{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "568b3cae-6a1b-41ab-b3d9-8d8190de802e",
   "metadata": {},
   "source": [
    "# Photonics-integrated terahertz transmission lines"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1187e70-6aa6-417a-93fc-082528ee17e2",
   "metadata": {},
   "source": [
    "**Author: Yazan Lampert, PhD student at Ecole Polytechnique Fédérale de Lausanne**\n",
    "\n",
    "Recent efforts have focused on matching the velocities of optical and microwave modes to demonstrate phase and intensity modulators with low loss and low $V_\\pi$. Popular platforms include Lithium Niobate and organic silicon photonic platform. While such devices can operate at high speeds, frequencies above 500 GHz are not yet well studied. In this notebook, we simulate transmission lines that are phase-matched with the optical wavelength over the range [250 GHz - 5 THz]. This notebook is based on the paper:\n",
    "[Photonics-integrated terahertz transmission lines](https://www.nature.com/articles/s41467-025-62267-y). \n",
    "The transmission lines in this paper are used to provide efficient interaction between optical and terahertz pulses. The authors combined these structures with on-chip antennas to demonstrate terahertz generation and detection on-chip.\n",
    "\n",
    "<img src=\"img/THzTransmissionLine.png\" width=\"600\" alt=\"Schematic\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1071b980-19c0-4b93-8425-c0a7757be4f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tidy3d as td\n",
    "import tidy3d.plugins.microwave as mw\n",
    "import tidy3d.plugins.smatrix as sm\n",
    "from tidy3d.plugins.dispersion import FastDispersionFitter\n",
    "from tidy3d.plugins.mode import ModeSolver\n",
    "\n",
    "td.config.logging_level = \"ERROR\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e63afeb-9c29-4337-ba62-eb5709852a03",
   "metadata": {},
   "source": [
    "### Building the Simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90ac7055-75f1-4fd9-9917-da308862ce19",
   "metadata": {},
   "source": [
    "### Key Parameters"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "120b0333-feb4-43a8-9456-292bf3f20a61",
   "metadata": {},
   "source": [
    "We begin by defining the frequency range for both the terahertz and the optical modes. We will run two separate simulations for each range."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bd53fd47-7d45-4394-856e-78818ce30b64",
   "metadata": {},
   "outputs": [],
   "source": [
    "## frequencies for the terahertz mode\n",
    "# frequency range (Hz)\n",
    "f_min, f_max = (250e9, 5e12)\n",
    "\n",
    "# center frequency\n",
    "f0 = (f_max + f_min) / 2\n",
    "\n",
    "# frequency sampling points\n",
    "freqs = np.linspace(f_min, f_max, 50)\n",
    "\n",
    "## frequencies for the optical mode\n",
    "# wavelength range [um]\n",
    "wl_min, wl_max = (1.480, 1.620)\n",
    "\n",
    "nu_min, nu_max = (td.C_0 / wl_max, td.C_0 / wl_min)\n",
    "\n",
    "# center optical frequency\n",
    "nu0 = (nu_min + nu_max) / 2\n",
    "\n",
    "# optical frequency sampling points\n",
    "opt_freqs = np.linspace(nu_min, nu_max, 50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27e877a0",
   "metadata": {},
   "source": [
    "Next, we define the entire structure which is shown in detail in the supplementary material of the referenced paper. The structure consists of a photonic waveguide that is placed between two gold striplines. The optical waveguide is for guiding the optical mode and the striplines are a transmission line for the terahertz mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "038c67ba-f3e0-4cae-bc4b-da1737e8e55b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# geometry\n",
    "w_TL = 3.5  # signal strip width\n",
    "h_TL = 0.3  # transmission line thickness\n",
    "L = 5  # length of structure\n",
    "\n",
    "h_cladding = 1  # cladding thickness\n",
    "h_opening = h_cladding - h_TL  # opening above the stripline\n",
    "\n",
    "w_g = 3.3  # gap between edge-coupled pair\n",
    "\n",
    "h_SiO2 = 4.7  # oxide thickness\n",
    "h_Si = 2  # substrate thickness\n",
    "\n",
    "h_TF = 0.3  # thin-film lithium niobate thickness\n",
    "\n",
    "h_wg = 0.3  # waveguide height\n",
    "wg_w = 1.85  # waveguide width\n",
    "\n",
    "entire_height = h_Si + h_SiO2 + h_TF + h_wg + h_opening  # entire structure height\n",
    "\n",
    "len_inf = 1e6  # effective infinity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05c6d1fc",
   "metadata": {},
   "source": [
    "Due to strong dispersion, material properties must be defined separately for optical and terahertz frequencies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1e2fd70e-9708-4c69-9227-8bbb99007e9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "34905abe8880437eaf090bdc91a9fc44",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "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": [
    "# terahertz material properties\n",
    "cond = 49  # Conductivity of gold in S/um\n",
    "\n",
    "## for Lithium Niobate\n",
    "eps_inf = 0.95\n",
    "w = 2 * np.pi * freqs / 1e12 / 1000  # (rad/fs or rad THz /1000)\n",
    "A = 2.027e1  # (rad/fs)\n",
    "B = 1.068e1  # (rad/fs)\n",
    "eps1 = 16.6\n",
    "eps2 = 2.6\n",
    "omega_0_1 = 4.7e-2  # (rad/fs)\n",
    "omega_0_2 = 1.19e-1  # (rad/fs)\n",
    "delta_0_1 = 2.3e-3  # (rad/fs)\n",
    "delta_0_2 = 2.8e-3  # (rad/fs)\n",
    "epsilon_complex = (\n",
    "    eps_inf\n",
    "    + A**2 / (B**2 - w**2)\n",
    "    + eps1 * omega_0_1**2 / (omega_0_1**2 - 2j * delta_0_1 * w - w**2)\n",
    "    + eps2 * omega_0_2**2 / (omega_0_2**2 - 2j * delta_0_2 * w - w**2)\n",
    ")\n",
    "epsilon_r = np.real(epsilon_complex)\n",
    "epsilon_i = np.imag(epsilon_complex)\n",
    "\n",
    "n_Si_THz = 3.41\n",
    "n_SiO2_THz = 1.9599\n",
    "\n",
    "Si_THz = td.Medium(permittivity=n_Si_THz**2)\n",
    "SiO2_THz = td.Medium(permittivity=n_SiO2_THz**2)\n",
    "\n",
    "\n",
    "LN_e_THz = FastDispersionFitter.constant_loss_tangent_model(\n",
    "    epsilon_r,\n",
    "    epsilon_i / epsilon_r,\n",
    "    (f_min, f_max),\n",
    "    number_sampling_frequency=len(freqs),\n",
    "    tolerance_rms=2e-4,\n",
    ")\n",
    "\n",
    "\n",
    "LN = td.material_library[\"LiNbO3\"][\"Zelmon1997\"]\n",
    "LN_e_opt = LN(1)\n",
    "\n",
    "sio2_opt = td.material_library[\"SiO2\"][\"Horiba\"]\n",
    "si_opt = td.material_library[\"cSi\"][\"Li1993_293K\"]\n",
    "\n",
