{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2x2 MMI power splitter\n",
    "\n",
    "**Note: this notebook is 90% AI-generated.**\n",
    "\n",
    "In this notebook, we will design and simulate a 2x2 Multi-Mode Interference (MMI) power splitter for photonic integrated circuits (PICs). The MMI power splitter is a fundamental component in integrated photonics, providing equal power splitting (50/50) with high efficiency.\n",
    "\n",
    "The design follows standard Silicon-on-Insulator (SOI) platform specifications with cosine S-bends for optimal performance. We will demonstrate the complete simulation workflow including geometry setup using [Photonforge](https://photonforge.simulation.cloud/) and performance evaluation.\n",
    "\n",
    "For more integrated photonic examples such as the 8-Channel mode and polarization demultiplexer, the broadband bi-level taper polarization rotator-splitter, and the broadband directional coupler, please visit our [examples page](https://www.flexcompute.com/tidy3d/examples/).\n",
    "\n",
    "If you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101 tutorials](https://www.flexcompute.com/tidy3d/learning-center/fdtd-101/).\n",
    "\n",
    "FDTD simulations can diverge due to various reasons. If you run into any simulation divergence issues, please follow the steps outlined in our [troubleshooting guide](https://www.flexcompute.com/tidy3d/learning-center/troubleshooting/) to resolve it.\n",
    "\n",
    "<img src=\"./img/mmi_power_splitter_2x2.png\" alt=\"Schematic of the 2x2 MMI Power Splitter\"  width=\"400\"/>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Standard Python Imports\n",
    "\n",
    "We start by importing the necessary libraries for our simulation.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Standard python imports.\n",
    "import matplotlib.pylab as plt\n",
    "import numpy as np\n",
    "import photonforge as pf\n",
    "\n",
    "# Import regular tidy3d.\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MMI Power Splitter Structure\n",
    "\n",
    "The 2x2 MMI power splitter is based on a standard Silicon-on-Insulator (SOI) wafer with a device layer of 220 nm. The MMI section provides multimode interference for equal power splitting, while cosine S-bends route the input/output signals to offset positions for practical device integration.\n",
    "\n",
    "**Key Design Parameters:**\n",
    "- *Material Platform*: Silicon-on-Insulator (SOI)\n",
    "- *Wavelength Range*: 1.5 to 1.6 μm (telecom C-band)\n",
    "- *Design Goal*: Equal power splitting (50/50)\n",
    "\n",
    "The MMI length is designed to achieve optimal interference patterns for equal power splitting around 1.55 micrometers, while the S-bends provide smooth transitions to offset input/output waveguides.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# MMI power splitter setup.\n",
    "wavelength = 1.55  # Center simulation wavelength (um).\n",
    "freq0 = td.C_0 / wavelength  # Central frequency."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Materials.\n",
    "n_si = 3.48  # Silicon refractive index.\n",
    "n_sio2 = 1.44  # SiO2 refractive index.\n",
    "\n",
    "# Material definitions.\n",
    "mat_si = td.Medium(permittivity=n_si**2)  # Silicon waveguide material.\n",
    "mat_sio2 = td.Medium(permittivity=n_sio2**2)  # SiO2 substrate material."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This cell contains all the geometry, sources, monitors, and simulation creation\n",
    "\n",
    "# MMI power splitter dimensions.\n",
    "w_wg = 0.4  # Waveguide width (um).\n",
    "h_si = 0.22  # Silicon layer height (um).\n",
    "w_mmi = 1.0  # MMI section width (um).\n",
    "l_mmi = 3.0  # MMI section length (um).\n",
    "gap = 0.2  # Gap between output waveguides (um).\n",
    "\n",
    "# Waveguide lengths.\n",
    "l_input = 2.0  # Input waveguide length (um).\n",
    "l_output = 3.0  # Output waveguide length (um).\n",
    "\n",
    "# S-bend parameters.\n",
    "s_bend_offset = 1.0  # Lateral offset for S-bends (um).\n",
    "s_bend_length = 4.0  # Length of S-bend section (um)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Layout generation using [PhotonForge](https://photonforge.simulation.cloud/)\n",
    "\n",
    "We start by creating the layout using PhotonForge’s layout capabilities. In addition to layout generation, PhotonForge also provides a complete set of tools for photonic design automation, including PDK integration, parametric components, connectivity management, and technology definitions. You can check the many applications of this powerful tool [here](https://docs.flexcompute.com/projects/photonforge/en/latest/examples.html).\n",
