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import numpy as np
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
import meep as mp
from meep.materials import SiO2
resolution = 100 # pixels/um
dpml = 1.0
pml_layers = [mp.PML(thickness=dpml)]
r = 1.0 # radius of cylinder
dair = 2.0 # air padding thickness
s = 2*(dpml+dair+r)
cell_size = mp.Vector3(s,s)
wvl = 1.0
fcen = 1/wvl
# is_integrated=True necessary for any planewave source extending into PML
sources = [mp.Source(mp.GaussianSource(fcen,fwidth=0.1*fcen,is_integrated=True),
center=mp.Vector3(-0.5*s+dpml),
size=mp.Vector3(0,s),
component=mp.Ez)]
symmetries = [mp.Mirror(mp.Y)]
geometry = [mp.Cylinder(material=SiO2,
center=mp.Vector3(),
radius=r,
height=mp.inf)]
sim = mp.Simulation(resolution=resolution,
cell_size=cell_size,
boundary_layers=pml_layers,
sources=sources,
k_point=mp.Vector3(),
symmetries=symmetries,
geometry=geometry)
dft_fields = sim.add_dft_fields([mp.Dz,mp.Ez],
fcen,0,1,
center=mp.Vector3(),
size=mp.Vector3(2*r,2*r),
yee_grid=True)
# closed box surrounding cylinder for computing total incoming flux
flux_box = sim.add_flux(fcen, 0, 1,
mp.FluxRegion(center=mp.Vector3(x=-r),size=mp.Vector3(0,2*r),weight=+1),
mp.FluxRegion(center=mp.Vector3(x=+r),size=mp.Vector3(0,2*r),weight=-1),
mp.FluxRegion(center=mp.Vector3(y=+r),size=mp.Vector3(2*r,0),weight=-1),
mp.FluxRegion(center=mp.Vector3(y=-r),size=mp.Vector3(2*r,0),weight=+1))
sim.run(until_after_sources=100)
Dz = sim.get_dft_array(dft_fields,mp.Dz,0)
Ez = sim.get_dft_array(dft_fields,mp.Ez,0)
absorbed_power_density = 2*np.pi*fcen * np.imag(np.conj(Ez)*Dz)
dxy = 1/resolution**2
absorbed_power = np.sum(absorbed_power_density)*dxy
absorbed_flux = mp.get_fluxes(flux_box)[0]
err = abs(absorbed_power-absorbed_flux)/absorbed_flux
print("flux:, {} (dft_fields), {} (dft_flux), {} (error)".format(absorbed_power,absorbed_flux,err))
plt.figure()
sim.plot2D()
plt.savefig('power_density_cell.png',dpi=150,bbox_inches='tight')
plt.figure()
x = np.linspace(-r,r,Dz.shape[0])
y = np.linspace(-r,r,Dz.shape[1])
plt.pcolormesh(x,
y,
np.transpose(absorbed_power_density),
cmap='inferno_r',
shading='gouraud',
vmin=0,
vmax=np.amax(absorbed_power_density))
plt.xlabel("x (μm)")
plt.xticks(np.linspace(-r,r,5))
plt.ylabel("y (μm)")
plt.yticks(np.linspace(-r,r,5))
plt.gca().set_aspect('equal')
plt.title("absorbed power density" + "\n" +"SiO2 Labs(λ={} μm) = {:.2f} μm".format(wvl,wvl/np.imag(np.sqrt(SiO2.epsilon(fcen)[0][0]))))
plt.colorbar()
plt.savefig('power_density_map.png',dpi=150,bbox_inches='tight')
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