    "air = td.Medium(permittivity=1.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16b8d750",
   "metadata": {},
   "source": [
    "When plotting the refractive indices for both ranges, we notice that there is a great mismatch between optical and terahertz frequencies. This variation is due to the strong dispersion of lithium niobate compared to material such as silicon and silicon oxide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1c393abd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_plot = plt.subplots(1, 2, figsize=(8, 3), sharey=True, tight_layout=True)\n",
    "LN_e_THz.plot(freqs, ax=ax_plot[0])\n",
    "LN_e_opt.zz.plot(opt_freqs, ax=ax_plot[1])\n",
    "ax_plot[0].set_ylabel(\"complex refractive index\")\n",
    "ax_plot[0].set_title(\"Bulk Lithium Niobate - THz frequencies\")\n",
    "ax_plot[1].set_title(\"Bulk Lithium Niobate - Optical frequencies\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04b2d755-27a0-4e6b-b619-506e015e18c7",
   "metadata": {},
   "source": [
    "## Terahertz Simulation\n",
    "Now that we have defined the materials, we will create the structures. For the optical simulation, we will keep the structures and update the refractive indices. This is done after the terahertz simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "249d436d-1144-4ede-8680-f060fb848d71",
   "metadata": {},
   "outputs": [],
   "source": [
    "# metal medium which is needed for the terahertz mode\n",
    "med_metal = td.LossyMetalMedium(\n",
    "    conductivity=cond, frequency_range=(f_min, f_max), name=\"Metal\"\n",
    ")\n",
    "med_metal = med_metal.updated_copy(viz_spec=td.VisualizationSpec(facecolor=\"#edbe26\"))\n",
    "\n",
    "# silicon dioxide below thin-film lithium niobate layer\n",
    "oxide_box = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=(0, -h_TL / 2 - h_TF - h_SiO2 / 2, 0), size=(len_inf, h_SiO2, len_inf)\n",
    "    ),\n",
    "    medium=SiO2_THz,\n",
    "    name=\"oxide\",\n",
    ")\n",
    "\n",
    "# thin-film lithium niobate layer\n",
    "TFLN = td.Structure(\n",
    "    geometry=td.Box(center=(0, -h_TL / 2 - h_TF / 2, 0), size=(len_inf, h_TF, len_inf)),\n",
    "    medium=LN_e_THz,\n",
    "    name=\"TFLN\",\n",
    ")\n",
    "\n",
    "# due to fabrication constraints, the waveguide has sidewalls at an angle of 30 degrees\n",
    "sidewall_angle = 30\n",
    "points = np.array(\n",
    "    [\n",
    "        (-wg_w / 2, -h_wg / 2),\n",
    "        (wg_w / 2, -h_wg / 2),\n",
    "        (wg_w / 2 - np.tan(np.pi * sidewall_angle / 180) * h_wg, h_wg / 2),\n",
    "        (-wg_w / 2 + np.tan(np.pi * sidewall_angle / 180) * h_wg, h_wg / 2),\n",
    "    ]\n",
    ")\n",
    "wg = td.Structure(\n",
    "    geometry=td.PolySlab(vertices=points, axis=2, slab_bounds=(-L / 2, L / 2)),\n",
    "    medium=LN_e_THz,\n",
    "    name=\"waveguide\",\n",
    ")\n",
    "\n",
    "# substrate\n",
    "str_sub = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=(0, -h_TL / 2 - h_TF - h_SiO2 - h_Si / 2, 0),\n",
    "        size=(len_inf, h_Si, len_inf),\n",
    "    ),\n",
    "    medium=Si_THz,\n",
    "    name=\"substrate\",\n",
    ")\n",
    "\n",
    "# left transmission line strip\n",
    "str_strip_left = td.Structure(\n",
    "    geometry=td.Box(center=(-(w_g + w_TL) / 2, 0, 0), size=(w_TL, h_TL, len_inf)),\n",
    "    medium=med_metal,\n",
    "    name=\"left TL\",\n",
    ")\n",
    "\n",
    "# Right transmission line strip\n",
    "str_strip_right = td.Structure(\n",
    "    geometry=td.Box(center=((w_g + w_TL) / 2, 0, 0), size=(w_TL, h_TL, len_inf)),\n",
    "    medium=med_metal,\n",
    "    name=\"right TL\",\n",
    ")\n",
    "\n",
    "# opening above left transmission line strip\n",
    "left_opening = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=(-(w_g + w_TL) / 2, h_TL / 2 + h_opening / 2, 0),\n",
    "        size=(w_TL, h_opening, len_inf),\n",
    "    ),\n",
    "    medium=air,\n",
    "    name=\"left_opening_TL\",\n",
    ")\n",
    "\n",
    "# opening above right transmission line strip\n",
    "right_opening = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=((w_g + w_TL) / 2, h_TL / 2 + h_opening / 2, 0),\n",
    "        size=(w_TL, h_opening, len_inf),\n",
    "    ),\n",
    "    medium=air,\n",
    "    name=\"right_opening_TL\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9533498e-1efe-4a62-b8d2-80574393855a",
   "metadata": {},
   "source": [
    "### Grid and Boundaries"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5832a166-8514-46da-8532-f167c7f0492b",
   "metadata": {},
   "source": [
    "The [`LayerRefinementSpec`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.LayerRefinementSpec.html) feature is useful for refining the grid around metallic structures as it automatically detects metal edges and corners."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1d7e3ffc-72af-4081-9a90-7f21a655ddeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a LayerRefinementSpec from structures\n",
    "lr_spec = td.LayerRefinementSpec.from_structures(\n",
    "    structures=[str_strip_left, str_strip_right],\n",
    "    axis=1,  # layer normal is in y-direction\n",
    "    min_steps_along_axis=10,  # min  grid cells along normal direction\n",
    "    refinement_inside_sim_only=False,  # metal structures extend outside sim domain. Set 'False' to snap to corners outside sim.\n",
    "    bounds_snapping=\"bounds\",  # snap grid to metal boundaries\n",
    "    corner_refinement=td.GridRefinement(dl=h_TL / 20, num_cells=2),\n",
    ")\n",
    "\n",
    "# the rest of the grid is automatically generated based on the wavelength.\n",
    "grid_spec = td.GridSpec.auto(\n",
    "    wavelength=td.C_0 / f_max,\n",
    "    min_steps_per_wvl=50,\n",
    "    layer_refinement_specs=[lr_spec],\n",
    ")\n",
    "\n",
    "# perfectly matched layers for the boundaries\n",
    "boundary_spec = td.BoundarySpec(\n",
    "    x=td.Boundary.pml(),\n",
    "    y=td.Boundary.pml(),\n",
    "    z=td.Boundary.pml(),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "490311c3-1eb8-4b7f-ac96-eebe206653ff",
   "metadata": {},
   "source": [
    "### Wave Ports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6e9df262-b3a6-41c8-8f82-52ec4842aee0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define port specification\n",
    "wave_port_mode_spec = td.ModeSpec(num_modes=2, target_neff=2.2)\n",
    "\n",
    "# define current and voltage integrals\n",
    "current_integral = mw.CurrentIntegralAxisAligned(\n",
