{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "da3f0190",
   "metadata": {},
   "source": [
    "# Waveguide Y junction"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eab8c7bd",
   "metadata": {},
   "source": [
    "Power splitters such as Y-junctions are widely used in photonic integrated circuits across different applications. When designing a power splitter, we aim to achieve a flat broadband response, low insertion loss, and compact footprint. At the same time, the design needs to comply with the fabrication resolution and tolerance.\n",
    "\n",
    "In this example, we demonstrate the modeling of a Y-junction for integrated photonics. The designed device shows an average insertion loss below 0.2 dB in the wavelength range of 1500 nm to 1600 nm. At the same time, it has a small footprint. The junction area is smaller than 2 $\\mu m$ by 2 $\\mu m$, much smaller than the typical power splitters based on multimode interference devices. The design is adapted from [Yi Zhang, Shuyu Yang, Andy Eu-Jin Lim, Guo-Qiang Lo, Christophe Galland, Tom Baehr-Jones, and Michael Hochberg, \"A compact and low loss Y-junction for submicron silicon waveguide,\" Opt. Express 21, 1310-1316 (2013)](https://opg.optica.org/oe/fulltext.cfm?uri=oe-21-1-1310).\n",
    "\n",
    "<img src=\"img/y_junction_schematic.png\" width=\"600\" alt=\"Schematic of the waveguide Y junction\">\n",
    "\n",
    "For more integrated photonic examples such as the [8-Channel mode and polarization de-multiplexer](https://www.flexcompute.com/tidy3d/examples/notebooks/8ChannelDemultiplexer/), the [broadband bi-level taper polarization rotator-splitter](https://www.flexcompute.com/tidy3d/examples/notebooks/BilevelPSR/), and the [broadband directional coupler](https://www.flexcompute.com/tidy3d/examples/notebooks/BroadbandDirectionalCoupler/), 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](https://www.flexcompute.com/fdtd101/) tutorials. \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/examples/notebooks/DivergedFDTDSimulation/) to resolve it. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ad43045e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:04.429845Z",
     "iopub.status.busy": "2025-05-15T10:33:04.429764Z",
     "iopub.status.idle": "2025-05-15T10:33:05.697757Z",
     "shell.execute_reply": "2025-05-15T10:33:05.697146Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import photonforge as pf\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n",
    "from tidy3d.plugins.mode import ModeSolver"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "128b718e",
   "metadata": {},
   "source": [
    "## Simulation Setup  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c26dafaa",
   "metadata": {},
   "source": [
    "Define simulation wavelength range to be 1.5 $\\mu m$ to 1.6 $\\mu m$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3a2dd129",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:05.699326Z",
     "iopub.status.busy": "2025-05-15T10:33:05.699147Z",
     "iopub.status.idle": "2025-05-15T10:33:05.701652Z",
     "shell.execute_reply": "2025-05-15T10:33:05.701266Z"
    }
   },
   "outputs": [],
   "source": [
    "lda0 = 1.55  # central wavelength\n",
    "freq0 = td.C_0 / lda0  # central frequency\n",
    "ldas = np.linspace(1.5, 1.6, 101)  # wavelength range\n",
    "freqs = td.C_0 / ldas  # frequency range\n",
    "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))  # width of the source frequency range"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "946d0a45",
   "metadata": {},
   "source": [
    "In this model, the Y-junction is made of silicon. The top cladding is made of silicon oxide. We will directly use the silicon and oxide media from Tidy3D's [material library](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/material_library.html#). More specifically, we use the data from the widely used Handbook of Optical Constants of Solids by Palik. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b90f342c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:05.703000Z",
     "iopub.status.busy": "2025-05-15T10:33:05.702842Z",
     "iopub.status.idle": "2025-05-15T10:33:05.704787Z",
     "shell.execute_reply": "2025-05-15T10:33:05.704519Z"
    }
   },
   "outputs": [],
   "source": [
    "si = td.material_library[\"cSi\"][\"Palik_Lossless\"]\n",
    "\n",
    "sio2 = td.material_library[\"SiO2\"][\"Palik_Lossless\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "473f2133",
   "metadata": {},
   "source": [
    "The junction is discretized into 13 segments. Each segment is a tapper with the given widths. The optimum design is obtained by optimizing the 13 width parameters using the Particle Swarm Optimization algorithm. For the sake of simplicity, in this notebook, we skip the optimization procedure and only present the optimized result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c67cbbf5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:05.705939Z",
     "iopub.status.busy": "2025-05-15T10:33:05.705814Z",
     "iopub.status.idle": "2025-05-15T10:33:05.707791Z",
     "shell.execute_reply": "2025-05-15T10:33:05.707516Z"
    }
   },
   "outputs": [],
   "source": [
    "t = 0.22  # thickness of the silicon layer\n",
    "\n",
    "# width of the 13 segments\n",
    "w1 = 0.5\n",
    "w2 = 0.5\n",
    "w3 = 0.6\n",
    "w4 = 0.7\n",
    "w5 = 0.9\n",
    "w6 = 1.26\n",
    "w7 = 1.4\n",
    "w8 = 1.4\n",
    "w9 = 1.4\n",
    "w10 = 1.4\n",
    "w11 = 1.31\n",
    "w12 = 1.2\n",
    "w13 = 1.2\n",
    "\n",
    "l_in = 1  # input waveguide length\n",
