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Backward Euler, the selected SDIRK, and two-stage Radau IIA converge at their stated orders under controlled stage residuals

Statement

Let T>0, N≥1, h=T/N, and let y:[0,T]→Rd solve y′=f(t,y). Assume f is C3 on a neighborhood of a common compact tube containing the exact solution, all grid states, and all stage balls; f is L-Lipschitz in state there; and hL≤1/2. For each grid input u in the tube, use the local stage branch in a prescribed invariant product ball for one of: BE with order p=1, the tableau Selected two-stage singly diagonally implicit Runge–Kutta tableau with p=2, or the tableau Two-stage Radau IIA tableau with p=3. The exact stage root and any approximate stage vector being compared must lie in that same ball. For BE, also require the exact ODE endpoint y(tn+1) to lie in the same one-stage ball as the exact BE root, so its residual can be used in the branch estimate. Assume uniformly that the hypotheses of Small-step implicit Runge–Kutta stages have a unique branch and controlled residual error hold with ∥A∥∞=1, ∥b∥1=1, and that the exact one-step stages, approximate stages, and outputs stay in the tube.

Initialize y~0=y(0). At each step, use a stage vector Y~n in the prescribed ball whose update residual satisfies ∥Gn(Y~n)∥∞,2≤Dhp+1 for a constant D independent of h,n, and update by the method formula. Then there is a constant C∗, independent of h, such that max⁡0≤n≤N∥y~n−y(tn)∥2≤C∗hp. The same conclusion holds with an initial error bounded by C0hp. The residual condition is in update-residual units; if a derivative-scaled residual rn=Gn/h is used, it requires ∥rn∥∞,2=O(hp). A fixed absolute stage residual tolerance alone does not imply the stated order.

Facts & Assumptions

Given: The exact IVP, common tube, state Lipschitz and smoothness bounds, uniform invariant stage balls, a selected method, and residual bounds from the Statement.

[F1]

Implicit Runge–Kutta stage equations and update: the stages solve Yi=u+h∑jaijf(t+cjh,Yj), the update is u+h∑ibif(t+cih,Yi), and stiff accuracy means bT is the final row of A with cs=1.

[F2]

Small-step implicit Runge–Kutta stages have a unique branch and controlled residual error: if the stage fixed-point map is a contraction with constant q=h∥A∥∞L<1 on an invariant product ball, there is a unique stage root there and every approximate stage vector in the ball has error at most ∥G(Y~)∥∞,2/(1−q).

[F3]

The selected two-stage SDIRK method has order two and is scalar L-stable: the selected SDIRK coefficient satisfies 0<γ<1, and the method has local defect O(h3) on the stated smooth tube.

[F4]

Two-stage Radau IIA has order three and is scalar L-stable: the selected Radau IIA method has local defect O(h4) on the stated smooth tube.

[F5]

Global error from uniform one-step defect and stability: on a common tube, an exact one-step method with local defect O(hp+1), stability factor at most 1+L0h, and initial error O(hp) has global error O(hp).

[F6]

Finite geometric error bound from a one-step recurrence: if e0≤C0hp and en+1≤(1+L0h)en+Chp+1, then max⁡n≤Nen=O(hp) for h=T/N.

[F7]

Multivariable Taylor formula with a Lagrange remainder along a line segment is applied to each scalar coordinate of the exact 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. With k=1 and the uniformly bounded second derivatives on the tube, y(t+h)=y(t)+hy′(t)+O(h2) and y′(t+h)=y′(t)+O(h) in Euclidean norm; using y′=f(t,y) gives the BE update residual y(t+h)−y(t)−hf(t+h,y(t+h))=O(h2).

[F8]

Backward Euler step equation and algebraic residual: BE is the one-stage Runge–Kutta stage equation with A=b=c=(1), so its stage is its endpoint and its update is that stage.

[A1]

At every step, the approximate stages and exact stage roots lie in the same prescribed invariant product ball, the stage map is L-Lipschitz, and q=hL≤1/2. For BE, the exact ODE endpoint also lies in that one-stage ball.

Proof

1.1F1F2F3algebra

BE and both tableaux are stiffly accurate. Their row-sum norms satisfy ∥A∥∞=1, and their positive weights satisfy ∥b∥1=1: for BE this is immediate; for SDIRK the absolute row sums are γ,1 and b1+b2=1; for Radau they are 1/2,1 and b1+b2=1.

1.2F1A1algebra

For exact stages at two inputs u,v, subtract the fixed-point equations. The state Lipschitz bound [A1] gives ∥Y(u)−Y(v)∥∞,2≤∥u−v∥2+q∥Y(u)−Y(v)∥∞,2, hence ∥Y(u)−Y(v)∥∞,2≤2∥u−v∥2. The update formula and ∥b∥1=1 now give ∥Ψh(u)−Ψh(v)∥2≤(1+2Lh)∥u−v∥2.

1.3F1F2algebra

For an approximate stage vector and the exact stages with the same input, [F2] and q≤1/2 give ∥Y~n−Yn∥∞,2≤2Dhp+1. Stiff accuracy and the residual equation give the method output y~n+1=Y~n,s−Gn,s(Y~n), whereas the exact output is Yn,s. Since ∥Gn,s∥2≤∥Gn∥∞,2≤Dhp+1, the output perturbation is at most 3Dhp+1.

2.1F2F3F4F5F7F8step 1.2

The exact one-step map has local defect order p: for BE, [F8] identifies the endpoint with its one-stage value, [F7] gives residual O(h2) at the exact endpoint, and [F2] turns this into endpoint error O(h2) because both the endpoint and the selected stage root lie in the same ball; for SDIRK and Radau, use [F3] and [F4]. With the stability estimate in step 1.2, the exact-solve trajectory satisfies [F5] and has global error O(hp).

3.1F5F6step 1.2step 1.3step 2.1algebra∎

Let zn be the exact-solve trajectory from the same initial value and set dn=∥y~n−zn∥2. Steps 1.2 and 1.3 give dn+1≤(1+2Lh)dn+3Dhp+1,d0=0. Applying [F6] yields dn=O(hp) uniformly in n. The triangle inequality and step 2.1 give ∥y~n−y(tn)∥2≤dn+∥zn−y(tn)∥2=O(hp). An initial O(hp) error is handled by the same recurrence and [F5].

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