efficiencies_mx

miepython.core.efficiencies_mx(m, x, n_pole=0, field='Electric')[source]

Computes scattering and extinction efficiencies for a spherical particle using Mie theory.

Supports array inputs for wavelength-dependent calculations of the refractive index and size parameter.

Parameters:

  • m (complex or array-like) – Complex refractive index of the sphere, defined as m = n - ik, where n is the real part (phase velocity) and k is the imaginary part (absorption). Can be a scalar or an array.

  • x (float or array-like) – Size parameter of the sphere, defined as x = π d / λ, where d is the diameter of the sphere and λ is the wavelength in the surrounding medium. Can be a scalar or an array.

  • n_pole (int) – Multipole order to compute: - If 0 (default), computes contributions from all multipoles. - If non-zero, computes contributions from the specified multipole order.

  • field (str) – If “Electric” (default) If n_pole>0, then True value returns the electric multipole contribution otherwise the Magnetic field contribution

Returns:

tuple –

qext (float or array-like):

Extinction efficiency, representing the total attenuation of light (scattering plus absorption) by the particle.

qsca (float or array-like):

Scattering efficiency, representing the fraction of incident light scattered by the particle.

qback (float or array-like):

Backscattering efficiency, describing the fraction of incident light scattered in the exact backward direction (theta = 180 degrees).

g (float or array-like):

Asymmetry parameter, representing the average cosine of the scattering angle over all angles.

Notes

  • Ensure m and x have compatible dimensions if passed as arrays.

  • For accurate results, n_pole should be within the range of significant multipole contributions, typically n ~ x + 4*x**(1/3).

  • This implementation assumes spherical, homogeneous particles in a non-absorbing medium.

Examples

Compute efficiencies for a sphere with fixed parameters:

>>> import miepython as mie
>>> mie.efficiencies(1.5 - 0.01j, 2.0, 0)
(qext: 1.81, qsca: 1.72, qback: 0.27, g: 0.63)

Compute efficiencies for wavelength-dependent refractive indices:

>>> import miepython as mie
>>> m_array = np.array([1.5 - 0.01j, 1.45 - 0.02j])
>>> x_array = np.array([2.0, 2.5])
>>> mie.efficiencies(m_array, x_array, 0)
(qext: [1.81, 2.15], qsca: [1.72, 1.95], qback: [0.27, 0.31], g: [0.63, 0.70])