{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "411eea3f",
   "metadata": {},
   "source": [
    "# Grating Coupler: Bayesian Optimization for Initial Design\n",
    "\n",
    "> With our simulation setup in place, we now turn to optimization. Our goal is to find a set of grating parameters that maximizes the coupling efficiency. Since each simulation is computationally expensive, we will use Bayesian optimization. This technique is ideal for optimizing \"black-box\" functions that are costly to evaluate.\n",
    "\n",
    "## Why Bayesian Optimization?\n",
    "\n",
    "Exhaustive searches would require thousands of simulations. Bayesian optimization instead builds a probabilistic surrogate of the objective, balancing exploration of uncertain regions with exploitation of promising designs to converge in far fewer solver calls. It intelligently explores the parameter space to find the optimal design with a minimal number of simulations. Bayesian optimization works best when the design space has only a handful of effective degrees of freedom; beyond roughly five independent variables the surrogate becomes harder to learn, so we reserve higher-dimensional searches for gradient-based methods discussed later in the series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a776b66",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tidy3d as td\n",
    "from bayes_opt import BayesianOptimization\n",
    "from setup import (\n",
    "    center_wavelength,\n",
    "    get_mode_monitor_power,\n",
    "    make_simulation,\n",
    "    max_gap_si,\n",
    "    max_gap_sin,\n",
    "    max_width_si,\n",
    "    max_width_sin,\n",
    "    min_gap_si,\n",
    "    min_gap_sin,\n",
    "    min_width_si,\n",
    "    min_width_sin,\n",
    "    num_elements,\n",
    ")\n",
    "from setup import (\n",
    "    first_gap_si as default_first_gap_si,\n",
    ")\n",
    "from tidy3d import web"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdec7978",
   "metadata": {},
   "source": [
    "## The Evaluation Function\n",
    "\n",
    "The optimizer queries this function with a candidate set of grating parameters. We construct the simulation, run it in the cloud, and return the coupling efficiency from the mode monitor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d9a2952f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate(\n",
    "    width_si: float,\n",
    "    gap_si: float,\n",
    "    width_sin: float,\n",
    "    gap_sin: float,\n",
    "    first_gap_si: float,\n",
    ") -> float:\n",
    "    \"\"\"Return the coupling efficiency for a uniform grating parameterized array.\"\"\"\n",
    "    widths_si = np.full(num_elements, width_si)\n",
    "    gaps_si = np.full(num_elements, gap_si)\n",
    "    widths_sin = np.full(num_elements, width_sin)\n",
    "    gaps_sin = np.full(num_elements, gap_sin)\n",
    "\n",
    "    sim = make_simulation(\n",
    "        widths_si,\n",
    "        gaps_si,\n",
    "        widths_sin,\n",
    "        gaps_sin,\n",
    "        first_gap_si=first_gap_si,\n",
    "    )\n",
    "    sim_data = web.run(sim, task_name=\"gc_bopt_eval\", verbose=False)\n",
    "\n",
    "    power_da = get_mode_monitor_power(sim_data)\n",
    "    target_power = power_da.sel(f=td.C_0 / center_wavelength, method=\"nearest\").item()\n",
    "\n",
