1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171
|
[section:hankel Hankel Functions]
[section:cyl_hankel Cyclic Hankel Functions]
[h4 Synopsis]
#if !defined(__CUDACC__) && !defined(__CUDACC_RTC__)
template <class T1, class T2>
BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> cyl_hankel_1(T1 v, T2 x);
template <class T1, class T2, class ``__Policy``>
BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> cyl_hankel_1(T1 v, T2 x, const ``__Policy``&);
template <class T1, class T2>
BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> cyl_hankel_2(T1 v, T2 x);
template <class T1, class T2, class ``__Policy``>
BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> cyl_hankel_2(T1 v, T2 x, const ``__Policy``&);
#else // When using cuda we use namespace cuda::std:: instead of std::
template <class T1, class T2>
BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> cyl_hankel_1(T1 v, T2 x);
template <class T1, class T2, class ``__Policy``>
BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> cyl_hankel_1(T1 v, T2 x, const ``__Policy``&);
template <class T1, class T2>
BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> cyl_hankel_2(T1 v, T2 x);
template <class T1, class T2, class ``__Policy``>
BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> cyl_hankel_2(T1 v, T2 x, const ``__Policy``&);
#endif
[h4 Description]
The functions __cyl_hankel_1 and __cyl_hankel_2 return the result of the
[@http://dlmf.nist.gov/10.2#P3 Hankel functions] of the first and second kind respectively:
[expression ['cyl_hankel_1(v, x) = H[sub v][super (1)](x) = J[sub v](x) + i Y[sub v](x)]]
[expression ['cyl_hankel_2(v, x) = H[sub v][super (2)](x) = J[sub v](x) - i Y[sub v](x)]]
where:
['J[sub v](x)] is the Bessel function of the first kind, and ['Y[sub v](x)] is the Bessel function of the second kind.
The return type of these functions is computed using the __arg_promotion_rules
when T1 and T2 are different types. The functions are also optimised for the
relatively common case that T1 is an integer.
[optional_policy]
Note that while the arguments to these functions are real values, the results are complex.
That means that the functions can only be instantiated on types `float`, `double` and `long double`.
The functions have also been extended to operate over the whole range of ['v] and ['x]
(unlike __cyl_bessel_j and __cyl_neumann).
[h4 Performance]
These functions are generally more efficient than two separate calls to the underlying Bessel
functions as internally Bessel J and Y can be computed simultaneously.
[h4 Testing]
There are just a few spot tests to exercise all the special case handling - the bulk of the testing is done
on the Bessel functions upon which these are based.
[h4 Accuracy]
Refer to __cyl_bessel_j and __cyl_neumann.
[h4 Implementation]
For ['x < 0] the following reflection formulae are used:
[@http://functions.wolfram.com/Bessel-TypeFunctions/BesselJ/16/01/01/ [equation hankel1]]
[@http://functions.wolfram.com/Bessel-TypeFunctions/BesselY/16/01/01/ [equation hankel2]]
[@http://functions.wolfram.com/Bessel-TypeFunctions/BesselY/16/01/01/ [equation hankel3]]
Otherwise the implementation is trivially in terms of the Bessel J and Y functions.
Note however, that the Hankel functions compute the Bessel J and Y functions simultaneously,
and therefore a single Hankel function call is more efficient than two Bessel function calls.
The one exception is when ['v] is a small positive integer, in which case the usual Bessel function
routines for integer order are used.
[endsect] [/section:cyl_hankel Cyclic Hankel Functions]
[section:sph_hankel Spherical Hankel Functions]
[h4 Synopsis]
#if !defined(__CUDACC__) && !defined(__CUDACC_RTC__)
template <class T1, class T2>
BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> sph_hankel_1(T1 v, T2 x);
template <class T1, class T2, class ``__Policy``>
BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> sph_hankel_1(T1 v, T2 x, const ``__Policy``&);
template <class T1, class T2>
BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> sph_hankel_2(T1 v, T2 x);
template <class T1, class T2, class ``__Policy``>
BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> sph_hankel_2(T1 v, T2 x, const ``__Policy``&);
#else // When using cuda we use namespace cuda::std:: instead of std::
template <class T1, class T2>
BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> sph_hankel_1(T1 v, T2 x);
template <class T1, class T2, class ``__Policy``>
BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> sph_hankel_1(T1 v, T2 x, const ``__Policy``&);
template <class T1, class T2>
BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> sph_hankel_2(T1 v, T2 x);
template <class T1, class T2, class ``__Policy``>
BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> sph_hankel_2(T1 v, T2 x, const ``__Policy``&);
#endif
[h4 Description]
The functions __sph_hankel_1 and __sph_hankel_2 return the result of the
[@http://dlmf.nist.gov/10.47#P1 spherical Hankel functions] of the first and second kind respectively:
[equation hankel4]
[equation hankel5]
The return type of these functions is computed using the __arg_promotion_rules
when T1 and T2 are different types. The functions are also optimised for the
relatively common case that T1 is an integer.
[optional_policy]
Note that while the arguments to these functions are real values, the results are complex.
That means that the functions can only be instantiated on types `float`, `double` and `long double`.
The functions have also been extended to operate over the whole range of ['v] and ['x]
(unlike __cyl_bessel_j and __cyl_neumann).
[h4 Testing]
There are just a few spot tests to exercise all the special case handling - the bulk of the testing is done
on the Bessel functions upon which these are based.
[h4 Accuracy]
Refer to __cyl_bessel_j and __cyl_neumann.
[h4 Implementation]
These functions are trivially implemented in terms of __cyl_hankel_1 and __cyl_hankel_2.
[endsect] [/section:sph_hankel Spherical Hankel Functions]
[endsect] [/section:hankel Hankel Functions]
[/
Copyright 2012 John Maddock.
Distributed under the Boost Software License, Version 1.0.
(See accompanying file LICENSE_1_0.txt or copy at
http://www.boost.org/LICENSE_1_0.txt).
]
|