{ "cells": [ { "cell_type": "markdown", "id": "6f64f45c", "metadata": {}, "source": [ "# Plasmonic cavity resonator consisting of a gold nanorod array" ] }, { "cell_type": "markdown", "id": "45e67b25", "metadata": {}, "source": [ "Plasmonic structures have been under intense research interest in the past few decades, primarily because of their unique ability to confine light to subwavelength dimensions, significantly enhancing electromagnetic fields at their surfaces. This phenomenon has opened up new avenues in various scientific fields, including photovoltaics, sensing, and nanoscale imaging, by enabling the manipulation of light at the nanometer scale. \n", "\n", "In this notebook, we demonstrate the modeling of a hexagonal lattice of gold nanorods, which supports localized surface plasmon resonances. When excited by a plane wave, these resonances manifest as distinct dips in the reflectance spectrum, indicative of the efficient transfer of incident power into the plasmon modes. Through the examination of field profiles at these resonance points, it becomes possible to discern the standing waves correlating to various harmonics. The design is adopted from `David P. Lyvers, Jeong-Mi Moon, Alexander V. Kildishev, Vladimir M. Shalaev, and Alexander Wei, ACS Nano 2008, 2, 12, 2569–2576` [DOI: 10.1021/nn8006477](https://doi.org/10.1021/nn8006477).\n", "\n", "\"Schematic\n", "\n", "This notebook mainly aims to demonstrate how to model a hexagonal lattice within the FDTD simulation domain, which is rectangular. In addition, the plane wave source in `Tidy3D` by default has an incident power of 1 W. In this example, we also demonstrate how to perform field normalization to obtain a meaningful relative field enhancement factor. For more discussion on source normalization, refer to the [FAQ entry](https://www.flexcompute.com/tidy3d/learning-center/faq/#how-are-results-normalized).\n", "\n", "Periodic or quasi-periodic structures are common in photonic devices. In Tidy3D's example library, we have demonstrated a [gradient metasurface reflector](https://www.flexcompute.com/tidy3d/examples/notebooks/GradientMetasurfaceReflector/), a [metalens at the visible frequency](https://www.flexcompute.com/tidy3d/examples/notebooks/Metalens/), and a [graphene metamaterial absorber](https://www.flexcompute.com/tidy3d/examples/notebooks/GrapheneMetamaterial/). In addition, we also investigated a [frequency selected surface](https://www.flexcompute.com/tidy3d/examples/notebooks/MicrowaveFrequencySelectiveSurface/) for the microwave frequency range." ] }, { "cell_type": "code", "execution_count": 1, "id": "819a113b", "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:32:47.716346Z", "iopub.status.busy": "2025-05-15T10:32:47.716239Z", "iopub.status.idle": "2025-05-15T10:32:48.999500Z", "shell.execute_reply": "2025-05-15T10:32:48.999112Z" } }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import tidy3d as td\n", "import tidy3d.web as web" ] }, { "cell_type": "markdown", "id": "3e546025", "metadata": {}, "source": [ "## Simulation Setup" ] }, { "cell_type": "markdown", "id": "b3806184", "metadata": {}, "source": [ "Define the simulation wavelength (frequency) range." ] }, { "cell_type": "code", "execution_count": 2, "id": "e1c761c0", "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:32:49.001141Z", "iopub.status.busy": "2025-05-15T10:32:49.000913Z", "iopub.status.idle": "2025-05-15T10:32:49.003478Z", "shell.execute_reply": "2025-05-15T10:32:49.003245Z" } }, "outputs": [], "source": [ "lda0 = 1.15 # central wavelength\n", "freq0 = td.C_0 / lda0 # central frequency\n", "ldas = np.linspace(0.4, 1.9, 201) # wavelength range\n", "freqs = td.C_0 / ldas # frequency range\n", "fwidth = 0.5 * (np.max(freqs) - np.min(freqs)) # width of the source frequency range" ] }, { "cell_type": "markdown", "id": "f8b9448e", "metadata": {}, "source": [ "Define the geometric parameters for the nanorod array. " ] }, { "cell_type": "code", "execution_count": 3, "id": "411092a3", "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:32:49.004757Z", "iopub.status.busy": "2025-05-15T10:32:49.004679Z", "iopub.status.idle": "2025-05-15T10:32:49.006705Z", "shell.execute_reply": "2025-05-15T10:32:49.006302Z" } }, "outputs": [], "source": [ "h = 0.649 # height of the nanorods\n", "a = 0.098 # spacing between the nanorods\n", "d = 0.0636 # diameter of the nanorods\n", "t_base = 0.05 # thickness of the base plate" ] }, { "cell_type": "markdown", "id": "b6c6fbf3", "metadata": {}, "source": [ "Define the materials used in the simulation. Tidy3D's material library provides several options for gold. In this particular case, we will use the data from the widely used [paper](https://journals.aps.org/prb/abstract/10.1103/PhysRevB.6.4370) by Johnson and Christy in 1972. \n", "\n", "The Al$_2$O$_3$ is defined by a constant refractive index material in the wavelength range of interest." ] }, { "cell_type": "code", "execution_count": 4, "id": "c74e4ddf", "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:32:49.007981Z", "iopub.status.busy": "2025-05-15T10:32:49.007908Z", "iopub.status.idle": "2025-05-15T10:32:49.009673Z", "shell.execute_reply": "2025-05-15T10:32:49.009497Z" } }, "outputs": [], "source": [ "# define gold material from the material library\n", "gold = td.material_library[\"Au\"][\"JohnsonChristy1972\"]\n", "\n", "# define Al2O3 material as a constant refractive index\n", "n_eff = 1.61 # refractive index of Al2O3\n", "al2o3 = td.Medium(permittivity=n_eff**2)" ] }, { "cell_type": "markdown", "id": "9a0a1f93", "metadata": {}, "source": [ "Next we define the structures, which include the dielectric filling, two nanorods, and a base plate. \n", "\n", "The nanorods are arranged in a hexagonal lattice. In FDTD, the simulation domain needs to be rectangular. For a hexagonal lattice, we can identify a rectangular unit cell as indicated by the blue dashed box below. For a plane wave excitation, we can apply periodic boundary conditions for normal incidence or Bloch boundary conditions for oblique incidence. \n", "\n", "In addition, we notice that the unit cell structure has two reflection symmetries. Therefore, in the case of normal incidence of a plane wave linearly polarized either in the horizontal or vertical directions, we can utilize the symmetry to further reduce the simulation domain size by a factor of 4. For more details on symmetry, please refer to the tutorial [here](https://www.flexcompute.com/tidy3d/examples/notebooks/Symmetry/). Next we are going to take this approach and only model the unit cell.\n", "\n", "\"Schematic" ] }, { "cell_type": "code", "execution_count": 5, "id": "f4fb961b", "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:32:49.010985Z", "iopub.status.busy": "2025-05-15T10:32:49.010881Z", "iopub.status.idle": "2025-05-15T10:32:49.014051Z", "shell.execute_reply": "2025-05-15T10:32:49.013825Z" } }, "outputs": [], "source": [ "# define the Al2O3 filling structure\n", "dielectric = td.Structure(\n", " geometry=td.Box(center=(0, 0, h / 2), size=(td.inf, td.inf, h)), medium=al2o3\n", ")\n", "\n", "# define the first nanorod structure\n", "rod_1 = td.Structure(\n", " geometry=td.Cylinder(center=(0, 0, h / 2), radius=d / 2, length=h), medium=gold\n", ")\n", "\n", "# define the second nanorod structure\n", "rod_2 = td.Structure(\n", " geometry=td.Cylinder(center=(a / 2, np.sqrt(3) * a / 2, h / 2), radius=d / 2, length=h),\n", " medium=gold,\n", ")\n", "\n", "# define the third nanorod structure\n", "rod_3 = td.Structure(\n", " geometry=td.Cylinder(center=(a / 2, -np.sqrt(3) * a / 2, h / 2), radius=d / 2, length=h),\n", " medium=gold,\n", ")\n", "\n", "# define the forth nanorod structure\n", "rod_4 = td.Structure(\n", " geometry=td.Cylinder(center=(-a / 2, np.sqrt(3) * a / 2, h / 2), radius=d / 2, length=h),\n", " medium=gold,\n", ")\n", "\n", "# define the fifth nanorod structure\n", "rod_5 = td.Structure(\n", " geometry=td.Cylinder(center=(-a / 2, -np.sqrt(3) * a / 2, h / 2), radius=d / 2, length=h),\n", " medium=gold,\n", ")\n", "\n", "# define the base plate structure\n", "base = td.Structure(\n", " geometry=td.Box(center=(0, 0, -t_base / 2), size=(td.inf, td.inf, t_base)), medium=gold\n", ")" ] }, { "cell_type": "markdown", "id": "89259852", "metadata": {}, "source": [ "Next we define the source and monitors. A [PlaneWave](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PlaneWave.html) polarized in the $y$ direction is injected from the top of the nanorods. By default the plane wave is polarized in the $x$ direction. To make it $y$-polarized, we set `pol_angle` to $\\pi$/2.