def test_resonant_modes(self):
self.sim.sources = [mp.Source(mp.GaussianSource(self.fcen, fwidth=self.df),
mp.Hz, mp.Vector3())]
self.sim.symmetries = [mp.Mirror(mp.Y, phase=-1),
mp.Mirror(mp.X, phase=-1)]
h = mp.Harminv(mp.Hz, mp.Vector3(), self.fcen, self.df)
self.sim.run(mp.at_beginning(mp.output_epsilon),
mp.after_sources(h),
until_after_sources=400)
expected = [
0.23445415346009466,
-3.147812367338531e-4,
372.40808234438254,
5.8121430334347135,
-3.763107485715599,
-4.429450156854109,
]
m = h.modes[0]
res = [m.freq, m.decay, m.Q, abs(m.amp), m.amp.real, m.amp.imag]
np.testing.assert_allclose(expected, res)
def test_resonant_modes(self):
self.sim.sources = [
mp.Source(mp.GaussianSource(self.fcen, fwidth=self.df), mp.Hz,
mp.Vector3())
]
self.sim.symmetries = [
mp.Mirror(mp.Y, phase=-1),
mp.Mirror(mp.X, phase=-1)
]
h = mp.Harminv(mp.Hz, mp.Vector3(), self.fcen, self.df)
self.sim.run(mp.at_beginning(mp.output_epsilon),
mp.after_sources(h),
until_after_sources=400)
expected = [
0.23445415346009466,
-3.147812367338531e-4,
372.40808234438254,
5.8121430334347135,
-3.763107485715599,
-4.429450156854109,
]
m = h.modes[0]
res = [m.freq, m.decay, m.Q, abs(m.amp), m.amp.real, m.amp.imag]
np.testing.assert_allclose(expected, res)
def main():
c = mp.Cylinder(radius=3, material=mp.Medium(index=3.5))
e = mp.Ellipsoid(size=mp.Vector3(1, 2, 1e20))
src_cmpt = mp.Hz
sources = mp.Source(src=mp.GaussianSource(1, fwidth=0.1),
component=src_cmpt,
center=mp.Vector3())
if src_cmpt == mp.Ez:
symmetries = [mp.Mirror(mp.X), mp.Mirror(mp.Y)]
if src_cmpt == mp.Hz:
symmetries = [mp.Mirror(mp.X, -1), mp.Mirror(mp.Y, -1)]
sim = mp.Simulation(cell_size=mp.Vector3(10, 10),
geometry=[c, e],
boundary_layers=[mp.PML(1.0)],
sources=[sources],
symmetries=symmetries,
resolution=100)
def print_stuff(sim_obj):
v = mp.Vector3(4.13, 3.75, 0)
p = sim.get_field_point(src_cmpt, v)
print("t, Ez: {} {}+{}i".format(sim.round_time(), p.real, p.imag))
sim.run(mp.at_beginning(mp.output_epsilon),
mp.at_every(0.25, print_stuff),
mp.at_end(print_stuff),
mp.at_end(mp.output_efield_z),
until=23)
print("stopped at meep time = {}".format(sim.round_time()))
def main():
c = mp.Cylinder(radius=3, material=mp.Medium(index=3.5))
e = mp.Ellipsoid(size=mp.Vector3(1, 2, mp.inf))
src_cmpt = mp.Hz
sources = mp.Source(src=mp.GaussianSource(1, fwidth=0.1), component=src_cmpt, center=mp.Vector3())
if src_cmpt == mp.Ez:
symmetries = [mp.Mirror(mp.X), mp.Mirror(mp.Y)]
if src_cmpt == mp.Hz:
symmetries = [mp.Mirror(mp.X, -1), mp.Mirror(mp.Y, -1)]
sim = mp.Simulation(cell_size=mp.Vector3(10, 10),
geometry=[c, e],
boundary_layers=[mp.PML(1.0)],
sources=[sources],
symmetries=symmetries,
resolution=100)
def print_stuff(sim_obj):
v = mp.Vector3(4.13, 3.75, 0)
p = sim.get_field_point(src_cmpt, v)
print("t, Ez: {} {}+{}i".format(sim.round_time(), p.real, p.imag))
sim.run(mp.at_beginning(mp.output_epsilon),
mp.at_every(0.25, print_stuff),
mp.at_end(print_stuff),
mp.at_end(mp.output_efield_z),
until=23)
print("stopped at meep time = {}".format(sim.round_time()))
def main(args):
n = 3.4 # index of waveguide
w = 1 # width of waveguide
r = 1 # inner radius of ring
pad = 4 # padding between waveguide and edge of PML
dpml = 32 # thickness of PML
sr = r + w + pad + dpml # radial size (cell is from 0 to sr)
dimensions = mp.CYLINDRICAL
cell = mp.Vector3(sr, 0, 0)
# in cylindrical coordinates, the phi (angular) dependence of the fields
# is given by exp(i m phi), where m is given by:
m = args.m
geometry = [
mp.Block(center=mp.Vector3(r + (w / 2)),
size=mp.Vector3(w, 1e20, 1e20),
material=mp.Medium(index=n))
]
pml_layers = [mp.PML(dpml)]
resolution = 20
# If we don't want to excite a specific mode symmetry, we can just
# put a single point source at some arbitrary place, pointing in some
# arbitrary direction. We will only look for TM modes (E out of the plane).
fcen = args.fcen # pulse center frequency
df = args.df # pulse frequency width
sources = [
mp.Source(src=mp.GaussianSource(fcen, fwidth=df),
component=mp.Ez,
center=mp.Vector3(r + 0.1))
]
# note that the r -> -r mirror symmetry is exploited automatically
sim = mp.Simulation(cell_size=cell,
geometry=geometry,
boundary_layers=pml_layers,
resolution=resolution,
sources=sources,
dimensions=dimensions,
m=m)
sim.run(mp.after_sources(mp.Harminv(mp.Ez, mp.Vector3(r + 0.1), fcen, df)),
until_after_sources=200)
# Output fields for one period at the end. (If we output
# at a single time, we might accidentally catch the Ez field when it is
# almost zero and get a distorted view.) We'll append the fields
# to a file to get an r-by-t picture. We'll also output from -sr to -sr
# instead of from 0 to sr.
sim.run(mp.in_volume(
mp.Volume(center=mp.Vector3(), size=mp.Vector3(2 * sr)),
mp.at_beginning(mp.output_epsilon),
mp.to_appended("ez", mp.at_every(1 / fcen / 20, mp.output_efield_z))),
until=1 / fcen)
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_step_funcs(self):
sf = {self._get_meep_output_comp(f) for f in self.static_fields}
sf = (mp.at_beginning(f) for f in sf)
df = {self._get_meep_output_comp(f) for f in self.dynamic_fields}
df = (mp.at_every(self.dt, f) for f in df)
volume = mp.in_volume(mp.Volume(center=self.size / 2, size=self.size))
fields = mp.with_prefix(f'{results_dir}/', *sf, *df)
return volume, fields
def main(args):
n = 3.4 # index of waveguide
w = 1 # width of waveguide
r = 1 # inner radius of ring
pad = 4 # padding between waveguide and edge of PML
dpml = 32 # thickness of PML
sr = r + w + pad + dpml # radial size (cell is from 0 to sr)
dimensions = mp.CYLINDRICAL
cell = mp.Vector3(sr, 0, 0)
# in cylindrical coordinates, the phi (angular) dependence of the fields
# is given by exp(i m phi), where m is given by:
m = args.m
geometry = [mp.Block(center=mp.Vector3(r + (w / 2)),
size=mp.Vector3(w, mp.inf, mp.inf),
material=mp.Medium(index=n))]
pml_layers = [mp.PML(dpml)]
resolution = 20
# If we don't want to excite a specific mode symmetry, we can just
# put a single point source at some arbitrary place, pointing in some
# arbitrary direction. We will only look for Ez-polarized modes.
fcen = args.fcen # pulse center frequency
df = args.df # pulse frequency width
sources = [mp.Source(src=mp.GaussianSource(fcen, fwidth=df),
component=mp.Ez,
center=mp.Vector3(r + 0.1))]
# note that the r -> -r mirror symmetry is exploited automatically
sim = mp.Simulation(cell_size=cell,
geometry=geometry,
boundary_layers=pml_layers,
resolution=resolution,
sources=sources,
dimensions=dimensions,
m=m)
sim.run(mp.after_sources(mp.Harminv(mp.Ez, mp.Vector3(r + 0.1), fcen, df)),
until_after_sources=200)
# Output fields for one period at the end. (If we output
# at a single time, we might accidentally catch the Ez field when it is
# almost zero and get a distorted view.) We'll append the fields
# to a file to get an r-by-t picture. We'll also output from -sr to -sr
# instead of from 0 to sr.
sim.run(mp.in_volume(mp.Volume(center=mp.Vector3(), size=mp.Vector3(2 * sr)),
mp.at_beginning(mp.output_epsilon),
mp.to_appended("ez", mp.at_every(1 / fcen / 20, mp.output_efield_z))),
until=1 / fcen)
def run_simulation(self):
self.sim.run(mp.at_beginning(mp.output_epsilon),
mp.at_every(0.25, self.print_stuff),
mp.at_end(self.print_stuff),
mp.at_end(mp.output_efield_z),
until=23)
ref_out_field = self.ref_Ez if self.src_cmpt == mp.Ez else self.ref_Hz
out_field = self.sim.fields.get_field(self.src_cmpt, mp.vec(4.13, 3.75)).real
diff = abs(out_field - ref_out_field)
self.assertTrue(abs(diff) <= 0.05 * abs(ref_out_field), "Field output differs")
def main():
# Some parameters to describe the geometry:
eps = 13 # dielectric constant of waveguide
w = 1.2 # width of waveguide
r = 0.36 # radius of holes
# The cell dimensions
sy = 12 # size of cell in y direction (perpendicular to wvg.)
dpml = 1 # PML thickness (y direction only!)
cell = mp.Vector3(1, sy)
b = mp.Block(size=mp.Vector3(mp.inf, w, mp.inf),
material=mp.Medium(epsilon=eps))
c = mp.Cylinder(radius=r)
fcen = 0.25 # pulse center frequency
df = 1.5 # pulse freq. width: large df = short impulse
s = mp.Source(src=mp.GaussianSource(fcen, fwidth=df),
component=mp.Hz,
center=mp.Vector3(0.1234))
sym = mp.Mirror(direction=mp.Y, phase=-1)
sim = mp.Simulation(cell_size=cell,
geometry=[b, c],
sources=[s],
symmetries=[sym],
boundary_layers=[mp.PML(dpml, direction=mp.Y)],
resolution=20)
kx = False # if true, do run at specified kx and get fields
k_interp = 19 # # k-points to interpolate, otherwise
if kx:
sim.k_point = mp.Vector3(kx)
sim.run(mp.at_beginning(mp.output_epsilon),
mp.after_sources(
mp.Harminv(mp.Hz, mp.Vector3(0.1234), fcen, df)),
until_after_sources=300)
sim.run(mp.at_every(1 / fcen / 20, mp.output_hfield_z), until=1 / fcen)
else:
sim.run_k_points(
300, mp.interpolate(k_interp,
[mp.Vector3(), mp.Vector3(0.5)]))
def run_simulation(self):
self.sim.run(mp.at_beginning(mp.output_epsilon),
mp.at_every(0.25, self.print_stuff),
mp.at_end(self.print_stuff),
mp.at_end(mp.output_efield_z),
until=23)
ref_out_field = self.ref_Ez if self.src_cmpt == mp.Ez else self.ref_Hz
out_field = self.sim.fields.get_field(self.src_cmpt,
mp.vec(4.13, 3.75)).real
diff = abs(out_field - ref_out_field)
self.assertTrue(
abs(diff) <= 0.05 * abs(ref_out_field), "Field output differs")
def test_harminv(self):
self.init()
self.sim.run(
mp.at_beginning(mp.output_epsilon),
mp.after_sources(self.h),
until_after_sources=300
)
m1, m2, m3 = self.h.modes
self.assertAlmostEqual(m1.freq, 0.118101315147, places=4)
self.assertAlmostEqual(m1.decay, -0.000731513241623, places=4)
self.assertAlmostEqual(abs(m1.amp), 0.00341267634436, places=4)
self.assertAlmostEqual(m1.amp.real, -0.00304951667301, places=4)
self.assertAlmostEqual(m1.amp.imag, -0.00153192946717, places=4)
fp = self.sim.get_field_point(mp.Ez, mp.Vector3(1, 1))
self.assertAlmostEqual(fp, -0.08185972142450348)
def do_simrun(base_refl_data=None, do_live=True, geo=None, **kwargs):
sim = mp.Simulation(progress_interval=1e6 if do_live else 4,
**sim_kwargs(geo=geo, **kwargs))
sim.reset_meep()
# Now put in some flux monitors. Make sure the pulse source was selected
refl, tran = add_monitors(sim)
# for normal run, load negated fields to subtract incident from refl. fields
if base_refl_data is not None:
sim.load_minus_flux_data(refl, base_refl_data)
run_args = (
mp.at_beginning(livefield),
mp.at_every(5, livefield),
) if do_live else tuple()
t0 = time.time()
sim.run(*run_args, **monitor_until(geo=geo, **kwargs))
print('Realtime duration = {:.2f} seconds'.format(time.time() - t0))
return sim, refl, tran
def main():
n = 3.4 # index of waveguide
w = 1 # width of waveguide
r = 1 # inner radius of ring
pad = 4 # padding between waveguide and edge of PML
dpml = 2 # thickness of PML
sxy = 2 * (r + w + pad + dpml) # cell size
# Create a ring waveguide by two overlapping cylinders - later objects
# take precedence over earlier objects, so we put the outer cylinder first.
# and the inner (air) cylinder second.
c1 = mp.Cylinder(radius=r + w, material=mp.Medium(index=n))
c2 = mp.Cylinder(radius=r)
# If we don't want to excite a specific mode symmetry, we can just
# put a single point source at some arbitrary place, pointing in some
# arbitrary direction. We will only look for Ez-polarized modes.
fcen = 0.15 # pulse center frequency
df = 0.1 # pulse width (in frequency)
src = mp.Source(mp.GaussianSource(fcen, fwidth=df), mp.Ez, mp.Vector3(r + 0.1))
sim = mp.Simulation(cell_size=mp.Vector3(sxy, sxy),
geometry=[c1, c2],
sources=[src],
resolution=10,
symmetries=[mp.Mirror(mp.Y)],
boundary_layers=[mp.PML(dpml)])
sim.run(
mp.at_beginning(mp.output_epsilon),
mp.after_sources(mp.Harminv(mp.Ez, mp.Vector3(r + 0.1), fcen, df)),
until_after_sources=300
)
# Output fields for one period at the end. (If we output
# at a single time, we might accidentally catch the Ez field when it is
# almost zero and get a distorted view.)
sim.run(mp.at_every((1 / fcen / 20), mp.output_efield_z), until=(1 / fcen))
def test_harminv(self):
self.init()
self.sim.run(mp.at_beginning(mp.output_epsilon),
mp.after_sources(self.h),
until_after_sources=300)
m1 = self.h.modes[0]
self.assertAlmostEqual(m1.freq, 0.118101315147, places=4)
self.assertAlmostEqual(m1.decay, -0.000731513241623, places=4)
self.assertAlmostEqual(abs(m1.amp), 0.00341267634436, places=4)
self.assertAlmostEqual(m1.amp.real, -0.00304951667301, places=4)
self.assertAlmostEqual(m1.amp.imag, -0.00153192946717, places=3)
v = mp.Vector3(1, 1)
fp = self.sim.get_field_point(mp.Ez, v)
ep = self.sim.get_epsilon_point(v)
places = 5 if mp.is_single_precision() else 7
self.assertAlmostEqual(ep, 11.559999999999999, places=places)
self.assertAlmostEqual(fp, -0.08185972142450348, places=places)
def main():
n = 3.4 # index of waveguide
w = 1 # width of waveguide
r = 1 # inner radius of ring
pad = 4 # padding between waveguide and edge of PML
dpml = 2 # thickness of PML
sxy = 2*(r+w+pad+dpml) # cell size
# Create a ring waveguide by two overlapping cylinders - later objects
# take precedence over earlier objects, so we put the outer cylinder first.
# and the inner (air) cylinder second.
c1 = mp.Cylinder(radius=r+w, material=mp.Medium(index=n))
c2 = mp.Cylinder(radius=r)
# If we don't want to excite a specific mode symmetry, we can just
# put a single point source at some arbitrary place, pointing in some
# arbitrary direction. We will only look for Ez-polarized modes.
fcen = 0.15 # pulse center frequency
df = 0.1 # pulse width (in frequency)
src = mp.Source(mp.GaussianSource(fcen, fwidth=df), mp.Ez, mp.Vector3(r+0.1))
sim = mp.Simulation(cell_size=mp.Vector3(sxy, sxy),
geometry=[c1, c2],
sources=[src],
resolution=10,
symmetries=[mp.Mirror(mp.Y)],
boundary_layers=[mp.PML(dpml)])
sim.run(mp.at_beginning(mp.output_epsilon),
mp.after_sources(mp.Harminv(mp.Ez, mp.Vector3(r+0.1), fcen, df)),
until_after_sources=300)
# Output fields for one period at the end. (If we output
# at a single time, we might accidentally catch the Ez field when it is
# almost zero and get a distorted view.)
sim.run(mp.at_every(1/fcen/20, mp.output_efield_z), until=1/fcen)
def main(from_um_factor, resolution, courant, r, material, paper, reference,
submerged_index, displacement, surface_index, wlen_range, nfreq,
air_r_factor, pml_wlen_factor, flux_r_factor, time_factor_cell,
second_time_factor, series, folder, parallel, n_processes, n_cores,
n_nodes, split_chunks_evenly, load_flux, load_chunks, near2far):
#%% CLASSIC INPUT PARAMETERS
"""
# Simulation size
from_um_factor = 10e-3 # Conversion of 1 μm to my length unit (=10nm/1μm)
resolution = 2 # >=8 pixels per smallest wavelength, i.e. np.floor(8/wvl_min)
courant = 0.5
# Nanoparticle specifications: Sphere in Vacuum :)
r = 51.5 # Radius of sphere in nm
paper = "R"
reference = "Meep"
displacement = 0 # Displacement of the surface from the bottom of the sphere in nm
submerged_index = 1 # 1.33 for water
surface_index = 1 # 1.54 for glass
# Frequency and wavelength
wlen_range = np.array([350,500]) # Wavelength range in nm
nfreq = 100
# Box dimensions
pml_wlen_factor = 0.38
air_r_factor = 0.5
flux_r_factor = 0 #0.1
# Simulation time
time_factor_cell = 1.2
second_time_factor = 10
# Saving directories
series = "SilverRes4"
folder = "Test/TestSilver"
# Configuration
parallel = False
n_processes = 1
n_cores = 1
n_nodes = 1
split_chunks_evenly = True
load_flux = False
load_chunks = True
near2far = False
"""
#%% MORE INPUT PARAMETERS
# Frequency and wavelength
cutoff = 3.2 # Gaussian planewave source's parameter of shape
nazimuthal = 16
npolar = 20
### TREATED INPUT PARAMETERS
# Nanoparticle specifications: Sphere in Vacuum :)
r = r / (from_um_factor * 1e3) # Now in Meep units
if reference == "Meep":
medium = vmt.import_medium(material,
from_um_factor=from_um_factor,
paper=paper)
# Importing material constants dependant on frequency from Meep Library
elif reference == "RIinfo":
medium = vmt.MediumFromFile(material,
paper=paper,
reference=reference,
from_um_factor=from_um_factor)
# Importing material constants dependant on frequency from external file
else:
raise ValueError("Reference for medium not recognized. Sorry :/")
displacement = displacement / (from_um_factor * 1e3) # Now in Meep units
# Frequency and wavelength
wlen_range = np.array(wlen_range)
wlen_range = wlen_range / (from_um_factor * 1e3) # Now in Meep units
freq_range = 1 / wlen_range # Hz range in Meep units from highest to lowest
freq_center = np.mean(freq_range)
freq_width = max(freq_range) - min(freq_range)
# Space configuration
pml_width = pml_wlen_factor * max(wlen_range) # 0.5 * max(wlen_range)
air_width = air_r_factor * r # 0.5 * max(wlen_range)
flux_box_size = 2 * (1 + flux_r_factor) * r
# Saving directories
if series is None:
series = "Test"
if folder is None:
folder = "Test"
params_list = [
"from_um_factor", "resolution", "courant", "material", "r", "paper",
"reference", "submerged_index", "displacement", "surface_index",
"wlen_range", "nfreq", "nazimuthal", "npolar", "cutoff",
"flux_box_size", "cell_width", "pml_width", "air_width",
"source_center", "until_after_sources", "time_factor_cell",
"second_time_factor", "enlapsed", "parallel", "n_processes", "n_cores",
"n_nodes", "split_chunks_evenly", "near2far", "script", "sysname",
"path"
]
#%% GENERAL GEOMETRY SETUP
air_width = air_width - air_width % (1 / resolution)
pml_width = pml_width - pml_width % (1 / resolution)
pml_layers = [mp.PML(thickness=pml_width)]
# symmetries = [mp.Mirror(mp.Y),
# mp.Mirror(mp.Z, phase=-1)]
# Two mirror planes reduce cell size to 1/4
# Issue related that lead me to comment this lines:
# https://github.com/NanoComp/meep/issues/1484
cell_width = 2 * (pml_width + air_width + r)
cell_width = cell_width - cell_width % (1 / resolution)
cell_size = mp.Vector3(cell_width, cell_width, cell_width)
# surface_center = r/4 - displacement/2 + cell_width/4
# surface_center = surface_center - surface_center%(1/resolution)
# displacement = r/2 + cell_width/2 - 2*surface_center
displacement = displacement - displacement % (1 / resolution)
flux_box_size = flux_box_size - flux_box_size % (1 / resolution)
source_center = -0.5 * cell_width + pml_width
sources = [
mp.Source(mp.GaussianSource(freq_center,
fwidth=freq_width,
is_integrated=True,
cutoff=cutoff),
center=mp.Vector3(source_center),
size=mp.Vector3(0, cell_width, cell_width),
component=mp.Ez)
]
# Ez-polarized planewave pulse
# (its size parameter fills the entire cell in 2d)
# >> The planewave source extends into the PML
# ==> is_integrated=True must be specified
until_after_sources = time_factor_cell * cell_width * submerged_index
# Enough time for the pulse to pass through all the cell
# Originally: Aprox 3 periods of lowest frequency, using T=λ/c=λ in Meep units
# Now: Aprox 3 periods of highest frequency, using T=λ/c=λ in Meep units
geometry = [mp.Sphere(material=medium, center=mp.Vector3(), radius=r)]
