CircularlyPolarizedPatchAntenna.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# Circularly polarized patch antenna with parasitic strips\n",
    "\n",
    "In many applications, such as mobile communications, size, weight, and cost are the primary constraints that drive the design of antennas. In particular, cell phone antennas are required to be economical, low-profile, and easy to manufacture. Patch antennas are attractive devices for these applications, since they can be manufactured directly on printed-circuit boards, which makes their inclusion in cell phones especially convenient. In addition, the shape of a patch antenna can be chosen to imbue it with a variety of different characteristics, e.g., polarization, radiation pattern, and bandwidth.\n",
    "\n",
    "<img src=\"img/circularly_polarized_patch_antenna.png\" width=\"400\" alt=\"Rendering of a circularly polarized patch antenna\">\n",
    "\n",
    "This notebook reproduces the results from [Wu et al.](https://ieeexplore.ieee.org/document/6963272). In [1], the authors propose a circularly polarized antenna with parasitic strips that has a lower profile and an improved circularly polarized bandwidth when compared to existing designs. This notebook also serves to introduce many key components of Tidy3D that are used in antenna simulations: \n",
    "\n",
    "* [DirectivityMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.DirectivityMonitor.html): The directivity monitor records and stores electromagnetic field data, which it uses to calculate far-field quantities such as radiation intensity and directivity.\n",
    "* [CoaxialLumpedPort](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.smatrix.CoaxialLumpedPort.html): These ports are used to model a coaxial-type excitation, which includes a current source and load impedance.\n",
    "* [TerminalComponentModeler](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.smatrix.TerminalComponentModeler.html): This tool, in the `smatrix` plugin, enables the calculation of scattering parameters and also the incident and reflected powers at each port, which is needed for calculating the antenna gain. The `TerminalComponentModeler` may be used to calculate many parameters of interest in antenna design. These antenna parameters are returned as a [AntennaMetricsData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.AntennaMetricsData.html), which is calculated in a post-processing step after all simulations are completed.\n",
    "* [LobeMeasurer](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.microwave.LobeMeasurer.html): This helper class finds the lobes in a radiation pattern and calculates lobe measures, such as the half power beamwidth.\n",
    "  \n",
    "Since this notebook uses many features, you may find the following notebooks helpful for understanding each feature separately.\n",
    "\n",
    "* [Directivity and S-parameter Computation of Patch Antenna Notebook](https://www.flexcompute.com/tidy3d/examples/notebooks/AntennaCharacteristics/)\n",
    "* [Layer Refinement Notebook](https://www.flexcompute.com/tidy3d/examples/notebooks/LayerRefinement/)\n",
    "* [Coupled Line Bandpass Filter Notebook](https://www.flexcompute.com/tidy3d/examples/notebooks/CoupledLineBandpassFilter/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-30T16:12:46.772112Z",
     "start_time": "2025-01-30T16:12:44.481262Z"
    }
   },
   "outputs": [],
   "source": [
    "# standard python imports\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# tidy3d imports\n",
    "import tidy3d as td\n",
    "\n",
    "# Import a few plugins which contain some of the tools we will use in this tutorial\n",
    "import tidy3d.plugins.smatrix as smatrix\n",
    "from tidy3d.plugins.dispersion import FastDispersionFitter\n",
    "from tidy3d.plugins.microwave import LobeMeasurer\n",
    "\n",
    "td.config.logging_level = \"ERROR\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation Parameter Setup\n",
    "\n",
    "We begin by setting the frequency range of interest (2.2 GHz to 3 GHz), which will be used to set up the source and monitors in the simulation. Next, we define geometric parameters from [1] that describe the shape and placement of the various components used in the antenna design. To compute $S_{11}$ of the antenna, we will use the [TerminalComponentModeler](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.smatrix.TerminalComponentModeler.html#tidy3d.plugins.smatrix.TerminalComponentModeler), which requires setting up a port excitation. The antenna in [1] is backed by a ground plane and excited by a feeding pin. In order to emulate a 50 $\\Omega$ coaxial cable connected to the feeding pin, we introduce a 1.5 mm radius hole in the ground plane where we will place a `CoaxialLumpedPort`.\n",
    "\n",
    "\n",
    "We model all conductors from [1] as perfect electric conductors (PECs). In [1], the substrate is modeled with a relative permittivity of 2.55 and frequency-independent loss tangent of 0.002. To ensure causality, in Tidy3D the loss tangent must be modeled using a dispersive material with pole-residue pairs. Fortunately, we can use the [constant_loss_tangent_model](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.dispersion.FastDispersionFitter.html#tidy3d.plugins.dispersion.FastDispersionFitter.constant_loss_tangent_model) to easily generate such a model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "start_time": "2025-01-30T16:12:50.238269Z"
    },
    "jupyter": {
     "is_executing": true
    }
   },
   "outputs": [
    {
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       "model_id": "5a575e86b1054dde99fbbf009c618408",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
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   ],
   "source": [
