{ "cells": [ { "cell_type": "markdown", "id": "568b3cae-6a1b-41ab-b3d9-8d8190de802e", "metadata": {}, "source": [ "# 100 Ohm differential stripline benchmark" ] }, { "cell_type": "markdown", "id": "a1187e70-6aa6-417a-93fc-082528ee17e2", "metadata": {}, "source": [ "The stripline is a commonly used transmission line in printed circuit board (PCB) designs. Compared to the microstrip, the advantage of the stripline includes better shielding from EM interference, lower radiation loss, and better performance at higher frequencies. These strengths make it suitable for use in high-speed interconnects, where bandwidth, package size, and signal integrity are key concerns.\n", "\n", "In this notebook, we will build a 100 Ohm edge-coupled differential stripline and simulate it from 1 to 70 GHz. The results will be compared with benchmark data from other commercial RF simulation software. Both 2D mode solver and 3D FDTD results are presented. " ] }, { "cell_type": "markdown", "id": "3f3673da-abdf-4c5f-bd2e-ee7a08b02c6a", "metadata": {}, "source": [ "
" ] }, { "cell_type": "code", "execution_count": 1, "id": "1071b980-19c0-4b93-8425-c0a7757be4f1", "metadata": { "execution": { "iopub.execute_input": "2025-12-05T22:41:32.104793Z", "iopub.status.busy": "2025-12-05T22:41:32.104335Z", "iopub.status.idle": "2025-12-05T22:41:33.844422Z", "shell.execute_reply": "2025-12-05T22:41:33.843754Z" } }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import tidy3d as td\n", "import tidy3d.rf as rf\n", "import tidy3d.web as web\n", "from tidy3d.plugins.dispersion import FastDispersionFitter\n", "\n", "td.config.logging.level = \"ERROR\"" ] }, { "cell_type": "markdown", "id": "8e63afeb-9c29-4337-ba62-eb5709852a03", "metadata": {}, "source": [ "### Building the Simulation" ] }, { "cell_type": "markdown", "id": "90ac7055-75f1-4fd9-9917-da308862ce19", "metadata": {}, "source": [ "### Key Parameters" ] }, { "attachments": {}, "cell_type": "markdown", "id": "120b0333-feb4-43a8-9456-292bf3f20a61", "metadata": {}, "source": [ "We begin by defining some key parameters. The design impedance $Z_0$ for the differential mode will be 100 Ohms. The geometry parameters are chosen with that in mind. Material properties are assumed constant over the frequency band. " ] }, { "cell_type": "markdown", "id": "00beab83-4b93-4121-9fae-332f44f3509a", "metadata": {}, "source": [ "
" ] }, { "cell_type": "code", "execution_count": 2, "id": "bd53fd47-7d45-4394-856e-78818ce30b64", "metadata": { "execution": { "iopub.execute_input": "2025-12-05T22:41:33.846133Z", "iopub.status.busy": "2025-12-05T22:41:33.845801Z", "iopub.status.idle": "2025-12-05T22:41:33.847874Z", "shell.execute_reply": "2025-12-05T22:41:33.847596Z" } }, "outputs": [], "source": [ "# Frequency range (Hz)\n", "f_min, f_max = (1e9, 70e9)\n", "\n", "# Center frequency\n", "f0 = (f_max + f_min) / 2\n", "\n", "# Frequency sample points\n", "freqs = np.linspace(f_min, f_max, 101)\n", "\n", "# Frequency sample points (for field monitors)\n", "field_mon_freqs = np.linspace(f_min, f_max, 3)" ] }, { "cell_type": "code", "execution_count": 3, "id": "038c67ba-f3e0-4cae-bc4b-da1737e8e55b", "metadata": { "execution": { "iopub.execute_input": "2025-12-05T22:41:33.848921Z", "iopub.status.busy": "2025-12-05T22:41:33.848828Z", "iopub.status.idle": "2025-12-05T22:41:33.850499Z", "shell.execute_reply": "2025-12-05T22:41:33.850246Z" } }, "outputs": [], "source": [ "# Geometry\n", "mil = 25.4 # conversion to mils to microns (default unit)\n", "w = 3.2 * mil # Signal strip width\n", "t = 0.7 * mil # Conductor thickness\n", "h = 10.7 * mil # Substrate thickness\n", "se = 7 * mil # gap between edge-coupled pair\n", "L = 4000 * mil # Line length\n", "len_inf = 1e6 # Effective infinity" ] }, { "cell_type": "code", "execution_count": 4, "id": "1e2fd70e-9708-4c69-9227-8bbb99007e9d", "metadata": { "execution": { "iopub.execute_input": "2025-12-05T22:41:33.851641Z", "iopub.status.busy": "2025-12-05T22:41:33.851555Z", "iopub.status.idle": "2025-12-05T22:41:33.853018Z", "shell.execute_reply": "2025-12-05T22:41:33.852753Z" } }, "outputs": [], "source": [ "# Material properties\n", "cond = 60 # Metal conductivity in S/um\n", "eps = 4.4 # Relative permittivity, substrate\n", "losstan = 0.0012 # Loss tangent, substrate" ] }, { "cell_type": "markdown", "id": "04b2d755-27a0-4e6b-b619-506e015e18c7", "metadata": {}, "source": [ "### Mediums and Structures" ] }, { "cell_type": "markdown", "id": "3574ae35-425c-4231-97b6-7123405ff8b3", "metadata": {}, "source": [ "We wish to define constant loss for the metal and substrate over the frequency band:\n", "* Metal: The [`LossyMetalMedium`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.LossyMetalMedium.html) implements the surface impedance boundary condition for lossy metals .\n", "* Dielectric: 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) method in the [`FastDispersionFitter`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.dispersion.FastDispersionFitter.html) plugin automatically generates a `PoleResidue` medium given permittivity, loss tangent, and frequency range parameters. " ] }, { "cell_type": "code", "execution_count": 5, "id": "3cc5db8b-c640-4776-88bd-f68dab4047dd", "metadata": { "execution": { "iopub.execute_input": "2025-12-05T22:41:33.854066Z", "iopub.status.busy": "2025-12-05T22:41:33.853981Z", "iopub.status.idle": "2025-12-05T22:41:34.173077Z", "shell.execute_reply": "2025-12-05T22:41:34.172805Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "7687e4098931428a81868d4f5132320a", "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"
    }
   ],
   "source": [
    "med_sub = FastDispersionFitter.constant_loss_tangent_model(\n",
    "    eps, losstan, (f_min, f_max), tolerance_rms=2e-4\n",
    ")\n",
    "med_metal = rf.LossyMetalMedium(conductivity=cond, frequency_range=(f_min, f_max), name=\"Metal\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "535b6f19-71e1-454e-a86b-329cd29c9a01",
   "metadata": {},
   "source": [
    "We can also use `VisualizationSpec` to control the fill color of the materials during plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "24c32ea7-c2af-4862-9002-ff56045fb97d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.188836Z",
     "iopub.status.busy": "2025-12-05T22:41:34.188764Z",
     "iopub.status.idle": "2025-12-05T22:41:34.191071Z",
     "shell.execute_reply": "2025-12-05T22:41:34.190812Z"
    }
   },
   "outputs": [],
   "source": [
    "med_sub = med_sub.updated_copy(\n",
    "    viz_spec=td.VisualizationSpec(facecolor=\"#7cc48d\")\n",
    ")  # green tone for substrate\n",
