{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0d1000f4-6f69-446b-b11c-c9ced5471d2d",
   "metadata": {},
   "source": [
    "# Photonic crystal reflectance\n",
    "\n",
    "<b>Author: Leyang Liu, University of Illinois Urbana-Champaign</b>\n",
    "\n",
    "In this notebook, we simulate the optical reflection spectrum of a 1D photonic crystal / grating structure using Tidy3D. The structure consists of nanopatterned SiO₂ and TiO₂ grating structures, with an additional poly(vinyl alcohol) overcoating layer. A broadband plane wave is incident on the structure, and the notebook computes:\n",
    "\n",
    "- Reflection spectrum vs wavelength\n",
    "- Electric field distribution\n",
    "- Poynting vector flow\n",
    "\n",
    "This type of simulation is typical for biosensors, dielectric metasurfaces, or photonic crystal reflectors.\n",
    "\n",
    "<img src=\"img/photonic_crystal_reflectance.png\" alt=\"diagram\" width=\"600\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0c8a2e2a-1f6c-48b6-a521-3effcf7a50a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:53:46 UTC </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Using canonical configuration directory at                </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/tidy3d/.config/tidy3d'</span><span style=\"color: #800000; text-decoration-color: #800000\">. Found legacy directory at           </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'~/.tidy3d'</span><span style=\"color: #800000; text-decoration-color: #800000\">, which will be ignored. Remove it manually or run      </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d config migrate --delete-legacy'</span><span style=\"color: #800000; text-decoration-color: #800000\"> to clean up.               </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:53:46 UTC\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Using canonical configuration directory at                \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'/home/tidy3d/.config/tidy3d'\u001b[0m\u001b[31m. Found legacy directory at           \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'~/.tidy3d'\u001b[0m\u001b[31m, which will be ignored. Remove it manually or run      \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'tidy3d config migrate --delete-legacy'\u001b[0m\u001b[31m to clean up.               \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n",
    "from tidy3d.plugins.dispersion import FastDispersionFitter"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7be98084-8299-48c4-8946-06ab7c88582e",
   "metadata": {},
   "source": [
    "Define material properties:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cbdd1e1d-6a8e-48b6-b793-cc9ed630056a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# materials\n",
    "SiO2 = td.Medium(\n",
    "    name = 'SiO2',\n",
    "    permittivity = 2.1025,\n",
    ")\n",
    "TiO2 = td.Medium(\n",
    "    name = 'TiO2',\n",
    "    permittivity = 5.8081000000000005,\n",
    ")\n",
    "background = td.Medium(permittivity=1**2)\n",
    "PVA = td.Medium(permittivity = 1.483**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f581557-5952-4a3d-b25c-bfbbf75b3e9f",
   "metadata": {},
   "source": [
    "Define structure geometry:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e4f82f18-8842-4eb9-b032-d740f277ea0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "period = 0.39\n",
    "TiO2_thick = 0.105\n",
    "SiO2_thick = 0.1\n",
    "PVA_thick = 0.070\n",
    "PVA_bottom_thick = 0.048\n",
    "sub_thick = 2\n",
    "monitor_distance = 1.0\n",
    "monitor_gap = 0.1\n",
    "dutycycle_SiO2 = 0.55\n",
    "TiO2_bottom_thick = 0.067\n",
    "slope_angle = 70/180*np.pi\n",
    "dutycycle_TiO2 = 0.6\n",
    "size_z = sub_thick+SiO2_thick+TiO2_thick+monitor_distance+monitor_gap\n",
    "SiO2_top_width = dutycycle_SiO2*period\n",
    "SiO2_bottom_width = SiO2_top_width+2*SiO2_thick/np.tan(slope_angle)\n",
    "TiO2_top_width = dutycycle_TiO2*period\n",
    "TiO2_bottom_width = TiO2_top_width+2*TiO2_thick/np.tan(slope_angle)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66cb7a71-5d6c-409c-8560-5fa52c763ab0",
   "metadata": {},
   "source": [
    "Define simulation parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "402a629f-600d-4b4d-9faf-1e9cba4c5b84",
   "metadata": {},
   "outputs": [],
   "source": [
    "# the epoxy layer top surface is at z=0\n",
    "sim_center = (0, 0, 0)\n",
    "sim_size = (\n",
    "    period,\n",
    "    0,\n",
    "    size_z\n",
    ")\n",
    "\n",
    "# wavelength / frequency setup\n",
    "nm = 1e-3\n",
    "wavelength_min = 500 * nm\n",
    "wavelength_max = 700 * nm\n",
    "freq_min = td.C_0 / wavelength_max\n",
    "freq_max = td.C_0 / wavelength_min\n",
    "freq0 = td.C_0 / (500 * nm)\n",
    "fwidth = freq_max - freq_min\n",
    "run_time = 10e-11\n",
    "\n",
    "# SiO2 sub\n",
    "SiO2_sub = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=[0.0, 0.0, -0.5 * sub_thick],\n",
    "        size=[td.inf, td.inf, sub_thick],\n",
    "    ),\n",
    "    medium=SiO2,\n",
    "    name=\"SiO2_sub\",\n",
    ")\n",
    "\n",
    "# SiO2 teeth\n",
    "vertices1 = [[SiO2_bottom_width / 2, 0], \n",
