{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e06d909a",
   "metadata": {},
   "source": [
    "# Plasmonic Yagi-Uda nanoantenna"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d61adb8",
   "metadata": {},
   "source": [
    "Note: the cost of running the entire notebook is larger than 1 FlexCredit.\n",
    "\n",
    "Antennas are the fundamental building blocks for high-speed communication networks. The concept of an antenna is well-established, particularly in RF and microwave engineering, dating back over one century ago. An antenna transforms propagating electromagnetic waves to localized electromagnetic field and vice versa, depending on whether it is in the transmitting mode or receiving mode. Thus, it enables wireless communication and information transmission over long distances. \n",
    "\n",
    "Recent rapid developments in nanotechnology have sparked vast interest in constructing the optical counterpart of antennas by utilizing the plasmonic nature of metal at optical frequencies. The size of these antennas is usually in the order of 100 nm. Therefore, they are often termed plasmonic nanoantennas. As the demand for higher bandwidth information transmission keeps growing, plasmonic nanoantennas potentially be the technological cornerstone for future communication systems.\n",
    "\n",
    "In this example notebook, we demonstrate the modeling of a plasmonic Yagi-Uda nanoantenna made of aluminum nanorods excited by a point dipole source. The far-field radiation pattern is calculated. We show that the simulated plasmonic Yagi-Uda nanoantenna can achieve a high directivity, which is desirable in many applications. The model is based on [Tim H. Taminiau, Fernando D. Stefani, and Niek F. van Hulst, \"Enhanced directional excitation and emission of single emitters by a nano-optical Yagi-Uda antenna,\" Opt. Express 16, 10858-10866 (2008)](https://opg.optica.org/oe/fulltext.cfm?uri=oe-16-14-10858&id=167282).\n",
    "\n",
    "<img src=\"img/yagi_uda_antenna_schematic_1.png\" width=600 alt=\"Schematic of the plasmonic Yagi-Uda nanoantenna\">\n",
    "\n",
    "If you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101](https://www.flexcompute.com/fdtd101/) tutorials. For more simulation examples, please visit our [examples page](https://www.flexcompute.com/tidy3d/examples/). FDTD simulations can diverge due to various reasons. If you run into any simulation divergence issues, please follow the steps outlined in our [troubleshooting guide](https://www.flexcompute.com/tidy3d/examples/notebooks/DivergedFDTDSimulation/) to resolve it."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c4e33ec",
   "metadata": {},
   "source": [
    "## Simulation Setup "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39e69ef7",
   "metadata": {},
   "source": [
    "In this model, we are going to fit the refractive index of aluminum using data from the literature. Thus, we import the [DispersionFitter](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.dispersion.DispersionFitter.html) from the Tidy3D plugins."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1cd3ac66",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n",
    "from tidy3d.plugins.dispersion import DispersionFitter"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1868111",
   "metadata": {},
   "source": [
    "As schematically shown above, a typical Yagi-Uda antenna consists of three components: a feed element that is excited by a source, a reflector element that suppresses the radiation in the backward direction, and an array of director elements that enhances the radiation in the forward direction. Usually, having a large number of director elements is beneficial for achieving a high directivity. In practice, we need to consider the footprint, fabrication constraints, costs, and so on. In this particular example, our Yagi-Uda antenna has three director elements. All elements are made of aluminum nanorods with rounded ends.  \n",
    "\n",
    "The lengths and spacings of the elements are designed to achieve optimal performance at 570 nm wavelength. An initial design can be obtained by following the classical design principle of RF/microwave Yagi-Uda antennas. Since metals behave very differently in lower frequencies compared to optical frequencies, the parameters need to be optimized to account for the finite skin depth and ohmic loss. In this notebook, we skip the optimization process and only present the optimized design from the referenced paper. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f76b62d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "lda0 = 0.57  # operation wavelength\n",
    "freq0 = td.C_0 / lda0  # operation frequency"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bfd9947",
   "metadata": {},
   "source": [
    "The nanorods are made of aluminum. Before constructing the model, we first need to use the [DispersionFitter](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.dispersion.DispersionFitter.html) to fit the refractive index data of aluminum, which can be found in the [refractive index database](https://refractiveindex.info/). In particular, we use the data from [McPeak et al. 2015](https://pubs.acs.org/doi/10.1021/ph5004237). The csv file can be downloaded from our documentation [repo](https://github.com/flexcompute/tidy3d-notebooks/tree/develop/misc). Since we are only interested in the antenna response at 570 nm, we only need to fit the refractive index in the vicinity of the operation wavelength.\n",
    "\n",
    "The fitting results in a RMS error about of 0.01, which is reasonably good."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0c4d1567",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8f82b96f46ae46cdb2fc2eb2e73a895c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fname = \"misc/McPeak.csv\"  # read the refractive index data from a csv file\n",
    "fitter = DispersionFitter.from_file(fname, delimiter=\",\")  # construct a fitter\n",
    "al, rms_error = fitter.fit(num_poles=6, tolerance_rms=2e-2, num_tries=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1f03abd",
   "metadata": {},
   "source": [
    "Next, we construct the Yagi-Uda antenna by individually constructing the feed, reflector, and three directors. Each element consists of a cylinder and two spheres that represent the rounded caps on each end. For convenience, we define a function to build the antenna structures since it will be used repeatedly in the next section of this notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "db39d6c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# L_f is the length of the feed element\n",
    "# r is the radius of the nanorods.\n",
    "# medium is the material of the nanorods\n",
    "def construct_antenna(L_f, r, lda0, medium):\n",
    "    L_r = L_f * 1.25  # length of the reflector\n",
