binomial approximation

{{Short description|Approximation of powers of some binomials}}

{{distinguish|Binomial distribution#Normal approximation}}

{{refimprove|date=February 2016}}

The binomial approximation is useful for approximately calculating powers of sums of 1 and a small number x. It states that

: (1 + x)^\alpha \approx 1 + \alpha x.

It is valid when |x|<1 and |\alpha x| \ll 1 where x and \alpha may be real or complex numbers.

The benefit of this approximation is that \alpha is converted from an exponent to a multiplicative factor. This can greatly simplify mathematical expressions (as in the example below) and is a common tool in physics.For example calculating the multipole expansion. {{cite book |last=Griffiths |first=D. |year=1999 |title=Introduction to Electrodynamics |publisher=Pearson Education, Inc. |edition=Third |pages=146–148}}

The approximation can be proven several ways, and is closely related to the binomial theorem. By Bernoulli's inequality, the left-hand side of the approximation is greater than or equal to the right-hand side whenever x>-1 and \alpha \geq 1.

Derivations

= Using linear approximation =

The function

: f(x) = (1 + x)^{\alpha}

is a smooth function for x near 0. Thus, standard linear approximation tools from calculus apply: one has

: f'(x) = \alpha (1 + x)^{\alpha - 1}

and so

: f'(0) = \alpha.

Thus

: f(x) \approx f(0) + f'(0)(x - 0) = 1 + \alpha x.

By Taylor's theorem, the error in this approximation is equal to \frac{\alpha(\alpha - 1) x^2}{2} \cdot (1 + \zeta)^{\alpha - 2} for some value of \zeta that lies between 0 and {{mvar|x}}. For example, if x < 0 and \alpha \geq 2, the error is at most \frac{\alpha(\alpha - 1) x^2}{2}. In little o notation, one can say that the error is o(|x|), meaning that \lim_{x \to 0} \frac{\textrm{error}}

x
= 0.

= Using Taylor series =

The function

: f(x) = (1+x)^\alpha

where x and \alpha may be real or complex can be expressed as a Taylor series about the point zero.

:\begin{align}

f(x) &= \sum_{n=0}^{\infty} \frac{f^{(n)}(0)}{n!} x^n\\

f(x) &= f(0) + f'(0) x + \frac{1}{2} f(0) x^2 + \frac{1}{6} f'(0) x^3 + \frac{1}{24} f^{(4)}(0) x^4 + \cdots\\

(1+x)^{\alpha} &= 1 + \alpha x + \frac{1}{2} \alpha (\alpha-1) x^2 + \frac{1}{6} \alpha (\alpha-1)(\alpha-2)x^3 + \frac{1}{24} \alpha (\alpha-1)(\alpha-2)(\alpha-3)x^4 + \cdots

\end{align}

If |x| < 1 and |\alpha x| \ll 1, then the terms in the series become progressively smaller and it can be truncated to

:(1+x)^\alpha \approx 1 + \alpha x .

This result from the binomial approximation can always be improved by keeping additional terms from the Taylor series above. This is especially important when |\alpha x| starts to approach one, or when evaluating a more complex expression where the first two terms in the Taylor series cancel (see example).

Sometimes it is wrongly claimed that |x| \ll 1 is a sufficient condition for the binomial approximation. A simple counterexample is to let x=10^{-6} and \alpha=10^7. In this case (1+x)^\alpha > 22,000 but the binomial approximation yields 1 + \alpha x = 11. For small |x| but large |\alpha x|, a better approximation is:

: (1 + x)^\alpha \approx e^{\alpha x} .

Example

The binomial approximation for the square root, \sqrt{1+x} \approx 1+x/2, can be applied for the following expression,

: \frac{1}{\sqrt{a+b}} - \frac{1}{\sqrt{a-b}}

where a and b are real but a \gg b.

The mathematical form for the binomial approximation can be recovered by factoring out the large term a and recalling that a square root is the same as a power of one half.

:\begin{align}

\frac{1}{\sqrt{a+b}} - \frac{1}{\sqrt{a-b}} &= \frac{1}{\sqrt{a}} \left(\left(1+\frac{b}{a}\right)^{-1/2} - \left(1-\frac{b}{a}\right)^{-1/2}\right)\\

&\approx\frac{1}{\sqrt{a}} \left(\left(1+\left(-\frac{1}{2}\right)\frac{b}{a}\right) - \left(1-\left(-\frac{1}{2}\right)\frac{b}{a}\right)\right) \\

&\approx\frac{1}{\sqrt{a}} \left(1-\frac{b}{2a} - 1 -\frac{b}{2a}\right) \\

&\approx -\frac{b}{a \sqrt{a}}

\end{align}

Evidently the expression is linear in b when a \gg b which is otherwise not obvious from the original expression.

Generalization

{{further|Binomial series}}

While the binomial approximation is linear, it can be generalized to keep the quadratic term in the Taylor series:

: (1+x)^\alpha \approx 1 + \alpha x + (\alpha/2) (\alpha-1) x^2

Applied to the square root, it results in:

:\sqrt{1+x} \approx 1 + x/2 - x^2 / 8.

=Quadratic example=

Consider the expression:

: (1 + \epsilon)^n - (1 - \epsilon)^{-n}

where |\epsilon|<1 and |n \epsilon| \ll 1. If only the linear term from the binomial approximation is kept (1+x)^\alpha \approx 1 + \alpha x then the expression unhelpfully simplifies to zero

:\begin{align}

(1 + \epsilon)^n - (1 - \epsilon)^{-n} &\approx (1+ n \epsilon) - (1 - (-n) \epsilon)\\

&\approx (1+ n \epsilon) - (1 + n \epsilon)\\

&\approx 0 .

\end{align}

While the expression is small, it is not exactly zero.

So now, keeping the quadratic term:

:\begin{align}

(1+\epsilon)^n - (1 - \epsilon)^{-n}&\approx \left(1+ n \epsilon + \frac{1}{2} n (n-1) \epsilon^2\right) - \left(1 + (-n)(-\epsilon) + \frac{1}{2} (-n) (-n-1) (-\epsilon)^2\right)\\

&\approx \left(1+ n \epsilon + \frac{1}{2} n (n-1) \epsilon^2\right) - \left(1 + n \epsilon + \frac{1}{2} n (n+1) \epsilon^2\right)\\

&\approx \frac{1}{2} n (n-1) \epsilon^2 - \frac{1}{2} n (n+1) \epsilon^2\\

&\approx \frac{1}{2} n \epsilon^2 ((n-1) - (n+1)) \\

&\approx - n \epsilon^2

\end{align}

This result is quadratic in \epsilon which is why it did not appear when only the linear terms in \epsilon were kept.

References