# Au sphere with frequency-dependant characteristics imported from Meep.
if surface_index != 1:
geometry = [
mp.Block(material=mp.Medium(index=surface_index),
center=mp.Vector3(
r / 2 - displacement / 2 + cell_width / 4, 0, 0),
size=mp.Vector3(cell_width / 2 - r + displacement,
cell_width, cell_width)), *geometry
]
# A certain material surface underneath it
home = vs.get_home()
sysname = vs.get_sys_name()
path = os.path.join(home, folder, series)
if not os.path.isdir(path) and vm.parallel_assign(0, n_processes,
parallel):
os.makedirs(path)
file = lambda f: os.path.join(path, f)
# Computation
enlapsed = []
parallel_specs = np.array([n_processes, n_cores, n_nodes], dtype=int)
max_index = np.argmax(parallel_specs)
for index, item in enumerate(parallel_specs):
if item == 0: parallel_specs[index] = 1
parallel_specs[0:max_index] = np.full(parallel_specs[0:max_index].shape,
max(parallel_specs))
n_processes, n_cores, n_nodes = parallel_specs
parallel = max(parallel_specs) > 1
del parallel_specs, max_index, index, item
if parallel:
np_process = mp.count_processors()
else:
np_process = 1
#%% FIRST RUN
measure_ram()
params = {}
for p in params_list:
params[p] = eval(p)
stable, max_courant = vm.check_stability(params)
if stable:
print("As a whole, the simulation should be stable")
else:
print("As a whole, the simulation could not be stable")
print(f"Recommended maximum courant factor is {max_courant}")
if load_flux:
try:
flux_path = vm.check_midflux(params)[0]
flux_needed = False
except:
flux_needed = True
else:
flux_needed = True
if load_chunks and not split_chunks_evenly:
try:
chunks_path = vm.check_chunks(params)[0]
chunk_layout = os.path.join(chunks_path, "Layout.h5")
chunks_needed = False
except:
chunks_needed = True
flux_needed = True
else:
if not split_chunks_evenly:
chunks_needed = True
flux_needed = True
else:
chunk_layout = None
chunks_needed = False
if chunks_needed:
sim = mp.Simulation(
resolution=resolution,
cell_size=cell_size,
boundary_layers=pml_layers,
sources=sources,
k_point=mp.Vector3(),
Courant=courant,
default_material=mp.Medium(index=submerged_index),
output_single_precision=True,
split_chunks_evenly=split_chunks_evenly,
# symmetries=symmetries,
geometry=geometry)
sim.init_sim()
chunks_path = vm.save_chunks(sim, params, path)
chunk_layout = os.path.join(chunks_path, "Layout.h5")
del sim
if flux_needed:
#% FIRST RUN: SET UP
measure_ram()
sim = mp.Simulation(resolution=resolution,
cell_size=cell_size,
boundary_layers=pml_layers,
sources=sources,
k_point=mp.Vector3(),
Courant=courant,
default_material=mp.Medium(index=submerged_index),
split_chunks_evenly=split_chunks_evenly,
chunk_layout=chunk_layout,
output_single_precision=True) #,
# symmetries=symmetries)
# >> k_point zero specifies boundary conditions needed
# for the source to be infinitely extended
measure_ram()
# Scattered power --> Computed by surrounding it with closed DFT flux box
# (its size and orientation are irrelevant because of Poynting's theorem)
box_x1 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(x=-flux_box_size / 2),
size=mp.Vector3(0, flux_box_size, flux_box_size)))
box_x2 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(x=+flux_box_size / 2),
size=mp.Vector3(0, flux_box_size, flux_box_size)))
box_y1 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(y=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0, flux_box_size)))
box_y2 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(y=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0, flux_box_size)))
box_z1 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(z=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size, 0)))
box_z2 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(z=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size, 0)))
# Funny you can encase the sphere (r radius) so closely (2r-sided box)
measure_ram()
if near2far:
near2far_box = sim.add_near2far(
freq_center, freq_width, nfreq,
mp.Near2FarRegion(center=mp.Vector3(x=-flux_box_size / 2),
size=mp.Vector3(0, flux_box_size,
flux_box_size),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(x=+flux_box_size / 2),
size=mp.Vector3(0, flux_box_size,
flux_box_size),
weight=+1),
mp.Near2FarRegion(center=mp.Vector3(y=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0,
flux_box_size),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(y=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0,
flux_box_size),
weight=+1),
mp.Near2FarRegion(center=mp.Vector3(z=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size,
0),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(z=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size,
0),
weight=+1))
measure_ram()
else:
near2far_box = None
# used_ram.append(used_ram[-1])
#% FIRST RUN: INITIALIZE
temp = time()
sim.init_sim()
enlapsed.append(time() - temp)
measure_ram()
step_ram_function = lambda sim: measure_ram()
#% FIRST RUN: SIMULATION NEEDED TO NORMALIZE
temp = time()
sim.run(mp.at_beginning(step_ram_function),
mp.at_time(int(until_after_sources / 2), step_ram_function),
mp.at_end(step_ram_function),
until_after_sources=until_after_sources)
# mp.stop_when_fields_decayed(
# np.mean(wlen_range), # dT = mean period of source
# mp.Ez, # Component of field to check
# mp.Vector3(0.5*cell_width - pml_width, 0, 0), # Where to check
# 1e-3)) # Factor to decay
enlapsed.append(time() - temp)
#% SAVE MID DATA
for p in params_list:
params[p] = eval(p)
flux_path = vm.save_midflux(sim, box_x1, box_x2, box_y1, box_y2,
box_z1, box_z2, near2far_box, params, path)
freqs = np.asarray(mp.get_flux_freqs(box_x1))
box_x1_flux0 = np.asarray(mp.get_fluxes(box_x1))
box_x2_flux0 = np.asarray(mp.get_fluxes(box_x2))
box_y1_flux0 = np.asarray(mp.get_fluxes(box_y1))
box_y2_flux0 = np.asarray(mp.get_fluxes(box_y2))
box_z1_flux0 = np.asarray(mp.get_fluxes(box_z1))
box_z2_flux0 = np.asarray(mp.get_fluxes(box_z2))
data_mid = np.array([
1e3 * from_um_factor / freqs, box_x1_flux0, box_x2_flux0,
box_y1_flux0, box_y2_flux0, box_z1_flux0, box_z2_flux0
]).T
header_mid = [
"Longitud de onda [nm]", "Flujo X10 [u.a.]", "Flujo X20 [u.a]",
"Flujo Y10 [u.a]", "Flujo Y20 [u.a]", "Flujo Z10 [u.a]",
"Flujo Z20 [u.a]"
]
if vm.parallel_assign(0, n_processes, parallel):
vs.savetxt(file("MidFlux.txt"),
data_mid,
header=header_mid,
footer=params)
if not split_chunks_evenly:
vm.save_chunks(sim, params, path)
if parallel:
f = h5.File(file("MidRAM.h5"),
"w",
driver='mpio',
comm=MPI.COMM_WORLD)
current_process = mp.my_rank()
f.create_dataset("RAM", (len(used_ram), np_process), dtype="float")
f["RAM"][:, current_process] = used_ram
for a in params:
f["RAM"].attrs[a] = params[a]
f.create_dataset("SWAP", (len(used_ram), np_process), dtype="int")
f["SWAP"][:, current_process] = swapped_ram
for a in params:
f["SWAP"].attrs[a] = params[a]
else:
f = h5.File(file("MidRAM.h5"), "w")
f.create_dataset("RAM", data=used_ram)
for a in params:
f["RAM"].attrs[a] = params[a]
f.create_dataset("SWAP", data=swapped_ram)
for a in params:
f["SWAP"].attrs[a] = params[a]
f.close()
del f
#% PLOT FLUX FOURIER MID DATA
if vm.parallel_assign(1, np_process, parallel):
ylims = (np.min(data_mid[:, 1:]), np.max(data_mid[:, 1:]))
ylims = (ylims[0] - .1 * (ylims[1] - ylims[0]),
ylims[1] + .1 * (ylims[1] - ylims[0]))
fig, ax = plt.subplots(3, 2, sharex=True)
fig.subplots_adjust(hspace=0, wspace=.05)
for a in ax[:, 1]:
a.yaxis.tick_right()
a.yaxis.set_label_position("right")
for a, h in zip(np.reshape(ax, 6), header_mid[1:]):
a.set_ylabel(h)
for d, a in zip(data_mid[:, 1:].T, np.reshape(ax, 6)):
a.plot(1e3 * from_um_factor / freqs, d)
a.set_ylim(*ylims)
ax[-1, 0].set_xlabel("Wavelength [nm]")
ax[-1, 1].set_xlabel("Wavelength [nm]")
plt.savefig(file("MidFlux.png"))
del fig, ax, ylims, a, h
sim.reset_meep()
#%% SECOND RUN: SETUP
measure_ram()
sim = mp.Simulation(
resolution=resolution,
cell_size=cell_size,
boundary_layers=pml_layers,
sources=sources,
k_point=mp.Vector3(),
Courant=courant,
default_material=mp.Medium(index=submerged_index),
output_single_precision=True,
split_chunks_evenly=split_chunks_evenly,
chunk_layout=chunk_layout,
# symmetries=symmetries,
geometry=geometry)
measure_ram()
box_x1 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(x=-flux_box_size / 2),
size=mp.Vector3(0, flux_box_size, flux_box_size)))
box_x2 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(x=+flux_box_size / 2),
size=mp.Vector3(0, flux_box_size, flux_box_size)))
box_y1 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(y=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0, flux_box_size)))
box_y2 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(y=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0, flux_box_size)))
box_z1 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(z=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size, 0)))
box_z2 = sim.add_flux(
freq_center, freq_width, nfreq,
mp.FluxRegion(center=mp.Vector3(z=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size, 0)))
measure_ram()
if near2far:
near2far_box = sim.add_near2far(
freq_center, freq_width, nfreq,
mp.Near2FarRegion(center=mp.Vector3(x=-flux_box_size / 2),
size=mp.Vector3(0, flux_box_size, flux_box_size),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(x=+flux_box_size / 2),
size=mp.Vector3(0, flux_box_size, flux_box_size),
weight=+1),
mp.Near2FarRegion(center=mp.Vector3(y=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0, flux_box_size),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(y=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0, flux_box_size),
weight=+1),
mp.Near2FarRegion(center=mp.Vector3(z=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size, 0),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(z=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size, 0),
weight=+1))
measure_ram()
else:
near2far_box = None
# used_ram.append(used_ram[-1])
#%% SECOND RUN: INITIALIZE
temp = time()
sim.init_sim()
enlapsed.append(time() - temp)
measure_ram()
#%% LOAD FLUX FROM FILE
vm.load_midflux(sim, box_x1, box_x2, box_y1, box_y2, box_z1, box_z2,
near2far_box, flux_path)
measure_ram()
freqs = np.asarray(mp.get_flux_freqs(box_x1))
box_x1_flux0 = np.asarray(mp.get_fluxes(box_x1))
box_x1_data = sim.get_flux_data(box_x1)
box_x2_data = sim.get_flux_data(box_x2)
box_y1_data = sim.get_flux_data(box_y1)
box_y2_data = sim.get_flux_data(box_y2)
box_z1_data = sim.get_flux_data(box_z1)
box_z2_data = sim.get_flux_data(box_z2)
if near2far: near2far_data = sim.get_near2far_data(near2far_box)
temp = time()
sim.load_minus_flux_data(box_x1, box_x1_data)
sim.load_minus_flux_data(box_x2, box_x2_data)
sim.load_minus_flux_data(box_y1, box_y1_data)
sim.load_minus_flux_data(box_y2, box_y2_data)
sim.load_minus_flux_data(box_z1, box_z1_data)
sim.load_minus_flux_data(box_z2, box_z2_data)
if near2far: sim.load_minus_near2far_data(near2far_box, near2far_data)
enlapsed.append(time() - temp)
del box_x1_data, box_x2_data, box_y1_data, box_y2_data
del box_z1_data, box_z2_data
if near2far: del near2far_data
measure_ram()
#%% SECOND RUN: SIMULATION :D
step_ram_function = lambda sim: measure_ram()
temp = time()
sim.run(mp.at_beginning(step_ram_function),
mp.at_time(int(second_time_factor * until_after_sources / 2),
step_ram_function),
mp.at_end(step_ram_function),
until_after_sources=second_time_factor * until_after_sources)
# mp.stop_when_fields_decayed(
# np.mean(wlen_range), # dT = mean period of source
# mp.Ez, # Component of field to check
# mp.Vector3(0.5*cell_width - pml_width, 0, 0), # Where to check
# 1e-3)) # Factor to decay
enlapsed.append(time() - temp)
del temp
# Aprox 30 periods of lowest frequency, using T=λ/c=λ in Meep units
box_x1_flux = np.asarray(mp.get_fluxes(box_x1))
box_x2_flux = np.asarray(mp.get_fluxes(box_x2))
box_y1_flux = np.asarray(mp.get_fluxes(box_y1))
box_y2_flux = np.asarray(mp.get_fluxes(box_y2))
box_z1_flux = np.asarray(mp.get_fluxes(box_z1))
box_z2_flux = np.asarray(mp.get_fluxes(box_z2))
#%% SCATTERING ANALYSIS
scatt_flux = box_x1_flux - box_x2_flux
scatt_flux = scatt_flux + box_y1_flux - box_y2_flux
scatt_flux = scatt_flux + box_z1_flux - box_z2_flux
intensity = box_x1_flux0 / (flux_box_size)**2
# Flux of one of the six monitor planes / Área
# (the closest one, facing the planewave source)
# This is why the six sides of the flux box are separated
# (Otherwise, the box could've been one flux object with weights ±1 per side)
scatt_cross_section = np.divide(scatt_flux, intensity)
# Scattering cross section σ =
# = scattered power in all directions / incident intensity.
scatt_eff_meep = -1 * scatt_cross_section / (np.pi * r**2)
# Scattering efficiency =
# = scattering cross section / cross sectional area of the sphere
freqs = np.array(freqs)
scatt_eff_theory = [
ps.MieQ(np.sqrt(medium.epsilon(f)[0, 0] * medium.mu(f)[0, 0]),
1e3 * from_um_factor / f,
2 * r * 1e3 * from_um_factor,
nMedium=submerged_index,
asDict=True)['Qsca'] for f in freqs
]
# The simulation results are validated by comparing with
# analytic theory of PyMieScatt module
#%% ANGULAR PATTERN ANALYSIS
if near2far:
fraunhofer_distance = 8 * (r**2) / min(wlen_range)
radial_distance = max(10 * fraunhofer_distance, 1.5 * cell_width / 2)
# radius of far-field circle must be at least Fraunhofer distance
azimuthal_angle = np.arange(0, 2 + 2 / nazimuthal,
2 / nazimuthal) # in multiples of pi
polar_angle = np.arange(0, 1 + 1 / npolar, 1 / npolar)
poynting_x = []
poynting_y = []
poynting_z = []
poynting_r = []
for phi in azimuthal_angle:
poynting_x.append([])
poynting_y.append([])
poynting_z.append([])
poynting_r.append([])
for theta in polar_angle:
farfield_dict = sim.get_farfields(
near2far_box,
1,
where=mp.Volume(center=mp.Vector3(
radial_distance * np.cos(np.pi * phi) *
np.sin(np.pi * theta),
radial_distance * np.sin(np.pi * phi) *
np.sin(np.pi *
theta), radial_distance *
np.cos(np.pi * theta))))
Px = farfield_dict["Ey"] * np.conjugate(farfield_dict["Hz"])
Px -= farfield_dict["Ez"] * np.conjugate(farfield_dict["Hy"])
Py = farfield_dict["Ez"] * np.conjugate(farfield_dict["Hx"])
Py -= farfield_dict["Ex"] * np.conjugate(farfield_dict["Hz"])
Pz = farfield_dict["Ex"] * np.conjugate(farfield_dict["Hy"])
Pz -= farfield_dict["Ey"] * np.conjugate(farfield_dict["Hx"])
Px = np.real(Px)
Py = np.real(Py)
Pz = np.real(Pz)
poynting_x[-1].append(Px)
poynting_y[-1].append(Py)
poynting_z[-1].append(Pz)
poynting_r[-1].append(
np.sqrt(np.square(Px) + np.square(Py) + np.square(Pz)))
poynting_x = np.array(poynting_x)
poynting_y = np.array(poynting_y)
poynting_z = np.array(poynting_z)
poynting_r = np.array(poynting_r)
#%% SAVE FINAL DATA
for p in params_list:
params[p] = eval(p)
data = np.array(
[1e3 * from_um_factor / freqs, scatt_eff_meep, scatt_eff_theory]).T
header = [
"Longitud de onda [nm]", "Sección eficaz efectiva (Meep) [u.a.]",
"Sección eficaz efectiva (Theory) [u.a.]"
]
data_base = np.array([
1e3 * from_um_factor / freqs, box_x1_flux0, box_x1_flux, box_x2_flux,
box_y1_flux, box_y2_flux, box_z1_flux, box_z2_flux, intensity,
scatt_flux, scatt_cross_section
]).T
header_base = [
"Longitud de onda [nm]", "Flujo X10 [u.a.]", "Flujo X1 [u.a]",
"Flujo X2 [u.a]", "Flujo Y1 [u.a]", "Flujo Y2 [u.a]", "Flujo Z1 [u.a]",
"Flujo Z2 [u.a]", "Intensidad incidente [u.a.]",
"Flujo scattereado [u.a.]", "Sección eficaz de scattering [u.a.]"
]
if vm.parallel_assign(0, np_process, parallel):
vs.savetxt(file("Results.txt"), data, header=header, footer=params)
vs.savetxt(file("BaseResults.txt"),
data_base,
header=header_base,
footer=params)
if near2far:
header_near2far = [
"Poynting medio Px [u.a.]", "Poynting medio Py [u.a.]",
"Poynting medio Pz [u.a.]", "Poynting medio Pr [u.a.]"
