Adiabatic operation slope-loss algorithm (AO-SLA), how to do it: adiabatic coupling
I would like to write a code that can implement the equations of this paper: Adiabatic operation slope-loss algorithm for ultrashort and broadband waveguide taper
I tried it in python but it did not improve my coupling efficiency at all, mayba I am doing something wrong… Here it is my python code:
import sys
sys.path.append(r"C:Program FilesLumericalv241apipython")
import lumapi
import numpy as np
def create_adiabatic_taper(fdtd, width_input, width_output, alpha, lambda_0, n_eff):
# Define the number of segments to approximate the adiabatic taper
num_segments = 100
L_i_segments = np.zeros(num_segments)
# Widths for each section
widths = np.linspace(width_input, width_output, num_segments + 1)
vertices_x = []
vertices_y = []
for i in range(num_segments):
W1 = widths[i]
W2 = widths[i + 1]
W0 = (W1 + W2) / 2
epsilon = 1e-10 # Small value to prevent division by zero or very small numbers
theta = alpha * lambda_0 / (2 * (W0 + epsilon) * n_eff)
# Prevent theta from becoming too small
if np.abs(theta) < 1e-10:
theta = np.sign(theta) * 1e-10
L_i = (W1 – W2) / (2 * np.tan(theta))
# Ensure L_i is not negative
if L_i < 0:
L_i = 0
L_i_segments[i] = L_i
if i == 0:
vertices_x.append(0)
vertices_y.append(W1 / 2) # For half width
vertices_x.append(sum(L_i_segments[:i+1]))
vertices_y.append(W2 / 2) # For half width
vertices_x = np.array(vertices_x)
vertices_y = np.array(vertices_y)
vertices_x_full = np.concatenate([vertices_x, vertices_x[::-1]])
vertices_y_full = np.concatenate([vertices_y, -vertices_y[::-1]])
vertices = np.vstack((vertices_x_full, vertices_y_full)).T
print("L_i_segments:", L_i_segments)
print("Vertices X:", vertices_x_full)
print("Vertices Y:", vertices_y_full)
# Create the polygon
fdtd.addpoly(
x=0, # Center of the polygon in the x-direction
y=0, # Center of the polygon in the y-direction
z=0, # Center of the polygon in the z-direction
vertices=vertices, # Vertices of the polygon
material="Si (Silicon) – Palik",
name="adiabatic_taper_polygon"
)
fdtd.addtogroup("::model::Taper")
fdtd = lumapi.FDTD()
fdtd.selectall()
fdtd.delete()
# Parameters for the adiabatic taper
wavelength = 1550e-9 # Operating wavelength in meters
width_input = 0.5e-6 # Width of the input waveguide in meters
width_output = 0.075e-6 # Width of the output waveguide in meters
alpha = 1 # Slope angle in degrees
lambda_0 = 1550e-9 # Center wavelength in meters
n_eff = 3.47 # Effective index of the cross-section at the center of the taper
# Create the adiabatic taper
create_adiabatic_taper(fdtd, width_input, width_output, alpha, lambda_0, n_eff)I would like to write a code that can implement the equations of this paper: Adiabatic operation slope-loss algorithm for ultrashort and broadband waveguide taper
I tried it in python but it did not improve my coupling efficiency at all, mayba I am doing something wrong… Here it is my python code:
import sys
sys.path.append(r"C:Program FilesLumericalv241apipython")
import lumapi
import numpy as np
def create_adiabatic_taper(fdtd, width_input, width_output, alpha, lambda_0, n_eff):
# Define the number of segments to approximate the adiabatic taper
num_segments = 100
L_i_segments = np.zeros(num_segments)
# Widths for each section
widths = np.linspace(width_input, width_output, num_segments + 1)
vertices_x = []
vertices_y = []
for i in range(num_segments):
W1 = widths[i]
W2 = widths[i + 1]
W0 = (W1 + W2) / 2
epsilon = 1e-10 # Small value to prevent division by zero or very small numbers
theta = alpha * lambda_0 / (2 * (W0 + epsilon) * n_eff)
# Prevent theta from becoming too small
if np.abs(theta) < 1e-10:
theta = np.sign(theta) * 1e-10
L_i = (W1 – W2) / (2 * np.tan(theta))
# Ensure L_i is not negative
if L_i < 0:
L_i = 0
L_i_segments[i] = L_i
if i == 0:
vertices_x.append(0)
vertices_y.append(W1 / 2) # For half width
vertices_x.append(sum(L_i_segments[:i+1]))
