forked from chiuhans111/RCWA
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathtest_in_couple.py
138 lines (104 loc) · 3.96 KB
/
test_in_couple.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
import tensorflow as tf
from RCWA.Domain import Domain
from RCWA.Modes import Modes
from RCWA.EigenMode import EigenMode
from RCWA.ScatterMat import ScatterMatBuilder
from RCWA.Device import SlantGrating
from RCWA import Utils
import numpy as np
import matplotlib.pyplot as plt
# Reference:
# [1] M. A. Golub and A. A. Friesem,
# “Effective grating theory for resonance domain surface-relief diffraction gratings,”
# J. Opt. Soc. Am. A, vol. 22, no. 6, p. 1115, Jun. 2005, doi: 10.1364/JOSAA.22.001115.
period = 0.357
n1 = 1
n2 = 2
er1 = n1**2
er2 = n2**2
ur1 = 1
ur2 = 1
domain = Domain()
domain.set_period_centered(period, period)
modes = Modes(domain)
modes.set_harmonics(10, 0)
def run(AOI):
modes.set_incidence_AOI_POI(
AOI=np.deg2rad(AOI),
POI=np.deg2rad(0))
modes.set_wavelength(0.530)
# Default Matrix
sbuilder = ScatterMatBuilder(modes)
ref_mode = EigenMode(modes)
trn_mode = EigenMode(modes)
ref_mode.from_homogeneous(er1, ur1)
trn_mode.from_homogeneous(er2, ur2)
Sref = sbuilder.BuildScatterRef(ref_mode)
Strn = sbuilder.BuildScatterTrn(trn_mode)
Sglobal = Sref
# Create Device
S = SlantGrating(modes, sbuilder, n1=n1, n2=n2,
ff=0.5,
slant_angle=np.deg2rad(35),
depth=0.8,
dff=-1,
dz=0.02)
Sglobal = Sglobal @ S
Sglobal = Sglobal @ Strn
# Incidence
delta = (modes.mx == 0)*(modes.my == 0)
def incidence(S, pol_angle_deg):
# Set amplitudes for s and p polarizations
pol_angle = np.deg2rad(pol_angle_deg)
amp_s = tf.sin(pol_angle) # 90 degree, TE
amp_p = tf.cos(pol_angle) # 0 degree, TM
# Calculate the polarization vector based on s and p amplitudes
pol = modes.pol_vec_p * amp_p + modes.pol_vec_s * amp_s
# Calculate the incident electric field components
Einc = tf.cast(
tf.concat([delta*pol[0], delta*pol[1]], 0), tf.dtypes.complex128)
Einc_z = delta*pol[2]
# Calculate the incident intensity
Iinc = tf.reduce_sum(np.abs(Einc)**2)+tf.reduce_sum(np.abs(Einc_z)**2)
# Calculate the longitudinal wave vector components
kz_r = tf.sqrt((n1**2-modes.kx**2-modes.ky**2).astype('complex'))
kz_t = tf.sqrt((n2**2-modes.kx**2-modes.ky**2).astype('complex'))
# Calculate the electric field components using the scattering matrix
Eref = tf.reshape((S.value[0]@Einc[:, None]), [2, -1])
Etrn = tf.reshape((S.value[2]@Einc[:, None]), [2, -1])
# Calculate the longitudinal electric field components
Eref_z = -(Eref[0]*modes.kx+Eref[1]*modes.ky)/kz_r
Etrn_z = -(Etrn[0]*modes.kx+Etrn[1]*modes.ky)/kz_t
# Calculate the reflected and transmitted intensities
Iref = tf.reduce_sum(tf.abs(Eref)**2, 0)+tf.abs(Eref_z)**2
Itrn = tf.reduce_sum(tf.abs(Etrn)**2, 0)+tf.abs(Etrn_z)**2
# Calculate the reflection and transmission coefficients
R = Iref*tf.math.real(kz_r)/modes.k0z/Iinc
T = Itrn*tf.math.real(kz_t)/modes.k0z/Iinc
return Eref, Etrn, R, T
Eref, Etrn, R_TM, T_TM = incidence(Sglobal, 0)
Eref, Etrn, R_TE, T_TE = incidence(Sglobal, 90)
print(np.sum(R_TM+T_TM))
print("Error:", 1-np.sum(R_TM+T_TM))
print(np.sum(R_TE+T_TE))
print("Error:", 1-np.sum(R_TE+T_TE))
return R_TM, T_TM, R_TE, T_TE
plt.figure(figsize=(6, 4), dpi=150)
AOIs = np.linspace(-30, 30, 21)
tm = []
te = []
for AOI in AOIs:
R_TM, T_TM, R_TE, T_TE = run(AOI)
tm.append(np.sum(T_TM * (modes.mx == -1) * (modes.my == 0)))
te.append(np.sum(T_TE * (modes.mx == -1) * (modes.my == 0)))
plt.plot(AOIs, tm, label='TM')
plt.plot(AOIs, te, label='TE')
np.save(f'./save/in_couple_tm', tm)
np.save(f'./save/in_couple_te', te)
plt.grid()
plt.ylabel('Diffraction Efficiency, 1st order')
plt.xlabel('Incidence Angle')
plt.legend()
plt.tight_layout()
plt.savefig('./result/in_coupling.png')
plt.show()