{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "97acab82-a694-4a57-a095-d637e1124024",
   "metadata": {},
   "source": [
    "# Vertical Chiral Emission\n",
    "\n",
    "**Author: Dr. Zhiyi Yuan, Nayang Technological University.**\n",
    "\n",
    "This notebook reproduces the paper: [\"Vertical chiral emission from an intrinsically achiral metasurface enabled with anisotropic continuum\"](https://doi.org/10.1038/s41467-026-68728-2).\n",
    "\n",
    "In particular, we simulate the unit cell of a $\\sigma_z$-symmetric dielectric metasurface. We create a silicon dimer in PMMA with symmetry offset by parameters $\\alpha$ and $\\delta t$ in location and size. We reproduce the reflectance spectra for $\\alpha$ = 0.09 and $\\delta t$ = 11 nm, as well as the transmission spectra of the metasurface for TE and TM incidence in the xz plane.\n",
    "\n",
    "<img src=\"img/vertical_chiral_emission.png\" alt=\"diagram\" width=\"500\"/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7a683346",
   "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\">21:56:39 EST </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Configuration found in legacy location </span><span style=\"color: #008000; text-decoration-color: #008000\">'~/.tidy3d'</span><span style=\"color: #800000; text-decoration-color: #800000\">.       </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">Consider running </span><span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d config migrate'</span><span style=\"color: #800000; text-decoration-color: #800000\">.                          </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:56:39 EST\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Configuration found in legacy location \u001b[0m\u001b[32m'~/.tidy3d'\u001b[0m\u001b[31m.       \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31mConsider running \u001b[0m\u001b[32m'tidy3d config migrate'\u001b[0m\u001b[31m.                          \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\n",
    "from matplotlib.patches import Rectangle\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "710f3e0b-2911-43c9-a283-4feed23ea709",
   "metadata": {},
   "source": [
    "## Create Structures in Unit Cell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3c11b270",
   "metadata": {},
   "outputs": [],
   "source": [
    "P = 0.35\n",
    "L = 0.19\n",
    "W = 0.09\n",
    "H = 0.21\n",
    "delta = 0.011\n",
    "alpha = 0.09\n",
    "lba = 0.75"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ec067c2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "medium_structure = td.Medium(permittivity=3.90**2)\n",
    "medium_env = td.Medium(permittivity=1.45**2)\n",
    "\n",
    "box_1 = td.Box(center=(-P/4, 0, 0), size=(W, L, H))\n",
    "box_2 = td.Box(center=(P/4-delta, -L*alpha/2, 0), size=(W, L*(1-alpha), H))\n",
    "# create the chiral structure\n",
    "metasurface_geom = td.GeometryGroup(geometries=[box_1, box_2])\n",
    "metasurface_structure = td.Structure(geometry=metasurface_geom, medium=medium_structure)\n",
    "# create the substrate structure\n",
    "inf_eff = 1e2\n",
    "#substrate = td.Structure(\n",
    "#    geometry=td.Box(center=(0, 0, -H/2-lda/2), size=(td.inf, td.inf, lba)),\n",
    "#    medium=medium_env,\n",
    "#)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12728cd8-915b-415e-8ac7-13c370851b10",
   "metadata": {},
   "source": [
    "## Create First Simulations\n",
    "\n",
    "Here we create two simulations to measure the reflectance spectra for both x-polarized and y-polarized radiation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7229edf2",
   "metadata": {},
   "outputs": [],
   "source": [
    "lda_start = 0.7\n",
    "lda_end = 0.9\n",
    "n_freqs = 1001\n",
    "ldas = np.linspace(lda_start, lda_end, n_freqs)\n",
    "freqs = td.C_0 / ldas\n",
    "freq0 = td.C_0 / np.mean(ldas)\n",
    "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fe11b487",
   "metadata": {},
   "outputs": [],
   "source": [
    "run_time = 3e-12\n",
    "monitor_z = 1  # monitor z position\n",
    "flux_monitor = td.FluxMonitor(\n",
    "    center=[0, 0, -monitor_z], size=[td.inf, td.inf, 0], freqs=freqs, name=\"flux\"\n",
    ")\n",
    "source_z = 1  \n",
    "# create an oblique plane wave source\n",
    "plane_wave_x = td.PlaneWave(\n",
    "    center=[0, 0, source_z],\n",
    "    size=[td.inf, td.inf, 0],\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth, phase=0.0),\n",
    "    direction=\"-\",\n",
    "    angle_theta=0,\n",
    "    angle_phi=0,\n",
    "    pol_angle=0,\n",
    "    #angular_spec=td.FixedInPlaneKSpec(),              \n",
    ")\n",
    "\n",
    "plane_wave_y = td.PlaneWave(\n",
    "    center=[0, 0, source_z],\n",
    "    size=[td.inf, td.inf, 0],\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth, phase=0.0),\n",
    "    direction=\"-\",\n",
    "    angle_theta=0,\n",
    "    angle_phi=0,\n",
    "    pol_angle=np.pi/2, \n",
    "    #angular_spec=td.FixedInPlaneKSpec(),              \n",
    ")\n",
    "\n",
    "# construct simulation\n",
    "sim = td.Simulation(\n",
    "    center=(0,0,0),\n",
    "    size=(P, P, 3),\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=20, max_scale=1.5),\n",
    "    structures=[metasurface_structure],\n",
    "    sources=[plane_wave_x],\n",
    "    monitors=[flux_monitor],\n",
    "    run_time=run_time,\n",
    "    boundary_spec=td.BoundarySpec(\n",
    "        x=td.Boundary.periodic(),\n",
    "        y=td.Boundary.periodic(),\n",
