def modes_n_gain(wguide):
print('Commencing mode calculation for width a_x = %f' % wguide.inc_a_x)
# Expected effective index of fundamental guided mode.
n_eff = (wguide.material_a.n - 0.1) * wguide.inc_a_x / known_geo
# Calculate Electromagnetic modes.
sim_EM_pump = wguide.calc_EM_modes(num_modes_EM_pump, wl_nm, n_eff)
sim_EM_Stokes = mode_calcs.bkwd_Stokes_modes(sim_EM_pump)
k_AC = np.real(sim_EM_pump.Eig_values[EM_ival_pump] -
sim_EM_Stokes.Eig_values[EM_ival_Stokes])
# Calculate Acoustic modes.
sim_AC = wguide.calc_AC_modes(num_modes_AC, k_AC, EM_sim=sim_EM_pump)
# Calculate interaction integrals and SBS gain.
SBS_gain, SBS_gain_PE, SBS_gain_MB, linewidth_Hz, Q_factors, alpha = integration.gain_and_qs(
sim_EM_pump,
sim_EM_Stokes,
sim_AC,
k_AC,
EM_ival_pump=EM_ival_pump,
EM_ival_Stokes=EM_ival_Stokes,
AC_ival=AC_ival)
## Clear memory
#sim_EM_pump = sim_EM_Stokes = sim_AC = None
print('Completed mode calculation for width a_x = %f' % wguide.inc_a_x)
return [
sim_EM_pump, sim_AC, SBS_gain, SBS_gain_PE, SBS_gain_MB, linewidth_Hz,
k_AC
]
def modes_n_gain(inc_a_x):
inc_a_y = inc_a_x
# Use all specified parameters to create a waveguide object.
wguide = objects.Struct(unitcell_x,inc_a_x,unitcell_y,inc_a_y,inc_shape,
material_bkg=materials.materials_dict["Vacuum"],
material_a=materials.materials_dict["SiO2_2016_Smith"],
lc_bkg=1, lc_refine_1=400.0, lc_refine_2=50.0)
sim_EM_pump = wguide.calc_EM_modes(num_modes_EM_pump, wl_nm, n_eff=n_eff)
sim_EM_Stokes = mode_calcs.bkwd_Stokes_modes(sim_EM_pump)
k_AC = np.real(sim_EM_pump.Eig_values[EM_ival_pump] - sim_EM_Stokes.Eig_values[EM_ival_Stokes])
shift_Hz = 4e9
sim_AC = wguide.calc_AC_modes(num_modes_AC, k_AC, EM_sim=sim_EM_pump, shift_Hz=shift_Hz)
set_q_factor = 600.
SBS_gain, SBS_gain_PE, SBS_gain_MB, linewidth_Hz, Q_factors, alpha = integration.gain_and_qs(
sim_EM_pump, sim_EM_Stokes, sim_AC, k_AC,
EM_ival_pump=EM_ival_pump, EM_ival_Stokes=EM_ival_Stokes, AC_ival=AC_ival)#, fixed_Q=set_q_factor)
interp_values = plotting.gain_spectra(sim_AC, SBS_gain, SBS_gain_PE, SBS_gain_MB, linewidth_Hz, k_AC,
EM_ival_pump, EM_ival_Stokes, AC_ival, freq_min, freq_max, num_interp_pts=num_interp_pts,
save_fig=False, suffix_str='%i' %int(inc_a_x))
# Clear memory
wguide = sim_EM_pump = sim_EM_Stokes = sim_AC = None
SBS_gain = SBS_gain_PE = SBS_gain_MB = linewidth_Hz = Q_factors = alpha = None
return interp_values
def ac_mode_freqs(coat_y):
print('Commencing mode calculation for coat_y = %f'% coat_y)
wguide = objects.Struct(unitcell_x,inc_a_x,unitcell_y,inc_a_y,inc_shape,
slab_a_x=slab_a_x, slab_a_y=slab_a_y, inc_b_x=inc_b_x,
coat_y=coat_y,
material_bkg=materials.Vacuum, # background
material_a=materials.As2S3_2017_Morrison, # slot
material_b=materials.SiO2_2013_Laude, # slab
material_c=materials.Si_2016_Smith, # walls of slot
material_d=materials.SiO2_2013_Laude, # coating
lc_bkg=5, lc2=2000.0, lc3=1000.0)