    "    L_d = L_f * 0.9  # length of the directors\n",
    "    a_r = lda0 / 4.4  # spacing between the feed and the reflector\n",
    "    a_d = (\n",
    "        lda0 / 4\n",
    "    )  # spacing between the feed and the first director (also the spacing between directors)\n",
    "\n",
    "    feed = [\n",
    "        td.Structure(\n",
    "            geometry=td.Cylinder(center=(0, 0, 0), radius=r, length=L_f - 2 * r, axis=1),\n",
    "            medium=medium,\n",
    "        ),\n",
    "        td.Structure(\n",
    "            geometry=td.Sphere(center=(0, (L_f - 2 * r) / 2, 0), radius=r),\n",
    "            medium=medium,\n",
    "        ),\n",
    "        td.Structure(\n",
    "            geometry=td.Sphere(center=(0, -(L_f - 2 * r) / 2, 0), radius=r),\n",
    "            medium=medium,\n",
    "        ),\n",
    "    ]\n",
    "\n",
    "    reflector = [\n",
    "        td.Structure(\n",
    "            geometry=td.Cylinder(center=(-a_r, 0, 0), radius=r, length=L_r - 2 * r, axis=1),\n",
    "            medium=medium,\n",
    "        ),\n",
    "        td.Structure(\n",
    "            geometry=td.Sphere(center=(-a_r, (L_r - 2 * r) / 2, 0), radius=r),\n",
    "            medium=medium,\n",
    "        ),\n",
    "        td.Structure(\n",
    "            geometry=td.Sphere(center=(-a_r, -(L_r - 2 * r) / 2, 0), radius=r),\n",
    "            medium=medium,\n",
    "        ),\n",
    "    ]\n",
    "\n",
    "    director_1 = [\n",
    "        td.Structure(\n",
    "            geometry=td.Cylinder(center=(a_d, 0, 0), radius=r, length=L_d - 2 * r, axis=1),\n",
    "            medium=medium,\n",
    "        ),\n",
    "        td.Structure(\n",
    "            geometry=td.Sphere(center=(a_d, (L_d - 2 * r) / 2, 0), radius=r),\n",
    "            medium=medium,\n",
    "        ),\n",
    "        td.Structure(\n",
    "            geometry=td.Sphere(center=(a_d, -(L_d - 2 * r) / 2, 0), radius=r),\n",
    "            medium=medium,\n",
    "        ),\n",
    "    ]\n",
    "\n",
    "    director_2 = [\n",
    "        td.Structure(\n",
    "            geometry=td.Cylinder(center=(2 * a_d, 0, 0), radius=r, length=L_d - 2 * r, axis=1),\n",
    "            medium=medium,\n",
    "        ),\n",
    "        td.Structure(\n",
    "            geometry=td.Sphere(center=(2 * a_d, (L_d - 2 * r) / 2, 0), radius=r),\n",
    "            medium=medium,\n",
    "        ),\n",
    "        td.Structure(\n",
    "            geometry=td.Sphere(center=(2 * a_d, -(L_d - 2 * r) / 2, 0), radius=r),\n",
    "            medium=medium,\n",
    "        ),\n",
    "    ]\n",
    "\n",
    "    director_3 = [\n",
    "        td.Structure(\n",
    "            geometry=td.Cylinder(center=(3 * a_d, 0, 0), radius=r, length=L_d - 2 * r, axis=1),\n",
    "            medium=medium,\n",
    "        ),\n",
    "        td.Structure(\n",
    "            geometry=td.Sphere(center=(3 * a_d, (L_d - 2 * r) / 2, 0), radius=r),\n",
    "            medium=medium,\n",
    "        ),\n",
    "        td.Structure(\n",
    "            geometry=td.Sphere(center=(3 * a_d, -(L_d - 2 * r) / 2, 0), radius=r),\n",
    "            medium=medium,\n",
    "        ),\n",
    "    ]\n",
    "\n",
    "    antenna = feed + reflector + director_1 + director_2 + director_3\n",
    "    return antenna\n",
    "\n",
    "\n",
    "L_f = 0.16  # length of the feed\n",
    "r = 0.02  # radius of the nanorods\n",
    "medium = al  # material of the antenna\n",
    "\n",
    "antenna = construct_antenna(L_f, r, lda0, medium)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94620334",
   "metadata": {},
   "source": [
    "The Yagi-Uda antenna is usually fed by a small quantum emitter such as a laser-excited quantum dot. In the simulation, the source can be well approximated as a [PointDipole](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PointDipole.html), which is what we are going to use.\n",
    "\n",
    "To calculate the far-field radiation pattern and directivity, we will use the [FieldProjectionAngleMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldProjectionAngleMonitor.html) as well as a [FluxMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FluxMonitor.html). The [FieldProjectionAngleMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldProjectionAngleMonitor.html) yields the angular radiation power and the [FluxMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FluxMonitor.html) helps to calculate the total radiated power. Both are required in the calculation of directivity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "79a4c9d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define simulation domain size\n",
    "Lx = 3 * lda0\n",
    "Ly = 2 * lda0\n",
    "Lz = 2 * lda0\n",
    "sim_size = (Lx, Ly, Lz)\n",
    "\n",
    "# create an electrical point dipole source polarized in the y direction to excite the feed element\n",
    "d_dp = 0.004  # distance between the dipole and the feed element\n",
    "pulse = td.GaussianPulse(freq0=freq0, fwidth=freq0 / 20)\n",
    "pt_dipole = td.PointDipole(center=(0, L_f / 2 + d_dp, 0), source_time=pulse, polarization=\"Ey\")\n",
    "\n",
    "# create a FieldProjectionAngleMonitor to perform the near field to far field transformation in spherical coordinates\n",
    "theta_array = np.linspace(0, 2 * np.pi, 200)\n",
    "phi_array = np.linspace(0, np.pi, 100)\n",
    "n2f_monitor = td.FieldProjectionAngleMonitor(\n",
    "    center=(0, 0, 0),\n",
    "    size=(2 * lda0, 1 * lda0, 1 * lda0),\n",
    "    freqs=[freq0],\n",
    "    name=\"n2f_monitor\",\n",
    "    custom_origin=(0, 0, 0),\n",
    "    phi=phi_array,\n",
    "    theta=theta_array,\n",
    ")\n",
    "\n",
    "# create a flux monitor to calculate the total radiated power\n",
    "flux_monitor = td.FluxMonitor(\n",
    "    center=(0, 0, 0),\n",
    "    size=(Lx * 0.9, Ly * 0.9, Lz * 0.9),\n",
    "    freqs=[freq0],\n",
    "    name=\"power\",\n",
    ")\n",
    "\n",
    "# create the simulation with the above defined elements\n",
    "sim = td.Simulation(\n",
    "    center=(0, 0, 0),\n",
    "    size=sim_size,\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=40, wavelength=lda0),\n",
    "    structures=antenna,\n",
    "    sources=[pt_dipole],\n",
    "    monitors=[n2f_monitor, flux_monitor],\n",
    "    run_time=1e-13,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    ")\n",
    "\n",
    "# visualize the simulation setup\n",
    "sim.plot(z=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "820025da",
   "metadata": {},
   "source": [
    "For comparison, define an empty simulation with only the [PointDipole](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PointDipole.html). We will use this to show that the Yagi-Uda antenna exhibits a much higher directivity compared to a dipole radiation source."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4d0836a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "sim_empty = td.Simulation(\n",