    "l_junction = 2  # length of the junction\n",
    "l_bend = 6  # horizontal length of the waveguide bend\n",
    "h_bend = 2  # vertical offset of the waveguide bend\n",
    "l_out = 1  # output waveguide length\n",
    "inf_eff = 100  # effective infinity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98ae6d2c",
   "metadata": {},
   "source": [
    "First, define the junction structure by using a [PolySlab](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PolySlab.html). The vertices are given by the widths of the segments defined above. If a smooth curve is desirable, one can interpolate the vertices to a finer grid using a spline, for example. \n",
    "\n",
    "Before proceeding further to construct other structures, we can use the `plot` method to inspect the geometry. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f1bd7cba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:05.709084Z",
     "iopub.status.busy": "2025-05-15T10:33:05.708934Z",
     "iopub.status.idle": "2025-05-15T10:33:05.773877Z",
     "shell.execute_reply": "2025-05-15T10:33:05.773484Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(l_in, l_in + l_junction, 13)  # x coordinates of the top edge vertices\n",
    "y = np.array(\n",
    "    [w1, w2, w3, w4, w5, w6, w7, w8, w9, w10, w11, w12, w13]\n",
    ")  # y coordinates of the top edge vertices\n",
    "\n",
    "# using concatenate to include bottom edge vertices\n",
    "x = np.concatenate((x, np.flipud(x)))\n",
    "y = np.concatenate((y / 2, -np.flipud(y / 2)))\n",
    "\n",
    "# stacking x and y coordinates to form vertices pairs\n",
    "vertices = np.transpose(np.vstack((x, y)))\n",
    "\n",
    "junction = td.Structure(\n",
    "    geometry=td.PolySlab(vertices=vertices, axis=2, slab_bounds=(0, t)), medium=si\n",
    ")\n",
    "junction.plot(z=t / 2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f33fc2d8",
   "metadata": {},
   "source": [
    "For the output waveguide bends, we use S bend sine waveguides, which are described by the function\n",
    "$$\n",
    "y = \\frac{x h_{\\text{bend}}}{l_{\\text{bend}}} - \\frac{h_{\\text{bend}}}{2\\pi} \\sin\\left(\\frac{2\\pi x}{l_{\\text{bend}}}\\right).\n",
    "$$\n",
    "\n",
    "The easiest way is using PhotonForge’s layout capabilities. 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",
    "In this example, the waveguide bends are defined using 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>. The full trajectory of the bend is defined by assigning a sequence of points to the path, reproducing the desired smooth S-shaped transition.\n",
    "\n",
    "The straight output waveguide is defined separately as another [pf.Path](https://docs.flexcompute.com/projects/photonforge/en/latest/_autosummary/photonforge.Path.html) object and created with the <i>segment</i> method, ensuring continuity after the S-bend.\n",
    "\n",
    "Finally, we use [pf.boolean](https://docs.flexcompute.com/projects/photonforge/en/latest/_autosummary/photonforge.boolean.html) to combine the structures into polygons, 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": 6,
   "id": "3972962d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_start = l_in + l_junction  # starting x-position of the bends\n",
    "\n",
    "dx = l_bend  # horizontal length of the S-bend\n",
    "dy = h_bend  # vertical offset of the S-bend\n",
    "\n",
    "y0 = w13 / 2 - w1 / 2  # initial vertical position (top waveguide center)\n",
    "\n",
    "# create top S-bend + straight in a single path\n",
    "bend_up = pf.Path(origin=(x_start, y0), width=w1)\n",
    "bend_up.s_bend((dx, dy), relative=True)\n",
    "bend_up.segment((inf_eff, 0), relative=True)\n",
    "\n",
    "# create bottom by mirroring\n",
    "bend_down = bend_up.copy().mirror()\n",
    "\n",
    "# boolean union of all paths into polygons\n",
    "polygons = pf.boolean([bend_up, bend_down], [], \"+\")\n",
    "\n",
    "# convert polygons into Tidy3D PolySlab geometries\n",
    "geoms = [td.PolySlab(vertices=p.vertices, axis=2, slab_bounds=(0, t)) for p in polygons]\n",
    "\n",
    "# create Tidy3D structures\n",
    "wg_bend_1 = td.Structure(geometry=geoms[0], medium=si)\n",
    "wg_bend_2 = td.Structure(geometry=geoms[1], medium=si)\n",
    "\n",
    "# plot the top waveguide bend to visualize\n",
    "ax = wg_bend_1.plot(z=t / 2)\n",
    "ax.set_xlim(2, 10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fecdf772",
   "metadata": {},
   "source": [
    "Lastly, define the straight input waveguide using [Box](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Box.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "37f3f2e2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:05.827940Z",
     "iopub.status.busy": "2025-05-15T10:33:05.827853Z",
     "iopub.status.idle": "2025-05-15T10:33:05.830031Z",
     "shell.execute_reply": "2025-05-15T10:33:05.829650Z"
    }
   },
   "outputs": [],
   "source": [
    "# straight input waveguide\n",
    "wg_in = td.Structure(\n",
    "    geometry=td.Box.from_bounds(rmin=(-inf_eff, -w1 / 2, 0), rmax=(l_in, w1 / 2, t)),\n",
    "    medium=si,\n",
    ")\n",
    "\n",
    "# the entire model is the collection of all structures defined so far\n",
    "y_junction = [wg_in, junction, wg_bend_1, wg_bend_2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "051768d5",
   "metadata": {},
   "source": [
    "Define the simulation domain. Here we ensure sufficient buffer spacing in each direction. In general, we want to make sure that the structure is at least half a wavelength away from the domain boundaries unless it goes into the PML."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f0cef4aa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:05.831117Z",