    "# Frequency range of interest is 2.2 to 3 GHz\n",
    "freq_start = 2.2e9\n",
    "freq_stop = 3e9\n",
    "# Center frequency of 2.6 GHz\n",
    "freq0 = (freq_start + freq_stop) / 2\n",
    "fwidth = freq_stop - freq_start\n",
    "# Frequency sample points for monitors and post-processing\n",
    "freqs = np.linspace(freq_start, freq_stop, 51)\n",
    "# Center wavelength\n",
    "wavelength0 = td.C_0 / freq0\n",
    "# Longest wavelength\n",
    "wavelength_start = td.C_0 / freq_start\n",
    "# Run time of FDTD simulation\n",
    "run_time = 10 / fwidth\n",
    "# Tidy3D uses microns by default\n",
    "mm = 1e3\n",
    "\n",
    "# Parameters from [1]\n",
    "G = 130 * mm  # Length and width of ground sheet\n",
    "L = 73 * mm  # Length and width of substrate\n",
    "L1 = 39 * mm  # Length and width of center patch\n",
    "a = 21 * mm  # Width of corner cutout of center patch\n",
    "fx = 15 * mm  # X position of feed pin\n",
    "gx = 2 * mm  # Horizontal gap distance between center patch and parasitic patches\n",
    "gy = 8 * mm  # Vertical gap distance between substrate boundary and parasitic patches\n",
    "Ls = 36 * mm  # Length of parasitic patches\n",
    "Ws = 15 * mm  # Width of parasitic patches\n",
    "r1 = 2 * mm  # Ground pin pad size\n",
    "r2 = 1.7 * mm  # Feed pin pad size\n",
    "t = 1 * mm  # Substrate thickness\n",
    "H = 14 * mm  # Distance between ground and substrate\n",
    "rfeed = 0.65 * mm\n",
    "\n",
    "# Custom parameters chosen for this simulation, not specified in [1]\n",
    "# Chosen thickness of metal conductors other than the ground sheet (20 microns)\n",
    "patch_thickness = 0.02 * mm\n",
    "ground_thickness = 0.16 * mm\n",
    "# Using an outer radius of 1.5 mm gives about 50 Ohms\n",
    "# for the impedance of air filled coax that connects to the feeding pin.\n",
    "coax_radius = 1.5 * mm\n",
    "\n",
    "# Total structure height\n",
    "structure_height = t + H + ground_thickness + patch_thickness\n",
    "structure_center = 0.5 * (t + patch_thickness - H - ground_thickness)\n",
    "\n",
    "# Define key vertical locations within the simulation domain.\n",
    "top_substrate = t\n",
    "bottom_substrate = 0\n",
    "middle_ground = -H - ground_thickness / 2\n",
    "port_location = -H - ground_thickness  # Port is located at the bottom of the ground.\n",
    "# Calculate the diameter of the coaxial port based on the radius.\n",
    "port_diameter = 2 * coax_radius\n",
    "\n",
    "# PML buffer size added around structures\n",
    "PML_buffer = wavelength_start / 2\n",
    "# Simulation domain definition with sufficient padding around the structure for PMLs\n",
    "sim_size = (G + 2 * PML_buffer, G + 2 * PML_buffer, structure_height + 2 * PML_buffer)\n",
    "sim_center = [0, 0, structure_center]\n",
    "\n",
    "# Define media in the simulation\n",
    "epsr_sub = 2.55\n",
    "air = td.Medium()\n",
    "metal = td.PECMedium()\n",
    "# Use FastDispersionFitter to create a material with an approximately correct loss tangent for the frequency range.\n",
    "substrate_med = FastDispersionFitter.constant_loss_tangent_model(\n",
    "    epsr_sub, 0.002, (freq_start, freq_stop)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Structures\n",
    "\n",
    "Next, we use the defined parameters to create all of the structures in the Tidy3D simulation and plot the created structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def make_structures(differential_feed: bool = False):\n",
    "    \"\"\"Makes all of the Tidy3D structures that represent the antenna in [1]. As in [1], we can choose to model the antenna\n",
    "    with a differential feed, where a second feeding pin is added to the structure.\n",
    "    \"\"\"\n",
    "    # Make structures for the simulation for either the proposed or differential feeds in [1].\n",
    "    # Dielectric substrate that extends from the shorting and feeding pins to the patches\n",
    "    substrate = td.Structure(\n",
    "        geometry=td.Box(\n",
    "            center=[0, 0, t / 2],\n",
    "            size=[L, L, t],\n",
    "        ),\n",
    "        medium=substrate_med,\n",
    "    )\n",
    "    # A ground plane is connected to the bottom of the pins, where a small air gap is introduced for exciting the\n",
    "    # feeding pin\n",
    "    ground_box = td.Box(center=[0, 0, -H - ground_thickness / 2], size=[G, G, ground_thickness])\n",
    "    # A cylindrical hole is created in the ground plane to allow for the coaxial cable connection at the feeding pin.\n",
    "    feed_gap = td.Cylinder(\n",
    "        center=(fx, 0, -H - ground_thickness / 2),\n",
    "        radius=coax_radius,\n",
    "        length=ground_thickness,\n",
    "        axis=2,\n",
    "    )\n",
    "\n",
    "    if differential_feed:\n",
    "        left_feed_gap = td.Cylinder(\n",
    "            center=(-fx, 0, -H - ground_thickness / 2),\n",
    "            radius=coax_radius,\n",
    "            length=ground_thickness,\n",
    "            axis=2,\n",
    "        )\n",
    "        feed_gap = td.GeometryGroup(geometries=(feed_gap, left_feed_gap))\n",
    "\n",
    "    # The air gap is removed from the ground box\n",
    "    ground_with_holes = td.ClipOperation(\n",
    "        operation=\"difference\", geometry_a=ground_box, geometry_b=feed_gap\n",
    "    )\n",
    "    # The final ground plane structure is created\n",
    "    ground = td.Structure(\n",
    "        geometry=ground_with_holes,\n",
    "        medium=metal,\n",
    "    )\n",
    "    # Define the vertices that outline the shape of the central patch.\n",
    "    main_vertices = np.array(\n",
    "        [\n",
    "            (-L1 / 2, -L1 / 2),\n",
    "            (L1 / 2 - a, -L1 / 2),\n",
    "            (L1 / 2, -L1 / 2 + a),\n",
