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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "46aeafc3",
+   "metadata": {},
+   "source": [
+    "# Dielectric to plasmonic waveguide coupler\n",
+    "\n",
+    "This notebook explores the design and simulation of a dielectric-to-plasmonic waveguide coupler using Tidy3D. Such couplers enable efficient transfer of optical signals from conventional silicon photonic waveguides to plasmonic waveguides, which support highly confined modes beyond the diffraction limit.\n",
+    "\n",
+    "The coupler features a silicon strip waveguide that gradually tapers into a metallic slot waveguide. We utilize Bayesian optimization to systematically refine the design for maximum coupling efficiency.\n",
+    "\n",
+    "<img src=\"./img/silicon_to_plasmonic.png\" alt=\"Schematic of the 2x2 MMI Power Splitter\"  width=\"500\"/>\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "eb612311-c32f-4cb7-bd2e-51e37e2fdac5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import tidy3d as td\n",
+    "import tidy3d.web as web"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ce93687a",
+   "metadata": {},
+   "source": [
+    "## Base Simulation Setup\n",
+    "\n",
+    "Define central wavelength/frequency, a wavelength range, and its mapped frequency grid.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "07616f4d-8c47-4750-b9ac-e1c1533c1761",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# define frequency and wavelength range\n",
+    "lda0 = 1.50\n",
+    "freq0 = td.C_0 / lda0\n",
+    "ldas = np.linspace(1.45, 1.55, 21)\n",
+    "freqs = td.C_0 / ldas\n",
+    "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "42827fab",
+   "metadata": {},
+   "source": [
+    "Load silicon, silica, and gold mediums from the built-in [material library](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/material_library.html) for the coupler stack.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "039c1e6e-ea86-4f90-b690-7ac4f448461f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "si = td.material_library[\"cSi\"][\"Palik_Lossless\"]\n",
+    "sio2 = td.material_library[\"SiO2\"][\"Palik_Lossless\"]\n",
+    "au = td.material_library[\"Au\"][\"Olmon2012crystal\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "370634d2",
+   "metadata": {},
+   "source": [
+    "Set static geometric parameters such as the plasmonic slot length, silicon/gold layer thickness, slot width, and so on.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "bc0ff241-9b5f-4964-b2d9-48051497506a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "l_slot = 1.5  # plasmonic waveguide length\n",
+    "h = 0.25  # both silicon and gold layer thicknesses are 250 nm\n",
+    "w_slot = 0.2  # metal slot width\n",
+    "w_si = 0.45  # silicon waveguide width\n",
+    "inf_eff = 1e2  # effective infinity\n",
+    "buffer = 0.6 * lda0  # buffer spacing to pad the simulation domain"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "06bf354e",
+   "metadata": {},
+   "source": [
+    "To streamline the design optimization process, we define a function `make_sim()` which accepts tunable design parameters including the taper angle, taper tip width, and gap size, and constructs a corresponding Tidy3D [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html#tidy3d.Simulation) object.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "1eabf77c-674a-4fb0-b77a-e9dc3f30b2ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# define the oxide layer\n",
+    "box = td.Structure(\n",
+    "    geometry=td.Box.from_bounds(rmin=(-inf_eff, -inf_eff, -inf_eff), rmax=(inf_eff, inf_eff, 0)),\n",
+    "    medium=sio2,\n",
+    ")\n",
+    "\n",
+    "# add a mode source for excitation\n",
+    "mode_spec = td.ModeSpec(num_modes=1, target_neff=3.47)\n",
+    "mode_source = td.ModeSource(\n",
+    "    center=(-0.9 * buffer, 0, h / 2),\n",
+    "    size=(0, 4 * w_si, 6 * h),\n",
+    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
+    "    mode_spec=mode_spec,\n",
+    "    mode_index=0,\n",
+    "    direction=\"+\",\n",
+    "    num_freqs=1,\n",
+    ")\n",
+    "\n",
+    "# add a field monitor to visualize the field distribution\n",
+    "field_monitor = td.FieldMonitor(\n",
+    "    center=(0, 0, h / 2), size=(td.inf, td.inf, 0), freqs=[freq0], name=\"field\"\n",
+    ")\n",
+    "\n",
+    "# extrusion arguments for polyslab\n",
+    "polyslab_args = dict(axis=2, slab_bounds=(0, h))\n",
+    "\n",
+    "\n",
+    "# function to create a simulation given the design parameters\n",
+    "def make_sim(theta, d_tip, l_gap):\n",
+    "    # calculate the taper length\n",
+    "    l_taper = (w_si - d_tip) / (2 * np.tan(theta))\n",
+    "\n",
+    "    # define the input waveguide structure\n",
+    "    vertices = [\n",
+    "        (-inf_eff, -w_si / 2),\n",
+    "        (0, -w_si / 2),\n",
+    "        (l_taper, -d_tip / 2),\n",
+    "        (l_taper, d_tip / 2),\n",
+    "        (0, w_si / 2),\n",
+    "        (-inf_eff, w_si / 2),\n",
+    "    ]\n",
+    "    wg_in = td.Structure(geometry=td.PolySlab(vertices=vertices, **polyslab_args), medium=si)\n",
+    "\n",
+    "    # define the output waveguide structure\n",
+    "    vertices = [\n",
+    "        (l_taper + 2 * l_gap + l_slot, d_tip / 2),\n",
+    "        (2 * l_taper + 2 * l_gap + l_slot, w_si / 2),\n",
+    "        (inf_eff, w_si / 2),\n",
+    "        (inf_eff, -w_si / 2),\n",
+    "        (2 * l_taper + 2 * l_gap + l_slot, -w_si / 2),\n",
+    "        (l_taper + 2 * l_gap + l_slot, -d_tip / 2),\n",
+    "    ]\n",
+    "    wg_out = td.Structure(geometry=td.PolySlab(vertices=vertices, **polyslab_args), medium=si)\n",
+    "\n",
+    "    # define the top plasmonic waveguide\n",
+    "    vertices = [\n",
+    "        (l_taper + l_gap, w_slot / 2),\n",
+    "        (l_taper + l_gap + l_slot, w_slot / 2),\n",
+    "        (inf_eff, np.tan(theta) * inf_eff),\n",
+    "        (-inf_eff, np.tan(theta) * inf_eff),\n",
+    "    ]\n",
+    "    gold_top = td.Structure(geometry=td.PolySlab(vertices=vertices, **polyslab_args), medium=au)\n",
+    "\n",
+    "    # define the bottom plasmonic waveguide\n",
+    "    vertices = [\n",
+    "        (l_taper + l_gap, -w_slot / 2),\n",
+    "        (l_taper + l_gap + l_slot, -w_slot / 2),\n",
+    "        (inf_eff, -np.tan(theta) * inf_eff),\n",
+    "        (-inf_eff, -np.tan(theta) * inf_eff),\n",
+    "    ]\n",
+    "    gold_bottom = td.Structure(geometry=td.PolySlab(vertices=vertices, **polyslab_args), medium=au)\n",
+    "\n",
+    "    # add a mode monitor to measure transmission\n",
+    "    mode_monitor = td.ModeMonitor(\n",
+    "        center=(2 * l_taper + l_slot + 2 * l_gap + 0.9 * buffer, 0, h / 2),\n",
+    "        size=mode_source.size,\n",
+    "        freqs=freqs,\n",
+    "        mode_spec=mode_spec,\n",
+    "        name=\"mode\",\n",
+    "    )\n",
+    "\n",
+    "    # define simulation\n",
+    "    sim = td.Simulation(\n",
+    "        center=(l_taper + l_gap + l_slot / 2, 0, h / 2),\n",
+    "        size=(2 * l_taper + 2 * l_gap + l_slot + 2 * buffer, w_si + 2 * buffer, h + 2 * buffer),\n",
+    "        grid_spec=td.GridSpec.auto(min_steps_per_wvl=20),\n",
+    "        boundary_spec=td.BoundarySpec(\n",
+    "            x=td.Boundary.absorber(num_layers=80),\n",
+    "            y=td.Boundary.absorber(),\n",
+    "            z=td.Boundary.pml(),\n",
+    "        ),\n",
+    "        run_time=5e-13,\n",
+    "        structures=[box, wg_in, wg_out, gold_top, gold_bottom],\n",
+    "        sources=[mode_source],\n",
+    "        monitors=[mode_monitor, field_monitor],\n",
