def empty_run(self, sx, sy, animate=False):
sources, refl_fr, trans_fr = self.set_source(sx, sy)
sim = mp.Simulation(cell_size=mp.Vector3(sx, sy, self.sz),
geometry=[],
sources=sources,
boundary_layers=self.pml_layers,
k_point=self.k,
resolution=self.resolution)
refl = sim.add_flux(self.fcen, self.df, self.nfreq, refl_fr)
trans = sim.add_flux(self.fcen, self.df, self.nfreq, trans_fr)
if animate:
sim.run(mp.at_beginning(mp.output_epsilon),
mp.to_appended("ex", mp.at_every(0.6, mp.output_efield_z)),
until_after_sources=mp.stop_when_fields_decayed(25, mp.Ey, self.pt, 1e-3))
else:
sim.run(until_after_sources=mp.stop_when_fields_decayed(25, mp.Ey, self.pt, 1e-3))
# for normalization run, save flux fields data for reflection plane
self.store['straight_refl_data'] = sim.get_flux_data(refl)
# save incident power for transmission plane
self.store['flux_freqs'] = mp.get_flux_freqs(refl)
self.store['straight_tran_flux'] = mp.get_fluxes(trans)
self.store['straight_refl_flux'] = mp.get_fluxes(refl)
def get_flux_data_from_many(trans):
# simulation data are saved in trans
freqs = mp.get_flux_freqs(trans[0])
fluxes = [mp.get_fluxes(tran) for tran in trans]
data = np.column_stack((
freqs,
*fluxes,
))
return data
def get_flux_data_from_one(ntran, nsize):
# simulation data are saved in trans
freqs = mp.get_flux_freqs(ntran)
fluxes = mp.get_fluxes(ntran)
data = np.column_stack((
freqs,
fluxes,
))
data = np.insert(data, 1, nsize, axis=1)
return data
def my_display_fluxes(sim):
nonlocal my_display_count
nonlocal step_time
freqs=mp.get_flux_freqs(trans[0])
fluxes=[mp.get_fluxes(tran) for tran in trans]
data=np.column_stack((freqs, *fluxes,))
my.matrix_output(None,data,"{:10.3e}","flux")
my_display_count+=1
print('No. {} display at t={}'.format(
my_display_count,step_time))
mymeep.my_flush_step(sim)
def flux_monitor_cal(box_x1, box_x2, box_y1, box_y2, box_z1, box_z2):
box_x1_flux = mp.get_fluxes(box_x1)
box_x2_flux = mp.get_fluxes(box_x2)
box_y1_flux = mp.get_fluxes(box_y1)
box_y2_flux = mp.get_fluxes(box_y2)
box_z1_flux = mp.get_fluxes(box_z1)
box_z2_flux = mp.get_fluxes(box_z2)
frqs = mp.get_flux_freqs(box_x1)
p_flux = -(np.asarray(box_x1_flux) - np.asarray(box_x2_flux) +
np.asarray(box_y1_flux) - np.asarray(box_y2_flux) +
np.asarray(box_z1_flux) - np.asarray(box_z2_flux))
return frqs, p_flux
def runSimulation(thetaDegrees):
thetaRadians = np.radians(thetaDegrees)
kVector = mp.Vector3(np.sin(thetaRadians), 0,
np.cos(thetaRadians)).scale(minimumFrequency)
simulation = mp.Simulation(cell_size=cellSize,
sources=sources,
resolution=resolution,
boundary_layers=pmlLayers,
k_point=kVector)
incidentFluxMonitor = simulation.add_flux(frequency, frequencyWidth,
numberFrequencies,
incidentRegion)
simulation.run(until_after_sources=mp.stop_when_fields_decayed(
20, mp.Ex, transmissionMonitorLocation, powerDecayTarget))
incidentFluxToSubtract = simulation.get_flux_data(incidentFluxMonitor)
simulation = mp.Simulation(cell_size=cellSize,
sources=sources,
resolution=resolution,
boundary_layers=pmlLayers,
geometry=geometry,
k_point=kVector)
transmissionRegion = mp.FluxRegion(center=transmissionMonitorLocation)
transmissionFluxMonitor = simulation.add_flux(frequency, frequencyWidth,
numberFrequencies,
transmissionRegion)
reflectionRegion = incidentRegion
reflectionFluxMonitor = simulation.add_flux(frequency, frequencyWidth,
numberFrequencies,
reflectionRegion)
simulation.load_minus_flux_data(reflectionFluxMonitor,
incidentFluxToSubtract)
simulation.run(until_after_sources=mp.stop_when_fields_decayed(
20, mp.Ex, transmissionMonitorLocation, powerDecayTarget))
incidentFlux = np.array(mp.get_fluxes(incidentFluxMonitor))
transmittedFlux = np.array(mp.get_fluxes(transmissionFluxMonitor))
reflectedFlux = np.array(mp.get_fluxes(reflectionFluxMonitor))
R = np.array(-reflectedFlux / incidentFlux)
T = np.array(transmittedFlux / incidentFlux)
frequencies = np.array(mp.get_flux_freqs(reflectionFluxMonitor))
kx = kVector.x
angles = np.arcsin(kx / frequencies)
return angles, frequencies, R, T
def test_ninety_degree_bend(self):
# We have to run the straight waveguide version first to generate the 'refl-flux'
# file that this test uses. We can't just prepend run_with_straight_waveguide
# with 'test_' because execution order of unit tests isn't deterministic.
self.run_with_straight_waveguide()
self.sim = None
self.init()
self.sim.load_minus_flux('refl-flux', self.refl)
self.sim.run(until_after_sources=mp.stop_when_fields_decayed(
50, mp.Ez, self.pt, 1e-3))
expected = [
(0.09999999999999999, 1.8392235204829767e-5,
-7.259467687598002e-6),
(0.10101010101010101, 2.7629932558236724e-5,
-1.1107162110079347e-5),
(0.10202020202020202, 4.1001228946782745e-5,
-1.687561915798036e-5),
(0.10303030303030304, 6.018966076122556e-5,
-2.5425779493709066e-5),
(0.10404040404040406, 8.758554071933231e-5, -3.794958119189475e-5),
(0.10505050505050507, 1.2656696778129198e-4,
-5.612512808928115e-5),
(0.10606060606060609, 1.817948859871414e-4, -8.232188174309142e-5),
(0.10707070707070711, 2.594514094902856e-4,
-1.1981531280672989e-4),
(0.10808080808080812, 3.6736164837695035e-4,
-1.7300125173897737e-4),
(0.10909090909090914, 5.150131339048232e-4, -2.476730940385436e-4),
(0.11010101010101016, 7.136181099374187e-4,
-3.5145561406042276e-4),
(0.11111111111111117, 9.76491765781944e-4, -4.944142331545938e-4),
(0.11212121212121219, 0.001320033637882244, -6.897357105189368e-4),
(0.11313131313131321, 0.0017653940714397098,
-9.543556354451615e-4),
(0.11414141414141422, 0.0023404727796352857,
-0.0013095604571818236),
(0.11515151515151524, 0.0030813962415392098, -0.00178176942635486),
(0.11616161616161626, 0.00403238648982478, -0.0024036650652026112),
(0.11717171717171727, 0.005243320443599316, -0.003215529845495731),
(0.11818181818181829, 0.0067654019326068, -0.004266367104375331),
(0.11919191919191931, 0.008646855439680507, -0.005614491919262783),
]
res = list(
zip(mp.get_flux_freqs(self.trans), mp.get_fluxes(self.trans),
mp.get_fluxes(self.refl)))
np.testing.assert_allclose(expected, res[:20])
def force_norm():
"""perform normalization simulation"""
norm = meep.Simulation(cell_size=cell,
boundary_layers=[pml],
geometry=[],
resolution=resolution)
norm.init_fields()
source(norm)
flux_inc = meep_ext.add_flux_plane(norm, fcen, df, nfreq, [0,0,0], [2*radius, 2*radius, 0])
norm.run(until_after_sources=meep.stop_when_fields_decayed(.5*um, decay,
pt=meep.Vector3(0,0,0), decay_by=1e-5))
return {'frequency': np.array(meep.get_flux_freqs(flux_inc)), 'area': (2*radius)**2,
'incident': np.asarray(meep.get_fluxes(flux_inc))}
def plot_power(self):
flux_freqs = np.array(mp.get_flux_freqs(self.box_z2))
flux_up = np.array(mp.get_fluxes(self.box_z2))
flux_bot = np.array(mp.get_fluxes(self.box_z1))
flux_side = np.array(mp.get_fluxes(self.box_r))
flux_total = flux_bot + flux_up + flux_side
flux_wvl = 1 / flux_freqs
plt.figure(dpi=150)
plt.plot(flux_wvl, flux_total, 'r-', label='Total emission')
plt.plot(flux_wvl, flux_bot, 'g-', label='Bottom emission')
plt.plot(flux_wvl, flux_side, 'y-', label='Side emission')
plt.plot(flux_wvl, flux_up, 'b-', label='Upward emission')
plt.legend(loc='upper right')
plt.xlabel('Wavelength (µm)')
plt.ylabel('Arbitrary intensity')
return flux_freqs, flux_up, flux_bot, flux_side
def scat_sim():
"""perform scattering simulation"""
scat = meep.Simulation(cell_size=cell,
boundary_layers=[pml],
geometry=geometry,
default_material=medium,
resolution=resolution)
scat.init_fields()
source(scat)
flux_box_absorb = meep_ext.add_flux_box(scat, fcen, df, nfreq, [0,0,0], monitor_size)
flux_box_scat = meep_ext.add_flux_box(scat, fcen, df, nfreq, [0,0,0], monitor_size)
scat.load_minus_flux(norm_file_ext, flux_box_scat)
scat.run(until_after_sources=meep.stop_when_fields_decayed(.5*um, decay,
pt=meep.Vector3(0,0,monitor_size[2]/2), decay_by=1e-5))
return {'scattering': np.array(meep.get_fluxes(flux_box_scat)),'absorption': -np.array(meep.get_fluxes(flux_box_absorb)),
'frequency': np.array(meep.get_flux_freqs(flux_box_scat))}
def norm_sim():
"""perform normalization simulation"""
norm = meep.Simulation(cell_size=cell,
boundary_layers=[pml],
geometry=[],
default_material=medium,
resolution=resolution)
norm.init_fields()
source(norm)
flux_box_inc = meep_ext.add_flux_box(norm, fcen, df, nfreq, [0,0,0], monitor_size)
flux_inc = meep_ext.add_flux_plane(norm, fcen, df, nfreq, [0,0,0], [box[0], box[1], 0])
norm.run(until_after_sources=meep.stop_when_fields_decayed(.5*um, decay,
pt=meep.Vector3(0,0,monitor_size[2]/2), decay_by=1e-3))
norm.save_flux(norm_file_ext, flux_box_inc)
return {'frequency': np.array(meep.get_flux_freqs(flux_inc)), 'area': box[0]*box[1],
'incident': np.asarray(meep.get_fluxes(flux_inc))}
def get_signal(self):
trans = []
refls = []
for angle in [0, 90]:
sim = self.simulator(self.medium[angle])