    "med_metal = med_metal.updated_copy(\n",
    "    viz_spec=td.VisualizationSpec(facecolor=\"#ed8026\")\n",
    ")  # copper tone for metal"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83b24220-c9ba-4aa7-bf6c-a0fd575d0026",
   "metadata": {},
   "source": [
    "The structures are created below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "249d436d-1144-4ede-8680-f060fb848d71",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.191817Z",
     "iopub.status.busy": "2025-12-05T22:41:34.191731Z",
     "iopub.status.idle": "2025-12-05T22:41:34.194409Z",
     "shell.execute_reply": "2025-12-05T22:41:34.194147Z"
    }
   },
   "outputs": [],
   "source": [
    "# Substrate\n",
    "str_sub = td.Structure(\n",
    "    geometry=td.Box(center=(0, 0, 0), size=(len_inf, h, len_inf)), medium=med_sub\n",
    ")\n",
    "\n",
    "# Left signal strip\n",
    "str_strip_left = td.Structure(\n",
    "    geometry=td.Box(center=(-(se + w) / 2, 0, 0), size=(w, t, len_inf)), medium=med_metal\n",
    ")\n",
    "\n",
    "# Right signal strip\n",
    "str_strip_right = td.Structure(\n",
    "    geometry=td.Box(center=((se + w) / 2, 0, 0), size=(w, t, len_inf)), medium=med_metal\n",
    ")\n",
    "\n",
    "# Top ground plane\n",
    "str_gnd_top = td.Structure(\n",
    "    geometry=td.Box(center=(0, h / 2 + t / 2, 0), size=(len_inf, t, len_inf)), medium=med_metal\n",
    ")\n",
    "\n",
    "# Bottom ground plane\n",
    "str_gnd_bot = td.Structure(\n",
    "    geometry=td.Box(center=(0, -h / 2 - t / 2, 0), size=(len_inf, t, len_inf)), medium=med_metal\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9533498e-1efe-4a62-b8d2-80574393855a",
   "metadata": {},
   "source": [
    "### Grid and Boundaries"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5832a166-8514-46da-8532-f167c7f0492b",
   "metadata": {},
   "source": [
    "The [`LayerRefinementSpec`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.LayerRefinementSpec.html) feature is useful for refining the grid around metallic structures as it automatically detects metal edges and corners. In this model, we define `lr_spec` in order to refine the region around the left and right signal traces. The other specs `lr_spec2` and `lr_spec3` are used to refine the region around the top and bottom ground planes. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1d7e3ffc-72af-4081-9a90-7f21a655ddeb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.195297Z",
     "iopub.status.busy": "2025-12-05T22:41:34.195212Z",
     "iopub.status.idle": "2025-12-05T22:41:34.197728Z",
     "shell.execute_reply": "2025-12-05T22:41:34.197490Z"
    }
   },
   "outputs": [],
   "source": [
    "# Create a LayerRefinementSpec from signal trace structures\n",
    "lr_spec = rf.LayerRefinementSpec.from_structures(\n",
    "    structures=[str_strip_left, str_strip_right],\n",
    "    axis=1,  # Layer normal is in y-direction\n",
    "    min_steps_along_axis=10,  # Min 10 grid cells along normal direction\n",
    "    refinement_inside_sim_only=False,  # Metal structures extend outside sim domain. Set 'False' to snap to corners outside sim.\n",
    "    bounds_snapping=\"bounds\",  # snap grid to metal boundaries\n",
    "    corner_refinement=td.GridRefinement(\n",
    "        dl=t / 10, num_cells=2\n",
    "    ),  # snap to corners and apply added refinement\n",
    ")\n",
    "\n",
    "# Layer refinement for top and bottom ground planes\n",
    "lr_spec2 = lr_spec.updated_copy(center=(0, h / 2 + t / 2, 0), size=(len_inf, t, len_inf))\n",
    "lr_spec3 = lr_spec.updated_copy(center=(0, -h / 2 - t / 2, 0), size=(len_inf, t, len_inf))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99137d15-39fa-4e02-972c-5a6facf1b53e",
   "metadata": {},
   "source": [
    "The rest of the grid is automatically generated based on the wavelength. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e2267b72-5d69-47de-851a-65e0a5e54ef3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.198725Z",
     "iopub.status.busy": "2025-12-05T22:41:34.198639Z",
     "iopub.status.idle": "2025-12-05T22:41:34.200288Z",
     "shell.execute_reply": "2025-12-05T22:41:34.200042Z"
    }
   },
   "outputs": [],
   "source": [
    "# Define overall grid specification\n",
    "grid_spec = td.GridSpec.auto(\n",
    "    wavelength=td.C_0 / f_max,\n",
    "    min_steps_per_wvl=30,\n",
    "    layer_refinement_specs=[lr_spec, lr_spec2, lr_spec3],\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ce4e535-0abe-4494-a78e-2ff021ee294b",
   "metadata": {},
   "source": [
    "The top and bottom boundaries of this model are adjacent to the metal ground planes and can be set to PEC. All other boundaries are open and thus truncated by perfectly matched layers (PMLs)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ddce7f1b-a4c5-4a20-b259-7f29d867bb39",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.201183Z",
     "iopub.status.busy": "2025-12-05T22:41:34.201100Z",
     "iopub.status.idle": "2025-12-05T22:41:34.202762Z",
     "shell.execute_reply": "2025-12-05T22:41:34.202495Z"
    }
   },
   "outputs": [],
   "source": [
    "boundary_spec = td.BoundarySpec(\n",
    "    x=td.Boundary.pml(),\n",
    "    y=td.Boundary.pec(),\n",
    "    z=td.Boundary.pml(),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d047a619-9f41-4834-9791-5221cf5199bd",
   "metadata": {},
   "source": [
    "### Monitors"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56f2964e-14c2-4ac1-a2ff-e071ace162ea",
   "metadata": {},
   "source": [
    "For visualization purposes, we will add a `FieldMonitor` along the longitudinal plane. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "19e05161-e03c-4c0b-8191-9dd841d4e4a6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.203707Z",
     "iopub.status.busy": "2025-12-05T22:41:34.203623Z",
     "iopub.status.idle": "2025-12-05T22:41:34.205317Z",
     "shell.execute_reply": "2025-12-05T22:41:34.205081Z"
    }
   },
   "outputs": [],
   "source": [
    "field_mon_1 = td.FieldMonitor(\n",
    "    center=(0, 0, 0),\n",
    "    size=(len_inf, 0, len_inf),\n",
    "    freqs=field_mon_freqs,\n",
    "    name=\"longitudinal field (y=0)\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "490311c3-1eb8-4b7f-ac96-eebe206653ff",
   "metadata": {},
   "source": [
    "### Wave Ports"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f268971f-540c-4f9b-94ce-62aafc003055",
   "metadata": {},
   "source": [
    "[Wave ports](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.smatrix.WavePort.html) are used to excite the model and calculate S-parameters. In addition to the name, center, size, and orientation direction, the wave port also requires defining:\n",
