Basic Concepts for nth Order Linear Equations — Question 10

PDF ↗

Question 10

Two solutions of y(4)=0y^{(4)}=0 on ℝ\mathbb R have initial derivative errors δj=ỹ(j)(0)−y(j)(0),|δj|≤ε(j=0,1,2,3),\delta_j=\widetilde y^{(j)}(0)-y^{(j)}(0),\qquad |\delta_j|\le\varepsilon\quad(j=0,1,2,3), where ε≥0\varepsilon\ge 0. Let e=ỹ−ye=\widetilde y-y. We want a guaranteed error bound over a whole interval, not just at the initial point.

Tasks

  1. Find e(x)e(x) exactly in terms of the four initial errors.

  2. For T>0T>0, prove the sharp uniform bound max|x|≤T|e(x)|≤ε(1+T+T22+T36).\max_{|x|\le T}|e(x)|\le\varepsilon\left(1+T+\frac{T^2}{2}+\frac{T^3}{6}\right). Show that the constant cannot be improved when only the stated error information is available.

  3. At T=2T=2, find the largest ε\varepsilon guaranteeing solution error at most 10−210^{-2} for every admissible initial error vector. Evaluate the guarantee for ε=10−3\varepsilon=10^{-3}.

  4. If only δ0,δ1,δ2\delta_0,\delta_1,\delta_2 are controlled, can any finite uniform guarantee depending on those three errors alone hold on [−2,2][-2,2]? Construct a decisive example and interpret what the result says about a complete initial state.

Original worksheet page 1: question and worked solution for 7-1-010
Show solutionHide solution

Question 10 – Solution

Strategy. The linear initial-data map is explicit here, so its worst-case amplification can be determined exactly.

Step 1: Propagate all four initial errors. The difference satisfies e(4)=0e^{(4)}=0 and e(j)(0)=δje^{(j)}(0)=\delta_j. Therefore e(x)=δ0+δ1x+δ2x22+δ3x36.\boxed{e(x)=\delta_0+\delta_1x+\frac{\delta_2x^2}{2}+\frac{\delta_3x^3}{6}.} The factorials are required because the data are derivatives, not monomial coefficients.

Step 2: Prove and attain the uniform bound. For |x|≤T|x|\le T, the triangle inequality gives |e(x)|≤ε(1+|x|+|x|22+|x|36)≤ε(1+T+T22+T36).|e(x)|\le\varepsilon\left(1+|x|+\frac{|x|^2}{2}+\frac{|x|^3}{6}\right) \le\varepsilon\left(1+T+\frac{T^2}{2}+\frac{T^3}{6}\right). Choose all four δj=ε\delta_j=\varepsilon. At x=Tx=T, every term has the same nonnegative sign, attaining equality. Thus the stated worst-case constant is exact, including the trivial case ε=0\varepsilon=0.

Step 3: Translate the certificate into a tolerance. At T=2T=2, the amplification factor is 1+2+2+8/6=19/31+2+2+8/6=19/3. Consequently the largest admissible tolerance is εmax=10−219/3=31900.\boxed{\varepsilon_{\max}=\frac{10^{-2}}{19/3}=\frac 3{1900}.} Any larger value fails for the equal-sign error vector from Step 2. For ε=10−3\varepsilon=10^{-3}, the exact worst-case bound is 19/3000≈0.0063333<0.0119/3000\approx 0.0063333<0.01.

Step 4: Show why one uncontrolled component matters. Take y=0y=0 and ỹ=Mx3/6\widetilde y=Mx^3/6 for arbitrary real MM. Both solve the equation and have the same value, first derivative and second derivative at zero, but their third-derivative difference is MM. At x=2x=2, the solution error is 4|M|/34|M|/3, which is unbounded as |M|→∞|M|\to\infty. Thus controlling only three components cannot give the proposed finite guarantee. For the fourth-order IVP, the complete initial derivative vector is needed for this quantitative stability bound.

Original worksheet page 2: question and worked solution for 7-1-010

Original worksheet layout. Use Enlarge or open the PDF for a closer view.