{
 "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\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ad43045e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:09:13.898731Z",
     "iopub.status.busy": "2023-02-03T04:09:13.898331Z",
     "iopub.status.idle": "2023-02-03T04:09:15.524439Z",
     "shell.execute_reply": "2023-02-03T04:09:15.524012Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[22:09:14] </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING </span> This version of Tidy3D was pip installed from the <span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d-beta'</span> repository on   <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#103\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">103</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         PyPI. Future releases will be uploaded to the <span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d'</span> repository. From now on, <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         please use <span style=\"color: #008000; text-decoration-color: #008000\">'pip install tidy3d'</span> instead.                                        <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[22:09:14]\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING \u001b[0m This version of Tidy3D was pip installed from the \u001b[32m'tidy3d-beta'\u001b[0m repository on   \u001b]8;id=797860;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=116201;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#103\u001b\\\u001b[2m103\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m         PyPI. Future releases will be uploaded to the \u001b[32m'tidy3d'\u001b[0m repository. From now on, \u001b[2m               \u001b[0m\n",
       "\u001b[2;36m           \u001b[0m         please use \u001b[32m'pip install tidy3d'\u001b[0m instead.                                        \u001b[2m               \u001b[0m\n"
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     },
     "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><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Using client version: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.9</span>.0rc1                                                  <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#121\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">121</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Using client version: \u001b[1;36m1.9\u001b[0m.0rc1                                                  \u001b]8;id=811080;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=659310;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#121\u001b\\\u001b[2m121\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n",
    "from tidy3d.plugins import ModeSolver\n"
   ]
  },
  {
   "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": "2023-02-03T04:09:15.527050Z",
     "iopub.status.busy": "2023-02-03T04:09:15.526770Z",
     "iopub.status.idle": "2023-02-03T04:09:15.529446Z",
     "shell.execute_reply": "2023-02-03T04:09:15.529070Z"
    }
   },
   "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"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "946d0a45",
   "metadata": {},
   "source": [
    "In this model, the Y-junction is made of silicon. The top and bottom claddings are made of silicon oxide. We will model them as non-dispersive materials here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b90f342c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:09:15.531515Z",
     "iopub.status.busy": "2023-02-03T04:09:15.531359Z",
     "iopub.status.idle": "2023-02-03T04:09:15.533813Z",
     "shell.execute_reply": "2023-02-03T04:09:15.533425Z"
    }
   },
   "outputs": [],
   "source": [
    "n_si = 3.48  # silicon refractive index\n",
    "si = td.Medium(permittivity=n_si**2)\n",
    "\n",
    "n_sio2 = 1.44  # silicon oxide refractive index\n",
    "sio2 = td.Medium(permittivity=n_sio2**2)\n"
   ]
  },
  {
   "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": "2023-02-03T04:09:15.535806Z",
     "iopub.status.busy": "2023-02-03T04:09:15.535651Z",
     "iopub.status.idle": "2023-02-03T04:09:15.538741Z",
     "shell.execute_reply": "2023-02-03T04:09:15.538378Z"
    }
   },
   "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\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98ae6d2c",
   "metadata": {},
   "source": [
    "First, define the junction structure by using a [PolySlab](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.PolySlab.html?highlight=polyslab). 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 spline for example. \n",
    "\n",
    "Before proceeding further to construct other structures, we can use the [plot](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.Structure.html) method to inspect the geometry. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f1bd7cba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:09:15.540786Z",
     "iopub.status.busy": "2023-02-03T04:09:15.540650Z",
     "iopub.status.idle": "2023-02-03T04:09:15.708850Z",