    "    center=(0, 0, 0),\n",
    "    size=sim_size,\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=40, wavelength=lda0),\n",
    "    structures=[],  # this simulation is identical to the previous one besides the structures is set to an empty list\n",
    "    sources=[pt_dipole],\n",
    "    monitors=[n2f_monitor, flux_monitor],\n",
    "    run_time=1e-13,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38a3a87d",
   "metadata": {},
   "source": [
    "Submit both the antenna simulation and empty simulation to the server."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f25b9b66",
   "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\">13:04:52 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'plasmonic_yagi_uda'</span> with resource_id                 \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:04:52 UTC\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'plasmonic_yagi_uda'\u001b[0m with resource_id                 \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d'\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-6c3801ef-5b33-4a00-9e59-0121275afc5d\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b3</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">3-4a00-9e59-0121275afc5d'</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=259502;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=989486;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=259502;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=278266;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=259502;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[32m-6c3801ef-5b3\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=259502;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[32m3-4a00-9e59-0121275afc5d'\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/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" 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=713058;https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "12a43f9210924cf6bed1c844f020144f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:04:55 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.056</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;36m13:04:55 UTC\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.056\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\">13:04:56 UTC </span>status = queued                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:04:56 UTC\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": {
      "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\">13:05:05 UTC </span>starting up solver                                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:05 UTC\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\">13:05:06 UTC </span>running solver                                                     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:06 UTC\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3b14b85f3136481e8f3b6cd13fd323bc",
       "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\">13:05:14 UTC </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">56</span>%, exiting.                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:14 UTC\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m56\u001b[0m%, exiting.                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>status = postprocess                                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \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\">13:05:15 UTC </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:15 UTC\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\">13:05:17 UTC </span>View simulation result at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b3</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">3-4a00-9e59-0121275afc5d'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:17 UTC\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=995046;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=438576;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=995046;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=796050;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=995046;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[4;34m-6c3801ef-5b3\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=995046;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6c3801ef-5b33-4a00-9e59-0121275afc5d\u001b\\\u001b[4;34m3-4a00-9e59-0121275afc5d'\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": "d8355801e8ed4e29a6726992f7c37eb1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:05:21 UTC </span>Loading simulation from data/optical_yagi_uda.hdf5                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:21 UTC\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from data/optical_yagi_uda.hdf5                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'empty'</span> with resource_id                              \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-c107ffc3-6853-4f57-b874-50cb7716a974'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'empty'\u001b[0m with resource_id                              \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-c107ffc3-6853-4f57-b874-50cb7716a974'\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-c107ffc3-6853-4f57-b874-50cb7716a974\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-c107ffc3-685</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c107ffc3-6853-4f57-b874-50cb7716a974\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">3-4f57-b874-50cb7716a974'</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=959406;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c107ffc3-6853-4f57-b874-50cb7716a974\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=779314;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c107ffc3-6853-4f57-b874-50cb7716a974\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=959406;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c107ffc3-6853-4f57-b874-50cb7716a974\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=92544;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c107ffc3-6853-4f57-b874-50cb7716a974\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=959406;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c107ffc3-6853-4f57-b874-50cb7716a974\u001b\\\u001b[32m-c107ffc3-685\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=959406;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c107ffc3-6853-4f57-b874-50cb7716a974\u001b\\\u001b[32m3-4f57-b874-50cb7716a974'\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/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" 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=23411;https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4720d254cf364e8aab1595565067ed95",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:05:24 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</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;36m13:05:24 UTC\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.025\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\">13:05:26 UTC </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:26 UTC\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "112c07523bb14024bc55bca4fb485632",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:05:30 UTC </span>Loading simulation from data/optical_yagi_uda.hdf5                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:30 UTC\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from data/optical_yagi_uda.hdf5                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data = web.run(\n",
