Newton Raphson Works Great, Until It Doesn't - Part 1

Calculus Level 4

Consider the function given by f ( x ) = x ( x 1 ) ( x + 1 ) f(x) = x(x-1)(x+1) . If we apply the Newton Raphson method with the approximate root x 0 = 0.45 x_0 = 0.45 , which root would we converge to?

-1 0 1 No root is found

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4 solutions

Chung Gene Keun
Mar 27, 2014

Most people would likely have chose the option of 0, because that is the closest root to 0.45 0.45 .

However, if you applied the Newton Rahpson method, you would noticed that the approximated roots swing around some. In particular, if f ( x ) f'(x) is close to 0, then the next approximate root will be quite far away (see n = 2 n=2 below).

Here is the table of values, if you followed the method accordingly:

n n x n x_n f ( x ) f(x) f ( x ) f’(x)
0 0.45 -0.36 -0.39
1 -0.46 0.36 -0.35
2 0.57 -0.38 -0.04
3 -10.16 -1,037.49 308.46
4 -6.79 -306.65 137.43
5 -4.56 -90.35 61.42
6 -3.09 -26.43 27.65
7 -2.13 -7.60 12.67
8 -1.54 -2.09 6.07
9 -1.19 -0.50 3.26
10 -1.04 -0.08 2.23

Hence, with a starting approximation of 0.45, we actually end up with the root of -1!

Corrrrrrrrrrrect... :)

Dibyadarshan Pati - 7 years, 2 months ago
Tunk-Fey Ariawan
Mar 29, 2014

Using Ms. Excel spreadsheet, we can obtain the root will converge to 1 -1 for initial value x 0 = 0.45 x_0=0.45 . Take a look the picture below. Newton Raphson Newton Raphson Newton’s (or the Newton-Raphson) method is one of the most powerful and well-known numerical methods for solving a root-finding problem. Newton’s method is an extremely powerful technique because it is rapidly convergent than any other methods. In this case, it takes only 14 14 iterations to yield the root of f ( x ) = x ( x 1 ) ( x + 1 ) f(x)=x(x-1)(x+1) . Iteration should be stopped if x n = x n + 1 x_n=x_{n+1} or x n x n + 1 = ϵ |x_n-x_{n+1}|=\epsilon , where ϵ \epsilon is the tolerance value and it is chosen as close as possible to 0 0 for yielding the best accuracy of the root of function.


# Q . E . D . # \text{\# }\mathbb{Q.E.D.}\text{ \#}

Muhammad Shariq
Mar 30, 2014

The problem doesn't require any table of iterations. We simply apply Newton's method once. We first find f ( 0.45 ) f'(0.45) :

f ( x ) = x 3 x f ( x ) = 3 x 2 1 f(x)=x^3-x \implies f'(x) = 3x^2 - 1

Plugging in x = 0.45 x=0.45 gives us f ( 0.45 ) 0.3975 f'(0.45) \approx -0.3975 . Now we need to find the equation of this tangent line and determine it's x-intercept. We know it goes through the point ( 0.45 , f ( 0.45 ) ) = ( 0.45 , 0.3588 ) (0.45,f(0.45))=(0.45,-0.3588) . Using this information we determine the equation of the tangent line and then its x-intercept:

y = 0.3975 x 0.179925 x i n t 0.452 y=-0.3975x-0.179925 \implies x_{int} \approx -0.452 .

Since we know that f ( x ) = 0 f(x)=0 at x = 0 , 1 , 1 x=0,1,-1 , and the first iteration of Newton's method yields a negative x-intercept, then after a sufficient number of iterations, the root will converge to x = 1 \boxed{x=-1} . And we're done.

Note that the argument above is correct because if the root converged to x = 1 x=1 , then the first iteration would yield an x-intercept such that 0.45 < x i n t < 1 0.45<x_{int}<1 . If it was converging to x = 0 x = 0 then the first iteration would yield an x-intercept such that 0 < x i n t < 0.45 0<x_{int}<0.45 . However neither of these is true. Therefore we know for a fact that the root converges to x = 1 x = -1 by the above logic.

Note: The point of this post is to prove the validity of the logic used in the solution to arrive upon the answer.

Muhammad Shariq - 7 years, 2 months ago

just simply like this x+1 = 0 so that x = -1 .. -1 is the answer

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