def setUp(self):
susceptibilities = [
mp.LorentzianSusceptibility(frequency=1.1, gamma=1e-5, sigma=0.5),
mp.LorentzianSusceptibility(frequency=0.5, gamma=0.1, sigma=2e-5)
]
default_material = mp.Medium(epsilon=2.25,
E_susceptibilities=susceptibilities)
fcen = 1.0
df = 2.0
sources = mp.Source(mp.GaussianSource(fcen, fwidth=df),
component=mp.Ez,
center=mp.Vector3())
kmin = 0.3
kmax = 2.2
k_interp = 5
self.kpts = mp.interpolate(
k_interp, [mp.Vector3(kmin), mp.Vector3(kmax)])
self.sim = mp.Simulation(cell_size=mp.Vector3(),
geometry=[],
sources=[sources],
default_material=default_material,
resolution=20)
def test_list_split(self):
k_points = [
mp.Vector3(),
mp.Vector3(0.5),
mp.Vector3(0.5, 0.5),
mp.Vector3()
]
k_points = mp.interpolate(4, k_points)
ms = mpb.ModeSolver()
k_split = ms.list_split(k_points, 1, 0)
expected_list = [
mp.Vector3(),
mp.Vector3(0.10000000000000003),
mp.Vector3(0.20000000000000004),
mp.Vector3(0.30000000000000004),
mp.Vector3(0.4),
mp.Vector3(0.5),
mp.Vector3(0.5, 0.10000000000000003),
mp.Vector3(0.5, 0.20000000000000004),
mp.Vector3(0.5, 0.30000000000000004),
mp.Vector3(0.5, 0.4),
mp.Vector3(0.5, 0.5),
mp.Vector3(0.4, 0.4),
mp.Vector3(0.30000000000000004, 0.30000000000000004),
mp.Vector3(0.2, 0.2),
mp.Vector3(0.1, 0.1),
mp.Vector3(0.0, 0.0),
]
self.assertEqual(k_split[0], 0)
for res, exp in zip(k_split[1], expected_list):
self.assertTrue(res.close(exp))
def test_interpolate_vectors(self):
expected = [
mp.Vector3(),
mp.Vector3(0.024999999999999842),
mp.Vector3(0.04999999999999984),
mp.Vector3(0.07499999999999984),
mp.Vector3(0.09999999999999984),
mp.Vector3(0.12499999999999983),
mp.Vector3(0.14999999999999983),
mp.Vector3(0.17499999999999982),
mp.Vector3(0.19999999999999982),
mp.Vector3(0.2249999999999998),
mp.Vector3(0.2499999999999998),
mp.Vector3(0.2749999999999998),
mp.Vector3(0.2999999999999998),
mp.Vector3(0.32499999999999984),
mp.Vector3(0.34999999999999987),
mp.Vector3(0.3749999999999999),
mp.Vector3(0.3999999999999999),
mp.Vector3(0.42499999999999993),
mp.Vector3(0.44999999999999996),
mp.Vector3(0.475),
mp.Vector3(0.5)
]
res = mp.interpolate(19, [mp.Vector3(), mp.Vector3(0.5)])
np.testing.assert_allclose([v.x for v in expected], [v.x for v in res])
np.testing.assert_allclose([v.y for v in expected], [v.y for v in res])
np.testing.assert_allclose([v.z for v in expected], [v.z for v in res])
def triangular_with_defect():
k_points = [mp.Vector3(),
mp.Vector3(0., 0.5),
mp.Vector3(-1 / 3, 1 / 3),
mp.Vector3()]
k_points = mp.interpolate(10, k_points)
geometry_lattice = mp.Lattice(size=mp.Vector3(5, 5),
basis1=mp.Vector3(math.sqrt(3) / 2, 0.5),
basis2=mp.Vector3(math.sqrt(3) / 2, -0.5))
geometry = [mp.Cylinder(0.25, material=gaas)]
geometry = mp.geometric_objects_lattice_duplicates(geometry_lattice, geometry)
defect = mp.Cylinder(0.2, material=gaas)
geometry.append(defect)
default_material = bcb
resolution = 32
mesh_size = 7
num_bands = 5
ms = mpb.ModeSolver(num_bands=num_bands,
k_points=k_points,
geometry=geometry,
geometry_lattice=geometry_lattice,
resolution=resolution,
default_material=default_material,
mesh_size=mesh_size)
return ms
def test_interpolate_vectors(self):
expected = [
mp.Vector3(),
mp.Vector3(0.024999999999999842),
mp.Vector3(0.04999999999999984),
mp.Vector3(0.07499999999999984),
mp.Vector3(0.09999999999999984),
mp.Vector3(0.12499999999999983),
mp.Vector3(0.14999999999999983),
mp.Vector3(0.17499999999999982),
mp.Vector3(0.19999999999999982),
mp.Vector3(0.2249999999999998),
mp.Vector3(0.2499999999999998),
mp.Vector3(0.2749999999999998),
mp.Vector3(0.2999999999999998),
mp.Vector3(0.32499999999999984),
mp.Vector3(0.34999999999999987),
mp.Vector3(0.3749999999999999),
mp.Vector3(0.3999999999999999),
mp.Vector3(0.42499999999999993),
mp.Vector3(0.44999999999999996),
mp.Vector3(0.475),
mp.Vector3(0.5)
]
res = mp.interpolate(19, [mp.Vector3(), mp.Vector3(0.5)])
np.testing.assert_allclose([v.x for v in expected], [v.x for v in res])
np.testing.assert_allclose([v.y for v in expected], [v.y for v in res])
np.testing.assert_allclose([v.z for v in expected], [v.z for v in res])
def triangular():
k_points = [mp.Vector3(),
mp.Vector3(0., 0.5),
mp.Vector3(-1 / 3, 1 / 3),
mp.Vector3()]
k_points = mp.interpolate(10, k_points)
geometry = [mp.Cylinder(0.25, material=gaas)]
geometry_lattice = mp.Lattice(size=mp.Vector3(1, 1),
basis1=mp.Vector3(math.sqrt(3) / 2, 0.5),
basis2=mp.Vector3(math.sqrt(3) / 2, -0.5))
default_material = bcb
resolution = 32
mesh_size = 7
num_bands = 5
ms = mpb.ModeSolver(num_bands=num_bands,
k_points=k_points,
geometry=geometry,
geometry_lattice=geometry_lattice,
resolution=resolution,
default_material=default_material,
mesh_size=mesh_size)
return ms
def get_freqs_interpolate(hx=0.24, hy=0.24, a=0.33, wy=0.7, h=0.22):
'''
Useless
'''
import meep as mp
from meep import mpb
mode = "zEyO"
resolution = 20 # pixels/a, taken from simpetus example
a = round(a, 3) # units of um
h = round(h, 3) # units of um
w = round(wy, 3) # units of um
hx = round(hx, 3)
hy = round(hy, 3)
h = h / a # units of "a"
w = w / a # units of "a"
hx = hx / a # units of "a"
hy = hy / a # units of "a"
nSi = 3.45
Si = mp.Medium(index=nSi)
geometry_lattice = mp.Lattice(size=mp.Vector3(
1, 4, 4)) # dimensions of lattice taken from simpetus example
geometry = [
mp.Block(center=mp.Vector3(),
size=mp.Vector3(mp.inf, w, h),
material=Si),
mp.Ellipsoid(material=mp.air,
center=mp.Vector3(),
size=mp.Vector3(hx, hy, mp.inf))
]
num_k = 20 # from simpetus example, no. of k_points to evaluate the eigen frequency at
k_points = mp.interpolate(
num_k,
[mp.Vector3(0, 0, 0), mp.Vector3(0.5, 0, 0)])
num_bands = 2 # from simpetus example
ms = mpb.ModeSolver(geometry_lattice=geometry_lattice,
geometry=geometry,
k_points=k_points,
resolution=resolution,
num_bands=num_bands)
if mode == "te":
ms.run_te() # running for all modes and extracting parities
if mode == "zEyO":
ms.run_yodd_zeven()
return ms.freqs
def test_run_k_points(self):
all_freqs = self.sim.run_k_points(
5, mp.interpolate(19, [mp.Vector3(), mp.Vector3(0.5)]))
expected = [(0.1942497850393511, 0.001381460274205755),
(0.19782709203322993, -0.0013233828667934015),
(0.1927618763491877, 0.001034260690735336),
(0.19335527231544278, 4.6649450258959025e-4)]
self.assertTrue(any(l for l in all_freqs))
for (r, i), f in zip(expected, all_freqs[17:21][0]):
self.assertAlmostEqual(r, f.real)
self.assertAlmostEqual(i, f.imag)
def main():
# Some parameters to describe the geometry:
eps = 13 # dielectric constant of waveguide
w = 1.2 # width of waveguide
r = 0.36 # radius of holes
# The cell dimensions
sy = 12 # size of cell in y direction (perpendicular to wvg.)