    "    sim, task_name=\"plasmonic_yagi_uda\", path=\"data/optical_yagi_uda.hdf5\", verbose=True\n",
    ")\n",
    "sim_empty_data = web.run(\n",
    "    sim_empty, task_name=\"empty\", path=\"data/optical_yagi_uda.hdf5\", verbose=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a334ffc",
   "metadata": {},
   "source": [
    "## Postprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d002725e",
   "metadata": {},
   "source": [
    "After the simulations are complete, we calculate the directivity of the Yagi-Uda antenna and the single point dipole. The directivity is given by\n",
    "\n",
    "<center> $D(\\phi,\\theta)=\\frac{4\\pi P(\\phi,\\theta)}{P_0}$,</center>\n",
    "\n",
    "where $P$ is the angular radiated power and $P_0= \\iint P(\\phi,\\theta) d\\Omega$ is the total radiated power.\n",
    "\n",
    "The result shows that the dipole has a directivity of around 1.5, which is expected for a dipole radiator. On the other hand, the Yagi-Uda antenna has a much higher forward directivity above 6. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ff1fb3b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P0 = np.array(sim_data[\"power\"].flux)  # total radiated power of the yagi-uda antenna\n",
    "\n",
    "# angular radiated power of the yagi-uda antenna\n",
    "# by default, the power is calculated at 1 meter away from the antenna. The 1e12 factor normalizes the power to unit distance (1 um)\n",
    "P = 1e12 * sim_data[\"n2f_monitor\"].power.sel(f=freq0, phi=0, method=\"nearest\").values\n",
    "P = np.squeeze(P)\n",
    "D = 4 * np.pi * P / P0  # directivity of the yagi-uda antenna\n",
    "\n",
    "P0_dp = np.array(sim_empty_data[\"power\"].flux)  # total radiated power of the point dipole\n",
    "P_dp = (\n",
    "    1e12 * sim_empty_data[\"n2f_monitor\"].power.sel(f=freq0, phi=0, method=\"nearest\").values\n",
    ")  # angular radiated power of the point dipole\n",
    "P_dp = np.squeeze(P_dp)\n",
    "D_dp = 4 * np.pi * P_dp / P0_dp  # directivity of the point dipole\n",
    "\n",
    "# comparison of the directivity\n",
    "fig, ax = plt.subplots(subplot_kw={\"projection\": \"polar\"})\n",
    "ax.set_theta_direction(-1)\n",
    "ax.set_theta_offset(np.pi / 2.0)\n",
    "ax.plot(theta_array, D, theta_array, D_dp)\n",
    "ax.set_rlim(0, 8)\n",
    "ax.set_title(\"Directivity\")\n",
    "ax.legend((\"Yagi-Uda antenna\", \"Dipole\"))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fef9a61",
   "metadata": {},
   "source": [
    "When studying antennas, very often we want to plot the full 3D radiation pattern. Here we show how to do so. This requires us to convert the spherical coordinates representation of the radiation pattern to Cartesian coordinates representation. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c1d1e015",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P = 1e12 * sim_data[\"n2f_monitor\"].power.sel(f=freq0).values  # angular radiated power\n",
    "D = 4 * np.pi * np.squeeze(P) / P0  # directivity\n",
    "\n",
    "# convert the spherical coordinates representation to cartesian coordinates\n",
    "phi, theta = np.meshgrid(phi_array, theta_array)\n",
    "X = D * np.cos(phi) * np.sin(theta)\n",
    "Y = D * np.sin(phi) * np.sin(theta)\n",
    "Z = D * np.cos(theta)\n",
    "\n",
    "R = np.sqrt(\n",
    "    X**2 + Y**2 + Z**2\n",
    ")  # distance to the center will be used to plot the color on top of the radiation pattern\n",
    "R = R / np.max(R)  # normalize it to 1\n",
    "\n",
    "color = plt.cm.jet(R)  # define colormap using the distance\n",
    "\n",
    "# plotting the radiation pattern in 3d\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(1, 1, 1, projection=\"3d\")\n",
    "ax.set_xlim((-2, 8))\n",
    "ax.set_ylim((-5, 5))\n",
    "ax.set_zlim((-5, 5))\n",
    "ax.set_xlabel(\"X\")\n",
    "ax.set_ylabel(\"Y\")\n",
    "ax.set_zlabel(\"Z\")\n",
    "surf = ax.plot_surface(\n",
    "    X, Y, Z, cstride=1, rstride=1, facecolors=color, antialiased=True, shade=False\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62475fa2",
   "metadata": {},
   "source": [
    "## Alternative Approach: Extending the Simulation Domain into the Far-Field Zone"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e95638d",
   "metadata": {},
   "source": [
    "Performing the near field to far field transformation using the [FieldProjectionAngleMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldProjectionAngleMonitor.html) is a great way to reduce the computational cost by limiting the simulation domain only to the vicinity of the antenna. However, there are certain limitations. For example, the transformation assumes a homogeneous background medium. In practice, we often encounter inhomogeneous background such as when the antenna is placed on a dielectric substrate. \n",
    "\n",
    "Alternative to using the near field to far field transformation to obtain the far-field quantities, we can simply extend the simulation domain sufficiently far into the far-field zone. Here we harness the power of the highly optimized Tidy3D solver such that the simulation is still fast even when the domain size is large.\n",
    "\n",
    "Next, we demonstrate this alternative approach and compare the result to the previous simulation to verify the accuracy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "89dad19a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compared to the previous simulation, this simulation uses a much larger simulation domain size\n",
    "Lx = 15 * lda0\n",
    "Ly = 2 * lda0\n",
    "Lz = 15 * lda0\n",
    "sim_size = (Lx, Ly, Lz)\n",
    "\n",
    "# add a point dipole source\n",
    "pulse = td.GaussianPulse(freq0=freq0, fwidth=freq0 / 20)\n",
    "pt_dipole = td.PointDipole(center=(0, L_f / 2 + d_dp, 0), source_time=pulse, polarization=\"Ey\")\n",
    "\n",
    "# add a flux monitor to compute the total radiated power\n",