    "* The `mode_spec` setting, which controls the specification for the wave port mode solver. Typically, we solve for one mode with the `target_neff` close to the expected propagation index. \n",
    "* By default the `MicrowaveModeSpec` is setup to automatically compute impedance for modes using an `AutoImpedanceSpec`. Alternatively, you may use a `CustomImpedanceSpec` which requires either a `voltage_spec`, or `current_spec`, or both. These definitions are used to calculate the mode's characteristic impedance $Z_0$. Note that depending on which integral is specified, there are three possible conventions: PI, PV, or VI where P = power, V = voltage, I = current. Each convention will yield a slightly different value for the impedance. In this notebook, we use the VI convention. The `AutoImpedanceSpec` uses the PI convention for computing impedance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6e9df262-b3a6-41c8-8f82-52ec4842aee0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.206319Z",
     "iopub.status.busy": "2025-12-05T22:41:34.206238Z",
     "iopub.status.idle": "2025-12-05T22:41:34.210435Z",
     "shell.execute_reply": "2025-12-05T22:41:34.210162Z"
    }
   },
   "outputs": [],
   "source": [
    "# Define current and voltage integral specifications\n",
    "current_spec = rf.AxisAlignedCurrentIntegralSpec(\n",
    "    center=((se + w) / 2, 0, -L / 2), size=(2 * w, 3 * t, 0), sign=\"+\"\n",
    ")\n",
    "voltage_spec = rf.AxisAlignedVoltageIntegralSpec(\n",
    "    center=(0, 0, -L / 2),\n",
    "    size=(se, 0, 0),\n",
    "    extrapolate_to_endpoints=True,\n",
    "    snap_path_to_grid=True,\n",
    "    sign=\"+\",\n",
    ")\n",
    "# Define specification for computing characteristic impedance\n",
    "Z_VI_impedance_spec = rf.CustomImpedanceSpec(voltage_spec=voltage_spec, current_spec=current_spec)\n",
    "# Define port specification\n",
    "wave_port_mode_spec = rf.MicrowaveModeSpec(\n",
    "    num_modes=1, target_neff=np.sqrt(eps), impedance_specs=(Z_VI_impedance_spec,)\n",
    ")\n",
    "\n",
    "# Define wave ports\n",
    "WP1 = rf.WavePort(\n",
    "    center=(0, 0, -L / 2),\n",
    "    size=(len_inf, len_inf, 0),\n",
    "    mode_spec=wave_port_mode_spec,\n",
    "    direction=\"+\",\n",
    "    name=\"WP1\",\n",
    ")\n",
    "# Update the mode spec for the second wave port. We only need to update the sign of the current specification, since coordinates along\n",
    "# the longitudinal direction are ignored, and the ports are identical in the transverse plane.\n",
    "wave_port_mode_spec = wave_port_mode_spec.updated_copy(\n",
    "    path=\"impedance_specs/0/\", current_spec=current_spec.updated_copy(sign=\"-\")\n",
    ")\n",
    "WP2 = WP1.updated_copy(\n",
    "    name=\"WP2\",\n",
    "    center=(0, 0, L / 2),\n",
    "    direction=\"-\",\n",
    "    mode_spec=wave_port_mode_spec,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12730e2c-1a56-4fcb-9f06-86246b0b229f",
   "metadata": {},
   "source": [
    "## Define the Simulation and TerminalComponentModeler"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90c2cb15-6fb8-4537-b29a-b46b4caed7f2",
   "metadata": {},
   "source": [
    "The `Simulation` object in Tidy3D contains information about the entire simulation environment, including boundary conditions, grid, structures, and monitors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "66772086-16cf-4dd2-8730-be2fd29b6dfc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.211305Z",
     "iopub.status.busy": "2025-12-05T22:41:34.211219Z",
     "iopub.status.idle": "2025-12-05T22:41:34.236672Z",
     "shell.execute_reply": "2025-12-05T22:41:34.236334Z"
    }
   },
   "outputs": [],
   "source": [
    "sim = td.Simulation(\n",
    "    size=(50 * mil, h + 2 * t, 1.05 * L),\n",
    "    center=(0, 0, 0),\n",
    "    grid_spec=grid_spec,\n",
    "    boundary_spec=boundary_spec,\n",
    "    structures=[str_sub, str_strip_left, str_strip_right, str_gnd_top, str_gnd_bot],\n",
    "    monitors=[field_mon_1],\n",
    "    run_time=2e-9,  # simulation run time in seconds\n",
    "    shutoff=1e-7,  # lower shutoff threshold for more accurate small signal\n",
    "    plot_length_units=\"mm\",\n",
    "    symmetry=(-1, 0, 0),  # odd symmetry in x-direction\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a911a46-56c8-4fca-93f7-0a54cabb24f0",
   "metadata": {},
   "source": [
    "The [`TerminalComponentModeler`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.smatrix.TerminalComponentModeler.html) conducts a port sweep based on our previously defined `Simulation` in order to construct the full S-parameter matrix.   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4c802e18-251b-48b8-8b54-300a8d27308b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.237610Z",
     "iopub.status.busy": "2025-12-05T22:41:34.237527Z",
     "iopub.status.idle": "2025-12-05T22:41:34.239706Z",
     "shell.execute_reply": "2025-12-05T22:41:34.239454Z"
    }
   },
   "outputs": [],
   "source": [
    "tcm = rf.TerminalComponentModeler(\n",
    "    simulation=sim,  # simulation, previously defined\n",
    "    ports=[WP1, WP2],  # wave ports, previously defined\n",
    "    freqs=freqs,  # S-parameter frequency points\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2971c875-fcdb-405a-9bec-be719fe8743a",
   "metadata": {},
   "source": [
    "Before running, it is a good idea to double check the structures and grid. We see the substrate in green, and lossy metal in orange. The PEC top/bottom boundaries are displayed in gold. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6d626ca3-c367-4cc4-ad93-07645bf2c9dc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.240796Z",
     "iopub.status.busy": "2025-12-05T22:41:34.240714Z",
     "iopub.status.idle": "2025-12-05T22:41:34.402808Z",
     "shell.execute_reply": "2025-12-05T22:41:34.402546Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Inspect transverse grid\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "sim.plot(z=1, ax=ax)\n",
    "sim.plot_grid(z=1, ax=ax, hlim=(-w - se, w + se + 200), vlim=(-200, 200))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1966ca2a-1f76-48f9-b20f-23a7553d3218",
   "metadata": {},
   "source": [
    "## 2D Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ca6999c-990e-415f-8f52-fec7d5b927ce",
   "metadata": {},
   "source": [