     "iopub.status.busy": "2025-05-15T10:33:05.831039Z",
     "iopub.status.idle": "2025-05-15T10:33:05.832818Z",
     "shell.execute_reply": "2025-05-15T10:33:05.832554Z"
    }
   },
   "outputs": [],
   "source": [
    "Lx = l_in + l_junction + l_out + l_bend  # simulation domain size in x direction\n",
    "Ly = w13 + 2 * h_bend + 1.5 * lda0  # simulation domain size in y direction\n",
    "Lz = 10 * t  # simulation domain size in z direction\n",
    "sim_size = (Lx, Ly, Lz)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4eaa0e1e",
   "metadata": {},
   "source": [
    "We will use a [ModeSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeSource.html) to excite the input waveguide using the fundamental TE mode. \n",
    "\n",
    "A [ModeMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeMonitor.html) is placed at the top output waveguide to measure the transmission. A [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldMonitor.html) is added to the xy plane to visualize the power flow."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "dbf57f31",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:05.833899Z",
     "iopub.status.busy": "2025-05-15T10:33:05.833826Z",
     "iopub.status.idle": "2025-05-15T10:33:05.836314Z",
     "shell.execute_reply": "2025-05-15T10:33:05.836085Z"
    }
   },
   "outputs": [],
   "source": [
    "# add a mode source as excitation\n",
    "mode_spec = td.ModeSpec(num_modes=1, target_neff=3.5)\n",
    "mode_source = td.ModeSource(\n",
    "    center=(l_in / 2, 0, t / 2),\n",
    "    size=(0, 4 * w1, 6 * t),\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "    direction=\"+\",\n",
    "    mode_spec=mode_spec,\n",
    "    mode_index=0,\n",
    ")\n",
    "\n",
    "# add a mode monitor to measure transmission at the output waveguide\n",
    "mode_monitor = td.ModeMonitor(\n",
    "    center=(l_in + l_junction + l_bend + l_out / 2, w13 / 2 - w1 / 2 + h_bend, t / 2),\n",
    "    size=(0, 4 * w1, 6 * t),\n",
    "    freqs=freqs,\n",
    "    mode_spec=mode_spec,\n",
    "    name=\"mode\",\n",
    ")\n",
    "\n",
    "# add a field monitor to visualize field distribution at z=t/2\n",
    "field_monitor = td.FieldMonitor(\n",
    "    center=(0, 0, t / 2), size=(td.inf, td.inf, 0), freqs=[freq0], name=\"field\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "725eee9e",
   "metadata": {},
   "source": [
    "Set up the simulation with the previously defined structures, source, and monitors. All boundaries are set to PML to mimic infinite open space. Since the top and bottom claddings are silicon oxide, we will set the medium of the background to silicon oxide. \n",
    "\n",
    "In principle, we can impose symmetry to reduce the computational load. Since this model is relatively small and quick to solve anyway, we will simply model the whole device without using symmetry. To use symmetry, we just need to set `symmetry=(0,-1,1)` in the [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html) object initiation. To learn more about using symmetry, please refer to the dedicated [tutorial](https://www.flexcompute.com/tidy3d/examples/notebooks/Symmetry/).\n",
    "\n",
    "Using an [automatic nonuniform grid](https://www.flexcompute.com/tidy3d/examples/notebooks/AutoGrid/) is the most efficient and convenient. We set `min_steps_per_wvl=20` to achieve a very accurate result while still keeping the simulation cost at a minimum."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9a4ec279",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:05.837317Z",
     "iopub.status.busy": "2025-05-15T10:33:05.837241Z",
     "iopub.status.idle": "2025-05-15T10:33:05.910412Z",
     "shell.execute_reply": "2025-05-15T10:33:05.910003Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "run_time = 5e-13  # simulation run time\n",
    "\n",
    "# construct simulation\n",
    "sim = td.Simulation(\n",
    "    center=(Lx / 2, 0, 0),\n",
    "    size=sim_size,\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=20, wavelength=lda0),\n",
    "    structures=y_junction,\n",
    "    sources=[mode_source],\n",
    "    monitors=[mode_monitor, field_monitor],\n",
    "    run_time=run_time,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "    medium=sio2,\n",
    ")\n",
    "\n",
    "sim.plot(z=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0b7c40f",
   "metadata": {},
   "source": [
    "To have a better visualization, we can also plot the simulation in 3D."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9aefe40d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:05.911536Z",
     "iopub.status.busy": "2025-05-15T10:33:05.911450Z",
     "iopub.status.idle": "2025-05-15T10:33:05.918650Z",
     "shell.execute_reply": "2025-05-15T10:33:05.918361Z"
    }
   },
   "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": [
    "sim.plot_3d()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7f50958",
   "metadata": {},
   "source": [
    "Before submitting the simulation to the server, it is a good practice to visualize the mode profile at the [ModeSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeSource.html) to ensure we are launching the fundamental TE mode. To do so, we will use the [ModeSolver](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.mode.ModeSolver.html) plugin, which solves for the mode profile on your local computer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "da2af982",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:05.919710Z",