]
data_near2far = [
poynting_x.reshape(poynting_x.size),
poynting_y.reshape(poynting_y.size),
poynting_z.reshape(poynting_z.size),
poynting_r.reshape(poynting_r.size)
]
if vm.parallel_assign(1, np_process, parallel):
vs.savetxt(file("Near2FarResults.txt"),
data_near2far,
header=header_near2far,
footer=params)
if not split_chunks_evenly:
vm.save_chunks(sim, params, path)
if parallel:
f = h5.File(file("RAM.h5"), "w", driver='mpio', comm=MPI.COMM_WORLD)
current_process = mp.my_rank()
f.create_dataset("RAM", (len(used_ram), np_process), dtype="float")
f["RAM"][:, current_process] = used_ram
for a in params:
f["RAM"].attrs[a] = params[a]
f.create_dataset("SWAP", (len(used_ram), np_process), dtype="int")
f["SWAP"][:, current_process] = swapped_ram
for a in params:
f["SWAP"].attrs[a] = params[a]
else:
f = h5.File(file("RAM.h5"), "w")
f.create_dataset("RAM", data=used_ram)
for a in params:
f["RAM"].attrs[a] = params[a]
f.create_dataset("SWAP", data=swapped_ram)
for a in params:
f["SWAP"].attrs[a] = params[a]
f.close()
del f
if flux_needed and vm.parallel_assign(0, np_process, parallel):
os.remove(file("MidRAM.h5"))
#%% PLOT ALL TOGETHER
if vm.parallel_assign(0, np_process, parallel) and surface_index == 1:
plt.figure()
plt.plot(1e3 * from_um_factor / freqs,
scatt_eff_meep,
'bo-',
label='Meep')
plt.plot(1e3 * from_um_factor / freqs,
scatt_eff_theory,
'ro-',
label='Theory')
plt.xlabel('Wavelength [nm]')
plt.ylabel('Scattering efficiency [σ/πr$^{2}$]')
plt.legend()
plt.title('Scattering of Au Sphere With {:.1f} nm Radius'.format(
r * from_um_factor * 1e3))
plt.tight_layout()
plt.savefig(file("Comparison.png"))
#%% PLOT SEPARATE
if vm.parallel_assign(1, np_process, parallel):
plt.figure()
plt.plot(1e3 * from_um_factor / freqs,
scatt_eff_meep,
'bo-',
label='Meep')
plt.xlabel('Wavelength [nm]')
plt.ylabel('Scattering efficiency [σ/πr$^{2}$]')
plt.legend()
plt.title('Scattering of Au Sphere With {:.1f} nm Radius'.format(
r * from_um_factor * 1e3))
plt.tight_layout()
plt.savefig(file("Meep.png"))
if vm.parallel_assign(0, np_process, parallel) and surface_index == 1:
plt.figure()
plt.plot(1e3 * from_um_factor / freqs,
scatt_eff_theory,
'ro-',
label='Theory')
plt.xlabel('Wavelength [nm]')
plt.ylabel('Scattering efficiency [σ/πr$^{2}$]')
plt.legend()
plt.title('Scattering of Au Sphere With {:.1f} nm Radius'.format(r *
10))
plt.tight_layout()
plt.savefig(file("Theory.png"))
#%% PLOT ONE ABOVE THE OTHER
if vm.parallel_assign(1, np_process, parallel) and surface_index == 1:
fig, axes = plt.subplots(nrows=2, sharex=True)
fig.subplots_adjust(hspace=0)
plt.suptitle('Scattering of Au Sphere With {:.1f} nm Radius'.format(
r * from_um_factor * 1e3))
axes[0].plot(1e3 * from_um_factor / freqs,
scatt_eff_meep,
'bo-',
label='Meep')
axes[0].yaxis.tick_right()
axes[0].set_ylabel('Scattering efficiency [σ/πr$^{2}$]')
axes[0].legend()
axes[1].plot(1e3 * from_um_factor / freqs,
scatt_eff_theory,
'ro-',
label='Theory')
axes[1].set_xlabel('Wavelength [nm]')
axes[1].set_ylabel('Scattering efficiency [σ/πr$^{2}$]')
axes[1].legend()
plt.savefig(file("SeparatedComparison.png"))
#%% PLOT FLUX FOURIER FINAL DATA
if vm.parallel_assign(0, np_process, parallel):
ylims = (np.min(data_base[:, 2:8]), np.max(data_base[:, 2:8]))
ylims = (ylims[0] - .1 * (ylims[1] - ylims[0]),
ylims[1] + .1 * (ylims[1] - ylims[0]))
fig, ax = plt.subplots(3, 2, sharex=True)
fig.subplots_adjust(hspace=0, wspace=.05)
plt.suptitle('Final flux of Au Sphere With {:.1f} nm Radius'.format(
r * from_um_factor * 1e3))
for a in ax[:, 1]:
a.yaxis.tick_right()
a.yaxis.set_label_position("right")
for a, h in zip(np.reshape(ax, 6), header_base[1:7]):
a.set_ylabel(h)
for d, a in zip(data_base[:, 3:9].T, np.reshape(ax, 6)):
a.plot(1e3 * from_um_factor / freqs, d)
a.set_ylim(*ylims)
ax[-1, 0].set_xlabel("Wavelength [nm]")
ax[-1, 1].set_xlabel("Wavelength [nm]")
plt.savefig(file("FinalFlux.png"))
#%% PLOT ANGULAR PATTERN IN 3D
if near2far and vm.parallel_assign(1, np_process, parallel):
freq_index = np.argmin(np.abs(freqs - freq_center))
fig = plt.figure()
plt.suptitle(
'Angular Pattern of Au Sphere With {:.1f} nm Radius at {:.1f} nm'.
format(r * from_um_factor * 1e3,
from_um_factor * 1e3 / freqs[freq_index]))
ax = fig.add_subplot(1, 1, 1, projection='3d')
ax.plot_surface(poynting_x[:, :, freq_index],
poynting_y[:, :, freq_index],
poynting_z[:, :, freq_index],
cmap=plt.get_cmap('jet'),
linewidth=1,
antialiased=False,
alpha=0.5)
ax.set_xlabel(r"$P_x$")
ax.set_ylabel(r"$P_y$")
ax.set_zlabel(r"$P_z$")
plt.savefig(file("AngularPattern.png"))
#%% PLOT ANGULAR PATTERN PROFILE FOR DIFFERENT POLAR ANGLES
if near2far and vm.parallel_assign(0, np_process, parallel):
freq_index = np.argmin(np.abs(freqs - freq_center))
index = [
list(polar_angle).index(alpha) for alpha in [0, .25, .5, .75, 1]
]
plt.figure()
plt.suptitle(
'Angular Pattern of Au Sphere With {:.1f} nm Radius at {:.1f} nm'.
format(r * from_um_factor * 1e3,
from_um_factor * 1e3 / freqs[freq_index]))
ax_plain = plt.axes()
for i in index:
ax_plain.plot(poynting_x[:, i, freq_index],
poynting_y[:, i, freq_index],
".-",
label=rf"$\theta$ = {polar_angle[i]:.2f} $\pi$")
plt.legend()
ax_plain.set_xlabel(r"$P_x$")
ax_plain.set_ylabel(r"$P_y$")
ax_plain.set_aspect("equal")
plt.savefig(file("AngularPolar.png"))
#%% PLOT ANGULAR PATTERN PROFILE FOR DIFFERENT AZIMUTHAL ANGLES
if near2far and vm.parallel_assign(1, np_process, parallel):
freq_index = np.argmin(np.abs(freqs - freq_center))
index = [
list(azimuthal_angle).index(alpha)
for alpha in [0, .25, .5, .75, 1, 1.25, 1.5, 1.75, 2]
]
plt.figure()
plt.suptitle(
'Angular Pattern of Au Sphere With {:.1f} nm Radius at {:.1f} nm'.
format(r * from_um_factor * 1e3,
from_um_factor * 1e3 / freqs[freq_index]))
ax_plain = plt.axes()
for i in index:
ax_plain.plot(poynting_x[i, :, freq_index],
poynting_z[i, :, freq_index],
".-",
label=rf"$\phi$ = {azimuthal_angle[i]:.2f} $\pi$")
plt.legend()
ax_plain.set_xlabel(r"$P_x$")
ax_plain.set_ylabel(r"$P_z$")
plt.savefig(file("AngularAzimuthal.png"))
if near2far and vm.parallel_assign(0, np_process, parallel):
freq_index = np.argmin(np.abs(freqs - freq_center))
index = [
list(azimuthal_angle).index(alpha)
for alpha in [0, .25, .5, .75, 1, 1.25, 1.5, 1.75, 2]
]
plt.figure()
plt.suptitle(
'Angular Pattern of Au Sphere With {:.1f} nm Radius at {:.1f} nm'.
format(r * from_um_factor * 1e3,
from_um_factor * 1e3 / freqs[freq_index]))
ax_plain = plt.axes()
for i in index:
ax_plain.plot(np.sqrt(
np.square(poynting_x[i, :, freq_index]) +
np.square(poynting_y[i, :, freq_index])),
poynting_z[i, :, freq_index],
".-",
label=rf"$\phi$ = {azimuthal_angle[i]:.2f} $\pi$")
plt.legend()
ax_plain.set_xlabel(r"$P_\rho$")
ax_plain.set_ylabel(r"$P_z$")
plt.savefig(file("AngularAzimuthalAbs.png"))
def main(args):
resolution = 20 # pixels/um
eps = 13 # epsilon of waveguide
w = 1.2 # width of the waveguide
dpml = 1 # PML thickness
largC = 16 # largura da celula
altC = 16 # altura da celula
sx = largC + dpml
sy = altC + dpml
fcen = args.fcen # pulse centger frequency
df = args.df # pulse frequency width
cell = mp.Vector3(sx,sy,0)
def epsP(p):
valorIm = -0.5 + math.pow(math.cos((p.y)*(2*math.pi/(altC/4))),2)
return mp.Medium(epsilon=3, D_conductivity=2*math.pi*fcen*(valorIm)/3)
epsP.do_averaging = True
blk = mp.Block(size=mp.Vector3(mp.inf,mp.inf,mp.inf), material=mp.Medium(epsilon=eps))
geometry = [blk]
# AQUI ESTÁ A LINHA DE TESTE: USAMOS A FUNCAO PARA DEFINIR O EPSILON
# geometry.append(mp.Block(size=mp.Vector3(mp.inf,w,mp.inf)))
geometry.append(mp.Block(center=mp.Vector3(),size=mp.Vector3(mp.inf,altC,mp.inf),material=epsP))
pml_layers = [mp.PML(1.0)]
src = [mp.Source(mp.GaussianSource(fcen, fwidth=df),
component=mp.Ey,
center=mp.Vector3(-0.5*sx+dpml), # fonte na esquerda; para colocar na direita usar 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)
sim.run(mp.at_beginning(mp.output_epsilon),
mp.to_appended("hz",mp.at_every(0.4,mp.output_hfield_z)),
until=300)
epsilon0 = sim.get_array(center=mp.Vector3(), size=cell, component=mp.Dielectric)
plt.figure()
plt.imshow(epsilon0.transpose(), interpolation='spline36', cmap='RdBu')
plt.axis('off')
plt.savefig('epsilon.png',format='png')
plt.show()
results_plane = []
results_line = []
def get_slice_plane(sim):
results_plane.append(sim.get_array(
center=mp.Vector3(*plane_center),
size=mp.Vector3(*plane_size),
component=mp.Ez))
def get_slice_line(sim):
results_line.append(sim.get_array(
center=mp.Vector3(*line_center),
size=mp.Vector3(*line_size),
component=mp.Ez))
to_do_while_running = [mp.at_beginning(get_slice_line),
mp.at_beginning(get_slice_plane),
mp.at_every(period_line, get_slice_line),
mp.at_every(period_plane, get_slice_plane)]
#%% INITIALIZE
sim.reset_meep()
sim = mp.Simulation(resolution=resolution,
cell_size=cell_size,
boundary_layers=boundary_layers,
sources=sources,
symmetries=symmetries)
sim.init_sim()
def simulation(f_cen, df, fmin, fmax, sy, dpml, air, sx, resolution, nfreq,
geometry, init_refl_data, init_tran_flux, n, THICKNESS):
#----------------------Simulation------------------------------
cell = mp.Vector3(sx, sy)
thick = np.sum(THICKNESS)
#define Gaussian plane wave
sources = [
mp.Source(mp.GaussianSource(f_cen, fwidth=df),
component=mp.Ez,
center=mp.Vector3(0, 0.5 * sy - dpml - 0.02 * air, 0),
size=mp.Vector3(x=sx))
]
#define pml layers
pml_layers = [
mp.PML(thickness=dpml, direction=mp.Y, side=mp.High),
mp.Absorber(thickness=dpml, direction=mp.Y, side=mp.Low)
]
tran_fr = mp.FluxRegion(center=mp.Vector3(0, -0.5 * sy + dpml + 0.05),
size=mp.Vector3(x=sx))
refl_fr = mp.FluxRegion(center=mp.Vector3(0, 0.5 * sy - dpml - 0.1 * air),
size=mp.Vector3(x=sx))
mp.quiet(quietval=True)
if n == 0:
#if os.path.exists('dft_Z_empty.h5'):
#os.remove('dft_Z_empty.h5')
sim = mp.Simulation(cell_size=cell,
boundary_layers=pml_layers,
sources=sources,
symmetries=[mp.Mirror(mp.X)],
dimensions=2,
resolution=resolution,
k_point=mp.Vector3())
#----------------------Monitors------------------------------
refl = sim.add_flux(f_cen, df, nfreq, refl_fr)
tran = sim.add_flux(f_cen, df, nfreq, tran_fr)
dfts_Z = sim.add_dft_fields([mp.Ez],
fmin,
fmax,
nfreq,
where=mp.Volume(center=mp.Vector3(
0, -sy * 0.5 + dpml + THICKNESS * 0.5,
0),
size=mp.Vector3(
sx, THICKNESS)))
#----------------------Run------------------------------
sim.run(until_after_sources=mp.stop_when_fields_decayed(
5, mp.Ez, mp.Vector3(), 1e-3))
#----------------------Genetic------------------------------
sim.output_dft(dfts_Z, "dft_Z_empty")
init_refl_data = sim.get_flux_data(refl)
init_tran_flux = mp.get_fluxes(tran)
sim.reset_meep()
get = init_refl_data, init_tran_flux
elif n == 1:
#if os.path.exists('dft_Z_fields.h5'):
#os.remove('dft_Z_fields.h5')
sim = mp.Simulation(cell_size=cell,
boundary_layers=pml_layers,
sources=sources,
geometry=geometry,
symmetries=[mp.Mirror(mp.X)],
dimensions=2,
resolution=resolution,
k_point=mp.Vector3())
refl = sim.add_flux(f_cen, df, nfreq, refl_fr)
tran = sim.add_flux(f_cen, df, nfreq, tran_fr)
sim.load_minus_flux_data(refl, init_refl_data)
dfts_Z = sim.add_dft_fields([mp.Ez],
fmin,
fmax,
nfreq,
where=mp.Volume(center=mp.Vector3(
0, -sy * 0.5 + dpml + thick * 0.5, 0),
size=mp.Vector3(sx,
thick)))
sim.run(until_after_sources=mp.stop_when_fields_decayed(
5, mp.Ez, mp.Vector3(),
1e-3)) #mp.at_beginning(mp.output_epsilon),
sim.output_dft(dfts_Z, "dft_Z_fields")
flux_freqs = mp.get_flux_freqs(refl)
final_refl_flux = mp.get_fluxes(refl)
wl = []
Rs = []
for i in range(nfreq):
wl = np.append(wl, 1 / flux_freqs[i])
Rs = np.append(Rs, -final_refl_flux[i] / init_tran_flux[i])
sim.reset_meep()
#get = np.min(Rs)
en = enhance(Rs, 0)
get = en, Rs, wl
elif n == 2:
#if os.path.exists('dft_Z_fields.h5'):
#os.remove('dft_Z_fields.h5')
sim = mp.Simulation(cell_size=cell,
boundary_layers=pml_layers,
sources=sources,
geometry=geometry,
symmetries=[mp.Mirror(mp.X)],
dimensions=2,
resolution=resolution,
k_point=mp.Vector3())
refl = sim.add_flux(f_cen, df, nfreq, refl_fr)
tran = sim.add_flux(f_cen, df, nfreq, tran_fr)
sim.load_minus_flux_data(refl, init_refl_data)
dfts_Z = sim.add_dft_fields([mp.Ez],
fmin,
fmax,
nfreq,
where=mp.Volume(center=mp.Vector3(
0, -sy * 0.5 + dpml + thick * 0.5, 0),
size=mp.Vector3(sx,
thick)))
sim.run(mp.at_beginning(mp.output_epsilon),
until_after_sources=mp.stop_when_fields_decayed(
5, mp.Ez, mp.Vector3(),
1e-3)) #mp.at_beginning(mp.output_epsilon),
sim.output_dft(dfts_Z, "dft_Z_fields")
flux_freqs = mp.get_flux_freqs(refl)
final_refl_flux = mp.get_fluxes(refl)
final_tran_flux = mp.get_fluxes(tran)
wl = []
Rs = []
Ts = []
for i in range(nfreq):
wl = np.append(wl, 1 / flux_freqs[i])
Rs = np.append(Rs, -final_refl_flux[i] / init_tran_flux[i])
Ts = np.append(Ts, final_tran_flux[i] / init_tran_flux[i])
As = 1 - Rs - Ts
plt.clf()
plt.figure()
plt.plot(wl, Rs, 'bo-', label='reflectance')
plt.plot(wl, Ts, 'ro-', label='transmittance')
plt.plot(wl, As, 'go-', label='absorption')
plt.xlabel("wavelength (μm)")
plt.legend(loc="upper right")
plt.savefig('Extinction.png')
#get = np.min(Rs)
en = enhance(Rs, 1)
get = en, Rs, wl
#plt.figure()
#plt.plot(wl,Rs,'bo-',label='reflectance')
eps = h5py.File('_last-eps-000000000.h5', 'r')
eps = eps.get('eps').value
Enhance = np.rot90(eps)
plt.clf()
plt.figure()
heat_map = sb.heatmap(Enhance,
cmap='plasma',
xticklabels=False,
yticklabels=False)
plt.xlabel("x-axis")
plt.ylabel("y-axis")
plt.savefig('Epsilon.png')
return (get)
def main(args):
resolution = 20 # pixels/um
eps = 13 # dielectric constant of waveguide
w = 1.2 # width of waveguide
r = 0.36 # radius of holes
d = 1.4 # defect spacing (ordinary spacing = 1)
N = args.N # number of holes on either side of defect
sy = args.sy # size of cell in y direction (perpendicular to wvg.)