    "\n",
    "We start by defining a simple [pf.Rectangle](https://docs.flexcompute.com/projects/photonforge/en/latest/_autosummary/photonforge.Rectangle.html) structure.\n",
    "\n",
    "Next, we use the [pf.Path](https://docs.flexcompute.com/projects/photonforge/en/latest/_autosummary/photonforge.Path.html) object, which accepts the arguments <i>origin</i> and <i>width</i>. This object can then be used to create s-bends with the built-in <i>s_bend</i> method, as well as straight sections with the <i>segment</i> method.\n",
    "\n",
    "Finally, we use [pf.boolean](https://docs.flexcompute.com/projects/photonforge/en/latest/_autosummary/photonforge.boolean.html) to combine the structures into a single polygon, and define the Tidy3D geometry as a [PolySlab](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PolySlab.html) object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def make_mmi_shape(\n",
    "    l_mmi,\n",
    "    w_mmi,\n",
    "    w_wg,\n",
    "    s_bend_length,\n",
    "    s_bend_offset,\n",
    "    center=(0, 0),\n",
    "    slab_bounds=(-0.11, 0.11),\n",
    "    sidewall_angle=0,\n",
    "    reference_plane=\"top\",\n",
    "):\n",
    "\n",
    "    mmi = pf.Rectangle(size=(l_mmi, w_mmi))\n",
    "\n",
    "    x_out = l_mmi / 2\n",
    "    y_out = w_mmi / 2 - w_wg / 2\n",
    "\n",
    "    bend_out_up = pf.Path(origin=(x_out, y_out), width=w_wg)\n",
    "    bend_out_up.s_bend((s_bend_length, s_bend_offset), relative=True)\n",
    "    bend_out_up.segment((10, 0), relative=True)\n",
    "\n",
    "    bend_out_down = bend_out_up.copy().mirror()\n",
    "    bend_in_up = bend_out_up.copy().mirror((0, 1))\n",
    "    bend_in_down = bend_out_down.copy().mirror((0, 1))\n",
    "\n",
    "    polygons = pf.boolean(\n",
    "        [\n",
    "            mmi,\n",
    "            bend_out_up,\n",
    "            bend_out_down,\n",
    "            bend_in_up,\n",
    "            bend_in_down,\n",
    "        ],\n",
    "        [],\n",
    "        \"+\",\n",
    "    )\n",
    "\n",
    "    assert len(polygons) == 1, \"Expected a single polygon for the union.\"\n",
    "    polygon = polygons[0]\n",
    "    assert len(polygon.holes) == 0, \"Expected no holes.\"\n",
    "\n",
    "    polygon.translate(center)\n",
    "\n",
    "    geometry = td.PolySlab(\n",
    "        vertices=polygon.vertices,\n",
    "        axis=2,\n",
    "        slab_bounds=slab_bounds,\n",
    "        sidewall_angle=sidewall_angle,\n",
    "        reference_plane=reference_plane,\n",
    "    )\n",
    "\n",
    "    return geometry\n",
    "\n",
    "\n",
    "geometry = make_mmi_shape(l_mmi, w_mmi, w_wg, s_bend_length, s_bend_offset)\n",
    "mmi_structure = td.Structure(geometry=geometry, medium=mat_si)\n",
    "ax = mmi_structure.plot(z=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Complete MMI Power Splitter Simulation Setup\n",
    "\n",
    "Now we create the complete 2x2 MMI power splitter simulation with x-axis propagation. The simulation includes the MMI section, input/output waveguides, cosine S-bends, sources, and monitors.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate optimized simulation domain size for x-axis propagation.\n",
    "x_min = -1.5 - 3.0  # -4.5 um\n",
    "x_max = 5.5 + 3.0  # 8.5 um\n",
    "total_length = x_max - x_min  # 13.0 um\n",
    "total_width = w_mmi + 4.0  # Keep width buffer for offset waveguides\n",
    "total_height = 2.0  # Sufficient for SOI structure\n",
    "sim_size_optimized = (total_length, total_width, total_height)\n",
    "\n",
    "wavelengths = np.arange(1.5, 1.61, 0.01)  # 1.5 to 1.6 μm with 10 nm steps\n",
    "frequencies = td.C_0 / wavelengths\n",
    "\n",
    "# 9. Mode source at the upper input waveguide (x-axis propagation).\n",
    "source_position = (-6, 1.3, 0)\n",
    "source_size = (0, 6 * w_wg, 6 * h_si)\n",
    "mode_source = td.ModeSource(\n",
    "    center=source_position,\n",
    "    size=source_size,\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 10),\n",
    "    direction=\"+\",\n",
    "    mode_spec=td.ModeSpec(num_modes=1),\n",
    "    mode_index=0,\n",
    ")\n",
    "\n",
    "# 10. Mode monitors at the output waveguides (x-axis propagation).\n",
    "monitor_1_position = (l_mmi / 2 + s_bend_length + 0.5, w_wg / 2 + gap / 2 + s_bend_offset, 0)\n",
    "monitor_1_size = (0, 6 * w_wg, 6 * h_si)\n",
    "mode_monitor_1 = td.ModeMonitor(\n",
    "    center=monitor_1_position,\n",
    "    size=monitor_1_size,\n",
    "    freqs=frequencies,\n",
    "    mode_spec=td.ModeSpec(num_modes=1),\n",
