Dispersion.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Modeling dispersive materials"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction / Setup\n",
    "\n",
    "Here we show how to model dispersive materials in `Tidy3D` with an example showing transmission spectrum of a multilayer stack of slabs.\n",
    "\n",
    "If you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101](https://www.flexcompute.com/fdtd101/) tutorials. For simulation examples, please visit our [examples page](https://www.flexcompute.com/tidy3d/examples/). FDTD simulations can diverge due to various reasons. If you run into any simulation divergence issues, please follow the steps outlined in our [troubleshooting guide](https://www.flexcompute.com/tidy3d/examples/notebooks/DivergedFDTDSimulation/) to resolve it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# standard python imports\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import tidy3d as td\n",
    "from tidy3d import web\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, let us define some basic parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Wavelength and frequency range\n",
    "lambda_range = (0.5, 1.5)\n",
    "lam0 = np.sum(lambda_range) / 2\n",
    "freq_range = (td.constants.C_0 / lambda_range[1], td.constants.C_0 / lambda_range[0])\n",
    "Nfreq = 333\n",
    "\n",
    "# frequencies and wavelengths of monitor\n",
    "monitor_freqs = np.linspace(freq_range[0], freq_range[1], Nfreq)\n",
    "monitor_lambdas = td.constants.C_0 / monitor_freqs\n",
    "\n",
    "# central frequency, frequency pulse width and total running time\n",
    "freq0 = monitor_freqs[Nfreq // 2]\n",
    "freqw = 0.3 * (freq_range[1] - freq_range[0])\n",
    "t_stop = 100 / freq0\n",
    "\n",
    "# Thicknesses of slabs\n",
    "t_slabs = [0.5, 0.2, 0.4, 0.3]  # um\n",
    "\n",
    "# Grid resolution (min steps per wavelength in a material)\n",
    "res = 40\n",
    "\n",
    "# space between slabs and sources and PML\n",
    "spacing = 1 * lambda_range[-1]\n",
    "\n",
    "# simulation size\n",
    "sim_size = Lx, Ly, Lz = (1.0, 1.0, 4 * spacing + sum(t_slabs))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Defining Materials (4 Ways)\n",
    "\n",
    "Here, we will illustrate defining materials in four different ways:\n",
    "\n",
    "1. Simple, lossy dielectric defined by a real-valued relative permittivity, and DC conductivity.\n",
    "2. **Active** material defined by real and imaginary part of the refractive index ($n$) and ($k$) at a given frequency. Values are exact only at that frequency, so this approach is only good for narrow-band simulations.\n",
    "3. Simple, lossless dispersive material (one-pole fitting) defined by the real part of the refractive index $n$ and the dispersion $\\mathrm{d}n/\\mathrm{d}\\lambda$ at a given frequency. The dispersion must be negative. This is a convenient approach to incorporate weakly dispersive materials in your simulations, as the values can be taken directly from [refractiveindex.info](https://refractiveindex.info/)\n",
    "4. Dispersive material imported from our pre-defined library of materials.\n",
    "\n",
    "More complicated dispersive materials [can also be defined](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/index.html#dispersive-mediums) through dispersive models like Lorentz, Sellmeier, Debye, or Drude, if the model parameters are known. Finally, arbitrary dispersion data can also be fit, which is a the subject of [this tutorial](https://www.flexcompute.com/tidy3d/examples/notebooks/Fitting/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# simple, lossy material\n",
    "mat1 = td.Medium(permittivity=4.0, conductivity=0.005)\n",
    "\n",
    "# active material with n & k values at a specified frequency or wavelength\n",
    "# note: negative k value corresponds to a gain medium; it is only allowed \n",
    "#       when `allow_gain` is set to be True \n",
    "mat2 = td.Medium.from_nk(n=3.0, k=-0.1, freq=freq0, allow_gain=True)\n",
    "\n",
    "# weakly dispersive material defined by dn_dwvl at a given frequency\n",
    "mat3 = td.Sellmeier.from_dispersion(n=2.0, dn_dwvl=-0.1, freq=freq0)\n",
    "\n",
    "# dispersive material from tidy3d library\n",
    "mat4 = td.material_library[\"BK7\"][\"Zemax\"]\n",
    "\n",
    "# put all together\n",
    "mat_slabs = [mat1, mat2, mat3, mat4]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Simulation\n",
    "Now we set everything else up (structures, sources, monitors, simulation) to run the example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we define the multilayer stack structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "slabs = []\n",
    "slab_position = -Lz / 2 + 2 * spacing\n",
    "for t, mat in zip(t_slabs, mat_slabs):\n",
    "    slab = td.Structure(\n",
    "        geometry=td.Box(\n",
    "            center=(0, 0, slab_position + t / 2),\n",
    "            size=(td.inf, td.inf, t),\n",
    "        ),\n",
    "        medium=mat,\n",
    "    )\n",
    "    slabs.append(slab)\n",
    "    slab_position += t\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We must now define the excitation conditions and field monitors. We will excite the slab using a normally incident (along z) planewave, polarized along the x direciton."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Here we define the planewave source, placed just in advance (towards negative z) of the slab\n",
    "source = td.PlaneWave(\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=freqw),\n",
    "    size=(td.inf, td.inf, 0),\n",
    "    center=(0, 0, -Lz / 2 + spacing),\n",
    "    direction=\"+\",\n",
    "    pol_angle=0,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we define the field monitor, placed just past (towards positive z) of the stack."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# We are interested in measuring the transmitted flux, so we set it to be an oversized plane.\n",
    "monitor = td.FluxMonitor(\n",
    "    center=(0, 0, Lz / 2 - spacing),\n",
    "    size=(td.inf, td.inf, 0),\n",
    "    freqs=monitor_freqs,\n",
    "    name=\"flux\",\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, define the boundary conditions to use PMLs along z and the default periodic boundaries along x and y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "boundary_spec = td.BoundarySpec(\n",
    "    x=td.Boundary.periodic(), y=td.Boundary.periodic(), z=td.Boundary.pml()\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now it is time to define the simulation object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "sim = td.Simulation(\n",
    "    center=(0, 0, 0),\n",
    "    size=sim_size,\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=res),\n",
    "    structures=slabs,\n",
    "    sources=[source],\n",
    "    monitors=[monitor],\n",
    "    run_time=t_stop,\n",
    "    boundary_spec=boundary_spec,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot The Structure\n",
    "\n",
    "Let's now plot the permittivity profile to confirm that the structure was defined correctly."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we use the `Simulation.plot()` method to plot the materials only, which assigns a different color to each slab without knowledge of the material properties."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:40:39.117056Z",
     "iopub.status.busy": "2023-08-18T17:40:39.116912Z",
     "iopub.status.idle": "2023-08-18T17:40:39.357256Z",
     "shell.execute_reply": "2023-08-18T17:40:39.356745Z"
    },
    "tags": []
   },
   "outputs": [
    {
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OITIysl7vjPc1EUFpaSkSEhI8vgGavMNwNaBz5875zRt7b8WZM2fQqlUrX5cR8BiuBhQZGQkAeO2115z/7y2bzeZ8D2JUVFSNf7ukksViwYwZM+pcO7nHcDWgqkPByMhI59+eecNms6GsrMzZp6KiAiaTqVED5nA4nH8LFoiHtP6IB9Y+ZrPZUFRUhJCQELRo0QItWrRASEgIioqKavzjwIbmcDhw6dKlan+NQLeG4fKhG4PVvHlzaLVaaLVaNG/evNECVhWsiooKlw/AoVvHcPmIu2BVaayA3RisqhmTGg7D5QOeglVFdcBuDpYvLqA0dQxXI/MmWFVUBYzBahwMVyOqS7CqNHTAGKzGw3A1kvoEq0pDBYzBaly8z6VAZWWlSwAqKipQUlKC4OBgGI3Gel/yNhqNKCkpQWFhIZo1a1anCxAigpKSElRWVqJZs2YAUC2kFRUV9aqL3GO4FKisrHR+2KTD4YDNZoNer4dOp/P46VTeqPpwzLKyMuh0Oq9mQBGBzWaDVqtFREQE7Ha7288N9OazBMl7/AyNBmSxWGAymXDy5MlqH+EcCCwWC9q2bQuz2RyQ9fsbzlwKREdHB+QPZ3AwfxwaEi9oECnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwXbdkyRJ06dIFRqMRRqMR6enp+OKLL3xdFgUwhuu6Vq1a4ZVXXsG+ffuwd+9e9OvXD0OGDEF+fr6vS6MAxa8Q8iA6Ohqvv/46xo8f71X7qq8QCtSv4An0+v0NvzPGDbvdjrVr16KsrAzp6em+LocCFMN1g4MHDyI9PR3Xrl1DREQEPvnkE3To0KHG9lar1eWbIi0WS2OUSQGC51w3aNeuHQ4cOIDdu3dj0qRJGDNmDA4dOlRj+5ycHJhMJueSmJjYiNWSv+M5lweZmZlITk7G0qVL3T7vbuZKTEwM2HMWnnM1LB4WeuBwODx+Qbher4der2/EiiiQMFzXZWVl4YEHHkDr1q1RWlqKNWvWYNu2bdiwYYOvS6MAxXBdV1hYiNGjR+Pnn3+GyWRCly5dsGHDBtx///2+Lo0CFMN13fLly31dAjUxvFpIpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCL9CSAVbCWCz+7qKurPxC9MbEsOlwpl1QGSor6uou9JyX1fQpPCwkEgRhotIEYaLSBGec6mQOBQwGn1dRd1ZLACm+LqKJoPhUkHXDNAFYLh0Qb6uoEnhYSGRIgzXdTk5OejRowciIyPRsmVLDB06FEePHvV1WRTAGK7rtm/fjsmTJ2PXrl3Iy8tDRUUF+vfvj7KyMl+XRgFKIyLi6yL80cWLF9GyZUts374d9957r1d9LBYLTCYTzGYzjAF4QSPQ6/c3nLlqYDabAQDR0dE+roQCFa8WuuFwODBlyhTcfffd6NSpU43trFYrrFar87HFwvfm0a84c7kxefJk/POf/8QHH3zgsV1OTg5MJpNzSUxMbKQKKRDwnOsmTz/9NHJzc/HVV1+hbdu2Htu6m7kSExMD9pyF51wNi4eF14kInnnmGXzyySfYtm1brcECAL1eD71e3wjVUSBiuK6bPHky1qxZg9zcXERGRuL8+fMAAJPJhNDQAPzzEfI5HhZep9Fo3K5fuXIlxo4d69UYgX5YFej1+xvOXNfxdww1NF4tJFKE4SJShOEiUoThIlKE4SJShOEiUoThIlKE4SJShOEiUoThIlKE4SJShOEiUoThIlKE4SJShOEiUoThIlKE4SJShOEiUoThIlKE4SJShOEiUoThIlKE4SJShOEiUoThIlKE4SJShOEiUoThIlKE4SJShOEiUoThIlKE4SJShOEiUoThIlKE4SJShOEiUoThIlKE4SJShOG67quvvsLvfvc7JCQkQKPRYN26db4uiQIcw3VdWVkZunbtikWLFvm6FGoign1dgL944IEH8MADD/i6DGpCOHMRKcKZ6xZYrVZYrVbnY4vF4sNqyN9w5roFOTk5MJlMziUxMdHXJZEfYbhuQVZWFsxms3M5c+aMr0siP8LDwlug1+uh1+t9XQb5KYbruitXruD48ePOxydPnsSBAwcQHR2N1q1b+7AyClQM13V79+5F3759nY+nTp0KABgzZgxWrVrlo6ookDFc1/Xp0wci4usyqAnhBQ0iRRguIkUYLiJFGC4iRRguIkUYLiJFGC4iRRguIkV4E1mB77qORLg2xNdl1FmZo8LXJTQpnLmIFGG4iBRhuIgUYbiIFGG4iBRhuIgUYbiIFGG4iBRhuIgUYbiIFGG4iBRhuIgUYbiIFGG4iBThn5wosHzAY9Dpw3xdRp3ZrFeBpV/4uowmgzMXkSIMF5EiDBeRIgwXkSIMF5EiDBeRIgwXkSIMF5EiDBeRIgwXkSIMF5EiDBeRIgwXkSIMF5EiDNdNFi1ahNtvvx0GgwFpaWn47rvvfF0SBSiG6wYffvghpk6dijlz5uD7779H165dMWDAABQWFvq6NApAfheufv36ITs7u9r6kpIS9OvXT+m233jjDUyYMAHjxo1Dhw4d8PbbbyMsLAwrVqxQul1qmvwuXNu2bcNbb72FoUOHoqyszLneZrNh+/btyrZrs9mwb98+ZGZmOtdptVpkZmZi586dyrZLTZffhQsANm3ahPPnz+O3v/0tTp061SjbLCoqgt1uR2xsrMv62NhYnD9/3m0fq9UKi8XishBV8cvP0IiPj8f27dsxbtw49OjRA2vXrkX79u19XVY1OTk5bg9hn648gwitwQcV3Zorldfwga+LaEL8bubSaDQAAL1ejzVr1uC5557DwIEDsXjxYqXbbdGiBYKCgnDhwgWX9RcuXEBcXJzbPllZWTCbzc7lzJkzSmukwOJ34RIRl8ezZs3C6tWrMX/+fKXb1el06N69OzZv3uxc53A4sHnzZqSnp7vto9frYTQaXRaiKn53WHjy5EnExMS4rHvkkUeQkpKCvXv3Kt321KlTMWbMGNx1113o2bMnFixYgLKyMowbN07pdqlp8rtwtWnTxu36jh07omPHjkq3PWLECFy8eBGzZ8/G+fPn0a1bN3z55ZfVLnIQecPvwuVrTz/9NJ5++mlfl0FNgN+dcxE1FQwXkSIMF5EiPOdSYEVqR+hCw31dRp3Zystqb0Re48xFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkiEZu/kIsqjeLxQKTyQSz2RyQ39UV6PX7G85cRIowXESKMFxEijBcRIowXESKMFxEijBcRIowXESKMFxEijBc17388svIyMhAWFgYoqKifF0ONQEM13U2mw3Dhw/HpEmTfF0KNRH8wvHrsrOzAQCrVq3ybSHUZDBct8BqtcJqtTofWywWH1ZD/oaHhbcgJycHJpPJuSQmJvq6JPIjTTpcM2fOhEaj8bgcOXKk3uNnZWXBbDY7lzNnzjRg9RTomvRh4fPPP4+xY8d6bJOUlFTv8fV6PfR6fb37U9PWpMMVExODmJgYX5dB/6KadLjq4vTp0yguLsbp06dht9tx4MABAMAdd9yBiIgI3xZHAYnhum727Nn4n//5H+fj1NRUAMDWrVvRp08fH1VFgYyfodGAAv0zKAK9fn/TpK8WEvkSw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDRaQIw0WkCMNFpAjDFUDyTuQh70Ser8sgL/HjrAOE3WFH9vZsaKBBv7b9EKQN8nVJVAvOXAFi59md+Mn8E06ZT2HX2V2+Loe8wHAFiNwjuaiwV6DCXoHco7m+Loe8wHAFAPM1Mz4//jnCQsIQFhKG9T+sh8XK71/2dwxXANhwYgOKy4th1Bth1BtRUl6CDcc3+LosqgXDFQA+PvwxACBYG4xgbTBEBP84/A8fV0W1Ybj83IniE/iu4DsYdb9+X5ZRb8Segj34seRHH1ZGtWG4/Nxnxz7D1YqriND9+tWxEboIlFWU4bNjn/mwMqoNw+XH7A471h5aixBtCDQajXO9RqNBsDYYa/PXwu6w+7BC8oTh8mNV97ZMBlO156IMUbzn5ecYLj9WdW/LEGyo9pw+SM97Xn6O4fJTN97bckej0fCel59juPzUjfe2asJ7Xv6N4QJw6tQpjB8/Hm3btkVoaCiSk5MxZ84c2Gw2n9V0472tmvCel3/ju+IBHDlyBA6HA0uXLsUdd9yBf/7zn5gwYQLKysowb968Rq/H3b2tmtx4zyupWVIjVEfe4swFYODAgVi5ciX69++PpKQkPPTQQ5g2bRo+/vhjn9RTdW8rXBcOEYGIVGtTtT5cF857Xn6KM1cNzGYzoqOjPbaxWq2wWq3OxxZLw1xY2HRyEwSCgtICAIAGGrQytnJpU1BaAMGvocv7MQ/Ppj3bINunhsFwuXH8+HEsXLiw1kPCnJwcZGdnN/j2X+r7En66/BMA4JvT32D1wdXV2mg1WozqPAr3tL4HANAmqk2D10G3pkkfFs6cORMajcbjcuTIEZc+BQUFGDhwIIYPH44JEyZ4HD8rKwtms9m5nDlzpkHq7hbXDUNShmBIyhB0iOlQY7sOMR2c7brFdWuQbVPDadIz1/PPP4+xY8d6bJOU9OtFgHPnzqFv377IyMjAsmXLah1fr9dDr9ffapnURDXpcMXExCAmJsartgUFBejbty+6d++OlStXQqtt0pM6NYImHS5vFRQUoE+fPmjTpg3mzZuHixcvOp+Li4vzYWUUyBguAHl5eTh+/DiOHz+OVq1cr8q5uwxO5A0e+wAYO3as877RzYs/cIgDVyuuuiwOcfi6LKoFZy4FLJUWoLJhxtIGa503im8UrguHNlj7y7YaSEOORQyXEtvM2xDmcP9u9roKjwvH9AenV5uptBotwiPDsenypgbZDgBcLb3aYGMRw+X3tBotWhpb+roMqgeecxEpwnARKcLDQgX6mPrAaKz9z0X8jUXLCxoNieFSwBhshDE48MLFn4aGxcNCIkUYLiJFGC4iRRguIkUYLiJFGC4iRRguIkUYLiJFGC4iRRguIkUYLiJFGC4iRRguIkUYLiJFGC4iRRguIkUYLiJFGC4iRRguIkUYLiJFGC4iRRguIkUYLiJFGC4iRRguIkUYLiJFGC4iRRguIkUYLiJFGC4iRRguIkUYruseeughtG7dGgaDAfHx8Xj88cdx7tw5X5dFAYzhuq5v37746KOPcPToUfzjH//AiRMnMGzYMF+XRQFMIyLi6yL80aeffoqhQ4fCarUiJCTEqz4WiwUmkwlmszkwv7Y1wOv3N/yiTjeKi4uxevVqZGRkeAyW1WqF1Wp1PrZY+J3C9CseFt5gxowZCA8PR/PmzXH69Gnk5uZ6bJ+TkwOTyeRcEhMTG6lSCgRNOlwzZ86ERqPxuBw5csTZfvr06di/fz82btyIoKAgjB49Gp6OmrOysmA2m53LmTNnGuNlUYBo0udcFy9exKVLlzy2SUpKgk6nq7b+7NmzSExMxLfffov09HSvthfo5yyBXr+/adLnXDExMYiJialXX4fDAQAu51REddGkw+Wt3bt3Y8+ePbjnnnvQrFkznDhxAn/5y1+QnJzs9axFdLMmfc7lrbCwMHz88ce477770K5dO4wfPx5dunTB9u3bodfrfV0eBSjOXAA6d+6MLVu2+LoMamI4cxEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCcBEpwnARKcJwESnCz4pXoLi4GJWVlb4uo874tbMNi+FSYN26dQgNDXX7XGVlJSoqKhASEoLgYO92f336eOJwOGCz2aDRaKDT6aDRaAAA5eXltzw2/YrhUiA4OBgGg6Ha+rKyMpSVlSEiIgLh4eF1GrOsrAxXrlypV98bVVRUwGKxIDg4GM2aNXMGq+o5ajgMlwLBwcHVvgq2tLQUV69eRVRUFCIjI+s8pk6nQ3BwsDMY9RnDZrPBbDZDr9ejefPm0GpdT7kbYlakX3FvNoLS0lJYLBYYjcZ6haJKVd+qc6O6jGWz2VBUVISQkBC3waKGx3Ap1lDBqlKfgDFYvsFwKdTQwapSl4AxWL7DcCmiKlhVvAkYg+VbDJcCZWVlEBFlwariKWAMlu8xXAqUlZUhLi5OabCquAsYg+UfGC4FwsPDGyVYVW4MmM1mg9VqZbD8AMPVgEQEwC/vgDCbzY2+fbvdjuLiYgBATEwMSktL69S/avareh10azTCPdlgfvzxRyQnJ/u6jFt24sQJJCUl+bqMgMeZqwFFR0cDAE6fPg2TydTg41ssFiQmJuLMmTMwGo0NPr7ZbEbr1q2dr4NuDcPVgKrOb0wmk5If/ipGo1Hp+DxPaxjci0SKMFxEijBcDUiv12POnDnQ6/Ucn3i1kEgVzlxEijBcRIowXESKMFy3oLi4GKNGjYLRaERUVBTGjx+PK1eueOzTp08faDQal+XJJ590Pr9o0SLcfvvtMBgMSEtLw3fffedxvLVr1yIlJQUGgwGdO3fG559/7rF9XcZftWpVtVrdfTYI1UCo3gYOHChdu3aVXbt2yddffy133HGHPProox779O7dWyZMmCA///yzczGbzSIi8sEHH4hOp5MVK1ZIfn6+TJgwQaKiouTChQtux9qxY4cEBQXJa6+9JocOHZJZs2ZJSEiIHDx40G37uo6/cuVKMRqNLrWeP3++DnvoXxvDVU+HDh0SALJnzx7nui+++EI0Go0UFBTU2K93797y3HPPuX2uZ8+eMnnyZOdju90uCQkJkpOT47b9H/7wBxk8eLDLurS0NPnzn//cIOOvXLlSTCZTja+FPONhYT3t3LkTUVFRuOuuu5zrMjMzodVqsXv3bo99V69ejRYtWqBTp07IysrC1atXYbPZsG/fPmRmZjrbabVaZGZmYufOnTXWcGN7ABgwYIDb9vUZHwCuXLmCNm3aIDExEUOGDEF+fr7H10a/4nsL6+n8+fNo2bKly7rg4GBER0fj/PnzNfZ77LHH0KZNGyQkJOD//u//MGPGDBw9ehRvvfUW7HY7YmNjXdrHxsbiyJEjNdbgrr277RcVFdV5/Hbt2mHFihXo0qULzGYz5s2bh4yMDOTn56NVq1Y1vkb6BcN1k5kzZ+LVV1/12Obw4cP1Hn/ixInO/+/cuTPi4+Nx3333Ydq0afUeU5X09HSkp6c7H2dkZKB9+/ZYunQpXnrpJR9WFhgYrps8//zzGDt2rMc2SUlJiIuLQ2Fhocv6yspKFBcXIy4uzuvtpaWlAfjlymNQUBAuXLjg8vyFCxdqHC8uLs7r9i1atKjz+DcLCQlBamoqjh8/7lX7f3U857pJTEwMUlJSPC46nQ7p6em4fPky9u3b5+y7ZcsWOBwOZ2C8ceDAAQBA69at0b17d2zevNn5nMPhwObNm11mjxulp6e7tAeAvLw8t+11Ol2dx7+Z3W7HwYMHER8f71X7f3m+vqISyAYOHCipqamye/du+eabb+Q3v/mNy6X4s2fPSrt27WT37t0iInL8+HGZO3eu7N27V06ePCm5ubmSlJQk9957r4j8cqlcr9fLqlWr5NChQzJx4kSJiopyXv5+/PHHZebMmc7xd+zYIcHBwTJv3jw5fPiwzJkzp9ZL8XUZPzs7WzZs2CAnTpyQffv2yciRI8VgMEh+fn7D7sgmiuG6BZcuXZJHH31UIiIixGg0yrhx46S0tNT5/MmTJwWAbN26VURETp8+Lffee69ER0eLXq+XO+64Q6ZPn+68zyUisnDhQmndurXodDrp2bOn7Nq1y/lc7969ZcyYMS41fPTRR3LnnXeKTqeTjh07yvr16z3WXJfxp0yZ4mwbGxsrgwYNku+//74ee+pfE98VT6QIz7mIFGG4iBRhuIgUYbiIFGG4iBRhuIgUYbiIFGG4iBRhuIgUYbiIFGG4iBRhuPzcu+++i+bNm8NqtbqsHzp0KB5//HEfVUXeYLj83PDhw2G32/Hpp5861xUWFmL9+vV44oknfFgZ1Ybh8nOhoaF47LHHsHLlSue6999/H61bt0afPn18VxjViuEKABMmTMDGjRtRUFAA4JcP6xw7diw0Go2PKyNP+PdcAaJ79+4YNmwY+vfvj549e+LUqVNITEz0dVnkAT+gJkD86U9/woIFC1BQUIDMzEwGKwBw5goQZrMZCQkJqKysxLvvvosRI0b4uiSqBc+5AoTJZMIjjzyCiIgIDB061NflkBcYrgBSUFCAUaNG8WtVAwQPCwNASUkJtm3bhmHDhuHQoUNo166dr0siL/CCRgBITU1FSUkJXn31VQYrgHDmIlKE51xEijBcRIowXESKMFxEijBcRIowXESKMFxEijBcRIowXESK/D/SZkIduH9w1wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim.plot(x=0)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we use `Simulation.plot_eps()` to vizualize the permittivity of the stack. However, because the stack contains dispersive materials, we need to specify the `freq` of interest as an argument to the plotting tool.  Here we show the permittivity at the lowest and highest frequences in the range of interest.  Note that in this case, the real part of the permittivity (being plotted) only changes slightly between the two frequencies on the dispersive material.  However, for other materials with more dispersion, the effect can be much more prominent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:40:39.359274Z",
     "iopub.status.busy": "2023-08-18T17:40:39.359098Z",
     "iopub.status.idle": "2023-08-18T17:40:39.824781Z",
     "shell.execute_reply": "2023-08-18T17:40:39.824295Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the permittivity at a few frequencies\n",
    "freqs_plot = (freq_range[0], freq_range[1])\n",
    "fig, axes = plt.subplots(1, len(freqs_plot), tight_layout=True, figsize=(12, 4))\n",
    "for ax, freq_plot in zip(axes, freqs_plot):\n",
    "    sim.plot_eps(x=0, freq=freq_plot, ax=ax)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also take a look at the source to make sure it's defined correctly over our frequency range of interst."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:40:39.826859Z",
     "iopub.status.busy": "2023-08-18T17:40:39.826683Z",
     "iopub.status.idle": "2023-08-18T17:40:40.281674Z",