    "            (L1 / 2, L1 / 2),\n",
    "            (-L1 / 2 + a, L1 / 2),\n",
    "            (-L1 / 2, L1 / 2 - a),\n",
    "        ]\n",
    "    )\n",
    "    # Using the vertices, a polyslab structure is created with the previously defined patch_thickness.\n",
    "    main_patch = td.Structure(\n",
    "        geometry=td.PolySlab(\n",
    "            vertices=main_vertices.tolist(),\n",
    "            slab_bounds=(t, t + patch_thickness),\n",
    "            axis=2,\n",
    "        ),\n",
    "        medium=metal,\n",
    "    )\n",
    "    # The remaining parasitic strips are sequentially-rotated rectangles around the central patch.\n",
    "    patch_L = td.Box(\n",
    "        center=(-L / 2 + Ws / 2, -L / 2 + gy + Ls / 2, t + patch_thickness / 2),\n",
    "        size=(Ws, Ls, patch_thickness),\n",
    "    )\n",
    "    patch_R = td.Box(\n",
    "        center=(L / 2 - Ws / 2, L / 2 - gy - Ls / 2, t + patch_thickness / 2),\n",
    "        size=(Ws, Ls, patch_thickness),\n",
    "    )\n",
    "    patch_B = td.Box(\n",
    "        center=(L / 2 - Ls / 2 - gy, -L / 2 + Ws / 2, t + patch_thickness / 2),\n",
    "        size=(Ls, Ws, patch_thickness),\n",
    "    )\n",
    "    patch_T = td.Box(\n",
    "        center=(-L / 2 + Ls / 2 + gy, L / 2 - Ws / 2, t + patch_thickness / 2),\n",
    "        size=(Ls, Ws, patch_thickness),\n",
    "    )\n",
    "    # Conductive pads for the feeding and shorting pins, placed at the bottom of the substrate.\n",
    "    feed_disc = td.Cylinder(\n",
    "        center=(fx, 0, -patch_thickness / 2), radius=r2, length=patch_thickness, axis=2\n",
    "    )\n",
    "    if differential_feed:\n",
    "        shorted_disc = td.Cylinder(\n",
    "            center=(-fx, 0, -patch_thickness / 2), radius=r2, length=patch_thickness, axis=2\n",
    "        )\n",
    "    else:\n",
    "        shorted_disc = td.Cylinder(\n",
    "            center=(0, 0, -patch_thickness / 2), radius=r1, length=patch_thickness, axis=2\n",
    "        )\n",
    "    # All patch structures are collected into a list and assigned the same material\n",
    "    patch_geoms = [patch_L, patch_R, patch_B, patch_T, feed_disc, shorted_disc]\n",
    "    patch_structures = [td.Structure(geometry=patch, medium=metal) for patch in patch_geoms]\n",
    "\n",
    "    # Next, the shorting and feeding pins are added to the simulation as cylinders.\n",
    "    if differential_feed:\n",
    "        # Short pin represents the other feed when using the differential feed configuration.\n",
    "        short_pin = td.Structure(\n",
    "            geometry=td.Cylinder(\n",
    "                center=(-fx, 0, -H / 2 - ground_thickness / 2),\n",
    "                radius=rfeed,\n",
    "                length=H + ground_thickness,\n",
    "                axis=2,\n",
    "            ),\n",
    "            medium=metal,\n",
    "        )\n",
    "    else:\n",
    "        short_pin = td.Structure(\n",
    "            geometry=td.Cylinder(\n",
    "                center=(0, 0, -H / 2 - ground_thickness / 2),\n",
    "                radius=rfeed,\n",
    "                length=H + ground_thickness,\n",
    "                axis=2,\n",
    "            ),\n",
    "            medium=metal,\n",
    "        )\n",
    "    feed_pin = td.Structure(\n",
    "        geometry=td.Cylinder(\n",
    "            center=(fx, 0, -H / 2 - ground_thickness / 2),\n",
    "            radius=rfeed,\n",
    "            length=H + ground_thickness,\n",
    "            axis=2,\n",
    "        ),\n",
    "        medium=metal,\n",
    "    )\n",
    "    # Create a list of all structures in the simulation.\n",
    "    return [\n",
    "        substrate,\n",
    "        ground,\n",
    "        feed_pin,\n",
    "        short_pin,\n",
    "        main_patch,\n",
    "    ] + patch_structures\n",
    "\n",
    "\n",
    "structures_list = make_structures(differential_feed=False)\n",
    "# Setting up the scene for visualization, with all structures included\n",
    "# and units set to millimeters for the plot.\n",
    "scene = td.Scene(structures=structures_list, plot_length_units=\"mm\")\n",
    "fig, axs = plt.subplots(1, 2, figsize=(10, 5), tight_layout=True)\n",
    "sub_ax = axs[0]\n",
    "scene.plot(z=t, ax=sub_ax)\n",
    "sub_ax.set_xlim(-L / 2, L / 2)\n",
    "sub_ax.set_ylim(-L / 2, L / 2)\n",
    "sub_ax = axs[1]\n",
    "scene.plot(y=0, ax=sub_ax)\n",
    "sub_ax.set_xlim(-L / 3, L / 3)\n",
    "sub_ax.set_ylim(-H - t, 2 * t)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mesh Overrides and Layer Refinement Specification\n",
    "\n",
    "In this antenna design, there are many subwavelength features that may not be captured accurately using the default grid generated by Tidy3D, even when using the [PECConformal](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PECConformal.html#tidy3d.PECConformal) subpixel feature. For instance, both the metal patch thickness and the gap between the central patch and parasitic strips are subwavelength. In addition, the radius of the shorting pin and feeding pin are also relatively small. To enhance the accuracy of this simulation, we will use two components: [MeshOverrideStructures](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.MeshOverrideStructure.html#tidy3d.MeshOverrideStructure) and [LayerRefinementSpec](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.LayerRefinementSpec.html).\n",
    "\n",
    "The `MeshOverrideStructure`s are used to refine the grid near the locations of the shorting and feeding pins. We use `MeshOverrideStructure`s to ensure that there will be about four grid cells in the gap between the feeding pin and ground plane, where the excitation will be placed. Finally, another similar `MeshOverrideStructure` is added near the shorting pin to resolve the cylinder's surface accurately.\n",