dpml = 1 # PML thickness (y direction only!)
cell = mp.Vector3(1, sy)
b = mp.Block(size=mp.Vector3(mp.inf, w, mp.inf),
material=mp.Medium(epsilon=eps))
c = mp.Cylinder(radius=r)
fcen = 0.25 # pulse center frequency
df = 1.5 # pulse freq. width: large df = short impulse
s = mp.Source(src=mp.GaussianSource(fcen, fwidth=df),
component=mp.Hz,
center=mp.Vector3(0.1234))
sym = mp.Mirror(direction=mp.Y, phase=-1)
sim = mp.Simulation(cell_size=cell,
geometry=[b, c],
sources=[s],
symmetries=[sym],
boundary_layers=[mp.PML(dpml, direction=mp.Y)],
resolution=20)
kx = False # if true, do run at specified kx and get fields
k_interp = 19 # # k-points to interpolate, otherwise
if kx:
sim.k_point = mp.Vector3(kx)
sim.run(mp.at_beginning(mp.output_epsilon),
mp.after_sources(
mp.Harminv(mp.Hz, mp.Vector3(0.1234), fcen, df)),
until_after_sources=300)
sim.run(mp.at_every(1 / fcen / 20, mp.output_hfield_z), until=1 / fcen)
else:
sim.run_k_points(
300, mp.interpolate(k_interp,
[mp.Vector3(), mp.Vector3(0.5)]))
def test_triangular_lattice(self):
expected_brd = [
((0.0, mp.Vector3(0.0, 0.0,
0.0)), (0.2746902258623623,
mp.Vector3(-0.3333333333333333,
0.3333333333333333, 0.0))),
((0.44533108084715683, mp.Vector3(0.0, 0.5, 0.0)),
(0.5605181423162835, mp.Vector3(0.0, 0.0, 0.0))),
((0.4902389149027666,
mp.Vector3(-0.3333333333333333, 0.3333333333333333,
0.0)), (0.5605607947797747, mp.Vector3(0.0, 0.0,
0.0))),
((0.5932960873585144, mp.Vector3(0.0, 0.0, 0.0)),
(0.7907195974443698,
mp.Vector3(-0.3333333333333333, 0.3333333333333333, 0.0))),
((0.790832076332758,
mp.Vector3(-0.3333333333333333, 0.3333333333333333,
0.0)), (0.8374511167537562, mp.Vector3(0.0, 0.0,
0.0))),
((0.8375948528443267, mp.Vector3(0.0, 0.0, 0.0)),
(0.867200926490345, mp.Vector3(-0.2, 0.39999999999999997, 0.0))),
((0.8691349955739203,
mp.Vector3(-0.13333333333333336, 0.4333333333333333,
0.0)), (0.9941291022664892, mp.Vector3(0.0, 0.0,
0.0))),
((0.8992499095547049,
mp.Vector3(-0.3333333333333333, 0.3333333333333333,
0.0)), (1.098318352915696, mp.Vector3(0.0, 0.0,
0.0))),
]
ms = self.init_solver()
ms.geometry_lattice = mp.Lattice(
size=mp.Vector3(1, 1),
basis1=mp.Vector3(math.sqrt(3) / 2, 0.5),
basis2=mp.Vector3(math.sqrt(3) / 2, -0.5))
k_points = [
mp.Vector3(),
mp.Vector3(y=0.5),
mp.Vector3(-1 / 3, 1 / 3),
mp.Vector3()
]
ms.k_points = mp.interpolate(4, k_points)
ms.run_tm()
self.check_band_range_data(expected_brd, ms.band_range_data)
def test_material_dispersion_with_user_material(self):
susceptibilities = [
mp.LorentzianSusceptibility(frequency=1.1, gamma=1e-5, sigma=0.5),
mp.LorentzianSusceptibility(frequency=0.5, gamma=0.1, sigma=2e-5)
]
def mat_func(p):
return mp.Medium(epsilon=2.25, E_susceptibilities=susceptibilities)
fcen = 1.0
df = 2.0
sources = mp.Source(
mp.GaussianSource(fcen, fwidth=df),
component=mp.Ez,
center=mp.Vector3()
)
kmin = 0.3
kmax = 2.2
k_interp = 5
kpts = mp.interpolate(k_interp, [mp.Vector3(kmin), mp.Vector3(kmax)])
self.sim = mp.Simulation(
cell_size=mp.Vector3(),
geometry=[],
sources=[sources],
material_function=mat_func,
default_material=mp.air,
resolution=20
)
all_freqs = self.sim.run_k_points(200, kpts)
res = [f.real for fs in all_freqs for f in fs]
expected = [
0.1999342026399106,
0.41053963810375294,
0.6202409070451909,
0.8285737385146619,
1.0350739448523063,
1.2392775309110078,
1.4407208712852109,
]
np.testing.assert_allclose(expected, res)
def test_interpolate_numbers(self):
expected = [
1.0, 1.0909090909090908, 1.1818181818181819, 1.2727272727272727, 1.3636363636363635, 1.4545454545454546, 1.5454545454545454, 1.6363636363636365, 1.7272727272727273, 1.8181818181818181, 1.9090909090909092,
2.0, 2.090909090909091, 2.1818181818181817, 2.272727272727273, 2.3636363636363638, 2.4545454545454546, 2.5454545454545454, 2.6363636363636362, 2.727272727272727, 2.8181818181818183, 2.909090909090909,
3.0, 3.090909090909091, 3.1818181818181817, 3.272727272727273, 3.3636363636363638, 3.4545454545454546, 3.5454545454545454, 3.6363636363636362, 3.727272727272727, 3.8181818181818183, 3.909090909090909,
4.0, 4.090909090909091, 4.181818181818182, 4.2727272727272725, 4.363636363636363, 4.454545454545454, 4.545454545454546, 4.636363636363637, 4.7272727272727275, 4.818181818181818, 4.909090909090909,
5.0, 5.090909090909091, 5.181818181818182, 5.2727272727272725, 5.363636363636363, 5.454545454545454, 5.545454545454546, 5.636363636363637, 5.7272727272727275, 5.818181818181818, 5.909090909090909,
6.0, 6.090909090909091, 6.181818181818182, 6.2727272727272725, 6.363636363636363, 6.454545454545454, 6.545454545454546, 6.636363636363637, 6.7272727272727275, 6.818181818181818, 6.909090909090909,
7.0, 7.090909090909091, 7.181818181818182, 7.2727272727272725, 7.363636363636363, 7.454545454545454, 7.545454545454546, 7.636363636363637, 7.7272727272727275, 7.818181818181818, 7.909090909090909,
8.0, 8.090909090909092, 8.181818181818182, 8.272727272727273, 8.363636363636363, 8.454545454545455, 8.545454545454545, 8.636363636363637, 8.727272727272727, 8.818181818181818, 8.909090909090908,
9.0, 9.090909090909092, 9.181818181818182, 9.272727272727273, 9.363636363636363, 9.454545454545455, 9.545454545454545, 9.636363636363637, 9.727272727272727, 9.818181818181818, 9.909090909090908,
10.0
]
nums = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
result = mp.interpolate(10, nums)
np.testing.assert_allclose(expected, result)
def test_material_dispersion_with_user_material(self):
susceptibilities = [
mp.LorentzianSusceptibility(frequency=1.1, gamma=1e-5, sigma=0.5),
mp.LorentzianSusceptibility(frequency=0.5, gamma=0.1, sigma=2e-5)
]
def mat_func(p):
return mp.Medium(epsilon=2.25, E_susceptibilities=susceptibilities)
fcen = 1.0
df = 2.0
sources = mp.Source(mp.GaussianSource(fcen, fwidth=df),
component=mp.Ez,
center=mp.Vector3())
