Carlson symmetric form

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In mathematics, the Carlson symmetric forms of elliptic integrals are a small canonical set of elliptic integrals to which all others may be reduced. They are a modern alternative to the Legendre forms. The Legendre forms may be expressed in terms of the Carlson forms and vice versa.

The Carlson elliptic integrals are:

R_F(x,y,z) = \frac{1}{2}\int_0^\infty \frac{dt}{\sqrt{(t+x)(t+y)(t+z)}}
R_J(x,y,z,p) = \frac{3}{2}\int_0^\infty \frac{dt}{(t+p)\sqrt{(t+x)(t+y)(t+z)}}
R_C(x,y) = R_F(x,y,y) = \frac{1}{2} \int_0^\infty \frac{dt}{(t+y)\sqrt{(t+x)}}
R_D(x,y,z) = R_J(x,y,z,z) = \frac{3}{2} \int_0^\infty \frac{dt}{ (t+z) \,\sqrt{(t+x)(t+y)(t+z)}}

Since \scriptstyle{R_C} and \scriptstyle{R_D} are special cases of \scriptstyle{R_F} and \scriptstyle{R_J}, all elliptic integrals can ultimately be evaluated in terms of just \scriptstyle{R_F} and \scriptstyle{R_J}.

The term symmetric refers to the fact that in contrast to the Legendre forms, these functions are unchanged by the exchange of certain of their arguments. The value of \scriptstyle{R_F(x,y,z)} is the same for any permutation of its arguments, and the value of \scriptstyle{R_J(x,y,z,p)} is the same for any permutation of its first three arguments.

Contents

[edit] Relation to the Legendre forms

[edit] Incomplete elliptic integrals

Incomplete elliptic integrals can be calculated easily using Carlson symmetric forms:

F(\phi,k)=\sin\phi R_F\left(\cos^2\phi,1-k^2\sin^2\phi,1\right)
E(\phi,k)=\sin\phi R_F\left(\cos^2\phi,1-k^2\sin^2\phi,1\right) -\frac{1}{3}k^2\sin^3\phi R_D\left(\cos^2\phi,1-k^2\sin^2\phi,1\right)
\Pi(\phi,n,k)=\sin\phi R_F\left(\cos^2\phi,1-k^2\sin^2\phi,1\right)+
\frac{1}{3}n\sin^3\phi R_J\left(\cos^2\phi,1-k^2\sin^2\phi,1,1-n\sin^2\phi\right)

(Note: the above are only valid for 0\le\phi\le2\pi and 0\le k^2\sin^2\phi\le1)

[edit] Complete elliptic integrals

Complete elliptic integrals can be calculated by substituting \phi=\frac{\pi}{2}:

K(k)=R_F\left(0,1-k^2,1\right)
E(k)=R_F\left(0,1-k^2,1\right)-\frac{1}{3}k^2 R_D\left(0,1-k^2,1\right)
\Pi(n,k)=R_F\left(0,1-k^2,1\right)+\frac{1}{3}n R_J \left(0,1-k^2,1,1-n\right)

[edit] Special cases

When any two, or all three of the arguments of RF are the same, then a substitution of \sqrt{t + x} = u renders the integrand rational. The integral can then be expressed in terms of elementary transcendental functions.

R_{C}(x,y) = R_{F}(x,y,y) = \frac{1}{2} \int _{0}^{\infty}\frac{1}{\sqrt{t + x} (t + y)} dt =
\int _{\sqrt{x}}^{\infty}\frac{1}{u^{2} - x + y} du =
\begin{cases}
  \frac{\arccos \sqrt{\frac{x}{y}}}{\sqrt{y - x}},  & x < y \\
  \frac{1}{\sqrt{y}}, & x = y \\
  \frac{\mathrm{arccosh} \sqrt{\frac{x}{y}}}{\sqrt{x - y}},  & x > y \\
\end{cases}