    "        z=td.Boundary.pml(),),\n",
    "    medium=medium_env,\n",
    "    shutoff=1e-5,\n",
    ")\n",
    "\n",
    "#ax = sim.plot(z=h/2)\n",
    "#sim.plot_grid(z=h/2, ax=ax)\n",
    "#plt.show()\n",
    "#sim.plot_3d()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e0a2af20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sim.plot(z=0)\n",
    "sim.plot_grid(z=0, ax=ax)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04e484f0-5c03-4387-b89c-bd952c787dda",
   "metadata": {},
   "source": [
    "Run the simulations. The final field decay value will be small but above our automatic shutoff value of 1e-5, which will throw some warnings. This will have a negligible effect, so for demonstration purposes we will suppress the warnings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "97cf1335-4f78-4f25-b41e-2e9a6108602b",
   "metadata": {},
   "outputs": [],
   "source": [
    "td.config.logging.level = \"ERROR\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "77acc8de",
   "metadata": {
    "scrolled": true
   },
   "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\">21:56:41 EST </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'VerticalChiral_X'</span> with resource_id                   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-93e9dab4-c821-4e22-a710-df130b4a7a41'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:56:41 EST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'VerticalChiral_X'\u001b[0m with resource_id                   \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-93e9dab4-c821-4e22-a710-df130b4a7a41'\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-93e9dab4-c821-4e22-a710-df130b4a7a41\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-93e9dab4-c82</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-93e9dab4-c821-4e22-a710-df130b4a7a41\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">1-4e22-a710-df130b4a7a41'</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=769580;https://tidy3d.simulation.cloud/workbench?taskId=fdve-93e9dab4-c821-4e22-a710-df130b4a7a41\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=428539;https://tidy3d.simulation.cloud/workbench?taskId=fdve-93e9dab4-c821-4e22-a710-df130b4a7a41\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=769580;https://tidy3d.simulation.cloud/workbench?taskId=fdve-93e9dab4-c821-4e22-a710-df130b4a7a41\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=585943;https://tidy3d.simulation.cloud/workbench?taskId=fdve-93e9dab4-c821-4e22-a710-df130b4a7a41\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=769580;https://tidy3d.simulation.cloud/workbench?taskId=fdve-93e9dab4-c821-4e22-a710-df130b4a7a41\u001b\\\u001b[32m-93e9dab4-c82\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=769580;https://tidy3d.simulation.cloud/workbench?taskId=fdve-93e9dab4-c821-4e22-a710-df130b4a7a41\u001b\\\u001b[32m1-4e22-a710-df130b4a7a41'\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-86acd7be-dbf5-477e-9c86-3e20787acc03\" 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=615073;https://tidy3d.simulation.cloud/folders/folder-86acd7be-dbf5-477e-9c86-3e20787acc03\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "80a9bc19b52a48a38bda68ad3a11b97f",
       "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\">21:56:43 EST </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Minimum cost depends on task     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:56:43 EST\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Minimum cost depends on task     \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:56:45 EST </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:56:45 EST\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "159092f436c347029f2723ebfc5abf1e",
       "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\">21:56:46 EST </span>Loading simulation from simulation_data.hdf5                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:56:46 EST\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'VerticalChiral_Y'</span> with resource_id                   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-3a075e0a-0542-4027-84b2-9da4639aeb5d'</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'VerticalChiral_Y'\u001b[0m with resource_id                   \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-3a075e0a-0542-4027-84b2-9da4639aeb5d'\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-3a075e0a-0542-4027-84b2-9da4639aeb5d\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a075e0a-054</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a075e0a-0542-4027-84b2-9da4639aeb5d\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">2-4027-84b2-9da4639aeb5d'</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=914349;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a075e0a-0542-4027-84b2-9da4639aeb5d\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=46332;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a075e0a-0542-4027-84b2-9da4639aeb5d\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=914349;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a075e0a-0542-4027-84b2-9da4639aeb5d\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=566846;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a075e0a-0542-4027-84b2-9da4639aeb5d\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=914349;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a075e0a-0542-4027-84b2-9da4639aeb5d\u001b\\\u001b[32m-3a075e0a-054\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=914349;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a075e0a-0542-4027-84b2-9da4639aeb5d\u001b\\\u001b[32m2-4027-84b2-9da4639aeb5d'\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-86acd7be-dbf5-477e-9c86-3e20787acc03\" 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=184203;https://tidy3d.simulation.cloud/folders/folder-86acd7be-dbf5-477e-9c86-3e20787acc03\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "622b5ca93e7f401d88a4697b233189cf",