     "shell.execute_reply": "2023-08-18T17:40:40.281177Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RWM6xIyIiIqKmTFPHjoiIiCjSMdgRERERmURIL57QNA1Hjx5FXFzcOW2tQ0RERBTuhBCoqKhAVlYWZPnMfXIhHeyOHj2K7OzsYDeDiIiIKOgOHTqEDh06nPGYkA52cXFxALyfSHx8fJBbQ0RERBR45eXlyM7ONnLRmYR0sNOHX+Pj4xnsiIiIKKK1ZFoaF08QERERmQSDHREREZFJMNgRERERmURIz7EjIiIi/1FVFW63O9jNiHhWqxWKovjkXAx2REREEUYIgePHj6O0tDTYTaE6iYmJaNeuXZvr9jLYERERRRg91KWnpyM6OpqbAASREALV1dUoKCgAAGRmZrbpfAx2REREEURVVSPUpaSkBLs5BMDhcAAACgoKkJ6e3qZhWS6eICIiiiD6nLro6Oggt4Qa0r8fbZ3zyGBHREQUgTj8Glp89f1gsCMiIiIyCb8GO1VVcd999yE3NxcOhwNdunTBX/7yFwgh/HlZIiIiohbZv38/JEnC5s2bg90Un/Dr4oklS5bgueeew6uvvorevXtj/fr1mDFjBhISEnDHHXf489JEREREEcevwe7bb7/FFVdcgQkTJgAAcnJy8MYbb2Dt2rX+vCwRERFFAJfLBZvNFuxmhBS/DsVedNFFWLFiBXbt2gUA2LJlC7755huMHz/en5clIiIiExo5ciTmzJmDuXPnIjU1FWPHjsW2bdswfvx4xMbGIiMjAzfddBOKioqM5yxfvhzDhg1DYmIiUlJScPnllyM/Pz+In4V/+bXHbv78+SgvL0fPnj2hKApUVcXDDz+MKVOmNHu80+mE0+k07peXl/uzeRRBymrL4Na4bQ5ROLLKViREJQS7GaYmhIC7Jjjz360OqVUrQl999VX89re/xZo1a1BaWopRo0bhlltuwd/+9jfU1NTg7rvvxrXXXosvv/wSAFBVVYV58+ahX79+qKysxMKFC3HllVdi8+bNkGXzrSH1a7B766238Nprr+H1119H7969sXnzZsydOxdZWVmYNm1ak+MXL16MBx980J9NoghUVluGFza8gLLasmA3hYjOQUJUAn4z6DcMd37krhH4+wVHgnLt369tD1t0y4Ndt27d8OijjwIAHnroIeTl5WHRokXGx19++WVkZ2dj165d6N69O66++upGz3/55ZeRlpaG7du3o0+fPr75JEKIX4PdXXfdhfnz5+P6668HAPTt2xcHDhzA4sWLmw12CxYswLx584z75eXlyM7O9mcTKQK4NTfKasvgsDoQbWVBTqJwUu2uZo87NTJo0CDj/1u2bMHKlSsRGxvb5Lj8/Hx0794du3fvxsKFC/HDDz+gqKgImqYBAA4ePMhg11rV1dVNujkVRTG+qKey2+2w2+3+bBJFsGhrNGJtTX/5iSi01bhrgt0E07M6JPx+bfugXbs1YmJijP9XVlZi4sSJWLJkSZPj9D1XJ06ciE6dOuGll15CVlYWNE1Dnz594HK52tbwEOXXYDdx4kQ8/PDD6NixI3r37o1Nmzbhr3/9K26++WZ/XpaIiIhaQZKkVg2HhoqBAwfi3XffRU5ODiyWppGmuLgYP//8M1566SUMHz4cAPDNN98EupkB5ddZg08//TSuueYa/O53v0OvXr1w55134je/+Q3+8pe/+POyREREFAFmz56NkpIS3HDDDVi3bh3y8/Px2WefYcaMGVBVFUlJSUhJScGLL76IPXv24Msvv2w05cuM/Brs4uLi8OSTT+LAgQOoqalBfn4+HnroIdacISIiojbLysrCmjVroKoqxowZg759+2Lu3LlITEyELMuQZRlvvvkmNmzYgD59+uAPf/gDHnvssWA326/8OhRLRERE5CurVq1q8li3bt3w3nvvnfY5o0ePxvbt2xs91nBr05ycHFNtdWq+Ai5EREREEYrBjoiIiMgkGOyIiIiITILBjoiIiMgkGOyIiIiITILBjoiIiMgkGOyIiIiITILBjoiIiMgkGOyIiIiITII7TxAREREAoNJViVpPbcCuF2WJQqwtNmDXiwQMdkRERIRKVyVe3PAiiquLA3bNlOgU3DroVoY7H2KwIyIiItR6alFcXQyH1YFoa7Tfr1ftrkZxdTFqPbWmCnYulws2my1o1+ccOyIiIjJEW6MRa4v1++1cwuPIkSNx++23Y+7cuUhKSkJGRgZeeuklVFVVYcaMGYiLi0PXrl3x6aefGs/Ztm0bxo8fj9jYWGRkZOCmm25CUVGR8fF33nkHffv2hcPhQEpKCkaPHo2qqirjenPnzm3UhkmTJmH69OnG/ZycHPzlL3/B1KlTER8fj1tvvRUA8M0332D48OFwOBzIzs7GHXfcYZzXnxjsiIiIKGy8+uqrSE1Nxdq1a3H77bfjt7/9LSZPnoyLLroIGzduxJgxY3DTTTehuroapaWlGDVqFPLy8rB+/XosX74cJ06cwLXXXgsAOHbsGG644QbcfPPN2LFjB1atWoWrrroKQohWtenxxx9H//79sWnTJtx3333Iz8/HuHHjcPXVV2Pr1q1YtmwZvvnmG8yZM8cfX5JGOBRLREREYaN///7405/+BABYsGABHnnkEaSmpmLWrFkAgIULF+K5557D1q1b8b///Q95eXlYtGiR8fyXX34Z2dnZ2LVrFyorK+HxeHDVVVehU6dOAIC+ffu2uk2jRo3CH//4R+P+LbfcgilTphi9fd26dcNTTz2Fiy++GM899xyioqLO9dM/KwY7IiIiChv9+vUz/q8oClJSUhqFsYyMDABAQUEBtmzZgpUrVyI2tukcvvz8fIwZMwaXXnop+vbti7Fjx2LMmDG45pprkJSU1Ko2DR48uNH9LVu2YOvWrXjttdeMx4QQ0DQN+/btQ69evVp1/tZgsCMiIqKwYbVaG92XJKnRY5IkAQA0TUNlZSUmTpyIJUuWNDlPZmYmFEXBF198gW+//Raff/45nn76adx777344YcfkJubC1mWmwzLut3uJueKiYlpdL+yshK/+c1vcMcddzQ5tmPHji3/ZM8Bgx0RERGZ0sCBA/Huu+8iJycHFkvzkUeSJAwdOhRDhw7FwoUL0alTJ7z//vuYN28e0tLScOzYMeNYVVWxbds2XHLJJWe97vbt29G1a1effj4twcUTREREZEqzZ89GSUkJbrjhBqxbtw75+fn47LPPMGPGDKiqih9++AGLFi3C+vXrcfDgQbz33nsoLCw0hkpHjRqFTz75BJ988gl27tyJ3/72tygtLT3rde+++258++23mDNnDjZv3ozdu3fjww8/5OIJIiIiCqxqd7VprpOVlYU1a9bg7rvvxpgxY+B0OtGpUyeMGzcOsiwjPj4eq1evxpNPPony8nJ06tQJTzzxBMaPHw8AuPnmm7FlyxZMnToVFosFf/jDH87aWwd45wF+9dVXuPfeezF8+HAIIdClSxdcd911/v6UGeyIiIjIu71XSnQKiquLUeOuCcg1U6JTEGVp+QrRVatWNXls//79TR5rOC+uW7dueO+995o9X69evbB8+fLTXs9qteLZZ5/Fs88+e9pjmrs+AJx//vn4/PPPT/s8f2GwIyIiIsTaYnHroFu5V2yYY7AjIiIiADB2haDwxcUTRERERCbBYEdERERkEgx2RERERCbBYEdERBSBNE0LdhOoAV99P7h4goiIKILYbDbIsoyjR48iLS0NNpvN2IaLAk8IAZfLhcLCQsiyDJvN1qbzMdgRERFFEFmWkZubi2PHjuHo0aPBbg7ViY6ORseOHSHLbRtMZbAjIiKKMDabDR07doTH44GqqsFuTsRTFAUWi8UnPacMdkRERBFIkiRYrVZYrdZgN4V8iIsniIiIiEzC78HuyJEjuPHGG5GSkgKHw4G+ffti/fr1/r4sERERUcTx61DsyZMnMXToUFxyySX49NNPkZaWht27dyMpKcmflyUiIiKKSH4NdkuWLEF2djaWLl1qPJabm+vPSxIRERFFLL8Oxf73v//F4MGDMXnyZKSnpyMvLw8vvfTSaY93Op0oLy9vdCMiIiKilvFrsNu7dy+ee+45dOvWDZ999hl++9vf4o477sCrr77a7PGLFy9GQkKCccvOzvZn84iIiIhMxa/BTtM0DBw4EIsWLUJeXh5uvfVWzJo1C88//3yzxy9YsABlZWXG7dChQ/5sHhEREZGp+DXYZWZm4rzzzmv0WK9evXDw4MFmj7fb7YiPj290IyIiIqKW8WuwGzp0KH7++edGj+3atQudOnXy52WJiIiIIpJfg90f/vAHfP/991i0aBH27NmD119/HS+++CJmz57tz8sSERERRSS/Brvzzz8f77//Pt544w306dMHf/nLX/Dkk09iypQp/rwsERERUUTy+16xl19+OS6//HJ/X4aIQph6Ihqi0goICdAAaBIgJMjtKyHHu4LdPCIi0/B7sCOiyOb5KQVVj17Q7Mek5BrEPf4VJEUEuFVERObEYEdEfuVakwUAkGJdkKLdgARAFtAKoyFKHFD3JMLS42RwG0lEZBIMdkTkN8Ijwb0pAwAQfcfGRgGu+vn+cH+XBc+WNAY7IiIf8eviCSKKbOrPyUC1FVKcE0q3xuHN0r8AAODekhaMppmO8/NOqHx4CLTiqGA3hYiCiMGOiPzGvcHbW2cZWADplFcbS98iQBLQDsczjLSRZ1cSal/vBXVXMmrf6Bns5hBREDHYEZFfCK0+2FkHnWjycTnWDaVLKQDAvZW9dudK1CqoebGfd8UxAPe6THh2JgW5VUQULAx2ROQX6r4EiNIoIMoDy3nFzR5jGeAdjvVsZrA7V7Vv9oRWGA0ppQbWi44AAGpe7wWhBblhRBQUDHZE5BcevbeufwEka/Mpw9q/0Hvs9hQIF1+OWsu9JQ2ulR0BANGztiLqhp1AtBvagQS4v+4Q5NYRUTDwlZSIfE4IwL2+HQDA0swwrE7OroCUVAu4LPD8nByo5pmCVmlFzb/6AABsY/fB0qsEcrwLUVfsAQDUvtMdooaFD4giDYMdEfmcdiQW2okYwKrC2q/wtMdJEmDpVzccy9WxLSYEUPtKb4iyKMhZlYi6ZpfxMdvoA5DbVUKU21H73y5BbCURBQODHRH5nLEa9rxiSA71jMdaB9QNx25Oh+AGFC3i/j4T7nWZgKIh+tYtkGz1Q92SRXiHZAG4Ps+BeiI6WM0koiBgsCMinzvTathTWc4rBiwatMJoaMdj/N20sCc8Emr/cx4AwH7FHii55U2OsfQvhKVPIeCRUbusR6CbSERBxGBHRD6lFUVBO5AASAKWvIKzHi9FqbD0KAHA4diWUA/FQVTaIMW4YL98b7PHSBIQ9eudgKzBs6EdPDs4f5EoUjDYEZFPuTd6e+uU7ichx7ta9By97Al3oTg7dW8iAEDpUgpJOf3YtdK+EraRhwAArlXZgWgaEYUABjsi8qnWDMPqLHULLNSfk7mS8yzUvQkAAKVz2VmPtQ72fg88exL92SQiCiEMdkTkM1q5zbs/LADrwJYHO6VdNeSMKkCV4fkpxV/NMwU1PxFAy4Kd0rkUkAREUTS0Ert/G0ZEIYHBjoh8xrMpHRAS5E5lkNNqWvVcS38Ox56NqLZAOxYLAFByzx7sJIcKuaN3cYW6h9uMEUUCBjsi8hnPtlQAgLUFiyZOZdF3odiSxrInp6Hu8w7DSmnVLZ+/2LUUAODZneinVhFRKGGwIyKfUQ/FAQCUujDRGpYeJwG7B6IsCtrBOB+3zBw8dfPrLJ1LW/wcpdtJAIC6mz12RJGAwY6IfEI4ZaMOnZJd0ernS1bNGF7UAyI1ZqyIbcH8Op1FD3YH4yGcfMknMjv+lhORT6hHYwEhQYpzQkpwntM5lMwqAGCh4mYIAaj5+orY0hY/T0qphZRYC6gy1H2J/mkcEYUMBjsi8gntUDwAQM6ugCSd2znkdt5gp9YtEKB64mQURFkUIGtQOjXdbeJ0JKm+147z7IjMj8GOiHzCmF93DsOwOtnoseP+pqfS69fJHSoh2bWzHN2Y0q3Uew7OsyMyPQY7IvIJnwS7uh477UQMROuyi+npwc7SpbTVzzUWUOxJ5NeVyOQY7IiozYQANF8Eu7RqQNEAtwJR7PBV80zB04rCxKdSOpYDNhWiysb5i0Qmx2BHRG0mSu0QlTZAEpCzKs/5PJIMyBnVAACVAcQgNEDd3/qFEzrJIozncTiWyNwY7IiozfRhWDmzCpKtbWN9cjtvMNSOMdjptKOxQK0FsHvOOTjXFypmsCMyMwY7Imqz+mHYlq/WPB2WPGlKn1+n5JZBOsdX7Ybz7IjIvBjsiKjNjB67Nsyv0xkLKBjsDOdSmPhU+m4g2rFYaBVWH7SKiEIRgx0RtZlaV8OuLQsndHrJE5VDsYZz2UrsVHKs2xjGVfdwOJbIrBjsiKhNhFs25sP5MtiJEgeEU2nz+cKdcMn1Q91t6LEDAKWrvm9sYlubRUQhisGOiNpEOxYDqDIQ7YaUXNvm88mxbkgxLu+5WagY6oF4QJMhJdS2+etbvwMFe+yIzIrBjojapGFh4nPdSuxUxnAs59lBbVC/rq1fX2MHin0JEB4ffbOIKKQELNg98sgjkCQJc+fODdQliSgAVB+uiNUZCyi4Z2z9itg2DsMC3q+rFOsC3Iq3J5CITCcgwW7dunV44YUX0K9fv0BcjogCyBc7TpyKe8bW01fEnstWYqeSpIbz7DgcS2RGfg92lZWVmDJlCl566SUkJfGFhMhsfFnqRKew5AkAQKuwQiv0hlslp+09dgBg6V4KgPPsiMzK78Fu9uzZmDBhAkaPHn3WY51OJ8rLyxvdiCh0aeU2iLIoQBJQ2p/7VmKnqi95EgshfHbasKNvIya3q4QU4/HJOZUudT12dUO8RGQuFn+e/M0338TGjRuxbt26Fh2/ePFiPPjgg/5sEhH5kD4MK6dXQ4pSfXZeOb0akARQa4Eos0NKdPrs3OFEH4qWfRia9SFzUeKAqLFAcvgmMBJRaPBbj92hQ4fw+9//Hq+99hqioqJa9JwFCxagrKzMuB06dMhfzSMiH/DHMCwASFYNcmoNgMjeM1YfhpXTqn12TinGAynRWzZFPRq5X1sis/JbsNuwYQMKCgowcOBAWCwWWCwWfPXVV3jqqadgsVigqk3f3dvtdsTHxze6EVHoUv2wcEInZ9btkhDB8+yMYJde49Pz6jtQaEe56pjIbPw2FHvppZfixx9/bPTYjBkz0LNnT9x9991QFFaUJwp3/ih1opPbVQFbI3sBhVbgAODbHjsAULIqoW5PhcpgR2Q6fgt2cXFx6NOnT6PHYmJikJKS0uRxIgo/QpWgHfFnj51eyy4yg50QDXvsfBvs5Ky6ry2DHZHpcOcJIjon2vEYwCMDUR5Iqb4dKgQAJTOyS56IChvgtACSgJzS9q3aGtJXMGtHGOyIzMavq2JPtWrVqkBejoj8yBiG7VAByQ9vEeWMumBX6IDwSJAskVX3RCvw9tZJSbWQrJpPz23MsStyQDhlSHbfnp+Igoc9dkR0Tvyx40RDUpITiPIAmmyEnEiiFdbNr/PxMCwAyPEuSHEuQEjQjrPXjshMGOyI6Jz4q9SJTpIa9NpF4Dw7PczKab4f5gbqe+1UDscSmQqDHRGdE/Wwf3vsgMieZ+ePGnYNKUbJk8j72hKZGYMdEbWacMoQxXVDhVm+2xXhVHLdnrGRWMvOn0OxQP1uFuyxIzIXBjsiajVjYn+MC3Ks22/XieSSJ/4eilVYpJjIlBjsiKjV9KFROcM/vUk6pZ0+FBtZ4UO4ZYiT3q0Y/d1jp52IgXDzTwGRWfC3mYhaTT2hB7sqv15HH4oVFTZolVa/XiuUaMVRgJAAu8e7etUPpAQnEO2uWxkbeauOicyKwY6IWk07UTdM6OceOylKhZTkLc4bSQso6odhqyFJ/rmGJNUPx3JrMSLzYLAjolYzhmLb+bfHDgDkzMpG14wE9VuJ+Wd+nU7mDhREpsNgR0StFqgeO6DhPLvIGS7UCupWxPqp1ImOPXZE5sNgR0StImoUiDLvxH7Fz3PsAEBOrRuKrSuvEgn8XcNOZ2wtxh47ItNgsCOiVtEKvEOiUpwTUozH79eTkr3DkVpJlN+vFSqMOXZ+HopVGq6M9fhpMh8RBRSDHRG1ino8cMOwACDXLZ4QERLshAhcj52UXOvdj1eNzP14icyIwY6IWkU7EbiFEwAgp9QNxZ6MghABuWRQiQobUGsBAMip/u2xkyRAyeRwLJGZMNgRUatoAe6xkxKd3v+4FW/oMTl9KzEpqRaSTfP79YytxbiAgsgUGOyIqFW0ABUn1klWzVtMFzB2YzCzhjXsAoFbixGZC4MdEbWKHuyUdoEJHgAg6wsoiiMg2Bk17AI0h5E9dkSmwmBHRC0mqizGcKicHpgeOwD1u09EwAIKfShWTvPv/Dqd0WN3LAbC/yO/RORnDHZE1GL6HrFSQi0khxqw6+oLKCJhZWygh2Kl1BrApgJuxegtJKLwxWBHRC0WyB0nGpKTI6nHLrBDsZLcYNs2rowlCnsMdkTUYoHcI7ah+qFYc+8+ITyS0SsZqB47gFuLEZkJgx0RtZjeYxfIhRNA5AzFakUOQEiATYWU4ArYdfUFFOyxIwp/DHZE1GKBLnWiM1bFnowy9QT/hjtOSAHc4YslT4jMg8GOiFpECEA9HpxgJyU6AUkAHhmi0rxFigO9cEJXX/KEK2OJwh2DHRG1iKi0AtVWAIGb2K+TLKK+SLGJa9kZpU7SA1PqRCen1QAWDXBZIIrNPY+RyOwY7IioRfRhWCm5BpI98N06cgTUsms4FBtIkiKMsK73yhJReGKwI6IWCfQesaeSUiIg2BUEttRJQ/pKZ/37TEThicGOiFrE2EoswPPrdPW17Mw5VChE4HedaMgIdifYY0cUzhjsiKhFglWcWKcPxZq15ImosgI1dXMYUwP/NdYDu8ahWKKwxmBHRC2iBqk4sU5KqSt5YtJgpw/DSom1wZnD2I7BjsgMGOyI6KyEaFjDLkg9dibfVqx+GDZIX1892BU5INz800AUrvjbS0RnJcptQK0FkERQJvYD9cFOmLRIcX0Nu8DPrwPg3ekiygMIyQiZRBR+/BrsFi9ejPPPPx9xcXFIT0/HpEmT8PPPP/vzkkTkB0apk5QaSNbgpCqjSLEqe4OmyYii4PbYSRKgcDiWKOz5Ndh99dVXmD17Nr7//nt88cUXcLvdGDNmDKqqgjNHh4jOjf6HXgnSMCzgrbUmJXqLFJtxZax20jvErPdMBgPn2RGFP4s/T758+fJG91955RWkp6djw4YNGDFihD8vTUQ+ZNSwC9LCCZ2cXAv1ZJR3ZWznsqC2xdf0YCclBT/YsUgxUfgK6By7sjLvC3FycnIgL0tEbaQGeeGETko278pYvYyLnOQMWhvYY0cU/vzaY9eQpmmYO3cuhg4dij59+jR7jNPphNNZ/6JWXl4eqOYR0RnU17ALco+dSbcVEy4ZotI7b1AK5lBsXXDn7hNE4StgPXazZ8/Gtm3b8Oabb572mMWLFyMhIcG4ZWdnB6p5RHQa3lInITIUm2LOIsWi1O79j1WFFOMOWjv0IsWiLAqiJmDv+4nIhwIS7ObMmYOPP/4YK1euRIcOHU573IIFC1BWVmbcDh06FIjmEdEZiJN2wGUBZA1yanBKcejMWstOM4ZhayFJwWuHFOOBFF+3QIW9dkRhya9vyYQQuP322/H+++9j1apVyM3NPePxdrsddrvdn00iolbSCurm16XWQLKIoLZFH6bUFxqYhbFwIojDsDq5XRXUcjvU4zFQcjkdhijc+DXYzZ49G6+//jo+/PBDxMXF4fjx4wCAhIQEOBzmK1dAZEbB3iO2oVOLFEsmKbEuTgZ/4YROblcFdVcyF1AQhSm/viw+99xzKCsrw8iRI5GZmWncli1b5s/LEpEPhcrCCcC7jypkzVukuMw8vfuhUOpEp7SrW0BxgsGOKBz5fSiWiMJbqJQ6Abw9dFKiE6LEAa0kKiR6uHxBO+kNqXIIBDs9wHOOHVF4MslABhH5i7GHaZD2iD2VMRxrogUUosHiiWBrWKSY782Jwg+DHRGdVqNSJyHQYwc0XBlrnnm69UOxwe+BlNOrvXvy1lghKsy3Jy+R2THYEdFpiTIb4LQAkgh6qROdsTK2xBxz7IQGY75gMPeJ1Uk2DVJK3Q4fXEBBFHYY7IjotPRSJ1JKDSSrFuTWeNUPxZqjx06U2wFVBiQBKSH4PXYAoHBrMaKwxWBHRKelD8MqITIMC5ivSLG+cEJKcEJSQmNSW/2esVxAQRRuGOyI6LSM+XUhsnACAKTkumFCkwS7+hp2wR+G1enzKVX22BGFHQY7IjotY0VskPeIbcgYii21Q4TG6HCb6AE1FGrY6WQOxRKFLQY7IjotvUhtSPXYJTgBRQM0GaI0/BdQGD12IbBwQmfMsSuINkV4JookDHZE1CwhALUgtEqdAPVFigFzlDwx5tiFQKkTnZRa4w3PbgWiOPy/xkSRhMGOiJolKmxAtdVb6iQtdIIdAMh18+zMUKRYC8E5dpLMeXZE4YrBjoiapc+vk5JqIdlCazzOTCtjQ3EoFuDKWKJwxWBHRM0KtR0nGpJMEuyECM3FE0CDYHeCPXZE4cQS7AYQhRL1eDRcX2VDOxQHS69iWC84DjktNHZcCLT6UiehsyJWZ5r9Ymss3p09AMghNMcOAJQMrowlCkcMdhTxhEuGe307uL7qAHVnivG458c01L7VE0puKawXHIf1/MgKefquE6FUnFhnlqFYfX4dot2Q7GpwG3MKvccuUufYCU3g6BYXPC4Ba5QES5QEq0OCNUpGTKoMSZaC3USiZjHYUcQSGuD8b1e4Pu8EUVW32bkkYOlXCEvPErh/TIW6IwXqvkSo+xJRu6wn7JN2I+rKPcFteICE9FBs3bClVhrmwa4k9BZO6PRgJ4ocEG45ZLaUC4TKIhX/t6AYB75rvhc1KceC0fcmIefC8P75I3NisKOIJFwyal7sB/e6TADe3QxsIw7DNuIw5BTvH1n7L/dBK7fBvT4D7rWZUHekwPlBN8jtqmC78Fgwmx8Q9cEuBIdi68qdiFI7hACkMO08EXWlTkJt4QQASAkuIMoD1FqgFURDaV8Z7CYFxL41tfi/BcWoLtFgsUtIzFbgrhVw1wh46v49ud+Dt2cVoteEaIy8KxGxqUqwm01kYLCjiKNVWlH95ECou5MBRYNj+jZYhx2B1MxSIjneBfuoQ7CPOoTat7vD+XEX1PyrL5R2VVByywPf+ADRKq1GL6acHnrDz1JCXU+KKkNUWiHFuYPboHOkD8WG2sIJwBuW5YwqaAcSoB03f7BT3QLfPFOGtf+qAACkdrNi4uMpSO1ibXScs1LDN0+VYdObldjxSTX2rq7BiLmJ6D85hsOzFBK4KpYiilboQNVDv/CGumg3Yu5aB9uI5kPdqexX74KlfwHgVlD11EBoZTb/NzhIjFInibUhN/cLACSLgBTnAlBfLiQc1e8TG1oLJ3RKpr6AIjbILfGv8mMevDGtwAh1A66LwY1vpDcJdQBgj5Vx6T1JuPH1DGScZ4WzQuCLv5zE6zcVoKo49H5XKPIw2FHEEPuTUPnnC6Edi4WUXIPYe7+HpVdJi58vyUD0bVsgZ1ZClDhQ/UwehMec79BDeX6dTkqsm2dXFr7bioViceKG5Lpgpx417wIKzSPw/u1FOLbVBXu8hCv+loLL7kuGNerMfx7b9bHhxjcycOk9ibDFSDi6xYVlMwpQWcBwR8HFYEcRQdmXAe3xkRDldsgdyxG78DsoHVo/tCRFexD9+42Aww11VzJq/3OeH1obfMYesSE4v05nzLM7Gc7BTt9OLFSDnfd3RDtm3mC34T8VKNjpRlS8jGlvt0P3y1pekFlWJAz8dRymvpWBuHYKivd6e/7Kj3n82GKiM2OwI9Mr3ash5sXxgNMC5bwixN7zfZuGvpTMKkTftgWQBFwrO8L5ZbYPWxsa6mvYhXKPXd1+sWHcYydCeFUsAChZ3mCnHouFEEFujB+UHfVgzT+8c2VH3pmAhPbnNu08qZMVN7yajoQOCkoPecPdyYMMdxQcDHZkauXHPPjsDhfk6iggtxgxczdCcrR9qMQ6oBD2a3YBAGrf6AmtsulcnHCmz7ELxRp2OrluKDZc59gJtwxRUddjF4KrYoG6oXhJANVWCJPNKRVC4H8PnYS7RqDDYDv6XNm2XsmE9hbc8Go6knIsKD+q4s3pBSjeG56Leii8MdiRadWUqXjntkJUFwioGSch3/GNTxcC2CfshdyxHHBZ4FrR0WfnDQXhMccuvHvsRGldu60qpNjQDACSTYOc6l0VrR0z1wKKXf+rwd7VtZAtwJj7kiD5oGZOXIYF17+SjtSuFlQWeMNdUX5ofm/JvBjsyJTcNRrem12E4nwPotOAyts+gRTr8uk1JAmw/3IvAMD1RQ6Eyxy/TqLaYvQkheJ2Yrpwn2NnlDpJdIZ0HT7ZGI41zzw7Z4WGFYtOAgCG3BKPlGZWv56r2FQF1y1NR3ovK6pLNLw9qxBlRzgsS4Fjjr9ERA1oHoGP7izG0c3eVW5jnrJDJPunBpf1guOQUqshKmxwfd3BL9cINKPUSYLTJ8PW/hLuPXb6wolQnV+nMxZQHDVPj93XT5ehqlBDYkcLfjEr3ufnj05ScO0/04yeu7dmFaKqKHR/l8hcGOzIVIQQ+PzBk8j/qhYWu4Srnk5DUhf//ZhLioB93H4AgOvTXAgT7LqkGgsnQre3Dmgwx640Kiwn9of6wgmdUcvOJD12x350YtMb3rA6ZmESLHb/dJc6EhRMfjEdCe0VlB704J3bCuGsMMELBIU8Bjsyla//XoYf36+CJAOXP5qMDoP835tjG3EYUowLWmE0POvb+f16/qb32IXy/DqgbssrAPDIEFXht3gllHedaEhusDI23AnhLSYMAZw3MRqdfuHfhTex6Qomv5SG6BQZBTvdeG9OEdw1DHfkXwx2ZBob/r8K/PBPb+X4MQuT0O3SltejagvJrsI2+gAAwPlJ57DsPWrIqGEXwqVOAECyasa8yXCcZ2fsOpEcmrtO6OQsb4+dKHZA1Ib3nqiH1jlxYrsbVoeEkXcmBuSaSR2tmPxCGuxxEg5vcOK/fyyG6g7zFwkKaQx2ZAo7/q8KXy4pBQAMuz0B/a4JbO+CbfRBwKpC3Z8AdWdyQK/ta+GwIlZn7D5RGn4lT7QwGYqVY93G9m3a8fAejt28zNv7eN7EaMSkBC6kpve04ap/pMFil7B3dS3+754SaB6GO/IPBjsKe/vWeF8oAWDgr2Pxi1vjAt4GOd4F24jDALy9duGsPtiF9hw7oMHK2NLw67HTSkO7hl1D+gKKcF4ZW1moYvcKb+mWAdcFfli5w0A7fvXXFMgWYOen1fi/e0ugqQx35HsMdhTWjv3oxIdzi6B5gJ7jHBg1P9En9ajOhX3cPkAS8PyYBvVg4MOlL4haBaLM25OkhPhQLNBgZWyYBTuhNRiKDfEeO8AcK2O3vlsJzQO0z7MhvUdwii13udiBiY97w92OT6rxKcMd+QGDHYWtwxudePvWQrhrBDr9wo7xi1IgycErCCan18B6wTEAgPPT3KC1oy2MUiexLkgxoV97K1x77ESFDVBlQBKQEkJ7jh0AKHXz7MK1x07zCGx52/s5DLg+uOG0++hoTHzMG+62f1yNT//EcEe+xWBHYWnv1zV4+9ZCOCsE2g+0YdLfU2GxBb/Kq338PgCA+/tMYw5VOAmn+XVA+M6x03vrpHgnJEvo/1E3euzCdGXsnlU1qDyhIjpZRvfLArOo6ky6XxaNyx9LgaQA2z+qxvKFDHfkOwEJdv/4xz+Qk5ODqKgoDBkyBGvXrg3EZcmkdn5ajfdvL4KnViB3eBQmv5AGW0xovEdRcsuhdC8BNBnuteFX+kQ1VsSG/vw6IHx77OoXToR+bx1Q32OnHY8Jy1qN+qKJvlfFhMQbQADocVk0Jj7qDXc/fViN5feVcLUs+YTf/xouW7YM8+bNw/3334+NGzeif//+GDt2LAoKCvx9aTKhzW9V4qP/V+ydUzc+Glc+lQqrIzRCnc46xDsc616bGeSWtJ52tC7YZYZHsJOSwnOOXbjUsNNJKTWAVQU8MrTC4Pd4tUbJfjcOfOcEJKD/5NDqcewxNhqXL6kLd/+txrKbC1DJHSqojSz+vsBf//pXzJo1CzNmzAAAPP/88/jkk0/w8ssvY/78+f6+vGkIIaB5ANUtvBOvNQDC+7jQAEkGFKsE2SpBsSCoc838QWgC379UgW+eLgMA9L82BqPvTYKshN7naR18HLX/OQ9qfiK0QgfktJpgN6nF9MnxSnv/bMHma3KC3mPn3X0ilPdcbUivuyeHwYpYwPv6ImdWQTsYD+1YDJQwGaoHvG8GAaDLiCgktPf7n7xW6zkuGrYYCR//v2Ic2eTC/3fdCUx6MgWZfcPrzUpzVLdAbZmG2jINNWUaass1eGoEVI+A5hZQPd75j0IFJAsgKxJkGZAtEiQFsNglWGwSLFESFJsEa5T3/1ZH3b9194O1YC5U+fWn3OVyYcOGDViwYIHxmCzLGD16NL777jt/XrpVDq2vxf5vmxkSOU2lWSHgDVWo+1e/XxeyhOp9TFO99zVP3f9V77+qG94f6rofbNVd90Pu8n5MdQl4XAKa2/sx1e0Nda0hWwDFJiEqTkZUgoyoeBn2eBmOBBlx7RQktLcgPsv7b2y6AsUaur8YpYc8WH5fCQ6t936PhtwSh+G/TwjZX2Y50QWlRwnUnSlwr2sH+y/3BbtJLSJE/e4C+m4DoU5fFavvPiHFuoPboBYKtx47AFAyK73B7mgsMKAw2M1pEXeNhm0fhMaiiTPpPNyBG9/IwAd3FKF4rwdvTCvAmPuT0eeK0F6sIjSBsiMqiva4UXbYg7Ij3lvpYRXlxzxwVQZmaNnqkLwhUA99df+32L2B0GLT/w9v54dV8v6NtEpQ6kKkrHg7RCQFkGVAUiRIACDVvWHUb81IbG9B5xGOgHyuLeHXYFdUVARVVZGRkdHo8YyMDOzcubPJ8U6nE05nfcAqLy/3Z/MMR7e48P2LgblWoGh174Tc1SoqTpy5a1+SgcRsC9K6W5HWw4q07jakdbciIUsJas+f0AQ2v1WJr54og7tGeKvF35WIAdeG7gu0zjrkmDfYrQ2jYHcyCqi1AIoW8rtO6CSrBinGBVFl886zC5NgV1/qJDzm2AH1w/PhtDJ256fVcJYLJHRQkDs0tBfYJOdYMeX1DPzfgmLsWVmLT+8twYmfXBg+NwG26OBPNxGaQNEeN45vc6FgpxsFP7tR8LPr7OFNQoMOBgnWaNkbqizeESbZ4g1SWl0niNC8nSCqR0B1AR6naHyrEXDXalBd9Zdw1wi4a4I3P7HrKEfkBLvWWrx4MR588MGAXzfjPBsG/vo0YaFBrmnUQVSX3qW6SC9JgKR470uyBEn2/l+21P3gKt5uZkmpe5fQ4B2D9x2Et4dNafJ/733ZUvcca915ZP1a3nboPYNGD58bcNd6u8Bry+u6w8s11JSqqDimouyoB+VHVZQf9UB1AycPeHDygAe7vqgfNrTHScjsa0dWfxuyBtiQ2deOqPjAvMCUHfFg+cISHPzB+4cve7Ad4/6SjMTskPqRPS3r4BOo/XdvqPsSoRU4IKeH/nCserR+K7FwWKmpk5KcEFU2aKV2KB3Co6dRC6Madjq9Fzecatnpiyb6XxsbFtNT7LEyJv09Fd8+V45vnyvHxtcr8fMX1Rj6uwT0vTIGsiVwn4PHKXD8JxeObHTi8AYnjmxxwlne9HVBsQIpXa1IzLYgob1+U5CQZUF0qgx7rOyXKTOa6g167moBd23j0OdxeoOe6qobAXN6R8FUpz4MXBcc60bDNE/9aJtWFyyFpo/GCWPw7nTbRbbrE5y6iKfj17+SqampUBQFJ06caPT4iRMn0K5d0xWDCxYswLx584z75eXlyM7O9mcTAQA5F0Yh58LQfjd3NnpXssXe8Bfo7FvmCE2gslBFcb4HhbtcKNzlRuEuN4rz3XBWCOz/thb7v6374yMBKZ0taD/AjvZ5drTPsyGxo8VnQ6JCCBzZ5MK296uwc3m10Us34g8JyLs+PF6YdXK8C0qvYqjbU+Fam4moy/cGu0lnpf/BDpdhWJ2c4IR2OA4ijEqeGLtOhFGwU+p67LRjMWExn/HEdheO/+SGYgP6Xhk+vYySLGHo7ARk9Lbhy0dOouywis8fPIn1/67AiLkJ6DrK4ZdpKB6nwLGtThxc58ShdU4c3eJs1CsGeIc8M/vakN7LivQeNqT3tCI51xqUqTyyIsEWLcEWXmt5AsKvwc5ms2HQoEFYsWIFJk2aBADQNA0rVqzAnDlzmhxvt9tht4f/hNFwIskS4jIsiMuwIOei+j+MqlugaLcbR7Y4cXSzC0e3OFF22BsAi/M92Pqu90U+OllG1gA72vW2Iq2Hdwg3PlNp1QtPZYGKn/5bhR8/qMLJ/fWTCTsMtmPcn5OR1DE8eulOZRtyDDXbU+Fe2y6sgp0SZsFOD0fhsjJWOBWg2gogzIZi21UBkvAOe1fYIMW7zv6kINq53DudoOslDkQnBW5fWF/pOtKBnIuisGVZJb57oRwl+zz44PfFyBpgQ99JMcgZGoX4zHN/bawqUnHsR+9r+9HNLhzd2jTIRafI6DDIjg55drQfaEd6D2tAew3p3Pj9L+a8efMwbdo0DB48GBdccAGefPJJVFVVGatkKTQpVgkZ59m8w9Q3eB+rKlJxdIsTRza7cGSTEyd+cqG6RMOeL2uw58sGQ7jxEtK625DQXvEu2oiTjX8BGBNsy46oKD/iQflxtW4livcdYY+x0eh7VQza59lCdoFES1gGnQBe7Q3tQALU49FQ2oX2vDVV77ELk1InuvqVseER7IwAavMAUaG/u4dOsmmQUmsgCqOhHY2BHMLBTgiBnz/3/r71GBO+XToWm4RBN8Whz6QYrF1agfX/rvCGsM3er31yrvcNec5FUUjqZIHVIcEWLcPqkCBbJKhugYrj3oUM5Ue9U3BK9nlwbKsTZUeazr2OSZWRfX4UOl5gR/b5diR18t2IDAWO34Pdddddh8LCQixcuBDHjx/HgAEDsHz58iYLKij0xaQq6HZpNLpd6n2h9DgFTmz3vuPTJ9OW7HPDWS5weL0Th9e3/Nzt82zoe2UMeoyNDpliw20lx7lhOa8Ynm1pcK/NhPKr/GA36Yz0Gnbh12MXXrXsjFInSc6QH848lZJZCU9htHcHip4ng92c0yrY4UbZYRWWKAm5w8NniP507HEyht/hnZKy5Z1K7P+2Fsd+dKFknwcl+yqx8bWmv7OKFdDq5oo1SwJSu1iQ2c+OzH42ZA+yIymHQc4MAjLGNWfOnGaHXim8WexS3Vy7+j+oqlugON87T6+yUEVtuQZnuXfhRm25BggYE2zj23vLrSRmWxCTEn5DJS1hHXK8Lti1Q1QIBzut0gpRURc4ssKsx07ffeJkePwB17c/M0q1hBE5swrYGvorY3/+zNtb13lEVEisKPWV2HQFQ3+XgKG/S0BtuYaDa71zoA/+4ERVsQp3jXfiPwCodQvEFRsQn2VBfKZ3QUNCBwva9bEhs4/NGEUhcwnPyUsUshSrhPSeNqT3DK1VQsFiGXgCeKU3tEPxUI/GGFszhRp9fp2UUgPJHl6V7439YsvCpMeurmdRTgyfhRM6JQxWxnqHYb1TQ8J5GPZsouJldB8dje6j6z9HIby1UN3VGlzVAopNQkyyHFYLz6jtGNeJ/EiOdcPSpwhAaG8xFq7DsEDj/WJPV44glGgn9RWxYdpjh9DusSvY6UbpIQ8sdgmdR4RHL66vSJK3GK8j0ds7F5sa3FqkFBwMdkR+Zr3gOADAvbZpiZ9QUb9wIvyCnVS3eAJuBagO/UEIvSxLOPbY6cFOFDsgnKH552NX3aKJ3OHmGoYlain+1BP5mTXvBGDRoB2Jg3o4NIew6kudhOZQ8ZlINu/uE0B94d9QZtSwC8c5dvEuSLEuQEjQjoder12kDMMSnQmDHZGfSTEeWPp499Z0rw/NXjt9aC3cihPr9JAkwmCeXThuJ9aQ3qur7yscSgp/duPkAe8wbJeLQz/kE/kDgx1RAFgHFgAAPFvSgtySpoRTgSjy9m6Ea7DT59np89dClRANe+zCbygWqB+O1UJwnp3eW5czNMo0ZZOIWos/+UQBYOnn7bFT9yVAKw+tFcP6H2gpzgU5zh3k1pwbY2VsqG8rVmsBnN55gHIYDsUC9Qts1COh1WPXqCjx2NDZkJ0o0BjsiAJATnJC7lQGCAmeranBbk4j4bxwQtdwZWwoM3oUHW5IUeFVVkandKwAAGgH44PcksaKdrtxcr8His27HRdRpGKwIwoQa39vr51nS3qQW9JYOJc60elz7EJ994n6Gnbh2VsHAHKncgCAdiIGIoRWIevDsLnDHByGpYjGn36iALHUBTv3tlQIT+jUltInwYfbjhMNhU+PXd2uE0nhOb8O8NZmlFK9Q57qgdDotRNCGLtNdL+MvXUU2RjsiAJE6VwKKc4FVFuh7kkMdnMMeqmTcF04AYTPHDsz9NgBgFLXaxcqwa4437u5vWLlMCwRgx1RgEgyYOlb12sXIsOxwiNBO+FdERvOQ7HhsvtEOO8T25AR7PaHRrDTF03kDI3i/qcU8fgbQBRAFmOeXWiUPdEKogFVBuweSMnhOzxoBKUQ331C1C2ekMN4KBYAlJwyAIB6ICHILfHa86V3fl3DfVOJIhWDHVEAWfoUAZKAdiQOWlHwhw3rd5yohBQ60/5aTbJpQLS3VEsoD8dqZhmKzalbQHEsBqJWCWpbyo56ULDTDUkGOrMoMRGDHVEgybFuKN1OAgiN4Vhjx4nM8F04odP3Xg3lBRT1Q7Hh3WMnJ7i8n4OQoB6MC2pb8ld6e+va59kRnRTckEkUChjsiAIslIZjzbBwQhfqJU+EaLB4Iky3E2tI77UL9nDs7rpg1/US9tYRAQx2RAFnrduFwrMjBcIV3F/BhkOx4a5+AUVo/oEXVVbvHEAAUoIZgl3dPLsgLqCoLddweL33a9l1FFfDEgEMdkQBJ2dXQEquAVwKPDuSg9YOoQFqXXHicK5hpwv5Hjt9j9gYl3dOYJgLhZIne7+ugeYBUrpYkNTRGrR2EIUSBjuiAJOk0NiFQpREAS4LoGiQ06uD1g5f0Vea6itPQ019ceLw760DGiygOBIbtJ5nfTVsN/bWERkY7IiCwNJPr2eXFrS6a8YesRlVkJQQLv7WQvrwplYWmsGuvjhxeC+c0ElJtZDinIAmQz0U+AUUHpfA3q+9X0sOwxLVY7AjCgJL72LAqkIURUOrW5kaaPULJ8J/GBaoX5AgTobmHDt9iDjcixPrJKnhAorAD8ceWlsLd7VATJqMdr1tAb8+UahisCMKAsmuwtKzBADg2Ryc4Vh9fp0ZFk4AjXvsQnH3CT1whntx4oaCuYBid90wbNeRDkhyGBdhJPIxBjuiINHLnriDVPZEO+z9Y2yGUidAgyFOV2juPmG2Hjug4dZigS15IjSB/FUchiVqDoMdUZDo8+zU3UkQVYENIsItG8NnSueygF7bXyR7aO8+oZdhCfddJxoyFlAcjoPwBK7X7PhPLlQWqLBGS+g4JPS+10TBxGBHFCRKRrW3t0yV4d6WGtBrqwfjAI8MKc5lihWxOn2YUwvBlbF6myQTDcVKqTWQYlyAKkM7ErgFFHtWer+GucOiYLFxGJaoIQY7oiCyDCgAEPh5dmp+IgBA6Vwa1nvEnipUixQLDRBl5tgntiFJAmRjODZw8+z2GLtNcBiW6FQMdkRBZO1fF+x+TIMIYM1aI9h1KQ3cRQNACtEeO1FpA1Tvy60Zdp1oyFgZG6Bgd/KgB0W73ZAUoMsIBjuiUzHYEQWR0q0UiHZDVNig7k0M2HU9dcHO0rU0YNcMhPoixSHWY6cvnIh3QrKE4JLdNqjfgSIwCyj03rrswXZEJfBPGNGp+FtBFESSImDtW7cLxebArI7Vym0QhdGAJKDkmmPhhE7f1SHUeuyM+XUmGobVGSVPDsZBqP4f19d3m+AwLFHzGOyIgswyoK7sSYDm2enDsHJmJaRoT0CuGSh6yZOQm2NXar4adjo5vRqI8gBuxe/FtitOeHB4ozccd7uUwY6oOQx2REFm6VcISALaoXhoxf4PJGq+d8hMMdkwLNCwxy60gp0Za9jpJDlw9ex+/rwGEED7PBviM0OvViFRKGCwIwoyOdYNpetJAIEpVmzMrzNJ/bqGjDl2ZbaALkY5G2PXCZPsE3sqpVNgdqDY+am3NE/P8dF+vQ5ROGOwIwoB+nCsv8ueCA3GIg2zrYgFACneBUgC0GSI8tCZZ2f02CWZr8cOCMyesRVHNBzb6oIkA93HMNgRnY7fgt3+/fsxc+ZM5ObmwuFwoEuXLrj//vvhcrn8dUmisGXV69ltT4Fw+u/9lnY0Fqi1AHYP5A4VfrtOsEiKqN8zNoQWUOirYs1Uw66h+pInCRAu//z87vufCgDIvsCO2FTFL9cgMgO//QXZuXMnNE3DCy+8gJ9++gl/+9vf8Pzzz+Oee+7x1yWJwpbcvhJSajXgVuDZkeK366h7EgEASm4ZJJP214diyRPN5EOxclYlpMRawOW/n999X3iDXc9x7K0jOhO/vbSPGzcOS5cuxZgxY9C5c2f86le/wp133on33nvPX5ckCluSBFj7+3841lM3DGsx4TCsLtQWUDTcdcKsQ7GSBFjz6nqdN/n+51c+kYiSXQKyBeg+mqthic4koO/Zy8rKkJycfNqPO51OlJeXN7oRRQpL3S4U7i1pEH6qYWvsOGHCFbG6+pInoTEUK8rtgJAASUCKN2ewAwBL3gkAgHtTus9/fq0buwAAci6MgiORw7BEZxKwYLdnzx48/fTT+M1vfnPaYxYvXoyEhATjlp2dHajmEQWdpVcJYPNAlDigHfL9huqixgLtSCwA7x6xZhVyPXZ6ceIEp2mHv4G6n1+7B6I0CpoPV8cKAdg2dQUA9OAwLNFZtfplZv78+ZAk6Yy3nTt3NnrOkSNHMG7cOEyePBmzZs067bkXLFiAsrIy43bo0KHWf0ZEYUqyabD0Lgbgn2LF6r54QEiQUqshJ5p3EZMxxy5Eeuw0vTixSRdO6CSbBkufIgA+/vk9kgDlRBIUG9BtFIdhic6m1RUe//jHP2L69OlnPKZz587G/48ePYpLLrkEF110EV588cUzPs9ut8NuD40XY6JgsA4ogGdThnd7sV/l+/TcRv06E8+vA+qLAIdKj119cWJzLpxoyJpXAM+GdnBvSkfUlXt8ck6x1jty0/4iGfY4E3d5EvlIq4NdWloa0tJaVkT1yJEjuOSSSzBo0CAsXboUssxfSqIzsfTzLqBQ9yZCK46CnOK7MGCsiDVhYeKG6lfFhsabRL0dskkXTjRk6V+3i8qBBJ/8/AoBiHXeYNf5Ms6tI2oJvyWtI0eOYOTIkejYsSMef/xxFBYW4vjx4zh+/Li/LkkU9uRkJ5SexYCQ4Po2y2fnFaJBYWITL5wAGgS7Kpvfaqq1hj4Ua8btxE4lx7vqd1HxwXCsui8BKIqFsLnRYRiDHVFL+O1V74svvsCePXuwYsUKdOjQAZmZmcaNiE7PNvQoAMC9pr3PVheKIod3daaiQelo8tXm0R7A5q15Fgrz7OqLE5t/KBYArHl1ZXt8UPbE/YP374W7z35YHVKbz0cUCfwW7KZPnw4hRLM3Ijo96/nHAZsK7Vgs1L2+2VTdow/DdiyHZAuhTVT9QJLqQ1QozLPT22DWGnan0sueeHakQNScey+b0OqDnWugb+ebEplZ8McpiKgRyeGBdVBdTbA17X1yzkgZhtWFUsmTSOuxkzOrIGdUAR4Znm2p53we9w+Z3t1DYpzw9GSFBKKWYrAjCkHWoUcAAO7vMyHcbf81NQoTm3zhhC5UihQLj+QdAkfk9NhJEmCp24XiXOfZCQ1wfuitXSeN3g1YVZ+1j8jsGOyIQpCldxGkxFqIKhs8W1q2Cv10tEor1LqCsYrJS53opKTQGIrVtxKDokGKNW/twFNZB9RtL7Y5HeIcRv7dazOhHYsFot2QRu32ceuIzI3BjigESTJgvci7iMK1pm2rY93fZgGqDLljOeT0al80L+TppUWCXfJEK9Hn19WaeteJUyndTkKKcUFU2qDuSWrVcxv21tnH7YMU7fFHE4lMK4JeaojCi61uONazJR1ahfWcziEE4FrlrQNmG3kIUoQsLAyVHjs92MnJkTG/TidZhFGT0d3K1bHude2gHfX21tkvO+CP5hGZGoMdUYhSOlRCySkDVBnu78+tTJC6JxHakTjApsJ24VEftzB0GT12wZ5jV+zdAivSgh1QP8+uNWVPGvXWjdnP3jqic8BgRxTCjEUU57g6Vu+ts15wLKL+SDYsdxLMCkvGUGwEBjtr3yJA0aAdi4VnV2KLnuNZ3877RiTaDfuY/X5tH5FZMdgRhTDrL44BigZ1XyLUI7Gteq6otsC91tvTZ7s4sspFGLs8uBWgutU7J/pM/VBsTdDaECxStAfWX3h7iaufGwCt3HbG44UG1Oq9dZfthxQTOW9EiHyJwY4ohMnxrvq5Sq1cROH6LgtwKZCzKqF0K/VD60KXZNMgxXhXoQZznp3Qg50P9/wNJ46bdkBuVwlR4kDN8/3PuELWsyED2uE4wOGGfez+gLWRyGwY7IhCnG2YdzjW9W37VpWOcH3Vwfv8CFo00VAoLKDQSiJ3jh3gLbYdffsmwOaB56dUOD/o2uxxjXrrxhxgbx1RGzDYEYU4S/9Cb+mIk1Etnmun7ouHdiABsGjGPL1IE+ySJ8IjGXXsInGOnU7pUAnHjJ8AAM4Pu8G9pfFuFOqBeFQ9egG0Q/FAlAc2zq0jahMGO6IQJ1k12MbvAwDU/Oc8aAWOsz7H9VXdoonBxyHHuv3avlBl9NiVBqfHTug9hVYVUlzkFCduju2io7CN8pYuqXmhP7SiKGglUah+qS8q778I6o4UwKrCMWV7xP68EvlK8GYVE1GL2SfshWdrGtRdyah+oT9i7vkBktL8ck9Rq3jn18E7DBupgt1jpxXXza9Lqo3IofBTRf16J9R9CVD3JaLykSHe3kyXAgCwXngUUdf8DDk1cns2iXyFPXZEYUCSgejfbAEcbqh7kuD8b5fTHuv+IROotUDOqILSsySArQwtUmJwe+z0+XWRPAzbkGTVED1nk3daQWE04FKgdC9BzMJvEX3bFoY6Ih9hsCMKE3JqLRzT9LlKXeHZk9jscfowrO3iwxHdUxT0HrsI3XXiTOTUWkTP3QDL4OOIvn0jYu75AZYuZcFuFpGpMNgRhRHbhcdgvfAIICRUP98fosY7m0IIwLMjGVVP50HNTwQUDdZhh4Pb2CBrWKQ4GOpLnUReDbszsXQvRcztm2AdfCKi33gQ+Qvn2BGFGcfU7fDsToIojEbNq72hdD0J14qO0I7GGcfYx+2DnBDZE/b1xROizA6hSqedk+gv+hw7DsUSUSAx2BGFGSnag+jfbEXVoiFwf5cFd91CCdg93tWHlx6Akl0Z3EaGACneBcgaoMkQZTZIyc6AXj/Sa9gRUXAw2BGFIUv3k7BfuRvO97pDzqyE7dKDsA09ElH7wZ6NJHu3FhMlDmilUZADHOz0cicMdkQUSAx2RGEq6op87wKJBCfnKp2GnOiEWuII+AIK4ZIhKrx7o3KOHREFEoMdURiTEwPbCxVuglWkWF8RC7sHYC8qEQUQV8USkWnJ+gKKQPfYNSh1wt5UIgokBjsiMi2prkcz0CVPuHCCiIKFwY6ITKu+xy7AwY6lTogoSBjsiMi09N0ntNJgDcVy4QQRBRaDHRGZlrF4IuBDsSx1QkTBwWBHRKZlrBqutkI4A/dypwc7KYXBjogCi8GOiMzL4fGWHEFgS55w8QQRBQuDHRGZliTV99oFquSJqFWAaisAzrEjosBjsCMiU9NXpuq9aP5mFCeOdkNyqAG5JhGRjsGOiExN39JLKwpQsCvmMCwRBQ+DHRGZmpxWF+wKAxPsjFInSQx2RBR4AQl2TqcTAwYMgCRJ2Lx5cyAuSUQEAJDTqgEEsMdOXxHL+XVEFAQBCXb/7//9P2RlZQXiUkREjdT32EUH5HpGDTuWOiGiIPB7sPv000/x+eef4/HHH/f3pYiImpBTvT12ojgKQpX8fj3B4sREFEQWf578xIkTmDVrFj744ANERwfm3TIRUUNSohOwqoBbgSiJgpTm3yFS1rAjomDyW4+dEALTp0/HbbfdhsGDB7foOU6nE+Xl5Y1uRERtIcmBWxkrRMNdJzjHjogCr9XBbv78+ZAk6Yy3nTt34umnn0ZFRQUWLFjQ4nMvXrwYCQkJxi07O7u1zSMiaiJg8+yqLUCtdyCEq2KJKBhaPRT7xz/+EdOnTz/jMZ07d8aXX36J7777DnZ742rvgwcPxpQpU/Dqq682ed6CBQswb9484355eTnDHRG1mZwamJInRm9drAuSXfPrtYiImtPqYJeWloa0tLSzHvfUU0/hoYceMu4fPXoUY8eOxbJlyzBkyJBmn2O325sEQSKitjJKnvg92HnPL3F+HREFid8WT3Ts2LHR/djYWABAly5d0KFDB39dloioiUANxRqlTljDjoiChDtPEJHpSQEqUiyKWcOOiILLr+VOGsrJyYEQIlCXIyIy6D12ojQKwiVDsvln/pt2sm6OHRdOEFGQsMeOiExPinEDUR4A/u2101icmIiCjMGOiExPkgKzgEIU1xUn5lAsEQUJgx0RRQRjAUWRfxZQNCxOzMUTRBQsDHZEFBH0PWP91WMnKq2AWwEASElOv1yDiOhsGOyIKCL4u+SJ0GvYJTghWVmcmIiCg8GOiCJCfbDzT4+dVsxhWCIKPgY7IooI+uIJ4adVsfpqW4kLJ4goiBjsiCgi6PvFiiobRLXvS3hqx2MAAEq7Kp+fm4iopRjsiCgiSFEqpDgXAP8Mx6rHvMFOzmSwI6LgYbAjoohRvzLW9wsotGPe/bDlzEqfn5uIqKUY7IgoYtTXsvNtj52oUSDqthPjUCwRBRODHRFFDH/tPqHPr5MSnJBiPD49NxFRazDYEVHEkPxUy07Vh2HZW0dEQcZgR0QRQ18Z668eO4Xz64goyBjsiChiGEOxRQ4I4bvzake5IpaIQgODHRFFDDmlFpAE4LJAlNt8dl71OIMdEYUGBjsiihiSVYOU5N0Zwlfz7IRWPxTLOXZEFGwMdkQUUXw9z04UOwC3Alg0Y6iXiChYGOyIKKI0nGfnC8YwbEYVJL6iElGQ8WWIiCKKUaTYRz12GrcSI6IQwmBHRBFFD3aiyDdz7PRgx1InRBQKGOyIKKLU7xfro6FYY49Y9tgRUfAx2BFRRDGGYosdEFrbz2cMxXJFLBGFAAY7IoooUlItoGiAKkOcjGrTuUSNBaLUew6FPXZEFAIY7Igookhyw5InbZtnpx73Pl9KqIUU7Wlz24iI2orBjogijq9q2WlHOb+OiEILgx0RRRyjll1bg91xfUUsgx0RhQYGOyKKOHJ6XbCrW9F6rlQunCCiEMNgR0QRR8kpBwB49ia06Tz1xYlZw46IQgODHRFFHCW3DJAERFE0tHLbOZ1DaIB2gkOxRBRaGOyIKOJI0R5jwYN6jr12otgBuBXAqkKqW4xBRBRsDHZEFJGUzqUAADU/8Zyerx6tG4bNqIbEV1IiChF8OSKiiKR0KQVw7sFOO66XOuH8OiIKHX4Ndp988gmGDBkCh8OBpKQkTJo0yZ+XIyJqMUvnMgCAZ1/COW0tpi+cULgilohCiMVfJ3733Xcxa9YsLFq0CKNGjYLH48G2bdv8dTkiolaRO1QAVhWotkI7EdPqBRBGqRMunCCiEOKXYOfxePD73/8ejz32GGbOnGk8ft555/njckRErSZZBJScMqi7k6HmJ7Q62GkMdkQUgvwyFLtx40YcOXIEsiwjLy8PmZmZGD9+PHvsiCikKHXDserexFY9T1RbIMqivOdgsCOiEOKXYLd3714AwAMPPIA//elP+Pjjj5GUlISRI0eipKTktM9zOp0oLy9vdCMi8hdjAUUrS57ow7BSYi0kh8fXzSIiOmetCnbz58+HJElnvO3cuROa5p2JfO+99+Lqq6/GoEGDsHTpUkiShLfffvu051+8eDESEhKMW3Z2dts+OyKiM9AXUKgH4yFcLX851PeI5TAsEYWaVs2x++Mf/4jp06ef8ZjOnTvj2LFjABrPqbPb7ejcuTMOHjx42ucuWLAA8+bNM+6Xl5cz3BGR30ipNZDinBAVdqgH42HpWtqi53FFLBGFqlYFu7S0NKSlpZ31uEGDBsFut+Pnn3/GsGHDAAButxv79+9Hp06dTvs8u90Ou93emiYREZ0zSQKULmXwbE6HujehxcFO3e8dupWzWMOOiEKLX1bFxsfH47bbbsP999+P7OxsdOrUCY899hgAYPLkyf64JBHROVE6l3qDXX4igANnPV5UWeDZngIAsPQt8m/jiIhayW917B577DFYLBbcdNNNqKmpwZAhQ/Dll18iKSnJX5ckImq1+pWxLVtA4d6UDqgy5A4VXBFLRCHHb8HOarXi8ccfx+OPP+6vSxARtZmlbs9YrSAGWoUVcpz7jMe717cDAFgHH/d304iIWo17xRJRRJNiPMZ+r2erZydqLPBsSwUAWM9nsCOi0MNgR0QRT8lt2XCse3Ma4FYgZ1ZCbs+FE0QUehjsiCjiGYWK8xPPeFzDYVhJ8nOjiIjOAYMdEUW8hjtQCNH8McKpwLPVW+7Jev6JALWMiKh1GOyIKOIp2RWAVYWoskEriG72GM/WNMClQEqrhtyR2x0SUWhisCOiiCdZBJS6sHa64Vj3ugwA3kUTHIYlolDFYEdEBO8OFEDzCyiES4Z7SzoAljkhotDGYEdEBO8OFADg2ZYKUdO4xKdnWypQa4GUXGMUNCYiCkUMdkREACznFQNRHmjHYlH50BBoJVHGx9zruBqWiMIDgx0REQA5wYXY+T9ASqiFdjgelQ9eCPVAHIRHgntz3TAsV8MSUYhjsCMiqqPkliN24XeQsyogSqNQuegXqH27O1BthZRYC6XryWA3kYjojBjsiIgakFNrEfun76GcVwTUWuBa3hkAYB10AhJfMYkoxPFliojoFFKMBzF/XA/rsMPGY9wblojCgeXshxARRR7JIuC45UcoOWUQZXYoPUqC3SQiorNisCMiOg1JAuyXHQx2M4iIWoxDsUREREQmwWBHREREZBIMdkREREQmwWBHREREZBIMdkREREQmwWBHREREZBIMdkREREQmwWBHREREZBIMdkREREQmwWBHREREZBIMdkREREQmwWBHREREZBIMdkREREQmwWBHREREZBIMdkREREQmwWBHREREZBIMdkREREQmwWBHREREZBJ+C3a7du3CFVdcgdTUVMTHx2PYsGFYuXKlvy5HREREFPH8Fuwuv/xyeDwefPnll9iwYQP69++Pyy+/HMePH/fXJYmIiIgiml+CXVFREXbv3o358+ejX79+6NatGx555BFUV1dj27Zt/rgkERERUcSz+OOkKSkp6NGjB/79739j4MCBsNvteOGFF5Ceno5Bgwad9nlOpxNOp9O4X15e7o/mUYSqdlcHuwlE1Er8vSVqHb8EO0mS8L///Q+TJk1CXFwcZFlGeno6li9fjqSkpNM+b/HixXjwwQf90SSKYFbZioSoBJTVlqHGXRPs5hBRKyVEJcAqW4PdDKKwIAkhREsPnj9/PpYsWXLGY3bs2IEePXpg0qRJcLvduPfee+FwOPDPf/4T//3vf7Fu3TpkZmY2+9zmeuyys7NRVlaG+Pj4ljaTqImy2jK4NXewm0FE50B/c0YUqcrLy5GQkNCiPNSqYFdYWIji4uIzHtO5c2d8/fXXGDNmDE6ePNmoAd26dcPMmTMxf/78Fl2vNZ8IERERkRm1Jg+1aig2LS0NaWlpZz2uuto7J0KWG6/NkGUZmqa15pJERERE1EJ+WRV74YUXIikpCdOmTcOWLVuwa9cu3HXXXdi3bx8mTJjgj0sSERERRTy/BLvU1FQsX74clZWVGDVqFAYPHoxvvvkGH374Ifr37++PSxIRERFFvFbNsQs0zrEjIiKiSNeaPMS9YomIiIhMgsGOiIiIyCQY7IiIiIhMgsGOiIiIyCQY7IiIiIhMgsGOiIiIyCQY7IiIiIhMgsGOiIiIyCQY7IiIiIhMgsGOiIiIyCQswW7Amei7nZWXlwe5JURERETBoeegluwCG9LBrqKiAgCQnZ0d5JYQERERBVdFRQUSEhLOeIwkWhL/gkTTNBw9ehRxcXGQJMmv1yovL0d2djYOHTp01g12Kbzwe2tu/P6aG7+/5sbvb8sIIVBRUYGsrCzI8pln0YV0j50sy+jQoUNArxkfH88fLpPi99bc+P01N35/zY3f37M7W0+djosniIiIiEyCwY6IiIjIJBjs6tjtdtx///2w2+3Bbgr5GL+35sbvr7nx+2tu/P76XkgvniAiIiKilmOPHREREZFJMNgRERERmQSDHREREZFJMNgB+Mc//oGcnBxERUVhyJAhWLt2bbCbRD6wePFinH/++YiLi0N6ejomTZqEn3/+OdjNIj955JFHIEkS5s6dG+ymkI8cOXIEN954I1JSUuBwONC3b1+sX78+2M0iH1BVFffddx9yc3PhcDjQpUsX/OUvf2nRlll0ZhEf7JYtW4Z58+bh/vvvx8aNG9G/f3+MHTsWBQUFwW4atdFXX32F2bNn4/vvv8cXX3wBt9uNMWPGoKqqKthNIx9bt24dXnjhBfTr1y/YTSEfOXnyJIYOHQqr1YpPP/0U27dvxxNPPIGkpKRgN418YMmSJXjuuefwzDPPYMeOHViyZAkeffRRPP3008FuWtiL+FWxQ4YMwfnnn49nnnkGgHcbs+zsbNx+++2YP39+kFtHvlRYWIj09HR89dVXGDFiRLCbQz5SWVmJgQMH4tlnn8VDDz2EAQMG4Mknnwx2s6iN5s+fjzVr1uDrr78OdlPIDy6//HJkZGTgX//6l/HY1VdfDYfDgf/85z9BbFn4i+geO5fLhQ0bNmD06NHGY7IsY/To0fjuu++C2DLyh7KyMgBAcnJykFtCvjR79mxMmDCh0e8xhb///ve/GDx4MCZPnoz09HTk5eXhpZdeCnazyEcuuugirFixArt27QIAbNmyBd988w3Gjx8f5JaFv5DeK9bfioqKoKoqMjIyGj2ekZGBnTt3BqlV5A+apmHu3LkYOnQo+vTpE+zmkI+8+eab2LhxI9atWxfsppCP7d27F8899xzmzZuHe+65B+vWrcMdd9wBm82GadOmBbt51Ebz589HeXk5evbsCUVRoKoqHn74YUyZMiXYTQt7ER3sKHLMnj0b27ZtwzfffBPsppCPHDp0CL///e/xxRdfICoqKtjNIR/TNA2DBw/GokWLAAB5eXnYtm0bnn/+eQY7E3jrrbfw2muv4fXXX0fv3r2xefNmzJ07F1lZWfz+tlFEB7vU1FQoioITJ040evzEiRNo165dkFpFvjZnzhx8/PHHWL16NTp06BDs5pCPbNiwAQUFBRg4cKDxmKqqWL16NZ555hk4nU4oihLEFlJbZGZm4rzzzmv0WK9evfDuu+8GqUXkS3fddRfmz5+P66+/HgDQt29fHDhwAIsXL2awa6OInmNns9kwaNAgrFixwnhM0zSsWLECF154YRBbRr4ghMCcOXPw/vvv48svv0Rubm6wm0Q+dOmll+LHH3/E5s2bjdvgwYMxZcoUbN68maEuzA0dOrRJeaJdu3ahU6dOQWoR+VJ1dTVkuXEEURQFmqYFqUXmEdE9dgAwb948TJs2DYMHD8YFF1yAJ598ElVVVZgxY0awm0ZtNHv2bLz++uv48MMPERcXh+PHjwMAEhIS4HA4gtw6aqu4uLgm8yVjYmKQkpLCeZQm8Ic//AEXXXQRFi1ahGuvvRZr167Fiy++iBdffDHYTSMfmDhxIh5++GF07NgRvXv3xqZNm/DXv/4VN998c7CbFvYivtwJADzzzDN47LHHcPz4cQwYMABPPfUUhgwZEuxmURtJktTs40uXLsX06dMD2xgKiJEjR7LciYl8/PHHWLBgAXbv3o3c3FzMmzcPs2bNCnazyAcqKipw33334f3330dBQQGysrJwww03YOHChbDZbMFuXlhjsCMiIiIyiYieY0dERERkJgx2RERERCbBYEdERERkEgx2RERERCbBYEdERERkEgx2RERERCbBYEdERERkEgx2RERERCbBYEdEfiOEwK233ork5GRIkoTNmzcHu0khy+VyoWvXrvj22299et7ly5djwIAB3IOTqA1Wr16NiRMnIisrC5Ik4YMPPmjV82trazF9+nT07dsXFosFkyZNOuPxa9asgcViwYABA1rdVgY7IvKb5cuX45VXXsHHH3+MY8eOcQ/XM3j++eeRm5uLiy66yHjsdH9Apk+fftY/DLpx48bBarXitdde81FLiSJPVVUV+vfvj3/84x/n9HxVVeFwOHDHHXdg9OjRZzy2tLQUU6dOxaWXXnpO12KwIyK/yc/PR2ZmJi666CK0a9cOFoulyTEulysILQstQgg888wzmDlzpl/OP336dDz11FN+OTdRJBg/fjweeughXHnllc1+3Ol04s4770T79u0RExODIUOGYNWqVcbHY2Ji8Nxzz2HWrFlo167dGa9122234de//jUuvPDCc2orgx0R+cX06dNx++234+DBg5AkCTk5OQCAkSNHYs6cOZg7dy5SU1MxduxYAMC2bdswfvx4xMbGIiMjAzfddBOKioqM81VVVWHq1KmIjY1FZmYmnnjiCYwcORJz5841jmmuhysxMRGvvPKKcf/QoUO49tprkZiYiOTkZFxxxRXYv39/o3ZPmjQJjz/+ODIzM5GSkoLZs2fD7XYbxzidTtx9993Izs6G3W5H165d8a9//QtCCHTt2hWPP/54ozZs3rwZkiRhz549zX6tNmzYgPz8fEyYMKEVX2Gv/fv3Q5KkJreRI0cax0ycOBHr169Hfn5+q89PRGc3Z84cfPfdd3jzzTexdetWTJ48GePGjcPu3btbdZ6lS5di7969uP/++8+5LQx2ROQXf//73/HnP/8ZHTp0wLFjx7Bu3TrjY6+++ipsNhvWrFmD559/HqWlpRg1ahTy8vKwfv16LF++HCdOnMC1115rPOeuu+7CV199hQ8//BCff/45Vq1ahY0bN7aqTW63G2PHjkVcXBy+/vprrFmzBrGxsRg3blyjnsOVK1ciPz8fK1euxKuvvopXXnmlUTicOnUq3njjDTz11FPYsWMHXnjhBcTGxkKSJNx8881YunRpo+suXboUI0aMQNeuXZtt19dff43u3bsjLi6uVZ8PAGRnZ+PYsWPGbdOmTUhJScGIESOMYzp27IiMjAx8/fXXrT4/EZ3ZwYMHsXTpUrz99tsYPnw4unTpgjvvvBPDhg1r8lpwJrt378b8+fPxn//8p9nRjZY692cSEZ1BQkIC4uLioChKk6GHbt264dFHHzXuP/TQQ8jLy8OiRYuMx15++WVkZ2dj165dyMrKwr/+9S/85z//MeadvPrqq+jQoUOr2rRs2TJomoZ//vOfkCQJgDd0JSYmYtWqVRgzZgwAICkpCc888wwURUHPnj0xYcIErFixArNmzcKuXbvw1ltv4YsvvjDmynTu3Nm4xvTp07Fw4UKsXbsWF1xwAdxuN15//fUmvXgNHThwAFlZWc1+7IYbboCiKI0eczqdRu9ew69vbW0tJk2ahAsvvBAPPPBAo+dkZWXhwIEDrfhqEVFL/Pjjj1BVFd27d2/0uNPpREpKSovOoaoqfv3rX+PBBx9scp7WYrAjooAbNGhQo/tbtmzBypUrERsb2+TY/Px81NTUwOVyYciQIcbjycnJ6NGjR6uuu2XLFuzZs6dJz1htbW2jYcrevXs3ClOZmZn48ccfAXiHVRVFwcUXX9zsNbKysjBhwgS8/PLLuOCCC/DRRx/B6XRi8uTJp21XTU0NoqKimv3Y3/72tyaTre+++26oqtrk2JtvvhkVFRX44osvIMuNB2QcDgeqq6tP2wYiOjeVlZVQFAUbNmxo8iasude05lRUVGD9+vXYtGkT5syZAwDQNA1CCFgsFnz++ecYNWpUi87FYEdEARcTE9PofmVlJSZOnIglS5Y0OTYzM/O0c9NOJUkShBCNHms4N66yshKDBg1qdoVoWlqa8X+r1drkvHq5EIfDcdZ23HLLLbjpppvwt7/9DUuXLsV1112H6Ojo0x6fmppqBMdTtWvXrskQblxcHEpLSxs99tBDD+Gzzz7D2rVrmx3SLSkpafQ5EpFv5OXlQVVVFBQUYPjw4ed0jvj4+CavAc8++yy+/PJLvPPOO8jNzW3xuRjsiCjoBg4ciHfffRc5OTnNzi3p0qULrFYrfvjhB3Ts2BEAcPLkSezatatRz1laWhqOHTtm3N+9e3ejXqqBAwdi2bJlSE9PR3x8/Dm1tW/fvtA0DV999dVpyxb88pe/NFbBLV++HKtXrz7jOfPy8vDcc89BCGEMEbfGu+++iz//+c/49NNP0aVLlyYf13sk8/LyWn1uIvK+KWz4BnPfvn3YvHkzkpOT0b17d0yZMgVTp07FE088gby8PBQWFmLFihXo16+fMW1i+/btcLlcKCkpQUVFhVHXc8CAAZBluUk5qPT0dERFRbW6TBQXTxBR0M2ePRslJSW44YYbsG7dOuTn5+Ozzz7DjBkzoKoqYmNjMXPmTNx111348ssvsW3bNkyfPr3JcOOoUaPwzDPPYNOmTVi/fj1uu+22Rr1vU6ZMQWpqKq644gp8/fXX2LdvH1atWoU77rgDhw8fblFbc3JyMG3aNNx888344IMPjHO89dZbxjGKomD69OlYsGABunXrdtayBZdccgkqKyvx008/teKr5rVt2zZMnToVd999N3r37o3jx4/j+PHjKCkpMY75/vvvYbfbz7l8AlGkW79+PfLy8ow3R/PmzUNeXh4WLlwIwDtXd+rUqfjjH/+IHj16YNKkSVi3bp3xRhTwvuHLy8vDRx99hFWrVjU6ny8x2BFR0GVlZWHNmjVQVRVjxoxB3759MXfuXCQmJhrh7bHHHsPw4cMxceJEjB49GsOGDWsyV++JJ55AdnY2hg8fjl//+te48847Gw2BRkdHY/Xq1ejYsSOuuuoq9OrVCzNnzkRtbW2revCee+45XHPNNfjd736Hnj17YtasWaiqqmp0zMyZM+FyuTBjxoyzni8lJQVXXnnlORURXr9+Paqrq/HQQw8hMzPTuF111VXGMW+88QamTJlyxuFgIjq9kSNHQgjR5KavlrdarXjwwQexb98+uFwuHD16FO+99x769u1rnGP//v3NnuN0HnjggXParUcSZzorEVEIGzlyJAYMGIAnn3wy2E1p4uuvv8all16KQ4cOISMj46zHb926FZdddhny8/NbPOG6JYqKitCjRw+sX7++VfN0iCg8sceOiMiHnE4nDh8+jAceeACTJ09uUagDgH79+mHJkiXYt2+fT9uzf/9+PPvsswx1RBGCiyeIiHzojTfewMyZMzFgwAD8+9//btVzp0+f7vP2DB48GIMHD/b5eYkoNHEoloiIiMgkOBRLREREZBIMdkREREQmwWBHREREZBIMdkREREQmwWBHREREZBIMdkREREQmwWBHREREZBIMdkREREQmwWBHREREZBL/P8O2Wlhs5HwHAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check probe and source\n",
    "ax1 = sim.sources[0].source_time.plot(times=np.linspace(0, sim.run_time, 1001))\n",
    "ax1.set_xlim(0, 1e-13)\n",
    "ax2 = sim.sources[0].source_time.plot_spectrum(times=np.linspace(0, sim.run_time, 1001))\n",
    "ax2.fill_between(\n",
    "    freq_range, [-8e-16, -8e-16], [8e-16, 8e-16], alpha=0.4, color=\"g\", label=\"mesure\"\n",
    ")\n",
    "ax2.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run the simulation\n",
    "\n",
    "We will submit the simulation to run as a new project."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:40:40.283644Z",
     "iopub.status.busy": "2023-08-18T17:40:40.283488Z",
     "iopub.status.idle": "2023-08-18T17:41:23.122184Z",
     "shell.execute_reply": "2023-08-18T17:41:23.121440Z"
    },
    "tags": []
   },
   "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\">[10:40:40] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'dispersion'</span> with task_id                  <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#188\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">188</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-856a276d-7d85-4f17-b50c-be3e3f57777bv1'</span>.          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:40:40]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'dispersion'\u001b[0m with task_id                  \u001b]8;id=696507;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=515177;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#188\u001b\\\u001b[2m188\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'fdve-856a276d-7d85-4f17-b50c-be3e3f57777bv1'\u001b[0m.          \u001b[2m             \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                               <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#190\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">190</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-856a276d-7d85-4f17-b50c-be3e3f57777bv1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-</span></a> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-856a276d-7d85-4f17-b50c-be3e3f57777bv1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">856a276d-7d85-4f17-b50c-be3e3f57777bv1'</span></a>.                <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                               \u001b]8;id=467527;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=611785;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#190\u001b\\\u001b[2m190\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b]8;id=19615;https://tidy3d.simulation.cloud/workbench?taskId=fdve-856a276d-7d85-4f17-b50c-be3e3f57777bv1\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=658103;https://tidy3d.simulation.cloud/workbench?taskId=fdve-856a276d-7d85-4f17-b50c-be3e3f57777bv1\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=19615;https://tidy3d.simulation.cloud/workbench?taskId=fdve-856a276d-7d85-4f17-b50c-be3e3f57777bv1\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=929960;https://tidy3d.simulation.cloud/workbench?taskId=fdve-856a276d-7d85-4f17-b50c-be3e3f57777bv1\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=19615;https://tidy3d.simulation.cloud/workbench?taskId=fdve-856a276d-7d85-4f17-b50c-be3e3f57777bv1\u001b\\\u001b[32m-\u001b[0m\u001b]8;;\u001b\\ \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0m\u001b]8;id=19615;https://tidy3d.simulation.cloud/workbench?taskId=fdve-856a276d-7d85-4f17-b50c-be3e3f57777bv1\u001b\\\u001b[32m856a276d-7d85-4f17-b50c-be3e3f57777bv1'\u001b[0m\u001b]8;;\u001b\\.                \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "application/vnd.jupyter.widget-view+json": {
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[10:40:41] </span>status = queued                                         <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#361\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">361</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:40:41]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                         \u001b]8;id=990468;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=879973;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#361\u001b\\\u001b[2m361\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4576bda285674cfa936e1a24abcba006",