+    "        symmetry=(0, -1, 0),\n",
+    "    )\n",
+    "\n",
+    "    return sim"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "43a151e5",
+   "metadata": {},
+   "source": [
+    "Build a first design instance and render a top view at `z = h/2` to confirm geometry, source, and monitor locations.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "4b97a3c6-8b5b-4802-a64c-3acd125f0cec",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sim = make_sim(theta=np.deg2rad(20), d_tip=0.1, l_gap=0.2)\n",
+    "sim.plot(z=h / 2, monitor_alpha=0.1)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "df3536a1",
+   "metadata": {},
+   "source": [
+    "Submit the initial simulation to the cloud to generate fields and monitor data for the baseline geometry.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "484d701f-d57d-4c73-a62b-da4c006c8b99",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:11:22 Eastern Daylight Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'test run'</span> with task_id             \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-ef0ea98f-26b9-4a2c-8b50-827a0a39c3e1'</span> and  \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:11:22 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'test run'\u001b[0m with task_id             \n",
+       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-ef0ea98f-26b9-4a2c-8b50-827a0a39c3e1'\u001b[0m and  \n",
+       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-ef0ea98f-26b9-4a2c-8b50-827a0a39c3e1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-ef0ea98f-26b9-4a2c-8b50-827a0a39c3e1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-ef0ea98f-26b9-4a2c-8b50-827a0a39c3e1'</span></a>.     \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
+       "\u001b[2;36m                               \u001b[0m\u001b]8;id=933873;https://tidy3d.simulation.cloud/workbench?taskId=fdve-ef0ea98f-26b9-4a2c-8b50-827a0a39c3e1\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=858921;https://tidy3d.simulation.cloud/workbench?taskId=fdve-ef0ea98f-26b9-4a2c-8b50-827a0a39c3e1\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[2;36m                               \u001b[0m\u001b]8;id=933873;https://tidy3d.simulation.cloud/workbench?taskId=fdve-ef0ea98f-26b9-4a2c-8b50-827a0a39c3e1\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=438469;https://tidy3d.simulation.cloud/workbench?taskId=fdve-ef0ea98f-26b9-4a2c-8b50-827a0a39c3e1\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=933873;https://tidy3d.simulation.cloud/workbench?taskId=fdve-ef0ea98f-26b9-4a2c-8b50-827a0a39c3e1\u001b\\\u001b[32m-ef0ea98f-26b9-4a2c-8b50-827a0a39c3e1'\u001b[0m\u001b]8;;\u001b\\.     \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/639eb096-a602-4b56-a502-cac1f18f9557\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                          \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=713502;https://tidy3d.simulation.cloud/folders/639eb096-a602-4b56-a502-cac1f18f9557\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                          \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "217e069fcc2e42a3962fc9faca5bf22a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:11:24 Eastern Daylight Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.318</span>. Minimum cost     \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>depends on task execution details. Use           \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed       \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>FlexCredit cost after a simulation run.          \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:11:24 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.318\u001b[0m. Minimum cost     \n",
+       "\u001b[2;36m                               \u001b[0mdepends on task execution details. Use           \n",
+       "\u001b[2;36m                               \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed       \n",
+       "\u001b[2;36m                               \u001b[0mFlexCredit cost after a simulation run.          \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:11:25 Eastern Daylight Time </span>status = success                                 \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:11:25 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                 \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d9b989620bb14897942ab3ab68b573cd",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:11:26 Eastern Daylight Time </span>loading simulation from simulation_data.hdf5     \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:11:26 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5     \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sim_data = web.run(sim, \"test run\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "20785e99",
+   "metadata": {},
+   "source": [
+    "Plot the real part of Hz on the $xy$ plane to inspect coupling in the initial (non‑optimized) geometry.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "f86abba9-aa03-45b9-ad4b-6f38df0fd1a5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sim_data.plot_field(\"field\", \"Hz\", \"real\", vmax=0.3)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "df067500",
+   "metadata": {},
+   "source": [
+    "## Bayesian Optimization\n",
+    "\n",
+    "Define an objective function that computes the average broadband transmission\n",
+    "power in the fundamental mode based on simulation results. This serves as\n",
+    "the figure of merit to be maximized during optimization.\n",
+    "\n",
+    "For reference, the initial (unoptimized) device achieves a mean broadband transmission of 12.8%.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "3bceea0e-1718-417c-bf53-d8a1140a7fc5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Transmission = 12.83%\n"
+     ]
+    }
+   ],
+   "source": [
+    "def cal_transmission(sim_data):\n",
+    "    amp = sim_data[\"mode\"].amps.sel(mode_index=0, direction=\"+\").values\n",
+    "    T = np.abs(amp) ** 2\n",
+    "    return np.mean(T)\n",
+    "\n",
+    "\n",
+    "print(f\"Transmission = {1e2 * cal_transmission(sim_data):.2f}%\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d3be624",
+   "metadata": {},
+   "source": [
+    "Configure `tidy3d.plugins.design` to maximize transmission by sweeping `theta`, `d_tip`, and `l_gap` within bounds using a UCB acquisition function.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "13a67494-9617-47c5-9089-9fb68f1cff17",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:11:29 Eastern Daylight Time </span>Running <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span> Simulations                           \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:11:29 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m10\u001b[0m Simulations                           \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\">21:11:58 Eastern Daylight Time </span>Best Fit from Initial Solutions: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.322</span>           \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:11:58 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mBest Fit from Initial Solutions: \u001b[1;36m0.322\u001b[0m           \n",
+       "\u001b[2;36m                               \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>Running <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> Simulations                            \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \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\">21:12:49 Eastern Daylight Time </span>Latest Best Fit on Iter <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.355</span>                 \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:12:49 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m0\u001b[0m: \u001b[1;36m0.355\u001b[0m                 \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