    "    center=((w_g + w_TL) / 2, 0, -L / 2), size=(w_TL + w_g, 4 * h_TL, 0), sign=\"+\"\n",
    ")\n",
    "voltage_integral = mw.VoltageIntegralAxisAligned(\n",
    "    center=(0, 0, -L / 2),\n",
    "    size=(w_g, 0, 0),\n",
    "    extrapolate_to_endpoints=True,\n",
    "    snap_path_to_grid=True,\n",
    "    sign=\"+\",\n",
    ")\n",
    "\n",
    "# Define wave ports\n",
    "WP1 = sm.WavePort(\n",
    "    center=(0, 0, -L / 2),\n",
    "    size=(len_inf, len_inf, 0),\n",
    "    mode_spec=wave_port_mode_spec,\n",
    "    direction=\"+\",\n",
    "    name=\"WP1\",\n",
    "    mode_index=0,\n",
    "    current_integral=current_integral,\n",
    "    voltage_integral=voltage_integral,\n",
    ")\n",
    "WP2 = WP1.updated_copy(\n",
    "    name=\"WP2\",\n",
    "    center=(0, 0, L / 2),\n",
    "    direction=\"-\",\n",
    "    current_integral=current_integral.updated_copy(\n",
    "        center=((w_g + w_TL) / 2, 0, L / 2), sign=\"-\"\n",
    "    ),\n",
    "    voltage_integral=voltage_integral.updated_copy(center=(0, 0, L / 2)),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12730e2c-1a56-4fcb-9f06-86246b0b229f",
   "metadata": {},
   "source": [
    "### Define the Terahertz Simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90c2cb15-6fb8-4537-b29a-b46b4caed7f2",
   "metadata": {},
   "source": [
    "The `Simulation` object in Tidy3D contains information about the entire simulation environment, including boundary conditions, grid, structures, and monitors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "66772086-16cf-4dd2-8730-be2fd29b6dfc",
   "metadata": {},
   "outputs": [],
   "source": [
    "sim_thz = td.Simulation(\n",
    "    size=(4 * w_TL, entire_height, 1.01 * L),\n",
    "    center=(0, (h_cladding + h_opening - entire_height) / 2, 0),\n",
    "    grid_spec=grid_spec,\n",
    "    boundary_spec=boundary_spec,\n",
    "    structures=[\n",
    "        str_sub,\n",
    "        str_strip_left,\n",
    "        str_strip_right,\n",
    "        wg,\n",
    "        TFLN,\n",
    "        oxide_box,\n",
    "        left_opening,\n",
    "        right_opening,\n",
    "    ],\n",
    "    monitors=[],\n",
    "    run_time=5e-12,  # simulation run time in seconds\n",
    "    shutoff=1e-7,  # lower shutoff threshold for more accuracy at low frequencies\n",
    "    plot_length_units=\"um\",\n",
    "    medium=SiO2_THz,  # background_medium is silicon dioxide\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2971c875-fcdb-405a-9bec-be719fe8743a",
   "metadata": {},
   "source": [
    "Before running the simulation, it is recommended to verify that the structures have been created properly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6d626ca3-c367-4cc4-ad93-07645bf2c9dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
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       "    <script>\n",
       "        \n",
       "        /**\n",
       "        * Simulation Viewer Injector\n",
       "        *\n",
       "        * Monitors the document for elements being added in the form:\n",
       "        *\n",
       "        *    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"{...}\" />\n",
       "        *\n",
       "        * This script will then inject an iframe to the viewer application, and pass it the simulation data\n",
       "        * via the postMessage API on request. The script may be safely included multiple times, with only the\n",
       "        * configuration of the first started script (e.g. viewer URL) applying.\n",
       "        *\n",
       "        */\n",
       "        (function() {\n",
       "            const TARGET_CLASS = \"simulation-viewer\";\n",
       "            const ACTIVE_CLASS = \"simulation-viewer-active\";\n",
       "            const VIEWER_URL = \"https://tidy3d.simulation.cloud/simulation-viewer\";\n",
       "\n",
       "            class SimulationViewerInjector {\n",
       "                constructor() {\n",
       "                    for (var node of document.getElementsByClassName(TARGET_CLASS)) {\n",
       "                        this.injectViewer(node);\n",
       "                    }\n",
       "\n",
       "                    // Monitor for newly added nodes to the DOM\n",
       "                    this.observer = new MutationObserver(this.onMutations.bind(this));\n",
       "                    this.observer.observe(document.body, {childList: true, subtree: true});\n",
       "                }\n",
       "\n",
       "                onMutations(mutations) {\n",
       "                    for (var mutation of mutations) {\n",
       "                        if (mutation.type === 'childList') {\n",
       "                            /**\n",
       "                            * Have found that adding the element does not reliably trigger the mutation observer.\n",
       "                            * It may be the case that setting content with innerHTML does not trigger.\n",
       "                            *\n",
       "                            * It seems to be sufficient to re-scan the document for un-activated viewers\n",
       "                            * whenever an event occurs, as Jupyter triggers multiple events on cell evaluation.\n",
       "                            */\n",
       "                            var viewers = document.getElementsByClassName(TARGET_CLASS);\n",
       "                            for (var node of viewers) {\n",
       "                                this.injectViewer(node);\n",
       "                            }\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "\n",
       "                injectViewer(node) {\n",
       "                    // (re-)check that this is a valid simulation container and has not already been injected\n",
       "                    if (node.classList.contains(TARGET_CLASS) && !node.classList.contains(ACTIVE_CLASS)) {\n",
       "                        // Mark node as injected, to prevent re-runs\n",
       "                        node.classList.add(ACTIVE_CLASS);\n",
       "\n",
       "                        var uuid;\n",
       "                        if (window.crypto && window.crypto.randomUUID) {\n",
       "                            uuid = window.crypto.randomUUID();\n",
       "                        } else {\n",
       "                            uuid = \"\" + Math.random();\n",
       "                        }\n",
       "\n",
       "                        var frame = document.createElement(\"iframe\");\n",
