{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "60244b2c",
   "metadata": {},
   "source": [
    "# Band structure calculation of a photonic crystal slab\n",
    "\n",
    "In this notebook, we simulate a photonic crystal slab consisting of a square lattice of air holes in a dielectric slab. Our goal is to compute the band structure of this photonic crystal slab, as found in:\n",
    "\n",
    "> Shanhui Fan and J. D. Joannopoulos, \"Analysis of guided resonances in photonic crystal slabs,\" Phys. Rev. B 65, 235112 (2002).\n",
    "\n",
    "To this end, we excite the structure with several `PointDipole` sources, and we measure the response with several `FieldTimeMonitor` monitors. We excite modes with a fixed Bloch wavevector by using Bloch boundary conditions. We then use the `ResonanceFinder` to find the resonant frequencies. By sweeping the Bloch wavevector, we obtain the full band structure of the photonic crystal slab.\n",
    "\n",
    "See also the api reference for `ResonanceFinder` [here](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.resonance.ResonanceFinder.html).\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. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "193cb096",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:06:12.631685Z",
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     "shell.execute_reply": "2023-08-18T17:06:13.969348Z"
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   "source": [
    "# standard python imports\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import xarray as xr\n",
    "\n",
    "import tidy3d as td\n",
    "from tidy3d import web\n",
    "from tidy3d.plugins.resonance import ResonanceFinder\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6022fa5a",
   "metadata": {},
   "source": [
    "We will randomly position our sources and monitors. Here, we seed the random number generator to guarantee reproducible results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "be1a51fc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:06:13.972640Z",
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     "shell.execute_reply": "2023-08-18T17:06:13.990058Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "rng = np.random.default_rng(12345)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b3da68c",
   "metadata": {},
   "source": [
    "Now we define the parameters for the simulation, structure, sources, and monitors.\n",
    "\n",
    "We take the dipole polarization to be `Hz` and the symmetry to be `(0,0,1)` in order to excite only modes which are even with respect to the xy mirror plane."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "da1f5f85",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:06:13.992634Z",
     "iopub.status.busy": "2023-08-18T17:06:13.992460Z",
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     "shell.execute_reply": "2023-08-18T17:06:14.012192Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total runtime = 6.74 ps\n"
     ]
    }
   ],
   "source": [
    "# Simulation parameters\n",
    "runtime_fwidth = 200.0  # in units of 1/frequency bandwidth of the source\n",
    "t_start_fwidth = 5.0  # time to start monitoring after source has decayed, units of 1/frequency bandwidth\n",
    "dPML = 1.0  # space between PhC slabs and PML, in unit of longest wavelength of interest\n",
    "\n",
    "# Structure parameters (um)\n",
    "a_lattice = 1  # lattice constant \"a\"\n",
    "r_hole = 0.2 * a_lattice  # radius of the air holes\n",
    "t_slab = 0.5 * a_lattice  # slab thickness\n",
    "ep_slab = 12  # dielectric constant of the slab\n",
    "ep_hole = 1  # dielectric constant of the holes\n",
    "\n",
    "# Frequency range of interest (Hz)\n",
    "freq_range_unitless = np.array((0.1, 0.43))  # in units of c/a\n",
    "freq_scale = (\n",
    "    td.constants.C_0 / a_lattice\n",
    ")  # frequency scale determined by the lattice constant\n",
    "freq_range = freq_range_unitless * freq_scale\n",
    "lambda_range = (td.constants.C_0 / freq_range[1], td.constants.C_0 / freq_range[0])\n",
    "\n",
    "# Gaussian pulse parameters\n",
    "freq0 = np.sum(freq_range) / 2  # central frequency\n",
    "freqw = 0.3 * (freq_range[1] - freq_range[0])  # pulse width\n",
    "\n",
    "# Runtime\n",
    "run_time = runtime_fwidth / freqw\n",
    "print(f\"Total runtime = {(run_time*1e12):.2f} ps\")\n",
    "t_start = t_start_fwidth / freqw\n",
    "\n",
    "# Simulation size\n",
    "spacing = dPML * lambda_range[-1]  # space between PhC slabs and PML\n",
    "sim_size = Lx, Ly, Lz = (a_lattice, a_lattice, 2 * spacing + t_slab)\n",
    "\n",
    "# Number of k values to sample, per edge of the irreducible Brillouin zone\n",
    "Nk = 4\n",
    "\n",
    "# Number of dipoles and monitors\n",
    "num_dipoles = 7\n",
    "num_monitors = 2\n",
    "\n",
    "# Dipole polarization and symmetry\n",
    "polarization = \"Hz\"\n",
    "symmetry = (0, 0, 1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27c57eee",
   "metadata": {},
   "source": [
    "We define the materials and structures in terms of the above parameters. We take the photonic crystal slab to be lying in the xy plane. Because the photonic crystal slab is periodic in the x and y directions, we only need to simulate a single unit cell, containing the dielectric slab and a single air hole."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cbcc09f9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:06:14.015238Z",
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     "shell.execute_reply": "2023-08-18T17:06:14.035928Z"
    },
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   },
   "outputs": [],
   "source": [
    "mat_slab = td.Medium(permittivity=ep_slab, name=\"mat_slab\")\n",
    "mat_hole = td.Medium(permittivity=ep_hole, name=\"mat_hole\")\n",
    "\n",
    "slab = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=(0, 0, 0),\n",
    "        size=(td.inf, td.inf, t_slab),\n",
    "    ),\n",
    "    medium=mat_slab,\n",
    "    name=\"slab\",\n",
    ")\n",
    "\n",
    "hole = td.Structure(\n",
    "    geometry=td.Cylinder(\n",
    "        center=(0, 0, 0),\n",
    "        axis=2,\n",
    "        radius=r_hole,\n",
    "        length=t_slab,\n",
    "    ),\n",
    "    medium=mat_hole,\n",
    "    name=\"hole\",\n",
    ")\n",
    "\n",
    "structures = [slab, hole]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbda5f33",
   "metadata": {},
   "source": [
    "We will excite the photonic crystal slab with several `PointDipole` sources. Each dipole will have a random position and phase."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7cd6c4ed",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:06:14.038940Z",
     "iopub.status.busy": "2023-08-18T17:06:14.038764Z",
     "iopub.status.idle": "2023-08-18T17:06:14.065919Z",
     "shell.execute_reply": "2023-08-18T17:06:14.065387Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "dipole_positions = rng.uniform(\n",
    "    [-Lx / 2, -Ly / 2, 0], [Lx / 2, Ly / 2, 0], [num_dipoles, 3]\n",
    ")\n",
    "\n",
    "dipole_phases = rng.uniform(0, 2 * np.pi, num_dipoles)\n",
    "\n",
    "pulses = []\n",
    "dipoles = []\n",
    "for i in range(num_dipoles):\n",
    "    pulse = td.GaussianPulse(freq0=freq0, fwidth=freqw, phase=dipole_phases[i])\n",
    "    pulses.append(pulse)\n",
    "    dipoles.append(\n",
    "        td.PointDipole(\n",
    "            source_time=pulse,\n",
    "            center=tuple(dipole_positions[i]),\n",
    "            polarization=polarization,\n",
    "            name=\"dipole_\" + str(i),\n",
    "        )\n",
    "    )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "700880a7",
   "metadata": {},
   "source": [
    "We create `FieldTimeMonitors` to record the field as a function of time at several random locations within the photonic crystal slab. Crucially, we start the monitors after the source pulse has decayed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bc6dca60",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:06:14.068466Z",
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     "iopub.status.idle": "2023-08-18T17:06:14.241613Z",
     "shell.execute_reply": "2023-08-18T17:06:14.241062Z"
    },
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   },
   "outputs": [],
   "source": [
    "monitor_positions = rng.uniform(\n",
    "    [-Lx / 2, -Ly / 2, 0], [Lx / 2, Ly / 2, 0], [num_monitors, 3]\n",
    ")\n",
    "\n",
    "monitors_time = []\n",
    "for i in range(num_monitors):\n",
    "    monitors_time.append(\n",
    "        td.FieldTimeMonitor(\n",
    "            fields=[\"Hz\"],\n",
    "            center=tuple(monitor_positions[i]),\n",
    "            size=(0, 0, 0),\n",
    "            start=t_start,\n",
    "            name=\"monitor_time_\" + str(i),\n",
    "        )\n",
    "    )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6939eae",
   "metadata": {},
   "source": [
    "We will perform `3*Nk` different simulations, each with different Bloch boundary conditions, as we sweep the Bloch wavevector over the boundary of the irreducible Brillouin zone. We sweep over three lines, namely $\\Gamma X$, $XM$, and $M\\Gamma$. We use a PML in the z direction.\n",
    "\n",
    "Here, we simply define all of the boundary conditions we will use and put them into a single array."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "84ec0547",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:06:14.244042Z",
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     "shell.execute_reply": "2023-08-18T17:06:14.265543Z"
    },
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   },
   "outputs": [],
   "source": [
    "bspecs_gammax = []\n",
    "bspecs_xm = []\n",
    "bspecs_mgamma = []\n",
