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Constant-step BDF2 is second-order convergent with a consistent start and selected roots
Statement
Let and consider the family of constant grids , , . Let be a solution of . Suppose is compact, , and is defined on and is Lipschitz in the state variable there in the max norm. Start the BDF2 branch algorithm of Variable-step BDF2 with an explicit local implicit-branch rule with states satisfying At each step prescribe a closed branch ball and suppose that for every pair of preceding states in the BDF2 equation has exactly one root in ; select that root. Then, for all sufficiently small , the selected sequence satisfies . If , an exact BE startup also has under the following local condition: a closed Euclidean ball of positive radius contains both and the exact BE root, and the BE stage map maps this ball into itself and is -contractive there with . Sufficient conditions for this invariance and contraction are that is centered at , on it, , and is -Lipschitz there with ; the inclusion remains a separate requirement. A finite-tolerance startup must separately meet the displayed starter budget; a residual-tolerance status alone does not establish it. This statement makes no scalar stability claim.
Facts & Assumptions
Given: A exact solution, compact tube and Lipschitz bound, a constant positive grid, prescribed BDF2 branch balls with a unique root per step, and starting values satisfying the stated bound.
Variable-step BDF2 with an explicit local implicit-branch rule: BDF2 selects the unique root in each prescribed closed branch ball and makes no convergence assertion by itself.
Variable-step BDF2 is second-order convergent under a uniform ratio bound: under its solution, compact-tube, state-Lipschitz, ratio , and starting-pair hypotheses, BDF2 has maximum error for sufficiently small , provided there are fixed such that every preceding pair within of the exact history has exactly one step root in , and the prescribed branch ball contains exactly this same unique root.
First-order systems, initial value problems, and solutions on intervals: the exact solution satisfies on its interval.
Multivariable Taylor formula with a Lagrange remainder along a line segment is scalar-valued and is applied separately to each component of the solution. The supplier is scalar-valued. For a vector map , apply it separately to each real component ; its intermediate points may differ. If the absolute values of all order- component partial derivatives on the segment are at most , each component remainder is at most , where is a fixed finite constant, since . Hence the Euclidean remainder is at most . In one time variable the max-norm bound is . No common intermediate point for all components is asserted. Thus and uniformly in the fixed finite dimension. The same componentwise degree-two formula gives the cubic constant-step residual used below.
Backward Euler step equation and algebraic residual: an admissible BE endpoint satisfies and its update residual is .
Implicit Runge–Kutta stage equations and update: for one stage with , the stage equation is and the update is when a stage is selected.
Small-step implicit Runge–Kutta stages have a unique branch and controlled residual error: on an invariant product ball, if , there is a unique stage root there and every approximate stage vector in the ball has error at most its update residual divided by .
Squaring is monotone on the nonnegatives: if , then whenever .
The tube, Lipschitz, smoothness, starting-pair, branch-ball, and unique-root hypotheses above hold uniformly as . For the BE startup, contains and the exact BE root, and its stage map is invariant and -contractive with .
Proof
Choose so that every closed max-norm -ball about lies in ; such a uniform exists by compactness and the interior assumption. Set . Taylor expansion and give , with uniformly in and . For any within of , respectively, , so the assumed all-histories condition supplies the unique root in . Subtracting the exact residual equation and using the common Lipschitz constant gives Choose uniformly small enough that and . Then . Any two roots for the same history satisfy , hence coincide. Therefore the -ball contains exactly one root, and it is exactly the unique root in the prescribed selected by the algorithm. These and the step threshold are independent of and . On the constant grid choose and . All premises of the full revised theorem [F2], including its uniform local branch and selection premise, now hold, so it yields the asserted maximum error.
For an exact-start BE startup, the solution identity [F3] gives and . By [F4], and , so [F5] gives . By [F6], this is the stage update residual for the one-stage tableau . Write and . Since , the map satisfies and is -Lipschitz. Thus satisfies the one-stage hypotheses of [F7], which gives because . For each coordinate , by [F8], and [F9] therefore gives . Applying this to proves the required max-norm starter bound.
Depends on
- Variable-step BDF2 with an explicit local implicit-branch rule
- Variable-step BDF2 is second-order convergent under a uniform ratio bound
- First-order systems, initial value problems, and solutions on intervals
- Multivariable Taylor formula with a Lagrange remainder along a line segment
- Backward Euler step equation and algebraic residual
- Implicit Runge–Kutta stage equations and update
- Small-step implicit Runge–Kutta stages have a unique branch and controlled residual error
- The Euclidean inner product $\langle x,y\rangle = \sum_{k<n} x_k y_k$ on $\mathbb{R}^n$
- Squaring is monotone on the nonnegatives
Used by
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Sources
- Ernst Hairer, Syvert P. Nørsett, and Gerhard Wanner, Solving Ordinary Differential Equations I: Nonstiff Problems, 2nd ed., Chapter III.5 (standard reference, not scraped)
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, §6.6 Multistep methods (standard reference, not scraped)