       "                        frame.width = node.dataset.width || 800;\n",
       "                        frame.height = node.dataset.height || 800;\n",
       "                        frame.style.cssText = `width:${frame.width}px;height:${frame.height}px;max-width:none;border:0;display:block`\n",
       "                        frame.src = VIEWER_URL + \"?uuid=\" + uuid;\n",
       "\n",
       "                        var postMessageToViewer;\n",
       "                        postMessageToViewer = event => {\n",
       "                            if(event.data.type === 'viewer' && event.data.uuid===uuid){\n",
       "                                frame.contentWindow.postMessage({ type: 'jupyter', uuid, value: node.dataset.simulation, fileType: 'hdf5'}, '*');\n",
       "\n",
       "                                // Run once only\n",
       "                                window.removeEventListener('message', postMessageToViewer);\n",
       "                            }\n",
       "                        };\n",
       "                        window.addEventListener(\n",
       "                            'message',\n",
       "                            postMessageToViewer,\n",
       "                            false\n",
       "                        );\n",
       "\n",
       "                        node.appendChild(frame);\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            if (!window.simulationViewerInjector) {\n",
       "                window.simulationViewerInjector = new SimulationViewerInjector();\n",
       "            }\n",
       "        })();\n",
       "    \n",
       "    </script>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# inspect transverse grid\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "sim_thz.plot(z=1, ax=ax)\n",
    "\n",
    "# 3D plot of the simulation structure\n",
    "sim_thz.plot_3d()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1966ca2a-1f76-48f9-b20f-23a7553d3218",
   "metadata": {},
   "source": [
    "## 2D Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ca6999c-990e-415f-8f52-fec7d5b927ce",
   "metadata": {},
   "source": [
    "To obtain all the key transmission line parameters, such as attenuation $\\alpha$, characteristic impedance $Z_0$, and effective index $n_{\\text{eff}}$, we perform a 2D `ModeSolver` calculation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "34f7794e-3fab-473f-9213-782ac42b6789",
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert wave port to mode solver\n",
    "mode_solver_thz = WP1.to_mode_solver(sim_thz, freqs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca2348d0-7b8d-4080-860f-dcff97e9464f",
   "metadata": {},
   "source": [
    "We execute the mode solver study below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e84ee11e-a7fd-43da-9329-6829e463aa10",
   "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: #7fbfbf; text-decoration-color: #7fbfbf\">15:41:11 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'mode solver for terahertz mode'</span> with resource_id     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'mo-11a589e2-144d-40bc-b495-cc768e069709'</span> and task_type            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'MODE_SOLVER'</span>.                                                     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:41:11 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'mode solver for terahertz mode'\u001b[0m with resource_id     \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'mo-11a589e2-144d-40bc-b495-cc768e069709'\u001b[0m and task_type            \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'MODE_SOLVER'\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\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">40bc-b495-cc768e069709'</span></a>.                                           \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=187800;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=422648;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=187800;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=874459;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[32mmo\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=187800;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[32m-11a589e2-144d-\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=187800;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[32m40bc-b495-cc768e069709'\u001b[0m\u001b]8;;\u001b\\.                                           \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\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=997617;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1a90838cc98b4ce78c49632eba94a0c9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "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\">15:41:16 -03 </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.011</span>. Minimum cost depends on task     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <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;36m15:41:16 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.011\u001b[0m. Minimum cost depends on task     \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \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\">15:41:18 -03 </span>status = queued                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:41:18 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                    \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\">             </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or              \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the web UI.      \n",
       "\u001b[2;36m             \u001b[0mTerminating the Python script will not stop the job running on the \n",
