{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Second harmonic generation\n",
    "\n",
    "<b>Author: Daniil Lukin, [Brightlight Photonics](https://www.brightlightphotonics.com/)</b>\n",
    "\n",
    "This notebook demonstrates how to use linear fields to calculate the nonlinear polarization and apply it as a source to investigate Second Harmonic Generation (SHG) in a 2D photonic crystal cavity reported in the work of `Heungjoon Kim, Bong-Shik Song, Takashi Asano and Susumu Noda, entitled \"Enhanced second-harmonic generation in a photonic crystal waveguide-coupled nanocavity using a wavelength-selective reflector\", APL Photonics, 2023.` [DOI: https://doi.org/10.1063/5.0173196](https://doi.org/10.1063/5.0173196)\n",
    "\n",
    "\n",
    "We will achieve this in two steps:\n",
    "\n",
    "1. Run a linear simulation with a [`GaussianPulse`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.GaussianPulse.html) source to determine the resonant frequency and resonant fields.\n",
    "2. Run a CW simulation exciting the resonance frequency until reach the steady state.\n",
    "3. Use the linear field information to create the nonlinear polarization,\n",
    "\n",
    "$$P^{(2)}_{i,j,k} = \\epsilon_0 d_{i,j,k} E_j E_k$$\n",
    "\n",
    "transform to current with the relation,\n",
    "\n",
    "$$P^{(2)}(\\vec{r},t) = \\frac{\\partial J^{(2)}}{\\partial t} == -i \\omega_{sh} P^{(2)}(\\vec{r})$$\n",
    "\n",
    "and apply it as [`CustomCurrentSource`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.CustomCurrentSource.html).\n",
    "\n",
    "\n",
    "In this notebook, we will explore various features of Tidy3D, such as:\n",
    "\n",
    "- Anisotropic media.\n",
    "- Using [`ResonanceFinder`](https://www.flexcompute.com/tidy3d/examples/notebooks/ResonanceFinder/) to extract resonance information from time-domain field monitors efficiently.\n",
    "- Using a [`CustomCurrentSource`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.CustomCurrentSource.html).\n",
    "\n",
    "This notebook example was kindly shared by the [Brightlight Photonics](https://www.brightlightphotonics.com/) team.\n",
    "\n",
    "<img src=\"img/SHG.png\" width=\"600\" alt=\"Schematic of the photonic crystal\">\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
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       "                    var msg = \"WARNING: it looks like you might have loaded \" +\n",
       "                        \"jupyter_black in a non-lab notebook with \" +\n",
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   "source": [
    "# Standard python imports\n",
    "import jupyter_black\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tidy3d as td\n",
    "from tidy3d import web\n",
    "from tidy3d.plugins.resonance import ResonanceFinder\n",
    "\n",
    "jupyter_black.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parameters Definition    \n",
    "\n",
    "Here, we define the global parameters for the simulation as well as the anisotropic medium.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Universal parameters\n",
    "\n",
    "ep_hole = 1  # Dielectric constant of the holes\n",
    "\n",
    "n_ordinary_1550nm = 2.564\n",
    "n_extraordinary_1550nm = 2.608\n",
    "\n",
    "n_ordinary_775nm = 2.607\n",
    "n_extraordinary_775nm = 2.65\n",
    "\n",
    "# Defining anisotropic materials\n",
    "medium_xx_1550 = td.Medium(permittivity=n_ordinary_1550nm**2)\n",
    "medium_yy_1550 = td.Medium(permittivity=n_ordinary_1550nm**2)\n",
    "medium_zz_1550 = td.Medium(permittivity=n_extraordinary_1550nm**2)\n",
    "\n",
    "mat_slab_1550 = td.AnisotropicMedium(\n",
    "    xx=medium_xx_1550, yy=medium_yy_1550, zz=medium_zz_1550, name=\"mat_slab\"\n",
    ")\n",
    "mat_hole_1550 = td.Medium(permittivity=ep_hole, name=\"mat_hole\")\n",
    "\n",
    "medium_xx_775 = td.Medium(permittivity=n_ordinary_775nm**2)\n",
    "medium_yy_775 = td.Medium(permittivity=n_ordinary_775nm**2)\n",
    "medium_zz_775 = td.Medium(permittivity=n_extraordinary_775nm**2)\n",
    "\n",
    "mat_slab_775 = td.AnisotropicMedium(\n",
    "    xx=medium_xx_775, yy=medium_yy_775, zz=medium_zz_775, name=\"mat_slab\"\n",
    ")\n",
    "mat_hole_775 = td.Medium(permittivity=ep_hole, name=\"mat_hole\")\n",
    "\n",
    "a_lattice = 0.530\n",
    "r_hole = 0.26\n",
    "t_slab = 0.57\n",
    "sidewall_angle = 0\n",
    "sim_size = Lx, Ly, Lz = (a_lattice * 40, a_lattice * np.sqrt(3) / 2 * 12, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we define the photonic crystal cavity geometry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# potential well on half-integer grid\n",
    "def sqrt_potential(depth, width, n_max=100, plot=False):\n",
    "    x_points = np.arange(0, n_max, 0.5)\n",
    "    potential = np.sqrt(np.interp(x_points, [0, width, n_max], [depth, 0, 0]))\n",
    "    if plot:\n",
    "        plt.scatter(x_points, potential)\n",
    "\n",
    "    return x_points, potential\n",
    "\n",
    "\n",
    "# potential well on half-integer grid\n",
    "def linear_potential(depth, width, n_max=100, plot=False):\n",
    "    x_points = np.arange(0, n_max, 0.5)\n",
    "    potential = np.interp(x_points, [0, width, n_max], [depth, 0, 0])\n",
    "    if plot:\n",
    "        plt.scatter(x_points, potential)\n",
