Nonequispaced fast Fourier transform
NFFT on the sphere
NFSFT

# NFSFT - NFFT on the sphere

This library of C functions computes evaluates a function $$f \in \mathrm{L}^2(\mathbb{S}^2)$$ with finite orthogonal expansion $f(\vartheta,\varphi) = \sum_{k=0}^M \sum_{n=-k}^k a_k^n Y_{k}^n(\vartheta,\varphi) %= \quad (M \in \mathbb{N}_0)$ in terms of spherical harmonics $$Y_k^n$$ on a set of arbitary nodes $$\left(\vartheta_d,\varphi_d\right)$$, $$d=1,\ldots,D$$, $$D \in \mathbb{N}$$, in spherical coordinates. Furthermore, the fast evaluation of sums $\tilde{a}_{k}^n := \sum_{d=1}^{D} f\left(\vartheta_d,\varphi_d\right) \overline{Y_{k}^n\left(\vartheta_d,\varphi_d\right)}$ for given function values $$f\left(\vartheta_d,\varphi_d\right) \in \mathbb{C}$$ and all indices $$k=0,\ldots,M$$, $$n = -k,\ldots,k$$ is possible. The algorithm is also kwnon as fast spherical harmonic transform for nonequispaced data.

## Detailed Description

Fourier analysis on the sphere has practical relevance in tomography, geophysics, seismology, meteorology and crystallography. In analogy to the complex exponentials $$\mathrm{e}^{\mathrm{i} k x}$$ on the torus, the spherical harmonics form the orthogonal Fourier basis with respect to the usual inner product on the sphere.

### Spherical coordinates

Every point in $$\mathbb R^3$$ can be described in spherical coordinates by a vector $$(r,\vartheta,\varphi)^{\top}$$ with the radius $$r\ge 0$$ and two angles $$\vartheta \in [0,\pi]$$, $$\varphi \in [0,2\pi)$$. We denote by $$\mathbb S^2$$ the two-dimensional unit sphere embedded into $$\mathbb R^3$$, i.e. $\mathbb S^2 := \left\{\mathbf{x} \in \R^{3}:\; \|\mathbf{x}\|_2=1\right\}$ and identify a point from $$\mathbb S^2$$ with the corresponding vector $$(\vartheta,\varphi)^{\top}$$.

### Legendre polynomials and associated Legendre functions

The Legendre polynomials $$P_k : [-1,1]\rightarrow \R,\; k\ge 0$$, as classical orthogonal polynomials are given by their corresponding Rodrigues formula $P_k(x) := \frac{1}{2^k k!} \frac{\text{d}^k}{\text{d} x^k} \left(x^2-1\right)^k.$ The associated Legendre functions $$P_k^n : [-1,1] \rightarrow \R,\; k \ge n \ge 0$$ are defined by $P_k^n(x) := \left(\frac{(k-n)!}{(k+n)!}\right)^{1/2} \left(1-x^2\right)^{n/2} \frac{\text{d}^n}{\text{d} x^n} P_k(x).$ For $$n = 0$$, they coincide with the Legendre polynomials $$P_k = P_k^0$$. The associated Legendre functions $$P_{k}^n$$ obey the three-term recurrence relation $P_{k+1}^n(x) = \frac{2k+1}{((k-n+1)(k+n+1))^{1/2}} x P_k^n(x) - \frac{((k-n)(k+n))^{1/2}}{((k-n+1)(k+n+1))^{1/2}} P_{k-1}^n(x)$ for $$k \ge n \ge 0,\; P_{n-1}^n(x) = 0, \;P_{n}^n(x) = \frac{\sqrt{(2n)!}}{2^n n!}\left(1-x^2\right)^{n/2}$$. For fixed $$n$$, the set $$\{P_k^n:\: k \ge n\}$$ forms a set of orthogonal functions, i.e., $\left\langle P_k^n,P_l^n \right\rangle = \int_{-1}^{1} P_k^n(x) P_l^n(x) \text{d} x = \frac{2}{2k+1} \delta_{k,l}.$ Again, we denote by $$\bar{P}_{k}^n = \sqrt{\frac{2k+1}{2}} P_k^n$$ the orthonormal associated Legendre functions. In the following, we allow also for $$n \lt 0$$ and set $$P_{k}^n := P_{k}^{-n}$$ in this case.