    "    [-SiO2_bottom_width / 2, 0], \n",
    "    [-SiO2_top_width / 2, SiO2_thick], \n",
    "    [SiO2_top_width / 2, SiO2_thick]]\n",
    "SiO2_teeth = td.Structure(\n",
    "    geometry = td.PolySlab(axis = 1, slab_bounds = [-td.inf, td.inf], vertices = vertices1),\n",
    "    name = 'SiO2_teeth', \n",
    "    medium = SiO2\n",
    ")\n",
    "\n",
    "# TiO2 \n",
    "vertices2 = [[TiO2_bottom_width / 2, TiO2_bottom_thick], \n",
    "    [TiO2_top_width / 2, SiO2_thick + TiO2_thick], \n",
    "    [-TiO2_top_width / 2, SiO2_thick + TiO2_thick], \n",
    "    [-TiO2_bottom_width / 2, TiO2_bottom_thick], \n",
    "    [-period / 2, TiO2_bottom_thick], \n",
    "    [-period / 2, 0], \n",
    "    [-SiO2_bottom_width / 2, 0], \n",
    "    [-SiO2_top_width / 2, SiO2_thick], \n",
    "    [SiO2_top_width / 2, SiO2_thick], \n",
    "    [SiO2_bottom_width / 2, 0], \n",
    "    [period / 2, 0], \n",
    "    [period / 2, TiO2_bottom_thick]]\n",
    "TiO2 = td.Structure(\n",
    "    geometry = td.PolySlab(axis = 1, slab_bounds = [-td.inf, td.inf], vertices = vertices2),\n",
    "    medium = TiO2,\n",
    "    name = 'TiO2'\n",
    ")\n",
    "\n",
    "# PVA\n",
    "vertices3 = [[TiO2_bottom_width / 2, TiO2_bottom_thick + PVA_bottom_thick], \n",
    "    [TiO2_top_width / 2, SiO2_thick + TiO2_thick + PVA_thick], \n",
    "    [-TiO2_top_width / 2, SiO2_thick + TiO2_thick + PVA_thick], \n",
    "    [-TiO2_bottom_width / 2, TiO2_bottom_thick + PVA_bottom_thick], \n",
    "    [-period / 2, TiO2_bottom_thick + PVA_bottom_thick], \n",
    "    [-period / 2, TiO2_bottom_thick], \n",
    "    [-TiO2_bottom_width / 2, TiO2_bottom_thick], \n",
    "    [-TiO2_top_width / 2, SiO2_thick + TiO2_thick], \n",
    "    [TiO2_top_width / 2, SiO2_thick + TiO2_thick], \n",
    "    [TiO2_bottom_width / 2, TiO2_bottom_thick], \n",
    "    [period / 2, TiO2_bottom_thick], \n",
    "    [period / 2, TiO2_bottom_thick + PVA_bottom_thick]]\n",
    "PVA = td.Structure(\n",
    "    geometry = td.PolySlab(axis = 1, slab_bounds = [-td.inf, td.inf], vertices = vertices3),\n",
    "    medium = PVA,\n",
    "    name = 'PVA'\n",
    ")\n",
    "\n",
    "# the order here matters, because the teeth must override the bottom film layer\n",
    "geometry = [SiO2_sub, SiO2_teeth, TiO2, PVA]\n",
    "# geometry = [epoxy_layer, bottom_film, grating_teeth, top_film]\n",
    "# boundary conditions: the simulation is periodic in the x-y plane, and simulates\n",
    "# an infinite domain along z\n",
    "boundary_spec = td.BoundarySpec(\n",
    "    x=td.Boundary.periodic(),\n",
    "    y=td.Boundary.periodic(),\n",
    "    z=td.Boundary.pml(),\n",
    ")\n",
    "\n",
    "# grid specification\n",
    "grid_spec = td.GridSpec.auto(min_steps_per_wvl=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a17b4c7a-6d85-4965-961c-1f22ae43bd70",
   "metadata": {},
   "source": [
    "Define source:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "74ea52ba-80f0-4c11-882b-519a49de5e63",
   "metadata": {},
   "outputs": [],
   "source": [
    "source_time = td.GaussianPulse(freq0=freq0, fwidth=fwidth)\n",
    "source = td.PlaneWave(\n",
    "    center=[0, 0, TiO2_thick + SiO2_thick + monitor_distance],\n",
    "    size=[td.inf, td.inf, 0.0],\n",
    "    source_time=source_time,\n",
    "    pol_angle=0,\n",
    "#    pol_angle=np.pi/2,\n",
    "    direction=\"-\",\n",
    "    angle_theta=np.deg2rad(0),\n",
    "    angular_spec=td.FixedAngleSpec(),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ac01d3d-2554-4a1d-a643-85b814d9d35e",
   "metadata": {},
   "source": [
    "Define monitors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fdb44bd1-70ef-478e-904a-7dc24aaa209d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create field monitor\n",
    "monitor_xz = td.FieldMonitor(\n",
    "    center=sim_center,\n",
    "    size=[td.inf, 0, td.inf],\n",
    "    freqs=[freq0],\n",
    "    name=\"fields_xz\",\n",
    ")\n",
    "\n",
    "# create flux monitors\n",
    "freqs = np.linspace(freq_min, freq_max, 1000)\n",
    "monitor_flux_refl = td.FluxMonitor(\n",
    "    center=[0, 0, monitor_distance],\n",
    "    size=[td.inf, td.inf, 0.0],\n",
    "    freqs=freqs,\n",
    "    name=\"flux_refl\",\n",
    ")\n",
    "monitors = [monitor_xz, monitor_flux_refl]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61a05b9c-4700-462f-977d-e94750c8a7c6",
   "metadata": {},
   "source": [
    "Put everything together in a simulation object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8de04898-c51e-4687-9d8b-671472327929",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:53:49 UTC </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Structure at </span><span style=\"color: #008000; text-decoration-color: #008000\">'structures[2]'</span><span style=\"color: #800000; text-decoration-color: #800000\"> has bounds that extend       </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">exactly to simulation edges. This can cause unexpected behavior. If</span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">intending to extend the structure to infinity along one dimension, </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">use td.inf as a size variable instead to make this explicit.       </span>\n",