tran_monitor = sim.add_flux(self.f_center, self.f_width,
self.n_freq, self.tran_fr)
refl_monitor = sim.add_flux(self.f_center, self.f_width,
self.n_freq, self.refl_fr)
sim.load_minus_flux_data(refl_monitor, self.refl_straight)
sim.run(until=self.sim_time)
trans.append(sim.get_flux_data(tran_monitor).E[:self.n_freq])
refls.append(sim.get_flux_data(refl_monitor).E[:self.n_freq])
return \
np.array(trans), \
np.array(refls), \
np.array(mp.get_flux_freqs(tran_monitor))
def simulation(sim, cell, det_dir, det_tran, det_tran_2, **simrun_args):
#inicialitzo els dos detectors (a les diferents posicions)
det_dir = det_dir #Detectors(center=mp.Vector3(-4.25,0,0),size=mp.Vector3(0,5.0,0))
det_tran = det_tran #Detectors(center=mp.Vector3(3.25,0,0),size=mp.Vector3(0,5.0,0))
det_tran_2 = det_tran_2
#afegeixo els fluxos
direct = sim.add_flux(Wave.fcen, Wave.df, Wave.nfreq, det_dir.detect_fr)
tran = sim.add_flux(Wave.fcen, Wave.df, Wave.nfreq, det_tran.detect_fr)
tran_2 = sim.add_flux(Wave.fcen, Wave.df, Wave.nfreq, det_tran_2.detect_fr)
sim.run(**simrun_args)
#prenc les dades per fer els dibuixos
eps_data = sim.get_array(center=mp.Vector3(),
size=cell,
component=mp.Dielectric)
ez_data = sim.get_array(center=mp.Vector3(), size=cell, component=mp.Ez)
#prenc les dades per fer les gràfiques
flux_freqs = mp.get_flux_freqs(direct)
direct_data = mp.get_fluxes(direct)
tran_data = mp.get_fluxes(tran)
tran_data_2 = mp.get_fluxes(tran_2)
reset = sim.reset_meep()
return eps_data, ez_data, flux_freqs, direct_data, tran_data, tran_data_2, reset
def run_chi3(k_pow, amp=1):
k = 10**k_pow
default_material = mp.Medium(index=1, chi3=k)
sources = mp.Source(mp.GaussianSource(fcen, fwidth=df),
component=mp.Ex,
center=mp.Vector3(0, 0, -0.5 * sz + dpml),
amplitude=amp)
sim = mp.Simulation(cell_size=cell,
geometry=[],
sources=[sources],
boundary_layers=[pml_layers],
default_material=default_material,
resolution=resolution,
dimensions=dimensions)
trans = sim.add_flux(
0.5 * (fmin + fmax), fmax - fmin, nfreq,
mp.FluxRegion(mp.Vector3(0, 0, 0.5 * sz - dpml - 0.5)))
# Single frequency point at omega
trans1 = sim.add_flux(
fcen, 0, 1, mp.FluxRegion(mp.Vector3(0, 0, 0.5 * sz - dpml - 0.5)))
# Singel frequency point at 3omega
trans3 = sim.add_flux(
3 * fcen, 0, 1, mp.FluxRegion(mp.Vector3(0, 0, 0.5 * sz - dpml - 0.5)))
sim.run(until_after_sources=mp.stop_when_fields_decayed(
50, mp.Ex, mp.Vector3(0, 0, 0.5 * sz - dpml - 0.5), 1e-6))
omega_flux = mp.get_fluxes(trans1)
omega3_flux = mp.get_fluxes(trans3)
freqs = mp.get_flux_freqs(trans)
spectra = mp.get_fluxes(trans)
return freqs, spectra, omega_flux, omega3_flux
def run_power(self, time_after_sources=100):
self.time_after_sources = time_after_sources
self._sim.run(until_after_sources=self.time_after_sources)
flux_freqs = np.array(mp.get_flux_freqs(self.box_z2))
flux_up = np.array(mp.get_fluxes(self.box_z2))
flux_bot = np.array(mp.get_fluxes(self.box_z1))
flux_side = np.array(mp.get_fluxes(self.box_r))
flux_total = flux_bot + flux_up + flux_side
max_uppower = max(flux_up)
max_totalpower = max(flux_total)
max_upindex = np.where(flux_up == max_uppower)
maxwvl = 1 / flux_freqs[max_upindex] # find the wavelength of maximum
sum_upratio = sum(flux_up) / sum(
flux_total) # the ratio of total upward power
max_upratio = max(flux_up) / max(
flux_total
) # at the most productive wavelength, thr ratio of upward power
flux_wvl = 1 / flux_freqs
plt.figure(dpi=150)
plt.axvline(x=maxwvl, color='b',
linestyle='--') # mark where moset productive wavelength
plt.plot(flux_wvl, flux_total, 'r-', label='Total emission')
plt.plot(flux_wvl, flux_bot, 'g-', label='Bottom emission')
plt.plot(flux_wvl, flux_side, 'y-', label='Side emission')
plt.plot(flux_wvl, flux_up, 'b-', label='Upward emission')
plt.legend(loc='upper right')
plt.xlabel('Wavelength (µm)')
plt.ylabel('Arbitrary intensity')
return flux_freqs, flux_up, flux_bot, flux_side
def sim_cavity(N=3, sy=6):
sx = 2 * (pad + dpml + N) + d - 1 # size of cell in x direction
cell = mp.Vector3(sx, sy, 0)
blk = mp.Block(size=mp.Vector3(mp.inf, w, mp.inf),
material=mp.Medium(epsilon=eps))
geometry = [blk]
for i in range(N):
geometry.append(mp.Cylinder(r, center=mp.Vector3(d / 2 + i)))
geometry.append(mp.Cylinder(r, center=mp.Vector3(-(d / 2 + i))))
src = [
mp.Source(mp.GaussianSource(fcen, fwidth=df),
component=mp.Ey,
center=mp.Vector3(-0.5 * sx + dpml),
size=mp.Vector3(0, w))
]
sim = mp.Simulation(cell_size=cell,
geometry=geometry,
boundary_layers=pml_layers,
sources=src,
symmetries=sym,
resolution=resolution)
freg = mp.FluxRegion(center=mp.Vector3(0.5 * sx - dpml - 0.5),
size=mp.Vector3(0, 2 * w))
nfreq = 500
trans = sim.add_flux(fcen, df, nfreq, freg)
sim.run(until_after_sources=mp.stop_when_fields_decayed(
50, mp.Ey, mp.Vector3(0.5 * sx - dpml - 0.5), 1e-3))
freqs = mp.get_flux_freqs(trans)
psd = mp.get_fluxes(trans)
return freqs, psd
def adjoint_run(self):
# Grab the simulation step size from the forward run
self.dt = self.sim.fields.dt
# Prepare adjoint run
self.sim.reset_meep()
# Replace sources with adjoint sources
self.adjoint_sources = []
for mi, m in enumerate(self.objective_arguments):
dJ = jacobian(self.objective_function,mi)(*self.results_list) # get gradient of objective w.r.t. monitor
self.adjoint_sources.append(m.place_adjoint_source(dJ,self.dt)) # place the appropriate adjoint sources
self.sim.change_sources(self.adjoint_sources)
# register design flux
# TODO use yee grid directly
self.design_region_monitors = [self.sim.add_dft_fields([mp.Ex,mp.Ey,mp.Ez],self.fcen,self.df,self.nf,where=dr,yee_grid=False) for dr in self.design_regions]
# add monitor used to track dft convergence
mdft = self.sim.add_dft_fields(self.decay_fields,self.fcen,self.df,1,center=self.design_regions[0].center,size=mp.Vector3(1/self.sim.resolution))
# Adjoint run
self.sim.run(until_after_sources=stop_when_dft_decayed(mdft, self.decay_dt, self.decay_fields, self.fcen, self.decay_by))
# Store adjoint fields for each design basis in array (x,y,z,field_components,frequencies)
# FIXME allow for multiple design regions
self.a_E = [np.zeros((len(dg.x),len(dg.y),len(dg.z),3,self.nf),dtype=np.complex128) for dg in self.design_grids]
for nb, dgm in enumerate(self.design_region_monitors):
for f in range(self.nf):
for ic, c in enumerate([mp.Ex,mp.Ey,mp.Ez]):
self.a_E[nb][:,:,:,ic,f] = np.atleast_3d(self.sim.get_dft_array(dgm,c,f))
# store frequencies (will be same for all monitors)
self.frequencies = np.array(mp.get_flux_freqs(self.design_region_monitors[0]))
# update optimizer's state
self.current_state = "ADJ"
def compute_flux(m=1, n=0):
if m == 1:
sources = []
for n in range(ndipole):
sources.append(
mp.Source(
mp.CustomSource(src_func=lambda t: np.random.randn()),
component=mp.Ez,
center=mp.Vector3(sx * (-0.5 + n / ndipole),
-0.5 * sy + dAg + 0.5 * dsub)))
else:
sources = [
mp.Source(mp.GaussianSource(fcen, fwidth=df),
component=mp.Ez,
center=mp.Vector3(sx * (-0.5 + n / ndipole),
-0.5 * sy + dAg + 0.5 * dsub))
]
sim = mp.Simulation(cell_size=cell_size,
resolution=resolution,
k_point=mp.Vector3(),
boundary_layers=pml_layers,
geometry=geometry,
sources=sources)
flux_mon = sim.add_flux(
fcen, df, nfreq,
mp.FluxRegion(center=mp.Vector3(0, 0.5 * sy - dpml),
size=mp.Vector3(sx)))
sim.run(until=run_time)
flux = mp.get_fluxes(flux_mon)
freqs = mp.get_flux_freqs(flux_mon)
return freqs, flux
def notch(w):
print("#----------------------------------------")
print("NOTCH WIDTH: %s nanometers" % (w * 1000))
print("#----------------------------------------")
# w is the width of the notch in the waveguide
angrad = ang * pi / 180
bottomoffset = e * h / tan(angrad)
vertices = [
mp.Vector3(w / 2 + bottomoffset, (.5 + e) * h),
mp.Vector3(-w / 2 - bottomoffset, (.5 + e) * h),
mp.Vector3(-w / 2 + bottomoffset, (.5 - e) * h),
mp.Vector3(w / 2 - bottomoffset, (.5 - e) * h)
]
if bottomoffset > w / 2:
ratio = (w / 2) / bottomoffset
vertices = [
mp.Vector3(w / 2, h / 2),
mp.Vector3(-w / 2, h / 2),
mp.Vector3(0, (.5 - e * ratio) * h)
]
print(vertices)
#Waveguide Geometry
cell = mp.Vector3(a, H)
geometry = [
mp.Block(cell, center=mp.Vector3(0, 0), material=default_material),
mp.Block(mp.Vector3(a, hu + h / 2),
center=mp.Vector3(0, (hu + h / 2) / 2),
material=upper_material),
mp.Block(mp.Vector3(a, hl + h / 2),
center=mp.Vector3(0, -(hl + h / 2) / 2),
material=lower_material),
mp.Block(mp.Vector3(a, h),
center=mp.Vector3(0, 0),
material=core_material)
]
if w > 0:
geometry.append(mp.Prism(vertices, height=1, material=upper_material))
pml_layers = [mp.Absorber(thickness=dpml)]
r00 = None
r01 = None
r10 = None
r11 = None
t00 = None
t01 = None
t10 = None
t11 = None
su0 = None
sd0 = None
su1 = None
sd1 = None
modes = [0, 1]
if only_fund:
modes = [0]
# eig_parity_fund = mp.EVEN_Z+mp.EVEN_Y;
# eig_parity_first = mp.EVEN_Z+mp.ODD_Y;
eig_parity_fund = mp.EVEN_Y