kmin = 0.3
kmax = 2.2
k_interp = 5
kpts = mp.interpolate(k_interp, [mp.Vector3(kmin), mp.Vector3(kmax)])
self.sim = mp.Simulation(cell_size=mp.Vector3(),
geometry=[],
sources=[sources],
material_function=mat_func,
default_material=mp.air,
resolution=20)
all_freqs = self.sim.run_k_points(200, kpts)
res = [f.real for fs in all_freqs for f in fs]
expected = [
0.1999342026399106,
0.41053963810375294,
0.6202409070451909,
0.8285737385146619,
1.0350739448523063,
1.2392775309110078,
1.4407208712852109,
]
np.testing.assert_allclose(expected, res)
def test_interpolate_numbers(self):
expected = [
1.0, 1.0909090909090908, 1.1818181818181819, 1.2727272727272727, 1.3636363636363635, 1.4545454545454546, 1.5454545454545454, 1.6363636363636365, 1.7272727272727273, 1.8181818181818181, 1.9090909090909092,
2.0, 2.090909090909091, 2.1818181818181817, 2.272727272727273, 2.3636363636363638, 2.4545454545454546, 2.5454545454545454, 2.6363636363636362, 2.727272727272727, 2.8181818181818183, 2.909090909090909,
3.0, 3.090909090909091, 3.1818181818181817, 3.272727272727273, 3.3636363636363638, 3.4545454545454546, 3.5454545454545454, 3.6363636363636362, 3.727272727272727, 3.8181818181818183, 3.909090909090909,
4.0, 4.090909090909091, 4.181818181818182, 4.2727272727272725, 4.363636363636363, 4.454545454545454, 4.545454545454546, 4.636363636363637, 4.7272727272727275, 4.818181818181818, 4.909090909090909,
5.0, 5.090909090909091, 5.181818181818182, 5.2727272727272725, 5.363636363636363, 5.454545454545454, 5.545454545454546, 5.636363636363637, 5.7272727272727275, 5.818181818181818, 5.909090909090909,
6.0, 6.090909090909091, 6.181818181818182, 6.2727272727272725, 6.363636363636363, 6.454545454545454, 6.545454545454546, 6.636363636363637, 6.7272727272727275, 6.818181818181818, 6.909090909090909,
7.0, 7.090909090909091, 7.181818181818182, 7.2727272727272725, 7.363636363636363, 7.454545454545454, 7.545454545454546, 7.636363636363637, 7.7272727272727275, 7.818181818181818, 7.909090909090909,
8.0, 8.090909090909092, 8.181818181818182, 8.272727272727273, 8.363636363636363, 8.454545454545455, 8.545454545454545, 8.636363636363637, 8.727272727272727, 8.818181818181818, 8.909090909090908,
9.0, 9.090909090909092, 9.181818181818182, 9.272727272727273, 9.363636363636363, 9.454545454545455, 9.545454545454545, 9.636363636363637, 9.727272727272727, 9.818181818181818, 9.909090909090908,
10.0
]
nums = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
result = mp.interpolate(10, nums)
np.testing.assert_allclose(expected, result)
def example_case():
num_bands = 3
resolution = 32
k_point = [
mp.Vector3(),
mp.Vector3(0.5),
mp.Vector3(0.5, 0.5),
mp.Vector3()
]
k_points = mp.interpolate(40, k_point)
geometry = [mp.Cylinder(0.2, material=mp.Medium(epsilon=12))]
geometry_lattice = mp.Lattice(size=mp.Vector3(1, 1))
ms = mpb.ModeSolver(num_bands=num_bands,
k_points=k_points,
geometry=geometry,
geometry_lattice=geometry_lattice,
resolution=resolution)
ms.run_te()
return ms
def init_solver(self, geom=True):
num_bands = 8
k_points = [
mp.Vector3(),
mp.Vector3(0.5),
mp.Vector3(0.5, 0.5),
mp.Vector3()
]
geometry = [mp.Cylinder(0.2, material=mp.Medium(
epsilon=12))] if geom else []
k_points = mp.interpolate(4, k_points)
geometry_lattice = mp.Lattice(size=mp.Vector3(1, 1))
resolution = 32
return mpb.ModeSolver(num_bands=num_bands,
k_points=k_points,
geometry=geometry,
geometry_lattice=geometry_lattice,
resolution=resolution,
filename_prefix=self.filename_prefix,
deterministic=True,
tolerance=1e-12)
mp.Block(material=mp.Medium(epsilon=eps),
size=mp.Vector3(mp.inf, mp.inf, h)),
mp.Cylinder(r, material=mp.air, height=supercell_h)
]
# 1st Brillouin zone of a triangular lattice:
Gamma = mp.Vector3()
M = mp.Vector3(y=0.5)
K = mp.Vector3(1 / -3, 1 / 3)
only_K = False # run with only_K=true to only do this k_point
k_interp = 4 # the number of k points to interpolate
if only_K:
k_points = [K]
else:
k_points = mp.interpolate(k_interp, [Gamma, M, K, Gamma])
resolution = mp.Vector3(32, 32, 16)
num_bands = 9
ms = mpb.ModeSolver(geometry_lattice=geometry_lattice,
geometry=geometry,
resolution=resolution,
num_bands=num_bands,
k_points=k_points)
def main():
# Run even and odd bands, outputting fields only at the K point:
if loweps == 1.0:
# we only have even/odd classification for symmetric structure
# k_points = [
# mp.Vector3(), # Gamma
# mp.Vector3(y=0.5), # M
# mp.Vector3(-1./3, 1./3), # K
# mp.Vector3(), # Gamma
# ]
# =============================================================================
k_points = [
mp.Vector3(-1. / 3, 1. / 3), # K
mp.Vector3(), # Gamma
mp.Vector3(y=0.5), # M
mp.Vector3(-1. / 3, 1. / 3) # K
]
k_points = mp.interpolate(50, k_points)
ms = mpb.ModeSolver(geometry=geometry,
geometry_lattice=geometry_lattice,
k_points=k_points,
resolution=resolution,
num_bands=num_bands)
ms.run_tm(
mpb.output_at_kpoint(mp.Vector3(-1. / 3, 1. / 3), mpb.fix_efield_phase,
mpb.output_efield_z))
tm_freqs = ms.all_freqs
tm_gaps = ms.gap_list
ms.run_te()
te_freqs = ms.all_freqs
te_gaps = ms.gap_list
basis1=mp.Vector3(-1, 1, 1),
basis2=mp.Vector3(1, -1, 1),
basis3=mp.Vector3(1, 1, -1))
# Corners of the irreducible Brillouin zone for the "I" lattice,
# in order that matches Maldovan2002 Fig 10
vlist = [
mp.Vector3(0, 0, 0.5), # N
mp.Vector3(0.25, 0.25, 0.25), # P
mp.Vector3(0, 0, 0), # Gamma
mp.Vector3(0, 0, 0.5), # N
mp.Vector3(0.5, -0.5, 0.5), # H
mp.Vector3(0.25, 0.25, 0.25) # P
]
k_points = mp.interpolate(4, vlist)
# define a couple of parameters (which we can set from the command_line)
#eps = 20.00 # the dielectric constant of the spheres
#r = 0.25 # the radius of the spheres
#diel = mp.Medium(epsilon=eps)
# A diamond lattice has two "atoms" per unit cell:
#geometry = [mp.Sphere(r, center=mp.Vector3(0.125, 0.125, 0.125), material=diel),
