# 4.3. Thermo-optic phase shifter (Heater)¶

A thermo-optic phase shifter works by varying the temperature of the waveguide. This modulates the refractive index of the waveguide material through the thermo-optic effect. This, in turn, modulates the effective index and the phase of the light at the end of the waveguide.

## 4.3.1. Layout¶

SiFab contains a heater that is used in this tutorial. This heated waveguide can be used as any other waveguide in IPKISS.

from si_fab import all as pdk
from ipkiss3 import all as i3

# Heater

ht = pdk.HeatedWaveguide(contact_pitch=0.6,
heater_width=0.6,
heater_offset=1.0,
m1_width=1.0,
length_via_section=3.0,
via_pitch=1.0,)
ht_lv = ht.Layout(shape=[(0.0, 0.0), (10.0, 0.0)])
ht_lv.visualize(annotate=True)

xs = ht_lv.cross_section(cross_section_path=i3.Shape([(1.0, -8.0), (1.0, 8.0)]))
xs.visualize()


## 4.3.2. Model¶

As described here, the phase shift is proportional to the dissipated power in the heater. As the dynamics controlling the temperature are much slower than the electro-optic effects in the phase shifter, we chose an instantaneous model. By doing so, we can reach steady-state without immediately in simulations. The heater in SiFab has a simulation recipe, which is used to ramp up the voltage and check the phase variation.

from si_fab import all as pdk
from si_fab.components.heater.simulate.simulate import simulate_heater
from si_fab.components.heater.pcell.cell import r_sheet, j_max
import pylab as plt
import numpy as np
import os
# Phase Shifter

name = "heater_sweep"
results_array = []
length = 100
ht = pdk.HeatedWaveguide(contact_pitch=0.6,
heater_width=0.6,
heater_offset=1.0,
m1_width=1.0,
length_via_section=3.0,
via_pitch=1.0,)
ht_lv = ht.Layout(shape=[(0.0, 0.0), (length, 0.0)])

P_pi = 30e-3  # W
p_pi_sq = r_sheet * P_pi

ht.CircuitModel(p_pi_sq=p_pi_sq)

results = simulate_heater(cell=ht,
v_bias_start=0,
v_bias_end=1,
nsteps=500,
center_wavelength=1.5,
simulate_sources=True,
simulate_circuit=True,
debug=False)
times = results["timesteps"]
results_array.append(results)

def phase_unwrap_normalize(results):
unwrapped = np.unwrap(np.angle(results))
return (unwrapped - unwrapped[0]/np.pi)

outputs = ["in", "elec1", "elec2", "out", "current_density"]
process = [np.real, np.real, np.real, phase_unwrap_normalize, np.real]
axis_y = ["V", "V", "V", "[rad/pi]", "A/um^2"]
fig, axs = plt.subplots(nrows=len(outputs), ncols=1, figsize=(6, 10))

for cnt, (f, pn) in enumerate(zip(process, outputs)):
axs[cnt].set_title(pn)
axs[cnt].plot(times, f(results[pn]), label="length: {}".format(length))
axs[cnt].set_ylabel(axis_y[cnt])

axs[len(process)-1].axhline(y=j_max)

plt.tight_layout()
fig.savefig(os.path.join("{}.png".format(name)), bbox_inches='tight')


1. Open topical_training/mzm/explore_heater/example_heaterwaveguide.py.
1. Open topical_training/mzm/explore_heater/example_heater_simulation.py.
3. With the heater having a $$P_{\pi}=30 mW$$, find the the length of the heater that would lead to a tuning range of $$\pi/2$$ under a voltage swing of 0 to 1.
Solution