eig_parity_first = mp.ODD_Y
# for mode in [0, 1]:
for mode in modes:
if mode == 0:
eig_parity = eig_parity_fund # Fundamental
print("-----------")
print("MODE TYPE: FUNDAMENTAL")
else:
eig_parity = eig_parity_first # First Order
print("-----------")
print("MODE TYPE: FIRST ORDER")
sources = [
mp.EigenModeSource(mp.ContinuousSource(frequency=fcen),
size=mp.Vector3(0, H),
center=mp.Vector3(Ls, 0),
eig_parity=eig_parity)
]
sim = mp.Simulation(cell_size=cell,
boundary_layers=pml_layers,
geometry=geometry,
sources=sources,
resolution=resolution,
force_complex_fields=True)
'''
#--------------------------------------------------
#FOR DISPLAYING THE GEOMETRY
sim.run(until = 200)
eps_data = sim.get_array(center=mp.Vector3(), size=cell, component=mp.Dielectric)
plt.figure(dpi=100)
plt.imshow(eps_data.transpose(), interpolation='spline36', cmap='binary')
#plt.axis('off')
plt.show()
quit()
#----------------------------------------------------
'''
'''
#------------------------------------------------------
#FOR GENERATING THE ELECTRIC FIELD GIF
#Note: After running this program, write the following commands in Terminal:
# $ source deactivate mp
# $ cd notch-out/
# $ python ../NotchIP.py
sim.use_output_directory()
sim.run(mp.at_beginning(mp.output_epsilon),
mp.to_appended("ez", mp.at_every(0.6, mp.output_efield_z)),
until = 200)
#sim.run(mp.at_every(0.6 , mp.output_png(mp.Ez, "-Zc dkbluered")), until=200)
#---------------------------------------------------------
'''
#---------------------------------------------------------
# FOR GENERATING THE TRANSMITTANCE SPECTRUM
nfreq = 1 # number of frequencies at which to compute flux
refl_fr1 = mp.FluxRegion(center=mp.Vector3(Lr1, 0),
size=mp.Vector3(
0, monitorheight)) # Reflected flux 1
refl_fr2 = mp.FluxRegion(center=mp.Vector3(Lr2, 0),
size=mp.Vector3(
0, monitorheight)) # Reflected flux 2
tran_fr = mp.FluxRegion(center=mp.Vector3(Lt, 0),
size=mp.Vector3(
0, monitorheight)) # Transmitted flux
su_fr = mp.FluxRegion(center=mp.Vector3(0, monitorheight / 2),
size=mp.Vector3(
a, 0)) # Flux loss above the waveguide
sd_fr = mp.FluxRegion(center=mp.Vector3(0, -monitorheight / 2),
size=mp.Vector3(
a, 0)) # Flux loss below the waveguide
# refl1 = sim.add_flux(fcen, df, nfreq, refl_fr1)
# refl2 = sim.add_flux(fcen, df, nfreq, refl_fr2)
# tran = sim.add_flux(fcen, df, nfreq, tran_fr)
# su = sim.add_flux(fcen, df, nfreq, su_fr)
# sd = sim.add_flux(fcen, df, nfreq, sd_fr)
# ------------------------ CODE FOR SEPARATING FUND AND FIRST ORDER MODE STARTS HERE ------------------------
refl_vals = []
tran_vals = []
def get_refl_slice(sim):
# print(sim.get_array(center=mp.Vector3(Lr1,0), size=mp.Vector3(0,H), component=mp.Ez, cmplx=True))
# refl_val = sim.get_array(center=mp.Vector3(Lr1,0), size=mp.Vector3(0,H), component=mp.Ez, cmplx=True)
refl_vals.append(
sim.get_array(center=mp.Vector3(Lr1, 0),
size=mp.Vector3(0,
monitorheight - 2 / resolution),
component=mp.Ez,
cmplx=True))
def get_tran_slice(sim):
# print(sim.get_array(center=mp.Vector3(Lt, 0), size=mp.Vector3(0,H), component=mp.Ez, cmplx=True))
# tran_val = sim.get_array(center=mp.Vector3(Lt, 0), size=mp.Vector3(0,H), component=mp.Ez, cmplx=True)
tran_vals.append(
sim.get_array(center=mp.Vector3(Lt, 0),
size=mp.Vector3(0,
monitorheight - 2 / resolution),
component=mp.Ez,
cmplx=True))
gif = True
if gif: # and w == 0.1:
sim.use_output_directory()
sim.run(mp.at_beginning(mp.output_epsilon),
mp.at_end(get_refl_slice),
mp.at_end(get_tran_slice),
until=100)
refl1 = sim.add_flux(fcen, df, nfreq, refl_fr1)
refl2 = sim.add_flux(fcen, df, nfreq, refl_fr2)
tran = sim.add_flux(fcen, df, nfreq, tran_fr)
su = sim.add_flux(fcen, df, nfreq, su_fr)
sd = sim.add_flux(fcen, df, nfreq, sd_fr)
# sim.run(mp.at_every(wavelength / 20, mp.output_efield_z), until=wavelength)
# sim.run(mp.at_every(wavelength/20 , mp.output_png(mp.Ez, "-RZc bluered -A notch-out/notch-eps-000000000.h5 -a gray:.2")), until=19*wavelength/20)
sim.run(mp.at_every(
wavelength / 20,
mp.output_png(
mp.Ez,
"-RZc bluered -A notch-out/notch-eps-000000.00.h5 -a gray:.2"
)),
until=19 * wavelength / 20)
sim.run(until=50)
else:
sim.run(mp.at_end(get_refl_slice),
mp.at_end(get_tran_slice),
until=100)
sim.run(until_after_sources=mp.stop_when_fields_decayed(
50, mp.Ez, mp.Vector3(), 1e-5))
os.system(
"h5topng notch-out/notch-eps-000000.00.h5; mv notch-out/notch-eps-000000.00.png "
+ case + "-" + str(int(w * 1000)) + "-" + str(mode) + "-eps.png")
os.system("cp notch-out/notch-ez-000100.00.png " + case + "-" +
str(int(w * 1000)) + "-" + str(mode) + ".png")
os.system("convert notch-out/notch-ez-*.png " + case + "-" +
str(int(w * 1000)) + "-" + str(mode) + ".gif")
# get_eigenmode(fcen, mp., refl_fr1, 1, kpoint)
# v = mp.volume(mp.vec(Lr1, -monitorheight/2), mp.vec(Lr1, monitorheight/2))
# mode = get_eigenmode(fcen, mp.X, v, v, 1, mp.vec(0, 0, 0), True, 0, 0, 1e-7, True)
# print(mode.amplitude)
# coef_refl_fund = mp.get_eigenmode_coefficients_and_kpoints(refl_fr1, 1, eig_parity=eig_parity_fund, eig_resolution=resolution, eig_tolerance=1e-7)
# coef_refl_first = mp.get_eigenmode_coefficients_and_kpoints(refl_fr1, 1, eig_parity=eig_parity_first, eig_resolution=resolution, eig_tolerance=1e-7)
#
# coef_tran_fund = mp.get_eigenmode_coefficients_and_kpoints(tran_fr, 1, eig_parity=eig_parity_fund, eig_resolution=resolution, eig_tolerance=1e-7)
# coef_tran_first = mp.get_eigenmode_coefficients_and_kpoints(tran_fr, 1, eig_parity=eig_parity_first, eig_resolution=resolution, eig_tolerance=1e-7)
ep = mp.ODD_Z
#coef_refl_fund, vgrp, kpoints_fund = sim.get_eigenmode_coefficients(refl1, [1], eig_parity=ep, eig_resolution=resolution, eig_tolerance=1e-7)
#coef_refl_first, vgrp, kpoints_first = sim.get_eigenmode_coefficients(refl1, [2], eig_parity=ep, eig_resolution=resolution, eig_tolerance=1e-7)
#coef_tran_fund, vgrp, kpoints_fund = sim.get_eigenmode_coefficients(tran, [1], eig_parity=ep, eig_resolution=resolution, eig_tolerance=1e-7)
#coef_tran_first, vgrp, kpoints_first = sim.get_eigenmode_coefficients(tran, [2], eig_parity=ep, eig_resolution=resolution, eig_tolerance=1e-7)
# print(kpoints_fund)
# print(kpoints_first)
# print(kpoints_fund[0])
# print(type(kpoints_fund[0]))
# print(dir(kpoints_fund[0]))
# n_eff_fund = wavelength*kpoints_fund[0].x
# n_eff_first = wavelength*kpoints_first[0].x
n_eff_fund = neff
n_eff_first = 1
print(n_eff_fund)
print(n_eff_first)
# print(coef_refl_fund)
# print(type(coef_refl_fund))
# print(dir(coef_refl_fund))
# print(coef_refl_fund[0])
# print(coef_refl_fund[0][0,0,:])
#
# fund_refl_amp = coef_refl_fund[0][0,0,1];
# first_order_refl_amp = coef_refl_first[0][0,0,1];
# fund_tran_amp = coef_tran_fund[0][0,0,0];
# first_order_tran_amp = coef_tran_first[0][0,0,0];
print("get_eigenmode_coefficients:\n")
#print(coef_refl_fund)
#print(coef_refl_first)
#print(coef_tran_fund)
#print(coef_tran_first)
print("\n")
# print(coef_refl_fund[0,0,:])
#fund_refl_amp = coef_refl_fund[0,0,1];
#first_order_refl_amp = coef_refl_first[0,0,1];
#fund_tran_amp = coef_tran_fund[0,0,0];
#first_order_tran_amp = coef_tran_first[0,0,0];
refl_val = refl_vals[0]
tran_val = tran_vals[0]
# n_eff must satisfy n_e <= n_eff <= n_c for the mode to be bound.
def fund_func(n_eff):
if n_eff >= n_c and n_eff <= n_e:
return sqrt(n_eff**2 - n_c**2) - sqrt(n_e**2 - n_eff**2) * tan(
pi * h / wavelength * sqrt(n_e**2 - n_eff**2))
def first_order_func(n_eff):
if n_eff >= n_c and n_eff <= n_e:
return sqrt(n_eff**2 - n_c**2) - sqrt(n_e**2 - n_eff**2) * tan(
pi * h / wavelength * sqrt(n_e**2 - n_eff**2) - pi / 2)
initial_guess = (n_c + n_e) / 2
# n_eff_fund = fsolve(fund_func, initial_guess)
# n_eff_first = fsolve(first_order_func, n_c)
print(n_eff_fund, n_eff_first)
assert (n_eff_fund > n_eff_first)
if len(n_eff_funds) == 0:
n_eff_funds.append(n_eff_fund)
if len(n_eff_firsts) == 0:
n_eff_firsts.append(n_eff_first)
ky0_fund = np.abs(2 * pi / wavelength * sqrt(n_e**2 - n_eff_fund**2))
ky0_first = np.abs(2 * pi / wavelength * sqrt(n_e**2 - n_eff_first**2))
ky1_fund = ky0_fund # np.abs(2 * pi / wavelength * sqrt(n_eff_fund **2 - n_c**2))
ky1_first = ky0_first # np.abs(2 * pi / wavelength * sqrt(n_eff_first**2 - n_c**2))
E_fund = lambda y: cos(ky0_fund * y) if np.abs(y) < h / 2 else cos(
ky0_fund * h / 2) * np.exp(-ky1_fund * (np.abs(y) - h / 2))
E_first_order = lambda y: sin(ky0_first * y) if np.abs(
y) < h / 2 else sin(ky0_first * h / 2) * np.exp(-ky1_first * (
np.abs(y) - h / 2)) * np.sign(y)
# y_list = np.arange(-H/2+.5/resolution, H/2-.5/resolution, 1/resolution)
#print("Y LIST: ", y_list)
#print("SIZE OF Y LIST: ", y_list.size)
E_fund_vec = np.zeros(y_list.size)
E_first_order_vec = np.zeros(y_list.size)
for index in range(y_list.size):
y = y_list[index]
E_fund_vec[index] = E_fund(y)
E_first_order_vec[index] = E_first_order(y)
