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1: 22.3 Graphics
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Figure 22.3.26: Density plot of | sn ( 5 , k ) | as a function of complex k 2 , 10 ( k 2 ) 20 , 10 ( k 2 ) 10 . … Magnify
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Figure 22.3.27: Density plot of | sn ( 10 , k ) | as a function of complex k 2 , 10 ( k 2 ) 20 , 10 ( k 2 ) 10 . … Magnify
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Figure 22.3.28: Density plot of | sn ( 20 , k ) | as a function of complex k 2 , 10 ( k 2 ) 20 , 10 ( k 2 ) 10 . … Magnify
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Figure 22.3.29: Density plot of | sn ( 30 , k ) | as a function of complex k 2 , 10 ( k 2 ) 20 , 10 ( k 2 ) 10 . … Magnify
2: 10.75 Tables
  • Zhang and Jin (1996, pp. 185–195) tabulates J n ( x ) , J n ( x ) , Y n ( x ) , Y n ( x ) , n = 0 ( 1 ) 10 ( 10 ) 50 , 100 , x = 1 , 5, 10, 25, 50, 100, 9S; J n + α ( x ) , J n + α ( x ) , Y n + α ( x ) , Y n + α ( x ) , n = 0 ( 1 ) 5 , 10 , 30 , 50 , 100 , α = 1 4 , 1 3 , 1 2 , 2 3 , 3 4 , x = 1 , 5 , 10 , 50 , 8S; real and imaginary parts of J n + α ( z ) , J n + α ( z ) , Y n + α ( z ) , Y n + α ( z ) , n = 0 ( 1 ) 15 , 20 ( 10 ) 50 , 100 , α = 0 , 1 2 , z = 4 + 2 i , 20 + 10 i , 8S.

  • Zhang and Jin (1996, pp. 240–250) tabulates I n ( x ) , I n ( x ) , K n ( x ) , K n ( x ) , n = 0 ( 1 ) 10 ( 10 ) 50 , 100 , x = 1 , 5 , 10 , 25 , 50 , 100 , 9S; I n + α ( x ) , I n + α ( x ) , K n + α ( x ) , K n + α ( x ) , n = 0 ( 1 ) 5 , 10, 30, 50, 100, α = 1 4 , 1 3 , 1 2 , 2 3 , 3 4 , x = 1 , 5, 10, 50, 8S; real and imaginary parts of I n + α ( z ) , I n + α ( z ) , K n + α ( z ) , K n + α ( z ) , n = 0 ( 1 ) 15 , 20(10)50, 100, α = 0 , 1 2 , z = 4 + 2 i , 20 + 10 i , 8S.

  • Zhang and Jin (1996, pp. 296–305) tabulates 𝗃 n ( x ) , 𝗃 n ( x ) , 𝗒 n ( x ) , 𝗒 n ( x ) , 𝗂 n ( 1 ) ( x ) , 𝗂 n ( 1 ) ( x ) , 𝗄 n ( x ) , 𝗄 n ( x ) , n = 0 ( 1 ) 10 ( 10 ) 30 , 50, 100, x = 1 , 5, 10, 25, 50, 100, 8S; x 𝗃 n ( x ) , ( x 𝗃 n ( x ) ) , x 𝗒 n ( x ) , ( x 𝗒 n ( x ) ) (Riccati–Bessel functions and their derivatives), n = 0 ( 1 ) 10 ( 10 ) 30 , 50, 100, x = 1 , 5, 10, 25, 50, 100, 8S; real and imaginary parts of 𝗃 n ( z ) , 𝗃 n ( z ) , 𝗒 n ( z ) , 𝗒 n ( z ) , 𝗂 n ( 1 ) ( z ) , 𝗂 n ( 1 ) ( z ) , 𝗄 n ( z ) , 𝗄 n ( z ) , n = 0 ( 1 ) 15 , 20(10)50, 100, z = 4 + 2 i , 20 + 10 i , 8S. (For the notation replace j , y , i , k by 𝗃 , 𝗒 , 𝗂 ( 1 ) , 𝗄 , respectively.)

  • 3: 20.10 Integrals
    20.10.1 0 x s 1 θ 2 ( 0 | i x 2 ) d x = 2 s ( 1 2 s ) π s / 2 Γ ( 1 2 s ) ζ ( s ) , s > 1 ,
    20.10.2 0 x s 1 ( θ 3 ( 0 | i x 2 ) 1 ) d x = π s / 2 Γ ( 1 2 s ) ζ ( s ) , s > 1 ,
    20.10.3 0 x s 1 ( 1 θ 4 ( 0 | i x 2 ) ) d x = ( 1 2 1 s ) π s / 2 Γ ( 1 2 s ) ζ ( s ) , s > 0 .
    Let s , , and β be constants such that s > 0 , > 0 , and | β | + | β | . …
    20.10.4 0 e s t θ 1 ( β π 2 | i π t 2 ) d t = 0 e s t θ 2 ( ( 1 + β ) π 2 | i π t 2 ) d t = s sinh ( β s ) sech ( s ) ,
    4: 6.19 Tables
  • Abramowitz and Stegun (1964, Chapter 5) includes the real and imaginary parts of z e z E 1 ( z ) , x = 19 ( 1 ) 20 , y = 0 ( 1 ) 20 , 6D; e z E 1 ( z ) , x = 4 ( .5 ) 2 , y = 0 ( .2 ) 1 , 6D; E 1 ( z ) + ln z , x = 2 ( .5 ) 2.5 , y = 0 ( .2 ) 1 , 6D.