       "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\">21:56:48 EST </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Minimum cost depends on task     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:56:48 EST\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Minimum cost depends on task     \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:56:49 EST </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:56:49 EST\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d47a1325abad4c4ba74cc8cabc2f86ee",
       "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\">21:56:50 EST </span>Loading simulation from simulation_data.hdf5                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:56:50 EST\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data_x = td.web.run(sim,task_name=\"VerticalChiral_X\",verbose=True)\n",
    "\n",
    "sim_data_y = sim.copy(update={\"sources\": [plane_wave_y]})\n",
    "sim_data_y = td.web.run(sim_data_y,task_name=\"VerticalChiral_Y\",verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df927139-f562-4175-afc3-08b6fba1b0aa",
   "metadata": {},
   "source": [
    "Visualize the reflectance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3fdc696b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "monitor_data_lcp = sim_data_x.monitor_data\n",
    "monitor_data_rcp = sim_data_y.monitor_data\n",
    "T_lcp = monitor_data_lcp[\"flux\"].flux\n",
    "T_rcp = monitor_data_rcp[\"flux\"].flux\n",
    "plt.plot(ldas, -T_lcp, linewidth=2.5, label=\"LCP\")\n",
    "plt.plot(ldas, -T_rcp, linewidth=2.5, label=\"RCP\")\n",
    "plt.xlabel(\"Wavelength (μm)\")\n",
    "plt.ylabel(\"Reflectance\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17f5c99e-9bbb-492e-8476-cb80b3213cd5",
   "metadata": {},
   "source": [
    "## Create Simulation Batch for TM Transmission\n",
    "\n",
    "Where the input plane wave radiation is P-polarized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "dbf545e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_sim(theta):\n",
    "    # create a plane wave source\n",
    "    source_z = 0.6   \n",
    "    # create an oblique plane wave source\n",
    "    plane_wave_x = td.PlaneWave(\n",
    "        center=[0, 0, source_z],\n",
    "        size=[td.inf, td.inf, 0],\n",
    "        source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "        direction=\"-\",\n",
    "        angle_theta=theta,\n",
    "        angle_phi=0,\n",
    "        pol_angle=0,\n",
    "        angular_spec=td.FixedInPlaneKSpec()\n",
    "    )\n",
    "\n",
    "    # construct simulation\n",
    "    sim = td.Simulation(\n",
    "        size=(P, P, 3),\n",
    "        grid_spec=td.GridSpec.auto(min_steps_per_wvl=20, max_scale=1.5),\n",
    "        structures=[metasurface_structure],\n",
    "        sources=[plane_wave_x],\n",
    "        monitors=[flux_monitor],\n",
    "        run_time=run_time,\n",
    "        boundary_spec=td.BoundarySpec(\n",
    "            x=td.Boundary.bloch_from_source(source=plane_wave_x, domain_size=P, axis=0, medium=medium_env),\n",
    "            y=td.Boundary.bloch_from_source(source=plane_wave_x, domain_size=P, axis=1, medium=medium_env),\n",
    "            z=td.Boundary.pml(),\n",
    "        ),\n",
    "        medium=medium_env,\n",
    "        shutoff=1e-5,\n",
    "    )\n",
    "\n",
    "    return sim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8a78a279",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ebe6a00b95e54264a9f02fd4d77fad2c",
       "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\">21:56:59 EST </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span> tasks.                      \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:56:59 EST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m36\u001b[0m tasks.                      \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\">21:57:32 EST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.900</span> for the whole batch.                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:57:32 EST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.900\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after    \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>completion.                                                        \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7d40290c373043df890e35a5304f1383",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:58:19 EST </span>Batch complete.                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:58:19 EST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "theta_list = np.linspace(-18, 18, 36)  # theta values for the parameter sweep\n",
    "# create a dictionary of simulations\n",
    "sims = {f\"theta={theta:.1f}\": make_sim(np.deg2rad(theta)) for theta in theta_list}\n",
    "# create and run a batch of simulations\n",
    "batch = web.Batch(simulations=sims)\n",
    "batch_results = batch.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "94237a03",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "T = np.array(\n",