# mp.Sphere(r, center=mp.Vector3(-0.125, -0.125, -0.125), material=diel)]
# (A simple fcc lattice would have only one sphere/object at the origin.)
resolution = 16 # use a 16x16x16 grid
mesh_size = 5
basis3=mp.Vector3(1, 1)
)
# Corners of the irreducible Brillouin zone for the fcc lattice,
# in a canonical order:
vlist = [
mp.Vector3(0, 0.5, 0.5), # X
mp.Vector3(0, 0.625, 0.375), # U
mp.Vector3(0, 0.5, 0), # L
mp.Vector3(0, 0, 0), # Gamma
mp.Vector3(0, 0.5, 0.5), # X
mp.Vector3(0.25, 0.75, 0.5), # W
mp.Vector3(0.375, 0.75, 0.375) # K
]
k_points = mp.interpolate(4, vlist)
# define a couple of parameters (which we can set from the command_line)
eps = 11.56 # the dielectric constant of the spheres
r = 0.25 # the radius of the spheres
diel = mp.Medium(epsilon=eps)
# A diamond lattice has two "atoms" per unit cell:
geometry = [mp.Sphere(r, center=mp.Vector3(0.125, 0.125, 0.125), material=diel),
mp.Sphere(r, center=mp.Vector3(-0.125, -0.125, -0.125), material=diel)]
# (A simple fcc lattice would have only one sphere/object at the origin.)
resolution = 16 # use a 16x16x16 grid
mesh_size = 5
# far away from the mode field.
sc_y = 2 # supercell width (um)
sc_z = 2 # supercell height (um)
geometry_lattice = mp.Lattice(size=mp.Vector3(0, sc_y, sc_z))
# define the 2d blocks for the strip and substrate
geometry = [mp.Block(size=mp.Vector3(mp.inf, mp.inf, 0.5 * (sc_z - h)),
center=mp.Vector3(z=0.25 * (sc_z + h)), material=SiO2),
mp.Block(size=mp.Vector3(mp.inf, w, h), material=Si)]
# The k (i.e. beta, i.e. propagation constant) points to look at, in
# units of 2*pi/um. We'll look at num_k points from k_min to k_max.
num_k = 9
k_min = 0.1
k_max = 3.0
k_points = mp.interpolate(num_k, [mp.Vector3(k_min), mp.Vector3(k_max)])
resolution = 32 # pixels/um
# Increase this to see more modes. (The guided ones are the ones below the
# light line, i.e. those with frequencies < kmag / 1.45, where kmag
# is the corresponding column in the output if you grep for "freqs:".)
num_bands = 4
filename_prefix = 'strip-' # use this prefix for output files
ms = mpb.ModeSolver(
geometry_lattice=geometry_lattice,
geometry=geometry,
k_points=k_points,
resolution=resolution,
basis2=mp.Vector3(math.sqrt(3) / 2, -0.5))
eps = 12 # the dielectric constant of the rods
r = 0.2 # the rod radius in the bulk crystal
geometry = [mp.Cylinder(r, material=mp.Medium(epsilon=eps))]
# duplicate the bulk crystal rods over the supercell:
geometry = mp.geometric_objects_lattice_duplicates(geometry_lattice, geometry)
# add a rod of air, to erase a row of rods and form a waveguide:
geometry += [mp.Cylinder(r, material=mp.air)]
Gamma = mp.Vector3()
K_prime = mp.lattice_to_reciprocal(mp.Vector3(0.5), geometry_lattice) # edge of Brillouin zone.
k_points = mp.interpolate(4, [Gamma, K_prime])
# the bigger the supercell, the more bands you need to compute to get
# to the defect modes (the lowest band is "folded" supercell_y times):
extra_bands = 5 # number of extra bands to compute above the gap
num_bands = supercell_y + extra_bands
resolution = 32
ms = mpb.ModeSolver(
geometry_lattice=geometry_lattice,
geometry=geometry,
k_points=k_points,
num_bands=num_bands,
resolution=resolution
)
import math import sys import os import meep as mp import matplotlib.pyplot as plt from meep import mpb num_bands = 10 interp = 19 # honeycomb: k_points = [mp.Vector3(2 / 3, 1 / 3), mp.Vector3(0, 0), mp.Vector3(0, 0.5)] k_points = mp.interpolate(interp, k_points) # argv[1]: radius of airhole # argv[2]: radius of center # argv[3]: n_back # argv[4]: n_cen # argv[5]: resolution resolution = int(sys.argv[6]) #!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!amorphous!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! r_air = 0.001 * int(sys.argv[1]) r_cen1 = 0.001 * int(sys.argv[2]) # r_cen1 = 1/3-r_air r_cen2 = 0.4 * r_cen1 vertices = [
def get_mode_solver_rib(
wg_width: float = 0.45,
wg_thickness: float = 0.22,
slab_thickness: int = 0.0,
ncore: float = 3.47,
nclad: float = 1.44,
sy: float = 2.0,
sz: float = 2.0,
res: int = 32,
nmodes: int = 4,
) -> mpb.ModeSolver:
"""Returns a mode_solver simulation.
Args:
wg_width: wg_width (um)
wg_thickness: wg height (um)
slab_thickness: thickness for the waveguide slab
ncore: core material refractive index
nclad: clad material refractive index
sy: simulation region width (um)
sz: simulation region height (um)
res: resolution (pixels/um)
nmodes: number of modes
"""
material_core = mp.Medium(index=ncore)
material_clad = mp.Medium(index=nclad)
# Define the computational cell. We'll make x the propagation direction.
# the other cell sizes should be big enough so that the boundaries are
# far away from the mode field.
geometry_lattice = mp.Lattice(size=mp.Vector3(0, sy, sz))
# define the 2d blocks for the strip and substrate
geometry = [
mp.Block(
size=mp.Vector3(mp.inf, mp.inf, mp.inf),
material=material_clad,
),
# uncomment this for air cladded waveguides
# mp.Block(
# size=mp.Vector3(mp.inf, mp.inf, 0.5 * (sz - wg_thickness)),
# center=mp.Vector3(z=0.25 * (sz + wg_thickness)),
# material=material_clad,
# ),
mp.Block(
size=mp.Vector3(mp.inf, mp.inf, slab_thickness),
material=material_core,
center=mp.Vector3(z=-0.5 * slab_thickness),
),
mp.Block(
size=mp.Vector3(mp.inf, wg_width, wg_thickness),
material=material_core,
center=mp.Vector3(z=0),
),
]
# The k (i.e. beta, i.e. propagation constant) points to look at, in
# units of 2*pi/um. We'll look at num_k points from k_min to k_max.
num_k = 9
k_min = 0.1
k_max = 3.0
k_points = mp.interpolate(num_k, [mp.Vector3(k_min), mp.Vector3(k_max)])