       "</pre>\n"
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      "text/plain": [
       "\u001b[2;36m15:53:49 UTC\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Structure at \u001b[0m\u001b[32m'structures\u001b[0m\u001b[32m[\u001b[0m\u001b[32m2\u001b[0m\u001b[32m]\u001b[0m\u001b[32m'\u001b[0m\u001b[31m has bounds that extend       \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31mexactly to simulation edges. This can cause unexpected behavior. If\u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31mintending to extend the structure to infinity along one dimension, \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31muse td.inf as a size variable instead to make this explicit.       \u001b[0m\n"
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     },
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     "output_type": "display_data"
    },
    {
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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\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Suppressed </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span><span style=\"color: #800000; text-decoration-color: #800000\"> WARNING messages.                            </span>\n",
       "</pre>\n"
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     "metadata": {},
     "output_type": "display_data"
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     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create the simulation\n",
    "sim = td.Simulation(\n",
    "    center=sim_center,\n",
    "    size=sim_size,\n",
    "    grid_spec=grid_spec,\n",
    "    structures=geometry,\n",
    "    sources=[source],\n",
    "    monitors=monitors,\n",
    "    run_time=run_time,\n",
    "    boundary_spec=boundary_spec,\n",
    "    medium=background,\n",
    "    shutoff=1e-7,\n",
    ")\n",
    "\n",
    "# plot the simulation domain\n",
    "#sim.plot_3d()\n",
    "#plt.show()\n",
    "sim.plot(y=0.0, vlim=[0, 0.5])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ec8f6077-6800-411b-9738-4b8505cc28aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Simulation has </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6.33e+06</span><span style=\"color: #800000; text-decoration-color: #800000\"> time steps. The </span><span style=\"color: #008000; text-decoration-color: #008000\">'run_time'</span><span style=\"color: #800000; text-decoration-color: #800000\"> may be </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">unnecessarily large, unless there are very long-lived resonances.  </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Simulation has \u001b[0m\u001b[1;36m6.33e+06\u001b[0m\u001b[31m time steps. The \u001b[0m\u001b[32m'run_time'\u001b[0m\u001b[31m may be \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31munnecessarily large, unless there are very long-lived resonances.  \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>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'biosensor'</span> with resource_id                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-9878e97e-7c50-4fd4-8631-65f84387e98b'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'biosensor'\u001b[0m with resource_id                          \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-9878e97e-7c50-4fd4-8631-65f84387e98b'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-9878e97e-7c50-4fd4-8631-65f84387e98b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-9878e97e-7c5</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-9878e97e-7c50-4fd4-8631-65f84387e98b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">0-4fd4-8631-65f84387e98b'</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=127856;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9878e97e-7c50-4fd4-8631-65f84387e98b\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=994303;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9878e97e-7c50-4fd4-8631-65f84387e98b\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=127856;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9878e97e-7c50-4fd4-8631-65f84387e98b\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=367526;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9878e97e-7c50-4fd4-8631-65f84387e98b\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=127856;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9878e97e-7c50-4fd4-8631-65f84387e98b\u001b\\\u001b[32m-9878e97e-7c5\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=127856;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9878e97e-7c50-4fd4-8631-65f84387e98b\u001b\\\u001b[32m0-4fd4-8631-65f84387e98b'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-8f8ce399-9090-4f9c-a1fd-aa65aac04626\" 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=615951;https://tidy3d.simulation.cloud/folders/folder-8f8ce399-9090-4f9c-a1fd-aa65aac04626\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "eecb5461a1d64a0faa711a070e9b16bf",