    "Before running the 3D simulation, let us first perform a 2D `ModeSolver` calculation. From the `ModeSolver` results, we can obtain all the key transmission line parameters, such as attenuation $\\alpha$, characteristic impedance $Z_0$, and effective index $n_{\\text{eff}}$. \n",
    "\n",
    "Since we have previously defined a `WavePort`, we can skip the usual setup process and use the `to_mode_solver()` method to quickly define a `ModeSolver` simulation. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "34f7794e-3fab-473f-9213-782ac42b6789",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.403975Z",
     "iopub.status.busy": "2025-12-05T22:41:34.403882Z",
     "iopub.status.idle": "2025-12-05T22:41:34.407130Z",
     "shell.execute_reply": "2025-12-05T22:41:34.406880Z"
    }
   },
   "outputs": [],
   "source": [
    "# Convert wave port to mode solver\n",
    "mode_solver = WP1.to_mode_solver(sim, freqs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca2348d0-7b8d-4080-860f-dcff97e9464f",
   "metadata": {},
   "source": [
    "We execute the mode solver study below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e84ee11e-a7fd-43da-9329-6829e463aa10",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:41:34.408270Z",
     "iopub.status.busy": "2025-12-05T22:41:34.408183Z",
     "iopub.status.idle": "2025-12-05T22:42:05.555995Z",
     "shell.execute_reply": "2025-12-05T22:42:05.555497Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
17:41:34 EST Created task 'mode solver' with resource_id                        \n",
       "             'mo-07340d73-0320-4a69-a9a7-60328363d77b' and task_type            \n",
       "             'MODE_SOLVER'.                                                     \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:41:34 EST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'mode solver'\u001b[0m with resource_id                        \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'mo-07340d73-0320-4a69-a9a7-60328363d77b'\u001b[0m and task_type            \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'MODE_SOLVER'\u001b[0m.                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             View task using web UI at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-\n",
       "             4a69-a9a7-60328363d77b'.                                           \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=813685;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=12799;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=813685;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=795470;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[32mmo\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=813685;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[32m-07340d73-0320-\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=813685;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[32m4a69-a9a7-60328363d77b'\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=958793;https://tidy3d.simulation.cloud/folders/f89aec3e-3357-4624-9c24-096a87582f12\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ac6f0fe2fee8453ab6d0162586964a6c",
       "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": [
       "
17:41:42 EST Estimated FlexCredit cost: 0.014. 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;36m17:41:42 EST\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.014\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": [
       "
17:41:43 EST status = queued                                                    \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:41:43 EST\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             To cancel the simulation, use 'web.abort(task_id)' or              \n",
       "             'web.delete(task_id)' or abort/delete the task in the web UI.      \n",
       "             Terminating the Python script will not stop the job running on the \n",
       "             cloud.                                                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or              \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the web UI.      \n",
       "\u001b[2;36m             \u001b[0mTerminating the Python script will not stop the job running on the \n",
       "\u001b[2;36m             \u001b[0mcloud.                                                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1b45a9980ffd4775b64275545e69f13c",
       "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": [
       "
17:41:55 EST starting up solver                                                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:41:55 EST\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             running solver                                                     \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
17:42:02 EST status = success                                                   \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:42:02 EST\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-\n",
       "             4a69-a9a7-60328363d77b'.                                           \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=81607;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=579925;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=81607;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=922385;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[4;34mmo\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=81607;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[4;34m-07340d73-0320-\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=81607;https://tidy3d.simulation.cloud/workbench?taskId=mo-07340d73-0320-4a69-a9a7-60328363d77b\u001b\\\u001b[4;34m4a69-a9a7-60328363d77b'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                           \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "988306fb497141b281a61b2bb377a396",
       "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": [
       "
17:42:05 EST Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:42:05 EST\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mode_data = td.web.run(mode_solver, task_name=\"mode solver\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3210d5ff-9e20-468e-be39-eccd0083db41",
   "metadata": {},
   "source": [
    "Below, the `Ey` and `Ex` components of the mode field are plotted at the center frequency. The integration paths for the impedance calculation are also shown (current in blue and voltage in red). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e63b1de6-a98b-4bc1-9541-c6457fad3637",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:42:05.655539Z",