    "for i in range(Nk):\n",
    "    bspecs_gammax.append(\n",
    "        td.BoundarySpec(\n",
    "            x=td.Boundary.bloch((1 / 2) * i / Nk),\n",
    "            y=td.Boundary.periodic(),\n",
    "            z=td.Boundary.pml(),\n",
    "        )\n",
    "    )\n",
    "    bspecs_xm.append(\n",
    "        td.BoundarySpec(\n",
    "            x=td.Boundary.bloch(1 / 2),\n",
    "            y=td.Boundary.bloch((1 / 2) * i / Nk),\n",
    "            z=td.Boundary.pml(),\n",
    "        )\n",
    "    )\n",
    "    bspecs_mgamma.append(\n",
    "        td.BoundarySpec(\n",
    "            x=td.Boundary.bloch((1 / 2) * (1 - i / Nk)),\n",
    "            y=td.Boundary.bloch((1 / 2) * (1 - i / Nk)),\n",
    "            z=td.Boundary.pml(),\n",
    "        )\n",
    "    )\n",
    "bspecs = bspecs_gammax + bspecs_xm + bspecs_mgamma\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e80d5995",
   "metadata": {},
   "source": [
    "Now we define the simulations we want to run. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0c0a8a8a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:06:14.268679Z",
     "iopub.status.busy": "2023-08-18T17:06:14.268498Z",
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     "shell.execute_reply": "2023-08-18T17:06:14.328277Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "sims = {}\n",
    "for i in range(3 * Nk):\n",
    "    sims[f\"sim_{i}\"] = td.Simulation(\n",
    "        center=(0, 0, 0),\n",
    "        size=sim_size,\n",
    "        grid_spec=td.GridSpec.auto(),\n",
    "        structures=structures,\n",
    "        sources=dipoles,\n",
    "        monitors=monitors_time,\n",
    "        run_time=run_time,\n",
    "        shutoff=0,\n",
    "        boundary_spec=bspecs[i],\n",
    "        normalize_index=None,\n",
    "        symmetry=symmetry,\n",
    "    )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22ff9910",
   "metadata": {},
   "source": [
    "Let's check that the structure and source look correct. The source spectrum must fill the entire frequency range of interest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "443a41b7",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2023-08-18T17:06:15.090363Z"
    },
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   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, tight_layout=True, figsize=(10, 4))\n",
    "sims[\"sim_0\"].plot(z=0.0, ax=ax[0])\n",
    "sims[\"sim_0\"].plot(x=0, freq=freq0, ax=ax[1])\n",
    "plt.show()\n",
    "\n",
    "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(8, 4))\n",
    "plot_time = 5 / freqw\n",
    "ax1 = (\n",
    "    sims[\"sim_0\"]\n",
    "    .sources[0]\n",
    "    .source_time.plot(times=np.linspace(0, plot_time, 1001), val=\"abs\", ax=ax1)\n",
    ")\n",
    "ax1.set_xlim(0, plot_time)\n",
    "ax2 = (\n",
    "    sims[\"sim_0\"]\n",
    "    .sources[0]\n",
    "    .source_time.plot_spectrum(\n",
    "        times=np.linspace(0, sims[\"sim_0\"].run_time, 10001), val=\"abs\", ax=ax2\n",
    "    )\n",
    ")\n",
    "ax2.hlines(1.5e-15, freq_range[0], freq_range[1], linewidth=10, color=\"g\", alpha=0.4)\n",
    "ax2.legend((\"source spectrum\", \"measurement\"))\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7983aad",
   "metadata": {},
   "source": [
    "Now we run the simulations as a `Batch`.\n",
    "\n",
    "We set `verbose=True` to keep track of the status of the jobs in the `Batch`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "70058b88",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:06:15.093374Z",
     "iopub.status.busy": "2023-08-18T17:06:15.093227Z",
     "iopub.status.idle": "2023-08-18T17:08:27.948645Z",
     "shell.execute_reply": "2023-08-18T17:08:27.947959Z"
    }
   },
   "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\">10:32:45 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_0'</span> with task_id                                  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-c0a72a0d-28ff-4592-883d-50030bf85839'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:32:45 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_0'\u001b[0m with task_id                                  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-c0a72a0d-28ff-4592-883d-50030bf85839'\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-c0a72a0d-28ff-4592-883d-50030bf85839\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-c0a72a0d-28f</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c0a72a0d-28ff-4592-883d-50030bf85839\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">f-4592-883d-50030bf85839'</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=347470;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c0a72a0d-28ff-4592-883d-50030bf85839\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=411087;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c0a72a0d-28ff-4592-883d-50030bf85839\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=347470;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c0a72a0d-28ff-4592-883d-50030bf85839\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=284510;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c0a72a0d-28ff-4592-883d-50030bf85839\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=347470;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c0a72a0d-28ff-4592-883d-50030bf85839\u001b\\\u001b[32m-c0a72a0d-28f\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=347470;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c0a72a0d-28ff-4592-883d-50030bf85839\u001b\\\u001b[32mf-4592-883d-50030bf85839'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "94c045371af642939b74e244f22a50e0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:32:47 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_1'</span> with task_id                                  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-686c623f-3acd-4a21-90a8-35c049d842fe'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:32:47 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_1'\u001b[0m with task_id                                  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-686c623f-3acd-4a21-90a8-35c049d842fe'\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-686c623f-3acd-4a21-90a8-35c049d842fe\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-686c623f-3ac</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-686c623f-3acd-4a21-90a8-35c049d842fe\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">d-4a21-90a8-35c049d842fe'</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=575659;https://tidy3d.simulation.cloud/workbench?taskId=fdve-686c623f-3acd-4a21-90a8-35c049d842fe\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=67224;https://tidy3d.simulation.cloud/workbench?taskId=fdve-686c623f-3acd-4a21-90a8-35c049d842fe\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=575659;https://tidy3d.simulation.cloud/workbench?taskId=fdve-686c623f-3acd-4a21-90a8-35c049d842fe\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=140403;https://tidy3d.simulation.cloud/workbench?taskId=fdve-686c623f-3acd-4a21-90a8-35c049d842fe\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=575659;https://tidy3d.simulation.cloud/workbench?taskId=fdve-686c623f-3acd-4a21-90a8-35c049d842fe\u001b\\\u001b[32m-686c623f-3ac\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=575659;https://tidy3d.simulation.cloud/workbench?taskId=fdve-686c623f-3acd-4a21-90a8-35c049d842fe\u001b\\\u001b[32md-4a21-90a8-35c049d842fe'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5b7ebaf3c5b14995bcfdf1a18b735628",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:32:49 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_2'</span> with task_id                                  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-948fdcb0-9da5-4dc0-99ae-3ea1f5bdcc2f'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:32:49 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_2'\u001b[0m with task_id                                  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-948fdcb0-9da5-4dc0-99ae-3ea1f5bdcc2f'\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-948fdcb0-9da5-4dc0-99ae-3ea1f5bdcc2f\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-948fdcb0-9da</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-948fdcb0-9da5-4dc0-99ae-3ea1f5bdcc2f\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">5-4dc0-99ae-3ea1f5bdcc2f'</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=721408;https://tidy3d.simulation.cloud/workbench?taskId=fdve-948fdcb0-9da5-4dc0-99ae-3ea1f5bdcc2f\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=767064;https://tidy3d.simulation.cloud/workbench?taskId=fdve-948fdcb0-9da5-4dc0-99ae-3ea1f5bdcc2f\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=721408;https://tidy3d.simulation.cloud/workbench?taskId=fdve-948fdcb0-9da5-4dc0-99ae-3ea1f5bdcc2f\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=152526;https://tidy3d.simulation.cloud/workbench?taskId=fdve-948fdcb0-9da5-4dc0-99ae-3ea1f5bdcc2f\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=721408;https://tidy3d.simulation.cloud/workbench?taskId=fdve-948fdcb0-9da5-4dc0-99ae-3ea1f5bdcc2f\u001b\\\u001b[32m-948fdcb0-9da\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=721408;https://tidy3d.simulation.cloud/workbench?taskId=fdve-948fdcb0-9da5-4dc0-99ae-3ea1f5bdcc2f\u001b\\\u001b[32m5-4dc0-99ae-3ea1f5bdcc2f'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "model_id": "6b9eaa75d3984e5db3f23f20b8e51ce4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:32:50 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_3'</span> with task_id                                  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-4db18d44-fbcf-479f-b9d3-4bba6aad61b4'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:32:50 