    "\n",
    "We also make use of the `LayerRefinementSpec` feature, which automatically creates refined mesh in each layer defined by the user. We choose to refine the mesh around metallic objects on the top and bottom of the substrate. In addition, we add a `LayerRefinementSpec` corresponding to the ground plane."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_grid_spec(use_differential_feed: bool = False):\n",
    "    # Make a GridSpec for the simulation for either the proposed or differential feeds in [1].\n",
    "    # Set the size of grid cells to be used for the portion of the structure containing all patches.\n",
    "    # Choose the cell size in the xy-plane to ensure there are 4 cells across the gap between the main patch and parasitic strips.\n",
    "    dl_plane = gx / 4\n",
    "    # Vertical cell size around printed components\n",
    "    dz_metal = 100\n",
    "\n",
    "    # Provide a larger cell size (dl value) for regions or dimensions that do not require fine resolution.\n",
    "    dl_background = 10 * mm\n",
    "    # Set the cell size at the port to fit approximately `port_cells` between the feed pin and ground\n",
    "    port_cells = 4\n",
    "    dl_pins = (coax_radius - rfeed) / port_cells\n",
    "    # Add MeshOverrideStructures around both pins, which will capture the curved geometry of the cylinders more accurately.\n",
    "    # These MeshOverrideStructures also improve the accuracy of the fields in the air gap, where the port excitation will be placed.\n",
    "    short_x_center = 0\n",
    "    if use_differential_feed:\n",
    "        short_x_center = -fx\n",
    "    mesh_overrides = [\n",
    "        td.MeshOverrideStructure(\n",
    "            geometry=td.Box(\n",
    "                center=[fx, 0, middle_ground],\n",
    "                size=[port_diameter, port_diameter, ground_thickness],\n",
    "            ),\n",
    "            dl=[dl_pins, dl_pins, dl_background],\n",
    "        ),\n",
    "        td.MeshOverrideStructure(\n",
    "            geometry=td.Box(\n",
    "                center=[short_x_center, 0, middle_ground],\n",
    "                size=[port_diameter, port_diameter, ground_thickness],\n",
    "            ),\n",
    "            dl=[dl_pins, dl_pins, dl_background],\n",
    "        ),\n",
    "    ]\n",
    "\n",
    "    top_substrate_spec = td.LayerRefinementSpec.from_layer_bounds(\n",
    "        bounds=(top_substrate, top_substrate + patch_thickness),\n",
    "        axis=2,\n",
    "        bounds_snapping=\"lower\",\n",
    "        bounds_refinement=td.GridRefinement(dl=dz_metal),\n",
    "        corner_refinement=td.GridRefinement(dl=dl_plane / 2),\n",
    "    )\n",
    "    bottom_substrate_spec = td.LayerRefinementSpec.from_layer_bounds(\n",
    "        bounds=(bottom_substrate - patch_thickness, bottom_substrate),\n",
    "        axis=2,\n",
    "        bounds_snapping=\"upper\",\n",
    "        bounds_refinement=td.GridRefinement(dl=dz_metal),\n",
    "    )\n",
    "    ground_spec = td.LayerRefinementSpec.from_layer_bounds(\n",
    "        min_steps_along_axis=1,\n",
    "        bounds=(-H - ground_thickness, -H),\n",
    "        axis=2,\n",
    "        bounds_snapping=\"bounds\",\n",
    "    )\n",
    "    return td.GridSpec.auto(\n",
    "        min_steps_per_wvl=20,\n",
    "        wavelength=td.C_0 / freq_stop,\n",
    "        layer_refinement_specs=[top_substrate_spec, bottom_substrate_spec, ground_spec],\n",
    "        override_structures=mesh_overrides,\n",
    "    )\n",
    "\n",
    "\n",
    "grid_spec = make_grid_spec(use_differential_feed=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we plot the created geometry along with the FDTD grid to see how the `MeshOverrideStructure`s and `LayerRefinementSpec`s have affected the grid. In the first figure, you can clearly see the mesh refinement created by the `MeshOverrideStructure`s around the shorting and feeding pins. The figure on the right shows a close-up of the gap region between the central patch and a parasitic strip. The purple markers indicate the locations of corners where the mesh grid has been snapped and refined. The subsequent plot illustrates the refined grid near the port location, clearly showing the desired four grid cells between the inner and outer conductors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Nx': 274, 'Ny': 255, 'Nz': 103, 'grid_points': 7196610, 'min_grid_size': 75.0, 'max_grid_size': 4996.540966666886, 'computational_complexity': 95954.8}\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create simulation object, so that we can view the created grid superimposed with simulation structures.\n",
    "sim = td.Simulation(\n",
    "    center=sim_center,\n",
    "    size=sim_size,\n",
    "    grid_spec=grid_spec,\n",
    "    structures=structures_list,\n",
    "    run_time=run_time,\n",
    "    plot_length_units=\"mm\",\n",
    ")\n",
    "\n",
    "# Display information about the simulation grid, including the number of cells along each axis and the smallest cell size,\n",
    "# which are important for simulation accuracy.\n",
    "print(sim.grid_info)\n",
    "\n",
    "# Create two plots: one showing the overall grid and simulation setup, and another zoomed in near the gap and feed pin location.\n",
    "fig, axs = plt.subplots(1, 2, figsize=(10, 10), tight_layout=True)\n",
    "sub_ax = axs[0]\n",
    "sim.plot(z=t, ax=sub_ax, monitor_alpha=0)\n",
    "sim.plot_grid(z=t, ax=sub_ax)\n",
    "sub_ax.set_xlim(-L / 2, L / 2)\n",
    "sub_ax.set_ylim(-L / 2, L / 2)\n",
    "sub_ax = axs[1]\n",
    "sim.plot(z=t, ax=sub_ax, monitor_alpha=0)\n",
    "sim.plot_grid(z=t, ax=sub_ax)\n",
    "sub_ax.set_xlim(L1 / 2 - 4 * gx, L1 / 2 + 4 * gx)\n",
