Arithmetic–geometric mean

File:Generalized means + agm.png

Plot of the arithmetic–geometric mean $\mathrm{agm}(1,x)$ among several generalized means.

In mathematics, the arithmetic–geometric mean (AGM or agM) of two positive real numbers Template:Math and Template:Math is the mutual limit of a sequence of arithmetic means and a sequence of geometric means. The arithmetic–geometric mean is used in fast algorithms for exponential, trigonometric functions, and other special functions, as well as some mathematical constants, in particular, [[computing π|computing Template:Mvar]].

The AGM is defined as the limit of the interdependent sequences $a_i$ and $g_i$. Assuming $x\ge y\ge 0$, we write:$$\begin{array}{rl}{a}_0& =x,\\ g_0& =y\\ a_{n+1}& =\frac{1}{2}(a_n+g_n),\\ g_{n+1}& =\sqrt{a_n{g}_n}.\end{array}$$These two sequences converge to the same number, the arithmetic–geometric mean of Template:Math and Template:Math; it is denoted by Template:Math, or sometimes by Template:Math or Template:Math.

The arithmetic–geometric mean can be extended to complex numbers and, when the branches of the square root are allowed to be taken inconsistently, it is a multivalued function.

Example

To find the arithmetic–geometric mean of Template:Math and Template:Math, iterate as follows:$$\begin{array}{rcccl}{a}_1& =& \frac{1}{2}(24+6)& =& 15\\ g_1& =& \sqrt{24\cdot 6}& =& 12\\ a_2& =& \frac{1}{2}(15+12)& =& 13.5\\ g_2& =& \sqrt{15\cdot 12}& =& 13.4164078649\dots \\ & & ⋮& & \end{array}$$The first five iterations give the following values:

Template:Math	Template:Math	Template:Math
0	24	6
1	Template:Underline5	Template:Underline2
2	Template:Underline.5	Template:Underline.416 407 864 998 738 178 455 042...
3	Template:Underline 203 932 499 369 089 227 521...	Template:Underline 139 030 990 984 877 207 090...
4	Template:Underline45 176 983 217 305...	Template:Underline06 053 858 316 334...
5	Template:Underline20...	Template:Underline06...

The number of digits in which Template:Math and Template:Math agree (underlined) approximately doubles with each iteration. The arithmetic–geometric mean of 24 and 6 is the common limit of these two sequences, which is approximately Template:Val.

History

The first algorithm based on this sequence pair appeared in the works of Lagrange. Its properties were further analyzed by Gauss.

Properties

Both the geometric mean and arithmetic mean of two positive numbers Template:Mvar and Template:Mvar are between the two numbers. (They are strictly between when Template:Math.) The geometric mean of two positive numbers is never greater than the arithmetic mean. So the geometric means are an increasing sequence Template:Math; the arithmetic means are a decreasing sequence Template:Math; and Template:Math for any Template:Mvar. These are strict inequalities if Template:Math.

Template:Math is thus a number between Template:Math and Template:Math; it is also between the geometric and arithmetic mean of Template:Math and Template:Math.

If Template:Math then Template:Math.

There is an integral-form expression for Template:Math:$$\begin{array}{rl}M(x,y)& =\frac{\pi }{2}{\left(\underset{0}{\overset{\frac{\pi }{2}}{\int }}\frac{d\theta }{\sqrt{x^2{\cos }^2\theta +y^2{\sin }^2\theta }}\right)}^{-1}\\ & =\pi {\left(\underset{0}{\overset{\mathrm{\infty }}{\int }}\frac{dt}{\sqrt{t(t+x^2)(t+y^2)}}\right)}^{-1}\\ & =\frac{\pi }{4}\cdot \frac{x+y}{K\left(\frac{x-y}{x+y}\right)}\end{array}$$where Template:Math is the complete elliptic integral of the first kind:$$K(k)=\underset{0}{\overset{\frac{\pi }{2}}{\int }}\frac{d\theta }{\sqrt{1-k^2{\sin }^2\theta }}$$Since the arithmetic–geometric process converges so quickly, it provides an efficient way to compute elliptic integrals, which are used, for example, in elliptic filter design.