    "    return target_power"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1f09563",
   "metadata": {},
   "source": [
    "## Setting Up the Bayesian Optimizer\n",
    "\n",
    "We configure the optimizer with sensible defaults and practical bounds:\n",
    "- `parameter_bounds` (the `pbounds` argument) defines the design window we explore.\n",
    "- `init_points` sets how many random samples to collect before modeling.\n",
    "- `n_iter` controls the number of guided optimization iterations.\n",
    "\n",
    "## Framing the Problem: A 5-Parameter Global Search\n",
    "\n",
    "Rather than tune every tooth individually (30 variables per layer), we search a five-dimensional space of uniform widths, gaps, and inter-layer offset. This captures the dominant physics, keeps simulations fast, and yields a design that later gradient-based passes can refine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1e3c0d2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "seed = 12345\n",
    "\n",
    "init_points = 15\n",
    "n_iter = 60\n",
    "\n",
    "parameter_bounds = {\n",
    "    \"width_si\": (min_width_si, max_width_si),\n",
    "    \"gap_si\": (min_gap_si, max_gap_si),\n",
    "    \"width_sin\": (min_width_sin, max_width_sin),\n",
    "    \"gap_sin\": (min_gap_sin, max_gap_sin),\n",
    "    \"first_gap_si\": (\n",
    "        default_first_gap_si - 0.2,\n",
    "        default_first_gap_si + 0.2,\n",
    "    ),\n",
    "}\n",
    "\n",
    "default_design = {\n",
    "    \"width_si\": 0.45,\n",
    "    \"gap_si\": 0.55,\n",
    "    \"width_sin\": 0.35,\n",
    "    \"gap_sin\": 0.65,\n",
    "    \"first_gap_si\": default_first_gap_si,\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8a6cf940",
   "metadata": {},
   "outputs": [],
   "source": [
    "optimizer = BayesianOptimization(\n",
    "    f=evaluate,\n",
    "    pbounds=parameter_bounds,\n",
    "    random_state=seed,\n",
    "    verbose=2,\n",
    ")\n",
    "\n",
    "optimizer.probe(params=default_design, lazy=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f958972",
   "metadata": {},
   "source": [
    "## Running the Optimization\n",
    "\n",
    "Calling `optimizer.maximize(...)` alternates between exploration and exploitation to efficiently discover improved grating designs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "44b0a4cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|   iter    |  target   | first_... |  gap_si   |  gap_sin  | width_si  | width_sin |\n",
      "-------------------------------------------------------------------------------------\n",
      "| \u001b[39m1        \u001b[39m | \u001b[39m0.007373 \u001b[39m | \u001b[39m-0.7     \u001b[39m | \u001b[39m0.55     \u001b[39m | \u001b[39m0.65     \u001b[39m | \u001b[39m0.45     \u001b[39m | \u001b[39m0.35     \u001b[39m |\n",
      "| \u001b[39m2        \u001b[39m | \u001b[39m0.001166 \u001b[39m | \u001b[39m-0.5282  \u001b[39m | \u001b[39m0.4531   \u001b[39m | \u001b[39m0.4287   \u001b[39m | \u001b[39m0.2841   \u001b[39m | \u001b[39m0.6542   \u001b[39m |\n",
      "| \u001b[39m3        \u001b[39m | \u001b[39m0.002181 \u001b[39m | \u001b[39m-0.6618  \u001b[39m | \u001b[39m0.9716   \u001b[39m | \u001b[39m0.7572   \u001b[39m | \u001b[39m0.774    \u001b[39m | \u001b[39m0.7229   \u001b[39m |\n",
