Mathematical Methods for Physics and Engineering : A Comprehensive Guide

(Darren Dugan) #1

NUMERICAL METHODS


nAn f(An) Bn f(Bn) xn f(xn)
1 1.0000 − 4 .0000 1.7000 5.4186 1.3500 − 2. 1610
2 1.3500 − 2 .1610 1.7000 5.4186 1.5250 0. 5968
3 1.3500 − 2 .1610 1.5250 0.5968 1.4375 − 0. 9946
4 1.4375 − 0 .9946 1.5250 0.5968 1.4813 − 0. 2573
5 1.4813 − 0 .2573 1.5250 0.5968 1.5031 0. 1544
6 1.4813 − 0 .2573 1.5031 0.1544 1.4922 − 0. 0552
7 1.4922 − 0 .0552 1.5031 0.1544 1.4977 0. 0487
8 1.4922 − 0 .0552 1.4977 0.0487 1.4949 − 0. 0085

Table 27.3 Successive approximations to the root of (27.1) using binary
chopping.

27.1.3 Binary chopping

Again two values ofx,A 1 andB 1 , that straddle the root are chosen, such that


A 1 <B 1 andf(A 1 )andf(B 1 ) have opposite signs. The interval between them is


then halved by forming


xn=^12 (An+Bn), (27.9)

withn=1,andf(x 1 ) is evaluated. It should be noted thatx 1 is determined


solely byA 1 andB 1 , and not by the values off(A 1 )andf(B 1 ) as in the linear


interpolation method. Nowx 1 is used to replace eitherA 1 orB 1 , depending on


which off(A 1 )orf(B 1 ) has the same sign asf(x 1 ), i.e. iff(A 1 )andf(x 1 ) have the


same sign thenx 1 replacesA 1. The process isthen repeated to obtainx 2 ,x 3 ,etc.


This has been carried through in table 27.3 for our standard equation (27.1)

and is illustrated in figure 27.2(c). The entries have been rounded to four places


of decimals. It is suggested that the reader follows through the sequential replace-


ments of theAnandBnin the table and correlates the first few of these with


graph (c) of figure 27.2.


Clearly, the accuracy with whichξis known in this approach increases by only

a factor of 2 at each step, but this accuracy is predictable at the outset of the


calculation and (unlessf(x) has very violent behaviour nearx=ξ)arangeofx


in whichξlies can be safely stated at any stage. At the stage reached in the last


row of table 27.3 it may be stated that 1. 4949 <ξ< 1 .4977. Thus binary chopping


gives a simple approximation method (it involves less multiplication than linear


interpolation, for example) that is predictable and relatively safe, although its


convergence is slow.


27.1.4 Newton–Raphson method

The Newton–Raphson (NR) procedure is somewhat similar to the interpolation


method, but, as will be seen, has one distinct advantage over the latter. Instead

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