Similarly, when at least two of the first three arguments of RJ are the same,

R_{J}(x,y,y,p) = 3 \int _{\sqrt{x}}^{\infty}\frac{1}{(u^{2} - x + y) (u^{2} - x + p)} du =
\begin{cases}
  \frac{3}{p - y} (R_{C}(x,y) - R_{C}(x,p)),  & y \ne p \\
  \frac{3}{2 (y - x)} \left( R_{C}(x,y) - \frac{1}{y} \sqrt{x}\right),  & y = p \ne x \\
  \frac{1}{y^{\frac{3}{2}}},  &y = p = x \\
\end{cases}

[edit] Properties

[edit] Homogeneity

By substituting in the integral definitions t = κu for any constant κ, it is found that

R_F\left(\kappa x,\kappa y,\kappa z\right)=\kappa^{-1/2}R_F(x,y,z)
R_J\left(\kappa x,\kappa y,\kappa z,\kappa p\right)=\kappa^{-3/2}R_J(x,y,z,p)

[edit] Duplication theorem

R_F(x,y,z)=2R_F(x+\lambda,y+\lambda,z+\lambda)=
R_F\left(\frac{x+\lambda}{4},\frac{y+\lambda}{4},\frac{z+\lambda}{4}\right),

where \lambda=\sqrt{xy}+\sqrt{yz}+\sqrt{zx}.

\begin{align}R_{J}(x,y,z,p) & = 2 R_{J}(x + \lambda,y + \lambda,z + \lambda,p + \lambda) + 6 R_{C}(d^{2},d^{2} + (p - x) (p - y) (p - z)) \\
 & = \frac{1}{4} R_{J}\left( \frac{x + \lambda}{4},\frac{y + \lambda}{4},\frac{z + \lambda}{4},\frac{p + \lambda}{4}\right) + 6 R_{C}(d^{2},d^{2} + (p - x) (p - y) (p - z)) \end{align}

where d = (\sqrt{p} + \sqrt{x}) (\sqrt{p} + \sqrt{y}) (\sqrt{p} + \sqrt{z}) and \lambda = \sqrt{x y} + \sqrt{y z} + \sqrt{z x}

[edit] Series Expansion

In obtaining a Taylor series expansion for \scriptstyle{R_{F}} or \scriptstyle{R_{J}} it proves convenient to expand about the mean value of the several arguments. So for \scriptstyle{R_{F}}, letting the mean value of the arguments be \scriptstyle{A = (x + y + z)/3}, and using homogeneity, define \scriptstyle{\Delta x}, \scriptstyle{\Delta y} and \scriptstyle{\Delta z} by

\begin{align}R_{F}(x,y,z) & = R_{F}(A (1 - \Delta x),A (1 - \Delta y),A (1 - \Delta z)) \\
 & = \frac{1}{\sqrt{A}} R_{F}(1 - \Delta x,1 - \Delta y,1 - \Delta z) \end{align}

that is \scriptstyle{\Delta x = 1 - x/A} etc. The differences \scriptstyle{\Delta x}, \scriptstyle{\Delta y} and \scriptstyle{\Delta z} are defined with this sign (such that they are subtracted), in order to be in agreement with Carlson's papers. Since \scriptstyle{R_{F}(x,y,z)} is symmetric under permutation of \scriptstyle{x}, \scriptstyle{y} and \scriptstyle{z}, it is also symmetric in the quantities \scriptstyle{\Delta x}, \scriptstyle{\Delta y} and \scriptstyle{\Delta z}. It follows that both the integrand of \scriptstyle{R_{F}} and its integral can be expressed as functions of the elementary symmetric polynomials in \scriptstyle{\Delta x}, \scriptstyle{\Delta y} and \scriptstyle{\Delta z} which are

E1 = Δx + Δy + Δz = 0
E2 = ΔxΔy + ΔyΔz + ΔzΔx
E3 = ΔxΔyΔz

Expressing the integrand in terms of these polynomials, performing a multidimensional Taylor expansion and integrating term-by-term...