    "\n",
    "    return x_points, potential\n",
    "\n",
    "\n",
    "def noda_potential(n_max=100):\n",
    "    x_points = np.arange(0, n_max, 0.5)\n",
    "    potential = np.interp(\n",
    "        x_points,\n",
    "        [0, 0.5, 1.5, 2, 2.5, 3, 3.5, n_max],\n",
    "        [0.0094, 0.0094, 0.0047, 0.0047, 0.0047, 0, 0, 0],\n",
    "    )\n",
    "    return x_points, potential\n",
    "\n",
    "\n",
    "def normed_x_hole_position_from_potential(x, y):\n",
    "    cumsum = np.cumsum(y + 1) * 0.5\n",
    "    return x, cumsum - cumsum[0]\n",
    "\n",
    "\n",
    "def define_geometry(mat_slab, mat_hole):\n",
    "    vector_1_normed = np.array([1 / 2, np.sqrt(3) / 2])\n",
    "    vector_2_normed = np.array([-1 / 2, np.sqrt(3) / 2])\n",
    "\n",
    "    period_indices, x_position_normed = normed_x_hole_position_from_potential(\n",
    "        *noda_potential()\n",
    "    )\n",
    "\n",
    "    num_periods = 80\n",
    "    sim_lim_x = Lx / 2 - a_lattice / 2\n",
    "    sim_lim_y = Ly / 2 - a_lattice / 2\n",
    "\n",
    "    hole_positions = []\n",
    "    for a1 in np.arange(-num_periods, num_periods):\n",
    "        for a2 in np.arange(-num_periods, num_periods):\n",
    "            normed_lattice_coord = a1 * vector_1_normed + a2 * vector_2_normed\n",
    "\n",
    "            x_lattice_index = normed_lattice_coord[0]\n",
    "\n",
    "            if x_lattice_index < 0:\n",
    "                continue\n",
    "\n",
    "            matches = np.where(period_indices == x_lattice_index)[0]\n",
    "            if len(matches) != 1:\n",
    "                print(x_lattice_index)\n",
    "                continue\n",
    "\n",
    "            final_hole_coord = a_lattice * np.array(\n",
    "                [x_position_normed[matches[0]], normed_lattice_coord[1]]\n",
    "            )\n",
    "\n",
    "            if (\n",
    "                sim_lim_y >= final_hole_coord[1] > 0\n",
    "                and 0 <= final_hole_coord[0] < sim_lim_x\n",
    "            ):\n",
    "                hole_positions.append(final_hole_coord)\n",
    "\n",
    "    # reflect along y:\n",
    "    hole_positions_reflected_x = []\n",
    "\n",
    "    for pos in hole_positions:\n",
    "        if pos[0] > a_lattice / 10:\n",
    "            hole_positions_reflected_x.append([-pos[0], pos[1]])\n",
    "\n",
    "    hole_positions.extend(hole_positions_reflected_x)\n",
    "\n",
    "    hole_positions.extend([[pos[0], -pos[1]] for pos in hole_positions])\n",
    "\n",
    "    hole_positions = np.array(hole_positions)\n",
    "\n",
    "    plot = False\n",
    "    if plot:\n",
    "        plt.scatter(hole_positions[:, 0], hole_positions[:, 1])\n",
    "        plt.axis(\"equal\")\n",
    "        # plt.xlim(0, 1)\n",
    "        plt.show()\n",
    "\n",
    "    slab = td.Structure(\n",
    "        geometry=td.Box(\n",
    "            center=(0, 0, 0),\n",
    "            size=(td.inf, td.inf, t_slab * a_lattice),\n",
    "        ),\n",
    "        medium=mat_slab,\n",
    "        name=\"slab\",\n",
    "    )\n",
    "\n",
    "    holes = []\n",
    "    for hole_pos in hole_positions:\n",
    "        holes.append(\n",
    "            td.Structure(\n",
    "                geometry=td.Cylinder(\n",
    "                    center=(hole_pos[0], hole_pos[1], 0),\n",
    "                    axis=2,\n",
    "                    radius=r_hole * a_lattice,\n",
    "                    length=t_slab * a_lattice,\n",
    "                    sidewall_angle=-sidewall_angle * np.pi / 180,\n",
    "                ),\n",
    "                medium=mat_hole,\n",
    "                name=\"hole_\" + str(len(holes)),\n",
    "            )\n",
    "        )\n",
    "\n",
    "    structures = [slab] + holes\n",
    "    return structures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "structures_list = define_geometry(mat_slab_1550, mat_hole_1550)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gaussian Pulse Simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we define a [`PointDipole`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PointDipole.html) source with Gaussian time dependency."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Central frequency around which we'll look for the cavity mode (Hz)\n",
    "freq0 = 1.908e14\n",
    "\n",
    "# Source bandwidth (Hz)\n",
    "fwidth = 4e13\n",
    "\n",
    "# Simulation run time (s)\n",
    "run_time = 20e-12\n",
    "\n",
    "# Plot time dependence to verify when the source pulse decayed\n",
    "source = td.PointDipole(\n",
    "    center=(0, 0, 0),\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "    polarization=\"Ey\",\n",
    ")\n",
    "\n",
    "# Source pulse is much shorter than the simulation run_time defined above,\n",
    "# so we only examine the signal up to a shorter time = 10e-13fs\n",
    "fig, ax = plt.subplots(1, 2, figsize=(10, 4))\n",
    "source.source_time.plot(np.linspace(0, 1e-13, 2000), ax=ax[0])\n",
    "source.source_time.plot_spectrum(times=np.linspace(0, 5e-13, 2000), ax=ax[1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Suppress warnings for some of the holes being too close to the PML\n",
    "td.config.logging_level = \"ERROR\"\n",
    "\n",
    "refine_box = td.MeshOverrideStructure(\n",