### Spherical harmonics

The spherical harmonics $$Y_k^n : \mathbb S^2 \rightarrow \mathbb C,\; k \ge |n|,\; n\in\mathbb Z$$, are given by $Y_k^n(\vartheta,\varphi) := P_k^{n}(\cos\vartheta) \, \mathrm{e}^{\mathrm{i} n \varphi}.$ They form an orthogonal basis for the space of square integrable functions on the sphere, i.e., $\left\langle Y_k^n,Y_l^m \right\rangle = \int_{0}^{2\pi} \int_{0}^{\pi} Y_k^n(\vartheta,\varphi) \overline{Y_l^m(\vartheta,\varphi)} \sin \vartheta \; \mathrm{d} \vartheta \; \mathrm{d} \varphi = \frac{4\pi}{2k+1} \delta_{k,l}\delta_{n,m}.$ The orthonormal spherical harmonics are denoted by $$\bar{Y}_k^n = \sqrt{\frac{2k+1}{4\pi}} Y_k^n$$. Hence, any square integrable function $$f:\mathbb S^2\rightarrow\mathbb C$$ has the expansion $f = \sum_{k=0}^{\infty} \sum_{n=-k}^{k} \hat{f}(k,n) \bar{Y}_k^n,$ with the spherical Fourier coefficients $$\hat{f}(k,n) = \left\langle f, \bar{Y}_k^n \right\rangle$$. The function $$f$$ is called bandlimited, if $$\hat{f}(k,n)=0$$ for $$k>N$$ and some $$N\in\N$$. In analogy to the NFFT on the Torus $$\mathbb{T}$$, we define the sampling set $\mathcal{X}: = \left\{\left(\vartheta_{j},\varphi_{j}\right) \in \mathbb{S}^2:\,j=0,\dots,M-1\right\}$ of nodes on the sphere $$\mathbb S^2$$ and the set of possible ''frequencies'' $\mathcal{I}_{N} := \left\{(k,n):\,k=0,1,\ldots,N;\; n=-k,\ldots,k\right\}.$ The nonequispaced discrete spherical Fourier transform (NDSFT) is defined as the evaluation of the finite spherical Fourier sum $f_j= f\left(\vartheta_{j},\varphi_{j}\right) = \sum_{(k,n) \in \, \mathcal{I}_{N}} \hat{f}_k^n \, Y_k^n\left(\vartheta_{j},\varphi_{j}\right) = \sum_{k=0}^N \sum_{n=-k}^k \hat{f}_k^n \, Y_k^n\left(\vartheta_{j},\varphi_{j}\right)$ for $$j=0,\dots,M-1$$. In matrix vector notation, this reads $$\mathbf{f} = \mathbf{Y} \; \mathbf{\hat f}$$ with $\mathbf{f} := \left(f_j\right)_{j=0}^{M-1} \in \mathbb{C}^{M},\ f_{j} := f\left(\vartheta_{j},\varphi_{j}\right),$ $\mathbf{Y} := \left(Y_k^n\left(\vartheta_j,\varphi_j\right)\right)_{j=0,\ldots,M-1;\; (k,n) \in \mathcal{I}_N} \in \mathbb{C}^{M \times (N+1)^2},$$\mathbf{\hat f} := \left(\hat f_k^n\right)_{(k,n) \in \mathcal{I}_N} \in \mathbb{C}^{(N+1)^2}.$ The corresponding adjoint nonequispaced discrete fast spherical Fourier transform (adjoint NDSFT) is defined as the evaluation of $\hat h_{k}^n = \sum_{j = 0}^{M-1} f\left(\vartheta_{j},\varphi_{j}\right) \overline{Y_k^n\left(\vartheta_{j},\varphi_{j}\right)}$ for all $$(k,n) \in \mathcal{I}_{N}$$. Again, in matrix vector notation, this reads $$\mathbf{\hat h} = \mathbf{Y}^{H} \, \mathbf{f}$$. The coefficients $$\hat h_{k}^n$$ are, in general, not identical to the Fourier coefficients $$\hat{f}(k,n)$$ of the function $$f$$. However, provided that for the sampling set $$\mathcal{X}$$ a quadrature rule with weights $$w_{j}$$, $$j=0,\dots,M-1$$, and sufficient degree of exactness is available, one might recover the Fourier coefficients $$\hat{f}(k,n)$$ by evaluating $\hat{f}_{k}^n = \int_{0}^{2\pi} \int_{0}^{\pi} f(\vartheta,\varphi) \overline{Y_{k}^n(\vartheta,\varphi)} \sin\vartheta \; \mathrm{d} \vartheta \; \mathrm{d} \varphi = \sum_{j = 0}^{M-1} w_{j} f\left(\vartheta_{j},\varphi_{j}\right) \overline{Y_k^n\left(\vartheta_{j},\varphi_{j}\right)}$ for all $$(k,n) \in \mathcal{I}_{N}$$. Direct algorithms for computing the NDSFT and adjoint NDSFT transformations need $$\mathcal O(M N^2)$$ arithmetic operations. A combination of the fast polynomial transform and the NFFT leads to approximate algorithms with $$\mathcal O(N^2 \log^2 N + M)$$ arithmetic operations. These are denoted NFSFT and adjoint NFSFT, respectively.

## Algorithm

The algorithms are implemented by Jens Keiner in ./kernel/nfsft. The OpenMP parallelization was implemented by Toni Volkmer. The Matlab interface was implemented by Stefan Kunis in ./matlab/nfsft. Related paper are

• Gräf, M., Kunis, S., Potts, D.
On the computation of nonnegative quadrature weights on the sphere.
Appl. Comput. Harm. Anal. 27(1),   (full paper ps, pdf),   2009

• Keiner, J., Potts, D.
Fast evaluation of quadrature formulae on the sphere
Math. Comput. 77, 397 - 419,   (full paper ps, pdf),   2008

• Kunis, S. and Potts, D.
Fast spherical Fourier algorithms.
J. Comput. Appl. Math. 161, 75-98. (full paper ps, pdf),   2003

• Potts, D., Steidl G., and Tasche M.
Fast and stable algorithms for discrete spherical Fourier transforms.
Linear Algebra Appl. 275, 433-450. (full paper ps.Z, pdf),   1998