     "iopub.status.busy": "2025-12-05T22:42:05.655463Z",
     "iopub.status.idle": "2025-12-05T22:42:06.189347Z",
     "shell.execute_reply": "2025-12-05T22:42:06.188873Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot mode field\n",
    "fig, ax = plt.subplots(1, 2, figsize=(11, 2), tight_layout=True)\n",
    "mode_solver.plot_field(field_name=\"Ey\", val=\"real\", mode_index=0, f=f0, ax=ax[0])\n",
    "mode_solver.plot_field(field_name=\"Ex\", val=\"real\", mode_index=0, f=f0, ax=ax[1])\n",
    "for axis in ax:\n",
    "    current_spec.plot(z=-L / 2, ax=axis)\n",
    "    voltage_spec.plot(z=-L / 2, ax=axis)\n",
    "    axis.set_xlim(-20 * mil, 20 * mil)\n",
    "ax[0].set_title(\"Re(Ey)\")\n",
    "ax[1].set_title(\"Re(Ex)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f0c1382-9489-49e0-b6bf-50871cdee8d9",
   "metadata": {},
   "source": [
    "The mode solver solution data includes $n_{\\text{eff}}$ and attenuation $\\alpha$ in dB/cm. From this, we can also derive the real part of the propagation constant, $\\beta$, as well as the complex propagation constant $\\gamma$. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b700acdf-1d07-48c2-a4d0-a3a59fae0785",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:42:06.190712Z",
     "iopub.status.busy": "2025-12-05T22:42:06.190611Z",
     "iopub.status.idle": "2025-12-05T22:42:07.155263Z",
     "shell.execute_reply": "2025-12-05T22:42:07.154906Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "mode_data: td.MicrowaveModeSolverData = mode_data\n",
    "# Gather alpha, neff from mode solver results\n",
    "neff_mode = mode_data.modes_info[\"n eff\"].squeeze()\n",
    "alphadB_mode = mode_data.modes_info[\"loss (dB/cm)\"].squeeze()\n",
    "\n",
    "# Retrieve beta (rad/m), alpha (in Np/m), and gamma\n",
    "beta_mode = mode_data.beta\n",
    "alpha_mode = mode_data.alpha\n",
    "gamma_mode = mode_data.gamma"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ce91cf5-9be1-416a-bdd9-d13b4dc779b8",
   "metadata": {},
   "source": [
    "We obtain $Z_0$ by accessing the `Z0` field in the `TransmissionLineDataset`, making use of the previously defined current and voltage specifications."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "56e80ec1-be6d-4365-8272-69bdf8fb47e8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:42:07.156857Z",
     "iopub.status.busy": "2025-12-05T22:42:07.156739Z",
     "iopub.status.idle": "2025-12-05T22:42:07.158563Z",
     "shell.execute_reply": "2025-12-05T22:42:07.158176Z"
    }
   },
   "outputs": [],
   "source": [
    "Z0_mode = mode_data.transmission_line_data.Z0.isel(mode_index=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fd9130a-becf-4567-be5a-1696a12bfff2",
   "metadata": {},
   "source": [
    "Let's import some benchmark data for comparison. We will use mode data from a commercial FEM and FIT solver respectively. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "908f5306-d3c9-4165-8644-f70fa10c1ea3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:42:07.159648Z",
     "iopub.status.busy": "2025-12-05T22:42:07.159562Z",
     "iopub.status.idle": "2025-12-05T22:42:07.165658Z",
     "shell.execute_reply": "2025-12-05T22:42:07.165263Z"
    }
   },
   "outputs": [],
   "source": [
    "# Import benchmark data\n",
    "freqs_ben1, neff_ben1, alphadB_ben1, Z0_ben1 = np.loadtxt(\n",
    "    \"./misc/stripline_fem_mode.csv\", delimiter=\",\", skiprows=1, unpack=True\n",
    ")\n",
    "freqs_ben2, neff_ben2, alphadB_ben2, Z0_ben2 = np.loadtxt(\n",
    "    \"./misc/stripline_fit_mode.txt\", delimiter=\",\", unpack=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1789a602-ed29-43f7-8422-f51852ac1b11",
   "metadata": {},
   "source": [
    "Let's compare the effective index $n_{\\text{eff}}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2cc5749f-3441-4d3e-adb2-495a2d87f256",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:42:07.166651Z",
     "iopub.status.busy": "2025-12-05T22:42:07.166562Z",
     "iopub.status.idle": "2025-12-05T22:42:07.168509Z",
     "shell.execute_reply": "2025-12-05T22:42:07.168219Z"
    }
   },
   "outputs": [],
   "source": [
    "def plot_data_and_band(data, err_band, ax, label=\"\"):\n",
    "    \"\"\"Plots frequency-domain data together with a fractional error band\"\"\"\n",
    "    ax.plot(freqs / 1e9, data, label=label, color=\"#328362\")\n",
    "    ax.fill_between(\n",
    "        freqs / 1e9,\n",
    "        (1 + err_band) * data,\n",
    "        (1 - err_band) * data,\n",
    "        alpha=0.5,\n",
    "        color=\"#DDDDDD\",\n",
    "        label=f\"+/-{err_band * 100:.2f}%\",\n",
    "    )\n",
    "    ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a249957b-28a5-4f3c-b93d-e1a73741ad91",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:42:07.169657Z",
     "iopub.status.busy": "2025-12-05T22:42:07.169525Z",
     "iopub.status.idle": "2025-12-05T22:42:07.343733Z",
     "shell.execute_reply": "2025-12-05T22:42:07.343215Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 4), tight_layout=True)\n",
    "plot_data_and_band(neff_mode, 0.002, ax=ax, label=\"RF Photonics solver (Flexcompute)\")\n",
    "ax.plot(freqs_ben1, neff_ben1, \"--\", color=\"#888888\", label=\"Commercial FEM\")\n",
    "ax.plot(freqs_ben2, neff_ben2, \":\", color=\"#888888\", label=\"Commercial FIT\")\n",
    "ax.set_title(\"Effective index\")\n",
    "ax.set_xlabel(\"f (GHz)\")\n",
    "ax.set_ylabel(\"$n_{\\\\text{eff}}$\")\n",
    "ax.set_ylim(2.09, 2.14)\n",
    "ax.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a8f21e2-b076-47ae-afda-4cc688dab21a",
   "metadata": {},
   "source": [
    "We observe that $n_{\\text{eff}}$ is in good agreement with the benchmarks, and is close to the substrate index $\\sqrt \\epsilon \\approx 2.10$."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1053c9df-4351-4103-8ecf-283fd2feccfd",
   "metadata": {},
   "source": [
    "Next, let's compare the transmission line losses $\\alpha$ (dB/cm)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "1e765678-23bc-48d1-ad96-5a6930c7e292",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:42:07.344930Z",
     "iopub.status.busy": "2025-12-05T22:42:07.344827Z",
     "iopub.status.idle": "2025-12-05T22:42:07.431231Z",
     "shell.execute_reply": "2025-12-05T22:42:07.430864Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 4), tight_layout=True)\n",
    "plot_data_and_band(alphadB_mode, 0.05, ax=ax, label=\"RF Photonics solver (Flexcompute)\")\n",
