def supplementary_material1():
""" SE rate for Silicon to air semi-infinite half spaces."""
# """Plot leaky and guided SE rates and then sum for randomly orientated dipole."""
# WIDTH = 412.56 # the number (in pt) latex spits out when typing: \the\linewidth (paper 246, thesis 412.56)
# FACTOR = 0.8 # the fraction of the width you'd like the figure to occupy
lam0 = 1540
# Create structure
st = SPE()
st.add_layer(0.05 * lam0, 3.48)
st.add_layer(50, 2)
st.add_layer(0.05 * lam0, 1)
st.set_vacuum_wavelength(lam0)
st.info()
# Calculate
res = st.calc_spe_structure(th_pow=11)
z = res['z']
# Convert z into z/lam0 and center
z = st.calc_z_to_lambda(z)
# ------- Plots -------
# Plot data
fig, ax1 = plt.subplots()
ax1.plot(z, res['leaky']['avg'], label='Avg')
ax1.plot(z, res['leaky']['parallel'], '--', label=r'$\parallel$')
ax1.plot(z, res['leaky']['perpendicular'], '-.', label=r'$\bot$')
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax1.set_xlabel('Position z [$\lambda$]')
ax1.legend(fontsize='small')
ax1.set_ylim(0, ax1.get_ylim()[1])
bounds = ax1.get_ylim()
# Draw rectangles for the refractive index
ax2 = ax1.twinx()
for z0, dz, n in zip(st.d_cumulative, st.d_list, st.n_list):
z0 = st.calc_z_to_lambda(z0)
dz = st.calc_z_to_lambda(dz, center=False)
rect = Rectangle((z0 - dz, 0), dz, n.real, facecolor='c', alpha=0.15)
ax2.add_patch(rect) # Note: add to ax1 so that zorder has effect
ax2.set_ylabel('n')
ax2.set_ylim(bounds)
ax1.set_zorder(ax2.get_zorder() + 1) # put ax1 in front of ax2
ax1.patch.set_visible(False) # hide ax1'canvas'
for zb in st.get_layer_boundaries()[:-1]:
zb = st.calc_z_to_lambda(zb)
ax1.axvline(x=zb, color='k', lw=2)
ax1.set_xlim([min(z), max(z)])
if SAVE:
plt.savefig('../Images/SupplementaryMaterial1')
plt.show()
def fig4():
""" n=3 or n=1 (air) to n=1.5 (Erbium deposition) semi-infinite half spaces.
Plot the average total spontaneous emission rate of dipoles as a function of
distance from the interface.
"""
# Vacuum wavelength
lam0 = 1550
# Plotting units
units = lam0 / (2 * pi)
# Create plot
f, ax = plt.subplots()
for n in [1, 2]:
print('Evaluating n={:g}'.format(n))
# Create structure
st = SPE()
st.add_layer(4 * units, n)
st.add_layer(4 * units, 1.5)
st.set_vacuum_wavelength(lam0)
st.info()
# Calculate spontaneous emission over whole structure
result = st.calc_spe_structure()
z = result['z']
# Shift so centre of structure at z=0
z -= st.get_structure_thickness() / 2
spe = result['leaky']['avg']
# Plot spontaneous emission rates
ax.plot(z / units, spe, label=('n=' + str(n)), lw=2)
ax.axhline(y=n, xmin=0, xmax=0.4, ls='dotted', color='k', lw=2)
# Plot internal layer boundaries
for z in st.get_layer_boundaries()[:-1]:
# Shift so centre of structure at z=0
z -= st.get_structure_thickness() / 2
ax.axvline(z / units, color='k', lw=2)
ax.axhline(1.5, ls='--', color='k', lw=2)
ax.set_title(
'Spontaneous emission rate at boundary for semi-infinite media. RHS n=1.5.'
)
ax.set_ylabel('$\Gamma / \Gamma_0$')
ax.set_xlabel('Position z ($\lambda$/2$\pi$)')
plt.legend(title='LHS n')
plt.tight_layout()
if SAVE:
plt.savefig('../Images/spe_vs_n.png', dpi=300)
plt.show()
def example3():
""" SE rate for Silicon to air semi-infinite half spaces."""