    "sub_ax.set_ylim(L / 2 - gy - Ls - 2 * gx, L / 2 - gy - Ls + 6 * gx)\n",
    "plt.show()\n",
    "\n",
    "# Create a detailed plot at the port location to verify the mesh refinement in this critical region.\n",
    "fig, ax = plt.subplots(figsize=(5, 5), tight_layout=True)\n",
    "sim.plot(z=port_location, ax=ax)\n",
    "sim.plot_grid(z=port_location, ax=ax)\n",
    "ax.set_xlim(fx - 5 * mm, fx + 5 * mm)\n",
    "ax.set_ylim(-5 * mm, 5 * mm)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation Monitors\n",
    "\n",
    "In this notebook, we wish to compute a variety of antenna parameters. We will first create plots of the normalized radiation pattern at 2.6 GHz for right-handed and left-handed circular polarizations. We will also reproduce a few plots from [1] that are functions of frequency, i.e., the axial ratio and the antenna gain along the *z* axis. In order to create these plots efficiently, we use one `DirectivityMonitor` that records the far-field pattern over a range of directions at a fixed frequency. We use a separate `DirectivityMonitor` to capture the field over a range of frequencies at a specific observation point, denoted by spherical coordinates $(\\theta=0, \\phi=0)$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Place the far field monitors just inside simulation boundaries\n",
    "farfield_size = (sim_size[0] * 0.9, sim_size[1] * 0.9, sim_size[2] * 0.9)\n",
    "# Radial distance away from the origin at which to project fields.\n",
    "r_proj = 50 * wavelength0\n",
    "# Theta and Phi angles at which to observe fields\n",
    "theta_proj = np.linspace(0, 2 * np.pi, 200, endpoint=False)\n",
    "phi_proj = np.linspace(0, np.pi / 2, 2)\n",
    "\n",
    "# First, create a FieldProjectionAngleMonitor that will be used to plot the radiation pattern in the xz and yz planes\n",
    "mon_rad_spatial = td.DirectivityMonitor(\n",
    "    center=sim_center,\n",
    "    size=farfield_size,\n",
    "    # the size and center of any far field monitor should indicate where the *near* fields are recorded\n",
    "    freqs=[freq0],\n",
    "    name=\"rad_spatial\",\n",
    "    phi=list(phi_proj),\n",
    "    theta=list(theta_proj),\n",
    "    proj_distance=r_proj,\n",
    "    far_field_approx=True,  # Compute the radiated fields in the far field.\n",
    ")\n",
    "\n",
    "# Next, create a FieldProjectionAngleMonitor that will be used to compute radiated fields normal to the antenna vs the frequency.\n",
    "mon_rad_freqency = td.DirectivityMonitor(\n",
    "    center=sim_center,\n",
    "    size=farfield_size,\n",
    "    freqs=freqs,  # Record radiated fields for different frequencies.\n",
    "    name=\"rad_frequency\",\n",
    "    phi=[0],  # Record radiated fields normal to the antenna\n",
    "    theta=[0],\n",
    "    proj_distance=r_proj,\n",
    "    far_field_approx=True,  # Compute the radiated fields in the far field.\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set up the `TerminalComponentModeler`\n",
    "\n",
    "The last step before launching the simulation is to set up the `TerminalComponentModeler`, which will simplify the calculation of $S_{11}$. As previously mentioned, we use a `CoaxialLumpedPort` with a reference impedance of $50 \\Omega$ as the source. The `CoaxialLumpedPort` will model a radially directed uniform current source and an annular resistive load between the feed pin and ground plane. Scattering parameters calculated with this definition of the `CoaxialLumpedPort` should match experimental results where a coaxial cable is used with characteristic impedance of $50 \\Omega$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use a CoaxialLumpedPort to excite the feed pin. The CoaxialLumpedPort models a radially symmetric current\n",
    "# flowing from the feed pin to the ground plane through a resistive element.\n",
    "coax_center = [fx, 0, port_location]\n",
    "coax_port = smatrix.CoaxialLumpedPort(\n",
    "    center=coax_center,\n",
    "    outer_diameter=port_diameter,\n",
    "    # Defines the boundary for the outer conductor, which in this case is the ground plane.\n",
    "    inner_diameter=2\n",
    "    * rfeed,  # Defines the boundary for the inner conductor, corresponding to the feed pin diameter.\n",
    "    normal_axis=2,\n",
    "    direction=\"+\",  # Indicates that the current will flow in the positive direction along the feed pin.\n",
    "    name=\"coax_port\",\n",
    "    num_grid_cells=None,  # The port grid refinement is handled manually with MeshOverrideStructures, hence 'None'.\n",
    ")\n",
    "modeler = smatrix.TerminalComponentModeler(\n",
    "    simulation=sim,\n",
    "    ports=[coax_port],\n",
    "    radiation_monitors=(mon_rad_spatial, mon_rad_freqency),\n",
    "    freqs=freqs,\n",
    "    remove_dc_component=True,\n",
    "    verbose=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we run the simulation that computes the scattering matrix. After the simulation is complete, we retrieve the `BatchData` and `SimulationData`, which contain the results from the far-field monitors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "98806fdc13ec40e0b5790c0ad45a0068",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:55:17 EST </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> tasks.                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:55:17 EST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\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\">15:55:18 EST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.245</span> for the whole batch.                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:55:18 EST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.245\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 the\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Batch has completed.                                               \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 the\n",