# Increase this to see more modes. (The guided ones are the ones below the
# light line, i.e. those with frequencies < kmag / 1.45, where kmag
# is the corresponding column in the output if you grep for "freqs:".)
# use this prefix for output files
filename_prefix = tmp / f"rib_{wg_width}_{wg_thickness}_{slab_thickness}"
mode_solver = mpb.ModeSolver(
geometry_lattice=geometry_lattice,
geometry=geometry,
k_points=k_points,
resolution=res,
num_bands=nmodes,
filename_prefix=str(filename_prefix),
)
mode_solver.nmodes = nmodes
return mode_solver
geometry_lattice = mp.Lattice(size=mp.Vector3(1, 1)) # 2d cell
#geometry = [mp.Cylinder(r, material=GaAs)]
#Gamma = mp.Vector3()
#X = mp.Vector3(0.5, 0)
#M = mp.Vector3(0.5, 0.5)
vlist = [
mp.Vector3(0.0, 0.0), # Gamma
mp.Vector3(0.5, 0.0), # X
mp.Vector3(0.5, 0.5), # M
mp.Vector3(0.0, 0.0) # Gamma
]
tick_labs = ['$\Gamma$', 'X', 'M', '$\Gamma$']
k_points = mp.interpolate(k_interp, vlist)
resolution = 32
num_bands = 8
ms = mpb.ModeSolver(
geometry_lattice=geometry_lattice,
# geometry=geometry,
k_points=k_points,
resolution=resolution,
num_bands=num_bands,
epsilon_input_file='epsilon.h5')
def main():
ms.run_te()
#tmax: number of time steps over which sim will run
cell, fcen, src_z, pml_layers = mp.Vector3(1,1,1), 0.8, mp.Vector3(0,0,-10), [mp.PML(1.0,mp.Z)]
df=2.0
#df: frequency width of source
#-------------------------------------------------------#
# Create light source:
#-------------------------------------------------------#
src=[mp.Source(mp.GaussianSource(fcen, fwidth=df), component=mp.Ex, center=src_z), mp.Source(mp.GaussianSource(fcen, fwidth=df), component=mp.Ey, center=src_z, amplitude=1j)]
#-------------------------------------------------------#
# Set up k-values over which to plot w(k) frequencies:
#-------------------------------------------------------#
kz=mp.Vector3(0,0,0.18)
kzm, n = mp.Vector3(0,0,-0.18), 30
kpts=mp.interpolate(n, [kzm, kz])
#-------------------------------------------------------#
# Create and run sim:
#-------------------------------------------------------#
#simulate for left-handed polarized light
sim=mp.Simulation(cell_size=cell, geometry=[], sources=src, default_material=mp.vacuum, resolution=20)
allfreqs=sim.run_k_points(tmax, kpts)
print(allfreqs, kpts)
print('len(allfreqs)==len(kpts):', len(allfreqs)==len(kpts))
freqs=[]
for i in range(len(allfreqs)):
freqs+=[allfreqs[i][4]] #freqs: take out first freq of each kpt, put into a list.
mp.LorentzianSusceptibility(frequency=1.1, gamma=1e-5, sigma=0.5),
mp.LorentzianSusceptibility(frequency=0.5, gamma=0.1, sigma=2e-5)
]
default_material = mp.Medium(epsilon=2.25, E_susceptibilities=susceptibilities)
fcen = 1.0
df = 2.0
sources = [mp.Source(mp.GaussianSource(fcen, fwidth=df), component=mp.Ez, center=mp.Vector3())]
kmin = 0.3
kmax = 2.2
k_interp = 99
kpts = mp.interpolate(k_interp, [mp.Vector3(kmin), mp.Vector3(kmax)])
sim = mp.Simulation(
cell_size=cell,
geometry=[],
sources=sources,
default_material=default_material,
resolution=resolution
)
all_freqs = sim.run_k_points(200, kpts) # a list of lists of frequencies
for fs, kx in zip(all_freqs, [v.x for v in kpts]):
for f in fs:
print("eps:, {:.6g}, {:.6g}, {:.6g}".format(f.real, f.imag, (kx / f)**2))
def main(args):
resolution = 30 # pixels/um
a_start = args.a_start # starting periodicity
a_end = args.a_end # ending periodicity
s_cav = args.s_cav # cavity length
r = args.r # hole radius (units of a)
h = args.hh # waveguide height
w = args.w # waveguide width
dair = 1.00 # air padding
dpml = 1.00 # PML thickness
Ndef = args.Ndef # number of defect periods
a_taper = mp.interpolate(Ndef, [a_start, a_end])
dgap = a_end - 2 * r * a_end
Nwvg = args.Nwvg # number of waveguide periods
sx = 2 * (Nwvg * a_start + sum(a_taper)) - dgap + s_cav
sy = dpml + dair + w + dair + dpml
sz = dpml + dair + h + dair + dpml
cell_size = mp.Vector3(sx, sy, sz)
boundary_layers = [mp.PML(dpml)]
nSi = 3.45
Si = mp.Medium(index=nSi)
geometry = [
mp.Block(material=Si,
center=mp.Vector3(),
size=mp.Vector3(mp.inf, w, h))
]
for mm in range(Nwvg):
geometry.append(
mp.Cylinder(material=mp.air,
radius=r * a_start,
height=mp.inf,
center=mp.Vector3(
-0.5 * sx + 0.5 * a_start + mm * a_start, 0, 0)))
geometry.append(
mp.Cylinder(material=mp.air,
radius=r * a_start,
height=mp.inf,
center=mp.Vector3(
+0.5 * sx - 0.5 * a_start - mm * a_start, 0, 0)))
for mm in range(Ndef + 2):
geometry.append(
mp.Cylinder(material=mp.air,
radius=r * a_taper[mm],
height=mp.inf,
center=mp.Vector3(
-0.5 * sx + Nwvg * a_start +
(sum(a_taper[:mm]) if mm > 0 else 0) +
0.5 * a_taper[mm], 0, 0)))
geometry.append(
mp.Cylinder(material=mp.air,
radius=r * a_taper[mm],
height=mp.inf,
center=mp.Vector3(
+0.5 * sx - Nwvg * a_start -
(sum(a_taper[:mm]) if mm > 0 else 0) -
0.5 * a_taper[mm], 0, 0)))
lambda_min = 1.46 # minimum source wavelength
lambda_max = 1.66 # maximum source wavelength
fmin = 1 / lambda_max
fmax = 1 / lambda_min
fcen = 0.5 * (fmin + fmax)
df = fmax - fmin
sources = [
mp.Source(mp.GaussianSource(fcen, fwidth=df),
component=mp.Ey,
center=mp.Vector3())
]
symmetries = [
mp.Mirror(mp.X, +1),
mp.Mirror(mp.Y, -1),
mp.Mirror(mp.Z, +1)
]
sim = mp.Simulation(resolution=resolution,
cell_size=cell_size,
boundary_layers=boundary_layers,
geometry=geometry,
sources=sources,
dimensions=3,
symmetries=symmetries)
#sim.run(mp.in_volume(mp.Volume(center=mp.Vector3(), size=mp.Vector3(sx,sy,0)), mp.at_end(mp.output_epsilon, mp.output_efield_y)),
# mp.after_sources(mp.Harminv(mp.Ey, mp.Vector3(), fcen, df)),
# until_after_sources=500)
sim.run(mp.after_sources(mp.Harminv(mp.Ey, mp.Vector3(), fcen, df)),
until_after_sources=500)
def get_mode_solver_rib(
wg_width: float = 0.45,
wg_thickness: float = 0.22,
slab_thickness: float = 0.0,
ncore: float = 3.47,
nclad: float = 1.44,
nslab: Optional[float] = None,
sy: float = 2.0,
sz: float = 2.0,
resolution: int = 32,
nmodes: int = 4,
sidewall_angle: float = None,
# sidewall_taper: int = 1,
) -> mpb.ModeSolver:
"""Returns a mode_solver simulation.
