Loading Refractive Index Data

written by Jaren Ashcraft

Polarization ray tracing is a core part of what Poke does, which requires a raytrace file, material data, and the patience to simulate optical polarization. In this demo, we illustrate how we tried to make loading material data just one step easier.

The folks at RefractiveIndex.INFO [1] have assembled an incredibly useful library of different optical materials and their properties. Not only that, but they made their database free to use and distribute under the CC0 1.0 Universal Public Domain Dedication so that other investigators can use it as they please.

In Poke, we make use of this catalogue to provide our users with easilly-accessible material data that will enable polarization ray tracing simulations.

References

• [1] M. N. Polyanskiy, “Refractive index database,” https://refractiveindex.info. Accessed on 2023-12-08.

A simple index model

Refractive index data is typically available on a nonuniform set of samples as a function of wavelength. In order to choose our sampling along this curve we use scipy.interpolate to create 1D splines of the data that are callable. We demonstrate a simple example of this here.

To see the materials currently available in Poke, import avail_materials from poke.materials

import numpy as np
import matplotlib.pyplot as plt
from poke.materials import create_index_model, avail_materials
print(avail_materials)

['Al', 'Ag', 'HfO2', 'SiO2', 'Ta2O5', 'TiO2', 'Nb2O5', 'SiN', 'MgF2', 'CaF2', 'LiF', 'Silica']

Creating an index model is done by simply supplying one of the strings from this list to the create_index_model function, which generates a spline at the limits of the data.

# A simple Aluminum reflector
wvl = np.arange(0.4,1,0.01) # wavelength, microns
n_Al = create_index_model('Al')

This function assumes that the supplied wavelength is in microns. We can plot it and observe that the fit to the data is quite good.

pth_to_Al = '../../poke/material_data/Cheng_Al.csv'
Al_data = np.genfromtxt(pth_to_Al,skip_header=1,delimiter=',').T
n_Al_data = Al_data[1,:427]
k_Al_data = Al_data[1,428:]
wvl_data = Al_data[0,:427]

n = np.real(n_Al(wvl))
k = np.imag(n_Al(wvl))

plt.style.use('bmh') # because it's pretty
plt.figure()
plt.plot(wvl,n,label='n spline',linewidth=4)
plt.plot(wvl,k,label='k spline',linewidth=4)
plt.plot(wvl_data,n_Al_data,label='n data', linestyle='dashed')
plt.plot(wvl_data,k_Al_data,label='k data', linestyle='dashed')
plt.title('Refractive Index of Aluminum ' + r'$n + ik$')
plt.legend()
plt.xlabel('Wavelength, microns')
plt.show()