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Hankel transform
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=== Special cases === ==== Fourier transform in two dimensions ==== If a two-dimensional function {{math|''f''('''r''')}} is expanded in a [[multipole expansion|multipole series]], :<math>f(r, \theta) = \sum_{m=-\infty}^\infty f_m(r) e^{im\theta_{\mathbf{r}}},</math> then its two-dimensional Fourier transform is given by<math display="block">F(\mathbf k) = 2\pi \sum_m i^{-m} e^{im\theta_{\mathbf{k}}} F_m(k),</math>where<math display="block">F_m(k) = \int_0^\infty f_m(r) J_m(kr) \,r\,\mathrm{d}r</math>is the <math display="inline">m</math>-th order Hankel transform of <math>f_m(r)</math> (in this case <math display="inline">m</math> plays the role of the angular momentum, which was denoted by <math display="inline">l</math> in the previous section). ==== Fourier transform in three dimensions ==== If a three-dimensional function {{math|''f''('''r''')}} is expanded in a [[multipole expansion|multipole series]] over [[spherical harmonics]], :<math>f(r,\theta_{\mathbf{r}},\varphi_{\mathbf{r}}) = \sum_{l = 0}^{+\infty} \sum_{m=-l}^{+l}f_{l,m}(r)Y_{l,m}(\theta_{\mathbf{r}},\varphi_{\mathbf{r}}),</math> then its three-dimensional Fourier transform is given by<math display="block">F(k,\theta_{\mathbf{k}},\varphi_{\mathbf{k}}) = (2 \pi)^{3/2} \sum_{l = 0}^{+\infty} (-i)^{l} \sum_{m=-l}^{+l} F_{l,m}(k) Y_{l,m}(\theta_{\mathbf{k}},\varphi_{\mathbf{k}}),</math>where<math display="block">\sqrt{k} F_{l,m}(k) = \int_{0}^{+\infty}\sqrt{r} f_{l,m}(r)J_{l+1/2}(kr)r\mathrm{d}r.</math>is the Hankel transform of <math>\sqrt{r} f_{l,m}(r)</math> of order <math display="inline">(l+1/2)</math>. This kind of Hankel transform of half-integer order is also known as the spherical Bessel transform. ==== Fourier transform in {{math|''d''}} dimensions (radially symmetric case) ==== If a {{math|''d''}}-dimensional function {{math|''f''(''r'')}} does not depend on angular coordinates, then its {{math|''d''}}-dimensional Fourier transform {{math|''F''(''k'')}} also does not depend on angular coordinates and is given by<ref>{{cite web|url=http://math.arizona.edu/~faris/methodsweb/hankel.pdf|title=Radial functions and the Fourier transform: Notes for Math 583A, Fall 2008|last=Faris|first=William G.|date=2008-12-06|website=University of Arizona, Department of Mathematics|accessdate=2015-04-25}}</ref><math display="block">k^{d/2-1}F(k) = (2 \pi)^{d/2} \int_{0}^{+\infty}r^{d/2-1}f(r)J_{d/2-1}(kr)r\mathrm{d}r.</math>which is the Hankel transform of <math>r^{d/2-1}f(r)</math> of order <math display="inline">(d/2-1)</math> up to a factor of <math>(2 \pi)^{d/2} </math>. ====2D functions inside a limited radius==== If a two-dimensional function {{math|''f''('''r''')}} is expanded in a [[multipole expansion|multipole series]] and the expansion coefficients {{math|''f<sub>m</sub>''}} are sufficiently smooth near the origin and zero outside a radius {{mvar|R}}, the radial part {{math|''f''(''r'')/''r<sup>m</sup>''}} may be expanded into a [[power series]] of {{math|1 β (''r''/''R'')^2}}: :<math>f_m(r)= r^m \sum_{t \ge 0} f_{m,t} \left(1 - \left(\tfrac{r}{R}\right)^2 \right)^t, \quad 0 \le r \le R,</math> such that the two-dimensional Fourier transform of {{math|''f''('''r''')}} becomes :<math>\begin{align} F(\mathbf k) &= 2\pi\sum_m i^{-m} e^{i m\theta_k} \sum_t f_{m,t} \int_0^R r^m \left(1 - \left(\tfrac{r}{R}\right)^2 \right)^t J_m(kr) r\,\mathrm{d}r && \\ &= 2\pi\sum_m i^{-m} e^{i m\theta_k} R^{m+2} \sum_t f_{m,t} \int_0^1 x^{m+1} (1-x^2)^t J_m(kxR) \,\mathrm{d}x && (x = \tfrac{r}{R})\\ &= 2\pi\sum_m i^{-m} e^{i m\theta_k} R^{m+2} \sum_t f_{m,t} \frac{t!2^t}{(kR)^{1+t}} J_{m+t+1}(kR), \end{align}</math> where the last equality follows from Β§6.567.1 of.<ref>{{cite book |last1=Gradshteyn|first1=I. S. |last2=Ryzhik|first2=I. M. |editor1-last=Zwillinger|editor1-first=Daniel |title=Table of Integrals, Series, and Products |date=2015 |publisher=Academic Press |isbn=978-0-12-384933-5 |edition=Eighth |page=687}}</ref> The expansion coefficients {{math|''f<sub>m,t</sub>''}} are accessible with [[discrete Fourier transform]] techniques:<ref>{{cite journal |first1=JosΓ© D. |last1=Secada |title=Numerical evaluation of the Hankel transform |journal=Comput. Phys. Commun. |volume=116 |issue=2β3 |pages=278β294 |bibcode=1999CoPhC.116..278S |year=1999 |doi = 10.1016/S0010-4655(98)00108-8 }}</ref> if the radial distance is scaled with :<math>r/R\equiv \sin\theta,\quad 1-(r/R)^2 = \cos^2\theta,</math> the Fourier-Chebyshev series coefficients {{math|''g''}} emerge as :<math>f(r)\equiv r^m \sum_j g_{m,j} \cos(j\theta)= r^m\sum_jg_{m,j} T_j(\cos\theta).</math> Using the re-expansion :<math> \cos(j\theta) = 2^{j-1}\cos^j\theta-\frac{j}{1}2^{j-3}\cos^{j-2}\theta +\frac{j}{2}\binom{j-3}{1}2^{j-5}\cos^{j-4}\theta - \frac{j}{3}\binom{j-4}{2}2^{j-7}\cos^{j-6}\theta + \cdots </math> yields {{math|''f''<sub>''m,t''</sub>}} expressed as sums of {{math|''g''<sub>''m,j''</sub>}}. This is one flavor of fast Hankel transform techniques.
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