       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "66549e0bc733437592010ca0a0352e2b",
       "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\">15:56:17 EST </span>Batch complete.                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:56:17 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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1e80ca8686234a51aa37c288d0af4fa9",
       "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"
    }
   ],
   "source": [
    "# Run the TerminalComponentModeler and populate the scattering matrix of this single CoaxialLumpedPort network.\n",
    "s_matrix = modeler.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Postprocessing\n",
    "### Polar plots of normalized radiation patterns\n",
    "We will use the simulation results to reproduce Fig. 10 (b) from [1]. First, we retrieve the radiation intensities using the helper method `get_antenna_metrics_data`, which returns a `AntennaMetricsData` object. The radiation intensities are obtained in the circular polarization basis, which is decomposed into right-handed circular polarization (RHCP) and left-handed circular polarization (LHCP) components. Then, we normalize by the peak total radiation intensity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "antenna_parameters_spatial = modeler.get_antenna_metrics_data(monitor_name=\"rad_spatial\")\n",
    "partial_U = antenna_parameters_spatial.partial_radiation_intensity(pol_basis=\"circular\").sel(\n",
    "    f=freq0\n",
    ")\n",
    "peakU = np.max(antenna_parameters_spatial.radiation_intensity)\n",
    "normalized_partial_U = partial_U / peakU\n",
    "\n",
    "# Select fields along theta for phi = 0 and phi = pi/2\n",
    "Urad_RH_Phi_0 = normalized_partial_U.Uright.sel(phi=0).squeeze().values\n",
    "Urad_LH_Phi_0 = normalized_partial_U.Uleft.sel(phi=0).squeeze().values\n",
    "Urad_RH_Phi_90 = normalized_partial_U.Uright.sel(phi=np.pi / 2).squeeze().values\n",
    "Urad_LH_Phi_90 = normalized_partial_U.Uleft.sel(phi=np.pi / 2).squeeze().values\n",
    "\n",
    "# Plot the normalized radiation pattern similar to [1].\n",
    "fig, ax = plt.subplots(1, 2, subplot_kw={\"projection\": \"polar\"}, figsize=(8, 4))\n",
    "sub_ax = ax[0]\n",
    "sub_ax.set_theta_direction(-1)\n",
    "sub_ax.set_theta_offset(np.pi / 2.0)\n",
    "sub_ax.plot(theta_proj, 10 * np.log10(Urad_RH_Phi_0), \"-k\", label=\"RHCP\")\n",
    "sub_ax.plot(theta_proj, 10 * np.log10(Urad_LH_Phi_0), \"-r\", label=\"LHCP\")\n",
    "sub_ax.set_rlim(-40, 0)\n",
    "sub_ax.set_rticks([-40, -30, -20, -10, 0])\n",
    "sub_ax.set_title(r\"Radiation Pattern ($\\phi = 0$)\")\n",
    "sub_ax.legend(loc=\"lower center\", ncols=2)\n",
    "\n",
    "sub_ax = ax[1]\n",
    "sub_ax.set_theta_direction(-1)\n",
    "sub_ax.set_theta_offset(np.pi / 2.0)\n",
    "sub_ax.plot(theta_proj, 10 * np.log10(Urad_RH_Phi_90), \"-k\", label=\"RHCP\")\n",
    "sub_ax.plot(theta_proj, 10 * np.log10(Urad_LH_Phi_90), \"-r\", label=\"LHCP\")\n",
    "sub_ax.set_rlim(-40, 0)\n",
    "sub_ax.set_rticks([-40, -30, -20, -10, 0])\n",
    "sub_ax.set_title(r\"Radiation Pattern ($\\phi = \\pi/2$)\")\n",
    "sub_ax.legend(loc=\"lower center\", ncols=2)\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Finding antenna lobes with the `LobeMeasurer`\n",
    "\n",
    "Given a 1D array of values representing the radiation pattern, we can use the `LobeMeasurer` tool to find the direction of the main antenna lobes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The main lobe direction in the xz-plane is 5.40 degrees.\n",
      "The main lobe direction in the yz-plane is -10.80 degrees.\n"
     ]
    }
   ],
   "source": [
    "xz_plane_lobe_measurer = LobeMeasurer(angle=theta_proj, radiation_pattern=Urad_RH_Phi_0)\n",
    "main_lobe_phi_0 = xz_plane_lobe_measurer.main_lobe[\"direction\"] * 180 / np.pi\n",
    "\n",
    "yz_plane_lobe_measurer = LobeMeasurer(angle=theta_proj, radiation_pattern=Urad_RH_Phi_90)\n",
    "main_lobe_phi_90 = yz_plane_lobe_measurer.main_lobe[\"direction\"] * 180 / np.pi - 360\n",
    "\n",
    "print(f\"The main lobe direction in the xz-plane is {main_lobe_phi_0:.2f} degrees.\")\n",
    "print(f\"The main lobe direction in the yz-plane is {main_lobe_phi_90:.2f} degrees.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The beam directions are close to the values reported in [1], which are 5 degrees in the *xz* plane and -10 degrees in the *yz* plane."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot of $S_{11}$\n",
    "Next, we reproduce Fig. 9 (a) from [1] using the scattering parameter computed by the `TerminalComponentModeler`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the reflection coefficient using the scattering parameter computed by the TerminalComponentModeler\n",
    "freq = s_matrix.f / 1e9\n",
    "s_11 = 20 * np.log10(np.abs(s_matrix.isel(port_out=0, port_in=0).values.flatten()))\n",
    "plt.plot(freq, s_11, \"-b\")\n",
    "plt.xlabel(\"Frequency (GHz)\")\n",
    "plt.ylabel(r\"$|S_{11}|$ (dB)\")\n",
    "plt.title(r\"Plot of $S_{11}$\")\n",
    "# Make the plot identical to [1].\n",
    "plt.xlim(2.1, 3.1)\n",
    "plt.ylim(-40, 0)\n",
    "plt.yticks([-40, -30, -20, -10, 0])\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute and plot the axial ratio\n",
    "Next, we use the simulation results to reproduce Fig. 9 (a) from [1]."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Retrieve the field data from the \"rad_frequency\" monitor\n",
    "antenna_parameters_freq = modeler.get_antenna_metrics_data(monitor_name=\"rad_frequency\")\n",
    "axial_ratio = antenna_parameters_freq.axial_ratio\n",