pad = 2 # padding between last hole and PML edge
dpml = 1 # PML thickness
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))))
fcen = args.fcen # pulse center frequency
df = args.df # pulse frequency width
nfreq = 500 # number of frequencies at which to compute flux
sim = mp.Simulation(cell_size=cell,
geometry=geometry,
sources=[],
boundary_layers=[mp.PML(dpml)],
resolution=20)
if args.resonant_modes:
sim.sources.append(mp.Source(mp.GaussianSource(fcen, fwidth=df),
component=mp.Hz,
center=mp.Vector3()))
sim.symmetries.append(mp.Mirror(mp.Y, phase=-1))
sim.symmetries.append(mp.Mirror(mp.X, phase=-1))
sim.run(mp.at_beginning(mp.output_epsilon),
mp.after_sources(mp.Harminv(mp.Hz, mp.Vector3(), fcen, df)),
until_after_sources=400)
sim.run(mp.at_every(1/fcen/20, mp.output_hfield_z), until=1/fcen)
else:
sim.sources.append(mp.Source(mp.GaussianSource(fcen, fwidth=df),
component=mp.Ey,
center=mp.Vector3(-0.5*sx+dpml),
size=mp.Vector3(0,w)))
sim.symmetries.append(mp.Mirror(mp.Y, phase=-1))
freg = mp.FluxRegion(center=mp.Vector3(0.5*sx-dpml-0.5),
size=mp.Vector3(0,2*w))
# transmitted flux
trans = sim.add_flux(fcen, df, nfreq, freg)
vol = mp.Volume(mp.Vector3(), size=mp.Vector3(sx))
sim.run(mp.at_beginning(mp.output_epsilon),
mp.during_sources(mp.in_volume(vol, mp.to_appended("hz-slice", mp.at_every(0.4, mp.output_hfield_z)))),
until_after_sources=mp.stop_when_fields_decayed(50, mp.Ey, mp.Vector3(0.5*sx-dpml-0.5), 1e-3))
sim.display_fluxes(trans) # print out the flux spectrum
def main(from_um_factor, resolution_wlen, courant, submerged_index,
displacement, surface_index, wlen_center, wlen_width, nfreq,
air_wlen_factor, pml_wlen_factor, flux_wlen_factor, time_factor_cell,
second_time_factor, series, folder, parallel, n_processes,
split_chunks_evenly):
#%% CLASSIC INPUT PARAMETERS
"""
# Simulation size
from_um_factor = 100e-3 # Conversion of 1 μm to my length unit (=100nm/1μm)
resolution_wlen = 20 # >=8 pixels per smallest wavelength, i.e. np.floor(8/wvl_min)
courant = 0.5
# Nanoparticle specifications: Sphere in Vacuum :)
paper = "R"
reference = "Meep"
displacement = 0 # Displacement of the surface from the bottom of the sphere in nm
submerged_index = 1.33 # 1.33 for water
surface_index = 1.54 # 1.54 for glass
# Frequency and wavelength
wlen_center = 650 # Main wavelength range in nm
wlen_width = 200 # Wavelength band in nm
nfreq = 100
# Box dimensions
pml_wlen_factor = 0.38
air_wlen_factor = 0.15
flux_wlen_factor = 0.1
# Simulation time
time_factor_cell = 1.2
second_time_factor = 10
# Saving directories
series = "1stTest"
folder = "Test/TestDipole/DipoleGlass"
# Configuration
parallel = False
n_processes = 1
split_chunks_evenly = True
"""
#%% MORE INPUT PARAMETERS
# Simulation size
resolution = (from_um_factor * 1e3) * resolution_wlen / (wlen_center +
wlen_width / 2)
resolution = int(np.ceil(resolution / 2)) * 2
# Frequency and wavelength
cutoff = 3.2 # Gaussian planewave source's parameter of shape
nazimuthal = 16
npolar = 20
### TREATED INPUT PARAMETERS
# Nanoparticle specifications: Sphere in Vacuum :)
displacement = displacement / (from_um_factor * 1e3) # Now in Meep units
# Frequency and wavelength
wlen_center = wlen_center / (from_um_factor * 1e3) # Now in Meep units
wlen_width = wlen_width / (from_um_factor * 1e3) # Now in Meep units
freq_center = 1 / wlen_center # Hz center frequency in Meep units
freq_width = 1 / wlen_width # Hz range in Meep units from highest to lowest
# Space configuration
pml_width = pml_wlen_factor * (wlen_center + wlen_width / 2
) # 0.5 * max(wlen_range)
air_width = air_wlen_factor * (wlen_center + wlen_width / 2)
flux_box_size = flux_wlen_factor * (wlen_center + wlen_width / 2)
# Computation
enlapsed = []
if parallel:
np_process = mp.count_processors()
else:
np_process = 1
# Saving directories
if series is None:
series = "Test"
if folder is None:
folder = "Test"
params_list = [
"from_um_factor", "resolution_wlen", "resolution", "courant",
"submerged_index", "displacement", "surface_index", "wlen_center",
"wlen_width", "cutoff", "nfreq", "nazimuthal", "npolar",
"flux_box_size", "cell_width", "pml_width", "air_width",
"until_after_sources", "time_factor_cell", "second_time_factor",
"enlapsed", "parallel", "n_processes", "split_chunks_evenly", "script",
"sysname", "path"
]
#%% GENERAL GEOMETRY SETUP
air_width = air_width - air_width % (1 / resolution)
pml_width = pml_width - pml_width % (1 / resolution)
pml_layers = [mp.PML(thickness=pml_width)]
# symmetries = [mp.Mirror(mp.Y),
# mp.Mirror(mp.Z, phase=-1)]
# Two mirror planes reduce cell size to 1/4
# Issue related that lead me to comment this lines:
# https://github.com/NanoComp/meep/issues/1484
cell_width = 2 * (pml_width + air_width)
cell_width = cell_width - cell_width % (1 / resolution)
cell_size = mp.Vector3(cell_width, cell_width, cell_width)
# surface_center = r/4 - displacement/2 + cell_width/4
# surface_center = surface_center - surface_center%(1/resolution)
# displacement = r/2 + cell_width/2 - 2*surface_center
displacement = displacement - displacement % (1 / resolution)
flux_box_size = flux_box_size - flux_box_size % (1 / resolution)
sources = [
mp.Source(mp.GaussianSource(freq_center,
fwidth=freq_width,
is_integrated=True,
cutoff=cutoff),
center=mp.Vector3(),
component=mp.Ez)
]
# Ez-polarized point pulse
# (its size parameter is null and it is centered at zero)
# >> The planewave source extends into the PML
# ==> is_integrated=True must be specified
until_after_sources = time_factor_cell * cell_width * submerged_index
# Enough time for the pulse to pass through all the cell
# Originally: Aprox 3 periods of lowest frequency, using T=λ/c=λ in Meep units
# Now: Aprox 3 periods of highest frequency, using T=λ/c=λ in Meep units
# if surface_index != 1:
# geometry = [mp.Block(material=mp.Medium(index=surface_index),
# center=mp.Vector3(
# - displacement/2 + cell_width/4,
# 0, 0),
# size=mp.Vector3(
# cell_width/2 + displacement,
# cell_width, cell_width))]
# else:
# geometry = []
# A certain material surface underneath it
home = vs.get_home()
sysname = vs.get_sys_name()
path = os.path.join(home, folder, series)
if not os.path.isdir(path) and vm.parallel_assign(0, n_processes,
parallel):
os.makedirs(path)
file = lambda f: os.path.join(path, f)
#%% BASE SIMULATION: SETUP
measure_ram()
params = {}
for p in params_list:
params[p] = eval(p)
sim = mp.Simulation(resolution=resolution,
cell_size=cell_size,
boundary_layers=pml_layers,
sources=sources,
k_point=mp.Vector3(),
Courant=courant,
default_material=mp.Medium(index=submerged_index),
output_single_precision=True,
split_chunks_evenly=split_chunks_evenly)
measure_ram()
near2far_box = sim.add_near2far(
freq_center, freq_width, nfreq,
mp.Near2FarRegion(center=mp.Vector3(x=-flux_box_size / 2),
size=mp.Vector3(0, flux_box_size, flux_box_size),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(x=+flux_box_size / 2),
size=mp.Vector3(0, flux_box_size, flux_box_size),
weight=+1),
mp.Near2FarRegion(center=mp.Vector3(y=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0, flux_box_size),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(y=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0, flux_box_size),
weight=+1),
mp.Near2FarRegion(center=mp.Vector3(z=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size, 0),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(z=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size, 0),
weight=+1))
measure_ram()
# used_ram.append(used_ram[-1])
#%% BASE SIMULATION: INITIALIZE
temp = time()
sim.init_sim()
enlapsed.append(time() - temp)
measure_ram()
#%% BASE SIMULATION: SIMULATION :D
step_ram_function = lambda sim: measure_ram()
temp = time()
sim.run(mp.at_beginning(step_ram_function),
mp.at_time(int(second_time_factor * until_after_sources / 2),
step_ram_function),
mp.at_end(step_ram_function),
until_after_sources=second_time_factor * until_after_sources)
# mp.stop_when_fields_decayed(
# np.mean(wlen_range), # dT = mean period of source
# mp.Ez, # Component of field to check
# mp.Vector3(0.5*cell_width - pml_width, 0, 0), # Where to check
# 1e-3)) # Factor to decay
enlapsed.append(time() - temp)
del temp
# Aprox 30 periods of lowest frequency, using T=λ/c=λ in Meep units
#%% BASE SIMULATION: ANGULAR PATTERN ANALYSIS
freqs = np.linspace(freq_center - freq_center / 2,
freq_center + freq_width / 2, nfreq)
wlens = 1 / freqs
# fraunhofer_distance = 8 * (r**2) / min(wlen_range)
# radial_distance = max( 10 * fraunhofer_distance , 1.5 * cell_width/2 )
# radius of far-field circle must be at least Fraunhofer distance
radial_distance = cell_width
azimuthal_angle = np.arange(0, 2 + 2 / nazimuthal,
2 / nazimuthal) # in multiples of pi
polar_angle = np.arange(0, 1 + 1 / npolar, 1 / npolar)
poynting_x = []
poynting_y = []
poynting_z = []
poynting_r = []
for phi in azimuthal_angle:
poynting_x.append([])
poynting_y.append([])
poynting_z.append([])
poynting_r.append([])
for theta in polar_angle:
farfield_dict = sim.get_farfields(
near2far_box,
1,
where=mp.Volume(center=mp.Vector3(
radial_distance * np.cos(np.pi * phi) *
np.sin(np.pi * theta),
radial_distance * np.sin(np.pi * phi) *
np.sin(np.pi *
theta), radial_distance * np.cos(np.pi * theta))))
Px = farfield_dict["Ey"] * np.conjugate(farfield_dict["Hz"])
Px -= farfield_dict["Ez"] * np.conjugate(farfield_dict["Hy"])
Py = farfield_dict["Ez"] * np.conjugate(farfield_dict["Hx"])
Py -= farfield_dict["Ex"] * np.conjugate(farfield_dict["Hz"])
Pz = farfield_dict["Ex"] * np.conjugate(farfield_dict["Hy"])
Pz -= farfield_dict["Ey"] * np.conjugate(farfield_dict["Hx"])
Px = np.real(Px)
Py = np.real(Py)
Pz = np.real(Pz)
poynting_x[-1].append(Px)
poynting_y[-1].append(Py)
poynting_z[-1].append(Pz)
poynting_r[-1].append(
np.sqrt(np.square(Px) + np.square(Py) + np.square(Pz)))
del phi, theta, farfield_dict, Px, Py, Pz
poynting_x = np.array(poynting_x)
poynting_y = np.array(poynting_y)
poynting_z = np.array(poynting_z)
poynting_r = np.array(poynting_r)
#%% BASE SIMULATION: SAVE DATA
for p in params_list:
params[p] = eval(p)
os.chdir(path)
sim.save_near2far("BaseNear2Far", near2far_box)
if vm.parallel_assign(0, np_process, parallel):
f = h5.File("BaseNear2Far.h5", "r+")
for key, par in params.items():
f[list(f.keys())[0]].attrs[key] = par
f.close()
del f
os.chdir(syshome)
if vm.parallel_assign(1, np_process, parallel):
f = h5.File(file("BaseResults.h5"), "w")
f["Px"] = poynting_x
f["Py"] = poynting_y
f["Pz"] = poynting_z
f["Pr"] = poynting_r
for dset in f.values():
for key, par in params.items():
dset.attrs[key] = par
f.close()
del f
# if not split_chunks_evenly:
# vm.save_chunks(sim, params, path)
if parallel:
f = h5.File(file("BaseRAM.h5"),
"w",
driver='mpio',
comm=MPI.COMM_WORLD)
current_process = mp.my_rank()
f.create_dataset("RAM", (len(used_ram), np_process), dtype="float")
f["RAM"][:, current_process] = used_ram
for a in params:
f["RAM"].attrs[a] = params[a]
f.create_dataset("SWAP", (len(used_ram), np_process), dtype="int")
f["SWAP"][:, current_process] = swapped_ram
for a in params:
f["SWAP"].attrs[a] = params[a]
else:
f = h5.File(file("BaseRAM.h5"), "w")
f.create_dataset("RAM", data=used_ram)
for a in params:
f["RAM"].attrs[a] = params[a]
f.create_dataset("SWAP", data=swapped_ram)
for a in params:
f["SWAP"].attrs[a] = params[a]
f.close()
del f
sim.reset_meep()
#%% FURTHER SIMULATION
if surface_index != 1:
#% FURTHER SIMULATION: SETUP
measure_ram()
params = {}
for p in params_list:
params[p] = eval(p)
sim = mp.Simulation(resolution=resolution,
cell_size=cell_size,
boundary_layers=pml_layers,
sources=sources,
k_point=mp.Vector3(),
Courant=courant,
default_material=mp.Medium(index=surface_index),
output_single_precision=True,
split_chunks_evenly=split_chunks_evenly)
measure_ram()
near2far_box = sim.add_near2far(
freq_center, freq_width, nfreq,
mp.Near2FarRegion(center=mp.Vector3(x=-flux_box_size / 2),
size=mp.Vector3(0, flux_box_size, flux_box_size),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(x=+flux_box_size / 2),
size=mp.Vector3(0, flux_box_size, flux_box_size),
weight=+1),
mp.Near2FarRegion(center=mp.Vector3(y=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0, flux_box_size),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(y=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, 0, flux_box_size),
weight=+1),
mp.Near2FarRegion(center=mp.Vector3(z=-flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size, 0),
weight=-1),
mp.Near2FarRegion(center=mp.Vector3(z=+flux_box_size / 2),
size=mp.Vector3(flux_box_size, flux_box_size, 0),
weight=+1))
measure_ram()
# used_ram.append(used_ram[-1])
#% FURTHER SIMULATION: INITIALIZE
temp = time()
sim.init_sim()
enlapsed.append(time() - temp)
measure_ram()
#% FURTHER SIMULATION: SIMULATION :D
step_ram_function = lambda sim: measure_ram()
temp = time()
sim.run(mp.at_beginning(step_ram_function),
mp.at_time(int(second_time_factor * until_after_sources / 2),
step_ram_function),
mp.at_end(step_ram_function),
until_after_sources=second_time_factor * until_after_sources)
# mp.stop_when_fields_decayed(
# np.mean(wlen_range), # dT = mean period of source
# mp.Ez, # Component of field to check
# mp.Vector3(0.5*cell_width - pml_width, 0, 0), # Where to check
# 1e-3)) # Factor to decay
enlapsed.append(time() - temp)
del temp
# Aprox 30 periods of lowest frequency, using T=λ/c=λ in Meep units
#% FURTHER SIMULATION: ANGULAR PATTERN ANALYSIS
poynting_x2 = []
poynting_y2 = []
poynting_z2 = []
poynting_r2 = []
for phi in azimuthal_angle:
poynting_x2.append([])
poynting_y2.append([])
poynting_z2.append([])
poynting_r2.append([])
for theta in polar_angle:
farfield_dict = sim.get_farfields(
near2far_box,
1,
where=mp.Volume(center=mp.Vector3(
radial_distance * np.cos(np.pi * phi) *
np.sin(np.pi * theta),
radial_distance * np.sin(np.pi * phi) *
np.sin(np.pi *
theta), radial_distance *
np.cos(np.pi * theta))))
Px = farfield_dict["Ey"] * np.conjugate(farfield_dict["Hz"])
Px -= farfield_dict["Ez"] * np.conjugate(farfield_dict["Hy"])
Py = farfield_dict["Ez"] * np.conjugate(farfield_dict["Hx"])
Py -= farfield_dict["Ex"] * np.conjugate(farfield_dict["Hz"])
Pz = farfield_dict["Ex"] * np.conjugate(farfield_dict["Hy"])
Pz -= farfield_dict["Ey"] * np.conjugate(farfield_dict["Hx"])
Px = np.real(Px)
Py = np.real(Py)
Pz = np.real(Pz)
poynting_x2[-1].append(Px)
poynting_y2[-1].append(Py)
poynting_z2[-1].append(Pz)
poynting_r2[-1].append(
np.sqrt(np.square(Px) + np.square(Py) + np.square(Pz)))
del phi, theta, farfield_dict, Px, Py, Pz
poynting_x2 = np.array(poynting_x2)
poynting_y2 = np.array(poynting_y2)
poynting_z2 = np.array(poynting_z2)
poynting_r2 = np.array(poynting_r2)
#% FURTHER SIMULATION: SAVE DATA
for p in params_list:
params[p] = eval(p)
os.chdir(path)
sim.save_near2far("FurtherNear2Far", near2far_box)
if vm.parallel_assign(0, np_process, parallel):
f = h5.File("FurtherNear2Far.h5", "r+")
for key, par in params.items():
f[list(f.keys())[0]].attrs[key] = par
f.close()
del f
os.chdir(syshome)
if vm.parallel_assign(1, np_process, parallel):
f = h5.File(file("FurtherResults.h5"), "w")
f["Px"] = poynting_x2
f["Py"] = poynting_y2
f["Pz"] = poynting_z2
f["Pr"] = poynting_r2
for dset in f.values():
for key, par in params.items():
dset.attrs[key] = par
f.close()
del f
# if not split_chunks_evenly:
# vm.save_chunks(sim, params, path)
if parallel:
f = h5.File(file("FurtherRAM.h5"),
"w",
driver='mpio',
comm=MPI.COMM_WORLD)
current_process = mp.my_rank()
f.create_dataset("RAM", (len(used_ram), np_process), dtype="float")
f["RAM"][:, current_process] = used_ram
for a in params:
f["RAM"].attrs[a] = params[a]
f.create_dataset("SWAP", (len(used_ram), np_process), dtype="int")
f["SWAP"][:, current_process] = swapped_ram
for a in params:
f["SWAP"].attrs[a] = params[a]
else:
f = h5.File(file("FurtherRAM.h5"), "w")
f.create_dataset("RAM", data=used_ram)
for a in params:
f["RAM"].attrs[a] = params[a]
f.create_dataset("SWAP", data=swapped_ram)
for a in params:
f["SWAP"].attrs[a] = params[a]
f.close()
del f
#%% NORMALIZE AND REARANGE DATA
if surface_index != 1:
max_poynting_r = np.max(
[np.max(np.abs(poynting_r)),
np.max(np.abs(poynting_r2))])
else:
max_poynting_r = np.max(np.abs(poynting_r))
poynting_x = np.array(poynting_x) / max_poynting_r
poynting_y = np.array(poynting_y) / max_poynting_r
poynting_z = np.array(poynting_z) / max_poynting_r
poynting_r = np.array(poynting_r) / max_poynting_r
if surface_index != 1:
poynting_x0 = np.array(poynting_x)
poynting_y0 = np.array(poynting_y)
poynting_z0 = np.array(poynting_z)
poynting_r0 = np.array(poynting_r)
poynting_x2 = np.array(poynting_x2) / max_poynting_r
poynting_y2 = np.array(poynting_y2) / max_poynting_r
poynting_z2 = np.array(poynting_z2) / max_poynting_r
poynting_r2 = np.array(poynting_r2) / max_poynting_r
#%%
"""
poynting_x = np.array(poynting_x0)
poynting_y = np.array(poynting_y0)
poynting_z = np.array(poynting_z0)
poynting_r = np.array(poynting_r0)
"""
if surface_index != 1:
polar_limit = np.arcsin(displacement / radial_distance) + .5
for i in range(len(polar_angle)):
if polar_angle[i] > polar_limit:
index_limit = i
break
poynting_x[:, index_limit:, :] = poynting_x2[:, index_limit:, :]
poynting_y[:, index_limit:, :] = poynting_y2[:, index_limit:, :]
poynting_z[:, index_limit:, :] = poynting_z2[:, index_limit:, :]
poynting_r[:, index_limit:, :] = poynting_r2[:, index_limit:, :]
poynting_x[:, index_limit - 1, :] = np.array([[
np.mean([p2, p0]) for p2, p0 in zip(poy2, poy0)
] for poy2, poy0 in zip(poynting_x2[:, index_limit -
1, :], poynting_x0[:, index_limit -
1, :])])
poynting_y[:, index_limit - 1, :] = np.array([[
np.mean([p2, p0]) for p2, p0 in zip(poy2, poy0)
] for poy2, poy0 in zip(poynting_y2[:, index_limit -
1, :], poynting_y0[:, index_limit -
1, :])])
poynting_z[:, index_limit - 1, :] = np.array([[
np.mean([p2, p0]) for p2, p0 in zip(poy2, poy0)
] for poy2, poy0 in zip(poynting_z2[:, index_limit -
1, :], poynting_z0[:, index_limit -
1, :])])
poynting_r[:, index_limit - 1, :] = np.sqrt(
np.squared(poynting_x[:, index_limit - 1, :]) +
np.squared(poynting_y[:, index_limit - 1, :]) +
np.squared(poynting_y[:, index_limit - 1, :]))
#%% SAVE FINAL DATA
if surface_index != 1 and vm.parallel_assign(0, np_process, parallel):
os.remove(file("BaseRAM.h5"))
os.rename(file("FurtherRAM.h5"), file("RAM.h5"))
elif vm.parallel_assign(0, np_process, parallel):
os.rename(file("BaseRAM.h5"), file("RAM.h5"))
#%% PLOT ANGULAR PATTERN IN 3D
if vm.parallel_assign(1, np_process, parallel):
freq_index = np.argmin(np.abs(freqs - freq_center))
fig = plt.figure()
plt.suptitle(
f'Angular Pattern of point dipole molecule at {from_um_factor * 1e3 * wlen_center:.0f} nm'
)
ax = fig.add_subplot(1, 1, 1, projection='3d')
ax.plot_surface(poynting_x[:, :, freq_index],
poynting_y[:, :, freq_index],
poynting_z[:, :, freq_index],
cmap=plt.get_cmap('jet'),
linewidth=1,
antialiased=False,
alpha=0.5)
ax.set_xlabel(r"$P_x$")
ax.set_ylabel(r"$P_y$")
ax.set_zlabel(r"$P_z$")
plt.savefig(file("AngularPattern.png"))
#%% PLOT ANGULAR PATTERN PROFILE FOR DIFFERENT POLAR ANGLES
if vm.parallel_assign(0, np_process, parallel):
freq_index = np.argmin(np.abs(freqs - freq_center))
index = [
list(polar_angle).index(alpha) for alpha in [0, .25, .5, .75, 1]
]
plt.figure()
plt.suptitle(
f'Angular Pattern of point dipole molecule at {from_um_factor * 1e3 * wlen_center:.0f} nm'
)
ax_plain = plt.axes()
for i in index:
ax_plain.plot(poynting_x[:, i, freq_index],
poynting_y[:, i, freq_index],
".-",
label=rf"$\theta$ = {polar_angle[i]:.2f} $\pi$")
plt.legend()
ax_plain.set_xlabel(r"$P_x$")
ax_plain.set_ylabel(r"$P_y$")
ax_plain.set_aspect("equal")
plt.savefig(file("AngularPolar.png"))
#%% PLOT ANGULAR PATTERN PROFILE FOR DIFFERENT AZIMUTHAL ANGLES
if vm.parallel_assign(1, np_process, parallel):
freq_index = np.argmin(np.abs(freqs - freq_center))
index = [
list(azimuthal_angle).index(alpha)
for alpha in [0, .25, .5, .75, 1, 1.25, 1.5, 1.75, 2]
]
plt.figure()
plt.suptitle(
f'Angular Pattern of point dipole molecule at {from_um_factor * 1e3 * wlen_center:.0f} nm'
)
ax_plain = plt.axes()
for i in index:
ax_plain.plot(poynting_x[i, :, freq_index],
poynting_z[i, :, freq_index],
".-",
label=rf"$\phi$ = {azimuthal_angle[i]:.2f} $\pi$")
plt.legend()
ax_plain.set_xlabel(r"$P_x$")
ax_plain.set_ylabel(r"$P_z$")
plt.savefig(file("AngularAzimuthal.png"))
if vm.parallel_assign(0, np_process, parallel):
freq_index = np.argmin(np.abs(freqs - freq_center))
index = [
list(azimuthal_angle).index(alpha)
for alpha in [0, .25, .5, .75, 1, 1.25, 1.5, 1.75, 2]
]
plt.figure()
plt.suptitle(
f'Angular Pattern of point dipole molecule at {from_um_factor * 1e3 * wlen_center:.0f} nm'
)
ax_plain = plt.axes()
for i in index:
ax_plain.plot(np.sqrt(
np.square(poynting_x[i, :, freq_index]) +
np.square(poynting_y[i, :, freq_index])),
poynting_z[i, :, freq_index],
".-",
label=rf"$\phi$ = {azimuthal_angle[i]:.2f} $\pi$")
plt.legend()
ax_plain.set_xlabel(r"$P_\rho$")
ax_plain.set_ylabel(r"$P_z$")
plt.savefig(file("AngularAzimuthalAbs.png"))
def main(args):
# Some parameters to describe the geometry:
eps = 13 # dielectric constant of waveguide
w = 1.2 # width of waveguide
r = 0.36 # radius of holes
d = 1.4 # defect spacing (ordinary spacing = 1)
N = args.N # number of holes on either side of defect
# The cell dimensions
sy = args.sy # size of cell in y direction (perpendicular to wvg.)