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      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[10:40:50] </span>status = preprocess                                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#355\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">355</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:40:50]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                     \u001b]8;id=946281;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=877706;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#355\u001b\\\u001b[2m355\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[10:40:54] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.106</span>. Use                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#341\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">341</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed FlexCredit   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>cost after a simulation run.                            <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:40:54]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.106\u001b[0m. Use                     \u001b]8;id=644139;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=144210;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#341\u001b\\\u001b[2m341\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit   \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mcost after a simulation run.                            \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>starting up solver                                      <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#377\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">377</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                      \u001b]8;id=345975;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=347335;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#377\u001b\\\u001b[2m377\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>running solver                                          <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#386\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">386</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                          \u001b]8;id=883190;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=17186;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#386\u001b\\\u001b[2m386\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or   <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#387\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">387</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>web UI. Terminating the Python script will not stop the <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>job running on the cloud.                               <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or   \u001b]8;id=941165;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=167474;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the   \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mweb UI. Terminating the Python script will not stop the \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mjob running on the cloud.                               \u001b[2m             \u001b[0m\n"
      ]
     },
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    {
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      },
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       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[10:41:18] </span>early shutoff detected, exiting.                        <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#404\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">404</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:41:18]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                        \u001b]8;id=44549;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=101605;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#404\u001b\\\u001b[2m404\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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    {
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    {
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       "</pre>\n"
      ],
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       "\n"
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    {
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      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>status = postprocess                                    <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#419\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">419</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                    \u001b]8;id=206095;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=143274;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#419\u001b\\\u001b[2m419\u001b[0m\u001b]8;;\u001b\\\n"
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       "Output()"
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       "<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\">[10:41:22] </span>status = success                                        <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#426\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">426</span></a>\n",
       "</pre>\n"
      ],
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       "\u001b[2;36m[10:41:22]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                        \u001b]8;id=521402;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=699626;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#426\u001b\\\u001b[2m426\u001b[0m\u001b]8;;\u001b\\\n"
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       "Output()"
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    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
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     },
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       "\n"
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    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[10:41:23] </span>loading SimulationData from data/sim_data.hdf5          <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#590\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">590</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:41:23]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/sim_data.hdf5          \u001b]8;id=748573;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=582633;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#590\u001b\\\u001b[2m590\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
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    }
   ],
   "source": [
    "sim_data = web.run(sim, task_name=\"dispersion\", path=\"data/sim_data.hdf5\", verbose=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Postprocess and Plot\n",
    "\n",
    "Once the simulation has completed, we can download the results and load them into the simulation object."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we compute the transmitted flux and plot the transmission spectrum."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:41:23.991057Z",
     "iopub.status.busy": "2023-08-18T17:41:23.990818Z",
     "iopub.status.idle": "2023-08-18T17:41:24.100299Z",
     "shell.execute_reply": "2023-08-18T17:41:24.099680Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Retrieve the power flux through the monitor plane.\n",
    "transmission = sim_data[\"flux\"].flux\n",
    "plt.plot(monitor_lambdas, transmission, color=\"k\")\n",
    "plt.xlabel(\"wavelength (um)\")\n",
    "plt.ylabel(\"transmitted flux\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In `Tidy3D`, results are normalized by default. In some cases, and largely depending on the required accuracy, a normalizing run may still be needed. Here, we show how to do such a normalizing run by simulating an empty simulation with the exact same source and monitor but none of the structures."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:41:24.103592Z",
     "iopub.status.busy": "2023-08-18T17:41:24.103401Z",
     "iopub.status.idle": "2023-08-18T17:41:53.436273Z",
     "shell.execute_reply": "2023-08-18T17:41:53.435426Z"
    },
    "tags": []
   },
   "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\">[10:41:24] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'docs_dispersion_norm'</span> with task_id        <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#188\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">188</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-66335a77-705d-42a5-be83-4aac692b3f9fv1'</span>.          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:41:24]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'docs_dispersion_norm'\u001b[0m with task_id        \u001b]8;id=547994;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=657414;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#188\u001b\\\u001b[2m188\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'fdve-66335a77-705d-42a5-be83-4aac692b3f9fv1'\u001b[0m.          \u001b[2m             \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                               <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#190\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">190</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-66335a77-705d-42a5-be83-4aac692b3f9fv1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-</span></a> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-66335a77-705d-42a5-be83-4aac692b3f9fv1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">66335a77-705d-42a5-be83-4aac692b3f9fv1'</span></a>.                <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                               \u001b]8;id=823276;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=318320;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#190\u001b\\\u001b[2m190\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b]8;id=570233;https://tidy3d.simulation.cloud/workbench?taskId=fdve-66335a77-705d-42a5-be83-4aac692b3f9fv1\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=4942;https://tidy3d.simulation.cloud/workbench?taskId=fdve-66335a77-705d-42a5-be83-4aac692b3f9fv1\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=570233;https://tidy3d.simulation.cloud/workbench?taskId=fdve-66335a77-705d-42a5-be83-4aac692b3f9fv1\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=513962;https://tidy3d.simulation.cloud/workbench?taskId=fdve-66335a77-705d-42a5-be83-4aac692b3f9fv1\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=570233;https://tidy3d.simulation.cloud/workbench?taskId=fdve-66335a77-705d-42a5-be83-4aac692b3f9fv1\u001b\\\u001b[32m-\u001b[0m\u001b]8;;\u001b\\ \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0m\u001b]8;id=570233;https://tidy3d.simulation.cloud/workbench?taskId=fdve-66335a77-705d-42a5-be83-4aac692b3f9fv1\u001b\\\u001b[32m66335a77-705d-42a5-be83-4aac692b3f9fv1'\u001b[0m\u001b]8;;\u001b\\.                \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "beba03511d8d4f40b0acf15b312c3f94",
