{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "223695de",
   "metadata": {},
   "source": [
    "# 90 degree optical hybrid"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29d2491d",
   "metadata": {},
   "source": [
    "Note: The cost of running the entire notebook is higher than 1 FlexCredit.\n",
    "\n",
    "90 degree optical hybrids (also known as quadrature optical hybrids) are essential components in coherent transmission systems. A 90 degree optical hybrid is a six-port device consisting of two inputs and four outputs. In the ideal case, the outputs are the mixed signals of the inputs with 0, $\\pi$/2, $\\pi$, and 3$\\pi$/2 relative phase shifts. \n",
    "\n",
    "This notebook demonstrates the simulation of a compact and low-loss 90 degree optical hybrid based on a silicon-on-insulator platform. The device consists of a Y-branch, three 2x2 MMIs, and four 90 degree waveguide bends. Building those structures natively in `Tidy3D` is certainly doable but time consuming. Here, we build the device structures in a separate CAD editor and import the stl file into `Tidy3D` for simulation. \n",
    "\n",
    "The device design is adapted from [Hang Guan et al., \"Compact and low loss 90\u00b0 optical hybrid on a silicon-on-insulator platform,\" Opt. Express 25, 28957-28968 (2017)](https://opg.optica.org/oe/fulltext.cfm?uri=oe-25-23-28957&id=376719).\n",
    "\n",
    "<img src=\"img/optical_hybrid_schematic.png\" width=\"700\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0c653ce0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:52:10.326340Z",
     "iopub.status.busy": "2023-03-27T23:52:10.326160Z",
     "iopub.status.idle": "2023-03-27T23:52:11.520338Z",
     "shell.execute_reply": "2023-03-27T23:52:11.519748Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a604f3ef",
   "metadata": {},
   "source": [
    "## Simulation of the 2x2 MMI "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97cb0b02",
   "metadata": {},
   "source": [
    "To design the optical hybrid, we first design each component individually. For the Y-branch, we will use the same low-loss design demonstrated in the [reference](https://opg.optica.org/oe/fulltext.cfm?uri=oe-21-1-1310&id=248418) and our Y-branch [notebook](../notebooks/YJunction.html). The waveguide bends can be Euler bends or circular bands, which is also demonstrated in another [notebook](../notebooks/EulerWaveguideBend.html). \n",
    "\n",
    "For the 2x2 MMIs, an optimized design is demonstrated here. The design aims to have equal power splitting and a 90 degree phase difference in the through port and cross port. To simulate the MMI, we also built the structure as a stl file and only import it here.\n",
    "\n",
    "First, define some basic simulation parameters. We simulate at a relatively narrow wavelength band of 1530 nm to 1560 nm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "145c702f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:52:11.523003Z",
     "iopub.status.busy": "2023-03-27T23:52:11.522711Z",
     "iopub.status.idle": "2023-03-27T23:52:11.541265Z",
     "shell.execute_reply": "2023-03-27T23:52:11.540696Z"
    }
   },
   "outputs": [],
   "source": [
    "lda0 = 1.55  # central wavelength\n",
    "freq0 = td.C_0 / lda0  # central frequency\n",
    "ldas = np.linspace(1.53, 1.56, 101)  # wavelength range\n",
    "freqs = td.C_0 / ldas  # frequency range\n",
    "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5103bb83",
   "metadata": {},
   "source": [
    "Define material properties. For simplicity, we only use non-dispersive materials in this simulation. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e3439f1c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:52:11.543327Z",
     "iopub.status.busy": "2023-03-27T23:52:11.543150Z",
     "iopub.status.idle": "2023-03-27T23:52:11.560593Z",
     "shell.execute_reply": "2023-03-27T23:52:11.560026Z"
    }
   },
   "outputs": [],
   "source": [
    "n_si = 3.47  # silicon refractive index\n",
    "si = td.Medium(permittivity=n_si**2)\n",
    "\n",
    "n_sio2 = 1.45  # silicon oxide refractive index\n",
    "sio2 = td.Medium(permittivity=n_sio2**2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d4136ea",
   "metadata": {},
   "source": [
    "The structures will be imported from stl files, but it is good to define some geometric parameters to help set up the source, monitors, and simulation domains."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "db0b8467",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:52:11.562606Z",
     "iopub.status.busy": "2023-03-27T23:52:11.562428Z",
     "iopub.status.idle": "2023-03-27T23:52:11.579465Z",
     "shell.execute_reply": "2023-03-27T23:52:11.578963Z"
    }
   },
   "outputs": [],
   "source": [
    "thickness = 0.22  # si layer thickness\n",
    "width = 0.5  # waveguide width\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01374e67",
   "metadata": {},
   "source": [
    "Import the MMI geometry from the stl file and define the MMI structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0c2bd24e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:52:11.581529Z",
     "iopub.status.busy": "2023-03-27T23:52:11.581364Z",
     "iopub.status.idle": "2023-03-27T23:52:11.604743Z",
     "shell.execute_reply": "2023-03-27T23:52:11.604163Z"
    }
   },
   "outputs": [],
   "source": [
    "# import mmi geometry from a stl file\n",
    "mmi_geometry = td.TriangleMesh.from_stl(\n",
    "    filename=\"misc/mmi_stl.stl\",\n",
    ")\n",
    "\n",
    "# define mmi structure\n",
    "mmi = td.Structure(geometry=mmi_geometry, medium=si)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92f94448",
   "metadata": {},
   "source": [
    "Define a [ModeSource](../_autosummary/tidy3d.ModeSource.html) launching the TE0 mode at the top left waveguide. Two [ModeMonitors](../_autosummary/tidy3d.ModeMonitor.html) are added to the waveguides on the right to measure the power and phase of the outputs. To visualize the field distribution within the MMI region, we also add a [FieldMonitor](../_autosummary/tidy3d.FieldSource.html) in the xy plane. Finally, define a [Simulation](../_autosummary/tidy3d.Simulation.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9a9eacde",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:52:11.607029Z",
     "iopub.status.busy": "2023-03-27T23:52:11.606830Z",
     "iopub.status.idle": "2023-03-27T23:52:11.634134Z",
     "shell.execute_reply": "2023-03-27T23:52:11.632475Z"
    }
   },
   "outputs": [],
   "source": [
    "mode_spec = td.ModeSpec(\n",
    "    num_modes=1, target_neff=n_si\n",
    ")  # define a ModeSpec used in mode source and monitors\n",
    "\n",
    "# define a mode source\n",
    "mode_source = td.ModeSource(\n",
    "    center=(-5, 0.45, 0),\n",
    "    size=(0, 2 * width, 6 * thickness),\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "    direction=\"+\",\n",
    "    mode_spec=td.ModeSpec(num_modes=1, target_neff=n_si),\n",
    "    mode_index=0,\n",
    ")\n",
    "\n",
    "# define a mode monitor at the through port\n",
    "mode_monitor_through = td.ModeMonitor(\n",
    "    center=(6, 0.45, 0),\n",
    "    size=(0, 2 * width, 6 * thickness),\n",
    "    freqs=freqs,\n",
    "    name=\"through\",\n",
    "    mode_spec=mode_spec,\n",
    ")\n",
    "\n",
    "# define a mode monitor at the cross port\n",
    "mode_monitor_cross = td.ModeMonitor(\n",
    "    center=(6, -0.45, 0),\n",
    "    size=(0, 2 * width, 6 * thickness),\n",
    "    freqs=freqs,\n",
    "    name=\"cross\",\n",
    "    mode_spec=mode_spec,\n",
    ")\n",
    "\n",
    "# define a field monitor at the xp plane\n",
    "field_monitor = td.FieldMonitor(\n",
    "    center=(0, 0, 0), size=(td.inf, td.inf, 0), freqs=[freq0], name=\"field\"\n",
    ")\n",
    "\n",
    "run_time = 1e-12  # simulation run time\n",
    "\n",
    "sim = td.Simulation(\n",
    "    size=(13, 5, 10 * thickness),\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=30, wavelength=lda0),\n",
    "    structures=[mmi],\n",
    "    sources=[mode_source],\n",
    "    monitors=[field_monitor, mode_monitor_through, mode_monitor_cross],\n",
    "    run_time=run_time,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "    medium=sio2,\n",
    "    symmetry=(0, 0, 1),\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e664e13",
   "metadata": {},
   "source": [
    "Visualize the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e6dcdfa3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:52:11.639677Z",
     "iopub.status.busy": "2023-03-27T23:52:11.639304Z",
     "iopub.status.idle": "2023-03-27T23:52:11.961362Z",
     "shell.execute_reply": "2023-03-27T23:52:11.960853Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sim.plot(z=0)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9da5f01a",
   "metadata": {},
   "source": [
    "Submit the simulation job to the server."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1b6fec84",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:52:11.963534Z",
     "iopub.status.busy": "2023-03-27T23:52:11.963361Z",
     "iopub.status.idle": "2023-03-27T23:54:09.277934Z",
     "shell.execute_reply": "2023-03-27T23:54:09.277363Z"
    }
   },
   "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\">[11:55:19] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'mmi'</span> with task_id <span style=\"color: #008000; text-decoration-color: #008000\">'fdve-1d1735e0-8574-44f4-bfe0-4f6207e5722dv1'</span>.             <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#139\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">139</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:55:19]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'mmi'\u001b[0m with task_id \u001b[32m'fdve-1d1735e0-8574-44f4-bfe0-4f6207e5722dv1'\u001b[0m.             \u001b]8;id=66922;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=474223;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6a535a70ffdd44a2b9a41591ede1066a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cbf0eb85a9144e98a587cff0341193c8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[11:55:22] </span>status = queued                                                                            <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#269\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">269</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:55:22]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                                            \u001b]8;id=704302;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=608282;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#269\u001b\\\u001b[2m269\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[11:55:29] </span>status = preprocess                                                                        <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#263\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">263</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:55:29]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                                        \u001b]8;id=902667;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=768854;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#263\u001b\\\u001b[2m263\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": []
     },
     "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\">[11:55:32] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.116</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed FlexCredit cost <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#286\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">286</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>after a simulation run.                                                                    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:55:32]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.116\u001b[0m. 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 FlexCredit cost \u001b]8;id=761893;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=914725;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#286\u001b\\\u001b[2m286\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0mafter a simulation run.                                                                    \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>starting up solver                                                                         <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#290\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">290</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                                         \u001b]8;id=194882;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=357593;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#290\u001b\\\u001b[2m290\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>running solver                                                                             <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#300\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">300</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                                             \u001b]8;id=582172;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=34027;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#300\u001b\\\u001b[2m300\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7eb03692bdf945b2986fa3f58e45ff82",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[11:56:44] </span>early shutoff detected, exiting.                                                           <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#313\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">313</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:56:44]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                                                           \u001b]8;id=886825;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=410187;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#313\u001b\\\u001b[2m313\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": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[11:56:45] </span>status = postprocess                                                                       <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#330\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">330</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:56:45]\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                                                       \u001b]8;id=867329;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=190729;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#330\u001b\\\u001b[2m330\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[11:57:03] </span>status = success                                                                           <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#337\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">337</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:57:03]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                                           \u001b]8;id=715023;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=155220;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#337\u001b\\\u001b[2m337\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": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1b6342e380d040f8a5c0608895cd7c10",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[11:57:05] </span>loading SimulationData from data/simulation_data.hdf5                                      <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#512\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">512</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:57:05]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/simulation_data.hdf5                                      \u001b]8;id=508188;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=957158;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"mmi\", verbose=True)\n",
    "sim_data = job.run(path=\"data/simulation_data.hdf5\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e8dd3b3",
   "metadata": {},
   "source": [
    "The simulation is complete and the monitor data have been downloaded. First, we plot the field intensity distribution to visualize the power flow. We can observe that the two outputs have a similar intensity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ceed0bb5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:54:10.964547Z",
     "iopub.status.busy": "2023-03-27T23:54:10.964415Z",
     "iopub.status.idle": "2023-03-27T23:54:12.263157Z",
     "shell.execute_reply": "2023-03-27T23:54:12.262477Z"
    }
   },
   "outputs": [
    {
     "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_monitor_name=\"field\", field_name=\"E\", val=\"abs^2\", vmax=2000)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "daca909a",
   "metadata": {},
   "source": [
    "To quantitatively investigate the power in the two output waveguides, we compute the power from the mode amplitudes. Compared to the simulation results reported in the reference, the small discrepancy here is likely due to the different material properties used.\n",
    "\n",
    "Ideally, both power levels are 3 dB. Here, we see the through port has a slightly lower power level than the cross port. However, the small difference is acceptable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5ce5307d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:54:12.265182Z",
     "iopub.status.busy": "2023-03-27T23:54:12.265009Z",
     "iopub.status.idle": "2023-03-27T23:54:12.531491Z",
     "shell.execute_reply": "2023-03-27T23:54:12.530959Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compute power at the through port\n",
    "P_through = np.abs(sim_data[\"through\"].amps.sel(direction=\"+\").values) ** 2\n",
    "# compute power at the cross port\n",
    "P_cross = np.abs(sim_data[\"cross\"].amps.sel(direction=\"+\").values) ** 2\n",
    "\n",
    "# plot loss\n",
    "plt.plot(ldas, -10 * np.log10(P_through), label=\"through port\")\n",
    "plt.plot(ldas, -10 * np.log10(P_cross), label=\"cross port\")\n",
    "plt.xlabel(\"Wavelength ($\\mu m$)\")\n",
    "plt.ylabel(\"Insertion loss (dB)\")\n",
    "plt.ylim(2.5, 4)\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d38f9656",
   "metadata": {},
   "source": [
    "Lastly, we check the phase difference in the two outputs. Within the wavelength range, the phase difference is only about 1 degree from the ideal 90 degree."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "38b9fa2c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:54:12.533674Z",
     "iopub.status.busy": "2023-03-27T23:54:12.533494Z",
     "iopub.status.idle": "2023-03-27T23:54:12.687873Z",
     "shell.execute_reply": "2023-03-27T23:54:12.687284Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjMAAAG0CAYAAADHD6Y/AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy88F64QAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA6w0lEQVR4nO3de3xT9f3H8XfSpmla2kCBQgulcpP7RRAVZFwmE1GRCVNkoIzLfGxjMkBR2IbKEFE2meDv94OpUwRhbm7D6ZhcRGDcRK4VUbkJljsKbdNr2ibn90faQKBAUlLCKa/n45FHcr7nm5NPvo8DfT/O+Z4ci2EYhgAAAEzKGukCAAAArgRhBgAAmBphBgAAmBphBgAAmBphBgAAmBphBgAAmBphBgAAmFp0pAuoal6vV8eOHVNCQoIsFkukywEAAEEwDEO5ublKTU2V1XrpYy/VPswcO3ZMaWlpkS4DAABUwuHDh9WwYcNL9qn2YSYhIUGSbzASExMjXA0AAAiGy+VSWlqa/+/4pVT7MFN+aikxMZEwAwCAyQQzRYQJwAAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQIMwAAwNQiHmZyc3M1btw4paeny+FwqFu3btqyZUuFfX/2s5/JYrHo5ZdfvrpFAgCAa1bEw8zo0aO1cuVKLVy4ULt27dKdd96pPn366OjRowH9lixZok8++USpqakRqhQAAFyLIhpmCgsL9Y9//EMzZ85Ujx491KxZMz377LNq1qyZ5s6d6+939OhRPfbYY1q0aJFsNlsEKwYAANea6Eh+eGlpqTwej2JjYwPaHQ6H1q9fL0nyer16+OGHNXHiRLVp0+ay23S73XK73f5ll8sV3qIBAMA1JaJHZhISEtS1a1dNmzZNx44dk8fj0dtvv61Nmzbp+PHjkqQXX3xR0dHRGjt2bFDbnDFjhpxOp/+RlpZWlV8BAABEWMTnzCxcuFCGYahBgway2+2aM2eOhgwZIqvVqm3btmn27NmaP3++LBZLUNubPHmycnJy/I/Dhw9X8TcAAACRZDEMw4h0EZKUn58vl8ullJQUDR48WHl5efrBD36gCRMmyGo9m7k8Ho+sVqvS0tJ06NChy27X5XLJ6XQqJydHiYmJVfgNAABAuITy9zuic2bOFR8fr/j4eGVlZWn58uWaOXOmBg0apD59+gT069u3rx5++GGNGDEiQpUCAIBrScTDzPLly2UYhlq0aKH9+/dr4sSJatmypUaMGCGbzabatWsH9LfZbKpfv75atGgRoYoBAMC1JOJzZnJycjRmzBi1bNlSjzzyiLp3767ly5dzCTYAAAjKNTNnpqowZwYAAPMJ5e93xI/MAAAAXAnCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMDXCDAAAMLWIh5nc3FyNGzdO6enpcjgc6tatm7Zs2SJJKikp0VNPPaV27dopPj5eqampeuSRR3Ts2LEIVw0AAK4VEQ8zo0eP1sqVK7Vw4ULt2rVLd955p/r06aOjR4+qoKBA27dv15QpU7R9+3b985//1J49e3TfffdFumwAAHCNsBiGYUTqwwsLC5WQkKB//etfuueee/ztnTt3Vr9+/fTcc89d8J4tW7bolltu0TfffKNGjRpd9jNcLpecTqdycnKUmJgY1voBAEDVCOXvd/RVqqlCpaWl8ng8io2NDWh3OBxav359he/JycmRxWJRzZo1K1zvdrvldrv9yy6XK2z1AgCAa09ETzMlJCSoa9eumjZtmo4dOyaPx6O3335bmzZt0vHjxy/oX1RUpKeeekpDhgy5aEqbMWOGnE6n/5GWllbVXwMAAERQRE8zSdKBAwc0cuRI/fe//1VUVJQ6deqkG2+8Udu2bdOXX37p71dSUqJBgwbpyJEjWrNmzUXDTEVHZtLS0jjNBACAiZjmNJMkNW3aVGvXrlV+fr5cLpdSUlI0ePBgNWnSxN+npKREDz74oL755ht9/PHHl/xSdrtddrv9apQOAACuARG/mqlcfHy8UlJSlJWVpeXLl2vAgAGSzgaZffv26aOPPlLt2rUjXCkAALiWRPzIzPLly2UYhlq0aKH9+/dr4sSJatmypUaMGKGSkhL96Ec/0vbt2/Xvf/9bHo9HJ06ckCQlJSUpJiYmwtUDAIBIi3iYycnJ0eTJk3XkyBElJSVp0KBBmj59umw2mw4dOqT3339fktSxY8eA961evVq9evW6+gUDAIBrSsQnAFc1fmcGAADzCeXv9zUzZwYAAKAyCDMAAMDUCDMAAMDUCDMAAMDUCDMAAMDUCDMAAMDUCDMAAMDUCDMAAMDUCDMAAMDUCDMAAMDUCDMAAMDUKh1miouLtWfPHpWWloazHgAAgJCEHGYKCgo0atQoxcXFqU2bNsrMzJQkPfbYY3rhhRfCXiAAAMClhBxmJk+erIyMDK1Zs0axsbH+9j59+uivf/1rWIsDAAC4nOhQ3/Dee+/pr3/9q2677TZZLBZ/e5s2bXTgwIGwFgcAAHA5IR+Z+fbbb5WcnHxBe35+fkC4AQAAuBpCDjM333yzli5d6l8uDzCvv/66unbtGr7KAAAAghDyaabnn39e/fr10xdffKHS0lLNnj1bX3zxhTZu3Ki1a9dWRY0AAAAXFfKRme7du2vnzp0qLS1Vu3bttGLFCiUnJ2vTpk3q3LlzVdQIAABwURbDMIxIF1GVXC6XnE6ncnJylJiYGOlyAABAEEL5+x3ykZn//Oc/Wr58+QXty5cv14cffhjq5gAAAK5IyGFm0qRJ8ng8F7QbhqFJkyaFpSgAAIBghRxm9u3bp9atW1/Q3rJlS+3fvz8sRQEAAAQr5DDjdDr19ddfX9C+f/9+xcfHh6UoAACAYIUcZgYMGKBx48YF/Nrv/v379fjjj+u+++4La3EAAACXE3KYmTlzpuLj49WyZUs1btxYjRs3VqtWrVS7dm394Q9/qIoaAQAALirkH81zOp3auHGjVq5cqYyMDDkcDrVv3149evSoivoAAAAuid+ZAQAA15xQ/n6HfGRGklatWqVVq1bp1KlT8nq9AeveeOONymwSAACgUkIOM1OnTtXvfvc73XzzzUpJSeFO2QAAIKJCDjPz5s3T/Pnz9fDDD1dFPQAAACEJ+Wqm4uJidevWrSpqAQAACFnIYWb06NFavHhxVdQCAAAQspBPMxUVFenVV1/VRx99pPbt28tmswWsnzVrVtiKAwAAuJyQw8xnn32mjh07SpI+//zzgHVMBgYAAFdbyGFm9erVVVEHAABApYQ8Z6bc/v37tXz5chUWFkqSqvlv7wEAgGtUyGHm9OnTuuOOO3TjjTfq7rvv1vHjxyVJo0aN0uOPPx72AgEAAC4l5DAzfvx42Ww2ZWZmKi4uzt8+ePBgLVu2LKzFAQAAXE7Ic2ZWrFih5cuXq2HDhgHtzZs31zfffBO2wgAAAIIR8pGZ/Pz8gCMy5c6cOSO73R6WogAAAIIVcpj53ve+pwULFviXLRaLvF6vZs6cqd69e4e1OAAAgMsJ+TTTzJkzdccdd2jr1q0qLi7Wk08+qd27d+vMmTPasGFDVdQIAABwUSEfmWnbtq327t2r7t27a8CAAcrPz9fAgQO1Y8cONW3atCpqBAAAuKiQjsyUlJTorrvu0rx58/Sb3/ymqmoCAAAIWkhHZmw2mz777LOqqgUAACBkIZ9mGjZsmP785z9XRS0AAAAhC3kCcGlpqd544w199NFH6ty5s+Lj4wPWc9dsAABwNYUcZj7//HN16tRJkrR3796Addw1GwAAXG3cNRsAAJgad80GAACmxl2zAQCAqXHXbAAAYGrcNRsAAJgad80GAACmxl2zAQCAqXHXbAAAYGrcNRsAAJhaUEdmBg4cqPnz5ysxMVELFizQ4MGDuWs2AAC4JgR1ZObf//638vPzJUkjRoxQTk5OlRYFAAAQrKCOzLRs2VKTJ09W7969ZRiG/va3vykxMbHCvo888khYCwQAALgUixHEfQg2bNigxx9/XAcOHNCZM2eUkJBQ4U0lLRaLzpw5UyWFVpbL5ZLT6VROTs5FAxgAALi2hPL3O6gwcy6r1aoTJ04oOTn5ioq8WggzAACYTyh/v4OaMzNw4EC5XC5J0ptvvqmEhIQrr7JMbm6uxo0bp/T0dDkcDnXr1k1btmzxrzcMQ08//bRSUlLkcDjUp08f7du3L2yfDwAAzC3kCcAjR45Ubm5u2AoYPXq0Vq5cqYULF2rXrl2688471adPHx09elSS73dt5syZo3nz5mnz5s2Kj49X3759VVRUFLYaAACAeQV1mql9+/bq1KmTevfurREjRmjOnDlhmQBcWFiohIQE/etf/9I999zjb+/cubP69eunadOmKTU1VY8//rieeOIJSVJOTo7q1aun+fPn66GHHrrsZ3CaCQAA8wnl73dQVzPNmzdPEyZM0NKlS2WxWPTb3/72ohOAQwkzpaWl8ng8io2NDWh3OBxav369Dh48qBMnTqhPnz7+dU6nU7feeqs2bdpUYZhxu91yu93+5fLTYwAAoHoKKsx069ZNn3zyiSTfBOC9e/eGZQJwQkKCunbtqmnTpqlVq1aqV6+e/vKXv2jTpk1q1qyZTpw4IUmqV69ewPvq1avnX3e+GTNmaOrUqVdcGwAAMIeQb2dw8OBB1a1bN2wFLFy4UIZhqEGDBrLb7ZozZ46GDBkiqzXk0iRJkydPVk5Ojv9x+PDhsNUKAACuPUEdmfnss8/Utm1bWa1W5eTkaNeuXRft2759+5AKaNq0qdauXav8/Hy5XC6lpKRo8ODBatKkierXry9JOnnypFJSUvzvOXnypDp27Fjh9ux2u+x2e0g1AAAA8woqzHTs2NH/2zIdO3aUxWLRufOGy5ctFos8Hk+lComPj1d8fLyysrK0fPlyzZw5U40bN1b9+vW1atUqf3hxuVzavHmzfv7zn1fqcwAAQPUSVJg599TSwYMHw1rA8uXLZRiGWrRoof3792vixIlq2bKlRowYIYvFonHjxum5555T8+bN1bhxY02ZMkWpqan64Q9/GNY6AACAOQUVZtLT0yt8HQ45OTmaPHmyjhw5oqSkJA0aNEjTp0+XzWaTJD355JPKz8/Xo48+quzsbHXv3l3Lli274AooAABwfQrqd2bef//9oDd43333XVFB4cbvzAAAYD5h/52Z80/pVDRnplxl58wAAABURlDXP3u9Xv9jxYoV6tixoz788ENlZ2crOztb//nPf9SpUyctW7asqusFAAAIENSRmXONGzdO8+bNU/fu3f1tffv2VVxcnB599FF9+eWXYS0QAADgUkIOMwcOHFDNmjUvaHc6nTp06FAYSjKHnYeztW7vt2qY5FCDmnFqWMuheomxirJeeJsHAABQdUIOM126dNGECRO0cOFC/20GTp48qYkTJ+qWW24Je4HXqo0HvtNLK/cGtEVbLUqpGauGZeEmLcn33LBWnBrUcqg+YQcAgLALOcy88cYbuv/++9WoUSOlpaVJkg4fPqzmzZvrvffeC3d916yW9RP0QOeGOppdqCNZhTqeU6gSj6HDZwp1+Exhhe+JtlpU3xmrhrV8R3Ma1HL4wk5NhxrUcijF6VBMdOVu4wAAwPUqqEuzz2cYhlauXKmvvvpKktSqVSv16dOnwjtpR9rVujTb4zV0KrdIR7MKdTirQEfOlD1nFepodqGOZfvCzqVYLFLdGnY1qOVQg5plj1oOpTodSi1bTnREX5PjDABAOIXy97tSYcZMrpXfmfF4DX2b69aRrAL/0Rzfw7d8NKtQ7lLvZbcTHxOl1JqOsw9nrP91g5oO1XPaZY+OugrfCACAqhP235nBlYsqO8VU3xmrmytYbxiGTucX61hZsPEdzSnSsexCHcvxtZ3OL1Z+sUf7TuVp36m8i35W3QR7WbiJVarTofplgSfFGasUp0N1E+zM3QEAVBuEmWuExWJRnRp21alhV/uGNSvsU1Ti8YWbspBzJLtQx7MLdTzHt3w023d059tct77NdSvjcMWfFW21qF5irFJr+sJNyjmhpzzw1I6PkZXAAwAwAcKMicTaotSkbg01qVujwvWGYehMfrGOZRf55+kczynUsZwincgp0vHsQp3MdavUa/hObWUXSsqqcFu2KF/gSXHGqr7Td1SnfmKs/+hSijNWdWvYFR3FhGUAQGQRZqoRi8Wi2jXsql3DrnYNnRX2KZ+ofCy7yBd0yo70nMgp0nGXL/B8m+dWicfwz+u5WOCxWnyntPwhJ9EXfOo77aqf6PC3OWKYwwMAqDqVCjMHDhzQm2++qQMHDmj27NlKTk7Whx9+qEaNGqlNmzbhrhFhFGW1+E4tOR2SalXYp8Tj1alct07kFOpEjlvHc3ynsk64fKHnRE6RTrqKVOo1dNLl1kmXWxlHci76mQmx0aqX6As2yYl21UuMVb0Eu+o7Y5Vc1l43wS4bR3kAAJUQ8tVMa9euVb9+/XT77bfrv//9r7788ks1adJEL7zwgrZu3aq///3vVVVrpVwrVzNVN16voe/y3TpZFnZOuooCA0/Zc0FxcDcetVik2vExSk6IVb2ywJOcYFdy2XO9siBUpwahBwCuB1V6aXbXrl31wAMPaMKECUpISFBGRoaaNGmiTz/9VAMHDtSRI0euqPhwI8xEjmEYynOX6qSrqOwIji/knCp7Xd5+Krfosr/BU6489NRNKAs7CXbVLXtOLjvC42vn9BYAmFmVXpq9a9cuLV68+IL25ORkfffdd6FuDtWYxWJRQqxNCbE2NUtOuGg/r9dQVkGxP/CcdBXpVK4v5PjCjlvflrWVeg19l1es7/KK9eXxS39+gj1adRPsqlMWeOrWKHs+JwTVTbArKS6GicwAYGIhh5maNWvq+PHjaty4cUD7jh071KBBg7AVhuuH1Xp24nLr1Iunb6/X0JmCYn/Y+dbl1rd5bp0qX851+0NQUYlXue5S5bpL9fV3+Zf8/PKjPXXKws7Z5xj/cvkjKT6G3+gBgGtMyGHmoYce0lNPPaV3331XFotFXq9XGzZs0BNPPKFHHnmkKmoEJPlCT3mouNQ0c8MwlOsu1SmXW9/luf2/u3Mq98Ll0/luGYb8R3u+OpF76RosUlJ8jGrH21UnwReA/K/LnmvH21W7hm9drI1TXQBQ1UKeM1NcXKwxY8Zo/vz58ng8io6Olsfj0Y9//GPNnz9fUVHX1n/ezJnBpXi8vt/m+facoOMPPHnnthUrq6BYod78Iz4mquyoU1nIiY9R7RoxSio7EpRUtlz+msnNAOBzVe7NdPjwYe3atUt5eXm66aab1Lx580oVW9UIMwiXUo9XZwqK9V1usU7n+4LO6bxiX+gpazudV+xvL/Zc/l5b53M6bKod7ws7SecEn1pxvkdSfIxqxccoKS5GSTViFB8TxY1HAVRLV+XeTGlpaUpLS5PH49GuXbuUlZWlWrUq/t0SoDqIjrIqOSFWyQmxl+1bfqrrdF6xTuf5juycznfrTF6xTueXPfLcOpPvO711Jt8tryHlFJYop7DksvN8ysVEWVUr3qakeLuS4m1nA09cjGrF2VQrPkY143zhp1bZ+jgCEIBqJuQwM27cOLVr106jRo2Sx+NRz549tXHjRsXFxenf//63evXqVQVlAuZisViUGGtTYqxNjevEX7a/12sou7BEp/PcOp1frDPnBJ7sghKdyfed5jqTX6ys/GKdKShWUYlXxR6v/4cLgxUTbS0LN2WBJy5GNc97Lg8+5W2JsTbu1QXgmhVymPn73/+uYcOGSZI++OADff311/rqq6+0cOFC/eY3v9GGDRvCXiRQ3VmtFv+ppWBP2BYWe3SmoFhn8nzhJqssBJ0pCzvZBcXKyi9RVkFx2aNExaVeFZd6fT9q6CoKuj6LxXcKrFZcjJwOm2rG2VTTYVPNsmV/W5xNTsfZNqfDppho5gEBqFohz5mJjY3V/v371bBhQz366KOKi4vTyy+/rIMHD6pDhw5yuVxVVWulMGcG8DEMQwXFnoCjPNkFJf6gkx3w7AtC2QXFyg/yV5wvJi4myh9sEs8JOTXLX8fZAsJPeZ/EWIIQcD2r0jkz9erV0xdffKGUlBQtW7ZMc+fOlSQVFBRcc1cyATjLYrEo3h6teHu00pLign6fu9Tjm8tTUOIPO9lly9mFvkBUPtcnu6wtp6BErqJSSVJBsUcFxR4dzwn+SFA5hy2qLOBE+8NOQqxNibHRSnTYlBAbrcTYC0NQQmy0EmKj+TFE4DoRcpgZMWKEHnzwQaWkpMhisahPnz6SpM2bN6tly5ZhLxBAZNmjo5ScEBXUxOdzebyGcovOhpzywFP+cBUGhiB/e1GJcsuCUGGJR4UlHp2o5AFfhy1KNcqCjT8ElYWdRIdvOSHWF5YS7DZ/38RYm2rYo1UjNprL5QETCDnMPPvss2rbtq0OHz6sBx54QHa7XZIUFRWlSZMmhb1AAOYUZbWoZpzvaqr02qG9tzwIuQpL/QGnPOyUt7uKfIHIVVRa9lwekkpVWOI7NVYehr7NDX6C9PlibVbVsPsCUA17tOLtUQHLCbG+0JNg9wWj8hBUwx4d8NoebeUqMqCKVPp3ZsyCOTPA9afE41VeUalyi0r9R3pyz392+0JQeR9X2bry95UHonCJtvpO85WHnHh7lGrE2lTDHlW2HK34mLJne5T/9dkAdbZPnD2KI0ao9qr8d2by8/O1du1aZWZmqri4OGDd2LFjK7NJAAgbW5TVd+l5fEylt1Hq8Srf7VGuu0R57lJ/yMkte53nLg9HpWfXu0vK1vke+W6P8ty+U2alXsN/dCkcYqKtio+JUlxMWfgpDzoxvtdxMb4A5IiJ8geguLL+cee+L8bXx2HzPbgEH2YUcpjZsWOH7r77bhUUFCg/P19JSUn67rvvFBcXp+TkZMIMgGohOsoqZ5xVzjjbFW3H6zVUUOLxh5x899mwk1dUqvxiXyDK96/zqKA4sG95KCooLlWJx3cwvfwy+6yC8ISjcvZoa0DYccRE+0OTIyZKcbYoX/g577XD5gtLsWWhyBFz4XJsNGEJVSPkMDN+/Hj1799f8+bNk9Pp1CeffCKbzaZhw4bpV7/6VVXUCACmZbVa/KeWwqG41KuC4lLlF3v8Aaig/HXxOa/LQlF+sUeFZW2FJR5/f9/D1+/cU2ruUq/cVRCSysXarP6jQOcGoVhblOzR5aHHGtDue1hlj46SPdpa1tfXp3zd+X0JTteXkP917dy5U3/6059ktVoVFRUlt9utJk2aaObMmRo+fLgGDhxYFXUCAOQ7vRQTHaOawV9df1ler6GiUl/oKSj2hZuCYo8K3L4wdG7oKSwu9a8vKnsuPOc9RWWTrouKPSoo8a1zl569T1lRiVdFJV5lqWrC0rlioqyyR1tlLw8454Wic4ORPTpKdpv17OvowP6+cbcqJsoqW7TV//5z3xcTbZU96mzfKMLUVRNymLHZbLJafRPPkpOTlZmZqVatWsnpdOrw4cNhLxAAULWsVkvZXJpohXjhWVDOD0v+EFQWdopKPGXrvf4w5C579vXxyl3q8R81cpeUvafE6wtO5dsp9fhPw0lSscd3y4/csnlLV1uU1aKYKGtAECoPPeXLFb22R1tlizrbZvM/WxRt9YWpmPNe26Ksio7y9YmJspYtn31ti7bKZrUouqzdZvU9R1st1eIqu5DDzE033aQtW7aoefPm6tmzp55++ml99913Wrhwodq2bVsVNQIATKyqw9K5PF5D7lJP2RGgs6GnqNT32heGzglHJeeEpHOWi857Lp+j5PaUv/Zc8J5ij1fnXh/s8Roq9HrCfmVcuEVbLf7wY4uyBiyXv44qD0JWi+/1ec/92qZoUOeGkfsOob7h+eefV25uriRp+vTpeuSRR/Tzn/9czZs31xtvvBH2AgEACFaUPzhd/c82DEOlXsMXesrCT4nn7Otiz9lQVOzxyF1yTtu568qXPWe3UVJqqKSsrcTjVanHUInXUEn5+nNel9dQ4il/lC17A8NWuVKvoVKvR1dy5q9F/YTKvzkM+J0ZAACuEx6vLxSVP5d4DJV6feGouDwklQWi0rL1Hq+vj+89vmWPYchT9j6P11CrlER1SKsZ1lqr/HdmAACA+URZLYqyVr/7KIb8E5InT57Uww8/rNTUVEVHRysqKirgAQAAcDWFfGTmJz/5iTIzMzVlyhT/zSYBAAAiJeQws379eq1bt04dO3asgnIAAABCE/JpprS0NFXzOcMAAMBEQg4zL7/8siZNmqRDhw5VQTkAAAChCeo0U61atQLmxuTn56tp06aKi4uTzRZ4E7YzZ86Et0IAAIBLCCrMvPzyy1VcBgAAQOUEFWaGDx9e1XUAAABUStBzZrxer1588UXdfvvt6tKliyZNmqTCwsKqrA0AAOCygg4z06dP169//WvVqFFDDRo00OzZszVmzJiqrA0AAOCygg4zCxYs0P/93/9p+fLleu+99/TBBx9o0aJF8nq9VVkfAADAJQUdZjIzM3X33Xf7l/v06SOLxaJjx45VSWEAAADBCDrMlJaWKjY2NqDNZrOppOQK7hkOAABwhYK+nYFhGPrJT34iu93ubysqKtLPfvYzxcfH+9v++c9/hrdCAACASwg6zFR0efawYcPCWgwAAECogg4zb775ZlXWAQAAUCkh35sJAADgWkKYAQAApkaYAQAApkaYAQAApkaYAQAApkaYAQAApkaYAQAApkaYAQAApkaYAQAApkaYAQAAphbRMOPxeDRlyhQ1btxYDodDTZs21bRp02QYhr9PXl6efvnLX6phw4ZyOBxq3bq15s2bF8GqAQDAtSToezNVhRdffFFz587VW2+9pTZt2mjr1q0aMWKEnE6nxo4dK0maMGGCPv74Y7399tu64YYbtGLFCv3iF79Qamqq7rvvvkiWDwAArgERPTKzceNGDRgwQPfcc49uuOEG/ehHP9Kdd96pTz/9NKDP8OHD1atXL91www169NFH1aFDh4A+AADg+hXRMNOtWzetWrVKe/fulSRlZGRo/fr16tevX0Cf999/X0ePHpVhGFq9erX27t2rO++8s8Jtut1uuVyugAcAAKi+InqaadKkSXK5XGrZsqWioqLk8Xg0ffp0DR061N/nlVde0aOPPqqGDRsqOjpaVqtVr732mnr06FHhNmfMmKGpU6dera8AAAAiLKJHZv72t79p0aJFWrx4sbZv36633npLf/jDH/TWW2/5+7zyyiv65JNP9P7772vbtm166aWXNGbMGH300UcVbnPy5MnKycnxPw4fPny1vg4AAIgAi3HupUNXWVpamiZNmqQxY8b425577jm9/fbb+uqrr1RYWCin06klS5bonnvu8fcZPXq0jhw5omXLll32M1wul5xOp3JycpSYmFgl3wMAAIRXKH+/I3pkpqCgQFZrYAlRUVHyer2SpJKSEpWUlFyyDwAAuL5FdM5M//79NX36dDVq1Eht2rTRjh07NGvWLI0cOVKSlJiYqJ49e2rixIlyOBxKT0/X2rVrtWDBAs2aNSuSpQMAgGtERE8z5ebmasqUKVqyZIlOnTql1NRUDRkyRE8//bRiYmIkSSdOnNDkyZO1YsUKnTlzRunp6Xr00Uc1fvx4WSyWy34Gp5kAADCfUP5+RzTMXA2EGQAAzMc0c2YAAACuFGEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYGmEGAACYWkTDjMfj0ZQpU9S4cWM5HA41bdpU06ZNk2EYAf2+/PJL3XfffXI6nYqPj1eXLl2UmZkZoaoBAMC1JDqSH/7iiy9q7ty5euutt9SmTRtt3bpVI0aMkNPp1NixYyVJBw4cUPfu3TVq1ChNnTpViYmJ2r17t2JjYyNZOgAAuEZYjPMPg1xF9957r+rVq6c///nP/rZBgwbJ4XDo7bffliQ99NBDstlsWrhwYaU+w+Vyyel0KicnR4mJiWGpGwAAVK1Q/n5H9DRTt27dtGrVKu3du1eSlJGRofXr16tfv36SJK/Xq6VLl+rGG29U3759lZycrFtvvVXvvffeRbfpdrvlcrkCHgAAoPqKaJiZNGmSHnroIbVs2VI2m0033XSTxo0bp6FDh0qSTp06pby8PL3wwgu66667tGLFCt1///0aOHCg1q5dW+E2Z8yYIafT6X+kpaVdza8EAACusoieZnrnnXc0ceJE/f73v1ebNm20c+dOjRs3TrNmzdLw4cN17NgxNWjQQEOGDNHixYv977vvvvsUHx+vv/zlLxds0+12y+12+5ddLpfS0tI4zQQAgImEcpopohOAJ06c6D86I0nt2rXTN998oxkzZmj48OGqU6eOoqOj1bp164D3tWrVSuvXr69wm3a7XXa7vcprBwAA14aInmYqKCiQ1RpYQlRUlLxeryQpJiZGXbp00Z49ewL67N27V+np6VetTgAAcO2K6JGZ/v37a/r06WrUqJHatGmjHTt2aNasWRo5cqS/z8SJEzV48GD16NFDvXv31rJly/TBBx9ozZo1kSscAABcMyI6ZyY3N1dTpkzRkiVLdOrUKaWmpmrIkCF6+umnFRMT4+/3xhtvaMaMGTpy5IhatGihqVOnasCAAUF9BpdmAwBgPqH8/Y5omLkaCDMAAJiPaX5nBgAA4EoRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKkRZgAAgKlFR7qAqmYYhiTJ5XJFuBIAABCs8r/b5X/HL6Xah5nc3FxJUlpaWoQrAQAAocrNzZXT6bxkH4sRTOQxMa/Xq2PHjikhIUEWiyWs23a5XEpLS9Phw4eVmJgY1m1XN4xV8Bir4DFWwWOsgsdYBa8qx8owDOXm5io1NVVW66VnxVT7IzNWq1UNGzas0s9ITExkhw8SYxU8xip4jFXwGKvgMVbBq6qxutwRmXJMAAYAAKZGmAEAAKZGmLkCdrtdzzzzjOx2e6RLueYxVsFjrILHWAWPsQoeYxW8a2Wsqv0EYAAAUL1xZAYAAJgaYQYAAJgaYQYAAJgaYQYAAJjadRlm/vvf/6p///5KTU2VxWLRe++9d8n+a9askcViueBx4sQJf5+5c+eqffv2/h8O6tq1qz788MOA7RQVFWnMmDGqXbu2atSooUGDBunkyZNV8RXDKlLj1atXrwu28bOf/awqvmLYVMVYneuFF16QxWLRuHHjAtrNuG9FaqzYr3yeffbZC9a3bNkyYDvsVz7BjBX71VlHjx7VsGHDVLt2bTkcDrVr105bt271rzcMQ08//bRSUlLkcDjUp08f7du374q+y3UZZvLz89WhQwf97//+b0jv27Nnj44fP+5/JCcn+9c1bNhQL7zwgrZt26atW7fq+9//vgYMGKDdu3f7+4wfP14ffPCB3n33Xa1du1bHjh3TwIEDw/a9qkqkxkuSfvrTnwZsY+bMmWH5TlWlKsaq3JYtW/SnP/1J7du3v2CdGfetSI2VxH5Vrk2bNgHr169fH7Ce/eqsy42VxH4lSVlZWbr99ttls9n04Ycf6osvvtBLL72kWrVq+fvMnDlTc+bM0bx587R582bFx8erb9++KioqqvyXMa5zkowlS5Zcss/q1asNSUZWVlZI265Vq5bx+uuvG4ZhGNnZ2YbNZjPeffdd//ovv/zSkGRs2rQp1LIj5mqNl2EYRs+ePY1f/epXoRd5jQjnWOXm5hrNmzc3Vq5cecG4VId962qNlWGwX5V75plnjA4dOlx0PfvVWZcbK8Ngvyr31FNPGd27d7/oeq/Xa9SvX9/4/e9/72/Lzs427Ha78Ze//CXUsv2uyyMzldWxY0elpKToBz/4gTZs2HDRfh6PR++8847y8/PVtWtXSdK2bdtUUlKiPn36+Pu1bNlSjRo10qZNm6q89ki4kvEqt2jRItWpU0dt27bV5MmTVVBQUNVlR8TlxmrMmDG65557AvafctfbvnUlY1WO/cpn3759Sk1NVZMmTTR06FBlZmb617FfBbrUWJVjv5Lef/993XzzzXrggQeUnJysm266Sa+99pp//cGDB3XixImA/crpdOrWW2+9ov2q2t9oMhxSUlI0b9483XzzzXK73Xr99dfVq1cvbd68WZ06dfL327Vrl7p27aqioiLVqFFDS5YsUevWrSVJJ06cUExMjGrWrBmw7Xr16l30nL9ZhWO8JOnHP/6x0tPTlZqaqs8++0xPPfWU9uzZo3/+85+R+FpVIpixeuedd7R9+3Zt2bKlwm1cL/tWOMZKYr8qH6tbb71V8+fPV4sWLXT8+HFNnTpV3/ve9/T5558rISGB/SqEsZLYr8rH6uuvv9bcuXM1YcIE/frXv9aWLVs0duxYxcTEaPjw4f59p169egHbvuL9qtLHdKoJBXForSI9evQwhg0bFtDmdruNffv2GVu3bjUmTZpk1KlTx9i9e7dhGIaxaNEiIyYm5oLtdOnSxXjyyScrVXskXK3xqsiqVasMScb+/ftD/vxICMdYZWZmGsnJyUZGRoZ//fmHs6vDvnW1xqoi1+N+VZGsrCwjMTHRf6qX/Sr4sarI9bpf2Ww2o2vXrgF9HnvsMeO2224zDMMwNmzYYEgyjh07FtDngQceMB588MHQCy/DaaZKuuWWW7R///6AtpiYGDVr1kydO3fWjBkz1KFDB82ePVuSVL9+fRUXFys7OzvgPSdPnlT9+vWvVtkRE+p4VeTWW2+VpAu2U92cO1bbtm3TqVOn1KlTJ0VHRys6Olpr167VnDlzFB0dLY/Hc13vW6GOVUWux/2qIjVr1tSNN97o78N+FfxYVeR63a9SUlICjrBLUqtWrfyn5cr3nfOvirvS/YowU0k7d+5USkrKJft4vV653W5JUufOnWWz2bRq1Sr/+j179igzM/OCeSLVUajjdbFtSLrsdszu3LG64447tGvXLu3cudP/uPnmmzV06FDt3LlTUVFR1/W+FepYXWwb0vW1X1UkLy9PBw4c8Pdhvwp+rC62Den6269uv/127dmzJ6DP3r17lZ6eLklq3Lix6tevH7BfuVwubd68+Yr2q+tyzkxeXl5Akjx48KB27typpKQkNWrUSJMnT9bRo0e1YMECSdLLL7+sxo0bq02bNioqKtLrr7+ujz/+WCtWrPBvY/LkyerXr58aNWqk3NxcLV68WGvWrNHy5csl+SY4jRo1ShMmTFBSUpISExP12GOPqWvXrrrtttuu7gCEKBLjdeDAAS1evFh33323ateurc8++0zjx49Xjx49Lnq57bUg3GOVkJCgtm3bBnxGfHy8ateu7W83674VibFivzr7b/CJJ55Q//79lZ6ermPHjumZZ55RVFSUhgwZIon9KpSxYr86O1bjx49Xt27d9Pzzz+vBBx/Up59+qldffVWvvvqqJPl/++m5555T8+bN1bhxY02ZMkWpqan64Q9/WPkvU+kTVCZWfnnZ+Y/hw4cbhmEYw4cPN3r27Onv/+KLLxpNmzY1YmNjjaSkJKNXr17Gxx9/HLDNkSNHGunp6UZMTIxRt25d44477jBWrFgR0KewsND4xS9+YdSqVcuIi4sz7r//fuP48eNV/XWvWCTGKzMz0+jRo4eRlJRk2O12o1mzZsbEiRONnJycq/GVK60qxup8Fc0DMeO+FYmxYr86a/DgwUZKSooRExNjNGjQwBg8ePAF8zvYr3wuN1bsV4E++OADo23btobdbjdatmxpvPrqqwHrvV6vMWXKFKNevXqG3W437rjjDmPPnj1X9F0shmEYlY9CAAAAkcWcGQAAYGqEGQAAYGqEGQAAYGqEGQAAYGqEGQAAYGqEGQAAYGqEGQAAYGqEGQAAYGqEGQAAYGqEGQAAYGqEGQBXTa9evTRu3LhIl+FX2XpOnz6t5ORkHTp0KOw1ne+hhx7SSy+9VOWfA5gZYQaoZubNm6eEhASVlpb62/Ly8mSz2dSrV6+AvmvWrJHFYtGBAweucpVXV7hD1PTp0zVgwADdcMMNYdvmxfz2t7/V9OnTlZOTU+WfBZgVYQaoZnr37q28vDxt3brV37Zu3TrVr19fmzdvVlFRkb999erVatSokZo2bRqJUk2poKBAf/7znzVq1Kir8nlt27ZV06ZN9fbbb1+VzwPMiDADVDMtWrRQSkqK1qxZ429bs2aNBgwYoMaNG+uTTz4JaO/du7ckadmyZerevbtq1qyp2rVr69577w04YvPqq68qNTVVXq834PMGDBigkSNHSpK8Xq9mzJihxo0by+FwqEOHDvr73/9+0VqD6d+rVy+NHTtWTz75pJKSklS/fn09++yzAX1yc3M1dOhQxcfHKyUlRX/84x/9R2N+8pOfaO3atZo9e7YsFossFkvA6SGv13vJbZ/vP//5j+x2u2677baA9vXr18tmswWExUOHDsliseibb77xv/7HP/6hHj16yOFwqEuXLsrMzNS6det02223KS4uTnfccYeys7MDtt2/f3+98847l6wLuJ4RZoBqqHfv3lq9erV/efXq1erVq5d69uzpby8sLNTmzZv9YSY/P18TJkzQ1q1btWrVKlmtVt1///3+8PLAAw/o9OnTAds9c+aMli1bpqFDh0qSZsyYoQULFmjevHnavXu3xo8fr2HDhmnt2rUV1hls/7feekvx8fHavHmzZs6cqd/97ndauXKlf/2ECRO0YcMGvf/++1q5cqXWrVun7du3S5Jmz56trl276qc//amOHz+u48ePKy0tLehtn2/dunXq3LnzBe07d+5Uq1atFBsb62/bsWOHatWqpfT0dGVkZEiS5s6dq+eff14bN27UyZMnNWzYML3wwgv6n//5H61evVoZGRl68803A7Z9yy236NNPP5Xb7b5oXcB1zQBQ7bz22mtGfHy8UVJSYrhcLiM6Oto4deqUsXjxYqNHjx6GYRjGqlWrDEnGN998U+E2vv32W0OSsWvXLn/bgAEDjJEjR/qX//SnPxmpqamGx+MxioqKjLi4OGPjxo0B2xk1apQxZMgQwzAMo2fPnsavfvUrwzCMoPqXv6d79+4Bfbp06WI89dRThmEYhsvlMmw2m/Huu+/612dnZxtxcXH+zzr3c891uW1X5PwxKDd69GjjkUceCWh7+umnjV69ehmGYRjPPvuskZSUZHz33Xf+9cOGDTNuuOEGIz8/39921113GU8++WTAdjIyMgxJxqFDhy5aF3A948gMUA316tVL+fn52rJli9atW6cbb7xRdevWVc+ePf3zZtasWaMmTZqoUaNGkqR9+/ZpyJAhatKkiRITE/2TWzMzM/3bHTp0qP7xj3/4jxAsWrRIDz30kKxWq/bv36+CggL94Ac/UI0aNfyPBQsWVDjBOJT+7du3D1hOSUnRqVOnJElff/21SkpKdMstt/jXO51OtWjRIqixutS2K1JYWBhw9KXczp071bFjx4C2HTt2+NsyMjJ0//33q3bt2v71mZmZGjx4sOLi4gLaGjduHLAdh8MhyTdfB8CFoiNdAIDwa9asmRo2bKjVq1crKytLPXv2lCSlpqYqLS1NGzdu1OrVq/X973/f/57+/fsrPT1dr732mn9uTNu2bVVcXBzQxzAMLV26VF26dNG6dev0xz/+UZLviilJWrp0qRo0aBBQj91uv6DGUPrbbLaAZYvFcsHcncoKddt16tRRVlZWQJvH49Hnn3+um266KaB9+/btGjRokCRf2Jk8eXLA+oyMDI0fP96/XFRUpD179qhDhw4B/c6cOSNJqlu3bpDfCri+EGaAaqp3795as2aNsrKyNHHiRH97jx499OGHH+rTTz/Vz3/+c0m+303Zs2ePXnvtNX3ve9+T5JvQer7Y2FgNHDhQixYt0v79+9WiRQt16tRJktS6dWvZ7XZlZmb6w9OlhNr/Ypo0aSKbzaYtW7b4jzLl5ORo79696tGjhyQpJiZGHo+n0p9xrptuuumCK4v27NmjoqIipaam+ts2bdqko0ePqmPHjnK5XDp06FBA2Dl48KBycnIC2nbt2iXDMNSuXbuA7X/++edq2LCh6tSpE5bvAFQ3hBmgmurdu7fGjBmjkpKSgLDQs2dP/fKXv1RxcbF/8m+tWrVUu3Ztvfrqq0pJSVFmZqYmTZpU4XaHDh2qe++9V7t379awYcP87QkJCXriiSc0fvx4eb1ede/eXTk5OdqwYYMSExM1fPjwgO2E2v9iEhISNHz4cE2cOFFJSUlKTk7WM888I6vVKovFIkm64YYbtHnzZh06dEg1atRQUlKSrNbKnWXv27evJk+erKysLNWqVUuS76iLJL3yyisaO3as9u/fr7Fjx0qSiouLlZGRoaioKLVt29a/nZ07dyopKUnp6ekBbU2bNlWNGjUCPnPdunW68847K1UvcD1gzgxQTfXu3VuFhYVq1qyZ6tWr52/v2bOncnNz/ZdwS5LVatU777yjbdu2qW3btho/frx+//vfV7jd73//+0pKStKePXv04x//OGDdtGnTNGXKFM2YMUOtWrXSXXfdpaVLl14wB6Sy/S9m1qxZ6tq1q+6991716dNHt99+e8CVRU888YSioqLUunVr1a1bN2AeUKjatWunTp066W9/+5u/befOnerbt6++/vprtWvXTr/5zW80depUJSYmas6cOcrIyFCLFi0C5tpkZGRccFoqIyPjglNMRUVFeu+99/TTn/600jUD1Z3FMAwj0kUAQDjl5+erQYMGeumll6rkx+2WLl2qiRMn6vPPP5fValXfvn3VpUsXPffcc2H/rLlz52rJkiVasWJF2LcNVBecZgJgejt27NBXX32lW265RTk5Ofrd734nyfeDflXhnnvu0b59+3T06FGlpaUpIyPD/8OB4Waz2fTKK69UybaB6oIjMwBMb8eOHRo9erT27NmjmJgYde7cWbNmzbpgIm1VOHHihFJSUrR79261bt26yj8PwIUIMwAAwNSYAAwAAEyNMAMAAEyNMAMAAEyNMAMAAEyNMAMAAEyNMAMAAEyNMAMAAEyNMAMAAEyNMAMAAEyNMAMAAEzt/wED3ybZeeF6BQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compute phase at the through port\n",
    "phase_through = np.angle(sim_data[\"through\"].amps.sel(direction=\"+\").values)\n",
    "# compute phase at the cross port\n",
    "phase_cross = np.angle(sim_data[\"cross\"].amps.sel(direction=\"+\").values)\n",
    "# compute phase difference\n",
    "delta_phase = (phase_through - phase_cross) * 180 / np.pi\n",
    "\n",
    "# plot phase difference\n",
    "plt.plot(ldas, delta_phase)\n",
    "plt.xlabel(\"Wavelength ($\\mu m$)\")\n",
    "plt.ylabel(\"Phase difference\")\n",
    "plt.ylim(85, 95)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1da6cff",
   "metadata": {},
   "source": [
    "## Simulation of the Optical Hybrid -- LO Input "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1eda90a4",
   "metadata": {},
   "source": [
    "Now that we have tested individual components, we can put them together and simulate the whole device. Again, we directly import the geometry from a stl file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1b616031",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:54:12.689885Z",
     "iopub.status.busy": "2023-03-27T23:54:12.689741Z",
     "iopub.status.idle": "2023-03-27T23:54:12.749087Z",
     "shell.execute_reply": "2023-03-27T23:54:12.748238Z"
    }
   },
   "outputs": [],
   "source": [
    "# import optical hybrid geometry from a stl file\n",
    "optical_hybrid_geometry = td.TriangleMesh.from_stl(\n",
    "    filename=\"misc/optical_hybrid_stl.stl\",\n",
    ")\n",
    "\n",
    "# define optical hybrid structure\n",
    "optical_hybrid = td.Structure(geometry=optical_hybrid_geometry, medium=si)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c88dd404",
   "metadata": {},
   "source": [
    "In the first case, define a [ModeSource](../_autosummary/tidy3d.ModeSource.html) at the LO input and four ModeMonitors at the outputs. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e9115162",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:54:12.752123Z",
     "iopub.status.busy": "2023-03-27T23:54:12.751906Z",
     "iopub.status.idle": "2023-03-27T23:54:12.775305Z",
     "shell.execute_reply": "2023-03-27T23:54:12.774856Z"
    }
   },
   "outputs": [],
   "source": [
    "# define a mode source at the LO input waveguide on the top y branch\n",
    "mode_source_LO = td.ModeSource(\n",
    "    center=(0, 1, 0),\n",
    "    size=(2 * width, 0, 4 * thickness),\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "    direction=\"-\",\n",
    "    mode_spec=mode_spec,\n",
    "    mode_index=0,\n",
    ")\n",
    "\n",
    "# define mode monitors at the four output waveguides\n",
    "\n",
    "mode_monitor_Qn = td.ModeMonitor(\n",
    "    center=(-16, -6, 0),\n",
    "    size=(0, 2 * width, 4 * thickness),\n",
    "    freqs=freqs,\n",
    "    name=\"port_Qn\",\n",
    "    mode_spec=mode_spec,\n",
    ")\n",
    "\n",
    "mode_monitor_Qp = td.ModeMonitor(\n",
    "    center=(-16, -6.9, 0),\n",
    "    size=(0, 2 * width, 4 * thickness),\n",
    "    freqs=freqs,\n",
    "    name=\"port_Qp\",\n",
    "    mode_spec=mode_spec,\n",
    ")\n",
    "\n",
    "\n",
    "mode_monitor_In = td.ModeMonitor(\n",
    "    center=(16, -6, 0),\n",
    "    size=(0, 2 * width, 4 * thickness),\n",
    "    freqs=freqs,\n",
    "    name=\"port_In\",\n",
    "    mode_spec=mode_spec,\n",
    ")\n",
    "\n",
    "mode_monitor_Ip = td.ModeMonitor(\n",
    "    center=(16, -6.9, 0),\n",
    "    size=(0, 2 * width, 4 * thickness),\n",
    "    freqs=freqs,\n",
    "    name=\"port_Ip\",\n",
    "    mode_spec=mode_spec,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5991fddf",
   "metadata": {},
   "source": [
    "Define the simulation. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "338b72df",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:54:12.777374Z",
     "iopub.status.busy": "2023-03-27T23:54:12.777205Z",
     "iopub.status.idle": "2023-03-27T23:54:12.802741Z",
     "shell.execute_reply": "2023-03-27T23:54:12.802180Z"
    }
   },
   "outputs": [],
   "source": [
    "run_time = 2e-12  # simulation run time\n",
    "\n",
    "# define simulation\n",
    "sim = td.Simulation(\n",
    "    center=(0, -10, 0),\n",
    "    size=(32, 23, 10 * thickness),\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=20, wavelength=lda0),\n",
    "    structures=[optical_hybrid],\n",
    "    sources=[mode_source_LO],\n",
    "    monitors=[\n",
    "        field_monitor,\n",
    "        mode_monitor_Qn,\n",
    "        mode_monitor_Qp,\n",
    "        mode_monitor_In,\n",
    "        mode_monitor_Ip,\n",
    "    ],\n",
    "    run_time=run_time,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "    medium=sio2,\n",
    "    symmetry=(0, 0, 1),\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d11a3a5a",
   "metadata": {},
   "source": [
    "Visualize the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c2f7cdc2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:54:12.804832Z",
     "iopub.status.busy": "2023-03-27T23:54:12.804657Z",
     "iopub.status.idle": "2023-03-27T23:54:13.073789Z",
     "shell.execute_reply": "2023-03-27T23:54:13.073283Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim.plot(z=0)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b733c0b8",
   "metadata": {},
   "source": [
    "Submit the simulation job to the server."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7ae31213",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:54:13.075948Z",
     "iopub.status.busy": "2023-03-27T23:54:13.075777Z",
     "iopub.status.idle": "2023-03-27T23:55:55.744868Z",
     "shell.execute_reply": "2023-03-27T23:55:55.744273Z"
    }
   },
   "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\">[11:57:08] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'optical_hybrid_lo_input'</span> with task_id                                        <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#139\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">139</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-cd6d59bf-3acc-45c4-a502-e128a574f7a3v1'</span>.                                             <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:57:08]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'optical_hybrid_lo_input'\u001b[0m with task_id                                        \u001b]8;id=129112;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=883961;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'fdve-cd6d59bf-3acc-45c4-a502-e128a574f7a3v1'\u001b[0m.                                             \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "256a73ae80844e5dbd4a8a52ae932d43",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "44424a97e2de460ca2c8b1d21c551f2a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[11:57:11] </span>status = queued                                                                            <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#269\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">269</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:57:11]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                                            \u001b]8;id=411440;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=144815;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#269\u001b\\\u001b[2m269\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[11:57:18] </span>status = preprocess                                                                        <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#263\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">263</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:57:18]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                                        \u001b]8;id=282411;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=604267;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#263\u001b\\\u001b[2m263\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": []
