{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "881e2d64",
   "metadata": {},
   "source": [
    "# SiN-to-AlOx integrated waveguide vertical coupler\n",
    "\n",
    "This notebook models optical coupling between a silicon nitride (SiN) waveguide and an alumina (Al₂O₃ / AlOx) waveguide stack relevant to monolithically integrated Er-doped Al₂O₃ amplifiers on a silicon photonics platform. The simulated device element is an interlayer taper coupler: a SiN waveguide transitions from a wide section to a narrow tip while an AlOx waveguide transitions from a narrow tip to a wider section above it, separated by a spacer and including a SiO₂ gap layer within the SiN stack, with the goal of transferring the guided mode efficiently between layers near the C-band. The design is based on `C. E. Osornio-Martinez, D. B. Bonneville, I. Hegeman, M. Dijkstra, Q. Segondat, R. Dekker, and S. M. García-Blanco, \"Monolithically integrated erbium-doped polycrystalline Al2O3 waveguide amplifier on silicon photonics platform,\" Opt. Express 33, 23491-23502 (2025).` [DOI: 10.1364/OE.562888](https://doi.org/10.1364/OE.562888).\n",
    "\n",
    "<img src=\"img/vertical_coupler.png\" alt=\"shematic of the coupler\" width=\"500\" />\n",
    "\n",
    "The workflow first runs a set of mode-solver simulations to visualize modal fields and quantify mode overlap versus horizontal shift of the waveguide at multiple wavelengths, identifying alignment sensitivity. Then, it sets up an eigenmode expansion (EME) model and performs a length sweep of the taper region to study how transmission/coupling behavior evolves with taper length. Finally, an FDTD simulation is performed to verify the device performance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7b58b9a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d7ec873",
   "metadata": {},
   "source": [
    "## Simulation Setup\n",
    "\n",
    "We start with the basic simulation setup by defining the wavelength range of interest, materials, and geometries of the vertical coupler. See the referenced paper for details of the design and layer stack. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e2b09b5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define central wavelength and corresponding frequency\n",
    "lda0 = 1.55\n",
    "freq0 = td.C_0 / lda0\n",
    "\n",
    "# Define wavelength range and convert to frequencies\n",
    "ldas = np.linspace(1.48, 1.62, 3)\n",
    "freqs = td.C_0 / ldas\n",
    "\n",
    "# Source bandwidth\n",
    "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42dccd75",
   "metadata": {},
   "source": [
    "We will create a lossless AlOx medium using a constant refractive index, and we will load predefined SiN and oxide materials from the [material library](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/material_library.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2c66732e",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_AlOx = 1.724  # Refractive index for AlOx\n",
    "\n",
    "AlOx = td.Medium.from_nk(\n",
    "    n=n_AlOx, k=0, freq=freq0\n",
    ")  # Create AlOx medium using constant n and zero extinction (lossless)\n",
    "\n",
    "SiN = td.material_library[\"Si3N4\"][\n",
    "    \"Luke2015Sellmeier\"\n",
    "]  # Silicon nitride material model from library\n",
    "\n",
    "SiO2 = td.material_library[\"SiO2\"][\n",
    "    \"Palik_Lossless\"\n",
    "]  # Lossless silicon dioxide model from Palik in material library"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3e196e2",
   "metadata": {},
   "source": [
    "Define geometric parameters for a multilayer SiN stack and an AlOx layer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c6d2555a",
   "metadata": {},
   "outputs": [],
   "source": [
    "w_SiN_tip = 0.3  # SiN tip width\n",
    "w_SiN_wg = 1.2  # SiN waveguide width\n",
    "\n",
    "t_SiN_top = 0.175  # SiN top layer thickness\n",
    "t_SiN_gap = 0.1  # Gap thickness between SiN layers\n",
    "t_SiN_bottom = 0.075  # SiN bottom layer thickness\n",