\n", "\n", "To measure reflection, we define a [FluxMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FluxMonitor.html) above the [PlaneWave](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PlaneWave.html). In addition, we define a [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldMonitor.html) to help visualize the field profiles at the resonances. In principle, one needs to run the simulation first without the [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldMonitor.html) to determine the resonance wavelengths (frequencies) and then rerun it with the [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldMonitor.html) set to record the resonance frequencies. For presentation purposes, the resonance wavelengths (frequencies) are pre-determined here." ] }, { "cell_type": "code", "execution_count": 6, "id": "442e1480", "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:32:49.015407Z", "iopub.status.busy": "2025-05-15T10:32:49.015300Z", "iopub.status.idle": "2025-05-15T10:32:49.017856Z", "shell.execute_reply": "2025-05-15T10:32:49.017662Z" } }, "outputs": [], "source": [ "# define a plane wave incident on the nanorod array from the top\n", "plane_wave = td.PlaneWave(\n", " source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n", " size=(td.inf, td.inf, 0),\n", " center=(0, 0, h + 0.4 * lda0),\n", " direction=\"-\",\n", " pol_angle=np.pi / 2,\n", ")\n", "\n", "# define a flux monitor above the plane wave to measure reflection\n", "flux_monitor = td.FluxMonitor(\n", " center=[0, 0, h + 0.5 * lda0], size=[td.inf, td.inf, 0], freqs=freqs, name=\"R\"\n", ")\n", "\n", "# pre-determined resonance wavelengths\n", "res_ldas = np.array([1.6, 1.25, 0.93, 0.765, 0.675])\n", "# corresponding resonance frequencies\n", "res_freqs = td.C_0 / res_ldas\n", "\n", "# define a field monitor at the resonance frequencies to visualize the excited modes\n", "monitor_field = td.FieldMonitor(\n", " center=[a / 4, a * np.sqrt(3) / 4, h / 2],\n", " size=[0, a * np.sqrt(3) / 2, 2 * h],\n", " freqs=res_freqs,\n", " name=\"field\",\n", ")" ] }, { "cell_type": "markdown", "id": "b5941330", "metadata": {}, "source": [ "With everything in place, we are ready to define the [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html). Since the simulation domain is very small, we can afford to use a very fine grid without increasing the cost. In this case, we use an automatic nonuniform grid with a minimum steps per wavelength of 80. \n", "\n", "For the boundary condition, we apply the periodic boundary condition in the $x$ and $y$ directions and PML in the $z$ direction. `symmetry=(1,-1,0)` is used since the incident light is polarized in the $y$ direction.\n", "\n", "The default automatic shutoff level is `1e-5` but we decreased it to `1e-7` to further enhance the simulation accuracy, which is typically not required. It can be needed in simulations like plasmonics where strong fields are concentrated in relatively small volumes." ] }, { "cell_type": "code", "execution_count": 7, "id": "9187a83c", "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:32:49.019145Z", "iopub.status.busy": "2025-05-15T10:32:49.019004Z", "iopub.status.idle": "2025-05-15T10:32:49.029483Z", "shell.execute_reply": "2025-05-15T10:32:49.029253Z" } }, "outputs": [], "source": [ "run_time = 2e-13 # simulation run time\n", "\n", "# define simulation domain size\n", "sim_size = (a, np.sqrt(3) * a, 1.5 * lda0 + h)\n", "\n", "# set up simulation\n", "sim = td.Simulation(\n", " center=(0, 0, h / 2),\n", " size=sim_size,\n", " grid_spec=td.GridSpec.auto(min_steps_per_wvl=80, wavelength=lda0),\n", " structures=[dielectric, base, rod_1, rod_2, rod_3, rod_4, rod_5],\n", " sources=[plane_wave],\n", " monitors=[flux_monitor, monitor_field],\n", " run_time=run_time,\n", " boundary_spec=td.BoundarySpec(\n", " x=td.Boundary.periodic(), y=td.Boundary.periodic(), z=td.Boundary.pml()\n", " ),\n", " symmetry=(1, -1, 0),\n", " shutoff=1e-7, # reducing the default shutoff level\n", ")" ] }, { "cell_type": "markdown", "id": "24ccd2d1", "metadata": {}, "source": [ "After the simulation is set up, we can inspect the structure