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Multistep Methods 📂Numerical Analysis

Multistep Methods

Definition 1

Given a continuous function defined in $D \subset \mathbb{R}^2$ for the initial value problem given in $\begin{cases} y ' = f(x,y) \\ ( y( x_{0} ) , \cdots , y(x_{p}) ) = (Y_{0}, \cdots , Y_{p} ) \end{cases}$, let’s say we have broken down interval $(a,b)$ into nodes like $a \le x_{0} < x_{1} < \cdots < x_{n} < \cdots x_{N} \le b$. Especially for a sufficiently small $h > 0$, if we say $x_{j} = x_{0} + j h$, then for the initial value and $0 \le p \le m$, if $a_{p} \ne 0$ or $b_{p} \ne 0$, the following is called a $(p+1)$-step method. $$ y_{n+1} = \sum_{j=0}^{p} a_{j} y_{n-j} + h \sum_{j = -1}^{p} b_{j} f (x_{n-j} , y_{n-j} ) $$

Explanation

Of course, it is permissible to think of a sufficiently large $q \ge 1$ and $f \in C^{q}(D)$ defined from $D \subset \mathbb{R}^2$. Especially in this general form, if particularly $p=0$ and $a_{0} = 1 , b_{0} = 1 , b_{-1} = 0$ then it becomes the Euler method.

Multistep methods generally have a higher accuracy as they use more data information compared to one-step methods. For the initial value problem given in $\begin{cases} y ' = f(x,y) \\ ( y( x_{0} ) , \cdots , y(x_{p}) ) = (Y_{0}, \cdots , Y_{p} ) \end{cases}$, let’s consider the truncation error as $$ T_{n} (Y) := Y_{n+1} - \sum_{j=0}^{p} a_{j} Y_{n-j} + h \sum_{j = -1}^{p} b_{j} Y’_{n-j} $$ and write this as $\displaystyle \tau_{n} (Y) := {{1} \over {h}} T_{n} (Y) $, if it satisfies $\displaystyle \lim_{h \to 0} \max_{x_{p} \le x_{n} \le b} | \tau_{n} (Y) | = 0$, then the method is said to have a consistency condition. It might look complicated when written in equations but simply put, this means the speed at which the truncation error decreases is faster than the speed at which $h$ decreases. Where $$ \tau (h) : = \max_{x_{p} \le x_{n} \le b} | \tau_{n} (Y) | = O (h^m) $$ among $m$, the highest number is called the method’s order of convergence.

Especially if $b_{-1} = 0$, then $y_{n+1}$ is referred to as an explicit method because it appears only in the left side. If $b_{-1} \ne 0$, then because $y_{n+1}$ appears on both sides, it is referred to as an implicit method. While explicit methods are convenient for calculations, generally known implicit methods perform well but require additional calculations.


  1. Atkinson. (1989). An Introduction to Numerical Analysis(2nd Edition): p357. ↩︎