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+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
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+       "\u001b[2;36m21:14:06 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m1\u001b[0m: \u001b[1;36m0.361\u001b[0m                 \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
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+       "\u001b[2;36m21:14:07 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
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+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:15:23 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
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+      ],
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+       "\u001b[2;36m21:16:12 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m3\u001b[0m: \u001b[1;36m0.373\u001b[0m                 \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
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+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Running <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> Simulations                            \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
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+       "\u001b[2;36m21:17:31 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m4\u001b[0m: \u001b[1;36m0.374\u001b[0m                 \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
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+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Running <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> Simulations                            \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
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+     },
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
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+      ],
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+       "\u001b[2;36m21:18:19 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m5\u001b[0m: \u001b[1;36m0.379\u001b[0m                 \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
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+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:18:20 Eastern Daylight Time </span>Running <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> Simulations                            \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:18:20 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
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+    {
+     "data": {
+      "text/html": [
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
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+      ],
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+       "\u001b[2;36m21:19:04 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m6\u001b[0m: \u001b[1;36m0.381\u001b[0m                 \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
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+      "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 <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> Simulations                            \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
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+     },
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+     "output_type": "display_data"
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+      "text/html": [
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
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+      ],
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+       "\u001b[2;36m21:20:25 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m7\u001b[0m: \u001b[1;36m0.387\u001b[0m                 \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
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+    {
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+      "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\">21:20:26 Eastern Daylight Time </span>Running <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> Simulations                            \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:20:26 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \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\">21:21:14 Eastern Daylight Time </span>Latest Best Fit on Iter <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.389</span>                 \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
+       "</pre>\n"
+      ],
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+       "\u001b[2;36m21:21:14 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m8\u001b[0m: \u001b[1;36m0.389\u001b[0m                 \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
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+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:21:15 Eastern Daylight Time </span>Running <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> Simulations                            \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:21:15 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
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+     "data": {
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+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:22:36 Eastern Daylight Time </span>Latest Best Fit on Iter <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.395</span>                 \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
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+      ],
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+       "\u001b[2;36m21:22:36 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m9\u001b[0m: \u001b[1;36m0.395\u001b[0m                 \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
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+    },
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+      "text/html": [
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+       "</pre>\n"
+      ],
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+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
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+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:23:57 Eastern Daylight Time </span>Running <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> Simulations                            \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:23:57 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
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+      ],
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+       "\u001b[2;36m21:25:17 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m11\u001b[0m: \u001b[1;36m0.4\u001b[0m                  \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
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+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:25:18 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
+      ]
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+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:26:38 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
+      ]
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+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:28:00 Eastern Daylight Time </span>Latest Best Fit on Iter <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.401</span>                \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
