Bessel Function of the First Kind

This module computes the Bessel function of the first kind or its \(n\)th derivative

\[\frac{\partial^n J_{\nu}(z)}{\partial z^n},\]

where

  • \(n \in \mathbb{N}\) is the order of the derivative (\(n = 0\) indicates no derivative).

  • \(\nu \in \mathbb{R}\) is the order of the Bessel function.

  • \(z \in \mathbb{C}\) is the input argument.

Syntax

This function has the following syntaxes depending on whether it is used in Python or Cython, or the input argument z is complex or real.

Interface

Input Type

Function Signature

Python

Real or Complex

besselj(nu, z, n=0)

Cython

Real

double besselj(double nu, double z, int n)

Complex

double complex cbesselj(double nu, double complex z, int n)

Input Arguments:

nu: double

The parameter \(\nu\) of Bessel function.

z: double or double complex

The input argument \(z\) of Bessel function.

  • In Python, the function besselj accepts double and double complex types.

  • In Cython, the function besselj accepts double type.

  • In Cython, the function cbesselj accepts double complex type.

n: int = 0

The order \(n\) of the derivative of Bessel function. Zero indicates no derivative.

  • For the Python interface, the default value is 0 and this argument may not be provided.

  • For the Cython interfaces, no default value is defined and this argument should be provided.

Examples

Using in Cython Code

The codes below should be used in a .pyx file and compiled with Cython.

As shown in the codes below, the python’s global lock interpreter, or gil, can be optionally released inside the scope of with nogil: statement. This is especially useful in parallel OpenMP environments.

Real Function

This example shows the real function besselj to compute the Bessel function of the first kind for a real argument z. The output variables d0j, d1j, and d2j represent the values of Bessel function and its first and second derivatives, respectively.

>>> # cimport module in a *.pyx file
>>> from special_functions cimport besselj

>>> # Declare typed variables
>>> cdef double nu = 2.5
>>> cdef double z = 2.0
>>> cdef double d0j, d1j, d2j

>>> # Releasing gil to secure maximum cythonic speedup
>>> with nogil:
...     d0j = besselj(nu, z, 0)    # no derivative
...     d1j = besselj(nu, z, 1)    # 1st derivative
...     d2j = besselj(nu, z, 2)    # 2nd derivative

Complex Function

The example below is similar to the above, except, the complex function cbesselj with complex argument z is used. The output variables d0j, d1j, and d2j are also complex.

>>> # cimport module in a *.pyx file
>>> from special_functions cimport cbesselj

>>> # Declare typed variables
>>> cdef double nu = 2.5
>>> cdef double complex z = 2.0 + 1.0j
>>> cdef double complex d0j, d1j, d2j

>>> # Releasing gil to secure maximum cythonic speedup
>>> with nogil:
...     d0j = cbesselj(nu, z, 0)    # no derivative
...     d1j = cbesselj(nu, z, 1)    # 1st derivative
...     d2j = cbesselj(nu, z, 2)    # 2nd derivative

Using in Python Code

The codes below should be used in a .py file and no compilation is required. The python’s global lock interpreter, or gil, cannot be released.

Real Function

The example below uses the function besselj with the real argument z to compute the Bessel function of the first kind and its first and second derivatives.

>>> # import module in a *.py file
>>> from special_functions import besselj

>>> nu = 2.5
>>> z = 2.0

>>> d0j = besselj(nu, z)       # no derivative
>>> d1j = besselj(nu, z, 1)    # 1st derivative
>>> d2j = besselj(nu, z, 2)    # 2nd derivative

Complex Function

To use a complex input argument z in the Python interface, the same function besselj as the previous example can be used. This is unlike the Cython interface in which cbesselj should be used.

>>> # import module in a *.py file
>>> from special_functions import besselj

>>> nu = 2.5
>>> z = 2.0 + 1.0j

>>> d0j = besselj(nu, z)       # no derivative
>>> d1j = besselj(nu, z, 1)    # 1st derivative
>>> d2j = besselj(nu, z, 2)    # 2nd derivative

Tests

The test script of this module is located at tests/test_besselj.py. The test compares the results of this module with scipy.special package (functions j0, j1, jn, jv, and jvp) for several combinations of input parameters with multiple values. Run the test by

git clone https://github.com/ameli/special_functions.git
cd special_functions/tests
python test_besselj.py

Algorithm

Depending on the values of the input parameters \((\nu, z, n)\), one of the following three algorithms is employed.

  • If \(z \in \mathbb{R}\) (that is, z is of type double) and \(\nu = 0\) or \(\nu = 1\), the computation is carried out by Cephes C library (see [Cephes-1989]), respectively using j0 or j1 functions in that library.