    "t_SiN = t_SiN_bottom + t_SiN_gap + t_SiN_top  # Total SiN stack thickness\n",
    "\n",
    "t_spacer = 0.35  # Spacer layer thickness\n",
    "\n",
    "w_AlOx_tip = 0.2  # AlOx tip width\n",
    "w_AlOx_wg = 1.75  # AlOx waveguide width\n",
    "t_AlOx = 0.75  # AlOx layer thickness\n",
    "\n",
    "sidewall_angle = np.deg2rad(10)  # Sidewall angle in radians (converted from degrees)\n",
    "inf_eff = 1e4  # Effective infinity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "870d07f9",
   "metadata": {},
   "source": [
    "We design the vertical coupler by optimizing the taper length and the horizontal offset between the AlOx and SiN waveguides. To support this, we define a `create_structures` function that generates the coupler geometry for a given taper length and horizontal shift."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7cb26034",
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_structures(l_taper, y_shift):\n",
    "    \"\"\"Create simulation structures for a coupled SiN–AlOx taper with an SiO2 gap.\n",
    "\n",
    "    Args:\n",
    "        l_taper: Taper length used for both SiN and AlOx polygon definitions.\n",
    "        y_shift: Vertical (y-axis) offset applied to the AlOx waveguide geometry.\n",
    "\n",
    "    Returns:\n",
    "        List of `td.Structure` objects in the order: [AlOx waveguide, SiN waveguide, SiO2 gap].\n",
    "    \"\"\"\n",
    "    # Define SiN taper polygon (x, y) vertices, centered about y = 0\n",
    "    vertices = [\n",
    "        (-inf_eff, -w_SiN_wg / 2),\n",
    "        (-inf_eff, w_SiN_wg / 2),\n",
    "        (0, w_SiN_wg / 2),\n",
    "        (l_taper, w_SiN_tip / 2),\n",
    "        (l_taper, -w_SiN_tip / 2),\n",
    "        (0, -w_SiN_wg / 2),\n",
    "    ]\n",
    "\n",
    "    # Create SiN waveguide geometry as an extruded polygon in z\n",
    "    SiN_wg_geometry = td.PolySlab(\n",
    "        vertices=vertices,\n",
    "        axis=2,\n",
    "        slab_bounds=(0, t_SiN),\n",
    "        sidewall_angle=sidewall_angle,\n",
    "        reference_plane=\"top\",\n",
    "    )\n",
    "\n",
    "    # Wrap SiN geometry into a structure with the SiN material\n",
    "    wg_SiN = td.Structure(geometry=SiN_wg_geometry, medium=SiN)\n",
    "\n",
    "    # Create SiO2 gap layer as a box spanning the full simulation x/y extents\n",
    "    SiO2_gap = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-inf_eff, -inf_eff, t_SiN_bottom),  # bottom of gap in z\n",
    "            rmax=(inf_eff, inf_eff, t_SiN_bottom + t_SiN_gap),  # top of gap in z\n",
    "        ),\n",
    "        medium=SiO2,\n",
    "    )\n",
    "\n",
    "    # Define AlOx taper polygon vertices with vertical offset (y_shift)\n",
    "    vertices = [\n",
    "        (0, -w_AlOx_tip / 2 + y_shift),\n",
    "        (0, w_AlOx_tip / 2 + y_shift),\n",
    "        (l_taper, w_AlOx_wg / 2 + y_shift),\n",
    "        (inf_eff, w_AlOx_wg / 2 + y_shift),\n",
    "        (inf_eff, -w_AlOx_wg / 2 + y_shift),\n",
    "        (l_taper, -w_AlOx_wg / 2 + y_shift),\n",
    "    ]\n",
    "\n",
    "    # Create AlOx waveguide geometry (positioned above SiN with spacer and AlOx thickness)\n",
    "    AlOx_wg_geometry = td.PolySlab(\n",
    "        vertices=vertices,\n",
    "        axis=2,\n",
    "        slab_bounds=(t_SiN + t_spacer, t_SiN + t_spacer + t_AlOx),\n",
    "        sidewall_angle=sidewall_angle,\n",
    "        reference_plane=\"top\",\n",
    "    )\n",
    "\n",
    "    # Wrap AlOx geometry into a structure with the AlOx material\n",
    "    wg_AlOx = td.Structure(geometry=AlOx_wg_geometry, medium=AlOx)\n",
    "\n",
    "    # Return structures in the intended stacking/usage order\n",
    "    return [wg_AlOx, wg_SiN, SiO2_gap]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a1d9b78",
   "metadata": {},
   "source": [
    "## Mode Overlap Calculation for Misalignment Analysis\n",
    "\n",