    "flux_monitor = td.FluxMonitor(\n",
    "    center=(0, 0, 0),\n",
    "    size=(Lx * 0.9, Ly * 0.9, Lz * 0.9),\n",
    "    freqs=[freq0],\n",
    "    name=\"power\",\n",
    ")\n",
    "\n",
    "# add a field monitor to compute the field far away from the antenna to calculate the directivity\n",
    "field_monitor = td.FieldMonitor(\n",
    "    center=(0, 0, 0),\n",
    "    size=(td.inf, 0, td.inf),\n",
    "    freqs=[freq0],\n",
    "    name=\"field\",\n",
    ")\n",
    "\n",
    "# create the simulation with the above defined elements\n",
    "sim = td.Simulation(\n",
    "    center=(0, 0, 0),\n",
    "    size=sim_size,\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=40, wavelength=lda0),\n",
    "    structures=antenna,\n",
    "    sources=[pt_dipole],\n",
    "    monitors=[flux_monitor, field_monitor],\n",
    "    run_time=1e-13,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    ")\n",
    "\n",
    "# visualize the simulation setup\n",
    "sim.plot(z=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df2c4a9d",
   "metadata": {},
   "source": [
    "Submit the simulation to the server."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7ce54de3",
   "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\">13:05:33 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'plasmonic_yagi_uda'</span> with resource_id                 \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:33 UTC\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'plasmonic_yagi_uda'\u001b[0m with resource_id                 \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422'\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-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e9</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">6-4a0e-8abf-40a6eed7e422'</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=683719;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=334277;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=683719;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=843731;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=683719;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[32m-bce7dfcb-2e9\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=683719;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[32m6-4a0e-8abf-40a6eed7e422'\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/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" 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=521775;https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "af8009da48c84805be85c28a97acfc6e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:05:35 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.744</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;36m13:05:35 UTC\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.744\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\">13:05:38 UTC </span>status = queued                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:38 UTC\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": {
      "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\">13:05:46 UTC </span>starting up solver                                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:46 UTC\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\">13:05:47 UTC </span>running solver                                                     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:05:47 UTC\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "304d8fee111d4bda952d3464f8f96a19",
       "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\">13:06:58 UTC </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64</span>%, exiting.                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:06:58 UTC\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m64\u001b[0m%, exiting.                            \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\">13:06:59 UTC </span>status = postprocess                                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:06:59 UTC\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \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\">13:07:02 UTC </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:07:02 UTC\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\">13:07:04 UTC </span>View simulation result at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e9</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">6-4a0e-8abf-40a6eed7e422'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:07:04 UTC\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=266442;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=107663;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=266442;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=366794;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=266442;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[4;34m-bce7dfcb-2e9\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=266442;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bce7dfcb-2e96-4a0e-8abf-40a6eed7e422\u001b\\\u001b[4;34m6-4a0e-8abf-40a6eed7e422'\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": "a39c2ea2a33e4abe998a5c7b0a235ee7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:07:09 UTC </span>Loading simulation from data/optical_yagi_uda.hdf5                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:07:09 UTC\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from data/optical_yagi_uda.hdf5                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data = web.run(\n",
    "    sim, task_name=\"plasmonic_yagi_uda\", path=\"data/optical_yagi_uda.hdf5\", verbose=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fb88e64",
   "metadata": {},
   "source": [
    "In this simulation, the way to calculate the directivity is a little different. The simulation domain size is 15$\\lambda$. We can evaluate the radiated field at a circle 7$\\lambda$ away from the antenna. At this distance, the near field should completely decay away so the field is purely radiated field. Therefore, the power is directly given by\n",
    "\n",
    "<center>$P = \\frac{E^2}{2\\eta}$,</center>\n",
    "\n",
    "where $E$ is the peak-to-peak electric field strength and $\\eta=\\eta_0/n$ is the intrinsic impedance of the medium. $\\eta_0=377$ $\\Omega$ is the free space impedance and $n$ is the refractive index.\n",
    "\n",
    "As expected, the directivity pattern from this approach is practically identical to that from the near field to far field transformation, which verifies the validity of both methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f5f98fd5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = 7 * lda0  # distance at which the radiation pattern is evaluated\n",
    "Z0 = 377  # free space impedance\n",
