{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Monostatic radar cross section (RCS) of a PEC sphere\n",
        "\n",
        "Monostatic RCS measures the power of an electromagnetic wave reflected\n",
        "directly back to the radar source (transmitter and receiver are\n",
        "co-located). Mathematically, it is defined as:\n",
        "\n",
        "$$\\sigma = \\lim_{R \\to \\infty} 4\\pi R^2 \\frac{|\\mathbf{E}_{\\text{scattered}}|^2}{|\\mathbf{E}_{\\text{incident}}|^2} $$\n",
        "\n",
        "where: - \\$ R \\$ : Distance between the radar and target. - \\$ *{} \\$ :\n",
        "Electric field of the scattered wave. - \\$* {} \\$ : Electric field of\n",
        "the incident wave.\n",
        "\n",
        "In this notebook, we aim to benchmark the accuracy of Tidy3D by\n",
        "simulating the monostatic RCS of a PEC sphere and compare the results to\n",
        "the well-known analytical solution based on Mie theory."
      ],
      "id": "48673cd9-71bb-469d-96ec-70be7fed4f0e"
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import tidy3d as td\n",
        "import tidy3d.web as web"
      ],
      "id": "ff84edbb"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Simulation Setup\n",
        "\n",
        "The monostatic RCS calculation for a PEC sphere is a classic problem in\n",
        "electromagnetics. The RCS is usually normalized by the physical cross\n",
        "section area of the sphere $\\pi r^2$, where $r$ is the radius. Our goal\n",
        "is to calculate the normalized RCS as a function of the unitless\n",
        "relative frequency $2 \\pi r/\\lambda_0$.\n",
        "\n",
        "In this particular case, we will calculate the RCS for a relative\n",
        "frequency range from 1 to 10. The result will be plotted in a log scale\n",
        "so the frequency points are generated in a log scale here."
      ],
      "id": "299f08ec-9742-4cd2-9d9a-7e5397630c6f"
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [],
      "source": [
        "r = 1  # radius of the sphere\n",
        "rel_freqs = np.logspace(0, 1, 201)  # relative frequency in log scale\n",
        "ldas = 2 * np.pi * r / rel_freqs  # wavelength range\n",
        "freqs = td.C_0 / ldas  # frequency range\n",
        "\n",
        "freq0 = (freqs[-1] + freqs[0]) / 2  # central frequency for the source\n",
        "fwidth = (freqs[-1] - freqs[0]) / 2  # frequency width for the source"
      ],
      "id": "d1058fcb"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create the PEC sphere."
      ],
      "id": "b8b3fcf6-70e9-4871-804c-aa05ed821b08"
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [],
      "source": [
        "sphere = td.Structure(geometry=td.Sphere(radius=r), medium=td.PECMedium())"
      ],
      "id": "ac2a92c9"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Next, we define a\n",
        "[TFSF](https://www.flexcompute.com/tidy3d/examples/notebooks/TFSF/)\n",
        "source as the excitation. For RCS calculation, the\n",
        "[TFSF](https://www.flexcompute.com/tidy3d/examples/notebooks/TFSF/)\n",
        "source is the most suitable since it injects a plane wave with unit\n",
        "power density, which makes the normalization of the RCS calculation\n",
        "automatic. The source needs to enclose the sphere. The incident angle\n",
        "and direction do not matter due to the symmetry of the sphere but we\n",
        "have it injected in the $z$ axis in this case."
      ],
      "id": "d754ab06-9fa8-43e9-82a6-3736b9ec9e2c"
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [],
      "source": [
        "source_size = 3 * r\n",
        "\n",
        "source = td.TFSF(\n",
        "    size=[source_size] * 3,\n",
        "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
        "    injection_axis=2,\n",
        "    direction=\"-\",\n",
        ")"
      ],
      "id": "77d2fe95"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The RCS calculation is automatically done in a\n",
        "[FieldProjectionAngleMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldProjectionAngleMonitor.html).\n",
        "The monitor needs to enclose both the source and the sphere. Since we\n",
        "are only interested in the monostatic RCS, we only need to project to\n",
        "one particular angle, namely the opposite direction of the incident\n",
        "direction."
      ],
      "id": "8038ec89-000a-42b5-b67d-4afa671f7668"
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [],
      "source": [
        "monitor_size = 4 * r\n",
        "\n",
        "monitor = td.FieldProjectionAngleMonitor(\n",
        "    size=[monitor_size] * 3,\n",
        "    freqs=freqs,\n",
        "    name=\"far_field\",\n",
        "    phi=[0],\n",
        "    theta=[0],\n",
        ")"
      ],
      "id": "c5afd5d4"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Put everything into a\n",
        "[Simulation](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html)\n",
        "instance. Here we use a uniform grid of size $r$/100 to sufficiently\n",
        "resolve the curved surface of the sphere. By default, we apply a\n",
        "subpixel averaging method known as the conformal mesh scheme to PEC\n",
        "boundaries.\n",
        "\n",
        "The automatic shutoff level by default is at `1e-5`. Here to further\n",
        "push the accuracy, we lower it to `1e-8`."