       "\u001b[2;36m             \u001b[0mcloud.                                                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f9b5fc13dbef4044ae618dacb83b8dd0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "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\">15:41:23 -03 </span>starting up solver                                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:41:23 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \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\">15:41:24 -03 </span>running solver                                                     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:41:24 -03\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \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\">15:41:52 -03 </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:41:52 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \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\">             </span>View simulation result at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">40bc-b495-cc768e069709'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                           \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=739232;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=454487;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=739232;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=375298;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[4;34mmo\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=739232;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[4;34m-11a589e2-144d-\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=739232;https://tidy3d.simulation.cloud/workbench?taskId=mo-11a589e2-144d-40bc-b495-cc768e069709\u001b\\\u001b[4;34m40bc-b495-cc768e069709'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                           \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "33b4f9ce778443e4a1ac5c9778e819d4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "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\">15:42:01 -03 </span>loading simulation from simulation_data.hdf5                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:42:01 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mode_data_thz = td.web.run(mode_solver_thz, task_name=\"mode solver for terahertz mode\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3210d5ff-9e20-468e-be39-eccd0083db41",
   "metadata": {},
   "source": [
    "A great advantage of this transmission line structure is that it provides the same mode shape over the entire frequency range from 250 GHz up to 5 THz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9ec97501",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1100x1100 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(5, 1, figsize=(11, 11), tight_layout=True)\n",
    "frequencies_to_plot = [250e9, 500e9, 1e12, 3e12, 5e12]\n",
    "for k, axis in enumerate(ax):\n",
    "    mode_solver_thz.plot_field(\n",
    "        field_name=\"Ex\", val=\"real\", mode_index=0, f=frequencies_to_plot[k], ax=axis\n",
    "    )\n",
    "    axis.set_title(f\"Re(Ex) at {frequencies_to_plot[k] / 1e12} THz\")\n",
    "    axis.set_ylim(-6, 1)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0aef672f",
   "metadata": {},
   "source": [
    "Next, we plot the effective index for the first mode and compare it to the refractive index of bulk lithium niobate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d142f7be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "neff_mode = mode_data_thz.modes_info[\"n eff\"].squeeze()\n",
    "ax.plot(freqs * 1e-12, neff_mode[:, 0], label=\"transmission line mode\")\n",
    "\n",
    "# get the complex permittivity from the fitted model\n",
    "eps_complex = LN_e_THz.eps_model(freqs)\n",
    "\n",
    "# convert to refractive index (n + ik)\n",
    "n_complex = np.sqrt(eps_complex)\n",
    "\n",
    "# extract only the real part\n",
    "n_real = np.real(n_complex)\n",
    "\n",
    "ax.plot(freqs * 1e-12, n_real, label=\"bulk lithium niobate\")\n",
    "plt.legend()\n",
    "plt.ylim(0, 6)\n",
    "plt.ylabel(\"Refractive index\")\n",
    "plt.xlabel(\"Frequency (THz)\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f0c1382-9489-49e0-b6bf-50871cdee8d9",
   "metadata": {},
   "source": [
    "The mode solver solution data includes $n_{\\text{eff}}$ and attenuation $\\alpha$ in dB/cm. From this, we can also derive the real part of the propagation constant, $\\beta$, as well as the complex propagation constant $\\gamma$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b700acdf-1d07-48c2-a4d0-a3a59fae0785",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "neff_mode = mode_data_thz.modes_info[\"n eff\"].squeeze()\n",
    "alphadB_mode = mode_data_thz.modes_info[\"loss (dB/cm)\"].squeeze()\n",
    "# calculate beta, alpha (in 1/um), and gamma\n",
    "beta_mode = 2 * np.pi * freqs * neff_mode[:, 0] / td.C_0\n",
    "alpha_mode = alphadB_mode / 8.686 / 1e4\n",
    "gamma_mode = alpha_mode + 1j * beta_mode"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ce91cf5-9be1-416a-bdd9-d13b4dc779b8",
   "metadata": {},
   "source": [
    "We obtain $Z_0$ by calling the `compute_impedance()` method in the [`ImpedanceCalculator`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.microwave.ImpedanceCalculator.html) class, making use of the previously defined current and voltage integrals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "56e80ec1-be6d-4365-8272-69bdf8fb47e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "Z0_mode = (\n",
    "    mw.ImpedanceCalculator(\n",
    "        voltage_integral=voltage_integral, current_integral=current_integral\n",
    "    )\n",
    "    .compute_impedance(mode_data_thz)\n",
    "    .isel(mode_index=0)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b85cbd24",
   "metadata": {},
   "source": [
    "We can show that the simulation results give similar values to an analytical model from \n",
    "[Garg, Ramesh, and Inder J. Bahl. Microstrip lines and slotlines. Artech House, 2024](https://us.artechhouse.com/Microstrip-Lines-and-Slotlines-Fourth-Edition-P2417.aspx).\n",
    "\n",
    "\\begin{equation}\n",
    "Z_{TL}=\\frac{120 \\pi}{ \\sqrt{\\varepsilon_{eff}}} \\frac{k}{k'}\n",
    "\n",
    "\\end{equation}\n",
    "\n",
    "where \n",
    "$k' = \\sqrt{\\,1 - k^2\\,} $ and the parameter $k$ is determined by the dimensions of the transmission line: $k =\\frac{w_g}{w_{TL}+2\\cdot w_g} $"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "af91c158",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = w_g * 1e-6\n",
    "w = w_TL * 1e-6\n",
    "k = s / (s + 2 * w)\n",
    "k_prime = np.sqrt(1 - k**2)\n",
    "\n",
    "K_ratio = np.pi / np.log(2 * (1 + np.sqrt(k_prime)) / (1 - np.sqrt(k_prime)))\n",
    "Z_0_analytical = 120 * np.pi / neff_mode[:, 0] * K_ratio\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5, 4), tight_layout=True)\n",
    "\n",
    "Z_simulation = Z0_mode.real\n",
    "plt.plot(freqs * 1e-12, Z_0_analytical, label=\"analytical\")\n",
    "plt.plot(freqs * 1e-12, Z_simulation, label=\"Tidy3D simulation\")\n",
    "\n",
    "plt.ylim(0, 200)\n",
    "plt.xlabel(\"frequency [THz]\")\n",
    "plt.ylabel(r\"$\\mathrm{Z_{TL}}$ [Ω]\")\n",