    "ax.plot(freqs_ben1, alphadB_ben1, \"--\", color=\"#888888\", label=\"Commercial FEM\")\n",
    "ax.plot(freqs_ben2, alphadB_ben2, \":\", color=\"#888888\", label=\"Commercial FIT\")\n",
    "ax.set_title(\"Attenuation\")\n",
    "ax.set_xlabel(\"f (GHz)\")\n",
    "ax.set_ylabel(\"$\\\\alpha$ (dB/cm)\")\n",
    "ax.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97bb8bcc-e29b-4115-92c4-49d725203e89",
   "metadata": {},
   "source": [
    "Although the metal and substrate mediums are both lossy in this simulation, the metal losses dominate in this frequency range and scale as $f^{1/2}$ due to the skin depth. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0765443-551b-47b6-8f45-360445fa1573",
   "metadata": {},
   "source": [
    "Let's compare the impedance $Z_0$ of the differential mode. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d4476ebc-17f1-4d57-9c67-d84398947f55",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:42:07.432586Z",
     "iopub.status.busy": "2025-12-05T22:42:07.432476Z",
     "iopub.status.idle": "2025-12-05T22:42:07.529551Z",
     "shell.execute_reply": "2025-12-05T22:42:07.529158Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 4), tight_layout=True)\n",
    "plot_data_and_band(np.real(Z0_mode), 0.005, ax=ax, label=\"RF Photonics solver (Flexcompute)\")\n",
    "ax.plot(freqs_ben1, Z0_ben1, \"--\", color=\"#888888\", label=\"Commercial FEM\")\n",
    "ax.plot(freqs_ben2, Z0_ben2, \":\", color=\"#888888\", label=\"Commercial FIT\")\n",
    "ax.set_title(\"Differential impedance\")\n",
    "ax.set_xlabel(\"f (GHz)\")\n",
    "ax.set_ylabel(\"$Z_0$ ($\\\\Omega$)\")\n",
    "ax.set_ylim(98, 102)\n",
    "ax.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "706cb4a7-951f-4b44-a008-b21014ff10ed",
   "metadata": {},
   "source": [
    "## 3D Analysis"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "2dd09e6e-eca9-4d75-8dbc-cd58c16304a6",
   "metadata": {},
   "source": [
    "Since the transmission line is longitudinally invariant, the results of the 2D analysis can fully describe the propagating TEM mode. \n",
    "\n",
    "That said, for tutorial purposes, we will demonstrate how to perform a 3D full-wave simulation to obtain S-parameters. We will be simulating a 4 inch length of the transmission line, which is quite optically large. The level of grid refinement required for converged S-parameters is lower than those used for the 2D solver. To reduce the simulation cost, we define a grid specification with reduced refinement below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "bff45342-096f-48d6-9baf-b79dbae2103d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:42:07.530770Z",
     "iopub.status.busy": "2025-12-05T22:42:07.530654Z",
     "iopub.status.idle": "2025-12-05T22:42:07.588921Z",
     "shell.execute_reply": "2025-12-05T22:42:07.588465Z"
    }
   },
   "outputs": [],
   "source": [
    "# Update layer refinement with reduced fidelity\n",
    "lr_spec_3d = lr_spec.updated_copy(\n",
    "    min_steps_along_axis=3,\n",
    "    corner_refinement=td.GridRefinement(dl=t / 2, num_cells=2),\n",
    ")\n",
    "\n",
    "# Similarly for top and bottom ground planes\n",
    "lr_spec2_3d = lr_spec_3d.updated_copy(center=(0, h / 2 + t / 2, 0), size=(len_inf, t, len_inf))\n",
    "lr_spec3_3d = lr_spec_3d.updated_copy(center=(0, -h / 2 - t / 2, 0), size=(len_inf, t, len_inf))\n",
    "\n",
    "# Update overall grid specification\n",
    "grid_spec_3d = grid_spec.updated_copy(layer_refinement_specs=[lr_spec_3d, lr_spec2_3d, lr_spec3_3d])\n",
    "\n",
    "# Update sim and TCM\n",
    "sim_3d = sim.updated_copy(grid_spec=grid_spec_3d)\n",
    "tcm_3d = tcm.updated_copy(simulation=sim_3d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c2dc7097-4217-4b7d-a48a-85d0c65d89cb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:42:07.590007Z",
     "iopub.status.busy": "2025-12-05T22:42:07.589911Z",
     "iopub.status.idle": "2025-12-05T22:42:07.694974Z",
     "shell.execute_reply": "2025-12-05T22:42:07.694643Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the simplified 3D grid\n",
    "fig, ax = plt.subplots()\n",
    "sim_3d.plot(z=0, ax=ax)\n",
    "sim_3d.plot_grid(z=0, ax=ax, hlim=(0, 20 * mil))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b25750a-8c50-4f26-bc10-f62113d35d2b",
   "metadata": {},
   "source": [
    "We execute the TCM using the `tidy3d.web.run()` method below. The output is a TCM data object, from which we obtain the S-matrix using the `smatrix()` method. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "eeb0274f-2549-4d82-940b-b1af7f1dc73a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:42:07.696124Z",
     "iopub.status.busy": "2025-12-05T22:42:07.695987Z",
     "iopub.status.idle": "2025-12-05T22:47:11.558285Z",
     "shell.execute_reply": "2025-12-05T22:47:11.557760Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
17:42:08 EST Created task 'diff_stripline_3d' with resource_id                  \n",
       "             'sid-6336c6d1-6c63-47f4-b1d9-83fd2704f790' and task_type           \n",
       "             'TERMINAL_CM'.                                                     \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:42:08 EST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'diff_stripline_3d'\u001b[0m with resource_id                  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'sid-6336c6d1-6c63-47f4-b1d9-83fd2704f790'\u001b[0m and task_type           \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'TERMINAL_CM'\u001b[0m.                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             View task using web UI at                                          \n",
       "             'https://tidy3d.simulation.cloud/rf?taskId=pa-7d02d4c9-9d33-4555-90\n",
       "             2f-2c7d9cdafbc9'.                                                  \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=806102;https://tidy3d.simulation.cloud/rf?taskId=pa-7d02d4c9-9d33-4555-902f-2c7d9cdafbc9\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/rf?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=303445;https://tidy3d.simulation.cloud/rf?taskId=pa-7d02d4c9-9d33-4555-902f-2c7d9cdafbc9\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=806102;https://tidy3d.simulation.cloud/rf?taskId=pa-7d02d4c9-9d33-4555-902f-2c7d9cdafbc9\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=975518;https://tidy3d.simulation.cloud/rf?taskId=pa-7d02d4c9-9d33-4555-902f-2c7d9cdafbc9\u001b\\\u001b[32mpa\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=806102;https://tidy3d.simulation.cloud/rf?taskId=pa-7d02d4c9-9d33-4555-902f-2c7d9cdafbc9\u001b\\\u001b[32m-7d02d4c9-9d33-4555-90\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=806102;https://tidy3d.simulation.cloud/rf?taskId=pa-7d02d4c9-9d33-4555-902f-2c7d9cdafbc9\u001b\\\u001b[32m2f-2c7d9cdafbc9'\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=508793;https://tidy3d.simulation.cloud/folders/f89aec3e-3357-4624-9c24-096a87582f12\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "57170234034e48bf94f1e5bbe910ad8e",