       "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\">15:53:50 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.040</span>. Minimum cost depends on task     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:53:50 UTC\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.040\u001b[0m. Minimum cost depends on task     \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "98a1ce135edf456392f50295d47d6053",
       "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\">15:53:51 UTC </span>Loading simulation from data/biosensor.hdf5                        \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:53:51 UTC\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from data/biosensor.hdf5                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Structure at </span><span style=\"color: #008000; text-decoration-color: #008000\">'structures[2]'</span><span style=\"color: #800000; text-decoration-color: #800000\"> has bounds that extend       </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">exactly to simulation edges. This can cause unexpected behavior. If</span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">intending to extend the structure to infinity along one dimension, </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">use td.inf as a size variable instead to make this explicit.       </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Structure at \u001b[0m\u001b[32m'structures\u001b[0m\u001b[32m[\u001b[0m\u001b[32m2\u001b[0m\u001b[32m]\u001b[0m\u001b[32m'\u001b[0m\u001b[31m has bounds that extend       \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31mexactly to simulation edges. This can cause unexpected behavior. If\u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31mintending to extend the structure to infinity along one dimension, \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31muse td.inf as a size variable instead to make this explicit.       \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><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Suppressed </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span><span style=\"color: #800000; text-decoration-color: #800000\"> WARNING messages.                            </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Suppressed \u001b[0m\u001b[1;36m3\u001b[0m\u001b[31m WARNING messages.                            \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><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Warning messages were found in the solver log. For more   </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">information, check </span><span style=\"color: #008000; text-decoration-color: #008000\">'SimulationData.log'</span><span style=\"color: #800000; text-decoration-color: #800000\"> or use                     </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.download_log(task_id)'</span><span style=\"color: #800000; text-decoration-color: #800000\">.                                       </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Warning messages were found in the solver log. For more   \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31minformation, check \u001b[0m\u001b[32m'SimulationData.log'\u001b[0m\u001b[31m or use                     \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'web.download_log\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m\u001b[31m.                                       \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import tidy3d.web as web\n",
    "\n",
    "sim_data = web.run(sim, task_name=\"biosensor\", path=\"data/biosensor.hdf5\", verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f76c0f78-f428-4349-bcb5-5b5b0d3ac695",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 3, figsize=(8, 6), tight_layout=True)\n",
    "\n",
    "sim_data.plot_field(\"fields_xz\", field_name=\"E\", val=\"abs\", f=freq0, ax=ax[0])\n",
    "sim_data.plot_field(\"fields_xz\", field_name=\"Sz\", val=\"real\", f=freq0, ax=ax[1])\n",
    "sim_data.plot_field(\"fields_xz\", field_name=\"Sx\", val=\"real\", f=freq0, ax=ax[2])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6d301288-f14e-4346-8258-b8d88972ae00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "reflection = sim_data[\"flux_refl\"].flux+1\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(9, 4))\n",
    "\n",
    "ax.plot(td.C_0 / freqs * 1e3, reflection, label=\"Reflection\")\n",
    "\n",
    "# wavelength for the field plots\n",
    "ax.axvline(td.C_0 / freq0 * 1e3, ls=\"--\", color=\"k\", lw=1)\n",
    "\n",
    "ax.set(\n",
    "    xlabel=\"Wavelength (nm)\",\n",
    "    ylabel=\"Flux\",\n",
    "    xlim=(wavelength_min * 1e3, wavelength_max * 1e3),\n",
    ")\n",
    "ax.legend()\n",
    "ax.grid()\n",
    "#plt.xlim(550, 650)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Passive photonic integrated circuit components"
  ],
  "description": "This notebook calculates the reflectance for a 1-dimensional photonic crystal.",
  "feature_image": "./img/photonic_crystal_reflectance.png",
  "features": [
   "Adjoint inverse design"
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "FDTD, Tidy3D, photonic crystal",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.8"
  },
  "title": "Photonic crystal reflectance | Flexcompute"
 },
 "nbformat": 4,
 "nbformat_minor": 5
}