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big q-Jacobi polynomials

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21: 8.27 Approximations
  • DiDonato (1978) gives a simple approximation for the function F ( p , x ) = x p e x 2 / 2 x e t 2 / 2 t p d t (which is related to the incomplete gamma function by a change of variables) for real p and large positive x . This takes the form F ( p , x ) = 4 x / h ( p , x ) , approximately, where h ( p , x ) = 3 ( x 2 p ) + ( x 2 p ) 2 + 8 ( x 2 + p ) and is shown to produce an absolute error O ( x 7 ) as x .

  • Luke (1969b, p. 186) gives hypergeometric polynomial representations that converge uniformly on compact subsets of the z -plane that exclude z = 0 and are valid for | ph z | < π .

  • Verbeeck (1970) gives polynomial and rational approximations for E p ( x ) = ( e x / x ) P ( z ) , approximately, where P ( z ) denotes a quotient of polynomials of equal degree in z = x 1 .

  • 22: 2.8 Differential Equations with a Parameter
    For example, u can be the order of a Bessel function or degree of an orthogonal polynomial. …
    2.8.11 W n , 1 ( u , ξ ) = e u ξ ( s = 0 n 1 A s ( ξ ) u s + O ( 1 u n ) ) , ξ 𝚫 1 ( α 1 ) ,
    2.8.12 W n , 2 ( u , ξ ) = e u ξ ( s = 0 n 1 ( 1 ) s A s ( ξ ) u s + O ( 1 u n ) ) , ξ 𝚫 2 ( α 2 ) ,
    2.8.15 W n , 1 ( u , ξ ) = Ai ( u 2 / 3 ξ ) ( s = 0 n 1 A s ( ξ ) u 2 s + O ( 1 u 2 n 1 ) ) + Ai ( u 2 / 3 ξ ) ( s = 0 n 2 B s ( ξ ) u 2 s + ( 4 / 3 ) + O ( 1 u 2 n 1 ) ) ,
    2.8.16 W n , 2 ( u , ξ ) = Bi ( u 2 / 3 ξ ) ( s = 0 n 1 A s ( ξ ) u 2 s + O ( 1 u 2 n 1 ) ) + Bi ( u 2 / 3 ξ ) ( s = 0 n 2 B s ( ξ ) u 2 s + ( 4 / 3 ) + O ( 1 u 2 n 1 ) ) .
    23: 19.27 Asymptotic Approximations and Expansions
    19.27.2 R F ( x , y , z ) = 1 2 z ( ln 8 z a + g ) ( 1 + O ( a z ) ) , a / z 0 .
    19.27.3 R F ( x , y , z ) = R F ( 0 , y , z ) 1 h ( x h + O ( x h ) ) , x / h 0 .
    19.27.4 R G ( x , y , z ) = z 2 ( 1 + O ( a z ln z a ) ) , a / z 0 .
    19.27.5 R G ( x , y , z ) = R G ( 0 , y , z ) + x O ( x / h ) , x / h 0 .
    19.27.6 R G ( 0 , y , z ) = z 2 + y 8 z ( ln ( 16 z y ) 1 ) ( 1 + O ( y z ) ) , y / z 0 .
    24: 27.11 Asymptotic Formulas: Partial Sums
    27.11.1 n x f ( n ) = F ( x ) + O ( g ( x ) ) ,
    where F ( x ) is a known function of x , and O ( g ( x ) ) represents the error, a function of smaller order than F ( x ) for all x in some prescribed range. …
    27.11.2 n x d ( n ) = x ln x + ( 2 γ 1 ) x + O ( x ) ,
    Dirichlet’s divisor problem (unsolved as of 2022) is to determine the least number θ 0 such that the error term in (27.11.2) is O ( x θ ) for all θ > θ 0 . …
    27.11.3 n x d ( n ) n = 1 2 ( ln x ) 2 + 2 γ ln x + O ( 1 ) ,
    25: 3.7 Ordinary Differential Equations
    This converts the problem into a tridiagonal matrix problem in which the elements of the matrix are polynomials in λ ; compare §3.2(vi). …
    3.7.18 w n + 1 = w n + 1 6 ( k 1 + 2 k 2 + 2 k 3 + k 4 ) + O ( h 5 ) ,
    The order estimate O ( h 5 ) holds if the solution w ( z ) has five continuous derivatives. …
    w n + 1 = w n + 1 6 h ( 6 w n + k 1 + k 2 + k 3 ) + O ( h 5 ) ,
    The order estimates O ( h 5 ) hold if the solution w ( z ) has five continuous derivatives. …
    26: 18.28 Askey–Wilson Class
    Duality
    §18.28(v) Continuous q -Ultraspherical Polynomials
    These polynomials are also called Rogers polynomials.
    §18.28(vi) Continuous q -Hermite Polynomials
    From Askey–Wilson to Big q -Jacobi
    27: 8.11 Asymptotic Approximations and Expansions
    8.11.11 γ ( 1 a , x ) = x a 1 ( cos ( π a ) + sin ( π a ) π ( 2 π F ( y ) + 2 3 2 π a ( 1 y 2 ) ) e y 2 + O ( a 1 ) ) ,
    For related expansions involving Hermite polynomials see Pagurova (1965). …
    28: 24.18 Physical Applications
    §24.18 Physical Applications
    Bernoulli polynomials appear in statistical physics (Ordóñez and Driebe (1996)), in discussions of Casimir forces (Li et al. (1991)), and in a study of quark-gluon plasma (Meisinger et al. (2002)). Euler polynomials also appear in statistical physics as well as in semi-classical approximations to quantum probability distributions (Ballentine and McRae (1998)).
    29: 13.14 Definitions and Basic Properties
    13.14.14 M κ , μ ( z ) = z μ + 1 2 ( 1 + O ( z ) ) , 2 μ 1 , 2 , 3 , .
    13.14.15 W 1 2 ± μ + n , μ ( z ) = ( 1 ) n ( 1 ± 2 μ ) n z 1 2 ± μ + O ( z 3 2 ± μ ) .
    13.14.19 W κ , 0 ( z ) = z Γ ( 1 2 κ ) ( ln z + ψ ( 1 2 κ ) + 2 γ ) + O ( z 3 / 2 ln z ) .
    Except when μ κ = 1 2 , 3 2 , (polynomial cases), …
    30: 3.11 Approximation Techniques
    §3.11(i) Minimax Polynomial Approximations
    The Chebyshev polynomials T n are given by … Suppose a function f ( x ) is approximated by the polynomialSplines are defined piecewise and usually by low-degree polynomials. …