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Uniform inverse bound for the sampled midpoint linearized BVP

Statement

Here Ck means each coordinate has continuous total derivatives through order k. Let f,B be C2 near an exact solution y∗∈C3([a,b],Rd) of a square BVP, and suppose the continuous linearized operator L in Continuous linearized BVP operator and its conditioning is boundedly invertible. For uniform meshes with h=(b−a)/N, let Yi∗=y∗(ti) and let Jh=DGh(Y∗) be the Jacobian of the normalized midpoint residual. There are h0>0 and C<∞ such that for every mesh width 0<h≤h0, Jh is invertible and

∥Jh−1∥∞→∞≤C,

where both finite-dimensional norms are the maximum of the Euclidean block norms. The bound is independent of h; this is a local linear inverse result, not a nonlinear convergence theorem.

Facts & Assumptions

Given: The square BVP, C2 data near y∗, y∗∈C3, uniform meshes, and bounded invertibility of the continuous operator L.

[F1]

Normalized implicit-midpoint collocation residual for a two-point BVP: Gh has normalized interior midpoint rows and the boundary row B(Y0,YN); differentiating its rows gives the stated midpoint Jacobian blocks.

[F2]

Continuous linearized BVP operator and its conditioning: Lv=(v′−Av,B1v(a)+B2v(b)), and bounded invertibility implies in particular that its kernel is zero.

[F3]

Picard-Lindelöf local existence and uniqueness for first-order systems: a continuous coefficient matrix defines unique local solutions of the linear IVP X′=A(t)X.

[F4]

Gronwall's integral inequality with variable and constant coefficients: a bound u(t)≤C+M∫atu implies u(t)≤CeM(t−a).

[F5]

The chain rule for total derivatives: D(g∘f)(a)=Dg(f(a))∘Df(a): differentiating a composition gives the product of its total derivatives.

[F6]

R and Rn for n≥1 with the Euclidean metric are complete, componentwise from the Cauchy criterion in R: finite-dimensional Euclidean spaces, hence also with an equivalent maximum norm, are complete.

[F7]

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.

[F8]

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.

[F9]

For a≤b and f:[a,b]→Rm integrable when a<b, ∥∫abf∥2≤∫ab∥f∥2; for a<b, ∥f∥2 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

1.1givenF2F3F4F7F8

Write A(t)=Dyf(t,y∗(t)) and let X(t) solve X′=A(t)X, X(a)=Id. Since A is continuous and bounded on [a,b], extend it continuously by its endpoint values to an open interval containing [a,b]. 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 b, boundedness of X′=AX would give a finite endpoint limit from which local existence extends it, a contradiction. Thus X exists on [a,b]. Define Q=B1+B2X(b). If Qc=0, then v(t)=X(t)c satisfies Lv=(0,0); [F2] forces v=0, and v(a)=c then gives c=0. The square matrix Q is therefore invertible.

1.2F1F5F6given

For each mesh let Cih=Dyf(ti+h/2,(Yi∗+Yi+1∗)/2). Uniform continuity of y∗ and Dyf on a compact neighborhood implies max⁡i∥Cih−A(ti+h/2)∥op→0. Also sup⁡h,i∥Cih∥op<∞. Applying the chain rule [F5] to the rows in [F1], the interior equation Jhz=(r0,…,rN−1,q) is (I−hCih/2)zi+1=(I+hCih/2)zi+hri. For small h, I−hCih/2 is invertible by its convergent geometric series; its inverse norm is at most 2, and the induced transition matrices Mih=(I−hCih/2)−1(I+hCih/2) satisfy ∥Mih∥≤1+C0h for a constant independent of i,h.

2.1F3F4F7F8F9step 1.2algebra

Let Mh=MN−1h⋯M0h, the discrete homogeneous transfer from z0 to zN. By [F8] on each column, the exact fundamental matrix X satisfies X(ti+1)−X(ti)=∫titi+1A(t)X(t)dt. The integrand is uniformly continuous, so its average over each cell differs from its midpoint value by a quantity tending uniformly to zero as h→0. Explicitly, put mi=ti+h/2, H(t)=A(t)X(t) and ωG(ρ)=sup⁡∣s−t∣≤ρ∥G(s)−G(t)∥op for s,t∈[a,b] and G=H,X. Write SX=sup⁡t∥X(t)∥op, SA=sup⁡t∥A(t)∥op, and δh=max⁡i∥Cih−A(mi)∥op→0 by step 1.2. By [F9], ∥h−1∫titi+1H(t)dt−H(mi)∥op≤ωH(h/2). Define the normalized midpoint defect by ηih=(X(ti+1)−X(ti))/h−Cih(X(ti)+X(ti+1))/2. Adding and subtracting H(mi) and A(mi)(X(ti)+X(ti+1))/2 therefore gives max⁡i∥ηih∥op≤ωH(h/2)+δhSX+SAωX(h/2)→0, since H and X are uniformly continuous on [a,b]. The transition bound in step 1.2 propagates the increment defects hηih with total bound at most C1(b−a)max⁡i∥ηih∥; hence Mh→X(b).

3.1F1step 1.2step 2.1algebra

Put Qh=B1+B2Mh. By step 2.1, Qh→Q. Since Q is invertible, determinant continuity makes Qh invertible for all sufficiently small h, and the adjugate formula gives a uniform bound on ∥Qh−1∥. For arbitrary forcing blocks ri, the recurrence in step 1.2 and its transition bound give zN=Mhz0+wh and max⁡i∥zi∥2≤C2(∥z0∥2+max⁡i∥ri∥2), with ∥wh∥2≤C2max⁡i∥ri∥2. The boundary row B1z0+B2zN=q becomes Qhz0=q−B2wh, so z0 and then every zi are bounded by C3max⁡(max⁡i∥ri∥2,∥q∥2) uniformly in h.

4.1givenstep 3.1algebra∎

For every right-hand side (r0,…,rN−1,q), step 3.1 constructs a unique solution of the square linear system Jhz=(r0,…,rN−1,q) and gives the asserted uniform operator bound. Therefore Jh is onto and one-to-one, hence invertible, with the stated estimate.

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