# """Plot leaky and guided SE rates and then sum for randomly orientated dipole."""
lam0 = 1540
# Create structure
st = SPE()
st.add_layer(0.5 * lam0, 1.45)
st.add_layer(100, 1.65)
st.add_layer(500, 1.45)
st.add_layer(0.5 * lam0, 1)
st.set_vacuum_wavelength(lam0)
st.info()
# Calculate
res = st.calc_spe_structure(th_pow=11)
z = res['z']
# Convert z into z/lam0 and center
z = st.calc_z_to_lambda(z)
# ------- Plots -------
# Plot data
fig, ax1 = plt.subplots()
if st.supports_guiding():
ax1.plot(z, res['leaky']['avg'] + res['guided']['avg'], label='Avg')
ax1.plot(z,
res['leaky']['parallel'] + res['guided']['parallel'],
'--',
label=r'$\parallel$')
ax1.plot(z,
res['leaky']['perpendicular'] +
res['guided']['perpendicular'],
'-.',
label=r'$\bot$')
else:
ax1.plot(z, res['leaky']['avg'], label='Avg')
ax1.plot(z, res['leaky']['parallel'], '--', label=r'$\parallel$')
ax1.plot(z, res['leaky']['perpendicular'], '-.', label=r'$\bot$')
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax1.set_xlabel('Position z [$\lambda$]')
ax1.legend(fontsize='small')
ax1.set_ylim(0, ax1.get_ylim()[1])
bounds = ax1.get_ylim()
# Draw rectangles for the refractive index
ax2 = ax1.twinx()
for z0, dz, n in zip(st.d_cumulative, st.d_list, st.n_list):
z0 = st.calc_z_to_lambda(z0)
dz = st.calc_z_to_lambda(dz, center=False)
rect = Rectangle((z0 - dz, 0), dz, n.real, facecolor='c', alpha=0.15)
ax2.add_patch(rect) # Note: add to ax1 so that zorder has effect
ax2.set_ylabel('n')
ax2.set_ylim(bounds)
ax1.set_zorder(ax2.get_zorder() + 1) # put ax1 in front of ax2
ax1.patch.set_visible(False) # hide ax1'canvas'
for zb in st.get_layer_boundaries()[:-1]:
zb = st.calc_z_to_lambda(zb)
ax1.axvline(x=zb, color='k', lw=2)
ax1.set_xlim([min(z), max(z)])
if SAVE:
plt.savefig('../Images/Air')
plt.show()
def example1():
""" SE rate for Silicon to air semi-infinite half spaces."""
from lifetmm.SPE import SPE
import pandas as pd
from lifetmm.Materials import n_1540nm as sample
"""Plot leaky and guided SE rates and then sum for randomly orientated dipole."""
# Load Sample Data
df = pd.read_csv('../Data/Screening.csv', index_col='Sample ID')
n = df.loc[sample]['n']
d = df.loc[sample]['d'] * 1e3 # in nm not um
chip = {'Sample ID': sample, 'n': n, 'd': d}
# Create Structure
st = SPE()
st.set_vacuum_wavelength(lam0)
st.add_layer(d_clad * lam0, n_dict['SiO2'])
st.add_layer(chip['d'], chip['n'])
st.add_layer(d_clad * lam0, n_dict['Air'])
st.info()
# Calculate
res = st.calc_spe_structure(th_pow=11)
z = res['z']
z = st.calc_z_to_lambda(z)
# ------- Plots -------
fig, (ax1, ax2) = plt.subplots(2, 1, sharex='col', sharey='none')
ax1.plot(z, res['leaky']['avg'])
if st.supports_guiding():
ax2.plot(z, res['guided']['avg'])
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax2.set_ylabel('$\Gamma / \Gamma_0$')
ax2.set_xlabel('Position z ($\lambda$)')
ax1.set_title('Leaky')
ax2.set_title('Guided')
for zb in st.get_layer_boundaries()[:-1]:
zb = st.calc_z_to_lambda(zb)
ax1.axvline(x=zb, color='k', lw=2)
ax2.axvline(x=zb, color='k', lw=2)
# Draw rectangles for the refractive index
ax1b = ax1.twinx()
ax2b = ax2.twinx()
for z0, dz, n in zip(st.d_cumulative, st.d_list, st.n_list):
z0 = st.calc_z_to_lambda(z0)
dz = st.calc_z_to_lambda(dz, center=False)
rect = Rectangle((z0 - dz, 0), dz, n.real, facecolor='c', alpha=0.2)
ax1b.add_patch(rect)
ax1b.set_ylabel('n')
ax1b.set_ylim(0, 1.5 * max(st.n_list.real))
rect = Rectangle((z0 - dz, 0), dz, n.real, facecolor='c', alpha=0.2)
ax2b.add_patch(rect)