The arithmetic–geometric mean is connected to the Jacobi theta function ${\theta }_3$ by$$M(1,x)={\theta }_3^{-2}(\exp (-\pi \frac{M(1,x)}{M(1,\sqrt{1-x^2})}))={(\sum _{n\in \mathbb{\mathbb{Z}}}\exp (-n^2\pi \frac{M(1,x)}{M(1,\sqrt{1-x^2})}))}^{-2},$$which upon setting $x=1/\sqrt{2}$ gives$$M(1,1/\sqrt{2})={\left(\sum _{n\in \mathbb{\mathbb{Z}}}{e}^{-n^2\pi }\right)}^{-2}.$$

Related concepts

The reciprocal of the arithmetic–geometric mean of 1 and the square root of 2 is Gauss's constant.$$\frac{1}{M(1,\sqrt{2})}=G=0.8346268\dots$$In 1799, Gauss proved that$$M(1,\sqrt{2})=\frac{\pi }{\varpi }$$where $\varpi$ is the lemniscate constant.

In 1941, $M(1,\sqrt{2})$ (and hence $G$) was proved transcendental by Theodor Schneider. The set $\{\pi ,M(1,1/\sqrt{2})\}$ is algebraically independent over $\mathbb{\mathbb{Q}}$, but the set $\{\pi ,M(1,1/\sqrt{2}),M^{\prime }(1,1/\sqrt{2})\}$ (where the prime denotes the derivative with respect to the second variable) is not algebraically independent over $\mathbb{\mathbb{Q}}$. In fact,$$\pi =2\sqrt{2}\frac{M^3(1,1/\sqrt{2})}{M^{\prime }(1,1/\sqrt{2})}.$$The geometric–harmonic mean GH can be calculated using analogous sequences of geometric and harmonic means, and in fact Template:Math. The arithmetic–harmonic mean is equivalent to the geometric mean.

The arithmetic–geometric mean can be used to compute – among others – logarithms, complete and incomplete elliptic integrals of the first and second kind, and Jacobi elliptic functions.

Proof of existence

The inequality of arithmetic and geometric means implies that$$g_n\le a_n$$and thus$$g_{n+1}=\sqrt{g_n\cdot a_n}\ge \sqrt{g_n\cdot g_n}=g_n$$that is, the sequence Template:Math is nondecreasing and bounded above by the larger of Template:Math and Template:Math. By the monotone convergence theorem, the sequence is convergent, so there exists a Template:Math such that:$$\underset{n\to \mathrm{\infty }}{\lim }{g}_n=g$$However, we can also see that:$$a_n=\frac{g_{n+1}^2}{g_n}$$ and so: $$\underset{n\to \mathrm{\infty }}{\lim }{a}_n=\underset{n\to \mathrm{\infty }}{\lim }\frac{g_{n+1}^2}{g_n}=\frac{g^2}{g}=g$$

Q.E.D.

Proof of the integral-form expression

This proof is given by Gauss. Let

$$I(x,y)=\underset{0}{\overset{\pi /2}{\int }}\frac{d\theta }{\sqrt{x^2{\cos }^2\theta +y^2{\sin }^2\theta }},$$

Changing the variable of integration to ${\theta }^{\prime }$, where

$$\begin{array}{rl}\sin \theta & =\frac{2x\sin {\theta }^{\prime }}{(x+y)+(x-y){\sin }^2{\theta }^{\prime }}\\ \Rightarrow d(\sin \theta )& =d\left(\frac{2x\sin {\theta }^{\prime }}{(x+y)+(x-y){\sin }^2{\theta }^{\prime }}\right)\\ \Rightarrow \cos \theta d\theta & =2x\frac{(x+y)-(x-y){\sin }^2{\theta }^{\prime }}{((x+y)+(x-y){\sin }^2{\theta }^{\prime }{)}^2}\cos {\theta }^{\prime }d{\theta }^{\prime }\end{array}$$

$$\begin{array}{rl}\cos \theta & =\frac{\sqrt{(x+y{)}^2-2(x^2+y^2){\sin }^2{\theta }^{\prime }+(x-y{)}^2{\sin }^4{\theta }^{\prime }}}{(x+y)+(x-y){\sin }^2{\theta }^{\prime }}\\ & =\frac{\cos {\theta }^{\prime }\sqrt{(x-y{)}^2{\cos }^2{\theta }^{\prime }+4xy}}{(x+y)+(x-y){\sin }^2{\theta }^{\prime }}\\ & =\frac{\cos {\theta }^{\prime }\sqrt{(x+y{)}^2{\cos }^2{\theta }^{\prime }+4xy{\sin }^2{\theta }^{\prime }}}{(x+y)+(x-y){\sin }^2{\theta }^{\prime }},\end{array}$$