    "\n",
    "freq = axial_ratio.f.values.squeeze() / 1e9\n",
    "axial_ratio_dB = 20 * np.log10(np.abs(axial_ratio.values.squeeze()))\n",
    "plt.plot(freq, axial_ratio_dB, \"-b\")\n",
    "plt.xlabel(\"Frequency (GHz)\")\n",
    "plt.ylabel(\"Axial ratio (dB)\")\n",
    "plt.title(\"Axial ratio\")\n",
    "# Make the plot identical to [1].\n",
    "plt.xlim(2.1, 3.1)\n",
    "plt.ylim(0, 12)\n",
    "plt.yticks([0, 3, 6, 9, 12])\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute and plot the antenna gain for RHCP\n",
    "We plot the antenna gain for the RHCP component. These results can be retrieved from `AntennaMetricsData` by specifying a \"circular\" polarization basis.\n",
    "The gain is calculated by multiplying the directivity by the radiation efficiency of the antenna. The resulting plot will replicate Fig. 9 (b) from [1]."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "freq = antenna_parameters_freq.f.squeeze() / 1e9\n",
    "gain = antenna_parameters_freq.partial_gain(pol_basis=\"circular\").Gright.values.squeeze()\n",
    "gain_dB = 10 * np.log10(gain)\n",
    "plt.plot(freq, gain_dB, \"-b\")\n",
    "plt.xlabel(\"Frequency (GHz)\")\n",
    "plt.ylabel(\"Gain (dB)\")\n",
    "plt.title(\"Gain\")\n",
    "plt.xlim(2.1, 3.1)\n",
    "plt.ylim(5, 10)\n",
    "plt.yticks([6, 7, 8, 9])\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting Up and Simulating the Differential Feed Antenna Configuration\n",
    "\n",
    "In [1], the proposed single-feed excitation is compared to a differential feed excitation, where the ground pin is removed and a second feed pin is added. We can reproduce the results in [1] by changing the Tidy3D simulation to reflect the new geometry, as well as adding an additional coaxial port to the `TerminalComponentModeler`.\n",
    "\n",
    "The radiated fields due to the differential feed configuration can be calculated as a post-processsing step in the `TerminalComponentModeler`, which forms a superposition of the fields with user-defined port amplitudes. However, unlike the single feed case, we need to recompute the radiated power by integrating over a spherical surface. As a result, we need to ensure that the `DirectivityMonitor` samples the electromagnetic field over an entire sphere. In this section, we will use a single `DirectivityMonitor` that will sample both the spatial coordinates and all desired frequency values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create simulation in the differential feed configuration\n",
    "structures_list = make_structures(True)\n",
    "grid_spec = make_grid_spec(True)\n",
    "\n",
    "# Create a new monitor that samples entire spherical surface\n",
    "theta_proj2 = np.linspace(0, np.pi, 101)\n",
    "phi_proj2 = np.linspace(0, 2 * np.pi, 200)\n",
    "\n",
    "# First, create a DirectivityMonitor that will be used to plot the radiation pattern in the xz and yz planes\n",
    "mon_rad_spatial = td.DirectivityMonitor(\n",
    "    center=sim_center,\n",
    "    size=farfield_size,\n",
    "    freqs=freqs,\n",
    "    name=\"rad_spatial\",\n",
    "    phi=list(phi_proj2),\n",
    "    theta=list(theta_proj2),\n",
    "    proj_distance=r_proj,\n",
    "    far_field_approx=True,  # Compute the radiated fields in the far field.\n",
    ")\n",
    "sim = sim.updated_copy(structures=structures_list, grid_spec=grid_spec)\n",
    "\n",
    "# Setting up the scene for visualization, with all structures included\n",
    "# and units set to millimeters for the plot.\n",
    "scene = td.Scene(structures=structures_list, plot_length_units=\"mm\")\n",
    "fig, axs = plt.subplots(1, 2, figsize=(10, 5), tight_layout=True)\n",
    "sub_ax = axs[0]\n",
    "scene.plot(z=t, ax=sub_ax)\n",
    "sub_ax.set_xlim(-L / 2, L / 2)\n",
    "sub_ax.set_ylim(-L / 2, L / 2)\n",
    "sub_ax = axs[1]\n",
    "scene.plot(y=0, ax=sub_ax)\n",
    "sub_ax.set_xlim(-L / 3, L / 3)\n",
    "sub_ax.set_ylim(-H - t, 2 * t)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, we create a new `TerminalComponentModeler` with an additional port, the modified `Simulation`, and the modified radiation monitor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "diff_center = [-fx, 0, port_location]\n",
    "diff_port = coax_port.updated_copy(center=diff_center, name=\"diff_port\")\n",
    "\n",
    "modeler_diff_feed = modeler.updated_copy(\n",
    "    simulation=sim, ports=[coax_port, diff_port], radiation_monitors=[mon_rad_spatial]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e148caebdcaf4ce8a0128fe2190ac1f0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:56:23 EST </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span> tasks.                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:56:23 EST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m2\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\">15:56:25 EST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.669</span> for the whole batch.                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:56:25 EST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.669\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 the\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Batch has completed.                                               \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 the\n",
       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7d09c1131030415791e429312cb00f6c",
       "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\">15:57:08 EST </span>Batch complete.                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:57:08 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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1e5494fbbaa7403c9d505d7b6ba1469b",