    "plt.legend()\n",
    "\n",
    "plt.savefig(\"Z_TL.pdf\", format=\"pdf\", transparent=True)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f319cf2",
   "metadata": {},
   "source": [
    "## Optical Simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9244e3f",
   "metadata": {},
   "source": [
    "To determine phase matching between optical and terahertz modes, we run an optical simulation to determine the group index at telecom frequencies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "07d4367a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# silicon dioxide below thin-film lithium niobate layer\n",
    "oxide_box = oxide_box.updated_copy(medium=sio2_opt)\n",
    "\n",
    "# thin-film lithium niobate layer\n",
    "TFLN = TFLN.updated_copy(medium=LN_e_opt)\n",
    "\n",
    "# waveguide\n",
    "wg = wg.updated_copy(medium=LN_e_opt)\n",
    "\n",
    "# substrate\n",
    "str_sub = str_sub.updated_copy(medium=si_opt)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85cac836",
   "metadata": {},
   "source": [
    "We will consider the gold stripline to be a perfect electrical conductor for the optical frequencies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "39ef22cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# left transmission line strip\n",
    "str_strip_left = str_strip_left.updated_copy(medium=td.PEC)\n",
    "\n",
    "# right transmission line strip\n",
    "str_strip_right = str_strip_right.updated_copy(medium=td.PEC)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "974b0953",
   "metadata": {},
   "source": [
    "The grid specification for the optical simulation is automatic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4a91efae",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define overall grid specification\n",
    "grid_spec = td.GridSpec.auto(wavelength=td.C_0 / nu_max, min_steps_per_wvl=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65ee5836",
   "metadata": {},
   "source": [
    "Since we know that the optical mode will be confined inside the waveguide, we define the simulation domain to be around the lithium niobate waveguide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "c855dcf2",
   "metadata": {},
   "outputs": [],
   "source": [
    "sim_opt = td.Simulation(\n",
    "    size=(3 * wg_w, h_wg * 5, 1.01 * L),\n",
    "    center=(0, 0, 0),\n",
    "    grid_spec=grid_spec,\n",
    "    boundary_spec=boundary_spec,\n",
    "    structures=[\n",
    "        str_sub,\n",
    "        str_strip_left,\n",
    "        str_strip_right,\n",
    "        wg,\n",
    "        TFLN,\n",
    "        oxide_box,\n",
    "        left_opening,\n",
    "        right_opening,\n",
    "    ],\n",
    "    monitors=[],\n",
    "    run_time=5e-12,  # simulation run time in seconds\n",
    "    shutoff=1e-7,  # lower shutoff threshold for more accuracy at low frequency\n",
    "    plot_length_units=\"um\",\n",
    "    medium=sio2_opt,  # background_medium is silicon dioxide\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "edf4ec0f",
   "metadata": {},
   "source": [
    "The goal of such structures is to exploit the nonlinear $d_{333}$ coefficient of lithium niobate. This tensor coefficient is along the z-axis of the crystal (x-axis in the simulation). Therefore, we are only interested in the TE polarization of the optical mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "0ddf1286",
   "metadata": {},
   "outputs": [],
   "source": [
    "mode_spec = td.ModeSpec(\n",
    "    filter_pol=\"te\",\n",
    "    precision=\"double\",\n",
    "    num_pml=(5, 5),\n",
    "    group_index_step=True,\n",
    "    num_modes=2,\n",
    ")\n",
    "\n",
    "plane = td.Box(\n",
    "    center=(0, 0, -L / 2), size=(1.8 * wg_w, h_wg * 4, 0)\n",
    ")  # create simulation plane\n",
    "\n",
    "mode_solver_opt = ModeSolver(\n",
    "    simulation=sim_opt,\n",
    "    plane=plane,\n",
    "    mode_spec=mode_spec,\n",
    "    freqs=opt_freqs,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "96ff3448",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"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\" ></div>\n",
       "    <script>\n",
       "        \n",
       "        /**\n",
       "        * Simulation Viewer Injector\n",
       "        *\n",
       "        * Monitors the document for elements being added in the form:\n",
       "        *\n",
       "        *    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"{...}\" />\n",
       "        *\n",
       "        * This script will then inject an iframe to the viewer application, and pass it the simulation data\n",
       "        * via the postMessage API on request. The script may be safely included multiple times, with only the\n",
       "        * configuration of the first started script (e.g. viewer URL) applying.\n",
       "        *\n",
       "        */\n",
       "        (function() {\n",
       "            const TARGET_CLASS = \"simulation-viewer\";\n",
       "            const ACTIVE_CLASS = \"simulation-viewer-active\";\n",
       "            const VIEWER_URL = \"https://tidy3d.simulation.cloud/simulation-viewer\";\n",
       "\n",
       "            class SimulationViewerInjector {\n",
       "                constructor() {\n",
       "                    for (var node of document.getElementsByClassName(TARGET_CLASS)) {\n",
       "                        this.injectViewer(node);\n",
       "                    }\n",
       "\n",
       "                    // Monitor for newly added nodes to the DOM\n",
       "                    this.observer = new MutationObserver(this.onMutations.bind(this));\n",
       "                    this.observer.observe(document.body, {childList: true, subtree: true});\n",
       "                }\n",
       "\n",
       "                onMutations(mutations) {\n",
       "                    for (var mutation of mutations) {\n",
       "                        if (mutation.type === 'childList') {\n",
       "                            /**\n",
       "                            * Have found that adding the element does not reliably trigger the mutation observer.\n",
       "                            * It may be the case that setting content with innerHTML does not trigger.\n",
       "                            *\n",
       "                            * It seems to be sufficient to re-scan the document for un-activated viewers\n",
       "                            * whenever an event occurs, as Jupyter triggers multiple events on cell evaluation.\n",