    "    name=\"mode_output_1\",\n",
    ")\n",
    "\n",
    "monitor_2_position = (l_mmi / 2 + s_bend_length + 0.5, -w_wg / 2 - gap / 2 - s_bend_offset, 0)\n",
    "monitor_2_size = (0, 6 * w_wg, 6 * h_si)\n",
    "mode_monitor_2 = td.ModeMonitor(\n",
    "    center=monitor_2_position,\n",
    "    size=monitor_2_size,\n",
    "    freqs=frequencies,\n",
    "    mode_spec=td.ModeSpec(num_modes=1),\n",
    "    name=\"mode_output_2\",\n",
    ")\n",
    "\n",
    "# 11. Field monitor at xy plane - record fields at specific wavelengths (x-axis propagation).\n",
    "field_freqs = [td.C_0 / 1.55, td.C_0 / 1.58]  # 1.55 and 1.58 um\n",
    "field_monitor = td.FieldMonitor(\n",
    "    center=(0, 0, 0), size=(td.inf, td.inf, 0), freqs=field_freqs, name=\"field_xy\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 12. Create the complete simulation.\n",
    "sim_mmi = td.Simulation(\n",
    "    size=sim_size_optimized,\n",
    "    structures=[mmi_structure],\n",
    "    sources=[mode_source],\n",
    "    monitors=[mode_monitor_1, mode_monitor_2, field_monitor],\n",
    "    run_time=1e-12,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "    medium=mat_sio2,\n",
    "    grid_spec=td.GridSpec(\n",
    "        grid_x=td.AutoGrid(min_steps_per_wvl=20),\n",
    "        grid_y=td.AutoGrid(min_steps_per_wvl=20),\n",
    "        grid_z=td.AutoGrid(min_steps_per_wvl=20),\n",
    "        wavelength=wavelength,\n",
    "    ),\n",
    "    symmetry=(0, 0, 0),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation Visualization\n",
    "\n",
    "Let's visualize the complete MMI power splitter setup to verify the geometry and propagation direction.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Simulation Setup Visualization - XY Setup Plane\n",
    "fig_xy = sim_mmi.plot(z=0)  # XY cross-section at z=0 (MMI center) - shows complete setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"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\" ></div>\n",
       "    <script>\n",
       "        \n",
       "        /**\n",
       "        * Simulation Viewer Injector\n",
       "        *\n",
       "        * Monitors the document for elements being added in the form:\n",
       "        *\n",
       "        *    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"{...}\" />\n",
       "        *\n",
       "        * This script will then inject an iframe to the viewer application, and pass it the simulation data\n",
       "        * via the postMessage API on request. The script may be safely included multiple times, with only the\n",
       "        * configuration of the first started script (e.g. viewer URL) applying.\n",
       "        *\n",
       "        */\n",
       "        (function() {\n",
       "            const TARGET_CLASS = \"simulation-viewer\";\n",
       "            const ACTIVE_CLASS = \"simulation-viewer-active\";\n",
       "            const VIEWER_URL = \"https://tidy3d.simulation.cloud/simulation-viewer\";\n",
       "\n",
       "            class SimulationViewerInjector {\n",
       "                constructor() {\n",
       "                    for (var node of document.getElementsByClassName(TARGET_CLASS)) {\n",
       "                        this.injectViewer(node);\n",
       "                    }\n",
       "\n",
       "                    // Monitor for newly added nodes to the DOM\n",
       "                    this.observer = new MutationObserver(this.onMutations.bind(this));\n",
       "                    this.observer.observe(document.body, {childList: true, subtree: true});\n",
       "                }\n",
       "\n",
       "                onMutations(mutations) {\n",
       "                    for (var mutation of mutations) {\n",
       "                        if (mutation.type === 'childList') {\n",
       "                            /**\n",
       "                            * Have found that adding the element does not reliably trigger the mutation observer.\n",
       "                            * It may be the case that setting content with innerHTML does not trigger.\n",
       "                            *\n",
       "                            * It seems to be sufficient to re-scan the document for un-activated viewers\n",
       "                            * whenever an event occurs, as Jupyter triggers multiple events on cell evaluation.\n",
       "                            */\n",
       "                            var viewers = document.getElementsByClassName(TARGET_CLASS);\n",
       "                            for (var node of viewers) {\n",