     "iopub.status.busy": "2025-05-15T10:33:05.919636Z",
     "iopub.status.idle": "2025-05-15T10:33:06.201904Z",
     "shell.execute_reply": "2025-05-15T10:33:06.201498Z"
    }
   },
   "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\">11:37:00 -03 </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Use the remote mode solver with subpixel averaging for    </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">better accuracy through </span><span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d.web.run(...)'</span><span style=\"color: #800000; text-decoration-color: #800000\"> or the deprecated    </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d.plugins.mode.web.run(...)'</span><span style=\"color: #800000; text-decoration-color: #800000\">.                                </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:37:00 -03\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Use the remote mode solver with subpixel averaging for    \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31mbetter accuracy through \u001b[0m\u001b[32m'tidy3d.web.run\u001b[0m\u001b[32m(\u001b[0m\u001b[32m...\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m\u001b[31m or the deprecated    \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'tidy3d.plugins.mode.web.run\u001b[0m\u001b[32m(\u001b[0m\u001b[32m...\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m\u001b[31m.                                \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mode_solver = ModeSolver(\n",
    "    simulation=sim,\n",
    "    plane=td.Box(center=mode_source.center, size=mode_source.size),\n",
    "    mode_spec=mode_spec,\n",
    "    freqs=[freq0],\n",
    ")\n",
    "mode_data = mode_solver.solve()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c0322c9",
   "metadata": {},
   "source": [
    "Visualize the mode profile. We confirm that we are exciting the waveguide with the fundamental TE mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a2e49017",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:06.203228Z",
     "iopub.status.busy": "2025-05-15T10:33:06.203128Z",
     "iopub.status.idle": "2025-05-15T10:33:06.441825Z",
     "shell.execute_reply": "2025-05-15T10:33:06.441331Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2, ax3) = plt.subplots(1, 3, tight_layout=True, figsize=(10, 3))\n",
    "abs(mode_data.Ex.isel(mode_index=0)).plot(x=\"y\", y=\"z\", ax=ax1, cmap=\"magma\")\n",
    "abs(mode_data.Ey.isel(mode_index=0)).plot(x=\"y\", y=\"z\", ax=ax2, cmap=\"magma\")\n",
    "abs(mode_data.Ez.isel(mode_index=0)).plot(x=\"y\", y=\"z\", ax=ax3, cmap=\"magma\")\n",
    "\n",
    "ax1.set_title(\"|Ex(x, y)|\")\n",
    "ax1.set_aspect(\"equal\")\n",
    "ax2.set_title(\"|Ey(x, y)|\")\n",
    "ax2.set_aspect(\"equal\")\n",
    "ax3.set_title(\"|Ez(x, y)|\")\n",
    "ax3.set_aspect(\"equal\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e904938",
   "metadata": {},
   "source": [
    "Now that we verified all the settings, we are ready to submit the simulation job to the server. Before running the simulation, we can get a cost estimation using `estimate_cost`. This prevents us from accidentally running large jobs that we set up by mistake. The estimated cost is the maximum cost corresponding to running all the time steps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "15e791dd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:06.442842Z",
     "iopub.status.busy": "2025-05-15T10:33:06.442756Z",
     "iopub.status.idle": "2025-05-15T10:33:10.165891Z",
     "shell.execute_reply": "2025-05-15T10:33:10.165395Z"
    }
   },
   "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\">             </span>Loading simulation from local cache. View cached task using web UI \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>at                                                                 \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-f40dbc85-3454-4aa6-b46f-96830081d830\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-f40dbc85-345</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-f40dbc85-3454-4aa6-b46f-96830081d830\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">4-4aa6-b46f-96830081d830'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mLoading simulation from local cache. View cached task using web UI \n",
       "\u001b[2;36m             \u001b[0mat                                                                 \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=591243;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f40dbc85-3454-4aa6-b46f-96830081d830\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=305981;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f40dbc85-3454-4aa6-b46f-96830081d830\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=591243;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f40dbc85-3454-4aa6-b46f-96830081d830\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=4314;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f40dbc85-3454-4aa6-b46f-96830081d830\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=591243;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f40dbc85-3454-4aa6-b46f-96830081d830\u001b\\\u001b[32m-f40dbc85-345\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=591243;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f40dbc85-3454-4aa6-b46f-96830081d830\u001b\\\u001b[32m4-4aa6-b46f-96830081d830'\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\">11:37:03 -03 </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.113</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;36m11:37:03 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.113\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"