     },
     "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\">[11:57:22] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.848</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed FlexCredit cost <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#286\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">286</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>after a simulation run.                                                                    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:57:22]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.848\u001b[0m. 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 FlexCredit cost \u001b]8;id=56536;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=243041;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#286\u001b\\\u001b[2m286\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0mafter a simulation run.                                                                    \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>starting up solver                                                                         <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#290\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">290</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                                         \u001b]8;id=279244;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=417796;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#290\u001b\\\u001b[2m290\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>running solver                                                                             <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#300\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">300</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                                             \u001b]8;id=931223;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=768128;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#300\u001b\\\u001b[2m300\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9c478bd0568e4162b6ba23b367ed7917",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[12:06:19] </span>early shutoff detected, exiting.                                                           <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#313\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">313</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[12:06:19]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                                                           \u001b]8;id=162975;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=217807;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#313\u001b\\\u001b[2m313\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": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>status = postprocess                                                                       <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#330\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">330</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                                                       \u001b]8;id=653372;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=839149;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#330\u001b\\\u001b[2m330\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[12:06:34] </span>status = success                                                                           <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#337\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">337</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[12:06:34]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                                           \u001b]8;id=565829;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=686778;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#337\u001b\\\u001b[2m337\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": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a2ce15a1ec7a46f794853bd8c8668a12",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[12:06:38] </span>loading SimulationData from data/simulation_data.hdf5                                      <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#512\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">512</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[12:06:38]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/simulation_data.hdf5                                      \u001b]8;id=655055;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=764768;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"optical_hybrid_lo_input\", verbose=True)\n",
    "sim_data = job.run(path=\"data/simulation_data.hdf5\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b0921a6",
   "metadata": {},
   "source": [
    "Visualize the field intensity distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "07018789",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:55:57.284859Z",
     "iopub.status.busy": "2023-03-27T23:55:57.284705Z",
     "iopub.status.idle": "2023-03-27T23:56:00.492794Z",
     "shell.execute_reply": "2023-03-27T23:56:00.492266Z"
    }
   },
   "outputs": [
    {
     "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_monitor_name=\"field\", field_name=\"E\", val=\"abs^2\", vmax=1500)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b7eb83c",
   "metadata": {},
   "source": [
    "Besides the error in the relative phase, there are three additional figures of merit (FOM) the characterize the performance of the 90 degree optical hybrid: insertion loss, common mode rejection ratio (CMRR), and imbalance. We define a function to calculate those FOMs and plot the results.\n",
    "\n",
    "The insertion loss is calculated as $-10log_{10}(P_{tot})$, where $P_{tot}=P_{Ip}+P_{In}+P_{Qp}+P_{Qn}$ is the total power at four output ports.\n",
    "\n",
    "The CMRR is calculated as CMRR$_I=-20log_{10}(\\left|\\frac{P_{Ip}-P_{In}}{P_{Ip}+P_{In}}  \\right|)$ and CMRR$_Q=-20log_{10}(\\left|\\frac{P_{Qp}-P_{Qn}}{P_{Qp}+P_{Qn}}  \\right|)$.\n",
    "\n",
    "The imbalance is defined as Imbalance$_I = -10log_{10}(\\frac{P_{Ip}}{P_{In}})$ and Imbalance$_Q = -10log_{10}(\\frac{P_{Qp}}{P_{Qn}})$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "89763cfc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:56:00.494868Z",
     "iopub.status.busy": "2023-03-27T23:56:00.494691Z",
     "iopub.status.idle": "2023-03-27T23:56:00.519317Z",
     "shell.execute_reply": "2023-03-27T23:56:00.518598Z"
    }
   },
   "outputs": [],
   "source": [
    "def calculate_FOM(sim_data):\n",
    "    # compute power at the Ip port\n",
    "    P_Ip = np.abs(sim_data[\"port_Ip\"].amps.sel(direction=\"+\").values) ** 2\n",
    "    # compute power at the In port\n",
    "    P_In = np.abs(sim_data[\"port_In\"].amps.sel(direction=\"+\").values) ** 2\n",
    "    # compute power at the Qp port\n",
    "    P_Qp = np.abs(sim_data[\"port_Qp\"].amps.sel(direction=\"-\").values) ** 2\n",
    "    # compute power at the Qn port\n",
    "    P_Qn = np.abs(sim_data[\"port_Qn\"].amps.sel(direction=\"-\").values) ** 2\n",
    "\n",
    "    fig, ax = plt.subplots(3, 1, tight_layout=True, figsize=(6, 10))\n",
    "\n",
    "    # compute and plot insertion loss\n",
    "    loss = -10 * np.log10(P_Ip + P_In + P_Qp + P_Qn)\n",
    "    ax[0].plot(ldas, loss)\n",
    "    ax[0].set_xlabel(\"Wavelength ($\\mu m$)\")\n",
    "    ax[0].set_ylabel(\"Insertion loss (dB)\")\n",
    "    ax[0].set_ylim(0, 1)\n",
    "\n",
    "    # compute and plot CMRR\n",
    "    CMRR_I = -20 * np.log10(np.abs((P_Ip - P_In) / (P_Ip + P_In)))\n",
    "    CMRR_Q = -20 * np.log10(np.abs((P_Qp - P_Qn) / (P_Qp + P_Qn)))\n",
    "    ax[1].plot(ldas, CMRR_I, label=\"CMRR$_I$\")\n",
    "    ax[1].plot(ldas, CMRR_Q, label=\"CMRR$_Q$\")\n",
    "    ax[1].set_xlabel(\"Wavelength ($\\mu m$)\")\n",
    "    ax[1].set_ylabel(\"CMRR (dB)\")\n",
    "    ax[1].set_ylim(25, 45)\n",
    "    ax[1].legend()\n",
    "\n",
    "    # compute and plot imbalance\n",
    "    Imbalance_I = -10 * np.log10(P_Ip / P_In)\n",
    "    Imbalance_Q = -10 * np.log10(P_Qp / P_Qn)\n",
    "    ax[2].plot(ldas, Imbalance_I, label=\"Imbalance$_I$\")\n",
    "    ax[2].plot(ldas, Imbalance_Q, label=\"Imbalance$_Q$\")\n",
    "    ax[2].set_xlabel(\"Wavelength ($\\mu m$)\")\n",
    "    ax[2].set_ylabel(\"Imbalance (dB)\")\n",
    "    ax[2].set_ylim(-0.5, 0.5)\n",
    "    ax[2].legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf88df32",
   "metadata": {},
   "source": [
    "Calculate those FOMs and plot the results. Due to symmetry, CMRR$_I$ and CMRR$_Q$ are identical. So is Imbalance$_I$ and Imbalance$_Q$. \n",
    "\n",
    "Overall, we see that the design has a good performance. The insertion loss is about 0.3 dB while the CMRRs are above 30 dB and the Imbalances are around 0.1 dB."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d6d31259",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:56:00.522358Z",
     "iopub.status.busy": "2023-03-27T23:56:00.522209Z",
     "iopub.status.idle": "2023-03-27T23:56:01.019198Z",
     "shell.execute_reply": "2023-03-27T23:56:01.018604Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 600x1000 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "calculate_FOM(sim_data)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23536beb",
   "metadata": {},
   "source": [
    "## Simulation of the Optical Hybrid -- Signal Input "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c51e262",
   "metadata": {},
   "source": [
    "Finally, we simulate the case where the input signal is from the bottom signal port. To do so, we only need to define a ModeSource at the signal port and update the previous simulation since other settings of the simulation is identical."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "fc12ac48",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:56:01.021748Z",
     "iopub.status.busy": "2023-03-27T23:56:01.021549Z",
     "iopub.status.idle": "2023-03-27T23:56:01.307540Z",
     "shell.execute_reply": "2023-03-27T23:56:01.306870Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAnAAAAHgCAYAAAAlnVB9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy88F64QAAAACXBIWXMAAA9hAAAPYQGoP6dpAABpAElEQVR4nO3deZhcZYEu8Pc7p07t1fuWTmcPZCMhEEgAQbYMgYm74s4AOqCAciWoAyMGiQMoKOIoy/Xegfiog4jPFUZxIUAQhLAIBLOThCyd3pJeq2s/y3f/qO5Kd7qr6lTvVfX+nqee7q46y9d1uk+//a1CSilBRERERHlDmewCEBEREVFuGOCIiIiI8gwDHBEREVGeYYAjIiIiyjMMcERERER5hgGOiIiIKM8wwBERERHlGQY4IiIiojzDAEdERESUZxjgiIjSeOGFFyCEwAsvvDDZRSEiGoQBjoiK3oMPPoiNGzdOdjFG5L//+79x//33T3YxAACWZeGee+7BnDlz4Ha7sWzZMjz22GO29+/u7sa1116L6upq+Hw+XHjhhXjrrbeG3fZ//ud/cPrpp8PtdmPmzJm4/fbbYRjGWH0rRFOe4FqoRFTsTjnlFFRVVQ2pabMsC4lEAk6nE4oyNf/f/cAHPoDt27fj4MGDk10U3Hrrrfje976Ha665BmeeeSaeeuopPP3003jsscfw6U9/OuO+lmXhvPPOwzvvvINvfOMbqKqqwoMPPojGxka8+eabOOmkk1Lb/ulPf8LatWtxwQUX4DOf+Qy2bduGBx54ANdeey0eeuih8f42iaYEBjgiAgCEw2H4fL7JLsakSBfg8sFUCXBNTU2YM2cOrr32Wvz0pz8FAEgpcf755+PAgQM4ePAgVFVNu/9vfvMbfOpTn8ITTzyBT3ziEwCAY8eO4eSTT8Zll12G//7v/05tu2TJEmiahr///e9wOBwAgNtuuw133XUXdu7ciYULF47jd0o0NUzNfymJaFSamprwxS9+EfX19XC5XJgzZw6uu+46JBIJAMDGjRshhMBf//pXXH/99aipqUFDQ0Nq/wcffBBLliyBy+VCfX09brjhBnR3dw86x969e/Hxj38cdXV1cLvdaGhowKc//Wn09PSkttm0aRPOPfdclJWVwe/3Y8GCBfj3f//3rOW3s188Hsftt9+O+fPnw+VyYcaMGfjmN7+JeDw+5Hi//OUvsXLlSni9XpSXl+P9738/nnnmGQDA7NmzsWPHDvz1r3+FEAJCCFxwwQUA0veBe+KJJ7BixQp4PB5UVVXh85//PJqamgZtc9VVV8Hv96OpqQkf+chH4Pf7UV1dja9//eswTTPre/DUU09h7dq1qWs4b948fPe73x207wUXXICnn34ahw4dSpV99uzZaY951VVXpbY78fGd73wna5mylVfXdVx//fWp54QQuO6663DkyBFs2bIl4/6//e1vUVtbi4997GOp56qrq/HJT34STz31VOq67ty5Ezt37sS1116bCm8AcP3110NKid/+9rej+j6I8oUj+yZElE+am5uxcuXKVH+ihQsXoqmpCb/97W8RiUTgdDpT215//fWorq7G+vXrEQ6HAQDf+c53cMcdd2D16tW47rrrsGfPHjz00EN444038PLLL0PTNCQSCaxZswbxeBxf/epXUVdXh6amJvzhD39Ad3c3SktLsWPHDnzgAx/AsmXLsGHDBrhcLuzbtw8vv/xyxvLb2c+yLHzoQx/C3/72N1x77bVYtGgRtm3bhh/96Ed499138eSTT6a2veOOO/Cd73wH55xzDjZs2ACn04nXXnsNzz//PC655BLcf//9+OpXvwq/349vfetbAIDa2tq05du4cSOuvvpqnHnmmbj77rvR1taGH//4x3j55Zfx9ttvo6ysLLWtaZpYs2YNVq1ahR/84Ad49tln8cMf/hDz5s3Dddddl/F92LhxI/x+P9atWwe/34/nn38e69evRzAYxL333gsA+Na3voWenh4cOXIEP/rRjwAAfr8/7TG/9KUvYfXq1YOe+/Of/4xf/epXqKmpST3X3t6esWz9AoEAXC4XAODtt9+Gz+fDokWLBm2zcuXK1Ovnnntu2mO9/fbbOP3004c0Va9cuRI/+9nP8O6772Lp0qV4++23AQBnnHHGoO3q6+vR0NCQep2o4EkiKij/8i//IhVFkW+88caQ1yzLklJK+eijj0oA8txzz5WGYaReP3r0qHQ6nfKSSy6Rpmmmnv/pT38qAchHHnlESinl22+/LQHIJ554Im05fvSjH0kA8tixYzmV385+v/jFL6SiKPKll14a9PzDDz8sAciXX35ZSinl3r17paIo8qMf/eig70fK4++FlFIuWbJEnn/++UPOs3nzZglAbt68WUopZSKRkDU1NfKUU06R0Wg0td0f/vAHCUCuX78+9dyVV14pAcgNGzYMOuZpp50mV6xYkflNkFJGIpEhz33pS1+SXq9XxmKx1HNr166Vs2bNynq84ezdu1eWlpbKf/qnfxr0cwDA1uPRRx8dVI65c+cOOUc4HJYA5C233JKxLD6fT37hC18Y8vzTTz8tAcg///nPUkop7733XglAHj58eMi2Z555pjzrrLPsfvtEeY1NqEQFxLIsPPnkk/jgBz84pIYCSDZpDXTNNdcM6pf07LPPIpFI4Gtf+9qgmpBrrrkGJSUlePrppwEApaWlAIC//OUviEQiw5alvybqqaeegmVZtr8HO/s98cQTWLRoERYuXIj29vbU46KLLgIAbN68GQDw5JNPwrIsrF+/fkjNzonvhR1///vfcfToUVx//fVwu92p59euXYuFCxem3p+BvvzlLw/6+rzzzsN7772X9Vwejyf1eW9vL9rb23HeeechEolg9+7dOZf9ROFwGB/96EdRXl6Oxx57bNDPwaZNm2w91qxZk9onGo2mauMG6n+fotFoxvLY3b//Y7pts52HqFCwCZWogBw7dgzBYBCnnHKKre3nzJkz6OtDhw4BABYsWDDoeafTiblz56ZenzNnDtatW4f77rsPv/rVr3DeeefhQx/6ED7/+c+nwt2nPvUp/N//+3/xr//6r7jllltw8cUX42Mf+xg+8YlPZBzRaWe/vXv3YteuXaiurh72GEePHgUA7N+/H4qiYPHixbbej2zSvT8AsHDhQvztb38b9Jzb7R5SxvLycnR1dWU9144dO3Dbbbfh+eefRzAYHPTawH6GI3XNNddg//79eOWVV1BZWTnotRObWe3weDzD9j+MxWKp18di//6P6bbNdh6iQsEAR1TERvPH7oc//CGuuuoqPPXUU3jmmWdw44034u6778arr76KhoYGeDwevPjii9i8eTOefvpp/PnPf8bjjz+Oiy66CM8880zaEYl29rMsC0uXLsV999037DFmzJgx4u9rLGUadZlJd3c3zj//fJSUlGDDhg2YN28e3G433nrrLfzbv/1bTjWaw/nxj3+Mxx57DL/85S+xfPnyIa+3trbaOk5paWnqZ2jatGnYvHkzpJSDajdbWloAJPuoZTJt2rTUtgOduP+0adNSz594nVtaWlJ97ogKHZtQiQpIdXU1SkpKsH379hHtP2vWLADAnj17Bj2fSCRw4MCB1Ov9li5dittuuw0vvvgiXnrpJTQ1NeHhhx9Ova4oCi6++GLcd9992LlzJ+688048//zzqSbOdLLtN2/ePHR2duLiiy/G6tWrhzz6a8jmzZsHy7Kwc+fOjOez25ya7v3pf+7E92ekXnjhBXR0dGDjxo34X//rf+EDH/gAVq9ejfLy8iHb5toU/NJLL+HrX/86vva1r+Fzn/vcsNtMmzbN1uPxxx9P7bN8+XJEIhHs2rVr0LFee+211OuZLF++HG+99daQcPraa6/B6/Xi5JNPHnScv//974O2a25uxpEjR7Keh6hQMMARFRBFUfCRj3wEv//974f8gQOS83Jlsnr1ajidTvznf/7noG3/67/+Cz09PVi7di0AIBgMDpn1funSpVAUJdW01dnZOeT4/X9ch2v+6mdnv09+8pNoamrC//k//2fIttFoNDWi9iMf+QgURcGGDRuGBIOB35/P5xsyTcpwzjjjDNTU1ODhhx8e9D386U9/wq5du1Lvz2j119wNLGMikcCDDz44ZFufz2e7SbWlpQWf/OQnce6556ZGsg5nJH3gPvzhD0PTtEFllFLi4YcfxvTp03HOOecMKsfu3buh63rquU984hNoa2vD//t//y/1XHt7O5544gl88IMfTPV5W7JkCRYuXIif/exng6ZUeeihhyCESM0hR1To2IRKVGDuuusuPPPMMzj//PNTU2y0tLTgiSeewN/+9rdB01ycqLq6GrfeeivuuOMOXHrppfjQhz6EPXv24MEHH8SZZ56Jz3/+8wCA559/Hl/5yldw+eWX4+STT4ZhGPjFL34BVVXx8Y9/HACwYcMGvPjii1i7di1mzZqFo0eP4sEHH0RDQ0PG6STs7HfFFVfgN7/5Db785S9j8+bNeN/73gfTNLF792785je/wV/+8hecccYZmD9/Pr71rW/hu9/9Ls477zx87GMfg8vlwhtvvIH6+nrcfffdAIAVK1bgoYcewn/8x39g/vz5qKmpSQ2IGEjTNHz/+9/H1VdfjfPPPx+f+cxnUtOIzJ49GzfddNNIL9sg55xzDsrLy3HllVfixhtvhBACv/jFL4YN4CtWrMDjjz+OdevW4cwzz4Tf78cHP/jBYY9744034tixY/jmN7+JX//614NeW7ZsGZYtWwZgZH3gGhoa8LWvfQ333nsvdF3HmWeeiSeffBIvvfQSfvWrXw1qTr711lvx85//HAcOHEjNW/eJT3wCZ511Fq6++mrs3LkztRKDaZq44447Bp3r3nvvxYc+9CFccskl+PSnP43t27fjpz/9Kf71X/91yDQmRAVrEkfAEtE4OXTokPyXf/kXWV1dLV0ul5w7d6684YYbZDwel1Ien0ZkuKlGpExOG7Jw4UKpaZqsra2V1113nezq6kq9/t5778kvfOELct68edLtdsuKigp54YUXymeffTa1zXPPPSc//OEPy/r6eul0OmV9fb38zGc+I999992MZbe7XyKRkN///vflkiVLpMvlkuXl5XLFihXyjjvukD09PYO2feSRR+Rpp52W2u7888+XmzZtSr3e2toq165dKwOBgASQmlLkxGlE+j3++OOp41VUVMjPfe5z8siRI4O2ufLKK6XP5xvy/d1+++3Szq335ZdflmeddZb0eDyyvr5efvOb35R/+ctfhpQnFArJz372s7KsrEwCyDilyPnnn592SpDbb789a5myMU1T3nXXXXLWrFnS6XTKJUuWyF/+8pdDtuufYuXAgQODnu/s7JRf/OIXZWVlpfR6vfL8889P+zP6u9/9Ti5fvly6XC7Z0NAgb7vtNplIJEb9PRDlCy6lRURERJRn2AeOiIiIKM8wwBERERHlGQY4IiIiojzDAEdERESUZxjgiIiIiPIMAxwRERFRnuFEviewLAvNzc0IBAI5L1FDRERENBpSSvT29qK+vh6Kkr6ejQHuBM3NzVNmIWwiIiIqTo2NjWhoaEj7OgPcCQKBAADgm1+/CR6PC/3THFeVaNAc41cjl9AtdIeT6/qV+VQ4tYlv3ZZS4lhPcn1LlyZQ6pucH4+esIG4nnzjq0sdk1ITyutxHK9HUrrr0RtLIBI30u7nUAQqA54xKwevRxJ/P47j9Tgu366Hbki0B5NrAvcXNRqN454f/CiVR9JhgDtB/8X2eFzw+7ywLAlLAiUBDc5xCnAJ3UJYN1Had610Cyh1T+wvoSUlOoImfD4NLodATJdQVAUBr5p95zHUGzGhag5UeAXihoQuBSoDKpQJ/CXk9TiO1yMp4/VQVUBNpN3XoQiUjlGA4/VI4u/Hcbwex+Xj9UgYEmHdAUUAijK4nNnCJwNcGpaFvvAmIWUyJY8HXbfQFTbhUAVKfckf9q6QiaM9Bsp9KrQJ+CWUUqIrZMIwZeqcStREdzj5nM8zMb+E4aiJUMyC363A51Hh7ntvjnZLlPvVCflPitfjOF6PpGzXw4KEZaXf30LyJj1avB5J/P04jtfjuHy9HrohIaWEBSRvFgDsLnDKAJeGYQGmJZOrPEsgrlswrbH9AbAsIGFYcGkKnA6Rqvb1OJVkKo9bcJpAhj6MoyZl8o+LIgC/W4UpATNhQVUFfG4FCVNCRpM/kOPJMCV0U8LnVqCqArFE8ifZ71aRMCwEIxacDoHx/B3k9TiO1yPJzvUwLcDKcG8wcPz9GylejyT+fhzH63FcPl8Pw0y28g0smt1/9xjg0nBpgNupwO9Ovvn/fGZpKlETEfXb1dSJva3BtK97NAf+aVndBJaIiPJFT9jEH9/ogUtTUv3sg73p+9QOxACXRoXPgYQEQjELHqeCUp+KigDfLiIazOcR0LT0NWwup+S9g4jScqgCmkOk+tnbHTDJiXzT0DQFVQEVhinHpP8KERER0VhhgMvAqSko96mQdnsUEhEREU0A1utnoWkKnOZkl4KIiIjoONbA2TCeo3iIiIioeGWahigTRhMiIiKiSZIwLOh67imOAY6IiIhokggh0BU2kcgxxDHAEREREU0Sp0PAoQq09+YW4hjgiIiIiCaJEEC5X4XWF+LsNqcywBERERFNIiEEKkuSIa47Ym/qCwY4IiIiokmm9IU4u2vHMsARERERTQGKECizue46AxwRERFRnmGAIyIiIpoCLCnRHWYfOCIiIqK8YEmJjqAJw7S3/jrXQiUiIiKaRFJKdAQt6KZEmZd94IiIiIimNCmBrpAJ3ZSoCqjQNHvRjAGOiIiIaJIkDAmjL7w5bYY3gAGOiIiIaNJIKVHuyy28AQxwRERERJPG6VBsN5sOVJAB7oEHHsDs2bPhdruxatUqvP7666M6nmV/bVkiIiIi25QRJrGCC3CPP/441q1bh9tvvx1vvfUWTj31VKxZswZHjx4d0fF03ULCYIIjIiKiqaPgAtx9992Ha665BldffTUWL16Mhx9+GF6vF4888siw28fjcQSDwUGPfgndQlfYhBD21iUjIiIimggFFeASiQTefPNNrF69OvWcoihYvXo1tmzZMuw+d999N0pLS1OPGTNmAEjWvLX3mnCoAk4HAxwRERFNHQUV4Nrb22GaJmprawc9X1tbi9bW1mH3ufXWW9HT05N6NDY2AgC6IyY0VaDcr4IVcERERDSVFP1KDC6XCy6Xa8jzDlWgskSFYQKAvWUtiIiIiCZCQdXAVVVVQVVVtLW1DXq+ra0NdXV1OR2rzKdCYdUbEWXRG0tkfD2qG9BNe4tTExHZVVABzul0YsWKFXjuuedSz1mWheeeew5nn312TsfiwAUiysayLLR0hTNvIyWas2xDRJSrgmtCXbduHa688kqcccYZWLlyJe6//36Ew2FcffXVk100IiowbcGordq15q4QZlWVTECJiKhYFFyA+9SnPoVjx45h/fr1aG1txfLly/HnP/95yMAGIqLRauoM2duuKwRLSnbLIKIxU3ABDgC+8pWv4Ctf+cpkF4OIClxTl70AF9dNdPTGUF3iGecSEVGxKKg+cGMpHGOnYyJKrysUQyjLAIaBGjuC2TciIrKJAS6NcMxCb4QhjoiG99bB3Jbne7elO6fAR0SUCQNcGj63gmDUQjjKEEdEgx1qD6K1J7eRpaa08OaBtuwbEhHZwACXhs+tosSjIBSzYJicyJeIksIxHW8dyK32rd+RzhD2t3WPbYGIqCgV5CCGsRLwqjBMiQQDHBEB6I7EsXlHIyIJfcTHeHVfCwzTwoL6ijEsGREVG9bAZeHzqNBUDv0nKnbtvVFs2nZoVOGt398PtOEfh4+NQamIqFgxwNngYIAjKmpx3cTzOxqRMMauT+y2xna8d7RnzI5HRPlJjrCRjwGOiCiL9471jMt6prubO8f8mESUXxKGhBxBimOAIyLKQEqJvS1d43LsrnAMx4LRcTk2EeUHKSW6QiasHEMcAxwRUQYJw0LvOM7f1hFigCMqZk6HAsOU6AjmFuIY4IiIJhHHuBMVN0UByn0q9L4QZ7c5lQGOiIiIaBJpmoKqQDLEdYft9bdlgCMiIiKaZM6+EGd38QAGOCIiIqIpwKkpKPOqtrZlgCMiIiKaIjTNXjRjgCMiIiKaIsIx9oEjIiIiyhu9ERPhmGVrWwY4IqIMVEVAYPyW09NU3oaJKBneglELPjebUImIRs2hKqgMuMft+LUl3nE7NhHlh3A0Gd5KPAp8bg5iICIaE3VlvnE5rs+lIeBxjsuxiSg/GKZEKJYMbwGbI1ABBjgioqyml/nH57jl43NcIsofuinhd+cW3gAGOCKirCoDbvic2pgfd2ZVYMyPSUT5RVMFfJ7cwhvAAGdLDmvLElEBEkJgxhiHLbemopr934iKnkMd2SApBrgspJRIGExwRMWuZIz7qgU8Tihi/Ea3ElFhY4DLwJISXSETklVwREVvrO8CvK0Q0Wg4JrsAU5WUEh1BE4Yp4bc5pJeICpiNwFXiccKhJP8v7o4kYMn0E3IywBHRaDDApdEdNuF0SZT7VJi80RIVPctG4jrn5HpU+j0AgN+/tR/BaCLttrytENFosAk1DcOUqAqotheVJaLCZidwqcrx+4VDyXzvYNcMIhoNppM0yrwqnAxvRNTHsrKvT+hQjg9KcGRZIstOjR4RUTpMKGmw5o2IBorpZtZtBta6qUrmEaYx3Rh1mYioeDGlEBHZYCfAqQPmc1KzNKHGdROWxVo4IhoZBjgiIhtiicw1ZopQBtXAubTso9djBmvhiGhkGOCIiGyIZmny9LocEAMm5vU6sw/yjyWy1+oREQ2HAS4NXc/eYZmIike2Pms+l3bC19lXbmA/OCIaKQa4NLojJhIMcUQEwDAtxLP0gfO7Bte4+d3Za+DCcX1U5SKi4sUAl4ZDFWjvNVkTR0TojsSzbuM9oQbuxK+HPW44+3GJiIbDAJdGmU+Fpgp0hU3YmP6JiApYVziWdZsTm0x9NvrA2TkuEdFwGODSEEKgskSFQxVIGExwRMWsM5S9pqzEMzjAKYqCgDtzP7iucJwT+hLRiDDAZaAIgXK/OmhkGREVn84sNWXJe4VryPOVfnfG/QzLQijGfnBElDsGuCyEEHA6GOCIipVlWejJ0letzOcadu3TyoAn6/E7Q2xGJaLcMcDZwAo4ouLVHUnAlJm7UVT5hw9q6Z4fqCMUHVG5iKgwGObIulEwwBERZdDUFcq6TWWaoFbmd0HJ8h9gs43jE1Hh0k2JcDT3Sb0Z4IiIMmjqtBHgSobv6+ZQFJT5MveDC0YTCEYTIyobEeU/TRUIxSz0RnILcQxwRERpxBJG1iZOl6aiJMNo0+qS7M2odkIiERUmhyrgdysIRnMLcQxwRERp2Gk+nV7uzzhSfXq5f0zOQ0SFy+dRUeJJhrhwzF6IY4AjIkrDTrBqqAhkfL22xAOnqmbc5lgwgoTBhe2JilnAmwxx4Zi9uWcZ4IiIhqGbJlq6whm3UYWCaWW+jNsoioLpFZlr4SwpcYTNqERFL+BV4XPbi2YMcEREwzhwLAgjyzp608q9cKjZb6PZAhwA7G3tsl02IipcPnfmGvt+DHBERMPY29KddZtszaf96sv9UEXm2217b5RroxIRdJ1NqEREI3I0GEF3JPvyWdNtBjhNVTCt3Jt1u72t3baOR0SFKaFb6LY5EpUBjojoBHaC1IzKANyavaYOAJhXW551m4PHeqCbHMxAVIwSuoX2XhMO1d7yTwxwREQDxHQTh9t7s253Ul1ZTsetL/fB59IybqObFg4cDeZ0XCLKf3pfeNNUgTIf+8AREeVsV1MHrCxrn5Z53agtzTz69ESKEDipLnst3K7mTlhZBk8QUeGwLKArnAxvlSVqxnklB2KAIyLqE0no2NOSfTRorrVv/ebVlkLJMpghFEtgX1vPiI5PRPknYVhw9IW3bGsnD8QAR0TUZ3tjB8wstV+aqmBOTcmIju/WHJhVlX3gw7bGdhgma+GIioEQAuX+3MIbwABHRAQA6I0msL+tO+t2c2vKoGVZWSGTBfXZm1FjuoHdzZ0jPgcR5Q+nQ9huNh2IAc4Gw5STXQQiGmf/OHwMlsz8u+5QFCxpqBjVeSr9HjTYmNh3Z1Mn4jpHpBIVuhFkNwAMcFmFoyZ0BjiigtbeG8XB9uyjPxdMq4DHmXkkqR2nzqzOuo1umtjW2D7qcxFRYWKAy6A3YiIUs6DZnJOFiPKPaVl4dW9L1u2cqopF00dX+9avzOfGnOrSrNvtaenE0WBkTM5JRIWFAS6NcMxEMGrB71ZsT6pHRPlnW2MHeqLxrNstml4BVw4T92azdEaVrU7Lr+5t4YAGIhqCAS6NcMxCiUeBzzN2N2wimlo6QlHsPNKRdTu35sDC+rGpfesX8Dgxr7Ys63a9sQT+cfjYmJ6biPIfA1waPreCgJfhjahQWZaFV/e2QiJ7H9fls6rhUMf+drlsRhWcjuz3mV3NnTgWjI75+YkofzHApeFzM7wRFbJ3DrdnXbAeAOrKfLZqykbC7XRgxZxaW9u+uq+Z66QSUQoDHBEVnUPtQexsyt506lAUrJpXN65lmVtTimll2acVCUYTeOXdZsgsU50QUXFggCOiotIVitkadQoAp86qht/tHOcSAavm1cGhZL8dH+kMcWoRIgLAAEdERSSmG/jr7iMwbCwWX+X34ORp2VdNGAs+t4ZTZ2WfGw5ILrPVaGPOOiIqbAxwabCZgqiwWJaFv+1pRjiuZ91WVRSsml+X89qEo3HytHLUlHhtbfvK3hZ0hbP33yOiwsUAl0Z32My6rA4R5QdLSry6rxVtPWFb26+aX4cyn3ucSzWYIgTet6AeHs2RdVvDsvDXXUcQjmUPo0RUmBjg0jBMiY6gyZo4ojwnpcTr+1pw4FiPre1Priu3tUrCePA6NZy7cLqtmr9wXMezOw4zxBEVKQa4NMq8KnRToitkghmOKD9JKfH6/lbsP2ovvFUFPFgxp2acS5VZTYkXp822V4ZQLIFndxxGxEazMBEVFga4NDRNQVVAhWFKJAwmOKJ89MZ7bdjX1m1rW7fmwHkLp0OxMRp0vC2sr8CsqhJb24ZiCTy7/TAiCYY4omIy+XeqKcypKSj3qWxGJcozVl/N297WLlvbK0LBuQvq4XVq41wy+86aPw3lNvvh9cYSeG47m1OJiklBBbjZs2dDCDHo8b3vfW9Ux9Q0BU5HQb1NRAVNN038ddcR2+FNQODcBfWoLfWNc8ly41AVXLR4Bko89uahC0YT+PM/DqKdS24RFYWCSyYbNmxAS0tL6vHVr3511MecAi0qRGRDKJbAX/5xCM1dIdv7nHXSNMyoDIxjqUbO7XTgosUz4bNZMxjTDTy7/TAO2hywQUSTz8a0lMPKPl49zwQCAdTVje/SN0Q09