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_3'\u001b[0m with task_id                                  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-4db18d44-fbcf-479f-b9d3-4bba6aad61b4'\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-4db18d44-fbcf-479f-b9d3-4bba6aad61b4\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-4db18d44-fbc</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-4db18d44-fbcf-479f-b9d3-4bba6aad61b4\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">f-479f-b9d3-4bba6aad61b4'</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=749212;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4db18d44-fbcf-479f-b9d3-4bba6aad61b4\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=84200;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4db18d44-fbcf-479f-b9d3-4bba6aad61b4\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=749212;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4db18d44-fbcf-479f-b9d3-4bba6aad61b4\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=419566;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4db18d44-fbcf-479f-b9d3-4bba6aad61b4\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=749212;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4db18d44-fbcf-479f-b9d3-4bba6aad61b4\u001b\\\u001b[32m-4db18d44-fbc\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=749212;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4db18d44-fbcf-479f-b9d3-4bba6aad61b4\u001b\\\u001b[32mf-479f-b9d3-4bba6aad61b4'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:32:52 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_4'</span> with task_id                                  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-f2352afa-b7a2-46c7-b6a0-18a6aeaa62bf'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:32:52 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_4'\u001b[0m with task_id                                  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-f2352afa-b7a2-46c7-b6a0-18a6aeaa62bf'\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-f2352afa-b7a2-46c7-b6a0-18a6aeaa62bf\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-f2352afa-b7a</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-f2352afa-b7a2-46c7-b6a0-18a6aeaa62bf\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">2-46c7-b6a0-18a6aeaa62bf'</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=88275;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f2352afa-b7a2-46c7-b6a0-18a6aeaa62bf\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=478651;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f2352afa-b7a2-46c7-b6a0-18a6aeaa62bf\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=88275;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f2352afa-b7a2-46c7-b6a0-18a6aeaa62bf\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=604539;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f2352afa-b7a2-46c7-b6a0-18a6aeaa62bf\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=88275;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f2352afa-b7a2-46c7-b6a0-18a6aeaa62bf\u001b\\\u001b[32m-f2352afa-b7a\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=88275;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f2352afa-b7a2-46c7-b6a0-18a6aeaa62bf\u001b\\\u001b[32m2-46c7-b6a0-18a6aeaa62bf'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3e01a0a3fda3452ba319c4cfd7b9316a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:32:53 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_5'</span> with task_id                                  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-ac7c9002-6841-4a84-ac76-a179805c7c09'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:32:53 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_5'\u001b[0m with task_id                                  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-ac7c9002-6841-4a84-ac76-a179805c7c09'\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-ac7c9002-6841-4a84-ac76-a179805c7c09\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-ac7c9002-684</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-ac7c9002-6841-4a84-ac76-a179805c7c09\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">1-4a84-ac76-a179805c7c09'</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=275260;https://tidy3d.simulation.cloud/workbench?taskId=fdve-ac7c9002-6841-4a84-ac76-a179805c7c09\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=533879;https://tidy3d.simulation.cloud/workbench?taskId=fdve-ac7c9002-6841-4a84-ac76-a179805c7c09\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=275260;https://tidy3d.simulation.cloud/workbench?taskId=fdve-ac7c9002-6841-4a84-ac76-a179805c7c09\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=327426;https://tidy3d.simulation.cloud/workbench?taskId=fdve-ac7c9002-6841-4a84-ac76-a179805c7c09\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=275260;https://tidy3d.simulation.cloud/workbench?taskId=fdve-ac7c9002-6841-4a84-ac76-a179805c7c09\u001b\\\u001b[32m-ac7c9002-684\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=275260;https://tidy3d.simulation.cloud/workbench?taskId=fdve-ac7c9002-6841-4a84-ac76-a179805c7c09\u001b\\\u001b[32m1-4a84-ac76-a179805c7c09'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "16fbd3ed970a4e01bc6459be99bfcd7f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:32:55 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_6'</span> with task_id                                  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-3366543d-e1c2-4335-9944-d31b6fa369b0'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:32:55 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_6'\u001b[0m with task_id                                  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-3366543d-e1c2-4335-9944-d31b6fa369b0'\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-3366543d-e1c2-4335-9944-d31b6fa369b0\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-3366543d-e1c</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-3366543d-e1c2-4335-9944-d31b6fa369b0\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">2-4335-9944-d31b6fa369b0'</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=662536;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3366543d-e1c2-4335-9944-d31b6fa369b0\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=515915;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3366543d-e1c2-4335-9944-d31b6fa369b0\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=662536;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3366543d-e1c2-4335-9944-d31b6fa369b0\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=918266;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3366543d-e1c2-4335-9944-d31b6fa369b0\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=662536;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3366543d-e1c2-4335-9944-d31b6fa369b0\u001b\\\u001b[32m-3366543d-e1c\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=662536;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3366543d-e1c2-4335-9944-d31b6fa369b0\u001b\\\u001b[32m2-4335-9944-d31b6fa369b0'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f99080ace7594902ac79ac462f4ab194",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:32:56 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_7'</span> with task_id                                  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-4b425659-89c6-4f0f-a9a8-5f82b141a547'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:32:56 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_7'\u001b[0m with task_id                                  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-4b425659-89c6-4f0f-a9a8-5f82b141a547'\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-4b425659-89c6-4f0f-a9a8-5f82b141a547\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-4b425659-89c</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-4b425659-89c6-4f0f-a9a8-5f82b141a547\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">6-4f0f-a9a8-5f82b141a547'</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=347021;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4b425659-89c6-4f0f-a9a8-5f82b141a547\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=784725;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4b425659-89c6-4f0f-a9a8-5f82b141a547\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=347021;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4b425659-89c6-4f0f-a9a8-5f82b141a547\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=436942;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4b425659-89c6-4f0f-a9a8-5f82b141a547\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=347021;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4b425659-89c6-4f0f-a9a8-5f82b141a547\u001b\\\u001b[32m-4b425659-89c\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=347021;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4b425659-89c6-4f0f-a9a8-5f82b141a547\u001b\\\u001b[32m6-4f0f-a9a8-5f82b141a547'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7492c4f437dd49c4b2c3332a3d32ebce",