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+      ],
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+       "\u001b[2;36m21:28:00 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m13\u001b[0m: \u001b[1;36m0.401\u001b[0m                \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
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+       "</pre>\n"
+      ],
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+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m1\u001b[0m Simulations                            \n"
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+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:29:22 Eastern Daylight Time </span>Latest Best Fit on Iter <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.401</span>                \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:29:22 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLatest Best Fit on Iter \u001b[1;36m14\u001b[0m: \u001b[1;36m0.401\u001b[0m                \n",
+       "\u001b[2;36m                               \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>Best Result: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.401350274778198</span>                   \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Best Parameters: d_tip: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.13292462551997172</span>      \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>l_gap: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.1</span> theta: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.08726646259971647</span>            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>                                                 \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mBest Result: \u001b[1;36m0.401350274778198\u001b[0m                   \n",
+       "\u001b[2;36m                               \u001b[0mBest Parameters: d_tip: \u001b[1;36m0.13292462551997172\u001b[0m      \n",
+       "\u001b[2;36m                               \u001b[0ml_gap: \u001b[1;36m0.1\u001b[0m theta: \u001b[1;36m0.08726646259971647\u001b[0m            \n",
+       "\u001b[2;36m                               \u001b[0m                                                 \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import tidy3d.plugins.design as tdd\n",
+    "\n",
+    "# define optimization method\n",
+    "method = tdd.MethodBayOpt(\n",
+    "    initial_iter=10,\n",
+    "    n_iter=15,\n",
+    "    acq_func=\"ucb\",\n",
+    "    kappa=0.3,\n",
+    "    seed=1,\n",
+    ")\n",
+    "\n",
+    "# define optimization parameters\n",
+    "parameters = [\n",
+    "    tdd.ParameterFloat(name=\"theta\", span=(np.deg2rad(5), np.deg2rad(20))),\n",
+    "    tdd.ParameterFloat(name=\"d_tip\", span=(0.05, 0.2)),\n",
+    "    tdd.ParameterFloat(name=\"l_gap\", span=(0.1, 0.3)),\n",
+    "]\n",
+    "\n",
+    "# define a design space\n",
+    "design_space = tdd.DesignSpace(\n",
+    "    method=method, parameters=parameters, task_name=\"bay_opt\", path_dir=\"./data\"\n",
+    ")\n",
+    "\n",
+    "# run the design optimization\n",
+    "results = design_space.run(make_sim, cal_transmission, verbose=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "973bf527",
+   "metadata": {},
+   "source": [
+    "Rebuild the simulation with the best parameters from optimization.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "876fceb2-8ba4-413a-9429-6275d26c4fe9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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CCCFNAoUdIYQQQkiTwOCJEkHm+2XLlulkl5z0mRBCCCH1Al5zmDIPydlHm62Fwq5EIOqQxTwUqs0ly594Gpn4K6l4TExdqdskvpv/+2HapXq7YEI0Y3YBD8yKkD/9VT3A1FzezQNRjymh6g3rIwvrw4X1kYX1kYX1Mfb6MAxDzxhTDcNNNfrzYjMTLV26VM8UMxIUdiUCS53bcMNiSI0sdt5hlYgZsiraf/I6U90c7hVipk+L+1HlTs9ZNwwTN5n72qnO/TCmaxGEMrA+WB8erI/hZWB9sD7GXB9GuvwqIP15HipdMGiR0aCwKxFPxWtRV+uR2DEc39StupI9FWKkMwUwTOV+Z1XnYWeUAYs+r0rfaHhdz3L4r4UEoAysD9aHd2rWx/AysD5YH9WqD6f6l61KxzPS17IUiyKFHcm9Kf03Qc66Ot+U3jkz6/SbBlyLIJSB9eG+DEoZWB/uy6CUgfXhvgxKGVq5PoIBo2JbniI3pXdzeDdGI25KybtBq2YjL+daBKEMrA/WB+ujeBlYH6yPINRHcKCwa2mK3JSZj+t0cxa8KaXON+dI1yIIZWB9BKsMrI9glYH1EawytFp9BAsKu5ZllJuyXjfniDdlvW7OUq5FEMrA+ghWGVgfwSoD6yNYZWiV+ggeFHYtSYk3Za1vzpJuylrfnOVciyCUgfURrDKwPoJVBtZHsMrQ7PURTCjsWo4yb8pa3Zxl3ZS1ujkruRZBKAPrI1hlYH0Eqwysj2CVoVnrI7hQ2I0h6eD4o8Kbsto3Z0U3ZbVvzrFciyCUgfURrDKwPoJVBtZHsMrQbPURbCjsyqXcdhQYxnhTVuvmHNNNWa2bsxrXIghlYH0Eqwysj2CVgfURrDI0S30EHwq7MsBULeOTKt2UY705q3JTjvXmrOa1CEIZWB/BKgPrI1hlYH0EqwzjvT7GBxR2ZaDnvRt39V/lm7LSm7OqN2WlN2ctrkUQysD6CFYZWB/BKgPrI1hlGK/1MX6gsGtqanRTlntz1uSmLPfmrOW1CEIZWB/BKgPrI1hlYH0EqwxBrY/mgMKuaanxTVnqzVnTm7LUH6p6XIsglIH1EawysD6CVQbWR7DKEMD6CDJlFJHCrimp00052s1Zl5tytB+qel6LIJSB9RGsMrA+glUG1kewyhDA+mgCQo0uAKk2db4pM6ctYM6u202ZOaH725T5QZAGXIsglIH1EawysD6CVQbWR7DKEKD6kAAPx5ZRNAq7ZsNM175Tx5uy2M1Z15sy74fK9P1Q1fMHyl8GnJ/1wfrwYH3kloH1wfoIXH00BxyKJYQQQghpEmixazaQak8/bOHpTz+G1e/c2pzvMxl7fht1ferylUE16lqkywBYH6wPD9ZHbhkA64P1Eaj6aA4o7MrNYxd0DN9N0Ij7wX8TqrwfjbpQ5Pu3XBnSsD4CUoY0rI+AlCEN6yMgZQhKfQSYMq4DhV0ZrF69WtZZe4qYZvqxwvA3QP9VH+mzapJ3HrgkJMMcYSeEEELKwhEjnAhOf55XhnLMShR2lU4plqmAQk6mUFgqz7Rs1LAR+I9tiigKO0IIIaRkdDdqFDZd1r0/H64pVBlTmlIBVEJJ4eC1nK6kQSlNCCGEkJbDGFf9eeCE3aOPPioHHHCATJ8+XQzDkLvvvnvUfR555BHZaaedJBqNyqabbio33njjsG2uuuoq2WijjSQWi8nuu+8uzz77bNllQ3kMS8qogFo0Boo6QgghpL4Y46Y/D5yw6+/vl+23314LsVJYsmSJ7L///rLPPvvI3//+d5k3b54cd9xx8sADD2S2ue222+T000+XBQsWyOLFi/Xx58yZIytXriyrbBCO5ecZqmZjoKgjhBBCGoMxLvpzQwU41BMWsrvuuksOPvjgotuceeaZ8oc//EFeeumlzLrDDjtMBzosWrRIv4eFbtddd5Urr7wy4yu3wQYbyDe+8Q353ve+V1JZenp6ZP78+TKxa5KYptmAShxtf3eMXiUhPgOn1wkhhJDgYiB4Il6iD12t+/PhQLf88MLzZM2aNdLV1TXituNeATz11FMye/bsnHWwxmE9SCQS8vzzz+dsA2GG9942hYjH41rM+RccqzFKn5Y6QgghJBgYge7Px72wW758uUyZMiVnHd5DiA0ODsoHH3wgtm0X3Ab7FmPhwoXS3d2dWWDha0xjoKgjhBBCgoUR2P583Au7WnHWWWdpk6e3LF26tAGNgaKOEEIICSZGIPvzcZ/HburUqbJixYqcdXiPMei2tjaxLEsvhbbBviMFSuhgiVpPuuxN/FzQZ46ijhBCCAkuRuD683FvsZs1a5Y89NBDOesefPBBvR5EIhHZeeedc7aBEyLee9sET+lT1BFCCCHjAyNQ/XnghF1fX59OW4LFS2eC1++8805miPSoo47KbH/SSSfJm2++KWeccYb861//kquvvlpuv/12+da3vpXZBqlOrrvuOrnpppvklVdekZNPPlmnVTn66KMleI2Boo4QQggZXwSnPw/cUOxzzz2nc9L5RRmYO3euTjz8/vvvZ0QemDlzpk53AiF32WWXyfrrry/XX3+9joz1OPTQQ2XVqlVy7rnn6oCJHXbYQadCyQ+oCIQZ14OijhBCCBlHGIHozwOdxy5IIMoWVsF115lWYR670VAiZroqnErz4jCPHSGEEFLbPHa17s/HlscucBa71iRP3Rd1wCwdOxyXvmlLctZ1vj9TLAg/QgghpIUIGUmZHM0NolwVnyIpFQ58f14uNO00HF8jgLJ3ajXRMCGEEEKavT+nsGsohRwrazHRMCGEEEJaoT+nsGsYI0XLUNwRQggh4wMVqP6cwq4hlBICTXFHCCGEBBsVuP6cwq7ulJPXhuKOEEIICSYqkP05hV1dqSRZIcUdIYQQEixUYPtzCrsyCIXGkh1mLBmoKe4IIYSQYKAC3Z9T2JUp7IyKUtFUY1oRijtCCCGksajA9+cUdmWQSqXEwBXzJx8clWrOFUdxRwghhDQGNS76cwq7MoWdcgrMA1eUWkwATHFHCCGE1Bc1bvpzCrsy0TProiJGFXe1aAQeFHeEEEJIfVDjqj+nsKsEVMKI4q6WjcCD4o4QQgipLSoQ/Xk5/v0UdlUXd/VoBIUaQw1PQwghhDQ9KiD9eZ64M5Tr318iY8nfQXIqIV0PdWsE/sZQbkAHIYQQQnJJG2vQqTa6P8eiX7vvlV36USjsqinu8NLzwaurCQ2NIX1+QgghhFSGCkJ/ni6DmRWWSjv4lwaHYqtBzvWudyPwn5cQQggh478/9523zAE5WuzGjM9kmjHj+ix59YJDsYQQQsjY8Cx1je7Pta5IF6bM/p3CbkwUcaysd2PImI1ptSOEEELGRMP787So87l6MXiikaJO1bkx+J0sCSGEEFI5nrWuof25T9RVECBJYVcRo4RA16sx5DQCutkRQgghYyMI/Xn+OQxRNoVdbSklBLrWjWFYI6DJjhBCCKk6de/Px0Ygo2Kvuuoq2WijjSQWi8nuu+8uzz77bNFtb7zxRjEMI2fBfn4QJnzuuefKtGnTpK2tTWbPni2vvfZaRWXLjHOXEgI96gwVwWgEhBBCCGmO/jxwwu62226T008/XRYsWCCLFy+W7bffXubMmSMrV64suk9XV5e8//77meXtt9/O+fyiiy6Syy+/XK699lp55plnpKOjQx9zaGiorLJFIhFfkILRmMZAUUcIIYTUHzU++vPACbuf//zncvzxx8vRRx8tW221lRZj7e3tcsMNNxTdB1a6qVOnZpYpU6bkWOsuvfRSmT9/vhx00EGy3Xbbyc033yzLli2Tu+++u6yymaaZzv5sNKYxUNQRQgghjUMFvz8PlLBLJBLy/PPP66FSv5jC+6eeeqrofn19fTJjxgzZYIMNtHj75z//mflsyZIlsnz58pxjdnd36yHekY4Zj8elp6cnZ8G6hjUGijpCCCGk8ahg9+eBEnYffPCB2LadY3EDeA9xVogttthCW/Puuece+c1vfiOO48gnP/lJeffdd/Xn3n7lHBMsXLhQC0BvgWgsZ0qPqjYGijpCCCEkOKjg9ueBEnaVMGvWLDnqqKNkhx12kL333lvuvPNOmTx5svzP//zPmI571llnyZo1azLL0qVLG9MYKOoIIYSQ4KGC2Z8HKt3JOuusI5ZlyYoVK3LW4z1850ohHA7LjjvuKK+//rp+7+2HYyAq1n9MiMFiRKNRvTQ0dJqijhBCCAkuKnj9eaAsdog63XnnneWhhx7KrMPQKt7DMlcKGMp98cUXMyJu5syZWtz5jwl/OUTHlnrMhih9ijpCCCEk+Khg9eeBstgBpDqZO3eu7LLLLrLbbrvpiNb+/n4dJQsw7LreeutpHzjwgx/8QPbYYw/ZdNNNZfXq1XLxxRfrdCfHHXdcJmJ23rx5csEFF8hmm22mhd4555wj06dPl4MPPjiYSp+ijhBCCBk/qOD054ETdoceeqisWrVKJxRGcAOGSxctWpQJfnjnnXd0pKzHxx9/rNOjYNu11lpLW/yefPJJnSrF44wzztDi8IQTTtDib6+99tLHzE9kHIjG4L2mqCOEEELGD6r6/bllmXoRcUrex1BjDvVsDTB8C4E4bdp0EWWKcqp82fwm3IoaAfYXUcmoLp8djkvftCU5W3S+P1MsfE4IIYS0ECEjKZOjuf77q+JTJKXC7hvDESMcT8/OadSsP8coomkZErJMvUC0hSwjI+BCodx13p4DQwk57qR5OpgTkzKM+F3HVvrWY/2p3dIei4ijlKRsJbbtZJbse/dvyvea+pkQQghpPgzDyBFjStD/2/hA2mNhmdAey3xu+sRaraCwqxDTMCQSMkRCo8efQNI5jiooACH+huIJSaZsMcTUgtHxTK4ciiWEEELqjmG6VjW/YMu+N8UKZT83TSMj1nr7h6Snb0jW6erQ7/Hadmxpb0tbBusAhV0dQIVbpiGWaYmErZzP0AhStiFrT+yUCR2uz18PGkbvoLS3RSUWCWcEoBaDTvp1Cq+zFkFCCCGEFCcSMaUtFpG2tpC0xcKyYdt60tbRIZ3tYT10+vQ/Xtefx6Ih3WeXiyfqujpjmf4cYB3wr6slFHYNpFgj6OqIaTGIz8IhUyZ0jtwYMMo7lEjKwGBS9tppcx1c8lH/Gvmn6pFEwpZ4IqX/dgy0SbzXkHhcT3hLCCGEjGtisbB0doSlsz0inR0R6fD/bY9Iu/4sKp0xJeGht3J37txYxHL9zj9a0y+LX7YkHDKqKuoyBps6ijsKuwZRrBFU0hgMw7UIQgRuuH63rN3dIX2pTnH63svZbrfOXaQz1KmHfSEC+/sT0j+YkL5+VxT2DyR8S0oG9GcJSaVoESSEEFIHDJGONggzCLZo+m9EOjpcoabf4y/WtUV0sEFJ2GOY672O/XlDhN2SJUvkscce07niBgYG9PRdmOkByX4DkT5kHDBaI6h1YwiHLOmegKW04yUSKekfSEqfFnwQgQktCvsGkzKQXgcxiM8hEB2bgSKEEEJc4IPWnhZo+Za19jb8DUsHrGrt+BvR248Xehvcn49J2N1yyy1y2WWXyXPPPadzyiHBb1tbm3z00UfyxhtvaFF3xBFHyJlnnikzZsyoWYHHO6U2gkaacfOJREJ6WWti26jbIvp3KA4hmBV8etEi0BOA7l/9fjCRDi8nhBAyXoClDNYzLci0MPOsaVHp7HT/eta2WDQ8rsTaeO/PSxJ2sMhhuq+vfe1r8r//+7+ywQYb5Hwej8flqaeekltvvVXPGHH11VfLIYccIs0Y0lzPRhAkcVfONYJTKpZ11h59e0QLDwxlhV7GKqjFICyDrvjzPhsaStXjaxBCSMsRDpvS0eFazrzhzuF/XTEXi1pj7hPHM70B7s9LEnY//vGPZc6cOUU/j0aj8ulPf1ovF154obz1Vp6DYpOA75lK2iKx+jWC8SjuygFPcdo03x4paXv4+yFRY9Ya6FoC+wbi7rqMCHTFIYJGCCGkVYnFQr7hTn9ggevDpoVa+i9GZsj4789LqsWRRF0+kyZN0ksz4jiOrOkb0lE4kXCobo2g2cVdueZ/XEcspZBM2hnB5waLJAsOE+Mz+AcyUIQQMt4jQTvSkaD4C59qUj3GQ39esTxfuXKlXiB2/Gy33XbSrCQSCTFsW1auXCNrxcIS1vO3jUx/IiV9iZR0RkISTaYksbpvTGVAYHa7IbL64z5J9Q9JR/oJK5nOc7fmH2+KEQtLvzEo/aHlOfuuTr0mSTW6n9x4wIiGJNQRE6s9JiFk9e6IiVlAbIfDlkzsxhIryT8wnrBdq186OCTjC+izELpi0H1d9anlCCGtxyiRoJ0+oQbrGxLj1gI7kRJ7YEhs5FdN/1WJJnF/UQmx7NxMEbaVFDHc0aI1Q0n93ZNxE2kmGtqfFyKVTNVO2D3//PMyd+5ceeWVVzLTZGGcHa/x18Y0Gk1MbGBQ4qGQfBhPSpdjj3gBBw1DBgxT2pUj4aG4JKpUBuSvjhmG9CRSklKOtGF6M1S8YcpHT74kSeXIYDgpfevlCrsP30vIQLJ+2a/rjRENS6g9qkUeBB/+atEH8dcRFau9TSz87WgTKxrRmcVz9jcMnZgSy6SJ7SX5B2YCRXzpY3KHiSEQIRST2peQgSKEtAYjRYJmcqylh0RrFQmKB097MJ4r1gaGJIXZEAbddXrBOog4uBo1KYaRkkjsw5x1iaGVopTbi/capqRi7WIop+DPdD3780Ik84xoVRV2xxxzjGy++ebyy1/+UkfHtprzJL5tl+NIj2lKj2kVFXf+RlCsosaCe0xHnwN/w5yLVlQ8KUksH5fwFGWaYvlEIKx/ruWvkDCMihkKFf7hbsMTdFgml1A+WFQx3JvJGahFIIRh2j8wM1TsppRhoAghwY8EzQq2+kSCOqmUK9LSgsweiEuqf1DsflfAZddDtGFSe/YNpVJMOtW7Py90Dkw6WjNh9+abb+rI2E033VRaldHEXa0bQaHGEBVH6ElRBpiOrW9QL6VgxiIZAajFX1tMrM7coeDMkHA0XPCBB3MKTuiM6qUUvETSAyXkEMSSTNI/kJCxRoJ6Qq1ekaAY7bLjCbFhRfMsap440xa1uKQGXOEGixseYEltSCHZv5KG9+f54g6P+AOWVTtht++++8o//vGPlhZ2I4m7ejWC/MbQb5gS45NZzXCGEnpJftQz6rZGyHItfvkWQc8SmBaAEIihtqgYRW7YihNJpyODs8Eh7nCx6zeY9RnkHMOkmSNBM3nV0j5r9YwEdVK2HgL1W9L8Q54ZS1vfoDiDcVG8FwPTr/eZloQa3J/7xR1EHTSGqWo4FHv99ddrH7uXXnpJttlmGwmHc322DjzwQGlVcYfh0IRh1K0ReOBctjiSarFh8aCiUrakevr1UgpmWzTHH1C/9iyD7W05foNmJFTUYlB+ImlEDCMa2LX8eTOH6CFhnzUQ6/AZ/QNJI2lrgxgLS2db/SNBcb84cde53vNRc/3V4hnB5g84wEMgGX+ElIhtqIb35564S4mSpGGIJUqiZcQvlC3skIj4iSeekD/+8Y/DPmuF4Ili4u4j09KNIKJUXRuBB6x1A2WMwZPggCd2LElZU5I1MNSZZ/nzhogzlsD0ujYEiJgjJJIO6UWktECRwSEvGCSbHsabSs7LJ+jNPTyEQBFCAhwJCitZCoEF/mFPiDZtVUuv9/mr4YGNNDfoQTu1saax/blrqXOFpaQ1RjmPCmULu2984xty5JFHyjnnnKODJ4jIkM+CAnWdyhujrwcw1yrquqYHnUtydb9eRgVPerD2pS1+ng+gJwo9gThSuhgPOIG7Q1uRkgJFUrYjg9rSN3wWkUy0sM9vMB5np9kqkaCezxrEWrWDC9x0HWl/tDzB5lnUvPV4mKIVmuQTD0h/jnP7NUY5jzVll/fDDz+Ub33rWxR1afxj8LCajRYtW6tGAL+ASBV+pR5KfCzLVUJmh9eSKWZps0GQgIIh+rTVQVaVYA2MZHMD6sUn/Nx0MT5hGIsOSxfjJ1RBoEh26Ne1+rn5BNN/B5Paakgai2kZ2srmF2zuzDEYJq1+JKhCkNNgYlhAgX6NdB15AQfNnK6DDMcQR0yxRYlZlfBBW4soUzp8/XmvacoE3Z/Xx3Li+dRh+BWWuqG0xgibpf/+la09vvjFL8rDDz8sm2yyibQ6hRwrS0mFUqtGAP+AsbIo+ZE8mlojN8VXyJ6hLtkvMkl2tjrFpP9e04NEpMlEX4XpYqIS8vIE+oaER0oX4wc+URO7sLTebCqthk7XkfFRy4sA1ak70q91njWm6yD5eDIuJZaR0q8TKlYVYZcy4NaU25/3moYWd92Orc+gtMAz6iLqDJ/PXV8Rt5pClK07kMPurLPOkscff1y23XbbYcET3/zmN6UVKBYtU2qeu2o3gnYHwRPV8UHBkwlSNP4p+bH8JblaZlgxOSA8SfYNT5S1zeZNcExqly7GiEVcyx/EICyBbXniL/03vPaElsuN2QzAspb4qDcjyDLiLEe4MV0HGQuQbo6EjKRY2raGoMHqBsmElOuv7oFfIgg69OdrzJB0O0kJi9JjY5CXrsirnajzgMZIlvGAU1FUbGdnp/z1r3/Vix/8IFdD2F111VVy8cUXy/Lly2X77beXK664Qnbbbbei299xxx3a5++tt96SzTbbTH7yk5/IfvvtlxPRtGDBArnuuutk9erVsueee8o111yjt62E0UKg6yHu8htBKQMQK+2k9KdGdsEcFDQoQ7qMkHQZInHlyBJ7SC6135Ub4svl06GJ8rnIWrKt1cEOmJSMQqoYnS5m5O02O/MrtXoYJjUE4u3t6+5rdDFIk1rnEB8aMmz9Gj1uSgs6w5e6FxJrtHQgquA6bz8cDf1p/nZuf56SNWZYL3gd0f0kel3s7Z59LD9cI4k6j2gtZ55YsmSJ1JLbbrtNTj/9dLn22mtl9913l0svvVTmzJkjr776qqy77rrDtn/yySfl8MMPl4ULF8rnP/95+e1vfysHH3ywLF68WKdjARdddJFcfvnlctNNN8nMmTO1CMQxX375ZYnFyhv6iZumJEvIa1NLcVdKIyjEWb1vyXujCDt8I7/dL2qYMtkwxVZK+pQt9yY/kD8mP5LNrDY5MDJJ9glPlE6DqZEJIYRUC6WtclbaOoc+Dj1drqDztjQkZCQkNErcqF2gp4xKHDFmmoRhiSFt2iroCrwsMHbAcrfGtKTHDOn+PKxLhP4SgssVd95Sj/58JKoWP/7+++9rATVWfv7zn8vxxx8vRx99tGy11VZa4LW3t8sNN9xQcPvLLrtMPvvZz8p3v/td+cQnPiE//OEPZaeddpIrr7wyY62DOJw/f74cdNBBst1228nNN98sy5Ytk7vvvrussoVCIS3sSs1r44k7VBgqrhoTRI2lEQykFf8Ewyq6dBmWTDKGS1DLMKTbDMm6RljaDFNesQfkx4NL5bDeV+SKwffkNXswM3cwIYQQUi6wf0GgxYxBiRpDWtSl7XVpH7rhPR6GY0dbioNhVcO3Xa5Ayy7ZYVmvP0+mh2LdIdlsIAcWdw/VEFFX8VyxhXj77bfl2WeflTPOOKPiwiQSCXn++ee1D5+HaZoye/ZsnT+vEFgPC58fWOM80QYLI4Z0cQyP7u5ubQ3EvocddljB48bjcb149PT06OSvUZWSNlRYiTWgxZ2ypccIaetdl0ITrUwApcTQx8ETBY6TOxJqiBiIy4bPky1GOCURI1t+sE40KTHHka4qyXnXiheXv8gyeSK1XLYw2+SgyDqyU6izOicgLUdycNWI0bYkmKTigyLhgUYXg4xTtLQy0De6vnMQTBBO1fLLUDornCESyu0TJeyeA/ZByCFlOCJYivTRWtyJLWuMsPRY6M9dnzv3HB6uwNOvVPFh2pH78wLUMir2448/znmPhMSYP/aVV16Rq6++WsbCBx98oI+Xn0oF7//1r38V3AeirdD2WO997q0rtk0hMLR7/vnn56w7f/43pS3aK2KWF1LvijuRHrtTesSSLqtP+wuUQ0pZen9LhvT+wxqBskRUWGSdl0VCAxIxlcyI5TbiUzZLSUopCVXZNw7HxG0DQ3a3uQxTKVT1+KR1WPXycp1/j4wvMIWWbLCi0cUg4xZHlKEkmRZ11Xa0ddIBD8P6bscTj4bYqXaRNRNEGUlRo/TP/v58gtUv4bzt02dLY5TfnxfAdGo4V+xdd91VcP2FF16orWQnnniiNAOwGvotgbDY3fyLH7uVpMo3eWlxZw5Ij9MhPalO6bIGShZ3biNoF8uAtQ3zS5jDHyiQnRiLExaxI+IoR1JO7uBvT9LRAixchRF4ZA7CsfAPzxxTjLBMNyMyEefniCypEDM8odFFIBVhi9i5D/2ElIqb0MP9Pzv4Wc3UIo57nPzRAC2W0uewQ+ks/6Of0+3P+3V/3pvqLCDuivvaldSfj5GqBWsigOGCCy4Y0zHWWWcdsSxLVqzIffLD+6lTpxbcB+tH2t77i3XTpk3L2WaHHXYoWpZoNKqXYaDiK2xnUOWuuGuXHrtDuqx+CWmzb3FSytTbWobtNoKi0j7dGNFQtY+cMyyvz5Bjy4CCmXjkVgThV8iqBx86SMVUOnK20wjJDDMq65lRiXmpVkpzLSCkIGYIwUy02I07VErEqXd+ftJMeN2Ga7PzomH9Ak+K/DZkhWAxjLQHnHZX8uNk0w6b2nqX3aP0/rxDeu0OmWANaHE3UvBE6f15AcqYWqpqd+I//vEP2XHHHcd0jEgkIjvvvLM89NBDOrIVOI6j35966qkF95k1a5b+fN68eZl1Dz74oF4PEAULcYdtPCEH69szzzwjJ598clnl0/kBTW8MvjJ0YzB6XTOu0z7isKxW9g6UfapEc60jEh7UQ7GGoSRi5g7FbtNmSnyUxoHI1yFBOHe2kauMdQ7h4IZ0G5aso9OhhMTU16K0XGaEjEZycCWF3ThEz6MaKWGaO0JKAH2Nm0wEaEmWkXz5QNS5dr7RMczcUSxlZSWQnXKFH/zs/EOxxqj9eY+sqUl/nkctExTnByp41q977rlH9t9//5zPEeFayfHnzp0ru+yyi85dh4jW/v5+HSULjjrqKFlvvfW0Dxw47bTTZO+995af/exn+vy33nqrPPfcc/KLX/xCfw5FDNEHayLy1nnpTqZPn54Rj6WCijAgZCDuxoBrxu2RntQE13IX6pVQ3th/yrHSyj6lPx+1ETjYAMETSZFQQgu7kJHbiKdhup9RhpHfQ647HZkEi59nHjcknBZ0E4yQhHVh8Gk50xITkotu0pjY3TR1wIRhmmIneijsxiMYCZiAEQNHlO3Aa9x93ehykXGN136yLSkr7dw1br9XSpoRA9vliy4zKxaR7lhb9LD4AhW8iFhvTe75XbrM3ur254XKX4bsKFvYvfDCCwXX77rrrrJy5Uq96EJU6AB96KGHyqpVq+Tcc8/VwQ2wsi1atCgT/PDOO+/oSFmPT37ykzp3HdKZnH322Vq8wdfPy2EHEKkLcXjCCSfoBMV77bWXPma5OexsW0Tpcfix/1xpcWcMSY9ql55kd86wbI651hgSA35rowHBhgCKwS4RKyKO6ciAmRulFhlszzM3D2dpskeWOQmxDNc6t44R1jNPwIeO04qR0TAsS4yQJWbY/WuEQmKGTDHCIXc91unPQunoV7apZiE2MX+N0iIP1jwEV6hkKvvaW5Le+5QrCAkpQG6P69rnkCLESyuCLLEYvB0ZR0wrdxTLseFuld7PjmVdmXwGEM8W6P+lyheRVe/PC6C08