     "shell.execute_reply": "2023-02-03T04:09:15.708452Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: title={'center': 'cross section at z=0.11'}, xlabel='x', ylabel='y'>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "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"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f33fc2d8",
   "metadata": {},
   "source": [
    "The waveguide bends are defined in a similar way. Here, we use S bend sine waveguides, which are described by the function\n",
    "<center>$y = \\frac{xh_{band}}{l_{bend}}-\\frac{h_{bend}}{2\\pi}sin(\\frac{2\\pi x}{l_{bend}})$.</center>\n",
    "\n",
    "Different types of bend can also be used here. Again, to ensure the structure is defined correctly, use the `plot` method to inspect it before proceeding."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2f517ebb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:09:15.711025Z",
     "iopub.status.busy": "2023-02-03T04:09:15.710855Z",
     "iopub.status.idle": "2023-02-03T04:09:15.856604Z",
     "shell.execute_reply": "2023-02-03T04:09:15.856135Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: title={'center': 'cross section at z=0.11'}, xlabel='x', ylabel='y'>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_start = l_in + l_junction  # x coordinate of the starting point of the waveguide bends\n",
    "x = np.linspace(\n",
    "    x_start, x_start + l_bend, 100\n",
    ")  # x coordinates of the top edge vertices\n",
    "y = (\n",
    "    (x - x_start) * h_bend / l_bend\n",
    "    - h_bend * np.sin(2 * np.pi * (x - x_start) / l_bend) / (np.pi * 2)\n",
    "    + w13 / 2\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, np.flipud(y - w1)))\n",
    "\n",
    "# stacking x and y coordinates to form vertices pairs\n",
    "vertices = np.transpose(np.vstack((x, y)))\n",
    "\n",
    "wg_bend_1 = td.Structure(\n",
    "    geometry=td.PolySlab(vertices=vertices, axis=2, slab_bounds=(0, t)), medium=si\n",
    ")\n",
    "\n",
    "# the second waveguide bend can be obtained simply by flipping the sign of the y coordinates of the first bend\n",
    "vertices = np.transpose(np.vstack((x, -y)))\n",
    "\n",
    "wg_bend_2 = td.Structure(\n",
    "    geometry=td.PolySlab(vertices=vertices, axis=2, slab_bounds=(0, t)), medium=si\n",
    ")\n",
    "\n",
    "wg_bend_1.plot(z=t / 2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fecdf772",
   "metadata": {},
   "source": [
    "Lastly, define the straight input and output waveguides using `Box`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "37f3f2e2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:09:15.858767Z",
     "iopub.status.busy": "2023-02-03T04:09:15.858593Z",
     "iopub.status.idle": "2023-02-03T04:09:15.862984Z",
     "shell.execute_reply": "2023-02-03T04:09:15.862635Z"
    }
   },
   "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",
    "# top straight output waveguide\n",
    "wg_out_1 = td.Structure(\n",
    "    geometry=td.Box.from_bounds(\n",
    "        rmin=(l_in + l_junction + l_bend, w13 / 2 - w1 + h_bend, 0),\n",
    "        rmax=(inf_eff, w13 / 2 + h_bend, t),\n",
    "    ),\n",
    "    medium=si,\n",
    ")\n",
    "\n",
    "# bottom straight output waveguide\n",
    "wg_out_2 = td.Structure(\n",
    "    geometry=td.Box.from_bounds(\n",
    "        rmin=(l_in + l_junction + l_bend, -w13 / 2 - h_bend, 0),\n",
    "        rmax=(inf_eff, -w13 / 2 + w1 - h_bend, t),\n",
    "    ),\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, wg_out_1, wg_out_2]\n"
   ]
  },
  {
   "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": "2023-02-03T04:09:15.865178Z",
     "iopub.status.busy": "2023-02-03T04:09:15.865017Z",
     "iopub.status.idle": "2023-02-03T04:09:15.867429Z",
     "shell.execute_reply": "2023-02-03T04:09:15.867060Z"
    }
   },
   "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)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4eaa0e1e",
   "metadata": {},
   "source": [
    "We will use a [ModeSource](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.ModeSource.html?highlight=modesource) to excite the input waveguide using the fundamental TE mode. \n",
    "\n",
    "A [FluxMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FluxMonitor.html) is placed at the top output waveguide to measure the transmission. Similarly, A [ModeMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.ModeMonitor.html) is placed at the same location. Since we prefer not to excite higher order mode at the output waveguides, we need to perform mode decomposition to inspect the mode profile. Lastly, a [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_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": "2023-02-03T04:09:15.869482Z",
     "iopub.status.busy": "2023-02-03T04:09:15.869321Z",
     "iopub.status.idle": "2023-02-03T04:09:15.874464Z",
     "shell.execute_reply": "2023-02-03T04:09:15.874117Z"
    }
   },
   "outputs": [],
   "source": [
    "# add a mode source as excitation\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=freq0 / 10),\n",
    "    direction=\"+\",\n",
    "    mode_spec=td.ModeSpec(num_modes=1, target_neff=n_si),\n",
    "    mode_index=0,\n",
    ")\n",
    "\n",
    "# add a flux monitor to measure transmission at the output waveguide\n",