    "P0 = np.array(sim_data[\"power\"].flux)  # total radiated power\n",
    "\n",
    "# evaluate the radiated power at 7*lda0 away from the antenna\n",
    "P = np.zeros(len(theta_array))\n",
    "for i, theta in enumerate(theta_array):\n",
    "    Ex = sim_data[\"field\"].Ex.sel(x=d * np.sin(theta), z=d * np.cos(theta), method=\"nearest\")\n",
    "    Ey = sim_data[\"field\"].Ey.sel(x=d * np.sin(theta), z=d * np.cos(theta), method=\"nearest\")\n",
    "    Ez = sim_data[\"field\"].Ez.sel(x=d * np.sin(theta), z=d * np.cos(theta), method=\"nearest\")\n",
    "    P[i] = (\n",
    "        d**2 * (abs(Ex) ** 2 + abs(Ey) ** 2 + abs(Ez) ** 2) / (2 * Z0)\n",
    "    ).item()  # we multiple the power by d^2 to normalize it to the power at unit distance\n",
    "D = 4 * np.pi * P / P0  # directivity of the yagi-uda antenna\n",
    "\n",
    "fig, ax = plt.subplots(subplot_kw={\"projection\": \"polar\"})\n",
    "ax.set_theta_direction(-1)\n",
    "ax.set_theta_offset(np.pi / 2.0)\n",
    "ax.plot(theta_array, D)\n",
    "ax.set_rlim(0, 8)\n",
    "ax.set_title(\"Directivity\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd2e1744",
   "metadata": {},
   "source": [
    "## Modeling Antenna on Substrate "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1b0f582",
   "metadata": {},
   "source": [
    "The approach of extending the simulation domain directly into the far-field zone really shows the benefit when the background medium is not uniform. Here we investigate such a case where a Yagi-Uda is placed on a glass substrate. It was predicted in the referenced paper that a lossless Yagi-Uda antenna on a glass substrate can achieve a directivity above 20, much higher than suspended in free space. \n",
    "\n",
    "For the lossless antenna, we will use PEC as the medium for the antenna structure. To make sure the mesh around the PEC domains is not excessively fine, we will utilize a mesh override structure and set the refractive index to 10. \n",
    "\n",
    "<img src=\"img/yagi_uda_antenna_schematic_2.png\" width=\"600\" alt=\"Schematic of the Yagi-Uda nanoantenna on glass\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d40ee38b",
   "metadata": {},
   "outputs": [],
   "source": [
    "pec = td.PECMedium()  # pec medium\n",
    "\n",
    "n_glass = 1.5  # glass has a refractive index of 1.5\n",
    "glass = td.Medium(permittivity=n_glass**2)\n",
    "\n",
    "L_f = 0.187  # length of the feed element\n",
    "antenna_pec = construct_antenna(\n",
    "    L_f, r, lda0, pec\n",
    ")  # construct the lossless yagi-uda antenna with pec\n",
    "\n",
    "inf_eff = 100  # effective infinity\n",
    "# construct the substrate\n",
    "sub = td.Structure(\n",
    "    geometry=td.Box.from_bounds(rmin=(-inf_eff, -inf_eff, -inf_eff), rmax=(inf_eff, inf_eff, -r)),\n",
    "    medium=glass,\n",
    ")\n",
    "\n",
    "# the whole structure is the antenna plus the substrate\n",
    "antenna_pec.append(sub)\n",
    "\n",
    "# to control the mesh around the antenna area, we construct a mesh override structure\n",
    "# refractive index of the override structure is set to 10 to ensure sufficiently but not excessively fine mesh\n",
    "refine_medium = td.Medium(permittivity=10**2)\n",
    "antenna_refine = construct_antenna(\n",
    "    L_f, r, lda0, refine_medium\n",
    ")  # construct the mesh override structure"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3ae09b0",
   "metadata": {},
   "source": [
    "Construct the source, monitors, and simulation in a similar way to the previous simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f9960aea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Lx = 15 * lda0\n",
    "Ly = 2 * lda0\n",
    "Lz = 15 * lda0\n",
    "sim_size = (Lx, Ly, Lz)\n",
    "\n",
    "pulse = td.GaussianPulse(freq0=freq0, fwidth=freq0 / 20)\n",
    "pt_dipole = td.PointDipole(center=(0, L_f / 2 + d_dp, 0), source_time=pulse, polarization=\"Ey\")\n",
    "\n",
    "flux_monitor = td.FluxMonitor(\n",
    "    center=(0, 0, 0),\n",
    "    size=(Lx * 0.9, Ly * 0.9, Lz * 0.9),\n",
    "    freqs=[freq0],\n",
    "    name=\"power\",\n",
    ")\n",
    "\n",
    "field_monitor = td.FieldMonitor(\n",
    "    center=(0, 0, 0),\n",
    "    size=(td.inf, 0, td.inf),\n",
    "    freqs=[freq0],\n",
    "    name=\"field\",\n",
    ")\n",
    "\n",
    "sim = td.Simulation(\n",
    "    center=(0, 0, 0),\n",
    "    size=sim_size,\n",
    "    grid_spec=td.GridSpec.auto(\n",
    "        min_steps_per_wvl=40, wavelength=lda0, override_structures=antenna_refine\n",
    "    ),\n",
    "    structures=antenna_pec,\n",
    "    sources=[pt_dipole],\n",
    "    monitors=[flux_monitor, field_monitor],\n",
    "    run_time=1e-13,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    ")\n",
    "\n",
    "sim.plot(y=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28a1aafb",
   "metadata": {},
   "source": [
    "Submit the simulation to the server."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "632a8a6f",
   "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\">13:07:17 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'plasmonic_yagi_uda_on_glass'</span> with resource_id        \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-e7d2fa01-23b9-489f-b51a-57812d5b0f2c'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:07:17 UTC\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'plasmonic_yagi_uda_on_glass'\u001b[0m with resource_id        \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-e7d2fa01-23b9-489f-b51a-57812d5b0f2c'\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-e7d2fa01-23b9-489f-b51a-57812d5b0f2c\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-e7d2fa01-23b</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-e7d2fa01-23b9-489f-b51a-57812d5b0f2c\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">9-489f-b51a-57812d5b0f2c'</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=348120;https://tidy3d.simulation.cloud/workbench?taskId=fdve-e7d2fa01-23b9-489f-b51a-57812d5b0f2c\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=695384;https://tidy3d.simulation.cloud/workbench?taskId=fdve-e7d2fa01-23b9-489f-b51a-57812d5b0f2c\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=348120;https://tidy3d.simulation.cloud/workbench?taskId=fdve-e7d2fa01-23b9-489f-b51a-57812d5b0f2c\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=877300;https://tidy3d.simulation.cloud/workbench?taskId=fdve-e7d2fa01-23b9-489f-b51a-57812d5b0f2c\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=348120;https://tidy3d.simulation.cloud/workbench?taskId=fdve-e7d2fa01-23b9-489f-b51a-57812d5b0f2c\u001b\\\u001b[32m-e7d2fa01-23b\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=348120;https://tidy3d.simulation.cloud/workbench?taskId=fdve-e7d2fa01-23b9-489f-b51a-57812d5b0f2c\u001b\\\u001b[32m9-489f-b51a-57812d5b0f2c'\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/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" 