Args:
wg_width: wg_width (um)
wg_thickness: wg height (um)
slab_thickness: thickness for the waveguide slab
ncore: core material refractive index
nclad: clad material refractive index
nslab: Optional slab material refractive index. Defaults to ncore.
sy: simulation region width (um)
sz: simulation region height (um)
resolution: resolution (pixels/um)
nmodes: number of modes
sidewall_angle: waveguide sidewall angle (radians),
tapers from wg_width at top of slab, upwards, to top of waveguide
::
. = origin
__________________________
|
|
| width
| <---------->
| ___________ _ _ _
| | | |
sz|_____| |_______|
| | wg_thickness
|slab_thickness |
|___________._____________|
|
|
|__________________________
<------------------------>
sy
"""
material_core = mp.Medium(index=ncore)
material_clad = mp.Medium(index=nclad)
material_slab = mp.Medium(index=nslab or ncore)
# Define the computational cell. We'll make x the propagation direction.
# the other cell sizes should be big enough so that the boundaries are
# far away from the mode field.
geometry_lattice = mp.Lattice(size=mp.Vector3(0, sy, sz))
geometry = []
# define the 2d blocks for the strip and substrate
if sidewall_angle:
geometry.append(
mp.Prism(
vertices=[
mp.Vector3(y=-wg_width / 2, z=slab_thickness),
mp.Vector3(y=wg_width / 2, z=slab_thickness),
mp.Vector3(x=1, y=wg_width / 2, z=slab_thickness),
mp.Vector3(x=1, y=-wg_width / 2, z=slab_thickness),
],
height=wg_thickness - slab_thickness,
center=mp.Vector3(z=slab_thickness +
(wg_thickness - slab_thickness) / 2, ),
# If only 1 angle is specified, use it for all waveguides
sidewall_angle=sidewall_angle,
# axis=mp.Vector3(z=sidewall_taper),
material=material_core,
))
else:
geometry.append(
mp.Block(
size=mp.Vector3(mp.inf, wg_width, wg_thickness),
material=material_core,
center=mp.Vector3(z=wg_thickness / 2),
))
# uncomment this for not oxide cladded waveguides
# geometry.append(
# mp.Block(
# size=mp.Vector3(mp.inf, mp.inf, 0.5 * (sz - wg_thickness)),
# center=mp.Vector3(z=0.25 * (sz + wg_thickness)),
# material=material_clad,
# ),
# )
geometry += [
mp.Block(
size=mp.Vector3(mp.inf, mp.inf, slab_thickness),
material=material_slab,
center=mp.Vector3(z=slab_thickness / 2),
),
]
# The k (i.e. beta, i.e. propagation constant) points to look at, in
# units of 2*pi/um. We'll look at num_k points from k_min to k_max.
num_k = 9
k_min = 0.1
k_max = 3.0
k_points = mp.interpolate(num_k, [mp.Vector3(k_min), mp.Vector3(k_max)])
# Increase this to see more modes. (The guided ones are the ones below the
# light line, i.e. those with frequencies < kmag / 1.45, where kmag
# is the corresponding column in the output if you grep for "freqs:".)
# use this prefix for output files
filename_prefix = tmp / f"rib_{wg_width}_{wg_thickness}_{slab_thickness}"
mode_solver = mpb.ModeSolver(
geometry_lattice=geometry_lattice,
geometry=geometry,
k_points=k_points,
resolution=resolution,
num_bands=nmodes,
default_material=material_clad,
filename_prefix=str(filename_prefix),
)
mode_solver.nmodes = nmodes
mode_solver.info = dict(
wg_width=wg_width,
wg_thickness=wg_thickness,
slab_thickness=slab_thickness,
ncore=ncore,
nclad=nclad,
sy=sy,
sz=sz,
resolution=resolution,
nmodes=nmodes,
)
return mode_solver
geometry_lattice = mp.Lattice(size=mp.Vector3(1, 1),
basis1=mp.Vector3(math.sqrt(3) / 2, 0.5),
basis2=mp.Vector3(math.sqrt(3) / 2, -0.5))
kz = 0 # use non-zero kz to consider vertical propagation
k_points = [
mp.Vector3(z=kz), # Gamma
mp.Vector3(0, 0.5, kz), # M
mp.Vector3(1 / -3, 1 / 3, kz), # K
mp.Vector3(z=kz) # Gamma
]
k_interp = 4
k_points = mp.interpolate(k_interp, k_points)
# Now, define the geometry, etcetera:
eps = 12 # the dielectric constant of the background
r = 0.45 # the hole radius
default_material = mp.Medium(epsilon=eps)
geometry = [mp.Cylinder(r, material=mp.air)]
resolution = 32
num_bands = 8
ms = mpb.ModeSolver(
geometry_lattice=geometry_lattice,
geometry=geometry,
# Define a function of position p (in the lattice basis) that returns
# the material at that position. In this case, we use the function:
# index-min + 0.5 * (index-max - index-min)
# * (1 + cos(2*pi*x))
# This is periodic, and also has inversion symmetry.
def eps_func(p):
return mp.Medium(index=index_min + 0.5 * (index_max - index_min) *
(1 + math.cos(2 * math.pi * p.x)))
geometry_lattice = mp.Lattice(size=mp.Vector3(1)) # 1d cell
# We'll just make it the default material, so that it goes everywhere.
default_material = eps_func
k_points = mp.interpolate(9, [mp.Vector3(), mp.Vector3(x=0.5)])
resolution = 32
num_bands = 8
ms = mpb.ModeSolver(num_bands=num_bands,
k_points=k_points,
geometry_lattice=geometry_lattice,
resolution=resolution,
default_material=default_material)
def main():
# the TM and TE bands are degenerate, so we only need TM:
ms.run_tm()
print("{0} {1} {0}".format(stars, h))
# Our First Band Structure
print_heading("Square lattice of rods in air")
num_bands = 8
k_points = [
mp.Vector3(), # Gamma
mp.Vector3(0.5), # X
mp.Vector3(0.5, 0.5), # M
mp.Vector3()
] # Gamma
k_points = mp.interpolate(4, k_points)
geometry = [mp.Cylinder(0.2, material=mp.Medium(epsilon=12))]
geometry_lattice = mp.Lattice(size=mp.Vector3(1, 1))
resolution = 32
ms = mpb.ModeSolver(num_bands=num_bands,
k_points=k_points,
geometry=geometry,
geometry_lattice=geometry_lattice,
resolution=resolution)
print_heading("Square lattice of rods: TE bands")
ms.run_te()
print_heading("Square lattice of rods: TM bands")
ms.run_tm()
# Define a function of position p (in the lattice basis) that returns
# the material at that position. In this case, we use the function:
# index-min + 0.5 * (index-max - index-min)
# * (1 + cos(2*pi*x))
# This is periodic, and also has inversion symmetry.
def eps_func(p):
return mp.Medium(index=index_min + 0.5 * (index_max - index_min) *
(1 + math.cos(2 * math.pi * p.x)))
geometry_lattice = mp.Lattice(size=mp.Vector3(1)) # 1d cell
# We'll just make it the default material, so that it goes everywhere.
default_material = eps_func
k_points = mp.interpolate(9, [mp.Vector3(), mp.Vector3(x=0.5)])
resolution = 32
num_bands = 8
ms = mpb.ModeSolver(
num_bands=num_bands,
k_points=k_points,
geometry_lattice=geometry_lattice,
resolution=resolution,
default_material=default_material
)
def main():