\begin{align}R_{F}(x,y,z) & = \frac{1}{2 \sqrt{A}} \int _{0}^{\infty}\frac{1}{\sqrt{(t + 1)^{3} - (t + 1)^{2} E_{1} + (t + 1) E_{2} - E_{3}}} dt \\
 & = \frac{1}{2 \sqrt{A}} \int _{0}^{\infty}\left( \frac{1}{(t + 1)^{\frac{3}{2}}} - \frac{E_{2}}{2 (t + 1)^{\frac{7}{2}}} + \frac{E_{3}}{2 (t + 1)^{\frac{9}{2}}} + \frac{3 E_{2}^{2}}{8 (t + 1)^{\frac{11}{2}}} - \frac{3 E_{2} E_{3}}{4 (t + 1)^{\frac{13}{2}}} + O(E_{1}) + O(\Delta^{6})\right) dt \\
 & = \frac{1}{\sqrt{A}} \left( 1 - \frac{1}{10} E_{2} + \frac{1}{14} E_{3} + \frac{1}{24} E_{2}^{2} - \frac{3}{44} E_{2} E_{3} + O(E_{1}) + O(\Delta^{6})\right) \end{align}

The advantage of expanding about the mean value of the arguments is now apparent; it reduces \scriptstyle{E_{1}} identically to zero, and so eliminates all terms involving \scriptstyle{E_{1}} - which otherwise would be the most numerous.

An ascending series for \scriptstyle{R_{J}} may be found in a similar way. There is a slight difficulty because \scriptstyle{R_{J}} is not fully symmetric; its dependence on its fourth argument, \scriptstyle{p}, is different from its dependence on \scriptstyle{x}, \scriptstyle{y} and \scriptstyle{z}. This is overcome by treating \scriptstyle{R_{J}} as a fully symmetric function of five arguments, two of which happen to have the same value \scriptstyle{p}. The mean value of the arguments is therefore take to be

A = \frac{x + y + z + 2 p}{5}

and the differences \scriptstyle{\Delta x}, \scriptstyle{\Delta y} \scriptstyle{\Delta z} and \scriptstyle{\Delta p} defined by

\begin{align}R_{J}(x,y,z,p) & = R_{J}(A (1 - \Delta x),A (1 - \Delta y),A (1 - \Delta z),A (1 - \Delta p)) \\
 & = \frac{1}{A^{\frac{3}{2}}} R_{J}(1 - \Delta x,1 - \Delta y,1 - \Delta z,1 - \Delta p) \end{align}

The elementary symmetric polynomials in \scriptstyle{\Delta x}, \scriptstyle{\Delta y}, \scriptstyle{\Delta z}, \scriptstyle{\Delta p} and (again) \scriptstyle{\Delta p} are in full

E1 = Δx + Δy + Δz + 2Δp = 0
E2 = ΔxΔy + ΔyΔz + 2ΔzΔp + Δp2 + 2ΔpΔx + ΔxΔz + 2ΔyΔp
E3 = ΔzΔp2 + ΔxΔp2 + 2ΔxΔyΔp + ΔxΔyΔz + 2ΔyΔzΔp + ΔyΔp2 + 2ΔxΔzΔp
E4 = ΔyΔzΔp2 + ΔxΔzΔp2 + ΔxΔyΔp2 + 2ΔxΔyΔzΔp
E5 = ΔxΔyΔzΔp2

However, it is possible to simplify the formulae for \scriptstyle{E_{2}}, \scriptstyle{E_{3}} and \scriptstyle{E_{4}} using the fact that \scriptstyle{E_{1} = 0}. Expressing the integrand in terms of these polynomials, performing a multidimensional Taylor expansion and integrating term-by-term as before...