RwNRvDi7iOI6/bXCz1jTi3m1kzOiFO7fG4NF50yE5u2HUTMxvdmSgsvv9uMnkgCy2ZWQUzgXHZElLuEYUHTAacjtzXYC65u6Xvf+x4qKytx2mmn4d5774VhGBm3j8fjCAaDgx5ElF/ebe3Cc9sP5xTeTp1ZjQX1FeNYqrFT4nHiosUzoan2b/Dbj7Tjpd1NOb0nRDTxhBDoCptI6LlVxRVUDdyNN96I008/HRUVFXjllVdw6623oqWlBffdd1/afe6++27ccccdE1hKIhorkYSO1/a15tRkCgDLZlbjlBlV41Sq8VHud+OiJTPwwq5G26GssbMX7VtjOGt+HerL/eNcQiIaCadDwLQE2ntNVOXQm2PK18DdcsstQwYmnPjYvXs3AGDdunW44IILsGzZMnz5y1/GD3/4Q/zkJz9BPB5Pe/xbb70VPT09qUdjY+NEfWtENAqHjgXx9NsHcgpvAgKr5k/D0jwLb/2qAh5csnQ2/G57AxsAIJrQsXlnI17f3wrDHGFnGyIaN0IA5X4VmpoMcbrNmrgpXwN3880346qrrsq4zdy5c4d9ftWqVTAMAwcPHsSCBQuG3cblcsHlco22mEQ0QeK6iTfea8WhHBd0VxUF5y6YjoaK/K6JKvE4ccnSmXhh5xF05rAe6t7WLrR0h3H2SdNsr7lKRBNDCIHKEhUdQRPdvfZq2Kd8gKuurkZ1dfWI9t26dSsURUFNzeTOrE5Eo2dZFt5t7ca2xnYkjNz6dbk0FRcsnIGqEs84lW5ieZwaVi+diRd3N6G12976rkBylO6mbYcwp7oUp86qhs81dea9Iyp2Sl+IC0fsDTya8gHOri1btuC1117DhRdeiEAggC1btuCmm27C5z//eZSXl0928YhoFBrbg3j70DH0xhI571vqceH9ixpsz6eWLzRVxYWLGnJabaLfgWM9ONzei4XTK7CkoSKnwRFENH4UIVDms/f7WDABzuVy4de//jW+853vIB6PY86cObjpppuwbt26yS4aEY1Qe28Ubx88iqPByIj2n1tTijPn1sGhTvnuviOiKApWzZ+GmlIvXt/XCiOHCaVMaWHHkXbsb+vG0plVmF9TOiWWESMiewomwJ1++ul49dVXJ7sYRDRKlpRo6gphT1Mn2kYY3ByKgjPm1mFe7dSe422szKkuRaXfg7/taUJXDv3igOTkv2/sb8WOxg6cPK0M82vL4dJYI0c0GSwp0R0ukD5wRFQcdNPCe23d2N3ShdAImkr7lXpcOHfhdJR5i2twUnJwwyy8eSD3JlUgOSXL1kPHsL2xA3NqSrGwvqLgmp2JpjJLSnQETRimvfXXGeCIaNJIKXEsGMWhjiAOHA1CN0c+6ayAwIL6cpw6s7pgm0yzcajJJtVpZT78/cBRRBO5L25vWBb2tnZhb2sX6sv9mF1dgoYKP/vJEY0jKSU6ghZ0U6LMW2R94MacNIF4B2AKwFCBjn2AZxngmFoLXhPlG0tKHAtGcLijF40doRGFjBNV+j1YOa8OFX73GJQw/82sKsG0ch/eOXQMe1q6Rnyc5q4QmrtCUISCaeVezKxMhrlcl/whohMYYaDzTSCiQep16IoosIQLVSUORGP2/gFlgBsrZgLY978Bdw1QvhzwzwcU3uSIAKAnGsexYBTHghG0dEfGJLQByZGYy2dVY35dGRSu+TmIpqo4Y24d5tSU4vV9rTnNGXciS1po6gyhqTMZ5urKvKgOeFBd4kFlwAMHBz8QJcWOAt3/ALq3A/WXAiULs+6SMBUYlkBNuQKnpiBq81eVAW6sWDEg1gqEDgCdbwHOcqDidKDsVMBTO+rDSykRN0xEE8agRyRhIDbgoyUlFEVAESL1UR3wtSoGfN7/fN82YsC26jDHGPq6AkVB39cKFIG+7RWoA54vRqZlwZKAZUmY0oJlSViy/3kJy0r+UTQtCUtKmJaE7PuYfP3488O+3v95/+vD7GMN+KgIAbfTAc+Ah7f/c80Bj8sBl0Md9cLnliURjusIxRLoisRxLBjBsd7ouKzHObu6FKfNrobXybnMMqn0e7Dm1Nl4t6UL24+0j/paWNJK1cwBgCIUVPhdyTDn96DE7YTf44Q2Bs3Yumn13ev0vo/mgM+T9z3dtAbf37Ld/9I8Lwa8roph7ncn3C+Hu6cOvFcWm8H3HwuWhb770gn3wr7PLcuCOeB5KXF834GfD3Oc5L0TfffCvs9TzyfvtZASLs0Bj1Ptu89p8DhVeJ0OuJ1a3/1PHZuR10YE6NmR/NsfPgxYCQBWshXPBimBco8OpyO3eSoZ4NJIGCZ0h4RhJn+QQrEEzGAUUh3+F1MYUZRbElC8kEKFEusEmp+BbNkMw92AeGAZEr6FkGr6JljDsoYEs1RY05PhLB8pYmC4K8wb2/HAlPwDNxWFs9R6KULAraUJeU4HhBAwLAumaUE3LRimTP3MhmIJ9MZ0ROL6uP+czqwqwdKGSpT52FxqlyIEFtZXYF5tKfY0d2FXc2fOkyGnY0kL7b1RtPdGBz3v1hzwuzUE3E74XBocqgJNVeBQFKiqgKYqUBTRd58bHMyievKjnqdLfwkMDnSFSQ4IThISU+/vU1Q30J1lILtLU1PhLnmv0+DRkkHPqakQSHP9pAktehDO0Ha4wrsgzOSJpOKGVAJQzF6EownEeoYvgDCjcEUTCMUkHIoFASv5z5UAEjb/yWKAG8aXLgYq8S56YtNhWgoSFrC/rQei81V4xfCznqvQ4VZ0WFKFAQHABUDCAR2avg/O3n0AXGixZqFRzsMxWQ+J4mhi7f+PCvl5Ly4alpSIJHRExqh5c6zNrCzBKTMqUc7gNmKaquKUGVU4eVo59rR0YVdT56gGjmQS0w3EdGNIsCsGEsmaKBPAOFQ+0xiK6ybiupk16PXzoxsNynuYIfbCKXqhwEJUOqDDBZlaXl6HR5hoa9qBrqajwx9IWgAEwroXccOAZerwWC2Y6T6IKs2wVRYGuGHc8XHAcL2Mp9o/CUMqMGQyaC1W3kSJ6IKF4atcBSRi0AY9Y8AJQzohYEFDArOUdzET+xCWfhyWJ6HJmotecKUIouEoQsHMSj8WNzC4jSWnQ8XSGVVY0Bfk9rV2T9ngTjTZNMRQLw5hhrIPlaINKgxYUkFCOmFliFHTlfcwHe8NeV5AwoKK98yFCOP4usQne3ZjReB1mFaRLaU1lsJxwOOSMCwFMcMNVemvOpIwpANx5L6eooSCBNxISECBAS9CWKy8iQXKO+iUNWi05qNZzkYC/CNFFHA7cVJdOebUlMLNSWXHTX+QWzK9Es3dIext7U71bSMqZgIWqkUzpov3UK8chAsxSAC6dCIOH5CuabVPVKbvLqXAhEvEhj2CJRWETB+A7GscM8ClIQFEDC+EkHCIsa0Dt+BADA5AJptYq0QzqtVmnILXcMBaiB3WqjE9H1E+UISCGZV+nFRXhtpSTtczkRRFoKEigIaKAMIxHfuOdmN/W8+YjRYmyifVohnLlZfg62siNaQDUXgHNJFODQxwaUgpoAgLbiUGA+M3yk1AQgCQEDClAwkU1+zxVNycDhXTy/1oqPBjWrmPk8VOAT63hlNnVmPZjCp0hGI40jd9SHdk5NOQEOUTU6p9fdqStdECFsQUHKbBAJeBzxGBJRWM7VWTUGHAKeIQAHQ4ccSaiyNyHtrkDJi8JFTgyrxuTCvzYnqFH9UBL5SCHaWX34QQqAp4UBXwYPmsavTGEqm54Np7ozAsjkqiwtSJWrxgfhhlaMd05T3MEPvhEWEISOhSgw4nsjWhTgSmhWH4XIAOAZGsGkuRUKCKZP+14QhIRKUX1jCjSxWY0JCAKkyYUNEtq3HYOglNcg5iYHMRFSaPU0OV343KgBtVAQ8q/G7WsuWpgNuJhfUVWFhfAUtK9ETi6AjF0NEbRXtvDD2R+BSsoyAaKYFuVKPbqsYurECtOIIGsR91SiO8CENCQJdOGHBguDDXH/jSMaEOeVVCQAiJgMNeP1QGuGF87RfAJR+6ACc2d2+zVsGN4ccaa9CxWH0DCqwBAU5CQwKa0CEhEJNeNFrz0GTNRReqMRUSPNFIKUKBQxVwOlT4XBr8bm3IR06yW5gUIVDuc6Pc58b82jIAyUl3Q9EEQnEdobiOcExHKJ5AOGYgpuupeQOJ8o0FB1rkbLTI2XBZEUwXBzBT2YtS0QEn4jClAh2uIZU3h6yT0S7rhj2m6MsHA+2KLEbQLEUioQN4Omu5GOCG8estwPs+Ogdl7gR0UyBmqDi5vhz+ulMgVe+w+wijF979WyGFCkBAMaOAAKTiguFbDL1kGRTfSZilODErzXlNyxqyskJkwGS+Md3e3DBEI3HiJL4nTujrVFWoqoBDSU7GyqZPGkhTFZT73SjPsB5t/2oihmXB6JsQetBEvvrxz5P3QBPmFJ0Ym/KfpirHJ+/tW5khOalv8nOXQwWGnXz+FEBKWPFmqMHtcAf/Aa8RBGQCUnFBKi4opoqZtYtRV37WsOcWZgRaz9voimrY3aXC7QBUdyW6RD2C8SgY4EbBoSpQFQFTJmfU9mgOlHqcgCPNIAM9DigiuUCt6gJ8DUDlCqB0KVRnqe2hCZUZXrMsiZhhDFlOq3/lhnBMR080nuu3SkWg1OOCz60NCmTu/pUWNAfc2hgtKUOUgRACDlXAoSpIjQ3L0oMkrvev0mAeX1ZrQNDrDMUZ8mgIt6ai1Os+HsycWnLZwL7PvU5H8udwNHxzgYq5gHUZEHwX6NoKBHcDVi8AC16nA15vmr/+hgFEHYgZjuSqHUpydRIIxXa5GODGiuoBfHMAT11y/VNvQ5rkPnKKIuB1pm+W6onE8Ye3h04aSPS+BfWcCJfykktT4dJUlKUJen/cegBdYY6QpcHm1pThtNk1E3MyRQPKliQfehDo3gb07ATco18HPRMGuDTCUROlahgwVcDUgPBBwJgPONLcRRQNmP+vE1pGIiIimkK0EqD6fclHJkYE6N0LxLyAWQ5AByw/kMMgLwa4NMIJoNcshcthAlAB32zAMXz/NwCAZQAH/xtw1wDlpwLuujGvgSMiIqIpzAgD3TuA4E6g5v2Af+7w2zm8QOAkQNWS3a4cDkDJbYQ+A1waPrdAMKbC6xRQFRtD480I0Lsn2QZ+9MVkE2rF6UDpKYDmH7NyxXUTkYTeN8DBRGxAf5BQLJH9AFSUtuxtgb+/D5zm6OsDovb1g9Pg4nJVNEUZpjW4v69u9A18SPb9DUZ536OhDhwLojsSHzooS+vrA6w5xm4glmUCoX3Jv/89O5N5QFrJgJYuwI0BBrg03A5AVQz0xBzwaibiholQTAccw98shKHDIyWkmmxiFaEDQOg9QHkaRmAhzNJlML3zACX9W378RtU3CktPjsKKJPTkKFSOyKIR6grHMvYTUoUCt1PtG+CgJT/Xkp97+oKeS1P7RqAKDnigEZNSwrAkDNM6fs/TBw/ISg1WSJjQzbFdypCKQ/LnJ/NScMONvO8f4OXRkve8TBFPxI/C0bMNjuBWiERXMrQpTkg1AGH0IqGbMNJVrBg6HLqJuKFASsCSyQwAIWCa9v7OM8AN46NnAC7jEBJqJVS4EEk4sLupE3rbG3CL4f8IOpDAUlWHJa2+pbfcELCgIQZH/O+Q7W8iJv1olPNxxJqHIMrBeeBoqjClhXDcQjiuA4hm3V4RfdOJqApcmgp/37xvfrczNQec361BZdArKpG4jt5Ycu63UDyBUCw5J1w0YUA3TRimhMm54GiKiOnJ6bm6sq8bn+JEDPXiIGYo+1AhjsKCgZhUkIATVmq+CR0eYeLgoV1oP9gz7HEETDgRQ0T3IpKoha7rcOjHMM3ZDCfsrUEspJScOnuAYDCI6K9KoTvr8D8dl8O0FMQtJ1bU7sQi11aUis60+x5fiWFoLlZgwok4FGHBhANdsgqHrZPQLGcjAc94fktEk6J/stf+5ZiqAm743c7JLhaNEd000d6bXInhWG8UHaEo4jpry6jwCJioFs2YIfZjmnIITsQhgb6VGDQMVxnjFSFkWofThIYD5kK069V4++giaELH0pJ/4Az/GwAsBK6MoKenByUlJWmPwRq4YYTjgMd1/L9ERSQvggILpnQgPoLAZUFFDF5ASjhgoFK0okptxSl4HS3WLByR83BM1g+7DBdRPrKkREco+Yd9T0vyOY/mQHWpFw0Vfkwv98Pp4M97vrCkxLFgBEc6Q2jtjnBxeyp4AXRhuvIeZoq98IkQBCwY0oEovJAnLtV0gohM3/ddgQmXiB1faksCEIDStxhdrxEA0qz6NBAD3IQTMKDBkFpfE2sCs5R3MRN7EZF+7LNOwX65dLILSTQuorqBw+1BHG4PQhECNaVezKgIoKHSz2W3piDDstDaHcGRzl4c6exlDRsVhTIcw1L1NVSIo1BhwJIK4tI5bOvaWDCkCoe012w6EAPcJJIQsKBCwoSAhFPE4RW9mWpdiQqGJSVau8No7Q7jjfeAmhIvTqorw4zKAPvOTbKOUBR7W7tx6FiQ65dS0XGKOLzohQITgIQFBVaWGrfRkAAipifnP/0McJNAgQkNcajCggkVXbIah62T0CTnII4Mc80RFbCjwQiOBiNwayrm1ZTjpLoy+NyslZsohmnhUHsv9rZ2oSOUfSALUaE6KhuwyfwkasQRNIj9qFMa4UUEEqKv35sDYzkI0SFMJCwNppVbSGSAG4bPBZjDXhwBhzCgYPghKwISMelJ049NQkMCmtAhIRCVPjRa89BkzUU3qsARqURJMd3EjqZ27Ghqx/RyPxZNr0BtaZYFM2nEogkdu5o7sb+tBwmDTaREQLLfequchVY5Cy4rgnpxEDOVvSgT7XAiDlMq0OFK22/dLSLH+7gNISGhpF4VAnA7YpBSQIEFvxqyVUYGuGHc/T/A2RedNeT53dbyvpElQzlgYJ6yHQqsARc0OWBBEwkISOhwotGahyNyHtpkw7i1pxMViqauEJq6QphW5sOps6pR6eeI7bES103sbOrAnpYuTu1BlEEcXhyQi3HAXIRSdGK6sh8zxX54RAgCEoZ0IAEnMKCZVUCiWc5Gt6wc9pgCEuaA8OcQFg7E58HsVqEbBoDns5aLCWIYP/4zMOfCRSh3J6CbAnFTxZyaUriqF0GqwzdxKkYvPI17IIUCKRQoVgxCmpDCAcM5A1H/qYj7FsHvCGAhgIXDHMM0LUR1E5GEgVhCRyRh9k1yqed952EBAUURGKuJr6caSwKWJfvGEOUvl6bCoyUn701ObKnB63TAo6kQigLDNKGbFgxTwrAs6KaJWMJEbzSBYCwxbjU4Ld1htHSHMaMigGUzq1Dmc4/LeYqBbprY3dyFXU2d4zpJriIUBNwaAh4NPrcTmpqcN1Drmz9QUxUIIRAfMInvwIl8Y7oBK89nuVKEArVAu3MmJ5+VeX+NHIqSdjJf17Cj5GcCWI64NIDIfrjC2+GJ7IXXSo7KthQ3pHBCNRVUVp4Cb+nKYc8rzAg8oXfQHXViV5cKlyqhuOpx0GxAS08EDHCj4HKo0FQFEgKGFCjxOFFR5ku/mL1uAc0iuQ6aogHOUqD8NKB8GRye6XCPcl1Uy7L6Vmjom6E8TdCzLEBVBFQhIPo+JoPT8Y/qgK9PfD3d16oQEAP37X++/5gnnG+48xYDS0pYlhz00bQkTCkh+z72Pyf7PvbfBK3+1wd8PPH5gV/3H8884XzDva4o6Atmjr5wpsGjqX03qr6Q5lRHvcJCXDcRjCbQG0ugOxxDW08EXeH4mAXbxs5eNHb2Yk51KU6bXQOPk7cwuywpsbelC9uOtI/5P4Rep4aaUi+q/G4EPE6UeJzwurRR/d5LKRHXzUGrNJwY9GIJAwnT7LvHKH33o2RwSt6HAEVR+u5DyRVHlAHbqApS+yoCffet5OfJ/ZW+/QSEovS9fsJxBjx/4nmLhWlZffc1wJJW373o+PNW3/OmNfz9z87Xw90nj9/3Bp6r7/4nAbemDl1K64SgpuWwePwQFSsArAD0XqBnO9D5JtRIM2D1AkKi3OdCeXma6UQMAVguWNCgKgIOVYFTc8DtVBH32buv8e43VhQ34KwEShYD5cuBkpOTQW6sDq8o8LmVvk7dbEaaqhQhoKjFEVaH49JUVGseVJd4AJQCABKGiaPBKI72hNEWjKArNPpAd+BYD5q6Qjh9dg3m1ZaNvuAFrjscw2v7W9HeOzaDE7xODbWlXtSUelFb4kXAM/YTNAsh4O6rCSlnF8gpTVUUqACSSyoX4dyOWgCoOhuoPAuItgDd7wDd2wFn+cgOp9kL/wxwY0V1AovWTXYpiKYcp0NFQ4UfDRXJ/0SjCR2H2ntx4FgPOkMjnww2YZh4dV8LDhwLYuW8OpSMQ4jId4ZlYUdjB3Y2dYy6qcutOTCrqgSzq0tQFeA/kURDCAF465OP+stGfJhwzF4NOQNcOkIFXJWAIQFYQOWZgINvF9FoeZwaFtZXYGF9BYLRBA4c68HBY0GE0i36nEVbTxh/fPsATplRicXTK6EUakfLHB3tieC1/S0IRkf2vgLJ/kEzKgOYXV2CulIf31uiseLwATXvB3oNwNEFOBVACPRGTIRjXMyeiKa4Eo8Tp86sxqkzq9HcFcLOIx1oC2ZfQuZEprTwzuFjaO2J4H0n1xd13zgpJXYc6cA/DrePuKna49SwqL4C8+tKR9dHiIhs642YCEYt+NxsQiWiPFJf7kd9uR/HglHsbGrHkU57cyEN1NYTxp/eOYhzT65HTWnxTYod101s2duMpq7c3zsACLidWDS9AnNrSrkaBtEECkdNRBISJR4FlmnvnyYGOCKaUqpLPDi/ZAa6wzHsONKBg+3BnPaPJnQ8u/0wls+uxuLpw8/BVIg6QlG8tLsJ4XjuayqWelxYOqMKM6oCRTNinGiqMEyJcMxCmU9FwKuip9fefgxwRDQllfnceN+C6ThpWjn+/l4busL2BzxISLx98Cjag1Gcc3I9HIU6GVef/W3deH1/GyyZ24S8mqpg6cxqLKgrK6ppL4imEt2U8LsVBLy5dVfgbywRTWk1JV5cumw2zphTm3N/rMbOXjy343DeT4SdybbGdry6ryXn8DanuhQfOH0uFtVXMLwRTSJNFfB5cu9ryho4G/J8ommivKcoAgvqKzCrqgRbDx3F/qM9tvdt741i07ZDuGjJDHhdYzc342STUuLNA0exp6Uzp/3KvG6cObe2KPsIEk1FjhHOHcp/u7KQUiJhMMERTQVupwNnnVSP8xfNgHPYZW6G1xON45lth0Y1pcZUYlkWXnm3OefwtmBaBS49dRbDG1EBYIDLwJISXSETklVwRFNKQ4Uf/7x8Tt+KD/aE4zqe2XYQHaGxWY1gshimhRd2NeU0uMOpqnj/wgacMbeWo0uJCgR/k9OQUqIjaMIwJZwOvk1EU43PpWH1kllY0lBle5+4buL5HY3oicTHsWTjx7IsvLSnCS3d9qcJqQp48M/L52BGZWAcS0ZEE43JJI3usAndlCj3qeA/rERTk6IILJ9VjYsWz4TT5gCHhJEMceFY7tNtTCYpJV7d14rmHOZ4W1RfgX86ZWbfGspEVEgYTdIwTImqgGp7UVkimjzTyn34p6Uz4XHaCyqRhI7ndx5GLI9Gp7518CgOHLM/eGPFnFqcPqeWI0yJChR/s9Mo86pwMrwR5Y0ynxtrls6yvah9MJrACzsboZu5Tb8xGXY0tmN3s70BC4oQeN/J9VhYXzHOpSKiycSEkgZr3ojyj8+t4Z+WzkaV397gho5QFH/b0wRrCg9Ueu9oD7YePmZrW4ei4IJFDZhdXTrOpSKiycaUQkQFxa2puPiUmZhW5re1fXNXCNsb28e5VCPTFY7h9f2ttrZ1aSpWL52JaeX2vm8iym8McERUcByqgvcvnG57mpFtje05DQ6YCLpp4qXdTTCt7E28yZq3Gai0WfNIRPmPAY6ICpJDVXD+whko9bpsbf/K3uYRLQQ/Xl7d24reWPaJhxUhcN7C6agKMLwRFRMGuDR0fep3bCaizFyaiosWz4DPxujUuG4m+8PZqPEab7ubO3G4w95EvWedNA31bDYlKjoMcGl0R0wkGOKI8p7XpeHCJfaW3mrvjeKdw5PbH64zFMPbB4/a2vb02bWYwwELREWJAS4NhyrQ3muyJo6oAJR6XTh/YQMEsi8avaupE52h2ASUaijLknh1X4utUbEn15Vj0XROFUJUrBjg0ijzqdBUga6wiSnQokJEo1RT6sWymdmX3ZLoC1HWxE8tsqelE13h7OGx3OfGaXNqJqBERDRVMcClIYRAZYkKhyqQMJjgiArBkoZKTCvzZd2uKxzDnhZ7E+eOld5YwlbzraYqOHfBdDi4wgJRUeMdIANFCJT7VQiRvdmFiKY+IQTOPqkeHs2Rddt3DrfbGgU6Vl7f32prypCV8+psrzZBRIWLAS4LIQScDgY4okLhcTpwzoL6rNuZloU39rdNQImAg8d60NodzrrdvNoyrrJARAAY4GxhBRxRYakr9dkaANDSHUJrT/ZgNRqWZWHroexLZfndTpwxp3Zcy0JEE88wR9bflgGOiIrS0hnV8NqYH+4dG+FqNPa19diaQHjFnFo4VN6yiQqNbkqEo2bO+/FuQERFSVMVnD47+0jO9t4ojnSOzzJbhmlh+5GOrNtNL/ejoYKT9RIVIk0VCMUs9EZyC3EMcERUtGZVl6C2NPuo1H8cPgZpY262XO1t7UI0kbn2TRUKVrDplKhgOVQBv1tBMJpbiGOAI6KidsbcWihZOrp2hWM43NE7pufVTRM7mrLXvi1qqECAo06JCprPo6LEkwxx4Zi9EMcAR0RFrczrwsnTyrNut8NGU2cu9rX2IK5nvlF7nRqWTK8c0/MS0dQU8CZDXDhmb+5ZBjgiKnqLp1dAFZlvh13hGI4GI2NyPikl3m3tslUuDlwgKh4Brwqf297vPO8MRFT0PE4Nc2qzz6+2t7V7TM7X0h1GKMskwW5NxbzasjE5HxHlD59btbUdAxwREZK1XdkWuz/c3ouYboz6XHtt1L4tmMbaN6JipOtsQiUisi3gdmJWVSDjNpa0sL+te1TnCcd0NHVmnhxYUxVb/fKIqLAkdAvdNkeiMsAREfVZ3JB9wMDe1m5Yo5hSZF9bNyQy739SXTmcDnvNKERUGBK6hfZeEw7V3vJPDHBERH3Kfe6s88KF4zrae6MjPseBYz1Zt2HtG1Fx0fvCm6YKlPnYB46IKGdzqkuybnNkhHPCdYViWZfNqi31wefKvsQXERUGywK6wsnwVlmiQthcgJ0BjohogBmVgaxTijSOcGmtxs7swc9OgCSiwpEwLDj6wlu2ScUHYoAjIhrA6VAxPcu6o6FYAl3hWM7HzramqioUzKjMPJCCiAqLEALl/tzCG8AAR0Q0xGw7zag51sLZCX3TK/wcvEBUZJwOYbvZdKC8CXB33nknzjnnHHi9XpSVlQ27zeHDh7F27Vp4vV7U1NTgG9/4Bgxj9HM2GebYL2JNRFNXfbkva5BqzLEfnJ1mVzvBkYgKywiyG4A8CnCJRAKXX345rrvuumFfN00Ta9euRSKRwCuvvIKf//zn2LhxI9avXz+q84ajJnQGOKKioioK6ssyj0btCseyrmU6UFtP5rnfFKFgWpZzEhH1yznAXXnllXjxxRfHoywZ3XHHHbjpppuwdOnSYV9/5plnsHPnTvzyl7/E8uXLcdlll+G73/0uHnjgASQSmZesSac3YiIUs6DZnJOFiApHTak36zYdIfvTiXRkmXqkMuDmygtEZFvOd4uenh6sXr0aJ510Eu666y40NTWNR7lytmXLFixduhS1tbWp59asWYNgMIgdO3ak3S8ejyMYDA56AEA4ZiIYteB3K7Yn1SOiwpFtPjgAtueD640mEMtSW1drIzASEfXLOcA9+eSTaGpqwnXXXYfHH38cs2fPxmWXXYbf/va30PXM8xuNp9bW1kHhDUDq69bW1rT73X333SgtLU09ZsyYAQAIxyyUeBT4POxQTFSMSjxOeJyZ52OzG+DabdTU1ZQwwBGRfSOqr6+ursa6devwzjvv4LXXXsP8+fNxxRVXoL6+HjfddBP27t1r6zi33HILhBAZH7t37x5JEW279dZb0dPTk3o0NjYCAHxuBQEvwxtRMasp8WR8vb03BmljWa32YOYApwiB6kDmcxERDeQYzc4tLS3YtGkTNm3aBFVV8c///M/Ytm0bFi9ejHvuuQc33XRTxv1vvvlmXHXVVRm3mTt3rq2y1NXV4fXXXx/0XFtbW+q1dFwuF1wu15DnfW6GN6JiV1vqxaH2YNrXddNETzSBMu/Qe8hA2Wrg2P+NiHKVc4DTdR3/8z//g0cffRTPPPMMli1bhq997Wv47Gc/i5KS5BD43/3ud/jCF76QNcBVV1ejurp6ZCU/wdlnn40777wTR48eRU1NDQBg06ZNKCkpweLFi8fkHERUXCr87qzb9ETiWQNcTzjzQKoKP2vfiCg3OQe4adOmwbIsfOYzn8Hrr7+O5cuXD9nmwgsvTDtX20gdPnwYnZ2dOHz4MEzTxNatWwEA8+fPh9/vxyWXXILFixfjiiuuwD333IPW1lbcdtttuOGGG4atYSMiyqbE48y6TSjL2qaRhA5TWpnP485+HiKigXIOcD/60Y9w+eWXw+1O/59pWVkZDhw4MKqCnWj9+vX4+c9/nvr6tNNOAwBs3rwZF1xwAVRVxR/+8Adcd911OPvss+Hz+XDllVdiw4YNY1oOIioemqrCrTkQ09NPCB6KZQ5w2V4HgAADHBHlKOcAd8UVV4xHObLauHEjNm7cmHGbWbNm4Y9//OOYnM9Ox2QiKnwlHmfGABeOZW4eDWepoes/BxFRLthrNo3usAmLIY6o6AWyhKvR1sCpQoHXNarxZERUhBjg0jBMiY6gyZo4oiKXrXkzHDcy3iey1dD5PdqIFrImouLGAJdGmVeFbkp0hUwwwxEVL1+W2jFLWogb6QcpRLOswOBzZZ4smIhoOAxwaWiagqqACsOUSBhMcETFys78bKaZPsAZGV4DAIfC2zAR5Y53jgycmoJyn8pmVKIiZifA6Wb6WjY9S4DTuNYyEY0Ae85moWkKnJlbQIiogGk2Apxhpf8nz7Sy1MBxBQYiGgHeOWxgCwdR8bLTxJkppBlm5hp8h8Jl+4iKWZb/8dJiNCEiysBWDVyGkGZkuTuzCZWouCUMC7qee4pjgCMiysRGvkrXB05KmXUQg53jE1HhEkKgK2wikWOIY4AjIsogmki/CkO2bWJ69gnBs00zQkSFzekQcKgC7b25hTgGOCKiDOwEuEiabUYT/oioOAgBlPtVaH0hzm5zKgMcEVEGowlh9vbNvlYqERU2IQQqS5Ihrjtir1aeAY6IKAM7ISyWLsDpdgIcm1CJCFD6QpzD5sAmBjgiogzGvQk1ziZUIkpShECZz97UQgxwREQZjHcTqiktxDmQgYhyxABHRJSBnRBmWNawU4nY7d9mp6mViAqfJSW6w+wDR0Q0anan+RiuL5vd/m0ciUpElpToCJpZV2/pxwBHRJSGJWXaAQonGq62zW4wY4AjKm6yL7zppkSZl33giIhGJaYbkLD33/CJIUxKyQBHRFlJCXSFkuGtKqBC0+xFMwY4IqI0cglWJ24b080Rhz8iKh4JQ8LoC29Om+ENYIAjIkprNAEup305iIGoaEkpUe7LLbwBDHBERGnlEsJOnAtuNOGPiIqH06HYbjYdiAHOBsv+2rJEVEByCVYnDnaI5VCrxgBHVLyUESYxBrgsdN1CwmCCIypGo6mBS7c6w2jPQ0QEMMBllNAtdIVNCGFvXTIiKiwT1QfOtLgaAxHlxjHZBZiqdN1CWDfhUAWcDgY4omJkWPZGkSa3tfDYK3tSX1syt5p7U1oA7M3/RETEGrg0uiMmNFWg3K+CFXBExUnJ8Zffklbqkfu5eDsmIvt4x0jDoQpUlqhsPiUqYuoE3iEn8lxElP94y0ijzKfm/N83ERWWiawV4/2GiHLBAJcGa96ISFEm7j6gjnQuASIqSrxjEBGloU5QfmPtGxHligGOiCgNMUG1YgxwRJQrBjgiojTUCQpWE9lUS0SFgQEujXCMk2oSFTt1goIVa+CIKFcMcGmEYxZ6IwxxRMVsogYzTVRQJKLCwZUY0vC5FQSjFrymhDpRPZmJaEqZqFzFGjgiyhVr4NLwuVWUeBSEYhYM0/5yOkRUOCasCZU1cESUI9bAZRDwqjBMiQQDHFFRmqiJfFkDR0S5Yg1cFj6PCo1NqERFaaJq4CZqtCsRFQ4GOBscDHBERWmimjbZhEpUvOQIG/kY4IiI0piopk02oRIVr4QhIUeQ4hjgiIjSmKhgxWlEiIqXlBJdIRNWjiGOAY6IKA1O5EtE483pUGCYEh3B3EIcAxwRURoT1oTKGjiioqUoQLlPhd4X4uw2pzLAERGlwT5wRDQRNE1BVSAZ4rrD9laBYoAjIkpDmaA7JPvAEZGzL8TZXTyAAY6IKA2VE/kS0QRyagrKvKqtbRngiIjS4DxwRDTRNM1eNGOAIyJKY8ICHGvgiKhPOMY+cEREo8JRqEQ0kXojJsIxy9a2DHBERGlM1BqlXAuViHojJoJRCz63vWjmGOfyEBHlrYkahcoaOKLiFo6aiCQkSjwKLJODGIiIRkXhKFQiGmeGKRGKWSjxKAjYHIEKMMAREaU1UfOzcR44ouKlmxJ+d27hDWCAIyJKiysxENF401QBnye38AYwwNmSw9qyRFRAOA8cEY03hzqy338GuCyklEgYTHBExWoiVmNgDRwR5YoBLgNLSnSFTEhWwREVrYmoHWMfOCLKFQNcGlJKdARNGKaE08G3iahYTcRUIqyBI6JcMZmk0R02oZsS5T51wuaCIqKpZyKaUFkDR0S5YjRJwzAlqgKq7UVliagwTUQTqmANHBHliOkkjTKvCifDG1HRm4jKMdbAEVGumFDSYM0bEQGAOgF9KNgHjohyxZRCRJTBRDRvch44IsoVAxwRUQYjnGMzJ6yBI6JcMcAREWWgsAmViKYgBrg0dN2a7CIQERERDYsBLo3uiIkEQxwRERFNQQxwaThUgfZekzVxRERENOUwwKVR5lOhqQJdYRMWMxwRERFNIQxwaQghUFmiwqEKJAwmOCIiIpo6GOAyUIRAuV/lMjdEREQ0pTDAZSGEgNPBAEdERERTR94EuDvvvBPnnHMOvF4vysrKht1GCDHk8etf/3rU52YFHBEREY0Hw5Qj2s8xxuUYN4lEApdffjnOPvts/Nd//Vfa7R599FFceumlqa/ThT0iIiKiyaabEuGoCWcgt0iWNwHujjvuAABs3Lgx43ZlZWWoq6ubgBIRERERjY6mCoRiFhyqiYBXtb1f3jSh2nXDDTegqqoKK1euxCOPPAIpM1dNxuNxBIPBQQ8iIiKiieBQBfxuBcGohd6IaX+/cSzThNuwYQMuuugieL1ePPPMM7j++usRCoVw4403pt3n7rvvTtXuEREREU00n0eFQ7UQjFoQlr0QN6k1cLfccsuwAw8GPnbv3m37eN/+9rfxvve9D6eddhr+7d/+Dd/85jdx7733Ztzn1ltvRU9PT+rR2Ng42m+LiIiIKCcBr4oSj4JwzN7cs5NaA3fzzTfjqquuyrjN3LlzR3z8VatW4bvf/S7i8ThcLtew27hcrrSvEREREU2UgFdFb9he3dqkBrjq6mpUV1eP2/G3bt2K8vJyBjQiIiLKCz63vYEMedMH7vDhw+js7MThw4dhmia2bt0KAJg/fz78fj9+//vfo62tDWeddRbcbjc2bdqEu+66C1//+tcnt+BERERENul6HjSh5mL9+vX4+c9/nvr6tNNOAwBs3rwZF1xwATRNwwMPPICbbroJUkrMnz8f9913H6655prJKjIRERGRbQndQrfNkah5E+A2btyYcQ64Sy+9dNAEvkRERET5IqFbaO814VDtLf+UNwGOiIiIqBDpuoWeqAVNFfD67PWBK7iJfImIiIjyhWUBXWETmipQWaJC2FyAnQGOiIiIaJIkDAuOvvCm2AxvAJtQiYiIiCaNEALlPiWn8AawBo6IiIho0jgdwnaz6UAMcDYYppzsIhAREVEBGkF2A8AAl1U4akJngCMiIqIphAEug96IiVAsOayXiIiIaKrgIIY0wjETUrHgdytQGeCIiIhoCmENXBrhmIUSjwKfx96EekREREQThQEuDZ9bQcDL8EZERERTDwNcGj43wxsRERFNTQxwRERERHmGAY6IiIgozzDAEREREeUZBrg0pOTkvURERDQ1McCl0R02YTHEERER0RTEAJeGYUp0BE3WxBEREdGUwwCXRplXhW5KdIVMMMMRERHRVMIAl4amKagKqDBMiYTBBEdERERTBwNcBk5NQblPZTMqERERTSlczD4LTVPgNCe7FERERETHsQbOBoXvEhEREY0DyxrZfowmRERERJMkYVjQ9dxTHAMcERER0SQRQqArbCKRY4hjgCMiIiKaJE6HgEMVaO/NLcQxwBERERFNEiGAcr8KrS/E2W1OZYAjIiIimkRCCFSWJENcd8Te1BcMcERERESTTOkLcQ5V2Nt+nMtDRERERDYoQqDMp9rbdpzLQkRERERjjAGOiIiIaAqwpER3mH3giIiIiPKCJSU6giYM097661wLlYiIiGgSSSnREbSgmxJlXvaBIyIiIprSpAS6QiZ0U6IqoELT7EUzBjgiogyktNecMbqTjP8piGhqShgSRl94c9oMbwADHBFRRpY1/unKnIiQSERTkpQS5b7cwhvAAEdElNFEhCvLym0RayIqHE6HYrvZdCAGOBt4byUqXhNRAzcBpyCiKUoZYRJjgMtC1y0kDCY4omJlTUgNHBMcEeWGAS6DhG6hK2xCCHvrkhFR4ZmIAGdK/pNIRLnhPHBp6LqFsG7CoQo4HQxwRMXKnIgmVOY3IsoRa+DS6I6Y0FSBcr8KVsARFS+OQiWiqYgBLg2HKlBZorL5lKjITUQTqmQVHBHliAEujTKfCoXhjajoTUQTKmvgiChXDHBpsOaNiKSUkBOwTAIr4IgoVwxwRERpTFTNGEehElGuGOCIiNKYqPnZOA8cEeWKAY6IKI2JGMCQPM+EnIaICggDXBrhmDnZRSCiSTZhAY6d4IgoRwxwaYRjFnojDHFExWwiRqACHIVKRLnjSgxp+NwKglELXlNCVTkilagYsQmViKYq1sCl4XOrKPEoCMUsGCbvrkTFaOIGMbAJlYhywxq4DAJeFYYpkWCAIypKE1cDx3sMEeWGNXBZ+DwqNDahEhWlCesDxwo4IsoRA5wNDgY4oqI0cTVwTHBExWqktxkGOCKiNCasDxxbUImKVsKQkCNIcQxwRERpTNT0HlyJgah4SSnRFTJzrvFngCMiSmOighXXQiUqXk6HAsOU6AjmFuIY4IiI0pi4lRgm5DRENAUpClDuU6H3hTi7zakMcEREaUxcHzg2oRIVM01TUBVIhrjusL1VoBjgiIjSmKg+cCar4IiKnrMvxNldPIABjogoDdbAEdFEcmoKyryqrW0Z4IiI0mAfOCKaaJpmL5oxwBERpTFxNXBMcESUFI6xDxwR0aic2AdOSglD2ru55nQezgNHRAB6IybCMXv/0DHAERGlcWIN3FvR93BP2++QsIyxPQ/zG1HR642YCEYt+NxsQiUiGpUT+8BtCe1Bi96FnbHGMT4Pm1CJilk4mgxvJR4FPjcHMRARjcrAGrg2vRv7E62IWTr+Htk3buchouJimBKhWDK8BWyOQAUY4IiI0hrYB+7t6AEkLAMB1YNdsSPoMsJjdh6OQiUqXrop4XfnFt4ABjgiorT6a8YsaeH18LtQhQKPcCJm6dgaPTBm5+FaqETFS1MFfJ7cwhvAAGcL59gkKk79NXB74y1oN3rhUZxQhIAQAq+F37W9ZqEdFqvhiIqSQxUj2o8BLgspJRIGExxRMZJ9NXBvRt6DKS1oSP6X7BVOtOhdOJQ4NmbnYjc4IspFXgS4gwcP4otf/CLmzJkDj8eDefPm4fbbb0cikRi03T/+8Q+cd955cLvdmDFjBu65555RndeSEl0hc0z/yyai/GFKiYgVxzvRA3AKB4RI/qfsFA7o0sRbkffG7lxMcESUA8dkF8CO3bt3w7Is/O///b8xf/58bN++Hddccw3C4TB+8IMfAACCwSAuueQSrF69Gg8//DC2bduGL3zhCygrK8O1116b8zmllOgImjBMCb/NIb1EVFgsS+If0UMImzGUqN7U80IIaELFm9H9+EDpGXAqo7+VJqcS4b2GiOzJiwB36aWX4tJLL019PXfuXOzZswcPPfRQKsD96le/QiKRwCOPPAKn04klS5Zg69atuO+++0YU4LrDJpwuiXKfCpP/GBMVrb+H90ECUMXgBguv4kSPGcHOWCOWe+dAQODsk6elXt/f1oO2nrEbqUpENFBeNKEOp6enBxUVFamvt2zZgve///1wOp2p59asWYM9e/agq6sr7XHi8TiCweCgB5Ccl6UqoNpeVJaICk+HFcT+RCs8inPIaw6hQkqZmhPO43RgTnVp6lHpd9s+j4CAy5EX/08T0RSRl+lk3759+MlPfoIvfelLqedaW1tRW1s7aLv+r1tbW9Me6+6770ZpaWnqMWPGDABAmVeFk+GNqKi9HtqHhGXALbRhX3crWmpOOI9zcADzOu0HMremQlFGNhKNiIrTpCaUW265BaJvSH66x+7duwft09TUhEsvvRSXX345rrnmmlGX4dZbb0VPT0/q0diYXCKHNW9Exc20LDzfsROqUFKDF07kHjAnnMc5uP/aiYEuk1y2JSICJrkP3M0334yrrroq4zZz585Nfd7c3IwLL7wQ55xzDn72s58N2q6urg5tbW2Dnuv/uq6uLu3xXS4XXC5XjiUnokK3pf09tMa7h20+7TdwTrhrtHMHveZxDl9rNxwGOCLK1aTeNaqrq1FdXW1r26amJlx44YVYsWIFHn30USjK4Bqys88+G9/61reg6zo0LXnj3LRpExYsWIDy8vIxLzsRFbanjmyFIS34kD7AAQPmhNOPYRWOD2I4sUYuEwY4IspVXrQTNjU14YILLsDMmTPxgx/8AMeOHUNra+ugvm2f/exn4XQ68cUvfhE7duzA448/jh//+MdYt27dJJaciPJRTyKKPzZvh9ehpW0+7dc/J9zfuvYMet7NJlQiGkd5cdfYtGkT9u3bh3379qGhoWHQa/2T7JaWluKZZ57BDTfcgBUrVqCqqgrr168f0RQiAKDrXNaGqFj9pWUHOuJhOBUVETMGIQS8wjkozBnSRMzSAQAWLDzfsQtRIwGPI1lj51AUOB0qEoaZ9XwMcESUq7y4a1x11VVZ+8oBwLJly/DSSy+NyTm7IyZKAhaQ5b9vIio8MVNHnbsEFiS6jTh6zSg0ocI54JbZa8XgFk5oQoEbGko0N3qNWCrAAclgxgBHROOBd400HKpAe6+JUk9etDIT0Rj6l7ln41/mng0AeHjLG/j2oceHbiQl5rvr8OXqNQCAj5150pAg5tEc6EE86/kY4IgoV0wnaZT5VGiqQFfYhMXWVKKiZacvm4CAWxs6aMFuMGOAI6JcMcClIYRAZYkKhyqQMJjgiIqVW8serjxOx7CDHewEMwEBN1dhIKIcMcBloAiBcr+adRQaERWu4WrWTpQuqNkJcFyFgYhGggEuCyEEnA7eXImKlctWgBt+G1sBjs2nRDQCDHA2sAKOqHjZad5Mt+qC18ZqDLmsmUpEhccw5Yj2452DiCgDV9+6yEEzCgXH/5vTpZH6PH0T6sibX4moOOimRDhqwhnI7V7AOwcR0QBRMzro6+n+AE7zzUa8b9LegU7xNMAUCaiaOWg/j+pJfrQRzhjgiIqbpgqEYhYcqomA1/4SfLxzEBENsCu6a9DXBiQ+NmNu2u0jaEIzwohF3annTvefDgBQFQWqosDMMBeR5rB/wyaiwuNQBfxuBcFobjNeMMARERERTSKfR4VDtRCMWhBW9tVbAAY4IiIioknX33za2mGvJo6jUImIiIimgIBXhc9tL5qxBo6IaIBFnkWDvk6YJnZHMt8qZ6n1aPD4x7NYRFQkfG57/WIZ4IiIBugfQdpPsUyo0plxH6dwDdmPiGgkdJ1NqERERER5I6Fb6I7YG8TAAEdEREQ0yRK6hfZeEw7V3vJPbEIlIiIimkS6bqEnakFTBbw+9oEbFd2QSBgSuiFhmBI9YXtVmkRUWBKGCV3P3FgRjFjo7DWGfS2hC1hW+v1DUZl2XyIqbD1hEwldIpIw4XQoKPEq6A3Z25cBLo1jQR1h3QFLSkgJ/PGNHjhUAcOU0E0JTRVZqzmlBBKGhJQSTocCZYwarC0LSBgWhBBwOgREltrWXMpsV67fW65ltovXI4nX47ixvh5SAl1hb8ZjvBCMw+k4vtTWwO8tkvACSL9YdU+Pjr+rXbweIyizXfz9OI7X47ipcD10Q6Krr4LIsiy0dklEokOX7RsOA1waAoDSdz0lkgtaJ3QL4ZgFv1uBz2OvitPtlOgKmQjFTJT7VGja6K66rlsIxpJt5OU+BcLmT3I4aiKUY9nTkTL5PRmmzOl70nSgK2zCtATK/artsqcTjpq8HuD1GGg8rodlSShK+gAGAE4NcPeV/cTrETctyAy7aw7A61J4PQbg70cSr8dxhXo9uuMWIJP3AbUvdNj9zhjg0hACUBQBWICFZPqPJCTKfGpOi80CAjVlAh1BEz1RC1UOAecIL3qir43cpSmoLFGh5PAD7Aw44FBNBKMWHKqV4/dwnCUlOoIWLAnUlDpy+l6cDhWaQ6C910QwYuX8PQzUGzF5PcDrMdB4XQ/TQtb/th1qsmZguOvRHUPGANe/L6/Hcfz96MfrkSpDgV4Pp0PANCVURSQzB2C7hpGjUG0wTIlQ1EKJRxnRD64iBCpLVGhq8ocvYXOOl4H6R6doqhjxD27Aq6LEk1wwt9fmMOWBkr98JnRToiqgjugH16kpqAqo0M3ksaxMf9nS6I0kbyS8Hrwe/Xg9juP1SOL1OI7X47ipdj3K/GoquOWKNXAnkH0/ENFoHACg68kaOKdfgWU60NM78mNrQiIcN3E4IlHmtV/9qvfNC+PoG53SGxpd1bGwTLR2WOgNK7ZnfJZSojucrPYu86qIxhREYyMvgxMWuntNhCMCZT771eHhWLLa2+dWYJkqrwevx7hfD8uSiETiGfdxwMLRuBj2ekQi8Yw1cIq0YOmDBzHwehzH348kXo/jCul6hEJAtK/PW/+30Z8/ZJaAKmS2LYrMkSNHMGPGjMkuBhERERWxxsZGNDQ0pH2dAe4ElmWhubkZgUBg1J0k+wWDQcyYMQONjY0oKSkZk2MWM76fY4vv59ji+zm2+H6OLb6fY2s83k8pJXp7e1FfXw8lQwdcNqGeQFGUjIl3NEpKSvgLM4b4fo4tvp9ji+/n2OL7Obb4fo6tsX4/S0tLs27DQQxEREREeYYBjoiIiCjPMMBNAJfLhdtvvx0ul2uyi1IQ+H6OLb6fY4vv59ji+zm2+H6Orcl8PzmIgYiIiCjPsAaOiIiIKM8wwBERERHlGQY4IiIiojzDAEdERESUZxjgxtmdd96Jc845B16vF2VlZcNuI4QY8vj1r389sQXNE3bez8OHD2Pt2rXwer2oqanBN77xDRiGMey2NNjs2bOH/Cx+73vfm+xi5Y0HHngAs2fPhtvtxqpVq/D6669PdpHy0ne+850hP4cLFy6c7GLljRdffBEf/OAHUV9fDyEEnnzyyUGvSymxfv16TJs2DR6PB6tXr8bevXsnp7B5INv7edVVVw35eb300kvHvVwMcOMskUjg8ssvx3XXXZdxu0cffRQtLS2px0c+8pGJKWCeyfZ+mqaJtWvXIpFI4JVXXsHPf/5zbNy4EevXr5/gkuavDRs2DPpZ/OpXvzrZRcoLjz/+ONatW4fbb78db731Fk499VSsWbMGR48eneyi5aUlS5YM+jn829/+NtlFyhvhcBinnnoqHnjggWFfv+eee/Cf//mfePjhh/Haa6/B5/NhzZo1iMVGscJ8Acv2fgLApZdeOujn9bHHHhv/gkmaEI8++qgsLS0d9jUA8ne/+92EliffpXs///jHP0pFUWRra2vquYceekiWlJTIeDw+gSXMT7NmzZI/+tGPJrsYeWnlypXyhhtuSH1tmqasr6+Xd9999ySWKj/dfvvt8tRTT53sYhSEE/++WJYl6+rq5L333pt6rru7W7pcLvnYY49NQgnzy3B/r6+88kr54Q9/eMLLwhq4KeKGG25AVVUVVq5ciUceeQSS0/ONyJYtW7B06VLU1tamnluzZg2CwSB27NgxiSXLH9/73vdQWVmJ0047Dffeey+bn21IJBJ48803sXr16tRziqJg9erV2LJlyySWLH/t3bsX9fX1mDt3Lj73uc/h8OHDk12kgnDgwAG0trYO+lktLS3FqlWr+LM6Ci+88AJqamqwYMECXHfddejo6Bj3c3Ix+ylgw4YNuOiii+D1evHMM8/g+uuvRygUwo033jjZRcs7ra2tg8IbgNTXra2tk1GkvHLjjTfi9NNPR0VFBV555RXceuutaGlpwX333TfZRZvS2tvbYZrmsD97u3fvnqRS5a9Vq1Zh48aNWLBgAVpaWnDHHXfgvPPOw/bt2xEIBCa7eHmt/z443M8q75Ejc+mll+JjH/sY5syZg/379+Pf//3fcdlll2HLli1QVXXczssANwK33HILvv/972fcZteuXbY73X77299OfX7aaachHA7j3nvvLZoAN9bvJw2Wy/u7bt261HPLli2D0+nEl770Jdx9991ceocmzGWXXZb6fNmyZVi1ahVmzZqF3/zmN/jiF784iSUjGurTn/506vOlS5di2bJlmDdvHl544QVcfPHF43ZeBrgRuPnmm3HVVVdl3Gbu3LkjPv6qVavw3e9+F/F4vCj+aI7l+1lXVzdk5F9bW1vqtWI0mvd31apVMAwDBw8exIIFC8ahdIWhqqoKqqqmftb6tbW1Fe3P3VgqKyvDySefjH379k12UfJe/89jW1sbpk2blnq+ra0Ny5cvn6RSFZa5c+eiqqoK+/btY4Cbaqqrq1FdXT1ux9+6dSvKy8uLIrwBY/t+nn322bjzzjtx9OhR1NTUAAA2bdqEkpISLF68eEzOkW9G8/5u3boViqKk3ksantPpxIoVK/Dcc8+lRpBbloXnnnsOX/nKVya3cAUgFAph//79uOKKKya7KHlvzpw5qKurw3PPPZcKbMFgEK+99lrW2RLIniNHjqCjo2NQQB4PDHDj7PDhw+js7MThw4dhmia2bt0KAJg/fz78fj9+//vfo62tDWeddRbcbjc2bdqEu+66C1//+tcnt+BTVLb385JLLsHixYtxxRVX4J577kFraytuu+023HDDDUUTiEdqy5YteO2113DhhRciEAhgy5YtuOmmm/D5z38e5eXlk128KW/dunW48sorccYZZ2DlypW4//77EQ6HcfXVV0920fLO17/+dXzwgx/ErFmz0NzcjNtvvx2qquIzn/nMZBctL4RCoUG1lQcOHMDWrVtRUVGBmTNn4mtf+xr+4z/+AyeddBLmzJmDb3/726ivr+f0VWlkej8rKipwxx134OMf/zjq6uqwf/9+fPOb38T8+fOxZs2a8S3YhI97LTJXXnmlBDDksXnzZimllH/605/k8uXLpd/vlz6fT5566qny4YcflqZpTm7Bp6hs76eUUh48eFBedtll0uPxyKqqKnnzzTdLXdcnr9B54s0335SrVq2SpaWl0u12y0WLFsm77rpLxmKxyS5a3vjJT34iZ86cKZ1Op1y5cqV89dVXJ7tIeelTn/qUnDZtmnQ6nXL69OnyU5/6lNy3b99kFytvbN68edj75JVXXimlTE4l8u1vf1vW1tZKl8slL774Yrlnz57JLfQUlun9jEQi8pJLLpHV1dVS0zQ5a9Ysec011wyaymq8CCk5XwURERFRPuE8cERERER5hgGOiIiIKM8wwBERERHlGQY4IiIiojzDAEdERESUZxjgiIiIiPIMAxwRERFRnmGAIyIiIsozDHBEREREeYYBjoiIiCjPMMARERER5RkGOCKiUTp27Bjq6upw1113pZ575ZVX4HQ68dxzz01iyYioUHExeyKiMfDHP/4RH/nIR/DKK69gwYIFWL58OT784Q/jvvvum+yiEVEBYoAjIhojN9xwA5599lmcccYZ2LZtG9544w24XK7JLhYRFSAGOCKiMRKNRnHKKaegsbERb775JpYuXTrZRSKiAsU+cEREY2T//v1obm6GZVk4ePDgZBeHiAoYa+CIiMZAIpHAypUrsXz5cixYsAD3338/tm3bhpqamskuGhEVIAY4IqIx8I1vfAO//e1v8c4778Dv9+P8889HaWkp/vCHP0x20YioALEJlYholF544QXcf//9+MUvfoGSkhIoioJf/OIXeOmll/DQQw9NdvGIqACxBo6IiIgoz7AGjoiIiCjPMMARERER5RkGOCIiIqI8wwBHRERElGcY4IiIiIjyDAMcERERUZ5hgCMiIiLKMwxwRERERHmGAY6IiIgozzDAEREREeUZBjgiIiKiPPP/AeB/Z8tJHn7IAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define a mode source at the signal input waveguide at the bottom MMI\n",