    "    geometry=td.Box(center=(0, 0, 0), size=(td.inf, td.inf, t_slab * a_lattice)),\n",
    "    dl=[None, None, t_slab * a_lattice / 12],\n",
    ")\n",
    "\n",
    "# Mesh step in x, y, z, in microns\n",
    "steps_per_unit_length_xy = 15\n",
    "steps_per_unit_length_z = 15\n",
    "grid_spec = td.GridSpec(\n",
    "    grid_x=td.AutoGrid(min_steps_per_wvl=steps_per_unit_length_xy),\n",
    "    grid_y=td.AutoGrid(min_steps_per_wvl=steps_per_unit_length_xy),\n",
    "    grid_z=td.AutoGrid(min_steps_per_wvl=steps_per_unit_length_z),\n",
    "    override_structures=[refine_box],\n",
    ")\n",
    "\n",
    "# Starting time after the source has decayed\n",
    "t_start = 10e-13\n",
    "\n",
    "# Time series monitor for Q-factor computation\n",
    "time_series_mnt = td.FieldTimeMonitor(\n",
    "    center=[0, 0, 0], size=[0, 0, 0], start=t_start, name=\"time_series\"\n",
    ")\n",
    "\n",
    "# Flux time  monitor\n",
    "flux_time = td.FluxTimeMonitor(\n",
    "    center=(0, 0, 0), size=(0.8 * Lx, 0.8 * Ly, 0.8 * Lz), name=\"flux_time\"\n",
    ")\n",
    "\n",
    "eps_monitor = td.PermittivityMonitor(\n",
    "    center=(0, 0, 0), size=(Lx, Ly, Lz), freqs=[freq0], name=\"eps_monitor\"\n",
    ")\n",
    "\n",
    "apodization = td.ApodizationSpec(start=t_start, width=2e-13)\n",
    "field_mnt = td.FieldMonitor(\n",
    "    center=(0, 0, 0),\n",
    "    size=(Lx, Ly, Lz),\n",
    "    name=\"field_mnt\",\n",
    "    freqs=[freq0],\n",
    "    apodization=apodization,\n",
    ")\n",
    "\n",
    "\n",
    "sim = td.Simulation(\n",
    "    size=sim_size,\n",
    "    grid_spec=grid_spec,\n",
    "    structures=structures_list,\n",
    "    sources=[source],\n",
    "    monitors=[time_series_mnt, flux_time, field_mnt, eps_monitor],\n",
    "    run_time=run_time,\n",
    "    boundary_spec=td.BoundarySpec(\n",
    "        x=td.Boundary.pml(), y=td.Boundary.pml(), z=td.Boundary.pml()\n",
    "    ),\n",
    "    symmetry=(1, -1, 1),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of grid points (millions): 6.6\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot simulation and overlay grid in the xy planes\n",
    "def plot_sim_grid(sim):\n",
    "    fig, ax = plt.subplots(1, 1, figsize=(12, 6))\n",
    "    sim.plot(z=0, ax=ax, monitor_alpha=0)\n",
    "    sim.plot_grid(x=0, ax=ax, lw=0.4, colors=\"r\")\n",
    "    plt.ylim(-1, 0)\n",
    "    plt.xlim(0, 1)\n",
    "    print(f\"Total number of grid points (millions): {sim.num_cells / 1e6:1.2}\")\n",
    "\n",
    "    return ax\n",
    "\n",
    "\n",
    "plot_sim_grid(sim)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"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\" />\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.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": [
    "# Visualize simulation\n",
    "sim.plot_3d()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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\">20:59:33 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'1_fundamental_mode_spectrum'</span> with task_id            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:59:33 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'1_fundamental_mode_spectrum'\u001b[0m with task_id            \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7'\u001b[0m and task_type \u001b[32m'FDTD'\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=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">7-465f-8690-ce810e8c5bd7'</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=494482;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=374037;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=494482;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=139176;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=494482;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[32m-1ac35438-20c\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=494482;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[32m7-465f-8690-ce810e8c5bd7'\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-2d594d1c-257b-417d-92d0-e6dcb36d63f0\" 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=169505;https://tidy3d.simulation.cloud/folders/folder-2d594d1c-257b-417d-92d0-e6dcb36d63f0\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2ab6a28b0b70420d823df3fa51f2bb9a",
       "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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">20:59:36 -03 </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.194</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;36m20:59:36 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.194\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\">20:59:38 -03 </span>status = queued                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:59:38 -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": "7b36f2345b7a4a7286939b49a5db9b62",