    "We first optimize the horizontal offset by maximizing the mode-overlap integral. This requires running mode-solver simulations across a range of horizontal offsets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "afd600a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Buffer spacing\n",
    "buffer_x = 5\n",
    "buffer_y = 2.5\n",
    "buffer_z = 2\n",
    "\n",
    "l_taper_0 = 100  # Base taper length used to define the simulation domain\n",
    "\n",
    "# Define a simulation domain box\n",
    "sim_box = td.Box.from_bounds(\n",
    "    rmin=(-buffer_x, -w_AlOx_wg / 2 - buffer_y, -buffer_z),\n",
    "    rmax=(\n",
    "        l_taper_0 + buffer_x,\n",
    "        w_AlOx_wg / 2 + buffer_y,\n",
    "        t_SiN + t_spacer + t_AlOx + buffer_z,\n",
    "    ),\n",
    ")\n",
    "\n",
    "# Finite difference grid specification\n",
    "grid_spec = td.GridSpec.auto(min_steps_per_wvl=30, wavelength=lda0)\n",
    "\n",
    "# Mode solving specification\n",
    "mode_spec = td.ModeSpec(precision=\"double\", target_neff=2, num_modes=1)\n",
    "\n",
    "# Set up a mode simulation\n",
    "mode_sim_c1 = td.ModeSimulation(\n",
    "    center=sim_box.center,\n",
    "    size=sim_box.size,\n",
    "    freqs=freqs,\n",
    "    grid_spec=grid_spec,\n",
    "    structures=create_structures(l_taper_0, 1),\n",
    "    plane=td.Box(center=(-buffer_x / 2, 0, 0), size=(0, td.inf, td.inf)),\n",
    "    mode_spec=mode_spec,\n",
    "    medium=SiO2,\n",
    ")\n",
    "\n",
    "# Plot the mode simulation\n",
    "mode_sim_c1.plot(x=l_taper_0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3f04eca9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">y_shift=0.00    → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:09</span>\n",
       "y_shift=0.10    → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:09</span>\n",
       "y_shift=0.20    → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:09</span>\n",
       "y_shift=0.30    → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:09</span>\n",
       "y_shift=0.40    → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:09</span>\n",
       "y_shift=0.50    → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:09</span>\n",
       "y_shift=0.60    → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:09</span>\n",
       "y_shift=0.70    → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:09</span>\n",
       "y_shift=0.80    → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:08</span>\n",
       "y_shift=0.90    → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:08</span>\n",
       "y_shift=1.00    → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:08</span>\n",
       "c1              → <span style=\"color: #008000; text-decoration-color: #008000\">success</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:08</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "y_shift=0.00    → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:09\u001b[0m\n",
       "y_shift=0.10    → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:09\u001b[0m\n",
       "y_shift=0.20    → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:09\u001b[0m\n",
       "y_shift=0.30    → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:09\u001b[0m\n",
       "y_shift=0.40    → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:09\u001b[0m\n",
       "y_shift=0.50    → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:09\u001b[0m\n",
       "y_shift=0.60    → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:09\u001b[0m\n",
       "y_shift=0.70    → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:09\u001b[0m\n",
       "y_shift=0.80    → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:08\u001b[0m\n",
       "y_shift=0.90    → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:08\u001b[0m\n",
       "y_shift=1.00    → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:08\u001b[0m\n",
       "c1              → \u001b[32msuccess\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:08\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">23:13:36 Eastern Standard Time </span>Batch complete.                                  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m23:13:36 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mode_sim_c2 = mode_sim_c1.updated_copy(\n",
    "    plane=td.Box(\n",
    "        center=(0, 0, 0), size=(0, td.inf, td.inf)\n",
    "    ),  # Update the mode plane to the y-z plane at x=0\n",
    ")\n",
    "\n",
    "y_shift_list = np.linspace(0, 1, 11)  # Sweep y-shift values from 0 to 1 with 11 samples\n",
    "mode_sims = {\n",
    "    f\"y_shift={y_shift:.2f}\": mode_sim_c2.updated_copy(\n",
    "        structures=create_structures(l_taper_0, y_shift)\n",
    "    )\n",
    "    for y_shift in y_shift_list  # Build a dict of simulations keyed by formatted y-shift label\n",
    "}\n",
    "mode_sims[\"c1\"] = mode_sim_c1\n",
    "\n",
    "batch = web.Batch(simulations=mode_sims)  # Create a batch job containing all simulations\n",
    "batch_results = batch.run(path_dir=\"data\")  # Run the batch"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "039cb553",
   "metadata": {},
   "source": [
    "Plot the mode profiles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "46ed57c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 1, figsize=(8, 8), tight_layout=True)\n",
    "\n",
    "batch_results[\"c1\"].plot_field(\"E\", \"abs\", f=freq0, vmax=30, ax=ax[0])\n",
    "\n",
    "batch_results[f\"y_shift={y_shift_list[0]:.2f}\"].plot_field(\n",
    "    \"E\",\n",
    "    \"abs\",\n",
    "    f=freq0,\n",
    "    vmax=30,\n",
    "    ax=ax[1],\n",
    ")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fc45f1d",
   "metadata": {},
   "source": [
    "The mode overlap integral can be calculated by the `outer_dot` method. We plot the overlap as a function of horizontal shift and find that 1 µm shift will significantly reduce the mode mismatch compared to a smaller shift. For the rest of the design, we will use 1 µm shift."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6dccc226",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "overlap = np.array(\n",
    "    [\n",
    "        # Compute the mode overlap between the shifted case and the reference (\"c1\") for each y-shift\n",
    "        batch_results[f\"y_shift={y_shift:.2f}\"]\n",
    "        .modes.outer_dot(\n",
    "            batch_results[\"c1\"].modes\n",
    "        )  # Outer product of modes to get overlaps between mode sets\n",
    "        .values.squeeze()\n",
    "        for y_shift in y_shift_list\n",
    "    ]\n",
    ")\n",
    "\n",
    "# Plot overlap magnitude (in dB) versus y-shift for each wavelength index\n",
    "plt.plot(y_shift_list, 20 * np.log10(np.abs(overlap[:, 0])), label=\"1620 nm\")\n",
    "plt.plot(y_shift_list, 20 * np.log10(np.abs(overlap[:, 1])), label=\"1550 nm\")\n",
    "plt.plot(y_shift_list, 20 * np.log10(np.abs(overlap[:, 2])), label=\"1480 nm\")\n",
    "\n",
    "\n",
    "plt.xlabel(\"y shift (μm)\")\n",
    "plt.ylabel(\"Mode overlap (dB)\")\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4e22ced",
   "metadata": {},
   "source": [
    "## EME Simulation\n",
    "\n",
    "Next, we need to optimize the coupler length to maximize coupling efficiency. EME enables this to be done very efficiently. We will sweep the taper length from 100 µm to 1 mm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d4aedce8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid_1 = td.EMEUniformGrid(\n",
    "    num_cells=1,  # Single EME cell for uniform sections\n",
    "    mode_spec=td.EMEModeSpec(num_modes=10, precision=\"double\"),\n",
    ")\n",
    "grid_2 = td.EMEUniformGrid(\n",
    "    num_cells=60,  # Finer discretization for the taper region\n",
    "    mode_spec=td.EMEModeSpec(num_modes=10, precision=\"double\"),\n",
    ")\n",
    "\n",
    "l_taper_list = np.linspace(100, 1000, 100)  # Taper lengths to sweep\n",
    "\n",
    "eme_grid = td.EMECompositeGrid(\n",
    "    subgrids=[grid_1, grid_2, grid_1],  # Left uniform -> taper -> right uniform\n",
    "    subgrid_boundaries=[\n",
    "        0,\n",
    "        l_taper_0,\n",
