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 implicit-midpoint collocation for a nonlinear BVP
Definition
Fix a uniform mesh and the open nodal domain and normalized residual from Normalized implicit-midpoint collocation residual for a two-point BVP. If and are on the required domains (total differentiability with continuous derivative entries), then is a square map from the open subset into . Given an initial node vector , tolerance , and correction budget , apply Finite-budget Newton for a square vector residual to using its exact Jacobian. Return the last node vector and its root, singular-jacobian, invalid-trial, or iteration-budget-exhausted status as defined by that procedure. A root status means only that ; it is not a branch, convergence, or error certificate.
Depends on
Used by
- Finite-budget phase-fixed periodic-orbit correction and validation Algorithm
- Local Newton convergence on the selected midpoint collocation branch Corollary
- Multiple-shooting and midpoint-collocation residuals for a phase-fixed periodic orbit Definition
- A midpoint BVP residual can have two simple solution branches Example
Dependency tree · two levels
7 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
- T. A. Driscoll and R. J. Braun, Fundamentals of Numerical Computation, Chapter 10 (standard reference, not scraped)