# the TM and TE bands are degenerate, so we only need TM:
# far away from the mode field.
sc_y = 2 # supercell width (um)
sc_z = 2 # supercell height (um)
geometry_lattice = mp.Lattice(size=mp.Vector3(0, sc_y, sc_z))
# define the 2d blocks for the strip and substrate
geometry = [mp.Block(size=mp.Vector3(mp.inf, mp.inf, 0.5 * (sc_z - h)),
center=mp.Vector3(z=0.25 * (sc_z + h)), material=SiO2),
mp.Block(size=mp.Vector3(mp.inf, w, h), material=Si)]
# The k (i.e. beta, i.e. propagation constant) points to look at, in
# units of 2*pi/um. We'll look at num_k points from k_min to k_max.
num_k = 9
k_min = 0.1
k_max = 3.0
k_points = mp.interpolate(num_k, [mp.Vector3(k_min), mp.Vector3(k_max)])
resolution = 32 # pixels/um
# Increase this to see more modes. (The guided ones are the ones below the
# light line, i.e. those with frequencies < kmag / 1.45, where kmag
# is the corresponding column in the output if you grep for "freqs:".)
num_bands = 4
filename_prefix = 'strip-' # use this prefix for output files
ms = mpb.ModeSolver(
geometry_lattice=geometry_lattice,
geometry=geometry,
k_points=k_points,
resolution=resolution,
mp.LorentzianSusceptibility(frequency=1.1, gamma=1e-5, sigma=0.5),
mp.LorentzianSusceptibility(frequency=0.5, gamma=0.1, sigma=2e-5)
]
default_material = mp.Medium(epsilon=2.25, E_susceptibilities=susceptibilities)
fcen = 1.0
df = 2.0
sources = [mp.Source(mp.GaussianSource(fcen, fwidth=df), component=mp.Ez, center=mp.Vector3())]
kmin = 0.3
kmax = 2.2
k_interp = 99
kpts = mp.interpolate(k_interp, [mp.Vector3(kmin), mp.Vector3(kmax)])
sim = mp.Simulation(
cell_size=cell,
geometry=[],
sources=sources,
default_material=default_material,
resolution=resolution
)
all_freqs = sim.run(kpts, k_points=200) # a list of lists of frequencies
for fs, kx in zip(all_freqs, [v.x for v in kpts]):
for f in fs:
print("eps:, {.6f}, {.6f}, {.6f}".format(f.real, f.imag, (kx / f)**2))
k_point_K_cart = mp.Vector3(math.sqrt(2) / 2, 0)
k_point_M_cart = mp.Vector3(math.sqrt(2) / 4, math.sqrt(2) / 4)
dk_x = (math.sqrt(2) / 2) / (nbr_points_x + 1)
dk_y = (math.sqrt(2) / 4) / (nbr_points_y + 1)
seg = []
for j in range(0, nbr_points_y + 2):
k_point_gamma_dk_cart = k_point_gamma + mp.Vector3(0, j * dk_y)
k_point_K_dk_cart = k_point_K_cart + mp.Vector3(0, j * dk_y)
k_point_gamma_dk_rec = mp.cartesian_to_reciprocal(k_point_gamma_dk_cart,
geometry_lattice)
k_point_K_dk_rec = mp.cartesian_to_reciprocal(k_point_K_dk_cart,
geometry_lattice)
seg_temp = mp.interpolate(nbr_points_x,
[k_point_gamma_dk_rec, k_point_K_dk_rec])
seg = seg + seg_temp
def outputgv(ms):
global gv
gv.append(ms.compute_group_velocities())
gv = []
ms = mpb.ModeSolver()
ms.geometry = C_0
ms.geometry_lattice = geometry_lattice
ms.resolution = resolution
ms.num_bands = Nbands
def print_heading(h):
stars = "*" * 10
print("{0} {1} {0}".format(stars, h))
# Our First Band Structure
print_heading("Square lattice of rods in air")
num_bands = 8
k_points = [mp.Vector3(), # Gamma
mp.Vector3(0.5), # X
mp.Vector3(0.5, 0.5), # M
mp.Vector3()] # Gamma
k_points = mp.interpolate(4, k_points)
geometry = [mp.Cylinder(0.2, material=mp.Medium(epsilon=12))]
geometry_lattice = mp.Lattice(size=mp.Vector3(1, 1))
resolution = 32
ms = mpb.ModeSolver(num_bands=num_bands,
k_points=k_points,
geometry=geometry,
geometry_lattice=geometry_lattice,
resolution=resolution)
print_heading("Square lattice of rods: TE bands")
ms.run_te()
print_heading("Square lattice of rods: TM bands")
ms.run_tm()
beam = mp.Prism([mp.Vector3(0,-w/2, h/2), mp.Vector3(0,w/2, h/2), mp.Vector3(0,0, -h/2)], a, axis=mp.Vector3(1,0,0),
center=None, material=mp.Medium(epsilon=n**2))
#Diamond: n = 2.4063; n^2 = ep_r
hole = mp.Ellipsoid(size=[hx, hy, mp.inf], material=mp.Medium(epsilon=1))
geometry = [beam, hole]
#Symmetry points
k_points = [
mp.Vector3(0,0,0), # Gamma
mp.Vector3(0.5,0,0), # X (normalized to a?)
]
#how many points to solve for between each specified point above
k_points = mp.interpolate(kpt_resolution, k_points)
#geometry_center
#ModeSolver documentation: https://mpb.readthedocs.io/en/latest/Python_User_Interface/
ms = mpb.ModeSolver(
geometry=geometry,
geometry_lattice=geometry_lattice,
k_points=k_points,
resolution=resolution,
num_bands=num_bands,
)
#https://mpb.readthedocs.io/en/latest/Python_User_Interface/
ms.run_yeven(mpb.output_at_kpoint(mp.Vector3(0.5,0,0), mpb.fix_efield_phase,
mpb.output_efield_z)) #This will output the electric field at the xpoint only
tm_freqs = ms.all_freqs
#######################
df1 = f0 - 1j*fcen*alpha
df2 = fcen + 1j*gamma
muperp = mu_r + sn * df1/(df1**2 - df2**2)
xi = sn * df2 / (df1**2 - df2**2)
tmax = 1/f0
kz=mp.Vector3(0,0, 0.5)
kzm, n = mp.Vector3(0,0,0.02), 80
kpts=mp.interpolate(n, [kzm, kz])
#simulate for left-handed polarized light
sim_left_circ_src=mp.Simulation(cell_size=cell, geometry=geometry, sources=[source], default_material=mat, resolution=20)
allfreqs_left_circ=sim_left_circ_src.run_k_points(tmax, kpts)
print(allfreqs_left_circ, kpts)
print('len(allfreqs_left_circ)==len(kpts):', len(allfreqs_left_circ)==len(kpts))
freqs=[]
f=[]
data_store=[]
for i in range(len(allfreqs_left_circ)):
data_store+=[allfreqs_left_circ[i][0].real]
f+=data_store
def get_mode_solver_coupler(
wg_width: float = 0.5,
gap: float = 0.2,
wg_widths: Optional[Floats] = None,
gaps: Optional[Floats] = None,
wg_thickness: float = 0.22,
slab_thickness: float = 0.0,
ncore: float = 3.47,
nclad: float = 1.44,
nslab: Optional[float] = None,
ymargin: float = 2.0,
sz: float = 2.0,
resolution: int = 32,
nmodes: int = 4,
sidewall_angles: Union[Tuple[float, ...], float] = None,
# sidewall_taper: int = 1,
) -> mpb.ModeSolver:
"""Returns a mode_solver simulation.