    "flux_monitor = td.FluxMonitor(\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",
    "    name=\"flux\",\n",
    ")\n",
    "\n",
    "# add a filed 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",
    ")\n",
    "\n",
    "# add a mode monitor to measure mode composition 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=td.ModeSpec(num_modes=4, target_neff=n_si),\n",
    "    name=\"mode\",\n",
    ")\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, we will simply model the whole device without using symmetry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9a4ec279",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:09:15.876614Z",
     "iopub.status.busy": "2023-02-03T04:09:15.876459Z",
     "iopub.status.idle": "2023-02-03T04:09:16.062088Z",
     "shell.execute_reply": "2023-02-03T04:09:16.061487Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: title={'center': 'cross section at z=0.00'}, xlabel='x', ylabel='y'>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 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=30, wavelength=lda0),\n",
    "    structures=y_junction,\n",
    "    sources=[mode_source],\n",
    "    monitors=[flux_monitor, field_monitor, mode_monitor],\n",
    "    run_time=5e-13,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "    medium=sio2,\n",
    ")\n",
    "\n",
    "sim.plot(z=0)\n"
   ]
  },
  {
   "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` to ensure we are launching the fundamental TE mode. To do so, we will use the [ModeSolver](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.plugins.ModeSolver.html) plugin, which solves for the mode profile on your local computer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "da2af982",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:09:16.064307Z",
     "iopub.status.busy": "2023-02-03T04:09:16.064127Z",
     "iopub.status.idle": "2023-02-03T04:09:16.629124Z",
     "shell.execute_reply": "2023-02-03T04:09:16.628472Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
      "  r = _umath_linalg.det(a, signature=signature)\n",
      "/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
      "  r = _umath_linalg.det(a, signature=signature)\n"
     ]
    }
   ],
   "source": [
    "mode_spec = td.ModeSpec(num_modes=1, target_neff=n_si)\n",
    "mode_solver = ModeSolver(\n",
    "    simulation=sim,\n",
    "    plane=td.Box(center=(l_in / 2, 0, t / 2), size=(0, 4 * w1, 6 * t)),\n",
    "    mode_spec=mode_spec,\n",
    "    freqs=[freq0],\n",
    ")\n",
    "mode_data = mode_solver.solve()\n"
   ]
  },
  {
   "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": 12,
   "id": "a2e49017",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:09:16.633573Z",
     "iopub.status.busy": "2023-02-03T04:09:16.633260Z",
     "iopub.status.idle": "2023-02-03T04:09:17.084846Z",
     "shell.execute_reply": "2023-02-03T04:09:17.084442Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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()\n"
   ]
  },
  {
   "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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "15e791dd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:09:17.087283Z",
     "iopub.status.busy": "2023-02-03T04:09:17.086965Z",
     "iopub.status.idle": "2023-02-03T04:13:11.245581Z",
     "shell.execute_reply": "2023-02-03T04:13:11.245104Z"
    }
   },
   "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\">[22:09:17] </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Created task <span style=\"color: #008000; text-decoration-color: #008000\">'y_junction'</span> with task_id <span style=\"color: #008000; text-decoration-color: #008000\">'84aecb17-55cf-42b9-800c-e4b2955a99b8'</span>.    <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#120\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">120</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[22:09:17]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Created task \u001b[32m'y_junction'\u001b[0m with task_id \u001b[32m'84aecb17-55cf-42b9-800c-e4b2955a99b8'\u001b[0m.    \u001b]8;id=332687;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=706591;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#120\u001b\\\u001b[2m120\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\"></pre>\n"
      ],
      "text/plain": [
       "\u001b[?25l"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2a5133b83ea44928a838ded70495acdd",
       "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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n",
       "\u001b[?25h"