vertices_y.append(W2 / 2) # For half width
vertices_x = np.array(vertices_x)
vertices_y = np.array(vertices_y)
vertices_x_full = np.concatenate([vertices_x, vertices_x[::-1]])
vertices_y_full = np.concatenate([vertices_y, -vertices_y[::-1]])
vertices = np.vstack((vertices_x_full, vertices_y_full)).T
print("L_i_segments:", L_i_segments)
print("Vertices X:", vertices_x_full)
print("Vertices Y:", vertices_y_full)
# Create the polygon
fdtd.addpoly(
x=0, # Center of the polygon in the x-direction
y=0, # Center of the polygon in the y-direction
z=0, # Center of the polygon in the z-direction
vertices=vertices, # Vertices of the polygon
material="Si (Silicon) – Palik",
name="adiabatic_taper_polygon"
)
fdtd.addtogroup("::model::Taper")
fdtd = lumapi.FDTD()
fdtd.selectall()
fdtd.delete()
# Parameters for the adiabatic taper
wavelength = 1550e-9 # Operating wavelength in meters
width_input = 0.5e-6 # Width of the input waveguide in meters
width_output = 0.075e-6 # Width of the output waveguide in meters
alpha = 1 # Slope angle in degrees
lambda_0 = 1550e-9 # Center wavelength in meters
n_eff = 3.47 # Effective index of the cross-section at the center of the taper
# Create the adiabatic taper
create_adiabatic_taper(fdtd, width_input, width_output, alpha, lambda_0, n_eff) I would like to write a code that can implement the equations of this paper: Adiabatic operation slope-loss algorithm for ultrashort and broadband waveguide taper
I tried it in python but it did not improve my coupling efficiency at all, mayba I am doing something wrong… Here it is my python code:
import sys
sys.path.append(r"C:Program FilesLumericalv241apipython")
import lumapi
import numpy as np
def create_adiabatic_taper(fdtd, width_input, width_output, alpha, lambda_0, n_eff):
# Define the number of segments to approximate the adiabatic taper
num_segments = 100
L_i_segments = np.zeros(num_segments)
# Widths for each section
widths = np.linspace(width_input, width_output, num_segments + 1)
vertices_x = []
vertices_y = []
for i in range(num_segments):
W1 = widths[i]
W2 = widths[i + 1]
W0 = (W1 + W2) / 2
epsilon = 1e-10 # Small value to prevent division by zero or very small numbers
theta = alpha * lambda_0 / (2 * (W0 + epsilon) * n_eff)
# Prevent theta from becoming too small
if np.abs(theta) < 1e-10:
theta = np.sign(theta) * 1e-10
L_i = (W1 – W2) / (2 * np.tan(theta))
# Ensure L_i is not negative
if L_i < 0:
L_i = 0
L_i_segments[i] = L_i
if i == 0:
vertices_x.append(0)
vertices_y.append(W1 / 2) # For half width
vertices_x.append(sum(L_i_segments[:i+1]))
vertices_y.append(W2 / 2) # For half width
vertices_x = np.array(vertices_x)
vertices_y = np.array(vertices_y)
vertices_x_full = np.concatenate([vertices_x, vertices_x[::-1]])
vertices_y_full = np.concatenate([vertices_y, -vertices_y[::-1]])
vertices = np.vstack((vertices_x_full, vertices_y_full)).T
print("L_i_segments:", L_i_segments)
print("Vertices X:", vertices_x_full)
print("Vertices Y:", vertices_y_full)
# Create the polygon
fdtd.addpoly(
x=0, # Center of the polygon in the x-direction
y=0, # Center of the polygon in the y-direction
z=0, # Center of the polygon in the z-direction
vertices=vertices, # Vertices of the polygon
material="Si (Silicon) – Palik",
name="adiabatic_taper_polygon"
)
fdtd.addtogroup("::model::Taper")
fdtd = lumapi.FDTD()
fdtd.selectall()
fdtd.delete()
# Parameters for the adiabatic taper
wavelength = 1550e-9 # Operating wavelength in meters
width_input = 0.5e-6 # Width of the input waveguide in meters
width_output = 0.075e-6 # Width of the output waveguide in meters
alpha = 1 # Slope angle in degrees
lambda_0 = 1550e-9 # Center wavelength in meters
n_eff = 3.47 # Effective index of the cross-section at the center of the taper
# Create the adiabatic taper
create_adiabatic_taper(fdtd, width_input, width_output, alpha, lambda_0, n_eff) python, taper, coupling, matlab MATLAB Answers — New Questions
