{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1535d9e4-b444-46e3-9a39-9d5a6ce1f724",
   "metadata": {},
   "source": [
    "# Adjoint-based shape optimization of a waveguide bend\n",
    "\n",
    "In this notebook, we will apply the adjoint method to the optimization of a low-loss waveguide bend. We start with a 90 degree bend in a SiN waveguide, parameterized using a `td.PolySlab`. \n",
    "\n",
    "We define an objective function that seeks to maximize the transmission of the TE0 output mode amplitude with respect to the position of the polygon vertices defining the bend. A penalty is applied to keep the local radii of curvature larger than a predefined value.\n",
    "\n",
    "The resulting device demonstrates low loss and exhibits a smooth geometry.\n",
    "\n",
    "> To install the `autograd` package required for this feature, we recommend running `pip install autograd`.\n",
    "\n",
    "<img src=\"img/adjoint_8.png\" width=400 alt=\"Schematic of the waveguide bend\">\n",
    "\n",
    "If you are unfamiliar with inverse design, we also recommend our [intro to inverse design tutorials](https://www.flexcompute.com/tidy3d/learning-center/inverse-design/) and our [primer on automatic differentiation with tidy3d](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd1Intro/).\n",
    "\n",
    "## Setup\n",
    "\n",
    "First, we import `tidy3d`. We will also use `numpy`, `matplotlib` and `autograd`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "49188672-e1c3-43f1-92c0-a575810aa0ac",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:06.838269Z",
     "start_time": "2026-03-17T10:59:02.677947Z"
    }
   },
   "outputs": [],
   "source": [
    "import autograd as ag\n",
    "import autograd.numpy as anp\n",
    "import matplotlib.pylab as plt\n",
    "import numpy as np\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba08a4ef-c31c-41bc-bff7-922bf83a7b1e",
   "metadata": {},
   "source": [
    "Next, we define all the global parameters for our device and optimization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "330887eb-6c9a-4173-8b73-b7583c8c5869",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:06.858090Z",
     "start_time": "2026-03-17T10:59:06.853028Z"
    }
   },
   "outputs": [],
   "source": [
    "wavelength = 1.5\n",
    "freq0 = td.C_0 / wavelength\n",
    "\n",
    "# frequency of measurement and source\n",
    "# note: we only optimize results at the central frequency for now.\n",
    "fwidth = freq0 / 10\n",
    "num_freqs = 1\n",
    "freqs = np.linspace(freq0 - fwidth / 2, freq0 + fwidth / 2, num_freqs)\n",
    "freqs = np.array([freq0])\n",
    "\n",
    "# define the discretization of the bend polygon in angle\n",
    "num_pts = 60\n",
    "angles = np.linspace(0, np.pi / 2, num_pts + 2)[1:-1]\n",
    "\n",
    "# refractive indices of waveguide and substrate (air above)\n",
    "n_wg = 2.0\n",
    "n_sub = 1.5\n",
    "\n",
    "# min space between waveguide and PML\n",
    "spc = 1 * wavelength\n",
    "\n",
    "# length of input and output straight waveguide sections\n",
    "t = 1 * wavelength\n",
    "\n",
    "# distance between PML and the mode source / mode monitor\n",
    "mode_spc = t / 2.0\n",
    "\n",
    "# height of waveguide core\n",
    "h = 0.7\n",
    "\n",
    "# minimum, starting, and maximum allowed thicknesses for the bend geometry\n",
    "wmin = 0.5\n",
    "wmid = 1.5\n",
    "wmax = 2.5\n",
    "\n",
    "# average radius of curvature of the bend\n",
    "radius = 6\n",
    "\n",
    "# minimum allowed radius of curvature of the polygon\n",
    "min_radius = 150e-3\n",
    "\n",
    "# name of the monitor measuring the transmission amplitudes for optimization\n",
    "monitor_name = \"mode\"\n",
    "\n",
    "# how many grid points per wavelength in the waveguide core material\n",
    "min_steps_per_wvl = 20\n",
    "\n",
    "# how many mode outputs to measure\n",
    "num_modes = 3\n",
    "mode_spec = td.ModeSpec(num_modes=num_modes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "491189f1-8d54-45d2-bd14-f0e46163cdc5",
   "metadata": {},
   "source": [
    "Using all of these parameters, we can define the total simulation size."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "099d588f-6745-4db4-8ca0-452a498e6d2b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:06.965668Z",
     "start_time": "2026-03-17T10:59:06.963217Z"
    }
   },
   "outputs": [],
   "source": [
    "Lx = Ly = t + radius + abs(wmax - wmid) + spc\n",
    "Lz = spc + h + spc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89afa716-793b-40ff-b762-2dfccf05c867",
   "metadata": {},
   "source": [
    "### Define parameterization\n",
    "\n",
    "Next we describe how the geometry looks as a function of our design parameters.\n",
    "\n",
    "At each angle on our bend discretization, we define a parameter that can range between `-inf` and `+inf` to control the thickness of that section. If that parameter is `-inf`, `0`, and `+inf`, the thickness of that section is `wmin`, `wmid`, and `wmax`, respectively.\n",
    "\n",
    "This gives us a smooth way to constrain our measurable parameter without needing to worry about it in the optimization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "104ab125-3ac9-4569-ab70-873acd41f0fc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:06.981304Z",
     "start_time": "2026-03-17T10:59:06.977911Z"
    }
   },
   "outputs": [],
   "source": [
    "def thickness(param: float) -> float:\n",
    "    \"\"\"thickness of a bend section as a function of a parameter in (-inf, +inf).\"\"\"\n",
    "    param_01 = (anp.tanh(param) + 1.0) / 2.0\n",
    "    return wmax * param_01 + wmin * (1 - param_01)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7261fdc3-9520-4995-9610-1586d330ed13",
   "metadata": {},
   "source": [
    "Next we write a function to generate all of our bend polygon vertices given our array of design parameters. Note that we add extra vertices at the beginning and end of the bend that are **independent** of the parameters (static) and are only there to make it easier to connect the bend to the input and output waveguide sections."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f04524c0-9ac4-4990-a142-c3596323606d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:07.031742Z",
     "start_time": "2026-03-17T10:59:07.028331Z"
    }
   },
   "outputs": [],
   "source": [
    "def make_vertices(params: np.ndarray) -> list:\n",
    "    \"\"\"Make bend polygon vertices as a function of design parameters.\"\"\"\n",
    "    vertices = []\n",
    "    vertices.append((-Lx / 2 + 1e-2, -Ly / 2 + t + radius))\n",
    "    vertices.append((-Lx / 2 + t, -Ly / 2 + t + radius + wmid / 2))\n",
    "    for angle, param in zip(angles, params):\n",
    "        thickness_i = thickness(param)\n",
    "        radius_i = radius + thickness_i / 2.0\n",
    "        x = radius_i * np.sin(angle) - Lx / 2 + t\n",
    "        y = radius_i * np.cos(angle) - Ly / 2 + t\n",
    "        vertices.append((x, y))\n",
    "    vertices.append((-Lx / 2 + t + radius + wmid / 2, -Ly / 2 + t))\n",
    "    vertices.append((-Lx / 2 + t + radius, -Ly / 2 + 1e-2))\n",
    "    vertices.append((-Lx / 2 + t + radius - wmid / 2, -Ly / 2 + t))\n",
    "    for angle, param in zip(angles[::-1], params[::-1]):\n",
    "        thickness_i = thickness(param)\n",
    "        radius_i = radius - thickness_i / 2.0\n",
    "        x = radius_i * np.sin(angle) - Lx / 2 + t\n",
    "        y = radius_i * np.cos(angle) - Ly / 2 + t\n",
    "        vertices.append((x, y))\n",
    "    vertices.append((-Lx / 2 + t, -Ly / 2 + t + radius - wmid / 2))\n",
    "    return vertices"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e5f676f-0e63-4e41-9df9-514afd08eb7e",
   "metadata": {},
   "source": [
    "Let's try out our `make_vertices` function on a set of all `0` parameters, which should give the starting waveguide width of `wmid` across the bend."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "580d21d7-6423-4299-b889-676294966565",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:07.082983Z",
     "start_time": "2026-03-17T10:59:07.079834Z"
    }
   },
   "outputs": [],
   "source": [
    "params = np.zeros(num_pts)\n",
    "vertices = make_vertices(params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cea18164-b71b-4fca-9d0e-801390531f9c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:07.221183Z",
     "start_time": "2026-03-17T10:59:07.131381Z"
    }
   },
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(*np.array(vertices).T)\n",
    "ax = plt.gca()\n",
    "ax.set_aspect(\"equal\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b4df320-a42a-463c-9a9a-bcd84c7f7dd3",
   "metadata": {},
   "source": [
    "Looks good, note again that the extra points on the ends are just to ensure a solid overlap with the in and out waveguides. At this time, the autograd differentiation does not handle polygons that extend outside of the simulation domain so we need to also ensure that all points are inside of the domain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "044f2377-62e8-4be8-9815-87cc1368d3ba",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:07.232813Z",
     "start_time": "2026-03-17T10:59:07.230915Z"
    }
   },
   "outputs": [],
