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.
A smooth finite-variation integrand and its deterministic error bound
Example
On , take and the one-point set . Then so the Koksma–Hlawka bound is valid for this smooth integrand.
Facts & Assumptions
Given: The function on the unit square and the point set containing .
For functions, upper-anchor Hardy–Krause variation is the sum of the integrals of the absolute mixed derivatives on all nonempty upper faces. (Mixed-derivative formula for smooth Hardy–Krause variation)
The unit square has volume ; grid cells' volumes sum to that volume, and for the constant-one function every lower and upper Darboux sum equals the sum of the cell volumes, so its integral is . (Axis-parallel rectangles in and their volume, Grid partitions of a rectangle in , their cells, refinements and mesh, Lower and upper Darboux sums over a grid partition in , The lower and upper Darboux integrals over a nondegenerate rectangle in )
A continuous function on the square is Riemann integrable, and its integrable sections have iterated integrals equal to the multiple integral. (Every continuous function on a closed nondegenerate rectangle in is Riemann integrable, Riemann--Fubini on product rectangles, with lower and upper section integrals and content-zero exceptional sections)
Star discrepancy is the supremum over of the absolute difference between the fraction of nodes in and its volume. (Star discrepancy, digital nets, and digital sequences)
If is continuous on , differentiable on , and its interior derivative has a Riemann-integrable extension, then its integral is . (Newton–Leibniz needs only continuity on , differentiability on , and a Riemann-integrable extension of the interior derivative)
For a finite nonempty point multiset and an integrand of finite upper-anchor Hardy–Krause variation, . (Koksma–Hlawka integration bound with upper-anchor variation)
Verification
The upper faces are and , and the full mixed derivative is . By [F1], ; the one-dimensional integrals and the square integral of equal the respective volumes by [F2].
At the point is excluded from the half-open anchored box, so the discrepancy there is . If or , the box is empty and its volume is at most . If both coordinates exceed those thresholds, the box contains the point and its error is ; values approach as . Thus . Also . By [F3], the double integral equals the iterated Riemann integral, and [F5] evaluates it as .
The error is , consistent with [F6].
Depends on
- Star discrepancy, digital nets, and digital sequences
- The lower and upper Darboux integrals over a nondegenerate rectangle in $\mathbb{R}^m$
- Axis-parallel rectangles in $\mathbb{R}^m$ and their volume
- Grid partitions of a rectangle in $\mathbb{R}^m$, their cells, refinements and mesh
- Lower and upper Darboux sums over a grid partition in $\mathbb{R}^m$
- Hardy–Krause variation anchored at the upper corner
- Mixed-derivative formula for smooth Hardy–Krause variation
- Koksma–Hlawka integration bound with upper-anchor variation
- Newton–Leibniz needs only continuity on $[a,b]$, differentiability on $(a,b)$, and a Riemann-integrable extension of the interior derivative
- Every continuous function on a closed nondegenerate rectangle in $\mathbb{R}^m$ is Riemann integrable
- Riemann--Fubini on product rectangles, with lower and upper section integrals and content-zero exceptional sections
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
60 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 Book: The Quasi-Monte Carlo Parts, Chapter 15 §15.4 and end notes (standard reference, not scraped)
- Harald Niederreiter, Random Number Generation and Quasi-Monte Carlo Methods, Chapter 2 §2.2 (standard reference, not scraped)
- Lukas Einkemmer, Quasi-Monte Carlo Methods, §2.3 (standard reference, not scraped)