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 one-sided Neumann closure gives only first-order error
Example
Let for an integer , , , and . The exact solution solves on with and . Discretize the interior equation by for , impose the one-sided Neumann row , and impose . The unique grid solution is
so . The boundary residual of the exact samples is , and the global error is only first order.
Facts & Assumptions
Given: An integer , , , the displayed centered second difference and one-sided forward Neumann row, and the stated mixed discrete equations.
The grid equations are for , , and .
Verification
For the exact samples , , whereas . Thus the imposed Neumann row has residual exactly .
Define . Then , , so ; also . Since the second difference of the quadratic part is and the second difference of the affine part is , at every interior node. Hence satisfies [A1].
If two grid solutions existed, their difference would satisfy for , , and . The recurrence says is constant in ; the forward boundary row makes that constant , and then makes every . Therefore the solution in step 1.2 is unique.
The error is . Because , its maximum absolute value is , attained at . The boundary residual and global error are both first order in .
Used by
Nothing in the library uses this result yet.
Dependency tree · 0 levels
Nothing. This result depends on no other item in the library.
Sources
- Benjamin Seibold, MIT 18.336 Lecture 5: Finite Difference Approximation (standard reference, not scraped)