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=273876;https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bcbea9c4de734605a8408cf19d28f938",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:07:21 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4.546</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;36m13:07:21 UTC\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m4.546\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\">13:07:23 UTC </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:07:23 UTC\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "26af60db6de2448ea88a16785c36517d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:07:31 UTC </span>Loading simulation from data/optical_yagi_uda.hdf5                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:07:31 UTC\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from data/optical_yagi_uda.hdf5                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data = web.run(\n",
    "    sim,\n",
    "    task_name=\"plasmonic_yagi_uda_on_glass\",\n",
    "    path=\"data/optical_yagi_uda.hdf5\",\n",
    "    verbose=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6918092c",
   "metadata": {},
   "source": [
    "After the simulation is complete, we calculate the directivity in the same way as previously. Note that the intrinsic impedance $\\eta=\\eta_0/n$ is different in the glass ($n=1.5$) compared to in the free space ($n=1$). \n",
    "\n",
    "From the directivity plot, we can see that a directivity close to 25 can be achieved in this case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "210e80f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P0 = np.array(sim_data[\"power\"].flux)  # total radiated power\n",
    "\n",
    "# evaluate the radiated power at 7*lda0 away from the antenna\n",
    "P = np.zeros(len(theta_array))\n",
    "for i, theta in enumerate(theta_array):\n",
    "    Ex = sim_data[\"field\"].Ex.sel(x=d * np.sin(theta), z=d * np.cos(theta), method=\"nearest\")\n",
    "    Ey = sim_data[\"field\"].Ey.sel(x=d * np.sin(theta), z=d * np.cos(theta), method=\"nearest\")\n",
    "    Ez = sim_data[\"field\"].Ez.sel(x=d * np.sin(theta), z=d * np.cos(theta), method=\"nearest\")\n",
    "    if d * np.cos(theta) > 0:\n",
    "        P[i] = (d**2 * (abs(Ex) ** 2 + abs(Ey) ** 2 + abs(Ez) ** 2) / (2 * Z0)).item()\n",
    "    else:\n",
    "        # inside the substrate, the impedance of the glass needs to be taken into account\n",
    "        P[i] = (n_glass * d**2 * (abs(Ex) ** 2 + abs(Ey) ** 2 + abs(Ez) ** 2) / (2 * Z0)).item()\n",
    "\n",
    "D = 4 * np.pi * P / P0  # directivity\n",
    "\n",
    "# plotting the directivity pattern\n",
    "fig, ax = plt.subplots(subplot_kw={\"projection\": \"polar\"})\n",
    "ax.set_theta_direction(-1)\n",
    "ax.set_theta_offset(np.pi / 2.0)\n",
    "ax.plot(theta_array, D)\n",
    "ax.set_rlim(0, 25)\n",
    "ax.set_title(\"Directivity\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0fac2e64",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "applications": [
   "Optical scattering and far-field radiation",
   "Nanophotonics",
   "Quantum emitters",
   "Plasmonics"
  ],
  "description": "This notebook demonstrates how to model a plasmonic Yagi-Uda nanoantenna in Tidy3D FDTD.",
  "feature_image": "./img/yagi_uda_antenna_schematic_2.png",
  "features": [
   "Far field projection"
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "plasmonic Yagi-Uda nanoantenna, directivity, Tidy3D, FDTD",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.2"
  },
  "title": "Plasmonic Yagi-Uda Nanoantenna | Flexcompute",
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "03ddabd9bd3d43dfab3aa8fad46cf074": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "063ec8a4c86d474f9f763f59f3f79b46": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_fac131eb18db48109450ae547d18d5e7",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">42.5/42.5 MB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">3.9 MB/s</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m42.5/42.5 MB\u001b[0m • \u001b[31m3.9 MB/s\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "18572846cfb54176a481ec7b345f44c1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "1d4b79c9c6be4d57a99aa83766402b4f": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_6bcc4beef8c645a6bac1f1e222c3375a",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">🚶 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'plasmonic_yagi_uda'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m🚶 \u001b[0m \u001b[1;32mStarting 'plasmonic_yagi_uda'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "288850be79fe463e8fe0f0f3b15463b2": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_ab260eaf6a1d4507875bac08d4327786",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">23.1/23.1 MB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">4.1 MB/s</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m23.1/23.1 MB\u001b[0m • \u001b[31m4.1 MB/s\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "28f36e635f914be2b0ff19c89147154f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "3272c5062ba6478bba12bbfe2503d04d": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_3d319b8894334e83acec1609a73821f0",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">🚶 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Finishing 'empty'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m🚶 \u001b[0m \u001b[1;32mFinishing 'empty'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "3d319b8894334e83acec1609a73821f0": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "40c5504fab574eeca001bac5e2850cde": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "47f000bec52747c5aa0585c9767dd3fb": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_895ffe3818f8481a9342c60aac49c11e",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">🏃 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'plasmonic_yagi_uda_on_glass'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m🏃 \u001b[0m \u001b[1;32mStarting 'plasmonic_yagi_uda_on_glass'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "4a45453e8a76432db800762c7ef86132": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_6a5ac57440974178999c5cc98dd8a211",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">2.2/2.2 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m2.2/2.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "4e31fcc01fb340a289b77b9b3f2a0d3c": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_970e2f37538842d6a2022b5e143308c9",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">1.1/1.1 MB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">3.0 MB/s</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m1.1/1.1 MB\u001b[0m • \u001b[31m3.0 MB/s\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "541159f7adca4e57b7c788b49e76fe3e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "591edb011b704284a2677a0bd95a0a4d": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_ec4b0802e51f4ac59d6d856f982d37a1",