pad = 2 # padding between last hole and PML edge
dpml = 1 # PML thickness
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))))
fcen = args.fcen # pulse center frequency
df = args.df # pulse frequency width
nfreq = 500 # number of frequencies at which to compute flux
sim = mp.Simulation(cell_size=cell,
geometry=geometry,
sources=[],
boundary_layers=[mp.PML(dpml)],
resolution=20)
if args.resonant_modes:
sim.sources.append(
mp.Source(mp.GaussianSource(fcen, fwidth=df), mp.Hz, mp.Vector3()))
sim.symmetries.append(mp.Mirror(mp.Y, phase=-1))
sim.symmetries.append(mp.Mirror(mp.X, phase=-1))
sim.run( # mp.at_beginning(mp.output_epsilon),
mp.after_sources(mp.Harminv(mp.Hz, mp.Vector3(), fcen, df)),
until_after_sources=400)
# sim.run(mp.at_every(1 / fcen / 20, mp.output_hfield_z), until=1 / fcen)
else:
sim.sources.append(
mp.Source(mp.GaussianSource(fcen, fwidth=df),
mp.Ey,
mp.Vector3(dpml + (-0.5 * sx)),
size=mp.Vector3(0, w)))
sim.symmetries.append(mp.Mirror(mp.Y, phase=-1))
freg = mp.FluxRegion(center=mp.Vector3((0.5 * sx) - dpml - 0.5),
size=mp.Vector3(0, 2 * w))
# transmitted flux
trans = sim.add_flux(fcen, df, nfreq, freg)
vol = mp.Volume(mp.Vector3(), size=mp.Vector3(sx))
sim.run(mp.at_beginning(mp.output_epsilon),
mp.during_sources(
mp.in_volume(
vol,
mp.to_appended("hz-slice",
mp.at_every(0.4, mp.output_hfield_z)))),
until_after_sources=mp.stop_when_fields_decayed(
50, mp.Ey, mp.Vector3((0.5 * sx) - dpml - 0.5, 0), 1e-3))
sim.display_fluxes(trans) # print out the flux spectrum
def generate_model(params, args):
cell = mp.Vector3(params.cell_width, params.cell_height, 0)
spheres = mplib.geo2D_spherical_pc(params.ps_n, params.si_n,
params.ps_thickness, params.si_thickness, params.cell_height, params.num_layers,
params.cell_width/2-200, params.sph_radius,
params.sph_spacing, params.offset, params.xoffset)
thin_film = mplib.geo2D_thin_film(params.ps_n, params.ps_thickness, params.cell_height,
params.cell_width/2-100)
pc_ideal = mplib.geo2D_photonic_crystal(params.ps_n, params.other_n,
params.ps_thickness, params.cell_height,
params.si_thickness, params.si_n,
5, params.cell_width/2-200, 50)
geometry = pc_ideal
if args.background:
geometry = []
## Gaussian source
source_pos = -1*params.cell_width/2 + params.dpml+5
sources = [mp.Source(mp.GaussianSource(frequency=params.freq, fwidth=params.df),
mp.Ez, center=mp.Vector3(source_pos,0,0),
size=mp.Vector3(0,params.cell_height,0))]
pml_layers = [mp.PML(params.dpml, direction=mp.X)]
sim = mp.Simulation(cell_size = cell,
boundary_layers = pml_layers,
geometry = geometry,
filename_prefix=args.filename,
sources = sources,
k_point = mp.Vector3(0,0,0),
resolution = params.resolution)
freg_trans = mp.FluxRegion(center = mp.Vector3(0.5*params.cell_width - params.dpml - 1,0,0),
size = mp.Vector3(0, params.cell_height, 0))
freg_ref = mp.FluxRegion(center = mp.Vector3(source_pos + 10, 0, 0),
size = mp.Vector3(0, params.cell_height), weight=1.0)
trans_flux = sim.add_flux(params.freq, params.df , 500, freg_trans)
ref_flux = sim.add_flux(params.freq, params.df, 500, freg_ref)
vol = mp.Volume(mp.Vector3(0), size = mp.Vector3(params.cell_width,0,0))
if not args.reflectflux:
sim.load_minus_flux("pulse_bg_flux_{:d}".format(params.wavelength),ref_flux)
if args.outdir:
print("Output directory: {:s}".format(args.outdir))
sim.use_output_directory(args.outdir)
if args.geometry:
sim.run(mp.at_beginning(mp.output_epsilon),
until=1)
else:
sim.run(mp.at_beginning(mp.output_epsilon),
mp.to_appended("ez", mp.at_every(params.dt, mp.output_efield_z)),
#mp.to_appended("ep", mp.at_every(params.dt, mp.output_dpwr)),
mp.in_volume(vol, mp.to_appended("ez_slice", mp.at_every(params.dt, mp.output_efield_z))),
until=params.time)
if args.reflectflux:
sim.save_flux("pulse_bg_flux_{:d}".format(params.wavelength),ref_flux)
#sim.save_flux("bg_flux_other", trans_flux)
sim.display_fluxes(trans_flux, ref_flux)
import meep as mp
cell_size = mp.Vector3(6, 6, 0)
geometry1 = [
mp.Cylinder(center=mp.Vector3(), radius=1.0, material=mp.Medium(index=3.5))
]
sim1 = mp.Simulation(cell_size=cell_size, geometry=geometry1, resolution=20)
sim1.init_sim()
geometry2 = [
mp.Cylinder(center=mp.Vector3(1, 1),
radius=1.0,
material=mp.Medium(index=3.5))
]
sim2 = mp.Simulation(cell_size=cell_size, geometry=geometry2, resolution=20)
sim2.init_sim()
sim1.fields.phase_in_material(sim2.structure, 10.0)
sim1.run(mp.at_beginning(mp.output_epsilon),
mp.at_every(0.5, mp.output_epsilon),
until=10)
def simulate(self, config):
start = time.time()
dpml = config["dpml"]
resolution = config["resolution"]
use_fixed_time = config["use_fixed_time"]
simulation_time = config["simulation_time"]
padding = config["padding"]
ff_pts = config["ff_pts"]
ff_cover = config["ff_cover"]
ff_calc = config["ff_calc"]
use_symmetries = config["use_symmetries"]
calculate_flux = config["calculate_flux"]
calculate_source_flux = config["calculate_source_flux"]
pixels = config["source_flux_pixel_size"]
ff_calculations = config["ff_calculations"]
ff_angle = math.pi / config["ff_angle"]
FibonacciSampling = config["fibb_sampling"]
simulation_ratio = eval(config["simulation_ratio"])
substrate_ratio = eval(config["substrate_ratio"])
output_ff = config["output_ff"]
polarization_in_plane = config["polarization_in_plane"]
geometry = config["geometry"]
material_function = config["material_function"]
substrate_height = self.pyramid_height * substrate_ratio #height of the substrate, measured as fraction of pyramid height
#"Cell size"
sx = self.pyramid_width * simulation_ratio #size of the cell in xy-plane is measured as a fraction of pyramid width
sy = sx
sz = self.pyramid_height * simulation_ratio #z-"height" of sim. cell measured as a fraction of pyramid height.
sh = substrate_height
sh = 0
padding = padding ##distance from pml_layers to flux regions so PML don't overlap flux regions
cell = mp.Vector3(sx + 2 * dpml, sy + 2 * dpml, sz +
2 * dpml) #size of the simulation cell in meep units
if self.CL_material == "Au":
CL_material = Au
elif self.CL_material == "Ag":
CL_material = Ag
elif self.CL_material == "Ag_visible":
CL_material = Ag_visible
else:
CL_material = GaN
print('CL MATERIAL:', CL_material, self.CL_material)
#Symmetries for the simulation
def create_symmetry(self):
if self.source_direction == mp.Ex or self.source_direction == [
1, 0, 0
]:
symmetry = [mp.Mirror(mp.Y), mp.Mirror(mp.X, phase=-1)]
elif self.source_direction == mp.Ey or self.source_direction == [
0, 1, 0
]:
symmetry = [mp.Mirror(mp.X), mp.Mirror(mp.Y, phase=-1)]
elif self.source_direction == mp.Ez or self.source_direction == [
0, 0, 1
]:
symmetry = [mp.Mirror(mp.X), mp.Mirror(mp.Y)]
else:
symmetry = []
return symmetry
#Flux regions to calculate the total flux emitted from the simulation
def define_flux_regions(sx, sy, sz, padding):
fluxregion = []
fluxregion.append(
mp.FluxRegion( #region x to calculate flux from
center=mp.Vector3(sx / 2 - padding, 0, 0),
size=mp.Vector3(0, sy - padding * 2, sz - padding * 2),
direction=mp.X))
fluxregion.append(
mp.FluxRegion( # region -x to calculate flux from
center=mp.Vector3(-sx / 2 + padding, 0, 0),
size=mp.Vector3(0, sy - padding * 2, sz - padding * 2),
direction=mp.X,
weight=-1))
fluxregion.append(
mp.FluxRegion( #region y to calculate flux from
center=mp.Vector3(0, sy / 2 - padding, 0),
size=mp.Vector3(sx - padding * 2, 0, sz - padding * 2),
direction=mp.Y))
fluxregion.append(
mp.FluxRegion( #region -y to calculate flux from
center=mp.Vector3(0, -sy / 2 + padding, 0),
size=mp.Vector3(sx - padding * 2, 0, sz - padding * 2),
direction=mp.Y,
weight=-1))
fluxregion.append(
mp.FluxRegion( #z-bottom region to calculate flux from
center=mp.Vector3(0, 0, sz / 2 - padding),
size=mp.Vector3(sx - padding * 2, sy - padding * 2, 0),
direction=mp.Z))
fluxregion.append(
mp.FluxRegion( #z-top region to calculate flux from
center=mp.Vector3(0, 0, -sz / 2 + padding),
size=mp.Vector3(sx - padding * 2, sy - padding * 2, 0),
direction=mp.Z,
weight=-1))
return fluxregion
#Flux regions to calculate the far field flux
def define_nearfield_regions(sx, sy, sz, sh, padding, ff_cover):
nearfieldregions = []
nfrAbove = []
nfrBelow = []
#if ff_calc == True:
#If we wish to calculate the far-field above and below the pyramid
# if ff_calc == "Both":
nfrAbove.append(
mp.Near2FarRegion(center=mp.Vector3(sx / 2 - padding, 0,
-sh / 2),
size=mp.Vector3(0, sy - padding * 2,
sz - sh - padding * 2),
direction=mp.X))
nfrAbove.append(
mp.Near2FarRegion(center=mp.Vector3(-sx / 2 + padding, 0,
-sh / 2),
size=mp.Vector3(0, sy - padding * 2,
sz - sh - padding * 2),
direction=mp.X,
weight=-1))
nfrAbove.append(
mp.Near2FarRegion(center=mp.Vector3(0, sy / 2 - padding,
-sh / 2),
size=mp.Vector3(sx - padding * 2, 0,
sz - sh - padding * 2),
direction=mp.Y))
nfrAbove.append(
mp.Near2FarRegion(center=mp.Vector3(0, -sy / 2 + padding,
-sh / 2),
size=mp.Vector3(sx - padding * 2, 0,
sz - sh - padding * 2),
direction=mp.Y,
weight=-1))
nfrAbove.append(
mp.Near2FarRegion( #nearfield -z. above pyramid.
center=mp.Vector3(0, 0, -sz / 2 + padding),
size=mp.Vector3(sx - padding * 2, sy - padding * 2, 0),
direction=mp.Z,
weight=-1))
#Far-field to calculate below transmissions
nfrBelow.append(
mp.Near2FarRegion(center=mp.Vector3(sx / 2 - padding, 0,
sz / 2 - sh / 2),
size=mp.Vector3(0, sy - padding * 2,
sh - padding * 2),
direction=mp.X))
nfrBelow.append(
mp.Near2FarRegion(center=mp.Vector3(-sx / 2 + padding, 0,
sz / 2 - sh / 2),
size=mp.Vector3(0, sy - padding * 2,
sh - padding * 2),
direction=mp.X,
weight=-1))
nfrBelow.append(
mp.Near2FarRegion(center=mp.Vector3(0, sy / 2 - padding,
sz / 2 - sh / 2),
size=mp.Vector3(sx - padding * 2, 0,
sh - padding * 2),
direction=mp.Y))
nfrBelow.append(
mp.Near2FarRegion(center=mp.Vector3(0, -sy / 2 + padding,
sz / 2 - sh / 2),
size=mp.Vector3(sx - padding * 2, 0,
sh - padding * 2),
direction=mp.Y,
weight=-1))
nfrBelow.append(
mp.Near2FarRegion(center=mp.Vector3(0, 0, sz / 2 - padding),
size=mp.Vector3(sx - padding * 2,
sy - padding * 2, 0),
direction=mp.Z))
if ff_cover == True:
nfrAbove.append(
mp.Near2FarRegion(center=mp.Vector3(
0, 0, sz / 2 - padding),
size=mp.Vector3(sx - padding * 2,
sy - padding * 2, 0),
direction=mp.Z))
nfrBelow.append(
mp.Near2FarRegion(center=mp.Vector3(
0, 0, -sz / 2 - padding),
size=mp.Vector3(sx - padding * 2,
sy - padding * 2, 0),
direction=mp.Z,
weight=-1))
nearfieldregions.append(nfrAbove)
nearfieldregions.append(nfrBelow)
return nearfieldregions
###GEOMETRY FOR THE SIMULATION#################################################
#"Material parameters"
air = mp.Medium(epsilon=1) #air dielectric value
SubstrateEps = GaN #substrate epsilon
#"Geometry to define the substrate and block of air to truncate the pyramid if self.truncation =/= 0"
geometries = []
#Substrate
geometries.append(
mp.Sphere(center=mp.Vector3(0, 0, self.distance / 2 + self.radius),
radius=self.radius,
material=CL_material))
geometries.append(
mp.Sphere(center=mp.Vector3(0, 0,
-self.distance / 2 - self.radius),
radius=self.radius,
material=CL_material))
if geometry == None:
geometries = []
if material_function == None:
material_function = None
###SYMMETRIES#########################################################
#"Symmetry logic."
if use_symmetries:
symmetry = create_symmetry(self)
print('symmetry on:', symmetry)
else:
symmetry = []
###PML_LAYERS###################################################################
pml_layer = [mp.PML(dpml)]
###SOURCE#######################################################################
#"A gaussian with pulse source proportional to exp(-iwt-(t-t_0)^2/(2w^2))"
abs_source_position_x = 0
abs_source_position_y = 0
abs_source_position_z = 0
source = [
mp.Source(
mp.GaussianSource(
frequency=self.frequency_center,
fwidth=self.frequency_width,
cutoff=self.cutoff), #gaussian current-source
component=mp.Ez,
amplitude=1,
center=mp.Vector3(abs_source_position_x, abs_source_position_y,
abs_source_position_z))
]
#source.append(mp.Source(mp.GaussianSource(frequency=self.frequency_center,fwidth=self.frequency_width, cutoff=self.cutoff), #gaussian current-source
# component=mp.Ey,
# amplitude=self.source_direction[1],
# center=mp.Vector3(abs_source_position_x,abs_source_position_y,abs_source_position_z)))
#source.append(mp.Source(mp.GaussianSource(frequency=self.frequency_center,fwidth=self.frequency_width, cutoff=self.cutoff), #gaussian current-source
# component=mp.Ez,
# amplitude=self.source_direction[2],
# center=mp.Vector3(abs_source_position_x,abs_source_position_y,abs_source_position_z)))
#MEEP simulation constructor
sim = mp.Simulation(
cell_size=cell,
geometry=geometries,
symmetries=symmetry,
sources=source,
#eps_averaging=True,
#subpixel_tol=1e-4,
#subpixel_maxeval=1000,
dimensions=3,
#default_material=GaN,
Courant=0.1,
extra_materials=[CL_material],
boundary_layers=pml_layer,
split_chunks_evenly=False,
resolution=resolution)
###SOURCE REGION###################################################
print('pixels', pixels)
def define_flux_source_regions(abs_source_position_x,
abs_source_position_y,
abs_source_position_z, resolution,
pixels):
distance = pixels * 1 / resolution
source_region = []
source_region.append(
mp.FluxRegion( #region x to calculate flux from
center=mp.Vector3(abs_source_position_x + distance,
abs_source_position_y,
abs_source_position_z),
size=mp.Vector3(0, 2 * pixels * 1 / resolution,
2 * pixels * 1 / resolution),
direction=mp.X))
source_region.append(
mp.FluxRegion( # region -x to calculate flux from
center=mp.Vector3(abs_source_position_x - distance,
abs_source_position_y,
abs_source_position_z),
size=mp.Vector3(0, 2 * pixels * 1 / resolution,
2 * pixels * 1 / resolution),
direction=mp.X,
weight=-1))
source_region.append(
mp.FluxRegion( #region y to calculate flux from
center=mp.Vector3(abs_source_position_x,
abs_source_position_y + distance,
abs_source_position_z),
size=mp.Vector3(2 * pixels * 1 / resolution, 0,
2 * pixels * 1 / resolution),
direction=mp.Y))
source_region.append(
mp.FluxRegion( #region -y to calculate flux from
center=mp.Vector3(abs_source_position_x,
abs_source_position_y - distance,
abs_source_position_z),
size=mp.Vector3(2 * pixels * 1 / resolution, 0,
2 * pixels * 1 / resolution),
direction=mp.Y,
weight=-1))
source_region.append(
mp.FluxRegion( #z-bottom region to calculate flux from
center=mp.Vector3(abs_source_position_x,
abs_source_position_y,
abs_source_position_z + distance),
size=mp.Vector3(2 * pixels * 1 / resolution,
2 * pixels * 1 / resolution, 0),
direction=mp.Z))
source_region.append(
mp.FluxRegion( #z-top region to calculate flux from
center=mp.Vector3(abs_source_position_x,
abs_source_position_y,
abs_source_position_z - distance),
size=mp.Vector3(2 * pixels * 1 / resolution,
2 * pixels * 1 / resolution, 0),
direction=mp.Z,
weight=-1))
return source_region
###REGIONS######################################################################
#"These regions define the borders of the cell with distance 'padding' between the flux region and the dpml region to avoid calculation errors."
if calculate_flux:
flux_regions = define_flux_regions(sx, sy, sz, padding)
fr1, fr2, fr3, fr4, fr5, fr6 = flux_regions
flux_total = sim.add_flux(self.frequency_center,
self.frequency_width,
self.number_of_freqs, fr1, fr2, fr3, fr4,
fr5,
fr6) #calculate flux for flux regions
if calculate_source_flux:
sr1, sr2, sr3, sr4, sr5, sr6 = define_flux_source_regions(
abs_source_position_x, abs_source_position_y,
abs_source_position_z, resolution, pixels)
flux_source = sim.add_flux(self.frequency_center,
self.frequency_width,
self.number_of_freqs, sr1, sr2, sr3,
sr4, sr5, sr6)
###FAR FIELD REGION#############################################################
#"The simulation calculates the far field flux from the regions 1-5 below. It correspons to the air above and at the side of the pyramids. The edge of the simulation cell that touches the substrate is not added to this region. Far-field calculations can not handle different materials."