      ],
      "id": "cb1c014f-d0b6-478b-aef3-4642b4fe5a25"
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">06:00:14 UTC </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: RF simulations and functionality will require new license </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">requirements in an upcoming release. All RF-specific classes are   </span>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">now available within the sub-package </span><span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d.rf'</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\"> - Contains sources defined for RF wavelengths.                    </span>\n",
              "</pre>"
            ]
          }
        }
      ],
      "source": [
        "run_time = 1e-13\n",
        "sim_size = 6 * r\n",
        "\n",
        "sim = td.Simulation(\n",
        "    size=[sim_size] * 3,\n",
        "    grid_spec=td.GridSpec.uniform(dl=r / 100),\n",
        "    structures=[sphere],\n",
        "    sources=[source],\n",
        "    monitors=[monitor],\n",
        "    run_time=run_time,\n",
        "    shutoff=1e-8,\n",
        ")"
      ],
      "id": "b59753d2"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Visualize the simulation to ensure the setup is correct."
      ],
      "id": "e6d09191-c38f-4eda-b513-7f106ddc7915"
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
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0er1eOZ3OpPkWCAAAAEBs+Hy+pBnRWSL4IgHaC71NnE5m1QIAAABS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bpV99xzj3VCruOOO06XXHJJ1GoAAAAAQKLiVIwhzJ8/X5dffnnQaU8//bSefvpp677L5VJlZWVE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\nLwAAAACgW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3WurKzUnDlztG/fvlZfLSYakuY7vuEYN26cPv/8c61cuVIrV64M2qZ37966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\nmjx5siTpwIED+uKLL/T8889r3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          }
        }
      ],
      "source": [
        "sim.plot(y=0)\n",
        "plt.show()"
      ],
      "id": "a9d57bda"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Submit the Simulation to the Server\n",
        "\n",
        "Once we confirm that the simulation is set up properly, we can run it."
      ],
      "id": "1a1953d6-cce1-4336-8478-4ace4375ad06"
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">06:00:15 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'pec_sphere_rcs'</span> with resource_id                     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-01496b75-2d35-4d6e-8516-aedfe86ee71d'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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-01496b75-2d35-4d6e-8516-aedfe86ee71d\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-01496b75-2d3</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-01496b75-2d35-4d6e-8516-aedfe86ee71d\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">5-4d6e-8516-aedfe86ee71d'</span></a>.                                         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"4617744680724725992d38ccb28756d0\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">06:00:16 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.596</span>. This assumes the FDTD solver runs\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>for the full simulation time; if early shutoff is reached, the     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed cost can be lower. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed FlexCredit cost after a simulation run.                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">06:00:17 UTC </span>status = queued                                                    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"083b0a26103146ffb8ce0cc225f25f13\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
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          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">06:00:27 UTC </span>status = preprocess                                                \n",
              "</pre>"
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          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
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        {
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          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">06:00:32 UTC </span>starting up solver                                                 \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>running solver                                                     \n",
              "</pre>"
            ]
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        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"df54bc55d8bd44f28c004ed97a7a5c12\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
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        {
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          "metadata": {},
          "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\">06:01:47 UTC </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">64</span>%, exiting.                            \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>"
            ]
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        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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 = postprocess                                               \n",
              "</pre>"
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        {
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          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"d57bcaffd0c54561b20cc44758671f88\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
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        {
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          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">06:01:50 UTC </span>status = success                                                   \n",
              "</pre>"
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        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>"
            ]
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        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">06:01:52 UTC </span>View simulation result at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-01496b75-2d35-4d6e-8516-aedfe86ee71d\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-01496b75-2d3</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-01496b75-2d35-4d6e-8516-aedfe86ee71d\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">5-4d6e-8516-aedfe86ee71d'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"7ff27242fb9a45ec99e4989212e0a614\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">06:01:53 UTC </span>Loading results from simulation_data.hdf5                          \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>"
            ]
          }
        }
      ],
      "source": [
        "sim_data = web.run(simulation=sim, task_name=\"pec_sphere_rcs\")"
      ],
      "id": "2d782a9d"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Postprocessing and Visualization\n",
        "\n",
        "Once the simulation is complete, we can calculate the RCS directly from\n",
        "the monitor data and normalize it to the physical cross section of the\n",
        "sphere."