       "msg_id": "",
       "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\">solver progress (field decay = 1.16e-05) <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "solver progress (field decay = 1.16e-05) \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "626a9ce51e63470d893a93173512b719": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_7c7faf72ed8642a48571e84aa6082b22",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">🏃 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Finishing 'plasmonic_yagi_uda'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m🏃 \u001b[0m \u001b[1;32mFinishing 'plasmonic_yagi_uda'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "6a5ac57440974178999c5cc98dd8a211": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "6bcc4beef8c645a6bac1f1e222c3375a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "6dc0eb981d904a56a47d686f3456f58a": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_719a32ca4c3b48b98ff98cb0788fe2eb",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">5.3/5.3 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m5.3/5.3 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "719a32ca4c3b48b98ff98cb0788fe2eb": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "7c7faf72ed8642a48571e84aa6082b22": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "7d500296a8114f0b8049fe7ee1dd81ed": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_f08da24f623641cf9ab151499ae52f6a",
       "msg_id": "",
       "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\">solver progress (field decay = 1.27e-06) <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "solver progress (field decay = 1.27e-06) \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "880b9b14b2b84ac4ba13ee2bc064555b": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_18572846cfb54176a481ec7b345f44c1",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">🚶 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Finishing 'plasmonic_yagi_uda'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m🚶 \u001b[0m \u001b[1;32mFinishing 'plasmonic_yagi_uda'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "895ffe3818f8481a9342c60aac49c11e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "8c77040efc5442df9a2691b0e95e9a0e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "8f985a7d5de843dd95f05765c9c17b4a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "970e2f37538842d6a2022b5e143308c9": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "a35b8dc342224e73880f8da9ecc90368": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_40c5504fab574eeca001bac5e2850cde",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">🏃 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Finishing 'plasmonic_yagi_uda_on_glass'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m🏃 \u001b[0m \u001b[1;32mFinishing 'plasmonic_yagi_uda_on_glass'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "a7f1d04e89fd4bb4adf03b0731a2fb2e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "a980579a9d89450aab5d8bddc1046fbc": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_541159f7adca4e57b7c788b49e76fe3e",
       "msg_id": "",
       "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\">Best RMS error: 0.0184 <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "Best RMS error: 0.0184 \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "ab260eaf6a1d4507875bac08d4327786": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "af2eea783c3a4a63be90f90e63ec818d": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_8c77040efc5442df9a2691b0e95e9a0e",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">1.8/1.8 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m1.8/1.8 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "b6988600a2ec4f50a803a03b043d5d2c": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_03ddabd9bd3d43dfab3aa8fad46cf074",
       "msg_id": "",
       "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\">solver progress (field decay = 0.00e+00) <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "solver progress (field decay = 0.00e+00) \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "cb5fe3efb90048a19ff682fa4cd6cdb4": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_8f985a7d5de843dd95f05765c9c17b4a",
       "msg_id": "",
       "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\">solver progress (field decay = 4.67e-01) <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "solver progress (field decay = 4.67e-01) \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "cb995242275d470aa6c5855695728a97": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_28f36e635f914be2b0ff19c89147154f",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">4.4/4.4 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m4.4/4.4 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "dac13ede3900420ca982c8149249e0f1": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_e70abba83c4643f6bbe40f657202d078",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">🏃 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'plasmonic_yagi_uda'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m🏃 \u001b[0m \u001b[1;32mStarting 'plasmonic_yagi_uda'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "dbd9fc619ddb42418f70571077ef6a80": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_eae4c6a6db854af68c4f898b28c7809a",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">1.0/1.0 MB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">1.7 MB/s</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m1.0/1.0 MB\u001b[0m • \u001b[31m1.7 MB/s\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "df40ff8aff9041dc94501b053f5115a6": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_a7f1d04e89fd4bb4adf03b0731a2fb2e",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">🚶 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'empty'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m🚶 \u001b[0m \u001b[1;32mStarting 'empty'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "e70abba83c4643f6bbe40f657202d078": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "eae4c6a6db854af68c4f898b28c7809a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "ec4b0802e51f4ac59d6d856f982d37a1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "f08da24f623641cf9ab151499ae52f6a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "fac131eb18db48109450ae547d18d5e7": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}