   "source": [
    "def make_polyslab(params: np.ndarray) -> td.PolySlab:\n",
    "    \"\"\"Make a `tidy3d.PolySlab` for the bend given the design parameters.\"\"\"\n",
    "    vertices = make_vertices(params)\n",
    "    return td.PolySlab(vertices=vertices, slab_bounds=(-h / 2, h / 2), axis=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b57aa022-e979-4a19-9826-016ec22574ca",
   "metadata": {},
   "source": [
    "Let's visualize this as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ea0df1fd-0c81-4185-9455-81c1a2af2a4a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:07.385361Z",
     "start_time": "2026-03-17T10:59:07.280739Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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vikWXdXvrrbfE0NBQUaVSiS1bthR//PHHMvPdOpUlOTm51OOZmZniiBEjRF9fX9HNzU3s2bNnuT+jq1evFqOiokS1Wi02bNhQnDlzpmg2m+/5NVDtEETxDtuviIiIXAj3MRIREZXAYiQiIiqBxUhERFQCi5GIiKgEFiMREVEJLEYiIqISXOoEf7vdjrS0NHh6et7V3QuIiMg5iaKI3NxcBAUFVXijAMDFijEtLc1hLuBMRES17/Lly2jYsGGF87hUMXp6egIoemN0Op3EaYiIqLYYDAYEBwcX90BFXKoYb20+1el0LEYiIhdUmd1oPPiGiIioBBYjERFRCSxGIiKiEliMREREJbAYiYiISmAxEhERlcBiJCIiKoHFSEREVAKLkYiIqASXuvINVZ3NZsPOnTtRUFAAuVwOuVwOhUJR6k+VSgWtVgs3N7dSk0LBHy8icj785KLbstvtWLlyJWbNjsH5s+fu6jkUCgU0Wg08dTp4eXnB18cHvj6+8Pb2hpeXF7y9veHj4wN/f38EBAQgICAA9evXh16v591PiEgyLEYqxW63Y9WqVYiZHYOzCWehDfGG96AWUOg1EEURsIuAWHQLF4gA7CJEux2i1Q5Yi/4sNVlsMFhsyDbdRPLV6xAv2SCzihDNdthNVlgLTLDb7KUyKJVK+PrVQ/2AAISGhCIkJKR4Cg4ORkhICOrXrw+5XC7Nm0REdRqLkQAUFeKvv/6KmNkxOHP6DDR/FaKq/p2vRH8vRFGEaLbBbrTAXmAp+tNoQW6BBdnGVCQcvwTss8KSWwibyVK8nFwhR2BQEJo2aYImjZugcePGaNy4MRo1aoSIiAioVKoazU1EdZcgiqIodYjaYjAYoNfrkZOTw7tr/MVut2PNmjWImR2D+FPx0AR7Q9s+sMYLsapuFagtzwx7ngm2PDNsuSbYDCYIeRaYswtgt9gAADKZDIENgtC6ZSu0atUKLVu2RMuWLdGiRQu4u7tL/EqISApV+fxnMbooURSxZs0azJodg/iTp6AJ9oK2XRBUgY5ViJUliiLs+WbYDCZYcwphyymELbsQyDHDlJ1fPF/DkGC0bd0Gbdq0Qfv27dG+fXuEh4dznyZRHcdiLAeLsahAfvvtN8yKmYWTJ05C09CraIQYWHffD7vFBluWEdYsI6yZRtizC2HPKoQ51wgA8NR5ol379ujcsVNxWTZu3BgyGc9mIqorWIzlcOViFEUR69evx6yYWfgz7k9oGvxViEGu9T6UZCuwwJqRD0tGPmwZBRCzTMWjS0+dJ+677z5079YdXbt2RZcuXaDX6yVOTER3q04W42effYbPPvsMFy9eBAC0bNkSMTExePjhhyv9HK5YjKIoYuPGjZgVMwvHjx2HpoEe2vZBLl2IFbEXWmHJyIflRh5sN/JhSy+ApcAEQRDQpGkT9Li/B7p3745evXohLCxM6rhEVEl1shjXrVsHuVyOxo0bQxRFfPfdd1iwYAGOHz+Oli1bVuo5XKkYRVHEpk2bMCtmFo4dPQZNkB7a9oFQBum4P60KRFGELacQlut5sFzPg5hhRGFGLiACDRo2QN8+fdGrVy8WJZGDq5PFeDs+Pj5YsGABRowYUan5XaEYRVHEli1bMCtmFo4cPgJNoB6a9oFQNWAhVhd7oRXmawZY0nJhv16AwnQDIAJBDYLQt09f9OvXDw8++CD8/f2ljkpEf6nK579Tnsdos9mwcuVK5Ofno2vXruXOZzKZYDKZir82GAy1EU8Soihi27ZtmDlrJg7/cRia+jp4PdIUqoa8ikx1k2kU0IT5QBPmAwDwNFlhvpqL7DQDVmxaje+//x4A0CaqLR59+BH0798fXbt25bmVRE7CqUaMJ0+eRNeuXVFYWAgPDw8sXboUjzzySLnzz5kzB3Pnzi3zeF0aMYqiiB07dmDmrFk4dPAgNPV1RSNEFqJkbPlmmK/kwHwlB7a0PFgKTHBzd0Pv3n0wcMAAPPbYYwgMDJQ6JpFLqbObUs1mM1JSUpCTk4NVq1bh66+/xu7du9GiRYvbzn+7EWNwcHCdKEZRFLFz507MipmFA/sPQBPwVyEGsxAdiSiKsGbkw3Q5B7bUXJiuGiCKIjp07IDHBz+OQYMGoWXLlvw3I6phdbYY/65v376IjIzEF198Uan568o+xtjYWMyKmYV9v+8rKsR29aEK8eKHqxOwGy0wXc6G+VI2LFcMsJmtCA4JwROPP47HH38c999/P68BS1QD6vw+xlvsdnupEWFdt3v3bsycNQu/790Ljb8nvB5qwkJ0MjKtEtomftA28YNotcOcZkDGpSx89u2X+PDDD1HP3w9PPzUUTz31FEuSSCJOU4zTp0/Hww8/jJCQEOTm5mLp0qXYtWsXtmzZInW0Grd3717MnDULe3bvhtrfE/r+TaAOZSE6O0EhgzrEC+oQL4iiCMv1PBRcyMRXP3yLRYsWsSSJJOI0m1JHjBiBHTt24OrVq9Dr9WjTpg2mTp2KBx98sNLP4WybUn///XfMionBrthYqP08oWlXH+owbxZiHXerJE0XMmG9lAOzwQj/+gF44flhGDZsGNq0aSN1RCKn4zL7GKvKWYpx//79mDlrFmJ37oS6ngc07QKhDmchuqJbJVmYeBPW5GxYCkxo0aolXhr+Ip599lkEBQVJHZHIKbAYy+HoxXjw4EHMmjUL27dvZyFSGaLNDvPlHBQm3oT5UjZEmx29oqPx0osvYsiQIdBqtVJHJHJYLMZyOGox/vHHH5gVMwtbt2wtKsSo+lBH+LAQqVx2kxWm5EyYE7NQmJoND09PDH/hBbzyyiuIioqSOh6Rw2ExlsPRivHw4cOImR2DzZs2Q+37VyFGshCpaqw5hSg8mw5LYhbMuUa0bReF0a+OwrPPPusQP+dEjoDFWA5HKcajR49iVswsbNq4CWofD6jbBUAT4QtBxkKkuyfaRZhSsmE+m4HCS1lQa9T4x9P/wPjx49G+fXup4xFJisVYDqmL8dixY4iJicGGDRug9nGHOqo+NJEsRKp+tnwzjGfTYTmbCbOhAJ27dMY/X/8nhgwZwmu2kktiMZZDqmKMi4tDzOwYrPttHdTefxViIxYi1byiUWQWTKfTUXg5G75+9fDa6DEYNWoUGjRoIHU8olrDYixHbRfjn3/+idlz5mDtmjV/FWIANI3qsRBJEtYsIwrir8OcmAnRasOTTzyJN954A507d5Y6GlGNYzGWo7aK8cSJE5g9Zw7WrF4NtddfhdiYhUiOwW62ovBcBsynM2DKyke37t0wdcpUPPbYY5DJZFLHI6oRVfn85/+CanTq1CkMGTIEbdu2xcbYLdD1jIB+SAtom/qxFMlhyFQKuLWqD/2QltD3a4xjyfEYNGgQGjdtgi+++AJGo1HqiESS4oixGsTHx2Pu3LlYtWoVlDotNLdGiHL+3kHOwXw9F4Unr6PwQia8vL0w4Z8TMH78eHh7e0sdjahacFNqOaq7GM+cOYM5c+Zg5cqVUHpqoY4KgLYJC5GclzWnEAUnr8F8LgNqlQb/fP11TJw4EX5+flJHI7onLMZyVFcxJiQkYO7cuVi+fHlRIbYNgLYpC5HqDluBBQUnrsKUkAGFIMNrY17DG2+8wWuzktNiMZbjXovx3LlzmDt3Ln5etgxKD/VfhejHQqQ6y15oRcHJazCdTodgEzFixAhMmzYNoaGhUkcjqhIWYznuthjPnz+PefPmYenSpVC4/1WIzViI5DrsZiuM8TdgOnUDotmGUaNGYcaMGRxBktNgMZbjbopx8eLFeOWVV4oKsY0/tM38IShYiOSa7BYbjKeuo/DkdcjswPhx4zF16lTugySHx9M1qpFCoYAgCBBFEaLdZX6HILotmVIO93ZB8H66NZQt/fDhJx8hNCwUM2fORFZWltTxiKoFi/EOhg0bhvPnz2PY0GdR8McVZC0/iYKT1yBa7VJHI5KMTK2AR6eG8H66NYTGXnj7f+8gJDQU77zzDs+DJKfHYqyE8PBwfPPNNzh/7jyeG/IP5B+6jOzlJ1FwigVJrk2mVcLzvhB4/6M1bCFumD5jBiIbN8L3338Pu53/N8g5sRirICIiAosXL8bZhLP4xxNDkX/gMrJXnGJBksuTu6mguz8MPk+1QrbahOHDhyOqXRS2b98udTSiKmMx3oVGjRrhu+++Q0JCAoYOevL/CzL+OkQbC5Jcl8JLC92DjeA9qAXOp1/Cgw8+iAf79cPJkyeljkZUaSzGe9C4cWP88MMPOH36NJ4a+ATy9qcUFeRpFiS5NlV9T+gGNIP+wcbYe2Q/2kZFYcyYMbh586bU0YjuiMVYDZo2bYoff/wRp+Pj8eSjg5H3+yVkr4hHwekbLEhyWYIgQBPhA/2TLeDepSG+XvwNIiIjsGjRIlitVqnjEZWLxViNmjVrhqVLlyI+Ph6PPzwAeb9fRPbKeBScYUGS6xLkMri3CYT3061hCVRj3PjxaBPVFrGxsVJHI7otFmMNaN68OZYtW4aTJ09icP/HkLe3qCCNCSxIcl0yrRK6nhHwebwlkjNT0bt3bzw5ZAhSUlKkjkZUCouxBrVs2RLLly/HiRMnMODBR2DYnYycVfEwJqSzIMllKf3coRvQFLrekVi/dSOaNmuKhQsXwmKxSB2NCACLsVa0atUKq1auxIkTJ/BI74dg2H0BOatOw3g2nVfTIZckCAK0jetBP6QFZJFemDJlCtq1b4cDBw5IHY2IxVibWrdujV9/+QVxcXF4qFdfGHZdKBpBnmNBkmuSqRTw7B4K78dbIin9Mrp164ZXX30VmZmZUkcjF8ZilEDbtm2xZvUaHD9+HP0f6AND7K2CzGBBkktS+rlDN7AZPLuHYvH3S9C4SWP8+OOPcKF7HJADYTFKKCoqCmvXrMWxY8fw4P3RMMQmIeeXeBjPsyDJ9QgyAW6t6sPrqVYwegsYNmwYHn7kYVy+fFnqaORiWIwOoF27dlj32zocOXIEfe7rCcPOJOT8chrGRBYkuR65uwq6Po3g1b8JYvftQfPmzfHFF1/w2qtUa1iMDqRDhw7YsGED/vjjD/S+rwcMO5KQ8+tpFCbe5CYlcjnqMG/on2wBe7A7Ro8ejejevZGUlCR1LHIBLEYH1KlTJ2zcsBGHDh1Cr07dkbMjETm/nEZhEguSXItMrYCuZzi8Hm2Gg3GH0bJVS3zwwQew2WxSR6M6zGmKcf78+ejUqRM8PT3h7++PwYMH4+zZs1LHqlGdO3fG5k2bceDAAfRo3xU52xOLRpAXWJDkWtQN9dA/2QKyRl6YOGkSevbqhYsXL0odi+oopynG3bt3Y+zYsTh48CC2bdsGi8WCfv36IT8/X+poNe6+++7Dtq1bsX//fnRv2wU52xKRs/oMCi9ksiDJZciUcui6h8H7sWY4fOIoWrZqhcWLF/P/AFU7QXTSn6r09HT4+/tj9+7deOCBByq1jMFggF6vR05ODnQ6XQ0nrDn79u3DrJgYxO7cCbWfJzTt6kMd5g1BEKSORlQr7CYr8vanwHguHQMGDsDXX30Nf39/qWORA6vK57/TjBj/LicnBwDg4+MjcZLa1717d+zcsQN79uzBfS07IGfr+aIR5EWOIMk1yNQK6KIjoO/XGJu3b0WLli3w22+/SR2L6ginLEa73Y4JEyage/fuaNWqVbnzmUwmGAyGUlNd0qNHD+yKjcWuXbvQuXk75Gw5D8OaMzBdzGJBkkvQhBfd1irfQ8SgQYMwatQoGI1GqWORk3PKYhw7dixOnTqFZcuWVTjf/Pnzodfri6fg4OBaSli7evbsiT27dyM2NhYdmrRB9pZzMKw9A9MlFiTVfXI3FXT9GsGzRzi+WfwN2ndoj1OnTkkdi5yY0+1jHDduHNauXYs9e/YgPDy8wnlNJhNMJlPx1waDAcHBwU6/j7EioigiNjYWM2fNxIH9B6AJ0EHTPhCqYD33QVKdZ80sQF5sMsRcCz768EO8+uqr/LknAHV0H6Moihg3bhxWr16NnTt33rEUAUCtVkOn05Wa6jpBENC7d2/s+30ftm/fjqiIlsjedBaG3xJgSsnmCJLqNIWPG/SDmkMeqcfo0aPx5JAhyMrKkjoWORmnKcaxY8fixx9/xNKlS+Hp6Ylr167h2rVr3J9QDkEQ0KdPH+zftw9bt25Fm9Bm/1+Ql1mQVHcJChl0PcKhf7Ax1m1cj9ZtWvN2VlQlTrMptbzNIYsXL8aLL75YqeeoK6dr3A1RFLF161bMnDUTRw4fgSZQB037IKga6LipieosW64JebEXYEnPx3vvvofx48fz591FVeXz32mKsTq4cjHeIooiNm/ejJmzZuLY0WPQBOqL9kGyIKmOEm125B26jIKT1zB06FB888038PDwkDoW1bI6uY+RqocgCHj44Ydx5PARbNiwAc0DI5C9IQGG9WdhTs2ROh5RtRPkMnh2C4W+byP8snY12ndoj9OnT0sdixwYi9FFCYKARx55BEePHMW6devQNCAcWesTkLP+LMxpdet8TyIA0ET6wmtQc6TcvIqOnTri559/ljoSOSgWo4sTBAGPPfYYjh89hrVr16JJvRBkrTvDgqQ6SeGthW5QM6CBO5599llMmDABVqtV6ljkYFiMBKCoIAcOHIi443FYs2YNGvsGFxXkhrMwXc6G3WiBvdAKu8kKu8UG0WrnTZTJKcmUcnhGR8Czeyg++vgjPNivH27evCl1LHIgPPiGbstut2Pt2rWYFTML8afiy51PkMkgVykgU8ohU8ggKOQQ5QJEpQCoZJCpFBDUcsjUCghqBWRaJeRaJWRuSsi0SggK/m5G0jGnGZC34wIC/etjw7r1FV5ikpwbj0otB4ux6ux2O+Lj43HhwgXYbLbiyWq1wmq1wmg0oqCgAAUFBcV/z83NRU5ODjJu3kRmViaysrKQk52NvNy8MudPKjQqKNzVgJsccFdC7qGC3ENd9KenGjIPNQQZj5almmPLNSF3WxJk+Vb89ONPePzxx6WORDWAxVgOFqO0rFYr0tPTcf369VJTamoqLl++jAvJF3D58mXczPj/zVoyuQwqLzfAQwmZTg25Tg2FtxZybzfItAqeYkLVQrTYkLs7Gcakm5g9ezZiYmIgk3FrRl3CYiwHi9E5FBYW4vLly0hOTsb58+eRmJiIc+fOIeHcWaRcvFR8sITSTQ25txaCXgWFjxsUvm5Q+rpBUMolfgXkjERRRP7xNOQfvoIhQ4bg+++/h1arlToWVRMWYzlYjM7ParUiKSkJ8fHxOHXqFOLj4xF34k8kJSbCZrVBEASofT0AbzUU9dyg9HOHsp47y5IqrTA5E3mxyWjfrh3Wr1vPGyDXESzGcrAY6y6TyYT4+HgcO3YMx44dwx+HD+PkyZMwm0wQZDKo/Twg1NNCGeABVYAHZJ5qboalcllu5CF3axLq1/PHlk2b0bx5c6kj0T1iMZaDxeharFYr4uPjceDAARw4cAB7ft+LixeSAQAqTy1kAW5QBuqgCvKEXK9hUVIptlwTcrcmQmkSsGb1avTp00fqSHQPWIzlYDFSRkYGDh48iL1792L7zh2IO34cdpu9uChVDXRQNdRD7qGWOio5ALvJitwdF2BJM+CLL77AiBEjpI5Ed4nFWA4WI/1dbm4u9u3bh127dmHbju2IO3YcdrsdmnoekAV6QBWshypQx/MtXZhoF5G77yKMp29gzpw5iImJ4dYFJ8RiLAeLke4kMzMT27dvx5YtW7Bh40Zcv3YNcqUcygY6KEO8oA7xgtxdJXVMqmWiKKLgeBryDl/Bq6++ik8//RRyOQ/ociYsxnKwGKkqRFHE6dOnsXHjRqxZuwYHDxwsGk3W10MR7Al1uDcU3m5Sx6RaZExIR+7eZAwYMADLfl7G0zmcCIuxHCxGuhcZGRnYuHEj1q5di02bN8FYYITa1wOKMD00ET5Q+LAkXYHpUhZyd1xAl86dsWH9Bnh5eUkdiSqBxVgOFiNVl8LCQmzduhUrV67E6jVrkJ+X9/8l2cgXCi+OJOoy87Vc5G1NRKPwSGzdshUNGzaUOhLdAYuxHCxGqgkmk6m4JH9dvRr5eXnQ1NdBGekNTaQvZFql1BGpBlizjMjdnAg/vQ92x+5CZGSk1JGoAizGcrAYqaYZjUasX78e333/HTZv3gy7XYQ6xAvqxj5Qh3pDkPPo1rrElmdC7qbz0CvdEbszFi1atJA6EpWDxVgOFiPVpvT0dCxfvhxLvluCo0eOQumuhjLSG9pm/lB4c1NrXWErsCB383lorXLs2L4D7du3lzoS3QaLsRwsRpJKfHw8vvnmGyxeshjZWdnQBOmhauILTaQvz5GsA+yFVuRuOQ95nh1bNm9G9+7dpY5Ef8NiLAeLkaRmMpmwZs0afPHll4jduRNKrRrKJj5wa+EPuU4jdTy6B3azDblbE4HMQqz7bR369u0rdSQqoSqf//xVlagWqdVqPP3009i5YwfOnz+P8WPGQp6ch4xlfyJny3mYLmeXuZkzOQeZSg5d/0aAvxaPPPIINm7cKHUkukssRiKJNGrUCO+++y6upl3Fl198iQiPQGRvPIucVadRcOYGRKtd6ohURYJSDt2DjaBo6InBgwezHJ0Ui5FIYu7u7hg5ciROnTiJ3bt346EH+iJv70VkLTuJvKOpsBstUkekKhDkMnj2iWQ5OjEWI5GDEAQBDzzwANasXo2zZ8/ilRdeguVkOjJ/PgHD3mTYck1SR6RKYjk6NxYjkQNq3LgxPv30U1y5fBkxM2dBc82Cm8tOwLDrAqzZRqnjUSWwHJ0Xi5HIgfn5+SEmJgaXUy7j3YUL4ZEtIHPFSRh2JMFys0DqeHQHfy/HTZs2SR2JKoHFSOQE3N3dMXHiRKRcvIRFixbBx6RB5qqTMGxPhDWLBenIbpWjvIEnBj/+OHbt2iV1JLoDFiORE9FoNBgzZgySky7gm2++gY9Zi5srT8KwMwnWnEKp41E5BLkMuj6RkPlr8ehjj+LQoUNSR6IKsBiJnJBSqcTLL7+MC4lJ+HTRp/DMlSNzxQkY9iTDlseDdByRoJBB92Aj2HVK9OvfDydOnJA6EpWDxUjkxFQqFcaMGYOLF5KxcMFCaK5bkLXiJHIPpcBuskodj/5GUMrh2b8RTGoRvfv0xtmzZ6WORLfBYiSqA7RaLSZNmoRLFy9hxrQZsJ/NQvaKUyg4eQ2ijRcKcCQytQK6hxojTzShV+9oXLx4UepI9DdOVYx79uzBgAEDEBQUBEEQsGbNGqkjETkUT09PzJs3D0mJSXjhmeeRd/AyslfFo/DCTV5qzoHItEp4PtwYWQUGRPfpjRs3bkgdiUpwqmLMz89H27ZtsWjRIqmjEDm0oKAgfP311zjx55/o3fUB5GxLhGHDOZ7i4UDk7ip4PNwIqdev4qGHH0JeXp7UkegvTnt3DUEQsHr1agwePLjSy/DuGuSqNm/ejHGvj8eFxCRomvvBo1NDyDRKqWMRAEtGPgzrz6LXA72wYf16qFQqqSPVSby7xl9MJhMMBkOpicgVPfTQQzh9Kh4LFy6ELKUA2SviURB/HaLdKX8vrlOU9dzh+WAkdsbuxMsvvwy7nfuEpVani3H+/PnQ6/XFU3BwsNSRiCSjUqkwadIkJCUm4vl/PIvc3y/CsC4Blox8qaO5PFUDPTx7heOnpUsxdepUqeO4vDpdjNOnT0dOTk7xdPnyZakjEUkuICAA3377Lfbt24dw34bI+jUeufsvwW62SR3NpWkifeHZNQQLFy7Ee++9J3Ucl1ani1GtVkOn05WaiKhIt27d8OfxOLzzzjuwJ2YjZ1U8Ci9kSh3Lpbm1rg+3qEC88cYb+PXXX6WO47LqdDESUcWUSiUmT56MhDMJePCB3sjZdh6GbYmwFfAekFLx6BwMTYQPnn3uWRw+fFjqOC7JqYoxLy8PcXFxiIuLAwAkJycjLi4OKSkp0gYjcnKhoaFYt24dli9fDm2OiJxV8TCey+C5jxIQBAGevSIgeKnxyKOP4NKlS1JHcjlOdbrGrl27EB0dXebx4cOHY8mSJXdcnqdrEN1ZRkYGXn/9dfz888/QhvrA/f4QyD3UUsdyOXajBTm/JSAyKBQH9h+AXq+XOpJTq8rnv1MV471iMRJV3m+//YaRr45EZk423LoGQ9PYF4IgSB3LpVizjMj5LQG97n8AGzduhFLJc0/vFs9jJKJ7NnDgQCScScDQJ4bAEJuE3B1JsBdy32NtUnhr4dk3Ajt27sT48eOljuMyWIxEVC5vb2/89NNPWLFiBVQ3rcj+5TRMKdlSx3IpqgZ6eNwfii+++AKff/651HFcAouRiO7oqaeewun404ju/gCyN52FYe9FiFZeoaW2uDX3h1vLAIwbPw579+6VOk6dx2IkokoJCgrC5k2b8emnn8KWlIWctWdgzeJFyWuLR9cQKAM8MfjxwTwSv4axGImo0gRBwJgxY3D0yFGE1WuA7NVnUHDmBk/rqAWCXAbPPhHIsxZiwMABKCjgLyU1hcVIRFXWqlUrHDt6DC+/+BJy9yQXHZhjskodq86TaZXw6BuB+DOn8fLLL/MXkhrCYiSiu+Lm5oYvv/wSK1asgPyGGYa1CbzfYy1Q1nOHxwNhWL58ORYuXCh1nDqJxUhE9+Spp55C3PHjaNwwHDlrz8B4Nl3qSHWeJtIXblGBmDZ9Gnbv3i11nDqHxUhE9ywyMhJ/HPoDLzw/DIZdF2DYk8yjVmuYR6dgqOrrMOSpIbh69arUceoUFiMRVQutVotvv/0WX3/9NaxJ2chZlwBbrknqWHWWIBPg0TsCBmMenho6FFYr9/FWFxYjEVWrESNG4NDBg6in1iNn7RmYrxqkjlRnyd2UcO8djv3792HGjBlSx6kzWIxEVO3atWuH40ePoUv7zshefxYFp69LHanOUgXq4N45GAsWLMDq1auljlMnsBiJqEb4+flh544deG3MGOTuvQjD3mSINu53rAlubepDG+GLYS+8gAsXLkgdx+mxGImoxiiVSnzyySf46quvYDmXCcOm87AXcl9YdRMEAR4PhMGisGPo00NhsfBi7/eCxUhENe6VV17Bzp07oSkADL8lwJpTKHWkOkemVsAjOhzHjh3HzJkzpY7j1FiMRFQrevTogcN/HEaQTwAMvyXAfC1X6kh1jtLfA+6dGuB///sftm7dKnUcp8ViJKJa06hRIxw+9Ac6t++EnA1nYUzMkDpSnePWNhCaYG88+/xzuH6dBz3dDRYjEdUqX19f7Ni+Hc/+4xkYdiQh/0+enF6dBEGAR69wGIx5eP7552G384CnqmIxElGtU6vV+P777zFjxgzkHUxB7oFLvCB2NZK7KeH+QCi2b9+O9957T+o4TofFSESSEAQB//3vf/HRRx/BePI6cmMv8HSOaqQO9oJbm/qYMWMGTpw4IXUcp8JiJCJJjR8/HsuWLYP1Yg4MW87DbrZJHanO8OgUDJlejWefexYmEy/PV1ksRiKS3NChQ7FlyxbIMy3I3XSO93asJoJCBveeYThz5gxmz54tdRynwWIkIocQHR2NXbt2QV0owLDhHOxGnqReHZT13OHWIQj/+9//8Pvvv0sdxymwGInIYXTs2BG/7/0dOkEDw/qzsOVx8191cGsbBHV9HZ59/jnk5vL80TthMRKRQ2nVqhX279uPem5eMKw/x6vkVANBJsC9ZxjSrqZh0qRJUsdxeCxGInI4jRo1wv59+9GgXn3kbmQ5VgeFXgO3Lg3x9ddfY9u2bVLHcWgsRiJySCEhIdi393c09A9iOVYTbXN/aBp64aURLyMvL0/qOA6LxUhEDiswMBC/79nLcqwmgiDA/f5QXLt+jTc2rgCLkYgcGsuxein0Gmg7BOHjjz/mUarlYDESkcP7eznacnm06r1wa1UfmkA9hr/0IoxGo9RxHA6LkYicQmBgIPbu3oP6Pv5F5ZhvljqS0xJkAtx7hOLixYuYM2eO1HEcDouRiJxGUFAQdu2MhZdWh9zN53kRgHug8NbCrX0gFr67EHFxcVLHcShOV4yLFi1CWFgYNBoNunTpgj/++EPqSERUi8LDw7FrZyzcRRVyt5zn5ePugVubQCi93TDy1ZGw2XiN2lucqhiXL1+OSZMmYfbs2Th27Bjatm2L/v3748aNG1JHI6Ja1KxZM+zYvgNKo4DcrYkQrbwrx90Q5DK4dQvBkcNH8NVXX0kdx2EIohPdBK1Lly7o1KkTPvnkEwCA3W5HcHAwxo8fj2nTpt1xeYPBAL1ej5ycHOh0upqOS0Q17MCBA4juHQ1ZoDs8+zaCIBOkjuSUDLuTIU81IvH8eQQEBEgdp0ZU5fPfaUaMZrMZR48eRd++fYsfk8lk6Nu3Lw4cOCBhMiKSSteuXfHLql9gSslG7u8XebPju+TRpSFMNjMvF/cXpynGjIwM2Gy2Mr/NBAQE4Nq1a7ddxmQywWAwlJqIqG559NFH8fVXX8N45gbyj6ZKHccpyTRKaDs3wNKlS7Fjxw6p40jOaYrxbsyfPx96vb54Cg4OljoSEdWAl156CW+99Rbyj6ai4PR1qeM4JU2TetA08MKro0fBbHbtU2Gcphjr1asHuVyO69dL/9Bfv34d9evXv+0y06dPR05OTvF0+fLl2ohKRBKYNm0axo0bh7zfL8GUki11HKcjCALcuwUj+cIFfPjhh1LHkZTTFKNKpUKHDh1KDfPtdjt27NiBrl273nYZtVoNnU5XaiKiukkQBHzwwQd45JFHkLvzAiw3C6SO5HQUPm7QtPDHnLlzcPXqVanjSMZpihEAJk2ahK+++grfffcdzpw5gzFjxiA/Px8vvfSS1NGIyAHI5XIsW7YMLZs1R96WRF4d5y54dGwIi2ir1JH+dZVTFePTTz+NhQsXIiYmBlFRUYiLi8PmzZvr7OHFRFR1Hh4e2LhhI7w99EXnOFp44npVyNQKaDoE4vvvv8ehQ4ekjiMJpzqP8V7xPEYi1xEXF4du3btBDNBC92AjCALPcaws0S4iZ80ZtAptgj8O/QGZzKnGULdVJ89jJCKqiqioKCz7eRkKkzORf4yncVSFIBPg1rUhjh45iu+//17qOLWOxUhEddbAgQPx73//G/lHUlGYnCl1HKeiCtRB28gXU6ZNRX5+vtRxahWLkYjqtDfffBNPPPkk8nZfhDWTR6pWhXunhrh58ybee+89qaPUKhYjEdVpgiDguyVL0KxxE+RuS4K9kHfjqCy5TgNNCz/Mf/vtMueQ12UsRiKq8zw8PLDut3XQQonc2Au8pmoVuLdrAIvd6lI3NGYxEpFLCA8Px7Kfl8F0ORv5x9OkjuM0ZBoFNFH18eVXXyIhIUHqOLWCxUhELuOhhx7CrFmzkH8kFaYrOVLHcRpuLQOg8NBgytQpUkepFSxGInIpMTEx6NunD/Jjk2HLM0kdxykIChk0HQKx7rd12Lt3r9RxahyLkYhcilwux88//4x63r7I25kM0WaXOpJT0DTyhdrPE9OmT6vz+2hZjETkcurVq4dfV/0Cy4085B25InUcpyAIArQdArF/335s375d6jg1isVIRC7pvvvuw3/+8x8U/HmN+xsrSRXiBU19HabPmF6nR40sRiJyWVOmTEHv6Gjk774Iu9EidRyHJwgCNB2CcPTIUaxfv17qODWGxUhELksmk+HHH3+Ep9oNubuS6/QoqLqoGuigaeCF6W/OgN1eN/fPshiJyKUFBgbipx9/QmFKFgpOXpM6jsMr2tcYhPiTp/DLL79IHadGsBiJyOU99NBD+Oc//4mCw6mwZvF6qneiCvSEJsQbb86aWSdHjSxGIiIA8+fPR2RkJPJ3XeQpHJWgbR+I82fP4ddff5U6SrVjMRIRAdBqtfj5p6Ww3Czg/RsrQRXgCU2wF+bOm1vn9s2yGImI/tKhQwfMnj0bBcevwnw9V+o4Dk8bFYhTJ09hw4YNUkepVixGIqISpk+fjg4dO6BgzyWIVm5SrYgy0BOaIH2dGzWyGImISlAoFPj+u+9hzzUj7yivilMRQRCgiaqPI4ePYOfOnVLHqTYsRiKiv2nevDnmzJkD44lrsKTnSR3Hoaka6qEJ0GHuvHlSR6k2LEYiotuYPHkyWrdujfw9l3iUagUEQYC6bQD27tmDAwcOSB2nWrAYiYhuQ6lU4rsl38GaZeSNje9AHeYNtY87FixcKHWUasFiJCIqR1RUFKZNmwZj3FVYs4xSx3FYgiBA1dIfa1avRlJSktRx7hmLkYioAjNnzkRIaCjy96XUqSMvq5u2ST0o3FR4//33pY5yz1iMREQV0Gg0+PLzL1CYmo3C8xlSx3FYgkIGVbN6+Pqbr3Hz5k2p49wTFiMR0R08+OCD+Mc//gHjH6mwF1qljuOw3FoGwGqz4vPPP5c6yj1hMRIRVcL7778PtUyFvD8uSx3FYcm0Sqga++L9Dz9AYWGh1HHuGouRiKgS6tevj3fefhvGMzdgucFzG8vj1ro+bqZnYNmyZVJHuWtVLsbhw4djz549NZGFiMihjRo1Cq1at0LBgcs8EKccCi8tNKHe+OCjD532PapyMebk5KBv375o3Lgx3nrrLaSm8ir0ROQa5HI5Fn2yCIXXDCg8xwNxyqNp4Y8/j8fh0KFDUke5K1UuxjVr1iA1NRVjxozB8uXLERYWhocffhirVq2CxWKpiYxERA7jgQcewNChQ2E8kga72SZ1HIekCtZD7eWGjz/+WOood+Wu9jH6+flh0qRJ+PPPP3Ho0CE0atQIw4YNQ1BQECZOnIjz589Xd04iIoexcOFCyKwi79tYDkEQoGxeDytWrMD169eljlNl93TwzdWrV7Ft2zZs27YNcrkcjzzyCE6ePIkWLVpU+0me//3vf9GtWze4ubnBy8urWp+biKgqgoODMWP6DBSeug6rwXmPvqxJ2qZ+EAXgq6++kjpKlQliFfeOWiwW/Pbbb1i8eDG2bt2KNm3a4JVXXsGzzz4LnU4HAFi9ejVefvllZGVlVVvQ2bNnw8vLC1euXME333yD7OzsKj+HwWCAXq9HTk5OcVYiortRUFCAiMgIGDys0PVpJHUch2TYkwxdtgyXL6VAqVRKm6UKn/+Kqj55YGAg7HY7nnnmGfzxxx+IiooqM090dHS1j+rmzp0LAFiyZEm1Pi8R0d1wc3PDW/99CyNGjIC2dX0o/T2kjuRwtC39cX3VKaxfvx6PP/641HEqrcqbUt9//32kpaVh0aJFty1FAPDy8kJycvK9ZrtnJpMJBoOh1EREVF2GDx+O5i2ao+DQFac9NaEmKX3doamvw5dffSl1lCqpcjEOGzYMGo2mJrJUu/nz50Ov1xdPwcHBUkciojpELpfj3YXvojAtB+ZL2VLHcUjKJr7YumUrLl92nisGSXrlm2nTpkEQhAqnhISEu37+6dOnIycnp3hypn8YInIODz30EHr26gXjkTSIdo4a/04T6QtBIXOq3WBVPvimOqWnp9/xKuwRERFQqVTFXy9ZsgQTJkzgwTdE5DD++OMPdOnSBbroSGib1JM6jsMx7L4An3w1Ui5egkwmzXisRg++qU5+fn7w8/OTMgIR0T3r3LkzHhvwGLbtjYUm0geCnJehLknTzA+pa05j+/bt6Nevn9Rx7shp/vVSUlIQFxeHlJQU2Gw2xMXFIS4uDnl5vJgvEUnvv//5L0zZ+TDyUnFlKP09oK7n4TTnNDpNMcbExKBdu3aYPXs28vLy0K5dO7Rr1w5HjhyROhoREdq0aYOhQ4fCFHcNos0udRyHIggClI19sGbNGmRmZkod546cphiXLFkCURTLTL169ZI6GhERgKLzrS15JhjP3JA6isPRNKoHm92GFStWSB3ljpymGImIHF2zZs3w7DPPwHTyBkeNfyN3U0Id7IUl3y2ROsodsRiJiKrRjBkzYMkt5L7G21A18sGhg4eQlJQkdZQKsRiJiKpRixYt8PgTT8B04jrPa/wbTag35GolfvzxR6mjVIjFSERUzWbNnAlzdgEKEys+T9vVCEo5lKF6LPnuO4e+hB6LkYiomkVFReGRRx6B6c9rDl0AUtA0roeLyck4dOiQ1FHKxWIkIqoBM2fOhCkzHyZeQ7UUVZAOKk8tfvrpJ6mjlIvFSERUA7p27You990H00nnu4N9TRJkAhRheixfuQI2m03qOLfFYiQiqiFTp0xBYVoOLNd5ha6S1BE+SL9+A/v27ZM6ym2xGImIasjAgQMRFhEO48lrUkdxKMoAD6g8tVi5cqXUUW6LxUhEVEPkcjmmvDEZhRcyYTMUSh3HYQhC0ebUZSuWO+TmVBYjEVENGj58OPReehSc4r7GktQRPsi4ke6Qm1NZjERENcjNzQ2jXh0F8/lM2C2ONzqSijLAAyqd1iGvncpiJCKqYaNHj4bdbEXheV4m7hZBEKAILTo61W53rOvKshiJiGpYWFgYHn3sMZjPZPCE/xLUYd7IuJHucLcPZDESEdWC18ePhykjD5aruVJHcRjK+p5QatX47bffpI5SCouRiKgW9OnTB5GNG8EYz3s13iLIBMiDPfHL6l+ljlIKi5GIqBYIgoDxY8fBdDELdqNF6jgOQx3qhYTTZ3DhwgWpoxRjMRIR1ZJhw4ZBoVDAeDZd6igOQ9XQCzKFHOvWrZM6SjEWIxFRLfHx8cGTTzwBy/lMHoTzF5lKDlWQDqvXrJE6SjEWIxFRLXr11VdhysyH5RoPwrlFGaLH3r17kJ2dLXUUACxGIqJa1bNnT4SGh6Ewgec03qIO8YLdZsf27duljgKAxUhEVKtkMhlGjXwV5uQs2M1WqeM4BLmnGmofD2zZskXqKABYjEREte7555+H3WqDKTlL6igOQxbkjo2bNjrEvlcWIxFRLQsODkaPBx6AOTFT6igOQx3shbTUNJw9e1bqKCxGIiIpvDh8OApTs2HLM0kdxSGoAj0hk8sdYnMqi5GISAJPPvkkVCoVChNvSh3FIQhKOVSBnti0eZPUUViMRERS0Ol0GDxoMKxJ2VJHcRiKBp7YtWsXCgulvakzi5GISCLPPfccCjNyYc0qkDqKQ1AF62EqNOHgwYOS5mAxEhFJpF+/fnBzd0dhEg/CAQCFjxuUWhV27dolaQ4WIxGRRDQaDR4fPBi2SwapozgEQRAgr++BHTt3SpqDxUhEJKGhQ4dyc2oJykBPHDp0SNL9jCxGIiIJcXNqacpAT1jMZhw6dEiyDE5RjBcvXsSIESMQHh4OrVaLyMhIzJ49G2azWepoRET3pHhzago3pwKAwlf6/YxOUYwJCQmw2+344osvEB8fj/fffx+ff/45ZsyYIXU0IqJ7NnjwYBSm58JmkPY0BUcgCALkAdLuZxRER7gw3V1YsGABPvvssyrd9dlgMECv1yMnJwc6na4G0xERVV5ubi58fX2h6RQEt9b1pY4jufwTV2E6eg15ublQqVTV8pxV+fx3ihHj7eTk5MDHx0fqGERE98zT0xO9onvBkpIjdRSHoAoo2s94/PhxSdbvlMWYmJiIjz/+GKNGjapwPpPJBIPBUGoiInJEgwcNhiktB3YTb0WlqOcGmUKOAwcOSLJ+SYtx2rRpEAShwikhIaHUMqmpqXjooYfw1FNPYeTIkRU+//z586HX64un4ODgmnw5RER3bcCAARDtIkwp2VJHkZwgl0Hl5yHZFXAk3ceYnp6OmzcrvoBuRERE8TbmtLQ09OrVC/fddx+WLFkCmaziXjeZTDCZ/v/K9QaDAcHBwdzHSEQOqXWbNkgsvAp970ipo0gu98AleN2UIfVKarU8X1X2MSqqZY13yc/PD35+fpWaNzU1FdHR0ejQoQMWL158x1IEALVaDbVafa8xiYhqxaOPPIL3PvkQoihCEASp40hKGeCJtBPnkZaWhqCgoFpdt1PsY0xNTUWvXr0QEhKChQsXIj09HdeuXcO1a9ekjkZEVG369+8PS34hrDd5FRxlgAcASLKfUdIRY2Vt27YNiYmJSExMRMOGDUt9z0nPNiEiKqN79+7QumlhvpwDZT13qeNISu6uglrvhgMHDuDJJ5+s1XU7xYjxxRdfhCiKt52IiOoKlUqF6OhoWFNzpY7iEARfDf44fLjW1+sUxUhE5CoefuhhmK8ZYLfYpI4iOUU9Nxw7dgx2u71W18tiJCJyIH369IHdZoflGkeNinruyM/Lq9IVzqoDi5GIyIE0a9YMPvV8YU5jMd7az3rs2LFaXS+LkYjIgQiCgD7RvWG/ni91FMnJtEqodW4sRiIiVxcdHQ3T9VyI3M8IwUeDI0eO1Oo6WYxERA6mZ8+eEO12mK/nSR1FcvJ6Whw5drRWz0JgMRIROZjmzZvD29cHljTe+EDp646crGykplbPpeEqg8VIRORgBEFAj+73w5bOK+DIfbQAgPj4+FpbJ4uRiMgBdevWDdb0fIh2176QidxTDblKgVOnTtXaOlmMREQOqGvXrrCaLLBmufaoURAEKL3dOGIkInJ1HTt2hFwhh4UH4AB6Ff48eaLWVsdiJCJyQG5ubmjVujWLEYDCW4szp8/U2qXhWIxERA6qe9duwM1CqWNITuHjBmNBAVJSUmplfSxGIiIH1aFDBxRm5rn8if4K79o9MpXFSETkoNq3bw+IgMXFb1ws81BBppTj/PnztbO+WlkLERFVWYsWLaBUKmHNcO3rpgqCAJXejcVIROTqVCoVWrRsAUu6axcjAIgeCpw7f65W1sViJCJyYJ07dQayTFLHkJxcr0HC2bO1si4WIxGRA2vbti3MmfkQbbV7F3tHI9dpkHYlFWazucbXxWIkInJgLVu2hN1mh83g2qdtKPRq2O12JCcn1/i6WIxERA6sZcuWAABrplHiJNKS6zUAgMTExBpfF4uRiMiB+fn5waeeL6xZrl2MMncVZAo5kpKSan5dNb4GIiK6J61atXL5YhQEASpPLS5fvlzj62IxEhE5uDatWkMwWKSOIT13Ra1cFo7FSETk4Jo2bQpzVoHL35sRbgokX7xY46thMRIRObjGjRvDbrPBnl/zpyo4MrmHGpdSLtX4eliMREQOrnHjxgAAa45rn7Ih81Ah/foNWCw1u1mZxUhE5OBCQkIgV8hhc/FilHuoIIoiUlNTa3Q9LEYiIgenUCgQEhrKYvRQA0CNH4DDYiQicgLNmjSFzeDa10yVuSkBANeuXavZ9dTosxMRUbUICwuDzOjaNywWVHLI5DJcv369RtfDYiQicgIhISGw5rr2iFEQBCg9NCxGIiIqKkaL0QS7xbVHjTKtksV4y8CBAxESEgKNRoPAwEAMGzYMaWlpUsciIqoVwcHBAAB7nmufy2hXy7iP8Zbo6GisWLECZ8+exS+//IKkpCQMGTJE6lhERLUiJCQEAGDLc/HNqVoF0q7W7KBIUaPPXo0mTpxY/PfQ0FBMmzYNgwcPhsVigVKplDAZEVHNCwoKgiAIsLn4iFGuVeJaDW9KdZpiLCkzMxM//fQTunXrVmEpmkwmmEz//9uVwWCojXhERNVOqVRC7+0Fi9G1LyYuaBTIvHmjRtfhNJtSAWDq1Klwd3eHr68vUlJSsHbt2grnnz9/PvR6ffF0axs9EZEzCggIgL3AtYtRplag0FgIs7nmRs6SFuO0adMgCEKFU0JCQvH8kydPxvHjx7F161bI5XK88MILEMXyrzY/ffp05OTkFE+1cR8vIqKaElQ/EHZXHzGqizZ0Zmdn19g6JN2U+q9//QsvvvhihfNEREQU/71evXqoV68emjRpgubNmyM4OBgHDx5E165db7usWq2GWq2uzshERJIJDAyEcO6Y1DEkJVPJAQBZWVnw9/evkXVIWox+fn7w8/O7q2XtdjsAlNqHSERUlwUEBACFrn0eY50fMVbWoUOHcPjwYdx///3w9vZGUlISZs2ahcjIyHJHi0REdY2/vz9sLr+P8f9HjDW2jhp75mrk5uaGX3/9FX369EHTpk0xYsQItGnTBrt37+amUiJyGd7e3rAWmis8tqKu44jxL61bt8bOnTuljkFEJCkvLy+IogjRYoOgcoqP72onKGQQZAJHjEREVDRiBADR5Lr7GQVBgFylRH5+fo2tg8VIROQkvLy8AAB2s1XaIBKTKeUoKCioueevsWcmIqJqxRFjEZmCxUhERAD0ej0AwG527WIUFDIWIxERFR2hDwCw2qUNIjWFwGIkIiJAq9UCAEQXL0ZRzmIkIiIAcrkcSqUSotW1N6WKcgFGo7HGnp/FSETkRDRajcuPGCED8ni6BhERAYBGq2UxygTYrDV3ygqLkYjIiajVaog2170kHFB0kr/VVnObk1mMRERORC6XAS58rVQAgCDAaq25i6mzGImInIhcrmAxygRYa/AAJBYjEZETUSgUgIv3oiAANhv3MRIREYpO2RDtbEYLD74hIiKgqBhhc/GjUkURNh58Q0REANDrgZ6wXMqB3eSad9iwm22wphjQo/v9NbYOFiMRkROZPn06BBtQEH9d6iiSMMZfh2i2YcaMGTW2DhYjEZETCQoKwpjRo2E6ecPlRo12sw2mkzcwcuRIhISE1Nh6WIxERE5m2rRpkIlAwalrUkepVcZT1wCrvUZHiwCLkYjI6QQGBmLM6DEwnUp3mVGj3WxF4akbePXVV9GwYcMaXReLkYjICU2dOrVo1HjSNUaNBaeuQ7AV7WOtaSxGIiInFBgYiLGvjYXpVN3f12g3WWE6eQOjR41CgwYNanx9LEYiIic1depUyAUZCk7U7VFjwalrEOxF+1ZrA4uRiMhJBQQEYNzYcTCdvgF7Yd0cNdpNVphOpWPM6NEICgqqlXWyGImInNiUKVOgEOQoOHlV6ig1ouDkNcjE2hstAixGIiKn5u/vj/HjxsMUn17nRo12kxWm+HS8NuY1BAYG1tp6WYxERE7ujTfegEImR8GJujVqLDhxDXIImDp1aq2ul8VIROTk/P398fr411F4Oh12Y83dwLc2FY0Wb2Dsa2NRv379Wl03i5GIqA6YPHkyVHIF8uvIqLHgxFXIBRmmTJlS6+tmMRIR1QH16tXDP1//J0x1YNRoLyzatzh+3HgEBATU+vpZjEREdcQbb7wBtVLl9KPGghNXoZDJMXnyZEnWz2IkIqojfH19MeGfE5x61GgvtKDwdNFo0d/fX5IMTleMJpMJUVFREAQBcXFxUschInIokyZNglqpRv6fzjlqzP/zGlRyhWSjRcAJi3HKlCm1dvUDIiJn4+vri4kTJsB0xvlGjXajBeYz6Xh9/Ovw8/OTLIdTFeOmTZuwdetWLFy4UOooREQOa9KkSdCoNMiPS5M6SpXkn7gKpVyJN954Q9IcTlOM169fx8iRI/HDDz/Azc1N6jhERA7Lx8cHkyZOhOlMBmwFZqnjVIrdaIHpdDom/POfqFevnqRZnKIYRVHEiy++iNGjR6Njx46VXs5kMsFgMJSaiIhcwcSJE6HVaFHgJPsa8/+8CrVSjX/9619SR5G2GKdNmwZBECqcEhIS8PHHHyM3N7fKN6icP38+9Hp98RQcHFxDr4SIyLF4e3vjX5MmOcWo0W60wHQmHRMnTICvr6/UcSCIoihKtfL09HTcvHmzwnkiIiIwdOhQrFu3DoIgFD9us9kgl8vx3HPP4bvvvrvtsiaTCSaTqfhrg8GA4OBg5OTkQKfTVc+LICJyUNnZ2QgOCYE9zB2e3UKljlOu3AOXgKRcXE5JgY+PT42sw2AwQK/XV+rzX1EjCSrJz8+vUkceffTRR/jPf/5T/HVaWhr69++P5cuXo0uXLuUup1aroVarqyUrEZGz8fLywuQ33sC8/8yDW9tAyN1VUkcqw1ZggelMBqZPnVZjpVhVko4Y79bFixcRHh6O48ePIyoqqtLLVeU3BiKiuiAnJwfBISGwhmih6x4mdZwycg9cgnAhD5dTUuDt7V1j66nK579THHxDRER3R6/XY/Ibb8CUkAFbvmPta7QVmGE6k4F/TZpUo6VYVU45YrxbHDESkSsyGAwIDgmGpaEWuvvDpI5TLHf/Jcgu5uNySgq8vLxqdF0cMRIRUTGdTocpk6fAdNZxRo22fDNMCel441//qvFSrCoWIxGRCxg/fjw8PTyQf9wxroaTH5cGN607JkyYIHWUMliMREQuQKfTYeqUqUWjxjzTnReoQUWjxQxMfuMN6PV6SbPcDouRiMhFjBs3DjpPT8lHjflxaXB3c8frr78uaY7ysBiJiFyEp6cnpk2dVjRqzJVm1HhrtDhl8mSHHC0CLEYiIpcyduxY6PV6ye68kX88DZ4eHg47WgRYjERELsXDw0OyUaMtzwTT2QxMmTzFoU+Z43mMREQuJj8/HyGhITD6K6B7ILzW1mvYmwz1VTNSLqXA09Oz1tYL8DxGIiKqgLu7O6ZPm47CWhw12nKLRotTp0yt9VKsKo4YiYhcUH5+PkLDQlFQTw5dz5ofNRr2JkNzzYKUSynw8PCo8fWVWT9HjEREVBF3d3fMmD4DhecyYDMU1ui6bo0Wp02dJkkpVhVHjERELqqgoAAhYaEo8BWg6xlRY+sx7EmG5rp0o0WAI0YiIqoENzc3vPnXqNGaUzOjRluuCYVnMzB92nSnGC0CHDESEbk0o9GI0LBQ5HkDul7VP2o07E6GW4YNly5egru7e7U/f6VzcMRIRESVodVq8eaMN1F4vvpHjTZDIQrPFY0WpSzFquKIkYjIxRmNRoSGhyFPL0IXXX2jRsPuC3C7KSLl4iW4ublV2/PeVRaOGImIqLK0Wi1mvTmzWkeN1pyi0eKb02dIXopVxREjERGhsLAQYRHhMHhaoYuOvOfnM+y6AI8s4NLFS9BqtdWQ8B7zcMRIRERVodFo/ho13oQ123hPz2XNKUTh+QzMmD7DIUqxqjhiJCIiACVGjR5W6Hrf/ajREHsBHjkCLiVfdJhi5IiRiIiqTKPRIGbmLBQm3oQ16+5GjbdGizNnvOkwpVhVHDESEVExk8mE8MgIZLuZ72rUaIhNgqdBjkvJF6HRaGog4d3hiJGIiO6KWq1GzMxZMN7FqNGabUTh+ZuY9eZMhyrFquKIkYiISjGbzQiPjECWxgRdn8qPGg07k6DLU+DihWSHK0aOGImI6K6pVCrMnhUDY9JNWDMLKrWMNcuIwsSbiJk5y+FKsao4YiQiojLMZjMiGkUiU2WErm+jO85v2JEEfYESFy8kQ61W10LCquGIkYiI7olKpcKcmNkwXsi846jRmmWEMalotOiIpVhVHDESEdFtWSwWRDSKxE1lQYWjRsOOJHgbVbiQdMFhi5EjRiIiumdKpbJo1Jh0E5abtx81WjMLikaLs2IcthSriiNGIiIql8ViQaMmjZEuy4PuwbKjRsP2RPiYtbiQmASVSiVBwsrhiJGIiKpF8ajxwk1YbuaX+p41swDGC5mYPSvGoUuxqjhiJCKiClmtVjRq0hjXYYC+X+Pixw3bE+FrccOFxCQolUoJE94ZR4xERFRtFAoF5s6eg8LkTFgyikaNlptF+xbnxMx2+FKsKqcpxrCwMAiCUGp6++23pY5FROQSnnvuOYRFhMN4LA0AYDyWhuDQELzwwgsSJ6t+CqkDVMW8efMwcuTI4q89PT0lTENE5DpujRqHDx8O5dl0GC/cxJxv/lfnRouAE40YgaIirF+/fvHk7u4udSQiIpfx7LPPIjwyAoZdFxASFophw4ZJHalGOFUxvv322/D19UW7du2wYMECWK3WCuc3mUwwGAylJiIiujsKhQL/njsPMpkMc2fPqZOjRcCJjkp977330L59e/j4+GD//v2YPn06XnrpJbz33nvlLjNnzhzMnTu3zOM8KpWIyLVU5ahUSYtx2rRpeOeddyqc58yZM2jWrFmZx7/99luMGjUKeXl55V5twWQywWQyFX9tMBgQHBzMYiQicjFOU4zp6em4efNmhfNERETc9sTR+Ph4tGrVCgkJCWjatGml1sfzGImIXFNVPv8lPSrVz88Pfn5+d7VsXFwcZDIZ/P39qzkVERG5Mqc4XePAgQM4dOgQoqOj4enpiQMHDmDixIl4/vnn4e3tLXU8IiKqQ5yiGNVqNZYtW4Y5c+bAZDIhPDwcEydOxKRJk6SORkREdYxTFGP79u1x8OBBqWMQEZELcKrzGImIiGoai5GIiKgEFiMREVEJLEYiIqISWIxEREQlOMVRqdXl1kV+eDFxIiLXcutzvzIXe3OpYszNzQUABAcHS5yEiIikkJubC71eX+E8TnN3jepgt9uRlpYGT09PCIJwx/lvXXT88uXLTnFtVWfK60xZAefK60xZAefK60xZAefKW9NZRVFEbm4ugoKCIJNVvBfRpUaMMpkMDRs2rPJyOp3O4X+oSnKmvM6UFXCuvM6UFXCuvM6UFXCuvDWZ9U4jxVt48A0REVEJLEYiIqISWIwVUKvVmD17drk3QnY0zpTXmbICzpXXmbICzpXXmbICzpXXkbK61ME3REREd8IRIxERUQksRiIiohJYjERERCWwGKsgLCwMgiCUmt5++22pY1XIZDIhKioKgiAgLi5O6jjlGjhwIEJCQqDRaBAYGIhhw4YhLS1N6lhlXLx4ESNGjEB4eDi0Wi0iIyMxe/ZsmM1mqaOV67///S+6desGNzc3eHl5SR2nlEWLFiEsLAwajQZdunTBH3/8IXWk29qzZw8GDBiAoKAgCIKANWvWSB2pXPPnz0enTp3g6ekJf39/DB48GGfPnpU6Vrk+++wztGnTpvj8xa5du2LTpk2SZmIxVtG8efNw9erV4mn8+PFSR6rQlClTEBQUJHWMO4qOjsaKFStw9uxZ/PLLL0hKSsKQIUOkjlVGQkIC7HY7vvjiC8THx+P999/H559/jhkzZkgdrVxmsxlPPfUUxowZI3WUUpYvX45JkyZh9uzZOHbsGNq2bYv+/fvjxo0bUkcrIz8/H23btsWiRYukjnJHu3fvxtixY3Hw4EFs27YNFosF/fr1Q35+vtTRbqthw4Z4++23cfToURw5cgS9e/fGoEGDEB8fL10okSotNDRUfP/996WOUWkbN24UmzVrJsbHx4sAxOPHj0sdqdLWrl0rCoIgms1mqaPc0f/+9z8xPDxc6hh3tHjxYlGv10sdo1jnzp3FsWPHFn9ts9nEoKAgcf78+RKmujMA4urVq6WOUWk3btwQAYi7d++WOkqleXt7i19//bVk6+eIsYrefvtt+Pr6ol27dliwYAGsVqvUkW7r+vXrGDlyJH744Qe4ublJHadKMjMz8dNPP6Fbt25QKpVSx7mjnJwc+Pj4SB3DqZjNZhw9ehR9+/Ytfkwmk6Fv3744cOCAhMnqnpycHABwip9Rm82GZcuWIT8/H127dpUsB4uxCl5//XUsW7YMsbGxGDVqFN566y1MmTJF6lhliKKIF198EaNHj0bHjh2ljlNpU6dOhbu7O3x9fZGSkoK1a9dKHemOEhMT8fHHH2PUqFFSR3EqGRkZsNlsCAgIKPV4QEAArl27JlGqusdut2PChAno3r07WrVqJXWccp08eRIeHh5Qq9UYPXo0Vq9ejRYtWkiWx+WLcdq0aWUOqPn7lJCQAACYNGkSevXqhTZt2mD06NF499138fHHH8NkMjlU1o8//hi5ubmYPn16reS617y3TJ48GcePH8fWrVshl8vxwgsvVOreaVJkBYDU1FQ89NBDeOqppzBy5MhayXkvecn1jB07FqdOncKyZcukjlKhpk2bIi4uDocOHcKYMWMwfPhwnD59WrI8Ln/lm/T0dNy8ebPCeSIiIqBSqco8Hh8fj1atWiEhIQFNmzatqYjFKpt16NChWLduXalba9lsNsjlcjz33HP47rvvajoqgHt7b69cuYLg4GDs37+/VjapVDVrWloaevXqhfvuuw9Lliy5421sqtvdvLdLlizBhAkTkJ2dXcPp7sxsNsPNzQ2rVq3C4MGDix8fPnw4srOzHXprgSAIWL16dancjmjcuHFYu3Yt9uzZg/DwcKnjVEnfvn0RGRmJL774QpL1u9Rtp27Hz88Pfn5+d7VsXFwcZDIZ/P39qznV7VU260cffYT//Oc/xV+npaWhf//+WL58Obp06VKTEUu5l/fWbrcDQK2NxquSNTU1FdHR0ejQoQMWL15c66UI3Nt76whUKhU6dOiAHTt2FBeM3W7Hjh07MG7cOGnDOTlRFDF+/HisXr0au3btcrpSBIp+Fmrr//7tuHwxVtaBAwdw6NAhREdHw9PTEwcOHMDEiRPx/PPPw9vbW+p4pYSEhJT62sPDAwAQGRl5V/ejrGmHDh3C4cOHcf/998Pb2xtJSUmYNWsWIiMjJd0Bfzupqano1asXQkNDsXDhQqSnpxd/r379+hImK19KSgoyMzORkpICm81WfD5ro0aNin82pDBp0iQMHz4cHTt2ROfOnfHBBx8gPz8fL730kmSZypOXl4fExMTir5OTkxEXFwcfH58y/9+kNnbsWCxduhRr166Fp6dn8T5bvV4PrVYrcbqypk+fjocffhghISHIzc3F0qVLsWvXLmzZskW6UJIdD+tkjh49Knbp0kXU6/WiRqMRmzdvLr711ltiYWGh1NHuKDk52aFP1zhx4oQYHR0t+vj4iGq1WgwLCxNHjx4tXrlyRepoZSxevFgEcNvJUQ0fPvy2eWNjY6WOJn788cdiSEiIqFKpxM6dO4sHDx6UOtJtxcbG3vY9HD58uNTRyijv53Px4sVSR7utl19+WQwNDRVVKpXo5+cn9unTR9y6daukmVx+HyMREVFJLn9UKhERUUksRiIiohJYjERERCWwGImIiEpgMRIREZXAYiQiIiqBxUhERFQCi5GIiKgEFiMREVEJLEYiIqISWIxEREQlsBiJ6rD09HTUr18fb731VvFj+/fvh0qlwo4dOyRMRuS4eBFxojpu48aNGDx4MPbv34+mTZsiKioKgwYNwnvvvSd1NCKHxGIkcgFjx47F9u3b0bFjR5w8eRKHDx+GWq2WOhaRQ2IxErkAo9GIVq1a4fLlyzh69Chat24tdSQih8V9jEQuICkpCWlpabDb7bh48aLUcYgcGkeMRHWc2WxG586dERUVhaZNm+KDDz7AyZMn4e/vL3U0IofEYiSq4yZPnoxVq1bhzz//hIeHB3r27Am9Xo/169dLHY3IIXFTKlEdtmvXLnzwwQf44YcfoNPpIJPJ8MMPP2Dv3r347LPPpI5H5JA4YiQiIiqBI0YiIqISWIxEREQlsBiJiIhKYDESERGVwGIkIiIqgcVIRERUAouRiIioBBYjERFRCSxGIiKiEliMREREJbAYiYiISmAxEhERlfB/PSobIHE9h0gAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "polyslab = make_polyslab(params)\n",