if ff_calculations == True:
nearfieldregions = define_nearfield_regions(
sx, sy, sz, sh, padding, ff_cover)
if ff_cover == True:
nfrA1, nfrA2, nfrA3, nfrA4, nfrA5, nfrA6 = nearfieldregions[0]
nfrB1, nfrB2, nfrB3, nfrB4, nfrB5, nfrB6 = nearfieldregions[1]
else:
nfrA1, nfrA2, nfrA3, nfrA4, nfrA6 = nearfieldregions[0]
nfrB1, nfrB2, nfrB3, nfrB4, nfrB6 = nearfieldregions[1]
if ff_calc == "Both" and ff_cover == True:
nearfieldAbove = sim.add_near2far(self.frequency_center,
self.frequency_width,
self.number_of_freqs, nfrA1,
nfrA2, nfrA3, nfrA4, nfrA5,
nfrA6)
nearfieldBelow = sim.add_near2far(self.frequency_center,
self.frequency_width,
self.number_of_freqs, nfrB1,
nfrB2, nfrB3, nfrB4, nfrB5,
nfrB6)
elif ff_calc == "Above" and ff_cover == True:
nearfieldAbove = sim.add_near2far(self.frequency_center,
self.frequency_width,
self.number_of_freqs, nfrA1,
nfrA2, nfrA3, nfrA4, nfrA5,
nfrA6)
elif ff_calc == "Above" and ff_cover == False:
nearfieldAbove = sim.add_near2far(self.frequency_center,
self.frequency_width,
self.number_of_freqs, nfrA1,
nfrA2, nfrA3, nfrA4, nfrA6)
elif ff_calc == "Below" and ff_cover == True:
nearfieldBelow = sim.add_near2far(self.frequency_center,
self.frequency_width,
self.number_of_freqs, nfrB1,
nfrB2, nfrB3, nfrB4, nfrB5,
nfrB6)
elif ff_calc == "Below" and ff_cover == False:
nearfieldBelow = sim.add_near2far(self.frequency_center,
self.frequency_width,
self.number_of_freqs, nfrB1,
nfrB2, nfrB3, nfrB4, nfrB6)
#Assumed ff_calc == Both and ff_cover == False
else:
nearfieldAbove = sim.add_near2far(self.frequency_center,
self.frequency_width,
self.number_of_freqs, nfrA1,
nfrA2, nfrA3, nfrA4, nfrA6)
nearfieldBelow = sim.add_near2far(self.frequency_center,
self.frequency_width,
self.number_of_freqs, nfrB1,
nfrB2, nfrB3, nfrB4, nfrB6)
###RUN##########################################################################
#"Run the simulation"
if True:
sim.plot2D(output_plane=mp.Volume(
center=mp.Vector3(0, 0 * abs_source_position_y, 0),
size=mp.Vector3(0, sy + 2 * dpml, sz + 2 * dpml)))
#plt.show()
plt.savefig('foo.pdf')
sim.plot2D(output_plane=mp.Volume(
center=mp.Vector3(0 * abs_source_position_x, 0, 0),
size=mp.Vector3(sx + 2 * dpml, 0, sz + 2 * dpml)))
#plt.show()
plt.savefig('foo2.pdf')
sim.plot2D(output_plane=mp.Volume(
center=mp.Vector3(0, 0, abs_source_position_z),
size=mp.Vector3(sx + 2 * dpml, sy + 2 * dpml, 0)))
#sim.plot2D(output_plane=mp.Volume(center=mp.Vector3(0,0,sz/2-sh-0.01),size=mp.Vector3(sx+2*dpml,sy+2*dpml,0)))
plt.savefig('foo3.pdf')
if use_fixed_time:
sim.run(
mp.dft_ldos(self.frequency_center, self.frequency_width,
self.number_of_freqs),
# mp.at_beginning(mp.output_epsilon),
#until_after_sources=mp.stop_when_fields_decayed(2,mp.Ey,mp.Vector3(0,0,sbs_cource_position+0.2),1e-2))
until=simulation_time)
else:
#Withdraw maximum dipole amplitude direction
max_index = self.source_direction.index(max(self.source_direction))
if max_index == 0:
detector_pol = mp.Ex
elif max_index == 1:
detector_pol = mp.Ey
else:
detector_pol = mp.Ez
#TODO: exchange self.source_direction to maxmimum dipole ampltitude
sim.run(
mp.dft_ldos(self.frequency_center, self.frequency_width,
self.number_of_freqs),
#mp.to_appended("ex", mp.at_every(0.6, mp.output_efield_x)),
mp.at_beginning(mp.output_epsilon),
until_after_sources=mp.stop_when_fields_decayed(
2, detector_pol,
mp.Vector3(0, 0, abs_source_position_z + 0.2), 1e-3))
###OUTPUT CALCULATIONS##########################################################
#"Calculate the poynting flux given the far field values of E, H."
myIntegration = True
nfreq = self.number_of_freqs
r = 2 * math.pow(
self.pyramid_height, 2
) * self.frequency_center * 2 * 10 # 10 times the Fraunhofer-distance
if ff_calculations:
fields = []
P_tot_ff = np.zeros(self.number_of_freqs)
npts = ff_pts #number of far-field points
Px = 0
Py = 0
Pz = 0
theta = ff_angle
phi = math.pi * 2
#"How many points on the ff-sphere"
#global xPts
#xPts=[]
#global yPts
#yPts=[]
#global zPts
#zPts=[]
Pr_Array = []
if myIntegration == True:
#how to pick ff-points, this uses fibbonaci-sphere distribution
if FibonacciSampling == True:
if theta == math.pi / 3:
offset = 1.5 / npts
elif theta == math.pi / 4:
npts = npts * 2
offset = 1.15 / npts
elif theta == math.pi / 5:
npts = npts * 2.5
offset = 0.95 / npts
elif theta == math.pi / 6:
#npts=npts*3
offset = 0.8 / npts
elif theta == math.pi / 7:
npts = npts * 3
offset = 0.7 / npts
elif theta == math.pi / 8:
npts = npts * 3
offset = 0.6 / npts
elif theta == math.pi / 12:
npts = npts * 3
offset = 0.4 / npts
else:
offset = 0.2 / npts
xPts, yPts, zPts = fibspherepts(r, theta, npts, offset)
range_npts = int((theta / math.pi) * npts)
else:
#check out Lebedev quadrature
#if not fibb sampling then spherical sampling
theta_pts = npts
phi_pts = npts * 2
xPts, yPts, zPts = sphericalpts(r, theta, phi, theta_pts,
phi_pts)
range_npts = int(theta_pts * phi_pts + 1)
if ff_calc == "Both":
#Pr_ArrayA for above, B for below
Pr_ArrayA = []
Pr_ArrayB = []
P_tot_ffA = [0] * (self.number_of_freqs)
P_tot_ffB = [0] * (self.number_of_freqs)
for n in range(range_npts):
ffA = sim.get_farfield(
nearfieldAbove,
mp.Vector3(xPts[n], yPts[n], zPts[n]))
ffB = sim.get_farfield(
nearfieldBelow,
mp.Vector3(xPts[n], yPts[n], -1 * zPts[n]))
i = 0
for k in range(nfreq):
"Calculate the poynting vector in x,y,z direction"
PrA = myPoyntingFlux(ffA, i)
PrB = myPoyntingFlux(ffB, i)
Pr_ArrayA.append(PrA)
Pr_ArrayB.append(PrB)
"the spherical cap has area 2*pi*r^2*(1-cos(theta))"
"divided by npts and we get evenly sized area chunks"
surface_Element = 2 * math.pi * pow(
r, 2) * (1 - math.cos(theta)) / range_npts
P_tot_ffA[k] += surface_Element * (1) * (PrA)
P_tot_ffB[k] += surface_Element * (1) * (PrB)
i = i + 6 #to keep track of the correct entries in the ff array
if ff_calc == "Below":
for n in range(range_npts):
ff = sim.get_farfield(
nearfieldBelow,
mp.Vector3(xPts[n], yPts[n], -1 * zPts[n]))
fields.append({
"pos": (xPts[n], yPts[n], zPts[n]),
"field": ff
})
i = 0
for k in range(nfreq):
"Calculate the poynting vector in x,y,z direction"
Pr = myPoyntingFlux(ff, i)
Pr_Array.append(Pr)
"the spherical cap has area 2*pi*r^2*(1-cos(theta))"
"divided by npts and we get evenly sized area chunks"
surface_Element = 2 * math.pi * pow(
r, 2) * (1 - math.cos(theta)) / range_npts
P_tot_ff[k] += surface_Element * (1) * (Pr)
i = i + 6 #to keep track of the correct entries in the ff array
if ff_calc == "Above":
for n in range(range_npts):
ff = sim.get_farfield(
nearfieldAbove,
mp.Vector3(xPts[n], yPts[n], zPts[n]))
fields.append({
"pos": (xPts[n], yPts[n], zPts[n]),
"field": ff
})
# print('ff,n,x,y,z',n,xPts[n],yPts[n],zPts[n],ff)
# print('fields',fields[n])
# print('------')
i = 0
for k in range(nfreq):
"Calculate the poynting vector in x,y,z direction"
Pr = myPoyntingFlux(ff, i)
Pr_Array.append(Pr)
"the spherical cap has area 2*pi*r^2*(1-cos(theta))"
"divided by npts and we get evenly sized area chunks"
surface_Element = 2 * math.pi * pow(
r, 2) * (1 - math.cos(theta)) / range_npts
P_tot_ff[k] += surface_Element * (1) * (Pr)
#print('S',surface_Element,'r',r,'theta',theta,'range npts',range_npts)
i = i + 6 #to keep track of the correct entries in the ff array
# print('P_tot_ff',P_tot_ff)
# print('fields',fields)
# print('Pr_Array',Pr_Array)
##CALCULATE FLUX OUT FROM BOX###########################################
if calculate_flux:
#"Initialize variables to be used, pf stands for 'per frequency'"
flux_tot_value = np.zeros(
self.number_of_freqs) #total flux out from box
flux_tot_ff_ratio = np.zeros(self.number_of_freqs)
flux_tot_out = mp.get_fluxes(flux_total) #save total flux data
freqs_out = mp.get_flux_freqs(flux_total)
print('freqs', freqs_out)
if calculate_source_flux:
source_flux_out = mp.get_fluxes(flux_source)
elapsed_time = round((time.time() - start) / 60, 1)
print('LDOS', sim.ldos_data)
print('LDOS0', sim.ldos_data[0])
for i in range(len(flux_tot_out)):
print(flux_tot_out[i] * 100 / source_flux_out[i],
'LE percentage for lambda: ', 1 / freqs_out[i])
if False:
fig = plt.figure()
ax = fig.gca(projection='3d')
Pr_Max = max(Pr_Array)
R = [n / Pr_Max for n in Pr_Array]
print(R)
# R=1
pts = len(Pr_Array)
theta, phi = np.linspace(0, np.pi,
pts), np.linspace(0, 2 * np.pi, pts)
THETA, PHI = np.meshgrid(theta, phi)
#print(xPts)
# print(yPts)
# print(zPts)
X = np.zeros(pts**2)
Y = np.zeros(pts**2)
Z = np.zeros(pts**2)
print('R pts', pts)
print('sample pts', len(xPts))
for n in range(pts):
xPts[n] = R[n] * xPts[n]
yPts[n] = R[n] * yPts[n]
zPts[n] = R[n] * zPts[n]
# #print(X)
# #print(Y)
# #print(Z)
#ax.set_xlim(-100,100)
#ax.set_zlim(-100,100)
#ax.set_ylim(-100,100)
#ax.scatter(xPts,yPts,zPts)
u = np.linspace(0, 2 * np.pi, 120)
v = np.linspace(0, np.pi / 6, 120)
r_ = np.asarray(R)
x = np.outer(np.cos(u), np.sin(v))
y = np.outer(np.sin(u), np.sin(v))
z = R * np.outer(np.ones(np.size(u)), np.cos(v))
print('lenx', len(x), 'leny', len(y), 'lenz', len(z))
#r = np.sqrt(xPts**2+yPts**2+zPts**2)
#plot(r)
ax.plot_surface(x, y, z, cmap='plasma')
#ax.quiver(0,0,0,0,0,1,length=1.2,color='brown',normalize='true')
#ax.text(0,0,1.3, '$\mathcal{P}$',size=20, zdir=None)
#ax.set_zlim(-1,1)
#ax.axis('off')
#ax.plot_trisurf(list(x),list(y),list(z),cmap='plasma')
plt.show()
for n in range(len(flux_tot_out)):
flux_tot_out[n] = round(flux_tot_out[n], 11)
# P_tot_ff[n]=round(P_tot_ff[n],9)
##Some processing to calculate the flux ratios per frequency
if ff_calculations:
for n in range(len(flux_tot_out)):
# flux_tot_out[n]=round(flux_tot_out[n],9)
P_tot_ff[n] = round(P_tot_ff[n], 11)
for i in range(self.number_of_freqs):
flux_tot_ff_ratio[i] = round(P_tot_ff[i] / flux_tot_out[i],
11)
if ff_calc == "Both":
P_tot_ff = []
P_tot_ff.append(P_tot_ffA)
P_tot_ff.append(P_tot_ffB)
flux_tot_ff_ratio = []
flux_tot_ff_ratioA = [0] * (self.number_of_freqs)
flux_tot_ff_ratioB = [0] * (self.number_of_freqs)
for i in range(self.number_of_freqs):
flux_tot_ff_ratioA[i] = round(
P_tot_ffA[i] / flux_tot_out[i], 11)
flux_tot_ff_ratioB[i] = round(
P_tot_ffB[i] / flux_tot_out[i], 11)
flux_tot_ff_ratio.append(flux_tot_ff_ratioA)
flux_tot_ff_ratio.append(flux_tot_ff_ratioB)
return {
"total_flux": flux_tot_out,
"source_flux": source_flux_out,
"ff_at_angle": P_tot_ff,
"flux_ratio": flux_tot_ff_ratio,
"LDOS": sim.ldos_data,
"Elapsed time (min)": elapsed_time
}
else:
return {
"total_flux": flux_tot_out,
"source_flux": source_flux_out,
"ff_at_angle": None,
"flux_ratio": None,
"LDOS": sim.ldos_data,
"Elapsed time (min)": elapsed_time
}
def main(args):
print("\nstart time:", datetime.now())
# --------------------------------------------------------------------------
# physical parameters characterizing light source and interface characteris-
# tics (must be adjusted - eihter here or via command line interface (CLI))
# --------------------------------------------------------------------------
interface = args.interface
s_pol = args.s_pol
ref_medium = args.ref_medium
n1 = args.n1
n2 = args.n2
kw_0 = args.kw_0
kr_w = args.kr_w
kr_c = args.kr_c
# angle of incidence
chi_deg = args.chi_deg
#chi_deg = 1.0*Critical(n1, n2)
#chi_deg = 0.95*Brewster(n1, n2)
test_output = args.test_output
# --------------------------------------------------------------------------
# specific Meep parameters (may need to be adjusted)
# --------------------------------------------------------------------------
sx = 5 # size of cell including PML in x-direction
sy = 5 # size of cell including PML in y-direction
pml_thickness = 0.25 # thickness of PML layer
freq = 12 # vacuum frequency of source (5 to 12 is good)
runtime = 10 # runs simulation for 10 times freq periods
# number of pixels per wavelength in the denser medium (at least 10,
# 20 to 30 is a good choice)
pixel = 10
# source position with respect to the center (point of impact) in Meep
# units (-2.15 good); if equal -r_w, then source position coincides with
# waist position
source_shift = -2.15
# --------------------------------------------------------------------------
# derived (Meep) parameters (do not change)
# --------------------------------------------------------------------------
k_vac = 2 * math.pi * freq
k1 = n1 * k_vac
n_ref = (1 if ref_medium == 0 else
n1 if ref_medium == 1 else
n2 if ref_medium == 2 else math.nan)
r_w = kr_w / (n_ref * k_vac)
w_0 = kw_0 / (n_ref * k_vac)
r_c = kr_c / (n_ref * k_vac)
shift = source_shift + r_w
chi_rad = math.radians(chi_deg)
params = dict(W_y=w_0, k=k1)
# --------------------------------------------------------------------------
# placement of the dielectric interface within the computational cell
# --------------------------------------------------------------------------
# helper functions
def alpha(chi_rad):
"""Angle of inclined plane with y-axis in radians."""
return math.pi/2 - chi_rad
def Delta_x(alpha):
"""Inclined plane offset to the center of the cell."""
sin_alpha = math.sin(alpha)
cos_alpha = math.cos(alpha)
return (sx/2) * (((math.sqrt(2) - cos_alpha) - sin_alpha) / sin_alpha)
cell = mp.Vector3(sx, sy, 0) # geometry-lattice
if interface == "planar":
default_material = mp.Medium(index=n1)
# located at lower right edge for 45 degree
geometry = [mp.Block(size=mp.Vector3(mp.inf, sx*math.sqrt(2), mp.inf),
center=mp.Vector3(+sx/2 + Delta_x(alpha(chi_rad)),
-sy/2),
e1=mp.Vector3(1/math.tan(alpha(chi_rad)), 1, 0),
e2=mp.Vector3(-1, 1/math.tan(alpha(chi_rad)), 0),
e3=mp.Vector3(0, 0, 1),
material=mp.Medium(index=n2))]
elif interface == "concave":
default_material = mp.Medium(index=n2)
# move center to the right in order to ensure that the point of impact
# is always centrally placed
geometry = [mp.Cylinder(center=mp.Vector3(-r_c*math.cos(chi_rad),
+r_c*math.sin(chi_rad)),
height=mp.inf,
radius=r_c,
material=mp.Medium(index=n1))]
elif interface == "convex":
default_material = mp.Medium(index=n1)
# move center to the right in order to ensure that the point of impact
# is always centrally placed
geometry = [mp.Cylinder(center=mp.Vector3(+r_c*math.cos(chi_rad),
-r_c*math.sin(chi_rad)),
height=mp.inf,
radius=r_c,
material=mp.Medium(index=n2))]
# --------------------------------------------------------------------------
# add absorbing boundary conditions and discretize structure
# --------------------------------------------------------------------------
pml_layers = [mp.PML(pml_thickness)]
resolution = pixel * (n1 if n1 > n2 else n2) * freq
# set Courant factor (mandatory if either n1 or n2 is smaller than 1)
Courant = (n1 if n1 < n2 else n2) / 2
# --------------------------------------------------------------------------
# beam profile distribution (field amplitude) at the waist of the beam
# --------------------------------------------------------------------------
def Gauss(r, params):
"""Gauss profile."""
W_y = params['W_y']
return math.exp(-(r.y / W_y)**2)
# --------------------------------------------------------------------------
# spectrum amplitude distribution
# --------------------------------------------------------------------------
def f_Gauss(k_y, params):
"""Gaussian spectrum amplitude."""
W_y = params['W_y']
return math.exp(-(k_y*W_y/2)**2)
if test_output:
print("Gauss spectrum:", f_Gauss(0.2, params))
# --------------------------------------------------------------------------
# plane wave decomposition
# (purpose: calculate field amplitude at light source position if not
# coinciding with beam waist)
# --------------------------------------------------------------------------
def psi(r, x, params):
"""Field amplitude function."""
try:
getattr(psi, "called")
except AttributeError:
psi.called = True
print("Calculating inital field configuration. "
"This will take some time...")
def phase(k_y, x, y):
"""Phase function."""
return x*math.sqrt(k1**2 - k_y**2) + k_y*y
try:
(result,
real_tol,
imag_tol) = complex_quad(lambda k_y:
f_Gauss(k_y, params) *
cmath.exp(1j*phase(k_y, x, r.y)),
-k1, k1)
except Exception as e:
print(type(e).__name__ + ":", e)
sys.exit()
return result
# --------------------------------------------------------------------------
# some test outputs (uncomment if needed)
# --------------------------------------------------------------------------
if test_output:
x, y, z = -2.15, 0.3, 0.5
r = mp.Vector3(0, y, z)
print()
print("psi :", psi(r, x, params))
sys.exit()
# --------------------------------------------------------------------------
# display values of physical variables
# --------------------------------------------------------------------------
print()
print("Specified variables and derived values:")
print("n1:", n1)
print("n2:", n2)
print("chi: ", chi_deg, " [degree]")
print("incl.:", 90 - chi_deg, " [degree]")
print("kw_0: ", kw_0)
if interface != "planar":
print("kr_c: ", kr_c)
print("kr_w: ", kr_w)
print("k_vac:", k_vac)
print("polarisation:", "s" if s_pol else "p")
print("interface:", interface)
print()
# --------------------------------------------------------------------------
# specify current source, output functions and run simulation
# --------------------------------------------------------------------------
force_complex_fields = False # default: False
eps_averaging = True # default: True
filename_prefix = None
sources = [mp.Source(src=mp.ContinuousSource(frequency=freq, width=0.5),
component=mp.Ez if s_pol else mp.Ey,
size=mp.Vector3(0, 2, 0),
center=mp.Vector3(source_shift, 0, 0),
#amp_func=lambda r: Gauss(r, params)
amp_func=lambda r: psi(r, shift, params)
)
]
sim = mp.Simulation(cell_size=cell,
boundary_layers=pml_layers,
default_material=default_material,
Courant=Courant,
geometry=geometry,
sources=sources,
resolution=resolution,
force_complex_fields=force_complex_fields,
eps_averaging=eps_averaging,
filename_prefix=filename_prefix
)
sim.use_output_directory(interface) # put output files in a separate folder
def eSquared(r, ex, ey, ez):
"""Calculate |E|^2.
With |.| denoting the complex modulus if 'force_complex_fields?'
is set to true, otherwise |.| gives the Euclidean norm.
