Merge branch 'HelgeGehring:main' into plot_component

.github/workflows/docs.yml

@@ -32,13 +32,14 @@ jobs:
       - name: Install Poetry
         uses: snok/install-poetry@v1
         with:
-          version: 1.7.1
+          version: 1.8.1
           virtualenvs-create: false
           installer-parallel: true
       - name: Install dependencies
         run: |
           sudo apt-get install -y libglu1-mesa
           poetry install --no-interaction
+          pip install --upgrade scipy
           mamba install slepc4py=*=complex* -y
           mamba install julia
           pip install jupyter-book

.pre-commit-config.yaml

@@ -5,23 +5,23 @@ repos:
 #    - id: markdownlint
 
   - repo: https://github.com/pycqa/isort
-    rev: 5.12.0
+    rev: 5.13.2
     hooks:
       - id: isort
         args: [--profile, black]
 
   - repo: https://github.com/psf/black
-    rev: 23.10.0
+    rev: 24.2.0
     hooks:
       - id: black
 
   - repo: https://github.com/python-poetry/poetry
-    rev: 1.6.0
+    rev: 1.8.0
     hooks:
       - id: poetry-check
 
   - repo: "https://github.com/domluna/JuliaFormatter.jl"
-    rev: "v1.0.40"
+    rev: "v1.0.50"
     hooks:
       - id: "julia-formatter"
 

docs/photonics/examples/effective_area.py

@@ -12,7 +12,10 @@
 #     name: python3
 # ---
 # %% [markdown]
-# # Effective area and effective refractive index of a Si-NCs waveguide from {cite}`Rukhlenko2012`.
+# # Effective area of a Si-NCs waveguide
+
+# In this example we calculate the effective area and the effective refractive index of a Si-NCs waveguide from {cite}`Rukhlenko2012`
+
 # %% tags=["hide-input"]
 from collections import OrderedDict
 

docs/photonics/examples/metal_heater_phase_shifter.py

@@ -30,9 +30,18 @@
 from femwell.thermal import solve_thermal
 
 # %% [markdown]
-# Simulating the TiN TOPS heater in {cite}`Jacques2019`.
+# In this example we'll show how to calculate the efficiency of a thermal phase shifter based on calculating the temperature distribution on a 2D plane.
+# I.e. we make the approximation, that the thermal phase shifter is quite long, so that boundary effects will play a negligible role.
+
+# We'll reproduce the TiN TOPS heater presented in {cite}`Jacques2019`.
 # First we set up the mesh:
 
+# It consists of a substrate, with a box layer ontop.
+# On the box layer, a waveguide is structured. In this example it's a silicon waveguide, which has a quite high thermal optical coefficient.
+
+# Above the waveguide, within the deposited cladding layer, a TiN resistor is placed for heating up the thermal phase shifter.
+# We refine the mesh within the region of most intered (for very precise results, of course an even finer mesh is required).
+
 # %% tags=["remove-stderr"]
 
 w_sim = 8 * 2
@@ -105,7 +114,13 @@
 mesh.draw().show()
 
 # %% [markdown]
-# And then we solve it!
+# Using the previously defined geometry and the resulting mesh, we can calculate the thermal distribution!
+# For this we start with defining the current densities we want to simulate within the TiN resistor.
+# Here we use the same values as in the referenced paper.
+
+# For each temperature distribution we calculate the modes of the waveguide and track their change in effective refractive index.
+# Using the change of the effective refractive index we can calculate the phase shift accumulated within the thermal phase shifter of a given length.
+# To stay consistent with the referenced paper, we use a length of 320um.
 