    "ax = polyslab.plot(z=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc3b3303-3942-4004-a49b-f66fc07a0eb3",
   "metadata": {},
   "source": [
    "Keeping with this theme, we add a function to generate the structure itself."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8db1381a-dd4a-4e99-a207-6f1c1363d173",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:07.396933Z",
     "start_time": "2026-03-17T10:59:07.394886Z"
    }
   },
   "outputs": [],
   "source": [
    "def make_structure(params) -> td.Structure:\n",
    "    polyslab = make_polyslab(params)\n",
    "    medium = td.Medium(permittivity=n_wg**2)\n",
    "    return td.Structure(geometry=polyslab, medium=medium)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2ab62467-2ac4-4908-8344-2c342944f8e1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:07.553712Z",
     "start_time": "2026-03-17T10:59:07.445335Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ring = make_structure(params)\n",
    "ax = ring.plot(z=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92d145cd-20e9-4762-ba3b-227d667b3fcd",
   "metadata": {},
   "source": [
    "Next, we define the other geometries, such as the input waveguide section, output waveguide section, and substrate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0e756863-4009-421a-9b86-20509d1d807b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:07.568837Z",
     "start_time": "2026-03-17T10:59:07.563680Z"
    }
   },
   "outputs": [],
   "source": [
    "box_in = td.Box.from_bounds(\n",
    "    rmin=(-Lx / 2 - 1, -Ly / 2 + t + radius - wmid / 2, -h / 2),\n",
    "    rmax=(-Lx / 2 + t + 1e-3, -Ly / 2 + t + radius + wmid / 2, +h / 2),\n",
    ")\n",
    "box_out = td.Box.from_bounds(\n",
    "    rmin=(-Lx / 2 + t + radius - wmid / 2, -Ly / 2 - 1, -h / 2),\n",
    "    rmax=(-Lx / 2 + t + radius + wmid / 2, -Ly / 2 + t, +h / 2),\n",
    ")\n",
    "\n",
    "geo_sub = td.Box.from_bounds(\n",
    "    rmin=(-td.inf, -td.inf, -10000),\n",
    "    rmax=(+td.inf, +td.inf, -h / 2),\n",
    ")\n",
    "\n",
    "wg_in = td.Structure(geometry=box_in, medium=td.Medium(permittivity=n_wg**2))\n",
    "wg_out = td.Structure(geometry=box_out, medium=td.Medium(permittivity=n_wg**2))\n",
    "substrate = td.Structure(geometry=geo_sub, medium=td.Medium(permittivity=n_sub**2))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36c7b8fa-51fb-4852-9e62-f231410d8e0e",
   "metadata": {},
   "source": [
    "## Fabrication Constraints\n",
    "\n",
    "With the current parameterization, it is possible to generate structures with wildly varying radii of curvature which may be difficult to fabricate. To alleviate this, we introduce a minimum radius of curvature penalty transformation using the tidy3d `autograd` utilities. The penalty will take a set of vertices, compute the local radius of curvature using a quadratic Bezier curve, and return an average penalty function that depends on how much smaller the local radii are compared to a desired minimum radius."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a4e9cb73-c8a9-41ec-a4e2-af2eac220c04",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:08.461544Z",
     "start_time": "2026-03-17T10:59:07.693477Z"
    }
   },
   "outputs": [],
   "source": [
    "from tidy3d.plugins.autograd import make_curvature_penalty\n",
    "\n",
    "penalty = make_curvature_penalty(min_radius)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "557d4e5b-8441-433f-8965-e81c2f4b6231",
   "metadata": {},
   "source": [
    "We then wrap this penalty to look at only the inner and outer vertices independently and average the penalty from each."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4e4bc5d9-2c57-412c-8cc2-cc026b39857b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:08.468220Z",
     "start_time": "2026-03-17T10:59:08.465956Z"
    }
   },
   "outputs": [],
   "source": [
    "def eval_penalty(params):\n",
    "    \"\"\"Evaluate penalty on a set of params looking at radius of curvature.\"\"\"\n",
    "    vertices = make_vertices(params)\n",
    "    _vertices = anp.array(vertices)\n",
    "    vertices_top = _vertices[1 : num_pts + 3]  # select outer set of points along bend\n",
    "    vertices_bot = _vertices[num_pts + 4 :]  # select inner set of points along bend\n",
    "    penalty_top = penalty(vertices_top)\n",
    "    penalty_bot = penalty(vertices_bot)\n",
    "    return (penalty_top + penalty_bot) / 2.0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9881812c-1795-4f83-a24f-0b01833638e7",
   "metadata": {},
   "source": [
    "Let's try this out on our starting parameters. We see we get an autograd traced float that seems reasonably low given our smooth starting structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d13993be-d625-4537-af2a-f7700c199612",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:08.517422Z",
     "start_time": "2026-03-17T10:59:08.513171Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(3.579734103732553e-23)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eval_penalty(params)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28462443-1777-4b35-8c03-32490755f475",
   "metadata": {},
   "source": [
    "## Define Simulation\n",
    "\n",
    "Now we define our sources, monitors, and simulation.\n",
    "\n",
    "We first define a mode source injected at the input waveguide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "96cf199b-0a3b-4ace-9e1e-ba6c62d165f7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:08.575211Z",
     "start_time": "2026-03-17T10:59:08.566667Z"
    }
   },
   "outputs": [],
   "source": [
    "mode_width = wmid + 2 * spc\n",
    "mode_height = Lz\n",
    "\n",
    "mode_src = td.ModeSource(\n",
    "    size=(0, mode_width, mode_height),\n",
    "    center=(-Lx / 2 + t / 2, -Ly / 2 + t + radius, 0),\n",
    "    direction=\"+\",\n",
    "    source_time=td.GaussianPulse(\n",
    "        freq0=freq0,\n",
    "        fwidth=fwidth,\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79c7db54-87c6-4ba4-9da7-68ae176a222f",
   "metadata": {},
   "source": [
    "Next, we define monitors for storing:\n",
    "\n",
    "- The output mode amplitude at the central frequency.\n",
    "\n",
    "- The flux on the output plane (for reference).\n",
    "\n",
    "- The output mode amplitude across a frequency range (for examining the transmission spectrum of our final device).\n",
    "\n",
    "- A field monitor to measure fields directly in the z-normal plane intersecting the waveguide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "731f5f2f-0c38-4e86-add9-7ba8eea6c951",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:08.627427Z",
     "start_time": "2026-03-17T10:59:08.617340Z"
    }
   },
   "outputs": [],
   "source": [
    "mode_mnt = td.ModeMonitor(\n",
    "    size=(mode_width, 0, mode_height),\n",
    "    center=(-Lx / 2 + t + radius, -Ly / 2 + t / 2, 0),\n",
    "    name=monitor_name,\n",
    "    freqs=[freq0],\n",
    "    mode_spec=mode_spec,\n",
    ")\n",
    "\n",
    "flux_mnt = td.FluxMonitor(\n",
    "    size=(mode_width, 0, mode_height),\n",
    "    center=(-Lx / 2 + t + radius, -Ly / 2 + t / 2, 0),\n",
    "    name=\"flux\",\n",
    "    freqs=[freq0],\n",
    ")\n",
    "\n",
    "mode_mnt_bb = td.ModeMonitor(\n",
    "    size=(mode_width, 0, mode_height),\n",
    "    center=(-Lx / 2 + t + radius, -Ly / 2 + t / 2, 0),\n",
    "    name=\"mode_bb\",\n",
    "    freqs=freqs.tolist(),\n",
    "    mode_spec=mode_spec,\n",
    ")\n",
    "\n",
    "fld_mnt = td.FieldMonitor(\n",
    "    size=(td.inf, td.inf, 0),\n",
    "    freqs=[freq0],\n",
    "    name=\"field\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e47e54a-65f3-463f-b790-fd873597659e",
   "metadata": {},
   "source": [
    "Next we put everything together into a function that returns a `td.Simulation` given our parameters and an optional boolean specifying whether to include the field monitor (to save data when fields are not required)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f33bcf5e-2f31-4969-acb7-42bc06b1347e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:08.673852Z",
     "start_time": "2026-03-17T10:59:08.671522Z"
    }
   },
   "outputs": [],
   "source": [
    "def make_sim(params, use_fld_mnt: bool = True) -> td.Simulation:\n",
    "    monitors = [mode_mnt_bb, flux_mnt]\n",
    "    if use_fld_mnt:\n",
    "        monitors += [fld_mnt]\n",
    "    ring = make_structure(params)\n",
    "    return td.Simulation(\n",
    "        size=(Lx, Ly, Lz),\n",
    "        structures=[substrate, wg_in, wg_out, ring],\n",
    "        sources=[mode_src],\n",
    "        grid_spec=td.GridSpec.auto(min_steps_per_wvl=min_steps_per_wvl),\n",
    "        boundary_spec=td.BoundarySpec.pml(x=True, y=True, z=True),\n",
    "        monitors=monitors + [mode_mnt],\n",
    "        run_time=10 / fwidth,\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7d38368-afd9-4a29-864a-4c6c6385acea",
   "metadata": {},
   "source": [
    "Let's try it out and plot our simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "42fcce5a-11e9-4de2-b03e-97ca75af1628",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:09.192013Z",