      "| \u001b[35m4        \u001b[39m | \u001b[35m0.04058  \u001b[39m | \u001b[35m-0.6009  \u001b[39m | \u001b[35m0.969    \u001b[39m | \u001b[35m0.3059   \u001b[39m | \u001b[35m0.1958   \u001b[39m | \u001b[35m0.439    \u001b[39m |\n",
      "| \u001b[39m5        \u001b[39m | \u001b[39m0.0007281\u001b[39m | \u001b[39m-0.6374  \u001b[39m | \u001b[39m0.8479   \u001b[39m | \u001b[39m0.9105   \u001b[39m | \u001b[39m0.9682   \u001b[39m | \u001b[39m0.7789   \u001b[39m |\n",
      "| \u001b[35m6        \u001b[39m | \u001b[35m0.181    \u001b[39m | \u001b[35m-0.643   \u001b[39m | \u001b[35m0.774    \u001b[39m | \u001b[35m0.6273   \u001b[39m | \u001b[35m0.393    \u001b[39m | \u001b[35m0.5517   \u001b[39m |\n",
      "| \u001b[39m7        \u001b[39m | \u001b[39m0.00206  \u001b[39m | \u001b[39m-0.6081  \u001b[39m | \u001b[39m0.9952   \u001b[39m | \u001b[39m0.7738   \u001b[39m | \u001b[39m0.8117   \u001b[39m | \u001b[39m0.3367   \u001b[39m |\n",
      "| \u001b[39m8        \u001b[39m | \u001b[39m0.0008147\u001b[39m | \u001b[39m-0.8893  \u001b[39m | \u001b[39m0.8403   \u001b[39m | \u001b[39m0.9326   \u001b[39m | \u001b[39m0.1222   \u001b[39m | \u001b[39m0.5934   \u001b[39m |\n",
      "| \u001b[39m9        \u001b[39m | \u001b[39m0.01132  \u001b[39m | \u001b[39m-0.6895  \u001b[39m | \u001b[39m0.6771   \u001b[39m | \u001b[39m0.3364   \u001b[39m | \u001b[39m0.9056   \u001b[39m | \u001b[39m0.7826   \u001b[39m |\n",
      "| \u001b[39m10       \u001b[39m | \u001b[39m0.009404 \u001b[39m | \u001b[39m-0.5727  \u001b[39m | \u001b[39m0.6002   \u001b[39m | \u001b[39m0.8671   \u001b[39m | \u001b[39m0.1864   \u001b[39m | \u001b[39m0.3752   \u001b[39m |\n",
      "| \u001b[39m11       \u001b[39m | \u001b[39m0.02459  \u001b[39m | \u001b[39m-0.7965  \u001b[39m | \u001b[39m0.5745   \u001b[39m | \u001b[39m0.6216   \u001b[39m | \u001b[39m0.7386   \u001b[39m | \u001b[39m0.3424   \u001b[39m |\n",
      "| \u001b[39m12       \u001b[39m | \u001b[39m0.004018 \u001b[39m | \u001b[39m-0.6874  \u001b[39m | \u001b[39m0.3342   \u001b[39m | \u001b[39m0.8382   \u001b[39m | \u001b[39m0.9354   \u001b[39m | \u001b[39m0.6876   \u001b[39m |\n",
      "| \u001b[39m13       \u001b[39m | \u001b[39m0.000441 \u001b[39m | \u001b[39m-0.8399  \u001b[39m | \u001b[39m0.5917   \u001b[39m | \u001b[39m0.5641   \u001b[39m | \u001b[39m0.8637   \u001b[39m | \u001b[39m0.9289   \u001b[39m |\n",
      "| \u001b[39m14       \u001b[39m | \u001b[39m8.261e-05\u001b[39m | \u001b[39m-0.7465  \u001b[39m | \u001b[39m0.4524   \u001b[39m | \u001b[39m0.6979   \u001b[39m | \u001b[39m0.269    \u001b[39m | \u001b[39m0.3007   \u001b[39m |\n",
      "| \u001b[39m15       \u001b[39m | \u001b[39m0.001766 \u001b[39m | \u001b[39m-0.625   \u001b[39m | \u001b[39m0.8397   \u001b[39m | \u001b[39m0.7015   \u001b[39m | \u001b[39m0.9759   \u001b[39m | \u001b[39m0.7072   \u001b[39m |\n",
      "| \u001b[39m16       \u001b[39m | \u001b[39m0.02805  \u001b[39m | \u001b[39m-0.5446  \u001b[39m | \u001b[39m0.5963   \u001b[39m | \u001b[39m0.5461   \u001b[39m | \u001b[39m0.7428   \u001b[39m | \u001b[39m0.6031   \u001b[39m |\n",
      "| \u001b[39m17       \u001b[39m | \u001b[39m0.1787   \u001b[39m | \u001b[39m-0.6397  \u001b[39m | \u001b[39m0.7773   \u001b[39m | \u001b[39m0.6306   \u001b[39m | \u001b[39m0.3964   \u001b[39m | \u001b[39m0.555    \u001b[39m |\n",
      "| \u001b[35m18       \u001b[39m | \u001b[35m0.3217   \u001b[39m | \u001b[35m-0.6909  \u001b[39m | \u001b[35m0.8335   \u001b[39m | \u001b[35m0.5581   \u001b[39m | \u001b[35m0.3556   \u001b[39m | \u001b[35m0.5659   \u001b[39m |\n",