 # %% tags=["remove-stderr"]
 currents = np.linspace(0.0, 7.4e-3, 10)
@@ -151,12 +166,18 @@
 
     neffs.append(np.real(modes[0].n_eff))
 
-print(f"Phase shift: {2 * np.pi / 1.55 * (neffs[-1] - neffs[0]) * 320}")
 plt.xlabel("Current / mA")
 plt.ylabel("Effective refractive index $n_{eff}$")
 plt.plot(currents * 1e3, neffs)
 plt.show()
 
+# %% [markdown]
+
+# Using the values we calculated for no applied current density and the highest applied current density, we can calculate the phase shift introduced by the current:
+
+# %% tags=["remove-stderr"]
+
+print(f"Phase shift: {2 * np.pi / 1.55 * (neffs[-1] - neffs[0]) * 320}")
 
 # %% [markdown]
 # ## Bibliography

docs/photonics/examples/vary_width.py

@@ -15,6 +15,11 @@
 
 # %% [markdown]
 # # Variation of the width
+#
+# To understand the propagation in a waveguide, it's often helpful to look at how the effective refractive indices of the modes change when adjusting the width of the waveguide.
+# As the modes continously change their refractive index, we can track them through their evolution.
+# We gray the area which would indicate a effective refractive index below the refractive index of the underlying layer (commonly refered to as box), as such modes would not be guided.
+# The refractive index of the box called "cutoff", as it defines the effective refractive index level under which modes stop being guided.
 
 # %% tags=["hide-input"]
 
@@ -39,7 +44,7 @@
 all_neffs = np.zeros((widths.shape[0], num_modes))
 all_te_fracs = np.zeros((widths.shape[0], num_modes))
 for i, width in enumerate(tqdm(widths)):
-    core = box(0, 0, width, 0.5)
+    core = box(0, 0, width, 0.33)
     polygons = OrderedDict(
         core=core,
         box=clip_by_rect(core.buffer(1.0, resolution=4), -np.inf, -np.inf, np.inf, 0),
@@ -63,9 +68,20 @@
 all_neffs = np.real(all_neffs)
 plt.xlabel("Width of waveguide / µm")
 plt.ylabel("Effective refractive index")
-plt.ylim(1.444, np.max(all_neffs) + 0.1 * (np.max(all_neffs) - 1.444))
+plt.fill_between(widths, 1.444, alpha=0.5, color="gray")
+plt.ylim(1.36, np.max(all_neffs) + 0.1 * (np.max(all_neffs) - 1.444))
 for lams, te_fracs in zip(all_neffs.T, all_te_fracs.T):
     plt.plot(widths, lams)
     plt.scatter(widths, lams, c=te_fracs, cmap="cool")
 plt.colorbar().set_label("TE fraction")
 plt.show()
+
+# %% [markdown]
+
+# The graph shows a TE mode emerging (getting a greater effective refractive index than the box) at a width of ~750nm.
+# The second mode emerges at a wavelength of ~1700nm.
+# Thus, the waveguide is a single mode waveguide with a width within the range from ~750nm to 1700nm.
+
+# The second mode is at the width at which it emerges a TM-mode, but shows for slightly wider waveguides an anti-crossing with the emerging TE-mode.
+# After this anti-crossing, the mode with the second highest effective refracteive index is TE10-mode, while the TM00-mode keeps existing in the system with an effective refractive inded slightly above the cutoff.
+# At a  width of ~2600nm, a third TE-mode starts being guided.

femwell/pn_analytical.py

@@ -33,9 +33,7 @@ def dn_carriers(wavelength: float, dN: float, dP: float) -> float:
         return -2.98 * 1e-22 * np.power(dN, 1.016) - 1.25 * 1e-18 * np.power(dP, 0.835)
     else:
         wavelength *= 1e-6
-        return -3.64 * 1e-10 * wavelength**2 * dN - 3.51 * 1e-6 * wavelength**2 * np.power(
-            dP, 0.8
-        )
+        return -3.64 * 1e-10 * wavelength**2 * dN - 3.51 * 1e-6 * wavelength**2 * np.power(dP, 0.8)
 
 
 def dalpha_carriers(wavelength: float, dN: float, dP: float) -> float: