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Constant-step BDF2 is second-order convergent with a consistent start and selected roots

Statement

Let T>0 and consider the family of constant grids tn=nh, h=T/N→0, N≥2. Let y:[0,T]→Rd be a C3 solution of y′=f(t,y). Suppose K⊂Rd is compact, y([0,T])⊂int⁡K, and f is defined on [0,T]×K 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 Y0,Y1 satisfying ∥Y0−y(0)∥∞+∥Y1−y(h)∥∞=O(h2). At each step prescribe a closed branch ball Bn+1⊂K and suppose that for every pair of preceding states in K the BDF2 equation has exactly one root in Bn+1; select that root. Then, for all sufficiently small h, the selected sequence satisfies max⁡0≤n≤N∥Yn−y(tn)∥∞=O(h2). If Y0=y(0), an exact BE startup also has ∥Y1−y(h)∥∞=O(h2) under the following local condition: a closed Euclidean ball BBE⊂K of positive radius contains both y(h) and the exact BE root, and the BE stage map Φ(z)=y(0)+hf(h,z) maps this ball into itself and is q-contractive there with q=hL2≤1/2. Sufficient conditions for this invariance and contraction are that BBE is centered at y(0), ∥f(h,z)∥2≤M on it, hM≤rad⁡(BBE), and f(h,⋅) is L2-Lipschitz there with hL2≤1/2; the inclusion y(h)∈BBE remains a separate requirement. A finite-tolerance startup must separately meet the displayed O(h2) starter budget; a residual-tolerance status alone does not establish it. This statement makes no scalar stability claim.

Facts & Assumptions

Given: A C3 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 O(h2) bound.

[F1]

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.

[F2]

Variable-step BDF2 is second-order convergent under a uniform ratio bound: under its C3 solution, compact-tube, state-Lipschitz, ratio 0<rmin⁡≤rn≤r∗<1+2, and O(H2) starting-pair hypotheses, BDF2 has maximum error O(H2) for sufficiently small H, provided there are fixed η,ε>0 such that every preceding pair within η of the exact history has exactly one step root in B‾(y(tn+1),ε)⊂K, and the prescribed branch ball contains exactly this same unique root.

[F3]

First-order systems, initial value problems, and solutions on intervals: the exact solution satisfies y′=f(t,y) on its interval.

[F4]

Multivariable Taylor formula with a Lagrange remainder along a line segment is scalar-valued and is applied separately to each component of the C3 solution. The supplier is scalar-valued. For a vector map F:U⊂Rs→Rd, apply it separately to each real component Fi; its intermediate points θi may differ. If the absolute values of all order-(k+1) component partial derivatives on the segment are at most M, each component remainder is at most MCs,k∥v∥2k+1, where Cs,k=∑∣α∣=k+11/α! is a fixed finite constant, since ∣vα∣≤∥v∥2k+1. Hence the Euclidean remainder is at most dMCs,k∥v∥2k+1. In one time variable the max-norm bound is M∣h∣k+1/(k+1)!. No common intermediate point for all components is asserted. Thus y(h)=y(0)+hy′(0)+O(h2) and y′(h)=y′(0)+O(h) uniformly in the fixed finite dimension. The same componentwise degree-two formula gives the cubic constant-step residual used below.

[F5]

Backward Euler step equation and algebraic residual: an admissible BE endpoint satisfies z=y0+hf(h,z) and its update residual is z−y0−hf(h,z).

[F6]

Implicit Runge–Kutta stage equations and update: for one stage with A=b=c=(1), the stage equation is Z=y0+hf(h,Z) and the update is Z when a stage is selected.

[F7]

Small-step implicit Runge–Kutta stages have a unique branch and controlled residual error: on an invariant product ball, if q=h∥A∥∞L<1, there is a unique stage root there and every approximate stage vector in the ball has error at most its update residual divided by 1−q.

[F9]

Squaring is monotone on the nonnegatives: if a,b≥0, then a≤b whenever a2≤b2.

[A1]

The tube, Lipschitz, smoothness, O(h2) starting-pair, branch-ball, and unique-root hypotheses above hold uniformly as h→0. For the BE startup, BBE contains y(h) and the exact BE root, and its stage map is invariant and q-contractive with q=hL2≤1/2.

Proof

1.1A1F1F2F3F4algebra

Choose ε>0 so that every closed max-norm ε-ball about y([0,T]) lies in K; such a uniform ε exists by compactness and the interior assumption. Set η=ε/10. Taylor expansion and y∈C3 give ρn=3y(tn+1)−4y(tn)+y(tn−1)−2hf(tn+1,y(tn+1)), with ∥ρn∥∞≤Cρh3 uniformly in n and h. For any U,V within η of y(tn),y(tn−1), respectively, U,V∈K, so the assumed all-histories condition supplies the unique root Z in Bn+1⊂K. Subtracting the exact residual equation and using the common Lipschitz constant L gives (3−2hL)∥Z−y(tn+1)∥∞≤4∥U−y(tn)∥∞+∥V−y(tn−1)∥∞+Cρh3≤5η+Cρh3. Choose h uniformly small enough that 2hL≤1 and Cρh3≤ε/2. Then ∥Z−y(tn+1)∥∞≤ε/2<ε. Any two roots Z,W∈K for the same history satisfy 3∥Z−W∥∞≤2hL∥Z−W∥∞, hence coincide. Therefore the ε-ball contains exactly one root, and it is exactly the unique root in the prescribed Bn+1 selected by the algorithm. These ε,η and the step threshold are independent of n and N. On the constant grid choose rmin⁡=r∗=1 and H=h. All premises of the full revised theorem [F2], including its uniform local branch and selection premise, now hold, so it yields the asserted O(h2) maximum error.

2.1A1F3F4F5F6F7F8F9algebra∎

For an exact-start BE startup, the solution identity [F3] gives y′(0)=f(0,y(0)) and y′(h)=f(h,y(h)). By [F4], y(h)−y(0)−hy′(0)=O(h2) and y′(h)−y′(0)=O(h), so [F5] gives GBE(y(h))=y(h)−y(0)−hf(h,y(h))=O(h2). By [F6], this is the stage update residual for the one-stage tableau A=b=c=(1). Write BBE={z:∥z−c∥2≤R} and Φ(z)=y(0)+hf(h,z). Since Φ(BBE)⊆BBE, the map F^(z)=(Φ(z)−c)/h satisfies ∥F^(z)∥2≤R/h and is L2-Lipschitz. Thus Φ(z)=c+hF^(z) satisfies the one-stage hypotheses of [F7], which gives ∥Y1−y(h)∥2≤∥GBE(y(h))∥2/(1−q)=O(h2) because q=hL2≤1/2. For each coordinate i, ∣vi∣2≤∑jvj2=∥v∥22 by [F8], and [F9] therefore gives ∥v∥∞≤∥v∥2. Applying this to v=Y1−y(h) proves the required max-norm starter bound.

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