     "start_time": "2026-03-17T10:59:08.717933Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">specified</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">)</span><span style=\"color: #800000; text-decoration-color: #800000\"> was detected as being less than half of a central       </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">wavelength from a PML on side x-min. The structure will be         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">automatically extruded to the end of the PML region to ensure      </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">translational invariance.                                          </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m11:59:09 CET\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Structure: simulation.structures\u001b[0m\u001b[1;31m[\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;31m]\u001b[0m\u001b[31m \u001b[0m\u001b[1;31m(\u001b[0m\u001b[31mno `name` was        \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31mspecified\u001b[0m\u001b[1;31m)\u001b[0m\u001b[31m was detected as being less than half of a central       \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31mwavelength from a PML on side x-min. The structure will be         \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31mautomatically extruded to the end of the PML region to ensure      \u001b[0m\n",
       "\u001b[2;36m             \u001b[0m\u001b[31mtranslational invariance.                                          \u001b[0m\n"
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     "metadata": {},
     "output_type": "display_data"
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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\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Suppressed </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span><span style=\"color: #800000; text-decoration-color: #800000\"> WARNING message.                             </span>\n",
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Suppressed \u001b[0m\u001b[1;36m1\u001b[0m\u001b[31m WARNING message.                             \u001b[0m\n"
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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim = make_sim(params)\n",
    "\n",
    "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(10, 4))\n",
    "ax = sim.plot(z=0.01, ax=ax1)\n",
    "ax = sim.plot(x=-Lx / 2 + t / 2, ax=ax2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "fa5b961a-1b10-416d-9b68-c4d1d24d087a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:09.203296Z",
     "start_time": "2026-03-17T10:59:09.199338Z"
    }
   },
   "outputs": [],
   "source": [
    "# let's turn off warnings because we know this ring is intersecting with our waveguide ports.\n",
    "td.config.logging.level = \"ERROR\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b11fca49-0b3f-4f96-9b2e-933b0c8ea6ac",
   "metadata": {},
   "source": [
    "## Select the desired waveguide mode\n",
    "\n",
    "Next, we use the [ModeSolver](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.mode.ModeSolver.html) to solve and select the `mode_index` that gives us the proper injected and measured modes. We plot all of the fields for the first 3 modes and see that the TE0 mode is `mode_index=0`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8480cca1-a8df-4c43-81d0-18b7ffa5076f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:11.031996Z",
     "start_time": "2026-03-17T10:59:09.245950Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Effective index of computed modes:  [[1.79689322 1.75290062 1.60455161]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x1000 with 18 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from tidy3d.plugins.mode import ModeSolver\n",
    "\n",
    "ms = ModeSolver(simulation=sim, plane=mode_src, mode_spec=mode_spec, freqs=mode_mnt.freqs)\n",
    "data = ms.solve()\n",
    "\n",
    "print(\"Effective index of computed modes: \", np.array(data.n_eff))\n",
    "\n",
    "fig, axs = plt.subplots(num_modes, 3, figsize=(14, 10), tight_layout=True)\n",
    "for mode_ind in range(num_modes):\n",
    "    for field_ind, field_name in enumerate((\"Ex\", \"Ey\", \"Ez\")):\n",
    "        field = data.field_components[field_name].sel(mode_index=mode_ind)\n",
    "        ax = axs[mode_ind, field_ind]\n",
    "        field.real.plot(x=\"y\", y=\"z\", ax=ax, cmap=\"RdBu\")\n",
    "        ax.set_title(f\"{field_name}, mode_ind={mode_ind}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9fe1aaf-5e75-445a-80a5-e7a75197a8ee",
   "metadata": {},
   "source": [
    "Since this is already the default mode index, we can leave the original `make_sim()` function as is. However, to generate a new mode source with a different `mode_index`, we could do the following and rewrite that function with the returned `mode_src`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5e1974b0-28c8-4d65-9d79-976cb012b870",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:11.046932Z",
     "start_time": "2026-03-17T10:59:11.044574Z"
    }
   },
   "outputs": [],
   "source": [
    "# select the mode index\n",
    "mode_index = 0\n",
    "\n",
    "# make the mode source with appropriate mode index\n",
    "mode_src = ms.to_source(\n",
    "    mode_index=mode_index,\n",
    "    source_time=mode_src.source_time,\n",
    "    direction=mode_src.direction,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab0e3e8c-3336-4fa3-9eca-6e89e0c50812",
   "metadata": {},
   "source": [
    "## Defining objective function\n",
    "\n",
    "Now we can define our objective function to maximize. The objective function first generates a simulation given the parameters, runs the simulation using the builtin `web.run()` function, measures the power transmitted into the TE0 output mode at our desired polarization, and then subtracts the radius of curvature penalty that we defined earlier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9f02432c-1de7-45da-ac8d-dc730093acff",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:11.098493Z",
     "start_time": "2026-03-17T10:59:11.096372Z"
    }
   },
   "outputs": [],
   "source": [
    "def objective(params: np.ndarray, use_fld_mnt: bool = True) -> float:\n",
    "    sim = make_sim(params, use_fld_mnt=use_fld_mnt)\n",
    "    sim_data = web.run(sim, task_name=\"bend\", verbose=False)\n",
    "\n",
    "    # be sure to take .values here before summing the transmission\n",
    "    amps = sim_data[monitor_name].amps.sel(direction=\"-\", mode_index=mode_index).values\n",
    "\n",
    "    transmission = anp.abs(anp.array(amps)) ** 2\n",
    "    J = anp.sum(transmission) - eval_penalty(params)\n",
    "    return J"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e82ef72-d130-48dd-b88d-bdc5e5ccde0f",
   "metadata": {},
   "source": [
    "Next, we use [autograd.value_and_grad](https://ag.readthedocs.io/en/latest/_autosummary/ag.value_and_grad.html) to transform this objective function into a function that returns the \n",
    "\n",
    "* Objective function evaluated at the passed parameters.\n",
    "\n",
    "* Gradient of the objective function with respect to the passed parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d8390c85-0506-4a4f-aa85-fa9311a969bd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:11.143945Z",
     "start_time": "2026-03-17T10:59:11.142336Z"
    }
   },
   "outputs": [],
   "source": [
    "val_grad = ag.value_and_grad(objective)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1cad86d-800f-40c8-8966-d2483cdd254e",
   "metadata": {},
   "source": [
    "Let's run this function and take a look at the outputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "99393577-a86b-4d20-98b2-8e45b4b88058",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:43.393676Z",
     "start_time": "2026-03-17T10:59:11.189178Z"
    }
   },
   "outputs": [],
   "source": [
    "val, grad = val_grad(params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "0adcb4f4-8b8d-4526-bfcd-5be2caf810c2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:59:43.414265Z",
     "start_time": "2026-03-17T10:59:43.411516Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5688219093836469\n",
      "[-0.01866849 -0.02957353 -0.03683549 -0.05133026 -0.05874484 -0.07073193\n",
      " -0.07991981 -0.08868294 -0.09495217 -0.09855133 -0.09982713 -0.09789156\n",
      " -0.09222325 -0.08173699 -0.07358428 -0.0578309  -0.04006191 -0.02346232\n",
      " -0.00709274  0.00908331  0.0249656   0.04008588  0.05221564  0.06248672\n",
      "  0.07392343  0.08150386  0.08701337  0.09042763  0.09344378  0.09338623\n",
      "  0.09338619  0.09344375  0.0904277   0.08701327  0.08150366  0.07392331\n",
      "  0.06248663  0.05221551  0.04008583  0.02496569  0.00908343 -0.00709262\n",
      " -0.02346213 -0.04006165 -0.05783056 -0.07358369 -0.08173629 -0.09222265\n",
      " -0.09789066 -0.09982697 -0.09855116 -0.09495221 -0.08868361 -0.07992135\n",
      " -0.07073474 -0.05874907 -0.05133595 -0.03684226 -0.02958225 -0.01867818]\n"
     ]
    }
   ],
   "source": [
    "print(val)\n",
    "print(grad)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6aea9708-fe5c-4f9e-aae3-0d4aa769fa17",
   "metadata": {},
   "source": [
    "These seem reasonable and can now be used for plugging into our optimization algorithm.\n",
    "\n",
    "## Optimization Procedure\n",
    "\n",
    "With our gradients defined, we can optimize using `tidy3d.plugins.autograd.optimize()` with Tidy3D's built-in Adam optimizer. The intermediate values, parameters, and data are stored for visualization later.\n",
    "\n",
    "> Note: this will take several minutes. While not shown here, it is good practice to checkpoint your optimization results by saving to file on every iteration, or ensure you have a stable internet connection. See [this notebook](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd6GratingCoupler/) for more details. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f0a6b1e7-6d87-483e-a54e-ac8ca19a03fa",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T12:14:29.745766Z",
     "start_time": "2026-03-17T10:59:43.470548Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 1\n",
      "\tJ = 5.6882e-01\n",
      "\tgrad_norm = 5.4148e-01\n",
      "step = 2\n",
      "\tJ = 6.0577e-01\n",
      "\tgrad_norm = 5.3093e-01\n",
      "step = 3\n",
      "\tJ = 6.4261e-01\n",
      "\tgrad_norm = 5.1894e-01\n",
      "step = 4\n",
      "\tJ = 6.7755e-01\n",
      "\tgrad_norm = 5.0539e-01\n",
      "step = 5\n",
      "\tJ = 7.1130e-01\n",
      "\tgrad_norm = 4.8593e-01\n",
      "step = 6\n",
      "\tJ = 7.4267e-01\n",
      "\tgrad_norm = 4.6448e-01\n",
      "step = 7\n",
      "\tJ = 7.7251e-01\n",
      "\tgrad_norm = 4.4222e-01\n",
      "step = 8\n",
      "\tJ = 8.0000e-01\n",
      "\tgrad_norm = 4.1889e-01\n",
      "step = 9\n",
      "\tJ = 8.2584e-01\n",
      "\tgrad_norm = 3.9185e-01\n",
      "step = 10\n",
      "\tJ = 8.4878e-01\n",
      "\tgrad_norm = 3.6315e-01\n",
      "step = 11\n",
      "\tJ = 8.6880e-01\n",
      "\tgrad_norm = 3.3430e-01\n",
      "step = 12\n",
      "\tJ = 8.8653e-01\n",
      "\tgrad_norm = 3.0386e-01\n",
      "step = 13\n",
      "\tJ = 9.0190e-01\n",
      "\tgrad_norm = 2.7190e-01\n",
      "step = 14\n",
      "\tJ = 9.1492e-01\n",
      "\tgrad_norm = 2.4047e-01\n",
      "step = 15\n",
      "\tJ = 9.2581e-01\n",
      "\tgrad_norm = 2.1068e-01\n",
      "step = 16\n",
      "\tJ = 9.3429e-01\n",
      "\tgrad_norm = 1.8425e-01\n",
      "step = 17\n",
      "\tJ = 9.4106e-01\n",
      "\tgrad_norm = 1.6016e-01\n",
      "step = 18\n",
      "\tJ = 9.4615e-01\n",
      "\tgrad_norm = 1.3911e-01\n",
      "step = 19\n",
      "\tJ = 9.5013e-01\n",
      "\tgrad_norm = 1.2196e-01\n",
      "step = 20\n",
      "\tJ = 9.5269e-01\n",
      "\tgrad_norm = 1.1020e-01\n",
      "step = 21\n",
      "\tJ = 9.5477e-01\n",
      "\tgrad_norm = 1.0253e-01\n",
      "step = 22\n",
      "\tJ = 9.5613e-01\n",
      "\tgrad_norm = 9.8925e-02\n",
      "step = 23\n",
      "\tJ = 9.5701e-01\n",
      "\tgrad_norm = 9.7993e-02\n",
      "step = 24\n",
      "\tJ = 9.5785e-01\n",
      "\tgrad_norm = 9.9140e-02\n",
      "step = 25\n",
      "\tJ = 9.5855e-01\n",
      "\tgrad_norm = 1.0086e-01\n",
      "step = 26\n",
      "\tJ = 9.5913e-01\n",
      "\tgrad_norm = 1.0258e-01\n",
      "step = 27\n",
      "\tJ = 9.5982e-01\n",
      "\tgrad_norm = 1.0440e-01\n",
      "step = 28\n",
      "\tJ = 9.6046e-01\n",
      "\tgrad_norm = 1.0586e-01\n",
      "step = 29\n",
      "\tJ = 9.6111e-01\n",
      "\tgrad_norm = 1.0666e-01\n",
      "step = 30\n",
      "\tJ = 9.6198e-01\n",
      "\tgrad_norm = 1.0442e-01\n",
      "step = 31\n",
      "\tJ = 9.6294e-01\n",
      "\tgrad_norm = 9.9214e-02\n",
      "step = 32\n",
      "\tJ = 9.6391e-01\n",
      "\tgrad_norm = 9.3257e-02\n",
      "step = 33\n",
      "\tJ = 9.6472e-01\n",
      "\tgrad_norm = 8.7381e-02\n",
      "step = 34\n",
      "\tJ = 9.6561e-01\n",
      "\tgrad_norm = 8.1408e-02\n",
      "step = 35\n",
      "\tJ = 9.6632e-01\n",
      "\tgrad_norm = 7.5074e-02\n",
      "step = 36\n",
      "\tJ = 9.6695e-01\n",
      "\tgrad_norm = 6.8924e-02\n",
      "step = 37\n",
      "\tJ = 9.6736e-01\n",
      "\tgrad_norm = 6.3220e-02\n",
      "step = 38\n",
      "\tJ = 9.6775e-01\n",
      "\tgrad_norm = 5.8340e-02\n",
      "step = 39\n",
      "\tJ = 9.6800e-01\n",
      "\tgrad_norm = 5.4721e-02\n",
      "step = 40\n",
      "\tJ = 9.6829e-01\n",
      "\tgrad_norm = 5.1848e-02\n"
     ]
    }
   ],
   "source": [
    "from tidy3d.plugins.autograd import adam, optimize\n",
    "\n",
    "# hyperparameters\n",
    "num_steps = 40\n",
    "learning_rate = 0.01\n",
    "\n",
    "optimizer = adam(learning_rate=learning_rate)\n",
    "\n",
    "# store history\n",
    "param_history = [params.copy()]\n",
    "\n",
    "\n",
    "def record_step(current_params, grad, state, step_index, objective_val):\n",
    "    print(f\"step = {step_index + 1}\")\n",
    "    print(f\"\\tJ = {objective_val:.4e}\")\n",
    "    print(f\"\\tgrad_norm = {np.linalg.norm(grad):.4e}\")\n",
    "\n",
    "\n",
    "# optimize() minimizes, so maximize J by minimizing -J.\n",
    "params, opt_state, history = optimize(\n",
    "    objective,\n",
    "    params0=params,\n",
    "    optimizer=optimizer,\n",
    "    num_steps=num_steps,\n",
    "    callback=record_step,\n",
    "    direction=\"max\",\n",
    ")\n",
    "param_history.append(np.array(params))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9760808f-512b-4806-85b6-809ba15e389c",
   "metadata": {},
   "source": [
    "## Analyzing results\n",
    "\n",
    "After the optimization is finished, let's look at the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "09aac45c-d7d8-4fd1-a599-0a7888257120",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T12:14:29.887028Z",
     "start_time": "2026-03-17T12:14:29.807704Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plt.plot(history[\"objective_fn_val\"])\n",
    "ax = plt.gca()\n",
    "ax.set_xlabel(\"iteration number\")\n",
    "ax.set_ylabel(\"objective function\")\n",
    "ax.set_title(\"optimization progress\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdbff561-b56c-4e83-8841-3c1ea7d5ba9e",
   "metadata": {},
   "source": [
    "Next, we can grab our initial and final device from the history lists."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d782b925-2af0-4bb8-bf87-88526a3f359f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T12:15:23.061342Z",
     "start_time": "2026-03-17T12:14:29.906409Z"
    }
   },
   "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\">13:14:30 CET </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'start'</span> with resource_id                              \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-206d13ae-dcac-46f5-9521-079abdd418b9'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:14:30 CET\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'start'\u001b[0m with resource_id                              \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-206d13ae-dcac-46f5-9521-079abdd418b9'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-206d13ae-dcac-46f5-9521-079abdd418b9\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-206d13ae-dca</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-206d13ae-dcac-46f5-9521-079abdd418b9\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">c-46f5-9521-079abdd418b9'</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=966743;https://tidy3d.simulation.cloud/workbench?taskId=fdve-206d13ae-dcac-46f5-9521-079abdd418b9\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=399283;https://tidy3d.simulation.cloud/workbench?taskId=fdve-206d13ae-dcac-46f5-9521-079abdd418b9\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=966743;https://tidy3d.simulation.cloud/workbench?taskId=fdve-206d13ae-dcac-46f5-9521-079abdd418b9\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=234997;https://tidy3d.simulation.cloud/workbench?taskId=fdve-206d13ae-dcac-46f5-9521-079abdd418b9\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=966743;https://tidy3d.simulation.cloud/workbench?taskId=fdve-206d13ae-dcac-46f5-9521-079abdd418b9\u001b\\\u001b[32m-206d13ae-dca\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=966743;https://tidy3d.simulation.cloud/workbench?taskId=fdve-206d13ae-dcac-46f5-9521-079abdd418b9\u001b\\\u001b[32mc-46f5-9521-079abdd418b9'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\" 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=704325;https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "322ffef08f324577b9237cbbbb3e1d9d",
       "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\">13:14:40 CET </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.029</span>. Minimum cost depends on task     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:14:40 CET\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.029\u001b[0m. Minimum cost depends on task     \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:14:41 CET </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:14:41 CET\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1ed46045ebdd48239c439ceac4f3574b",
