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A first-order Neumann closure limits the global rate
Example
Fix and consider the mixed-boundary problem on , , . On the grid , , use the same centered interior stencil as Centered finite differences for the zero-Dirichlet boundary-value problem, but close the right boundary with the first-order backward difference . The exact solution is . This example changes the boundary condition and closure; it makes no claim that the assigned zero-Dirichlet theorem covers Neumann data.
Facts & Assumptions
Given: , , , the BVP and finite-difference equations in the Example, and the exact sampled values .
Centered finite differences for the zero-Dirichlet boundary-value problem supplies the uniform nodes and centered interior operator ; this example replaces its right Dirichlet closure by the stated backward-difference condition.
Verification
For , one has , , and , so solves the stated mixed-boundary BVP.
Put . Each interior equation is equivalent to , while the boundary closure sets . Starting from this last difference and applying for determines every ; then and determine a unique discrete vector.
The exact quadratic samples satisfy each centered interior equation exactly. Their final backward difference is , so the boundary difference error for is .
Subtracting the identical interior equations gives , hence the increments are constant. Since and the final increment is by step 2.1, every increment equals , and therefore for .
Thus . This is not as : such a bound would imply for all , whereas is unbounded. The first-order boundary closure has reduced the global rate to first order despite the interior stencil being exact on the quadratic solution.
Remarks
The modified problem has a Neumann condition at the right endpoint, so this is a boundary-closure witness rather than a counterexample to the zero-Dirichlet error theorem.
Depends on
Used by
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Sources
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, author-source revision 2025.01.27, Chapter 10, linear.md (standard reference, not scraped)
- Benjamin Seibold, MIT OpenCourseWare 18.336, Lecture 5: Finite Difference Approximation, Spring 2009 (standard reference, not scraped)
- Benjamin Seibold, MIT OpenCourseWare 18.336, Lecture 6: General Linear Second Order Equation, Spring 2009 (standard reference, not scraped)