    }
   ],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"y_junction\", verbose=True)\n",
    "estimated_cost = web.estimate_cost(job.task_id)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cedcee1e",
   "metadata": {},
   "source": [
    "The cost is reasonable so we can run the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "73df031e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:10.172375Z",
     "iopub.status.busy": "2025-05-15T10:33:10.172313Z",
     "iopub.status.idle": "2025-05-15T10:33:14.498455Z",
     "shell.execute_reply": "2025-05-15T10:33:14.498076Z"
    }
   },
   "outputs": [],
   "source": [
    "sim_data = job.run(path=\"data/simulation_data.hdf5\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fec4554c",
   "metadata": {},
   "source": [
    "## Result Visualization "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17041534",
   "metadata": {},
   "source": [
    "After the simulation is complete, we first inspect the insertion loss. Within this wavelength range, we see that the insertion loss is generally below 0.2 dB."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "04666ade",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:14.514720Z",
     "iopub.status.busy": "2025-05-15T10:33:14.514570Z",
     "iopub.status.idle": "2025-05-15T10:33:14.618303Z",
     "shell.execute_reply": "2025-05-15T10:33:14.617945Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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9UrHF2XFdQTaFE7pqjCAFNECl5Q7tPZmr7SlZ2p6Sre2pWRc9PedttSg+Olg9W4WqR6tQ9YgJVZeoYK4mAjyQn4+XWjerGId4OQUl5UrPO9ejdX4P1+n8c6cZMwtKZXecmzh1f1pelfu1WHRuuojzpoo4P3g5e7oYRC+JIAU0CBn5Jdp2NEtbU7K07WiWdh7LUUm5w2Udi0XqGBGk3rFh6t06VD1bhyme0AQ0SYE2b7WzeV92PJfdYSirsNQ5huv0+WO4zuv5Ontlo8OQMiunl5CqHs8lVUx30ryyJ6tiXq6zE6TaXCZNPdveGIMXQQqoY2fHNm06nKnNRzK16UimDp2+8KqfsAAf9WvTTH1jw9S3TTP1ig1lagEANeJltTh7krpGV72u3WE4p4k4Oy1ERn6Jc7qIX4avcodRcUPw4upduShVTBnhDFeVpzzPPp7fFh7gq/AgXwV7wC2BCFJALTMMQymZhfrx0Bn9eChTPx46o5MXGUjauWWQ+sc1U782zdQ/rpnatQhs8P8BAdB4eFktztN2l+OovBLxbNByToqaXzkxamXbuclSK04xnp0yIiXz8vN0SRXDF5oF+qpZgI/CAnwVVnkPxrDAysfKe2uGBVTcKqpZ5WNd9nwRpIBacCK7SOsOZmj9z2cuGpy8rRb1bB2qgW3DNbBduBLiwhUaQG8TAM9gtZ4bRN+pGusbhqHconKdKShxCVdnl6zKtrOz1WcVlqqw1K5yR81uCXSWv4+Xgq3mbqZdUwQpwA1yisq04ecMrTt4RusOZujQL7q5fbws6hMbpsHtm2tw++bq16YZ0w4AaDIsFotCA3wUGuCj9hHV26a4zO4MWjlFZRX3XSwsU3ZB5WNRqXIKK9qzC8uUXVRxf0aHoYqrGktqFr7MIkgBJpTbHUo6lqO1P53W2p8ytCM1W3aH4XzfapF6tg7TsA7NNbRDC/WPIzgBQE34+XgppvJendXlcFRMlppdWKrUU2d01au1V99ZBCmgmtLzirUm+bRWHzittQdOK7e43OX99hGBuqpjCw3r2EKD2jdXqD+n6gCgLlmtFoX6+yjU30fNfKq+wbq7EKSAS3A4DCUdy9bK/elalZyu3cdzXd4P8fPW8E4tNKJThIZ3alGtuV8AAI0LQQo4T0FJudb+dFor9lWEp4x818GKPVuFalSXCI3qEqk+sWHysnJVHQA0ZQQpNHmncou1fO8pfbfvlNYfPKNS+7mJMINt3hrROUKj4yM1snNEtS4LBgA0HQQpNEkH0/O0bHealu89paRjOS7vxTUP0Nj4lhrXNVIJbcPl6819pwAAF0eQQpNgGIb2nMjV/+1J0ze703Qw/dytDywWqU9smK7u1lLXdGupDhFBTIQJAKgWghQarbPh6atdJ/XVzpMuM+n6eFk0rGMLje8epbFdIxUZ7FePlQIAPBVBCo2KYRjan5anL3ee0Fc7T+rImXPhyc/HqpGdIzShR5TGxLdkegIAwBUjSKFROJJRoM+TTujzpBMup+1s3laNiY/UpF7RGhMfqQBf/pUHALiP6V+VlJQUHT16VIWFhYqIiFD37t1ls3FFE+pOem6xMzztPG/AuK+3VaM6R+i63jEaGx+pQBvhCQBQO2r0C3PkyBG99dZb+uCDD3Ts2DEZxrlbYvj6+uqqq67SzJkzdfPNN8tq5UonuF9BSbn+b0+aPt1+XOsOZujsXVm8rBVjnib3itb4HlEK8eO0HQCg9lmM89NQFR544AG9++67Gj9+vCZPnqyBAwcqJiZG/v7+yszM1O7du7V27Vp98MEH8vLy0uLFizVgwIDarr/W5ebmKjQ0VDk5OQoJCanvcpoku8PQuoMZ+mTbMf3fnlMqKjs37X//uGa6oU+Mru0ZrRZB9IgCACrU1e93tXukAgMDdejQITVv3vyC9yIjIzVmzBiNGTNGTz75pJYtW6bU1NRGEaRQfw6m5+k/W4/rs+3HlZZb7Gxv1yJQN/RppRv6xiiueWA9VggAaOqq3SPVVNEjVbfyisv0RdJJ/XtLqpJSs53tof4++lXvGN3Ur5X6xIYxzxMAoEoNrkeqKqWlpSotLVVQUJA7docmxjAMbT6SpX9vTtXXu046T915WS0a3SVCN/drrTFdI2Xz9qrnSgEAcFXjILV48WJt27ZNgwcPVmJioubPn69XXnlF5eXlGjNmjD744IOLnv4DfimroFQfbzumpZtSdOh0gbO9Q0Sgbh0Qqxv7tubedgCABq1GQeq5557Tc889p2HDhmnp0qX64Ycf9Nlnn+mZZ56R1WrVa6+9pscff1xvvfVWbdULD2cYhjYdztTSTSn6Zlea8wbBAb5euq5XtG4dEKt+bZpx6g4A4BFqFKT++c9/6p133tFtt92mLVu2aNCgQfrwww918803S5J69Oih3/zmN7VSKDxbTmGZPtl+TEs2prhMmNk9JkS3D2qjX/WOUTBTFgAAPEyNglRKSoqGDx8uSUpISJC3t7d69OjhfL9Xr146efKkeyuExzIMQ0nHcrTkx6P6YucJFZed6336Ve8Y3T6ojXq2CqX3CQDgsWoUpMrKylxmL/f19ZWPz7leBG9vb9nt9ottiiakuMyuL3ee1Lvrj2jX8XMzjsdHBStxcJxu6EPvEwCgcajxYPO9e/cqLS1NUuUNYvfvV35+xamajIwM91YHj5KWU6x//XhU729K0ZmCUkkVt2u5rme0EgfHqV8bpi0AADQuNZpHymq1ymKx6GKbnG23WCyNqleKeaSqZhiGtqVka/G6w/pmd5rslfdsiQ71051D4jR1QBuFB/rWc5UAgKamQc4jdfjw4dqqAx6mtNyhb3af1D/WHXGZOHNgu3DdM7Stru7WUt5e3G8RANC41ShIxcXF1VYd8BDZhaVasjFF7204olO5JZIqTt9d3ztG04a1VfeY0HquEACAulPtILVz585q77RXr16mikHDdSSjQP9Yd1gfbTnmnHk8ItimOwfH6fZBbbhhMACgSap2kOrTp4/LOKiqNKYxUk3d1qOZ+tuaQ1q+75TODo3rGh2iGVe103W9YuTrzek7AEDTVe0gdf74qO3bt+uRRx7R3LlzNWTIEEnShg0b9PLLL+vFF190f5WoUw6HoVXJ6Vq45mdtPpLlbB/dJUIzrmqvIR2ac/UdAACqQZA6f3zULbfcotdee00TJ050tvXq1UuxsbF64okndMMNN7i1SNSNMrtDXySd0N/WHFLyqTxJkq+XVTf2baUZI9qpY2RwPVcIAEDDUuN5pCRp165dateu3QXt7dq10969e6+4KNSt4jK7PtySqr+tOaTj2UWSpCCbtxIHtdG9w9upZYhfPVcIAEDDZGqAS9euXbVgwQKVlpY620pLS7VgwQJ17drVbcWdLzMzU4mJiQoJCVFYWJimT5/unAj0Uuv//ve/V5cuXeTv7682bdrogQceUE5OziW3aWpyi8v05qqDGv7CSv3pv3t0PLtILYJ89YcJXbRu3hjNn9iVEAUAQBVM9UgtXLhQkydPVuvWrZ1X6O3cuVMWi0VffPGFWws8KzExUSdPntTy5ctVVlame+65RzNnztTSpUsvuv6JEyd04sQJvfTSS+rWrZuOHj2q3/zmNzpx4oT+85//1EqNniKroFTv/HBY764/oryScklS62b++vWI9rolIVZ+Pl71XCEAAJ6hRjObn6+goEBLlizR/v37JVX0Ut1+++0KDAx0a4GStG/fPnXr1k2bN29WQkKCJGnZsmWaOHGijh07ppiYmGrt56OPPtIdd9yhgoICeXtXL0M2ppnNMwtK9fe1h/Tu+iMqKK24srJTZJB+N7qDrusVIx8m0AQANBINcmbz8wUGBmrmzJnurOWSNmzYoLCwMGeIkqRx48bJarVq48aNuvHGG6u1n7P/MKsKUSUlJSopKXG+zs3NNV94A3Emv0Rvrz2s9zYcUWFlgOoaHaIHx3bUNd2iZLVyBR4AAGZUO0j9+OOPGjx4cLXWLSws1OHDh9W9e3fThZ0vLS1NkZGRLm3e3t4KDw933kD5cjIyMvTss89eNvwtWLBATz/9tOlaG5LMglIt+v6QS4Dq0SpED4zppKu7tWQKAwAArlC1z+XceeedGj9+vD766CMVFBRcdJ29e/fq0UcfVYcOHbR169bL7nPevHmyWCxVLmdPHV6J3NxcTZo0Sd26ddNTTz1V5brz589XTk6Oc0lNTb3iz69rWQWlenHZfl31wkotXPOzCkvt6tkqVO/cnaAvZg3XNd2jCFEAALhBtXuk9u7dq7feekuPP/64br/9dnXu3FkxMTHy8/NTVlaW9u/fr/z8fN1444369ttv1bNnz8vu8+GHH9a0adOqXKd9+/aKiopSenq6S3t5ebkyMzMVFRVV5fZ5eXmaMGGCgoOD9emnn8rHx6fK9W02m2w2z7zdSW5xmf6+9rD+8cNh5VcOIu/RKkQPje2ssV0jCU8AALiZqcHmW7Zs0Q8//KCjR4+qqKhILVq0UN++fTV69GiFh4e7vcizg823bNmi/v37S5K+/fZbTZgwocrB5rm5uRo/frxsNpu+/vprBQQE1PizPWGweWFpud5df1QL1/ysnKIySVL3mBA9NK6zxhGgAABNUF39fpu+aq+uXXvttTp16pQWLlzonP4gISHBOf3B8ePHNXbsWL333nsaOHCgcnNzdc0116iwsFCffvqpy9WEERER8vKq3iX+DTlIlZTb9cGmVL2+8qAy8isGyHeMDNLDV3fWhB6cvgMANF0N/qq9urZkyRLNmjVLY8eOldVq1c0336zXXnvN+X5ZWZmSk5NVWFgoSdq2bZs2btwoSerYsaPLvg4fPqy2bdvWWe3uZncY+u+O43pl+QEdy6qYibxNeIAeGtdJ1/dpJS+uwgMAoE54TI9UfWlIPVKGYWjFvnT9z/8lO++FFxls0wNjO2lKQqx8vZkHCgAAiR4p/MKWI5l6/pv92nI0S5IU4uet347qqGlD28rfl5nIAQCoDwSpBu5gep5eWJas5XtPSZJs3lbdM6ydfjuyg0IDqr4CEQAA1C63Bans7GyFhYW5a3dN3qncYr363QH9e3OqHIZktUi3DojVg2M7KyqUGwkDANAQmBpU88ILL+jf//638/WUKVPUvHlztWrVSklJSW4rrikqKCnXK98ma+T/rNL7mypC1NXdWurb2SO04KZehCgAABoQUz1SCxcu1JIlSyRJy5cv1/Lly/XNN9/oww8/1Ny5c/Xtt9+6tcimwO4w9J+tqXrp2wM6nVcxlUH/uGaaf228Etq6f24uAABw5UwFqbS0NMXGxkqSvvzyS02ZMkXXXHON2rZtq0GDBrm1wKbgh58y9Oev9mp/WsWVeHHNAzRvQjxzQQEA0MCZClLNmjVTamqqYmNjtWzZMv35z3+WVHF5vt1ud2uBjdmh0/l67qt9WrG/4vY3IX7eemBsJ905JE42b67EAwCgoTMVpG666Sbdfvvt6tSpk86cOaNrr71WkrR9+/YLJr/EhXKKyvTaip/07vojKncY8rZadOeQOD0wppOaBfrWd3kAAKCaTAWpv/71r2rbtq1SU1P14osvKigoSJJ08uRJ/e53v3NrgY1Jud2h9zen6pVvk5VVWHFPvDHxkXp0Yld1jAyq5+oAAEBNMbP5ZbhrZtQfD53RU5/vcY6D6hgZpCeu66aRnSPcVSoAAKhUVzObm5r+4N1339VXX33lfP2HP/xBYWFhGjp0qI4ePeq24hqDE9lF+v372zV10Y/an5anUH8fPTW5m7558CpCFAAAHs5UkPrLX/4if39/SdKGDRv05ptv6sUXX1SLFi00e/ZstxboqYrL7Hpj5U8a+/IafZF0QhaLlDiojVY9MkrThrWTjxf3xQMAwNOZGiOVmprqHFT+2Wef6eabb9bMmTM1bNgwjRo1yp31eaQ1B07ryf/u1pEzhZKkAW2b6cnJ3dWjVWg9VwYAANzJVJAKCgrSmTNn1KZNG3377beaM2eOJMnPz09FRUVuLdCTnMgu0jNf7NWyPWmSpMhgmx6b1FW/6h3DfFAAADRCpoLU1Vdfrfvuu099+/bVgQMHNHHiREnSnj171LZtW3fW5xFKyx1654fDem3FTyoqs8vLatG0oW310LhOCvbjxsIAADRWpoLUm2++qccff1ypqan6+OOP1bx5c0nS1q1bddttt7m1wIbux0Nn9MRnu/VTer4kaWDbcD1zQ3fFR9XeFQIAAKBhYPqDy7jU5ZOn80q04Ot9+mT7cUlS80BfPTqxq27q14rTeAAA1LO6mv7AVI+UJGVnZ+udd97Rvn37JEndu3fXvffeq9DQxj2g2uEwtGRTiv5n2X7lFpc7r8abe028QgM4jQcAQFNiqkdqy5YtGj9+vPz9/TVw4EBJ0ubNm1VUVKRvv/1W/fr1c3uh9eX8RHuiUJr/yS5tT8mWJPVsFao/39BDvWPD6rVGAADgqq56pEwFqauuukodO3bU22+/LW/vik6t8vJy3XfffTp06JC+//57txdaX84eiKf+s1n/39Z0lTsMBdm89cg1nXXnkLbysnIaDwCAhqZBByl/f39t375d8fHxLu179+5VQkKCCgsL3VZgfTt7IGIf+lBWW4DGd2+pp3/VQ1GhfvVdGgAAuIQGPUYqJCREKSkpFwSp1NRUBQcHu6WwhqZliE3PTemva7pH1XcpAACggTAVpG699VZNnz5dL730koYOHSpJWrdunebOndtopz/476zhiokIr+8yAABAA2IqSL300kuyWCy66667VF5eLkny8fHRb3/7Wz3//PNuLbChCLKZvsARAAA0Ulc0j1RhYaF+/vlnSVKHDh0UEBDgtsIairo6xwoAANynQY+ROisgIEA9e/Z0Vy0AAAAepdpB6qabbqr2Tj/55BNTxQAAAHiSagepxj5jOQAAQE1VO0gtXry4NusAAADwONb6LgAAAMBTEaQAAABMIkgBAACYRJACAAAwiSAFAABgkukJOVesWKEVK1YoPT1dDofD5b1//OMfV1wYAABAQ2cqSD399NN65plnlJCQoOjoaFksFnfXBQAA0OCZClILFy7UP//5T915553urgcAAMBjmBojVVpaqqFDh7q7FgAAAI9iKkjdd999Wrp0qbtrAQAA8CimTu0VFxdr0aJF+u6779SrVy/5+Pi4vP/KK6+4pTgAAICGzFSQ2rlzp/r06SNJ2r17t8t7DDwHAABNhakgtWrVKnfXAQAA4HGueELOY8eO6dixY+6oBQAAwKOYClIOh0PPPPOMQkNDFRcXp7i4OIWFhenZZ5+9YHJOAACAxsrUqb3HHntM77zzjp5//nkNGzZMkvTDDz/oqaeeUnFxsZ577jm3FgkAANAQWQzDMGq6UUxMjBYuXKhf/epXLu3//e9/9bvf/U7Hjx93W4H1LTc3V6GhocrJyVFISEh9lwMAAKqhrn6/TZ3ay8zMVHx8/AXt8fHxyszMvOKiAAAAPIGpINW7d2+98cYbF7S/8cYb6t279xUXBQAA4AlMjZF68cUXNWnSJH333XcaMmSIJGnDhg1KTU3V119/7dYCAQAAGipTPVIjR47UgQMHdOONNyo7O1vZ2dm66aablJycrKuuusrdNQIAADRIpgabNyUMNgcAwPPU1e93tU/t7dy5Uz169JDVatXOnTurXLdXr15XXBgAAEBDV+0g1adPH6WlpSkyMlJ9+vSRxWLRxTqzLBaL7Ha7W4sEAABoiKodpA4fPqyIiAjncwAAgKau2kEqLi7O+fzo0aMaOnSovL1dNy8vL9f69etd1gUAAGisTF21N3r06ItOvJmTk6PRo0dfcVEAAACewFSQMgxDFovlgvYzZ84oMDDwiosCAADwBDWakPOmm26SVDGgfNq0abLZbM737Ha7du7cqaFDh7q3QgAAgAaqRkEqNDRUUkWPVHBwsPz9/Z3v+fr6avDgwZoxY4Z7KwQAAGigahSkFi9e7Jzy4PXXX1dQUFCtFAUAAOAJajxGyjAMLVmyRCdPnqyNegAAADxGjYOU1WpVp06ddObMmdqoBwAAwGOYumrv+eef19y5c7V792531wMAAOAxTAWpu+66S5s2bVLv3r3l7++v8PBwl6U2ZGZmKjExUSEhIQoLC9P06dOVn59f5Ta//vWv1aFDB/n7+ysiIkLXX3+99u/fXyv1AQCApqdGg83PevXVV91cxuUlJibq5MmTWr58ucrKynTPPfdo5syZWrp06SW36d+/vxITE9WmTRtlZmbqqaee0jXXXKPDhw/Ly8urDqsHAACNkcW42J2HG5h9+/apW7du2rx5sxISEiRJy5Yt08SJE3Xs2DHFxMRUaz87d+5U7969dfDgQXXo0KFa2+Tm5io0NFQ5OTkKCQkx/R0AAEDdqavfb1On9iTp559/1uOPP67bbrtN6enpkqRvvvlGe/bscVtxZ23YsEFhYWHOECVJ48aNk9Vq1caNG6u1j4KCAi1evFjt2rVTbGzsJdcrKSlRbm6uywIAAHAxpoLUmjVr1LNnT23cuFGffPKJc6xSUlKSnnzySbcWKElpaWmKjIx0afP29lZ4eLjS0tKq3Pb//b//p6CgIAUFBembb77R8uXL5evre8n1FyxYoNDQUOdSVegCAABNm6kgNW/ePP35z3++IJSMGTNGP/74Y432Y7FYqlyudHB4YmKitm/frjVr1qhz586aMmWKiouLL7n+/PnzlZOT41xSU1Ov6PMBAEDjZWqw+a5duy46yDsyMlIZGRnV3s/DDz+sadOmVblO+/btFRUV5Tx9eFZ5ebkyMzMVFRVV5fZne5Y6deqkwYMHq1mzZvr000912223XXR9m83mcg9BAACASzEVpMLCwnTy5Em1a9fOpX379u1q1apVtfcTERGhiIiIy643ZMgQZWdna+vWrerfv78kaeXKlXI4HBo0aFC1P88wDBmGoZKSkmpvAwAAcCmmTu1NnTpVf/zjH5WWliaLxSKHw6F169bpkUce0V133eXuGtW1a1dNmDBBM2bM0KZNm7Ru3TrNmjVLU6dOdV6xd/z4ccXHx2vTpk2SpEOHDmnBggXaunWrUlJStH79et1yyy3y9/fXxIkT3V4jAABoekwFqb/85S+Kj49XbGys8vPz1a1bN40YMUJDhw7V448/7u4aJUlLlixRfHy8xo4dq4kTJ2r48OFatGiR8/2ysjIlJyersLBQkuTn56e1a9dq4sSJ6tixo2699VYFBwdr/fr1FwxcBwAAMOOK5pFKTU3Vrl27lJ+fr759+6pTp07urK1BYB4pAAA8T139fpsaI3VWbGysYmNjZbfbtWvXLmVlZalZs2buqg0AAKBBM3Vq76GHHtI777wjSbLb7Ro5cqT69eun2NhYrV692p31AQAANFimgtR//vMf9e7dW5L0xRdf6NChQ9q/f79mz56txx57zK0FAgAANFSmglRGRoZz/qavv/5aU6ZMUefOnXXvvfdq165dbi0QAACgoTIVpFq2bKm9e/fKbrdr2bJluvrqqyVJhYWF8vLycmuBAAAADZWpweb33HOPpkyZoujoaFksFo0bN06StHHjRsXHx7u1QAAAgIbKVJB66qmn1KNHD6WmpuqWW25x3lLFy8tL8+bNc2uBAAAADdUVzSPVFDCPFAAAnqfBzyO1YsUKrVixQunp6XI4HC7v/eMf/7jiwgAAABo6U0Hq6aef1jPPPKOEhATnOCkAAICmxlSQWrhwof75z3/qzjvvdHc9AAAAHsPU9AelpaUaOnSou2sBAADwKKaC1H333aelS5e6uxYAAACPYurUXnFxsRYtWqTvvvtOvXr1ko+Pj8v7r7zyiluKAwAAaMhMBamdO3eqT58+kqTdu3e7vMfAcwAA0FSYClKrVq1ydx0AAAAex9QYKQAAANSwR+qmm26q1nqffPKJqWIAAAA8SY2CVGhoaG3VAQAA4HFqFKQWL15cW3UAAAB4HMZIAQAAmESQAgAAMIkgBQAAYBJBCgAAwCSCFAAAgEkEKQAAAJMIUgAAACYRpAAAAEwiSAEAAJhEkAIAADCJIAUAAGASQQoAAMAkghQAAIBJBCkAAACTCFIAAAAmEaQAAABMIkgBAACYRJACAAAwiSAFAABgEkEKAADAJIIUAACASQQpAAAAkwhSAAAAJhGkAAAATCJIAQAAmESQAgAAMIkgBQAAYBJBCgAAwCSCFAAAgEkEKQAAAJMIUgAAACYRpAAAAEwiSAEAAJhEkAIAADCJIAUAAGASQQoAAMAkghQAAIBJBCkAAACTCFIAAAAmEaQAAABMIkgBAACYRJACAAAwiSAFAABgkscEqczMTCUmJiokJERhYWGaPn268vPzq7WtYRi69tprZbFY9Nlnn9VuoQAAoMnwmCCVmJioPXv2aPny5fryyy/1/fffa+bMmdXa9tVXX5XFYqnlCgEAQFPjXd8FVMe+ffu0bNkybd68WQkJCZKk119/XRMnTtRLL72kmJiYS267Y8cOvfzyy9qyZYuio6PrqmQAANAEeESP1IYNGxQWFuYMUZI0btw4Wa1Wbdy48ZLbFRYW6vbbb9ebb76pqKioan1WSUmJcnNzXRYAAICL8YgglZaWpsjISJc2b29vhYeHKy0t7ZLbzZ49W0OHDtX1119f7c9asGCBQkNDnUtsbKzpugEAQONWr0Fq3rx5slgsVS779+83te/PP/9cK1eu1Kuvvlqj7ebPn6+cnBznkpqaaurzAQBA41evY6QefvhhTZs2rcp12rdvr6ioKKWnp7u0l5eXKzMz85Kn7FauXKmff/5ZYWFhLu0333yzrrrqKq1evfqi29lsNtlstup+BQAA0ITVa5CKiIhQRETEZdcbMmSIsrOztXXrVvXv319SRVByOBwaNGjQRbeZN2+e7rvvPpe2nj176q9//asmT5585cUDAIAmzyOu2uvatasmTJigGTNmaOHChSorK9OsWbM0depU5xV7x48f19ixY/Xee+9p4MCBioqKumhvVZs2bdSuXbu6/goAAKAR8ojB5pK0ZMkSxcfHa+zYsZo4caKGDx+uRYsWOd8vKytTcnKyCgsL67FKAADQlFgMwzDqu4iGLDc3V6GhocrJyVFISEh9lwMAAKqhrn6/PaZHCgAAoKEhSAEAAJhEkAIAADCJIAUAAGASQQoAAMAkghQAAIBJBCkAAACTCFIAAAAmEaQAAABMIkgBAACYRJACAAAwiSAFAABgEkEKAADAJIIUAACASQQpAAAAkwhSAAAAJhGkAAAATCJIAQAAmESQAgAAMIkgBQAAYBJBCgAAwCSCFAAAgEkEKQAAAJMIUgAAACYRpAAAAEwiSAEAAJhEkAIAADCJIAUAAGASQQoAAMAkghQAAIBJBCkAAACTCFIAAAAmEaQAAABMIkgBAACYRJACAAAwiSAFAABgEkEKAADAJIIUAACASQQpAAAAkwhSAAAAJhGkAAAATCJIAQAAmESQAgAAMIkgBQAAYBJBCgAAwCSCFAAAgEkEKQAAAJMIUgAAACYRpAAAAEwiSAEAAJhEkAIAADCJIAUAAGASQQoAAMAkghQAAIBJBCkAAACTCFIAAAAmEaQAAABMIkgBAACYRJACAAAwiSAFAABgEkEKAADAJIIUAACASQQpAAAAkzwmSGVmZioxMVEhISEKCwvT9OnTlZ+fX+U2o0aNksVicVl+85vf1FHFAACgsfOu7wKqKzExUSdPntTy5ctVVlame+65RzNnztTSpUur3G7GjBl65plnnK8DAgJqu1QAANBEeESQ2rdvn5YtW6bNmzcrISFBkvT6669r4sSJeumllxQTE3PJbQMCAhQVFVVXpQIAgCbEI4LUhg0bFBYW5gxRkjRu3DhZrVZt3LhRN9544yW3XbJkif71r38pKipKkydP1hNPPFFlr1RJSYlKSkqcr3NyciRJubm5bvgmAACgLpz93TYMo1Y/xyOCVFpamiIjI13avL29FR4errS0tEtud/vttysuLk4xMTHauXOn/vjHPyo5OVmffPLJJbdZsGCBnn766QvaY2NjzX8BAABQL86cOaPQ0NBa23+9Bql58+bphRdeqHKdffv2md7/zJkznc979uyp6OhojR07Vj///LM6dOhw0W3mz5+vOXPmOF9nZ2crLi5OKSkptXogcHm5ubmKjY1VamqqQkJC6rucJo1j0bBwPBoOjkXDkZOTozZt2ig8PLxWP6deg9TDDz+sadOmVblO+/btFRUVpfT0dJf28vJyZWZm1mj806BBgyRJBw8evGSQstlsstlsF7SHhobyR9FAhISEcCwaCI5Fw8LxaDg4Fg2H1Vq7ExTUa5CKiIhQRETEZdcbMmSIsrOztXXrVvXv31+StHLlSjkcDmc4qo4dO3ZIkqKjo03VCwAAcD6PmEeqa9eumjBhgmbMmKFNmzZp3bp1mjVrlqZOneq8Yu/48eOKj4/Xpk2bJEk///yznn32WW3dulVHjhzR559/rrvuuksjRoxQr1696vPrAACARsIjgpRUcfVdfHy8xo4dq4kTJ2r48OFatGiR8/2ysjIlJyersLBQkuTr66vvvvtO11xzjeLj4/Xwww/r5ptv1hdffFGjz7XZbHryyScveroPdYtj0XBwLBoWjkfDwbFoOOrqWFiM2r4uEAAAoJHymB4pAACAhoYgBQAAYBJBCgAAwCSCFAAAgElNKkh9//33mjx5smJiYmSxWPTZZ59Vuf7q1atlsVguWH55W5o333xTbdu2lZ+fnwYNGuScggGXVhvHYsGCBRowYICCg4MVGRmpG264QcnJybX8TTxfbf1dnPX888/LYrHooYcecn/xjVBtHY/jx4/rjjvuUPPmzeXv76+ePXtqy5YttfhNPF9tHAu73a4nnnhC7dq1k7+/vzp06KBnn3221u8H5+lqeiykinvnPvbYY4qLi5PNZlPbtm31j3/8w2Wdjz76SPHx8fLz81PPnj319ddf17i2JhWkCgoK1Lt3b7355ps12i45OVknT550Luff9+/f//635syZoyeffFLbtm1T7969NX78+AtmYoer2jgWa9as0f33368ff/xRy5cvV1lZma655hoVFBS4u/xGpTaOxVmbN2/W3/72N+Zuq4HaOB5ZWVkaNmyYfHx89M0332jv3r16+eWX1axZM3eX36jUxrF44YUX9NZbb+mNN97Qvn379MILL+jFF1/U66+/7u7yGxUzx2LKlClasWKF3nnnHSUnJ+v9999Xly5dnO+vX79et912m6ZPn67t27frhhtu0A033KDdu3fXrDijiZJkfPrpp1Wus2rVKkOSkZWVdcl1Bg4caNx///3O13a73YiJiTEWLFjgpkobP3cdi19KT083JBlr1qy5sgKbEHcei7y8PKNTp07G8uXLjZEjRxoPPvig2+psKtx1PP74xz8aw4cPd29xTYy7jsWkSZOMe++916XtpptuMhITE91QZdNQnWPxzTffGKGhocaZM2cuuc6UKVOMSZMmubQNGjTI+PWvf12jeppUj5RZffr0UXR0tK6++mqtW7fO2V5aWqqtW7dq3Lhxzjar1apx48Zpw4YN9VFqo3epY3ExOTk5klTrN6xsqi53LO6//35NmjTJ5e8Dtaeq4/H5558rISFBt9xyiyIjI9W3b1+9/fbb9VRp41fVsRg6dKhWrFihAwcOSJKSkpL0ww8/6Nprr62PUhuts//Ov/jii2rVqpU6d+6sRx55REVFRc51NmzYcMF/n8aPH1/j3+96vddeQxcdHa2FCxcqISFBJSUl+vvf/65Ro0Zp48aN6tevnzIyMmS329WyZUuX7Vq2bKn9+/fXU9WN0+WOxS85HA499NBDGjZsmHr06FEPFTde1TkWH3zwgbZt26bNmzfXc7WNX3WOx6FDh/TWW29pzpw5evTRR7V582Y98MAD8vX11d13313P36DxqM6xmDdvnnJzcxUfHy8vLy/Z7XY999xzSkxMrOfqG5dDhw7phx9+kJ+fnz799FNlZGTod7/7nc6cOaPFixdLktLS0i76+32p8Z6XVKP+q0ZE1egavJgRI0YYd9xxh2EYhnH8+HFDkrF+/XqXdebOnWsMHDjQHWU2Ce44Fr/0m9/8xoiLizNSU1OvsLqmxR3HIiUlxYiMjDSSkpKc73Nqzxx3/W34+PgYQ4YMcVnn97//vTF48OArLbHJcNexeP/9943WrVsb77//vrFz507jvffeM8LDw41//vOfbqy2cavOsbj66qsNPz8/Izs729n28ccfGxaLxSgsLDQMo+LvYunSpS7bvfnmm0ZkZGSN6uHUXg0NHDhQBw8elCS1aNFCXl5eOnXqlMs6p06dUlRUVH2U16ScfyzON2vWLH355ZdatWqVWrduXQ+VNT3nH4utW7cqPT1d/fr1k7e3t7y9vbVmzRq99tpr8vb2lt1ur+dqG79f/m1ER0erW7duLut07dpVKSkpdV1ak/PLYzF37lzNmzdPU6dOVc+ePXXnnXdq9uzZWrBgQT1W2fhER0erVatWCg0NdbZ17dpVhmHo2LFjkqSoqCi3/H4TpGpox44dio6OllRxY+T+/ftrxYoVzvcdDodWrFihIUOG1FeJTcb5x0KSDMPQrFmz9Omnn2rlypVq165dPVbXtJx/LMaOHatdu3Zpx44dziUhIUGJiYnasWOHvLy86rnaxu+XfxvDhg27YCqQAwcOKC4urq5La3J+eSwKCwtltbr+9Hp5ecnhcNR1aY3asGHDdOLECeXn5zvbDhw4IKvV6vwf7CFDhrj8fkvS8uXLa/z73aTGSOXn57v8n8Hhw4e1Y8cOhYeHq02bNpo/f76OHz+u9957T5L06quvql27durevbuKi4v197//XStXrtS3337r3MecOXN09913KyEhQQMHDtSrr76qgoIC3XPPPXX+/TxJbRyL+++/X0uXLtV///tfBQcHO89zh4aGyt/fv26/oAdx97EIDg6+YFxaYGCgmjdvzni1aqiNv43Zs2dr6NCh+stf/qIpU6Zo06ZNWrRokRYtWlTn38+T1MaxmDx5sp577jm1adNG3bt31/bt2/XKK6/o3nvvrfPv50lqeixuv/12Pfvss7rnnnv09NNPKyMjQ3PnztW9997r/D148MEHNXLkSL388suaNGmSPvjgA23ZsqXmfxc1OhHo4c5emvrL5e677zYMwzDuvvtuY+TIkc71X