       "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\">[10:41:25] </span>status = queued                                         <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#361\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">361</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:41:25]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                         \u001b]8;id=550319;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=673364;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#361\u001b\\\u001b[2m361\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9bbf734471234b7bb9aef2ca26f39c92",
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[10:41:33] </span>status = preprocess                                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#355\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">355</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:41:33]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                     \u001b]8;id=165196;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=566202;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#355\u001b\\\u001b[2m355\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[10:41:38] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#341\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">341</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed FlexCredit   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>cost after a simulation run.                            <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:41:38]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Use                     \u001b]8;id=337606;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=356289;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#341\u001b\\\u001b[2m341\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit   \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mcost after a simulation run.                            \u001b[2m             \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>starting up solver                                      <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#377\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">377</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                      \u001b]8;id=435774;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=734489;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#377\u001b\\\u001b[2m377\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>running solver                                          <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#386\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">386</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                          \u001b]8;id=233769;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=10535;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#386\u001b\\\u001b[2m386\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or   <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#387\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">387</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>web UI. Terminating the Python script will not stop the <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>job running on the cloud.                               <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or   \u001b]8;id=539889;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=393880;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the   \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mweb UI. Terminating the Python script will not stop the \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mjob running on the cloud.                               \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "model_id": "fc942ee0849c4142ab6bd69ccc2fb1dc",
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[10:41:43] </span>early shutoff detected, exiting.                        <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#404\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">404</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
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       "\u001b[2;36m[10:41:47]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                        \u001b]8;id=371728;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=195904;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#426\u001b\\\u001b[2m426\u001b[0m\u001b]8;;\u001b\\\n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
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       "\n"
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    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[10:41:53] </span>loading SimulationData from data/sim_data.hdf5          <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#590\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">590</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:41:53]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/sim_data.hdf5          \u001b]8;id=125162;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=459159;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#590\u001b\\\u001b[2m590\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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   ],
   "source": [
    "sim_norm = sim.copy(update={\"structures\": []})\n",
    "\n",
    "sim_data_norm = web.run(\n",
    "    sim_norm, task_name=\"docs_dispersion_norm\", path=\"data/sim_data.hdf5\", verbose=True,\n",
    ")\n",
    "transmission_norm = sim_data_norm[\"flux\"].flux\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:41:53.902482Z",
     "iopub.status.busy": "2023-08-18T17:41:53.902352Z",
     "iopub.status.idle": "2023-08-18T17:41:54.037260Z",
     "shell.execute_reply": "2023-08-18T17:41:54.036745Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(monitor_lambdas, transmission, label=\"with structure\")\n",
    "plt.plot(monitor_lambdas, transmission_norm, label=\"no structure\")\n",
    "plt.plot(monitor_lambdas, transmission / transmission_norm, \"k--\", label=\"normalized\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"wavelength (um)\")\n",
    "plt.ylabel(\"fraction of transmitted power (normalized)\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that since the flux monitor already takes the source power into account, the normalizing run has no visible effect on the results."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analytical Comparison\n",
    "\n",
    "We will use a transfer matrix method (TMM) [code](https://github.com/sbyrnes321/tmm) to compare `Tidy3D`'s simulated transmission to a semi-analytical result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:41:54.040749Z",
     "iopub.status.busy": "2023-08-18T17:41:54.040565Z",
     "iopub.status.idle": "2023-08-18T17:41:54.067256Z",
     "shell.execute_reply": "2023-08-18T17:41:54.066662Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# import TMM package\n",
    "import tmm\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:41:54.069314Z",
     "iopub.status.busy": "2023-08-18T17:41:54.069175Z",
     "iopub.status.idle": "2023-08-18T17:41:54.137198Z",
     "shell.execute_reply": "2023-08-18T17:41:54.136623Z"
    }
   },
   "outputs": [],
   "source": [
    "# prepare list of thicknesses including air boundaries\n",
    "d_list = [np.inf] + t_slabs + [np.inf]\n",
    "\n",
    "# convert the complex permittivities at each frequency to refractive indices\n",
    "n_list1 = np.sqrt(mat1.eps_model(monitor_freqs))\n",
    "n_list2 = np.sqrt(mat2.eps_model(monitor_freqs))\n",
    "n_list3 = np.sqrt(mat3.eps_model(monitor_freqs))\n",
    "n_list4 = np.sqrt(mat4.eps_model(monitor_freqs))\n",
    "\n",
    "# loop through wavelength and record TMM computed transmission\n",
    "transmission_tmm = []\n",
    "for i, lam in enumerate(monitor_lambdas):\n",
    "\n",
    "    # create list of refractive index at this wavelength including outer material (air)\n",
    "    n_list = [1, n_list1[i], n_list2[i], n_list3[i], n_list4[i], 1]\n",
    "\n",
    "    # get transmission at normal incidence\n",
    "    T = tmm.coh_tmm(\"s\", n_list, d_list, 0, lam)[\"T\"]\n",
    "    transmission_tmm.append(T)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:41:54.139089Z",
     "iopub.status.busy": "2023-08-18T17:41:54.138949Z",
     "iopub.status.idle": "2023-08-18T17:41:54.261167Z",
     "shell.execute_reply": "2023-08-18T17:41:54.260584Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(monitor_lambdas, transmission_tmm, label=\"TMM\")\n",
    "plt.plot(monitor_lambdas, transmission / transmission_norm, \"k--\", label=\"Tidy3D\")\n",
    "plt.xlabel(\"wavelength ($\\mu m$)\")\n",
    "plt.ylabel(\"Transmitted\")\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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