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     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[22:09:20] </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Maximum FlexUnit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.172</span>                                                      <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#253\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">253</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m[22:09:20]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Maximum FlexUnit cost: \u001b[1;36m0.172\u001b[0m                                                      \u001b]8;id=59450;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=616033;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#253\u001b\\\u001b[2m253\u001b[0m\u001b]8;;\u001b\\\n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> status = queued                                                                   <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#262\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">262</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = queued                                                                   \u001b]8;id=902135;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=350207;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#262\u001b\\\u001b[2m262\u001b[0m\u001b]8;;\u001b\\\n"
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       "\u001b[?25l"
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       "\u001b[2;36m[22:09:27]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = preprocess                                                               \u001b]8;id=109854;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=257901;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#274\u001b\\\u001b[2m274\u001b[0m\u001b]8;;\u001b\\\n"
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       "\n",
       "\u001b[?25h\r",
       "\u001b[1A\u001b[2K"
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       "</pre>\n"
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       "\u001b[2;36m[22:09:31]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m starting up solver                                                                \u001b]8;id=521083;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=483131;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#278\u001b\\\u001b[2m278\u001b[0m\u001b]8;;\u001b\\\n"
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       "</pre>\n"
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       "\u001b[2;36m[22:09:41]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m running solver                                                                    \u001b]8;id=777085;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=10262;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#284\u001b\\\u001b[2m284\u001b[0m\u001b]8;;\u001b\\\n"
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = postprocess                                                              \u001b]8;id=338940;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=115432;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#301\u001b\\\u001b[2m301\u001b[0m\u001b]8;;\u001b\\\n"
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       "\u001b[?25l"
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       "\u001b[2;36m[22:13:06]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = success                                                                  \u001b]8;id=508137;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=706250;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#307\u001b\\\u001b[2m307\u001b[0m\u001b]8;;\u001b\\\n"
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       "</pre>\n"
      ],
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       "\n",
       "\u001b[?25h\r",
       "\u001b[1A\u001b[2K"
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       "</pre>\n"
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Billed FlexUnit cost: \u001b[1;36m0.083\u001b[0m                                                       \u001b]8;id=918832;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=250100;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#311\u001b\\\u001b[2m311\u001b[0m\u001b]8;;\u001b\\\n"
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       "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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n",
       "\u001b[?25h"
      ]
     },
     "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\">[22:13:11] </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> loading SimulationData from data/simulation_data.hdf5                             <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#415\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">415</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[22:13:11]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m loading SimulationData from data/simulation_data.hdf5                             \u001b]8;id=814437;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=138706;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#415\u001b\\\u001b[2m415\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"y_junction\")\n",
    "sim_data = job.run(path=\"data/simulation_data.hdf5\")\n"
   ]
  },
  {
   "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": 14,
   "id": "04666ade",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:13:14.576466Z",
     "iopub.status.busy": "2023-02-03T04:13:14.576352Z",
     "iopub.status.idle": "2023-02-03T04:13:14.790387Z",
