Numerical Methods Contents - SAM
Numerical Methods Contents - SAM
Numerical Methods Contents - SAM
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Partial derivative:<br />
dG<br />
dz (0,z) = I<br />
Implicit function theorem: for sufficiently small |h| the equation G(h,z) = 0 defines a continuous<br />
function z = z(h).<br />
Recall the interpretation of the y k as approximations of y(t k ):<br />
Ψ(h,y) ≈ Φ h y , (11.2.6)<br />
where Φ is the evolution operator (→ Def. 11.1.6) for ẏ = f(y).<br />
The Euler methods provide approximations for evolution operator for ODEs<br />
How to interpret the sequence (y k ) N k=0 from (11.2.1)?<br />
△<br />
This is what every single step method does: it tries to approximate the evolution operator Φ for an<br />
ODE by a mapping of the type (11.2.5).<br />
➙ mapping Ψ from (11.2.5) is called discrete evolution.<br />
By “geometric insight” we expect: y k ≈ y(t k )<br />
Vice versa:<br />
a mapping Ψ as in (11.2.5) defines a single step method.<br />
(Throughout, we use the notation y(t) for the exact solution of an IVP.)<br />
If we are merely interested in the final state y(T), then the explicit Euler method will give us the<br />
answer y N .<br />
Ôº ½½º¾<br />
☞ In a sense, a single step method defined through its associated discrete evolution does not<br />
approximate and initial value problem, but tries to approximate an ODE.<br />
Ôº ½½º¾<br />
If we are interested in an approximate solution y h (t) ≈ y(t) as a function [t 0 , T] ↦→ R d , we have to<br />
do<br />
Definition 11.2.1 (Single step method (for autonomous ODE)).<br />
Given a discrete evolution Ψ : Ω ⊂ R × D ↦→ R d , an initial state y 0 , and a temporal mesh<br />
M := {t 0 < t 1 < · · · < t N = T } the recursion<br />
post-processing = reconstruction of a function from y k , k = 0,...,N<br />
y k+1 := Ψ(t k+1 − t k ,y k ) , k = 0,...,N − 1 , (11.2.7)<br />
Technique: interpolation, see Ch. 8<br />
defines a single step method (SSM, ger.: Einschrittverfahren) for the autonomous IVP ẏ = f(y),<br />
y(0) = y 0 .<br />
Simplest option: piecewise linear interpolation (→ Sect. 9.2.1) ➙ Euler polygon, see Fig. 134.<br />
Procedural view of discrete evolutions:<br />
Abstract single step methods<br />
Ψ h y ←→ function y1 = esvstep(h,y0) .<br />
( function y1 = esvstep(@(y) rhs(y),h,y0) )<br />
Recall Euler methods for autonomous ODE ẏ = f(y):<br />
explicit Euler: y k+1 = y k + h k f(y k ) ,<br />
implicit Euler: y k+1 : y k+1 = y k + h k f(y k+1 ) .<br />
Both formulas provide a mapping<br />
Ôº ½½º¾<br />
(y k , h k ) ↦→ Ψ(h,y k ) := y k+1 . (11.2.5)<br />
✎ Notation: Ψ h y := Ψ(h,y)<br />
Concept of single step method according to Def. 11.2.1 can be generalized to non-autonomous ODEs,<br />
which leads to recursions of the form:<br />
y k+1 := Ψ(t k ,t k+1 ,y k ) , k = 0,...,N − 1 ,<br />
Ôº ½½º¾