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The purpose of this package is to provide methods to numerically handle real spherical harmonics expansions in Cartesian coordinates.

• Mathematical Background
  • Definition of the Spherical Harmonics
  • Spherical Harmonics Expansions
• Usage
  • Polynomial Representation of the Spherical Harmonics
  • Polynomial Representation of the Spherical Harmonics Expansions
  • Transformation of Expansion Coefficients under Translation
  • Numerical Evaluation
• Further Reading

The normalized real spherical harmonics on the unit sphere are defined by

where , , and are the spherical angular coordinates,

is the normalization factor and

are the associated Legendre polynomials which can be derived from the Legendre polynomials

Note that you will also find a convention in literature, where the are scaled by .

Each function satisfying Laplace's equation in a region can be written as a spherical harmonic expansion

for all , where denote the spherical coefficients and .

The term

can be transformed from spherical to Cartesian coordinates, where it can be expressed as a homogeneous polynomial of degree .

Generate a MultivariatePolynomials.Polynomial representation of

in variables α, β, and γ on the unit sphere by

using SphericalHarmonics
@polyvar α β γ
l = 7 
m = -2

p = ylm(l,m,α,β,γ)
63.28217501963252αβγ⁵ - 48.67859616894809αβγ³ + 6.63799038667474αβγ

The polynomial representation of

in variables x, y, and z on can be obtained by

@polyvar x y z

p = rlylm(l,m,x,y,z)
6.63799038667474x⁵yz + 13.27598077334948x³y³z - 35.40261539559861x³yz³ + 6.63799038667474xy⁵z - 35.40261539559861xy³z³ + 21.24156923735917xyz⁵

In case where a function is equal to or can be approximated by a finite Spherical harmonic expansion

with its multivariate polynomial representation has finite degree.

Coefficents can be initialized and populated by c[l,m] = 42.0.

L = 2
c = SphericalHarmonicCoefficients(L)
c[0,0] = 42.0 #c₀₀
c[2,-1] = -1.0 #c₂₋₁
c[2,1] = 2.0 #c₂₁

Internally, the coefficients are lexicographically stored in a vector (c[0,0], c[1,-1], c[1,0], c[1,1], c[2,-2], ...). So the above initialization is equivalent to

C = [42.0,0,0,0,0,-1,0,2,0]
c = SphericalHarmonicCoefficients(C)
f = sphericalHarmonicsExpansion(c,x,y,z)
2.1850968611841584xz + -1.0925484305920792yz + 11.847981254502882

Note that SphericalHarmonicCoefficients(C) will throw an error if length(C) is not for some . From there on the corresponding polynomial representation in cartesian coordinates x, y, and z can be obtained by

@polyvar x y z

f = sphericalHarmonicsExpansion(c,x,y,z)
2.1850968611841584xz - 1.0925484305920792yz + 11.847981254502882

Currently, expansions up to $L=66$ are supported.

If we change from a coordinate sytsem with coordinates x, y, and z into a translated one with new coordinates u = x + tx, v = y + ty, and w = z + tz we need transformed coefficients to express the expansion in these new coordinates. To this end, we can do

@polyvar u v w
translationVector = [0,0,1.0] # [tx,ty,tz]

cTranslated = translation(c,translationVector)
sphericalHarmonicsExpansion(cTranslated,u,v,w)
2.1850968611841584uw - 1.0925484305920792vw + 2.1850968611841584u - 1.0925484305920792v + 11.847981254502878

If you want to evaluate at a specific point you can use the standard interface of MultivariatePolynomials

f(x=>0.5, y=>-1.0, z=>0.25)
12.394255469798921
f((x,y,z)=>(0.5,-1.0,0.25))
12.394255469798921

In case where you want to evaluate for a large number of points you might run into performance issues. To this end we provide two methods to dynamically generate fast evaluating functions. Either use

g = @fastfunc f
g(0.5,-1.0,0.25)
12.394255469798921

which has moderate generation overhead. Usage from within local scope requires Base.invokelatest(foo, 1.0,2.0,3.0) instead of foo(1.0,2.0,3.0) to avoid issue #4. Or use

h = fastfunc(f)
h(0.5,-1.0,0.25)
12.394255469798921

which uses GeneralizedGenerated for function generation and comes with a significant overhead.

For more informations on the MultivariatePolynomials package please visit the project page on github.