       "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\">13:14:46 CET </span>Loading results from simulation_data.hdf5                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:14:46 CET\u001b[0m\u001b[2;36m \u001b[0mLoading results from simulation_data.hdf5                          \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>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'final'</span> with resource_id                              \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-90b24ee2-7073-45dd-a472-e01c1b392032'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'final'\u001b[0m with resource_id                              \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-90b24ee2-7073-45dd-a472-e01c1b392032'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-707</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">3-45dd-a472-e01c1b392032'</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=670632;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=913453;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=670632;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=535972;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=670632;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[32m-90b24ee2-707\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=670632;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[32m3-45dd-a472-e01c1b392032'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\" 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=249974;https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "71eebff4ed7840bd81025872a16b12e8",
       "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\">13:14:56 CET </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.029</span>. Minimum cost depends on task     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:14:56 CET\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.029\u001b[0m. Minimum cost depends on task     \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:14:58 CET </span>status = queued                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:14:58 CET\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or              \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the web UI.      \n",
       "\u001b[2;36m             \u001b[0mTerminating the Python script will not stop the job running on the \n",
       "\u001b[2;36m             \u001b[0mcloud.                                                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a4d97e38ee084a0da6c10b199f76720b",
       "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\">13:15:10 CET </span>status = preprocess                                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:15:10 CET\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \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\">13:15:15 CET </span>starting up solver                                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:15:15 CET\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:15:16 CET </span>running solver                                                     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:15:16 CET\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "852f5413ebb5460fa86e02509d207d8f",
       "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\">13:15:17 CET </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">33</span>%, exiting.                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:15:17 CET\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m33\u001b[0m%, exiting.                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:15:18 CET </span>status = success                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:15:18 CET\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View simulation result at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-707</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">3-45dd-a472-e01c1b392032'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=964022;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=161107;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=964022;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=586872;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=964022;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[4;34m-90b24ee2-707\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=964022;https://tidy3d.simulation.cloud/workbench?taskId=fdve-90b24ee2-7073-45dd-a472-e01c1b392032\u001b\\\u001b[4;34m3-45dd-a472-e01c1b392032'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "452400592bd84b2f92a679131ca4fcc8",
       "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\">13:15:23 CET </span>Loading results from simulation_data.hdf5                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m13:15:23 CET\u001b[0m\u001b[2;36m \u001b[0mLoading results from simulation_data.hdf5                          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_start = make_sim(param_history[0])\n",
    "data_start = web.run(sim_start, task_name=\"start\")\n",
    "\n",
    "sim_final = make_sim(param_history[-1])\n",
    "data_final = web.run(sim_final, task_name=\"final\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63a876ae-1d19-4f38-a958-170c9576b21a",
   "metadata": {},
   "source": [
    "Let's take a look at the final structure. We see that it has a smooth design which is symmetric about the 45 degree angle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "7ec2b20e-74de-4b82-949f-591696437315",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T12:15:23.204654Z",
     "start_time": "2026-03-17T12:15:23.068055Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sim_final.plot(z=0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95b503b9-a29e-455c-aef3-e4a97a0c59b2",
   "metadata": {},
   "source": [
    "Now let's inspect the difference between the initial and final intensity patterns. We notice that the final device is quite effective at coupling light into the output waveguide! This is especially evident when compared to the starting device."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a2dddafd-8cee-42fd-a1c7-ddc94f4ef9e8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T12:15:23.872517Z",
     "start_time": "2026-03-17T12:15:23.217545Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, tight_layout=True, figsize=(10, 6))\n",
    "\n",
    "_ = data_start.plot_field(\"field\", \"E\", \"abs^2\", ax=ax1)\n",
    "_ = sim_start.plot(z=0, ax=ax2)\n",
    "ax1.set_title(\"starting device\")\n",
    "ax2.set_title(\"starting device\")\n",
    "\n",
    "_ = data_final.plot_field(\"field\", \"E\", \"abs^2\", ax=ax3)\n",
    "_ = sim_final.plot(z=0, ax=ax4)\n",
    "ax3.set_title(\"final device\")\n",
    "ax4.set_title(\"final device\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38997828-6ea8-489c-96b0-3cb4aae502c2",
   "metadata": {},
   "source": [
    "Let's view the transmission now, both in linear and dB scale.\n",
    "\n",
    "The mode amplitudes are simply an [xarray.DataArray](https://docs.xarray.dev/en/stable/generated/xarray.DataArray.html) that can be selected, post processed, and plotted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "9075ae74-7b0a-4336-98a6-0b89a650d0d3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T12:15:23.882422Z",
     "start_time": "2026-03-17T12:15:23.879568Z"
    }
   },
   "outputs": [],
   "source": [
    "amps = data_final[\"mode_bb\"].amps.sel(direction=\"-\", mode_index=mode_index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "93a9b8e8-7581-4fb3-a3f4-f718a80082d0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T12:15:23.927984Z",
     "start_time": "2026-03-17T12:15:23.925585Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "transmission of 96.864 %\n"
     ]
    }
   ],
   "source": [
    "transmission = abs(amps) ** 2\n",
    "transmission_percent = 100 * transmission\n",
    "\n",
    "print(f\"transmission of {transmission_percent.values[0]:.3f} %\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b2b6145",
   "metadata": {},
   "source": [
    "## Export to GDS\n",
    "The `Simulation` object has the [.to_gds_file](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html#tidy3d.Simulation.to_gds_file) convenience function to export the final design to a `GDS` file. In addition to a file name, it is necessary to set a cross-sectional plane (`z = 0` in this case) on which to evaluate the geometry. See the [GDS export](https://www.flexcompute.com/tidy3d/examples/notebooks/GDSExport/) notebook for a detailed example on using `.to_gds_file` and other GDS related functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e6dc501b-54ef-4ef5-b54d-a45ce55af44e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T12:15:23.980641Z",
     "start_time": "2026-03-17T12:15:23.972832Z"
    }
   },
   "outputs": [],
   "source": [
    "sim_final.to_gds_file(\n",
    "    fname=\"./misc/inverse_des_wg_bend.gds\",\n",
    "    z=0,\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Passive photonic integrated circuit components"
  ],
  "description": "This notebook demonstrates the adjoint optimization of a waveguide bend in Tidy3D using autograd.",
  "feature_image": "./img/adjoint_8.png",
  "features": [
   "Adjoint inverse design"
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "inverse design, bend, design optimization, adjoint, 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": "3.11.2"
  },
  "title": "Adjoint Optimization of a Waveguide Bend in Tidy3D | Flexcompute"
 },
 "nbformat": 4,
 "nbformat_minor": 5
}