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Local second-order midpoint collocation error with an algebraic residual budget
Statement
Here means continuously differentiable with continuous second total derivatives, and means the same through third derivatives. Let be on open neighborhoods of an exact solution of the square BVP, and suppose its continuous linearized BVP operator is boundedly invertible. For all sufficiently fine uniform meshes, the normalized midpoint residual has a unique zero in a fixed-radius maximum-norm ball about the sampled vector . Its Jacobian at is invertible with an inverse bound independent of . For every candidate in that ball with , its piecewise-linear interpolant satisfies
where is independent of and the candidate. This is a local branch result only; it asserts no branch selection outside the ball and no global Newton convergence.
Facts & Assumptions
Given: The square BVP, near the solution, , bounded invertibility of the continuous linearized BVP operator, and a uniform mesh.
Normalized implicit-midpoint collocation residual for a two-point BVP: consists of normalized midpoint ODE rows and the boundary row, with maximum Euclidean block norms.
Continuous linearized BVP operator and its conditioning: the continuous linearized operator is ; the theorem assumes it is boundedly invertible.
Uniform inverse bound for the sampled midpoint linearized BVP: at the sampled vector , is invertible with uniformly for small .
A contraction of a nonempty complete metric space into itself has exactly one fixed point, the limit of the iterates from any starting point: a contraction from a nonempty complete metric space into itself has a unique fixed point.
and for with the Euclidean metric are complete, componentwise from the Cauchy criterion in : a closed ball in a finite-dimensional normed Euclidean space is complete.
Multivariable Taylor formula with a Lagrange remainder along a line segment: the scalar Taylor formula with remainder applies to each coordinate of a vector-valued curve or residual block.
Proof
Let . Applying scalar Taylor's formula coordinatewise to the components of the curve on each cell gives and . Since , bounded first derivatives of make each normalized interior residual uniformly. The exact endpoint pair makes the boundary block zero; [F2] names the boundedly invertible continuous linearized operator assumed here, and thus . The Taylor remainder bounds are uniform because the derivatives are bounded on a compact neighborhood of the trajectory.
On a fixed-radius ball about , all midpoint states and endpoint pairs stay in compact subsets of the domains for sufficiently small radius. Bounded second derivatives of and imply a constant , independent of , such that on this ball: every interior row depends on only two node blocks and its nonlinear part is evaluated at their average, while the linear increment term has constant derivative; the boundary row depends only on the two endpoint blocks. The bounds on each row therefore do not grow with the number of mesh cells.
Choose small enough that the closed ball lies in the nodal domain and . Define . The mean-value bound from step 1.2 gives on the ball. Also , so for small enough this is at most ; then maps the ball into itself. It is a contraction on a nonempty complete ball by [F4] and [F5].
The contraction theorem gives a unique fixed point in the ball. Since is invertible, is equivalent to , so this is the unique residual zero there. The fixed-point estimate gives . Further, . For small , ; the geometric-series inverse of shows invertible with inverse norm at most .
For any candidate in the ball, put . Each interior residual block depends only on two node blocks, and the boundary block only on the two endpoint blocks. Apply [F6] to each scalar component of for ; the segment lies in the open nodal domain. The uniform second-derivative bounds from step 1.2, row locality, and fixed give a constant , independent of and , such that with . Since both points lie in the radius- ball, ; reduce initially if needed so . Using [step 3.1], , so . The piecewise-linear interpolant is a convex combination of adjacent nodes, hence . The linear interpolant of differs from by at most on each cell, and by step 3.1. Adding these bounds proves the stated estimate.
Depends on
- Normalized implicit-midpoint collocation residual for a two-point BVP
- Continuous linearized BVP operator and its conditioning
- Uniform inverse bound for the sampled midpoint linearized BVP
- A contraction of a nonempty complete metric space into itself has exactly one fixed point, the limit of the iterates from any starting point
- $\mathbb{R}$ and $\mathbb{R}^n$ for $n \ge 1$ with the Euclidean metric are complete, componentwise from the Cauchy criterion in $\mathbb{R}$
- Multivariable Taylor formula with a Lagrange remainder along a line segment
Used by
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Sources
- T. A. Driscoll and R. J. Braun, Fundamentals of Numerical Computation, Chapter 10 (standard reference, not scraped)