Args:
wg_width: wg_width (um)
gap:
wg_widths: list or tuple of waveguide widths.
gaps: list or tuple of waveguide gaps.
wg_thickness: wg height (um)
slab_thickness: thickness for the waveguide slab
ncore: core material refractive index
nclad: clad material refractive index
nslab: Optional slab material refractive index. Defaults to ncore.
ymargin: margin in y.
sz: simulation region thickness (um)
resolution: resolution (pixels/um)
nmodes: number of modes
sidewall_angles: waveguide sidewall angle (radians),
tapers from wg_width at top of slab, upwards, to top of waveguide
::
_____________________________________________________
|
|
| widths[0] widths[1]
| <----------> gaps[0] <---------->
| ___________ <-------------> ___________ _
| | | | | |
sz|_____| |_______________| |_____|
| | wg_thickness
|slab_thickness |
|___________________________________________________|
|
|<---> <--->
|ymargin ymargin
|____________________________________________________
<--------------------------------------------------->
sy
"""
wg_widths = wg_widths or (wg_width, wg_width)
gaps = gaps or (gap, )
material_core = mp.Medium(index=ncore)
material_clad = mp.Medium(index=nclad)
material_slab = mp.Medium(index=nslab or ncore)
# Define the computational cell. We'll make x the propagation direction.
# the other cell sizes should be big enough so that the boundaries are
# far away from the mode field.
sy = np.sum(wg_widths) + np.sum(gaps) + 2 * ymargin
geometry_lattice = mp.Lattice(size=mp.Vector3(0, sy, sz))
geometry = []
y = -sy / 2 + ymargin
gaps = list(gaps) + [0]
for i, wg_width in enumerate(wg_widths):
if sidewall_angles:
geometry.append(
mp.Prism(
vertices=[
mp.Vector3(y=y, z=slab_thickness),
mp.Vector3(y=y + wg_width, z=slab_thickness),
mp.Vector3(x=1, y=y + wg_width, z=slab_thickness),
mp.Vector3(x=1, y=y, z=slab_thickness),
],
height=wg_thickness - slab_thickness,
center=mp.Vector3(
y=y + wg_width / 2,
z=slab_thickness + (wg_thickness - slab_thickness) / 2,
),
# If only 1 angle is specified, use it for all waveguides
sidewall_angle=sidewall_angles if len(
np.unique(sidewall_angles)) == 1 else
sidewall_angles[i],
# axis=mp.Vector3(z=sidewall_taper),
material=material_core,
))
else:
geometry.append(
mp.Block(
size=mp.Vector3(mp.inf, wg_width, wg_thickness),
material=material_core,
center=mp.Vector3(y=y + wg_width / 2, z=wg_thickness / 2),
))
y += gaps[i] + wg_width
# define the 2D blocks for the strip and substrate
geometry += [
mp.Block(
size=mp.Vector3(mp.inf, mp.inf, slab_thickness),
material=material_slab,
center=mp.Vector3(z=slab_thickness / 2),
),
]
# The k (i.e. beta, i.e. propagation constant) points to look at, in
# units of 2*pi/um. We'll look at num_k points from k_min to k_max.
num_k = 9
k_min = 0.1
k_max = 3.0
k_points = mp.interpolate(num_k, [mp.Vector3(k_min), mp.Vector3(k_max)])
# Increase this to see more modes. (The guided ones are the ones below the
# light line, i.e. those with frequencies < kmag / 1.45, where kmag
# is the corresponding column in the output if you grep for "freqs:".)
# use this prefix for output files
wg_widths_str = "_".join([str(i) for i in wg_widths])
gaps_str = "_".join([str(i) for i in gaps])
filename_prefix = (
tmp /
f"coupler_{wg_widths_str}_{gaps_str}_{wg_thickness}_{slab_thickness}")
mode_solver = mpb.ModeSolver(
geometry_lattice=geometry_lattice,
geometry=geometry,
k_points=k_points,
resolution=resolution,
num_bands=nmodes,
filename_prefix=str(filename_prefix),
default_material=material_clad,
)
mode_solver.nmodes = nmodes
mode_solver.info = dict(
wg_widths=wg_widths,
gaps=gaps,
wg_thickness=wg_thickness,
slab_thickness=slab_thickness,
ncore=ncore,
nclad=nclad,
sy=sy,
sz=sz,
resolution=resolution,
nmodes=nmodes,
)
return mode_solver
eps = 12 # the dielectric constant of the rods
r = 0.2 # the rod radius in the bulk crystal
geometry = [mp.Cylinder(r, material=mp.Medium(epsilon=eps))]
# duplicate the bulk crystal rods over the supercell:
geometry = mp.geometric_objects_lattice_duplicates(geometry_lattice, geometry)
# add a rod of air, to erase a row of rods and form a waveguide:
geometry += [mp.Cylinder(r, material=mp.air)]
Gamma = mp.Vector3()
K_prime = mp.lattice_to_reciprocal(mp.Vector3(0.5),
geometry_lattice) # edge of Brillouin zone.
k_points = mp.interpolate(4, [Gamma, K_prime])
# the bigger the supercell, the more bands you need to compute to get
# to the defect modes (the lowest band is "folded" supercell_y times):
extra_bands = 5 # number of extra bands to compute above the gap
num_bands = supercell_y + extra_bands
resolution = 32
ms = mpb.ModeSolver(geometry_lattice=geometry_lattice,
geometry=geometry,
k_points=k_points,
num_bands=num_bands,
resolution=resolution)
size=mp.Vector3(mp.inf, mp.inf, 0.5 * supercell_h)),
mp.Block(material=mp.Medium(epsilon=eps), size=mp.Vector3(mp.inf, mp.inf, h)),
mp.Cylinder(r, material=mp.air, height=supercell_h)
]
# 1st Brillouin zone of a triangular lattice:
Gamma = mp.Vector3()
M = mp.Vector3(y=0.5)
K = mp.Vector3(1 / -3, 1 / 3)
only_K = False # run with only_K=true to only do this k_point
k_interp = 4 # the number of k points to interpolate
if only_K:
k_points = [K]
else:
k_points = mp.interpolate(k_interp, [Gamma, M, K, Gamma])
resolution = mp.Vector3(32, 32, 16)
num_bands = 9
ms = mpb.ModeSolver(
geometry_lattice=geometry_lattice,
geometry=geometry,
resolution=resolution,
num_bands=num_bands,
k_points=k_points
)
def main():
# Run even and odd bands, outputting fields only at the K point:
import meep as mp
from meep import mpb
import math
num_bands = 8
k_points = [mp.Vector3(),
mp.Vector3(0., 0.5),
mp.Vector3(-1/3, 1/3),
mp.Vector3()]
k_points = mp.interpolate(10, k_points)
geometry = [mp.Cylinder(0.25, material=mp.Medium(epsilon=12.96))]
geometry_lattice = mp.Lattice(size=mp.Vector3(1, 1),
basis1=mp.Vector3(math.sqrt(3)/2, 0.5),
basis2=mp.Vector3(math.sqrt(3)/2, -0.5))
default_material = mp.Medium(epsilon=2.4)
resolution = 32
ms = mpb.ModeSolver(num_bands=num_bands,
k_points=k_points,
geometry=geometry,
geometry_lattice=geometry_lattice,
resolution=resolution,
default_material=default_material)
ms.run_tm()
s = mp.Source(src=mp.GaussianSource(fcen, fwidth=df),
component=mp.Hz,
center=mp.Vector3(0.1234))
sym = mp.Mirror(direction=mp.Y, phase=-1)
sim = mp.Simulation(cell_size=cell,
geometry=[b, c],
sources=[s],
symmetries=[sym],
boundary_layers=[mp.PML(dpml, direction=mp.Y)],
resolution=20)
kx = False # if true, do run at specified kx and get fields
k_interp = 19 # # k-points to interpolate, otherwise
if kx:
sim.k_point = mp.Vector3(kx)
sim.run(mp.at_beginning(mp.output_epsilon),
mp.after_sources(
mp.Harminv(mp.Hz, mp.Vector3(0.1234), fcen, df)),
until_after_sources=300)
sim.run(mp.at_every(1 / fcen / 20, mp.output_hfield_z), until=1 / fcen)
else:
sim.run_k_points(
300, mp.interpolate(k_interp,
[mp.Vector3(), mp.Vector3(0.5)]))
