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21: 18.22 Hahn Class: Recurrence Relations and Differences
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18.22.2 x ⁒ p n ⁑ ( x ) = A n ⁒ p n + 1 ⁑ ( x ) ( A n + C n ) ⁒ p n ⁑ ( x ) + C n ⁒ p n 1 ⁑ ( x ) ,
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18.22.5 ( a + i ⁒ x ) ⁒ q n ⁑ ( x ) = A ~ n ⁒ q n + 1 ⁑ ( x ) ( A ~ n + C ~ n ) ⁒ q n ⁑ ( x ) + C ~ n ⁒ q n 1 ⁑ ( x ) ,
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18.22.10 A ⁑ ( x ) ⁒ p n ⁑ ( x + 1 ) ( A ⁑ ( x ) + C ⁑ ( x ) ) ⁒ p n ⁑ ( x ) + C ⁑ ( x ) ⁒ p n ⁑ ( x 1 ) n ⁒ ( n + α + β + 1 ) ⁒ p n ⁑ ( x ) = 0 ,
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18.22.12 A ⁑ ( x ) ⁒ p n ⁑ ( x + 1 ) ( A ⁑ ( x ) + C ⁑ ( x ) ) ⁒ p n ⁑ ( x ) + C ⁑ ( x ) ⁒ p n ⁑ ( x 1 ) + λ n ⁒ p n ⁑ ( x ) = 0 .
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18.22.14 A ⁑ ( x ) ⁒ p n ⁑ ( x + i ) ( A ⁑ ( x ) + C ⁑ ( x ) ) ⁒ p n ⁑ ( x ) + C ⁑ ( x ) ⁒ p n ⁑ ( x i ) + n ⁒ ( n + 2 ⁒ ⁑ ( a + b ) 1 ) ⁒ p n ⁑ ( x ) = 0 ,
22: 34.14 Tables
β–ΊBiedenharn and Louck (1981) give tables of algebraic expressions for Clebsch–Gordan coefficients and 6 ⁒ j symbols, together with a bibliography of tables produced prior to 1975. In Varshalovich et al. (1988) algebraic expressions for the Clebsch–Gordan coefficients with all parameters 5 and numerical values for all parameters 3 are given on pp. …
23: 5.8 Infinite Products
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5.8.4 k = 1 m a k = k = 1 m b k ,
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5.8.5 k = 0 ( a 1 + k ) ⁒ ( a 2 + k ) ⁒ β‹― ⁒ ( a m + k ) ( b 1 + k ) ⁒ ( b 2 + k ) ⁒ β‹― ⁒ ( b m + k ) = Ξ“ ⁑ ( b 1 ) ⁒ Ξ“ ⁑ ( b 2 ) ⁒ β‹― ⁒ Ξ“ ⁑ ( b m ) Ξ“ ⁑ ( a 1 ) ⁒ Ξ“ ⁑ ( a 2 ) ⁒ β‹― ⁒ Ξ“ ⁑ ( a m ) ,
24: 7.24 Approximations
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  • Luke (1969b, pp. 323–324) covers 1 2 ⁒ Ο€ ⁒ erf ⁑ x and e x 2 ⁒ F ⁑ ( x ) for 3 x 3 (the Chebyshev coefficients are given to 20D); Ο€ ⁒ x ⁒ e x 2 ⁒ erfc ⁑ x and 2 ⁒ x ⁒ F ⁑ ( x ) for x 3 (the Chebyshev coefficients are given to 20D and 15D, respectively). Coefficients for the Fresnel integrals are given on pp. 328–330 (20D).

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  • Bulirsch (1967) provides Chebyshev coefficients for the auxiliary functions f ⁑ ( x ) and g ⁑ ( x ) for x 3 (15D).

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  • Schonfelder (1978) gives coefficients of Chebyshev expansions for x 1 ⁒ erf ⁑ x on 0 x 2 , for x ⁒ e x 2 ⁒ erfc ⁑ x on [ 2 , ) , and for e x 2 ⁒ erfc ⁑ x on [ 0 , ) (30D).

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  • Shepherd and Laframboise (1981) gives coefficients of Chebyshev series for ( 1 + 2 ⁒ x ) ⁒ e x 2 ⁒ erfc ⁑ x on ( 0 , ) (22D).

