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.
The Simpson indicator misses a feature between its sample nodes
Example
On , let The root indicator is zero, so for every the call to Finite-depth adaptive Simpson with an indicator with and accepts its root panel and returns estimate . Choose ; for this tolerance the true error is strictly greater than .
Facts & Assumptions
Given: The polynomial above, the exact-real Simpson algorithm, and the adaptive call with , , and , where
Finite-depth adaptive Simpson with an indicator: the root call returns the refined Simpson value with accepted status when its indicator does not exceed .
Embedded Simpson refinement indicator: the root indicator is using the parent and its two child Simpson values.
Every continuous function on a closed nondegenerate rectangle in is Riemann integrable: a continuous real function on is Riemann integrable.
If on and both are integrable then ; and : if integrable functions satisfy pointwise on the interval, then .
Composite Simpson rule on an even uniform grid: for an even grid, the Simpson value is the stated weighted sum of its endpoint, midpoint and quarter-grid values.
For : is integrable on if and only if it is integrable on and on , and then ; with the oriented form for arbitrary : for bounded integrable and , ; applying this twice splits the integral over the three adjacent intervals used below.
If on then for every partition ; in particular every constant function is integrable, with : the constant function on an interval of length has integral .
Verification
Every parent and child sample node is in . Each node makes one factor of zero, so [F6] gives and [F2] gives indicator .
Since , [F1] accepts immediately, before the depth cap is relevant, and returns .
On , the five absolute factors are at least , respectively, so there. Since is a product of squares, on all of ; each factor has absolute value at most there, so and is bounded. By [F3]–[F4], its restrictions to the three adjacent intervals determined by and are integrable. Monotonicity [F5] and the constant integral [F8] give ; monotonicity [F5] gives nonnegative integrals on the two outer intervals. Applying the two-piece identity [F7] twice therefore yields . Step 2.1 gives returned estimate , so the returned error satisfies , despite the accepted status.
Depends on
- Finite-depth adaptive Simpson with an indicator
- Embedded Simpson refinement indicator
- Sums, scalar multiples, products, absolute values, maxima, minima and quotients with nonvanishing denominator of continuous functions are continuous, as are constants, the identity and every polynomial function
- Every continuous function on a closed nondegenerate rectangle in $\mathbb{R}^m$ is Riemann integrable
- If $f \le g$ on $[a,b]$ and both are integrable then $\int_a^b f \le \int_a^b g$; and $m(b-a) \le \int_a^b f \le M(b-a)$
- Composite Simpson rule on an even uniform grid
- For $a<c<b$: $f$ is integrable on $[a,b]$ if and only if it is integrable on $[a,c]$ and on $[c,b]$, and then $\int_a^b f = \int_a^c f + \int_c^b f$; with the oriented form for arbitrary $a,b,c$
- If $m \le f \le M$ on $[a,b]$ then $m(b-a) \le L(f,P) \le \underline{\int_a^b} f \le \overline{\int_a^b} f \le U(f,P) \le M(b-a)$ for every partition $P$; in particular every constant function is integrable, with $\int_a^b c = c(b-a)$
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
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Sources
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, §5.7 (standard reference, not scraped)
- Art B. Owen, Monte Carlo Theory, Methods and Examples, Chapter 7, §7.2 (standard reference, not scraped)