       "                            */\n",
       "                            var viewers = document.getElementsByClassName(TARGET_CLASS);\n",
       "                            for (var node of viewers) {\n",
       "                                this.injectViewer(node);\n",
       "                            }\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "\n",
       "                injectViewer(node) {\n",
       "                    // (re-)check that this is a valid simulation container and has not already been injected\n",
       "                    if (node.classList.contains(TARGET_CLASS) && !node.classList.contains(ACTIVE_CLASS)) {\n",
       "                        // Mark node as injected, to prevent re-runs\n",
       "                        node.classList.add(ACTIVE_CLASS);\n",
       "\n",
       "                        var uuid;\n",
       "                        if (window.crypto && window.crypto.randomUUID) {\n",
       "                            uuid = window.crypto.randomUUID();\n",
       "                        } else {\n",
       "                            uuid = \"\" + Math.random();\n",
       "                        }\n",
       "\n",
       "                        var frame = document.createElement(\"iframe\");\n",
       "                        frame.width = node.dataset.width || 800;\n",
       "                        frame.height = node.dataset.height || 800;\n",
       "                        frame.style.cssText = `width:${frame.width}px;height:${frame.height}px;max-width:none;border:0;display:block`\n",
       "                        frame.src = VIEWER_URL + \"?uuid=\" + uuid;\n",
       "\n",
       "                        var postMessageToViewer;\n",
       "                        postMessageToViewer = event => {\n",
       "                            if(event.data.type === 'viewer' && event.data.uuid===uuid){\n",
       "                                frame.contentWindow.postMessage({ type: 'jupyter', uuid, value: node.dataset.simulation, fileType: 'hdf5'}, '*');\n",
       "\n",
       "                                // Run once only\n",
       "                                window.removeEventListener('message', postMessageToViewer);\n",
       "                            }\n",
       "                        };\n",
       "                        window.addEventListener(\n",
       "                            'message',\n",
       "                            postMessageToViewer,\n",
       "                            false\n",
       "                        );\n",
       "\n",
       "                        node.appendChild(frame);\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            if (!window.simulationViewerInjector) {\n",
       "                window.simulationViewerInjector = new SimulationViewerInjector();\n",
       "            }\n",
       "        })();\n",
       "    \n",
       "    </script>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "sim_opt.plot(z=1, ax=ax)\n",
    "plt.show()\n",
    "# 3D plot of the simulation structure\n",
    "sim_opt.plot_3d()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "783a88e7",
   "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: #7fbfbf; text-decoration-color: #7fbfbf\">15:42:04 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'mode solver for optical mode'</span> with resource_id       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'mo-88baaa1b-f70c-4f29-84c1-1d51d076884a'</span> and task_type            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'MODE_SOLVER'</span>.                                                     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:42:04 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'mode solver for optical mode'\u001b[0m with resource_id       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'mo-88baaa1b-f70c-4f29-84c1-1d51d076884a'\u001b[0m and task_type            \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'MODE_SOLVER'\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\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">4f29-84c1-1d51d076884a'</span></a>.                                           \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=340241;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=107862;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=340241;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=74745;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[32mmo\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=340241;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[32m-88baaa1b-f70c-\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=340241;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[32m4f29-84c1-1d51d076884a'\u001b[0m\u001b]8;;\u001b\\.                                           \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\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=945791;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a0fb5018d7824623a133badc797a3ee6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "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\">15:42:07 -03 </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.014</span>. Minimum cost depends on task     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <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;36m15:42:07 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.014\u001b[0m. Minimum cost depends on task     \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \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\">15:42:09 -03 </span>status = queued                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:42:09 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                    \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\">             </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or              \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the web UI.      \n",
       "\u001b[2;36m             \u001b[0mTerminating the Python script will not stop the job running on the \n",