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:32:58 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_8'</span> with task_id                                  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-414b3dc7-e849-4f35-9b65-8f549365df22'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:32:58 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_8'\u001b[0m with task_id                                  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-414b3dc7-e849-4f35-9b65-8f549365df22'\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-414b3dc7-e849-4f35-9b65-8f549365df22\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-414b3dc7-e84</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-414b3dc7-e849-4f35-9b65-8f549365df22\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">9-4f35-9b65-8f549365df22'</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=164269;https://tidy3d.simulation.cloud/workbench?taskId=fdve-414b3dc7-e849-4f35-9b65-8f549365df22\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=675971;https://tidy3d.simulation.cloud/workbench?taskId=fdve-414b3dc7-e849-4f35-9b65-8f549365df22\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=164269;https://tidy3d.simulation.cloud/workbench?taskId=fdve-414b3dc7-e849-4f35-9b65-8f549365df22\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=173087;https://tidy3d.simulation.cloud/workbench?taskId=fdve-414b3dc7-e849-4f35-9b65-8f549365df22\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=164269;https://tidy3d.simulation.cloud/workbench?taskId=fdve-414b3dc7-e849-4f35-9b65-8f549365df22\u001b\\\u001b[32m-414b3dc7-e84\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=164269;https://tidy3d.simulation.cloud/workbench?taskId=fdve-414b3dc7-e849-4f35-9b65-8f549365df22\u001b\\\u001b[32m9-4f35-9b65-8f549365df22'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "27168a1679ff4b3cb40c3c99754e4a10",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:32:59 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_9'</span> with task_id                                  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-48663d55-7ce3-4131-ae50-e8297750ff76'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:32:59 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_9'\u001b[0m with task_id                                  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-48663d55-7ce3-4131-ae50-e8297750ff76'\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-48663d55-7ce3-4131-ae50-e8297750ff76\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-48663d55-7ce</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-48663d55-7ce3-4131-ae50-e8297750ff76\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">3-4131-ae50-e8297750ff76'</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=93163;https://tidy3d.simulation.cloud/workbench?taskId=fdve-48663d55-7ce3-4131-ae50-e8297750ff76\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=48857;https://tidy3d.simulation.cloud/workbench?taskId=fdve-48663d55-7ce3-4131-ae50-e8297750ff76\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=93163;https://tidy3d.simulation.cloud/workbench?taskId=fdve-48663d55-7ce3-4131-ae50-e8297750ff76\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=346013;https://tidy3d.simulation.cloud/workbench?taskId=fdve-48663d55-7ce3-4131-ae50-e8297750ff76\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=93163;https://tidy3d.simulation.cloud/workbench?taskId=fdve-48663d55-7ce3-4131-ae50-e8297750ff76\u001b\\\u001b[32m-48663d55-7ce\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=93163;https://tidy3d.simulation.cloud/workbench?taskId=fdve-48663d55-7ce3-4131-ae50-e8297750ff76\u001b\\\u001b[32m3-4131-ae50-e8297750ff76'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cc25424306c54549aadc99402ba7549e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:33:01 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_10'</span> with task_id                                 \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-fb4ca11f-4322-4c7c-96cc-31cc6c0668d1'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:33:01 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_10'\u001b[0m with task_id                                 \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-fb4ca11f-4322-4c7c-96cc-31cc6c0668d1'\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-fb4ca11f-4322-4c7c-96cc-31cc6c0668d1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-fb4ca11f-432</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-fb4ca11f-4322-4c7c-96cc-31cc6c0668d1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">2-4c7c-96cc-31cc6c0668d1'</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=586217;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fb4ca11f-4322-4c7c-96cc-31cc6c0668d1\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=277602;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fb4ca11f-4322-4c7c-96cc-31cc6c0668d1\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=586217;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fb4ca11f-4322-4c7c-96cc-31cc6c0668d1\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=937615;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fb4ca11f-4322-4c7c-96cc-31cc6c0668d1\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=586217;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fb4ca11f-4322-4c7c-96cc-31cc6c0668d1\u001b\\\u001b[32m-fb4ca11f-432\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=586217;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fb4ca11f-4322-4c7c-96cc-31cc6c0668d1\u001b\\\u001b[32m2-4c7c-96cc-31cc6c0668d1'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7cd930b9ae954aad940c33a23df77f2c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:33:02 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_11'</span> with task_id                                 \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-9ffca0b0-59bc-4ded-bd95-de6d9ff24499'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:33:02 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_11'\u001b[0m with task_id                                 \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-9ffca0b0-59bc-4ded-bd95-de6d9ff24499'\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-9ffca0b0-59bc-4ded-bd95-de6d9ff24499\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-9ffca0b0-59b</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-9ffca0b0-59bc-4ded-bd95-de6d9ff24499\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">c-4ded-bd95-de6d9ff24499'</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=354462;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9ffca0b0-59bc-4ded-bd95-de6d9ff24499\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=514146;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9ffca0b0-59bc-4ded-bd95-de6d9ff24499\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=354462;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9ffca0b0-59bc-4ded-bd95-de6d9ff24499\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=291852;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9ffca0b0-59bc-4ded-bd95-de6d9ff24499\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=354462;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9ffca0b0-59bc-4ded-bd95-de6d9ff24499\u001b\\\u001b[32m-9ffca0b0-59b\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=354462;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9ffca0b0-59bc-4ded-bd95-de6d9ff24499\u001b\\\u001b[32mc-4ded-bd95-de6d9ff24499'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ee8d17697ab54e9c86133a6f4951e11a",
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:33:14 -03 </span>Started working on Batch.                                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:33:14 -03\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch.                                          \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\">10:33:24 -03 </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.300</span> for the whole batch.                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:33:24 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.300\u001b[0m for the whole batch.                \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>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after the\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Batch has completed.                                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after the\n",
       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "efe3592991d846b080063174828c91e8",
       "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\">10:35:57 -03 </span>Batch complete.                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:35:57 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# initialize a batch and run them all\n",
    "batch = td.web.Batch(simulations=sims, verbose=True)\n",
    "\n",
    "# run the batch and store all of the data in the `data/` dir.\n",
    "batch_data = batch.run(path_dir=\"data\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c865c155",
   "metadata": {},
   "source": [
    "Now that the simulations are complete, we can analyze the data. Let's first look at one of the FieldTimeMonitors to make sure the source has decayed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4a97628f-c2d1-4e2f-82f2-ba97d88fe48e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:08:28.235611Z",
     "iopub.status.busy": "2023-08-18T17:08:28.235460Z",
     "iopub.status.idle": "2023-08-18T17:08:29.381759Z",
     "shell.execute_reply": "2023-08-18T17:08:29.381250Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "766aa64a3ee44d60bc27773bc460bb36",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:38:08 -03 </span>loading simulation from                                            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">686c623f-3acd-4a21-90a8-35c049d842fe</span>.hdf5                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:38:08 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
       "\u001b[2;36m             \u001b[0mdata/fdve-\u001b[93m686c623f-3acd-4a21-90a8-35c049d842fe\u001b[0m.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>loading simulation from                                            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">686c623f-3acd-4a21-90a8-35c049d842fe</span>.hdf5                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