       "                                this.injectViewer(node);\n",
       "                            }\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "\n",
       "                injectViewer(node) {\n",
       "                    // (re-)check that this is a valid simulation container and has not already been injected\n",
       "                    if (node.classList.contains(TARGET_CLASS) && !node.classList.contains(ACTIVE_CLASS)) {\n",
       "                        // Mark node as injected, to prevent re-runs\n",
       "                        node.classList.add(ACTIVE_CLASS);\n",
       "\n",
       "                        var uuid;\n",
       "                        if (window.crypto && window.crypto.randomUUID) {\n",
       "                            uuid = window.crypto.randomUUID();\n",
       "                        } else {\n",
       "                            uuid = \"\" + Math.random();\n",
       "                        }\n",
       "\n",
       "                        var frame = document.createElement(\"iframe\");\n",
       "                        frame.width = node.dataset.width || 800;\n",
       "                        frame.height = node.dataset.height || 800;\n",
       "                        frame.style.cssText = `width:${frame.width}px;height:${frame.height}px;max-width:none;border:0;display:block`\n",
       "                        frame.src = VIEWER_URL + \"?uuid=\" + uuid;\n",
       "\n",
       "                        var postMessageToViewer;\n",
       "                        postMessageToViewer = event => {\n",
       "                            if(event.data.type === 'viewer' && event.data.uuid===uuid){\n",
       "                                frame.contentWindow.postMessage({ type: 'jupyter', uuid, value: node.dataset.simulation, fileType: 'hdf5'}, '*');\n",
       "\n",
       "                                // Run once only\n",
       "                                window.removeEventListener('message', postMessageToViewer);\n",
       "                            }\n",
       "                        };\n",
       "                        window.addEventListener(\n",
       "                            'message',\n",
       "                            postMessageToViewer,\n",
       "                            false\n",
       "                        );\n",
       "\n",
       "                        node.appendChild(frame);\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            if (!window.simulationViewerInjector) {\n",
       "                window.simulationViewerInjector = new SimulationViewerInjector();\n",
       "            }\n",
       "        })();\n",
       "    \n",
       "    </script>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 3D Visualization\n",
    "fig_3d = sim_mmi.plot_3d()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cost Estimation\n",
    "\n",
    "Before running the simulation, let's estimate the computational cost."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:12:14 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'mmi_2x2_cost_estimation'</span> with resource_id            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-1bd22af7-75e7-4c3b-8742-a73826940c73'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:12:14 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'mmi_2x2_cost_estimation'\u001b[0m with resource_id            \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-1bd22af7-75e7-4c3b-8742-a73826940c73'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">7-4c3b-8742-a73826940c73'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=19472;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=598586;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=19472;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=381681;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=19472;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[32m-1bd22af7-75e\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=19472;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[32m7-4c3b-8742-a73826940c73'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-431883bc-afbb-4cc8-a95f-ddfeaeeb059a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=937212;https://tidy3d.simulation.cloud/folders/folder-431883bc-afbb-4cc8-a95f-ddfeaeeb059a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6d7688c1459a4adc8de934cb2b8c51e7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:12:20 -03 </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.077</span>. Minimum cost depends on task     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:12:20 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.077\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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estimated cost: 0.0772 Flex Credits\n"