       "\u001b[2;36m             \u001b[0mcloud.                                                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "316e01ac6ad74a1caa7c103d6735aa1e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "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\">15:42:14 -03 </span>starting up solver                                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:42:14 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \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\">             </span>running solver                                                     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \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\">15:43:11 -03 </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:43:11 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \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\">             </span>View simulation result at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">4f29-84c1-1d51d076884a'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                           \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=459080;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=27497;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=459080;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=936121;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[4;34mmo\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=459080;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[4;34m-88baaa1b-f70c-\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=459080;https://tidy3d.simulation.cloud/workbench?taskId=mo-88baaa1b-f70c-4f29-84c1-1d51d076884a\u001b\\\u001b[4;34m4f29-84c1-1d51d076884a'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                           \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f6ec103ff6704f93a6eb62c923dec704",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "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\">15:43:23 -03 </span>loading simulation from simulation_data.hdf5                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:43:23 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mode_data_opt = td.web.run(mode_solver_opt, task_name=\"mode solver for optical mode\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e9856ea",
   "metadata": {},
   "source": [
    "## Final Results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc8d0d70",
   "metadata": {},
   "source": [
    "We can plot both the optical and terahertz mode to show how they overlap mainly inside the gap of transmission line."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a0e3873f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1100x1100 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 1, figsize=(11, 11), sharex=True, tight_layout=True)\n",
    "\n",
    "mode_solver_opt.plot_field(\n",
    "    field_name=\"Ex\", val=\"real\", mode_index=0, f=193e12, ax=ax[0]\n",
    ")\n",
    "ax[0].set_title(\"Re(Ex) at 193 THz\")\n",
    "mode_solver_thz.plot_field(field_name=\"Ex\", val=\"real\", mode_index=0, f=1e12, ax=ax[1])\n",
    "ax[1].set_title(\"Re(Ex) at 1 THz\")\n",
    "ax[0].set_xlim(-6, 6)\n",
    "ax[1].set_ylim(-0.5, 0.5)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac72673b",
   "metadata": {},
   "source": [
    "Now, we can extract all refractive indices. We already plotted the terahertz refractive index. Let us extract the optical group index. By doing so, we can reproduce Fig. 1 c in the main article."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "b1f3eefd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "group_index = mode_data_opt.n_group[:, 0]\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(5, 3))\n",
    "ax1 = fig.add_subplot(111, label=\"1\")\n",
    "ax2 = fig.add_subplot(111, label=\"2\", frame_on=False)\n",
    "\n",
    "color = \"tab:blue\"\n",
    "ax1.set_xlabel(\"$f_{THz}$ [THz]\", color=color)\n",
    "ax1.set_ylabel(\"n($f_{THz}$)\", color=color)  # we already handled the x-label with ax1\n",
    "ax1.plot(freqs * 1e-12, n_real, \"--\", color=color, label=\"bulk lithium niobate\")\n",
    "ax1.plot(freqs * 1e-12, neff_mode[:, 0], \"-\", color=color, label=\"transmission line\")\n",
    "\n",
    "\n",
    "ax1.tick_params(axis=\"y\", labelcolor=color)\n",
    "ax1.tick_params(axis=\"x\", colors=color)\n",
    "ax1.tick_params(axis=\"y\", colors=color)\n",
    "ax1.set_ylim(0, 6)\n",
    "ax1.set_xlim(0, 5)\n",
    "ax1.legend(loc=(1.2, 0.1))\n",
    "\n",
    "color = \"tab:red\"\n",
    "ax2.set_xlabel(\" ν  [THz]\", color=color)\n",
    "ax2.yaxis.tick_right()\n",
    "ax2.set_ylabel(\"$n_g(ν)$\", color=color)\n",
    "ax2.xaxis.tick_top()\n",
    "ax2.xaxis.set_label_position(\"top\")\n",
    "ax2.yaxis.set_label_position(\"right\")\n",
    "ax2.plot(\n",
    "    opt_freqs * 1e-12,\n",
    "    group_index,\n",
    "    \"-\",\n",
    "    color=color,\n",
    "    label=\"group index of optical mode\",\n",
    ")\n",
    "ax2.tick_params(axis=\"y\", labelcolor=color)\n",
    "ax2.tick_params(axis=\"x\", colors=color)\n",
    "ax2.tick_params(axis=\"y\", colors=color)\n",
    "ax2.set_ylim(0, 6)\n",
    "\n",
    "\n",
    "ax2.legend(loc=(1.2, 0))\n",
    "plt.grid(False)\n",
    "plt.savefig(\"ref_index.pdf\", format=\"pdf\", transparent=True)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbfc783c",
   "metadata": {},
   "source": [
    "Finally, we determine the coherence length which is given by the formula\n",
    "$l_c=\\frac{c_0}{2 f |n_g - n_{TL}|}$.\n",
    "This parameter determines the length at which the phase mismatch reaches 180° between the terahertz and optical waves.\n",
    "For the optical mode, we will choose the group index at 193 THz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9faf7418",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "c_0 = 299792458\n",
    "n_g = group_index[25].item()\n",
    "l_c = c_0 / (2 * freqs * np.abs(neff_mode[:, 0] - n_g))  # in m\n",
    "plt.plot(freqs * 1e-12, l_c * 1e3)\n",
    "plt.ylim(0, 10)\n",
    "plt.xlim(0, 5)\n",
    "plt.xlabel(\"$f_{THz}$ [THz]\")\n",
    "plt.ylabel(\"Coherence length $l_c$ [mm]\")\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Microwave and RF devices"
  ],
  "description": "This notebook demonstrates how to simulate photonics-integrated terahertz transmission lines using Tidy3D.",
  "feature_image": "./img/THzTransmissionLine.png",
  "features": [
   "Wave port"
  ],
  "kernelspec": {
   "display_name": "td2100rc2",
   "language": "python",
   "name": "python3"
  },
  "keywords": "terahertz transmission lines, phase matching, optical–microwave interaction, Tidy3D, FDTD",
  "language_info": {
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  "title": "How to model thz transmission lines using Tidy3D | Flexcompute"
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