and grid to ensure the setup is correct and the grid is sufficiently fine." ] }, { "cell_type": "code", "execution_count": 8, "id": "501d8190", "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:32:49.030820Z", "iopub.status.busy": "2025-05-15T10:32:49.030700Z", "iopub.status.idle": "2025-05-15T10:32:49.206372Z", "shell.execute_reply": "2025-05-15T10:32:49.206063Z" } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax = sim.plot(z=h / 2)\n", "sim.plot_grid(z=h / 2, ax=ax)\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "dc627fed", "metadata": {}, "source": [ "Also plot the 3D visualization." ] }, { "cell_type": "code", "execution_count": 9, "id": "e37b0d79", "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:32:49.207750Z", "iopub.status.busy": "2025-05-15T10:32:49.207666Z", "iopub.status.idle": "2025-05-15T10:32:49.212755Z", "shell.execute_reply": "2025-05-15T10:32:49.212434Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sim.plot_3d()" ] }, { "cell_type": "markdown", "id": "c1cbd78f", "metadata": {}, "source": [ "## Run Simulation" ] }, { "cell_type": "markdown", "id": "58aa7a82", "metadata": {}, "source": [ "Now we are ready to submit the simulation to the server." ] }, { "cell_type": "code", "execution_count": 10, "id": "76e001ee", "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:32:49.214150Z", "iopub.status.busy": "2025-05-15T10:32:49.214012Z", "iopub.status.idle": "2025-05-15T10:32:55.959123Z", "shell.execute_reply": "2025-05-15T10:32:55.958732Z" }, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
12:32:50 CEST Created task 'nanorod_array' with task_id                         \n",
       "              'fdve-16dcd602-45e4-4e1e-affa-31be97ca71c4' and task_type 'FDTD'. \n",
       "
\n" ], "text/plain": [ "\u001b[2;36m12:32:50 CEST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'nanorod_array'\u001b[0m with task_id \n", "\u001b[2;36m \u001b[0m\u001b[32m'fdve-16dcd602-45e4-4e1e-affa-31be97ca71c4'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m. \n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
              View task using web UI at                                         \n",
       "              'https://tidy3d.simulation.cloud/workbench?taskId=fdve-16dcd602-45\n",
       "              e4-4e1e-affa-31be97ca71c4'.                                       \n",
       "
\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=510266;https://tidy3d.simulation.cloud/workbench?taskId=fdve-16dcd602-45e4-4e1e-affa-31be97ca71c4\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=745859;https://tidy3d.simulation.cloud/workbench?taskId=fdve-16dcd602-45e4-4e1e-affa-31be97ca71c4\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=510266;https://tidy3d.simulation.cloud/workbench?taskId=fdve-16dcd602-45e4-4e1e-affa-31be97ca71c4\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=900021;https://tidy3d.simulation.cloud/workbench?taskId=fdve-16dcd602-45e4-4e1e-affa-31be97ca71c4\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=510266;https://tidy3d.simulation.cloud/workbench?taskId=fdve-16dcd602-45e4-4e1e-affa-31be97ca71c4\u001b\\\u001b[32m-16dcd602-45\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[2;36m \u001b[0m\u001b]8;id=510266;https://tidy3d.simulation.cloud/workbench?taskId=fdve-16dcd602-45e4-4e1e-affa-31be97ca71c4\u001b\\\u001b[32me4-4e1e-affa-31be97ca71c4'\u001b[0m\u001b]8;;\u001b\\. \n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
              Task folder: 'default'.                                           \n",
       "
\n" ], "text/plain": [ "\u001b[2;36m \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=58323;https://tidy3d.simulation.cloud/folders/folder-bfe11006-2cae-4abd-bc02-04b6047e01be\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\. \n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "43b8e458dab34305bfe418017a7a684a", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Output()" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
12:32:51 CEST Maximum FlexCredit cost: 0.030. Minimum cost depends on task      \n",
       "              execution details. Use 'web.real_cost(task_id)' to get the billed \n",
