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Linear numerical boundary-value problems — Examples
1 · Prerequisites
2 · Summary
Examples
The first example shows that the scheme represents its exact quadratic solution on every mesh. The second computes the global error produced by a first-order backward difference for a Neumann endpoint: the interior stencil is exact on a quadratic, but the boundary closure yields a max error of exactly . This mixed-boundary example illustrates the retained boundary-closure warning and is outside the theorem's zero-Dirichlet hypotheses. The last example defines the row-sum matrix norm, proves its equivalence with the induced infinity operator norm, and exhibits the uniform inverse bound sharply at .
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
The quadratic Dirichlet solution is represented exactly
Example
Take and on . Then and . We verify that the scheme in Centered finite differences for the zero-Dirichlet boundary-value problem returns its exact nodal values for every .
Facts & Assumptions
Given: The function , data , and an integer .
Centered finite differences for the zero-Dirichlet boundary-value problem uses , the interior equations , and the exact endpoint values .
Discrete maximum principle and uniform inverse bound for the Dirichlet stencil proves that, for every admissible exact input, the Thomas recurrence returns the unique solution of this finite-difference system and neither linear-solve-failure branch is reached.
Verification
Differentiating gives , so ; also .
Let . Since is quadratic, direct substitution gives for every interior ; its two endpoint values are zero. Thus the samples satisfy the system in [F1].
By [F2] the system has a unique solution, so the algorithm's output equals and its nodal error is exactly zero for every .
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.
The inverse infinity row-sum bound is uniform and sharp
Example
For a real matrix , define its row-sum matrix norm by . For the matrices from Centered finite differences for the zero-Dirichlet boundary-value problem, this norm of is at most for every ; at it is exactly .
Facts & Assumptions
Given: The row-sum norm just defined, the Dirichlet matrices for , and the inverse bound of Discrete maximum principle and uniform inverse bound for the Dirichlet stencil.
The triangle inequality gives for real .
Verification
The row-sum expression is nonnegative and equals zero only when every matrix entry is zero; ; and [F3] applied entrywise gives . Hence it is a matrix norm.
At , and [F1] gives with . Direct multiplication gives , since the displayed integer matrix multiplied by is .
Its value equals the induced infinity operator norm : for every such , each row obeys , while a row attaining the finite maximum is attained by the vector , with .
By [F2], whenever . Taking the supremum and using step 2.1 shows for every .
The three absolute row sums of this inverse are , , and , so its row-sum norm is . Along with the uniform bound in step 3.1, this proves the stated example and shows its constant is attained.
Sources
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, author-source revision 2025.01.27, Chapter 10, linear.md
- Benjamin Seibold, MIT OpenCourseWare 18.336, Lecture 5: Finite Difference Approximation, Spring 2009
- Benjamin Seibold, MIT OpenCourseWare 18.336, Lecture 6: General Linear Second Order Equation, Spring 2009