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Four ways to compute the inverse of the complete elliptic integral of the first kind. (English) Zbl 1360.65080
Summary: The complete elliptic integral of the first kind arises in many applications. This article furnishes four different ways to compute the inverse of the elliptic integral. One motive for this study is simply that the author needed to compute the inverse integral for an application. Another is to develop a case study comparing different options for solving transcendental equations like those in the author’s book [Solving transcendental equations. The Chebyshev polynomial proxy and other numerical rootfinders, perturbation series, and oracles. Philadelphia, PA: Society for Industrial and Applied Mathematics (SIAM) (2014; Zbl 1311.65047)]. A third motive is to develop analytical approximations, more useful to theorists than mere numbers. A fourth motive is to provide robust “black box” software for computing this function. The first solution strategy is “polynomialization” which replaces the elliptic integral by an exponentially convergent series of Chebyshev polynomials. The transcendental equation becomes a polynomial equation which is easily solved by finding the eigenvalues of the Chebyshev companion matrix. (The numerically ill-conditioned step of converting from the Chebyshev to monomial basis is never necessary). The second approximation is a regular perturbation series, accurate where the modulus is small. The third is a power-and-exponential series that converges over the entire range parameter range, albeit only sub-exponentially in the limit of zero modulus. Lastly, Newton’s iteration is promoted from a local iteration to a global method by a Never-Failing Newton’s Iteration (NFNI) in the form of the exponential of the ratio of a linear function divided by another linear polynomial. A short Matlab implementation is provided, easily translatable into other languages. The Matlab/Newton code is recommended for numerical purposes. The other methods are presented because (i) all are broadly applicable strategies useful for other rootfinding and inversion problems (ii) series and substitutions are often much more useful to theorists than numerical software and (iii) the Never-Failing Newton’s Iteration was discovered only after a great deal of messing about with power series, inverse power series and so on.
Reviewer: Reviewer (Berlin)

MSC:
65D20 Computation of special functions and constants, construction of tables
33E05 Elliptic functions and integrals
33F05 Numerical approximation and evaluation of special functions
Software:
DLMF; Equator; Matlab
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