     ]
    }
   ],
   "source": [
    "# Cost Estimation\n",
    "job = web.Job(simulation=sim_mmi, task_name=\"mmi_2x2_cost_estimation\", verbose=True)\n",
    "cost_info = web.estimate_cost(job.task_id)\n",
    "print(f\"Estimated cost: {cost_info:.4f} Flex Credits\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run Simulation\n",
    "\n",
    "Now we run the simulation to obtain the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:12:21 -03 </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.077</span>. Minimum cost depends on task     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:12:21 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.077\u001b[0m. Minimum cost depends on task     \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:12:23 -03 </span>status = queued                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:12:23 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                    \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>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
       "</pre>\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": "0778ca48320545998630a088dff3675f",
       "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\">11:12:43 -03 </span>starting up solver                                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:12:43 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \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\">11:12:44 -03 </span>running solver                                                     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:12:44 -03\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "71a4d80321844cf3915ba4dd043ea80a",
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      },
      "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\">11:12:56 -03 </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span>%, exiting.                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:12:56 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m36\u001b[0m%, exiting.                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">11:12:57 -03 </span>status = postprocess                                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:12:57 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "40de2d0fd0da4ce297d74ab13efdd489",
       "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\">11:13:01 -03 </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:13:01 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:13:03 -03 </span>View simulation result at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">7-4c3b-8742-a73826940c73'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:13:03 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=587670;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=942714;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=587670;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=837669;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=587670;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[4;34m-1bd22af7-75e\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=587670;https://tidy3d.simulation.cloud/workbench?taskId=fdve-1bd22af7-75e7-4c3b-8742-a73826940c73\u001b\\\u001b[4;34m7-4c3b-8742-a73826940c73'\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": "d04d1900cb9545c79e4156e67f291e3e",
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      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:13:08 -03 </span>Loading simulation from mmi_2x2_results.hdf5                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:13:08 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from mmi_2x2_results.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run Simulation\n",
    "sim_data = job.run(path=\"mmi_2x2_results.hdf5\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Result Analysis\n",
    "\n",
    "Let's analyze the simulation results to evaluate the MMI power splitter performance.\n",
    "\n",
    "**Key Performance Metrics:**\n",
    "\n",
    "- **Power Splitting Ratio**: The fraction of total power that goes to each output port. For an ideal 2x2 MMI power splitter, both outputs should have a splitting ratio of 0.5 (50/50 split).\n",
    "\n",
    "- **Total Power**: The sum of power from both output ports, showing the overall transmission efficiency of the device."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average splitting ratio 1: 0.500\n",