  • Zhang and Jin (1996, pp. 690–692) includes the real and imaginary parts of E 1 ( z ) , ± x = 0.5 , 1 , 3 , 5 , 10 , 15 , 20 , 50 , 100 , y = 0 ( .5 ) 1 ( 1 ) 5 ( 5 ) 30 , 50 , 100 , 8S.

  • 5: Software Index
    Open Source With Book Commercial
    10.77(vi) Bessel Functions–Imaginary Order and Real Argument
    16.27(ii) Real Arguments a
    20 Theta Functions
    22.22(ii) Real Argument
  • Commercial Software.

    Such software ranges from a collection of reusable software parts (e.g., a library) to fully functional interactive computing environments with an associated computing language. Such software is usually professionally developed, tested, and maintained to high standards. It is available for purchase, often with accompanying updates and consulting support.

  • 6: 9.18 Tables
  • Zhang and Jin (1996, p. 337) tabulates Ai ( x ) , Ai ( x ) , Bi ( x ) , Bi ( x ) for x = 0 ( 1 ) 20 to 8S and for x = 20 ( 1 ) 0 to 9D.

  • Woodward and Woodward (1946) tabulates the real and imaginary parts of Ai ( z ) , Ai ( z ) , Bi ( z ) , Bi ( z ) for z = 2.4 ( .2 ) 2.4 , z = 2.4 ( .2 ) 0 . Precision is 4D.

  • Harvard University (1945) tabulates the real and imaginary parts of h 1 ( z ) , h 1 ( z ) , h 2 ( z ) , h 2 ( z ) for x 0 z x 0 , 0 z y 0 , | x 0 + i y 0 | < 6.1 , with interval 0.1 in z and z . Precision is 8D. Here h 1 ( z ) = 2 4 / 3 3 1 / 6 i Ai ( e π i / 3 z ) , h 2 ( z ) = 2 4 / 3 3 1 / 6 i Ai ( e π i / 3 z ) .

  • Corless et al. (1992) gives the real and imaginary parts of β k for k = 1 ( 1 ) 13 ; 14S.

  • Nosova and Tumarkin (1965) tabulates e 0 ( x ) π Hi ( x ) , e 0 ( x ) = π Hi ( x ) , e ~ 0 ( x ) π Gi ( x ) , e ~ 0 ( x ) = π Gi ( x ) for x = 1 ( .01 ) 10 ; 7D. Also included are the real and imaginary parts of e 0 ( z ) and i e 0 ( z ) , where z = i y and y = 0 ( .01 ) 9 ; 6-7D.

  • 7: 25.12 Polylogarithms
    When z = e i θ , 0 θ 2 π , (25.12.1) becomes … The series also converges when | z | = 1 , provided that s > 1 . … valid when s > 0 and | ph ( 1 z ) | < π , or s > 1 and z = 1 . … valid when s > 0 , a > 0 or s > 1 , a = 0 . When s = 2 and e 2 π i a = z , (25.12.13) becomes (25.12.4). …
    8: 7.23 Tables
  • Zhang and Jin (1996, pp. 638, 640–641) includes the real and imaginary parts of erf z , x [ 0 , 5 ] , y = 0.5 ( .5 ) 3 , 7D and 8D, respectively; the real and imaginary parts of x e ± i t 2 d t , ( 1 / π ) e i ( x 2 + ( π / 4 ) ) x e ± i t 2 d t , x = 0 ( .5 ) 20 ( 1 ) 25 , 8D, together with the corresponding modulus and phase to 8D and 6D (degrees), respectively.

  • 9: 36.5 Stokes Sets
    where j denotes a real critical point (36.4.1) or (36.4.2), and μ denotes a critical point with complex t or s , t , connected with j by a steepest-descent path (that is, a path where Φ = constant ) in complex t or ( s , t ) space. In the following subsections, only Stokes sets involving at least one real saddle are included unless stated otherwise. … This part of the Stokes set connects two complex saddles. … In Figure 36.5.4 the part of the Stokes surface inside the bifurcation set connects two complex saddles. The distribution of real and complex critical points in Figures 36.5.5 and 36.5.6 follows from consistency with Figure 36.5.1 and the fact that there are four real saddles in the inner regions. …
    10: 18.40 Methods of Computation
    Given the power moments, μ n = a b x n d μ ( x ) , n = 0 , 1 , 2 , , can these be used to find a unique μ ( x ) , a non-decreasing, real, function of x , in the case that the moment problem is determined? Should a unique solution not exist the moment problem is then indeterminant. … In what follows we consider only the simple, illustrative, case that μ ( x ) is continuously differentiable so that d μ ( x ) = w ( x ) d x , with w ( x ) real, positive, and continuous on a real interval [ a , b ] . The strategy will be to: 1) use the moments to determine the recursion coefficients α n , β n of equations (18.2.11_5) and (18.2.11_8); then, 2) to construct the quadrature abscissas x i and weights (or Christoffel numbers) w i from the J-matrix of §3.5(vi), equations (3.5.31) and(3.5.32). … It is now necessary to take the limit ε 0 + of F ( x + i ε ) , and the imaginary part is the required Stieltjes–Perron inversion: …The question is then: how is this possible given only F N ( z ) , rather than F ( z ) itself? F N ( z ) often converges to smooth results for z off the real axis for z at a distance greater than the pole spacing of the x n , this may then be followed by approximate numerical analytic continuation via fitting to lower order continued fractions (either Padé, see §3.11(iv), or pointwise continued fraction approximants, see Schlessinger (1968, Appendix)), to F N ( z ) and evaluating these on the real axis in regions of higher pole density that those of the approximating function. Results of low ( 2 to 3 decimal digits) precision for w ( x ) are easily obtained for N 10 to 20 . …