    "mode_source_signal = td.ModeSource(\n",
    "    center=(-0.5, -21, 0),\n",
    "    size=(2 * width, 0, 4 * thickness),\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "    direction=\"+\",\n",
    "    mode_spec=mode_spec,\n",
    "    mode_index=0,\n",
    ")\n",
    "\n",
    "# copy simulation and change the source\n",
    "sim = sim.copy(update={\"sources\": [mode_source_signal]})\n",
    "sim.plot(z=0)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "cfcaf425",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:56:01.310412Z",
     "iopub.status.busy": "2023-03-27T23:56:01.310128Z",
     "iopub.status.idle": "2023-03-27T23:58:13.359383Z",
     "shell.execute_reply": "2023-03-27T23:58:13.358773Z"
    }
   },
   "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\">[12:06:43] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'optical_hybrid_signal_input'</span> with task_id                                    <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#139\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">139</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-cf4c2dfd-9d2f-4ba0-89a8-d807390e5076v1'</span>.                                             <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[12:06:43]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'optical_hybrid_signal_input'\u001b[0m with task_id                                    \u001b]8;id=38350;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=579289;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'fdve-cf4c2dfd-9d2f-4ba0-89a8-d807390e5076v1'\u001b[0m.                                             \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "45a4e3bca2844a7c89c2fedc3808c32d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "df98ef465b7442e19369a6dd94fff1fe",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[12:06:49] </span>status = queued                                                                            <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#269\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">269</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[12:06:49]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                                            \u001b]8;id=450916;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=503023;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#269\u001b\\\u001b[2m269\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[12:06:56] </span>status = preprocess                                                                        <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#263\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">263</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[12:06:56]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                                        \u001b]8;id=456670;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=162911;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#263\u001b\\\u001b[2m263\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": []
     },
     "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\">[12:06:59] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.848</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed FlexCredit cost <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#286\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">286</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>after a simulation run.                                                                    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[12:06:59]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.848\u001b[0m. 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 FlexCredit cost \u001b]8;id=182108;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=880297;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#286\u001b\\\u001b[2m286\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0mafter a simulation run.                                                                    \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>starting up solver                                                                         <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#290\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">290</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                                         \u001b]8;id=775518;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=537181;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#290\u001b\\\u001b[2m290\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>running solver                                                                             <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#300\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">300</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                                             \u001b]8;id=664120;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=844956;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#300\u001b\\\u001b[2m300\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e893c663577a4cbda16ba287ec0821a3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[12:10:25] </span>early shutoff detected, exiting.                                                           <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#313\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">313</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[12:10:25]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                                                           \u001b]8;id=646522;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=260968;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#313\u001b\\\u001b[2m313\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": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>status = postprocess                                                                       <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#330\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">330</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                                                       \u001b]8;id=122384;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=38889;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#330\u001b\\\u001b[2m330\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[12:10:36] </span>status = success                                                                           <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#337\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">337</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[12:10:36]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                                           \u001b]8;id=709071;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=578835;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#337\u001b\\\u001b[2m337\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": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "148eab49e0cc45b7abec302ffd60599c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[12:10:39] </span>loading SimulationData from data/simulation_data.hdf5                                      <a href=\"file://C:\\Users\\xinzhong\\Desktop\\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://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#512\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">512</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[12:10:39]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/simulation_data.hdf5                                      \u001b]8;id=238312;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=813906;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\web\\webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"optical_hybrid_signal_input\", verbose=True)\n",
    "sim_data = job.run(path=\"data/simulation_data.hdf5\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c35b8bb",
   "metadata": {},
   "source": [
    "Visualize the field intensity distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "03f76087",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:58:15.232922Z",
     "iopub.status.busy": "2023-03-27T23:58:15.232709Z",
     "iopub.status.idle": "2023-03-27T23:58:19.080274Z",
     "shell.execute_reply": "2023-03-27T23:58:19.079678Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAnIAAAHUCAYAAAC+g8X7AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy88F64QAAAACXBIWXMAAA9hAAAPYQGoP6dpAAC/UElEQVR4nOydeZwcZZn4v+9bR3fPPZNkkkxuEs5wBMMhyLlkOUQUzxUREREURBfxZFUEVpcVFFQ8WHdX8cB7XXThJ3Iqp+GMyB0gJOSYXHPPdHcd7/v7o6p7ppOZZDLMZJLh+eZTn0xXvfX229Vdbz3vcyprrUUQBEEQBEHY7dDjPQBBEARBEARhZIggJwiCIAiCsJsigpwgCIIgCMJuighygiAIgiAIuykiyAmCIAiCIOymiCAnCIIgCIKwmyKCnCAIgiAIwm6KCHKCIAiCIAi7KSLICYIgCIIw5tx3/3dYsWLFeA9jwqGksoMgCIIgCGPJypUr2XvvPTn4DXvx4AN/Ryk13kOaMIhGThAEQRCEMeVf/uXDvOUtR/LKinX8z//8z3gPZ0IhGjlBEARBEMaMxx9/nKOOOpKnn/kxf7rtYb7xjV/x9NMv4/v+eA9tQiAaOUEQBEEQxgRrLZ/+zIe56OPvYPbsqZzzoTfjeS7fv+HT4z20CYNo5ARBEARBGBP+3//7f3zgA2fwwvKbqK+vAeCWWx7i3A/9Oy+9tIr6+vpxHuHuj2jkBEEQBEEYdaIo4rOf/Rhf/NIHykIcwKmnvpH9D9iDf7vqwnEc3cRBBDlBEARBEEadH/3oUgqFgI985K0V+5VSXH31R7n+2//Dq6++Ok6jmziIaVUQBEEQhFGlt7eXPfecw3XXXcS73n3coG3Oev9X8DyXH//4tp07uAmGCHKCIAiCIIwqV1z5If74x6Xcf/93hswZ98orrey/8Gz++teHOeigg3byCCcOIsgJgiAIgjBqrF+/ngUL5nHr//sab3rTAdts+5nPfJ+/P/kyd9zxyE4a3cRDBDlBEARBEEaNj370baxf385v/+fK7bZtb+9mrz3P5Be/+A0nnXTSThjdxEMEOUEQBEEQRoXnnnuOgw8+iMce/0/23nv2sM657rpf89Of/InHH38Bx3HGeIQTD4laFQRBEARhVPjc5z7MOeecMmwhDuDCC0+nuzvPj3/8hTEc2cRFNHKCIAiCILxm7rvvPk499WSef+FnNDc37tC5v/rl3Xz2s9/nhRdWUlVVNUYjnJiIRk4QBEEQhNeEtZZPffp8PvPZM3ZYiAN493uOY/r0SVx73SfGYHQTGxHkBEEQBEF4Tfz6179mzepNXHzxu0Z0vtaar139Ua7+2i/YsGHDKI9uYiOmVUEQBEEQRkyxWGTffefxL//yfs750JtfU1+nv+0LzJkzle9853ejNLqJj2jkBEEQBEEYMd/93qeoqcnxgbNfe/qQq/79fP77v2/lhRdeGIWRvT4QjZwgCIIgCCOio6OD+fPn8JOffoGTTz5sVPq88IJr2bixg9/97t5R6W+iI4KcIAiCIAgj4tOfeS/LnniR2/50zZCluHaU1tY29tn7/dx22x286U1vGpU+JzIiyAmCIAiCMCKmT5/Ej3/yL5xwwuJR7ffif/42QRDxH//xh1HtdyIiPnKCIAiCIIwIY1waGmpGvd/6hhqsnTbq/U5E3PEegCAIgiAIuzHGgjGj26cYC4eNaOQEQRAEQRB2U0QjJwiCIAjCyLFGNHLjiAhygiAIgiCMHDGtjitiWhUEQRAEQdhNEY2cIAiCIAgjx9rR16CJQm7YiCAnCIIgCMLIER+5cUVMq4IgCIIgCLspopETBEEQBGHkSLDDuCKCnCAIgiAII0dMq+OKmFYFQRAEQRB2U0QjJwiCIAjCyDGikRtPRCMnCIIgCIKwmyIaOUEQBEEQRo4EO4wrIsgJgiAIgjBiFAZlR1eQU5IReNiIaVUQBEEQBGE3RTRygiAIgiCMHDGtjisiyAmCIAiCMHKMTbbRROS4YSOmVUEQBEEQhN0U0cgJgiAIgjBypLLDuCIaOUEQBEEQhN0UEeQEQRAEQRg5pWCH0dx2UCN37733ctppp9HS0oJSiptvvnnIth/96EdRSvHNb36zYn9bWxtnnnkmdXV1NDQ0cO6559LT01PR5sknn+Too48mm80ya9Ysrr766h0a51gggpwgCIIgCCPHmtHfdjDaobe3l4MOOojvfve722z3v//7v/z1r3+lpaVlq2NnnnkmTz/9NHfccQe33HIL9957L+eff375eFdXFyeeeCJz5szhscce45prruHyyy/nBz/4wQ6NdbQRHzlBEEbMn//8Z44//njuuecejjvuuPEejiAIr1NOOeUUTjnllG22WbNmDR//+Mf505/+xKmnnlpx7Nlnn+W2227jkUce4ZBDDgHg+uuv581vfjNf//rXaWlp4aabbiIIAn74wx/i+z4LFy5k2bJlXHvttRUC385GNHKCIGyX733ve9x4443jPYwR8fOf/3wrE8p4YYzh6quvZt68eWSzWQ488EB+8YtfDPv8jo4Ozj//fKZMmUJ1dTXHH388jz/++KBt//CHP/CGN7yBbDbL7Nmz+fKXv0wURaP1UQShHztMc+kOmlbjOKarq6tiKxaLIxqiMYazzjqLz3zmMyxcuHCr4w899BANDQ1lIQ5gyZIlaK1ZunRpuc0xxxyD7/vlNieddBLPP/887e3tIxrXaCCCnCAI22UoQe6YY44hn89zzDHH7PxBDZNdSZD7whe+wOc+9zn+8R//keuvv57Zs2fzvve9j1/+8pfbPdcYw6mnnsrPf/5zLrroIq6++mo2bNjAcccdx/Llyyva/vGPf+T000+noaGB66+/ntNPP52vfOUrfPzjHx+rjya8njH055Ibrc1ali1bRn19fcV21VVXjWiIX/va13Bdl0984hODHm9tbaW5ublin+u6NDU10draWm4zderUijal16U244GYVgVhmPT29lJdXT3ew9il0FqTzWbHexi7BWvWrOEb3/gGH/vYx/jOd74DwIc//GGOPfZYPvOZz/Dud78bx3GGPP+3v/0tDz74IL/5zW9417veBcB73vMe9tprL7785S/z85//vNz205/+NAceeCC33347rptM83V1dfzbv/0b//zP/8w+++wzhp9UEEaHRYsWcc8991Tsy2QyO9zPY489xre+9S0ef/xxlFKjNbxdBtHICa9L1qxZw7nnnktLSwuZTIZ58+ZxwQUXEAQBADfeeCNKKf7yl79w4YUX0tzczMyZM8vnf+9732PhwoVkMhlaWlr42Mc+RkdHR8V7LF++nHe+851MmzaNbDbLzJkzee9730tnZ2e5zR133MFRRx1FQ0MDNTU17L333vzLv/zLdsc/nPOKxSJf/vKXWbBgAZlMhlmzZvHZz352UNPEz372Mw477DCqqqpobGzkmGOO4fbbbwdg7ty5PP300/zlL39BKYVSquwP9+c//xmlFH/+858r+vvNb37D4sWLyeVyTJ48mfe///2sWbOmos0HP/hBampqWLNmDaeffjo1NTVMmTKFT3/608RxvN1r8Pvf/55TTz21/B3Onz+ff/3Xf60497jjjuPWW29l5cqV5bHPnTt3yD4/+MEPltttuV1++eXbHdP2xhuGIRdeeGF5n1KKCy64gNWrV/PQQw9t8/zf/va3TJ06lXe84x3lfVOmTOE973kPv//978vf6zPPPMMzzzzD+eefXxbiAC688EKstfz2t799TZ9DELZijEyrjuNQV1dXsY1EkLvvvvvYsGEDs2fPxnVdXNdl5cqVfOpTnyrPB9OmTWPDhg0V50VRRFtbG9OmTSu3Wb9+fUWb0utSm/FANHLC6461a9dy2GGHlf2N9tlnH9asWcNvf/tb+vr6KvwfLrzwQqZMmcJll11Gb28vAJdffjlXXHEFS5Ys4YILLuD555/n+9//Po888ggPPPAAnucRBAEnnXQSxWKRj3/840ybNo01a9Zwyy230NHRQX19PU8//TRvectbOPDAA7nyyivJZDK8+OKLPPDAA9sc/3DOM8bw1re+lfvvv5/zzz+ffffdl7///e9cd911vPDCCxWh+VdccQWXX345Rx55JFdeeSW+77N06VLuvvtuTjzxRL75zW/y8Y9/nJqaGr7whS8AbGVeGMiNN97IOeecw6GHHspVV13F+vXr+da3vsUDDzzAE088QUNDQ7ltHMecdNJJHH744Xz961/nzjvv5Bvf+Abz58/nggsu2OZ1uPHGG6mpqeGSSy6hpqaGu+++m8suu4yuri6uueYaIDFldnZ2snr1aq677joAampqhuzzIx/5CEuWLKnYd9ttt3HTTTdVmF02bdq0zbGVqK2tLT94nnjiCaqrq9l3330r2hx22GHl40cdddSQfT3xxBO84Q1vQOvK9fdhhx3GD37wA1544QUOOOAAnnjiCYAKXx+AlpYWZs6cWT4uCK8XzjrrrK3u65NOOomzzjqLc845B4AjjjiCjo4OHnvsMRYvXgzA3XffjTGGww8/vNzmC1/4AmEY4nkekCyq9957bxobG3fiJ9oCKwivMz7wgQ9YrbV95JFHtjpmjLHWWvujH/3IAvaoo46yURSVj2/YsMH6vm9PPPFEG8dxef93vvMdC9gf/vCH1lprn3jiCQvY3/zmN0OO47rrrrOA3bhx4w6Nfzjn/fSnP7Vaa3vfffdV7L/hhhssYB944AFrrbXLly+3Wmv79re/veLzWNt/Lay1duHChfbYY4/d6n3uueceC9h77rnHWmttEAS2ubnZ7r///jafz5fb3XLLLRawl112WXnf2WefbQF75ZVXVvR58MEH28WLF2/7Ilhr+/r6ttr3kY98xFZVVdlCoVDed+qpp9o5c+Zst7/BWL58ua2vr7f/+I//WPE7IMmNsN3tRz/6UcU49thjj63eo7e31wL285///DbHUl1dbT/0oQ9ttf/WW2+1gL3tttustdZec801FrCrVq3aqu2hhx5q3/jGNw734wvCdmlubrYP/+6LNn7hv0Z1++LH3mLPO++8YY+ju7vbPvHEE+W599prr7VPPPGEXbly5aDt58yZY6+77rqKfSeffLI9+OCD7dKlS+39999v99xzT3vGGWeUj3d0dNipU6fas846yz711FP2l7/8pa2qqrL/8R//MaJrN1qIaVV4XWGM4eabb+a0007bSmMBbOU/cd5551X4Ld15550EQcDFF19coRk577zzqKur49ZbbwWgvr4egD/96U/09fUNOpaSZur3v/89ZgfK2wznvN/85jfsu+++7LPPPmzatKm8/cM//ANA2e/k5ptvxhjDZZddtpWmZyS+JI8++igbNmzgwgsvrPCdO/XUU9lnn33K12cgH/3oRyteH3300bz88svbfa9cLlf+u7u7m02bNnH00UfT19fHc889t8Nj35Le3l7e/va309jYyC9+8YuK38Edd9wxrO2kk04qn5PP5wc1C5WuUz6f3+Z4hnt+6f+h2m7vfQRhR1HGoowZ1W1HEwI/+uijHHzwwRx88MEAXHLJJRx88MFcdtllw+7jpptuYp999uGEE07gzW9+M0cddVRFjrj6+npuv/12VqxYweLFi/nUpz7FZZddNq6pR0BMq8LrjI0bN9LV1cX+++8/rPbz5s2reL1y5UoA9t5774r9vu+zxx57lI/PmzePSy65hGuvvZabbrqJo48+mre+9a28//3vLwt5//RP/8R//dd/8eEPf5jPf/7znHDCCbzjHe/gXe9611ZC1UCGc97y5ct59tlnmTJlyqB9lHxBXnrpJbTW7LfffsO6HttjqOsDsM8++3D//fdX7Mtms1uNsbGxcVih/E8//TRf/OIXufvuu+nq6qo4NtAPcaScd955vPTSSzz44INMmjSp4tiWZprhkMvlBvVPLBQK5eOjcX7p/6Habu99BGF35LjjjsPugPD3yiuvbLWvqampImhoMA488EDuu+++HR3emCKCnCBsg9fy0PvGN77BBz/4QX7/+99z++2384lPfIKrrrqKv/71r8ycOZNcLse9997LPffcw6233sptt93Gr371K/7hH/6B22+/fcgIxuGcZ4zhgAMO4Nprrx20j1mzZo34c40m24rS3BYdHR0ce+yx1NXVceWVVzJ//nyy2SyPP/44n/vc53ZIwzkY3/rWt/jFL37Bz372MxYtWrTV8eGmGqivry//hqZPn84999yDtbZC27lu3TqAQTPND2T69OnltgPZ8vzp06eX92/5Pa9bt67skycIo4cd/SL3o9zdREZMq8LriilTplBXV8dTTz01ovPnzJkDwPPPP1+xPwgCVqxYUT5e4oADDuCLX/wi9957L/fddx9r1qzhhhtuKB/XWnPCCSdw7bXX8swzz/DVr36Vu+++e6uQ+y3Z3nnz58+nra2NE044gSVLlmy1lTRm8+fPxxjDM888s833G66ZdajrU9q35fUZKX/+85/ZvHkzN954I//8z//MW97yFpYsWTKow/GOmojvu+8+Pv3pT3PxxRdz5plnDtpm+vTpw9p+9atflc9ZtGgRfX19PPvssxV9lZKNDiYwDmTRokU8/vjjWwmpS5cupaqqir322quin0cffbSi3dq1a1m9evV230cQdpjRjlgdgWn19YwIcsLrCq01p59+Ov/3f/+31YMO2K5qfsmSJfi+z7e//e2Ktv/93/9NZ2dnuexLV1fXVln0DzjgALTWZZNXW1vbVv2XHrLbyl4+nPPe8573sGbNGv7zP/9zq7b5fL4cgXv66aejtebKK6/cSkAY+Pmqq6u3Sq8yGIcccgjNzc3ccMMNFZ/hj3/8I88+++xWZXFGSkmTN3CMQRDwve99b6u21dXVwza1rlu3jve85z0cddRR5cjXwRiJj9zb3vY2PM+rGKO1lhtuuIEZM2Zw5JFHVozjueeeIwzD8r53vetdrF+/nt/97nflfZs2beI3v/kNp512WtknbuHCheyzzz784Ac/qEjF8v3vfx+lVDkHnSAIEwMxrQqvO/7t3/6N22+/nWOPPbacmmPdunX85je/4f77769Ij7ElU6ZM4dJLL+WKK67g5JNP5q1vfSvPP/883/ve9zj00EN5//vfDyRh6xdddBHvfve72WuvvYiiiJ/+9Kc4jsM73/lOAK688kruvfdeTj31VObMmcOGDRv43ve+x8yZM7eZhmI455111ln8+te/5qMf/Sj33HMPb3rTm4jjmOeee45f//rX/OlPf+KQQw5hwYIFfOELX+Bf//VfOfroo3nHO95BJpPhkUceoaWlpZxFffHixXz/+9/nK1/5CgsWLKC5ubkcODEQz/P42te+xjnnnMOxxx7LGWecUU4/MnfuXD75yU+O9Gur4Mgjj6SxsZGzzz6bT3ziEyil+OlPfzqoIL548WJ+9atfcckll3DooYdSU1PDaaedNmi/n/jEJ9i4cSOf/exnt6q2cOCBB3LggQcCI/ORmzlzJhdffDHXXHMNYRhy6KGHcvPNN3Pfffdx0003VZiZL730Un784x+zYsWKcp6rd73rXbzxjW/knHPO4ZlnnmHy5Ml873vfI45jrrjiior3uuaaa3jrW9/KiSeeyHvf+16eeuopvvOd7/DhD394q/QngvCaMTbRoo0mopEbPuMXMCsI48fKlSvtBz7wATtlyhSbyWTsHnvsYT/2sY/ZYrFore1PPzJYihJrk3Qj++yzj/U8z06dOtVecMEFtr29vXz85Zdfth/60Ifs/PnzbTabtU1NTfb444+3d955Z7nNXXfdZd/2trfZlpYW6/u+bWlpsWeccYZ94YUXtjn24Z4XBIH92te+ZhcuXGgzmYxtbGy0ixcvtldccYXt7OysaPvDH/7QHnzwweV2xx57rL3jjjvKx1tbW+2pp55qa2trLVBORbJl+pESv/rVr8r9NTU12TPPPNOuXr26os3ZZ59tq6urt/p8X/7yl+1wpqYHHnjAvvGNb7S5XM62tLTYz372s/ZPf/rTVuPp6emx73vf+2xDQ4MFtpmK5Nhjjx0ylciXv/zl7Y5pe8RxbP/t3/7Nzpkzx/q+bxcuXGh/9rOfbdWulJplxYoVFfvb2trsueeeaydNmmSrqqrsscceO+Rv9H//93/tokWLbCaTsTNnzrRf/OIXbRAEr/kzCMJAmpub7SO//Jw1f//uqG5f/MgpO5R+5PWMslbEXkEQBEEQdpypU6dy67c+yOL9Zo9qv5d99xbW21kV6T+EwRHTqiAIgiAII6cUoDCaiI5p2EiwgyAIgiAIwm6KaOQEQRAEQRg5doyCHXa8uMzrEhHkBEEQBEEYOXYMEgILw0ZMq4IgCIIgCLspopETBEEQBGHkjFWwg5hWh4UIcltgjGHt2rXU1tbucGkfQRAEQRhvrLV0d3fT0tKC1jvB8GZJkgKPap9iqh0uIshtwdq1a3eZguKCIAiCMFJeffVVZs6cOd7DEMYYEeS2oLa2Nv1LI3pdQRgd9tprb3K53Fb7i8Uizz337CBnCIIwcixgBjzPxhjJIzeuiCC3Bf3mVIUIcoIwOjiOU1FLdOB+uc8EYWwQ96DXByLICYIgCIIwckQjN66IICcIgiAIwsgZk2CH0e1uIiN55ARBEARBEHZTRCMnCIIgCMLIsSbZRrVPUckNFxHkBEEQBEEYOcZKHrlxREyrgiAIgiAIuymikRMEQRAEYeRYK1Gr44ho5ARBEARBEHZTRCMnCIIgCMLIGRMfudHtbiIjgpwgCIIgCCPHSkLg8URMq4IgCIIgCLspopETBEEQBGHkSPqRcUUEOUEQBEEQRo61o58QWJzkho2YVgVBEARBEHZTRCMnCIIgCMLIsRK1Op6IRk4QBEEQBGE3ZUIKct/97neZO3cu2WyWww8/nIcffni8hyQIgiAIE5NSsMNobhLsMGwmnCD3q1/9iksuuYQvf/nLPP744xx00EGcdNJJbNiwYbyHJgiCIAgTD5OW6BrNTQS5YTPhBLlrr72W8847j3POOYf99tuPG264gaqqKn74wx+O99AEQRAEQRBGlQkV7BAEAY899hiXXnppeZ/WmiVLlvDQQw8Nek6xWKRYLJZfd3V1jfk4BUEQBGHCIMEO48qE0sht2rSJOI6ZOnVqxf6pU6fS2to66DlXXXUV9fX15W3WrFk7Y6iCIAiCMDEQH7lxZUIJciPh0ksvpbOzs7y9+uqr4z0kQRAEQRCEYTGhTKuTJ0/GcRzWr19fsX/9+vVMmzZt0HMymQyZTGZnDE8QhC1QSo33EARBeK3YNEBhVPsUjdxwmVAaOd/3Wbx4MXfddVd5nzGGu+66iyOOOGIcRyYIr1+01mSz2UGP+b6P606o9aQgCMJOZcLNoJdccglnn302hxxyCIcddhjf/OY36e3t5ZxzzhnvoQnC65L6+vptat7q6+vZvHnzThyRIAijikU0aOPIhBPk/umf/omNGzdy2WWX0drayqJFi7jtttu2CoAQBGHnUF9fv93jIsgJwm6MGYuoVREMh8uEE+QALrroIi666KLxHoYgCGxfkKurq0MphZWJWxAEYYeZUD5ygiDsWjQ2NuI4zjbbaK1pamraSSMSBGHUsWORfmTHhnDvvfdy2mmn0dLSglKKm2++uXwsDEM+97nPccABB1BdXU1LSwsf+MAHWLt2bUUfbW1tnHnmmdTV1dHQ0MC5555LT09PRZsnn3ySo48+mmw2y6xZs7j66qtHetVGDRHkBEEYE7TWzJw5c1htZ8yYsV2BTxCEXZTRLs81ghJdvb29HHTQQXz3u9/d6lhfXx+PP/44X/rSl3j88cf53e9+x/PPP89b3/rWinZnnnkmTz/9NHfccQe33HIL9957L+eff375eFdXFyeeeCJz5szhscce45prruHyyy/nBz/4wciu2ygxIU2rgiCMP7NmzcLzvGG1dV2X2bNns2LFijEelSAIE5FTTjmFU045ZdBj9fX13HHHHRX7vvOd73DYYYexatUqZs+ezbPPPsttt93GI488wiGHHALA9ddfz5vf/Ga+/vWv09LSwk033UQQBPzwhz/E930WLlzIsmXLuPbaaysEvp2NaOQEQRh15s6dy6RJk3bonMbGRvbYYw/JLScIuxuGcTet7iidnZ0opWhoaADgoYceoqGhoSzEASxZsgStNUuXLi23OeaYY/B9v9zmpJNO4vnnn6e9vX1sB7wNRJATBGFUmT9//oh93hoaGliwYMEoj0gQhDFlTHzkLHEc09XVVbENrI0+UgqFAp/73Oc444wzqKurA6C1tZXm5uaKdq7r0tTUVC7x2draOmgJ0NKx8UIEOUEQRo2amprtRqluj9ra2vLkKgjC65dly5ZV1EKvr6/nqquuek19hmHIe97zHqy1fP/73x+lkY4v4iMnCMKoMWXKlFHpp7m5ma6urlHpSxCEMWZM8sjBokWLuOeeeyp2v5aSmiUhbuXKldx9990VC8Zp06axYcOGivZRFNHW1lYu8Tlt2rRBS4CWjo0XopETBGHUGKoU144i9Y8FQXAch7q6uoptpHNDSYhbvnw5d95551Y+vEcccQQdHR089thj5X133303xhgOP/zwcpt7772XMAzLbe644w723ntvGhsbRzSu0UAEOUEQBEEQRoy1FmtGd9vR9CM9PT0sW7aMZcuWAbBixQqWLVvGqlWrCMOQd73rXTz66KPcdNNNxHFMa2srra2tBEEAwL777svJJ5/Meeedx8MPP8wDDzzARRddxHvf+15aWloAeN/73ofv+5x77rk8/fTT/OpXv+Jb3/oWl1xyyahezx1FTKuCIAiCIIwcu+OC1/b73LHmjz76KMcff3z5dUm4Ovvss7n88sv5wx/+ACTm2oHcc889HHfccQDcdNNNXHTRRZxwwglorXnnO9/Jt7/97XLb+vp6br/9dj72sY+xePFiJk+ezGWXXTauqUdABDlBEARBEHZzjjvuuG2W+RtOCcCmpiZ+/vOfb7PNgQceyH333bfD4xtLRJATBEEQBGHklPLIjSZSe3nYiCAnCIIgCMLIsWMTtSoMDwl2EARh1BiO+WJn9iMIgjDREY2cIAijRk9PD1VVVaPSjyAIuwljkkdOFnPDRTRygiCMGqOVxFeSAQuCIAwP0cgJgjBqdHd3E8cxjuOMuA9rrQhygrA7MUaVHYThIYKcIAijhrWWzs5OmpqaRtxHZ2cnxphRHJUgCGNJKSHwaPcpDA8xrQqCMKoUCoVxPV8QBOH1hGjkBEEYVZRS43q+IAg7mTHJIze63U1kRJATBGGnsXbtWjo7O6mtrWXmzJmDthFBThB2M8Ykj5xIcsNFBDlBEEaVbQli+XyefD6P68rUIwiCMBrIbCoIwqii9dCut6Ughm0FM2zrfEEQdkEkanVckRlTEIRRZVvatuEIcqKtEwRBGD4yYwqCMKp4njfksZIAF8fxiM4XBGEXxNox8GkTldxwEUFOEIRRZVsatSAIAAjDcMg2IsgJwu6FtWBHO/WjyHHDRkyrgiCMKkMJYsaYsibOWksURYO2E9OqIAjC8JEZUxCEUUNrPaQgVtLGlSgWi4O2LfUxlKAnCMIuhgQ7jCuikRMEYdSoqqoa8lixWKx4vaVgN9x+BEHYxSglBB7NTfLIDRsR5ARBGDV2RJDb8vVw+xEEQRD6EdOqIAijxrYEsN7e3m2+Hm4/giDsYoxBsIMo5IaPaOQEQRg1RJATBEHYuYhGThCEUcF1XbLZ7KDHoijayieutM/3/a3a+76P7/vb9KMTBGEXQYIdxhXRyAmCMCrU19cPeWwo7du2tHLb6k8QhF0ISxrwMIqbCHLDRgQ5QRBGhW0JXj09PTu0H6ChoeG1DkkQBGHCI4KcIAivGaUUdXV1Qx7v6OjYof0ANTU1aC1TlCDs6lhjR32TaIfhI7OkIAivmbq6uiGFrmKxOGSqkTAM6evrG/SYUkrMq4KwOzDaZlUxre4QIsgJgvCamTx58pDH2tvbt3nutrRy2+pXEARBEEFOEITXiOd529ScbUtQ297x2tpaMpnMCEcmCMJOw47BJgwLEeQEQXhNTJkyZchjxWJxSNNpiUKhQD6fH1H/giCMP2PhIycucsNHBDlBEF4TkyZNGvLYxo0bh9XHttpNmjQJpdQOj0sQBOH1gAhygiCMmMmTJ+N53qDHrLVs3rx5WP20tbVhzOA1fhzHEa2cIOzKSLDDuCKCnCAII0IpxfTp04c83tbWRhzHw+rLGLNNoW/atGmSikQQBGEQZGYUBGFENDc3D6mNg+GbVYfT3nVdpk6dukP9CYKwc7AWrBndTTRyw0cEOUEQdhitNdOmTRvyeFdX13aDHLakUChsM1XJ1KlTcRxnh/oUBGEnMBamVWHYiCAnCMIO09LSsk2has2aNSPqd+3atUMe01ozY8aMEfUrCIIwURFBThCEHaK6uprm5uYhj7e3t28znci2KBaL2/SVmzx5MjU1NSPqWxCEsWEsTKuSfmT4iCAnCMKwUUoxZ86cbbbZllZtOKxduxa7jVl87ty5EvggCLsSErU6rshsKAjCsGlpaSGbzQ55fOPGjUPWVR0uYRiyfv36IY/7vi8mVkEQhBQR5ARBGBY1NTXbjBwNgmDEvnFbsm7dum0KhFOmTKGurm5U3ksQhNeITc2ro7iJRm74iCAnCMJ28TyPPfbYY5ttVq1aNWRS3x3FWsvKlSu32WbevHlSh1UQhNc9IsgJgrBNlFIsWLAA13WHbNPW1kZXV9eovm9PTw+bNm0a8rjjOMyfP1/85QRhnJFgh/FFZkBBELbJ3LlzyeVyQx4Pw5BXX311TN579erVBEEw5PFsNsu8efPG5L0FQRgmEuwwroggJwjCkMyYMYPGxsYhj1trefnll4ddimtHMcbw8ssvbzOKtb6+nlmzZo3J+wuCIOzqiCAnCMKgtLS0bLcs1po1a+jt7R3TcfT19bFq1apttpkyZQozZ84c03EIgjA4o25WFY3cDiGCnCAIW9HS0rLNElyQJP7dsGHDThnP5s2bt+kvB0ntVxHmBGHnYxn9qNUdlePuvfdeTjvtNFpaWlBKcfPNN1eO0Vouu+wypk+fTi6XY8mSJSxfvryiTVtbG2eeeSZ1dXU0NDRw7rnn0tPTU9HmySef5OijjyabzTJr1iyuvvrqHb9go8yEEuTmzp2LUqpi+/d///fxHpYg7FYMR4jL5/O88sorO2dAKa+++up2tX8izAnC65Pe3l4OOuggvvvd7w56/Oqrr+bb3/42N9xwA0uXLqW6upqTTjqJQqFQbnPmmWfy9NNPc8cdd3DLLbdw7733cv7555ePd3V1ceKJJzJnzhwee+wxrrnmGi6//HJ+8IMfjPnn2xZDh6Htplx55ZWcd9555de1tbXjOBpB2H1QSjF37txt+sRBUkZr+fLl2/RbGwustbz44ovstdde2wy+aG5uxvd9VqxYsdPHKAivS4xKttFkB2/dU045hVNOOWXwrqzlm9/8Jl/84hd529veBsBPfvITpk6dys0338x73/tenn32WW677TYeeeQRDjnkEACuv/563vzmN/P1r3+dlpYWbrrpJoIg4Ic//CG+77Nw4UKWLVvGtddeWyHw7WwmlEYOEsFt2rRp5a26unq8hyQIuzyu67LXXnttV4gLgoAXXniBKIp20sgqieOY5cuXb7d6RENDA/vssw+e5+2kkQmCMNrEcUxXV1fFNpLKMStWrKC1tZUlS5aU99XX13P44Yfz0EMPAfDQQw/R0NBQFuIAlixZgtaapUuXltscc8wx+L5fbnPSSSfx/PPP097ePtKP+ZqZcILcv//7vzNp0iQOPvhgrrnmmu0+cIrF4lY/FEF4PZHL5dhnn322u+iJoojly5cThuFOGtlrG8dwP5cgCK+NsQp2WLZsGfX19RXbVVddtcPja21tBdgqeGvq1KnlY62trTQ3N1ccd12XpqamijaD9THwPcaDCWVa/cQnPsEb3vAGmpqaePDBB7n00ktZt24d11577ZDnXHXVVVxxxRU7cZSCsOswbdo0pk+fjlLbNouEYTgsTdjOoqQZ3HPPPStWx1vieR577703ra2trF27dieOUBBeTyisHV3TqrWKRYsWcc8991Tsl2ouW7PLa+Q+//nPbxXAsOX23HPPAXDJJZdw3HHHceCBB/LRj36Ub3zjG1x//fXbfPhceumldHZ2lrexSmwqCLsSmUyGvffeuxzhtS0KhQLPPfdchVPwrkCxWOS5554jn89vt+20adPYd999yWazO2FkgiCMBo7jUFdXV7GNRJArBW+tX7++Yv/69evLx6ZNm7ZVFH4URbS1tVW0GayPge8xHuzyGrlPfepTfPCDH9xmm6FqQB5++OFEUcQrr7zC3nvvPWibTCYjEr7wukEpRXNzM9OnTx9Waave3l5efPHFMUv4+1qJoojnn3+e+fPnbzewKZfLse+++7Ju3TrWr18vgRCCMEqUzaGj2unodTVv3jymTZvGXXfdxaJFi4AkAnXp0qVccMEFABxxxBF0dHTw2GOPsXjxYgDuvvtujDEcfvjh5TZf+MIXCMOw7H97xx13sPfee2/Xv3gs2eUFuSlTpjBlypQRnbts2TK01lvZvQXh9UhjYyMzZszYpilyIB0dHbtF5KcxhuXLlzN37lyampq22VYpRUtLC1OmTGHNmjW0tbXtpFEKwsRlLAS5HZ12enp6ePHFF8uvV6xYwbJly2hqamL27NlcfPHFfOUrX2HPPfdk3rx5fOlLX6KlpYXTTz8dgH333ZeTTz6Z8847jxtuuIEwDLnooot473vfS0tLCwDve9/7uOKKKzj33HP53Oc+x1NPPcW3vvUtrrvuutH62CNilxfkhstDDz3E0qVLOf7446mtreWhhx7ik5/8JO9///vHVVIWhPGmurqamTNnDtvp31rLmjVrdlqy39HilVdeoaenh1mzZm3XXOx5HnPnzqW5uZk1a9bQ3d29k0YpCMJY8Oijj3L88ceXX19yySUAnH322dx444189rOfpbe3l/PPP5+Ojg6OOuoobrvttgp3i5tuuomLLrqIE044Aa0173znO/n2t79dPl5fX8/tt9/Oxz72MRYvXszkyZO57LLLxjX1CICyu/pye5g8/vjjXHjhhTz33HMUi0XmzZvHWWedxSWXXLJDptOuri7q6+sBBxjlvDiCsBNpbGykubl5h6I2gyDg5Zdfpq+vbwxHNrbkcjn22GOPHbrv+/r62LBhg2johAmCBWI6Ozupq6sb03eaOnUqv3jDYSxqmjSq/V715BN0HnH4uCfb3R2YMBq5N7zhDfz1r38dk77VAIHOvgbDvdqGYLi9frc897WMY6IxWt/PRMB1XSZNmkRzc/MO51Brb29n5cqVGDPazi47l3w+z7PPPsvs2bO3a2otUVVVxdy5c5kxYwYbN25k8+bN455mRRhfSvPKlnPKjs7Fg837r/d5ShhdJowgN/oolNraGbziptxCmbnNG77C1DNYv2bQPvvP1VtMCBbY8oGrk31DKFktdsRCz6BCqFI77sjwWhnUZNZ/PdVW1yRlkHFOlMnUdV0aGxtpbGykpqZmh88PgoBXX32Vzs7OMRjd+GCM4ZVXXmHz5s3Mnj172No5z/NoaWmhpaWFnp4e2tvb6ejomFBC3ZD38qCU7i0zxOsB7OxKHyO8fwcKaOVrsdXnH2pO0VvNoUPOOVv004/p72NHr9l2XAbsqEccDI/ER270048Iw0MEuSFxUMofVJgrkdw0/V6eisrJpX+S0IBO+3JQSqPKr/v7spi0z5jEtJuORHs4jo9WHqWJITYBxgQYG6XvlfRnrUn3xQP6jsoZFhWqPEa1hdA3pCCaCpLlfennKX/oQamc/Lak9NkHn3gqHxoDr5NSHmqL/rbsy6bn9/cd939XANb0T8DbEcaHy8B0OGMd4am1prq6mpqaGmpra0ckvEHiC7dhwwbWrl27ywc0jJTu7m6eeeaZcqWX7fnODaSmpoaamhpmzZpFb28v3d3d9PT00NPTM+ZaS8dxsNaWtx1h6AUkVAgi5ftKbzHPJXOPVoM/HkrzTP98VSL53VtrBr2/t33PD/4eCVu0H3j/lvfZbd67g89lpfnMTeaV9D21clHK7f+cNsKS7Nfax9F++pYxKEMcB8QmTPvUWMxW8/vAz126btaG6fzZPy8NPvj+76l0bQbDWgO2MD4LVDsGcvzEnJLGBBHkhqAqO4Opuf1xUsFBDxCsDDEWQ2xDYkIiW8TYEIPB2njAjeyg0Wjl4aoMLhk8laUpbiaDD8oyo7oO5WjWqy7a/DUYt4ByY1zXASdC6xjtOGjl4Dk5HJVFo4hsQBgViE2MsslvPoxDjInAWow1RFFIbEOsMVhrieOQ2BQxJsYYgzURxkZYY4hNXH5oGGOSGxMNuCh8PLca18nhaJ+MU0uGalyVQ+OgrS5fo9JEZtJJvbRPDxC+NBqXxOwXExETo9MHjMUSkQinHh4OLo5Nrr2PS0Z5eGnrEo5SGCyxtRRsTFEFFFWRbqeNgu0ksJ0EcQ/GhiiVCLpKJYKt1qCwoEDrZLovCWQ6OVjxerC/BxMOoigiDEPCMCQIgvLfW27bQmtdTo9T2qqrq7dZZ3S4dHZ2smbNml0uN9xYYK1l3bp1tLW1MWPGDBoaGna4j+rq6gpfw3w+T29vL8VisWLbnoDnez6e5+F6Lp7nbbX5vo/rbj0tDxTqTHo/b/kaS/+x9BxjbPKAtYnoY63GpvcruGjloXWGnG7Ep5asraHK1JG1fvlec1TlvaZRxNYSWkORuHwvRtZQJJkHdXqPhiokSucCN51DI2IMMQpVXpRZzFYCSERETEigChgbYokp0kto8sRxgSDuxdiYOC5gKZBoukx6L/ffn452UFonAprWaO2itYPWHq6TRWsHpRSu4ycLZu2gFLjKw3E8kgk2xnE9HO3j6kz6eYtEcR5jI4wBG2ts7BFHBhtpVJRhSnEmzSqHiWLW9PQSW0NIRKdup6j6iG2IISQmwto4eYak10uRPD+UcnBw0Xg4yquYc0vXzihDTMjLHbdjzfbzKgoTCxHkhmDfvRYy2zsoEchSMUTZrVdCViUT98Dpu6wRSm+wZIpK9mmlyTk5sm4GX7v4ykUDddRj7UwiYgIVJpOYiokIyucqNC4+jnVwlEPsxxRUL7GKEoHJKmIVEdg8sQ3KY4hMnsgUkwnHxlgbEZsAa4NE8LQGbFwxjSoAlWoPlY9WfqIZ1Bk8J4dWPr7O4eCjlZtMNNZBb/GTGijAJa8Vym5pJh6cknCnrCr/rctiYSK8JZ8x+Rdj8FVAoDQxmjomEVFDZCYR2SKxCZKJ04QYGycPBxuTaOziAav6wTR1O4bruriuu12hqyTwxXGM4zhordFal/8ebbq6uli7du1uHcwwUorFIi+//DK5XI6WlpY0qGlk5HK5Qb9bYwxxnCyUSptSakgBbbgMXDA4jlN5rLJh+kd6jymFUg6JJUCh8HC0h9aJUOBoP1lk6ipc0gWnzeBbH9/6OKV7EIWjdMV7DbwnrLVb3Y9AKpbEWNV/LNlf0qol93PpdWk+TYS9iEglVoeIkNgGRLaK2BSJTVj+3xJiTHGAhSR5F1W+HiXtmE4+t86ilItWDo7ycJ0cvqrCUR4Gi6eyZGwOF688DhefjM0ki0oLgQowOsZoW77ank3nZjSecstLf51q0KpNA5GJCcKQQjS5vNgtPVe2nCv7v99+G8SW1ojSsyGx48S4fauI4x7iOObll18YtL+xwNoxqOwwqr1NbESQG4KZdftweN2s8m2j09+ohvLMWdpnKma0fqHOpH+ni2VKp2Y0aJ2c76nkf5OqpiOgEEFoLLGF2CaTnzEQpStwRylcR+GgyMdNFONkGsxoTWyhxwQUVLGsyep02sg7ncSpGTY0vRTjbqLIAWVTgSYYYCIuPQASc67jZMm4NXgqh6uzVNFIla0hZ7K4SpNRDlWOg6PTdb6m/HdswVHJPoAovThZNzHgFE3y2V2dXBdjk32k18nTyTkRSfuMk1yvQpQYckrfT9FAMYZCbAmNoRhb+uKQPEUCXaRPdRPYPJEtlAXbKM6nD4JUmCNKxEMLqG34LI4iJYFvrOns7GTdunWvSwFuS/L5PC+99BK5XI7p06ePSEM3FCVBfKezDQFOKy+xDigH18nh6gyuzuGrHL6qJmurqDbV+Molq1xyrsbTioyryDng6/45ytVQnQb0BzFENjmecSyxUfSlXgWlc/qi5N50AN9J5oNCnMyHjkru39Am97hOfFMommT+szb5vzeKKdqY2BryqkCv20WebiLTR2SLhHGeIOrBEiZmUDvQ7JoIb4rEdKq1R9ZrIKtrKS0Vq2ii3tThWocYQ1a51HgurlYEcTLnZl2HalcRp2OKbCKEugpcrVDpZ3EVuA7knOTzJebbVNBK5/jYJtet9NwofXX93+CAr3XLr3cApedKWpaUyMDqTVMpBGPv3rH1WNSo+8ghPnLDRgS5IZinp3HC1MTspLBoZVGAo1LVPaBV6U5MT7JgbDqFlP9WmAE/SK0sesBao9RHbHV6M2oKRhMaTWQgsIrIKEKriGyyL7LJ+/sORMYhHzsEJhF8LNAduvSGubKg2VbM0WUmpUO0dDkd9OrNGC+Z7ALTTRQX0/Gk/jHaxVM5lHLJqGrq7GRyNotnXepcj3rfodpLfkBVLkzJxPg6WZPnHEOtG+JqSyF2cJWhNhOilSUfuWChJlPEcw2FwCOINBk3piobYKwiX/QxVpHzQ1wnphC4FEIPpSw5LyKKNV1Fn6JxcZQhNJqu0KU7Sq5dEDv0RtBWdMjHPsW4hu64hj6Vp6D6KDhdBDpPoJxkZW/DxDyjVOJPCGBTX0KVrPAHfMW7DWEYsmnTJjZt2jShnPVHi3w+z8svv4zneUyaNInJkycPO1nyWJPKNNttk/wxwO9LJaY4pVwSoc7BdbM4qUbdUzkyuo4M1VTZGqpNjmrXo9Z3yLmKahcafcg6how21HoxdW5I1o0xVuFqQ2NtHteLiUKHKNJkcyGZ2hgTQdDrgrJkqmOUB4V2lyBwcF2Dn4uJipqe3uQaZ/0IC3T25oiMxnNijFF0Bhl6IgdHQdEoWgsevZGHtdAXV9FWrKcnjAgx5FWRHr+LPr+d2EaJxn2ANcJag6Mz5HQ9CgdLTA2TaTT1uEoRA7WOS2OVi6+SubXahVovEcoKJvm/xjV42hDEmphkn6cNrrL4GlxlcZXB1RZPG7JOjKMMSoGjLUrZ8nemUl1kYvFW6ffWP8eUnjfJiwG/grStsYpSa1PeB2HscEtXE4Vg98r/KLx2RJAbgmrPYWpVb/8OZdEKdHpTKpUKd5ryTQqllUm6UjK6rHIeqNip1OAlgl5sNbEp+ZpojEkEuMA4ZcHOpKu4gtEUjcJTFte1VMWaglG46Th8rcg4qhTDisUlF1WBgthYMpFHtarFt4mfWrfTg3EiPJvBwcFgcK1Ljkyy6rSKet8j6yi0UlSlk321k1yDatfQkivgO8lkX+UH1NUVcLOGMO/guBa/3qAzijhvsQbcOo3KKGxfEWssytPoKo2NLbYQ9Md7KIXpC4j6wMYKpSEsaHS3ITKJ0NkTeARGE9l08lWKyCbXIFl1W0LjEttMeskTYdzoGKUKKKOxqZ9LOZiMft/D8nI4Feh2ZWHOGENXVxebN2+eUFGoY0kYhrS2ttLa2kpdXR2TJk2irq5uKxPmrsSWQtxALZxSbr8GSjm4KoPjZHHx8HV1WYjL2Sw5x6XK1eRcRdaFnAu1Xky1kwglVU5MXTagJpss9BzXkmsKcWtLeibQNS6qNofSilwQg6tRVT5oRaanCGEMnovKuNhiRG1HEaxFV3nY0FC3rhMbgc6ACaBxk09vIYOjYyLjkHWq6YnSez3SVLsO+cjBAPkoS3dYQyGeCkCBiEjFZdeNUIcoFPW2CqUUoTVktUNDzsXTishYMo6iwU+0/7GFWs9S5SSfLWcUVY6hyjVEVhFqi6ss1W5cXih7KsZ3DZlUeNPa4DqpyVUbXNckz43ysyP96rZQvan0eZK8thVauMTPMRXaYpX4MA/wALFWEYVO2fd4Z2PHINhhgsZfjQkiyA1BEFs6ipUpC0pauEQ7Z9E6Fe5UaX2VUHoVm34hLkb3a+m2+IHGVhNZjbVJX07Zn4Tyqi1O/PFxNbjWkreKAIWPxdOWINX+ucqSSU0YpT7qfUWN66BTM2V15BDbLNVuMjHko2pcDTlXoVOTie8kK1NjITZQ4yXmE2uTCabOjalyEg+NrI6p8kMybkxsIJeN8GsMTjU42RjlglPvoDIOujY132ZccDTUWMp2idiijIUqsLHBFmNswYAG7UOch2KvS6HgUQg9IqMJYk1n6NMV6fJquRArinHymEmEb3CUxreJNtCoxGfHaEtkHZRK/GtiFZb9B/tNrarfdy41tyrb//3sCoRhSEdHB52dnXR3d0/YCNSdQVdXF11dXQDU1tZSX19PQ0PDTtfUbesbHOj7lfypt/aDczJo5ST+q06WjKrGVVl8cmRsjoz1ySgHVyUuGm6aSSg0EMQaX1nidBHqFDK4yuA4ltgYnK4YMLhVCpVLBEgiAzkX1ZCDjFde/KjqbOXYoxinJpOovlyNCiPcyGADg85qTJ8hVwzRjsVxDVHo0BR4VDmJZr8vcql2XAKj8LUlH2u6IheFi6OgN8pQNOCn7hw9UTK0Wi953ReVhLXEglE0CkdB1qEcb5rVFkdBlB7zUj+4IFbEKDKp1i1OLSSOkwhWsVHEOBA7mEClIW8WzzHpvG7KGrYtlQIVGrtSQgBlyxq7knKgpBgwphQB3K8YCGOXOA0U29mMhY+cMHxEkBuClWE7f9kwc6sJtTR9KhI5RKt+X4jScegXwkpatJJ/hKU/MchA3zlT8iVTiRCVqO6TSSS2iWASp/4oxkJXEpxKneegSCYoC2ScZPKJbb8PXqOf/q0tDomAk3MMTV6EIdFe1XshDdkiUawpRA4ZJ6auqkgxcOkJfLS2ZJyYfOjSG7mpWcFQiN3E7yV0iWKNsYowdokijefFiYzmGJwOi3bCRLPpA0SYokJ7FicHNoZieyLMulmDiTS9XT59xeQBGsWK7tCnLfAoGkUQa0KbCG290cBkK/0+hv3fmcLTCq08stbFNy5ZchRVDaEqUtR5CqoLayMiW0yi4dKACJsGRWCjZJCQOm6bskBXYmeIT9Za+vr66O3tLW9BEOyEd3790d3dTXd3N6tXr8b3/XLkanV1NVVVVTuUymSkbPUOWzjvq9SXVeHgaA+lk4Aj363BUT6u8vFUFRlbTdZmyVgfX7nkXBdfJRr20seILfSGiUDS7boD/OI86vqyZLTB1YlJMasNNV5Ifa6I6yYRl9lcgWyTQecUJp/cDW6zj8q62L4AExh0JnEes/kIGyROxHHeYooAhjjUFPs8oiixZsSxIuNG5LyIjJu4VUyKHHzXUJUtEoYu+dClNlckk43o7sqSD11yfkjWj+jsy9JZzJB1Ylxt6A59ukK3vPDuTecsYyGfWj2KRpGPk00BQWop6QiT/+s8TVvgUDSJsJbTBkdBaBRFqxKXGNO/mFbp16ZI5uGS31zZ71r1+17rQWaRxD2nX2Aztv/5MpDYQiHq2MFfmDAREEFuCFqjF3lsc20ab1qZUqAUQVmK6CpFcyUCXv/UGzMgDUApkkspYp2smiIVYVSMtg4ODo51cHHIKAdPO/haU+VqXA2RsRRiQ0Ynr3sjg7HQ6zupFi25ratcVTYReBpcF3xt8RTkXEO1Y/B1TK0X0VhVQOvEFFBdH+I3gSla4jw4OXCaXEx3geLmRJuotKXY57K5s4rEnVihDIRG0170UUCUfn6nN5dqEJPVq8ISGAdXG7JuTGQU+cjFUZYqLyIyivZiBgNUOTFFo2kPXApG4ZD4CvaE0JO6ekWp03FgLMZaXKXKARUl7WXGUanGFBzllM2ihUgTWI/QZAlMTJ4iBV1LqAoE5HFVhtDmU/+5gDh2ygEhZUdqq7AqHhX9f5IaJt4q2jGKIoIgoFgslv8vFouv+f2EHScIAoIgoL29vbwvk8mQ8TP4GR/f98lkMriuWw54KEUfO47z2oS+rQIZUvOpcsoCnKMz/f8rn6yqJUsNLh7ZOEdO+WR1Yk70HUXW0bgq1VoDnpP8XzTQFycBCFolGrrIwAat8bTG1/3Cpa+zNPrV6WITfGVpWheRcyLycfJombqiF8+LyQc5olhTkw3wvJjeviqC2MFzkrmhGDmJ1QIwqeDk6WQhaKzCdWM8LyKTgSoD2ZqI7GSLiQJMAP40F1WXpXpTHtNj0DUaXePRsKmbwsae9DpCvseloydH0TgUYxeLIjCWwGiCOPn8BaUIDXSnc02XmwhSncXEGtHlJovffGTxHMhqTWChNzTk45jQGCKbbAMj6hUKP33kakM5ajcZWhKRv+XPxFro78WWAxsGRgmXfhkGS77QQRRF4xLsYCQh8LghgtwQPP3MC/Q59VgMgQoYKjeaa91yrjO3LNqVwsn7f4ilFCQRhlhFNLi1FL2QTf4qiqoNz3PxfJ+sV4XvZ8l4War8WjLFaqpMFQ4O3bqbrM2StZkk+5qK6YpyuCgiLC6KGtcl42iUgqyjkogyrUBZHCzVbkSVG1HjB1RVF3F9g5OzuE0apz6DLsY4YYzKueiaDMotkDFBvy+Gicn0xgSxQxRrwliRjzRFoytWpHFqplGpVtCSmDk0SXBEbKE3tQLkUlNwaeJ0tUdgoC9KcmJ5WhHEhnycXEVPJevpKB1UVmu0k0y2ieZRkUlNw1CKiOvXVOZjpxw0Uowt+cgjH2cJ0qi4HidLYHsJdTEJBMFNAyIcrIrTXIFR4kOn0glzsMoR1g6ZPy4Kk7QjxaBIHMcVC4CJUnFiolMSrFV3av6iZB4rOUH1m+Udx6nIFTdYDjnP87YW+LYyofpbCXCuk8FRWXydRKH6NkvOVlNNjoxyyHjJgjDrKPw0mjLrJKbFUmS8ny6CMia5Ly1pdGUaQdodlkyCKhX4koVklavxHU2cRtlXuS5VDgTpT7jJz+LqJFLVWGjwLL62dEWJWbLKtWS1pWAS4ajaManlwOI7lqyOyaT+an7kksmEOL7BrTLoeg8N2NiiJ1VBYw1u1sf2FRPXjYyHcvNk3QI2NJgCmCgiF4SoMAksi9KFaNEo+qJkjoJkXugJYwKTzD+RtXTHRRSKjHLotQEFnSdnqnDQ9Ko+8rqH3rCTICxQDAIKYR9BEGAjyJlm6ouTqY0zbC72pGEoTvkZUfret3xmxDbJSBASJU8gVco1NyDRMhoXB2U1T/Y+TRR1sOs4fgg7AxHkhqCt5xk6nVcYWB1g2yTOuFtm3d4y70+JyioOlCsWKOUmCSuVi+9UU1fVzJ7uYuyCtQRBL67O4Ovq5Fa2EVldi4OfrvaqqI5qyYYZfKWpdj1iW4poVUQ4ZJ3EVBukJoXqqgA3iInzBmdTnjRoFeXFYIpEfRDmk50m1vT2+nQUMgTGoSdy6AwdemNNd5g8APoiSxBbAmPoiSOKNsRBY7F06x4MSVAFQFHlMSrGtR4GU9ZOalxiAhSaKltDxvqEqe9Hva7CU8mjMqs1GUdT7SXaOK2Sh1NGQ9ZJHhjWKpSyZHTi2xiaJDCk5MPYFyv6YpdC5FKILX1Rht6oioKN6FN5up3NRE6RyBQo6u4k+bMJk6TKNkhMrunEqmxMvlBgxcsrCMJg0FXxlg/58r4BD3A1yBwswt2uycDvruJ7U/3fs7JgYkMxLlIsJBrVob5P10kSBc+dO5eqqhwKB6VdEv83B1dncXSmnEoko+vwVQ7X+mRtFfW2hqxOUohUeZoqN1ko5ZwkOMlL/bJ8ZalyDcYqiibx41UKIqvoiTSBURRiiJ3EV6w3UvRGNhHYgMBYuqOADWGEh4vB0Kk7MEVDxubKOTB9MmjrEKkIjaLaVKPR5FUBbTV1KofvOITG4CjFpEyyENWqFD3qUeMYql1DfehRWwjwXENVMaAuLqI8Esf/nm7Uxj6UBhOYcr4Pk5pto4Im3+vS2ZujL3QJjENH6LK+6FKIk0XnpoKlK4yJrKFgInpUL3ndAxZCWyBPEjzk4BHYbqKgiOtkqHp5D54Nn6Azvz5NUpwkZk9ydUYDKu045efDUM+FgQwU1gZ/DvUH45T6jaPxCXCSYIfxRQS5IbA2xMS9Qx/fgQfrdpPfpqVglNJgi8TpPVsMN9MXbKTL38Cehclo5ROpAkXVVXZoD5zuJNt3mi6kqHvxVY4MOYphDZHN0BdpfJ34fITGw9NJssq6Yoba3qhsknSUwU1D6oHUD80p31BFo+mJNPlUCOyOFN1R4pNWiJNJsDsKKBIQqpAe3UE+bit/zCDqJTZhollAbaXBSLKm53BIyuNkVV15YenhklMeTb5XHm/OUVR7/dqERNOQCG1uGpSSBKgk6RQ0lsBaciYN6jCQjTVVRhO4kI8VvZFDdaQpxj69UYaMyRCogEAH9OjNBKYXYwNiExCaAnFcejCHmLiAMZZiMUqMJsplsHq4/cJc5W+gXCt3kCz3pXJiItCNH1vdx1vWQN7R77NM6eGuMFZTDAxRbFDaw9HV5ZJQjs7guzX4qgqlNL6qps40kTNJtZec49Lou2ScJAK1xoXqVOPl60QYympT9p/NOVGaD84hiEtVApIFUtEk90JgE3V6lQvZSNGb+olljAJ82qOkNovFEqmQgu2iT7VjraFoezEmGFDqypQ/izERjs6QUXW4xsMQkbE19PY1k1EOjtLUeA71vibnJGbdOs+h0fMSLb+2NHYG5NwoHbfCd+M0ch5i41CMHKI0KCBJUeTRGTqEJkk70hkqNhYgjJO8cB1BQBd5iqpIqBPBrRB3pwFQIUGUmGi1clL/WUMx6uTvPc/T1beuP+3JlqUBbbS1tnYLXuvzxJb/H5/5IRHkxBQ6XoggNwQKB+1U018zb7AVVDI5lVZcW9bzTDrauk7eQO2bo31cJ4fnZMulvGIbktT2S0LJPZ0tRzUZW8TEaV0/pTC2iCLxlwmdPIHuTcwtKkuvU0eXqSUTZ3CtS7bgUet6ZSfbjHbwneQnEKWetG560FhLkH4ENzWNFmJDZEoCkqU7CumzYTlze6/qpk+3E5ikbE1Y7CWIurFEqeAZlwXQkpO2q7MonZiqXZXDVUmahCx11Md1VGkfV2syWlGXcahLAk/RKok8y6YRu9jEFzDjmCQU3yo8lUR+OQNUJa6yVHlJ6oAwVmSd0rgSx+d8rInS3H2doaYn9MqffVOxiT4KoKDgFeilnaJNJvfIFimEHfihT0t9kgohJqQYd2FMlJZvMzhpDccSpUlfaxdF4osX2ygNtojKv6/YFLA2xJpgwGQtwt3OoF/rVooO1eX7OKl44qO1m7ZNqweopPxV6fscWH+0XMkg/T1o7eKoDNXOJFyVRHnmMu3k/EaqvMlkVFIazCNLvWkih4+1kMGhMetSk/oueA5MzVqy2qCUpcY11LoRjkp+Ib42ZNyIOI32LkXcG2UwOvnNxyQuCFXpfaFTAa/Ws1S5mg6duE64WlHtuTh9OYJ07nDiKXRqjwI9RCpEW5fAdGNsDNYQmb7+PI1phG0PbnLVtIPnVNPjbiYp9udRFTZRX6yjVFmi2vGo9ZLrHBtLxqlKIu1J3CQgTUaezlfBFgrxQpxYCwxJCGg+NnSZAjExRhl6dCcF20VkA2IbEMZ9aQmuAUFPJDoxpRwc7WOtpsGbRa5mMtbGRDZZ2BlMWnkiCZ4aqJ0baIkp3f+DiUBD1+be8lmU1m7FYKNOmQ9eh4ggNwQZv5kp1fvikknL1lTWXDXEhKpIbENCShUDisS2mKjVbX8YuFKJP11iMvXwdQ21upkqW0uDU88etQ3U5Vx6rKLV9pD3u7F+iOMqjFsAbTA2SCeEImqLXEHJQ6XSx8raiMD0gIaIAK00vbj0RJlyxYdSEIdVaRmddAJI/DAiYqKyL2BMRKySlaVrkmtRVL1E9NfqDE2RMO4hNAWwhtiEA6pGlEK4So7fJT+ffh+fnK4nQzU+GWpMDbVOJvXvg5yTmIkcnWjS3DTSK7JJxG7aOTGaYpxciyonEeJcbfGNTYMekgSejjJYrXGIyegYrS01kUvRaHxtiIyiI3TpiZNvPDCa1nyWfJxBKUU+MnQEDRRskqKkqAJ6Mp2QgWhSiBP4EGkKYVJnNRNmmUYdczIK10a82mXwrSE20B0mKWNKmeR7QkNnmAjJBVWgS3XQZVvpizdTCDuJ4kKqJciT1LxIomiTL9OWfwPCyBloAlc4oFwcncN1qsoLr6zTSLWeRI1toNE04CkHT2nqPJdaL9GCB8ZSiC05V+MoMFoxs87BaJe2CF4KewkyeTJuhmq3CnxL5IX4NtFc1VNDTrtYm/h+NlQ5VLuJKdDTMCkDtWnwkK8tU7MBvhMTGU3WjanxixijKUZp/VCd1me1isAkmvUk4XiygOmLk7yWnrZERlFIIzmrMDgkQlJAInjknCTfphOlSdLjLMQNaO1iiChoD+vGA0pqhRW/S2NCoIhSDtb4SdBPqtVyVYaC00OPrqYkqPjUkAtqgXROizReIbOVhkqj0bayvnP5PUnqwMYqJlQBkS4JZxEF21M5b6PSqhAO1sQ4+OWFuVIqeS44OeoW+hBrdJwlCg068MkEVUyx1WSB7kLIi/kN9ETdFOil12wmNH1l9xq7hduOIkkb4+oMTqlsmsri4OFYl4F1v2NCjDKEtkBEkdWd92LNzg+IGpP0I6LhGzYiyA3Bvnvvx4zMokRTZB0G1lwtkUQQJSuhSMVpMEOAVYaYCDNAQ2eTtW5SuNmx5Lxqsk6WrK3CtzmU49KoFFN0HcZCYAyRMWVfrYLuo8/pTFZ1mPR/W+4XSJN/+rhkUodohWt9fNIiz6STV/opiipPpIJU8EuEt8DmMSYuTy4WC7bfuVahk8mstAJMV5Q2jdAy6URo0lQdWvmgPGzq41aq9ai0g6N8PKcKVyV5rqpowLc+2mo85eCW4vTT0PtCBAUS4S2rk/x2EYmTsq8gcCBGEcapwOcqnDTIIeMkfkEZx+KaJLFvEohhqPZDMm5EMXIxRlGbSx4m3XmffOTiu4lgNzmTJR9rtDLkY017kKUQJ0JlaKvJR43llHiZmv70Wth+A2smTS1TY5P/TWQoBgbPxihrqXEM0/2A+bVdzFrYjfJi/nrbHF7q3JMnNsGLXQXWqU10sJ7O6FWKUTdh1FfW2KEM1sZlU2z5OxSGxZbaN6UyeG4NWbeeGm8q09iTZhqYUZVhr3rFIZPyNNVEHPBhH9tZpPOxmCdXT2VdmKFgHGKlCNH4nkZ7DmFaiiq2UBfDXBqTRYlKBLPSsSj9+kr5G2OjcLSl0YuoTqO6XW1p8gNyXkQxcnCUYXJDH0pZ+vp8HMeQzYVEoYPtyxDGOkkyHjsUjUNfnJgZC7FOS0YlglxvlARDOCqJEi8YqEmj5/viJEVJmJYZtLY/8tVV4CuXjM0AGVzlYbUlUH3EOsTRHpEpJvOGiRMtVWp5KC1EjQlRaGIdYuNuwrinrIkqmm56VH/VgoHmSkf5qDQTHICrs3gq2++2kQaluXho62BUYhIuvY5UVPoBoNCEOjGvQikiNCkI6OCW+9TKJWtrqDJVZB2fjOvg5BS+Tp4WoTGE1mLjiD2VR6ACwjikN+pGhS6R6k8bVHqyaOuWwuhwU39hnY5/sICoWEXl51CsIqp61hPH+XGptWpGWfCSWWv4iCA3BAvqF3N00xwS3VGas1b15wQqR3GSCBSJISLNG5dGRA5WZ7WUK851kmhOT/fXKvSULecjCoxD0UBPlKE3qqYvMgTxjGTVCmmUWFKQuxR6bq1NCjan5tHYJjKXk46tdA5AhKVosoQqMY2GKiRSRRQOsUod+G0ikCaBB4nglfQbYJXGU4k/m8EQ2ULaxkvbhBiidCJSFUJnSeB08BPBtiRwpkKcUYa8DTCpvSQixg2T5KWRtUTE5JSHqzVFE2OsJee4qW9Pko4k52pqPQebXvc6T5FzFW6UOG/XuDEZbXDcREuRy0b4cYxWltqpAToLDb15TKhway3KgbmbNVGgcD1LFCSlhozR+F6MtYowSv7O5gJcP/nitWtxcpaSu5zOKMio/qdf+nvCSX2UIgMFmwSZBA3EXZr5B2SZXMgwqydDe7dhU/cUDs5Opa9nIQ9syPK3zRHPmVV02DX0RhvJh+1EcV9aSDzs98cSM+xWVAQr4KC0j6Nz+G4ddZmZTFHzODgzizc1W05Z0Eq2Hv68uonGOoeaas30Oo9cNqLwYoCTyVKzj+Kow4uoaoPKpZrz0GBN+h2kZkhbiLDFONH4aTAFgy0aVHrvRt2WKK/RnkG7EBeT/V6tRfuKqCf5TTqNOsnF1pkKMFNcbMHgritgDTgZQxwlAlwhdohTX7GuSFNMK8J0BUmUqSKpV9xWTBZhVa6mEBm6oxBXOWQcTWQtvVGIqxSediiaJDjAKQlbNsQqmyzG8MmoahztoXGInSixWBAn5ub0d+mQJLKNbTLPeCpZeIa2iCVOtFHKJbIBkS2icfFUprygBXCVn2YTSBewKoNrM3jWw8VNswskC0RfOeVYFE8pHK3Kiy1XqSRxemyJrcXRClercq3rRODuX9C7Gmq8pNpNtZPMJUnC4CSoLDSawLgEJpcu0BNtavlZkd6OpWeLVsl8PTBHacnPdzBK9bxNmiVg44aZFIqtOz39iDC+iCA3BNN0E4sbiqngZiuEuIGUCxenK9oYlWZEJ/mfAVbFtA9XW/y0Lp8q7++vrxcaTSFOEk72RJpCnKT3iNP3ikyS50lBeTWfaKdSoZN+wdIOOKdUqDmMbZqDzSW2OUITUzQxIRGx6ndcjlSYTJaligalPE86xhDj2yw6/QmFqoBC45NBWU2oS4Jcsro0qdN3KXQ+CZn3MdZgKOXVCzHKlrWapRV2mJpvlXLSB4Elq2pQVhHpEAeXGlOPG7sEKsC1LnGYI0qLW3sqCTwoXTOT1rUNdVK/1tWGjJeMQTtxsirPaVw3TbnQmEFX+bjNITY2qKrkAV3XF6Icjcp52HRGVnU1UF+dSOpaQ1UOO6kJ6zjJxc9lwRu6jE7p5+UDhCGqt4eanl6mr9/I3qvbCF/pIb/RYVN7HZ1dNcyfApM6inx3xmZ+/cRRPLrZ8nhxFRvNi/QE6wmiLmKTx9ooEaTtAE3r65SKyOEBmjfXqaImM43J3gL2tvM5eYbHmUet4daXamlq9GmtbmKP5nZOW9SJ25xFzZ4ELbMxkyZBdVXFe1i2r1EYOJVoQG3enB7QuB0d0N1DOZw0X4QgBN8Da3E7e5NVWs6DviI615ek4aj2MHERa5J8bLag6e7N0lHMEsSqnJ+xM0p83YoGOoqW3sjgKoWxls1hnkCFZMMkzVG37iRSIX6cw2AoOr3lxZdVBqttOdrcqOSed5WHssl8UbIKKKsJVQgYtHL7U2/YxNSZnOviW5+YmKLOYzFkyJXPjXSx/F7JycmKyE2tEp718a2HTiPlPeWQc1z8VFhztCLn6vK86epkQd2fb5Jyfj1jk0W2myZhH+gz7Ja+PAVZbcilkbUZbcjopGRXxY+B5PkQmqSKT0mIs+kzovSccdJ1haOShOuoxK8XtXWyYEMqgKYJjYvG5TdtdRSKrdv55Y0+SWnKUdbIiWl12IggNwS1nkNLTR+QCFnQX+B+q/wQqVp5YCHk8k06xGyuUkd8SCbc2PZnGI+VxlMG5ajUF8UkfZdXX8kPPCnUbMv74lI5FxKtXmkyKsSKMDXXGAtFR1GIFV7qS1aMFU6cTDClaNKiiQkIU69ATZzmMFI2yX9Uot/gXNf/Wqk0iqkyaWUpMWZJC6hQGBVTJCBSISFFrI2TZLw2ICbJGB+ZYtmEWxL6elWmHA3nOTUEujfxtSEmo2rAJHUZYxWTtRmcQNGbjis0GoNO8s8pSzGdgFydFr7ebMiaCO2C9lW57Iaqz6FcBXU14LvJYyibhWwmEZ5dF1NfBzU1w/2ZbRvPwzY0QkMjduZMWJzcsHWdndS3rmePp1ZSfLGP9tYqXujYjxn7OUzvKfCV+g7+89F/5JFNfTyd/RtdwWoKUSdh1JkGS8Tln/DrSaAbyu8t4zVQ409lut6H4+tmct5BPXS4tXT5NawM63jLER1UzXfQe0/HHLgYMplhCWo7ip00qf/vpsbkjzBMknHn+6CvD4xFFYvgu2mCRA19qU9UbDBdRcKNhp7uKuI4mVdW91SzqegmgoSFjUVFR9GWKzd0BDHtcV+SiwxFu26jQBeOzmBtTMF0EphetCoFRqV1V3X/gkQpF1dlUGgc5eKSKQeAuNZHWY2b5tsEyFi/LHwN/G6c9O8YizE1ad8q9Z8z5bYWm5pGHTzlYFJNfalqhQOEaaLwatchkyb1TbTziYtDaXGecSCTRrk7CjLakMp9OCoJEtFYiibxIwTKkf0WhVbJwtx3bFJ31TF4OsbVSVkux7HoNAClXHJri/9LlNopZdFpHe/ys6J8027ZR/J3GCZ1dYXXHyLIDUFfGLOxL9cfHzhg1i6pucuLsiEWDkMJcYmGLNEGRVYRGCjEmtiqsq9KaQVWUrW7aUoNR4GvDFknEToMKgmnt8kqLraKwCjCAev9yPYn5IxtYj4pxIYoLYFQNJbAJiYSVyXrvoiYSEWJuRNNSEREhKMcMtZHoygSEmPRaDJpArpSoL2LwtEOkY2JUoHOSTV6IZRX5pEKCWwvgckT2WJSJisuEpl+Xz1jilQ48ytFUK4t6RDGfRR1Z/rdOAROLUXdkwqRhqyuIwwmpbmtIhrCWjqKPo5OHgg1rktLsQZfJ+lKGnuradoYUOWG5PyQ6qqQXH0XboNCVzvoQgQ12aSmpOtCoMBxwNGoYrH/Ae84kMlSfmJak+x7jdj6emx9Pey9Fz4wFZj+0svw4mqC59pZ9fxMjjkkw4INVZzQOJsf/v2N3L8hz9/sA3QV11AMO7A2EZqVjSe0MDeY8KZ1Bt+toyYznRl6P05unMUH997IBmcqcW0tucYM8xb04B87BbPvIsgkD8ctE8mMKcZCPo8KixBGqHwBenuhGEBvAbupC9sXYosx4fqYQpdDGLj0FTJszmfZWPTKOeJW5zUdRVvW1LcXQ9psT9nc2KN76NCtJJotj4Ltphh1lv1cY5PkUUzcLWzZnFkKWgLQaQokpVwc5eE6mTQKP5uYQXWSLxI0vvXL34vBolHJfKF0mh/TJD532sFRKrEYpFc/k/r+FmxiPXCtg4PCKojTagomnSMiY7BKUzQGFScWDU2ykC3Njk4a5eo7/UmQlUoi4JVKAj4sqRXFiQljRTFddJeSKYfGIbb9bhxa9S+yPZ1EEXvpfO3oxBIDVGjqSvQrC4bQwJUY5JYNYk1EuCO/slFjLPLITeBpadQRQW4I1sc9PNExPdWsVcQFAv31Vku+c6XVHfQLeqbyfi3f5FDKmJ6YNgID+cgSptnSNYkJwNOqnI3dV0luKDc1B+Rig1aJ+TVKNUpa2dRhGfIDBLd8lETOhan/WGgsBRMRESdZw1VIoAKMMrg4iRCni8REuNbDwU1MrbaIVi6BrUGjCEgclz2yZE0WqyxRqjFzcXGNW/a/K5lnkyzlBYr0YIiJTOL3EseFAcl2ozTaNalvatmiFJYlNb1GWOUk1TJM4jistYuxMYHuxdhE6xekaVlKvjl53UR3WF9e2ecKWTqCDJ5OIgtrXJda36XahWrHUOUY6jdENGSKVGdCqmt68Ku70DmSUkBp/Ujl6ESYK6UPK/1QQoMNks+gMi5ohekqYvoMylWonINyEruOyrqJb1VVBuproL4WM6V5K9Pdlpj5e8D8PXBPggXLnmSPp9fQ9UzM39ccwIy5Mb9ZsorLb13C/Z0beNF7kN7iRqK4G2OKTNQcdRWBCyi0U43n1FDlT2ZP5428sX4KH1+0mQcLdXQ0N7BvcztNbyrAgXti5szeIcFNdbSjOruhUIB8ITGFFgY8VIsBthijqnyoq0p+z8UQotTJXqcCvkmjY8K0uLKx2CDG5ENMV1QuodfX6ZMvuBTCHJ1Bhp7IIYgVHZFDR6DoDJKfYBBbNhYKdNtCOe1Jt+6gj3aU1jj4BLaPQtSOxaKVQ2zCdCFVytEWJYup8m8k/b0MKB1mVYCxSemwGI/YFNHaI9ZFQu0TqHzZjy3QWQIblB38HevgWQ/HOsTpAlKjcU3iP1tURQKd3N9Zm6RnKegCgerDt1k8m8EqQ6CKaDS9JotD0pe2mkzg46XaRAfoi1z81CfVVYnvbNZNvOsg8Q3MOYkmLDSJQ0kptVFJOA6MKrur5OPk6yqaJI2TsWlUq1a4Kkls7Kc+0b5O52kq66eWGMwXbssaq8l3kv7uBvxvgOK4JQSWYIfxRAS5IWiNX+bRTbWUxI80RrMiUkrTH8ua/FMMrLdaajvwgeCg8D2H2FoCE1MkpKDz9Kqusv+Xg4tnkojWalNNTnlkHYesq9OaogpXaQyJv5sp52aDyBqC2FKMDbE1xFgKNqSoikltV6JEKNNFIhJhKSYCY8pmUEuSNynpNHXrHZAXr2eLn41WTjk/Wn++LI0uRaLRv4ovOShHtkhsgiQowsZpOo0Am/5NSVNk40FvaGXj5EFiLSaOyw9si0dsgv5vQmnCuI+Cbi87VxdUO51OkjVfk0S8bYwbcCMPFw8/n6FKZclqhyrHIecmfja1fpZqB2pcQ9ZJtpxjyOioQniPrCYyOg2ESVbwJTk0SlfyvZGTFONOV+/aWvwByrqMNjRlemjKbqIm9yz1MwPcyT56/hTszGmJqXUIzKIDYdGB1G/cyFH3PM4ByyKebj2IN78h5CNBB19a+hYe955hQ/E5+orrMXEvViXm1okizJWEuJIWznWqqc3OZLq7kMWZuVxx+GZWu1laq/fk7YvXU/XGJsyhR2PqarffeW8f+pWV2BfXEK/ro7Be0d2RpTOfoTv06ItTLRUuYQxGKWLrYVFJsXk3SHIxKouxDhZV9okyVqW+W7qsnYmMRyGuJh87BGk5qe5Ik48UxbSkVjFOhLbuKKYvjuizBSIVEaiAHrU5SROUlnuKor5y9KhCY2yMMWH5nk+i0dP7sELIL/2dUq5MElOKYFdEoEKMdVHGIdbFpFqNSiL2He2hVbI4JM2P5qTHFU7qfJFEiJbmjzjNxZe8VxoUZNJ5izRdh+0PqBrYt0ajdMlBJK2YY6pwTVLSyrMeGfxE05cGjmUcje8kgl1cioJVCt9JbAqJFi7xv41iSz429JmQXtVHoAqpb3Fc9g2sNtVklYurHHytUEoRRIbQVC4VSgEUA4PpkoA5W7rCDC7eJBpNAxSLXeW6zcLrBxHkhuCRvz3ES9kNRLaYCh3FVEvUf/OV8sJ5upTINoOvqvBsBg8/zfnTn7DEpCHijnWJ/CJFrwPHUwSqndB24TgWx1VJAW6/mkymioyb5FbzTA4/qCqvqkOVmsaUk0xcJElpS8JZoumKMCYiigOsiYlsRBwHxHGEMSYRouI4NZek+aWMIY2vReOnOYsUxpRKifUnpiwJbVolCU0Hlp9xlJeWDtPpFBQPuA4xockT2yJRXCCyAcYE5XxTidkvTd0yhKao0mEdBhYU19pPJmWtB/giWhwnLTSuFFrbpNSR9tA6eeg72sV1fFwni6M0jpPBd3J4URWeypLpzeHZDFmbJaM8XBS+4+Iqr2w9TSb4pMQPQBjFBGGADjVZo5lf7VCjYjb0xLzSEWKimDhKhO+sk9SMVUrheZo9m1z2a7JssDWsXOpSU+Uyt1EzLbuGqdkXmTGji+xcF73nVMwhi7Yy29opU+A9J1H3Hjj8qWco3LqcF1+axVsO0Xy/uYEr/vwebu7+K5vyz1MMOzCmb0KYWvsLy3u4Ti3VmSlM9w7gjCl78tn3vsKtj9TDjByHLerFPbIFs+8bt6l9U+vWoZ55iej5Nlqfq2J1dw2vFnxWtNXTW6hmkopYmOvjubaAFZ15wsiiTPKQL8SWrKNwvERbu6DRYXo1dBiPV4oOm8KIyLW4noOTfn+e0vhOEqWdCA6WyEJgIiIbExCVF2YRAaEqEsYFQlMgMH0YExPFRcI4TxSHqaBmMHFyjxljsFZjbUwcB6mvlZMKb8kcYEzcv5gCSvciDC7sVwrOybV3tIfWfiKkKTeJVNcZtPZxVP+jx1UZSrnRkhRGpYTnqbuGLSaCnI0p1xC0cTnnXGLitRhiDAGkC1GtHbST6tmUwtVeOgeUEhBn0jnc6X+tNMq4uHGSr81Jfc5MWZBMImJ16usXqiIhfRToJgi7CcI8xWJvUkM5AqxPRk0iEzcSRRG5Yj06cImIKoI9rEprqqogdWIpUqSPiGL5GZQkJS6ZtXV5ntXKw1fJwnRV1+PEcS87W581FpUdJNhh+IggNwS9hdUUwrYkP5pN/LmAfs0UUCrDMzADd+IQrMsCz2A19SwG0xv1J3VNIwoTNFpX4bk1eE41tblJTKmaSwaDawNiGxOZkDw9RCafOAAbwDoYGxHZsJyc2NjERBnGeSJTwJgojV6srPNaMbby5xuQH6P8uoTeYt/ArOPppUmrVwz8zEC/YJe+f7/AZipW/ck5OzYZbS3cpWNDVWoWB461/LoyW7/rZPGdajynGjetlJHVtWTIUa3qyJIlqzzqvAzVnoufCo2BsfSFMa8UNxBHieDewfokcacNKZqepOqFyRMPkrizVMpIKY2/qRrfraNKN9Bs5zJDN2Kn+syeE3BrTxPVr05j8tMus6uL7POnW6k6IIfafx5mzwVb9Wv23w9//jz2f/BRJt3Sx183HMKp+3Uw6aU38n8b5/Ky91e68q+mZeniigXL7kS/MJ/Bc+uZUrUvB9g38J7ZPgfMszz88htYcshGat69ALNw320KcPrxvxE9sYpXn6jh5a4a1ndNZXNnyAH+Zp5c6fDwxh42qTY62Uif2UxgeohMkORCU5W1l0vfqbvex9VVuCqT1EhVWZKawnVkbBZcwzRvMvV+ppz0OjCW3jCkOypSsMmDvs/2UiRPYPLlhOShyVOMuonifJpX0KSVBErz14D7dovvtzz/bOHo9NruwYHly/qrEpTmy4rzBlynLffbAQvoynYD/RdK9H/O/jlpQHBWubJKMg5HJ8Klq/00n50uV9hxtQ9p1L7SNsnRqTNkdS1ZVYVWDlZZAvrYlH+VnsJmCmEXYdyTaLlL1ps0KlorN11k9j8XBn6ecoLg9LMNrAJR+XnLn6Z/8ZymfTImP9jXMuYkpmIxrY4XIsgNgbWJ5ip90b9/wM9LlaKGBmiFYhhk8hrsDcwA0+GAPrEY00MQ5AlUO33F9WzsfKE8+VSUYxlQ9qd/3ANvfNhKSOpvONxLMSzK16CULoHShLKlw1iJwcfyWrRB5XNt5fW0ycGBDSvPsaVIuIRYJTnhCgPKMVWWynHLgnrpwVBOzZKW4Un8iyq/qy0F121+BqCAAuWilMda/RhPOVXcv6aZ/1o/ixnxHBY11HLC9IjHdC0Pr53KvOUOC+5YzdzFz+IeMhdz0AGVnedymBOOZvrUZ5j85+Us/3sT+2breGuhj6sefQt3qz/RlV9FFHeDDV7TdzEeDNTEZf0pNGf34x31i7n81JU8tOEgpkztZcbRXbDkKExD4+B9dHaiHn2S/NI2nn6pmRc3TcHv7aU5XskTq6r4a3s71+nldIar6Qs2lwWmsrC01UJvAFssGgb+poABD2W3/3c1oE7plg/6QX9b5bqeA4KDBmHL2p+j9V0PvAfVwF7LTl1DR/Jvu+PS4o5K2+M2x7IFSm0hCm2xyBswP1UKm5WF6rcsmVX6HhI/wqjs09t/LWKsCjFoVKy2+F0MnB8p/36GO1+Xrwd5QO+2CzDhtSGC3JDY7d4UWwsOpkIgqJhJBgo6g/Ux8LVNfSFshFXFyslnW/lMtjNpjykVwQgD388M8ffOYbifvaKdTSZRm5bfquhh0BDlQQTUbTxohj8mwIYoCpgYwqiNQnEdbfpZViiPh/JZ/ntjLbX+dPayb2DxlHq6Zme5deU05t8dsLDxHuYeH8FRB2CnTusf4f774ey/H/utXMW8m57gqZdm8Kb9Yg7ddCo/W7eKl4sP0ltYDTbcaqGxq6JIcgVqp5qazHQO907lk3sp1lTX8mqwkOOO34w+52SsP3gOP/343wj+8gp/e6qZF9qy1BZqWbm+i/tWF3nM/I32YEU50XIp4pft5eSzgwhKWywahv5Aw9BuDPIb29Hvaiy/20H7Ho0F5Ej72Oo8U17kbVnma1jvMFhS0fL5W/w9ULAdINQOPbYd+G4GPH/GCynRNb6IIDfKbHnzlSeIHdQ6DaZd2vYJu/7Ddndkq+9q0Os8thNo5W/BYk0M5InjHsIo0dq2uS+ybF09/7N5Nke4i/HnV/PI2mqO7NQsevBvNB/xJPZtx1ckIzZzZpP9aC2H3PkwU+9z+cuqyfxbY8Q1T53Ko/YP5INNu4XfXEkT57r11GZncoA+jv8+oZ2Ho/05fe82Gk9uxBx72qDn6udfoO83z/HMiik8s3k60/JtPP2y4YHNHSznUXqC9RTCtnKVjG35bQ7GYO2Gda7czzuVEf2+d/A72lIL+lrN2IJQQgS5MUZuTmE06dfYQiJUxFgCiqaHYrCBrvzLrNGPcOvfpzA9cwC13QfxdGs9k1ZlOOHevzDjeIt9+z/299fUCO85iVknbObd/3k/TzzbzIW6h1uXn8FdhQfY2PccYbh5gMlu16KkiXPdembXvol3NRzIxUdsYIO/J285fCP6vNMGFbP1Xfez+fZuHl07mVfaplLV1cWvnuniMXsf3YU1iZ+TyaeRnBMzPYswPkzE39EWhuBR61MYHiLICcJuTKW2LhHsIhvSk+/l5eJGvvbii+ylj+Sc/abzm74GDu40HLXh/3BPWYSZPau/n0mTyJx7JIfdupTlf60jzPhMfvFofqeqWNPzMFHUCVv6/owzA4W4SdV78+EpB/KGPXxaMws48PQQc+rWWjjV0Y695SEeuquJxzY147d38stn1vM8j9BZeJUgai9Xvxhp0I0gvN4YC9Oq3HXDRwQ5QZhAlDV2NiCyIe29eR53W1n57F68u/5YCtNr6A5bOPLlp5h06mrMMUf0nztlCuqDb2GfKffQ+79ZtOvQ+PJivms72dy7nChq32XyzQ00p06q3ptTcsez//wq5syEBScXMKcu2eocvfQx2m9ezwMrp/LUq320rmnnT93PsLLwIGHUmTqrSy1aQRB2L0SQE4QJSL9AVyAIi7R2dfJfxVVM7dqfj/cdwgubmth/rWbJy7eg3nEsDEiEa049nsWTH2Pu7zagnQa+nD2e/3h1L57ru4Mgak+qQYyjwDNQE7egZgkXzljAjDn1HP/GzeTe/4YKTWOZm/7IbbdN4e/rJxO2buIHax9gY9+z6efJ71KaRkHY3TBjUdlBgh2GjQhygjCB6fepK5IvrmN11MM3VvVw4sajmKZquefuqbxp7d3k3r2wIv+cOXwxk9wn+Mf/WcvvzGQuzRj+5aXFrO17gmK4uay9UqidKgANFOImV+/HP89aQN3sJo7Ys5PsOYdhpk+vbL9xI8FPHuT+v7WwtrXAY0+28efwbtp6n09zfe2+OfMEYZfBiuA1noggJwivA5IcYwGh7WB9z5P8Pu7g1UdP4IML6/lDfgb/0L6cyRdXYWe0lM8xiw+mwXE4pqONO00zZ7S7/BLNmr7HKAQb01QKO0eYG1g3tWROfUv1MXgzJnHcgk6a/2nqVkIccUzXt5Zy5/IZ5Nd18OOnNvD36E66C2swpke0cIIgTAhEkBOE1wk2zU0YxR209/byF2ctq549hjM278+mvsmc9NUXWHDq85hTjy+fYxYdyIILn2Hyz1dwq27k3zfuzTUvTuVJ/h/FsANr8gPy7Y2NUNSf6NfBdeqZV3sMH5m2L1Nn1/P2o9aTOe8ozKRJFefox55g3c828YcXp7Lu5c38fMMTrOp7gCjqTKubiAAnCKOFISlROJpIBp7hs43SA4IgTESsNVgTEEXtrOi+l/9q/TPPP7uJW17M8eTNHvzqtor2Zv/9aHh7CwdMN9DcxAVzm5iWO5CM14DS/vCS146Qcg1P5eE69Uyq3pNzpuzLrNm1HDY3IHPWodgthDi1YQOrbmzj/16o47lnNvFfrXezqvsBwqhDhDhBECYcIsgJwusQi8XaiChqZ33Pk/y640/0vrqZW17QPHZ7Pfrehyram0MPZuER7cxsdpk1M8cJuUU0ZffAdWrTQulqq+z4r5WBhdhdp5aGqnkc4x3LwfN89p4B80+2FaZgSIS43u8v5ffPVxOu3sSv2u9gY89ThFHHblOlQhB2N0rpR0Z1G+X5ZCIjplVBeJ2SCHMhNu5gU/eTXGf6OHLjKexdM5nCDzMc8dQfcN53NDatS6o+dBqHNN7B83/KcP25K7jkR0fzB6C1Z1kaOBCN2tgGCnGOU0tz9X6cUnUU1717DRvDBcz5Jx9z1NEV5+i77ufF/4lY+koTjz+9iT/m72Rzz1NpYl8JaBCEscKiMKMseFkQUW6YiEZOEF7nJIXYi3T2reT+4P/4wV/Xc9fLEfcvnUb8m/sr275tCXu9qZvbnz+Yf3/zSt6gDq8wsY6GVq6/D43SObL+JA5z3sh171jB/esXMedEMEcdXnnOunW89LuQu17OsH5VJ3/M30l773IR4gRBmPCIICcIAtYajOmhu7CKpeEttK/q4M8rDY88OAX92BP9DbVCnXokh7Zs5rdrF3PB3pZJ2T1xdDVKDV6QfkQohVIOGa+BluxB/Mv+vdy88lAOm7sBc9o/VLbt7aP4k4e5Y0UVcWsb/7H+Kdp7lxPFXeIxLQg7AWtHfxMviOEjgpwgCEAqzMV99ORf4aaOm3nhhU388RXFkzf0ov90b3+7pkamnj2DN+/Zxku5Zk6reSNNVfNxdPXoaOXKwQ21zKhazIea92WZM5s3L9xI/QWLKprq5S/Sdvlf+PkDLax5uZ2vrX6Ild33EcUd4hMnCDuJUkLg0dzkzh0+IsgJglCm5DfX2beSO/N/ZO3Lm7l7XZZVt4TQ1V1uZw7cn+YlWf5hQcwVJ6xjH1ITK85rev9ECNQolSHrT+KN3n585gtdnLBPQMNbpmJnzqxo3/WTZ7ltRTMLulfz802PsL7n70ldWMkRJwjC6wQR5ARBqKBkZm3reZbftv8as76D/1vdRPyTuyvamZOPY+9TQpb2LOQTe2WZlT0E7VS/5nQkSnn4bh2z/UP4+tGv8pdbZjHnn6oxRxxaOc4f38pvn52Jv3Ez5z21nFe7HySM2iTFiCDsZErBDqO5SdTq8BFBThCErSgFQPQW1vHDFU9j27tZ9kQz+q4tgh+WHMFB07tRjXUckd0Lz6lB4YzIvFqKVNU6Q01mGodl5/FKOJdFe7RvFdygH3qEZfc1YTp6+PpTq1nd+whx3CPmVEEYB8bCR25H3VvjOOZLX/oS8+bNI5fLMX/+fP71X/8VO6Ajay2XXXYZ06dPJ5fLsWTJEpYvX17RT1tbG2eeeSZ1dXU0NDRw7rnn0tPTMxqXacwQQU4QhMGxFmP6WFn4K3/8+0buf9Vhwx970CtX9beprmLa4RFNU6u46IA+GnJzUDo3Yq2cwsFzapjpHMCH9y2QnVxD/QlNlW3WrWPD/2zmz6s0f1i2ieeDP1MMN4sQJwivY772ta/x/e9/n+985zs8++yzfO1rX+Pqq6/m+uuvL7e5+uqr+fa3v80NN9zA0qVLqa6u5qSTTqJQKJTbnHnmmTz99NPccccd3HLLLdx7772cf/754/GRho0IcoIgDEpS0ismX1zHfcXfoTa28cdXmun98bLKhqcfx6H7trLCn8GbnGOoykxFqcyOa+WUQmmfSbkFnD55Jqqpkf3e1IU5/siKZr3/8Sj/t6KZ4roO/lz4Lb2FVVhTECFOEMaJpETX+AY7PPjgg7ztbW/j1FNPZe7cubzrXe/ixBNP5OGHHwYSbdw3v/lNvvjFL/K2t72NAw88kJ/85CesXbuWm2++GYBnn32W2267jf/6r//i8MMP56ijjuL666/nl7/8JWvXrh3VazaaiCAnCMKQlIIf8sF6fvrqKno2dPPEiqnoVa/2N8rlyB41nf1bAi44UDElszfODmrlSkEOjs4xzx7AJSeuJFfn4xx/YGW71atZ+vI0Nrb28tPWp8gH65OkxiLECcKEI45jurq6KrZisTho2yOPPJK77rqLF154AYC//e1v3H///ZxyyikArFixgtbWVpYsWVI+p76+nsMPP5yHHkoq2Tz00EM0NDRwyCGHlNssWbIErTVLly4dq4/5mhFBThCEbZIEPxRZEfyV51b1smyDQ3THsoo25k2HMXdhJ61VkznEOYCsP2mHfeWUcvDdOo5oamDp2oXsNX8zZvasijbxH59g2SbFky93sjr/qCT8FYRdAJsGJ4zmBoply5ZRX19fsV111VWDjuHzn/88733ve9lnn33wPI+DDz6Yiy++mDPPPBOA1tZWAKZOnVpx3tSpU8vHWltbaW5urjjuui5NTU3lNrsiUqJLEITtY2O6C2v4Q8+DXNd7NE88OJlDZ9+H+cf+Mlnemw9k7mPref9Cj+efPJKng43EcQ9qOL5rysHR1UzO7sk5+3fiNFeRPW0vBopo+v6lLH1wCpn2Tu4s/JF8cb0IcYKwC2AtmFFWilsLixYt4p577qnYn8lkBm3/61//mptuuomf//znLFy4kGXLlnHxxRfT0tLC2WefPbqD28UQjZwgCNvFYrEmz+b8cv777z08uho6/9KJamsvtzF7zGPB5Haecxo5qmZ2klduGNUeVPrPc2tYYBZyfzCXmfM6MQv3rWjXc+cGHl2r+NkLr9KVX421g5tYBEGYGDiOQ11dXcU2lCD3mc98pqyVO+CAAzjrrLP45Cc/WdbgTZs2DYD169dXnLd+/frysWnTprFhw4aK41EU0dbWVm6zKyKCnCAIw8ISE0Rd/J1H2TfeyFNrpqAeWlbRpml/w6LpDv98YBuNmbmpr9z2TaxK56jJTOfYGbUc3GLJvmFSxXH9wMM8tXIKs4ttvGweIYq7pfyWIOwi7AqVHfr6+tC6UqRxHAdjEq39vHnzmDZtGnfddVf5eFdXF0uXLuWII44A4IgjjqCjo4PHHnus3Obuu+/GGMPhh1emQNqVENOqIAjDw1pM3Mum/Av84vmjWKAsc/4U03JqfxPn+AM5+Jmn+NHKeRzm1HJPdiOdfXksBmUZ3MSa+sbtxxEcM99hvz03Yk54W0WT9ls28dDaSTzxfJxq4yTAQRB2Ffr92ka3zx3htNNO46tf/SqzZ89m4cKFPPHEE1x77bV86EMfAkApxcUXX8xXvvIV9txzT+bNm8eXvvQlWlpaOP300wHYd999OfnkkznvvPO44YYbCMOQiy66iPe+9720tLSM6ucbTUSQEwRhWCSCU0wY9fDX/ErO9wP+3jaLmUsfwxy+GAAzexaNBz7F/q96NHa7PLFqDt16DXEcAvFWfZbMqtWZZt40uY6VbhNHH1Zd4RunNm/mmdZJ/GNmNT8K1xGbXkB84wRB6Of666/nS1/6EhdeeCEbNmygpaWFj3zkI1x22WXlNp/97Gfp7e3l/PPPp6Ojg6OOOorbbruNbDZbbnPTTTdx0UUXccIJJ6C15p3vfCff/va3x+MjDRsxrQqCMHysxdoia6O/89NnMvxtvSF4cHVFE33QHPZs7OWMf2xlntkbR2eHNq2mueOmOAs4Y2Efe9cH2IMqfePUX5/kqU2aXzxbRWv8LNYEYlYVhF2IUrDDaG47eovX1tbyzW9+k5UrV5LP53nppZf4yle+gu/75TZKKa688kpaW1spFArceeed7LXXXhX9NDU18fOf/5zu7m46Ozv54Q9/SE1NzWhcJgAef/xxLr30UtrbE//iL37xi6+5TxHkBEHYIawN6S6s5U89z3JCbj1PPtWMvveh8nGz/37MWdjNT59cyD9MraHKn5RWe3Aq+kl0cQ6eW88R2b24t6+FvVs2YZsa+9u0tbPhniLvmfkst7etobuwFotUcBAEYffk/PPPp6amhre//e10dnZy9913b/+k7SCCnCAIwyap9mCJTS8bw+f5yd9dXujOEC6rjPRyD5zKHpMd3jKrnVqvBUf7ZTNqmVQbV+VP4vhplgXNDjX7VXp7qL89y/LNjdz012bW8hyxKSAIwq7F2OSRm5hks1m+8IUvcM0113DuuedW1IIdKSLICYKww1gT0FvcyNKudSxfX2T9i9Wodev6j++/F7Nq8hzwfodpdg9cpwpU/3RT0sY5upombw/e+sZWZtfk0QfOrXif4uMbeX6D5d41AT3BBowpillVEHYxRtusaiwTVueey+UAOPTQQznllFMqImRHym4jyH31q1/lyCOPpKqqioaGhkHbrFq1ilNPPZWqqiqam5v5zGc+QxRFO3eggjDBsVgsMWHUycvxX2ko5vlbWwM8/HR/m4ZG5i1o5ye/nM1BVVPIeU0olaks26Vcsn4ji9R+/PKFfZm7V8dWueOef24SBzkbeMz8jWLYjrXhTvqUgiAIo89XvvKVslxy7rnn8utf//o197nDgtzZZ5/Nvffe+5rfeEcJgoB3v/vdXHDBBYMej+OYU089lSAIePDBB/nxj3/MjTfeWBGxIgjCKGEt2Ije4kaeX5dnba+m8HRvRRN/QQ0Lpmj2qlfknAa0SsymCgVKoXWGam8y+zd57DnVwd+3vuJ8/exzrOzN8ew6TUe4ktjkASP+cYKwi2EZ/VxyE9W8evjhh+O6/S4kpdQnr4UdTj/S2dnJkiVLmDNnDueccw5nn302M2bMeM0D2R5XXHEFADfeeOOgx2+//XaeeeYZ7rzzTqZOncqiRYv413/9Vz73uc9x+eWXV0SuCILw2kh85SLCqJN7e1+kZkMjK19tZGD8l9p/HvPueQl/Rp4ft85go34OYk2ShkTjOlU0qwWcPreT5ikOdvHBFe8RP7ScZzc289ArEb3F9WJWFYRdFMvom0In4p0+UiXY3LlzmT179pDHd1iQu/nmm9m4cSM//elP+fGPf8yXv/xllixZwrnnnsvb3vY2PG/7JXnGgoceeogDDjigoiDuSSedxAUXXMDTTz/NwQcfPOh5xWKRYrG/1E9XV9eYj1UQJgKJMBeyMX6RTLiINb1V7N3Zia1PNGtm9iwaJj/F9PcEND7SVNbIodKSXE41s5jKgZ+vo/BID3bKlIr+u19SNNsCy61o4wRB2P0ZSc3XUiLjT3ziE0O2GVFC4ClTpnDJJZdwySWX8Pjjj/OjH/2Is846i5qaGt7//vdz4YUXsueee46k6xHT2tpaIcQB5detra1DnnfVVVeVtX2CIOwgNqYv3IRXDNkYuKi168qCHJ5HpkXx6n05proa18mhUFh04h/n1jOvJkPvn9ZRdfCUChFNrVvH2k31VAd9bIxflNxxgrALUzKHjiYT8XZfsWLFmPT7moId1q1bxx133MEdd9yB4zi8+c1v5u9//zv77bcf11133XbP//znP49Sapvbc88991qGuF0uvfRSOjs7y9urr746pu8nCBONIOziz69upq0A9oXK5MDO/Mk81NnCvDoX36kGpZOIVeVR60zjsEkxdy+fj9qn0j1DPbmcl7qr+PmzBbqLkjtOEARhKHZYIxeGIX/4wx/40Y9+xO23386BBx7IxRdfzPve9z7q6uoA+N///V8+9KEP8clPfnKbfX3qU5/igx/84Dbb7LHHHsMa17Rp03j44Ycr9q1fv758bCgymQyZTGZY7yEIQiUWi7ERG3Qrvb1ziNf0Va4OJ9XTUtfD5hqL15YjWTsatHKpZRKHNW+m0NSAnTG9ot/olU42dGd5jhcJo56JuTwXhAmCZfSL5k3UO/7Xv/41p59+etlvf/Xq1bS0tKB1MnP29fXxne98h89+9rPD7nOHBbnp06djjOGMM87g4YcfZtGiRVu1Of7444dMETKQKVOmMGULv5iRcsQRR/DVr36VDRs20NzcDMAdd9xBXV0d++2336i8hyAIlSQJfmP6aCcXRxQ2KKoGNqitQaluqrIOrkoXTEqjlKbG1FLXkCfWFjtpUkW/va8q1nRGtMevYm1RtHGCsAtjrcKOsmmVCRq1esYZZ7Bu3bqynLLffvuxbNmystKqu7ubSy+9dGwFueuuu453v/vdFUVmt6ShoWHUbcGrVq2ira2NVatWEccxy5YtA2DBggXU1NRw4oknst9++3HWWWdx9dVX09rayhe/+EU+9rGPicZNEMaYwOZ5Q00PXR1ZqjduLAcu2KocDV7A8bM3k32pHqU8rA3R2meyU83UL+2L++P1lZ11ddPeWUVPb0g+bMPaeBw+kSAIwuizZSWH0ajssMOC3FlnnfWa33QkXHbZZfz4xz8uvy5Fod5zzz0cd9xxOI7DLbfcwgUXXMARRxxBdXU1Z599NldeeeW4jFcQJjoDy20ZG/L/27v38Lqq+87/77X2PlddbetmczE2JlwawFwS46RNk+AHm5JOecLQpEN4oGFIHmqSCeQ+5ZKQBlKSoQwZCqXPcEnbTDp5pk2bNGnxOIQ0PxySOj//AiQ4QHANNpKv0pF0bnvvtX5/HElGtmzL0pGOZD6vPPt5rH32WVlnW958z3et9V0v7Q9oLWZZsmfvgRWoQe0RU0haSPscxlggRWDTNIUBvNJHEI4P1OyePewrZWmiTOIqiMjc5tDQaiNNadVqIzz66KOHrSE3aunSpXz3u9+dnQ6JyNhODYmP2DXoGIxSsHdg7GWfThEGnp8NLWCBG8SaNI4q1qRYlAn49dcq9Jx50Jqr/gLFJGBFJsL7ev/nQUTqzY9sq1XvNmVy5k0gJyJzhxk3fyUAoFxNKMQBvnf/gZeam8mFMS+WsrSaLMZYjB+ZI5cy/D/7Onhf097xje8vMBTncJGGVEXk+PMv//IvtI3W23SOjRs38uyzzwLQ399/zO0pkBORabAjw6VQqMJwHOAKlUOmKVtrRsqOHMi+Jd5jrDmkCJIvlCnGTewqUwv8MIDRggeROcpT/y21jud/7QcXBv7whz887mdjju1eKpATkakZedgYLMYERA4qscdXxz/SPdQCNhgbKvXeUXUTP7B8NSEZeaMxFow9vp/qIvKG4Vz9p4sokBORKTMHfQtPJpgoY4AgMGSDYFxGDgBrODiWM8ZA4mgNPYHNMM265SIyw9xMzJGrb3PHNQVyInJMXh+8jQ53ep+QOAic4+DILJuOCKylPR1iTcjozLeUrWXqTPqgSC4TEuJZkE6wCuJE5oH6D60ej3Xkli1bdszDpsDM7LUqIm9cHn9QMOdIfIX+qiMVGkjGf5duaqmSS1tObLLY/tojx/mIwEAYWAjGP9hMNkUucJSMx9oQY6y+nYvIvHe0yhuHc8oppxzxdQVyIjI13oMB7yOci6k6jw0PzaDZlCN83XnnYxJXZW/ZUyTEVw6aM5IOyaYNNkiwJjXTn0JEpsmh8iOT8du//dsz0q4CORGZBof3jthVsIElZTkkw2bTEFpozoyeT0iSMkXnqXiDjw5qsjnHgnSRE0/dhX0+xWh5ExGZmzRHrrE0AUVEps578DFRUmSPLzIcW5Kh8Rm2sN2yMO1Z1VXB2hTeOzyOjuZatu2QpJuFlHUMFZtGTqienIjI4SiQE5Fj9vqabp6ExJUpZAYYiqE6YDH9B4oC29YU+dBBGBCYcGzlajK6gvXg1fixwwH/3/6uGf4UIlIvo7Xk6nXI5GloVUSmx3ucq0AqYSiG4nCaloFBfPsCAGx7nvYw5tU4R2hzQIA1aYoYUvbwc2G2DGVGmtc2XSJz2YwMrWpsddKUkROR6fMx5WA/A1VPsZKGYvHAax0tLG4usr2aJhu0YU1IKsxTNAn5ib5Kek8pDtlZ9jgfAU67OoiIHIYyciIyPcaACSGIiBJH4g4aFnGQChKCMDuyC0RIOmjChAaLP6QgMKUqFRcQB8rGicwHjkNnSEyXvrpNnjJyIjJ1xmAICIMWnCkdOJ+87rFeqeKcwQeWgBTWhqSCZggN1oDJjH8M+f5hImfJZWoFhEVE5PD0lBSRY3agILDF2DRNmU7y2WZSwUhQVqkcuHioRCUJIAjI0kxg07QGPTSl0zSHjmBRZty373hHkeF4IYy2pe+bInObN3hf3wUKWvAweQrkRGRaAttES2oJLdkuWlKGdJBAfCAj5wbKDFZbKIycsiZF1jeTToc0BQ7TnB4XyLkyVJ0hDiEYqU1iMJonJzJHaWi1sfRVV0SmxhgMhjDIstSdQXe4lI4MtDRXIFX7jmh27ybeWWFPJU3RQ0iGVJClxbXRlk2zIF2BfGZcs96P/IfBOlI2P1auREREDqWMnIgcs7H9Vo0lDHJ0Z1roDto4IReT74ggl8EMDGC2vcre7Xl6yyFDSZlOu4g4PJPLezpYvCDkxI4CNC050PBwEVetZeSG7TA21PdykblO5UcaS191RWRqvAfvsFiaMiFNYUBrKiZoMhCGtXly+wbZX8wyGEHFR+zq/jfCxbvZlm+mOxMThA5K1bEmzVCBajGgnNSKjgT6qikyL/g6HzJ5ekyKyLQ4HMZDPrTkghiTC2pDq95BNWY4zjEcQ2xilnScCsYySJlXSs2cvj9PS+F1NeeimKgakHgIfYglAwS1Eif6ii4icggFciIyZR6PcxFx4ggM5FIxtjWNz4zsyuAcxSSgUHXsN31Uk2FCm6dqqyQeMukYug9sxWWqEVEUEhhopZkMLQQ2jXNa8CAyVzkMru6rVmWyNLQqIlPy+qAq8VBJPJkgweQzkE7XVq7GtWuc91T8MNWkSGBSdPqFnJyPaespQ3PzgUYHhwBIW8jagFSSndXPJCIy3ygjJyLT4HA+JkoShmOHtR6as/hsDjtcxFVjLJAKLOkkjxnZxiEY2Ri73B+QfXkHZkEbBAEkjny+SjbwRC4hooLzMXivbJzIHDUT89r0r33yFMiJyLR474gSTyVxREkA1kA2g89mwBoSX8vIAXiXELlhCqbEvmo7hUKO1v0lDOBbWjEdC0k3bcMDw77KsNuH95GCOJE5zGvVakMpkBORafE4yi4m8Y5SHEI5AmPxTc3YfBqPIXKehCrGBoQmQ44MTYGjtaWMPWEhrqs2T8435UkqlmJsKNsSw9E+vKsepQciIm9cCuREZFq8d1R8TGAMw1EKv7sAQ0PQlIe2HFmbEJoUKZOnKdVFJ6ewJJvllKYSzUsdnNA91pb59XZ6d7cwEIHxlkRBnMicp50dGkuBnIhMW0KCxRA7cMUIWxioPYijhNAGZAJDJm7Cm4SMyxBYQzmxxPsd4Y4+TEszpliE3v1UkhQGCAkJTAZMiPGxhldF5ijvNRTaSFq1KiLTFpMQxQ47UoHAVCPM4CB+qEzV1R4zaZ8mRZaQAICyCygNpPC7BjH7ByBxkE/TmqmSC8B7T2gz2qJLROQIlJETkWnxPmbQDlB0VapuZN9UazBJgh8pP5IKDE0+T5PPsySb45RmOLW1QMtJMWZxB76zAyyYgUHSqVqB4IqvELkS3jtl40TmMI/BUe86cvVt73imr7oiMnXek7gqQ+yh4mOGYosrJFAq44MAkw1pDmOaQmgJ0yxKZejJG07KVVnYVSRYnIPmHJRKmL7d+F/3sbPQTH8VnHfESQl83OhPKSLzwI4dO/jABz7AokWLyOVynH322fzbv/3b2Ovee2677TYWL15MLpdjzZo1vPDCC+Pa2LdvH1dddRWtra20t7dz3XXXMTQ0NNsf5ZgokBORKfN4vI8ouwIREYNxQGm3hd37a3PegMA6Mhay1pILLbkAMrY2NdoXY9gzgNn2Kv757ZSeL7OzlGEodngPiYI4kTlvdI5cvY9jsX//ft7+9reTSqX43ve+xy9+8Qv+23/7byxYsGDsmrvvvpv77ruPBx98kKeffpqmpibWrl1LuVweu+aqq67iueeeY8OGDXznO9/hhz/8IR/60IfqdatmhIZWRWSaHJErUfVVhmPD8FCWlt1DmFRIsqdIKV5I7CBlDa1pw6J0woJsmbBp5EldjmpFqCKHDT25wBGagMhXCG0ajMV4bc8lMlfNhVWrf/qnf8pJJ53EI488MnZu2bJlB9rznnvvvZdbbrmF3/u93wPga1/7Gt3d3XzrW9/i/e9/P7/85S/553/+Z376059y4YUXAvDVr36V3/md3+ErX/kKS5YsmfbnmgnKyIlIXVR8kWT06es9lCN8KSF2hsBCLjR0Zz3LmouccEqB9JsXYld0QVc75DOYXIogD/kgITBQ8SWsSaHHlIgczT/+4z9y4YUXcuWVV9LV1cV5553HX/7lX469/vLLL9Pb28uaNWvGzrW1tbFq1So2bdoEwKZNm2hvbx8L4gDWrFmDtZann3569j7MMdITUkTqouJLJB6i2OIrCVRjSCC0nlwAzSEsTCd0tg2TWZGH007Cn7gYWptgsEj86hCFHWl2VVIMx47Ex3iSRn8sETmK0Z0d6nl4IEkSCoXCuKNSqUzYh1//+tc88MADnHbaafzLv/wLN9xwAx/96Ed57LHHAOjt7QWgu7t73Pu6u7vHXuvt7aVrpDj5qDAMWbhw4dg1c5ECORGZtsRVcN4xGMHuUp7qK1XcrkHiQU/iaqvPjIHQeMJUgsln8E1NkMuBcyS9Q+x7IcXPezv4ZcGyu1rC+ZhqPAxo1arIXOZn4ADYsmULbW1t44677rprwj445zj//PO58847Oe+88/jQhz7E9ddfz4MPPjgzH3oO0Rw5EZkeP5I9c45S7ClEIcX+FDYXUS6EDMQBQxEkQC5IyC5IoGcBvrOz9v44wi7Iks6UscYTJZ6SKVNNasEcvt6zb0RkPli5ciVPPPHEuHOZTGbCaxcvXsxZZ5017tyZZ57J//k//weAnp4eAPr6+li8ePHYNX19faxcuXLsml27do1rI45j9u3bN/b+uUgZORGpi8hXiEeHRbzBVaFSCSnGAVUPGQsntAyReUsX7tyzx97nu7owzRnSOUdTkJAKDLGJGYr24EeCOKOaUiJzlmMGhlY9BEFAa2vruONwgdzb3/52tm7dOu7cr371K5YuXQrUFj709PSwcePGsdcLhQJPP/00q1evBmD16tX09/ezefPmsWu+//3v45xj1apVdb5r9aOMnIjUReKiWjkSwDlw1ZH5coA1EFrIpGNoaz7kvW5ngddea2FbMUN/JaZkBkmSCr7ua+FE5Hh000038ba3vY0777yT3//93+cnP/kJDz30EA899BAAxhg+9rGP8Sd/8iecdtppLFu2jFtvvZUlS5Zw+eWXA7UM3rp168aGZKMo4sYbb+T973//nF2xCgrkRKQOvE8wPiB2nqHY0j+Uw3tDoZyl6gzOQ+KhUg2hXD3k/a7o2DncxK+HDNvdHobdXpxzOFfV/DiROW4m9lo91ube8pa38Pd///d89rOf5Y477mDZsmXce++9XHXVVWPXfOpTn2J4eJgPfehD9Pf385u/+Zv88z//M9lsduyav/mbv+HGG2/k4osvxlrLFVdcwX333VenTzUzFMiJyLR4ars7WJ+mnDj6oxS7yjkqLmB/JUN/FYYjT2AMYeChveWQNsKVS+jeMoQlRYE+itEeoniYONFiB5G5ztP4OnIA73nPe3jPe95z2NeNMdxxxx3ccccdh71m4cKFfP3rX5/C/3vjaI6ciEyb8zGWgMglJB4sntDUBkbLCZTiWijW3FrBva5I55jWJpozVbIjXy2TpEIUF/E+qv9XfRGR44gyciIybd47rA9JqMVdBgiMwwKxh8g5nLeEOQfp1KENvPwavUNNDFQ8VVfCE+Fchfp/zxeRehtdoFBP+v42eQrkRKQuQpch9gnFBPZGIQk59lYDKkmtrG/sIC5Z0hO81w9Vea3cwmvlCsVoDy4p450D7zWsKjLHvb72m8w+Da2KSF0Yb4hJKMUwGAXsqYT0R5ZK4vG+tnL1cCXhzBkn0JGOCDE4F+FJSJx2dRARORpl5ESkDhyJdyRmJPgaKfuWeKg6R+wd1kCq6TCRXFsrTan9ZIMs1gRAbZNrEZn7/EwMrda3ueOaAjkRmSZX206LEpGpYgzkrKMtlTCcWCLnKboq1SRN2HKYwr7PvsTeShOR82AshkBPcpF5wmPwdS7arX/+k6dATkSmzXtH5KojQ6ue4cQSWk/V1YqHRMTER3gy+7iWqQusIbQZIhvWHuTGaNaziMgRKJATkbpwLgEclcSxvxoQu4DBqDZEmiaFNeAiP+HEXLNiCd3Z3bSlmknFecomjXcGsBi04EFkLtOq1cbSYgcRmTZjLAYLWEJjSNva0EglgQRPaILaufgwDWQzZMKETGDI2FbCIA8mgxmZLyciIhNTRk5Eps17h3O14dFcaGhLeVIGCoEh8gkejzUQZA8zj2bbToajkNBAjhaKQZ7AZjEmxBsVBRaZyzxa7NBIysiJyPR4DyRUXJHa6tXaaWtqwVuCo2KqOAccLpBLBbRny3RkYaHrIB20ENgMxkxQPFhE5hQ/A4dMngI5EZk27x3exzgcQ1HCroqhP7JEDtKEWG+pekj6Jy4/4s4/m56zypzeUqYznSNn20kF+bHhWhERmZiGVkVk2oyxBCZNSBpDbZglHpkAHRpDxqdxHkp7Q1KFQWhtOagBi8laMjYhG2TIxE2kbBPGKIgTmeu02KGx9JQUkekxBmsy5Gkn9CGLsiGLc57WVG2FatU7PJ7QQBRZ7I4dhzbR34+x0JSOaE0bWlwLGduMHlEi84Gfgf/JZOkpKSJ1YUkREJAOIB84srb2KK5QpUoEQBh6sIc+dvwJS7BnLeGEkwp0ZSFvUlisMnIiIkcxb56SX/ziF3nb295GPp+nvb19wmuMMYcc3/jGN2a3oyJvcKUYhmNL5AwYsFhiEzMce4aH07C/MOH73DlvJnNmM92ZmFwQYkkpkBOZB0aHVut5KCM3efPmKVmtVrnyyiu54YYbjnjdI488wmuvvTZ2XH755bPTQZE3MGMsIQGBDygnnsHYUPWGjIUmkwZgf6XKc/vbqPxoB3bbtkMbSaUw+TRZm5ALA/K0z+pnEBGZj+bNYofPf/7zADz66KNHvK69vZ2enp5Z6JGIABgCrE3T4poJCWgKDS2hJ209diSj5vHEeApxwNDuNJmXXoVTTjm0sXRIynrSFtI+M7sfRESmRCVDGmveZOQma/369XR0dPDWt76Vhx9+GK+lLyIzxmDAWAKbptXmyJiABRlYlE7IWE/kYdhXiUwFAwRAkhgoVidsz5+xjAXZMilb3w24RWTm+JkYWtV/uidt3mTkJuOOO+7g3e9+N/l8nscff5w/+qM/YmhoiI9+9KOHfU+lUqFSqYz9XChMPH9HRA7PmhSZwBKagNBAYDwOQ+ygYiqUGWKIJnaVs7za38qCl3cTDA1Bc/O4dnx3D4va/43sznaAkTpyIiJyOA19Sn7mM5+ZcIHC64/nn39+0u3deuutvP3tb+e8887j05/+NJ/61Kf48pe/fMT33HXXXbS1tY0dJ5100nQ/lsgbjvcJifc4PEMxDMYBbmSOXNZnccTsN338+1DMS8NZ9m7LYXfsnLCtIPBkLGR8WosdROYB72fgaPSHmkcampH7+Mc/zrXXXnvEa5YvXz7l9letWsUXvvAFKpUKmczE820++9nPcvPNN4/9XCgUFMyJHCPPgR0bEg+RM+QCRy6s7ezg8FTdAAUXUYhChispKAxP2JaxEBhIj6xaNRg91EXmMDdySGM0NJDr7Oyks7NzxtrfsmULCxYsOGwQB5DJZI74uogcjSWwGXJBQGAMTSEsSCcAxA6GTYmyG8BgsMYQjE5/SwUTtpZuc2PXaGhVROTI5s0cue3bt7Nv3z62b99OkiRs2bIFgBUrVtDc3My3v/1t+vr6uOiii8hms2zYsIE777yTT3ziE43tuMhxrrY9V0gmBGsMuQCyNqGYBJQdlE0Rl9QWNwwFJfaUs+wq5jh178TzUW2zPRDsicic59EWXY00bwK52267jccee2zs5/POOw+AJ554gne+852kUinuv/9+brrpJrz3rFixgnvuuYfrr7++UV0WeUMZjb1iB2UXUHYG7yHlM1ibphoPsjvczo5iE6+W07hd+yduyEFoIGUCrE3Vxlr1UBcRmdC8CeQeffTRI9aQW7duHevWrZu9DokIAN47Eh9TjD155xiIIF8NSBlPLoBW38xuUpRchbIbxBlHznpsR/Nh59UE1pMeyfQBI/PkFM2JzEWjCxTq2mZ9mzuuzZtATkTmKkfiKhTjhJR3RK72EE5bT2ghwRH7Cs7FhKTIBSHNYQItuQlbs00BBoi9H1m1qnlyInPZTCx2UCA3eXpCisj0eIf3jqpLiH2CBbLWExqP8xCTjFxoiH2FvXGJfy+mcC/0TdicyYYjleI93ms9nIjIkSgjJyJ1keBHsm9QcQbnLYmHrEmTtwuJUxViV6E/tZe9lRaSgZiJ1q264QjvITBa8SAyH8zE0KpScpOnQE5Eps17R9VHRCaiFHv6q4ZsUNvZIR+ENLsOSsEAcVIiIE1rCsKTmid8VvtyLQMXGDOSkRORucyjodVG0tCqiEyZH/lf4qrstwMUzRADUUx/FWIPKQu5wBL4AOcjPJ6cz9GW9pjutgnbtO0pjIGqc9rZQUTkKPSUFJFpcjhfZZh9VClScQmOWgmRbABpa8j4DCmTw2AomRK7yoZk68Rz5GxzrUB31SfKyInMA977+h/KyU2aAjkRmTbvIyq+QORLVH1M4vxYgdBMYGgPciy0S8mHi3DE9Fc80WvxxG2VYxJfmx+X+Li2mEIPdRGRCWmOnIhMj/d4H1Nxg1R9kUE7xL5KlkwQkgkgtNCWCokq7cSmSt4305o2ZFbkJgzPkj1lnIe0CUhcRUGcyBznvHZ2aCRl5ESkLuKkQuIqlMwgg0mF4ciTeMhYyISG0AT4kSnRKQMmn5qwHZO1WKPJziLzia/zIZOnjJyITJ93xEmJ2FWIfJEqEQBpA80psAaGwoBMXCsCPBRD9OvChOVHgs48gfFU/MRDryIicoACORGZltrQZ1IL5JIyZTdI0RaJfSuBNTSHjqbAEFoLg52UnSM0MLwzpDWKIHVQZi6XIYCx7J2IzG2OGRharW9zxzUFciIyfd6TuDLOR0TxMMX0PgpRBwPVNO1pQ9Z6mkJDe8ZSjA3NKcguiA8N4gDfPwxkyZm0Vq2KzAOaI9dYmiMnIvXhY7yvkrgKZTdE0VWpJB7vITSerHWEI0+cxMPhSsT54QgDZO1EA68iIvJ6ysiJyLSNFgb2PiFxEY7a/LZMYFiUjunMVIi9pexyxM5QcdC7rYWlv34Zt3zZuLbs4haygcPhCYNa7Tl9OReZy+pf903/5idPgZyI1InDe4cnIknKREEtmMsGjvZshVToSLwhbTKUnaEUh/DyDjgokKNzASlbIvGe0KZrqTs91UXmrBkZWq1vc8c1BXIiUh++tuOicxFRUmQoVWAobqWcWByGIEhoS1epOEslsbRlK5CdYJsu7wkMpK3VFl0iIkehQE5E6sLja8WBiWvDqybB+1rpEYsnCGrfsWNnKDtDkpiJG3p1D4Ym2tMhhgCwI8Or+o4uMhd5PwOLE/TPfdL0dVdE6sYDBoO1AVmfpyllWZiusrCjSOsJVTrahskFCdXE0jvcRPLCrkPbiB3GQGgNgc0oKycicgR6QopI3bw+xxYTESUegyfV7Egta2HB+QFnnbiH5c0lYmco/tpjt78yvo2lnaSNo5J4MrYZY1JgDpO9E5GG83hcnY/pZOC/9KUvYYzhYx/72Ni5crnM+vXrWbRoEc3NzVxxxRX09fWNe9/27du57LLLyOfzdHV18clPfpI4nvuFyRXIiUjdee+JTUQl8QzGKaoDFleogDVkFji6mossypYJ0h5KpfFvDkOsqT3EQzIYPaZE5rTRodW6HlPsy09/+lP+4i/+gnPOOWfc+Ztuuolvf/vbfPOb3+TJJ59k586dvPe97x17PUkSLrvsMqrVKk899RSPPfYYjz76KLfddts07szs0BNSROrCYGqZMxMQBGlyrpmmlCUXJLWFp5WYZKBCPGxIHKRCh7EeSuXxDfXtxXlDJlAWTkQmb2hoiKuuuoq//Mu/ZMGCBWPnBwYG+J//839yzz338O53v5sLLriARx55hKeeeoof//jHADz++OP84he/4K//+q9ZuXIll156KV/4whe4//77qVarjfpIk6JATkTqwxgMAdZmSAdNtNFCRxZObC+QPz0keFMXYU8zQdYTu4BCOU1lKISB4XHNJK8MUHGWTACeRFt1icxxbgYOTy1LVigUxh2VSuWw/Vi/fj2XXXYZa9asGXd+8+bNRFE07vwZZ5zBySefzKZNmwDYtGkTZ599Nt3d3WPXrF27lkKhwHPPPTflezMbtGpVRKbNUAviMAGGAIMl9gmlBKrVEGwMi9qgcwHpOGFBf5GhaopKJYSh8Rk5E1pib6gko23r+6bIXOapTaeod6NbtmyhrW18iaLbb7+dz33uc4dc/o1vfIOf/exn/PSnPz3ktd7eXtLpNO3t7ePOd3d309vbO3bN64O40ddHX5vLFMiJSH0YizEhQZAhNBkAyjHsKubpfHU3mRMG4MRuTHc7TUt20jpQxXuD6z8okMuGJB7KiRspPyIib0QrV67kiSeeGHcuk8kcct0rr7zCf/kv/4UNGzaQzWZnq3tzhr7qikhdGBNgTEAmbKbdnsCJuTwnNsHCXLm2r+pAEXbvh1IV0xTQ2loik4lx/RH21y/XGqlUSPrKRM6SuNrQqojMbd4f2N2hXocHgiCgtbV13DFRILd582Z27drF+eefTxiGhGHIk08+yX333UcYhnR3d1OtVunv7x/3vr6+Pnp6egDo6ek5ZBXr6M+j18xVCuREZPqMwZoM1qSwJkXKZ2gODd2ZmK7uIVLLm2HxQshlIDAYC+mcI9MUQ2hgbz922zbsc88ztNNScrWFDrGvaI6ciBzRxRdfzDPPPMOWLVvGjgsvvJCrrrpq7M+pVIqNGzeOvWfr1q1s376d1atXA7B69WqeeeYZdu06UNtyw4YNtLa2ctZZZ836ZzoWGloVkWkxGMASBBmsTWEISExCKfEMxRYXG0w2BR0L8c3NmMBi9hexqSEAbFNYC/Cch6EixeEMxdhQdY6qL+G9m4Gy8SJSL6O13+rpWOrItbS08OY3v3ncuaamJhYtWjR2/rrrruPmm29m4cKFtLa28pGPfITVq1dz0UUXAXDJJZdw1llncfXVV3P33XfT29vLLbfcwvr16yfMAs4lCuREZNqMCUinWkjZLE3BItqSVqwxDMaGvt3NZLcNEC4ewJ+wBJ9OYYsl7LYhqv2WcCDGDpcgk4bEU4pChmLYF1WIXRHvo0Z/PBE5gpnYoqve7f3Zn/0Z1lquuOIKKpUKa9eu5c///M/HXg+CgO985zvccMMNrF69mqamJq655hruuOOO+nZkBiiQE5G6CG0Ka0OaXTvd2SzLmj0n5CJa8+XakyZOwDnIN0HHIoL2ndDvKO825J7vxbb34/YWGagsohRD0ZZwLgYNrYrIMfrBD34w7udsNsv999/P/ffff9j3LF26lO9+97sz3LP6UyAnInVhR1etEpCxhkXphJOah1hwakR4ykJY2AapFAC+pYWgp4XMwH7Keyyllx3GDlMaTLGrkqaceKKgSuxqNaOms12PiMwsPyNDqzJZCuREpA4sgU1hCSmbMoVqwr4ooBilIGVgUSvu9TWaLJBLESwISVdjyv0B5VKa3UN5dpUDClFMyRZIXBXvtXJVZC6biaFVmTytWhWR6TEGYyypIEfKZGhxLTSlAgKgmlh8yUGUQHjge6O3tULAyf6YasESVQKiKKAchwzHUExiqn6IxM3trXFERBpNGTkRqYOAlM2QMjm6U3nOaIMLO/bTdeIQqRW1HR1Gh1UBaG0Bayjttuzc3cb+SpqyC9hbDdhV9gwwSMUPkbgymiMnMrc1etXqG50CORGZHu+BhIQD2bMAagV/l2Xh1BNxJ5xw6PuacwSpAsU45LVymkJs6K9Cf7VKyQ6BSYBEYzYiIkegQE5Eps37mIQSjpihKGZ/lKFUzNCaxNDWOj4bNyqqzX2zxlNMDIMRDFY9RVelaoc1rCoyT3jvcXX+wqXvb5OnQE5E6sL7hMBkaA5CFqQ8Le1l7JIOXFfXIdfa7a8Q/2ove3c3sbucZiCCochTjBNKpkzVl0hGiwGLyJzmqf9QqIZWJ0+BnIjUgcUbT8Y3sbgp4M3tAzS/YxHuovMnvtx74n7HnlKOvkrI7rJjsJow7KoUg0HiuITmxomIHJ0CORGZNmMs4Mj6LM0hLGwtwfLlcLitbeIYFxlKScBgBP2ViH6GGbYFhtweoqSEMR4FcyJzn6P+/1KVj5s8BXIiUhdhUAvaijEUhrMsKlcmvM7s2AnP/zsDe3MMxgGVBCo+oWyLlBikmgySuApeQZzIvKCCwI2lOnIiUhdBEJLxafIhtOTKuBMWT3id6e0jeqnAzsFmdpUD+iNXmxdnyngf470bCeLi2f0AIiLzkDJyIjJt1mTwPqEtzHJqc5VFqwJ8c/PEF1djooJhXyVkX7U2rFqw+yi5ASJfwvkE5xKMMbP7IURkSjweX/dlpsrJTZYCORGZHhMQBnnSYZ6ObMjytj2Y80+b8DFs+vfjd+xnqD/NYBxQTqDsY0pugFK8jzgpkbgITzQyR05ERI5EgZyITJu1Ic1hJ7kArPWQTLw/qnn+JUq/KrFzoIN9VUMxclSJajNsvMP5BE+Ec1EtI6fyIyJz3szs7CCTpUBORKbFYAhshiazgHwImUyMb26a+OLhEkP70/SV0+wue/ZFVYZsYVzx39oQjcMa1ZISmQ9mZrGD/u1PlgI5EZkygwETkg3byZgsS7IJ7ecF+MUTL3TAQRSFFOOAwcjRbwYY9LupxIXaSlX/um25zEwUNRAROb4okBORabE2Q962kyFNVzbCnL7ksN+l4xf2s3t4EYXYUHWOmATvY5yLSNzoqtUEj9diB5F5wo/k5OrdpkyOAjkRmTpjsCakmQ5abJb2TBnaT5jwUrttG3tfTvFKMUtfGQaTCnFQwY0OzHhfC+JG5sUpkBOZHzRHrrFUR05EpsRQC7SsTdPmFrAwk6YtX8Z1dEx4vc9lASg5Q6GSsDfYTSHpo5oM4tzrhlRH6sRbo8eTiMjRKCMnItNgsSak1WTJpgz59io05Se+9HWBmQMiXyZKhoiSYZyvjq9D5UeGVr3XEIvIHKedHRpLgZyITEtgM3RlM6QDS/bkwz9S/MbN/Lyvg38fMgxEVWJTJvERiaviffVA0DYS0GloVWR+qA2tao5co2jsQkSmzGAIbZoFGUsuBLvoMNm4wiDlX1d5tRTSV4rZa/dScYM4FzG6MrX24B79MyiOExE5OmXkRGTqjMWaFK0pQzYwsOAw23K1tpBuN6RsLWCrmjLR6C4OPh7LwtWycqNtK5ITmQ88Dm/qXSpIGbnJUkZORKbFmpB84GlKG+hYcNjrfOJxIyOntSHVCs6X8C7Gk4A/dDcIDa+KiByZMnIiMi2j9aPS1uNbJ87I2V8+zysvtPDKsGeX76fo941k4/xIEDfxjJjagocZ7LyITJt2dmgsBXIiMnUjNd+cgYz1kM1NfN3u/ewq5thVjthveqlEBTyvnx8Ho7m31z++rbUkbuJ9W0VkbtBih8bS0KqITIv3Dochax0+P/FiB7/8JLryJXJBgMXgfFJb6DC6QvVwjWtkVUTkiOZFILdt2zauu+46li1bRi6X49RTT+X222+nWq2Ou+7nP/85v/Vbv0U2m+Wkk07i7rvvblCPRd44PAnOWKwBUqmJLzIW5w2x9yQ+GgnikiMOq4LmyInMB35sb4f6HZpTMXnzYmj1+eefxznHX/zFX7BixQqeffZZrr/+eoaHh/nKV74CQKFQ4JJLLmHNmjU8+OCDPPPMM3zwgx+kvb2dD33oQw3+BCLHn1r45fHeUXXgjvDcNdt38O+DTbyW7Gco2kWcDNX2VR3X3qEJOAVyInOfNw5X51Wr3iiQm6x5EcitW7eOdevWjf28fPlytm7dygMPPDAWyP3N3/wN1WqVhx9+mHQ6zW/8xm+wZcsW7rnnHgVyIjPGESUlBmMYjAMolSA3wTw55xmMA/awnXK0D+8qE37fHg3mRl+zdl4MGoiINMy8fUoODAywcOHCsZ83bdrEO97xDtLp9Ni5tWvXsnXrVvbv33/YdiqVCoVCYdwhIpPnfMxg1VFMDKZYnPiixZ2kreOM3lN4cesutm596bDtvT7Ac67etalEpN5GFzvU839a7DB58zKQe/HFF/nqV7/Khz/84bFzvb29dHd3j7tu9Ofe3t7DtnXXXXfR1tY2dpx00kkz02mR45GvDa1G1YTYA3E08WWZDACFwSrVqEKxVJ5U81E0cXsiIlLT0EDuM5/5DMaYIx7PP//8uPfs2LGDdevWceWVV3L99ddPuw+f/exnGRgYGDteeeWVabcp8oZhDB7HcJwwUHKYcnXiyyoVUnj2lqo4F4N3hwRphvFz5JxzysiJzAP1z8cpI3csGjpH7uMf/zjXXnvtEa9Zvnz52J937tzJu971Lt72trfx0EMPjbuup6eHvr6+cedGf+7p6Tls+5lMhsxItkBEpmY4iSlXE6hOHMgRxdgkpuITnI/xeKIoInW4Va7UsnEGowe6yBznR0oC17tNmZyGBnKdnZ10dnZO6todO3bwrne9iwsuuIBHHnnkkEnQq1ev5o//+I/H/cdhw4YNnH766SxYcPhtg0SkPtqDIyxd3dfP7qJhgCH8SBHhgzNyB69a1bCqiMjRzYs5cjt27OCd73wnJ598Ml/5ylfYvXs3vb294+a+/af/9J9Ip9Ncd911PPfcc/zt3/4t//2//3duvvnmBvZc5PjnvaPiY1Y2D8Phgq+hMgMlz7AZBhwGM5JxO6it1/1ZgZzI/OBI6n4oIzd586L8yIYNG3jxxRd58cUXOfHEE8e95kcqw7e1tfH444+zfv16LrjgAjo6OrjttttUekRkFlSosvLsHZA6zGIhC4FLSIjw3o0NrR7pUV17XQ9zkbluJoZWVRB48uZFIHfttdcedS4dwDnnnMO//uu/znyHRGSM9w5vHJm3dOHbWw9zleE3F+3iS6Yy8sA/dLHDwZSRExE5unkxtCoic5T3eB9TMiWi/3cHZugwdeSA0/5DQuIPBGcK5ESOD6M7O9TzUDZ+8hTIici0eBzDpp8XftwCA4MTX5TPwPkrxg2/xFF8xHYP3ktZREQONS+GVkVk7vI+ouKHiCsewmDii4plePlVIl8cW7V6tEBNGTmR+aFW+S2pa5v1n3N3/FIgJyLTVAve+osBHKaArx+qMPT9PVR9Ce8j8J7oMLtAjFIgJzI/+JFNuurbpoZWJ0tDqyIyLcZYAkJKyWGycYDJpUm1OLxP4PXDq/HEw6va1UFEZHIUyInI1BmDwRKaLJ3ZMn5J98TXLcgTtBhCm8GYAwMBh8u6HS7AE5G5x3uH80ldj2PNyN1111285S1voaWlha6uLi6//HK2bt067ppyucz69etZtGgRzc3NXHHFFYfsCLV9+3Yuu+wy8vk8XV1dfPKTn5zzzyMFciJSF8YAlfLEL2Yy2HxAxjQT2KaRiw/UgTzY4c6LyNwzOrRaz+NY68g9+eSTrF+/nh//+Mds2LCBKIq45JJLGB4eHrvmpptu4tvf/jbf/OY3efLJJ9m5cyfvfe97x15PkoTLLruMarXKU089xWOPPcajjz7KbbfdVq9bNSOM1xNznEKhQFtbG7V5PwfXnReRIznzzDPJ5XKHnK9UKjz33HOHnD/jjDPI5/OTvl5EJsMDCQMDA7S2Hq62Y310d3cTls4gE7bXtd39pee58urfPmRf9cnavXs3XV1dPPnkk7zjHe9gYGCAzs5Ovv71r/Mf/+N/BOD555/nzDPPZNOmTVx00UV873vf4z3veQ87d+6ku7s2uvDggw/y6U9/mt27d5NOp+v2+epJGTkRERGZsloWLanz4UiShEKhMO6oVCqT6tPAwAAACxcuBGDz5s1EUcSaNWvGrjnjjDM4+eST2bRpEwCbNm3i7LPPHgviANauXUuhUJjTXywVyImIiMics2XLFtra2sYdd91111Hf55zjYx/7GG9/+9t585vfDEBvby/pdJr29vZx13Z3d4/t297b2zsuiBt9ffS1uUrlR0RERGTK/Eglufq26Vm5ciVPPPHEuPOZTOao712/fj3PPvssP/rRj+rap7lKgZyIiIhM2UzUkQNPEATHPMfvxhtv5Dvf+Q4//OEPOfHEE8fO9/T0UK1W6e/vH5eV6+vro6enZ+yan/zkJ+PaG13VOnrNXKShVREREZnXvPfceOON/P3f/z3f//73WbZs2bjXL7jgAlKpFBs3bhw7t3XrVrZv387q1asBWL16Nc888wy7du0au2bDhg20trZy1llnzc4HmQJl5ERERGTKvB8t9l3PNo+toMb69ev5+te/zj/8wz/Q0tIyNqetra2NXC5HW1sb1113HTfffDMLFy6ktbWVj3zkI6xevZqLLroIgEsuuYSzzjqLq6++mrvvvpve3l5uueUW1q9fP6kh3UZRICciIiJT5mZojtyxeOCBBwB45zvfOe78I488wrXXXgvAn/3Zn2Gt5YorrqBSqbB27Vr+/M//fOzaIAj4zne+ww033MDq1atpamrimmuu4Y477pjWZ5lpCuRERERkXptMBi+bzXL//fdz//33H/aapUuX8t3vfreeXZtxCuQOcuCXQXWSRY5VkiQkyaFDLLVzh/6bOtbrRWQyav92Zq/ef62OXL3blMlRIHeQwcHBkT/pl0jkWP3qV784putfeOGXM9QTERkcHBzZqWhmeRzeN3Zo9Y1MgdxBlixZwiuvvEJLSwvGHPsWXYVCgZNOOolXXnllxrdGmet0Lw7QvThA96JG9+EA3YsD6nEvvPcMDg6yZMmSOvdO5iIFcgex1o6rPTNVra2tb/gH0ijdiwN0Lw7QvajRfThA9+KA6d6L2cjEjXIjJYHrSRm5yVMdOREREZF5Shk5ERERmTLvk7rXkWPWFmrMfwrk6iyTyXD77bfP6eKBs0X34gDdiwN0L2p0Hw7QvThgft4LX/ctujS0OnnGz976ZBERETmOdHd3Ux3uJAya6trucPlVPnDNZTz00EN1bfd4pIyciIiITFlti656l+xSjmmyFMiJiIjIlPkZKAisodXJ06pVERERkXlKGTkRERGZshkZWtX0/UlTRq6OvvjFL/K2t72NfD5Pe3v7hNcYYw45vvGNb8xuR2fBZO7F9u3bueyyy8jn83R1dfHJT36SOI5nt6MNcMoppxzyO/ClL32p0d2aFffffz+nnHIK2WyWVatW8ZOf/KTRXZp1n/vc5w75+z/jjDMa3a1Z8cMf/pDf/d3fZcmSJRhj+Na3vjXude89t912G4sXLyaXy7FmzRpeeOGFxnR2Bh3tPlx77bWH/I6sW7euMZ2VOU+BXB1Vq1WuvPJKbrjhhiNe98gjj/Daa6+NHZdffvnsdHAWHe1eJEnCZZddRrVa5amnnuKxxx7j0Ucf5bbbbpvlnjbGHXfcMe534CMf+UijuzTj/vZv/5abb76Z22+/nZ/97Gece+65rF27ll27djW6a7PuN37jN8b9/f/oRz9qdJdmxfDwMOeeey7333//hK/ffffd3HfffTz44IM8/fTTNDU1sXbtWsrl8iz3dGYd7T4ArFu3btzvyP/6X/9rFnt4bLz3Y1m5uh2aIzdpGlqto89//vMAPProo0e8rr29nZ6enlnoUeMc7V48/vjj/OIXv+D//t//S3d3NytXruQLX/gCn/70p/nc5z5HOp2exd7OvpaWluP+d+Bg99xzD9dffz1/+Id/CMCDDz7IP/3TP/Hwww/zmc98psG9m11hGL7h/v4BLr30Ui699NIJX/Pec++993LLLbfwe7/3ewB87Wtfo7u7m29961u8//3vn82uzqgj3YdRmUxm3vyO1DboUh25RlFGrgHWr19PR0cHb33rW3n44Yd5I5by27RpE2effTbd3d1j59auXUuhUOC5555rYM9mx5e+9CUWLVrEeeedx5e//OXjfki5Wq2yefNm1qxZM3bOWsuaNWvYtGlTA3vWGC+88AJLlixh+fLlXHXVVWzfvr3RXWq4l19+md7e3nG/I21tbaxateoN+Tvygx/8gK6uLk4//XRuuOEG9u7d2+guyRyljNwsu+OOO3j3u99NPp/n8ccf54/+6I8YGhriox/9aKO7Nqt6e3vHBXHA2M+9vb2N6NKs+ehHP8r555/PwoULeeqpp/jsZz/La6+9xj333NPors2YPXv2kCTJhH/nzz//fIN61RirVq3i0Ucf5fTTT+e1117j85//PL/1W7/Fs88+S0tLS6O71zCj/+4n+h053p8JB1u3bh3vfe97WbZsGS+99BL/9b/+Vy699FI2bdpEEASN7t4hPFrs0EgK5I7iM5/5DH/6p396xGt++ctfTnqy8q233jr25/POO4/h4WG+/OUvz4tArt734nhyLPfm5ptvHjt3zjnnkE6n+fCHP8xdd901z7blkal4/ZDaOeecw6pVq1i6dCn/+3//b6677roG9kzmitcPI5999tmcc845nHrqqfzgBz/g4osvbmDPJlab11bvOnL1LjB8/FIgdxQf//jHufbaa494zfLly6fc/qpVq/jCF75ApVKZ8/8Rr+e96OnpOWTFYl9f39hr88107s2qVauI45ht27Zx+umnz0DvGq+jo4MgCMb+jkf19fXNy7/vempvb+dNb3oTL774YqO70lCjvwd9fX0sXrx47HxfXx8rV65sUK/mhuXLl9PR0cGLL744JwM5aSwFckfR2dlJZ2fnjLW/ZcsWFixYMOeDOKjvvVi9ejVf/OIX2bVrF11dXQBs2LCB1tZWzjrrrLr8f8ym6dybLVu2YK0duw/Ho3Q6zQUXXMDGjRvHVmk759i4cSM33nhjYzvXYENDQ7z00ktcffXVje5KQy1btoyenh42btw4FrgVCgWefvrpo1YCON69+uqr7N27d1yAO5fUdnbQFl2NokCujrZv386+ffvYvn07SZKwZcsWAFasWEFzczPf/va36evr46KLLiKbzbJhwwbuvPNOPvGJTzS24zPgaPfikksu4ayzzuLqq6/m7rvvpre3l1tuuYX169fPi6B2qjZt2sTTTz/Nu971LlpaWti0aRM33XQTH/jAB1iwYEGjuzejbr75Zq655houvPBC3vrWt3LvvfcyPDw8tor1jeITn/gEv/u7v8vSpUvZuXMnt99+O0EQ8Ad/8AeN7tqMGxoaGpd5fPnll9myZQsLFy7k5JNP5mMf+xh/8id/wmmnncayZcu49dZbWbJkyXFXoulI92HhwoV8/vOf54orrqCnp4eXXnqJT33qU6xYsYK1a9c2sNcyZ3mpm2uuucZT+xox7njiiSe8995/73vf8ytXrvTNzc2+qanJn3vuuf7BBx/0SZI0tuMz4Gj3wnvvt23b5i+99FKfy+V8R0eH//jHP+6jKGpcp2fB5s2b/apVq3xbW5vPZrP+zDPP9Hfeeacvl8uN7tqs+OpXv+pPPvlkn06n/Vvf+lb/4x//uNFdmnXve9/7/OLFi306nfYnnHCCf9/73udffPHFRndrVjzxxBMTPheuueYa7733zjl/6623+u7ubp/JZPzFF1/st27d2thOz4Aj3YdisegvueQS39nZ6VOplF+6dKm//vrrfW9vb6O7PaGuri6fTZ/g89nldT3CoN1ff/31jf5484LxXktDRERE5Nh1d3czsD/A2vqOpETxfv7wg7/PQw89VNd2j0eqIyciIiIyT2mOnIiIiEyZx9d9sYN2dpg8BXIiIiIyZaP7o9a50fq2dxzT0KqIiIjIPKWMnIiIiEzZTGzRpaHVyVNGTkRERGSeUkZOREREpsGDdnZoGAVyIiIiMnV+Brbo0mKHSdPQqoiIiMg8pYyciIiITJmfgaFVLXaYPGXkRGTG7d69m56eHu68886xc0899RTpdJqNGzc2sGciMl2jdeTqeWiO3OQpIyciM66zs5OHH36Yyy+/nEsuuYTTTz+dq6++mhtvvJGLL7640d0TEZm3FMiJyKz4nd/5Ha6//nquuuoqLrzwQpqamrjrrrsa3S0RmTYHJHVuUxm5yVIgJyKz5itf+QpvfvOb+eY3v8nmzZvJZDKN7pKITFNtKNTUuU0FcpOlOXIiMmteeukldu7ciXOObdu2Nbo7IiLznjJyIjIrqtUqH/jAB3jf+97H6aefzn/+z/+ZZ555hq6urkZ3TUSmpf4ZOQ2tTp4yciIyK/74j/+YgYEB7rvvPj796U/zpje9iQ9+8ION7paIyLymQE5EZtwPfvAD7r33Xv7qr/6K1tZWrLX81V/9Ff/6r//KAw880Ojuich0eA/e1fdQRm7SNLQqIjPune98J1EUjTt3yimnMDAw0KAeiUi91Ir31jvwUiA3WcrIiYiIiMxTysiJiIjINNR3e64aZeQmS4GciIiITI/qvjWMhlZFRERE5ill5ERERGQa/AwMhCrDN1nKyImIiMiU7Nq1i5kKuoIgmJF2jzcK5ERERGSKDLXFDvUM5mrlTFQwfHKM1860IiIiMgWFQoG2tjZqeaF65YYSALyfidWwxx9l5ERERGRKWltb+R//439Qv6xcLRv30ksv1qGtNwZl5ERERGTKoiginU5Tn6ycsnHHShk5ERERmbJUKsXf/d3fMf2sXO39e/fuqU/H3iCUkRMREZFp8d5jraW2+GEqq009tWycxfukrn073ikjJyIiItNijGHTpk2MznE7drX3lErD9ezWG4ICOREREZm2iy66iAPlSI6FBxx//dd/TTabrX/HjnMaWhUREZG6ePHFFznttNOoDa+aSb7LAY4kSUaGZ+VY6I6JiIhIXaxYsYJjy8rVsnHf//73FcRNkTJyIiIiUjd79uyhs7OTyZUjUbmR6VL4KyIiInXT0dFBLbw4WjmS2sKIZ599Zlb6dbxSRk5ERETqqlQqkc/nOXJWTtm4elBGTkREROoql8vx2GOPcfisXC0bt3Pnjtnt2HFIGTkRERGpO+ccQRBwaFZutPivUTauDpSRExERkbqz1rJhwwYOzcrV/lwoDDSiW8cdBXIiIiIyI9asWcP4ciS1ciMPPPAALS0tjevYcURDqyIiIjJjfv7zn3PuuedSKxJcC+SiKCIMwwb37PiguygiIiIz5pxzzuFAVs7zD//wDwri6kgZOREREZlRO3bs4MQTTwRqiyCMmez2XXI0ColFRERkRp1wwgls3ryZrq4uBXF1poyciIiIyDylVasiIiIi85QCOREREZF5SoGciIiIyDylQE5ERERknlIgJyIiIjJPKZATERERmacUyImIiIjMUwrkREREROap/x+2hXwQcvl3JQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data.plot_field(field_monitor_name=\"field\", field_name=\"E\", val=\"abs^2\", vmax=1500)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "312ceacd",
   "metadata": {},
   "source": [
    "Calculate those FOMs and plot the results. Since the signal port is the left waveguide of the bottom MMI, CMRR$_I$ and CMRR$_Q$ are expected to be slghtly different. The device performance according to the insertion loss, CMRR, and Imbalance is comparable to the case with input from the LO port. In addition, from the phase simulation, we know the phase error is going to be small too. This means the overall design of the 90 degree optical hybrid works very well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "46801e77",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T23:58:19.082711Z",
     "iopub.status.busy": "2023-03-27T23:58:19.082406Z",
     "iopub.status.idle": "2023-03-27T23:58:19.642919Z",
     "shell.execute_reply": "2023-03-27T23:58:19.642289Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 600x1000 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "calculate_FOM(sim_data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "33b24fec",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "0861d7e41987404787e1f9accdb53b51": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "1c0952da300b46d1ace4be951b24ec98": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_274ed9b033264aadb0041f9d088be6cf",
       "msg_id": "",
       "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; font-weight: bold\">\u2193</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> \u2022 <span style=\"color: #008000; text-decoration-color: #008000\">10.3/10.3 MB</span> \u2022 <span style=\"color: #800000; text-decoration-color: #800000\">13.4 MB/s</span> \u2022 <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;32m\u2193\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100.0%\u001b[0m \u2022 \u001b[32m10.3/10.3 MB\u001b[0m \u2022 \u001b[31m13.4 MB/s\u001b[0m \u2022 \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "274ed9b033264aadb0041f9d088be6cf": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "30d61ecd7ffe4cabb485fa67dadd1be9": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_eea7bd70a748480bad6d5a2e60389417",
       "msg_id": "",
       "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: #800000; text-decoration-color: #800000; font-weight: bold\">\u2191</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> \u2022 <span style=\"color: #008000; text-decoration-color: #008000\">378.4/378.4 kB</span> \u2022 <span style=\"color: #800000; text-decoration-color: #800000\">1.1 MB/s</span> \u2022 <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m\u2191\u001b[0m \u001b[1;34msimulation.hdf5\u001b[0m \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100.0%\u001b[0m \u2022 \u001b[32m378.4/378.4 kB\u001b[0m \u2022 \u001b[31m1.1 MB/s\u001b[0m \u2022 \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "31d893223548411488f9f630fde45970": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_31dff594cb124942a7f6d0adad205f14",
       "msg_id": "",
       "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: #800000; text-decoration-color: #800000; font-weight: bold\">\u2191</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.json</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> \u2022 <span style=\"color: #008000; text-decoration-color: #008000\">8.5/8.5 kB</span> \u2022 <span style=\"color: #800000; text-decoration-color: #800000\">?</span> \u2022 <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m\u2191\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100.0%\u001b[0m \u2022 \u001b[32m8.5/8.5 kB\u001b[0m \u2022 \u001b[31m?\u001b[0m \u2022 \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "31dff594cb124942a7f6d0adad205f14": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "361c610288dd44a782896f0084cd6433": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_44328400343a4bbe84406c15a1113b16",
       "msg_id": "",
       "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\">\ud83d\udeb6 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'mmi'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m\ud83d\udeb6 \u001b[0m \u001b[1;32mStarting 'mmi'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "3a7e6503cb3549f592b98e62f9f49f35": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "44328400343a4bbe84406c15a1113b16": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "489bca269b664357aa474e42ab11aa21": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "56bfa1c1d2dc4fdd9bc8c8711f72ef2b": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "60fc620684fb4a6c911a6dcdaac4540b": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "6178849e85bc4b01884e1c62f9c95c91": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "69868875f7f54b668811b87f060df7bd": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_60fc620684fb4a6c911a6dcdaac4540b",
       "msg_id": "",
       "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\">% done (field decay = 6.00e-06) <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "% done (field decay = 6.00e-06) \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "6b9d423654554e77a8196ede3d3bfff9": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "6bc1ecaeeac04cb296bcf3b19d9c6ad1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "6f8d93fbad5d46019748b7986e695356": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_fd7af580164745dab7251d8a52d4898f",
       "msg_id": "",
       "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; font-weight: bold\">\u2193</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> \u2022 <span style=\"color: #008000; text-decoration-color: #008000\">74.7/74.7 MB</span> \u2022 <span style=\"color: #800000; text-decoration-color: #800000\">47.2 MB/s</span> \u2022 <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;32m\u2193\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100.0%\u001b[0m \u2022 \u001b[32m74.7/74.7 MB\u001b[0m \u2022 \u001b[31m47.2 MB/s\u001b[0m \u2022 \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "703269ad922849108a23c17c8a9e6f0e": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_d208c6ca031844fc8ae83d4d7ec14c84",
       "msg_id": "",
       "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; font-weight: bold\">\u2193</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> \u2022 <span style=\"color: #008000; text-decoration-color: #008000\">74.7/74.7 MB</span> \u2022 <span style=\"color: #800000; text-decoration-color: #800000\">47.3 MB/s</span> \u2022 <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;32m\u2193\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100.0%\u001b[0m \u2022 \u001b[32m74.7/74.7 MB\u001b[0m \u2022 \u001b[31m47.3 MB/s\u001b[0m \u2022 \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "747235970d644dd5a5f4433466fa587d": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_a505b86ac39a47e8a14e9260401d4651",
       "msg_id": "",
       "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\">% done (field decay = 3.25e-06) <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "% done (field decay = 3.25e-06) \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "7b3d0f3398ac41b7a9e77e6ff1ca76ea": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_56bfa1c1d2dc4fdd9bc8c8711f72ef2b",
       "msg_id": "",
       "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: #800000; text-decoration-color: #800000; font-weight: bold\">\u2191</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> \u2022 <span style=\"color: #008000; text-decoration-color: #008000\">112.2/112.2 kB</span> \u2022 <span style=\"color: #800000; text-decoration-color: #800000\">?</span> \u2022 <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m\u2191\u001b[0m \u001b[1;34msimulation.hdf5\u001b[0m \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100.0%\u001b[0m \u2022 \u001b[32m112.2/112.2 kB\u001b[0m \u2022 \u001b[31m?\u001b[0m \u2022 \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "868bd78cbc224570901b2b3533327a0b": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_e1167247552245f7bb5495b23b85383f",
       "msg_id": "",
       "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\">% done (field decay = 1.36e-03) <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "% done (field decay = 1.36e-03) \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "8ca5dc94593a431fb22e75e5c764532e": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_b1c6490780804a7885a8f0ee158d9f2c",
       "msg_id": "",
       "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\">\ud83c\udfc3 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Finishing 'mmi'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m\ud83c\udfc3 \u001b[0m \u001b[1;32mFinishing 'mmi'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "8d70895065144b8a923603c7d6e57e57": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "95d2bc9d2d794a5ab0044a3ae769afd9": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_489bca269b664357aa474e42ab11aa21",
       "msg_id": "",
       "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\">\ud83c\udfc3 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Finishing 'optical_hybrid_signal_input'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m\ud83c\udfc3 \u001b[0m \u001b[1;32mFinishing 'optical_hybrid_signal_input'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "96d9c56c4e37427cafa7dc9d1b144951": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_6178849e85bc4b01884e1c62f9c95c91",
       "msg_id": "",
       "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: #800000; text-decoration-color: #800000; font-weight: bold\">\u2191</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.json</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> \u2022 <span style=\"color: #008000; text-decoration-color: #008000\">13.3/13.3 kB</span> \u2022 <span style=\"color: #800000; text-decoration-color: #800000\">?</span> \u2022 <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m\u2191\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100.0%\u001b[0m \u2022 \u001b[32m13.3/13.3 kB\u001b[0m \u2022 \u001b[31m?\u001b[0m \u2022 \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "a24b9eaf69b346178871d3d375e83200": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_6bc1ecaeeac04cb296bcf3b19d9c6ad1",
       "msg_id": "",
       "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: #800000; text-decoration-color: #800000; font-weight: bold\">\u2191</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> \u2022 <span style=\"color: #008000; text-decoration-color: #008000\">378.4/378.4 kB</span> \u2022 <span style=\"color: #800000; text-decoration-color: #800000\">898.3 kB/s</span> \u2022 <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m\u2191\u001b[0m \u001b[1;34msimulation.hdf5\u001b[0m \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100.0%\u001b[0m \u2022 \u001b[32m378.4/378.4 kB\u001b[0m \u2022 \u001b[31m898.3 kB/s\u001b[0m \u2022 \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "a505b86ac39a47e8a14e9260401d4651": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "afc9241e24064a2480defcf077a50382": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_0861d7e41987404787e1f9accdb53b51",
       "msg_id": "",
       "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\">\ud83c\udfc3 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'optical_hybrid_signal_input'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m\ud83c\udfc3 \u001b[0m \u001b[1;32mStarting 'optical_hybrid_signal_input'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "b1c6490780804a7885a8f0ee158d9f2c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "c6e0f11cba9344dd9f193f3f539b696b": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_8d70895065144b8a923603c7d6e57e57",
       "msg_id": "",
       "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: #800000; text-decoration-color: #800000; font-weight: bold\">\u2191</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.json</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> \u2022 <span style=\"color: #008000; text-decoration-color: #008000\">13.3/13.3 kB</span> \u2022 <span style=\"color: #800000; text-decoration-color: #800000\">?</span> \u2022 <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
          "text/plain": "\u001b[1;31m\u2191\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;2;114;156;31m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[35m100.0%\u001b[0m \u2022 \u001b[32m13.3/13.3 kB\u001b[0m \u2022 \u001b[31m?\u001b[0m \u2022 \u001b[36m0:00:00\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "d208c6ca031844fc8ae83d4d7ec14c84": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "d7fab938f8a843e1a5c35a7de7f091cc": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_6b9d423654554e77a8196ede3d3bfff9",
       "msg_id": "",
       "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\">\ud83c\udfc3 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Finishing 'optical_hybrid_lo_input'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m\ud83c\udfc3 \u001b[0m \u001b[1;32mFinishing 'optical_hybrid_lo_input'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "e1167247552245f7bb5495b23b85383f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "eea7bd70a748480bad6d5a2e60389417": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "f3171fb880a6418484c64e2b2ffef2e5": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_3a7e6503cb3549f592b98e62f9f49f35",
       "msg_id": "",
       "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\">\ud83c\udfc3 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'optical_hybrid_lo_input'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m\ud83c\udfc3 \u001b[0m \u001b[1;32mStarting 'optical_hybrid_lo_input'...\u001b[0m\n"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "fd7af580164745dab7251d8a52d4898f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}