# print(dir(sim))
# print(type(sim.get_eigenmode_coefficients))
# print(dir(sim.get_eigenmode_coefficients))
# print(type(sim.get_eigenmode))
# print(dir(sim.get_eigenmode))
# print(sim.get_eigenmode.__code__.co_varnames)
# print(sim.get_eigenmode.__defaults__)
# E1 = sim.get_eigenmode(fcen, mp.X, refl1.where, 1, None)
# E2 = sim.get_eigenmode(fcen, mp.X, refl1.where, 2, None)
# E3 = sim.get_eigenmode(fcen, mp.X, refl1.where, 3, None)
# E4 = sim.get_eigenmode(fcen, mp.X, refl1.where, 4, None)
# E1 = sim.get_eigenmode(fcen, mp.X, refl1.where, 1, mp.Vector3(0, 0, 0))
# E2 = sim.get_eigenmode(fcen, mp.X, refl1.where, 2, mp.Vector3(0, 0, 0))
# E3 = sim.get_eigenmode(fcen, mp.X, refl1.where, 3, mp.Vector3(0, 0, 0))
# E4 = sim.get_eigenmode(fcen, mp.X, refl1.where, 4, mp.Vector3(0, 0, 0))
# print(refl1.where)
# numEA = 0
# E1 = sim.fields.get_eigenmode(fcen, mp.X, refl1.where, refl1.where, 1, mp.vec(0,0,0), True, 0, numEA, 1e-7, True)
# print(type(E1))
# print(dir(E1))
#
# print(refl1.where)
# # print(E1, E2, E3, E4)
# print(E1.amplitude, E1.band_num, E1.group_velocity, E1.k)
# print(type(E1.amplitude))
# print(dir(E1.amplitude))
# print(doc(E1.amplitude))
# print(self(E1.amplitude))
# print(E1.amplitude(y_list))
# print(type(E1.amplitude(y_list)))
# print(dir(E1.amplitude(y_list)))
# print(E1.amplitude, E2.amplitude, E3.amplitude, E4.amplitude)
# E1 = sim.get_eigenmode(fcen, mp.X, refl1.where, refl1.where, 1, mp.vec(0, 0, 0))
# E2 = sim.get_eigenmode(fcen, mp.X, refl1.where, refl1.where, 2, mp.vec(0, 0, 0))
# E3 = sim.get_eigenmode(fcen, mp.X, refl1.where, refl1.where, 3, mp.vec(0, 0, 0))
# E4 = sim.get_eigenmode(fcen, mp.X, refl1.where, refl1.where, 4, mp.vec(0, 0, 0))
# print(y_list)
#
# E1a = np.zeros(y_list.size, dtype='Complex128');
# E2a = np.zeros(y_list.size, dtype='Complex128');
# E3a = np.zeros(y_list.size, dtype='Complex128');
# E4a = np.zeros(y_list.size, dtype='Complex128');
#
# # print(mp.eigenmode_amplitude.__code__.co_varnames)
# # print(mp.eigenmode_amplitude.__defaults__)
#
# for i in range(y_list.size):
# # print(E1)
# # print(E1.swigobj)
# # print(E1.amplitude)
# # print(mp.vec(Lr1, y_list[i], 0))
# # print(mp.Vector3(Lr1, y_list[i], 0))
# # print(mp.Ez)
# # E1a[i] = mp.eigenmode_amplitude(E1.swigobj, mp.vec(Lr1, y_list[i], 0), mp.Ez);
# eval_point = mp.vec(Lr1, y_list[i], 0)
# # print(eval_point)
# E1a[i] = mp.eigenmode_amplitude(E1.swigobj, eval_point, mp.Ex)
# E2a[i] = mp.eigenmode_amplitude(E2.swigobj, eval_point, mp.Ex)
# E3a[i] = mp.eigenmode_amplitude(E3.swigobj, eval_point, mp.Ex)
# E4a[i] = mp.eigenmode_amplitude(E4.swigobj, eval_point, mp.Ex)
# # E1a[i] = mp.eigenmode_amplitude(E1.amplitude, mp.Vector3(Lr1, y_list[i], 0), mp.Ez);
#
# plt.plot(y_list, np.abs(E1a)**2, 'bo-', label='E1')
# plt.plot(y_list, np.abs(E2a)**2, 'ro-', label='E2')
# plt.plot(y_list, np.abs(E3a)**2, 'go-', label='E3')
# plt.plot(y_list, np.abs(E4a)**2, 'co-', label='E4')
# # plt.axis([40.0, 300.0, 0.0, 100.0])
# plt.xlabel("y (um)")
# plt.ylabel("Field (a.u.)")
# plt.legend(loc="center right")
# plt.show()
# print("r VECTOR: ", refl_val)
# print("t VECTOR: ", tran_val)
# print("E0 VECTOR: ", E_fund_vec)
# print("E1 VECTOR: ", E_first_order_vec)
# fund_refl_amp_2 = np.conj(np.dot(refl_val, E_fund_vec) / np.dot(E_fund_vec, E_fund_vec)) # Conjugate becasue MEEP uses physics exp(kz-wt) rather than engineering exp(wt-kz)
# first_order_refl_amp_2 = np.conj(np.dot(refl_val, E_first_order_vec) / np.dot(E_first_order_vec, E_first_order_vec))
# fund_tran_amp_2 = np.conj(np.dot(tran_val, E_fund_vec) / np.dot(E_fund_vec, E_fund_vec))
# first_order_tran_amp_2 = np.conj(np.dot(tran_val, E_first_order_vec) / np.dot(E_first_order_vec, E_first_order_vec))
fund_refl_amp = np.conj(
np.dot(refl_val, E0) / np.dot(E0, E0)
) # Conjugate becasue MEEP uses physics exp(kz-wt) rather than engineering exp(wt-kz)
first_order_refl_amp = 0 # np.conj(np.dot(refl_val, E1[:,2]) / np.dot(E1[:,2], E1[:,2]))
fund_tran_amp = np.conj(np.dot(tran_val, E0) / np.dot(E0, E0))
first_order_tran_amp = 0 # np.conj(np.dot(tran_val, E1[:,2]) / np.dot(E1[:,2], E1[:,2]))
fund_refl = np.conj(fund_refl_amp) * E0
not_fund_refl = refl_val - fund_refl
fund_tran = np.conj(fund_tran_amp) * E0
not_fund_tran = tran_val - fund_tran
fund_refl_power = np.dot(np.conj(fund_refl), fund_refl)
not_fund_refl_power = np.dot(np.conj(not_fund_refl), not_fund_refl)
fund_tran_power = np.dot(np.conj(fund_tran), fund_tran)
not_fund_tran_power = np.dot(np.conj(not_fund_tran), not_fund_tran)
fund_refl_ratio = np.abs(fund_refl_power /
(fund_refl_power + not_fund_refl_power))
first_order_refl_ratio = 0
fund_tran_ratio = np.abs(fund_tran_power /
(fund_tran_power + not_fund_tran_power))
first_order_tran_ratio = 0
# plt.plot(y_list, np.abs(refl_val), 'bo-',label='reflectance')
# plt.plot(y_list, np.abs(tran_val), 'ro-',label='transmittance')
# plt.plot(y_list, E0, 'go-',label='E0')
# plt.plot(y_list, fund_refl_amp*E0, 'co-',label='over')
# # plt.axis([40.0, 300.0, 0.0, 100.0])
# plt.xlabel("y (um)")
# plt.ylabel("Field")
# plt.legend(loc="center right")
# plt.show()
#
# print("\n")
#
# print(tran_val.size, refl_val.size)
#
# print("\n")
#
# print(tran_val, refl_val, E0)
#
# print("\n")
# # print(np.conj(tran_val), tran_val, E1[:,2])
# #
# # print(np.conj(refl_val), refl_val, E1[:,2])
#
# refl_tot_power = np.abs(np.dot(np.conj(refl_val), refl_val))
# tran_tot_power = np.abs(np.dot(np.conj(tran_val), tran_val))
#
# print(fund_refl_amp, refl_tot_power, fund_tran_amp, tran_tot_power)
# print(fund_refl_amp , fund_refl_amp_2 )
# print(first_order_refl_amp , first_order_refl_amp_2)
# print(fund_tran_amp , fund_tran_amp_2 )
# print(first_order_tran_amp , first_order_tran_amp_2)
#
# print(np.angle(fund_refl_amp), np.angle(fund_refl_amp_2))
# print(np.angle(first_order_refl_amp), np.angle(first_order_refl_amp_2))
# print(np.angle(fund_tran_amp), np.angle(fund_tran_amp_2))
# print(np.angle(first_order_tran_amp), np.angle(first_order_tran_amp_2))
# fund_refl_power = np.abs(fund_tran_amp) ** 2
# fund_refl_power = np.abs(fund_refl_amp) ** 2
# first_order_refl_power = np.abs(first_order_refl_amp) ** 2
# fund_tran_power = np.abs(fund_tran_amp) ** 2
# first_order_tran_power = np.abs(first_order_tran_amp) ** 2
# print(fund_refl_power, first_order_refl_power, fund_tran_power, first_order_tran_power)
# fund_refl_ratio = fund_refl_power / (fund_refl_power + first_order_refl_power)
# first_order_refl_ratio = first_order_refl_power / (fund_refl_power + first_order_refl_power)
# fund_tran_ratio = fund_tran_power / (fund_tran_power + first_order_tran_power)
# first_order_tran_ratio = first_order_tran_power / (fund_tran_power + first_order_tran_power)
# fund_refl_power = np.abs(fund_refl_amp) ** 2
# first_order_refl_power = np.abs(first_order_refl_amp) ** 2
# fund_tran_power = np.abs(fund_tran_amp) ** 2
# first_order_tran_power = np.abs(first_order_tran_amp) ** 2
#
# fund_refl_ratio = fund_refl_power / refl_tot_power
# first_order_refl_ratio = first_order_refl_power / refl_tot_power
# fund_tran_ratio = fund_tran_power / tran_tot_power
# first_order_tran_ratio = first_order_tran_power / tran_tot_power
#
# fund_refl_ratio = 1
# first_order_refl_ratio = 0
# fund_tran_ratio = 1
# first_order_tran_ratio = 0
print("Percentage of reflected light in fundamental mode: ",
fund_refl_ratio * 100)
print("Percentage of reflected light in first order mode: ",
first_order_refl_ratio * 100)
print("Percentage of transmitted light in fundamental mode: ",
fund_tran_ratio * 100)
print("Percentage of transmitted light in first order mode: ",
first_order_tran_ratio * 100)
# ------------------------ CODE FOR SEPARATING FUND AND FIRST ORDER MODE ENDS HERE ------------------------
wl = [] #list of wavelengths
refl1_flux = mp.get_fluxes(refl1)
refl2_flux = mp.get_fluxes(refl2)
tran_flux = mp.get_fluxes(tran)
su_flux = mp.get_fluxes(su)
sd_flux = mp.get_fluxes(sd)
flux_freqs = mp.get_flux_freqs(refl1)
for i in range(nfreq):
wl = np.append(wl, 1 / flux_freqs[i])
print(1 / flux_freqs[i])
# for ind, elt in enumerate(wl):
# #print(round(elt, 4))
# if round(elt, 3) == 0.637:
# #print("ALERT: MATCH FOUND")
# index = ind
index = 0
rp = refl1_flux[index]
tp = tran_flux[index]
# print("rp/tp:\n")
# print(rp)
# print(tp)
# print("\n")
R = -refl1_flux[index] / (refl2_flux[index] - refl1_flux[index])
T = tran_flux[index] / (refl2_flux[index] - refl1_flux[index])
S = (refl2_flux[index] - tran_flux[index]) / (refl2_flux[index] -
refl1_flux[index])
Su = su_flux[index] / (refl2_flux[index] - refl1_flux[index])
Sd = -sd_flux[index] / (refl2_flux[index] - refl1_flux[index])
S_correction = (1 - R - T) / (Su + Sd)
# print(R, T, S, Su, Sd)
r = sqrt(R)
t = sqrt(T)
# The amplitude ... times the phase ... accounting for the distance to the detector (Reverse exp(-kz) of phase).
# r_fund = (r * fund_refl_ratio) * (fund_refl_amp / np.abs(fund_refl_amp)) * (np.exp( 2j*pi * (-Lr1 - w/2) * n_eff_fund / wavelength)) # Lr1 is negative because it is the (negative) position of the monitor, not the distace from the monitor to the center.
# r_first = (r * first_order_refl_ratio) * (first_order_refl_amp / np.abs(first_order_refl_amp)) * (np.exp( 2j*pi * (-Lr1 - w/2) * n_eff_first / wavelength))
# t_fund = (t * fund_tran_ratio) * (fund_tran_amp / np.abs(fund_tran_amp)) * (np.exp( 2j*pi * ( Lt - w/2) * n_eff_fund / wavelength))
# t_first = (t * first_order_tran_ratio) * (first_order_tran_amp / np.abs(first_order_tran_amp)) * (np.exp( 2j*pi * ( Lt - w/2) * n_eff_first / wavelength))
r_fund = (r * fund_refl_ratio) * np.exp(
1j * np.angle(fund_refl_amp) + 2j * pi *
(-Lr1 - w / 2) * n_eff_fund / wavelength
) # Lr1 is negative because it is the (negative) position of the monitor, not the distace from the monitor to the center.