       "\u001b[2;36m             \u001b[0mdata/fdve-\u001b[93m686c623f-3acd-4a21-90a8-35c049d842fe\u001b[0m.hdf5                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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HMHToUAQGBkKhUGDJkiXVLtPcCDXcx7ZgwzH8eOAyhi5PqtHnEBERmSuLCktr1qxBbGwsFixYgNTUVISGhqJfv37IysoSvf727dsICgrCokWL4Ovra5QyzU1ND0c6n32rhp9ARERk3iwqLH3wwQeYOHEixo8fj7Zt22LFihVwdnbGV199JXp9586d8d5772HUqFFwcHAwSpnm5vJ/d2q0fAUUNVo+ERGRubOYsFRcXIyUlBTExMSojimVSsTExCApqWpdRDVRZm2bt/6oXtdtOHRV8lzKxf8Q+fZWbDp8TeucglmJiIjqOIsJS9nZ2SgtLYWPj4/GcR8fH2RkZNRqmUVFRcjLy9P4Mncv/nBQ8tyEr/cjM68IUxJStc4xKxERUV1nMWHJnMTFxcHd3V315e/vb+oqVUvJ3TJTV4GIiMhsWUxYatiwIWxsbJCZmalxPDMzU3Lwdk2VOXv2bOTm5qq+Ll26VKXn6yIIAg5dykFB0d0aKb+Cgn1tREREkiwmLNnb2yMsLAyJiYmqY2VlZUhMTERUVFStlung4AA3NzeNr5qw4dBVPLpsNx77dHeNlK8XBikiIqrjbE1dAUPExsZi7NixCA8PR0REBJYsWYKCggKMHz8eADBmzBg0btwYcXFxAMoHcB8/flz1/ZUrV5CWlgYXFxe0aNFCrzJN6ZfUKwCA05mmm77PqERERHWdRYWlkSNH4vr165g/fz4yMjLQsWNHbN68WTVAOz09HUrl/cayq1evolOnTqqfFy9ejMWLF6NXr17YsWOHXmWaUm016jAQERERSbOosAQAU6dOxdSpU0XPVQSgCoGBgXqtcC1XpinVWohRe9Clm7fh7+l8/5SelbhTXApHOyXHPxERkdWxmDFLVDs2VlprSZ/oc+JaHtrM34xXfjpcM5UiIiIyIYYlC1RaVnObnAhV2EBlxc5zAICfUi4buzpEREQmx7BkxqS6tBZs0G/Vbr2fo/Z95V7L1PQcg+4nIiKyNgxLZkwqhHy3N71K5ZVJtEhJhTJ913fiOCUiIrJmDEt1yO5z2QZdr2+HHKMSERFZM4YlM2bsBpvCEsO2NWEIIiIiYlgyc8aNK1LLKEiFMr3DGlMVERFZMYYl0hjUrc+6VJUpmJaIiMiKWdyilHVJdbrh9v57Q+tY5Rh0JecOui3apnmN2kX6hqCfU7lkABERWS+2LJmxKjTyqIz9KllnedN+OChbRlXC2sUbBYbfREREZMYYlqyUeNDSPHihBoJNr/d2GL1MIiIiU2JYshAJ+9Jxp7hU8vwHW07jpTVp98ccibQKaQco7YuMsTZ4Rm6hEUohIiIyDwxLFmLOuiMYsmy35PmliWew7uAV1YrbYj1olYOQod1subdL9LqusEQ61BEREVkahiULciozX+c1RdUMKpoz4zTPfbj1tH5lVKsGRERE5oVhycpU7Ggi1mpUOfwYOn77en5RlepERERkyRiWrJTYtH+hUpuPaKCSaRcq03N6XlXWaiIiIjJXDEtWRi7saLcsaacl9WOVy/rjaAY2H83Qow5ERETWg2HJyggy3XDG8Nx3KXrXgYiIyBowLFmYlbvOyZ5Purdyt1hWqhygaipQERERWROGJbOm3UTz9u8nZe9YvkM+TKmruawk3bT0+5Fr+HzXvzX2ZCIiImPj3nBWSmGEZqOqdqfJ3Tf5+1QAQNcWDdDOz71qDxCRmv4fCotL0bVFQ6OVSUREBLBlyWrpMyPNGIFK9Nl6XHPjVrHWsSs5d6o0k04QBDz+6R488cU+XM25Y/D9REREchiWzFrtDyoyRn7Sp4jKkejzXf+i26JtWLRZvptRl5gPdlbrfiIiosoYlsyaaaeV1ebT/+/3EwCAz3ZWbzzTbZn984iIiKqCYakOEVtXyVSMuXClvkWdzbqFffdmCxIREemLYakOkVuw0pgy83Rvi1KVmtwuvotvky7gWm7VxiXFfLATI1fuxfnsgirdT0REdRPDEhndU1/u032RWlr6+8x1zVMSTUVvbTqBeb8ew5Blu6tTPfyccrla9xMRUd3CsGSlxOKGod1wxugqe2fzSQxdvgdFd0tx7vqt+2Wr1fDpL5M17vnnbLZoWTtPlYeqyi1Xhtbyk+1nDbyDiIjqMq6zRDWqYpHMl9ak4fcj9/eVk8th57ML0KOlV01XjYiISC9sWTJj1WnYMZ+h3OXUgxIg/9qkznF7FiIiMgWGJZJUk8PBqxJ8pO4x5sw6XQRBwJnMfJSWcbdgIqK6gmHJjFWnJcUaP8rNYemDz//+Fw99uAszfzps6qoQEVEtYVgyY/o2mCz6w7BVr7NvFWHy9ym4IrI1iHocqcUGGw2VW4ruFJfi6z0XJLcyKS4tq41qAQA+2noGAPBzKmfUERHVFRzgbQVW7Dxn0PWv/3ZcawxRBfWYMuPHQ9Wolbw7JfqvtP3O5pNYteeC5Plnv00xQo30U8AVwomI6hy2LNVB+m42u/VEZo3VYWrCQQBA7p0SnddKLSVQ4e8z8ufFiK21VFhSii/+/hebj14TvefSzdsGP4eIiCwfW5bMWE3N/pIrVq9NcAUBCiNVbs66I9rl61GnwpJSONrZVPm57/15CkPDmqh+/nzXv6r96QBg3eSu6NS0vsY9GXmFVX4eERFZLrYsmTFTjBk6mZmv85odp6/rvEZfu3W0GgHAhRva25PIdcsV6tHFV3nrF/WgBABHr+Rq3WOMePjjgUtYsvW0EUoiIqLawrBUh1Q0Bsk1Cm06LN4Fpe6vY+LjnYyttEzAuoOXUVKqnRozcqVbeT4UCSO3i+9q/Kw+8z+/ULsrUHQFdCOkpZk/HcaSrWdEwxgREZkndsORwcqMOPlMLn98k3QBr/923OAyD17M0Tr24g8HNX6+nn9/y5Q5647qVe4PyZcMrouUnNu6x2oREZF5YMsSGaxyF5bRy79XfOKJLMlryu5dlJWv3cJUJtJ/uVWkrPQb5QO2xVrKxLpAfzLiBryHLucYrSwiIqpZDEtWqibHO+lbdkUYMbj8e/+V6/aqqMOybVXfFDe/qETyOWKBS+uaaqzi/d6fp6p8LxER1S6GpTqouithl6oFCbltP8avSq7Wc+RUhJlSkVBz4OJ/epVRcWtV348Nh66KHr+QXYBBS//GxsPi53W5casIZ/QYaE9ERLWDYcmMWcKWJbN+lt7249x17VlshtBneQKpoHNHj8UjVWFJpIjKGSxPZBD46UqBpqxMwL5/byB68Q4cu5qnWkvKUGFvbcVDH+7C+ezqvX9ERGQcDEt1kR4NKXKb06oHlLXVHMcjF4h2ySxRoCtH6bNCeMXYK7GiKr/6N/QYaP7jgUsYuXKvzuv0lSrSQnYt9w62n8qq1c2DiYjqOoYlEiU3uNocyLUKAZpjjr7657xsGWLe3HgcQ5btRvHd8ql/hy7laN9f6edf0+S73Q7rMah72fb7Y7DExk1FxW3D+Pj9+Ot4za2uTkREmhiWzFgNLeCtl3VpV0z2bENaTaTeI/Wg8cZG8Vah+wPJxUtJu5SDHaey7l2juy5J/96QPf/IJ7t1lqE+8Lvyu6C+2Ob7f8kPEL9dfBcZuYVsgSIiMgKGJTNWnY85uen9yedv6rzflEFNH/cX2JSoqQFvntxrlZsVp35Kn1XDDVV58PyiP06qvj+deQv/SOyJt+nwNbSd/ye6xCVWaZ0qIiLSxLBUhxgSgOTGEv2cehkHLugOXKb0hUTXm6HkZsypB1KpTFV55XBDzP5Fc9+8zUc114N66st9WvdsPnoNUxJSVT+LbQuTlVdY5WUdiIjqIoYlKyX24a7PoOf798sbtiLJwBpV7Tm63CoSDyMrd/2rfx3k1nOSu0YtIGVKbLL76fZzkmXv1dFtB5QvQ1BBqceb9aUeITHi7UT0fG87cmVWEd/77w38bMRFOImILBnDUh0S++Mhva81xj5oVfWuAQs2GnNVbUNVZKW995YLEHMl547k/ZVbjsREL96hap2qzlIKYi79J966tOnwNYxauRcz1h7Ckcvcw46IiGHJStX0liQ1qfhuGc5m3ZK95ru96bVSF33GR3+796LkuYoxT3dLtTfU03cdpbT0HADiAbakcrkGhNw1+8X3ulPvxpMKVEREdQnDkhUqKS1DYUn1drtV1lLTktRjYj7YWePPzlbbTFcXsVadiiObDl+TvC/vTnlXl9R6VJfvhZFDl3IQOGuT6DVyXYFrD2iWK9pbKJH4vt17EYGzNsl2B0p1LxIR1SUMS2asqtO+95zTPRZGF32iUsUaRFVVnb3VAJFWlUpybherwoiYZ745oPMZqenlC0OKvR9/imzAW9n2U+ULa26QWIOp6N57KDZYu4LcH4ObBZqB71qudrjZdOR+mPtNZIuWUTILacrNpvsm6QKe+zZF9M/BpZu3ZbfCISKyJAxLVkhuuntWvvFaCn6t5lpMCcnV60p7VWarFQDo+MYWdH9nu85y8gqlZ6xVDJg+fi1P69wFA2aUSa3BdONWMQAgX6YOFV2qpaXav1f1X3VJaRnSb2rXSb3l6IUfDN+C5UeR7rrSMgHzfz2Gzccy8E3SBY1zvx26ih7vbsczX+/XGWjX7E/HjwfEuwOJiMwFw5IZ02dAr5iKrh8xEf+XqOfDdV9iyOw6MXPXH0X2vbBQFb+kVn/hzJzbup+fL7IvXIWbBdW7f8RnumcVlgnlQeiqSKvR+1tOq1YXl/p9GNLAs+es9tpNMyuF0m0nM9F8zu+qn9/adELj/Ge7ymcAbj91HS1f+wPxu8Vn6OXeLsGrPx/BzJ8Oo0BiViMRkTlgWLJC01anmboKFuN0pvxAcgDIkZliP+Hr/Trvf+Zr3d19cgRBkB0M/vjyPQCk860hvbmVNweuULGR8JWcO/jfKu3Xo95lXHlGnlRXXuHd++HuZIZ2y50+Lt28rdciq0RE1cGwZMbMfasKM6+eXqo7jv3gvZlqcvbp+DDXp2tUbo2lirFB0i2R5ef1WTdJqoyK2YkvqM2UU/fZvXWtBEHAkSu6lxsYH5+MyLfvt3IOXa7dwlZYUoobt+QH4fd4dztGfJaEo3o8k4ioqhiWSIu+A7ePX61aa4A50Scr1fTEQLmFK8ufr4CumhbdLZUMVBWhdsZa6XW2Ui6WB7r/JLolK8o4d128hatiKxapbtW0ShsRVwx8l6tP8LzNCHtrK3q9t110MoB6a9thrgdFRDWIYcmMVXXMUnUt2HBUr+vWyAzMFVtXyBzptdBjDf8exLYkURf3+wmdge3bpIu4kC0+4Hy1xHpK6pbvKA9sS7aekbiiovVKvhyp9b02HRafDSjm2NVcjZamizdu4/O/tVdkf1ptBuF7f57UOg+UL80Q+2Majl2VDlO3i+/WyN5+RGQ9GJbMmKm64X5IvlS9XXwBfJMkvVCjOdEnB5l68PHJjHyd3UxvbTqBgUv/rvIzdA0Crzgv93aVlJZJriCuXv4n26QCWbmpCdoz9uL+0A5Dl/+7vzr6fxLjyqYkHMQvqVcwaOk/oufPZt1C2/l/os38zdVeyoKIrBfDEtWINzZaxm73+rQZ9f1wV43XQ5fqDtrXtW1J5W6yym4V3cWnO85KhhIA2HYyS2dXIAAs/uu07LOkBrOrr5m1/VSWbBl3ikvxbdIF1UxBAMgQmU1YsfipIADFIq2hpWUCvt93EWezxAe+E1HdwLBE4ky4N1xtMlVXZ20b/Il4y0qFmwXF+LbSeknqxsfvx7ub5ffsuyuyDlSFrySWD1CnaxHLvDvlLXzZt4owPl57FuKle2tMCYKANvM3Y96vxzTOJ+y7KHq9nNX70/HauqOI+UA6MOcVluhVFhFZLoYlEnXyGv8lXddUDheGEiBg3q/S491+SE7HgQvSMwNX75dfpPSv4xm4VXRXckPoifdWZJfavDi70ppYPd7VXLB0aaJ29+Br6+6/HrHWuZ2nr6PDwr/Q493tkoEpM68Q/7fpOC7ouRcgEZkfhiUSJbZitTUy9+UZLMnus9n4/Yj0FjCzfzmCYSukF+H86p/zsit+L9l6Bu0X/In9EksxnMzIx93SMpRJFJGwLx377q1mLhbaPt1xf1bi3dIy3Ko0Vm3wJ/9ojWsa+1Wy6vsDF8XrFfl2Ij7/+zyGrdgjXjEiMnsMS1SnVawfRNX3Q3L1ti05d70A0e/t0Hmd3Mrxe87dkB3PNHLlXly8USAZ2g6m/4fiu2V4+ON/0H7Bn1rn1QNP5aA9b712y9zFG/dbk7JvFYuG8+/3XcRDH+zEVYkWMSIyPYYlM8Y2j5r3yk/y+8tR7ZLqQtPXW5uOY8EG+e7En2W2yXns0z14aU0aTmaId0Onpufg6JVcpN+4jWazf9c4d6vortYSBv9WWpfqwy2nNVrP/isoxmvrjuJM1i10XbRN9JmzfzmMwFmb8N1ey5hhSmSNLC4sLVu2DIGBgXB0dERkZCSSk5Nlr1+7di2Cg4Ph6OiIkJAQ/P675l9w48aNg0Kh0Pjq379/Tb4EIqoh+mxfIzY2Sd2mI9dkz7+x8bhqfFRly7afw/9WlQ8+v1V0F5O+1bxu6bazeENt+5fK++ol7EvHP2c09+eraLGbu/4oLt28rTUQXhAEZOYZb4NsItJmUWFpzZo1iI2NxYIFC5CamorQ0FD069cPWVnize579uzB6NGjMWHCBBw8eBBDhgzBkCFDcPSo5iDU/v3749q1a6qvH374oTZejk51Y54WkWVJPn8TpyT20APKl1BIv3Eb7Rf8iRKRGYLf7r2IrPxCvPrTYfycqrkFzZx1R/CU2mKblfV4dzue/TZF49iHW88g8u1EBM7ahA2HruL7fdotUF/9cx7bT8ovt0BE0hSCBY1wjYyMROfOnfHJJ58AAMrKyuDv748XXngBs2bN0rp+5MiRKCgowMaNG1XHunTpgo4dO2LFihUAyluWcnJysH79+irXKy8vD+7u7sjNzYWbm1uVy6lsfHyyzm0hiMjy+Lo5IkOmNWjuoDYYFdEUF7IL8PDH2ss+HJrfF+7OdgCAwFmbtM5vfzkazRrWK//+ZBbG32vt+mhUR2TkFmJ4uD8869mrri8rE6BUKnA2Kx+HL+fisU6N68yyGlS36fv5bVuLdaqW4uJipKSkYPbs2apjSqUSMTExSEoSH6yZlJSE2NhYjWP9+vXTCkY7duyAt7c36tevj969e+Ott95CgwYNJOtSVFSEoqL7G3zm5dXMzDGLSbFEZBC5oASUd89V7qJTt/ivU3jj0XaS46+GLNuNQwv6AoAqKAH3Fzf9+0w2vnsmEkD59jKVVzi3s1FicKif6uc/jlxDftFdjAj3l603kbWymLCUnZ2N0tJS+Pj4aBz38fHByZPi+0JlZGSIXp+RcX96c//+/fH444+jWbNmOHfuHObMmYMBAwYgKSkJNjY2ouXGxcXh9ddfr+YrIiKqmnUHr+BbmQHfuXdKIAgCCkvE11H452w2Ui7eRF7hXbz/l/Zioy/8cFAjLD3/fSoA4KcDl5F84SY+ezoM/dr5ipadfasId0sF+Lo7GvKSiMyaxYSlmjJq1CjV9yEhIejQoQOaN2+OHTt2oE+fPqL3zJ49W6PFKi8vD/7+/BcXEdWOymtAiak8W68y9c2K5axRWyw0+d76VM9+m4ILiwapju86fR0z1h5CSGN3bLs3Nuro6/3g4lD+EZNfWILMvEI0a+iCt38/gchmnugrEbaIzJHFhKWGDRvCxsYGmZmZGsczMzPh6yv+P52vr69B1wNAUFAQGjZsiLNnz0qGJQcHBzg4OBj4CoiILEfMBztl1yH748g13Cq6i+4tG2LMvcU5t6kNIr/y3x209nUFUD4wPed2CexsFCgpFfDlP+exbUYvBHm5qK6/WVCM7FtF6PvhLtSzt0HKvIfgaCfeuk9U2yxmNpy9vT3CwsKQmJioOlZWVobExERERUWJ3hMVFaVxPQBs2bJF8noAuHz5Mm7cuIFGjRoZp+JERBZI14Ktz3+fild+OoyoOPH1oaavScPyHedwJjMfOfc2YFafHfjM1wdws6B8oc7YNWl44M0tqk2rC4pLRdeVEgQB01YfxNNf7tO5lyCRMVlMyxIAxMbGYuzYsQgPD0dERASWLFmCgoICjB8/HgAwZswYNG7cGHFxcQCAadOmoVevXnj//fcxaNAgrF69GgcOHMDKlSsBALdu3cLrr7+OoUOHwtfXF+fOncPMmTPRokUL9OvXz2Svk4jI0p24locT1/LwzmbxMaX/ZhfggTe3SN7/57EMXMm5g/7tfOHubIcp36ciPMATv6ZdBQBM/j4Fnz0drrq+Ykbf7rPZiN99Hm8OaY9G7k6iZZ/OzEcjd0e4OtpV4xVSXWJRYWnkyJG4fv065s+fj4yMDHTs2BGbN29WDeJOT0+HUnm/saxr165ISEjA3LlzMWfOHLRs2RLr169H+/btAQA2NjY4fPgwvv76a+Tk5MDPzw99+/bFm2++aRbdbJazqAMRkXHtv/Af9l/4D/G7L6iOnVNbEf3PY5kInLUJ02Na4ukuAQj/v60af2duPbENa5+LgoOtEh2aeCAjtxBOdjZ4/vsU7Dl3A64OtjjyuvY/is9dv4VFf5zEC71boEMTjxp8hWRJLGqdJXNVU+ssjf0qGTtPc50lIqLqGB3RFD8kp2sdH9XZH/lFd/HO0A54d/NJuDra4vNd51F8b0uaM/83AIUlpVotUJdu3oa9rRI+bpzxZ+msbp2luohrwhERVZ9YUAKA1fvLt5I5nZGPMyJjtFq+9gcAIGVuDP67XYzGHs5YsfMcPrq3Zc7ptwbgwMWbeKBpfdVg9LIyAdtPZcHB1gbdWjQQXdyzrExASVkZHGw5gN1SMCwREVGdJhaU1IW9tVX0eKu55WFqYIgvnooMwMFLOfBxc8TLaw8BAGLaeGPriSy8/kg7jIrwx95/byIi0BOjP9+L41fzsH9uDJLP30RoE3d4s5XKrLEbzgjYDUdERHJ6B3trLK2gztneBl+O7Yzfj1zDqwOCMTUhFSkX/8P3z0Qi6dwNDA1rgoYumuNoC0tKubSCEej7+c2wZAQMS0REVJMOzI3BkSu5CAuoj7c3ncDq/Zew7IkH4OFsBx83B7TwdlVdW1omYMvxTHRq6gGFAjh2NQ/Rrby4358IjlmyAvxzTUREABAu0hU4JSFV9f1bQ9rjwy2n0b1lQ9XyCkoFULEc1ZKRHeHubAc/dydczb2DBb8ew6LHQ7Du4BXkFZZgxVNhDFMy2LJkBGxZIiIiSzaxRzP4ezrD39MZrXxc8cTne/Fcr+Zwd7JD4oksvNq/tVWOq2LLEhEREenl87/Pax2b/csR1febjlxF9xZeyL1TjOVPhWHyd6lo1rAeRnRugqHLkzB3UBuM6xqIkxn5aNvIDV/tPo+ColJM6hmEn1IuoXcbHzT2EF8k1BKwZckI2LJERERU7sXeLbB021kAgI1Sodqa5r1hHbBqzwV8+uQDGLVyL67lFuKXyV0xbfVB9An2wcJH2kEQBK3uwJLSMtjZ1MzubBzgXYsYloiIiKonopknks/fxOLhoUi5+B+OXsnFR6M6ov9Hf+PhDo3wwYiORn8mw1ItYlgiIiKqWRcWDTJ6mfp+ftdMuxYRERGRlWBYIiIiIpLBsEREREQkg2GJiIiISAbDEhEREZEMhiUzxmmKREREpsewRERERCSDYYmIiIhIBsMSERERkQyGJSIiIiIZDEtEREREMhiWiIiIiGQwLBERERHJYFgiIiIiksGwRERERCSDYcmMCQLX8CYiIjI1hiUiIiIiGQxLZkyhUJi6CkRERHUew5IZYzccERGR6TEsEREREclgWCIiIiKSwbBEREREJINhiYiIiEgGwxIRERGRDIYlIiIiIhkMS0REREQyGJaIiIiIZDAsEREREclgWCIiIiKSwbBEREREJINhiYiIiEgGwxIRERGRDIYlIiIiIhkMS0REREQyGJaIiIiIZDAsEREREclgWCIiIiKSwbBEREREJINhiYiIiEgGwxIRERGRDIYlIiIiIhkMS0REREQyGJaIiIiIZDAsEREREclgWCIiIiKSwbBEREREJINhiYiIiEgGwxIRERGRDIYlM/b3mWxTV4GIiKjOY1giIiIiksGwRERERCSDYYmIiIhIRpXCUnp6OoqKirSOl5WVIT09vdqVIiIiIjIXVQpLgYGBeOCBB3Du3DmN49evX0ezZs2MUjEiIiIic1Dlbrg2bdogIiICiYmJGscFQah2pYiIiIjMRZXCkkKhwKeffoq5c+di0KBBWLp0qca5mrRs2TIEBgbC0dERkZGRSE5Olr1+7dq1CA4OhqOjI0JCQvD7779rnBcEAfPnz0ejRo3g5OSEmJgYnDlzpiZfAhEREVmQKoWlitajl156CevWrcP8+fMxceJEFBcXG7Vyla1ZswaxsbFYsGABUlNTERoain79+iErK0v0+j179mD06NGYMGECDh48iCFDhmDIkCE4evSo6pp3330XS5cuxYoVK7Bv3z7Uq1cP/fr1Q2FhYY2+FiIiIrIMCqEK/WZKpRIZGRnw9vYGABw/fhyPPPII6tWrh6NHj6K0tNToFQWAyMhIdO7cGZ988gmA8gHl/v7+eOGFFzBr1iyt60eOHImCggJs3LhRdaxLly7o2LEjVqxYAUEQ4OfnhxkzZuDll18GAOTm5sLHxwerVq3CqFGj9KpXXl4e3N3dkZubCzc3NyO80nKBszYZrSwiIiJLdmHRIKOXqe/nd5Valnr16gV7e3vVz23btsXevXvh4eFRY2OWiouLkZKSgpiYGNUxpVKJmJgYJCUlid6TlJSkcT0A9OvXT3X9+fPnkZGRoXGNu7s7IiMjJcsEgKKiIuTl5Wl8ERERkXUyKCxVBINff/0VSqVSIyzY29vjt99+Q05OTo1UNDs7G6WlpfDx8dE47uPjg4yMDNF7MjIyZK+v+K8hZQJAXFwc3N3dVV/+/v4Gvx4iIiKyDLaGXOzh4aHXAO6a6oYzF7Nnz0ZsbKzq57y8PAYmIiIiK2VQWNq+fbvqe0EQMHDgQHzxxRdo3Lix0StWWcOGDWFjY4PMzEyN45mZmfD19RW9x9fXV/b6iv9mZmaiUaNGGtd07NhRsi4ODg5wcHCoyssgIiIiC2NQWOrVq5fGzzY2NujSpQuCgoKMWikx9vb2CAsLQ2JiIoYMGQKgfIB3YmIipk6dKnpPVFQUEhMTMX36dNWxLVu2ICoqCgDQrFkz+Pr6IjExURWO8vLysG/fPjz//PM1+XKIiIjIQhgUlkwtNjYWY8eORXh4OCIiIrBkyRIUFBRg/PjxAIAxY8agcePGiIuLAwBMmzYNvXr1wvvvv49BgwZh9erVOHDgAFauXAmgfE2o6dOn46233kLLli3RrFkzzJs3D35+fqpARkRERHWbRYWlkSNH4vr165g/fz4yMjLQsWNHbN68WTVAOz09HUrl/THrXbt2RUJCAubOnYs5c+agZcuWWL9+Pdq3b6+6ZubMmSgoKMCkSZOQk5OD7t27Y/PmzXB0dKz110dERETiBEGo8YWvpVRpnaUKrq6uOHz4cJ3fD47rLBEREdWsf98eCKXSuGFJ389vg1qWHn/8cY2fCwsL8dxzz6FevXoax3/55RdDiiUiIiIyWwaFJXd3d42fn3rqKaNWhoiIiEhMzSx5rR+DwlJ8fHxN1YOIiIhIUvmoIdOMWarSdidEREREtcmULUsMS0REREQyGJaIiIjI7FV97n71MSwRERGR2RNM2BHHsEREREQkg2GJiIiIzB674YiIiIjMFMMSERERmT22LBERERGZKYYlIiIiMnucDUdEREQkg91wRERERGaKYYmIiIjMHveGIyIiIpIhmLAfjmGJiIiISAbDEhEREZk9dsMRERERyeBsOCIiIiI5DEtERERE5olhiYiIiMweV/AmIiIiksExS0RERERmimGJiIiIzB6XDiAiIiKSwRW8iYiIiGSwZYmIiIjITDEsERERkdnjbDgiIiIiGVxniYiIiMhMMSwRERGR+WM3HBEREZE0zoYjIiIiksEB3kRERERmimGJiIiIzB5nwxERERHJYDccERERkZliWCIiIiKzx9lwRERERDIEE/bDMSwRERGR2eOYJSIiIiIzxbBEREREJINhiYiIiMweu+GIiIiIzBTDEhEREZk9ruBNREREJIPdcEREREQyuCglERERkZliWCIiIiKzxxW8iYiIiGTY2Zgustia7MlEREREejjzfwMYloiIiIjWTOqC1fsvYXy3QJSWCXjs0z1Y9HiISYMSwLBERERERhI/rjPGr9qPrs0bYM+5GwAAOxsFWni7Ir+wBBumdsdbm46jS1AD1LO3xbt/nsSnTz6AgqJSKBVAeKAnIoMaqMq7sGiQqV6KBoVgyhFTViIvLw/u7u7Izc2Fm5ub0coNnLXJaGURERFVxZCOflifdhWDQ/3wwYhQJJ7IROdAT2w6cg1f/H0ea57tgr/PZKO1jytC/T1U9xWWlOLXtCvo0dILfh5OpnsBMvT9/GZYMgKGJSIislQvxbTCh1tPI+7xEPRs5YXjV/PQrUUDDF2ehK7NG2Dew21NXcUao+/nN7vhiIiILMDIcH+sOXBJ6/jbj4Xgt0NX8eaQdvh813kcupyD0RFNsWDDMQDA2ueicLu4FN1bNISNUoGs/EJ4uTjg6S+TUSYIeKF3C0yLaakqr/G9VqA/pvWonRdmAdiyZARsWSIioupydbRFfuFdreNvDmmPK//dwav9WyM1PQc3C4rh6miLUSv34o1H22FMVKDWPWVlApL+vYF2fm7wcLavhdpbJrYsERERmYHWPq5wdrCBf31nbDh0VeOcq6Mt1kyKQvatInRv0RDrDl6Bt5sDSssELNxwDG8/HoKuzRuqrg8LqK/6Xm7ws1KpQLcWDSXPk2EYloiIiHSIbu2FHaeuax0f1dkfcwa1gVKhwKWbtzHgo7/RtpEbjl/LA1A+HujFPi2gUChwp7gUA0N80dG/PrafysLhyzl4a0gIbJQKVXlDw5qovt/xinfNvzDSC7vhjIDdcERElslGqUBpmYDpMS2xZOsZrfM/PReF9o3d4WCrxG+Hr+HzXf/ikyc6Ye76o7CzUeKLMeFQqoWd28V34WRng8v/3cE/Z7Mx9IEmsLflZhnmirPhahHDEhGRafRt64O/jmdKnv/5+SjM//UYYh9qhQlfH9A6f+b/BkCpUECpALot2oaruYWY8VAr/Hk8A/3b+WJq75YipZK14JglIiKyeivHhEMQBPySegUz1h5SHbdRKjD/4bYIC/DEphfLZ3U91aUpvtubjg1Tu+G1dUfxaEc/jZWh98zuA0EQoFAo8EIfhiS6jy1LRsCWJSKiqmnn54b8wrtIv3lb69xjnRpj8fBQ2CgV+DXtCqatTgMADH2gCX5Nu4L1U7qhfWN3AOWzv+L+OIFLN+/gnaEd4O5sJ/q8ijBEBOj/+W0xHak3b97Ek08+CTc3N3h4eGDChAm4deuW7D2FhYWYMmUKGjRoABcXFwwdOhSZmZrNtQqFQutr9erVNflSiIjqhL9nPogpDzZHUMN6oudnDQjGb1O7Y8fL0XB3uh9uYh9qhRHhTfDesA6qwc+PdmyMjS90x29Tu+P9EaE4+/ZAVVACymd/vTaoLVY8HSYZlAAwKFGVWEzL0oABA3Dt2jV89tlnKCkpwfjx49G5c2ckJCRI3vP8889j06ZNWLVqFdzd3TF16lQolUrs3r1bdY1CoUB8fDz69++vOubh4QFHR0e968aWJSKyRk3qO+Hyf3ckzx97vR92n81GVn4R5q4/qjo+NioAw8P9NcKM+t9nZ/9vAM5ev4XWPq6q8HL4cg4mfZOCGX1bYXi4fw28GiJtVjXA+8SJE2jbti3279+P8PBwAMDmzZsxcOBAXL58GX5+flr35ObmwsvLCwkJCRg2bBgA4OTJk2jTpg2SkpLQpUsXAOVhad26dRgyZEiV68ewRESWSKkAyiQ+AZp71cN3z0Tiwy2ncbOgGFtPZKnO7XrlQTSp76QxC6xyGLKttEt8YUkphi7fg16tvDCzf7BxXwhRFVlVN1xSUhI8PDxUQQkAYmJioFQqsW/fPtF7UlJSUFJSgpiYGNWx4OBgNG3aFElJSRrXTpkyBQ0bNkRERAS++uor6MqPRUVFyMvL0/giIqpNfu7yrd/x4zpLnnt/eCiOv9EPya/FoG9bH3jW01zh+cQb/bHlpV5o5O6Ed4eFYvlTYRr3Nm3grBGUAGDPrN6YMzAYhxb01QpKAOBoZ4NNL/ZgUCKLZBFhKSMjA97emotz2drawtPTExkZGZL32Nvbw8PDQ+O4j4+Pxj1vvPEGfvzxR2zZsgVDhw7F5MmT8fHHH8vWJy4uDu7u7qovf382GRORcY3rGih63MPZDoseD8Ef03tK3nth0SA8GOyNv2c+CF83zVDl4+aAoWFN4Gxvi4YuDlg5JhzbX45WnR8Z7g8nexuNMGRno8Qvk7tizaQuGosmqvPzcMKkns01xh4RWQuThqVZs2aJDrBW/zp58mSN1mHevHno1q0bOnXqhFdffRUzZ87Ee++9J3vP7NmzkZubq/q6dEl7Y0MiIjHDw5rgwqJBiGkjvjrz4FA/JEyMxMJH2omeb+XtilERTeHuZIfjb/TTakFaOPj+DvH+ns7YO6cPVqi1DP0wsYtWme5Odni2ZxDq2dtgau8Wos99oGl9RAY10Pn6iKyRSddZmjFjBsaNGyd7TVBQEHx9fZGVlaVx/O7du7h58yZ8fX1F7/P19UVxcTFycnI0WpcyMzMl7wGAyMhIvPnmmygqKoKDg4PoNQ4ODpLniMi6LRjcFs72Nnj15yOi51/s0xJFd0vx2c5/Rc9XDHqW6u3/eHQn1fdrJnXBnHVHcO56gerYzP6tVd8729viwWBvfDshAk9/mYwG9ezxtMimqv3a+WBSzyC083NDkJeL6HNnD2yDmf2DNbbeIKJyJg1LXl5e8PLy0nldVFQUcnJykJKSgrCw8n8hbdu2DWVlZYiMjBS9JywsDHZ2dkhMTMTQoUMBAKdOnUJ6ejqioqIkn5WWlob69eszDBFZKT93R1zNLZQ8/3inxkhJ/w8Xb2iv+wMAY6ICcTozX/L+2IdaAQAiAj1FV4yu6Maa2T8YiSeztM6riwxqgMQZ0RqDp8MDPbWu69HSS3ZTVYVCgTkD28g+CwCDEpEEixiz1KZNG/Tv3x8TJ05EcnIydu/ejalTp2LUqFGqmXBXrlxBcHAwkpOTAQDu7u6YMGECYmNjsX37dqSkpGD8+PGIiopSzYT77bff8MUXX+Do0aM4e/Ysli9fjrfffhsvvPCCyV4rEdWsPbP74OEOjUTPBTRwxgcjO2LnKw+Kng/yqgcbpQJtGume9RoeoB1qAMDFofzfqK19XbXGJUl1zf3z6oNo4e2C/3usvc7nEpHxWcx2J99//z2mTp2KPn36QKlUYujQoVi6dKnqfElJCU6dOoXbt+//a/DDDz9UXVtUVIR+/frh008/VZ23s7PDsmXL8NJLL0EQBLRo0QIffPABJk6cWKuvjYj089NzUdh5+jo+3nZW9PyhBX3haKdE67mbZctxdRT/q++n57rK3udsb6P6fnREU/yQnK5xfu/sPqrv3Z3tkDI3BvmFdxG9eAcAYMqDzTWuX/hIO8zs3xoldwWcycpHWEB90ec2qe+MrbG9ZOtGRDXHItZZMnfWts7SrAHBWPRHzQ6sJxLzSKgfNhy6Knl+96zeuF10Fw99uEv0fEVXlNT/O8/2CsLsAW2QfasI4W9tlbwfAKYmpGLj4Wsa50Mau+O3F7oDAIrulmLUyr04mJ6D4WFN8H+PhUjuLp99qwi5d0oQ1LAeV5AmMiPcSJeqzJbjFsxO+8ZuOHrFvNfzsrdVovhuWbXK6B3sLRuWGns46VVOaBN3HLqcq3W8R4vyMZINXXSPSZw1IBibjlzTGIgd27eV6nsHWxusm9xNr/o0dHHQ65lEZJ4sYswSWZ7QJu66LzIDvYPFx4iYk/rOdpIzp2qLk50NAho4y16jVACRzcTH6QDlXViNZBZSjB/fGYM6NIKjnfhfS8297u8vJnVNhTeHaI/teT66Obq3bCh6fUhjd/z4rObEjyb1nXHqzQE4srAvhoU1wdLRnfBga/P/80JExsewRDVi1fgIU1dBL+rTtM2VQqGQ3JJCX3MH6Z4JJceznr3kuj8VFg8PxZBOjUXPPdsrCEcW9sPPz3fFg63FZ8D2bOkFOxslTr45QPR8PYf7DeHfP6M9C/afV+8Pyg5ooLlx6+bpPfCqzMrRG6Z2Q4RI0LO3VcLV0Q6Lh4fikVDtbZWIqG5gWKpDbJUKhPp7mLoaZiOoYT2ND2BzpVQodG7BAwAOEuNlAODJyACd9z/+gHjQAQA/D0edrSoPd/DDSIkNUGcPaAMbpQJ+Hk6IlwjScr2/Xq4O+GBEqOrnsEozzRYPD0WT+vdbvtyd7LB7Vm/89VJPnI8biGBf7bEIG6Z2w/hugTi0oC/HERGRLIalOsRGqcCsWtqXyZo+e8RaMWqTQgG4OcpvIfHVuHB0bS6+urKHsx2c1GZxiVkwuC36tpVerPWDER111hOA1n5hhlAPLOqtPG6Ottj/WgxaeLtK3jtMZAuOxh5OaKW2q31lHZp4YMHgdtyeg4h0YliqY6IkPlDV8V/Z9znZ2aBbC/FxLrVFqQDeHdZB9prewT6Qanv6dYruQciPP9AEfdv6SJ739yxvtfFwrplg8Uq/1ho/h6tNoa/cpVahh8T4IyIiY2NYskLVncym7+1LLWC8T3Xpei8XDw+VvwDAYxLjeACgtY+rziDUvYUXAhuKBwZ1zSW2sZAKG+rcneygVCrw90ztxRjHRt3vwkueE4M3HtUeuzTv4bZaxyqItfpUNrFHkMbP6mO0lj3xgOg9306IxJdjw5E4g+sPEVHNYliyQn+9VL0PD33D1iOhfni2Z5DoOYUekeuXyfILAOoySeLZxqSrlW2ozDifCtESA5rLywdGhPtLvo8AsPAR6SACAFtjy3eff+mhVrLXSXmgqYfq+4oWJHUxai1O9rZKjKm091jsQ60woXsz1c9zBmp29drZaP8188e0Hqrvd8/qrbU+0biugXCys8HoCH80lZmF16eNj2RIJCIyFoalOkTfCVW11Q3nrGMcjS5KHfVcOroThj6gu1VDjq53Qp/3Sm4WVcX97RpLL7XgqmO8UsVYHhcdg9UXDBYPXbpeg67g+0KlXeofCdUMkOpT/iu0aeSGz54Ow6dPPiC6dpKvuyOOLOyLuMflW92IiGoDwxJpGdBeeqCvMenT+iR7v47b+7b1Qah/Ndd7MkJulAsjFWequpD+iqfC9L52fLdmoscr167y+KEQmSAHaL8+X3dHTI4u39YjItBTqyWqQr92vhgYIr5HGwDYirRIERGZAv82qkP0/dz3dpNeONCYqtuApU93YXUXc6xuVvKsZy9f/r0HVLWe/Q0MtjP7t9Y6VjkcVeYuMqh79aQuOp4TjAuLBuHH56IktwAhIrIU/FusDqmRRaBl0kRTkfEvxhTUUH6siqOdDcqqmZb06WZ7Z2iI5Ll198ZlfT4mXPR8O7/y9X+EmvntaPlfpdaluMdDEBmkOUOyTG10tdTWN12CGmD+w23xzf8sY/FRIqLqYFgiUV+NE/9w15cAAc9HN5e9prqtNnKzzDoHlk89r27Lkj4rfI/s3FRyELfPvVa6hySm5b82qHwcUVn1tlTTm6OdjWormhkPtcLoiKZa16i/ZXJZ8X/dm6FnK+nB60RE1oJhqQ4xJJz0aFm9D8HqjkfShz4LIFa3ZUnfMGCrrNr/ShULIkYGie+pJrXQpJSfn4/Sec13z0Ti6/9FSIZZ9YH3tfF7JCIydwxLdUit7sWq52fscIk1eKrbslXRffZIR+mZaMZ9P8RL0zVjr0KT+s7YPau31vghfbYpUfdA0/oaP0cFaYctV0c79GrlJTmAWv2ZrXw5LZ+IiGGJqqU6LQ8KhXRXWu9g6dWk9Sr73n+9XaUHq1fkmC8kxhMZopdEC5RcVlo1vrPGz409nFCv0nIK6veP6iy+75rm9QoMUQuIni7yA8zFONnbYNOL3fF4p8ZY/qT+s+2IiKwVw5IVMsYySXJFhPp74PDCvgCkByYrFPo1LtVUa5f6e7BOYvFLfVt9ACCmjXZ4U1/J+gmJFiD1Z1TenqOhi4PW9ZXfD/XNa4fqsRI2ACwYrL3CtqHa+bnjg5EdRRepJCKqaxiWrFBNjzL58dkuOjd21a8ONVdT9RavTpW6pio/XZ/AJja9Xn39IBuJ8VPqR4N9NTeCbdPITev6yqtdq2+Aq77h69QHW4huTQIA9dWWK+CIIyKi6mNYskLGWIFb3zKkuuFqaxVwqc1f9RlvfX+NI91xqapT+9XfBvXHNKhnLxqw5PZRa+Xjipn9W2Px8FC83K+1bKvPU13KZ7lNrbS6NhERGY5hqS6pxRHe+kSlJvWdqjy1f/C9LUQ+fkJ8an//9tIrQ1fQ1Q2nvn1IVeupHhr1mZLvaGej6vKrCDzqJke30Gtj2reGhODkm/0R7KvdekVERIZhWLJCxmjTkSvDGNPJ7W2UcLSzqXKLzfvDQwEADrba+8u9/VgInqi0ftAMkU1mH+1YPrhcrAaNPZywZ3Zv1c/6hKXFw0MR1FB7HzSxMuRa3paO7oj48Z0x72H5DXR1cbSr3t57RERUjmHJCkl+DtfiABY7G6VsDHJ1LG+1EQshATK7zN8vX/rF9GjZUHIMkbqJPZpJ1mHTi901xmXpE+qGhTXBtpejVT/HtPHWOK9ehlztnO1t8WBrb9EgSEREtY9hyQpJtvwY0IhT3SFH9rbKKnddfTchslrPFqu72LH76wxpV9TDWXPKvSGvpWJtoye7aM6QC+DMMiIii8SwZIUc7OR/rTW9n5euXerViWUQfaary3VjGRrSqrslSmXfTIjA3zMf1Jj2D2iGJ6ntT4iIyPzY6r6ELE3FfmRa7uULPw/phRr1oW+rkz5dV/rMRNPl8Qca45fUK9UuR45nPf0Xd7SzUYoGPjsbJZJf64PtJ7PwSKj0vnZERGRe2LJkZcQWOlQxqBtOodqMVv46mcdVMwe5OeqX5W0rjU8Sq5NcXfSppp+Hk16b6uri7eqIkZ2baqyfRERE5o1hyeoYr0+pvrPhW2Wok6uJPrXcPL0n4h4PMfi5Yl10cs/TN7hULFdARER1C8NSHWTINh9i9L5br8Uepfl5OGF0hPZaQ8bwztD7IaxXSy/0CfZGkFc9zOzfGj8/L749ChER1U0cs2QF+gR7I/Fk1r2fdEeZZg3r4aG2PthyPLNKz9NYaLGK3VuGxLU5A4Px9u8npZ9T6UFiZVe+JsjLRfW9UqnAl