    "    [np.abs(batch_results[f\"theta={theta:.1f}\"][\"flux\"].flux.values) for theta in theta_list]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fb510bc-020d-4bbe-826f-0e4163663335",
   "metadata": {},
   "source": [
    "Transmission spectra of the metasurface for TM incidence. Under TM-polarized incidence, we can see that only the TM$_1$ mode is excited, as opposed to the TE incidence simulated below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a0cf95e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pcolormesh(theta_list,ldas*1e3,T.T, cmap=\"inferno_r\")\n",
    "plt.ylabel(\"Wavelength (nm)\")\n",
    "plt.xlabel(\"Incident angle (deg)\")\n",
    "plt.title(\"Transmission (TM)\")\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3acabc6d-8c23-4b9a-a7aa-db4524a003e1",
   "metadata": {},
   "source": [
    "## Create Simulation Batch for TE Transmission\n",
    "\n",
    "Where the input plane wave radiation is S-polarized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "80ac8ebc",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_sim(theta):\n",
    "    # create a plane wave source\n",
    "    source_z = 0.6   \n",
    "    # create an oblique plane wave source\n",
    "    plane_wave_y = td.PlaneWave(\n",
    "        center=[0, 0, source_z],\n",
    "        size=[td.inf, td.inf, 0],\n",
    "        source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "        direction=\"-\",\n",
    "        angle_theta=theta,\n",
    "        angle_phi=0,\n",
    "        pol_angle=np.pi/2,\n",
    "        angular_spec=td.FixedInPlaneKSpec(),              \n",
    "    )\n",
    "\n",
    "    # construct simulation\n",
    "    sim = td.Simulation(\n",
    "        size=(P, P, 3),\n",
    "        grid_spec=td.GridSpec.auto(min_steps_per_wvl=20, max_scale=1.5),\n",
    "        structures=[metasurface_structure],\n",
    "        sources=[plane_wave_y],\n",
    "        monitors=[flux_monitor],\n",
    "        run_time=run_time,\n",
    "        boundary_spec=td.BoundarySpec(\n",
    "            x=td.Boundary.bloch_from_source(source=plane_wave_y, domain_size=P, axis=0, medium=medium_env),\n",
    "            y=td.Boundary.bloch_from_source(source=plane_wave_y, domain_size=P, axis=1, medium=medium_env),\n",
    "            z=td.Boundary.pml(),\n",
    "        ),\n",
    "        medium=medium_env,\n",
    "        shutoff=1e-5,\n",
    "    )\n",
    "\n",
    "    return sim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b516eaf3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "17ce46b3d5d749a9a1d7f499a224a601",
       "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\">21:58:51 EST </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span> tasks.                      \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:58:51 EST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m36\u001b[0m tasks.                      \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\">21:59:24 EST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.900</span> for the whole batch.                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:59:24 EST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.900\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after    \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>completion.                                                        \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "70f7112d649747aa83df9a3f558ff4bb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">22:00:11 EST </span>Batch complete.                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m22:00:11 EST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "theta_list = np.linspace(-18, 18, 36)  # theta values for the parameter sweep\n",
    "# create a dictionary of simulations\n",
    "sims = {f\"theta={theta:.1f}\": make_sim(np.deg2rad(theta)) for theta in theta_list}\n",
    "# create and run a batch of simulations\n",
    "batch = web.Batch(simulations=sims)\n",
    "batch_results = batch.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "202a5b44",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "T = np.array(\n",
    "    [np.abs(batch_results[f\"theta={theta:.1f}\"][\"flux\"].flux.values) for theta in theta_list]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b79b1655-4cb2-4eb6-b5ce-5804512a0d2d",
   "metadata": {},
   "source": [
    "Transmission spectra of the metasurface for TE incidence. Under TE-polarized incidence, we can see 3 modes: TM$_1$, TE$_1$, and TM$_2$. The TM$_1$ mode has a dip in transmission, expected by the paper through coupling to the TM and TE components."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "eff3a7ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pcolormesh(theta_list,ldas*1e3,T.T, cmap=\"inferno_r\")\n",
    "plt.ylabel(\"Wavelength (nm)\")\n",
    "plt.xlabel(\"Incident angle (deg)\")\n",
    "plt.title(\"Transmission (TE)\")\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Metasurfaces"
  ],
  "description": "This notebook demonstrates vertical chiral emission from a metasurface",
  "feature_image": "./img/vertical_chiral_emission.png",
  "features": [
   "Metasurfaces"
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "metasurfaces, nanophotonics, Tidy3D, FDTD",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.8"
  },
  "title": "How to Simulate Vertical Chiral Emission Using Tidy3D | Flexcompute"
 },
 "nbformat": 4,
 "nbformat_minor": 5
}