    "    ],  # Boundary location(s) between subgrids (taper starts at x=0, ends at x=l_taper_0)\n",
    ")\n",
    "\n",
    "y_shift_opt = 1  # Optimal vertical shift\n",
    "\n",
    "eme_sim = td.EMESimulation(\n",
    "    center=sim_box.center,\n",
    "    size=sim_box.size,\n",
    "    structures=create_structures(l_taper_0, y_shift_opt),\n",
    "    grid_spec=grid_spec,\n",
    "    medium=SiO2,\n",
    "    eme_grid_spec=eme_grid,\n",
    "    freqs=freqs,\n",
    "    axis=0,\n",
    "    sweep_spec=td.EMELengthSweep(\n",
    "        scale_factors=l_taper_list / l_taper_0\n",
    "    ),  # Sweep taper length via scale factors\n",
    "    store_port_modes=False,\n",
    ")\n",
    "\n",
    "fig, ax = plt.subplots(2, 1, tight_layout=True)\n",
    "eme_sim.plot(z=t_SiN_bottom, ax=ax[0])\n",
    "ax[0].set_aspect(\"auto\")\n",
    "eme_sim.plot(z=t_SiN_top + t_SiN_bottom + t_SiN_gap + t_spacer + t_AlOx / 2, ax=ax[1])\n",
    "ax[1].set_aspect(\"auto\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c9e8735",
   "metadata": {},
   "source": [
    "Plot cross-sections of the coupler at multiple $x$ positions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c04a508f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 2, figsize=(10, 10), tight_layout=True)\n",
    "\n",
    "eme_sim.plot(x=-buffer_x / 2, ax=ax[0, 0])\n",
    "eme_sim.plot(x=0, ax=ax[0, 1])\n",
    "eme_sim.plot(x=l_taper_0, ax=ax[1, 0])\n",
    "eme_sim.plot(x=l_taper_0 + buffer_x / 2, ax=ax[1, 1])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba6076e1",
   "metadata": {},
   "source": [
    "Run the EME simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2b181504",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation_data.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">1.9/1.9 MB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">6.2 MB/s</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;32m↓\u001b[0m \u001b[1;34msimulation_data.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m1.9/1.9 MB\u001b[0m • \u001b[31m6.2 MB/s\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">23:14:01 Eastern Standard Time </span>Loading simulation from simulation_data.hdf5     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m23:14:01 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">23:14:02 Eastern Standard Time </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Warning messages were found in the      </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #800000; text-decoration-color: #800000\">solver log. For more information, check          </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'SimulationData.log'</span><span style=\"color: #800000; text-decoration-color: #800000\"> or use                      </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.download_log(task_id)'</span><span style=\"color: #800000; text-decoration-color: #800000\">.                     </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m23:14:02 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Warning messages were found in the      \u001b[0m\n",
       "\u001b[2;36m                               \u001b[0m\u001b[31msolver log. For more information, check          \u001b[0m\n",
       "\u001b[2;36m                               \u001b[0m\u001b[32m'SimulationData.log'\u001b[0m\u001b[31m or use                      \u001b[0m\n",
       "\u001b[2;36m                               \u001b[0m\u001b[32m'web.download_log\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m\u001b[31m.                     \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "eme_sim_data = web.run(eme_sim, task_name=\"EME\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef32b56a",
   "metadata": {},
   "source": [
    "Plot the coupling efficiency as a function of taper length. The coupling efficiency saturates at approximately 400 µm. Increasing the taper length beyond 400 µm provides no additional benefit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "89a5e3a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "T_0 = (\n",