       "              FlexCredit cost after a simulation run.                           \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m12:32:51 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.030\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": [
       "
12:32:52 CEST status = success                                                  \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m12:32:52 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "551de5d603ea4c26b84d7685427f6cdb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
12:32:55 CEST loading simulation from simulation_data.hdf5                      \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m12:32:55 CEST\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                      \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data = web.run(simulation=sim, task_name=\"nanorod_array\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48488a95",
   "metadata": {},
   "source": [
    "## Postprocessing and Result Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dad48101",
   "metadata": {},
   "source": [
    "Since the simulation domain is quite small, the simulation took less than a minute to finish. First, we plot the reflectance spectrum. Vertical lines are added to indicate the resonance wavelengths. At resonance, the incident wave excites the plasmon modes and thus the reflection is suppressed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "425bf44d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:32:55.977628Z",
     "iopub.status.busy": "2025-05-15T10:32:55.977561Z",
     "iopub.status.idle": "2025-05-15T10:32:56.091360Z",
     "shell.execute_reply": "2025-05-15T10:32:56.091041Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "R = sim_data[\"R\"].flux  # extract reflectance\n",
    "\n",
    "# plotting\n",
    "plt.plot(ldas, R, c=\"black\", linewidth=2)\n",
    "\n",
    "# adding vertical lines at the resonances\n",
    "for res_lda in res_ldas:\n",
    "    plt.axvline(x=res_lda, linestyle=\"--\", c=\"red\")\n",
    "\n",
    "plt.xlim(min(ldas), max(ldas))\n",
    "plt.ylim(0, 1)\n",
    "plt.xlabel(r\"Wavelength($\\mu m$)\", fontsize=15)\n",
    "plt.ylabel(\"Reflectance\", fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.xticks(fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a76802a",
   "metadata": {},
   "source": [
    "Finally, plot the field profiles at the resonance wavelengths. In particular, we plot the absolute value of $E_y$. Here we can clearly observe the standing wave patterns with increasing orders between the rods, consistent with the result presented in Figure 4 of the [original publication](https://doi.org/10.1021/nn8006477)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "73de6a56",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:32:56.092898Z",
     "iopub.status.busy": "2025-05-15T10:32:56.092771Z",
     "iopub.status.idle": "2025-05-15T10:32:56.533745Z",
     "shell.execute_reply": "2025-05-15T10:32:56.533236Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, len(res_ldas), figsize=(9, 4), tight_layout=True)\n",
    "for i, res_freq in enumerate(res_freqs):\n",
    "    E = np.sqrt(sim_data[\"field\"].intensity.sel(f=res_freq))  # field strength\n",
    "\n",
    "    # plotting\n",
    "    E.plot(x=\"y\", y=\"z\", ax=ax[i], vmin=0, vmax=1e3, cmap=\"jet\")\n",
    "    ax[i].set_title(rf\"$\\lambda$={res_ldas[i]} $\\mu m$\")\n",
    "    ax[i].set_ylim(-0.2, h + 0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ec5f751",
   "metadata": {},
   "source": [
    "## Normalization of the Field"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09dcdd3d",
   "metadata": {},
   "source": [
    "Note that in Tidy3D, the plane wave has a constant power of 1 W. Therefore, the field strength scales with the plane size of the source. Very often we want to get the normalized field enhancement relative to the source field strength. To get the source field strength, one can calculate it analytically based on the power and area of the source plane. Alternatively, in a more convenient and accurate way, one can run a reference simulation without any structures and get the incident field strength numerically. Here we demonstrate how to do it.\n",
    "\n",