      "Average splitting ratio 2: 0.500\n",
      "Average total power: 0.869\n"
     ]
    }
   ],
   "source": [
    "# Extract mode coefficients from ModeMonitors\n",
    "mode_coeff_1 = sim_data[\"mode_output_1\"].amps.sel(mode_index=0, direction=\"+\")\n",
    "mode_coeff_2 = sim_data[\"mode_output_2\"].amps.sel(mode_index=0, direction=\"+\")\n",
    "\n",
    "# Calculate power splitting\n",
    "power_1 = np.abs(mode_coeff_1) ** 2\n",
    "power_2 = np.abs(mode_coeff_2) ** 2\n",
    "total_power = power_1 + power_2\n",
    "\n",
    "# Calculate splitting ratio\n",
    "splitting_ratio_1 = power_1 / total_power\n",
    "splitting_ratio_2 = power_2 / total_power\n",
    "\n",
    "# Ensure arrays are numpy arrays for consistent indexing\n",
    "splitting_ratio_1 = np.array(splitting_ratio_1)\n",
    "splitting_ratio_2 = np.array(splitting_ratio_2)\n",
    "total_power = np.array(total_power)\n",
    "\n",
    "# Create comprehensive analysis plots\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 4))\n",
    "\n",
    "# Power splitting vs wavelength\n",
    "ax1.plot(wavelengths, splitting_ratio_1, \"b-\", label=\"Output 1\", linewidth=2)\n",
    "ax1.plot(wavelengths, splitting_ratio_2, \"r-\", label=\"Output 2\", linewidth=2)\n",
    "ax1.axhline(y=0.5, color=\"k\", linestyle=\"--\", alpha=0.7, label=\"Ideal 50/50\")\n",
    "ax1.set_xlabel(\"Wavelength (μm)\")\n",
    "ax1.set_ylabel(\"Power Splitting Ratio\")\n",
    "ax1.set_title(\"MMI Power Splitting vs Wavelength\")\n",
    "ax1.legend()\n",
    "ax1.grid(True, alpha=0.3)\n",
    "\n",
    "# Total power vs wavelength\n",
    "ax2.plot(wavelengths, total_power, \"g-\", linewidth=2)\n",
    "ax2.set_xlabel(\"Wavelength (μm)\")\n",
    "ax2.set_ylabel(\"Total Power\")\n",
    "ax2.set_title(\"Total Transmitted Power vs Wavelength\")\n",
    "ax2.grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Print key performance metrics\n",
    "print(f\"Average splitting ratio 1: {splitting_ratio_1.mean():.3f}\")\n",
    "print(f\"Average splitting ratio 2: {splitting_ratio_2.mean():.3f}\")\n",
    "print(f\"Average total power: {total_power.mean():.3f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Power Splitting Performance Analysis:**\n",
    "\n",
    "The power splitting ratio plot reveals several important characteristics of the MMI power splitter:\n",
    "\n",
    "- **Optimal Operating Wavelength**: The device achieves perfect 50/50 splitting at approximately 1.58 μm, where both output curves intersect the ideal 50/50 line.\n",
    "\n",
    "- **Wavelength Dependence**: The splitting ratio shows significant wavelength dependence:\n",
    "  - At shorter wavelengths (1.50 μm): Output 2 receives ~62% of power, Output 1 receives ~37%\n",
    "  - At longer wavelengths (1.60 μm): Output 1 receives ~54% of power, Output 2 receives ~46%\n",
    "\n",
    "- **Design Implications**: This wavelength dependence is typical for MMI devices and can be optimized by adjusting the MMI length, width, or using apodization techniques for broader bandwidth performance."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Field Intensity Analysis\n",
    "\n",
    "Finally, let's examine the field intensity distribution at specific wavelengths in the XY plane to understand the light propagation through the MMI."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x300 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a 2x1 subplot for the two wavelengths.\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 3))\n",
    "\n",
    "# Plot field intensity at 1.55 um using Tidy3D's built-in method.\n",
    "sim_data.plot_field(\"field_xy\", \"E\", val=\"abs^2\", f=td.C_0 / 1.55, ax=axes[0])\n",
    "axes[0].set_title(\"Field Intensity at 1.55 μm (XY plane)\")\n",
    "\n",
    "# Plot field intensity at 1.58 um using Tidy3D's built-in method.\n",
    "sim_data.plot_field(\"field_xy\", \"E\", val=\"abs^2\", f=td.C_0 / 1.58, ax=axes[1])\n",
    "axes[1].set_title(\"Field Intensity at 1.58 μm (XY plane)\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Passive photonic integrated circuit components"
  ],
  "description": "This notebook demonstrates the FDTD simulation of a 2x2 MMI Power Splitter using Tidy3D.",
  "feature_image": "./img/mmi_power_splitter_2x2.png",
  "features": [],
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "keywords": "mmi, power splitter, photonic integrated circuits, Tidy3D, FDTD",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  },
  "title": "2x2 MMI Power Splitter | Flexcompute"
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