      "| \u001b[39m19       \u001b[39m | \u001b[39m0.2231   \u001b[39m | \u001b[39m-0.7598  \u001b[39m | \u001b[39m0.8658   \u001b[39m | \u001b[39m0.5306   \u001b[39m | \u001b[39m0.3545   \u001b[39m | \u001b[39m0.6126   \u001b[39m |\n",
      "| \u001b[35m20       \u001b[39m | \u001b[35m0.3219   \u001b[39m | \u001b[35m-0.6909  \u001b[39m | \u001b[35m0.8335   \u001b[39m | \u001b[35m0.5583   \u001b[39m | \u001b[35m0.3559   \u001b[39m | \u001b[35m0.5661   \u001b[39m |\n",
      "| \u001b[39m21       \u001b[39m | \u001b[39m0.0415   \u001b[39m | \u001b[39m-0.6376  \u001b[39m | \u001b[39m0.9131   \u001b[39m | \u001b[39m0.5274   \u001b[39m | \u001b[39m0.3905   \u001b[39m | \u001b[39m0.5385   \u001b[39m |\n",
      "| \u001b[39m22       \u001b[39m | \u001b[39m0.1226   \u001b[39m | \u001b[39m-0.7002  \u001b[39m | \u001b[39m0.8083   \u001b[39m | \u001b[39m0.5893   \u001b[39m | \u001b[39m0.3262   \u001b[39m | \u001b[39m0.6175   \u001b[39m |\n",
      "| \u001b[35m23       \u001b[39m | \u001b[35m0.3379   \u001b[39m | \u001b[35m-0.7272  \u001b[39m | \u001b[35m0.8219   \u001b[39m | \u001b[35m0.555    \u001b[39m | \u001b[35m0.3927   \u001b[39m | \u001b[35m0.5517   \u001b[39m |\n",
      "| \u001b[35m24       \u001b[39m | \u001b[35m0.3426   \u001b[39m | \u001b[35m-0.6933  \u001b[39m | \u001b[35m0.7992   \u001b[39m | \u001b[35m0.5135   \u001b[39m | \u001b[35m0.3983   \u001b[39m | \u001b[35m0.5782   \u001b[39m |\n",
      "| \u001b[39m25       \u001b[39m | \u001b[39m0.01591  \u001b[39m | \u001b[39m-0.716   \u001b[39m | \u001b[39m0.8449   \u001b[39m | \u001b[39m0.427    \u001b[39m | \u001b[39m0.854    \u001b[39m | \u001b[39m0.7467   \u001b[39m |\n",
      "| \u001b[39m26       \u001b[39m | \u001b[39m0.2208   \u001b[39m | \u001b[39m-0.7426  \u001b[39m | \u001b[39m0.7811   \u001b[39m | \u001b[39m0.4777   \u001b[39m | \u001b[39m0.3799   \u001b[39m | \u001b[39m0.5267   \u001b[39m |\n",
      "| \u001b[39m27       \u001b[39m | \u001b[39m0.1707   \u001b[39m | \u001b[39m-0.7213  \u001b[39m | \u001b[39m0.8082   \u001b[39m | \u001b[39m0.5425   \u001b[39m | \u001b[39m0.47     \u001b[39m | \u001b[39m0.6034   \u001b[39m |\n",
      "| \u001b[39m28       \u001b[39m | \u001b[39m0.02944  \u001b[39m | \u001b[39m-0.6112  \u001b[39m | \u001b[39m0.7241   \u001b[39m | \u001b[39m0.3802   \u001b[39m | \u001b[39m0.1305   \u001b[39m | \u001b[39m0.7133   \u001b[39m |\n",
      "| \u001b[39m29       \u001b[39m | \u001b[39m0.295    \u001b[39m | \u001b[39m-0.6724  \u001b[39m | \u001b[39m0.7966   \u001b[39m | \u001b[39m0.5351   \u001b[39m | \u001b[39m0.4015   \u001b[39m | \u001b[39m0.5239   \u001b[39m |\n",
      "| \u001b[39m30       \u001b[39m | \u001b[39m0.2459   \u001b[39m | \u001b[39m-0.6254  \u001b[39m | \u001b[39m0.7534   \u001b[39m | \u001b[39m0.4725   \u001b[39m | \u001b[39m0.3783   \u001b[39m | \u001b[39m0.5916   \u001b[39m |\n",
      "| \u001b[39m31       \u001b[39m | \u001b[39m0.2677   \u001b[39m | \u001b[39m-0.696   \u001b[39m | \u001b[39m0.8142   \u001b[39m | \u001b[39m0.4183   \u001b[39m | \u001b[39m0.3826   \u001b[39m | \u001b[39m0.6427   \u001b[39m |\n",
      "| \u001b[39m32       \u001b[39m | \u001b[39m0.1886   \u001b[39m | \u001b[39m-0.6629  \u001b[39m | \u001b[39m0.7435   \u001b[39m | \u001b[39m0.3459   \u001b[39m | \u001b[39m0.4558   \u001b[39m | \u001b[39m0.6294   \u001b[39m |\n",