    "First we create a reference simulation by copying the previous simulation and updating the structures to an empty list, i.e. no structures. We run the simulation to get the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "69b9adda",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:32:56.535209Z",
     "iopub.status.busy": "2025-05-15T10:32:56.535125Z",
     "iopub.status.idle": "2025-05-15T10:33:01.599110Z",
     "shell.execute_reply": "2025-05-15T10:33:01.598849Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
12:32:56 CEST Created task 'reference' with task_id                             \n",
       "              'fdve-3cbe8316-b78b-4928-9c95-25c46e551951' and task_type 'FDTD'. \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m12:32:56 CEST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'reference'\u001b[0m with task_id                             \n",
       "\u001b[2;36m              \u001b[0m\u001b[32m'fdve-3cbe8316-b78b-4928-9c95-25c46e551951'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m. \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              View task using web UI at                                         \n",
       "              'https://tidy3d.simulation.cloud/workbench?taskId=fdve-3cbe8316-b7\n",
       "              8b-4928-9c95-25c46e551951'.                                       \n",
       "
\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=962550;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3cbe8316-b78b-4928-9c95-25c46e551951\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=186643;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3cbe8316-b78b-4928-9c95-25c46e551951\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=962550;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3cbe8316-b78b-4928-9c95-25c46e551951\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=594589;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3cbe8316-b78b-4928-9c95-25c46e551951\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=962550;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3cbe8316-b78b-4928-9c95-25c46e551951\u001b\\\u001b[32m-3cbe8316-b7\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=962550;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3cbe8316-b78b-4928-9c95-25c46e551951\u001b\\\u001b[32m8b-4928-9c95-25c46e551951'\u001b[0m\u001b]8;;\u001b\\.                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              Task folder: 'default'.                                           \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=599891;https://tidy3d.simulation.cloud/folders/folder-bfe11006-2cae-4abd-bc02-04b6047e01be\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                           \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1b3c960caf3b42eeb9287fdbb6bb2524",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
12:32:58 CEST Maximum FlexCredit cost: 0.025. Minimum cost depends on task      \n",
       "              execution details. Use 'web.real_cost(task_id)' to get the billed \n",
       "              FlexCredit cost after a simulation run.                           \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m12:32:58 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum 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": [
       "
12:32:59 CEST status = success                                                  \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m12:32:59 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f7391c96b5ed4029ad72d8d5a141007e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
12:33:01 CEST loading simulation from simulation_data.hdf5                      \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m12:33:01 CEST\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                      \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_ref = sim.copy(update={\"structures\": []})\n",
    "\n",
    "sim_data_ref = web.run(simulation=sim_ref, task_name=\"reference\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d80b8b1",
   "metadata": {},
   "source": [
