sources