     "shell.execute_reply": "2023-02-03T04:13:14.789920Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Insertion loss (dB)')"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2uK04AACAxtSgYLRo0SLnpTVWrVqlVatW6aOPPtLPf/5zzZw5060FAgAANJYGHa6fnZ3tDEYffPCBbrjhBv30pz9VQkKCkpKS3FogAABAY2nQiFG7du2c1xxbuXKlUlJSJFVd7d5ut7uvOgAAgEbUoBGja6+9VjfffLO6d++uU6dO6ec//7kkadu2bc5rmAEAADQ3DQpGf/rTn5SQkKCsrCzNnTtXbdq0kSSdOHFCd911l1sLBAAAaCyc+RoAADR5TfrM16+//ro+/PBD5/Pf//73atu2rYYPH64jR464rTgAAIDG1KBg9PTTTyswMFCStH79ei1cuFBz585VRESE7rvvPrcWCAAA0FgaNMcoKyvLOcn6/fff13XXXac77rhDI0aM0JgxY9xZHwAAQKNp0IhRmzZtdOrUKUnSxx9/rHHjxkmSAgICdO7cOfdVBwAA0IgaNGI0btw43X777Ro0aJD279+vX/ziF5KkPXv2KCEhwZ31AQAANJoGjRgtXLhQycnJOnnypN555x21b99ekrRlyxbddNNNbi0QAACgsXC4PgAAaPIa6/u7QbvSJCk/P1+vvPKKvv76a0lSnz59dNtttyksLMxtxQEAADSmBu1K27x5s7p27ao//elPOn36tE6fPq158+apa9eu2rp1q7trBAAAaBQN2pU2atQodevWTUuWLJGvb9WgU2VlpW6//XYdPHhQn3/+udsLdRd2pQEA0Pw01vd3g4JRYGCgtm3bpp49e7q07927V4mJiSopKXFbge5GMAIAoPlp0pcECQ0NVWZm5gXtWVlZCgkJ+dFFAQAAeEODgtHEiRM1bdo0LV++XFlZWcrKytKyZct0++23c7g+AABothp0VNpzzz0ni8WiyZMnq7KyUpLk5+enO++8U3PmzHFrgQAAAI3lR53HqKSkRN9++60kqWvXrgoKCnJbYZ7CHCMAAJqfJn8eI0kKCgpSv3793FULAACAV9U5GF177bV1Xum7777boGIAAAC8qc7BiDNaAwCAlq7Owei1117zZB0AAABe16DD9QEAAFoighEAAICJYAQAAGAiGAEAAJgIRgAAAKYGn+AxPT1d6enpys3NlcPhcHnt1Vdf/dGFAQAANLYGBaPHH39cTzzxhBITExUTEyOLxeLuugAAABpdg4LRokWLtHTpUt16663urgcAAMBrGjTHqLy8XMOHD3d3LQAAAF7VoGB0++23680333R3LQAAAF7VoF1ppaWlWrx4sT755BP1799ffn5+Lq/PmzfPLcUBAAA0pgYFo507d2rgwIGSpN27d7u8xkRsAADQXDUoGK1evdrddQAAAHjdjz7B49GjR3X06FF31AIAAOBVDQpGDodDTzzxhMLCwhQfH6/4+Hi1bdtWTz755AUnewQAAGguGrQr7aGHHtIrr7yiOXPmaMSIEZKkL774Qo899phKS0v11FNPubVIAACAxmAxDMOo70KxsbFatGiRfvWrX7m0//vf/9Zdd92lY8eOua1AdyssLFRYWJgKCgoUGhrq7XIAAEAdNNb3d4N2pZ0+fVo9e/a8oL1nz546ffr0jy4KAADAGxoUjAYMGKAFCxZc0L5gwQINGDDgRxfVGB7/7x7lFZV5uwwAANCENGiO0dy5czVhwgR98sknSk5OliStX79eWVlZWrFihVsL9JS3Nx/V/+0v1N1ju2nqiAQF+Pl4uyQAAOBlDRoxGj16tPbv369rrrlG+fn5ys/P17XXXquMjAyNGjXK3TV6RO+YUBWVVeqZlfuUMu8zfbDzuBow3QoAALQgDZp83ZxVT946cyZf6d+e1dz/26ecwqpdaoM6t9VDv+ilxIRwL1cJAABqaqzJ13UORjt37lTfvn1ltVq1c+fO7+3bv39/txTnCd/9wZaUV+rlzw5q8ecHda7CLkka3ydKD/yspy7p0MbL1QIAAKkJBiOr1ars7GxFRkbKarXKYrHUuuvJYrHIbre7vVB3udgPNqewVPM/2a/lm7LkMCRfq0U3J3XWjJ90V0Qbfy9WDAAAmlwwOnLkiDp37iyLxaIjR458b9/4+Hi3FOcJP/SD3Z9zVnM+2qdP9+VKkoJtPvrN6K6aNqqLgmwNmqsOAAB+pCYXjGr6/PPPNXz4cPn6ugaFyspKrVu3TpdffrnbCnS3uv5g132bp7QV+7TrWIEkKTLEX/eNu1TXD+kkX58ffYk5AABQD006GPn4+OjEiROKjIx0aT916pQiIyOb5a602jgchj7YdULP/t8+ZZ0+J0nqFtlGM8f30E97R8lisTRGyQAAtHpN+szXhmHUGgpOnTql4ODgH11UU2G1WvSrAbH6JHW0Hvllb7UN8tOB3CL979+26LqX1mnDwVPeLhEAALhRvSbNXHvttZKqJlj/+te/lr//+UnJdrtdO3fu1PDhw91bYRPg7+ujaSO76H+GdNLiz7/VK18c0tbMfE1c/JXG9Oig34/vqd6xXHcNAIDmrl7BKCwsTFLViFFISIgCAwOdr9lsNl122WWaPn26eytsQsIC/TRzfE9NSU7Qn9O/0bJNWVqTcVJrMk7qygGxui+lO4f4AwDQjNV7jpFhGLrtttv04osvqk2b5hcC3LmP8lBesZ7/OEMf7DwhSfKxWvQ/gztpRkp3dWwb+ANLAwCAumqyk68dDocCAgK0Z88ede/e3VN1eYwnfrB7jhdo3sf7lW4e4m/zsermpM66a2xXRYYEuOU9AABozZrs5Gur1aru3bvr1CkmHlfrExumV349VO/cOVyXXRKucrtDS9cd1uVzV+vpFV/rVFGZt0sEAAB10KCj0ubMmaOZM2dq9+7d7q6nWRsS305vTb9Mf5+WpEGd26q0wqHFnx/UqLmrNXflPp0pLvd2iQAA4Hs0KBhNnjxZGzdu1IABAxQYGKjw8HCXW30tXLhQCQkJCggIUFJSkjZu3HjRvkuWLNGoUaPUrl07tWvXTikpKd/bv7FZLBaN7B6hd+8crtemDlX/TmEqKbfrL2u+1ai5q/X8xxnKLyEgAQDQFDXoBI+vv/76974+ZcqUOq9r+fLlmjx5shYtWqSkpCTNnz9fb7/9tjIyMi44gaQkTZo0SSNGjNDw4cMVEBCgZ555Ru+995727Nmjjh07/uD7NdY+ymqGYeiTr3M1b9V+fX2iUJLUxt9XU0ckaNrILmobZPN4DQAANHdNdvK1uyUlJWno0KFasGCBpKrJ3XFxcbrnnnv04IMP/uDydrtd7dq104IFCzR58uQf7N/Ywaiaw2Ho473Zmv/JN9qXfVZSVUD69fCqgNQumIAEAMDFNNnJ19W+/fZbPfzww7rpppuUm1t1NNZHH32kPXv21Hkd5eXl2rJli1JSUs4XZLUqJSVF69evr9M6SkpKVFFRcdFdeGVlZSosLHS5eYPVatHP+sZoxYxRWnTLYPWMDlFRWaUWrD6gEc98qrQVXyv3bKlXagMAAFUaFIw+++wz9evXTxs2bNC7776roqIiSdKOHTs0e/bsOq8nLy9PdrtdUVFRLu1RUVHKzs6u0zoeeOABxcbGuoSrmtLS0hQWFua8xcXF1bk+T/huQOoTG6qScrte/vygRj2zWo/9Z49OFJzzao0AALRWDQpGDz74oP74xz9q1apVstnO7wK64oor9NVXX7mtuB8yZ84cLVu2TO+9954CAmo/X9CsWbNUUFDgvGVlZTVafd+nOiB9cM9IvfbroRrUua3KKs8f5v/Av3bqUF6xt8sEAKBVqdclQart2rVLb7755gXtkZGRysvLq/N6IiIi5OPjo5ycHJf2nJwcRUdHf++yzz33nObMmaNPPvlE/fv3v2g/f39/l2u6NTUWi0Vje0ZqTI8OWv/tKb3w6Tf66uBpLd+cpbe3ZOkX/WJ015huXIsNAIBG0KARo7Zt2+rEiRMXtG/btq1OR4ZVs9lsGjJkiNLT051tDodD6enpSk5Ovuhyc+fO1ZNPPqmVK1cqMTGxfsU3URaLRcO7RWjZHcl6585k/aRnpByG9MHOE/rFC2s19bWN+urgKXl5rjwAAC1ag4LRjTfeqAceeEDZ2dmyWCxyOBz68ssvdf/999fpyLCaUlNTtWTJEr3++uv6+uuvdeedd6q4uFhTp06VVHXOpFmzZjn7P/PMM3rkkUf06quvKiEhQdnZ2crOznbOc2oJhsSH65VfD9WKGaN05YBYWS3S6oyTunHxV7r6L+v00a4TsjsISAAAuFuDDtcvLy/X3XffraVLl8put8vX11d2u10333yzli5dKh8fn3qtb8GCBXr22WeVnZ2tgQMH6oUXXlBSUpIkacyYMUpISNDSpUslSQkJCTpy5MgF65g9e7Yee+yxH3wvbx2u/2MczivWX784qLc3H1VZpUOSlNA+SNNGXaL/GdxJgbb6/bwBAGhumsV5jLKysrRr1y4VFRVp0KBBzeKiss0xGFXLKyrTG+sO642vjii/pEKS1C7IT7deFq9bkxPUIaTpzqUCAODHaBbBqJrdbteuXbsUHx+vdu3auaMuj2nOwahaSXml/rkpS698eUhZp6sO7bf5WnXNwI6aNqqLLo0K8XKFAAC4V5MORr/73e/Ur18/TZs2TXa7XaNHj9a6desUFBSkDz74QGPGjPFAqe7REoJRNbvD0P/tydaStQe1LTPf2T6qe4RuG9lFo7t3kNVq8V6BAAC4SZMORp06ddL777+vxMREvf/++7rrrru0Zs0a/e1vf9Onn36qL7/80hO1ukVLCkY1bTlyWks+P6SP92arel521w7Bmjqii64d3FFBtgadmQEAgCahSQejgIAAHThwQJ06ddIdd9yhoKAgzZ8/X4cOHdKAAQO8dtmNumipwaha1ukSLV13WMs3ZamorFKSFBrgqxsS43Rrcrzi2wd7uUIAAOqvSV8rLSoqSnv37pXdbtfKlSs1btw4SVXXLavvEWlwr7jwID3yy95aP+sKzb6yt+LbB6mwtFJ//eKQxjy3Rrct3aQ1GblycLg/AAAXaND+lalTp+qGG25QTEyMLBaL8zplGzZsUM+ePd1aIBomJMBPU0d00ZTkBH22/6