Skip to main content

A Python package for multipole expansions of electrostatic or gravitational potentials

Project description

multipoles

PyPI version build

multipoles is a Python package for multipole expansions of the solutions of the Poisson equation (e.g. electrostatic or gravitational potentials). It can handle discrete and continuous charge or mass distributions.

Installation

Simply use pip:

pip install --upgrade multipoles

Documentation

The documentation is available here.

Theory

For a given function $\rho(x,y,z)$, the solution $\Phi(x,y,z)$ of the Poisson equation $\nabla^2\Phi=-4\pi \rho$ with vanishing Dirichlet boundary conditions at infinity is

$$\Phi(x,y,z)=\int d^3r'\frac{\rho(r')}{|r-r'|}$$

Examples of this are the electrostatic and Newtonian gravitational potential. If you need to evaluate $\Phi(x,y,z)$ at many points, calculating the integral for each point is computationally expensive. As a faster alternative, we can express $\Phi(x,y,z)$ in terms of the multipole moments $q_{lm}$ or $I_{lm}$ (note some literature uses the subscripts $(\cdot)_{nm}$):

$$\Phi(x,y,z)=\sum_{l=0}^\infty\underbrace{\sqrt{\frac{4\pi}{2l+1}}\sum_{m=-l}^lY_{lm}(\theta, \varphi)\frac{q_{lm}}{r^{l+1}}}_{\Phi^{(l)}}$$

for a exterior expansion, or

$$\Phi(x,y,z)=\sum_{l=0}^\infty\underbrace{\sqrt{\frac{4\pi}{2l+1}}\sum_{m=-l}^lY_{lm}(\theta, \varphi)I_{lm}r^{l}}_{\Phi^{(l)}}$$

for an interior expansion; where $r, \theta, \varphi$ are the usual spherical coordinates corresponding to the cartesian coordinates $x, y, z$ and $Y_{lm}(\theta, \varphi)$ are the spherical harmonics.

The multipole moments for the exterior expansion are:

$$q_{lm} = \sqrt{\frac{4\pi}{2l+1}}\int d^3 r' \rho(r')r'^l Y^*_{lm}(\theta', \varphi')$$

and the multipole moments for the interior expansion are:

$$I_{lm} = \sqrt{\frac{4\pi}{2l+1}}\int d^3 r' \frac{\rho(r')}{r'^{l+1}} Y^*_{lm}(\theta', \varphi')$$

This approach is usually much faster because the contributions $\Phi^{(l)}$ are getting smaller with increasing l. So we just have to calculate a few integrals for obtaining some $q_{lm}$ or $I_{lm}$.

Some literature considers the $\sqrt{\frac{4\pi}{2l+1}}$ as part of the definition of $Y_{lm}(\theta, \varphi)$.

Examples

Discrete Charge Distribution

As example for a discrete charge distribution we model two point charges with positive and negative unit charge located on the z-axis:

from multipoles import MultipoleExpansion

# Prepare the charge distribution dict for the MultipoleExpansion object:

charge_dist = {
    'discrete': True,     # point charges are discrete charge distributions
    'charges': [
        {'q': 1, 'xyz': (0, 0, 1)},
        {'q': -1, 'xyz': (0, 0, -1)},
    ]
}

l_max = 2   # where to stop the infinite multipole sum; here we expand up to the quadrupole (l=2)

Phi = MultipoleExpansion(charge_dist, l_max)

# We can evaluate the multipole expanded potential at a given point like this:

x, y, z = 30.5, 30.6, 30.7
value = Phi(x, y, z)

# The multipole moments are stored in a dict, where the keys are (l, m) and the values q_lm:
Phi.multipole_moments

Continuous Charge Distribution

As an example for a continuous charge distribution, we smear out the point charges from the previous example:

from multipoles import MultipoleExpansion
import numpy as np

# First we set up our grid, a cube of length 10 centered at the origin:

npoints = 101
edge = 10
x, y, z = [np.linspace(-edge/2., edge/2., npoints)]*3
XYZ = np.meshgrid(x, y, z, indexing='ij')


# We model our smeared out charges as gaussian functions:

def gaussian(XYZ, xyz0, sigma):
    g = np.ones_like(XYZ[0])
    for k in range(3):
        g *= np.exp(-(XYZ[k] - xyz0[k])**2 / sigma**2)
    g *= (sigma**2*np.pi)**-1.5
    return g

sigma = 1.5   # the width of our gaussians

# Initialize the charge density rho, which is a 3D numpy array:
rho = gaussian(XYZ, (0, 0, 1), sigma) - gaussian(XYZ, (0, 0, -1), sigma)


# Prepare the charge distribution dict for the MultipoleExpansion object:

charge_dist = {
    'discrete': False,     # we have a continuous charge distribution here
    'rho': rho,
    'xyz': XYZ
}

# The rest is the same as for the discrete case:

l_max = 2   # where to stop the infinite multipole sum; here we expand up to the quadrupole (l=2)

Phi = MultipoleExpansion(charge_dist, l_max)

x, y, z = 30.5, 30.6, 30.7
value = Phi(x, y, z)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

multipoles-0.4.1.tar.gz (143.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

multipoles-0.4.1-py3-none-any.whl (8.8 kB view details)

Uploaded Python 3

File details

Details for the file multipoles-0.4.1.tar.gz.

File metadata

  • Download URL: multipoles-0.4.1.tar.gz
  • Upload date:
  • Size: 143.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.0

File hashes

Hashes for multipoles-0.4.1.tar.gz
Algorithm Hash digest
SHA256 824e29c63102b74f5f08929b857ba898f9332df898f5d9e5ec8c6cc726317b3c
MD5 8394603446d42800b4b0004c40c038b5
BLAKE2b-256 54eeffe280e7d6facb06e06d7b59a344563568285500d4dca9c902834258834d

See more details on using hashes here.

File details

Details for the file multipoles-0.4.1-py3-none-any.whl.

File metadata

  • Download URL: multipoles-0.4.1-py3-none-any.whl
  • Upload date:
  • Size: 8.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.0

File hashes

Hashes for multipoles-0.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 e0ee1ea0f0d1873bd6b9c0ac21bf83e2e7811417010bfab90bc67052327e1763
MD5 7f939897d89763b9c5f129cb8ef0698b
BLAKE2b-256 0abe74f8abc9d9b9138c902e473a98a2959f4581ff812b087d084c70b026fbbd

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page