$$\Rightarrow \cos \theta d\theta =\frac{\cos {\theta }^{\prime }\sqrt{(x+y{)}^2{\cos }^2{\theta }^{\prime }+4xy{\sin }^2{\theta }^{\prime }}}{(x+y)+(x-y){\sin }^2{\theta }^{\prime }}d\theta =2x\frac{(x+y)-(x-y){\sin }^2{\theta }^{\prime }}{((x+y)+(x-y){\sin }^2{\theta }^{\prime }{)}^2}\cos {\theta }^{\prime }d{\theta }^{\prime },$$

$$\Rightarrow d\theta =\frac{x((x+y)-(x-y){\sin }^2{\theta }^{\prime })}{((x+y)+(x-y){\sin }^2{\theta }^{\prime })}\frac{2d{\theta }^{\prime }}{\sqrt{(x+y{)}^2{\cos }^2{\theta }^{\prime }+4xy{\sin }^2{\theta }^{\prime }}},$$

$$\begin{array}{rl}\sqrt{x^2{\cos }^2\theta +y^2{\sin }^2\theta }& =\frac{\sqrt{x^2((x+y{)}^2-2(x^2+y^2){\sin }^2{\theta }^{\prime }+(x-y{)}^2{\sin }^4{\theta }^{\prime })+4x^2{y}^2{\sin }^2{\theta }^{\prime }}}{((x+y)+(x-y){\sin }^2{\theta }^{\prime })}\\ & =\frac{x((x+y)-(x-y){\sin }^2{\theta }^{\prime })}{((x+y)+(x-y){\sin }^2{\theta }^{\prime })}\end{array}$$

This yields $$\frac{d\theta }{\sqrt{x^2{\cos }^2\theta +y^2{\sin }^2\theta }}=\frac{2d{\theta }^{\prime }}{\sqrt{(x+y{)}^2{\cos }^2{\theta }^{\prime }+4xy{\sin }^2{\theta }^{\prime }}}=\frac{d{\theta }^{\prime }}{\sqrt{((\frac{x+y}{2}{)}^2{\cos }^2{\theta }^{\prime }+(\sqrt{xy}{)}^2{\sin }^2{\theta }^{\prime }}},$$

gives

$$\begin{array}{rl}I(x,y)& =\underset{0}{\overset{\pi /2}{\int }}\frac{d{\theta }^{\prime }}{\sqrt{((\frac{x+y}{2}{)}^2{\cos }^2{\theta }^{\prime }+(\sqrt{xy}{)}^2{\sin }^2{\theta }^{\prime }}}\\ & =I(\frac{x+y}{2},\sqrt{xy}).\end{array}$$

Thus, we have

$$\begin{array}{rl}I(x,y)& =I(a_1,g_1)=I(a_2,g_2)=\cdots \\ & =I(M(x,y),M(x,y))=\pi /(2M(x,y)).\end{array}$$ The last equality comes from observing that $I(z,z)=\pi /(2z)$.

Finally, we obtain the desired result

$$M(x,y)=\pi /(2I(x,y)).$$

Applications

The number π

According to the Gauss–Legendre algorithm,

$$\pi =\frac{4M(1,1/\sqrt{2}{)}^2}{1-\sum _{j=1}^{\mathrm{\infty }}{2}^{j+1}{c}_j^2},$$

where

$$c_j=\frac{1}{2}(a_{j-1}-g_{j-1}),$$

with $a_0=1$ and $g_0=1/\sqrt{2}$, which can be computed without loss of precision using

$$c_j=\frac{c_{j-1}^2}{4a_j}.$$

Complete elliptic integral K(sinα)

Taking $a_0=1$ and $g_0=\cos \alpha$ yields the AGM

$$M(1,\cos \alpha )=\frac{\pi }{2K(\sin \alpha )},$$

where Template:Math is a complete elliptic integral of the first kind:

$$K(k)=\underset{0}{\overset{\pi /2}{\int }}(1-k^2{\sin }^2\theta {)}^{-1/2}d\theta .$$

That is to say that this quarter period may be efficiently computed through the AGM, $$K(k)=\frac{\pi }{2M(1,\sqrt{1-k^2})}.$$

Other applications

Using this property of the AGM along with the ascending transformations of John Landen, Richard P. Brent suggested the first AGM algorithms for the fast evaluation of elementary transcendental functions (Template:Math, Template:Math, Template:Math). Subsequently, many authors went on to study the use of the AGM algorithms.

See also

• Landen's transformation
• Gauss–Legendre algorithm
• Generalized mean

References

Sources

• Template:Main other