def main():
if len(sys.argv) > 1:
mode = sys.argv[1]
else:
mode = 'sim'
defaults.add_epsilon_as_inset = True
sim = TriHoles2D(
material='SiN',
radius=0.34,
numbands=4, #8,
k_interpolation=5, #31,
resolution=16,
mesh_size=7,
runmode=mode,
num_processors=2,
save_field_patterns=False,
convert_field_patterns=False)
if not sim:
log.error('an error occurred during simulation. See the .out file')
return
log.info(' ##### success! #####\n\n')
def main():
if len(sys.argv) > 1:
mode=sys.argv[1]
else:
mode='sim'
sim = TriHolesSlab3D(
material='Si',
substrate_material='glass',
radius=0.5 * 367 / pitch,
thickness=116 / pitch,
numbands=16,
k_interpolation=31,
resolution=32,
mesh_size=7,
supercell_z=10,
runmode=mode,
num_processors=8,
save_field_patterns=False,
convert_field_patterns=False,
job_name_suffix='_on_glass',
bands_title_appendix=' (on glass)',
modes=[''] # use (run), not (run-zeven) etc.
)
if not sim:
log.error('an error occurred during simulation. See the .out file')
else:
log.info(' ##### Si PhC slab on glass - success! #####\n\n')
def main():
if len(sys.argv) > 1:
mode=sys.argv[1]
else:
mode='sim'
defaults.add_epsilon_as_inset = True
sim = TriHoles2D(
material='SiN',
radius=0.34,
numbands=4,#8,
k_interpolation=5,#31,
resolution=16,
mesh_size=7,
runmode=mode,
num_processors=2,
save_field_patterns=False,
convert_field_patterns=False)
if not sim:
log.error('an error occurred during simulation. See the .out file')
return
log.info(' ##### success! #####\n\n')
def main():
if len(sys.argv) > 1:
mode = sys.argv[1]
else:
mode = 'sim'
# monkey patching:
# (don't output multiple tiles along y)
# (x and y are switched because of -T)
defaults.mpbdata_call = (
'mpb-data -T -rn%(resolution)s '
'-y%(number_of_tiles_to_output)s '
'-o%(output_file)s '
'%(h5_file)s')
defaults.number_of_tiles_to_output=5
ksteps = 5
# width of the supercell:
supercell_size = 3
# The bigger the unit cell, the more bands fold in below the
# waveguide band:
first_wg_band = int(3 + 2 * (supercell_size - 1))
sim = TriHolesSlab3D_Waveguide(
material='SiN',
radius=0.340,
thickness=0.8,
mode='zeven',
numbands=first_wg_band + 1,
k_steps=ksteps,
supercell_size=supercell_size,
supercell_z=3,
resolution=16,
mesh_size=3,
runmode=mode,
ydirection=False,
first_row_longitudinal_shift=0,
second_row_longitudinal_shift=0,
num_processors=2,
projected_bands_folder='./projected_bands_repo',
plot_crop_y=0.6,
#save_field_patterns_kvecs=[
# (x, 0, 0) for x in np.linspace(0, 0.5, num=ksteps)],
#save_field_patterns_bandnums=[
# 1, 2,
# first_wg_band, first_wg_band + 1, first_wg_band + 2],
#convert_field_patterns=True,
#field_pattern_plot_k_selection=[0, 5, 7, 9, 11, 13, 15, 16]
)
if not sim:
log.error('an error occurred during simulation. See the .out file')
return
def main():
if len(sys.argv) > 1:
mode = sys.argv[1]
else:
mode = 'sim'
# monkey patching:
# (don't output multiple tiles along y)
# (x and y are switched because of -T)
defaults.mpbdata_call = ('mpb-data -T -rn%(resolution)s '
'-y%(number_of_tiles_to_output)s '
'-o%(output_file)s '
'%(h5_file)s')
defaults.number_of_tiles_to_output = 5
ksteps = 5
# width of the supercell:
supercell_size = 3
# The bigger the unit cell, the more bands fold in below the
# waveguide band:
first_wg_band = int(3 + 2 * (supercell_size - 1))
sim = TriHolesSlab3D_Waveguide(
material='SiN',
radius=0.340,
thickness=0.8,
mode='zeven',
numbands=first_wg_band + 1,
k_steps=ksteps,
supercell_size=supercell_size,
supercell_z=3,
resolution=16,
mesh_size=3,
runmode=mode,
ydirection=False,
first_row_longitudinal_shift=0,
second_row_longitudinal_shift=0,
num_processors=2,
projected_bands_folder='./projected_bands_repo',
plot_crop_y=0.6,
#save_field_patterns_kvecs=[
# (x, 0, 0) for x in np.linspace(0, 0.5, num=ksteps)],
#save_field_patterns_bandnums=[
# 1, 2,
# first_wg_band, first_wg_band + 1, first_wg_band + 2],
#convert_field_patterns=True,
#field_pattern_plot_k_selection=[0, 5, 7, 9, 11, 13, 15, 16]
)
if not sim:
log.error('an error occurred during simulation. See the .out file')
return
def main():
if len(sys.argv) > 1:
mode=sys.argv[1]
else:
mode='sim'
minstep = 1
maxstep = 8.0
stepsize = 0.5
numsteps = int((maxstep - minstep) / stepsize + 1.5)
steps = np.linspace(minstep, maxstep, num=numsteps, endpoint=True)
# save previous step's data, needed for comparison with current data:
prev_step_data = None
for i, step in enumerate(steps):
log.info("running simulation with {0:n} supercell height steps:\n{1}".format(
numsteps, steps) +
'\n ### current step: #{0} ({1}) ###\n'.format(i+1, step))
### create and run simulation (according to mode) ###
sim = TriHolesSlab3D(
material='SiN',
radius=0.375,
thickness=0.8,
numbands=8,
k_interpolation=31,
resolution=32,
mesh_size=7,
supercell_z=step,
runmode=mode,
num_processors=8,
save_field_patterns=True,
convert_field_patterns=True,
job_name_suffix='_sct{0:03.0f}'.format(step*10),
bands_title_appendix=', supercell thickness={0:02.1f}'.format(step))
if not sim:
log.error('an error occurred during simulation. See the .out file')
return
### load some data ###
# load zeven mode band data:
fname = path.join(sim.workingdir, sim.jobname + '_zevenfreqs.csv')
data = np.loadtxt(fname, delimiter=',', skiprows=1)
gapbands = get_gap_bands(data[:, 5:], light_line=data[:, 4])
### save comparison data to file ###
# If this is not the first step, we have previous data to compare
# with:
if prev_step_data is not None:
sums = []
# compare the first 3 zeven bands:
for j in range(3):
sums.append(
sum_of_squares(
prev_step_data[:, 5 + j],
data[:, 5 + j],
data[:, 4]
)
)
with open("sum_of_squares.dat", "a") as f:
f.write('\t'.join([str(step)] + map(str, sums)) + '\n')
# save data for next iteration:
prev_step_data = data
### save the gap to file ###
# maybe there is no gap?
if len(gapbands) == 0:
gap = 0
elif gapbands[0][0] != 1:
# it must be a gap between band 1 and 2
gap = 0
else:
gap = gapbands[0][3]
# save gap sizes to file (first z-even gap):
with open("gaps.dat", "a") as f:
f.write("{0}\t{1}\n".format(step, gap))
log.info(' ##### step={0} - success! #####\n\n'.format(step))
# reset logger; the next stuff logged is going to next step's file:
log.reset_logger()
### finally, save some plots ###
data = np.loadtxt('sum_of_squares.dat')
fig = plt.figure()
ax = fig.add_subplot(111)
# make double-logarithmic plot for every band:
for i in range(data.shape[1] -1):
ax.loglog(data[:,0], data[:,i + 1], 'o-',
label='band {0}'.format(i+1))
compdata = np.power(data[:,0], -2)
ax.loglog(data[:,0], compdata, '.:', label='$x^{-2}$')
compdata = np.power(data[:,0], -4)
ax.loglog(data[:,0], compdata, '.:', label='$x^{-4}$')
compdata = np.power(data[:,0], -6)
ax.loglog(data[:,0], compdata, '.:', label='$x^{-6}$')
plt.legend()
plt.title('sum of squared differences between simulation steps')
fig.savefig('sum_of_squares.png')
data = np.loadtxt('gaps.dat')
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(data[:,0], data[:,1], 'o-')
plt.title('First z-even band gap for each simulation step')
fig.savefig('gaps.png')
def main():
if len(sys.argv) > 1:
mode=sys.argv[1]
else:
mode='sim'
minrad = 0.2
maxrad = 0.4
radstep = 0.05
numsteps = int((maxrad - minrad) / radstep + 1.5)
steps = np.linspace(minrad, maxrad, num=numsteps, endpoint=True)
for i, radius in enumerate(steps):
log.info("running simulation with {0:n} radius steps:\n{1}".format(
numsteps, steps) +
'\n ### current step: #{0} ({1}) ###\n'.format(i+1, radius))
sim = TriHolesSlab3D(
material='SiN',
radius=radius,
thickness=0.8,
numbands=4,#8,
k_interpolation=5,#31,
resolution=16,#32,
mesh_size=3,#7,
supercell_z=6,
runmode=mode,
num_processors=2,
save_field_patterns=True,
convert_field_patterns=True)
if not sim:
log.error('an error occurred during simulation. See the .out file')
return
# load zeven mode band data:
fname = path.join(sim.workingdir, sim.jobname + '_zevenfreqs.csv')
data = np.loadtxt(fname, delimiter=',', skiprows=1)
gapbands = get_gap_bands(data[:, 5:], light_line=data[:, 4])
