Finding Square Roots Using Newton’s Method - Penn Math
[Pages:2]Math 202
Jerry L. Kazdan
Finding Square Roots Using Newton's Method
Let A > 0 be a positive real number. We want to show that there is a real number x with x2 = A. We already know that for many real numbers, such as A = 2, there is no rational number x with this property. Formally, let f x) := x2 - A. We want to solve the equation f (x) = 0.
Newton gave a useful general recipe for solving equations of the form f (x) = 0. Say we have some approximation xk to a solution. He showed how to get a better approximation xk+1 . It works most of the time if your approximation is close enough to the solution.
Here's the procedure. Go to the point (xk, f (xk)) and find the tangent line. Its equation is
y = f (xk) + f (xk)(x - xk).
The next approximation, xk+1 , is where this tangent line crosses the x axis. Thus,
0 = f (xk) + f (xk)(xk+1 - xk),
that is,
xk+1
=
xk
-
f (xk) f (xk)
.
Applied to compute square roots, so f (x) := x2 - A, this gives
xk+1
=
1 2
xk
+
A xk
.
(1)
From this, by simple algebra we find that
xk+1
- xk
=
1 2xk
(A
-
x2k
).
(2)
Pick some x0 so that x20 > A. then equation (2) above shows that subsequent approximations x1 , x2 , . . . , are monotone decreasing. Equation (2) then shows that the sequence x1 x2 x3 . . . , is monotone decreasing and non-negative. By the monotone convergence property, it thus converges to some limit x.
I claim that x2 = A. Rewrite (2) as A - x2k = 2xk(xk+1 - xk) and let k . Since xk+1 - xk 0 and xk is bounded, this is obvious. We now know that A exists as a real number. then it is simple to use (1) to verify that
xk+1
-
A
=
1 2xk
(xk
-
A)2.
(3)
Equation (3) measures the error xk+1 - A. It shows that the error at the next step is the square of the error in the previous step. Thus, if the error at some step is roughly 10-6 (so 6 decimal places), then at the next step the error is roughly 10-12 (so 12 decimal places).
1
Example: To 20 decimal places, 7 = 2.6457513110645905905. Let's see what Newton's method gives with the initial approximation x0 = 3:
x1 = 2.6666666666666666666 x3 = 2.6457513123359580052
x2 = 2.6458333333333333333 x4 = 2.6457513110645905908
Remarkable accuracy.
2
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