+M6g4iISAxblqyAWChxlJkRp1Ao8PmY8Co/zyiLXhqwMdukns1xPm6g5PnKRYiOWap0la/UIHgdVo0vD1XqLVNERGTdGJasTnkoeG9YaI09QWO/M5G0U3FMnwHe+q7gbchec/qsMK7P8gRiolt748KiQRjZuWa6B4mIyPwwLFkBsWigT+tKlZ+nZ3CRXxagvAwnO/17gl8b2EbiOZVK1jEbTq7VjYiIqDJ+algd6SBjSOtM+fV6XCSShypadvq28wUABPu6SpYd2cxT7/qMjixvzam85lHlECg2u01jE9va3PeFiIgsHgd4WwFB5CexRh1DI4I+3WhlIhdVhBc/DyccWtAX9extsOfcDYz5KlmrLkqlAjFtvLH1RJZWOZW5ONji6Ov9ZPeFA6Cxp1uFp7sEYGnimfJnMisREZEB2LJkBYyxCnZNcXeyg62NEj1beeGF3i1Ux9Vbrd4f3lHv8lwcbLU3mFV7+a18XCDGy/X+Yp2GtrAREVHdxrBkBcSikr6bycrR53pDcpr6tepdYe7O2i1BhjDfqEhERNaAYckK6BtYjDFWp6W3ZstNWID2lihSzzHWAPPKDF24kg1LRERkCIYlK1BTLStiISygQT2Nn/u3961SecYMLBF6DhKvCHr92ulfZyIiIg7wtgL6jlkyNKDo070nNv5H6jmaM9I0tfZxxanMfEOqZ7CEiV2QeCKTe7wREZFB2LJkBfTd8LYmZsMZIqSxu+r7xSM0F82c0KOZUZ4h19Xo5eqAURFNUc+B/0YgIiL98VPDCozvFogNh67WQMnaaak6vWcD2vvivWEd0NbPDe383DXONfeqJ3EXERGRaTEsWQGxRRjFGDplXnStJj2KkLpEoVBgeLi/6LmwAE98ODIUzRqKT/3XFwdvExGRsTEsWQGlRkKQTgsz+rYyqFyxBSf1UsXE8linJlV7nsajmZaIiMi4OGbJCmhEJUXFMe3QML6b5rigkRKtPBXEZrpxqxAiIqprGJasQFU3zR0ert2SE93a6/75MO0wVZ1uuNrArUyIiMjYGJasgHrXkyFZQSxOLR3dSfW9UiR5xD6kuyvPwdZ0f6zaNHIz2bOJiMg6ccySFRDrhqsqsU1oKxyc9xDq19O9TEHc4yHVq0QVbHyhO9YfvIIX+rSs9WcTEZF1Y1iyAo3cnbSO6TO2yNDx27Y2+iWxIK/qzWirivaN3dG+sbvuC4mIiAzEbjgLp1Tov3RAZfqu/F2BM82IiKguYliycJ6VusU4W42IiMi4GJbM2LcTIjR+Dmnsjhbe4l1crve28OgSpN+mskDNbMA7jWOGiIjIyjAsmbGQSmNw7GwU+Gt6T9FAsunFHnilX2u8MaS93uUbe+83AHiorY/xCyUiIjIhDvC2IAqFAkqlQnTGW9MGzpjyYIuafX6Nlk5ERGSe2LJkQRSq/5omtnB8NxER1UUMS2ZMqptMn9W59SrfwHI4eJyIiOoihiUz5mhXtSUB9NXOz7B1idiyREREdRHDkhlzsrfB52PCVT8bO6y4O9nh4LyHjFomAxUREVkbhiUzJza7zJjdYfpsX0JERFSXMSxZEFOPGdKn1SjYlxvZEhGRdWFYsiBi25pIDQKvie4wXWHNy9UBNkr2wxERkXVhWLIA7w8PRbCvK94yYMHJmqArgDEmERGRNeKilBZgaFgTDA1rYtA9NbE6N8MQERHVRWxZsnC1OftMoeNhnAlHRETWiGHJwhmjBWnh4LZ6XacrC5l6ADoREVFNYFiyUoaszu3j5qjXdVItRxN7NAMAvDaojd7PJCIishQWE5Zu3ryJJ598Em5ubvDw8MCECRNw69Yt2XtWrlyJ6OhouLm5QaFQICcnxyjlWoIaGbMkkZbmDGyDg/MewuBQP+M/lIiIyMQsJiw9+eSTOHbsGLZs2YKNGzdi165dmDRpkuw9t2/fRv/+/TFnzhyjlmtqxtobzhCdA+tLnlMoFFzckoiIrJZFzIY7ceIENm/ejP379yM8vHz7j48//hgDBw7E4sWL4ecn3qIxffp0AMCOHTuMWq6p6dNqZEic0udajkciIqK6yiJalpKSkuDh4aEKNAAQExMDpVKJffv21Xq5RUVFyMvL0/iyZPqEL2eHmt3Ul4iIyFxZRFjKyMiAt7e3xjFbW1t4enoiIyOj1suNi4uDu7u76svf37/KdagKfVqChEoJaP2UblV61ocjQ9G2kRvefNS0C2ISERGZiknD0qxZs6BQKGS/Tp48acoqipo9ezZyc3NVX5cuXardCqgFIX272zr6e0gXJ1PKY52a4PdpPeDv6aznk4iIiKyLSccszZgxA+PGjZO9JigoCL6+vsjKytI4fvfuXdy8eRO+vr5Vfn5Vy3VwcICDg0OVn0tERESWw6RhycvLC15eXjqvi4qKQk5ODlJSUhAWFgYA2LZtG8rKyhAZGVnl59dUuTVNvR1Iati1IUsH1MQyA0RERNbCIsYstWnTBv3798fEiRORnJyM3bt3Y+rUqRg1apRqxtqVK1cQHByM5ORk1X0ZGRlIS0vD2bNnAQBHjhxBWloabt68qXe55sjY4SYsQHpZACIiorrOIsISAHz//fcIDg5Gnz59MHDgQHTv3h0rV65UnS8pKcGpU6dw+/Zt1bEVK1agU6dOmDhxIgCgZ8+e6NSpEzZs2KB3uebI2Oss+Xk44e+ZD+LQgr5GLZeIiMgaWMQ6SwDg6emJhIQEyfOBgYFaM8AWLlyIhQsXVqtcc+Tlcn+8lNQWJIYGKg7gJiIiEmcxLUt03+jIpmo/iacljkMiIiIyDoYlC+RgywUiiYiIagvDkpXq0VL3LEMiIiLSjWHJwkmNWfJy5TpQRERExsCwRERERCSDYYmIiIhIBsOShZNawRsAYtr4AAAGh5rvAptERETmzmLWWSJxjnbSM+M+GtURu05fR6/WHOxNRERUVWxZslDLnngAAQ2c8emTD0heU8/BFgNCGsHZnpmYiIioqvgpaqEGdWiEQR0amboaREREVo8tS0REREQyGJaIiIiIZDAsEREREclgWCIiIiKSwbBEREREJINhiYiIiEgGwxIRERGRDIYlIiIiIhkMS0REREQyGJaIiIiIZDAsEREREclgWCIiIiKSwbBEREREJINhiYiIiEiGrakrYA0EQQAA5OXlmbgmREREpK+Kz+2Kz3EpDEtGkJ+fDwDw9/c3cU2IiIjIUPn5+XB3d5c8rxB0xSnSqaysDFevXoWrqysUCoXstXl5efD398elS5fg5uZWSzU0X3w/tPE90cb3RBPfD218TzTx/dAm9p4IgoD8/Hz4+flBqZQemcSWJSNQKpVo0qSJQfe4ubnxD7Aavh/a+J5o43uiie+HNr4nmvh+aKv8nsi1KFXgAG8iIiIiGQxLRERERDIYlmqZg4MDFixYAAcHB1NXxSzw/dDG90Qb3xNNfD+08T3RxPdDW3XeEw7wJiIiIpLBliUiIiIiGQxLRERERDIYloiIiIhkMCwRERERyWBYqkXLli1DYGAgHB0dERkZieTkZFNXyWR27dqFwYMHw8/PDwqFAuvXrzd1lUwuLi4OnTt3hqurK7y9vTFkyBCcOnXK1NUymeXLl6NDhw6qBeSioqLwxx9/mLpaZmPRokVQKBSYPn26qatiMgsXLoRCodD4Cg4ONnW1TO7KlSt46qmn0KBBAzg5OSEkJAQHDhwwdbVMJjAwUOvPiUKhwJQpU/Qug2GplqxZswaxsbFYsGABUlNTERoain79+iErK8vUVTOJgoIChIaGYtmyZaauitnYuXMnpkyZgr1792LLli0oKSlB3759UVBQYOqqmUSTJk2waNEipKSk4MCBA+jduzceffRRHDt2zNRVM7n9+/fjs88+Q4cOHUxdFZNr164drl27pvr6559/TF0lk/rvv//QrVs32NnZ4Y8//sDx48fx/vvvo379+qaumsns379f48/Ili1bAADDhw/XvxCBakVERIQwZcoU1c+lpaWCn5+fEBcXZ8JamQcAwrp160xdDbOTlZUlABB27txp6qqYjfr16wtffPGFqathUvn5+ULLli2FLVu2CL169RKmTZtm6iqZzIIFC4TQ0FBTV8OsvPrqq0L37t1NXQ2zNm3aNKF58+ZCWVmZ3vewZakWFBcXIyUlBTExMapjSqUSMTExSEpKMmHNyJzl5uYCADw9PU1cE9MrLS3F6tWrUVBQgKioKFNXx6SmTJmCQYMGafx9UpedOXMGfn5+CAoKwpNPPon09HRTV8mkNmzYgPDwcAwfPhze3t7o1KkTPv/8c1NXy2wUFxfju+++w//+9z+dG9+rY1iqBdnZ2SgtLYWPj4/GcR8fH2RkZJioVmTOysrKMH36dHTr1g3t27c3dXVM5siRI3BxcYGDgwOee+45rFu3Dm3btjV1tUxm9erVSE1NRVxcnKmrYhYiIyOxatUqbN68GcuXL8f58+fRo0cP5Ofnm7pqJvPvv/9i+fLlaNmyJf788088//zzePHFF/H111+bumpmYf369cjJycG4ceMMus+2ZqpDRNUxZcoUHD16tM6Pv2jdujXS0tKQm5uLn376CWPHjsXOnTvrZGC6dOkSpk2bhi1btsDR0dHU1TELAwYMUH3foUMHREZGIiAgAD/++CMmTJhgwpqZTllZGcLDw/H2228DADp16oSjR49ixYoVGDt2rIlrZ3pffvklBgwYAD8/P4PuY8tSLWjYsCFsbGyQmZmpcTwzMxO+vr4mqhWZq6lTp2Ljxo3Yvn07mjRpYurqmJS9vT1atGiBsLAwxMXFITQ0FB999JGpq2USKSkpyMrKwgMPPABbW1vY2tpi586dWLp0KWxtbVFaWmrqKpqch4cHWrVqhbNnz5q6KibTqFEjrX9MtGnTps53TwLAxYsXsXXrVjzzzDMG38uwVAvs7e0RFhaGxMRE1bGysjIkJibW+fEXdJ8gCJg6dSrWrVuHbdu2oVmzZqauktkpKytDUVGRqathEn369MGRI0eQlpam+goPD8eTTz6JtLQ02NjYmLqKJnfr1i2cO3cOjRo1MnVVTKZbt25aS46cPn0aAQEBJqqR+YiPj4e3tzcGDRpk8L3shqslsbGxGDt2LMLDwxEREYElS5agoKAA48ePN3XVTOLWrVsa//o7f/480tLS4OnpiaZNm5qwZqYzZcoUJCQk4Ndff4Wrq6tqPJu7uzucnJxMXLvaN3v2bAwYMABNmzZFfn4+EhISsGPHDvz555+mrppJuLq6ao1fq1evHho0aFBnx7W9/PLLGDx4MAICAnD16lUsWLAANjY2GD16tKmrZjIvvfQSunbtirfffhsjRoxAcnIyVq5ciZUrV5q6aiZVVlaG+Ph4jB07Fra2VYg+NTc5jyr7+OOPhaZNmwr29vZCRESEsHfvXlNXyWS2b98uAND6Gjt2rKmrZjJi7wcAIT4+3tRVM4n//e9/QkBAgGBvby94eXkJffr0Ef766y9TV8us1PWlA0aOHCk0atRIsLe3Fxo3biyMHDlSOHv2rKmrZXK//fab0L59e8HBwUEIDg4WVq5caeoqmdyff/4pABBOnTpVpfsVgiAIxsltRERERNaHY5aIiIiIZDAsEREREclgWCIiIiKSwbBEREREJINhiYiIiEgGwxIRERGRDIYlIiIiIhkMS0RERGQUu3btwuDBg+Hn5weFQoH169eb9HklJSV49dVXERISgnr16sHPzw9jxozB1atXDXoOwxIRkYTo6GhMnz7d1NUgshgFBQUIDQ3FsmXLzOJ5t2/fRmpqKubNm4fU1FT88ssvOHXqFB555BGDnsO94YiIiMgoBgwYgAEDBkieLyoqwmuvvYYffvgBOTk5aN++Pd555x1ER0fXyPPc3d2xZcsWjWOffPIJIiIikJ6ervdepGxZIiISMW7cOOzcuRMfffQRFAoFFAoFLly4YOpqEVm0qVOnIikpCatXr8bhw4cxfPhw9O/fH2fOnKm1OuTm5kKhUMDDw0PvexiWiIhEfPTRR4iKisLEiRNx7do1XLt2Df7+/qauFpHFSk9PR3x8PNauXYsePXqgefPmePnll9G9e3fEx8fXSh0KCwvx6quvYvTo0XBzc9P7PoYlIiIR7u7usLe3h7OzM3x9feHr6wsbGxtTV4vIYh05cgSlpaVo1aoVXFxcVF87d+7EuXPnAAAnT55UteRKfc2aNatKzy8pKcGIESMgCAKWL19u0L0cs0REREQ17tatW7CxsUFKSorWPzxcXFwAAEFBQThx4oRsOQ0aNDD42RVB6eLFi9i2bZtBrUoAwxIRERHVgk6dOqG0tBRZWVno0aOH6DX29vYIDg426nMrgtKZM2ewffv2KoUthiUiIgn29vYoLS01dTWILMatW7dw9uxZ1c/nz59HWloaPD090apVKzz55JMYM2YM3n//fXTq1AnXr19HYmIiOnTogEGDBhn1eU2bNkVJSQmGDRuG1NRUbNy4EaWlpcjIyAAAeHp6wt7eXq/nKARBEAyuHRFRHTBp0iSkpaXhxx9/hIuLCzw9PaFUcqgnkZQdO3bgwQcf1Do+duxYrFq1CiUlJXjrrbfwzTff4MqVK2jYsCG6dOmC119/HSEhIUZ/3oULF9CsWTPRe7dv3673kgUMS0REEk6fPo2xY8fi0KFDuHPnDs6fP4/AwEBTV4uIahnDEhEREZEMticTERERyWBYIiIiIpLBsEREREQkg2GJiIiISAbDEhEREZEMhiUiIiIiGQxLRERERDIYloiIiIhkMCwRERERyWBYIiIiIpLBsEREREQkg2GJiIiISMb/A49B6GvwYiIyAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(\n",
    "    batch_data[\"sim_1\"].monitor_data[\"monitor_time_0\"].Hz.t,\n",
    "    np.real(batch_data[\"sim_1\"].monitor_data[\"monitor_time_0\"].Hz.squeeze()),\n",
    ")\n",
    "plt.title(\"FieldTimeMonitor data\")\n",
    "plt.xlabel(\"t\")\n",
    "plt.ylabel(\"Hz\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21bc59dc-0163-432b-9cf0-5c2d2617ef35",
   "metadata": {},
   "source": [
    "We see that the source has mostly decayed by the time we switch on the monitors, and the remaining data shows decay and oscillation due to the resonances inside the system.\n",
    "\n",
    "Looking at the Fourier transform of this data, we can see resonances at the band frequencies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e1b95adb-1ea6-40cb-ba63-ef5ac60de470",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:08:29.392606Z",
     "iopub.status.busy": "2023-08-18T17:08:29.392364Z",
     "iopub.status.idle": "2023-08-18T17:08:29.689950Z",
     "shell.execute_reply": "2023-08-18T17:08:29.689484Z"
    }
   },
   "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\">10:38:10 -03 </span>loading simulation from                                            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">686c623f-3acd-4a21-90a8-35c049d842fe</span>.hdf5                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:38:10 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
       "\u001b[2;36m             \u001b[0mdata/fdve-\u001b[93m686c623f-3acd-4a21-90a8-35c049d842fe\u001b[0m.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>loading simulation from                                            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">686c623f-3acd-4a21-90a8-35c049d842fe</span>.hdf5                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
       "\u001b[2;36m             \u001b[0mdata/fdve-\u001b[93m686c623f-3acd-4a21-90a8-35c049d842fe\u001b[0m.hdf5                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = 1 / np.amax(batch_data[\"sim_1\"].monitor_data[\"monitor_time_0\"].Hz.t)\n",
    "minn = int(freq_range[0] / df)\n",
    "maxn = int(freq_range[1] / df)\n",
    "spectrum = np.fft.fft(batch_data[\"sim_1\"].monitor_data[\"monitor_time_0\"].Hz.squeeze())\n",
    "plt.plot(\n",
    "    np.linspace(freq_range[0], freq_range[1], maxn - minn),\n",
    "    np.abs(spectrum[::-1][minn:maxn]),\n",
    ")\n",
    "plt.title(\"Spectrum at single wavevector\")\n",
    "plt.xlabel(\"Frequency (Hz)\")\n",
    "plt.ylabel(\"Amplitude\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "663c96ba-8b16-4056-9983-bef38e7a5c9a",
   "metadata": {},
   "source": [
    "We use the ResonanceFinder plugin to find the band frequencies.\n",
    "\n",
    "We first construct a `ResonanceFinder` object storing our parameters, and then call `run()` on our list of `FieldTimeData` objects. This will add up the signals from all of the monitors before searching for resonances. The `ResonanceFinder` class has additional methods in case the signal takes another form; see the api reference [here](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.resonance.ResonanceFinder.html).\n",