       "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">20:59:43 -03 </span>status = preprocess                                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:59:43 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \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\">20:59:47 -03 </span>starting up solver                                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:59:47 -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\">20:59:48 -03 </span>running solver                                                     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:59:48 -03\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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       "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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">21:01:51 -03 </span>status = postprocess                                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:01:51 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b70cf1136965475fbfca4f9063cbab64",
       "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:01:55 -03 </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:01:55 -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\">21:01:57 -03 </span>View simulation result at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">7-465f-8690-ce810e8c5bd7'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:01:57 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=229783;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=100007;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=229783;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=522823;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=229783;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[4;34m-1ac35438-20c\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=229783;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1ac35438-20c7-465f-8690-ce810e8c5bd7\u001b\\\u001b[4;34m7-465f-8690-ce810e8c5bd7'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "model_id": "078afc9601084d9ab4280b3eca246fb5",
       "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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">21:02:10 -03 </span>loading simulation from simulation_data.hdf5                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:02:10 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Running the simulation\n",
    "sim_data = web.run(sim, task_name=\"1_fundamental_mode_spectrum\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "eps_non_colocated = abs(sim_data[\"eps_monitor\"].eps_yy).isel(f=0)\n",
    "\n",
    "eps = eps_non_colocated.interp(\n",
    "    x=sim_data[\"field_mnt\"].Ex.coords[\"x\"],\n",
    "    y=sim_data[\"field_mnt\"].Ex.coords[\"y\"],\n",
    "    z=sim_data[\"field_mnt\"].Ex.coords[\"z\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sim_data.plot_field(\n",
    "    \"field_mnt\",\n",
    "    \"Ey\",\n",
    "    \"real\",\n",
    "    z=0,\n",
    "    robust=False,\n",
    "    eps_alpha=0,\n",
    ")\n",
    "\n",
    "ax.pcolormesh(\n",
    "    eps.x, eps.y, eps.sel(z=0, method=\"nearest\").real.T, alpha=0.2, cmap=\"binary\"\n",
    ")\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we will analyze the field time series data. As we can see, the resonances exhibit exponential decay, and the cavity resonance is clearly visible in the Fourier transform.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get data from the TimeMonitor\n",
    "tdata = sim_data[\"time_series\"]\n",
    "\n",
    "time_series = tdata.Ey.squeeze()\n",
    "\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 3))\n",
    "\n",
    "# Plot time dependence\n",
    "time_series.plot(ax=ax1)\n",
    "\n",
    "# Make frequency mesh and plot spectrum\n",
    "dt = sim_data.simulation.dt\n",
    "\n",
    "fmesh = np.linspace(-1 / dt / 2, 1 / dt / 2, time_series.size)\n",
    "spectrum = np.fft.fftshift(np.fft.fft(time_series))\n",
    "\n",
    "ax2.plot(fmesh, np.abs(spectrum))\n",
    "ax2.set_xlim(freq0 - fwidth, freq0 + fwidth)\n",
    "ax2.set_xlabel(\"Frequency [Hz]\")\n",
    "ax2.set_ylabel(\"Electric field [a.u.]\")\n",
    "ax2.set_title(\"Spectrum\")\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can use [`ResonanceFinder`](https://www.flexcompute.com/tidy3d/examples/notebooks/ResonanceFinder/) to calculate the resonant frequency and Q-factor:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>decay</th>\n",
       "      <th>Q</th>\n",
       "      <th>amplitude</th>\n",
       "      <th>phase</th>\n",
       "      <th>error</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1.916514e+14</th>\n",
       "      <td>1.265659e+10</td>\n",
       "      <td>47571.325619</td>\n",
       "      <td>676.657889</td>\n",
       "      <td>0.715587</td>\n",
       "      <td>0.000618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.921427e+14</th>\n",
       "      <td>2.446458e+11</td>\n",
       "      <td>2467.380475</td>\n",
       "      <td>76.432467</td>\n",
       "      <td>-2.481902</td>\n",
       "      <td>0.000839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.926705e+14</th>\n",
       "      <td>7.228575e+11</td>\n",
       "      <td>837.360110</td>\n",
       "      <td>82.764169</td>\n",
       "      <td>0.594612</td>\n",
       "      <td>0.002911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.934497e+14</th>\n",
       "      <td>1.414883e+12</td>\n",
       "      <td>429.533819</td>\n",
       "      <td>46.411220</td>\n",
       "      <td>2.004166</td>\n",
       "      <td>0.021042</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     decay             Q   amplitude     phase     error\n",
