CoreShell: B1 vs Core Diameter#

This example demonstrates how to compute and visualize the B1 scattering parameter as a function of core diameter for CoreShell scatterers using PyMieSim.

Importing the package dependencies: numpy, PyMieSim

import numpy as np
from PyMieSim.experiment.scatterer import CoreShell
from PyMieSim.experiment.source import Gaussian
from PyMieSim.experiment import Setup
from PyOptik import UsualMaterial
from PyMieSim import measure

Defining the source In the LMT framework, the source is always considered a plane wave with a default amplitude of one.

source = Gaussian(
    wavelength=800e-9,  # 800 nm
    polarization_value=0,  # Linear polarization angle in radians
    polarization_type='linear',
    optical_power=1e-3,  # 1 milliwatt
    NA=0.2  # Numerical Aperture
)

Defining the scatterer distribution Here, we explore core/shell scatterers with a constant shell diameter and variable core diameter.

scatterer = CoreShell(
    core_diameter=np.geomspace(100e-9, 3000e-9, 5000),  # Geometrically spaced core diameters
    shell_width=800e-9,  # Shell width of 800 nm
    core_index=1.6,  # Refractive index of the core
    shell_material=[UsualMaterial.BK7, UsualMaterial.Silver],  # BK7 glass material for the shell
    medium_index=1,  # Refractive index of the surrounding medium
    source=source
)

Defining the experiment setup Integrating the defined source and scatterers into a single experimental setup.

experiment = Setup(
    scatterer=scatterer,
    source=source
)

Measuring the B1 scattering parameter Here, we’re interested in the a3 (first magnetic coefficient) parameter, which seems to be a typo for B1.

data = experiment.get(measure.a3)

Plotting the results Visualizing how the B1 (a3) parameter varies with the core diameter.

figure = data.plot(
    x=experiment.core_diameter,  # Core diameter as the x-axis
    y_scale='linear'  # Linear scale for the y-axis
)

Displaying the plot

_ = figure.show()
plot coreshell a1 vs corediameter

Total running time of the script: (0 minutes 2.299 seconds)

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