# maybe there is no gap?
if len(gapbands) == 0:
gap = 0
elif gapbands[0][0] != 1:
# it must be a gap between band 1 and 2
gap = 0
else:
gap = gapbands[0][3]
# save gap sizes to file (first TE gap):
with open("gaps.dat", "a") as f:
f.write("{0}\t{1}\n".format(radius, gap))
log.info(' ##### radius={0} - success! #####\n\n'.format(radius))
# reset logger; the next stuff logged is going to next step's file:
log.reset_logger()
data = np.loadtxt('gaps.dat')
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(data[:,0], data[:,1], 'o-')
fig.savefig('gaps.png')
def main():
if len(sys.argv) > 1:
mode=sys.argv[1]
else:
mode='sim'
# monkey patching:
# (don't output multiple tiles along y)
# (x and y are switched because of -T)
defaults.mpbdata_call = (
'mpb-data -T -rn%(resolution)s '
'-y%(number_of_tiles_to_output)s '
'-o%(output_file)s '
'%(h5_file)s')
defaults.number_of_tiles_to_output = 5
# defaults.add_epsilon_as_inset = True
defaults.output_funcs_te = [
'fix-hfield-phase', 'output-hfield-z',
'output-dpwr', 'output-hpwr', 'output-tot-pwr']
# the knots of the cubic spline describing the
# k dependent epsilon function:
fknots = np.array(
[0. , 0.03125, 0.0625 , 0.09375, 0.125 , 0.15625,
0.1875 , 0.21875, 0.25 , 0.28125, 0.3125 , 0.34375,
0.375 , 0.40625, 0.4375 , 0.46875, 0.5 ])
# the coefficients of the cubic spline describing the
# k dependent epsilon function:
fcoeffs = np.array(
[[-1.26479352e-02, 3.79438056e-02, -1.39127287e-01,
5.18565342e-01, -1.93513408e+00, 7.22197099e+00,
-2.69527499e+01, 6.47721598e+01, -7.50651090e+01,
-1.26125949e+01, 2.63548544e+02, -2.26207933e+02,
-5.13747147e+01, 1.41246898e+02, -3.11230826e+01,
4.84425567e+01],
[ 3.95247975e-04, -7.90495950e-04, 2.76673582e-03,
-1.02764473e-02, 3.83390535e-02, -1.43079767e-01,
5.33980013e-01, -1.99284029e+00, 4.07954969e+00,
-2.95780428e+00, -4.14023504e+00, 2.05674410e+01,
-6.39552710e-01, -5.45593221e+00, 7.78596450e+00,
4.86817550e+00],
[ -1.70254597e+00, -1.70255832e+00, -1.70249656e+00,
-1.70273124e+00, -1.70185428e+00, -1.70512743e+00,
-1.69291180e+00, -1.73850118e+00, -1.67329151e+00,
-1.63823697e+00, -1.86005070e+00, -1.34670051e+00,
-7.23954002e-01, -9.14437905e-01, -8.41624396e-01,
-4.46182521e-01],
[ 3.64596772e+00, 3.59276316e+00, 3.53955860e+00,
3.48635403e+00, 3.43314947e+00, 3.37994491e+00,
3.32674035e+00, 3.27353579e+00, 3.21923818e+00,
3.16864095e+00, 3.11417266e+00, 3.06004574e+00,
3.03114342e+00, 3.00632747e+00, 2.97673374e+00,
2.95708665e+00]])
ksteps = np.linspace(0., 0.5, num=17)
supcellsize = 13
# The bigger the unit cell, the more bands fold in below the
# waveguide band:
first_wg_band = int(3 + 2 * (supcellsize - 1))
sim = TriHoles2D_Waveguide_effective_epsilon_k_dependent(
epsilon_cubspline_knots=fknots,
epsilon_cubspline_coeffs=fcoeffs,
band_number=first_wg_band,
extra_bands=10,
radius=0.38,
mode='te',
k_steps=ksteps,
supercell_size=supcellsize,
resolution=16,