       "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": [
       "
17:42:19 EST Maximum FlexCredit cost: 1.669. Minimum cost depends on task       \n",
       "             execution details. Use 'web.real_cost(task_id)' after run.         \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:42:19 EST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.669\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 after run.         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
17:42:20 EST Subtasks status - diff_stripline_3d                                \n",
       "             Group ID: 'pa-7d02d4c9-9d33-4555-902f-2c7d9cdafbc9'                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:42:20 EST\u001b[0m\u001b[2;36m \u001b[0mSubtasks status - diff_stripline_3d                                \n",
       "\u001b[2;36m             \u001b[0mGroup ID: \u001b[32m'pa-7d02d4c9-9d33-4555-902f-2c7d9cdafbc9'\u001b[0m                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ae647ddd4a69471fa77c3052ec32da67",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Batch status = preprocess                                          \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mBatch status = preprocess                                          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
17:42:29 EST Batch status = running                                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:42:29 EST\u001b[0m\u001b[2;36m \u001b[0mBatch status = running                                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
17:46:43 EST Batch status = postprocess                                         \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:46:43 EST\u001b[0m\u001b[2;36m \u001b[0mBatch status = postprocess                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
17:47:06 EST Modeler has finished running successfully.                         \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:47:06 EST\u001b[0m\u001b[2;36m \u001b[0mModeler has finished running successfully.                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
17:47:07 EST Billed flex credit cost: 1.288.                                    \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:47:07 EST\u001b[0m\u001b[2;36m \u001b[0mBilled flex credit cost: \u001b[1;36m1.288\u001b[0m.                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5a5378bf15b0466cacc2bf1876a3fb11",
       "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": [
       "
17:47:10 EST Loading component modeler data from cm_data.hdf5                   \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:47:10 EST\u001b[0m\u001b[2;36m \u001b[0mLoading component modeler data from cm_data.hdf5                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tcm_3d_data = web.run(tcm_3d, task_name=\"diff_stripline_3d\")\n",
    "s_matrix = tcm_3d_data.smatrix()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74692527-84ae-4652-bdc6-b0e2b4601a38",
   "metadata": {},
   "source": [
    "We use the `port_in` and `port_out` parameters to select the corresponding entry of the S-matrix. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b928901c-c3b8-4e6a-acf8-5034cabe6e46",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:47:13.245266Z",
     "iopub.status.busy": "2025-12-05T22:47:13.245194Z",
     "iopub.status.idle": "2025-12-05T22:47:13.247788Z",
     "shell.execute_reply": "2025-12-05T22:47:13.247473Z"
    }
   },
   "outputs": [],
   "source": [
    "# Get S-parameters\n",
    "S11 = np.conjugate(s_matrix.data.sel(port_in=\"WP1@0\", port_out=\"WP1@0\"))\n",
    "S21 = np.conjugate(s_matrix.data.sel(port_in=\"WP1@0\", port_out=\"WP2@0\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "24dfbd8f-4252-4e48-9ef0-b05820bb6a0c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:47:13.248848Z",
     "iopub.status.busy": "2025-12-05T22:47:13.248758Z",
     "iopub.status.idle": "2025-12-05T22:47:13.259815Z",
     "shell.execute_reply": "2025-12-05T22:47:13.259552Z"
    }
   },
   "outputs": [],
   "source": [
    "# Import benchmark data\n",
    "freqs_ben1, S11abs_ben1, S21abs_ben1 = np.loadtxt(\n",
    "    \"./misc/stripline_fem_sparam_long.csv\", delimiter=\",\", skiprows=1, unpack=True\n",
    ")\n",
    "freqs_ben2, S11abs_ben2, S21abs_ben2 = np.loadtxt(\n",
    "    \"./misc/stripline_fit_sparams_long.txt\", delimiter=\",\", unpack=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bab5304a-e214-43a0-bcee-dd14dfc9b25c",
   "metadata": {},
   "source": [
    "The insertion loss magnitude is plotted below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "bde8e965-d09f-4db4-acf2-5a3cd5aa6915",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:47:13.260810Z",
     "iopub.status.busy": "2025-12-05T22:47:13.260721Z",
     "iopub.status.idle": "2025-12-05T22:47:13.347456Z",
     "shell.execute_reply": "2025-12-05T22:47:13.347087Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 4), tight_layout=True)\n",
    "ax.plot(freqs / 1e9, np.abs(S21), label=\"RF Photonics solver (Flexcompute)\", color=\"#328362\")\n",
    "ax.plot(freqs_ben1, S21abs_ben1, \"--\", color=\"#888888\", label=\"Commercial FEM\")\n",
    "ax.plot(freqs_ben2, S21abs_ben2, \":\", color=\"#888888\", label=\"Commercial FIT\")\n",
    "ax.fill_between(\n",
    "    freqs / 1e9,\n",
    "    np.abs(S21) + 0.01,\n",
    "    np.abs(S21) - 0.01,\n",
    "    alpha=0.2,\n",
    "    color=\"gray\",\n",
    "    label=\"+/-0.01 delta S\",\n",
    ")\n",
    "ax.set_title(\"Insertion loss\")\n",
    "ax.set_ylabel(\"$|S21|$\")\n",
    "ax.set_xlabel(\"f (GHz)\")\n",
    "ax.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "592b34f3-2a46-4dd3-88d2-8d18320dc13e",
   "metadata": {},
   "source": [
    "In controlled testing, the RF solver is able to solve this relatively large model in about 3.5 minutes on two A100 GPUs.\n",
    "\n",
