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.
Embedded Simpson refinement indicator
Definition
Let , let be even, and let be real-valued at the nodes of the uniform grids with and subintervals. The coarse Simpson value is and the refined value is , using Composite Simpson rule on an even uniform grid. The signed refinement indicator is and its magnitude is
For the local two-panel case , is also the sum of the two one-block Simpson values on the halves of .
This definition alone is not a bound on the true error.
For data supplied only at the grid nodes, the calls to the Simpson procedure mean calls on the extension that agrees with those data at the nodes and is zero elsewhere. This extension is evaluable everywhere as required by the procedure. Its finite sums use only the prescribed nodes, so any other evaluable extension gives the same , and indicator; no off-grid values or regularity are required.
Remarks
The factor has asymptotic Richardson justification under the hypotheses of Conditional asymptotic validity of the Simpson /15 indicator; it remains a heuristic indicator at any finite grid.
Depends on
Used by
- Finite-depth adaptive Simpson with an indicator Algorithm
- A narrow peak reaches the adaptive Simpson depth cap Example
- Cancellation of the leading Simpson error coefficient Example
- The Simpson indicator misses a feature between its sample nodes Example
- Conditional asymptotic validity of the Simpson /15 indicator Theorem
- Termination and indicator bookkeeping for capped adaptive Simpson Theorem
Dependency tree · two levels
2 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
- Art B. Owen, Monte Carlo Theory, Methods and Examples, Chapter 7, §7.2 (standard reference, not scraped)
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, §§5.6–5.7 (standard reference, not scraped)
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, §5.6 (standard reference, not scraped)