    "    eme_sim_data.smatrix.S21.isel(mode_index_in=0, mode_index_out=0, f=0).abs\n",
    ") ** 2  # Power transmission at f index 0 (1480 nm)\n",
    "T_1 = (\n",
    "    eme_sim_data.smatrix.S21.isel(mode_index_in=0, mode_index_out=0, f=1).abs\n",
    ") ** 2  # Power transmission at f index 1 (1550 nm)\n",
    "T_2 = (\n",
    "    eme_sim_data.smatrix.S21.isel(mode_index_in=0, mode_index_out=0, f=2).abs\n",
    ") ** 2  # Power transmission at f index 2 (1620 nm)\n",
    "\n",
    "plt.plot(l_taper_list, 10 * np.log10(T_0), c=\"blue\", linewidth=2, label=\"1480 nm\")\n",
    "plt.plot(l_taper_list, 10 * np.log10(T_1), c=\"red\", linewidth=2, label=\"1550 nm\")\n",
    "plt.plot(l_taper_list, 10 * np.log10(T_2), c=\"purple\", linewidth=2, label=\"1620 nm\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"Taper length (µm)\")\n",
    "plt.ylabel(\"Coupling efficiency (dB)\")\n",
    "plt.ylim(-1, 0)\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d138fb8",
   "metadata": {},
   "source": [
    "## FDTD Simulation\n",
    "\n",
    "Finally, we will run an FDTD simulation using the optimal taper length to verify the design’s performance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8dc8555b",
   "metadata": {},
   "outputs": [],
   "source": [
    "l_taper_opt = 400  # Length of the optimized taper section (in simulation length units)\n",
    "\n",
    "mode_source = td.ModeSource(\n",
    "    center=(-buffer_x / 2, 0, 0),\n",
    "    size=(\n",
    "        0,\n",
    "        3 * w_SiN_wg,\n",
    "        5 * (t_SiN_bottom + t_SiN_top + t_SiN_gap),\n",
    "    ),\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "    mode_spec=td.ModeSpec(),\n",
    "    mode_index=0,\n",
    "    direction=\"+\",\n",
    "    num_freqs=1,\n",
    ")\n",
    "\n",
    "mode_monitor = td.ModeMonitor(\n",
    "    center=(\n",
    "        l_taper_opt + buffer_x / 2,\n",
    "        1,\n",
    "        t_SiN_bottom + t_SiN_top + t_SiN_gap + t_AlOx / 2,\n",
    "    ),\n",
    "    size=(0, 3 * w_AlOx_wg, 5 * t_AlOx),\n",
    "    freqs=freqs,\n",
    "    mode_spec=td.ModeSpec(),\n",
    "    name=\"mode\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c58b3587",
   "metadata": {},
   "source": [
    "Create a FDTD simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bc0ee89c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_box = td.Box.from_bounds(\n",
    "    rmin=(-buffer_x, -w_AlOx_wg / 2 - buffer_y, -buffer_z),\n",
    "    rmax=(\n",
    "        l_taper_opt + buffer_x,\n",
    "        w_AlOx_wg / 2 + buffer_y,\n",
    "        t_SiN_top + t_SiN_bottom + t_SiN_gap + t_spacer + t_AlOx + buffer_z,\n",
    "    ),\n",
    ")\n",
    "\n",
    "fdtd_sim = td.Simulation(\n",
    "    center=sim_box.center,\n",
    "    size=sim_box.size,\n",
    "    run_time=4e-12,\n",
    "    structures=create_structures(l_taper_opt, y_shift_opt),\n",
    "    sources=[mode_source],\n",
    "    monitors=[mode_monitor],\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=20, wavelength=lda0),\n",
    "    medium=SiO2,\n",
    ")\n",
    "\n",
    "fig, ax = plt.subplots(2, 1, tight_layout=True)\n",
    "fdtd_sim.plot(z=t_SiN_bottom, ax=ax[0])\n",
    "ax[0].set_aspect(\"auto\")\n",
    "fdtd_sim.plot(z=t_SiN_top + t_SiN_bottom + t_SiN_gap + t_spacer + t_AlOx / 2, ax=ax[1])\n",
    "ax[1].set_aspect(\"auto\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dfe59ddf",
   "metadata": {},
   "source": [
    "Run the FDTD simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "66f0e499",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">2.1/2.1 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m2.1/2.1 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">23:14:05 Eastern Standard Time </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.106</span>. Minimum cost   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>depends on task execution details. Use           \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>FlexCredit cost after a simulation run.          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m23:14:05 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m9.106\u001b[0m. Minimum cost   \n",