    "For comparison, this problem took about 1 hour to solve using the commercial FIT software, and close to 12 hours using the commercial FEM software. Benchmarking was done using a 20-core desktop workstation with 256 GB of RAM. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83280c6d-d9c1-47c8-b4fa-8c66a190f8c0",
   "metadata": {},
   "source": [
    "Below, we plot `Ex` in the signal plane at maximum frequency (f = 70 GHz)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "c89580d6-691a-4ebb-ade9-a9601e904980",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:47:13.348804Z",
     "iopub.status.busy": "2025-12-05T22:47:13.348708Z",
     "iopub.status.idle": "2025-12-05T22:47:13.350241Z",
     "shell.execute_reply": "2025-12-05T22:47:13.349967Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Load sim data for wave port 1\n",
    "sim_data = tcm_3d_data.data[\"WP1@0\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "50a8c717-297d-46bb-8af2-df3712895073",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-05T22:47:13.351579Z",
     "iopub.status.busy": "2025-12-05T22:47:13.351484Z",
     "iopub.status.idle": "2025-12-05T22:47:13.480746Z",
     "shell.execute_reply": "2025-12-05T22:47:13.480286Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Field plot\n",
    "fig, ax = plt.subplots(figsize=(14, 1))\n",
    "ex = sim_data[\"longitudinal field (y=0)\"].Ex.sel(f=f_max, method=\"nearest\")\n",
    "np.real(ex).plot(\n",
    "    x=\"z\",\n",
    "    y=\"x\",\n",
    "    ax=ax,\n",
    ")\n",
    "ax.set_ylim(-25 * mil, 25 * mil)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d4e9a1b3-61e8-4ea9-95b3-9506da46fb45",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "applications": [
   "Microwave and RF devices"
  ],
  "description": "This notebook demonstrates how to simulate a differential stripline in 2D mode analysis and 3D FDTD. Results are compared with commercial benchmarks.",
  "feature_image": "./img/differential_stripline_render.png",
  "features": [
   "Mode analysis",
   "Wave port"
  ],
  "kernelspec": {
   "display_name": "tidy3d_frontend",
   "language": "python",
   "name": "python3"
  },
  "keywords": "differential stripline, stripline, interconnect, high-speed, broadband, waveguide, microwave, 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": "3.13.7"
  },
  "title": "Differential Stripline Benchmark",
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "1b45a9980ffd4775b64275545e69f13c": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_f42eece37d1e4632ad396852aa405e1c",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "
🚶  Waiting for 'mode solver'...\n
\n",
          "text/plain": "\u001b[32m🚶 \u001b[0m \u001b[1;32mWaiting for 'mode solver'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "1de2aec1e5204d75bcd26ebec7012a2c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "57170234034e48bf94f1e5bbe910ad8e": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_99e1163b8b02464f85d720a49582aa1f",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "
↑ modeler.hdf5.gz ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100.0% • 2.9/2.9 kB • ? • 0:00:00\n
\n",
          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34mmodeler.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m2.9/2.9 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "58a5dc4097c84915be39087a5d1b3c40": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "5a5378bf15b0466cacc2bf1876a3fb11": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_1de2aec1e5204d75bcd26ebec7012a2c",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "
↓ cm_data.hdf5.gz ━━━━━━━━━━━━━━━━━━ 100.0% • 68.6/68.6 MB • 41.8 MB/s • 0:00:00\n
\n",
          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mcm_data.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m68.6/68.6 MB\u001b[0m • \u001b[31m41.8 MB/s\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "683102d7cd9c44b7893eca142036e757": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "7687e4098931428a81868d4f5132320a": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_683102d7cd9c44b7893eca142036e757",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "
Best weighted RMS error: 0.00018 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00\n
\n",
          "text/plain": "Best weighted RMS error: 0.00018 \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "8a35776cebdd43089c83a0f3e2c41e7c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "988306fb497141b281a61b2bb377a396": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_a9e24bd3f65441b995d4d647f1721117",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "
↓ mode_solver_data.hdf5.gz ━━━━━━━━━━ 100.0% • 76.7/76.7   • 59.0 MB/s • 0:00:00\n                                               MB                               \n
\n",
          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mmode_solver_data.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m76.7/76.7  \u001b[0m • \u001b[31m59.0 MB/s\u001b[0m • \u001b[36m0:00:00\u001b[0m\n                                               \u001b[32mMB         \u001b[0m                      \n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "99e1163b8b02464f85d720a49582aa1f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "a9e24bd3f65441b995d4d647f1721117": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "ac6f0fe2fee8453ab6d0162586964a6c": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_58a5dc4097c84915be39087a5d1b3c40",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "
↑ mode_solver.hdf5.gz ━━━━━━━━━━━━━━━━━━━━━━━━ 100.0% • 2.7/2.7 kB • ? • 0:00:00\n
\n",
          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34mmode_solver.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m2.7/2.7 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "ae647ddd4a69471fa77c3052ec32da67": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_8a35776cebdd43089c83a0f3e2c41e7c",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "
Run Total ━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:04:22\n  WP1@0   ━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:03:32\n  WP2@0   ━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:04:22\n
\n",
          "text/plain": "Run Total \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:04:22\u001b[0m\n  WP1@0   \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:03:32\u001b[0m\n  WP2@0   \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:04:22\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ],
       "tabbable": null,
       "tooltip": null
      }
     },
     "f42eece37d1e4632ad396852aa405e1c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}