  • If \(\nu + \frac{1}{2} \in \mathbb{Z}\), the Bessel function is computed using half-integer formulas in terms of elementary functions.

  • For other cases, the computation is carried out by Amos Fortran library (see [Amos-1986]) using zbesj subroutine in that library.

Special Cases

In the special cases below, the computation is performed by taking advantage of some of the known formulas and properties of the Bessel functions.

Branch-Cut

  • In the real domain where \(z \in\mathbb{R}\), if \(z < 0\) and \(\nu \notin \mathbb{Z}\), the value of NAN is returned.

  • However, in the complex domain \(z \in\mathbb{C}\) and on the branch-cut of the function, \(\Re(z) < 0\) and \(\Im(z) = 0\), its principal value corresponding to the branch

    \[\mathrm{arg}(z) \in (-\pi, \pi]\]

    is returned. This value may be finite, infinity or undefined depending on \(\nu\) and \(z\).

Negative \(\nu\)

When \(\nu < 0\) and for the two cases below, the Bessel function is related to the Bessel function of the positive parameter \(-\nu\).

  • If \(\nu \in \mathbb{Z}\) (see [DLMF] Eq. 10.4.1):

    \[J_{\nu}(z) = (-1)^{\nu} J_{-\nu}(z)\]
  • If \(\nu + \frac{1}{2} \in \mathbb{Z}\) (see [DLMF] Eq. 10.2.3):

    \[J_{\nu}(z) = \cos(\pi \nu) J_{-\nu}(z) + \sin(\pi \nu) Y_{-\nu}(z),\]

    where \(Y_{\nu}(z)\) is the Bessel function of the second kind.

Derivatives

If \(n > 0\), the following relation for the derivative is applied (see [DLMF] Eq. 10.6.7):

\[\frac{\partial^n J_{\nu}(z)}{\partial z^n} = \frac{1}{2^n} \sum_{i = 0}^n (-1)^i \binom{n}{i} J_{\nu - n + 2i}(z).\]

Half-Integer \(\nu\)

When \(\nu\) is half-integer, the Bessel function is computed in terms of elementary functions as follows.

  • If \(z = 0\):

    • If \(\nu > 0\), then \(J_{\nu}(0) = 0\).

    • If \(\nu \leq 0\):

      • If \(z \in \mathbb{R}\), then \(J_{\nu}(0) = -\mathrm{sign}(\sin(\pi \nu)) \times \infty\).

      • If \(z \in \mathbb{C}\), then NAN is returned.

  • If \(z < 0\) and \(z \in \mathbb{R}\), then NAN is returned.

  • If \(\nu = \pm \frac{1}{2}\) (see [DLMF] Eq. 10.16.1)

    \[\begin{split}J_{\frac{1}{2}}(z) = \sqrt{\frac{2}{\pi z}} \sin(z), \\ J_{-\frac{1}{2}}(z) = \sqrt{\frac{2}{\pi z}} \cos(z).\end{split}\]

    Depending on \(z\), the above relations are computed using the real or complex implementation of the elementary functions.

  • Higher-order half-integer parameter \(\nu\) is related to the above relation for \(\nu = \pm \frac{1}{2}\) using recursive formulas (see [DLMF] Eq. 10.6.1):

\[\begin{split}J_{\nu}(z) = \frac{2 (\nu - 1)}{z} J_{\nu - 1}(z) - J_{\nu - 2}(z), \qquad \nu > 0, \\ J_{\nu}(z) = \frac{2 (\nu + 1)}{z} J_{\nu + 1}(z) - J_{\nu + 2}(z), \qquad \nu < 0.\end{split}\]

References

[Cephes-1989]

Moshier, S. L. (1989). C language library with special functions for mathematical physics. Available at http://www.netlib.org/cephes.

[Amos-1986]

Amos, D. E. (1986). Algorithm 644: A portable package for Bessel functions of a complex argument and nonnegative order. ACM Trans. Math. Softw. 12, 3 (Sept. 1986), 265-273. DOI: https://doi.org/10.1145/7921.214331. Available at http://netlib.org/amos/.

[DLMF] (1,2,3,4,5)

Olver, F. W. J., Olde Daalhuis, A. B., Lozier, D. W., Schneider, B. I., Boisvert, R. F., Clark, C. W., Miller, B. R., Saunders, B. V., Cohl, H. S., and McClain, M. A., eds. NIST Digital Library of Mathematical Functions. http://dlmf.nist.gov/, Release 1.1.0 of 2020-12-15.