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 matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tidy3d as td\n",
    "from tidy3d import web"
   ]
  },
  {
   "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))"
   ]
  },
  {
   "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]"
   ]
  },
  {
   "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"
   ]
  },
  {
   "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 direction."
   ]
  },
  {
   "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",
    ")"
   ]
  },
  {
   "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",
    ")"
   ]
  },
  {
   "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",
    ")"
   ]
  },
  {
   "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",
    ")"
   ]
  },
  {
   "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": {
    "tags": []
   },
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim.plot(x=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we use `Simulation.plot_eps()` to visualize 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 frequencies 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": {
    "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()"
   ]
  },
  {
   "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 interest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "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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",
      "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=\"measure\"\n",
    ")\n",
    "ax2.legend()\n",
    "plt.show()"
   ]
  },
  {
   "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": {
    "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\">10:27:54 Eastern Daylight Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'dispersion'</span> with task_id           \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-12657b1d-2873-4588-a14c-f505cb802247'</span> and  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:27:54 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'dispersion'\u001b[0m with task_id           \n",
       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-12657b1d-2873-4588-a14c-f505cb802247'\u001b[0m and  \n",
       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-12657b1d-2873-4588-a14c-f505cb802247\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-12657b1d-2873-4588-a14c-f505cb802247\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-12657b1d-2873-4588-a14c-f505cb802247'</span></a>.     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=343017;https://tidy3d.simulation.cloud/workbench?taskId=fdve-12657b1d-2873-4588-a14c-f505cb802247\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=920609;https://tidy3d.simulation.cloud/workbench?taskId=fdve-12657b1d-2873-4588-a14c-f505cb802247\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=343017;https://tidy3d.simulation.cloud/workbench?taskId=fdve-12657b1d-2873-4588-a14c-f505cb802247\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=616090;https://tidy3d.simulation.cloud/workbench?taskId=fdve-12657b1d-2873-4588-a14c-f505cb802247\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=343017;https://tidy3d.simulation.cloud/workbench?taskId=fdve-12657b1d-2873-4588-a14c-f505cb802247\u001b\\\u001b[32m-12657b1d-2873-4588-a14c-f505cb802247'\u001b[0m\u001b]8;;\u001b\\.     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/639eb096-a602-4b56-a502-cac1f18f9557\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=901973;https://tidy3d.simulation.cloud/folders/639eb096-a602-4b56-a502-cac1f18f9557\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c6ae82d457374c9e9631193b2c03d50b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:27:55 Eastern Daylight Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.104</span>. Minimum cost     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>depends on task execution details. Use           \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       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>FlexCredit cost after a simulation run.          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:27:55 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.104\u001b[0m. Minimum cost     \n",
       "\u001b[2;36m                               \u001b[0mdepends on task execution details. Use           \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       \n",
       "\u001b[2;36m                               \u001b[0mFlexCredit cost after a simulation run.          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:27:56 Eastern Daylight Time </span>status = success                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:27:56 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f1ad7939f78743aca0d017313191eb08",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:27:57 Eastern Daylight Time </span>loading simulation from data/sim_data.hdf5       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:27:57 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/sim_data.hdf5       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data = web.run(sim, task_name=\"dispersion\", path=\"data/sim_data.hdf5\", verbose=True)"
   ]
  },
  {
   "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": {
    "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()"
   ]
  },
  {
   "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": {
    "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\">                               </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'docs_dispersion_norm'</span> with task_id \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-0eb95b51-1792-4d79-8760-9bf898e2e855'</span> and  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'docs_dispersion_norm'\u001b[0m with task_id \n",
       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-0eb95b51-1792-4d79-8760-9bf898e2e855'\u001b[0m and  \n",
       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-0eb95b51-1792-4d79-8760-9bf898e2e855\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-0eb95b51-1792-4d79-8760-9bf898e2e855\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-0eb95b51-1792-4d79-8760-9bf898e2e855'</span></a>.     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=447744;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0eb95b51-1792-4d79-8760-9bf898e2e855\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=358008;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0eb95b51-1792-4d79-8760-9bf898e2e855\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=447744;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0eb95b51-1792-4d79-8760-9bf898e2e855\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=996562;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0eb95b51-1792-4d79-8760-9bf898e2e855\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=447744;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0eb95b51-1792-4d79-8760-9bf898e2e855\u001b\\\u001b[32m-0eb95b51-1792-4d79-8760-9bf898e2e855'\u001b[0m\u001b]8;;\u001b\\.     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/639eb096-a602-4b56-a502-cac1f18f9557\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=485531;https://tidy3d.simulation.cloud/folders/639eb096-a602-4b56-a502-cac1f18f9557\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bfa212230367446385d64d2c3c73ac1d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:27:58 Eastern Daylight Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Minimum cost     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>depends on task execution details. Use           \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       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>FlexCredit cost after a simulation run.          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:27:58 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Minimum cost     \n",
       "\u001b[2;36m                               \u001b[0mdepends on task execution details. Use           \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       \n",
       "\u001b[2;36m                               \u001b[0mFlexCredit cost after a simulation run.          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:27:59 Eastern Daylight Time </span>status = success                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:27:59 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7a9e185fc37a444690296b49f305b862",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">10:28:00 Eastern Daylight Time </span>loading simulation from data/sim_data.hdf5       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m10:28:00 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/sim_data.hdf5       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_norm = sim.copy(update={\"structures\": []})\n",
    "\n",
    "sim_data_norm = web.run(\n",
    "    sim_norm,\n",
    "    task_name=\"docs_dispersion_norm\",\n",
    "    path=\"data/sim_data.hdf5\",\n",
    "    verbose=True,\n",
    ")\n",
    "transmission_norm = sim_data_norm[\"flux\"].flux"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "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()"
   ]
  },
  {
   "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": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# import TMM package\n",
    "import tmm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "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",
    "    # 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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "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",
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    "plt.xlabel(r\"wavelength ($\\mu m$)\")\n",
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