r_first = (r * first_order_refl_ratio
) * np.exp(1j * np.angle(first_order_refl_amp) + 2j * pi *
(-Lr1 - w / 2) * n_eff_first / wavelength)
t_fund = (t * fund_tran_ratio
) * np.exp(1j * np.angle(fund_tran_amp) + 2j * pi *
(Lt - w / 2) * n_eff_fund / wavelength)
t_first = (t * first_order_tran_ratio
) * np.exp(1j * np.angle(first_order_tran_amp) + 2j * pi *
(Lt - w / 2) * n_eff_first / wavelength)
if mode == 0:
r00 = r_fund
r01 = r_first
t00 = t_fund
t01 = t_first
su0 = sqrt(np.abs(Su * S_correction))
sd0 = sqrt(np.abs(Sd * S_correction))
# su0 = sqrt(Su)
# sd0 = sqrt(Sd)
r00s.append(r00)
r01s.append(r01)
t00s.append(t00)
t01s.append(t01)
su0s.append(su0)
sd0s.append(sd0)
if only_fund:
r10s.append(0)
r11s.append(0)
t10s.append(0)
t11s.append(1)
su1s.append(0)
sd1s.append(0)
else:
r10 = r_fund
r11 = r_first
t10 = t_fund
t11 = t_first
su1 = sqrt(np.abs(Su * S_correction))
sd1 = sqrt(np.abs(Sd * S_correction))
# su1 = sqrt(Su)
# sd1 = sqrt(Sd)
r10s.append(r10)
r11s.append(r11)
t10s.append(t10)
t11s.append(t11)
su1s.append(su1)
sd1s.append(sd1)
norm_Su = S * Su / (Su + Sd)
NET = round((R + T + S) * 100, 0)
if NET > 100.0:
NET = 100.0
NET_LOSS = round((Su + Sd) / S * 100, 0)
if NET_LOSS > 100.0:
NET_LOSS = 100.0
'''
np.append(ws, [w * 1000])
np.append(Rs, [R * 100])
np.append(Ts, [T * 100])
np.append(Ss, [S * 100])
np.append(NET_LIST, [NET])
np.append(Sus, [Su * 100])
np.append(Sds, [Sd * 100])
np.append(NET_LOSS_LIST, [NET_LOSS])
np.append(norm_Sus, [norm_Su * 100])
'''
if mode == 0:
ws.append(w * 1000)
Rs.append(R * 100)
Ts.append(T * 100)
Ss.append(S * 100)
NET_LIST.append(NET)
Sus.append(Su * 100)
Sds.append(Sd * 100)
NET_LOSS_LIST.append(NET_LOSS)
norm_Sus.append(norm_Su * 100)
if mode == 0:
f1.write("--------------------------------------------------- \n")
f1.write("Notch Width: %s nanometers \n" % (w * 1000))
f1.write("Reflection Percentage: %s\n" % (R * 100))
f1.write("Transmission Percentage: %s\n" % (T * 100))
f1.write("Total Loss Percentage: %s\n" % (S * 100))
f1.write("Percentage of Light Accounted For: %s\n" % (NET))
f1.write("Upper Loss Percentage: %s\n" % (Su * 100))
f1.write("Lower Loss Percentage: %s\n" % (Sd * 100))
f1.write("Percentage of Total Loss Accounted For: %s\n" %
(NET_LOSS))
f1.write("Normalized Upper Loss Percentage: %s\n" %
(norm_Su * 100))
f1.write("\n \n")
f1.write("FUNDAMENTAL MODE \n")
f1.write("n_eff: %s\n" % (n_eff_fund))
f1.write("Re(r00): %s\n" % (np.real(r00)))
f1.write("Im(r00): %s\n" % (np.imag(r00)))
f1.write("Re(r01): %s\n" % (np.real(r01)))
f1.write("Im(r01): %s\n" % (np.imag(r01)))
f1.write("Re(t00): %s\n" % (np.real(t00)))
f1.write("Im(t00): %s\n" % (np.imag(t00)))
f1.write("Re(t01): %s\n" % (np.real(t01)))
f1.write("Im(t01): %s\n" % (np.imag(t01)))
f1.write("Re(su0): %s\n" % (np.real(su0)))
f1.write("Im(su0): %s\n" % (np.imag(su0)))
f1.write("Re(sd0): %s\n" % (np.real(sd0)))
f1.write("Im(sd0): %s\n" % (np.imag(sd0)))
f1.write("\n")
else:
f1.write("FIRST ORDER MODE \n")
f1.write("n_eff: %s\n" % (n_eff_first))
f1.write("Re(r10): %s\n" % (np.real(r10)))
f1.write("Im(r10): %s\n" % (np.imag(r10)))
f1.write("Re(r11): %s\n" % (np.real(r11)))
f1.write("Im(r11): %s\n" % (np.imag(r11)))
f1.write("Re(t10): %s\n" % (np.real(t10)))
f1.write("Im(t10): %s\n" % (np.imag(t10)))
f1.write("Re(t11): %s\n" % (np.real(t11)))
f1.write("Im(t11): %s\n" % (np.imag(t11)))
f1.write("Re(su1): %s\n" % (np.real(su1)))
f1.write("Im(su1): %s\n" % (np.imag(su1)))
f1.write("Re(sd1): %s\n" % (np.real(sd1)))
f1.write("Im(sd1): %s\n" % (np.imag(sd1)))
f1.write("--------------------------------------------------- \n")
sim.reset_meep()
sources=sources,
ensure_periodicity=True,
k_point=mp.Vector3())
transmittance_first_fr = mp.FluxRegion(center=mp.Vector3(
0.5 * cellx - dpml, 0, 0),
size=mp.Vector3(0, celly))
transmittance_first = sim.add_flux(frq_cen, dfrq, nfrq,
transmittance_first_fr)
pt = mp.Vector3(0.5 * cellx - dpml, 0, 0)
sim.run(until_after_sources=100)
transmittance_first_flux = mp.get_fluxes(transmittance_first)
box_x1_data = sim.get_flux_data(transmittance_first)
flux_freqs = mp.get_flux_freqs(transmittance_first)
sim.reset_meep()
geometry = [
mp.Block(mp.Vector3(block_thicknessx, block_thicknessy, mp.inf),
center=mp.Vector3(),
material=Material)
]
pt = mp.Vector3(0.5 * cellx - dpml, 0, 0)
sim = mp.Simulation(resolution=resolution,
symmetries=symmetries,
cell_size=mp.Vector3(cellx, celly),
boundary_layers=pml_layers,
sources=sources,
k_point=mp.Vector3(),
ensure_periodicity=True,
def planar_reflectance(theta):
# rotation angle (in degrees) of source: CCW around Y axis, 0 degrees along +Z axis
theta_r = math.radians(theta)
# plane of incidence is XZ; rotate counter clockwise (CCW) about y-axis
k = mp.Vector3(z=fmin).rotate(mp.Vector3(y=1), theta_r)
# if normal incidence, force number of dimensions to be 1
if theta_r == 0:
dimensions = 1
else:
dimensions = 3
sources = [mp.Source(mp.GaussianSource(fcen,fwidth=df), component=mp.Ex, center=mp.Vector3(z=-0.5*sz+dpml))]
sim = mp.Simulation(cell_size=cell_size,
boundary_layers=pml_layers,
sources=sources,
k_point=k,
dimensions=dimensions,
resolution=resolution)
refl_fr = mp.FluxRegion(center=mp.Vector3(z=-0.25*sz))
refl = sim.add_flux(fcen, df, nfreq, refl_fr)
sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ex, mp.Vector3(z=-0.5*sz+dpml), 1e-9))
empty_flux = mp.get_fluxes(refl)
empty_data = sim.get_flux_data(refl)
sim.reset_meep()
# add a block with n=3.5 for the air-dielectric interface
geometry = [mp.Block(mp.Vector3(mp.inf,mp.inf,0.5*sz), center=mp.Vector3(z=0.25*sz), material=mp.Medium(index=3.5))]
sim = mp.Simulation(cell_size=cell_size,
geometry=geometry,
boundary_layers=pml_layers,
sources=sources,
k_point=k,
dimensions=dimensions,
resolution=resolution)
refl = sim.add_flux(fcen, df, nfreq, refl_fr)
sim.load_minus_flux_data(refl, empty_data)
sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ex, mp.Vector3(z=-0.5*sz+dpml), 1e-9))
refl_flux = mp.get_fluxes(refl)
freqs = mp.get_flux_freqs(refl)
wvls = np.empty(nfreq)
theta_out = np.empty(nfreq)
R = np.empty(nfreq)
for i in range(nfreq):
wvls[i] = 1/freqs[i]
theta_out[i] = math.degrees(math.asin(k.x/freqs[i]))
R[i] = -refl_flux[i]/empty_flux[i]
print("refl:, {}, {}, {}, {}".format(k.x,wvls[i],theta_out[i],R[i]))
return k.x*np.ones(nfreq), wvls, theta_out, R
def main(args):
resolution = args.res
dpml = 1.0 # PML thickness
sz = 10 + 2 * dpml # 10 is size of cell without PMLs
# A 1d cell must be used since a higher-dimensional cell
# will introduce artificial modes due to band folding.
cell_size = mp.Vector3(0, 0, sz)
pml_layers = [mp.PML(dpml)]
# Gaussian w/visible spectrum
wvl_min = 0.4 # min wavelength
wvl_max = 0.8 # max wavelength
fmin = 1 / wvl_max # min frequency
fmax = 1 / wvl_min # max frequency
fcen = 0.5 * (fmin + fmax) # center frequency
df = fmax - fmin # frequency width
nfreq = 50 # number of frequency bins
# Unlike a continuous-wave (CW) source, a pulsed source turns off.
# Rotation angle of planewave
# (input in degrees and transformed to radians)
theta_r = math.radians(args.theta)
# Counterclockwise (CCW) around Y axis
# 0 degrees along +Z axis
# Plane of incidence is XZ
k = mp.Vector3(math.sin(theta_r), 0, math.cos(theta_r)).scale(fmin)
# Where k is given by dispersion relation formula
# ω = c|k⃗|/n (planewave in homogeneous media of index n)
# As the source here is incident from air,
# |k⃗| = ω
# >> Note that a fixed wavevector only applies to a single frequency.
# Any broadband source is incident at a given angle
# for only a single frequency.
# >> In order to model the S-polarization, we must use an Ey source.
# This example involves just the P-polarization.
# If normal incidence, force number of dimensions to be 1
if theta_r == 0:
dimensions = 1
else:
dimensions = 3
# In Meep, a 1d cell is defined along the z direction.
# When k⃗ is not set, only the Ex and Hy field components are permitted.
sources = [
mp.Source(mp.GaussianSource(fcen, fwidth=df),
component=mp.Ex,
center=mp.Vector3(0, 0, -0.5 * sz + dpml))
]
sim = mp.Simulation(cell_size=cell_size,
boundary_layers=pml_layers,
sources=sources,
k_point=k,
dimensions=dimensions,
resolution=resolution)
refl_fr = mp.FluxRegion(center=mp.Vector3(0, 0, -0.25 * sz))
refl = sim.add_flux(fcen, df, nfreq, refl_fr)
sim.run(until_after_sources=mp.stop_when_fields_decayed(
50, mp.Ex, mp.Vector3(0, 0, -0.5 * sz + dpml), 1e-9))
empty_flux = mp.get_fluxes(refl)
empty_data = sim.get_flux_data(refl)
sim.reset_meep()
# add a block with n=3.5 for the air-dielectric interface
geometry = [
mp.Block(mp.Vector3(mp.inf, mp.inf, 0.5 * sz),
center=mp.Vector3(0, 0, 0.25 * sz),
material=mp.Medium(index=3.5))
]
sim = mp.Simulation(cell_size=cell_size,
geometry=geometry,
boundary_layers=pml_layers,
sources=sources,
k_point=k,
dimensions=dimensions,
resolution=resolution)
refl = sim.add_flux(fcen, df, nfreq, refl_fr)
sim.load_minus_flux_data(refl, empty_data)
sim.run(until_after_sources=mp.stop_when_fields_decayed(
50, mp.Ex, mp.Vector3(0, 0, -0.5 * sz + dpml), 1e-9))
refl_flux = mp.get_fluxes(refl)
freqs = mp.get_flux_freqs(refl)
for i in range(nfreq):
print("refl:, {}, {}, {}, {}".format(
k.x,
1 / freqs[i],
math.degrees(math.asin(k.x / freqs[i])), # if freq is freqmin
-refl_flux[i] / empty_flux[i]))
resolution=resolution)
refl_fr = mp.FluxRegion(center=mp.Vector3(0,0,-0.25*sz))
refl = sim.add_flux(fcen, df, nfreq, refl_fr)
sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ex, mp.Vector3(), 1e-9))
empty_flux = mp.get_fluxes(refl)
empty_data = sim.get_flux_data(refl)
sim.reset_meep()
geometry = [ mp.Block(mp.Vector3(mp.inf,mp.inf,0.5*sz), center=mp.Vector3(0,0,0.25*sz), material=fused_quartz) ]
sim = mp.Simulation(cell_size=cell_size,
boundary_layers=pml_layers,
geometry=geometry,
sources=sources,
dimensions=1,
resolution=resolution)
refl = sim.add_flux(fcen, df, nfreq, refl_fr)
sim.load_minus_flux_data(refl, empty_data)
sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ex, mp.Vector3(), 1e-9))
refl_flux = mp.get_fluxes(refl)
freqs = mp.get_flux_freqs(refl)
for i in range(nfreq):
print("refl:, {}, {}".format(1/freqs[i],-refl_flux[i]/empty_flux[i]))
def refl_angular(self, theta):
theta_r = math.radians(theta)
# wavevector (in source medium); plane of incidence is XZ
k = mp.Vector3(0, 0, 1).rotate(mp.Vector3(0, 1, 0),
theta_r).scale(self.n1 * self.fmin)
if theta == 0:
dimensions = 1
else:
dimensions = 3
cell_size = mp.Vector3(z=self.sz)
pml_layers = [mp.PML(self.dpml)]
sources = [
mp.Source(
mp.GaussianSource(self.fcen, fwidth=self.df),
component=mp.Ex, # P polarization
center=mp.Vector3(z=-0.5 * self.sz + self.dpml))
]
sim = mp.Simulation(resolution=self.resolution,
cell_size=cell_size,
dimensions=dimensions,
default_material=mp.Medium(index=self.n1),
sources=sources,
boundary_layers=pml_layers,
k_point=k)
mon_pt = -0.5 * self.sz + self.dpml + 0.25 * self.dz
refl_fr = mp.FluxRegion(center=mp.Vector3(z=mon_pt))
refl = sim.add_flux(self.fcen, self.df, self.nfreq, refl_fr)
termination_cond = mp.stop_when_fields_decayed(50, mp.Ex,
mp.Vector3(z=mon_pt),
1e-9)
sim.run(until_after_sources=termination_cond)
empty_data = sim.get_flux_data(refl)
empty_flux = mp.get_fluxes(refl)
sim.reset_meep()
geometry = [
mp.Block(size=mp.Vector3(mp.inf, mp.inf, 0.5 * self.sz),
center=mp.Vector3(z=0.25 * self.sz),
material=mp.Medium(index=self.n2))
]
sim = mp.Simulation(resolution=self.resolution,
cell_size=cell_size,
dimensions=dimensions,
default_material=mp.Medium(index=self.n1),
sources=sources,
boundary_layers=pml_layers,
k_point=k,
geometry=geometry)
refl = sim.add_flux(self.fcen, self.df, self.nfreq, refl_fr)
sim.load_minus_flux_data(refl, empty_data)
sim.run(until_after_sources=termination_cond)
refl_flux = mp.get_fluxes(refl)
freqs = mp.get_flux_freqs(refl)
Rs = -np.array(refl_flux) / np.array(empty_flux)
thetas = []
for i in range(self.nfreq):
thetas.append(math.asin(k.x / (self.n1 * freqs[i])))
return freqs, thetas, Rs
default_material=CdSe,
boundary_layers=pml_layers,
eps_averaging=False,
geometry=[],
ensure_periodicity=True,
sources=sources,
dimensions=3,
resolution=resolution)
before_block = sim.add_flux(1 / 0.550, 0.5, 5, secfr)
sim.run(until=60)
before_block_flux = mp.get_fluxes(before_block)
before_block_flux_data = sim.get_flux_data(before_block)
flux_freqs = mp.get_flux_freqs(before_block)
sim.reset_meep()
geometry = [
mp.Block(mp.Vector3(1, cell.y, cell.z),
center=mp.Vector3(-2),
material=mp.Medium(index=1.6))
]
# cadmium selineid QD
geometry.append(
mp.Block(mp.Vector3(1, cell.z, cell.z),
center=mp.Vector3(-1),
material=mp.Medium(index=2.52)))
numberof = int(cell.y // (2 * fingersize)) + 1
size=mp.Vector3(0,2*w,0)) #location of the flux region.
refl = sim.add_flux(fcen, df, nfreq, refl_fr) #capture of the actual flux.
# transmitted flux region...tran_fr
tran_fr=mp.FluxRegion(center=mp.Vector3(0.5*sx-dpml-0.5,wvg_ycen,0),
size=mp.Vector3(0,2*w,0)) #location of the flux region.
tran=sim.add_flux(fcen,df,nfreq,tran_fr) #capture of the actual flux.
pt=mp.Vector3(0.5*sx-dpml-0.5,wvg_ycen)
sim.run(until_after_sources=mp.stop_when_fields_decayed(50,mp.Ez,pt,1e-3))
straight_refl_data=sim.get_flux_data(refl)
straight_tran_data=sim.get_flux_data(tran)
# save incident power for reflection and transmission planes (sanity check to make sure that flux is transmitted along wg without loss).
straight_tran_flux=mp.get_fluxes(tran)
straight_refl_flux=mp.get_fluxes(refl)
flux_freqs=mp.get_flux_freqs(refl)
# end of normalisation run
#plot results
wl=[] #wavelgnth (inverse of frequency).
RNs=[] #Reflectance_Normal_straight_wg.
TNs=[] #Transmittance_Normal_straight_wg.
for i in range(nfreq):
wl=np.append(wl, 1/flux_freqs[i])
RNs=np.append(RNs,straight_refl_flux[i])
TNs=np.append(TNs,straight_tran_flux[i])
plt.subplot(311)
sim.run(until=600)
# Calculate the scattering params for each waveguide
bands = [1,2,3] # just look at first, second, and third, TE modes
m1_results = sim.get_eigenmode_coefficients(m1,[1],eig_parity=(mp.ODD_Z+mp.EVEN_Y)).alpha
m2_results = sim.get_eigenmode_coefficients(m2,bands,eig_parity=(mp.ODD_Z+mp.EVEN_Y)).alpha
a1 = m1_results[:,:,0] #forward wave
b1 = m1_results[:,:,1] #backward wave
a2 = m2_results[:,:,0] #forward wave
b2 = m2_results[:,:,1] #backward wave
S12_mode1 = a2[0,:] / a1[0,:]
S12_mode2 = a2[1,:] / a1[0,:]
S12_mode3 = a2[2,:] / a1[0,:]
freqs = np.array(mp.get_flux_freqs(m1))
# visualize results
plt.figure()
plt.semilogy(1/freqs,np.abs(S12_mode1)**2,'-o',label='S12 Input Mode 1 Output Mode 1')
plt.semilogy(1/freqs,np.abs(S12_mode2)**2,'-o',label='S12 Input Mode 1 Output Mode 2')
plt.semilogy(1/freqs,np.abs(S12_mode3)**2,'-o',label='S12 Input Mode 1 Output Mode 3')
plt.ylabel('Power')
plt.xlabel('Wavelength (microns)')
plt.legend()
plt.grid(True)
plt.savefig('Results.png')
plt.show()
refl_after = sim.add_flux(fcen, df, nfreq, refl_fr2)
# transmitted flux
tran_fr = mp.FluxRegion(center=mp.Vector3(sx/2-dpml-2.5,sy/2-5, 0), size=mp.Vector3(0,2*4,0))
tran = sim.add_flux(fcen, df, nfreq, tran_fr)
tran_fr2 = mp.FluxRegion(center=mp.Vector3(-(sx/2-dpml-2.5),sy/2-5, 0), size=mp.Vector3(0,2*4,0))
tran2= sim.add_flux(fcen, df, nfreq, tran_fr)
pt = mp.Vector3(sx/2-dpml-0.5,sy/2-5,0)
sim.use_output_directory()
sim.run(until_after_sources=mp.stop_when_fields_decayed(10,mp.Ez,pt,1e-3))
#mp.at_beginning(mp.output_epsilon), mp.at_every(0.1, mp.output_png(mp.Ez, "-Zc dkbluered")),
fluxfreqs=mp.get_flux_freqs(refl_before)
reflectedflux_after=mp.get_fluxes(refl_after)
reflectedflux_before=mp.get_fluxes(refl_before)
infrontofsrcflux=mp.get_fluxes(infrontofsrc)
tran_flux = mp.get_fluxes(tran)
tran2_flux = mp.get_fluxes(tran2)
refl, tran=[],[]
freq, refl_after_fl, refl_before_fl, tran2 = [],[],[],[]
infrontofsrc=[]
for i in range(nfreq):
freq=np.append(freq, fluxfreqs[i])
infrontofsrc=np.append(infrontofsrc, infrontofsrcflux[i])
refl_after=np.append(refl_after_fl, reflectedflux_after[i])
refl_before=np.append(refl_before_fl, reflectedflux_before[i])
tran=np.append(tran, tran_flux[i])
def test_refl_angular(self):
resolution = 100
dpml = 1.0
sz = 10
sz = sz + 2 * dpml
cell_size = mp.Vector3(z=sz)
pml_layers = [mp.PML(dpml)]
wvl_min = 0.4
wvl_max = 0.8
fmin = 1 / wvl_max
fmax = 1 / wvl_min
fcen = 0.5 * (fmin + fmax)
df = fmax - fmin
nfreq = 50
theta_r = math.radians(0)
k = mp.Vector3(math.sin(theta_r), 0, math.cos(theta_r)).scale(fcen)
dimensions = 1
sources = [mp.Source(mp.GaussianSource(fcen, fwidth=df), component=mp.Ex,
center=mp.Vector3(z=-0.5 * sz + dpml))]
sim = mp.Simulation(cell_size=cell_size,
boundary_layers=pml_layers,
sources=sources,
k_point=k,
dimensions=dimensions,
resolution=resolution)
refl_fr = mp.FluxRegion(center=mp.Vector3(z=-0.25 * sz))
refl = sim.add_flux(fcen, df, nfreq, refl_fr)
sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ex, mp.Vector3(z=-0.5 * sz + dpml), 1e-9))
empty_data = sim.get_flux_data(refl)
sim.reset_meep()
geometry = [mp.Block(mp.Vector3(mp.inf, mp.inf, 0.5 * sz), center=mp.Vector3(z=0.25 * sz),
material=mp.Medium(index=3.5))]
sim = mp.Simulation(cell_size=cell_size,
geometry=geometry,
boundary_layers=pml_layers,
sources=sources,
k_point=k,
dimensions=dimensions,
resolution=resolution)
refl = sim.add_flux(fcen, df, nfreq, refl_fr)
sim.load_minus_flux_data(refl, empty_data)
sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ex, mp.Vector3(z=-0.5 * sz + dpml), 1e-9))
refl_flux = mp.get_fluxes(refl)
freqs = mp.get_flux_freqs(refl)
expected = [
(1.25, -1.123696883299492e-6),
(1.2755102040816326, -2.5749667658387866e-6),
(1.3010204081632653, -5.70480204599006e-6),
(1.3265306122448979, -1.2220464827582253e-5),
(1.3520408163265305, -2.531247480206961e-5),
(1.3775510204081631, -5.069850309492639e-5),
(1.4030612244897958, -9.819256552437341e-5),
(1.4285714285714284, -1.8390448659017395e-4),
(1.454081632653061, -3.330762066794769e-4),
(1.4795918367346936, -5.833650417163753e-4),
(1.5051020408163263, -9.8807834237052e-4),
(1.5306122448979589, -0.001618472171445976),
(1.5561224489795915, -0.0025638388059825985),
(1.5816326530612241, -0.003927863989816029),
(1.6071428571428568, -0.005819831283556752),
(1.6326530612244894, -0.008339881000982728),
(1.658163265306122, -0.011558769654206626),
(1.6836734693877546, -0.015494308354153143),
(1.7091836734693873, -0.02008850084337135),
(1.73469387755102, -0.025190871516857616),
(1.7602040816326525, -0.030553756123198477),
(1.7857142857142851, -0.03584404966066722),
(1.8112244897959178, -0.040672967700428275),
(1.8367346938775504, -0.04464118393086191),
(1.862244897959183, -0.047392712128477496),
(1.8877551020408156, -0.048667403362887635),
(1.9132653061224483, -0.048341494285878264),
(1.938775510204081, -0.04644739000778679),
(1.9642857142857135, -0.043168390293742316),
(1.9897959183673462, -0.0388094755730579),
(2.0153061224489788, -0.03375052221907117),
(2.0408163265306114, -0.02839209067703472),
(2.066326530612244, -0.023104245646230648),
(2.0918367346938767, -0.01818725699718267),
(2.1173469387755093, -0.013849270759480073),
(2.142857142857142, -0.010201733597436358),
(2.1683673469387745, -0.007269616609175294),
(2.193877551020407, -0.005011210495189995),
(2.21938775510204, -0.0033417192031464896),
(2.2448979591836724, -0.0021557351734376256),
(2.270408163265305, -0.0013453062176115673),
(2.2959183673469377, -8.121742663131631e-4),
(2.3214285714285703, -4.7433135191915683e-4),
(2.346938775510203, -2.6799188013374266e-4),
(2.3724489795918355, -1.464781343401766e-4),
(2.397959183673468, -7.745339273024636e-5),
(2.423469387755101, -3.9621374769542025e-5),
(2.4489795918367334, -1.9608458558430508e-5),
(2.474489795918366, -9.38818477949983e-6),
(2.4999999999999987, -4.3484671364929225e-6),
]
np.testing.assert_allclose(expected, list(zip(freqs, refl_flux)), rtol=1e-6)
def run_mode_coeffs(self, mode_num, kpoint_func, nf=1, resolution=15):
w = 1 # width of waveguide
L = 10 # length of waveguide
Si = mp.Medium(epsilon=12.0)
dair = 3.0
dpml = 3.0
sx = dpml + L + dpml
sy = dpml + dair + w + dair + dpml
cell_size = mp.Vector3(sx, sy, 0)
prism_x = sx + 1
prism_y = w / 2
vertices = [mp.Vector3(-prism_x, prism_y),
mp.Vector3(prism_x, prism_y),
mp.Vector3(prism_x, -prism_y),
mp.Vector3(-prism_x, -prism_y)]
geometry = [mp.Prism(vertices, height=mp.inf, material=Si)]
boundary_layers = [mp.PML(dpml)]
# mode frequency
fcen = 0.20 # > 0.5/sqrt(11) to have at least 2 modes
df = 0.5*fcen
source=mp.EigenModeSource(src=mp.GaussianSource(fcen, fwidth=df),
eig_band=mode_num,
size=mp.Vector3(0,sy-2*dpml,0),
center=mp.Vector3(-0.5*sx+dpml,0,0),
eig_match_freq=True,
eig_resolution=2*resolution)
sim = mp.Simulation(resolution=resolution,
cell_size=cell_size,
boundary_layers=boundary_layers,
geometry=geometry,
sources=[source],
symmetries=[mp.Mirror(mp.Y, phase=1 if mode_num % 2 == 1 else -1)])
xm = 0.5*sx - dpml # x-coordinate of monitor
mflux = sim.add_mode_monitor(fcen, df, nf, mp.ModeRegion(center=mp.Vector3(xm,0), size=mp.Vector3(0,sy-2*dpml)))
mode_flux = sim.add_flux(fcen, df, nf, mp.FluxRegion(center=mp.Vector3(xm,0), size=mp.Vector3(0,sy-2*dpml)))
# sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ez, mp.Vector3(-0.5*sx+dpml,0), 1e-10))
sim.run(until_after_sources=200)