       "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"
    }
   ],
   "source": [
    "# Run the TerminalComponentModeler and populate the scattering matrix of this single CoaxialLumpedPort network.\n",
    "s_matrix = modeler_diff_feed.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comparison of the radiation patterns for the different feed configurations\n",
    "We use the simulation results to partially reproduce Fig. 7 (b) from [1]. We retrieve the directivities using the helper method `get_antenna_metrics_data`, which returns an `AntennaMetricsData` object. We retrieve the partial directivity, which corresponds with the right-handed circular polarization (RHCP) component."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get the directivity from the original modeler using the proposed feed\n",
    "D_right = antenna_parameters_spatial.partial_directivity(pol_basis=\"circular\").Dright.sel(f=freq0)\n",
    "# Select fields along theta for phi=0 and phi = pi/2\n",
    "D_Phi_0 = D_right.sel(phi=0).squeeze().values\n",
    "D_Phi_90 = D_right.sel(phi=np.pi / 2).squeeze().values\n",
    "\n",
    "# Create a differential excitation by setting the amplitudes of the two ports to be equal in magnitude but opposite in phase.\n",
    "port_amplitudes = {\"coax_port\": 1.0, \"diff_port\": -1.0}\n",
    "antenna_parameters_shell = modeler_diff_feed.get_antenna_metrics_data(\n",
    "    port_amplitudes, monitor_name=\"rad_spatial\"\n",
    ")\n",
    "D_right_diff = antenna_parameters_shell.partial_directivity(pol_basis=\"circular\").Dright.sel(\n",
    "    f=freq0\n",
    ")\n",
    "\n",
    "# These helper functions are used to extract the fields along theta for phi=0 and phi=pi/2, so that theta is in the range [0, 2*pi).\n",
    "D_Phi_0_diff = antenna_parameters_shell.get_phi_slice(D_right_diff, 0.0)\n",
    "D_Phi_90_diff = antenna_parameters_shell.get_phi_slice(D_right_diff, np.pi / 2)\n",
    "theta_plot = D_Phi_90_diff.theta.values\n",
    "# Convert to numpy arrays for plotting\n",
    "D_Phi_0_diff = D_Phi_0_diff.squeeze().values\n",
    "D_Phi_90_diff = D_Phi_90_diff.squeeze().values\n",
    "\n",
    "# Plot the partial directivities similar to [1].\n",
    "fig, ax = plt.subplots(1, 2, subplot_kw={\"projection\": \"polar\"}, figsize=(8, 4))\n",
    "sub_ax = ax[0]\n",
    "sub_ax.set_theta_direction(-1)\n",
    "sub_ax.set_theta_offset(np.pi / 2.0)\n",
    "sub_ax.plot(theta_plot, 10 * np.log10(D_Phi_0_diff), \"-.b\", label=\"Differential feed\")\n",
    "sub_ax.plot(theta_proj, 10 * np.log10(D_Phi_0), \"-r\", label=\"Proposed feed [1]\")\n",
    "sub_ax.set_rlim(-20, 12)\n",
    "sub_ax.set_rticks([-20, -10, 0, 10])\n",
    "sub_ax.set_title(r\"$D_{\\rm RHCP}$($\\phi = 0$)\")\n",
    "sub_ax.legend(loc=\"lower center\", ncols=2)\n",
    "\n",
    "sub_ax = ax[1]\n",
    "sub_ax.set_theta_direction(-1)\n",
    "sub_ax.set_theta_offset(np.pi / 2.0)\n",
    "sub_ax.plot(theta_plot, 10 * np.log10(D_Phi_90_diff), \"-.b\", label=\"Differential feed\")\n",
    "sub_ax.plot(theta_proj, 10 * np.log10(D_Phi_90), \"-r\", label=\"Proposed feed [1]\")\n",
    "sub_ax.set_rlim(-20, 12)\n",
    "sub_ax.set_rticks([-20, -10, 0, 10])\n",
    "sub_ax.set_title(r\"$D_{\\rm RHCP}$($\\phi = \\pi/2$)\")\n",
    "sub_ax.legend(loc=\"lower center\", ncols=2)\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gain comparison for the different feed configurations\n",
    "Next, we plot the gain of both feed types. Again, these results can be retrieved from the `AntennaMetricsData` object by specifying a \"circular\" polarization basis. The resulting plot will replicate Fig. 6 (b) from [1]."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "freq = antenna_parameters_shell.f.squeeze() / 1e9\n",
    "gain_diff = (\n",
    "    antenna_parameters_shell.partial_gain(pol_basis=\"circular\")\n",
    "    .Gright.sel(theta=0, phi=0)\n",
    "    .values.squeeze()\n",
    ")\n",
    "gain_diff_dB = 10 * np.log10(gain_diff)\n",
    "plt.plot(freq, gain_diff_dB, \"-.b\", label=\"Differential feed\")\n",
    "plt.plot(freq, gain_dB, \"-k\", label=\"Proposed feed [1]\")\n",
    "plt.xlabel(\"Frequency (GHz)\")\n",
    "plt.ylabel(\"Gain (dB)\")\n",
    "plt.title(\"Gain\")\n",
    "plt.xlim(2.1, 3.1)\n",
    "plt.ylim(7, 11)\n",
    "plt.yticks([7, 8, 9, 10, 11])\n",
    "plt.legend(loc=\"lower center\", ncols=2)\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "\n",
    "[1] J. Wu, Y. Yin, Z. Wang and R. Lian, \"Broadband Circularly Polarized Patch Antenna With Parasitic Strips,\" in *IEEE Antennas and Wireless Propagation Letters*, vol.   14, pp. 559-562, 2015.\n",
    "\n",
    "[2] C. A. Balanis, *Antenna Theory: Analysis and Design*. John Wiley & Sons, 2016."
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Microwave and RF devices"
  ],
  "description": "In many applications, such as mobile communications, size, weight, and cost are the primary constraints that drive the design of antennas. Patch antennas are ideal since they can be directly manufactured on printed-circuit boards. This notebook simulates a circularly polarized antenna with parasitic strips, offering a lower profile and improved bandwidth. It introduces key Tidy3D components like CoaxialLumpedPort, smatrix plugin, FieldProjectionAngleMonitor, and post-processing steps for antenna parameter computation.",
  "feature": [
   "Far field projection",
   "Lumped port",
   "Smatrix plugin"
  ],
  "feature_image": "./img/circularly_polarized_patch_antenna.png",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "microwave, RF, antenna, lobe, circular polarization, directivity, axial ratio, gain, 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": "3.12.8"
  },
  "title": "Circularly polarized patch antenna with parasitic strips in Tidy3D FDTD"
 },
 "nbformat": 4,
 "nbformat_minor": 4
}