       "freq                                                                    \n",
       "1.916514e+14  1.265659e+10  47571.325619  676.657889  0.715587  0.000618\n",
       "1.921427e+14  2.446458e+11   2467.380475   76.432467 -2.481902  0.000839\n",
       "1.926705e+14  7.228575e+11    837.360110   82.764169  0.594612  0.002911\n",
       "1.934497e+14  1.414883e+12    429.533819   46.411220  2.004166  0.021042"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resonance_finder = ResonanceFinder(\n",
    "    freq_window=(freq0 - fwidth / 2, freq0 + fwidth / 2), init_num_freqs=100\n",
    ")\n",
    "resonance_data = resonance_finder.run(sim_data[\"time_series\"])\n",
    "resonance_data.to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "cavity_resonance_freq = float(resonance_data.freq[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CW Run\n",
    "\n",
    "Now, we will run a CW simulation at the resonance frequency until the fields reach a steady state. Then, we will record the fields and use them in the calculation of the nonlinear polarization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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\">21:02:14 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'1_fundamental_mode_spectrumCW'</span> with task_id          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:02:14 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'1_fundamental_mode_spectrumCW'\u001b[0m with task_id          \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2'\u001b[0m and task_type \u001b[32m'FDTD'\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=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">6-4282-81e2-8f02a9c287c2'</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=668731;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=191109;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=668731;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=485118;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=668731;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[32m-8db353fb-06d\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=668731;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[32m6-4282-81e2-8f02a9c287c2'\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-2d594d1c-257b-417d-92d0-e6dcb36d63f0\" 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=541671;https://tidy3d.simulation.cloud/folders/folder-2d594d1c-257b-417d-92d0-e6dcb36d63f0\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8dfdb5e7e2a449098e3846566486fae9",
       "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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">21:02:17 -03 </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.995</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;36m21:02:17 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.995\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\">21:02:19 -03 </span>status = queued                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:02:19 -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": {
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       "model_id": "67d33d00bc264de89fd73f3f9663bb75",
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       "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:02:26 -03 </span>status = preprocess                                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:02:26 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
      ]
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     "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\">21:02:31 -03 </span>starting up solver                                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:02:31 -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"
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    {
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       "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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">21:12:16 -03 </span>status = postprocess                                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:12:16 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
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     },
     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
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       "Output()"
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     },
     "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\">21:13:03 -03 </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:13:03 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
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    {
     "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"
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      "text/plain": []
     },
     "metadata": {},
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    {