mesh_size=7,
ensure_y_parity='odd',
runmode=mode,
num_processors=2,
save_field_patterns_kvecs=[
(x, 0, 0) for x in ksteps],
plot_crop_y=False,
convert_field_patterns=True,
gap=(0.44090, 0.52120))
if not sim:
log.error('an error occurred during simulation. See the .out file')
return
log.info(' ##### success! #####\n\n')
def main():
if len(sys.argv) > 1:
mode=sys.argv[1]
else:
mode='sim'
# monkey patching:
# (don't output multiple tiles along y)
# (x and y are switched because of -T)
defaults.mpbdata_call = (
'mpb-data -T -rn%(resolution)s '
'-y%(number_of_tiles_to_output)s '
'-o%(output_file)s '
'%(h5_file)s')
defaults.number_of_tiles_to_output = 5
# defaults.add_epsilon_as_inset = True
defaults.output_funcs_te = [
'fix-hfield-phase', 'output-hfield-z',
'output-dpwr', 'output-hpwr', 'output-tot-pwr']
# the knots of the cubic spline describing the
# frequency dependent epsilon function:
fknots = np.array(
[ 0.43606492, 0.43632591, 0.43699937, 0.43826107, 0.43987166,
0.4405708 , 0.44359142, 0.4540687 , 0.46606201, 0.47865032,
0.49139404, 0.50431241, 0.51692864, 0.53029386, 0.54260207,
0.55531914, 0.56803985])
# the coefficients of the cubic spline describing the
# frequency dependent epsilon function:
fcoeffs = np.array(
[[ 1.05325162e+07, -7.53192904e+06, -5.34491361e+05,
7.35887805e+06, -1.78975790e+07, 1.11124611e+06,
3.50296450e+04, -7.75123125e+03, 2.52814337e+03,
-7.88904847e+02, -1.88305373e+02, -3.86288083e+02,
8.09187014e+03, -2.33155197e+04, 3.20396213e+04,
-1.69215816e+04],
[ 2.72848411e-11, 8.24663379e+03, -6.97063083e+03,
-8.99373723e+03, 2.65628394e+04, -1.09756189e+04,
-9.05673628e+02, 1.95372830e+02, -8.35160080e+01,
1.19591551e+01, -1.82015878e+01, -2.54993856e+01,
-4.01198768e+01, 2.84329111e+02, -5.76587375e+02,
6.45763294e+02],
[ 2.43974026e+01, 2.65496888e+01, 2.74090204e+01,
7.26674591e+00, 3.55635018e+01, 4.64610694e+01,
1.05722403e+01, 3.13021818e+00, 4.47175210e+00,
3.57097220e+00, 3.49142039e+00, 2.92687487e+00,
2.09900754e+00, 5.36291884e+00, 1.76574464e+00,
2.64545990e+00],
[ 2.95227326e+00, 2.95882797e+00, 2.97814765e+00,
3.00055966e+00, 3.01967836e+00, 3.05140955e+00,
3.12223419e+00, 3.17387217e+00, 3.22614445e+00,
3.27424502e+00, 3.32006195e+00, 3.36172191e+00,
3.39381359e+00, 3.43401941e+00, 3.49962690e+00,
3.49472848e+00]])
ksteps = np.linspace(0., 0.5, num=17)
supcellsize = 13
# The bigger the unit cell, the more bands fold in below the
# waveguide band:
first_wg_band = int(3 + 2 * (supcellsize - 1))
sim = TriHoles2D_Waveguide_effective_epsilon_frequency_dependent(
epsilon_cubspline_knots=fknots,
epsilon_cubspline_coeffs=fcoeffs,
band_number=first_wg_band,
extra_bands=4,
init_frequency=0.5,
radius=0.38,
mode='te',
k_steps=ksteps,
supercell_size=supcellsize,
resolution=16,
mesh_size=7,
ensure_y_parity='odd',
runmode=mode,
num_processors=2,
save_field_patterns_kvecs=[
(x, 0, 0) for x in ksteps],
plot_crop_y=False,