ax2b.set_ylabel('n')
ax2b.set_ylim(0, 1.5 * max(st.n_list.real))
ax1.set_zorder(ax1b.get_zorder() + 1) # put ax1 in front of ax2
ax1.patch.set_visible(False) # hide ax1'canvas'
ax2.set_zorder(ax2b.get_zorder() + 1) # put ax1 in front of ax2
ax2.patch.set_visible(False) # hide ax1'canvas'
if SAVE:
plt.savefig('../Images/{}_individual'.format(chip['Sample ID']))
fig, ax1 = plt.subplots()
if st.supports_guiding():
ax1.plot(z, res['leaky']['avg'] + res['guided']['avg'], label='Avg')
else:
ax1.plot(z, res['leaky']['avg'], label='Avg')
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax1.set_xlabel('Position z ($\lambda$)')
ax1.legend()
# Draw rectangles for the refractive index
ax2 = ax1.twinx()
for z0, dz, n in zip(st.d_cumulative, st.d_list, st.n_list):
z0 = st.calc_z_to_lambda(z0)
dz = st.calc_z_to_lambda(dz, center=False)
rect = Rectangle((z0 - dz, 0), dz, n.real, facecolor='c', alpha=0.15)
ax2.add_patch(rect) # Note: add to ax1 so that zorder has effect
ax2.set_ylabel('n')
ax2.set_ylim(0, 1.5 * max(st.n_list.real))
ax1.set_zorder(ax2.get_zorder() + 1) # put ax1 in front of ax2
ax1.patch.set_visible(False) # hide ax1'canvas'
for zb in st.get_layer_boundaries()[:-1]:
zb = st.calc_z_to_lambda(zb)
ax1.axvline(x=zb, color='k', lw=2)
if SAVE:
plt.savefig('../Images/{}_total'.format(chip['Sample ID']))
plt.show()
def fig7():
"""
Silicon layer bounded by two semi infinite air claddings.
"""
d_list = np.arange(start=11, stop=2511, step=5)
te_guided = []
tm_guided_p = []
te_leaky = []
tm_leaky_p = []
tm_guided_s = []
tm_leaky_s = []
k0 = 2 * np.pi / lam0
for d in d_list:
# Create structure
st = SPE()
st.add_layer(0, air)
st.add_layer(d, si)
st.add_layer(0, air)
st.set_vacuum_wavelength(lam0)
st.info()
# Calculate spontaneous emission of layer
result = st.calc_spe_structure(th_pow=9)
z = result['z']
iloc = int((len(z) - 1) / 2)
leaky = result['leaky']
try:
guided = result['guided']
te_guided.append(guided['TE'][iloc])
tm_guided_p.append(guided['TM_p'][iloc])
tm_guided_s.append(guided['TM_s'][iloc])
except KeyError:
te_guided.append(0)
tm_guided_p.append(0)
tm_guided_s.append(0)
te_leaky.append(leaky['TE'][iloc])
tm_leaky_p.append(leaky['TM_p'][iloc])
tm_leaky_s.append(leaky['TM_s'][iloc])
# Convert lists to arrays
d_list = np.array(d_list)
te_guided = np.array(te_guided)
tm_guided_p = np.array(tm_guided_p)
tm_guided_s = np.array(tm_guided_s)
te_leaky = np.array(te_leaky)
tm_leaky_p = np.array(tm_leaky_p)
tm_leaky_s = np.array(tm_leaky_s)
# Plot spontaneous emission rates
fig = plt.figure()
ax1 = fig.add_subplot(211)
ax1.plot(d_list * k0, te_guided, label='TE guided')
ax1.plot(d_list * k0, tm_guided_p, label='TM guided')
ax1.plot(d_list * k0, te_leaky, 'k', label='TE leaky')
ax1.plot(d_list * k0, tm_leaky_p, 'k', label='TM leaky')
total = tm_leaky_p + te_leaky + tm_guided_p + te_guided
ax1.plot(d_list * k0, total, 'k', label='total')
ax2 = fig.add_subplot(212)
ax2.plot(d_list * k0, tm_guided_s, 'k', label='TM guided')
ax2.plot(d_list * k0, tm_leaky_s * 20, 'k', label='TM leaky')
# ax1.set_ylim(0, 1.4)
# ax2.set_ylim(0, 1.4)
# ax1.set_title('Spontaneous Emission Rate. Silicon (n=3.48) with air cladding (n=1.)')
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax2.set_ylabel('$\Gamma /\Gamma_0$')
# ax2.set_xlabel('z/$\lambda$')
ax1.legend(title='Horizontal Dipoles',
loc='lower right',
fontsize='medium')
ax2.legend(title='Vertical Dipoles', loc='lower right', fontsize='medium')
if SAVE:
plt.savefig('../Images/creatore_fig6')
plt.show()