    "\n",
    "The `run()` method returns an `xr.Dataset` containing the decay rate, Q factor, amplitude, phase, and estimation error for each resonance as a function of frequency.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7496ef10-068e-41ce-8907-418bbcd60e26",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:08:29.693707Z",
     "iopub.status.busy": "2023-08-18T17:08:29.693525Z",
     "iopub.status.idle": "2023-08-18T17:08:31.106128Z",
     "shell.execute_reply": "2023-08-18T17:08:31.105255Z"
    }
   },
   "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\">10:38:11 -03 </span>loading simulation from                                            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">686c623f-3acd-4a21-90a8-35c049d842fe</span>.hdf5                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:38:11 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
       "\u001b[2;36m             \u001b[0mdata/fdve-\u001b[93m686c623f-3acd-4a21-90a8-35c049d842fe\u001b[0m.hdf5                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>decay</th>\n",
       "      <th>Q</th>\n",
       "      <th>amplitude</th>\n",
       "      <th>phase</th>\n",
       "      <th>error</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2.527775e+13</th>\n",
       "      <td>2.296547e+10</td>\n",
       "      <td>3457.903341</td>\n",
       "      <td>0.001526</td>\n",
       "      <td>1.530347</td>\n",
       "      <td>0.000320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9.788251e+13</th>\n",
       "      <td>7.422102e+11</td>\n",
       "      <td>414.312534</td>\n",
       "      <td>0.009620</td>\n",
       "      <td>2.030329</td>\n",
       "      <td>0.000019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.061235e+14</th>\n",
       "      <td>9.526460e+10</td>\n",
       "      <td>3499.692898</td>\n",
       "      <td>0.026843</td>\n",
       "      <td>-2.893037</td>\n",
       "      <td>0.000005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.131264e+14</th>\n",
       "      <td>2.127493e+12</td>\n",
       "      <td>167.049748</td>\n",
       "      <td>0.035868</td>\n",
       "      <td>1.792082</td>\n",
       "      <td>0.000024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.191562e+14</th>\n",
       "      <td>1.151470e+12</td>\n",
       "      <td>325.097664</td>\n",
       "      <td>0.020007</td>\n",
       "      <td>-2.087170</td>\n",
       "      <td>0.000019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.372938e+14</th>\n",
       "      <td>1.121671e+12</td>\n",
       "      <td>384.534325</td>\n",
       "      <td>0.021763</td>\n",
       "      <td>-0.424613</td>\n",
       "      <td>0.000020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     decay            Q  amplitude     phase     error\n",
       "freq                                                                  \n",
       "2.527775e+13  2.296547e+10  3457.903341   0.001526  1.530347  0.000320\n",
       "9.788251e+13  7.422102e+11   414.312534   0.009620  2.030329  0.000019\n",
       "1.061235e+14  9.526460e+10  3499.692898   0.026843 -2.893037  0.000005\n",
       "1.131264e+14  2.127493e+12   167.049748   0.035868  1.792082  0.000024\n",
       "1.191562e+14  1.151470e+12   325.097664   0.020007 -2.087170  0.000019\n",
       "1.372938e+14  1.121671e+12   384.534325   0.021763 -0.424613  0.000020"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resonance_finder = ResonanceFinder(freq_window=tuple(freq_range))\n",
    "resonance_data = resonance_finder.run(signals=batch_data[\"sim_1\"].data)\n",
    "resonance_data.to_dataframe()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46db3d3c",
   "metadata": {},
   "source": [
    "We see the four resonances from the previous figure. All four have reasonable Q factors, amplitudes, and errors, so they are likely to represent physical resonances. Note that in order to accurately obtain the Q factor for high-Q modes, it may be necessary to run the simulation for a longer time.\n",
    "\n",
    "Now we are ready to compute the band structure. We run the resonance finder at every Bloch wavevector."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4afe673e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:08:31.116954Z",
     "iopub.status.busy": "2023-08-18T17:08:31.116520Z",
     "iopub.status.idle": "2023-08-18T17:08:50.203875Z",
     "shell.execute_reply": "2023-08-18T17:08:50.202960Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:39:00 -03 </span>loading simulation from                                            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">9ffca0b0-59bc-4ded-bd95-de6d9ff24499</span>.hdf5                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:39:00 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
       "\u001b[2;36m             \u001b[0mdata/fdve-\u001b[93m9ffca0b0-59bc-4ded-bd95-de6d9ff24499\u001b[0m.hdf5                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "resonance_finder = ResonanceFinder(freq_window=tuple(freq_range))\n",
    "resonance_datas = []\n",
    "for i in range(3 * Nk):\n",
    "    sim_data = batch_data[f\"sim_{i}\"]\n",
    "    resonance_datas.append(resonance_finder.run(signals=sim_data.data))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f48f416-be79-4c85-9dd3-36a7101dfe70",
   "metadata": {},
   "source": [
    "We define a function to filter resonances based on their Q, amplitude, and error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "225f04aa-2390-456e-bcb0-395320ae4015",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:08:50.373773Z",
     "iopub.status.busy": "2023-08-18T17:08:50.373575Z",
     "iopub.status.idle": "2023-08-18T17:08:50.405541Z",
     "shell.execute_reply": "2023-08-18T17:08:50.404883Z"
    }
   },
   "outputs": [],
   "source": [
    "def filter_resonances(resonance_data, minQ, minamp, maxerr):\n",
    "    resonance_data = resonance_data.where(abs(resonance_data.Q) > minQ, drop=True)\n",
    "    resonance_data = resonance_data.where(resonance_data.amplitude > minamp, drop=True)\n",
    "    resonance_data = resonance_data.where(resonance_data.error < maxerr, drop=True)\n",
    "    return resonance_data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9398f9cc-e31c-4fc8-a8af-4fb89cee9034",
   "metadata": {},
   "source": [
    "We plot the band structure with the light line overlaid."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fc001a93",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:08:50.408852Z",
     "iopub.status.busy": "2023-08-18T17:08:50.408375Z",
     "iopub.status.idle": "2023-08-18T17:08:50.970373Z",
     "shell.execute_reply": "2023-08-18T17:08:50.969788Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:22: SyntaxWarning: invalid escape sequence '\\G'\n",
      "<>:22: SyntaxWarning: invalid escape sequence '\\G'\n",
      "<>:22: SyntaxWarning: invalid escape sequence '\\G'\n",
      "<>:22: SyntaxWarning: invalid escape sequence '\\G'\n",
      "/tmp/ipykernel_27549/2520820917.py:22: SyntaxWarning: invalid escape sequence '\\G'\n",
      "  plt.xticks([0, 0.5, 1, 1.5], [\"$\\Gamma$\", \"X\", \"M\", \"$\\Gamma$\"])\n",
      "/tmp/ipykernel_27549/2520820917.py:22: SyntaxWarning: invalid escape sequence '\\G'\n",
      "  plt.xticks([0, 0.5, 1, 1.5], [\"$\\Gamma$\", \"X\", \"M\", \"$\\Gamma$\"])\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(3 * Nk):\n",
    "    resonance_data = resonance_datas[i]\n",
    "    resonance_data = filter_resonances(\n",
    "        resonance_data=resonance_data, minQ=0, minamp=0.001, maxerr=100\n",
    "    )\n",
    "    freqs = resonance_data.freq.to_numpy()\n",
    "    Qs = resonance_data.Q.to_numpy()\n",
    "    plt.scatter(np.full(len(freqs), (1 / 2) * i / Nk), freqs / 3e14, color=\"blue\")\n",
    "\n",
    "lightx = np.linspace(0, 0.5, 100)\n",
    "lighty1 = lightx\n",
    "lighty3 = (0.5 - lightx) * np.sqrt(2)\n",
    "\n",
    "plt.plot(lightx, lighty1, color=\"blue\", alpha=0.2)\n",
    "plt.plot(1 + lightx, lighty3, color=\"blue\", alpha=0.2)\n",
    "\n",
    "plt.ylim(0, freq_range_unitless[1])\n",
    "\n",
    "plt.title(\"Band diagram\")\n",
    "plt.ylabel(\"Frequency (c/a)\")\n",
    "plt.xlabel(\"Wavevector\")\n",
    "plt.xticks([0, 0.5, 1, 1.5], [\"$\\Gamma$\", \"X\", \"M\", \"$\\Gamma$\"])\n",
    "plt.xlim(0, 1.5)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c9ac653-3d76-4588-946a-71b2db764030",
   "metadata": {},
   "source": [
    "The bandstructure we obtained matches the expected result from the paper. If we were seeing too many resonances, we could change the parameters to our filter_resonances function to eliminate the spurious ones. If we were seeing too few resonances even before filtering, we might have to change the parameters of the ResonanceFinder, for example decreasing `rcond` or increasing `init_num_freqs`. If the ResonanceFinder takes too long, we can decrease `init_num_freqs`. There can also be resonances on the light line associated with Wood's anomaly; we filter those out here based on their small amplitude."
   ]
  }
 ],
 "metadata": {
  "description": "This notebook demonstrates how to calculate the band structure of a photonic crystal in Tidy3D FDTD.",
  "feature_image": "./img/band_structure.png",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "photonic crystal, band structure, 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": "3.12.1"
  },
  "title": "Photonic Crystal Band Structure Calculation | Flexcompute",
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        {
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