##################################################
# If the number of analysis frequencies is >1, we
# are testing the unit-power normalization
# of the eigenmode source: we observe the total
# power flux through the mode_flux monitor (which
# equals the total power emitted by the source as
# there is no scattering in this ideal waveguide)
# and check that it agrees with the prediction
# of the eig_power() class method in EigenmodeSource.
##################################################
if nf>1:
power_observed=mp.get_fluxes(mode_flux)
freqs=mp.get_flux_freqs(mode_flux)
power_expected=[source.eig_power(f) for f in freqs]
return freqs, power_expected, power_observed
modes_to_check = [1, 2] # indices of modes for which to compute expansion coefficients
res = sim.get_eigenmode_coefficients(mflux, modes_to_check, kpoint_func=kpoint_func)
self.assertTrue(res.kpoints[0].close(mp.Vector3(0.604301, 0, 0)))
self.assertTrue(res.kpoints[1].close(mp.Vector3(0.494353, 0, 0), tol=1e-2))
self.assertTrue(res.kdom[0].close(mp.Vector3(0.604301, 0, 0)))
self.assertTrue(res.kdom[1].close(mp.Vector3(0.494353, 0, 0), tol=1e-2))
mode_power = mp.get_fluxes(mode_flux)[0]
TestPassed = True
TOLERANCE = 5.0e-3
c0 = res.alpha[mode_num - 1, 0, 0] # coefficient of forward-traveling wave for mode #mode_num
for nm in range(1, len(modes_to_check)+1):
if nm != mode_num:
cfrel = np.abs(res.alpha[nm - 1, 0, 0]) / np.abs(c0)
cbrel = np.abs(res.alpha[nm - 1, 0, 1]) / np.abs(c0)
if cfrel > TOLERANCE or cbrel > TOLERANCE:
TestPassed = False
self.sim = sim
# test 1: coefficient of excited mode >> coeffs of all other modes
self.assertTrue(TestPassed, msg="cfrel: {}, cbrel: {}".format(cfrel, cbrel))
# test 2: |mode coeff|^2 = power
self.assertAlmostEqual(mode_power / abs(c0**2), 1.0, places=1)
return res
def test_transmission_spectrum(self):
expected = [
(0.15, 7.218492264696595e-6),
(0.1504008016032064, 6.445696315927592e-6),
(0.1508016032064128, 5.140949243632777e-6),
(0.15120240480961922, 3.6159747936427164e-6),
(0.15160320641282563, 2.263940553705969e-6),
(0.15200400801603203, 1.4757165844336744e-6),
(0.15240480961923844, 1.5491803919142815e-6),
(0.15280561122244485, 2.612053246626972e-6),
(0.15320641282565126, 4.577504371188737e-6),
(0.15360721442885766, 7.1459089162998185e-6),
(0.15400801603206407, 9.856622013418823e-6),
(0.15440881763527048, 1.2182309227954296e-5),
(0.1548096192384769, 1.3647726444709649e-5),
(0.1552104208416833, 1.3947420613633674e-5),
(0.1556112224448897, 1.303466755716231e-5),
(0.1560120240480961, 1.115807915037775e-5),
(0.15641282565130252, 8.832335196969796e-6),
(0.15681362725450892, 6.743645773127985e-6),
(0.15721442885771533, 5.605913756087576e-6),
(0.15761523046092174, 5.996668564026961e-6),
(0.15801603206412815, 8.209400611614078e-6),
(0.15841683366733456, 1.2158641936828497e-5),
(0.15881763527054096, 1.73653230513453e-5),
(0.15921843687374737, 2.303382576477893e-5),
(0.15961923847695378, 2.821180350795834e-5),
(0.1600200400801602, 3.200359292911769e-5),
(0.1604208416833666, 3.3792624373001934e-5),
(0.160821643286573, 3.342171394788991e-5),
(0.1612224448897794, 3.1284866146526904e-5),
(0.16162324649298582, 2.830022088581398e-5),
(0.16202404809619222, 2.5758413657344014e-5),
(0.16242484969939863, 2.506899997971769e-5),
(0.16282565130260504, 2.7453508915303887e-5),
(0.16322645290581145, 3.365089813497114e-5),
(0.16362725450901786, 4.370486834112e-5),
(0.16402805611222426, 5.689050715055283e-5),
(0.16442885771543067, 7.181133157470506e-5),
(0.16482965931863708, 8.666168027415369e-5),
(0.16523046092184349, 9.961094123261317e-5),
(0.1656312625250499, 1.0923388232657953e-4),
(0.1660320641282563, 1.1489334204708105e-4),
(0.1664328657314627, 1.1698318060032011e-4),
(0.16683366733466912, 1.169621456132733e-4),
(0.16723446893787552, 1.1714995241571987e-4),
(0.16763527054108193, 1.2030783847222252e-4),
(0.16803607214428834, 1.2907652919660887e-4),
]
self.sim.sources = [
mp.Source(mp.GaussianSource(self.fcen, fwidth=self.df), mp.Ey,
mp.Vector3(self.dpml + (-0.5 * self.sx)), size=mp.Vector3(0, self.w))
]
self.sim.symmetries = [mp.Mirror(mp.Y, phase=-1)]
freg = mp.FluxRegion(center=mp.Vector3((0.5 * self.sx) - self.dpml - 0.5),
size=mp.Vector3(0, 2 * self.w))
trans = self.sim.add_flux(self.fcen, self.df, self.nfreq, freg)
self.sim.run(
until_after_sources=mp.stop_when_fields_decayed(
50, mp.Ey, mp.Vector3((0.5 * self.sx) - self.dpml - 0.5, 0), 1e-1)
)
res = zip(mp.get_flux_freqs(trans), mp.get_fluxes(trans))
for e, r in zip(expected, res):
np.testing.assert_allclose(e, r)
def simulation_fun():
resolution = 200
geom = common.geom
sig = common.sig
# source parameters
fcen = common.fcen
df = common.df
df2 = df * 1.4 # source frequency width
nfreq = 101 # number of frequency bins
pol = common.pol # polarization
src_cmpt = eval('mp.{}'.format(pol))
theta = common.theta # incident angle
theta_r = math.radians(theta)
# material
n_GaSb = 3.8
mat_src = mp.Medium(index=n_GaSb)
if geom == "Pda":
mat_metal = mym.lossy_Pd(common.r)
elif geom in ("Pd", "Empty"):
mat_metal = mat.Pd
else:
sys.exit("Wrong materials")
# geometry
# from bottom to top
sx = 0.1
sxx = 0.1 # periodic along x direction
d_back = 0.3
d_metal = 0.7
d_src = 1
dpml = 2
sy = d_back + d_metal + d_src
syy = sy + 2 * dpml
cell_size = mp.Vector3(sxx, syy, 0)
boundary_layers = [mp.PML(thickness=dpml, direction=mp.Y)]
if geom == "Empty":
geometry = [
mp.Block(size=mp.Vector3(sxx, syy, mp.inf),
center=mp.Vector3(0, 0, 0),
material=mat_src)
]
else:
tts = [d_back, d_metal]
ccs = my.center_from_thickness(tts, -sy / 2)
geometry = [
mp.Block(size=mp.Vector3(sxx, syy, mp.inf),
center=mp.Vector3(0, 0, 0),
material=mat_src),
mp.Block(size=mp.Vector3(sxx, tts[1], mp.inf),
center=mp.Vector3(0, ccs[1], 0),
material=mat_metal),
]
# bloch k vector
k = mp.Vector3(math.sin(theta_r), math.cos(theta_r), 0).scale(
fcen * mym.get_refractive_index(fcen, mat_src).real)
amp_func = lambda x: cmath.exp(1j * 2 * math.pi * k.dot(x))
# oblique source
y0 = -sy / 2 + d_back + d_metal # metal/GaSb interface
sources = [
mp.Source(mp.GaussianSource(fcen, fwidth=df2),
component=src_cmpt,
center=mp.Vector3(0, y0 + d_src * 0.8),
size=mp.Vector3(sxx, 0),
amp_func=amp_func)
]
# setup simulations
sim = mp.Simulation(cell_size=cell_size,
geometry=geometry,
boundary_layers=boundary_layers,
sources=sources,
k_point=k,
force_complex_fields=True,
filename_prefix=sig,
resolution=resolution)
# flux
y_frs = [
y0 + d_src * 0.4,
]
frs = [
mp.FluxRegion(center=mp.Vector3(0, y, 0),
size=mp.Vector3(sxx, 0, 0),
weight=-1) for y in y_frs
]
trans = [sim.add_flux(fcen, df, nfreq, fr) for fr in frs]
####
# define step function to display fluxes
my_display_count = 0
step_time_flush = 10
step_time_print = 200
step_time_terminate = 50
def my_display_fluxes(sim):
nonlocal my_display_count
print('=' * 40)
print('=' * 40)
freqs = mp.get_flux_freqs(trans[0])
fluxes = [mp.get_fluxes(tran) for tran in trans]
data = np.column_stack((
freqs,
*fluxes,
))
my.matrix_output(None, data, "{:10.3e}", "flux")
my_display_count += 1
print('=' * 40)
print('No. {} display at t={}'.format(my_display_count,
step_time_print))
my.my_flush_step(sim)
# run simulations
pt_field = mp.Vector3(0.1 * sxx, y0 + d_src * 0.4, 0) # monitor point
sim.run( # mp.at_beginning(mp.output_epsilon),
mp.at_every(step_time_flush, my.my_flush_step),
mp.at_every(step_time_print, my_display_fluxes),
until_after_sources=mp.stop_when_fields_decayed(
step_time_terminate, src_cmpt, pt_field, 1e-9))
sys.stdout.flush()
# collect data
freqs = mp.get_flux_freqs(trans[0])
fluxes = [mp.get_fluxes(tran) for tran in trans]
data = np.column_stack((
freqs,
*fluxes,
))
# output
fname = sig + ".dat"
my.matrix_output(fname, data, "{:10.3e}", "flux")
def test_transmission_spectrum(self):
expected = [
(0.15, 7.218492264696595e-6),
(0.1504008016032064, 6.445696315927592e-6),
(0.1508016032064128, 5.140949243632777e-6),
(0.15120240480961922, 3.6159747936427164e-6),
(0.15160320641282563, 2.263940553705969e-6),
(0.15200400801603203, 1.4757165844336744e-6),
(0.15240480961923844, 1.5491803919142815e-6),
(0.15280561122244485, 2.612053246626972e-6),
(0.15320641282565126, 4.577504371188737e-6),
(0.15360721442885766, 7.1459089162998185e-6),
(0.15400801603206407, 9.856622013418823e-6),
(0.15440881763527048, 1.2182309227954296e-5),
(0.1548096192384769, 1.3647726444709649e-5),
(0.1552104208416833, 1.3947420613633674e-5),
(0.1556112224448897, 1.303466755716231e-5),
(0.1560120240480961, 1.115807915037775e-5),
(0.15641282565130252, 8.832335196969796e-6),
(0.15681362725450892, 6.743645773127985e-6),
(0.15721442885771533, 5.605913756087576e-6),
(0.15761523046092174, 5.996668564026961e-6),
