mp.Block(center=mp.Vector3(y=Sy/4), material=mp.Medium(index=3.45), size=mp.Vector3(0.5, Sy/2, 0)), # vertical waveguide
mp.Block(center=design_region.center, size=design_region.size, epsilon_func=basis.func()) # design region
]
sim = mp.Simulation(cell_size=cell_size,
boundary_layers=pml_layers,
geometry=geometry,
sources=source,
eps_averaging=False,
resolution=resolution)
#----------------------------------------------------------------------
#- Objective quantities and objective function
#----------------------------------------------------------------------
TE0 = mpa.EigenmodeCoefficient(sim,mp.Volume(center=mp.Vector3(0,1,0),size=mp.Vector3(x=2)),mode=1)
ob_list = [TE0]
def J(alpha):
return npa.sum(npa.abs(alpha) ** 2)
#----------------------------------------------------------------------
#- Define optimization problem
#----------------------------------------------------------------------
opt = mpa.OptimizationProblem(
simulation = sim,
objective_function = J,
objective_arguments = ob_list,
basis = [basis],
fcen = fcen,
df = fwidth,
sim = mp.Simulation(cell_size=cell_size,
boundary_layers=pml_layers,
geometry=geometry,
sources=source,
eps_averaging=False,
resolution=resolution)
#----------------------------------------------------------------------
#- Objective quantities and objective function
#----------------------------------------------------------------------
mode = 1
TE0 = mpa.EigenmodeCoefficient(sim,
mp.Volume(center=mp.Vector3(x=-1),
size=mp.Vector3(y=1.5)),
mode,
eig_parity=mp.EVEN_Y)
TM0 = mpa.EigenmodeCoefficient(sim,
mp.Volume(center=mp.Vector3(x=-1),
size=mp.Vector3(y=1.5)),
mode,
eig_parity=mp.ODD_Y)
TE_top = mpa.EigenmodeCoefficient(sim,
mp.Volume(center=mp.Vector3(0, 1, 0),
size=mp.Vector3(x=1.5)),
mode,
eig_parity=mp.EVEN_Y)
TM_top = mpa.EigenmodeCoefficient(sim,
mp.Volume(center=mp.Vector3(0, 1, 0),
size=mp.Vector3(x=1.5)),
mp.Block(center=mp.Vector3(y=Sy/4), material=mp.Medium(index=3.45), size=mp.Vector3(0.5, Sy/2, 0)), # vertical waveguide
mp.Block(center=design_region.center, size=design_region.size, epsilon_func=basis.func()) # design region
]
sim = mp.Simulation(cell_size=cell_size,
boundary_layers=pml_layers,
geometry=geometry,
sources=source,
eps_averaging=False,
resolution=resolution)
#----------------------------------------------------------------------
#- Objective quantities and objective function
#----------------------------------------------------------------------
mode = 1
TE0 = mpa.EigenmodeCoefficient(sim,mp.Volume(center=mp.Vector3(x=-1),size=mp.Vector3(y=1.5)),mode)
TE_top = mpa.EigenmodeCoefficient(sim,mp.Volume(center=mp.Vector3(0,1,0),size=mp.Vector3(x=1.5)),mode)
ob_list = [TE0,TE_top]
def J(input,top):
return npa.abs(top/input) ** 2
#----------------------------------------------------------------------
#- Define optimization problem
#----------------------------------------------------------------------
opt = mpa.OptimizationProblem(
simulation=sim,
objective_function=J,
objective_arguments=ob_list,
basis=[basis],
fcen=fcen,
]
sim = mp.Simulation(cell_size=cell_size,
boundary_layers=pml_layers,
geometry=geometry,
sources=source,
eps_averaging=False,
resolution=resolution)
#----------------------------------------------------------------------
#- Objective quantities and objective function
#----------------------------------------------------------------------
mode = 1
TE0 = mpa.EigenmodeCoefficient(
sim, mp.Volume(center=mp.Vector3(x=-1), size=mp.Vector3(y=1.5)), mode)
TE_top = mpa.EigenmodeCoefficient(
sim, mp.Volume(center=mp.Vector3(0, 1, 0), size=mp.Vector3(x=1.5)), mode)
TE_bottom = mpa.EigenmodeCoefficient(sim,
mp.Volume(center=mp.Vector3(0, -1, 0),
size=mp.Vector3(x=1.5)),
mode,
forward=False)
ob_list = [TE0, TE_top, TE_bottom]
def J(source, top, bottom):
return npa.sum(0.5 * npa.abs(top / source)**2 +
0.5 * npa.abs(bottom / source)**2)