     "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\">21:13:05 -03 </span>View simulation result at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">6-4282-81e2-8f02a9c287c2'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:13:05 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=22579;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=631668;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=22579;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=31382;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=22579;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[4;34m-8db353fb-06d\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=22579;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8db353fb-06d6-4282-81e2-8f02a9c287c2\u001b\\\u001b[4;34m6-4282-81e2-8f02a9c287c2'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
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       "Output()"
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     "output_type": "display_data"
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    {
     "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"
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    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">21:14:40 -03 </span>loading simulation from simulation_data.hdf5                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:14:40 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
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    }
   ],
   "source": [
    "run_time_cw = 1e-10\n",
    "field_mnt_time = td.FieldTimeMonitor(\n",
    "    center=(0, 0, 0),\n",
    "    size=(Lx, Ly, Lz),\n",
    "    fields=[\"Ex\", \"Ey\", \"Ez\"],\n",
    "    start=run_time_cw - 1 / freq0,\n",
    "    interval=1,\n",
    "    colocate=True,\n",
    "    name=\"movie_monitor\",\n",
    ")\n",
    "\n",
    "sim_cw = sim.updated_copy(\n",
    "    sources=(\n",
    "        td.PointDipole(\n",
    "            center=(0, 0, 0),\n",
    "            source_time=td.ContinuousWave(freq0=cavity_resonance_freq, fwidth=fwidth),\n",
    "            polarization=\"Ey\",\n",
    "        ),\n",
    "    ),\n",
    "    monitors=list(sim.monitors) + [field_mnt_time],\n",
    "    run_time=run_time_cw,\n",
    ")\n",
    "\n",
    "sim_data_cw = web.run(sim_cw, task_name=\"1_fundamental_mode_spectrumCW\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get data from the TimeMonitor\n",
    "tdata = sim_data_cw[\"time_series\"]\n",
    "\n",
    "time_series = tdata.Ey.squeeze()\n",
    "\n",
    "# Get data from the TimeMonitor\n",
    "tdata_flux = sim_data_cw[\"flux_time\"]\n",
    "\n",
    "flux = tdata_flux.flux.squeeze()\n",
    "time_flux = tdata_flux.flux.coords[\"t\"]\n",
    "\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(10, 3))\n",
    "\n",
    "# Plot time dependence\n",
    "time_series.plot(ax=ax1)\n",
    "\n",
    "# Make frequency mesh and plot spectrum\n",
    "dt = sim_data_cw.simulation.dt\n",
    "fmesh = np.linspace(-1 / dt / 2, 1 / dt / 2, time_series.size)\n",
    "spectrum = np.fft.fftshift(np.fft.fft(time_series))\n",
    "\n",
    "ax2.plot(fmesh, np.abs(spectrum))\n",
    "ax2.set_xlim(freq0 - 2 * fwidth, freq0 + 2 * fwidth)\n",
    "ax2.set_xlabel(\"Frequency [Hz]\")\n",
    "ax2.set_ylabel(\"Electric field [a.u.]\")\n",
    "ax2.set_title(\"Spectrum\")\n",
    "\n",
    "ax3.plot(time_flux, np.abs(flux))\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "max_field_coord = sim_data_cw[\"movie_monitor\"].Ey.idxmax(dim=\"t\")\n",
    "\n",
    "Ey_array = np.array(sim_data_cw[\"movie_monitor\"].Ey)\n",
    "integrated_ey_time = np.sum(Ey_array, axis=(0, 1, 2))\n",
    "time_coord_max_field = np.argmax(integrated_ey_time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_28045/4225370433.py:1: DeprecationWarning: dropping variables using `drop` is deprecated; use drop_vars.\n",
      "  Ex = sim_data_cw[\"movie_monitor\"].Ex.isel(t=time_coord_max_field).drop(\"t\")\n",
      "/tmp/ipykernel_28045/4225370433.py:2: DeprecationWarning: dropping variables using `drop` is deprecated; use drop_vars.\n",
      "  Ey = sim_data_cw[\"movie_monitor\"].Ey.isel(t=time_coord_max_field).drop(\"t\")\n",
      "/tmp/ipykernel_28045/4225370433.py:3: DeprecationWarning: dropping variables using `drop` is deprecated; use drop_vars.\n",
      "  Ez = sim_data_cw[\"movie_monitor\"].Ez.isel(t=time_coord_max_field).drop(\"t\")\n"
     ]
    }
   ],
   "source": [
    "Ex = sim_data_cw[\"movie_monitor\"].Ex.isel(t=time_coord_max_field).drop(\"t\")\n",
    "Ey = sim_data_cw[\"movie_monitor\"].Ey.isel(t=time_coord_max_field).drop(\"t\")\n",
    "Ez = sim_data_cw[\"movie_monitor\"].Ez.isel(t=time_coord_max_field).drop(\"t\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The SHG will only occur in the nonlinear medium, so we will create a mask to exclude the holes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Permittivity distribution.\n",
    "eps_non_colocated = abs(sim_data_cw[\"eps_monitor\"].eps_yy).isel(f=0)\n",
    "\n",
    "eps = eps_non_colocated.interp(\n",
    "    x=Ex.coords[\"x\"],\n",
    "    y=Ex.coords[\"y\"],\n",
    "    z=Ex.coords[\"z\"],\n",
    ")\n",
    "\n",
    "\n",
    "eps_max = np.max(np.real(eps))\n",
    "\n",
    "nonlinear_material_mask = np.real(eps) - 1\n",
    "nonlinear_material_mask = nonlinear_material_mask / np.max(nonlinear_material_mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "tdata_flux_w0 = sim_data_cw[\"flux_time\"]\n",
    "flux_w0 = tdata_flux_w0.flux.squeeze()\n",
    "radiated_power = float(np.mean(flux_w0[int(len(flux_w0) * 0.99) : -1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "47623.6432485041\n"