convert_field_patterns=True)
if not sim:
log.error('an error occurred during simulation. See the .out file')
return
log.info(' ##### success! #####\n\n')
def main():
if len(sys.argv) > 1:
mode = sys.argv[1]
else:
mode = 'sim'
# monkey patching:
# (don't output multiple tiles along y)
# (x and y are switched because of -T)
defaults.mpbdata_call = ('mpb-data -T -rn%(resolution)s '
'-y%(number_of_tiles_to_output)s '
'-o%(output_file)s '
'%(h5_file)s')
defaults.number_of_tiles_to_output = 5
# defaults.add_epsilon_as_inset = True
defaults.output_funcs_te = [
'fix-hfield-phase', 'output-hfield-z', 'output-dpwr', 'output-hpwr',
'output-tot-pwr'
]
# the knots of the cubic spline describing the
# frequency dependent epsilon function:
fknots = np.array([
0.43606492, 0.43632591, 0.43699937, 0.43826107, 0.43987166, 0.4405708,
0.44359142, 0.4540687, 0.46606201, 0.47865032, 0.49139404, 0.50431241,
0.51692864, 0.53029386, 0.54260207, 0.55531914, 0.56803985
])
# the coefficients of the cubic spline describing the
# frequency dependent epsilon function:
fcoeffs = np.array(
[[
1.05325162e+07, -7.53192904e+06, -5.34491361e+05, 7.35887805e+06,
-1.78975790e+07, 1.11124611e+06, 3.50296450e+04, -7.75123125e+03,
2.52814337e+03, -7.88904847e+02, -1.88305373e+02, -3.86288083e+02,
8.09187014e+03, -2.33155197e+04, 3.20396213e+04, -1.69215816e+04
],
[
2.72848411e-11, 8.24663379e+03, -6.97063083e+03, -8.99373723e+03,
2.65628394e+04, -1.09756189e+04, -9.05673628e+02, 1.95372830e+02,
-8.35160080e+01, 1.19591551e+01, -1.82015878e+01, -2.54993856e+01,
-4.01198768e+01, 2.84329111e+02, -5.76587375e+02, 6.45763294e+02
],
[
2.43974026e+01, 2.65496888e+01, 2.74090204e+01, 7.26674591e+00,
3.55635018e+01, 4.64610694e+01, 1.05722403e+01, 3.13021818e+00,
4.47175210e+00, 3.57097220e+00, 3.49142039e+00, 2.92687487e+00,
2.09900754e+00, 5.36291884e+00, 1.76574464e+00, 2.64545990e+00
],
[
2.95227326e+00, 2.95882797e+00, 2.97814765e+00, 3.00055966e+00,
3.01967836e+00, 3.05140955e+00, 3.12223419e+00, 3.17387217e+00,
3.22614445e+00, 3.27424502e+00, 3.32006195e+00, 3.36172191e+00,
3.39381359e+00, 3.43401941e+00, 3.49962690e+00, 3.49472848e+00
]])
ksteps = np.linspace(0., 0.5, num=17)
supcellsize = 13
# The bigger the unit cell, the more bands fold in below the
# waveguide band:
first_wg_band = int(3 + 2 * (supcellsize - 1))
sim = TriHoles2D_Waveguide_effective_epsilon_frequency_dependent(
epsilon_cubspline_knots=fknots,
epsilon_cubspline_coeffs=fcoeffs,
band_number=first_wg_band,
extra_bands=4,
init_frequency=0.5,
radius=0.38,
mode='te',
k_steps=ksteps,
supercell_size=supcellsize,
resolution=16,
mesh_size=7,
ensure_y_parity='odd',
runmode=mode,
num_processors=2,
save_field_patterns_kvecs=[(x, 0, 0) for x in ksteps],
plot_crop_y=False,
convert_field_patterns=True)
if not sim:
log.error('an error occurred during simulation. See the .out file')
return
log.info(' ##### success! #####\n\n')