# Expected effective index of fundamental guided mode.
n_eff = wguide.material_a.n-0.1
# Calculate Electromagnetic modes.
sim_EM_pump = wguide.calc_EM_modes(num_modes_EM_pump, wl_nm, n_eff=n_eff)
sim_EM_Stokes = mode_calcs.bkwd_Stokes_modes(sim_EM_pump)
k_AC = np.real(sim_EM_pump.Eig_values[EM_ival_pump] - sim_EM_Stokes.Eig_values[EM_ival_Stokes])
shift_Hz = 4e9
# Calculate Acoustic modes.
sim_AC = wguide.calc_AC_modes(num_modes_AC, k_AC, EM_sim=sim_EM_pump, shift_Hz=shift_Hz)
# plotting.plt_mode_fields(sim_AC, xlim_min=0.4, xlim_max=0.4,
# ylim_min=0.7, ylim_max=0.0, EM_AC='AC',
# prefix_str=prefix_str, suffix_str='_%i' %int(coat_y))
set_q_factor = 1000.
SBS_gain, SBS_gain_PE, SBS_gain_MB, linewidth_Hz, Q_factors, alpha = integration.gain_and_qs(
sim_EM_pump, sim_EM_Stokes, sim_AC, k_AC,
EM_ival_pump=EM_ival_pump, EM_ival_Stokes=EM_ival_Stokes, AC_ival=AC_ival, fixed_Q=set_q_factor)
# Construct the SBS gain spectrum, built from Lorentzian peaks of the individual modes.
freq_min = 4 # np.real(sim_AC.Eig_values[0])*1e-9 - 2 # GHz
freq_max = 14 # np.real(sim_AC.Eig_values[-1])*1e-9 + 2 # GHz
plotting.gain_spectra(sim_AC, SBS_gain, SBS_gain_PE, SBS_gain_MB, linewidth_Hz, k_AC,
EM_ival_pump, EM_ival_Stokes, AC_ival, freq_min=freq_min, freq_max=freq_max,
prefix_str=prefix_str, suffix_str='_%i' %int(coat_y))
# Convert to GHz
mode_freqs = sim_AC.Eig_values*1.e-9
# Clear memory
wguide = sim_EM_pump = sim_EM_Stokes = sim_AC = None
SBS_gain = SBS_gain_PE = SBS_gain_MB = linewidth_Hz = Q_factors = alpha = None
print('Completed mode calculation for coating coat_y = %f'% coat_y)
# Return the frequencies and simulated k_ac value in a list
return mode_freqs
sim_EM_Stokes = mode_calcs.bkwd_Stokes_modes(sim_EM_pump)
k_AC = np.real(sim_EM_pump.Eig_values[0] - sim_EM_Stokes.Eig_values[0])
# Calculate Acoustic Modes
sim_AC_wguide = wguide.calc_AC_modes(num_AC_modes,
k_AC=k_AC,
EM_sim=sim_EM_pump)
# Calculate interaction integrals and SBS gain for PE and MB effects combined,
# as well as just for PE, and just for MB. Also calculate acoustic loss alpha.
SBS_gain, SBS_gain_PE, SBS_gain_MB, linewidth_Hz, Q_factors, alpha = integration.gain_and_qs(
sim_EM_pump,
sim_EM_Stokes,
sim_AC_wguide,
k_AC,
EM_ival_pump=EM_ival_pump,
EM_ival_Stokes=EM_ival_Stokes,
AC_ival=AC_ival)
# Mask negligible gain values to improve clarity of print out.
threshold = 1e-9
threshold_indices = abs(SBS_gain_PE) < threshold
SBS_gain_PE[threshold_indices] = 0
threshold_indices = abs(SBS_gain_MB) < threshold
SBS_gain_MB[threshold_indices] = 0
threshold_indices = abs(SBS_gain) < threshold
SBS_gain[threshold_indices] = 0
masked_PE = SBS_gain_PE[EM_ival_pump, EM_ival_Stokes, :]
masked_MB = SBS_gain_MB[EM_ival_pump, EM_ival_Stokes, :]
masked = SBS_gain[EM_ival_pump, EM_ival_Stokes, :]