aY0DMXkYyWB4dsrf3q2TIyUNxnvaODqwzxrK0TLukMZuWPwpR0HjSepwrJnxz9lgjUkKdOR1R25wm5if7uERhF2i1N9sspJyAZmTDawojq3HWld8IDmCrSsINNCDcIsnBZqPgEnVZrWzkVJynYklXIX/lA1HvwehSxLwmFTrGoLc+VkRZ8WfK4Q1GIwmRWD3jacQ7a1yWaZczIeeSNv7xQUdp4g7LVj8kT/1hI2kjm+77mBHPXpzwuRdAw55ZwrZM2aNdLV1TXitvR2bTD+gAqM0wMMoY61EVTK9laHiIWGSEtKs2JYEGaeKHMFWva9K+BMrMdrDJVWrfNWYjsqLdRsSaYcvWTeI2o7LeSSKVv/pZoLLrC4hkOmhEKu0AuFzOx7/dr9GwpbEsIQwGjtyDDFRF4xzD8+asaktDUwmcqxAGasfxlLYHqhNbDpyA6/mjU/z3jrz0sSdpjZ4bzzzpM99thjxO16e3t1LjvMJXvKKadUq4xNDyq83YxLD4Z5xX3dKF1FQTcOge+ntph51jP/UGhapOG95a6vplUNwU0pv0CzXVGWI9gyrx1R8L0iTQHqMpGw9TIq0GuWK/JyRV8BIQjL76idqeEO+6NNl1JYx2cNTKXFYLK4GCRkPPfnJQm7Qw45RL70pS/pGRsOOOAAHdiA4AP4qCFhMeZcffzxx+X+++/XAQwXX3xx7UveRGAYtdduz0TT4HUpqVBI84JAgqz1zLOk+YZB/Ra2UOGpdipBp7Sxs9YzV5S51rOMQEs6krTddY5NoUZKwMFQkqPb1agx9BjuTQu9jBUwXxDiNUQhxF1J2V1NMSOmSKQU/yaV6wuoBaDPMuj3C8RnHBImAevPSxJ2xx57rBx55JFyxx13yG233aYjTjHOC3BTYU5XTOP1t7/9Tc/XSkonP68NKCfPHRk/5AYP+IY784Y/sU05oe0jo3JEmTfEmfM6I+AcsTH8SUgjUaIfHrCUgpU/BJxvBdQC0LUOmiVZq+FXGhIrVJqnkkL0b6HhX+0b6AsYgQhEBB5pWlIB6c9L9rFDsl6IOywAwm5wcFAmTZokYfhEtALaTaR6GXizGajRCPoz5lovozU+K32GinS5EGaNXD1mdr66DDqHT239EVoJbSlIW9DMtN+aK8xM9Dbp4c+0P5tllViHKXEwY8gI97/rp2bnBBbYaWuIbSst2Oz0Z9i21OaK5qdHwQgZTzgiqYS7DI2yqWkZ2tqnhR4sgpbhBoIgICRkuIEhIbw3xSxnzmLEDUVFrCju8xHudZ0FxhN5riBEugUnCet3rigUfE5rYBVxCqQ78fWJyp2nttIs+9XtzwtQRnOsOHgCw7JYWgn4kesEh2PMY5fNa9Mplom8Nj05Y/Du3LKrpSfVJT1Om/48Py/OMBCmjRDtWI9IqF/PnNIeys1jZ8aSdEYvYQgUF0+LtnRuNVSOTs2h16c/x/tMPr/c65xpHXZ6GSXdH368Hcf7q8Tx/joquy69Xv/Qj1CHmW4Fv1WRMV8OQpoT3ENJd0kOuS+HiULD0OLO9P7qWx+Cz/2d0D8J+Kt/Iip0hdBJ7/V0P4UfuXHP65yA+Otk3yvHt973noyIGjZXrK/WU0mRfuSyQx9vN7Y/L4AxSkYLP4yKLQMEVilMmzPGp6icueKMwYJ5bdy8OIPSozrSeXFGUfpeHrsh5LELu3nsjFxvltBQ26h57JoN/YPrs6Z51jNDW9rSUaGW4fqvpUXcWIEA8yxmrlXN9VvTFrT0sGfmcwQU8PeYkHGNNt6nh4PdYV9Y/3zvMSxsmWIhQrgcS2A54CEwY/VLDw/78whinfe57sxa7YfHEcPMfcpWTsSXx66tYB67hvTnBVCNmFKsJdD3gWepGcMYvJ5WxJEua9C1AI04XcmgbjQw5bqNoZi1EMIOGfwjYmAY1nTEyZs+xTSj7oTDTYCOhvPlU6tlug43oKBQIEFuUIG3rrSAApRplGEbQsi4IYl+WqdJ836jsQK2wNEjhDPBIBVFCPsOXbJXlJcuJi9fYKF0MU2SKsYwlJh5OWgdI5aZg9VQaZGHPtlodH9egDJ0OIVdmYTaY/oGrISkbUjfQEgiESXd7Y6YRntJ+62tRNYMmNLnTJCJ7SkJWwVq2DbESZnSufkG0tVmS0olZTDpzgLiMSG8roSMFvGHHBEvlxqiO+Gkbbt/84ILPLHGgAJCSGAihNMBIRVHCA9LF9MiPhvKFkliykIf4S5YCdyPBy2xXopIKBQq3MfWsz8vVPwSg4kAhV0ZOEZYT4FYCWgEqwdCEjLRCFLaP6NUsC32WTMQ0scopzG0BiodNJC2otkFEt96oi0t4OhrSAhptQjhbPqYUiOEyXjsz8sWdnPnztXpT/7jP/5DWg9D+uJhiYTtsipyLI2gVcVdfuLbZKEh0LS1LWWnHYgJIaSFsTMjDLluOMVEYGhEIZh97Z+fvdUZD/152cIOaU5mz54tM2bMkKOPPloLvfXWW09aAUMlJYWpQgZCJVdoNRpBM4g7+Knl5lBDYIGdTnbrDkv4ZyqgUCOEkNqLwNzZUwuDqOCsT6AnCL2p5LwhYS9VTJXnEA4QyXHSn5ct7O6++25ZtWqV/PrXv5abbrpJFixYoIUerHgHHXRQU+e0w8x0E2JJGUhEShJ31WwEQRN3XkDB8Hk/88RbOjKUfmqEEDI+QbqlRDwliXiZcwinh33HNIdwQEiOo/68Ih+7yZMny+mnn66XxYsXy69+9Sv56le/queIRQLjr3/967LZZptJs4Ecs5YalAnhuPTE2+XjPpHuaOHJfZO2qbexzKRMCA+IQh7KKpZlQlhkjS6DKV1RROOIOHZI4r1vy1BiSByxJWK7ma89ElafpIpGYSJPmjsE6uZN8792J2/P5FZL51QrOZ9aOk8TIYSQFswVmH45LFhE5wL08gQaYum8gP732dduwuixqClHxM5LKmqtyqQ7icdjYtsd4khKJ3xvZH8etoYbQuzRR9erEzzx/vvvy4MPPqgXZO7eb7/95MUXX9RTjF100UXyrW99S5oJaBnDcDOUd5sJWTMUlZ5Ep3TFhnLUu24EiaiELCVdsYSYyItTZXC67raE9AzFpCfRIR2RhA61tsKdYkUigpaXEluLNSS21GmLUhFRjqlzqDmwttmuYMN7LIXPMj6epgghhDQbubNAYEYQiD38hbUPM/4gT2DmvQnLoPt3WISwckTS03xlD9jupjfBSyciKScsEaSy801C0Ij+vDsWzxF36Mf7ktGSj1d2CZPJpNx7773aSvenP/1JtttuO5k3b5585Stfka6uLr3NXXfdJcccc0zTCTuIeMMM68aEmWPWshxtPu2Nt2dMszDX9sTdcOnudgRZVC+UXBvJ9OwDbhJcvG4LJ6UvHpGewaiErZS8vRyV6kjSsSUR824It4GHBiwxkYCREEIIaVoh6AyPEA6JtFl2Zko5+AJaoYkSQnJ6w5QQxpiMkPQnLIlEat+f5wN5ObHD0cOyPfG2zLAsRF3vQEhKSo9aqbCbNm2aHqI7/PDD5dlnn5Uddthh2Db77LOPTJw4UZodXHRcfIg7VEZH1JY1g6WPwesm6Am19PRRnnjTws2bZioj6ArXbEglJanadSMcHExJzLLFyUvESAghhLRqhLBhONJm5Q4GD9pxUcrUIjApMXHsbknYIfmw15JYKCkDyYhYpiOdUUzHCS97TCtZuzLn+9x1t6WkP25JyjFkQmyUuSnHIuwuueQSOeSQQyQWixXdBqJuyZIl0gp44u7j/rCsHoCZ2A2wwOwDqQqFWrmgoUXNIUmq0k21hBBCCBEtABOYbs1xJGwMSSIVlUQqLKZhS0QGpd83gmvgn55D2J2y0p0+3J1fXP9Nzx3srqtc3K0egKZwndPX6kiWlSmibGGHIIlWJpFCQIE7v6cr1hAdakoqZWGSFrENR3rteE1VPSGEEELqj5J0AGEJ27oi0Cf0fCIQGsFd54nC6pWRM0+USSKRkpSvAmxlStyOimHYEjUTErdjMuS0Scx0I1XrAURm3InpufAIIYQQUj5KGZJ0onqu9UgV+nNXBLqvSomihdDDiYbsmDYctYfjkrDD8lGfJe3h0uNwmU56DLiirk2P3aPiLYg7a1CP2aMxVGmkdURwDvdchlglPUMQQgghJB9bEE2rGtafI0tFfzIqKduQsDEgjp0QS/WL49jSM1i6HY4WuzLArCqobPjR2Y4lCScqlpmSdqs/o+ZxQUOGLQN2uyRUVNrN7GfVBg1twOnQr9tCA6LElPZwn7SFBkUZjthmrqOoFcbsGdTyhBBCWgtDlLbC+THNlA6I0K9TbWKKI9HQoITS6U4a1Z93hPrEMrMWupDZK31J97NxJ+wQTICZLK677jpZvXq17LnnnnLNNdeMmOz4vPPOk/PPPz9n3RZbbCH/+te/Mu+Hhobk29/+ttx6660Sj8dlzpw5cvXVV8uUKVPKKp87Ju6Io0wZtNu1yEMF5Fe0aTnSYfTJQKpTb1dom6o0ArtTP03o4yMVjQpL1IpLzBrSws4xknnlMijsCCGEtB6GklBen6jz1Sm3c0a/HjaTYhlK9/ON7M9DPlHnFlSkI9w3PoUdkhpffvnleqqymTNnyjnnnKNF2MsvvzxiFO7WW28tf/7znzPvQ6Hcr4V8en/4wx/kjjvukO7ubjn11FPli1/8ojzxxBNllc+2RfvTJRx3+DVsJCTpFM9rEzbjeqi2J9ldVZ+77PAr8ukNiqMsPSzsqJB8PDRJBq1OcUxbUmZvzn6hoQnMY0cIIaTlKJzuxO1HwZAdFVuFtE+cpayG9ucJe/j5y5k+PRQka92ll14q8+fP13POgptvvllb1TA/7WGHHVZ0Xwi5qVOnFvxszZo18stf/lJ++9vfyn/+53/qdUiu/IlPfEKefvpp2WOPPUovoxjamRKOlaVUrGU4uqLQGKoVUJHfCHAOQgghhNSO8dSfB2ZcDnnvli9fLrNnz86sg3Vt9913l6eeemrEfV977TWZPn26bLzxxnLEEUfIO++8k/ns+eef17Nl+I+75ZZbyoYbbjjicTFk29PTk7MoA3ltVFkV6jWGajhgUtQRQgghjcEaJ/15YIQdRB3I93vDe++zQkD43XjjjbJo0SLtjweB+KlPfUp6e91hSOwbiUSGzYQx2nEXLlyohaW3bLDBBtpmF6lApVejMVDUEUIIIY3FGgf9ecOE3S233CKdnZ2ZBVa1Svjc5z6nZ8LAnLXwx7v//vt14MXtt98+pvKdddZZehjXW5YuXSqmSlZseh1LY6CoI4QQQoKBFfD+vGE+dgceeKC2tvmHPsGKFSv0fLQeeF9oPtpiwDK3+eaby+uvv67fw/cukUhosee32uG4xfzyQDQa1Uujx+gp6gghhJBgYQW4P2+YsJswYYJe/METEFoPPfRQRsjBr+2ZZ56Rk08+ueTj9vX1yRtvvJGZ+mznnXeWcDisj/ulL31Jr3v11Ve1H96sWbPKKzSSQutscZWDuedMa0BH42C2iLYRGoM/+XCbNTBiI0CGa0eUhMyUhMykOIYtRnryYw/LSOrAD0IIIaTVomItI7dPRF/pRcWGdCQs+nd3aWR/XnB/GYdRsZgrbd68eXLBBRfovHVeuhMERRx88MGZ7fbdd1/5whe+oFOWgO985ztywAEHyIwZM2TZsmU6D55lWXL44Yfrz+Efd+yxx8rpp58ua6+9tnR1dck3vvENLerKiYgFlilp4TQ2cRRON6j+VKckVEQ6rOF5cdAI8DmYEO4ZntcmDwNpTJRId+xD6UCyYkOJE8rLY9cWFyOds4cQQghpJUJ5wq5N9Wde96faJdSX0rnuRutva92fF8JwzPEn7MAZZ5wh/f39csIJJ+ih07322ksHRfhz2MEa98EHH2Tev/vuu1rEffjhhzJ58mS9D9KY4LXHJZdcIqZpaoudP0FxudiOSMoJVW1qkagZ10ofeXH8Sh/HH3TadMJE5N1RypJkgbw2OWVTpqRUSNYMTZK41aEtdnZbbkJDa7BTzAL5eQghhJBmxtBTfw7lrBtyYr48djHdv2NkDn1uI/vzQthl6A5DYQyUjAqGha/86dkSi4bENGo33yyoZAzeS1C8SefrErPiboLi9rwExQNMUEwIIaT1MEpIUPxG36ZiGqmKfd+q1Z8XAgmKvz3/Mh3MiZHHcWOxa0XyHTABAyUIIYSQ8YUVkP48MHnsWhm3MQxpUy0WvKaoI4QQQsYXVgD6cwq7AIDB8IRvzlm85gA5IYQQMr5QAejPKewajD+vTcwa1Es1pishhBBCSOv15xR2DaRQssJqzkVHCCGEkNbqzxk8UQaWJRI2k2KZY68dL68NAmw7CuS1wXkGUp2SLJIXJx/bsSSpRNaKfSjtOo+dI46VyNnGjA2JkY4AIoQQQloGQ+kcdX7aVJ9IOrfrQKpdrIGNJGygj7cb2p8XwnZK34nCrszKgzOkMUbZjd0H7A59rHZrQEwkE84TXFiH7NQDdrv0pSZIu9U/YmNwMCeGMiRuR8U0HC3s7FBuOS07RmFHCCGk5TAwP5OZ2/9p/zctx0T3nehDHcMoq5+sRX9eCKeMyQUo7MrAcZCnxhLlVM9ci0alkyIWIWLGdeh0n5ow4lx0bh47SwaSneI4YTePHVJi+wglmceOEEJI62HoUayR89ihD005ShtGGtmfF8tjVyo039SRSiYAps8dIYQQEixUgPtzCrsyUIZV10bgQXFHCCGEBAMV8P6cwq4MlIQk6YTr2gg8KO4IIYSQxqLGQX9OYVcGhqQk6UQkUYa4q0Yj8KC4I4QQQhqDGif9OYVdGRjKlrCZKFncVbMReFDcEUIIIfVFjaP+nFGxZYBI6Zg1JCnlSNyJiqVQKfHiIdBOh37dEeorOy/OaJUWMmwdOp1QUWk3ETptSsoxpD3cJ22hQTfdiZkbAWSFIU6p5QkhhLReupOImZfb1Uxl0p2YqTYxDVtCZmqYaKt/fz58O+axqxG42MgR12YNimE7OmwZIdSxPHHn5rXp1CocjSA/WWE1MC1HOow+nfRw0G7XU5cYhtJCE+JTJyjOS8ZoWuXl5yGEEEKaNUGxYTqZBMXIPQeRh//RzzeyP8d58sXdkIqVfDwKuzKwbdHBE7bCGLYSy0jKYKpd562JmMmC5lrkxUnYtcsdF/by4jghCRkp+XhokgxanW4eO7M3Z9vQEPPYEUIIaT2MtFFmpDx2cLNKOZjnNdHQ/rwn2Z2T5w6uXwk7UvJxaL4ZAxBzfp+7WozBlz5Gb4gjFG2EEEJIJZjiSAoiquH9edbnDmWBxoDWKBVa7MaIZ6nDhU9KRI/W16sReOBcESsuKVV+KhZCCCGEiB6CDZlOw/tznBOWO0xVBiDq8oeRR4IWuyqASYM94HxZz0aQPa+eLbbu5yWEEEKahbCRanh/jnPi3NkylS7qAC12Y8Qz10LZoyIwlyxMp54lr14knRBcPjPv4UsX6ZtY1zIQQgghQUQpUwZSHaNsIxJXsYb35zgnzm0Ztvbrg8aIGLn+gSNBYTcGCo3Be+PhoF6NAeeEX0C4BtE6hBBCSCvgiKX91WOhxvbnnk8dzmkrUw/LJlRbycegsCsHw82FY+aIOkParIGMuTZmJvTnCSei/+bnzak2OE/KiegGgHQnyMETqvPTBSGEEDKeCSkEHyqdLiycHgZtVH8e1aLOPRcsh6Y1IAOpcSrs7rzzTrn22mvl+eefl48++kheeOEF2WGHHUbd74477pBzzjlH3nrrLdlss83kJz/5iey3336Zz5VSsmDBArnuuutk9erVsueee8o111yjty0Hy5RM8sL+VKdeNyHcMyyvTdhKiGXHZMiOiSUp3VBqAY6fVCFpCw1ox0oET3THPpSO0EBNzkcIIYQ0I/2pdon0JtxABV+f3oj+PP8cCIs0fD5340rY9ff3y1577SVf/vKX5fjjjy9pnyeffFIOP/xwWbhwoXz+85+X3/72t3LwwQfL4sWLZZttttHbXHTRRXL55ZfLTTfdJDNnztQicM6cOfLyyy9LLFZ60j/bEUnaIelXbTqZIXLiKGVJskBeG0sc7YSJPHe2znOXqLqyx4Lj4lwYik2pkKwZmiRxa2Q/AkIIIYTkCiv4tRk61YnV0P48WSBnXTnTjRkK5qyAAcsbBFgpFrtDDz1UC8L77rsvs26PPfbQ+8H6h683ffp0+fa3vy3f+c539Odr1qyRKVOmyI033iiHHXZYwePG43G9ePT09MjNv/ixGKEJejC21BDo/PHyalDomBiHd1RINul8fdhMGIQQQggpDhIUv9G3qZjG8CnF6t2fF8JRIt+ef5nWL11dXc2d7uSpp56S2bNn56yDNQ7rwZIlS2T58uU523R3d8vuu++e2aYQsABiO2/ZYIMNxDHC4iijrLw2+UmMx0otGhYhhBBCmqM/H/fCDqIN1jc/eI/13ufeumLbFOKss87Sythbli5dqqMnotZQ2XltqtUYKOoIIYSQxhEZB/15w4TdLbfcIp2dnZnlsccekyARjUa1udO/GCqZMzlwPRsDRR0hhBDSeCIB788bFjxx4IEH6uFQj/XWW6+i40ydOlVWrFiRsw7vsd773Fs3bdq0nG1Kibj1M9aZHfzTj/nfjwZFHSGEEBIcIgHuzxtmsZswYYJsuummmaWtrfQcLX5mzZolDz30UM66Bx98UK8HCMKAuPNvg0CIZ555JrNNkJU+RR0hhBASPCIB7c8Dle4EueveeecdWbZsmX7/6quv6r8QZp7l7aijjtLWPQQ3gNNOO0323ntv+dnPfib777+/3HrrrfLcc8/JL37xC/25YRgyb948ueCCC3TeOi/dCSJlkRalHCwLk/EmxTLHaLmzEjJkp3Q2aUfnxYkXjdKxVTid12bkSFfbsSSpRNaKfSjtzGNHCCGElMxAql2sgY30vKxWGbM41aI/L4TtYKKzcSjs7r33Xjn66KMz771UJEgufN555+nXEH6mmTU0fvKTn9S56+bPny9nn322Fm933313JocdOOOMM3RKlBNOOEEnKEauvEWLFpWVww4gMQzy1xlVyBADtY6pyIZsb0qy3IqO21GJO1GJmnG9Lc47Eg4GipWh96vUD5AQQghpReJ2VPehjmGIMUp/W+v+vBDIyDGu89gFEQzfXvnTsyUWDYlZ+vWtyDRbibmWeewIIYSQ2uWxq1d/PtY8doGy2AUdJYZW2tVUwpZhi2MkJWFHMoocs0hgvld8BsFWCigX9o8XyFhNCCGEkOLEM32w2fD+vBDlmOAo7MrANrtk0DZrJhrjaedLA1OKOKYknWjZMbvvDMwQ06hMesIMbYuVOZopthhVtE6WVgYMK1v6egBLl6H+RmUtlNM3uH7VgOFt1kcW1odXBtaHB+sjC+tj7PXhwDDiRNN7qgb352ODwq7MykKDHWvak0KgMWbP496c5ZYNTQhPBUaFNzV+GGzbbRIYbg6bKRyy7qScUOZpJ2TZDfmRslVIB6QAw8QPZaruZWB9ZGF9ZGF9uLA+srA+xl4fhhbG6H3H3sePtT8vhCdWS4HCrmxU1Z9CMPEwqh7K3j2D2wwg0sosmm7ElfywwESMJwrLdPRExHE7JgkVlZgxWLenLjxtDSmkvTGkLTSkJ0VGmcqZwq0awCcC0UuIdgLwjzCVqmu6GdZHFtaHC+sjC+sjC+ujOvXh6D2RSWNserRq/Xke5YRDjPspxcY7aAQq3QhQ8driJo5ryNYNpB5lMHWoNix9MRM3ga1vBh3l4yDKp043peNFFLllQFlQJpRtLL4J5ZDv6FrtuQFLgfWRhfXhwvrIwvrIwvoIVn3YAejPAS12ZWBkFH11WmrK8RqBLSFf3pyQkUp/ZomtVM5nRUGRDPepoJwcPDDfJ/STVkrarf7M0xUaRsiwZcBu109e7Wb2s1rclANOh37dEerLKX/I7JUBu0OXsd0aKOu7lQtC0lMqLDFrKCdcPWQiR5Gj/S8s5QwLZa8mrI8srA8X1kcW1kcW1kd168N2LN23a3erCvr4qvbnBTDKSHdCYVcO2kRbzkh3cZLpikYjCBeoaKxLOtBrlqQc9/1o6LH8MoZi0dgG7XYtBnFD5N94puVIh9EnA6lOvV2hbapyU9qd+kkLxx/W6A2RTqNX+tNlaDcKbFOlUHfc/DFrsGC6mLbQoBj4sfSeTGvwY8n6yML6cGF9ZGF9ZGF9VL8+VLpwngGn0f15PuX4/VHYlRtxg8pX1TTXOkUTD+IzW6E6LUk6bmBE0bKlExQntb+FVZb5PGy4pvtihM243rYn2Z02b0tNzOeOsiRhFy47ygj/ib5kV9V9WPzDGUhmg1D1QuAzy0jKYKpdO+hW04eF9ZGF9eHC+sjC+sjC+qhNfThIZaYTFMM61tj+vBDltCD62NWZ/DH40ajFGH2+T8RoNxoaZLV9Job7RIzcbFHGWvhMlJs8shY+LKyPLKwPF9ZHFtZHFtZHsOrDDkB/XggKu7Iw6toIatEYyr0pa3FzlntT1urmrDQjeDV/LFkfWVgfLqyPLKyPLKyPYNWHHYD+vBgUdmVRuYddpY2gmo2h0puymjdnpTdltW/OsU7zUo0fS9ZHFtaHC+sjC+sjC+sjWPVhB6A/HwkKuzLB+Hg5k/FWoxFUozGM9aasxs051puyWjdntebuG8uPJesjC+vDhfWRhfWRhfURrPqwA9CfjwaFXVm4DcmRbGbrejWCsTSGat2UY7k5q3VTjvXmrNaP5Fh+LFkfWVgfLqyPLKyPLKyPYNWHHYD+vBQYFVsmhqREQdghtFlhupLirTLlawTI6VMtcKyUcjNa28p9n0llZ2CtyrspY2IatrRVMSIJxzOtARm02yTuxEY8dvamNKQNuYSqFSFmiLSbAzLotOnv2DbKDY9M5CknIlH9I+lmaa8GMR2d5h4ff0c6NusjC+vDhfWRhfWRhfVR3/qIpFPCFEt3Uu/+vEBxSz9m1UrXAqDh6emFEd6tInrCY0OlxDSHNzSEl6OiMBEyEkZWm7DhuHPipZMeQvmbhilhM5l5kkCeITyNYF0tcgjheS9kJnWOoISKSIc1/By4KfE5mBDuqUlOp7BK6HMgIWfBXEY671NMkiokbaEBndCz6mWwEmLZMX0eS1IFz8H6yML6cGF9ZGF9ZGF91L8+kjplC7zonWEJiuvdnxc6B6yVpUJhVwZoZEhiiH+4GWwJSUpCYjm5lju/ssfTRTkVUg7usfVZ9F+EdiCPnds4TP00hGTFESOhn/xqRdSM63MhT5H/yQvXC09DyA+Ep1OlLEkWyTM0VvAdB1Wb9Ca7hj0J48kUC55MLXEkWSTv01jBscNGSueNsnXeqOyTMOuD9cH6YH14sD6CVx8p5QorDHihB29kf448d37LHVy/dNlKhMKuTFRmyFPEUq64w6JguTPUsDH4Wk+Th3PAfItz4n+dpFjcJy34D0TNIS1Ga1kOPN1ErSF9zgGnXfsuAL9PBLZxqjJnR7FC4AdiSJ8TGcY9Pwy/jwqeDmtahvQTKH6i405E/4VPi99HhfXB+mB9sD5YH8Grj4gRl4TgOoREAtCfY3gW711RB6nGmSfqgl/c4cIrpbQht1qOlZU0Bpj3cTNUy9G1XIdY3Jy4IUG1HF3LdYjF+VEO+HHgxqyW43GpeOfCDzSyoWNhfbA+WB8urA8X1kfw6sNIBzIEpT93Z6pAJeD/0oeAGRVbFb8794K7jcD1d6s3MJnj3O4ThhfxU98yuDfnkDadY8Hret2U+T+WuAa4FqiLev5IeuCc7g3K+mB9uLA+srA+XFgfAasPgSiyG96fu9GyrrDU7yVVlr2Swq4K+Me+tetlmXnuqlIGreyzJFV1po8pB/hEwDfEA6+rMX1Mufi/O54+qzV9TDngnDh3oTLVC9ZHFtZHFtaHC+sjC+sji+vWFIT+PHvecvzrAIdiSwRmWRdMFOxLJ6IbARZHG3BRAa4ZF5/Up1W6tjpUvJK2kPvEg4mhDcOQSA0ieAqBb4oIKx2SHnLDxodSURly2nWZ6nVrJJyQDiCJWMjXBMfgmDbvx0Lxuj39uT4qUe0X0h4akqQTYn2wPlgfaVgfWVgfAaoPAz04+nIjMP05rIcoiT+JmV9/FMNQpWxF5N1335UNNtig0cUghBBCSIuydOlSWX/99UfchsKuRBzHkWXLlsmECRP0k0yj6Onp0QITldvV1SWtCK8BrwHgNeA18OB14DVo9muglJLe3l6ZPn26mObIw/Ucii0RXMjRVHI9QaNttoZbLrwGvAaA14DXwIPXgdegma9Bd3d3SdsxeIIQQgghpEmgsCOEEEIIaRIo7MYZ0WhUFixYoP+2KrwGvAaA14DXwIPXgdcA8Bq4MHiCEEIIIaRJoMWOEEIIIaRJoLAjhBBCCGkSKOwIIYQQQpoECjtCCCGEkCaBwq7B3HnnnfKZz3xGJk2apGe0+Pvf/17SfnfccYdsueWWEovFZNttt5X7778/53PExJx77rkybdo0aWtrk9mzZ8trr70mQeSqq66SjTbaSH+X3XffXZ599tmW+e7g0UcflQMOOEBnFEcbuPvuu0fd55FHHpGddtpJR39tuummcuONN475ujaShQsXyq677qpndll33XXl4IMPlldffXXU/ZqpLVxzzTWy3XbbZZKrzpo1S/74xz+2zPcvxI9//GN9T8ybN6+lrsN5552nv7d/wfdrpWsA3nvvPTnyyCN1/4gy43s999xzLfXbWBGIiiWN4+abb1bnn3++uu666xCdrF544YVR93niiSeUZVnqoosuUi+//LKaP3++CofD6sUXX8xs8+Mf/1h1d3eru+++W/3jH/9QBx54oJo5c6YaHBxUQeLWW29VkUhE3XDDDeqf//ynOv7449XEiRPVihUrmv67e9x///3q+9//vrrzzjt1G7jrrrtG3P7NN99U7e3t6vTTT9fX4IorrtDXZNGiRRVf10YzZ84c9atf/Uq99NJL6u9//7vab7/91IYbbqj6+vqK7tNsbeHee+9Vf/jDH9S///1v9eqrr6qzzz5bfx9ck1b4/vk8++yzaqONNlLbbbedOu2004pu14zXYcGCBWrrrbdW77//fmZZtWpVS12Djz76SM2YMUN97WtfU88884z+3XvggQfU66+/3lK/jZVAYRcQlixZUrKw+/KXv6z233//nHW77767OvHEE/Vrx3HU1KlT1cUXX5z5fPXq1Soajarf/e53Kkjstttu6pRTTsm8t21bTZ8+XS1cuLDpv3shShF2Z5xxhv7R93PooYdqcVTpdQ0aK1eu1Nfir3/9a9Ftmr0tgLXWWktdf/31Lff9e3t71WabbaYefPBBtffee48o7JrxOkDYbb/99iVv34zX4Mwzz1R77bVXWfu0wm9jKXAodhzy1FNPaTO6nzlz5uj1YMmSJbJ8+fKcbTDHHEzO3jZBIJFIyPPPP59TTszJi/fFytks330sjHYNKrmuQWPNmjX679prr110m2ZuC7Zty6233ir9/f16SLbVvv8pp5wi+++//7Dv10rXAcOkcM/YeOON5YgjjpB33nmnpa7BvffeK7vssosccsgh2j1jxx13lOuuu05a/bexFCjsxiG4QadMmZKzDu+x3vvcW1dsmyDwwQcf6A6snHI2y3cfC8WuQU9PjwwODlZ0XYOE4zjap2rPPfeUbbbZpuh2zdgWXnzxRens7NT+QSeddJLcddddstVWW7XM9wcQtIsXL9Z+l6XQjNcBggu+YYsWLdK+lxBmn/rUp6S3t7dlrsGbb76pv/tmm20mDzzwgJx88snyzW9+U2666aaW/W0slVDJW5Ixc8stt8iJJ56YeQ/HaNyshJBca81LL70kjz/+uLQaW2yxhQ6ggsXy97//vcydO1f++te/FhV3zcbSpUvltNNOkwcffFA7trcqn/vc5zKvEVADoTdjxgy5/fbb5dhjj5VWAA94sNj96Ec/0u9hscPvwrXXXqvvC1IcWuzqyIEHHqh/tL0FjbYSpk6dKitWrMhZh/dY733urSu2TRBYZ511xLKsssrZLN99LBS7BoikRORYJdc1KJx66qly3333ycMPPyzrr7/+iNs2Y1uIRCI6km/nnXfWFqvtt99eLrvsspb5/hgmW7lypY5qDIVCeoGwvfzyy/VrWFta4TrkM3HiRNl8883l9ddfL/h5M14DRO/mP9B84hOfGHFIupl/G8uBwq6OIJUDfrS9BQ2tEuBz89BDD+WswxOu54szc+ZM3Uj928AU/cwzzxT112lUJ4YOzF9OPKXhfbFyNst3HwujXYNKrmujQdwIRB2GHv/yl7/oehyNVmgLqLd4PN4y33/ffffVw9H5D8DwMcNrdMqtcB3y6evrkzfeeEOLnUI04zWAK0Z+yqN///vf2nLZSr+NFVFSiAWpGR9++KGOhEWaA1QHQrHxHuHtHl/96lfV9773vZzQ9lAopH7605+qV155RUdQFQptRwj3Pffco/7f//t/6qCDDgpkaDu+LyKzbrzxRh2efsIJJ+hyL1++vOm/uz8CEHWOBW3g5z//uX799ttv68/x/XEd8kP6v/vd7+prcNVVVxUM6R/pugaNk08+WadieOSRR3JSPAwMDGS2afa2gO+GKGBEyKOseG8YhvrTn/7UEt+/GPlRsa1wHb797W/rewFtAd9v9uzZap111tHR4q1yDZDuBt/pwgsvVK+99pq65ZZb9O/eb37zm8w2rfDbWAkUdg0GubvQmecvuDH9P2xz587N2e/2229Xm2++uc7Hg/BuCEM/CG8/55xz1JQpU3Qj3nfffXVurCCCXEPIWYbvglD0p59+umW+O3j44YcLtgHve+MvrkP+PjvssIO+BhtvvLFuR+Vc16BR6Ptj8X+vZm8LxxxzjM7bhe8yefJkXVZP1LXC9y9V2LXCdUCKjmnTpunvs9566+n3/vxtrXANwP/93/+pbbbZRpd3yy23VL/4xS9yPm+F38ZKMPBfZbY+QgghhBASJOhjRwghhBDSJFDYEUIIIYQ0CRR2hBBCCCFNAoUdIYQQQkiTQGFHCCGEENIkUNgRQgghhDQJFHaEEEIIIU0ChR0hhBBCSJNAYUcIIVXil7/8pXzmM5+p+XkWLVokO+ywg57nkhBC/FDYEUJIFRgaGpJzzjlHFixYUPNzffazn5VwOCy33HJLzc9FCBlfUNgRQkgV+P3vfy9dXV2y55571uV8X/va1+Tyyy+vy7kIIeMHCjtCCPGxatUqmTp1qvzoRz/KrHvyySclEonIQw89VHS/W2+9VQ444ICcdZ/+9Kdl3rx5OesOPvhgLco8NtpoI7ngggvkqKOOks7OTpkxY4bce++9uhwHHXSQXrfddtvJc889l3McnAvr3njjjSp8a0JIs0BhRwghPiZPniw33HCDnHfeeVo49fb2yle/+lU59dRTZd999y263+OPPy677LJLRee85JJLtKXvhRdekP3331+fD0LvyCOPlMWLF8smm2yi3yulMvtsuOGGMmXKFHnssccqOichpDmhsCOEkDz2228/Of744+WII46Qk046STo6OmThwoVFt1+9erWsWbNGpk+fXvH5TjzxRNlss83k3HPPlZ6eHtl1113lkEMOkc0331zOPPNMeeWVV2TFihU5++F8b7/9dkXnJIQ0JxR2hBBSgJ/+9KeSSqXkjjvu0EEK0Wi06LaDg4P6bywWq+hcGGr1gBUObLvttsPWrVy5Mme/trY2GRgYqOichJDmhMKOEEIKAN+1ZcuW6ZQib7311ojbTpo0SQzDkI8//njU49q2PWwdIlw9cJxi6/LTm3z00Ud66JgQQjwo7AghJI9EIqH92w499FD54Q9/KMcdd9wwa5kfBFZstdVW8vLLLw/7LH/49M0336xaehWIzx133LEqxyOENAcUdoQQksf3v/997TOHdCLwb4Of2zHHHDPiPnPmzNEBFPncc889cuedd2oRduGFF2rxB7+49957b0xlfPrpp/Xw8KxZs8Z0HEJIc0FhRwghPh555BG59NJL5de//rXOS2eapn6N6NNrrrmm6H7HHnus3H///VoQ+kGU60UXXaQteo8++qhcffXV8uyzz+pjjoXf/e53Orijvb19TMchhDQXhvLHzxNCCKkYRLHutNNOctZZZ2Xy2GHqLwjFavLBBx/IFltsodOxzJw5s6rHJoSMb2ixI4SQKnHxxRfrhMK1BsEcsPxR1BFC8qHFjhBCakStLHaEEFIMCjtCCCGEkCaBQ7GEEEIIIU0ChR0hhBBCSJNAYUcIIYQQ0iRQ2BFCCCGENAkUdoQQQgghTQKFHSGEEEJIk0BhRwghhBDSJFDYEUIIIYRIc/D/AQ8AT2hJbUZtAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sim_opt = make_sim(**results.optimizer.max[\"params\"])\n",