     ]
    }
   ],
   "source": [
    "# Compute energy in cavity\n",
    "integrand = eps * (\n",
    "    Ex * np.conjugate(Ex) + Ey * np.conjugate(Ey) + Ez * np.conjugate(Ez)\n",
    ")\n",
    "integrated_energy = td.EPSILON_0 / 2 * integrand.integrate(coord=(\"x\", \"y\", \"z\")).item()\n",
    "Q = (integrated_energy / radiated_power) * 2 * np.pi * cavity_resonance_freq\n",
    "\n",
    "print(Q)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Second Harmonic Simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Defining the relevant polarization tensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculating the second-order nonlinear polarization\n",
    "d15 = 6.7 * 1e-6  # um/V\n",
    "d31 = 6.5 * 1e-6  # um/V\n",
    "d33 = -11.7 * 1e-6  # um/V\n",
    "\n",
    "# Central frequency around which we'll look for the cavity mode (Hz)\n",
    "freq_SH = 2 * cavity_resonance_freq"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we will define the relevant polarization fields using the relation: $P_{i,j,k} = \\omega_0 \\epsilon_0 d_{i,j,k} E_j E_k$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "Pxxz = td.EPSILON_0 * d15 * nonlinear_material_mask * Ex * Ez\n",
    "Pyyz = td.EPSILON_0 * d15 * nonlinear_material_mask * Ey * Ez\n",
    "Pzxx = td.EPSILON_0 * d31 * nonlinear_material_mask * Ex * Ex\n",
    "Pzyy = td.EPSILON_0 * d31 * nonlinear_material_mask * Ey * Ey\n",
    "Pzzz = td.EPSILON_0 * d33 * nonlinear_material_mask * Ez * Ez\n",
    "\n",
    "\n",
    "Pxxz = Pxxz.expand_dims(dim={\"f\": 1}, axis=3)\n",
    "Pyyz = Pyyz.expand_dims(dim={\"f\": 1}, axis=3)\n",
    "Pzxx = Pzxx.expand_dims(dim={\"f\": 1}, axis=3)\n",
    "Pzyy = Pzyy.expand_dims(dim={\"f\": 1}, axis=3)\n",
    "Pzzz = Pzzz.expand_dims(dim={\"f\": 1}, axis=3)\n",
    "\n",
    "Pxxz = Pxxz.assign_coords(f=[freq_SH])\n",
    "Pyyz = Pyyz.assign_coords(f=[freq_SH])\n",
    "Pzxx = Pzxx.assign_coords(f=[freq_SH])\n",
    "Pzyy = Pzyy.assign_coords(f=[freq_SH])\n",
    "Pzzz = Pzzz.assign_coords(f=[freq_SH])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we create the polarization dataset to be used in the [`CustomCurrentSource`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.CustomCurrentSource.html) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "factor = -1j * (freq_SH * 2 * np.pi)\n",
    "polarization = td.FieldDataset(\n",
    "    Ex=factor * Pxxz,\n",
    "    Ey=factor * Pyyz,\n",
    "    Ez=factor * (Pzxx + Pzyy + Pzzz),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Source bandwidth (Hz)\n",
    "fwidth_SH = freq_SH * 0.3\n",
    "\n",
    "# Simulation run time (s)\n",
    "run_time_SH = 2e-12\n",
    "\n",
    "# In-built GaussianBeam source\n",
    "pulse = td.ContinuousWave(freq0=freq_SH, fwidth=fwidth_SH)\n",
    "\n",
    "custom_src_JM = td.CustomCurrentSource(\n",
    "    source_time=pulse,\n",
    "    center=(0, 0, 0),\n",
    "    size=(Lx, Ly, Lz),\n",
    "    current_dataset=polarization,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "structures_775 = define_geometry(mat_slab_775, mat_hole_775)\n",
    "\n",
    "simSH = td.Simulation(\n",
    "    size=sim.size,\n",
    "    grid_spec=td.GridSpec.from_grid(\n",
    "        sim.grid\n",
    "    ),  # Reference to the linear simulation for copying the grid\n",
    "    structures=structures_775,\n",
    "    sources=[custom_src_JM],\n",
    "    monitors=[time_series_mnt, eps_monitor, flux_time, field_mnt],\n",
    "    run_time=run_time_SH,\n",
    "    boundary_spec=td.BoundarySpec(\n",
    "        x=td.Boundary.pml(), y=td.Boundary.pml(), z=td.Boundary.pml()\n",
    "    ),\n",
    "    symmetry=(0, 0, 0),\n",
    "    shutoff=0,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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\">21:15:19 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'no name'</span> with task_id                                \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:15:19 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'no name'\u001b[0m with task_id                                \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe'\u001b[0m and task_type \u001b[32m'FDTD'\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=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">e-4e26-a2f4-5df4ce520afe'</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=657180;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=492456;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=657180;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=817856;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=657180;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[32m-c9d00a4e-448\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=657180;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[32me-4e26-a2f4-5df4ce520afe'\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-2d594d1c-257b-417d-92d0-e6dcb36d63f0\" 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=568358;https://tidy3d.simulation.cloud/folders/folder-2d594d1c-257b-417d-92d0-e6dcb36d63f0\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6dc6ed4609b34da891cdc186df3a3f2b",