3jhBaNDhw6Gn5+fER4ebowaNcpYuXLlBft9/fXXjTZt2hi+vr7GwIEDjR9//LGOvpHnqo1jcbH9STIWL15cd1/MA9XW38X5GCNVfbV1PL744gujR48ehs1mM+Lj441FixbV0TfyXLVxLHJzc40HH3zQaNOmjeHn52e0b9/eeOyxx4ySkpI6/Gaep6bHwjAMY9++fca4ceMMf39/o3Xr1sacOXOc46PO+vDDD43OnTsbvr6+Rvfu3Y2vvvqqxrVZDIPpVAEAAMxgjBQAAIBJBCkAAACTCFIAAAAmEaQAAABMIkgBAACYRJACAAAwiSAFAABgEkEKAADAJIIUAACASQQpAB5j1KhReuihh+q7DCez9Zw5c0aRkZE6cuSI22v6palTp+rll1+u9c8BmiqCFAAXCxcuVHBwsMrLy51t+fn58vHx0ahRo1zWXb16tSwWi37++ec6rrJuuTvAPffcc7r++uvVtm1bt+3zUh5//HE999xzysnJqfXPApoighQAF6NHj1Z+fr62bNnibFu7dq2ioqK0ceNGFRcXO9tXrVqlNm3aqEOHDvVRqkcqLCzUO++8o+nTp9fJ5/Xo0UMdOnTQv/71rzr5PKCpIUgBcNGlSxdFR0dr9erVzrbVq1fr+uuvV7t27fTjjz+6tI8ePVqStGzZMg0fPlxhYWFq3ry5rrvuOpeeqkWLFikmJkYOh8Pl866//nrde++9kiSHw6EFCxaoXbt28vf3V+/evfWf//znkrVWZ/1Ro0bpgQce0B/+8AeFh4crKipKTz31lMs6eXl5SkxMVGBgoKKjo/XXv/7V2Qs1bdo0rVmzRv/7v/8ri8Uii8XickrO4XBUue9f+vrrr2Wz2TR48GCX9h9++EE+Pj4uQfXIkSOyWCw6evSo8/nHH3+sESNGyN/fXwMGDFBKSorWrl2rwYMHKyAgQGPHjlV2drbLvidPnqwPPvigyroAmEOQAnCB0aNHa9WqVc7Xq1at0qhRozRy5Ehne1FRkTZu3OgMUgUFBZozZ462bNmiFStWyGq16sYbb3QGp1tuuUVnzpxx2W9mZqaWLVumxMRESdKCBQv03nvvaeHChdqzZ49mz56tO+64Q2vWrLlondVd/91331VgYKA2btyoF198Uc8884yWL1/ufH/OnDlat26dPv/8cy1fvlxr167Vtm3bJEn/+7//qyFDhmjGjBk6efKkTp48qdjY2Grv+5fWrl2r/v37X9C+Y8cOde3aVX5+fs627du3q1mzZoqLi1NSUpIk6a233tJf/vIXrV+/XqdOndIdd9yh559/Xm+88YZWrVqlpKQkLV682GXfAwcO1KZNm1RSUnLJugCYZADAL7z99ttGYGCgUVZWZuTm5hre3t5Genq6sXTpUmPEiBGGYRjGihUrDEnG0aNHL7qP06dPG5KMXbt2Oduuv/56495773W+/tvf/mbExMQYdrvdKC4uNgICAoz169e77Gf69OnGbbfdZhiGYYwcOdJ48MEHDcMwqrX+2W2GDx/uss6AAQOMP/7xj4ZhGEZubq7h4+NjfPTRR873s7OzjYCAAOdnnf+557vcvi/ml/8MzrrvvvuMu+66y6XtT3/6kzFq1CjDMAzjqaeeMsLDw42MjAzn+3fccYfRtm1bo6CgwNk2YcIE4w9/+IPLfpKSkgxJxpEjRy5ZFwBz6JECcIFRo0apoKBAmzdv1tq1a9W5c2dFRERo5MiRznFSq1evVvv27dWmTRtJ0k8//aTbbrtN7du3V0hIiHMgdUpKinO/iYmJ+vjjj509I0uWLNHUqVNltVp18OBBFRYW6uqrr1ZQUJBzee+99y46mL0m6/fq1cvldXR0tNLT0yVJhw4dUllZmQYOHOh8PzQ0VF26dKnWP6uq9n0xRUVFLr1OZ+3YsUN9+vRxadu+fbuzLSkpSTfeeKOaN2/ufD8lJUW33nqrAgICXNratWvnsh9/f39JFeOzALiXd30XAKDh6dixo1q3bq1Vq1YpKytLI0eOlCTFxMQoNjZW69ev16pVqzRmzBjnNpMnT1ZcXJzefvtt51ioHj16qLS01GUdwzD01VdfacCAAVq7dq3++te/Sqq4MlCSvvrqK7Vq1cqlHpvNdkGNNVnfx8fH5bXFYrlgrJZZNd13ixYtlJWV5dJmt9u1e/du9e3b16V927ZtuvnmmyVVBK358+e7vJ+UlKTZs2c7XxcXFys5OVm9e/d2WS8zM1OSFBERUc1vBaC6CFIALmr06NFavXq1srKyNHfuXGf7iBEj9M0332jTpk367W9/K6liXqTk5GS9/fbbuuqqqyRVDJ7+JT8/P910001asmSJDh48qC5duqhfv36SpG7duslmsyklJcUZ3KpS0/UvpX379vLx8dHmzZudvWs5OTk6cOCARowYIUny9fWV3W43/Rnn69u37wVX0CUnJ6u4uFgxMTHOtg0bNuj48ePq06ePcnNzdeTIEZegdfjwYeXk5Li07dq1S4ZhqGfPni773717t1q3bq0WLVq45TsAOIcgBeCiRo8erfvvv19lZWUuQWXkyJGaNWuWSktLnQPNmzVrpubNm2vRokWKjo5WSkqK5s2bd9H9JiYm6rrrrtOePXt0xx13ONuDg4P1yCOPaPbs2XI4HBo+fLhycnK0bt06hYSE6O6773bZT03Xv5Tg4GDdfffdmjt3rsLDwxUZGaknn3xSVqtVFotFktS2bVtt3LhRR44cUVBQkMLDw2W1mhsZMX78eM2fP19ZWVlq1qyZpIreJkl6/fXX9cADD+jgwYN64IEHJEmlpaVKSkqSl5eXevTo4dzPjh07FB4erri4OJe2Dh06KCgoyOUz165dq2uuucZUvQCqxhgpABc1evRoFRUVqWPHjmrZsqWzfeTIkcrLy3NOkyBJVqtVH3zwgbZu3aoePXpo9uzZ+p//+Z+L7nfMmDEKDw9XcnKybr/9dpf3nn32WT3xxBNasGCBunbtqgkTJuirr766YMyP2fUv5ZVXXtGQIUN03XXXady4cRo2bJjLFXSPPPKIvLy81K1bN0VERLiM+6qpnj17ql+/fvrwww+dbTt27ND48eN16NAh9ezZU4899piefvpphYSE6LXXXlNSUpK6dOniMrYqKSnpglOBSUlJF5zWKy4u1meffaYZM2aYrhnApVkMwzDquwgAaEgKCgrUqlUrvfzyy7UyceZXX32luXPnavfu3bJarRo/frwGDBigP//5z27/rLfeekuffvqpvv32W7fvGwCn9gBA27dv1/79+zVw4EDl5OTomWeekVQxWWhtmDRpkn766ScdP35csbGxSkpKck5K6m4+Pj56/fXXa2XfAOiRAgBt375d9913n5KTk+Xr66v+/fvrlVdeuWDQdm1IS0tTdHS09uzZo27dutX65wFwL4IUAACASQw2BwAAMIkgBQAAYBJBCgAAwCSCFAAAgEkEKQAAAJMIUgAAACYRpAAAAEwiSAEAAJhEkAIAADCJIAUAAGASQQoAAMCk/x9/DsiUD8RKzwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# extract the transmission data from the mode monitor\n",
    "amp = sim_data[\"mode\"].amps.sel(mode_index=0, direction=\"+\")\n",
    "T = np.abs(amp) ** 2  # transmission to the top waveguide\n",
    "T_total = 2 * T  # total transmission at the two output waveguides\n",
    "\n",
    "plt.plot(ldas, 10 * np.log10(T_total))\n",
    "plt.xlim(1.5, 1.6)\n",
    "plt.ylim(-0.5, 0)\n",
    "plt.xlabel(r\"Wavelength ($\\mu m$)\")\n",
    "plt.ylabel(\"Insertion loss (dB)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d9e0403",
   "metadata": {},
   "source": [
    "We can also visualize the field distribution. Here we can see the interference in the junction while no visible higher order modes are excited at the output waveguides."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e44e8128",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:33:14.619702Z",
     "iopub.status.busy": "2025-05-15T10:33:14.619613Z",
     "iopub.status.idle": "2025-05-15T10:33:14.991575Z",
     "shell.execute_reply": "2025-05-15T10:33:14.991115Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
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   ],
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    "sim_data.plot_field(\n",
    "    field_monitor_name=\"field\", field_name=\"E\", val=\"abs^2\", f=freq0, vmin=0, vmax=2e3\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "016a3a86",
   "metadata": {},
   "outputs": [],
   "source": []
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 "metadata": {
  "applications": [
   "Passive photonic integrated circuit components"
  ],
  "description": "This notebook demonstrates how to simulate a waveguide Y junction in Tidy3D FDTD.",
  "feature_image": "./img/y_junction_schematic.png",
  "features": [
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   "language": "python",
   "name": "python3"
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  "title": "Waveguide Y Junction Modeling in Tidy3D | Flexcompute",
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