       "\u001b[2;36m                               \u001b[0mdepends on task execution details. Use           \n",
       "\u001b[2;36m                               \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed       \n",
       "\u001b[2;36m                               \u001b[0mFlexCredit cost after a simulation run.          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">23:14:06 Eastern Standard Time </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.106</span>. Minimum cost   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>depends on task execution details. Use           \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>FlexCredit cost after a simulation run.          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m23:14:06 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m9.106\u001b[0m. Minimum cost   \n",
       "\u001b[2;36m                               \u001b[0mdepends on task execution details. Use           \n",
       "\u001b[2;36m                               \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed       \n",
       "\u001b[2;36m                               \u001b[0mFlexCredit cost after a simulation run.          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a job for the given FDTD simulation\n",
    "job = web.Job(simulation=fdtd_sim, task_name=\"test_name\")\n",
    "\n",
    "# Request an estimated compute cost for the created job\n",
    "_ = web.estimate_cost(job.task_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3020f323",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation_data.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">4.1/4.1 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;32m↓\u001b[0m \u001b[1;34msimulation_data.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m4.1/4.1 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">23:14:09 Eastern Standard Time </span>Loading simulation from simulation_data.hdf5     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m23:14:09 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data = job.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1fa7073",
   "metadata": {},
   "source": [
    "Plot the coupling efficiency as a function of wavelength. The results confirm the design’s low loss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "dbea604c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Extract mode transmission amplitudes for the fundamental mode in the forward (+) direction\n",
    "amp = sim_data[\"mode\"].amps.sel(mode_index=0, direction=\"+\").values\n",
    "\n",
    "# Convert complex amplitudes to power transmission (|amp|^2)\n",
    "T = np.abs(amp) ** 2\n",
    "\n",
    "# Report coupling efficiency in dB\n",
    "plt.plot(ldas, 10 * np.log10(T), linewidth=2)\n",
    "plt.xlabel(\"Wavelength (μm)\")\n",
    "plt.ylabel(\"Coupling efficiency (dB)\")\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7844afac-cf45-4a8d-9719-b8fa0f8ce580",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "applications": [
   "Passive photonic integrated circuit components"
  ],
  "description": "This notebook demonstrates mode-solver-based alignment sensitivity analysis and an eigenmode expansion (EME) taper-length sweep to optimize coupling between a silicon nitride (SiN) waveguide and an alumina (Al2O3/AlOx) waveguide stack across multiple wavelengths.",
  "feature_image": "./img/vertical_coupler.png",
  "features": [
   "Mode analysis",
   "Parameter sweep",
   "Eigenmode expansion (EME)"
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "Tidy3D, mode solver, mode overlap, mode matching, eigenmode expansion, EME, taper coupler, interlayer coupler, SiN, silicon nitride, Al2O3, alumina, AlOx, integrated amplifier, Er-doped alumina",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.11"
  },
  "title": "SiN-to-AlOx integrated waveguide vertical coupler"
 },
 "nbformat": 4,
 "nbformat_minor": 5
}