  • 25: 13.5 Continued Fractions
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    13.5.1 M ⁑ ( a , b , z ) M ⁑ ( a + 1 , b + 1 , z ) = 1 + u 1 ⁒ z 1 + u 2 ⁒ z 1 + β‹― ,
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    13.5.3 U ⁑ ( a , b , z ) U ⁑ ( a , b 1 , z ) = 1 + v 1 / z 1 + v 2 / z 1 + β‹― ,
    26: 13.17 Continued Fractions
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    13.17.1 z ⁒ M ΞΊ , ΞΌ ⁑ ( z ) M ΞΊ 1 2 , ΞΌ + 1 2 ⁑ ( z ) = 1 + u 1 ⁒ z 1 + u 2 ⁒ z 1 + β‹― ,
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    13.17.3 W ΞΊ , ΞΌ ⁑ ( z ) z ⁒ W ΞΊ 1 2 , ΞΌ 1 2 ⁑ ( z ) = 1 + v 1 / z 1 + v 2 / z 1 + β‹― ,
    27: 18.3 Definitions
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    Table 18.3.1: Orthogonality properties for classical OP’s: intervals, weight functions, standardizations, leading coefficients, and parameter constraints. …
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    Name p n ⁑ ( x ) ( a , b ) w ⁑ ( x ) h n k n k ~ n / k n Constraints
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    β–ΊFor explicit power series coefficients up to n = 12 for these polynomials and for coefficients up to n = 6 for Jacobi and ultraspherical polynomials see Abramowitz and Stegun (1964, pp. 793–801). …
    28: 33.11 Asymptotic Expansions for Large ρ
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    33.11.1 H β„“ ± ⁑ ( Ξ· , ρ ) e ± i ⁒ ΞΈ β„“ ⁑ ( Ξ· , ρ ) ⁒ k = 0 ( a ) k ⁒ ( b ) k k ! ⁒ ( ± 2 ⁒ i ⁒ ρ ) k ,
    29: 9.19 Approximations
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  • Prince (1975) covers Ai ⁑ ( x ) , Ai ⁑ ( x ) , Bi ⁑ ( x ) , Bi ⁑ ( x ) . The Chebyshev coefficients are given to 10-11D. Fortran programs are included. See also Razaz and Schonfelder (1981).

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  • Németh (1992, Chapter 8) covers Ai ⁑ ( x ) , Ai ⁑ ( x ) , Bi ⁑ ( x ) , Bi ⁑ ( x ) , and integrals 0 x Ai ⁑ ( t ) ⁒ d t , 0 x Bi ⁑ ( t ) ⁒ d t , 0 x 0 v Ai ⁑ ( t ) ⁒ d t ⁒ d v , 0 x 0 v Bi ⁑ ( t ) ⁒ d t ⁒ d v (see also (9.10.20) and (9.10.21)). The Chebyshev coefficients are given to 15D. Chebyshev coefficients are also given for expansions of the second and higher (real) zeros of Ai ⁑ ( x ) , Ai ⁑ ( x ) , Bi ⁑ ( x ) , Bi ⁑ ( x ) , again to 15D.

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  • Razaz and Schonfelder (1980) covers Ai ⁑ ( x ) , Ai ⁑ ( x ) , Bi ⁑ ( x ) , Bi ⁑ ( x ) . The Chebyshev coefficients are given to 30D.

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  • Corless et al. (1992) describe a method of approximation based on subdividing β„‚ into a triangular mesh, with values of Ai ⁑ ( z ) , Ai ⁑ ( z ) stored at the nodes. Ai ⁑ ( z ) and Ai ⁑ ( z ) are then computed from Taylor-series expansions centered at one of the nearest nodes. The Taylor coefficients are generated by recursion, starting from the stored values of Ai ⁑ ( z ) , Ai ⁑ ( z ) at the node. Similarly for Bi ⁑ ( z ) , Bi ⁑ ( z ) .

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  • MacLeod (1994) supplies Chebyshev-series expansions to cover Gi ⁑ ( x ) for 0 x < and Hi ⁑ ( x ) for < x 0 . The Chebyshev coefficients are given to 20D.

  • 30: 29.7 Asymptotic Expansions
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    29.7.1 a Ξ½ m ⁑ ( k 2 ) p ⁒ ΞΊ Ο„ 0 Ο„ 1 ⁒ ΞΊ 1 Ο„ 2 ⁒ ΞΊ 2 β‹― ,
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    29.7.3 Ο„ 0 = 1 2 3 ⁒ ( 1 + k 2 ) ⁒ ( 1 + p 2 ) ,
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    29.7.4 Ο„ 1 = p 2 6 ⁒ ( ( 1 + k 2 ) 2 ⁒ ( p 2 + 3 ) 4 ⁒ k 2 ⁒ ( p 2 + 5 ) ) .
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    29.7.6 Ο„ 2 = 1 2 10 ⁒ ( 1 + k 2 ) ⁒ ( 1 k 2 ) 2 ⁒ ( 5 ⁒ p 4 + 34 ⁒ p 2 + 9 ) ,
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    29.7.7 Ο„ 3 = p 2 14 ⁒ ( ( 1 + k 2 ) 4 ⁒ ( 33 ⁒ p 4 + 410 ⁒ p 2 + 405 ) 24 ⁒ k 2 ⁒ ( 1 + k 2 ) 2 ⁒ ( 7 ⁒ p 4 + 90 ⁒ p 2 + 95 ) + 16 ⁒ k 4 ⁒ ( 9 ⁒ p 4 + 130 ⁒ p 2 + 173 ) ) ,