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Uniform inverse bound for the sampled midpoint linearized BVP
Statement
Here means each coordinate has continuous total derivatives through order . Let be near an exact solution of a square BVP, and suppose the continuous linearized operator in Continuous linearized BVP operator and its conditioning is boundedly invertible. For uniform meshes with , let and let be the Jacobian of the normalized midpoint residual. There are and such that for every mesh width , is invertible and
where both finite-dimensional norms are the maximum of the Euclidean block norms. The bound is independent of ; this is a local linear inverse result, not a nonlinear convergence theorem.
Facts & Assumptions
Given: The square BVP, data near , , uniform meshes, and bounded invertibility of the continuous operator .
Normalized implicit-midpoint collocation residual for a two-point BVP: has normalized interior midpoint rows and the boundary row ; differentiating its rows gives the stated midpoint Jacobian blocks.
Continuous linearized BVP operator and its conditioning: , and bounded invertibility implies in particular that its kernel is zero.
Picard-Lindelöf local existence and uniqueness for first-order systems: a continuous coefficient matrix defines unique local solutions of the linear IVP .
Gronwall's integral inequality with variable and constant coefficients: a bound implies .
The chain rule for total derivatives: : differentiating a composition gives the product of its total derivatives.
and for with the Euclidean metric are complete, componentwise from the Cauchy criterion in : finite-dimensional Euclidean spaces, hence also with an equivalent maximum norm, are complete.
Every Picard–Lindelöf initial value problem has one maximal solution on an open interval: a Picard–Lindelöf IVP has a maximal solution and every other solution through the same data is its restriction.
A first-order initial value problem is equivalent to its Volterra integral equation: a solution of a continuous finite-dimensional IVP on an interval satisfies its Volterra integral equation, including on closed subintervals. Apply this to each column of the fundamental matrix.
For and integrable when , ; for , is integrable: the Euclidean norm of a vector-valued integral over an increasing interval is at most the integral of its norm. Applying this to a continuous matrix integrand acting on each unit vector gives the corresponding operator-norm bound.
Proof
Write and let solve , . Since is continuous and bounded on , extend it continuously by its endpoint values to an open interval containing . Local existence follows from [F3], and the integral equation [F8] gives the Gronwall bound for the maximal solution from [F7]; if it stopped at or before , boundedness of would give a finite endpoint limit from which local existence extends it, a contradiction. Thus exists on . Define . If , then satisfies ; [F2] forces , and then gives . The square matrix is therefore invertible.
For each mesh let . Uniform continuity of and on a compact neighborhood implies . Also . Applying the chain rule [F5] to the rows in [F1], the interior equation is . For small , is invertible by its convergent geometric series; its inverse norm is at most , and the induced transition matrices satisfy for a constant independent of .
Let , the discrete homogeneous transfer from to . By [F8] on each column, the exact fundamental matrix satisfies . The integrand is uniformly continuous, so its average over each cell differs from its midpoint value by a quantity tending uniformly to zero as . Explicitly, put , and for and . Write , , and by step 1.2. By [F9], . Define the normalized midpoint defect by . Adding and subtracting and therefore gives , since and are uniformly continuous on . The transition bound in step 1.2 propagates the increment defects with total bound at most ; hence .
Put . By step 2.1, . Since is invertible, determinant continuity makes invertible for all sufficiently small , and the adjugate formula gives a uniform bound on . For arbitrary forcing blocks , the recurrence in step 1.2 and its transition bound give and , with . The boundary row becomes , so and then every are bounded by uniformly in .
For every right-hand side , step 3.1 constructs a unique solution of the square linear system and gives the asserted uniform operator bound. Therefore is onto and one-to-one, hence invertible, with the stated estimate.
Depends on
- Normalized implicit-midpoint collocation residual for a two-point BVP
- Continuous linearized BVP operator and its conditioning
- Picard-Lindelöf local existence and uniqueness for first-order systems
- Every Picard–Lindelöf initial value problem has one maximal solution on an open interval
- Gronwall's integral inequality with variable and constant coefficients
- The chain rule for total derivatives: $D(g\circ f)(a)=Dg(f(a))\circ Df(a)$
- $\mathbb{R}$ and $\mathbb{R}^n$ for $n \ge 1$ with the Euclidean metric are complete, componentwise from the Cauchy criterion in $\mathbb{R}$
- A first-order initial value problem is equivalent to its Volterra integral equation
- For $a \le b$ and $f : [a,b] \to \mathbb{R}^m$ integrable when $a<b$, $\bigl\lVert\int_a^b f\bigr\rVert_2 \le \int_a^b \lVert f\rVert_2$; for $a<b$, $\lVert f\rVert_2$ is integrable
Used by
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Sources
- T. A. Driscoll and R. J. Braun, Fundamentals of Numerical Computation, Chapter10: Nonlinearity and boundary conditions (standard reference, not scraped)
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, author-source revision2025.01.27, Chapter10, Collocation for linear problems (standard reference, not scraped)