(0.15801603206412815, 8.209400611614078e-6),
(0.15841683366733456, 1.2158641936828497e-5),
(0.15881763527054096, 1.73653230513453e-5),
(0.15921843687374737, 2.303382576477893e-5),
(0.15961923847695378, 2.821180350795834e-5),
(0.1600200400801602, 3.200359292911769e-5),
(0.1604208416833666, 3.3792624373001934e-5),
(0.160821643286573, 3.342171394788991e-5),
(0.1612224448897794, 3.1284866146526904e-5),
(0.16162324649298582, 2.830022088581398e-5),
(0.16202404809619222, 2.5758413657344014e-5),
(0.16242484969939863, 2.506899997971769e-5),
(0.16282565130260504, 2.7453508915303887e-5),
(0.16322645290581145, 3.365089813497114e-5),
(0.16362725450901786, 4.370486834112e-5),
(0.16402805611222426, 5.689050715055283e-5),
(0.16442885771543067, 7.181133157470506e-5),
(0.16482965931863708, 8.666168027415369e-5),
(0.16523046092184349, 9.961094123261317e-5),
(0.1656312625250499, 1.0923388232657953e-4),
(0.1660320641282563, 1.1489334204708105e-4),
(0.1664328657314627, 1.1698318060032011e-4),
(0.16683366733466912, 1.169621456132733e-4),
(0.16723446893787552, 1.1714995241571987e-4),
(0.16763527054108193, 1.2030783847222252e-4),
(0.16803607214428834, 1.2907652919660887e-4),
]
self.sim.sources = [
mp.Source(mp.GaussianSource(self.fcen, fwidth=self.df),
mp.Ey,
mp.Vector3(self.dpml + (-0.5 * self.sx)),
size=mp.Vector3(0, self.w))
]
self.sim.symmetries = [mp.Mirror(mp.Y, phase=-1)]
freg = mp.FluxRegion(center=mp.Vector3((0.5 * self.sx) - self.dpml -
0.5),
size=mp.Vector3(0, 2 * self.w))
trans = self.sim.add_flux(self.fcen, self.df, self.nfreq, freg)
self.sim.run(until_after_sources=mp.stop_when_fields_decayed(
50, mp.Ey, mp.Vector3((0.5 * self.sx) - self.dpml - 0.5, 0), 1e-1))
res = zip(mp.get_flux_freqs(trans), mp.get_fluxes(trans))
for e, r in zip(expected, res):
np.testing.assert_allclose(e, r)
def run_bend_flux(self, from_gdsii_file):
# Normalization run
self.init(no_bend=True, gdsii=from_gdsii_file)
self.sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ez, self.pt, 1e-3))
# Save flux data for use in real run below
fdata = self.sim.get_flux_data(self.refl)
expected = [
(0.1, 3.65231563251e-05, 3.68932495077e-05),
(0.10101010101, 5.55606718876e-05, 5.6065539588e-05),
(0.10202020202, 8.38211697478e-05, 8.44909864736e-05),
(0.10303030303, 0.000125411162229, 0.000126268639045),
(0.10404040404, 0.000186089117531, 0.000187135303398),
(0.105050505051, 0.000273848867869, 0.000275039134667),
(0.106060606061, 0.000399674037745, 0.000400880269423),
(0.107070707071, 0.00057849953593, 0.000579454087881),
(0.108080808081, 0.000830418432986, 0.000830635406881),
(0.109090909091, 0.00118217282661, 0.00118084271347),
(0.110101010101, 0.00166896468348, 0.00166481944189),
(0.111111111111, 0.00233661613864, 0.00232776318321),
(0.112121212121, 0.00324409729096, 0.00322782257917),
(0.113131313131, 0.00446642217385, 0.00443896468822),
(0.114141414141, 0.0060978895019, 0.0060541922825),
(0.115151515152, 0.00825561352398, 0.00818906047274),
(0.116161616162, 0.0110832518495, 0.010985404883),
(0.117171717172, 0.0147547920552, 0.0146151488236),
(0.118181818182, 0.0194782085272, 0.0192840042241),
(0.119191919192, 0.0254987474079, 0.0252348211592),
]
res = list(zip(mp.get_flux_freqs(self.trans), mp.get_fluxes(self.trans), mp.get_fluxes(self.refl)))
tolerance = 1e-2 if from_gdsii_file else 1e-3
compare_arrays(self, np.array(expected), np.array(res[:20]), tol=tolerance)
# Real run
self.sim = None
self.init(gdsii=from_gdsii_file)
# Load flux data obtained from normalization run
self.sim.load_minus_flux_data(self.refl, fdata)
self.sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ez, self.pt, 1e-3))
expected = [
(0.09999999999999999, 1.8392235204829767e-5, -7.259467687598002e-6),
(0.10101010101010101, 2.7629932558236724e-5, -1.1107162110079347e-5),
(0.10202020202020202, 4.1001228946782745e-5, -1.687561915798036e-5),
(0.10303030303030304, 6.018966076122556e-5, -2.5425779493709066e-5),
(0.10404040404040406, 8.758554071933231e-5, -3.794958119189475e-5),
(0.10505050505050507, 1.2656696778129198e-4, -5.612512808928115e-5),
(0.10606060606060609, 1.817948859871414e-4, -8.232188174309142e-5),
(0.10707070707070711, 2.594514094902856e-4, -1.1981531280672989e-4),
(0.10808080808080812, 3.6736164837695035e-4, -1.7300125173897737e-4),
(0.10909090909090914, 5.150131339048232e-4, -2.476730940385436e-4),
(0.11010101010101016, 7.136181099374187e-4, -3.5145561406042276e-4),
(0.11111111111111117, 9.76491765781944e-4, -4.944142331545938e-4),
(0.11212121212121219, 0.001320033637882244, -6.897357105189368e-4),
(0.11313131313131321, 0.0017653940714397098, -9.543556354451615e-4),
(0.11414141414141422, 0.0023404727796352857, -0.0013095604571818236),
(0.11515151515151524, 0.0030813962415392098, -0.00178176942635486),
(0.11616161616161626, 0.00403238648982478, -0.0024036650652026112),
(0.11717171717171727, 0.005243320443599316, -0.003215529845495731),
(0.11818181818181829, 0.0067654019326068, -0.004266367104375331),
(0.11919191919191931, 0.008646855439680507, -0.005614491919262783),
]
res = list(zip(mp.get_flux_freqs(self.trans), mp.get_fluxes(self.trans), mp.get_fluxes(self.refl)))
tolerance = 1e-2 if from_gdsii_file else 1e-3
compare_arrays(self, np.array(expected), np.array(res[:20]), tol=tolerance)
def run_bend_flux(self, from_gdsii_file):
# Normalization run
self.init(no_bend=True, gdsii=from_gdsii_file)
self.sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ez, self.pt, 1e-3))
# Save flux data for use in real run below
fdata = self.sim.get_flux_data(self.refl)
expected = [
(0.1, 3.65231563251e-05, 3.68932495077e-05),
(0.10101010101, 5.55606718876e-05, 5.6065539588e-05),
(0.10202020202, 8.38211697478e-05, 8.44909864736e-05),
(0.10303030303, 0.000125411162229, 0.000126268639045),
(0.10404040404, 0.000186089117531, 0.000187135303398),
(0.105050505051, 0.000273848867869, 0.000275039134667),
(0.106060606061, 0.000399674037745, 0.000400880269423),
(0.107070707071, 0.00057849953593, 0.000579454087881),
(0.108080808081, 0.000830418432986, 0.000830635406881),
(0.109090909091, 0.00118217282661, 0.00118084271347),
(0.110101010101, 0.00166896468348, 0.00166481944189),
(0.111111111111, 0.00233661613864, 0.00232776318321),
(0.112121212121, 0.00324409729096, 0.00322782257917),
(0.113131313131, 0.00446642217385, 0.00443896468822),
(0.114141414141, 0.0060978895019, 0.0060541922825),
(0.115151515152, 0.00825561352398, 0.00818906047274),
(0.116161616162, 0.0110832518495, 0.010985404883),
(0.117171717172, 0.0147547920552, 0.0146151488236),
(0.118181818182, 0.0194782085272, 0.0192840042241),
(0.119191919192, 0.0254987474079, 0.0252348211592),
]
res = list(zip(mp.get_flux_freqs(self.trans), mp.get_fluxes(self.trans), mp.get_fluxes(self.refl)))
tolerance = 1e-2 if from_gdsii_file else 1e-3
compare_arrays(self, np.array(expected), np.array(res[:20]), tol=tolerance)
# Real run
self.sim = None
self.init(gdsii=from_gdsii_file)
# Load flux data obtained from normalization run
self.sim.load_minus_flux_data(self.refl, fdata)
self.sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ez, self.pt, 1e-3))
expected = [
(0.09999999999999999, 1.8392235204829767e-5, -7.259467687598002e-6),
(0.10101010101010101, 2.7629932558236724e-5, -1.1107162110079347e-5),
(0.10202020202020202, 4.1001228946782745e-5, -1.687561915798036e-5),
(0.10303030303030304, 6.018966076122556e-5, -2.5425779493709066e-5),
(0.10404040404040406, 8.758554071933231e-5, -3.794958119189475e-5),
(0.10505050505050507, 1.2656696778129198e-4, -5.612512808928115e-5),
(0.10606060606060609, 1.817948859871414e-4, -8.232188174309142e-5),
(0.10707070707070711, 2.594514094902856e-4, -1.1981531280672989e-4),
(0.10808080808080812, 3.6736164837695035e-4, -1.7300125173897737e-4),
(0.10909090909090914, 5.150131339048232e-4, -2.476730940385436e-4),
(0.11010101010101016, 7.136181099374187e-4, -3.5145561406042276e-4),
(0.11111111111111117, 9.76491765781944e-4, -4.944142331545938e-4),
(0.11212121212121219, 0.001320033637882244, -6.897357105189368e-4),
(0.11313131313131321, 0.0017653940714397098, -9.543556354451615e-4),
(0.11414141414141422, 0.0023404727796352857, -0.0013095604571818236),
(0.11515151515151524, 0.0030813962415392098, -0.00178176942635486),
(0.11616161616161626, 0.00403238648982478, -0.0024036650652026112),
(0.11717171717171727, 0.005243320443599316, -0.003215529845495731),
(0.11818181818181829, 0.0067654019326068, -0.004266367104375331),
(0.11919191919191931, 0.008646855439680507, -0.005614491919262783),
]
res = list(zip(mp.get_flux_freqs(self.trans), mp.get_fluxes(self.trans), mp.get_fluxes(self.refl)))
tolerance = 1e-2 if from_gdsii_file else 1e-3
compare_arrays(self, np.array(expected), np.array(res[:20]), tol=tolerance)