"""
return mp.Vector3(ex, ey, ez).norm()**2
def output_efield2(sim):
"""Output E-field intensity."""
name = "e2_s" if s_pol else "e2_p"
func = eSquared
cs = [mp.Ex, mp.Ey, mp.Ez]
return sim.output_field_function(name, cs, func, real_only=True)
sim.run(mp.at_beginning(mp.output_epsilon),
mp.at_end(mp.output_efield_z if s_pol else mp.output_efield_y),
mp.at_end(output_efield2),
until=runtime)
print("\nend time:", datetime.now())
def main():
# Prefix all output files with the command line argument
file_prefix = sys.argv[1]
# Number of pixels per micron
resolution = 150
# Simulation volume (um)
cell_x = 2
cell_y = 2
cell_z = 2.5
# Refractive indicies
index_si = 3.6 # previously 3.4467
index_sio2 = 1.444
# Durations in units of micron/c
duration = round(1.5 * cell_x + 2)
num_timesteps = duration * resolution
# Absorbing layer on boundary
pml = 0.5
# Geometry
src_buffer = pml / 16
nbn_buffer = src_buffer
nbn_length = cell_x - 2 * pml - src_buffer - nbn_buffer
nbn_center_x = (src_buffer + nbn_buffer) / 2
wavelength = 1.55
waveguide_width = 0.750 # 750 nm
waveguide_height = 0.110 # 110 nm
plane_shift_y = 0
# nbn is 10/8 times thicker than in reality to have enough simulation pixels
# so we reduce its absorption by a factor of 5/4 to compensate
nbn_thickness_comp = 250 / resolution
nbn_thickness = 0.008 * nbn_thickness_comp # Actually 8 nm, but simulating this for 2 grid points
nbn_width = 0.100 # 100 nm
nbn_spacing = 0.120 # 120 nm
# Also compensate the difference in index by the same amount
nbn_base_index = 5.23 # Taken from Hu thesis p86
nbn_index = (5.23 - index_si) / nbn_thickness_comp + index_si
nbn_base_k = 5.82 # Taken from Hu thesis p86
nbn_k = nbn_base_k / nbn_thickness_comp
conductivity = 2 * math.pi * wavelength * nbn_k / nbn_index
flux_length = cell_x - 2 * pml - 4 * src_buffer
# Generate simulation obejcts
cell = mp.Vector3(cell_x, cell_y, cell_z)
freq = 1 / wavelength
src_pt = mp.Vector3(-cell_x / 2 + pml + src_buffer, 0, 0)
output_slice = mp.Volume(center=mp.Vector3(y=(3 * waveguide_height / 4) +
plane_shift_y),
size=(cell_x, 0, cell_z))
# Log important quantities
print('ABSORBING RUN')
print('File prefix: {}'.format(file_prefix))
print('Duration: {}'.format(duration))
print('Resolution: {}'.format(resolution))
print('Dimensions: {} um, {} um, {} um'.format(cell_x, cell_y, cell_z))
print('Wavelength: {} um'.format(wavelength))
print('Si thickness: {} um'.format(waveguide_height))
print('NbN thickness: {} um'.format(nbn_thickness))
print('Si index: {}; SiO2 index: {}'.format(index_si, index_sio2))
print('Absorber dimensions: {} um, {} um, {} um'.format(
nbn_length, nbn_thickness, nbn_width))
print('Absorber n (base value): {} ({}), k: {} ({})'.format(
nbn_index, nbn_base_index, nbn_k, nbn_base_k))
print('Absorber compensation for thickness: {}'.format(nbn_thickness_comp))
print('Flux length: {} um'.format(flux_length))
print('\n\n**********\n\n')
default_material = mp.Medium(epsilon=1)
# Physical geometry of the simulation
geometry = [
mp.Block(mp.Vector3(mp.inf, cell_y, mp.inf),
center=mp.Vector3(0, -cell_y / 2 + plane_shift_y, 0),
material=mp.Medium(epsilon=index_sio2)),
mp.Block(mp.Vector3(mp.inf, waveguide_height, waveguide_width),
center=mp.Vector3(0, waveguide_height / 2 + plane_shift_y, 0),
material=mp.Medium(epsilon=index_si))
]
# Absorber will only be appended to geometry for the second simulation
absorber = [
mp.Block(mp.Vector3(nbn_length, nbn_thickness, nbn_width),
center=mp.Vector3(
nbn_center_x, waveguide_height +
nbn_thickness / nbn_thickness_comp / 2 + plane_shift_y,
nbn_spacing / 2),
material=mp.Medium(epsilon=nbn_index,
D_conductivity=conductivity)),
mp.Block(mp.Vector3(nbn_length, nbn_thickness, nbn_width),
center=mp.Vector3(
nbn_center_x, waveguide_height +
nbn_thickness / nbn_thickness_comp / 2 + plane_shift_y,
-nbn_spacing / 2),
material=mp.Medium(epsilon=nbn_index,
D_conductivity=conductivity)),
]
# geometry += absorber
# Calculate eigenmode source
src_max_y = cell_y - 2 * pml
src_max_z = cell_z - 2 * pml
src_y = src_max_y
src_z = src_max_z # min(3 * waveguide_width, src_max_z)
src_center_y = 0 # plane_shift_y
sources = [
mp.EigenModeSource(src=mp.ContinuousSource(frequency=freq),
center=mp.Vector3(-cell_x / 2 + pml + src_buffer,
src_center_y, 0),
size=mp.Vector3(0, src_y, src_z),
eig_match_freq=True,
eig_parity=mp.ODD_Z,
eig_band=1)
]
pml_layers = [mp.PML(pml)]
# Pass all simulation parameters to meep
sim = mp.Simulation(
cell_size=cell,
boundary_layers=pml_layers,
geometry=geometry,
sources=sources,
resolution=resolution,
# eps_averaging=False,
default_material=default_material,
symmetries=[mp.Mirror(mp.Z, phase=-1)])
# Create flux monitors to calculate transmission and absorption
fr_y = cell_y - 2 * pml
fr_z = cell_z - 2 * pml
# Reflected flux
refl_fr = mp.FluxRegion(center=mp.Vector3(
-0.5 * cell_x + pml + 2 * src_buffer, 0, 0),
size=mp.Vector3(0, fr_y, fr_z))
refl = sim.add_flux(freq, 0, 1, refl_fr)
# Transmitted flux
tran_fr = mp.FluxRegion(center=mp.Vector3(
0.5 * cell_x - pml - 2 * src_buffer, 0, 0),
size=mp.Vector3(0, fr_y, fr_z))
tran = sim.add_flux(freq, 0, 1, tran_fr)
# Run simulation, outputting the epsilon distribution and the fields in the
# x-y plane every 0.25 microns/c
sim.run(mp.at_beginning(mp.output_epsilon),
mp.to_appended(
"ez_z0",
mp.in_volume(output_slice,
mp.at_every(2 / resolution, mp.output_efield_z))),
until=duration)
print('\n\n**********\n\n')
sim.fields.synchronize_magnetic_fields()
# For normalization run, save flux fields data for reflection plane
no_absorber_refl_data = sim.get_flux_data(refl)
# Save incident power for transmission plane
no_absorber_tran_flux = mp.get_fluxes(tran)
print("Flux: {}".format(no_absorber_tran_flux[0]))
eps_data = sim.get_array(center=mp.Vector3(z=(nbn_spacing + nbn_width) /
2),
size=mp.Vector3(cell_x, cell_y, 0),
component=mp.Dielectric)
eps_cross_data = sim.get_array(center=mp.Vector3(x=cell_x / 4),
size=mp.Vector3(0, cell_y, cell_z),
component=mp.Dielectric)
max_field = 1.5
# Plot epsilon distribution
if mp.am_master():
plt.figure()
plt.imshow(eps_data.transpose(),
interpolation='spline36',
cmap='binary')
plt.axis('off')
plt.savefig(file_prefix + '_Eps_A.png', dpi=300)
print('Saved ' + file_prefix + '_Eps_A.png')
# Plot field on x-y plane
ez_data = sim.get_array(center=mp.Vector3(),
size=mp.Vector3(cell_x, cell_y, 0),
component=mp.Ez)
if mp.am_master():
plt.figure()
plt.imshow(eps_data.transpose(),
interpolation='spline36',
cmap='binary')
plt.imshow(ez_data.transpose(),
interpolation='spline36',
cmap='RdBu',
alpha=0.9)
plt.axis('off')
plt.savefig(file_prefix + '_Ez_A.png', dpi=300)
print('Saved ' + file_prefix + '_Ez_A.png')
energy_side_data = sim.get_array(center=mp.Vector3(),
size=mp.Vector3(cell_x, cell_y, 0),
component=mp.EnergyDensity)
if mp.am_master():
plt.figure()
plt.imshow(eps_data.transpose(),
interpolation='spline36',
cmap='binary')
plt.imshow(energy_side_data.transpose(),
interpolation='spline36',
cmap='hot',
alpha=0.9)
plt.axis('off')
plt.savefig(file_prefix + '_Pwr0_A.png', dpi=300)
print('Saved ' + file_prefix + '_Pwr0_A.png')
# Plot energy density on y-z plane
energy_data = sim.get_array(center=mp.Vector3(),
size=mp.Vector3(0, cell_y, cell_z),
component=mp.EnergyDensity)
if mp.am_master():
plt.figure()
plt.imshow(eps_cross_data, interpolation='spline36', cmap='binary')
plt.imshow(energy_data,
interpolation='spline36',
cmap='hot',
alpha=0.9)
plt.axis('off')
plt.savefig(file_prefix + '_Pwr1_A.png', dpi=300)
print('Saved ' + file_prefix + '_Pwr1_A.png')
energy_data = sim.get_array(center=mp.Vector3(x=cell_x / 4),
size=mp.Vector3(0, cell_y, cell_z),
component=mp.EnergyDensity)
if mp.am_master():
plt.figure()
plt.imshow(eps_cross_data, interpolation='spline36', cmap='binary')
plt.imshow(energy_data,
interpolation='spline36',
cmap='hot',
alpha=0.9)
plt.axis('off')
plt.savefig(file_prefix + '_Pwr2_A.png', dpi=300)
print('Saved ' + file_prefix + '_Pwr2_A.png')
# Plot cross-sectional fields at several locations to ensure seeing nonzero fields
num_x = 4
num_y = 3
fig, ax = plt.subplots(num_x, num_y)
fig.suptitle('Cross Sectional Ez Fields')
for i in range(num_x * num_y):
monitor_x = i * (cell_x / 4) / (num_x * num_y)
ez_cross_data = sim.get_array(center=mp.Vector3(x=monitor_x),
size=mp.Vector3(0, cell_y, cell_z),
component=mp.Ez)
ax_num = i // num_y, i % num_y
if mp.am_master():
ax[ax_num].imshow(eps_cross_data,
interpolation='spline36',
cmap='binary')
ax[ax_num].imshow(ez_cross_data,
interpolation='spline36',
cmap='RdBu',
alpha=0.9,
norm=ZeroNormalize(vmax=np.max(max_field)))
ax[ax_num].axis('off')
ax[ax_num].set_title('x = {}'.format(
round(cell_x / 4 + i / resolution, 3)))
if mp.am_master():
plt.savefig(file_prefix + '_Ez_CS_A.png', dpi=300)
print('Saved ' + file_prefix + '_Ez_CS_A.png')
fig_e, ax_e = plt.subplots(num_x, num_y)
fig_e.suptitle('Cross Sectional Energy Density')
for i in range(num_x * num_y):
monitor_x = i * (cell_x / 4) / (num_x * num_y)
energy_cross_data = sim.get_array(center=mp.Vector3(x=monitor_x),
size=mp.Vector3(0, cell_y, cell_z),
component=mp.EnergyDensity)
ax_num = i // num_y, i % num_y
if mp.am_master():
ax_e[ax_num].imshow(eps_cross_data,
interpolation='spline36',
cmap='binary')
ax_e[ax_num].imshow(energy_cross_data,
interpolation='spline36',
cmap='hot',
alpha=0.9)
ax_e[ax_num].axis('off')
ax_e[ax_num].set_title('x = {}'.format(
round(cell_x / 4 + i / resolution, 3)))
if mp.am_master():
plt.savefig(file_prefix + '_Pwr_CS_A.png', dpi=300)
print('Saved ' + file_prefix + '_Pwr_CS_A.png')
print('\n\n**********\n\n')
# Reset simulation for absorption run
"""
sim.reset_meep()
geometry += absorber
sim = mp.Simulation(cell_size=cell,
boundary_layers=pml_layers,
geometry=geometry,
sources=sources,
resolution=resolution,
eps_averaging=False,
default_material=default_material,
symmetries=[mp.Mirror(mp.Z, phase=-1)])
refl = sim.add_flux(freq, 0, 1, refl_fr)
tran = sim.add_flux(freq, 0, 1, tran_fr)
sim.load_minus_flux_data(refl, no_absorber_refl_data)
# Run simulation with absorber
sim.run(mp.at_beginning(mp.output_epsilon),
mp.to_appended("ez_z0",
mp.in_volume(output_slice,
mp.at_every(0.25, mp.output_efield_z))),
until=duration)
print('\n\n**********\n\n')
# Calculate transmission and absorption
absorber_refl_flux = mp.get_fluxes(refl)
absorber_tran_flux = mp.get_fluxes(tran)
transmittance = absorber_tran_flux[0] / no_absorber_tran_flux[0]
reflectance = absorber_refl_flux[0] / no_absorber_tran_flux[0]
absorption = 1 - transmittance
penetration_depth = - nbn_length / math.log(transmittance)
print('Flux: {}'.format(absorber_tran_flux[0]))
print("Transmittance: %f" % transmittance)
print("Reflectance: %f" % reflectance)
print("Absorption: {} over {} um".format(absorption, nbn_length))
print("lambda = {} mm".format(penetration_depth / 1000))
eps_data = sim.get_array(center=mp.Vector3(z=(nbn_spacing + nbn_width) / 2), size=mp.Vector3(cell_x, cell_y, 0), component=mp.Dielectric)
max_field = 1
# Plot epsilon distribution with absorber
if mp.am_master():
plt.figure()
plt.imshow(eps_data.transpose(), interpolation='spline36', cmap='binary')
plt.axis('off')
plt.savefig(file_prefix + '_Eps_B.png', dpi=300)
print('Saved ' + file_prefix + '_Eps_B.png')
# Plot fields in x-y plane with absorber
ez_data = sim.get_array(center=mp.Vector3(), size=mp.Vector3(cell_x, cell_y, 0), component=mp.Ez)
if mp.am_master():
plt.figure()
plt.imshow(eps_data.transpose(), interpolation='spline36', cmap='binary')
plt.imshow(ez_data.transpose(), interpolation='spline36', cmap='RdBu', alpha=0.9)
plt.axis('off')
plt.savefig(file_prefix + '_Ez_B.png', dpi=300)
print('Saved ' + file_prefix + '_Ez_B.png')
# Plot field cross sections with absorber
eps_cross_data = sim.get_array(center=mp.Vector3(x=cell_x/4), size=mp.Vector3(0, cell_y, cell_z), component=mp.Dielectric)
num_x = 4
num_y = 3
fig, ax = plt.subplots(num_x, num_y)
fig.suptitle('Cross Sectional Ez Fields')
for i in range(num_x * num_y):
monitor_x = cell_x/4 + i / resolution
ez_cross_data = sim.get_array(center=mp.Vector3(x=monitor_x), size=mp.Vector3(0, cell_y, cell_z), component=mp.Ez)
ax_num = i // num_y, i % num_y
if mp.am_master():
ax[ax_num].imshow(eps_cross_data, interpolation='spline36', cmap='binary')
ax[ax_num].imshow(ez_cross_data, interpolation='spline36', cmap='RdBu', alpha=0.9, norm=ZeroNormalize(vmax=np.max(max_field)))
ax[ax_num].axis('off')
ax[ax_num].set_title('x = {}'.format(round(cell_x/4 + i / resolution, 3)))
if mp.am_master():
plt.savefig(file_prefix + '_Ez_CS_B.png', dpi=300)
print('Saved ' + file_prefix + '_Ez_CS_B.png')
print('\n\n**********\n\n')
"""
print('Program finished.')
def main(args):
resolution = 30
nSiO2 = 1.4
SiO2 = mp.Medium(index=nSiO2)
# conversion factor for eV to 1/um
eV_um_scale = 1 / 1.23984193
# W, from Rakic et al., Applied Optics, vol. 32, p. 5274 (1998)
W_eps_inf = 1
W_plasma_frq = 13.22 * eV_um_scale
W_f0 = 0.206
W_frq0 = 1e-10
W_gam0 = 0.064 * eV_um_scale
W_sig0 = W_f0 * W_plasma_frq**2 / W_frq0**2
W_f1 = 0.054
W_frq1 = 1.004 * eV_um_scale # 1.235 um
W_gam1 = 0.530 * eV_um_scale
W_sig1 = W_f1 * W_plasma_frq**2 / W_frq1**2
W_f2 = 0.166
W_frq2 = 1.917 * eV_um_scale # 0.647
W_gam2 = 1.281 * eV_um_scale
W_sig2 = W_f2 * W_plasma_frq**2 / W_frq2**2
W_susc = [
mp.DrudeSusceptibility(frequency=W_frq0, gamma=W_gam0, sigma=W_sig0),
mp.LorentzianSusceptibility(frequency=W_frq1,
gamma=W_gam1,
sigma=W_sig1),
mp.LorentzianSusceptibility(frequency=W_frq2,
gamma=W_gam2,
sigma=W_sig2)
]
W = mp.Medium(epsilon=W_eps_inf, E_susceptibilities=W_susc)
# crystalline Si, from M.A. Green, Solar Energy Materials and Solar Cells, vol. 92, pp. 1305-1310 (2008)
# fitted Lorentzian parameters, only for 600nm-1100nm
Si_eps_inf = 9.14
Si_eps_imag = -0.0334
Si_eps_imag_frq = 1 / 1.55
Si_frq = 2.2384
Si_gam = 4.3645e-02
Si_sig = 14.797 / Si_frq**2
Si = mp.Medium(epsilon=Si_eps_inf,
D_conductivity=2 * math.pi * Si_eps_imag_frq * Si_eps_imag /
Si_eps_inf,
E_susceptibilities=[
mp.LorentzianSusceptibility(frequency=Si_frq,
gamma=Si_gam,
sigma=Si_sig)
])
a = args.a # lattice periodicity
cone_r = args.cone_r # cone radius
cone_h = args.cone_h # cone height
wire_w = args.wire_w # metal-grid wire width
wire_h = args.wire_h # metal-grid wire height
trench_w = args.trench_w # trench width
trench_h = args.trench_h # trench height
Np = args.Np # number of periods in supercell
dair = 1.0 # air gap thickness
dmcl = 1.7 # micro lens thickness
dsub = 3000.0 # substrate thickness
dpml = 1.0 # PML thickness
sxy = Np * a
sz = dpml + dair + dmcl + dsub + dpml
cell_size = mp.Vector3(sxy, sxy, sz)
boundary_layers = [
mp.PML(dpml, direction=mp.Z, side=mp.High),
mp.Absorber(dpml, direction=mp.Z, side=mp.Low)
]
geometry = []
if args.substrate:
geometry = [
mp.Sphere(material=SiO2,
radius=dmcl,
center=mp.Vector3(0, 0, 0.5 * sz - dpml - dair - dmcl)),
mp.Block(material=Si,
size=mp.Vector3(mp.inf, mp.inf, dsub + dpml),
center=mp.Vector3(0, 0, -0.5 * sz + 0.5 * (dsub + dpml))),
mp.Block(
material=W,
size=mp.Vector3(mp.inf, wire_w, wire_h),
center=mp.Vector3(0, -0.5 * sxy + 0.5 * wire_w,
-0.5 * sz + dpml + dsub + 0.5 * wire_h)),
mp.Block(
material=W,
size=mp.Vector3(mp.inf, wire_w, wire_h),
center=mp.Vector3(0, +0.5 * sxy - 0.5 * wire_w,
-0.5 * sz + dpml + dsub + 0.5 * wire_h)),
mp.Block(
material=W,
size=mp.Vector3(wire_w, mp.inf, wire_h),
center=mp.Vector3(-0.5 * sxy + 0.5 * wire_w, 0,
-0.5 * sz + dpml + dsub + 0.5 * wire_h)),
mp.Block(material=W,
size=mp.Vector3(wire_w, mp.inf, wire_h),
center=mp.Vector3(+0.5 * sxy - 0.5 * wire_w, 0,
-0.5 * sz + dpml + dsub + 0.5 * wire_h))
]
if args.substrate and args.texture:
for nx in range(Np):
for ny in range(Np):
cx = -0.5 * sxy + (nx + 0.5) * a
cy = -0.5 * sxy + (ny + 0.5) * a
geometry.append(
mp.Cone(material=SiO2,
radius=0,
radius2=cone_r,
height=cone_h,
center=mp.Vector3(
cx, cy,
0.5 * sz - dpml - dair - dmcl - 0.5 * cone_h)))
if args.substrate:
geometry.append(
mp.Block(material=SiO2,
size=mp.Vector3(mp.inf, trench_w, trench_h),
center=mp.Vector3(
0, -0.5 * sxy + 0.5 * trench_w,
0.5 * sz - dpml - dair - dmcl - 0.5 * trench_h)))
geometry.append(
mp.Block(material=SiO2,
size=mp.Vector3(mp.inf, trench_w, trench_h),
center=mp.Vector3(
0, +0.5 * sxy - 0.5 * trench_w,
0.5 * sz - dpml - dair - dmcl - 0.5 * trench_h)))
geometry.append(
mp.Block(material=SiO2,
size=mp.Vector3(trench_w, mp.inf, trench_h),
center=mp.Vector3(
-0.5 * sxy + 0.5 * trench_w, 0,
0.5 * sz - dpml - dair - dmcl - 0.5 * trench_h)))
geometry.append(
mp.Block(material=SiO2,
size=mp.Vector3(trench_w, mp.inf, trench_h),
center=mp.Vector3(
+0.5 * sxy - 0.5 * trench_w, 0,
0.5 * sz - dpml - dair - dmcl - 0.5 * trench_h)))
k_point = mp.Vector3(0, 0, 0)
lambda_min = 0.7 # minimum source wavelength
lambda_max = 1.0 # maximum source wavelength
fmin = 1 / lambda_max
fmax = 1 / lambda_min
fcen = 0.5 * (fmin + fmax)
df = fmax - fmin
sources = [
mp.Source(mp.GaussianSource(fcen, fwidth=df),
component=mp.Ex,
center=mp.Vector3(0, 0, 0.5 * sz - dpml - 0.5 * dair),
size=mp.Vector3(sxy, sxy, 0))
]
sim = mp.Simulation(resolution=resolution,
cell_size=cell_size,
boundary_layers=boundary_layers,
geometry=geometry,
dimensions=3,
k_point=k_point,
sources=sources)
nfreq = 50
refl = sim.add_flux(
fcen, df, nfreq,
mp.FluxRegion(center=mp.Vector3(0, 0, 0.5 * sz - dpml),
size=mp.Vector3(sxy, sxy, 0)))
trans_grid = sim.add_flux(
fcen, df, nfreq,
mp.FluxRegion(center=mp.Vector3(0, 0,
-0.5 * sz + dpml + dsub + wire_h),
size=mp.Vector3(sxy, sxy, 0)))
trans_sub_top = sim.add_flux(
fcen, df, nfreq,
mp.FluxRegion(center=mp.Vector3(0, 0, -0.5 * sz + dpml + dsub),
size=mp.Vector3(sxy, sxy, 0)))
trans_sub_bot = sim.add_flux(
fcen, df, nfreq,
mp.FluxRegion(center=mp.Vector3(0, 0, -0.5 * sz + dpml),
size=mp.Vector3(sxy, sxy, 0)))
sim.run(mp.at_beginning(mp.output_epsilon), until=0)
if args.substrate:
sim.load_minus_flux('refl-flux', refl)
sim.run(until_after_sources=mp.stop_when_fields_decayed(
50, mp.Ex, mp.Vector3(0, 0, -0.5 * sz + dpml + 0.5 * dsub), 1e-9))
if not args.substrate:
sim.save_flux('refl-flux', refl)
sim.display_fluxes(refl, trans_grid, trans_sub_top, trans_sub_bot)
def main(args):
sx = 8.0 #spatial extent along x including pmls (μm)
sy = 4
sz = 0
dpml = 1.0
cell = mp.Vector3(sx, sy, sz)
pml_layers = [mp.PML(dpml)]
resolution = args.res
wvl = args.wvl #source wavelength
fcen = 1 / wvl #center frequency
df = 0 #frequency bandwidth
nfreq = 1 #number of frequencies
dw = args.dw # slab thickness increment(um)
w_init = args.w_init # initial slab thickness(μm)
n = args.n
w = w_init + n * dw #next slab thicknessw
slab_center_y = 0.5 * w #slab center y coordinate
sfor_y = w + 0.005 #sfor_y = y coordinate of the slit_flux_output_region
s = 0.030 #slit width
print("wavelength =", wvl, "um")
print("slab size =", w, "um")
print("center frequency =", fcen, "1/um")
print("slit_flux_output_region y coordinate =", sfor_y, "um")
print("slab center y coordinate =", slab_center_y, "um")
geometry = [
mp.Block(mp.Vector3(mp.inf, w, mp.inf),
center=mp.Vector3(0, slab_center_y),
material=Ag)
]
source = [
mp.Source(mp.GaussianSource(fcen, df, nfreq),
component=mp.Ex,
center=mp.Vector3(0, -0.5 * (sy - 2.1), 0),
size=mp.Vector3(sx - 2.0, 0, 0))
]
symmetries = [mp.Mirror(mp.X), mp.Mirror(mp.Z)]
sim = mp.Simulation(cell_size=cell,
geometry=geometry,
sources=source,
resolution=resolution,
boundary_layers=pml_layers,
filename_prefix='slab_noslit')
sim.use_output_directory()
pt = mp.Vector3(
0, -0.5 * (sy - 2.1), 0
) #point where field intensity is measured (usually at source position)
slab_flux_in_region = mp.FluxRegion(
center=mp.Vector3(0, -0.005, 0),
size=mp.Vector3(sx, 0, 0)) #incident flux monitor 5nm above slab.