       "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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">21:15:51 -03 </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.095</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;36m21:15:51 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.095\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\">21:15:53 -03 </span>status = queued                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:15:53 -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": "ac795b7bea0b47d4b9e2e7354712c44d",
       "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:15:58 -03 </span>status = preprocess                                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:15:58 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \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\">21:16:07 -03 </span>starting up solver                                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:16:07 -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"
      ]
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     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "model_id": "fe23fa7aeea44f949ef9e76490d76a1b",
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       "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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">21:16:42 -03 </span>status = postprocess                                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:16:42 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3772f8e338b34515aba6da1bec0d1e05",
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       "version_minor": 0
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      "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:16:58 -03 </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:16:58 -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\">21:17:00 -03 </span>View simulation result at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">e-4e26-a2f4-5df4ce520afe'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:17:00 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=978210;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=977294;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=978210;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=410477;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=978210;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[4;34m-c9d00a4e-448\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=978210;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c9d00a4e-448e-4e26-a2f4-5df4ce520afe\u001b\\\u001b[4;34me-4e26-a2f4-5df4ce520afe'\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": "1f5953ccbcd247d2afc371e64f3c3826",
       "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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">21:17:38 -03 </span>loading simulation from simulation_data.hdf5                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:17:38 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data_SH = web.run(simSH, task_name=\"no name\", verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see in the plots above, the fields reach a steady-state after about 0.5 ps.\n",
    "\n",
    "Now, we can visualize the SHG fields from the resonant mode:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get data from the TimeMonitor\n",
    "tdata = sim_data_SH[\"time_series\"]\n",
    "\n",
    "time_series = tdata.Ez.squeeze()\n",
    "\n",
    "# Get data from the TimeMonitor\n",
    "tdata_flux = sim_data_SH[\"flux_time\"]\n",
    "\n",
    "flux = tdata_flux.flux.squeeze()\n",
    "time_flux = tdata_flux.flux.coords[\"t\"]\n",
    "\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(10, 3))\n",
    "\n",
    "# Plot time dependence\n",
    "time_series.plot(ax=ax1)\n",
    "\n",
    "# Make frequency mesh and plot spectrum\n",
    "dt = sim_data_SH.simulation.dt\n",
    "fmesh = np.linspace(-1 / dt / 2, 1 / dt / 2, time_series.size)\n",
    "spectrum = np.fft.fftshift(np.fft.fft(time_series))\n",
    "\n",
    "ax2.plot(fmesh, np.abs(spectrum))\n",
    "ax2.set_xlim(2 * freq0 - 2 * fwidth, 2 * freq0 + 2 * fwidth)\n",
    "ax2.set_xlabel(\"Frequency [Hz]\")\n",
    "ax2.set_ylabel(\"Electric field [a.u.]\")\n",
    "ax2.set_title(\"Spectrum\")\n",
    "\n",
    "ax3.plot(time_flux, np.abs(flux))\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sim_data_SH.plot_field(\n",
    "    \"field_mnt\", \"Ez\", \"real\", z=0, robust=False, eps_alpha=0, phase=np.pi\n",
    ")\n",
    "\n",
    "ax.pcolormesh(\n",
    "    eps.x, eps.y, eps.sel(z=0, method=\"nearest\").real.T, alpha=0.2, cmap=\"binary\"\n",
    ")\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Nanophotonics"
  ],
  "description": "This notebook simulates second harmonic generation in a 2D photonic crystal by using the nonlinear fields to calculate the nonlinear polarization and then using it as a source for the second harmonic generation.",
  "feature_image": "./img/SHG.png",
  "features": [
   "Custom source",
   "Resonance finder"
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "FDTD, Tidy3D, nonlinear optics, photonic crystal, second harmonic generation, SHG",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.0"
  },
  "title": "Second harmonic generation in a 2D photonic crystal cavity | Flexcompute"
 },
 "nbformat": 4,
 "nbformat_minor": 4
}