\begin{align}R_{J}(x,y,z,p) & = \frac{3}{2 A^{\frac{3}{2}}} \int _{0}^{\infty}\frac{1}{\sqrt{(t + 1)^{5} - (t + 1)^{4} E_{1} + (t + 1)^{3} E_{2} - (t + 1)^{2} E_{3} + (t + 1) E_{4} - E_{5}}} dt \\
 & = \frac{3}{2 A^{\frac{3}{2}}} \int _{0}^{\infty}\left( \frac{1}{(t + 1)^{\frac{5}{2}}} - \frac{E_{2}}{2 (t + 1)^{\frac{9}{2}}} + \frac{E_{3}}{2 (t + 1)^{\frac{11}{2}}} + \frac{3 E_{2}^{2} - 4 E_{4}}{8 (t + 1)^{\frac{13}{2}}} + \frac{2 E_{5} - 3 E_{2} E_{3}}{4 (t + 1)^{\frac{15}{2}}} + O(E_{1}) + O(\Delta^{6})\right) dt \\
 & = \frac{1}{A^{\frac{3}{2}}} \left( 1 - \frac{3}{14} E_{2} + \frac{1}{6} E_{3} + \frac{9}{88} E_{2}^{2} - \frac{3}{22} E_{4} - \frac{9}{52} E_{2} E_{3} + \frac{3}{26} E_{5} + O(E_{1}) + O(\Delta^{6})\right) \end{align}

As with \scriptstyle{R_{J}}, by expanding about the mean value of the arguments, more than half the terms (those involving \scriptstyle{E_{1}}) are eliminated.

[edit] Negative arguments

In general, the arguments x, y, z of Carlson's integrals may not be real and negative, as this would place a branch point on the path of integration, making the integral ambiguous. However, if the second argument of \scriptstyle{R_C}, or the fourth argument, p, of \scriptstyle{R_J} is negative, then this results in a simple pole on the path of integration. In these cases the Cauchy principal value (finite part) of the integrals may be of interest; these are

\mathrm{p.v.}\; R_C(x, -y) = \sqrt{\frac{x}{x + y}}\,R_C(x + y, y),

and

\begin{align}\mathrm{p.v.}\; R_{J}(x,y,z,-p) & = \frac{(q - y) R_{J}(x,y,z,q) - 3 R_{F}(x,y,z) + 3 \sqrt{y} R_{C}(x z,- p q)}{y + p} \\
 & = \frac{(q - y) R_{J}(x,y,z,q) - 3 R_{F}(x,y,z) + 3 \sqrt{\frac{x y z}{x z + p q}} R_{C}(x z + p q,p q)}{y + p} \end{align}

where

q = y + \frac{(z - y) (y - x)}{y + p}.

which must be greater than zero for \scriptstyle{R_{J}(x,y,z,q)} to be evaluated. This may be arranged by permuting x, y and z so that the value of y is between that of x and z.

[edit] Numerical evaluation

The duplication theorem can be used for a fast and robust evaluation of the Carlson symmetric form of elliptic integrals and therefore also for the evaluation of Legendre-form of elliptic integrals. Let us calculate RF(x,y,z): first, define x0 = x, y0 = y and z0 = z. Then iterate the series

\lambda_n=\sqrt{x_ny_n}+\sqrt{y_nz_n}+\sqrt{z_nx_n},
x_{n+1}=\frac{x_n+\lambda_n}{4}, y_{n+1}=\frac{y_n+\lambda_n}{4}, z_{n+1}=\frac{z_n+\lambda_n}{4}

until the desired precision is reached: if x, y and z are non-negative, all of the series will converge quickly to a given value, say, μ. Therefore,

R_F\left(x,y,z\right)=R_F\left(\mu,\mu,\mu\right)=\mu^{-1/2}.

Evaluating RC(x,y) is much the same due to the relation

R_C\left(x,y\right)=R_F\left(x,y,y\right).

[edit] References and External links

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