slab_flux_in = sim.add_flux(fcen, df, nfreq, slab_flux_in_region)
slab_flux_in_data = sim.get_flux_data(
slab_flux_in) #data are the E and H fields used to calculate S=ExH
slab_flux_out_region = mp.FluxRegion(
center=mp.Vector3(0, sfor_y, 0),
size=mp.Vector3(sx, 0, 0)) #trans flux monitor 5nm below slab.
slab_flux_out = sim.add_flux(fcen, df, nfreq, slab_flux_out_region)
slab_flux_out_data = sim.get_flux_data(slab_flux_out)
sim.run(mp.dft_ldos(fcen, df, nfreq),
mp.at_beginning(mp.output_epsilon),
until_after_sources=mp.stop_when_fields_decayed(
10, mp.Hz, pt, 1e-5))
slab_flux_input = []
slab_flux_output = []
slab_flux_input = mp.get_fluxes(slab_flux_in)
slab_flux_output = mp.get_fluxes(slab_flux_out)
print('incident flux slab =', slab_flux_input, ' ',
'transmitted flux slab =', slab_flux_output, ' ',
'normed transmitted flux=',
np.divide(slab_flux_output, slab_flux_input))
eps_data_slab = sim.get_array(center=mp.Vector3(0, 0, 0),
size=mp.Vector3(sx, sy, sz),
component=mp.Dielectric)
ex_data_slab = sim.get_array(center=mp.Vector3(0, 0, 0),
size=mp.Vector3(sx, sy, sz),
component=mp.Ex)
hz_data_slab = sim.get_array(center=mp.Vector3(0, 0, 0),
size=mp.Vector3(sx, sy, sz),
component=mp.Hz)
sim.reset_meep()
geometry = [
mp.Block(mp.Vector3(mp.inf, w, mp.inf),
center=mp.Vector3(0, 0.5 * (w)),
material=Ag),
mp.Block(mp.Vector3(s, w, 0),
center=mp.Vector3(0, 0.5 * (w), 0),
material=mp.Medium(epsilon=1))
]
sim = mp.Simulation(cell_size=cell,
geometry=geometry,
sources=source,
resolution=resolution,
boundary_layers=pml_layers,
filename_prefix="slab_slit")
sim.use_output_directory()
slit_flux_in_region = mp.FluxRegion(center=mp.Vector3(0, -0.005, 0),
size=mp.Vector3(
sx, 0,
0)) #same as slab_flux_in_region
slit_flux_in = sim.add_flux(fcen, df, nfreq, slit_flux_in_region)
slit_flux_in_data = sim.get_flux_data(slit_flux_in)
slit_flux_out_region = mp.FluxRegion(center=mp.Vector3(0, w + 0.005, 0),
size=mp.Vector3(
sx, 0,
0)) #same as slab_flux_out_region
slit_flux_out = sim.add_flux(fcen, df, nfreq, slit_flux_out_region)
slit_flux_out_data = sim.get_flux_data(slit_flux_out)
sim.load_minus_flux_data(slit_flux_out, slab_flux_out_data)
#subract transmitted slab flux data (slab_flux_out_data) from slit_flux_out. This is a correction so that flux only
#from the slit is registered in slit_flux_out.
sim.run(mp.dft_ldos(fcen, 0, nfreq),
mp.at_beginning(mp.output_epsilon),
until_after_sources=mp.stop_when_fields_decayed(
10, mp.Hz, pt, 1e-4))
slit_flux_input = []
slit_flux_output = []
slit_flux_input = mp.get_fluxes(slit_flux_in)
slit_flux_output = mp.get_fluxes(slit_flux_out)
print('slit flux net =', slit_flux_output, ' ', 'slit_flux_normed =',
np.divide(slit_flux_output, slab_flux_input))
eps_data_slit = sim.get_array(center=mp.Vector3(0, 0, 0),
size=mp.Vector3(sx, sy, sz),
component=mp.Dielectric)
ex_data_slit = sim.get_array(center=mp.Vector3(0, 0, 0),
size=mp.Vector3(sx, sy, sz),
component=mp.Ex)
hz_data_slit = sim.get_array(center=mp.Vector3(0, 0, 0),
size=mp.Vector3(sx, sy, sz),
component=mp.Hz)
slabFlux = []
slabFlux = np.append(slabFlux, slab_flux_input)
slitFlux = []
slitFlux = np.append(slitFlux, slit_flux_output)
fracFlux = np.divide(slitFlux, slabFlux)
print('normalised slit flux,',
end=" ") #suppress the print newline function with end=" "
np.savetxt(
sys.stdout, fracFlux, fmt='%7.5f'
) #print to stdout transmitted slit flux normalised to input flux.
print('slab thickness,', end=" ")
print(w)
#-------------------------------- Next three lines ok for data file in mp meep, but writes data np times (np no. processors) in pmp.
#f=open('fracFL.dat','ab')
#np.savetxt(f,fracFl,fmt='%6.5f')
#f.close()
#----------------------------------------------------
eps_data_slit = sim.get_array(center=mp.Vector3(0, 0, 0),
size=mp.Vector3(sx, sy, sz),
component=mp.Dielectric)
hz_data_slit = sim.get_array(center=mp.Vector3(0, 0, 0),
size=mp.Vector3(sx, sy, sz),
component=mp.Hz)
hz_scat = hz_data_slit - hz_data_slab
def get_step_funcs(self, dt):
sf = (mp.at_beginning(self.get_meep_output_comp(f))
for f in self.dynamic_fields)
df = (mp.at_every(dt, self.get_meep_output_comp(f))
for f in self.static_fields)
return (*sf, *df)
def main(args):
"""
Args:
* **fields** (boolean): If true, outputs the fields at the relevant waveguide cross-sections (top-down and side-view)
* **output_directory** (string): Name of the output directory (for storing the fields)
* **eps_input_file** (string): Name of the hdf5 file that defines the geometry through prisms
* **input_pol** (string): Either "TE", or "TM", corresponding to the desired input mode. Defaults to "TE"
* **res** (int): Resolution of the MEEP simulation
* **nfreq** (int): The number of wavelength points to record in the transmission/reflection spectra
* **input_direction** (1 or -1): Direction of propagation for the input eigenmode. If +1, goes in +x, else if -1, goes in -x. Defaults to +1.
* **dpml** (float): Length (in microns) of the perfectly-matched layer (PML) at simulation boundaries. Defaults to 0.5 um.
* **wl_center** (float): Center wavelength (in microns)
* **wl_span** (float): Wavelength span (determines the pulse width)
* **port_vcenter** (float): Vertical center of the waveguide
* **port_height** (float): Height of the port cross-section (flux plane)
* **port_width** (float): Width of the port cross-section (flux plane)
* **source_offset** (float): Offset (in x-direction) between reflection monitor and source. Defaults to 0.1 um.
* **center_x** (float): x-coordinate of the center of the simulation region
* **center_y** (float): y-coordinate of the center of the simulation region
* **center_z** (float): z-coordinate of the center of the simulation region
* **sx** (float): Size of the simulation region in x-direction
* **sx** (float): Size of the simulation region in y-direction
* **sz** (float): Size of the simulation region in z-direction
* **port_coords** (list): List of the port coordinates (variable length), in the format [x1, y1, x2, y2, x3, y3, ...] (*must* be even)
"""
#Boolean inputs
fields = args.fields
#String inputs
output_directory = args.output_directory
eps_input_file = args.eps_input_file
input_pol = args.input_pol
#Int inputs
res = args.res
nfreq = args.nfreq
input_direction = args.input_direction
#Float inputs
dpml = args.dpml
wl_center = args.wl_center
wl_span = args.wl_span
port_vcenter = args.port_vcenter
port_height = args.port_height
port_width = args.port_width
source_offset = args.source_offset
center_x, center_y, center_z = args.center_x, args.center_y, args.center_z
sx, sy, sz = args.sx, args.sy, args.sz
#List of floats
port_coords = [float(x) for x in args.port_coords[0].split(" ")]
ports = [(port_coords[2 * i], port_coords[2 * i + 1])
for i in range(int(len(port_coords) / 2))]
if input_pol == "TE":
parity = mp.ODD_Z
elif input_pol == "TM":
parity = mp.EVEN_Z
else:
raise ValueError(
"Warning! Improper value of 'input_pol' was passed to mcts.py (input_pol given ="
+ str(input_pol) + ")")
if len(port_coords) % 2 != 0:
raise ValueError(
"Warning! Improper port_coords was passed to `meep_compute_transmission_spectra`. Must be even number of port_coords in [x1, y1, x2, y2, ..] format."
)
# Setup the simulation geometries
prism_objects = get_prism_objects(eps_input_file)
geometry = []
for p in prism_objects:
# print('vertices='+str(p['vlist']))
# print('axis = '+str(mp.Vector3(0,1,0)))
# print('height = '+str(p['height']))
print('material = ' + str(p['eps']))
# print('\n')
geometry.append(
mp.Prism(p['vlist'],
axis=mp.Vector3(0, 1, 0),
height=p['height'],
material=mp.Medium(epsilon=p['eps'])))
# Setup the simulation sources
fmax = 1.0 / (wl_center - 0.5 * wl_span)
fmin = 1.0 / (wl_center + 0.5 * wl_span)
fcen = (fmax + fmin) / 2.0
df = fmax - fmin
if abs(abs(input_direction) - 1) > 1E-6:
print(input_direction)
raise ValueError("Warning! input_direction is not +1 or -1.")
# Use first port in 'ports' as the location of the eigenmode source
sources = [
mp.EigenModeSource(
src=mp.GaussianSource(fcen, fwidth=df, cutoff=30),
component=mp.ALL_COMPONENTS,
size=mp.Vector3(0, 3 * float(port_height), 3 * float(port_width)),
center=mp.Vector3(ports[0][0] + source_offset - center_x,
float(port_vcenter) - center_y,
ports[0][1] - center_z),
eig_match_freq=True,
eig_parity=parity,
eig_kpoint=mp.Vector3(float(input_direction) * wl_center, 0, 0),
eig_resolution=2 * res if res > 16 else 32,
)
]
# Setup the simulation
sim = mp.Simulation(cell_size=mp.Vector3(sx, sy, sz),
boundary_layers=[mp.PML(dpml)],
geometry=geometry,
sources=sources,
dimensions=3,
resolution=res,
filename_prefix=False)
""" Add power flux monitors """
print("ADDING FLUX MONITORS")
flux_plane_objects = []
for port in ports:
flux_region = mp.FluxRegion(size=mp.Vector3(0, float(port_height),
float(port_width)),
center=mp.Vector3(
float(port[0]) - center_x,
float(port_vcenter) - center_y,
float(port[1]) - center_z))
fpo = sim.add_flux(fcen, df, nfreq, flux_region)
flux_plane_objects.append(fpo)
sim.use_output_directory(str(output_directory))
""" Run the simulation """
""" Monitor the amplitude in the center of the structure """
decay_pt = mp.Vector3(0, port_vcenter, 0)
sv = mp.Volume(size=mp.Vector3(sx, sy, 0), center=mp.Vector3(0, 0, 0))
tv = mp.Volume(size=mp.Vector3(sx, 0, sz),
center=mp.Vector3(0, port_vcenter, 0))
print("RUNNING SIMULATION")
if fields:
sim.run(mp.at_beginning(mp.output_epsilon),
mp.at_beginning(
mp.with_prefix(str("sideview-"),
mp.in_volume(sv, mp.output_epsilon))),
mp.at_beginning(
mp.with_prefix(str("topview-"),
mp.in_volume(tv, mp.output_epsilon))),
mp.at_every(
1.0,
mp.to_appended(str("ez-sideview"),
mp.in_volume(sv, mp.output_efield_z))),
mp.at_every(
1.0,
mp.to_appended(str("ez-topview"),
mp.in_volume(tv, mp.output_efield_z))),
until_after_sources=mp.stop_when_fields_decayed(
20, mp.Ez, decay_pt, 1e-4))
else:
sim.run(until_after_sources=mp.stop_when_fields_decayed(
20, mp.Ez, decay_pt, 1e-4))
sim.display_fluxes(*flux_plane_objects)
print("FINISHED SIMULATION")
pml_layers = [mp.PML(1.0)]
force_complex_fields = True # so we can get time-average flux
resolution = 10
sim = mp.Simulation(
cell_size=cell,
geometry=geometry,
sources=sources,
boundary_layers=pml_layers,
force_complex_fields=force_complex_fields,
resolution=resolution
)
sim.run(
mp.at_beginning(mp.output_epsilon),
mp.at_end(mp.output_png(mp.Ez, "-a yarg -A $EPS -S3 -Zc dkbluered", rm_h5=False)),
until=200
)
flux1 = sim.flux_in_box(mp.X, mp.Volume(center=mp.Vector3(-6.0), size=mp.Vector3(1.8, 6)))
flux2 = sim.flux_in_box(mp.X, mp.Volume(center=mp.Vector3(6.0), size=mp.Vector3(1.8, 6)))
# averaged over y region of width 1.8
print("left-going flux = {}".format(flux1 / -1.8))
# averaged over y region of width 1.8
print("right-going flux = {}".format(flux2 / 1.8))
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()
#
dft_objx = []
for i in range(len(flux_freqsX)):
dft_objx = np.append(
dft_objx,
sim.add_dft_fields([polarisation],
flux_freqsX[i],
flux_freqsX[i],
1,
where=monitor))
dft_obj = sim.add_dft_fields([polarisation], fcen, fcen, 1, where=monitor)
sim.use_output_directory('flux-out_1')
sim.run(mp.in_volume(monitor, mp.at_beginning(mp.output_epsilon)),
mp.in_volume(
monitor,
mp.to_appended("ez", mp.at_every(time_step, mp.output_efield_x))),
until_after_sources=mp.stop_when_fields_decayed(
add_time, polarisation, pt, decay))
'''
sim.run(until_after_sources=mp.stop_when_fields_decayed(add_time,polarisation,pt,decay))
'''
#save scattered reflected flux from the surfaces
scat_refl_data_t = mp.get_fluxes(refl_t)
scat_refl_data_b = mp.get_fluxes(refl_b)
scat_refl_data_l = mp.get_fluxes(refl_l)
scat_refl_data_r = mp.get_fluxes(refl_r)
sources = [
mp.Source(mp.ContinuousSource(wavelength=2 * (11 * 0.5), width=20),
component=mp.Ez,
center=mp.Vector3(-7, -3.5),
size=mp.Vector3(0, 1))
]
resolution = 10
sim = mp.Simulation(cell_size=cell,
boundary_layers=pml_layers,
geometry=geometry,
sources=sources,
resolution=resolution)
sim.run(mp.at_beginning(mp.output_epsilon),
mp.at_beginning(mp.output_mu),
mp.to_appended("ez", mp.at_every(0.6, mp.output_efield_z)),
until=200)
"""Post-processing"""
# plot the epsilon and mu values
eps_data = sim.get_array(center=mp.Vector3(),
size=cell,
component=mp.Dielectric)
mu_data = sim.get_array(center=mp.Vector3(),
size=cell,
component=mp.Permeability)
fig, axs = plt.subplots(2, 2)
axs[0, 0].imshow(eps_data.transpose(), cmap='binary')
refl_fr = mp.FluxRegion(center=mp.Vector3((-0.5 * sx) + 1, 0),size=mp.Vector3(0, sy))
# reflected flux
refl = sim.add_flux(fcen, df, nfreq, refl_fr)
# for normal run, load negated fields to subtract incident from refl. fields
if not args.no_ARC:
sim.load_minus_flux('refl-flux', refl)
if args.no_ARC:
pt = mp.Vector3((T_Si / 2) - (T_Si / 100), 0)
else:
pt = mp.Vector3((T_Si / 2) - (T_Si / 100), 0)
sim.run(mp.at_beginning(mp.output_epsilon),until_after_sources=mp.stop_when_fields_decayed(50, mp.Ez, pt, 1e-3))
# for normalization run, save flux fields for refl. plane
if args.no_ARC:
sim.save_flux('refl-flux', refl)
sim.display_fluxes(trans, refl)
def test(inputv):
print(inputv)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('-n', '--no_ARC', action='store_true', default=False,
help="Straight waveguide without bend.")
parser.add_argument('-v')