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import matplotlib
import numpy as np
matplotlib.use("agg")
import matplotlib.pyplot as plt
from meep.materials import SiO2
import meep as mp
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(
f"flux:, {absorbed_power} (dft_fields), {absorbed_flux} (dft_flux), {err} (error)"
)
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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