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11: Bibliography F
  • D. F. Fang and J. F. Shriner (1992) A computer program for the calculation of angular-momentum coupling coefficients. Comput. Phys. Comm. 70 (1), pp. 147–153.
  • FDLIBM (free C library)
  • S. Fempl (1960) Sur certaines sommes des intégral-cosinus. Bull. Soc. Math. Phys. Serbie 12, pp. 13–20 (French).
  • S. Fillebrown (1992) Faster computation of Bernoulli numbers. J. Algorithms 13 (3), pp. 431–445.
  • G. Freud (1969) On weighted polynomial approximation on the whole real axis. Acta Math. Acad. Sci. Hungar. 20, pp. 223–225.
  • 12: 26.5 Lattice Paths: Catalan Numbers
    26.5.1 C ( n ) = 1 n + 1 ( 2 n n ) = 1 2 n + 1 ( 2 n + 1 n ) = ( 2 n n ) ( 2 n n 1 ) = ( 2 n 1 n ) ( 2 n 1 n + 1 ) .
    Table 26.5.1: Catalan numbers.
    n C ( n ) n C ( n ) n C ( n )
    6 132 13 7 42900 20 65641 20420
    26.5.5 C ( n + 1 ) = k = 0 n / 2 ( n 2 k ) 2 n 2 k C ( k ) .
    13: Bibliography C
  • B. C. Carlson (1965) On computing elliptic integrals and functions. J. Math. and Phys. 44, pp. 36–51.
  • B. C. Carlson (1972a) An algorithm for computing logarithms and arctangents. Math. Comp. 26 (118), pp. 543–549.
  • B. C. Carlson (1979) Computing elliptic integrals by duplication. Numer. Math. 33 (1), pp. 1–16.
  • H. Cohen (1993) A Course in Computational Algebraic Number Theory. Springer-Verlag, Berlin-New York.
  • M. Colman, A. Cuyt, and J. Van Deun (2011) Validated computation of certain hypergeometric functions. ACM Trans. Math. Software 38 (2), pp. Art. 11, 20.
  • 14: Bibliography O
  • A. B. Olde Daalhuis (2000) On the asymptotics for late coefficients in uniform asymptotic expansions of integrals with coalescing saddles. Methods Appl. Anal. 7 (4), pp. 727–745.
  • T. Oliveira e Silva (2006) Computing π ( x ) : The combinatorial method. Revista do DETUA 4 (6), pp. 759–768.
  • J. Oliver (1977) An error analysis of the modified Clenshaw method for evaluating Chebyshev and Fourier series. J. Inst. Math. Appl. 20 (3), pp. 379–391.
  • F. W. J. Olver (1994a) Asymptotic expansions of the coefficients in asymptotic series solutions of linear differential equations. Methods Appl. Anal. 1 (1), pp. 1–13.
  • M. L. Overton (2001) Numerical Computing with IEEE Floating Point Arithmetic. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA.
  • 15: 26.9 Integer Partitions: Restricted Number and Part Size
    Equations (26.9.2)–(26.9.3) are examples of closed forms that can be computed explicitly for any positive integer k . …
    26.9.4 [ m n ] q = j = 1 n 1 q m n + j 1 q j , n 0 ,
    is the Gaussian polynomial (or q -binomial coefficient); see also §§17.2(i)17.2(ii). …
    26.9.5 n = 0 p k ( n ) q n = j = 1 k 1 1 q j = 1 + m = 1 [ k + m 1 m ] q q m ,
    16: Bibliography G
  • GAP (website) The GAP Group, Centre for Interdisciplinary Research in Computational Algebra, University of St. Andrews, United Kingdom.
  • W. Gautschi (1967) Computational aspects of three-term recurrence relations. SIAM Rev. 9 (1), pp. 24–82.
  • W. Gautschi (1970) Efficient computation of the complex error function. SIAM J. Numer. Anal. 7 (1), pp. 187–198.
  • A. Gil, J. Segura, and N. M. Temme (2014) Algorithm 939: computation of the Marcum Q-function. ACM Trans. Math. Softw. 40 (3), pp. 20:1–20:21.
  • D. Goldberg (1991) What every computer scientist should know about floating-point arithmetic. ACM Computing Surveys 23 (1), pp. 5–48.
  • 17: Bibliography R
  • J. Raynal (1979) On the definition and properties of generalized 6 - j  symbols. J. Math. Phys. 20 (12), pp. 2398–2415.
  • REDUCE (free interactive system)
  • G. F. Remenets (1973) Computation of Hankel (Bessel) functions of complex index and argument by numerical integration of a Schläfli contour integral. Ž. Vyčisl. Mat. i Mat. Fiz. 13, pp. 1415–1424, 1636.
  • E. Ya. Remez (1957) General Computation Methods of Chebyshev Approximation. The Problems with Linear Real Parameters. Publishing House of the Academy of Science of the Ukrainian SSR, Kiev.
  • J. Rys, M. Dupuis, and H. F. King (1983) Computation of electron repulsion integrals using the Rys quadrature method. J. Comput. Chem. 4 (2), pp. 154–175.
  • 18: 18.40 Methods of Computation
    §18.40 Methods of Computation
    §18.40(i) Computation of Polynomials
    A simple set of choices is spelled out in Gordon (1968) which gives a numerically stable algorithm for direct computation of the recursion coefficients in terms of the moments, followed by construction of the J-matrix and quadrature weights and abscissas, and we will follow this approach: Let N be a positive integer and define …and these can be used for the recursion coefficientsResults of low ( 2 to 3 decimal digits) precision for w ( x ) are easily obtained for N 10 to 20 . …
    19: Bibliography V
  • H. Van de Vel (1969) On the series expansion method for computing incomplete elliptic integrals of the first and second kinds. Math. Comp. 23 (105), pp. 61–69.
  • J. Van Deun and R. Cools (2008) Integrating products of Bessel functions with an additional exponential or rational factor. Comput. Phys. Comm. 178 (8), pp. 578–590.
  • C. Van Loan (1992) Computational Frameworks for the Fast Fourier Transform. Frontiers in Applied Mathematics, Vol. 10, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA.
  • H. Volkmer (2004a) Error estimates for Rayleigh-Ritz approximations of eigenvalues and eigenfunctions of the Mathieu and spheroidal wave equation. Constr. Approx. 20 (1), pp. 39–54.
  • M. N. Vrahatis, T. N. Grapsa, O. Ragos, and F. A. Zafiropoulos (1997a) On the localization and computation of zeros of Bessel functions. Z. Angew. Math. Mech. 77 (6), pp. 467–475.
  • 20: 18.39 Applications in the Physical Sciences
    Derivations of (18.39.42) appear in Bethe and Salpeter (1957, pp. 12–20), and Pauling and Wilson (1985, Chapter V and Appendix VII), where the derivations are based on (18.39.36), and is also the notation of Piela (2014, §4.7), typifying the common use of the associated Coulomb–Laguerre polynomials in theoretical quantum chemistry. … The discrete variable representations (DVR) analysis is simplest when based on the classical OP’s with their analytically known recursion coefficients (Table 3.5.17_5), or those non-classical OP’s which have analytically known recursion coefficients, making stable computation of the x i and w i , from the J-matrix as in §3.5(vi), straightforward. For many applications the natural weight functions are non-classical, and thus the OP’s and the determination of the Gaussian quadrature points and weights represent a computational challenge. Table 18.39.1 lists typical non-classical weight functions, many related to the non-classical Freud weights of §18.32, and §32.15, all of which require numerical computation of the recursion coefficients (i. …