def t2_spe_vs_n():
n_list = np.append(np.linspace(1, 1.45, num=25), np.linspace(1.45, 1.55, num=50))
n_list = np.append(n_list, np.linspace(1.55, 2, num=25))
# n_list = [1, 1.33, 1.37, 1.47]
spe_list = []
leaky_list = []
guided_list = []
for n in n_list:
print('Evaluating n={:g}'.format(n))
# Create structure
st = LifetimeTmm()
st.set_vacuum_wavelength(lam0)
st.add_layer(0, sio2)
st.add_layer(d_etds, edts)
st.add_layer(0, n)
st.info()
# Calculate spontaneous emission of layer 0 (1st)
result = st.calc_spe_structure()
leaky = result['leaky']['avg']
try:
guided = result['guided']['avg']
except KeyError:
guided = 0
# Average over layer
leaky = np.mean(leaky)
guided = np.mean(guided)
# Append to list
leaky_list.append(leaky)
guided_list.append(guided)
spe_list.append(leaky + guided)
# Convert lists to arrays
n_list = np.array(n_list)
leaky_list = np.array(leaky_list)
guided_list = np.array(guided_list)
spe_list = np.array(spe_list)
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, sharex='col', sharey='none')
ax1.plot(n_list, spe_list, '.-', label='leaky + guided')
ax2.plot(n_list, leaky_list, '.-', label='leaky')
ax3.plot(n_list, guided_list, '.-', label='guided')
ax3.set_xlim(1, 2)
ax1.set_title('Average Spontaneous Emission Rate for Random Orientated Dipole in T2.')
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax2.set_ylabel('$\Gamma / \Gamma_0$')
ax2.set_xlabel('n')
ax1.legend()
ax2.legend()
ax3.legend()
plt.tight_layout()
if SAVE:
plt.savefig('../Images/t2_vs_n.png', dpi=300)
np.savez('../Data/t2_vs_n', n=n_list, spe=spe_list, guided=guided_list, leaky=leaky_list)
plt.show()
def t2():
"""
T2 EDTS layer next to air.
"""
# Create structure
st = LifetimeTmm()
st.set_vacuum_wavelength(lam0)
st.add_layer(2 * lam0, sio2)
st.add_layer(d_etds, edts)
st.add_layer(2 * lam0, air)
st.info()
# Calculate spontaneous emission for leaky and guided modes
result = st.calc_spe_structure(th_pow=9)
z = result['z']
z = st.calc_z_to_lambda(z)
# Plot results
fig, (ax1, ax2) = plt.subplots(2, 1, sharex='col', sharey='none')
ax1.plot(z, result['leaky']['avg'], label='leaky')
try:
ax2.plot(z, result['guided']['avg'], label='guided')
except KeyError:
pass
# Plot internal layer boundaries
for z in st.get_layer_boundaries()[:-1]:
z = st.calc_z_to_lambda(z)
ax1.axvline(z, color='k', lw=1, ls='--')
ax2.axvline(z, color='k', lw=1, ls='--')
# ax1.set_title('Spontaneous emission rate at boundary for semi-infinite media. LHS n=1.57.')
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax2.set_ylabel('$\Gamma / \Gamma_0$')
ax2.set_xlabel('Position z ($\lambda$/2$\pi$)')
ax1.legend()
ax2.legend()
plt.tight_layout()
if SAVE:
plt.savefig('../Images/t2.png', dpi=300)
plt.show()
def purcell_factor():
"""
T2 next to two mediums.
Leaky and guided separate plots.
Evaluate purcell factor for randomly orientated dipole averaged over film thickness.
"""
# Medium 1
# Create structure
st = LifetimeTmm()
st.set_vacuum_wavelength(lam0)
st.add_layer(2 * lam0, sio2)
st.add_layer(d_etds, edts)
st.add_layer(2 * lam0, air)
st.info()
# Calculate spontaneous emission for leaky and guided modes
result = st.calc_spe_structure(th_pow=11)
z = result['z']
z = st.calc_z_to_lambda(z)
# Plot results
fig, (ax1, ax2) = plt.subplots(2, 1, sharex='col', sharey='none')
ax1.plot(z, result['leaky']['avg'], label='leaky, air')
try:
ax2.plot(z, result['guided']['avg'], label='guided, air')
except KeyError:
pass
spe_air = result['leaky']['avg'] + result['guided']['avg']
# Medium 2
# Create structure
st = LifetimeTmm()
st.set_vacuum_wavelength(lam0)
st.add_layer(2 * lam0, sio2)
st.add_layer(d_etds, edts)
st.add_layer(2 * lam0, water)
st.info()
# Calculate spontaneous emission for leaky and guided modes
result = st.calc_spe_structure(th_pow=11)
z = result['z']
z = st.calc_z_to_lambda(z)
# Plot results
ax1.plot(z, result['leaky']['avg'], label='leaky, water')
try:
ax2.plot(z, result['guided']['avg'], label='guided, water')
except KeyError:
pass
spe_water = result['leaky']['avg'] + result['guided']['avg']
fp = np.mean(spe_water) / np.mean(spe_air)
print('Purcell Factor: {:e}'.format(fp))
# Plot internal layer boundaries
for z in st.get_layer_boundaries()[:-1]:
z = st.calc_z_to_lambda(z)
ax1.axvline(z, color='k', lw=1, ls='--')
ax2.axvline(z, color='k', lw=1, ls='--')
# ax1.set_title('Spontaneous emission rate at boundary for semi-infinite media. LHS n=1.57.')
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax2.set_ylabel('$\Gamma / \Gamma_0$')
ax2.set_xlabel('Position z ($\lambda$)')
ax1.legend()
ax2.legend()
plt.tight_layout()
if SAVE:
plt.savefig('../Images/T2_purcell_factor.png', dpi=300)
fig, ax1 = plt.subplots()
z = result['z']
ax1.plot(z, spe_air, label='Air')
ax1.plot(z, spe_water, label='Water')
# Plot internal layer boundaries
for z in st.get_layer_boundaries()[:-1]:
z = st.calc_z_to_lambda(z)
ax1.axvline(z, color='k', lw=1, ls='--')
ax1.set_ylabel('$\Gamma / \Gamma_0$')
ax1.set_xlabel('Position z ($\lambda$)')
# ax1.get_xaxis().get_major_formatter().set_useOffset(False)
ax1.legend()
plt.tight_layout()
if SAVE:
plt.savefig('../Images/T2_purcell_factor_total.png', dpi=300)
plt.show()