      ],
      "id": "4d35b070-4ba6-4e61-9172-7b61c348e2a0"
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [],
      "source": [
        "rcs_tidy3d = sim_data[\"far_field\"].radar_cross_section.real.squeeze(drop=True).values / (\n",
        "    np.pi * r**2\n",
        ")"
      ],
      "id": "3be8265f"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The normalized monostatic RCS (σ/πr²) of a PEC sphere is calculated\n",
        "using the Mie series solution:\n",
        "\n",
        "$$\\frac{\\sigma}{\\pi r^2} = \\frac{4}{x^2} \\left| \\sum_{n=1}^\\infty (-1)^n (n + 0.5) \\left(a_n - b_n \\right) \\right|^2 ,$$\n",
        "\n",
        "where:\n",
        "\n",
        "- Relative frequency:  \n",
        "  $$ x = \\frac{2\\pi r}{\\lambda} \\quad \\text{(unitless)} $$\n",
        "\n",
        "- Mie coefficients:\n",
        "  $$ a_n = -\\frac{\\left[x j_n(x)\\right]'}{\\left[x h_n^{(1)}(x)\\right]'} $$  \n",
        "  $$ b_n = -\\frac{j_n(x)}{h_n^{(1)}(x)} $$\n",
        "\n",
        "- Spherical Bessel function: $$ j_n(x) $$\n",
        "\n",
        "- Spherical Hankel function (1st kind):  \n",
        "  $$ h_n^{(1)}(x) = j_n(x) + i y_n(x) $$\n",
        "\n",
        "We calculate the RCS according to the formula above and compare it to\n",
        "the simulated RCS from Tidy3D."
      ],
      "id": "2fa08ca1-3a17-4782-94a9-eaaea1f4bb1b"
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [],
      "source": [
        "from scipy.special import spherical_jn, spherical_yn\n",
        "\n",
        "\n",
        "def normalized_rcs(rel_freq):\n",
        "    \"\"\"\n",
        "    Calculate the monostatic RCS of a PEC sphere normalized by πr².\n",
        "\n",
        "    Parameters:\n",
        "    relative_frequency (float): The relative frequency (2πr/λ), unitless.\n",
        "\n",
        "    Returns:\n",
        "    float: Normalized RCS (σ / πr²), unitless.\n",
        "    \"\"\"\n",
        "\n",
        "    if rel_freq <= 0:\n",
        "        return 0.0\n",
        "\n",
        "    # determine the maximum number of terms in the series\n",
        "    N_max = int(np.floor(rel_freq + 4 * rel_freq ** (1 / 3) + 2))\n",
        "    total_sum = 0.0j\n",
        "\n",
        "    for n in range(1, N_max + 1):\n",
        "        # compute spherical Bessel (jn) and Neumann (yn) functions\n",
        "        jn = spherical_jn(n, rel_freq)  # j_n(x)\n",
        "        jn_deriv = spherical_jn(n, rel_freq, True)  # j_n'(x)\n",
        "\n",
        "        yn = spherical_yn(n, rel_freq)  # y_n(x)\n",
        "        yn_deriv = spherical_yn(n, rel_freq, True)  # y_n'(x)\n",
        "\n",
        "        # spherical Hankel function of the first kind (hn1)\n",
        "        hn1 = jn + 1j * yn  # h_n^(1)(x)\n",
        "        hn1_deriv = jn_deriv + 1j * yn_deriv  # [h_n^(1)]'(x)\n",
        "\n",
        "        # calculate (x * jn)' and (x * hn1)'\n",
        "        x_jn_deriv = jn + rel_freq * jn_deriv\n",
        "        x_hn1_deriv = hn1 + rel_freq * hn1_deriv\n",
        "\n",
        "        # Mie coefficients for PEC sphere\n",
        "        a_n = -x_jn_deriv / x_hn1_deriv\n",
        "        b_n = -jn / hn1\n",
        "\n",
        "        # series term\n",
        "        term = ((-1) ** n) * (n + 0.5) * (a_n - b_n)\n",
        "        total_sum += term\n",
        "\n",
        "    # compute the normalized RCS\n",
        "    if rel_freq == 0:\n",
        "        return 0.0\n",
        "    rcs_normalized = (4.0 / rel_freq**2) * (np.abs(total_sum) ** 2)\n",
        "    return rcs_normalized.real\n",
        "\n",
        "\n",
        "rcs_analytic = [normalized_rcs(rel_freq) for rel_freq in rel_freqs]"
      ],
      "id": "38598e23"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Plot the simulated and calculated RCS together. The results overlap very\n",
        "well, indicating the good accuracy of the Tidy3D solver."
      ],
      "id": "550d3b51-a278-4171-9b5b-f1dcd496df0d"
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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iJJyI5J8+fbD99htGm7Z2u1vwN+vpzBVsydPDxMRAdHSeQoiIiIiIiIi4lZJw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wcqQeZ5JNIMctkzyOU5scToTcPoT5oggHTo7biBHOe21z91bUlMGNuoQrR/Dv/KRJ4SvV9Xde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\nUQa2ogIAAAAFHiEcAKBACg11fZ6mIO1QY1O/rEK4zON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          }
        }
      ],
      "source": [
        "plt.plot(rel_freqs, rcs_tidy3d, \"red\", linewidth=2, label=\"Tidy3D\")\n",
        "plt.scatter(rel_freqs, rcs_analytic, c=\"blue\", label=\"Analytic\")\n",
        "plt.xlabel(r\"Relative frequency (2$\\pi r$/$\\lambda_0$)\")\n",
        "plt.ylabel(r\"Monostatic RCS (2$\\pi r^2$)\")\n",
        "plt.xscale(\"log\")\n",
        "plt.yscale(\"log\")\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "id": "055c8dd6"
    }
  ],
  "nbformat": 4,
  "nbformat_minor": 5,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    }
  }
}