+    "sim_opt.plot(z=h / 2, monitor_alpha=0.2)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9a35c633",
+   "metadata": {},
+   "source": [
+    "Run the optimized simulation (cached) again and plot the real part of `Hz` on the $xy$ plane to confirm efficient coupling into the slot plasmonic mode.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "4c3b07b1-ba41-4577-9a54-911680c99b93",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:29:23 Eastern Daylight Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'optimal design'</span> with task_id       \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-33c63420-9e17-4c9c-b46a-929b1a526b2a'</span> and  \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:29:23 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'optimal design'\u001b[0m with task_id       \n",
+       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-33c63420-9e17-4c9c-b46a-929b1a526b2a'\u001b[0m and  \n",
+       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-33c63420-9e17-4c9c-b46a-929b1a526b2a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-33c63420-9e17-4c9c-b46a-929b1a526b2a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-33c63420-9e17-4c9c-b46a-929b1a526b2a'</span></a>.     \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
+       "\u001b[2;36m                               \u001b[0m\u001b]8;id=707335;https://tidy3d.simulation.cloud/workbench?taskId=fdve-33c63420-9e17-4c9c-b46a-929b1a526b2a\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=182780;https://tidy3d.simulation.cloud/workbench?taskId=fdve-33c63420-9e17-4c9c-b46a-929b1a526b2a\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[2;36m                               \u001b[0m\u001b]8;id=707335;https://tidy3d.simulation.cloud/workbench?taskId=fdve-33c63420-9e17-4c9c-b46a-929b1a526b2a\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=169619;https://tidy3d.simulation.cloud/workbench?taskId=fdve-33c63420-9e17-4c9c-b46a-929b1a526b2a\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=707335;https://tidy3d.simulation.cloud/workbench?taskId=fdve-33c63420-9e17-4c9c-b46a-929b1a526b2a\u001b\\\u001b[32m-33c63420-9e17-4c9c-b46a-929b1a526b2a'\u001b[0m\u001b]8;;\u001b\\.     \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/639eb096-a602-4b56-a502-cac1f18f9557\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                          \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=684768;https://tidy3d.simulation.cloud/folders/639eb096-a602-4b56-a502-cac1f18f9557\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                          \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d7b1582d16c74fbaa7aef8462d8dda28",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:29:24 Eastern Daylight Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.448</span>. Minimum cost     \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>depends on task execution details. Use           \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed       \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>FlexCredit cost after a simulation run.          \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:29:24 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.448\u001b[0m. Minimum cost     \n",
+       "\u001b[2;36m                               \u001b[0mdepends on task execution details. Use           \n",
+       "\u001b[2;36m                               \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed       \n",
+       "\u001b[2;36m                               \u001b[0mFlexCredit cost after a simulation run.          \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:29:25 Eastern Daylight Time </span>status = success                                 \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:29:25 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                 \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "908aa64d782d4c28b140fa3a80e47569",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:29:26 Eastern Daylight Time </span>loading simulation from simulation_data.hdf5     \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m21:29:26 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5     \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sim_data_opt = web.run(sim_opt, \"optimal design\")\n",
+    "sim_data_opt.plot_field(\"field\", \"Hz\", \"real\", vmax=0.5)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "70878b72",
+   "metadata": {},
+   "source": [
+    "Finally, compute and plot power transmission from the mode monitor across the wavelength range.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "25073db1-15bb-4b39-b2f2-f9f0f2e53b18",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "amp = sim_data_opt[\"mode\"].amps.sel(mode_index=0, direction=\"+\")\n",
+    "T = np.abs(amp) ** 2\n",
+    "plt.plot(ldas, T, c=\"red\", linewidth=2)\n",
+    "plt.xlabel(\"Wavelength (μm)\")\n",
+    "plt.ylabel(\"Transmission\")\n",
+    "plt.ylim(0, 1)\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "applications": [
+   "Passive photonic integrated circuit components"
+  ],
+  "description": "This notebook demonstrates the FDTD simulation and Bayesian optimization of a silicon to plasmonic waveguide coupler using Tidy3D.",
+  "feature_image": "./img/silicon_to_plasmonic.png",
+  "features": [
+   "Global optimization"
+  ],
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "keywords": "silicon photonics, waveguide, coupler, plasmonic, photonic integrated circuits, Tidy3D, FDTD",
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.0"
+  },
+  "title": "Dielectric to Plasmonic Waveguide Coupler | Flexcompute"
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/case_studies/pic.rst b/docs/case_studies/pic.rst
index 0dded619..a8a2ee1c 100644
--- a/docs/case_studies/pic.rst
+++ b/docs/case_studies/pic.rst
@@ -11,6 +11,7 @@ Passive photonic integrated circuit (PIC) components form the backbone of many o
     ../../WaveguideToRingCoupling
     ../../WaveguideCrossing
     ../../EulerWaveguideBend
+    ../../DirectionalCoupler
     ../../EdgeCoupler
     ../../EffectiveIndexApproximation
     ../../GratingCoupler
@@ -46,4 +47,4 @@ Passive photonic integrated circuit (PIC) components form the backbone of many o
     ../../AnisotropicMetamaterialBroadbandPBS
     ../../SWGWaveguideCrossing
     ../../SiWaveguideTPA    
-    ../../DirectionalCoupler
+    ../../SiliconToPlasmonicCoupler
diff --git a/img/silicon_to_plasmonic.png b/img/silicon_to_plasmonic.png
new file mode 100644
index 00000000..593b8744
Binary files /dev/null and b/img/silicon_to_plasmonic.png differ