ReX39YazJO6tN9ufp0X67i2wfplqR4/c+QTmoXbPvhFQIA0Ao0+Ki0f/3rX8rKytL111+vTp06SZJef/11tW3bVldddZVbi3Snlr4r7fscyivW39Yf0dubs3TW3M1m87Xqyv6xuuWyzhoY11YWC5O1AQBNT5OeY9ScteZgVK2kvFL/3n5cf//qiPYcPz8frHdMqG5K6qyrBsYqNMDPixUCAOCqyQej9PR0paenKzc3Vw6Hw+W1V1991S3FeQLB6DzDMLQ9K19/++qIPth5QuXmWbUD/Xw0oX+MbhrWWYM7M4oEAPC+Jh2MHn/8cT3xxBNKTEx0zjOq6b333nNbge5GMKpdfkm53t16TG9tzNQ3ueevO9c9so0mDo3T1YM6KqINZ9YGAHhHkw5GMTExmjt3rm699VZP1ORRBKPvZxiGtmae0ZsbsvThruMqragaRfK1WpTSK0oTh8bp8ks7yIcTRwIAGlGTDkbt27fXxo0b1bVrV0/U5FEEo7orLK3Qf3cc1z83ZWnH0QJne2SIv64Z3FH/M7iTunP5EQBAI2jSweiBBx5QmzZt9Mgjj3iiJo8iGDXMvuxC/XPTUb237ajOmBewlaT+ncJ03eBOunJArMI57B8A4CFNOhjde++9euONN9S/f3/1799ffn6uRzDNmzfPbQW6G8HoxymvdGh1Rq7+teWoVu/LVaV5okhfq0WXX9pBVw2M1U97RyvQxok+AQDu06SD0dixYy++QotFn3766Y8qypMIRu5zqqhM/9lxXO9sPardx84f9h9k89H4PtH61cBYjewWIT+fBp1gHQAApyYdjJozgpFnHMgt0r+3H9O/tx9X5ukSZ3u7ID/9vF+MfjUgVsMSwmVl0jYAoAEIRh5CMPKsqqPa8vWf7cf04a4Tyisqd74WFeqvn/eN0YT+MRrSuR0hCQBQZ00yGF177bV16vfuu+82uCBPIxg1nkq7Q18dPK3/7Dimj3Zn62xppfO1yBB//bxvtH7RL0aJCeEc/g8A+F6N9f1dr4vIhoWFeaoOtEC+PlaN7B6hkd0j9OTVfbV2f55W7DqhVXtzlHu2TK+vP6LX1x9RRBubxvWO0k/7RGt41/by92XiNgDAO9iVhkZXVmnXlwfytGJXtj7ek63CGiNJIf6+GtszUuN6R2l0jw5csw0AIKmJ7kprCQhGTUuF3aENB09r5Z4T+nhP1UhSNT8fi5K6tFdKr0j9pFeU4sKDvFgpAMCbCEYeQjBquhwOQ9uy8vXx3mx9sjdH354sdnn90qg2GtszUlf0iNSQ+Hby5TQAANBqEIw8hGDUfBw8WaT0r3O16uscbT58Wo4av6mhAb66/NIOGm3eIkMDvFcoAMDjCEYeQjBqnvJLyvXZ/pNavS9Xa/afVH6Ny5JIUs/oEI2+tIMuv7SDhsS3U4AfE7gBoCUhGHkIwaj5szsMbc86o9X7Turzb05q17EC1fwt9ve1amhCuEZ0i9CIbu3VJzaM0wEAQDNHMPIQglHLc6qoTF8cyNNn+09q7Td5OlljArckhQX6aViXcCVf0l7JXdurR1QIJ5cEgGaGYOQhBKOWzTAMHcgt0hcH8vTlgVP66uApFZVVuvQJD7YpqUu4hiaEa1iXcPWKCWVECQCaOIKRhxCMWpdKu0O7jhVo/cFTWv/tKW0+fEbnKuwufUL8fTUkoZ2GJoRrSHw7DejUVoE25igBQFNCMPIQglHrVl7p0M6j+dpw6LQ2HjqtLUfOXDCi5Gu1qE9sqAbHt9OQ+HYaGNdWHdsGymJhVAkAvIVg5CEEI9Rkdxj6+kShMyRtPnJaOYVlF/SLaOOvgXFtNahzWw2Ma6u+sWEKC+Ks3ADQWAhGHkIwwvcxDEPHC0q15cgZbTl8Wtuy8rX3eKEqHRf+mcS3D1LfjmHqZ976xIaqbZDNC1UDQMtHMPIQghHqq7TCrj3HC7QtM1/bsvK162iBMk+X1Nq3Y9tA9e0Yqj6xVUGpR3QIu+EAwA0IRh5CMII75JeUa/exQu06VqBdx/K1+1jhRcNSiL+vekSHqGdMiHpEhehS89YumNElAKirxvr+9vXYmoEWrG2QTSO7R2hk9whnW8G5Cu09Xqg9xwu053ihvj5RqG9PFulsWaU2HzmjzUfOuKyjQ4i/ekSFqFtkG3WLbKOuHdqoa2SwOrTxZ4QJQINV2h2qsBsqtztUUX2rdH1eXukwnxvO/pUOhyrN5SrN5xV2Q3bnvaFKR9XzSochu736+fl2u0NyGFVtdsOQw3y9+nn1Y4dhyGFUTV9wGFXLGOZzQzWfS4aq2itLi3/oo7sFwQhwk7BAPyV3rTqJZLXySocO5hUpI/us9p4o1Dc5VY+P5Z/TybNlOnm26uSUNYUE+OqSiGAlRASrS41bfPtghQUy4RtoDirtDp2rsKu0wqHSCrtKK+wXPC+trHpcVmFXWfXjGvdlFQ6VVdpVbq9+XBVoyirtNR47zNer+pVXOlTLlMgWwVFW+6i8u7ErDfCCorJKfZNzVhnZZ/XtySJ9e7JY354sUtbpku/9Ry0s0E/x7YMUFx6k+PCq+45tA9WpXaBi2wZyjTigDhwOQ6WVdpWU21VSZldJRaWKy+w6V25XSXmlzlVUP7Y7H5+rqHpeWlHdp0bgKbertNKuc+VVAeVchb3WAza8xc/HIl+rVTZf8+ZjlZ+PRX4+VvNmka+PVb7WqjZfs3/Ndl9rjcc+FvlYzj/3MV+3mo99LOZji6qeW63yscp5b7VU9bNaLLJaJIvFIouq2i2WqntV/ed8zWKRSoqK9LPBlzDHyN0IRmjKyirtOpxXokN5xTqUV6zD5v2hU8UXXOqkNh1C/NWxbaBi2wYoNqwqLMW2DVB0WKCiQwMU0cYmXx9rI3wS4MersDtcgktJedV9cVmlissrVVJe9fhcuV0lFXaVlFW1lZhhpbis0hlozoebSpVWOBr1cwT4WRXo56MAl5tVAb5V9/7mfYCfj/x9z9/7m/c2X2uNex+Xx9VBx9/PvPc9H4D8zODSUnbNM8cIaIX8fX3UIzpEPaJDLnitpLxSmadLdORUibLM+6NnSnQs/5yOnjmnknK7c/fc9qza12+1VIWnqNAARYYEqEOIvzqE+CvSvI9oY1P7YH+1b2NTG3/fFvMPKjyrvNJRFUTMsFLy3fsyu0uQqX6tuLxGmKkerSm3q9gMMuV2zweYIJuPgmw+CrT5KNjmqwA/H2db9eNAPx8F2nwVaD4PqG7z81GgzQw4Nh8F+FatJ9DPNejwd9S8EIyAZiLI5que0aHqGX3h/ykZhqH8kgodPXNOxwvO6Xh+9a1Ux/LPKaewVLlny2R3GMopLDNPYlnwve9n87WqfbBN4cE2tQuyqV2wTe2C/NQuyKa25n1YkJ/aBvqpbZBNIQG+Cgnwlb8vu/OaGofDqNol9J1dRFWjJ98dUXEdXTlX7nAGnKqRmcqqUZwawcfTu418rRYF+/sqyOajYH9fBdt8FGTzVbD/+ftAP/Pe5qMgPx8Fmf2rgo3vBWEnyOYrf18rF5TGBQhGQAtgsViqgkuwTf06hdXax+4wdKq4TDkFZcouLNXJs2XKPVvqHGXKPVumU8VlOlVUrpJyu8orHTpRUKoTBaX1qsXf16qQAD+FBvhWfYn5+6iNf/XjC7/Uqr+sqnct+Pud371QtTuhxu4Dn+b3RWYYVUfs1HZkUNXRQYZz0mzVkUJ256Ta6sm3pRXnJ9zWnJhbWmlO4q05obdGe9Xcl6r1Ngabj1VB/lXBJLCW7Rxs860amakONGaf6rbqcFM1gnP+dZsvu3/ReAhGQCvhY7UoMqRqF1o/1R6eqp0rt+tUcZnyisp1pqRcZ4rLdaakQmeKy3W6pFwF5ypUUFKh/HPlOlNcoYJzFc5rzpVVOlRWVKa8oh+eE9UQ1RNE/XwssvlazYmfVRNGnZNAzcmd1TdrjQmcFtWc2Gk+Nx9L3z1MuOrxdw8ttjsPUXY4D1WutLseylzzcOemJMDPWhVGnOHlu7uMLtx9VBVazIBjBp9gf1/n7qfqZfyYv4YWgGAE4AKBNh91sgWpU7ugOi9jdxgqKqvU2dIKnS2tVOG5ChWXV6qoerJsWaWKyirPz0WpMe+keqSjenTEOSpijpLUPESk0mGo0mHXuQoPfPBG4jwqyJwgWz1p1s+netKspdYJuc5JuTUm5vr71ZjT4lvVJ9BWPaH3/DqCzDkwzW3EDWhsBCMAbuFjtSgs0M/t51oyDEMVdkNllXZV2I3vnJyu6kR0508wV3Wyuponkqs+mdz5E8WdHwmSqtpqvlf1IcMWVd/LPPTYIqu1arel1WKRX/Vhyj7m4ciWqsd+5vPqw5htvlb5Wa3y8z1/CDSTcYGmi2AEoEmzWCyy+VqYZwKgUfAvDQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYvB6MFi5cqISEBAUEBCgpKUkbN268aN89e/bouuuuU0JCgiwWi+bPn994hQIAgBbPq8Fo+fLlSk1N1ezZs7V161YNGDBA48ePV25ubq39S0pKdMkll2jOnDmKjo5u5GoBAEBL59VgNG/ePE2fPl1Tp05V7969tWjRIgUFBenVV1+ttf/QoUP17LPP6sYbb5S/v38jVwsAAFo6rwWj8vJybdmyRSkpKeeLsVqVkpKi9evXu+19ysrKVFhY6HIDAACojdeCUV5enux2u6Kiolzao6KilJ2d7bb3SUtLU1hYmPMWFxfntnUDAICWxeuTrz1t1qxZKigocN6ysrK8XRIAAGiifL31xhEREfLx8VFOTo5Le05OjlsnVvv7+zMfCQAA1InXRoxsNpuGDBmi9PR0Z5vD4VB6erqSk5O9VRYAAGjFvDZiJEmpqamaMmWKEhMTNWzYMM2fP1/FxcWaOnWqJGny5Mnq2LGj0tLSJFVN2N67d6/z8bFjx7R9+3a1adNG3bp189rnAAAALYNXg9HEiRN18uRJPfroo8rOztbAgQO1cuVK54TszMxMWa3nB7WOHz+uQYMGOZ8/99xzeu655zR69GitWbOmscsHAAAtjMUwDMPbRTSmwsJChYWFqaCgQKGhod4uBwAA1EFjfX+3+KPSAAAA6opgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmJpEMFq4cKESEhIUEBCgpKQkbdy48Xv7v/322+rZs6cCAgLUr18/rVixopEqBQAALZnXg9Hy5cuVmpqq2bNna+vWrRowYIDGjx+v3NzcWvuvW7dON910k6ZNm6Zt27bp6quv1tVXX63du3c3cuUAAKClsRiGYXizgKSkJA0dOlQLFiyQJDkcDsXFxemee+7Rgw8+eEH/iRMnqri4WB988IGz7bLLLtPAgQO1aNGiH3y/wsJChYWFqaCgQKGhoe77IAAAwGMa6/vb12NrroPy8nJt2bJFs2bNcrZZrValpKRo/fr1tS6zfv16paamurSNHz9e77//fq39y8rKVFZW5nxeUFAgqeoHDAAAmofq721Pj+d4NRjl5eXJbrcrKirKpT0qKkr79u2rdZns7Oxa+2dnZ9faPy0tTY8//vgF7XFxcQ2sGgAAeMupU6cUFhbmsfV7NRg1hlmzZrmMMOXn5ys+Pl6ZmZke/cHihxUWFiouLk5ZWVns1mwC2B5NB9ui6WBbNB0FBQXq3LmzwsPDPfo+Xg1GERER8vHxUU5Ojkt7Tk6OoqOja10mOjq6Xv39/f3l7+9/QXtYWBi/5E1EaGgo26IJYXs0HWyLpoNt0XRYrZ49bsyrR6XZbDYNGTJE6enpzjaHw6H09HQlJyfXukxycrJLf0latWrVRfsDAADUldd3paWmpmrKlClKTEzUsGHDNH/+fBUXF2vq1KmSpMmTJ6tjx45KS0uTJN17770aPXq0nn/+eU2YMEHLli3T5s2btXjxYm9+DAAA0AJ4PRhNnDhRJ0+e1KOPPqrs7GwNHDhQK1eudE6wzszMdBk2Gz58uN588009/PDD+sMf/qDu3bvr/fffV9++fev0fv7+/po9e3atu9fQuNgWTQvbo+lgWzQdbIumo7G2hdfPYwQAANBUeP3M1wAAAE0FwQgAAMBEMAIAADARjAAAAEzNOhh9/vnnuvLKKxUbGyuLxXLR66VVW7NmjSwWywW3715OZOHChUpISFBAQICSkpK0ceNGD36KlsMT2yMtLU1Dhw5VSEiIIiMjdfXVVysjI8PDn6T589TfRrU5c+bIYrHod7/7nfuLb2E8tS2OHTumW265Re3bt1dgYKD69eunzZs3e/CTNH+e2BZ2u12PPPKIunTposDAQHXt2lVPPvmkx6/n1dzVd1tIVdc+feihhxQfHy9/f38lJCTo1Vdfdenz9ttvq2fPngoICFC/fv20YsWKetfWrINRcXGxBgwYoIULF9ZruYyMDJ04ccJ5i4yMdL62fPlypaamavbs2dq6dasGDBig8ePHKzc3193ltzie2B6fffaZ7r77bn311VdatWqVKioq9NOf/lTFxcXuLr9F8cS2qLZp0ya9/PLL6t+/v7vKbdE8sS3OnDmjESNGyM/PTx999JH27t2r559/Xu3atXN3+S2KJ7bFM888o5deekkLFizQ119/rWeeeUZz587Viy++6O7yW5SGbIsbbrhB6enpeuWVV5SRkaG33npLPXr0cL6+bt063XTTTZo2bZq2bdumq6++WldffbV2795dv+KMFkKS8d57731vn9WrVxuSjDNnzly0z7Bhw4y7777b+dxutxuxsbFGWlqamyptHdy1Pb4rNzfXkGR89tlnP67AVsSd2+Ls2bNG9+7djVWrVhmjR4827r33XrfV2Rq4a1s88MADxsiRI91bXCvjrm0xYcIE47bbbnNpu/baa41Jkya5ocrWoS7b4qOPPjLCwsKMU6dOXbTPDTfcYEyYMMGlLSkpyfjf//3fetXTrEeMGmrgwIGKiYnRuHHj9OWXXzrby8vLtWXLFqWkpDjbrFarUlJStH79em+U2ipcbHvUpqCgQJI8fhHB1uqHtsXdd9+tCRMmuPyNwDO+b1v85z//UWJioq6//npFRkZq0KBBWrJkiZcqbfm+b1sMHz5c6enp2r9/vyRpx44d+uKLL/Tzn//cG6W2WNW/83PnzlXHjh116aWX6v7779e5c+ecfdavX3/Bv03jx4+v9/e318983ZhiYmK0aNEiJSYmqqysTH/96181ZswYbdiwQYMHD1ZeXp7sdrvzrNvVoqKitG/fPi9V3XL90Pb4LofDod/97ncaMWJEnc90jrqpy7ZYtmyZtm7dqk2bNnm52patLtvi4MGDeumll5Samqo//OEP2rRpk2bMmCGbzaYpU6Z4+RO0HHXZFg8++KAKCwvVs2dP+fj4yG6366mnntKkSZO8XH3LcvDgQX3xxRcKCAjQe++9p7y8PN111106deqUXnvtNUlSdnZ2rd/fF5sreVH1Gl9qwlSHobjaXH755cYtt9xiGIZhHDt2zJBkrFu3zqXPzJkzjWHDhrmjzFbDHdvju37zm98Y8fHxRlZW1o+srnVxx7bIzMw0IiMjjR07djhfZ1da/bnr78LPz89ITk526XPPPfcYl1122Y8tsdVw17Z46623jE6dOhlvvfWWsXPnTuONN94wwsPDjaVLl7qx2patLtti3LhxRkBAgJGfn+9se+eddwyLxWKUlJQYhlH1d/Hmm2+6LLdw4UIjMjKyXvW0yl1pNQ0bNkwHDhyQJEVERMjHx0c5OTkufXJychQdHe2N8lqdmtujpt/+9rf64IMPtHr1anXq1MkLlbU+NbfFli1blJubq8GDB8vX11e+vr767LPP9MILL8jX11d2u93L1bZs3/27iImJUe/evV369OrVS5mZmY1dWqvz3W0xc+ZMPfjgg7rxxhvVr18/3XrrrbrvvvucFz6He8TExKhjx44KCwtztvXq1UuGYejo0aOSpOjoaLd8f7f6YLR9+3bFxMRIkmw2m4YMGaL09HTn6w6HQ+np6UpOTvZWia1Kze0hSYZh6Le//a3ee+89ffrpp+rSpYsXq2tdam6Ln/zkJ9q1a5e2b9/uvCUmJmrSpEnavn27fHx8vFxty/bdv4sRI0ZccNqK/fv3Kz4+vrFLa3W+uy1KSkpcLnQuST4+PnI4HI1dWos2YsQIHT9+XEVFRc62/fv3y2q1Ov9nOTk52eX7W5JWrVpV7+/vZj3HqKioyCW5Hzp0SNu3b1d4eLg6d+6sWbNm6dixY3rjjTckSfPnz1eXLl3Up08flZaW6q9//as+/fRTffzxx851pKamasqUKUpMTNSwYcM0f/58FRcXa+rUqY3++ZobT2yPu+++W2+++ab+/e9/KyQkxLmvOCwsTIGBgY37AZsRd2+LkJCQC+Z1BQcHq3379sz3+gGe+Lu47777NHz4cD399NO64YYbtHHjRi1evFiLFy9u9M/XnHhiW1x55ZV66qmn1LlzZ/Xp00fbtm3TvHnzdNtttzX652tO6rstbr75Zj355JOaOnWqHn/8ceXl5WnmzJm67bbbnN8F9957r0aPHq3nn39eEyZM0LJly7R58+b6/13Ua8dbE1N9KOV3b1OmTDEMwzCmTJlijB492tn/mWeeMbp27WoEBAQY4eHhxpgxY4xPP/30gvW++OKLRufOnQ2bzWYMGzbM+OqrrxrpEzVvntgeta1PkvHaa6813gdrhjz1t1ETc4zqxlPb4r///a/Rt29fw9/f3+jZs6exePHiRvpEzZcntkVhYaFx7733Gp07dzYCAgKMSy65xHjooYeMsrKyRvxkzU99t4VhGMbXX39tpKSkGIGBgUanTp2M1NRU5/yiav/85z+NSy+91LDZbEafPn2MDz/8sN61WQyD03MCAABIzDECAABwIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAfCqMWPG6He/+523y3BqaD2nTp1SZGSkDh8+7PaavuvGG2/U888/7/H3AVojghHQCixatEghISGqrKx0thUVFcnPz09jxoxx6btmzRpZLBZ9++23jVxl43J3IHvqqad01VVXKSEhwW3rvJiHH35YTz31lAoKCjz+XkBrQzACWoGxY8eqqKhImzdvdratXbtW0dHR2rBhg0pLS53tq1evVufOndW1a1dvlNoslZSU6JVXXtG0adMa5f369u2rrl276u9//3ujvB/QmhCMgFagR48eiomJ0Zo1a5xta9as0VVXXaUuXbroq6++cmkfO3asJGnlypUaOXKk2rZtq/bt2+uXv/yly0jS4sWLFRsbK4fD4fJ+V111lW677TZJksPhUFpamrp06aLAwEANGDBA//rXvy5aa136jxkzRjNmzNDvf/97hYeHKzo6Wo899phLn7Nnz2rSpEkKDg5WTEyM/vSnPzlHiX7961/rs88+05///GdZLBZZLBaXXWAOh+N71/1dK1askL+/vy677DKX9i+++EJ+fn4uwfPw4cOyWCw6cuSI8/E777yjyy+/XIGBgRo6dKgyMzO1du1aXXbZZQoKCtJPfvIT5efnu6z7yiuv1LJly763LgD1RzACWomxY8dq9erVzuerV6/WmDFjNHr0aGf7uXPntGHDBmcwKi4uVmpqqjZv3qz09HRZrVZdc801ziB0/fXX69SpUy7rPX36tFauXKlJkyZJktLS0vTGG29o0aJF2rNnj+677z7dcsst+uyzz2qts679X3/9dQUHB2vDhg2aO3eunnjiCa1atcr5empqqr788kv95z//0apVq7R27Vpt3bpVkvTnP/9ZycnJmj59uk6cOKETJ04oLi6uzuv+rrVr12rIkCEXtG/fvl29evVSQECAs23btm1q166d4uPjtWPHDknSSy+9pKefflrr1q1TTk6ObrnlFs2ZM0cLFizQ6tWrtWPHDr322msu6x42bJg2btyosrKyi9YFoAEMAK3CkiVLjODgYKOiosIoLCw0fH19jdzcXOPNN980Lr/8csMwDCM9Pd2QZBw5cqTWdZw8edKQZOzatcvZdtVVVxm33Xab8/nLL79sxMbGGna73SgtLTWCgoKMdevWuaxn2rRpxk033WQYhmGMHj3auPfeew3DMOrUv3qZkSNHuvQZOnSo8cADDxiGYRiFhYWGn5+f8fbbbztfz8/PN4KCgpzvVfN9a/qhddfmuz+DarfffrsxefJkl7ZHH33UGDNmjGEYhvHYY48Z4eHhRl5envP1W265xUhISDCKi4udbT/72c+M3//+9y7r2bFjhyHJOHz48EXrAlB/jBgBrcSYMWNUXFysTZs2ae3atbr00kvVoUMHjR492jnPaM2aNbrkkkvUuXNnSdI333yjm266SZdccolCQ0OdE4szMzOd6500aZLeeecd58jFP/7xD914442yWq06cOCASkpKNG7cOLVp08Z5e+ONN2qd3F2f/v3793d5HhMTo9zcXEnSwYMHVVFRoWHDhjlfDwsLU48ePer0s/q+ddfm3LlzLqNC1bZv366BAwe6tG3bts3ZtmPHDl1zzTVq37698/XMzExNnDhRQUFBLm1dunRxWU9gYKCkqvlNANzH19sFAGgc3bp1U6dOnbR69WqdOXNGo0ePliTFxsYqLi5O69at0+rVq3XFFVc4l7nyyisVHx+vJUuWOOcS9e3bV+Xl5S59DMPQhx9+qKFDh2rt2rX605/+JKnqyDdJ+vDDD9WxY0eXevz9/S+osT79/fz8XJ5bLJYL5jo1VH3XHRERoTNnzri02e127d69W4MGDXJp37p1q6677jpJVcFp1qxZLq/v2LFD9913n/N5aWmpMjIyNGDAAJd+p0+fliR16NChjp8KQF0QjIBWZOzYsVqzZo3OnDmjmTNnOtsvv/xyffTRR9q4caPuvPNOSVXn5cnIyNCSJUs0atQoSVWTib8rICBA1157rf7xj3/owIED6tGjhwYPHixJ6t27t/z9/ZWZmekMYt+nvv0v5pJLLpGfn582bdrkHP0qKCjQ/v37dfnll0uSbDab7HZ7g9+jpkGDBl1whFhGRoZKS0sVGxvrbFu/fr2OHTumgQMHqrCwUIcPH3YJTocOHVJBQYFL265du2QYhvr16+ey/t27d6tTp06KiIhwy2cAUIVgBLQiY8eO1d13362KigqX4DF69Gj99re/VXl5uXPidbt27dS+fXstXrxYMTExyszM1IMPPljreidNmqRf/vKX2rNnj2655RZne0hIiO6//37dd999cjgcGjlypAoKCvTll18qNDRUU6ZMcVlPfftfTEhIiKZMmaKZM2cqPDxckZGRmj17tqxWqywWiyQpISFBGzZs0OHDh9WmTRuFh4fLam3Y7ILx48dr1qxZOnPmjNq1ayepajRIkl588UXNmDFDBw4c0IwZMyRJ5eXl2rFjh3x8fNS3b1/nerZv367w8HDFx8e7tHXt2lVt2rRxec+1a9fqpz/9aYPqBXBxzDECWpGxY8fq3Llz6tatm6Kiopzto0eP1tmzZ52H9UuS1WrVsmXLtGXLFvXt21f33Xefnn322VrXe8UVVyg8PFwZGRm6+eabXV578skn9cgjjygtLU29evXSz372M3344YcXzJlpaP+LmTdvnpKTk/XLX/5SKSkpGjFihMsRYvfff798fHzUu3dvdejQwWXeVH3169dPgwcP1j//+U9n2/bt2zV+/HgdPHhQ/fr100MPPaTHH39coaGheuGFF7Rjxw716NHDZW7Sjh07Ltj1tmPHjgt2o5WWlur999/X9OnTG1wzgNpZDMMwvF0EAHhacXGxOnbsqOeff94jJ2L88MMPNXPmTO3evVtWq1Xjx4/X0KFD9cc//tHt7/XSSy/pvffe08cff+z2dQOtHbvSALRI27Zt0759+zRs2DAVFBToiSeekFR18klPmDBhgr755hsdO3ZMcXFx2rFjh/Mkl+7m5+enF1980SPrBlo7RowAtEjbtm3T7bffroyMDNlsNg0ZMkTz5s27YBKzJ2RnZysmJkZ79uxR7969Pf5+ANyHYAQAAGBi8jUAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACY/h8bhl2fwHmyzwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "T = sim_data[\"flux\"].flux  # transmission to the top waveguide\n",
    "plt.plot(ldas, -10 * np.log10(2 * T))\n",
    "plt.xlim(1.5, 1.6)\n",
    "plt.ylim(0, 0.5)\n",
    "plt.xlabel(\"Wavelength ($\\mu m$)\")\n",
    "plt.ylabel(\"Insertion loss (dB)\")\n"
   ]
  },
  {
   "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": 15,
   "id": "e44e8128",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:13:14.909754Z",
     "iopub.status.busy": "2023-02-03T04:13:14.909567Z",
     "iopub.status.idle": "2023-02-03T04:13:16.242874Z",
     "shell.execute_reply": "2023-02-03T04:13:16.242374Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: title={'center': 'cross section at z=0.11'}, xlabel='x', ylabel='y'>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data.plot_field(\"field\", \"int\", f=freq0, vmin=0, vmax=2000)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51e66ae5",
   "metadata": {},
   "source": [
    "To quantitatively determine the mode composition, we can extract the mode amplitudes at the output waveguide. The result clearly indicates that higher order modes are excited very little. The power is predominantly in the fundamental mode as desired."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2958d01b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:13:16.245441Z",
     "iopub.status.busy": "2023-02-03T04:13:16.245285Z",
     "iopub.status.idle": "2023-02-03T04:13:16.371220Z",
     "shell.execute_reply": "2023-02-03T04:13:16.370828Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x177edd8a0>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mode_amp = sim_data[\"mode\"].amps.sel(direction=\"+\")\n",
    "mode_power = np.abs(mode_amp) ** 2 / T\n",
    "plt.plot(ldas, mode_power)\n",
    "plt.xlim(1.5, 1.6)\n",
    "plt.xlabel(\"Wavelength ($\\mu m$)\")\n",
    "plt.ylabel(\"Power fraction of the mode (%)\")\n",
    "plt.legend([\"Mode 0\", \"Mode 1\", \"Mode 2\", \"Mode 3\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "016a3a86",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "language": "python",
   "name": "python3"
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    "name": "ipython",
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       "msg_id": "",
       "outputs": [
        {
         "data": {
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          "text/plain": "\r\u001b[2K\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m26.5/26.5 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m26.5/26.5 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m"
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       "_view_module": "@jupyter-widgets/output",
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       "_view_name": "OutputView",
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       "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: #008000; text-decoration-color: #008000\">🚶 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'y_junction'...</span>\n<span style=\"color: #008000; text-decoration-color: #008000\">🚶 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'y_junction'...</span></pre>\n",
          "text/plain": "\r\u001b[2K\u001b[32m🚶 \u001b[0m \u001b[1;32mStarting 'y_junction'...\u001b[0m\n\u001b[32m🚶 \u001b[0m \u001b[1;32mStarting 'y_junction'...\u001b[0m"
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