    "After getting the results, we can inspect it a bit. Since the incident plane wave is polarized in the $y$ direction, let's see the absolute value of $E_y$ at $z$=0. As expected, the field strength is a constant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3f91f7f4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:01.610598Z",
     "iopub.status.busy": "2025-05-15T10:33:01.610537Z",
     "iopub.status.idle": "2025-05-15T10:33:01.632650Z",
     "shell.execute_reply": "2025-05-15T10:33:01.632432Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "
<xarray.ScalarFieldDataArray (x: 1, y: 8)> Size: 32B\n",
       "array([[213.0657 , 213.0657 , 213.0657 , 213.0657 , 213.06573, 213.0657 ,\n",
       "        213.0657 , 213.0657 ]], dtype=float32)\n",
       "Coordinates:\n",
       "    z        float64 8B -0.004428\n",
       "    f        float64 8B 4.441e+14\n",
       "  * x        (x) float64 8B 0.0245\n",
       "  * y        (y) float64 64B -0.01415 0.0 0.01415 ... 0.05658 0.07073 0.08487\n",
       "Attributes:\n",
       "    long_name:  field value
"
      ],
      "text/plain": [
       " Size: 32B\n",
       "array([[213.0657 , 213.0657 , 213.0657 , 213.0657 , 213.06573, 213.0657 ,\n",
       "        213.0657 , 213.0657 ]], dtype=float32)\n",
       "Coordinates:\n",
       "    z        float64 8B -0.004428\n",
       "    f        float64 8B 4.441e+14\n",
       "  * x        (x) float64 8B 0.0245\n",
       "  * y        (y) float64 64B -0.01415 0.0 0.01415 ... 0.05658 0.07073 0.08487\n",
       "Attributes:\n",
       "    long_name:  field value"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim_data_ref[\"field\"].Ey.abs.sel(f=res_freqs[-1], z=0, method=\"nearest\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e0db101",
   "metadata": {},
   "source": [
    "Now we can normalize the field in the previous plot by the incident field strength and plot it again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7994c77d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:01.634013Z",
     "iopub.status.busy": "2025-05-15T10:33:01.633876Z",
     "iopub.status.idle": "2025-05-15T10:33:02.199839Z",
     "shell.execute_reply": "2025-05-15T10:33:02.199243Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, len(res_ldas), figsize=(9, 4), tight_layout=True)\n",
    "for i, res_freq in enumerate(res_freqs):\n",
    "    E_sim = np.sqrt(sim_data[\"field\"].intensity.sel(f=res_freq))  # simulated field strength\n",
    "    E_ref = (\n",
    "        sim_data_ref[\"field\"].Ey.abs.sel(f=res_freq, z=0, y=0, method=\"nearest\").values[0]\n",
    "    )  # incident field strength\n",
    "    E_norm = E_sim / E_ref  # normalization\n",
    "\n",
    "    # plotting field profiles\n",
    "    E_norm.plot(x=\"y\", y=\"z\", ax=ax[i], vmin=0, vmax=5, cmap=\"jet\")\n",
    "    ax[i].set_title(rf\"$\\lambda$={res_ldas[i]} $\\mu m$\")\n",
    "    ax[i].set_ylim(-0.2, h + 0.2)\n",
    "plt.show()"
   ]
  },
  {
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   "id": "0315cb84",
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   "source": [
    "Just as a check, we can calculate the incident field strength by $|E|= (2P/(c_0 \\varepsilon_0 A))^{1/2}$, where $\\varepsilon_0$ is the vacuum permittivity, $c_0$ is the speed of light, $A$ is the area of the source plane, and $P$ is the source power. \n",
    "\n",
    "As we can see, the result from this calculation is very close to the field strength from the previous reference simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "973b46b9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:02.201103Z",
     "iopub.status.busy": "2025-05-15T10:33:02.200983Z",
     "iopub.status.idle": "2025-05-15T10:33:02.203470Z",
     "shell.execute_reply": "2025-05-15T10:33:02.203108Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The calculated incident field strength is 212.83 V/um.\n"
     ]
    }
   ],
   "source": [
    "P = 1  # incident power is 1 W\n",
    "A = a * np.sqrt(3) * a  # source plane area in um^2\n",
    "E_ref = np.sqrt(2 * P / (td.C_0 * td.EPSILON_0 * A))\n",
    "print(f\"The calculated incident field strength is {E_ref:.2f} V/um.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7187886c",
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   "outputs": [],
   "source": []
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