NAG Library Routine Document

s17aqf (bessel_y0_real_vector)

1
Purpose

s17aqf returns an array of values of the Bessel function Y0x.

2
Specification

Fortran Interface
Subroutine s17aqf ( n, x, f, ivalid, ifail)
Integer, Intent (In):: n
Integer, Intent (Inout):: ifail
Integer, Intent (Out):: ivalid(n)
Real (Kind=nag_wp), Intent (In):: x(n)
Real (Kind=nag_wp), Intent (Out):: f(n)
C Header Interface
#include <nagmk26.h>
void  s17aqf_ (const Integer *n, const double x[], double f[], Integer ivalid[], Integer *ifail)

3
Description

s17aqf evaluates an approximation to the Bessel function of the second kind Y0xi for an array of arguments xi, for i=1,2,,n.
Note:  Y0x is undefined for x0 and the routine will fail for such arguments.
The routine is based on four Chebyshev expansions:
For 0<x8,
Y0 x = 2π lnx r=0 ar Tr t + r=0 br Tr t ,   with ​ t = 2 x8 2 - 1 .  
For x>8,
Y0 x = 2πx P0 x sinx-π4 + Q0 x cosx-π4  
where P0x=r=0crTrt,
and Q0x= 8xr=0drTrt,with ​ t=2 8x 2-1.
For x near zero, Y0x2π lnx2+γ , where γ denotes Euler's constant. This approximation is used when x is sufficiently small for the result to be correct to machine precision.
For very large x, it becomes impossible to provide results with any reasonable accuracy (see Section 7), hence the routine fails. Such arguments contain insufficient information to determine the phase of oscillation of Y0x; only the amplitude, 2πn , can be determined and this is returned on soft failure. The range for which this occurs is roughly related to machine precision; the routine will fail if x1/machine precision (see the Users' Note for your implementation for details).

4
References

NIST Digital Library of Mathematical Functions
Clenshaw C W (1962) Chebyshev Series for Mathematical Functions Mathematical tables HMSO

5
Arguments

1:     n – IntegerInput
On entry: n, the number of points.
Constraint: n0.
2:     xn – Real (Kind=nag_wp) arrayInput
On entry: the argument xi of the function, for i=1,2,,n.
Constraint: xi>0.0, for i=1,2,,n.
3:     fn – Real (Kind=nag_wp) arrayOutput
On exit: Y0xi, the function values.
4:     ivalidn – Integer arrayOutput
On exit: ivalidi contains the error code for xi, for i=1,2,,n.
ivalidi=0
No error.
ivalidi=1
On entry,xi is too large. fi contains the amplitude of the Y0 oscillation, 2πxi .
ivalidi=2
On entry,xi0.0, Y0 is undefined. fi contains 0.0.
5:     ifail – IntegerInput/Output
On entry: ifail must be set to 0, -1 or 1. If you are unfamiliar with this argument you should refer to Section 3.4 in How to Use the NAG Library and its Documentation for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value -1 or 1 is recommended. If the output of error messages is undesirable, then the value 1 is recommended. Otherwise, if you are not familiar with this argument, the recommended value is 0. When the value -1 or 1 is used it is essential to test the value of ifail on exit.
On exit: ifail=0 unless the routine detects an error or a warning has been flagged (see Section 6).

6
Error Indicators and Warnings

If on entry ifail=0 or -1, explanatory error messages are output on the current error message unit (as defined by x04aaf).
Errors or warnings detected by the routine:
ifail=1
On entry, at least one value of x was invalid.
Check ivalid for more information.
ifail=2
On entry, n=value.
Constraint: n0.
ifail=-99
An unexpected error has been triggered by this routine. Please contact NAG.
See Section 3.9 in How to Use the NAG Library and its Documentation for further information.
ifail=-399
Your licence key may have expired or may not have been installed correctly.
See Section 3.8 in How to Use the NAG Library and its Documentation for further information.
ifail=-999
Dynamic memory allocation failed.
See Section 3.7 in How to Use the NAG Library and its Documentation for further information.

7
Accuracy

Let δ be the relative error in the argument and E be the absolute error in the result. (Since Y0x oscillates about zero, absolute error and not relative error is significant, except for very small x.)
If δ is somewhat larger than the machine representation error (e.g., if δ is due to data errors etc.), then E and δ are approximately related by
E x Y1 x δ  
(provided E is also within machine bounds). Figure 1 displays the behaviour of the amplification factor xY1x.
However, if δ is of the same order as the machine representation errors, then rounding errors could make E slightly larger than the above relation predicts.
For very small x, the errors are essentially independent of δ and the routine should provide relative accuracy bounded by the machine precision.
For very large x, the above relation ceases to apply. In this region, Y0x 2πx sinx- π4. The amplitude 2πx  can be calculated with reasonable accuracy for all x, but sinx-π4 cannot. If x- π4  is written as 2Nπ+θ where N is an integer and 0θ<2π, then sinx- π4 is determined by θ only. If xδ-1, θ cannot be determined with any accuracy at all. Thus if x is greater than, or of the order of the inverse of machine precision, it is impossible to calculate the phase of Y0x and the routine must fail.
Figure 1
Figure 1

8
Parallelism and Performance

s17aqf is not threaded in any implementation.

9
Further Comments

None.

10
Example

This example reads values of x from a file, evaluates the function at each value of xi and prints the results.

10.1
Program Text

Program Text (s17aqfe.f90)

10.2
Program Data

Program Data (s17aqfe.d)

10.3
Program Results

Program Results (s17aqfe.r)