      "| \u001b[39m33       \u001b[39m | \u001b[39m0.2116   \u001b[39m | \u001b[39m-0.8001  \u001b[39m | \u001b[39m0.8154   \u001b[39m | \u001b[39m0.3366   \u001b[39m | \u001b[39m0.3902   \u001b[39m | \u001b[39m0.7036   \u001b[39m |\n",
      "| \u001b[39m34       \u001b[39m | \u001b[39m0.1522   \u001b[39m | \u001b[39m-0.6654  \u001b[39m | \u001b[39m0.8274   \u001b[39m | \u001b[39m0.3739   \u001b[39m | \u001b[39m0.4143   \u001b[39m | \u001b[39m0.7777   \u001b[39m |\n",
      "| \u001b[39m35       \u001b[39m | \u001b[39m0.02097  \u001b[39m | \u001b[39m-0.7357  \u001b[39m | \u001b[39m0.8873   \u001b[39m | \u001b[39m0.3      \u001b[39m | \u001b[39m0.4083   \u001b[39m | \u001b[39m0.6054   \u001b[39m |\n",
      "| \u001b[39m36       \u001b[39m | \u001b[39m0.1153   \u001b[39m | \u001b[39m-0.7497  \u001b[39m | \u001b[39m0.7184   \u001b[39m | \u001b[39m0.4285   \u001b[39m | \u001b[39m0.3821   \u001b[39m | \u001b[39m0.6787   \u001b[39m |\n",
      "| \u001b[39m37       \u001b[39m | \u001b[39m0.3122   \u001b[39m | \u001b[39m-0.7625  \u001b[39m | \u001b[39m0.8559   \u001b[39m | \u001b[39m0.6204   \u001b[39m | \u001b[39m0.3704   \u001b[39m | \u001b[39m0.485    \u001b[39m |\n",
      "| \u001b[39m38       \u001b[39m | \u001b[39m0.222    \u001b[39m | \u001b[39m-0.8684  \u001b[39m | \u001b[39m0.8764   \u001b[39m | \u001b[39m0.6099   \u001b[39m | \u001b[39m0.3932   \u001b[39m | \u001b[39m0.4762   \u001b[39m |\n",
      "| \u001b[39m39       \u001b[39m | \u001b[39m0.1586   \u001b[39m | \u001b[39m-0.7685  \u001b[39m | \u001b[39m0.8767   \u001b[39m | \u001b[39m0.7177   \u001b[39m | \u001b[39m0.428    \u001b[39m | \u001b[39m0.4673   \u001b[39m |\n",
      "| \u001b[39m40       \u001b[39m | \u001b[39m0.06846  \u001b[39m | \u001b[39m-0.7872  \u001b[39m | \u001b[39m0.8409   \u001b[39m | \u001b[39m0.5931   \u001b[39m | \u001b[39m0.2975   \u001b[39m | \u001b[39m0.4117   \u001b[39m |\n",
      "| \u001b[39m41       \u001b[39m | \u001b[39m0.08975  \u001b[39m | \u001b[39m-0.7685  \u001b[39m | \u001b[39m0.8588   \u001b[39m | \u001b[39m0.5832   \u001b[39m | \u001b[39m0.4436   \u001b[39m | \u001b[39m0.4799   \u001b[39m |\n",
      "| \u001b[39m42       \u001b[39m | \u001b[39m0.1084   \u001b[39m | \u001b[39m-0.7878  \u001b[39m | \u001b[39m0.8762   \u001b[39m | \u001b[39m0.6417   \u001b[39m | \u001b[39m0.3469   \u001b[39m | \u001b[39m0.5454   \u001b[39m |\n",
      "| \u001b[39m43       \u001b[39m | \u001b[39m0.2467   \u001b[39m | \u001b[39m-0.6835  \u001b[39m | \u001b[39m0.8234   \u001b[39m | \u001b[39m0.4741   \u001b[39m | \u001b[39m0.3515   \u001b[39m | \u001b[39m0.5887   \u001b[39m |\n",
      "| \u001b[39m44       \u001b[39m | \u001b[39m0.006366 \u001b[39m | \u001b[39m-0.5162  \u001b[39m | \u001b[39m0.5468   \u001b[39m | \u001b[39m0.664    \u001b[39m | \u001b[39m0.7499   \u001b[39m | \u001b[39m0.8926   \u001b[39m |\n",
      "| \u001b[39m45       \u001b[39m | \u001b[39m0.2918   \u001b[39m | \u001b[39m-0.7085  \u001b[39m | \u001b[39m0.8233   \u001b[39m | \u001b[39m0.6025   \u001b[39m | \u001b[39m0.3602   \u001b[39m | \u001b[39m0.4973   \u001b[39m |\n",
      "| \u001b[39m46       \u001b[39m | \u001b[39m0.2756   \u001b[39m | \u001b[39m-0.641   \u001b[39m | \u001b[39m0.8088   \u001b[39m | \u001b[39m0.4759   \u001b[39m | \u001b[39m0.4281   \u001b[39m | \u001b[39m0.6529   \u001b[39m |\n",
      "| \u001b[39m47       \u001b[39m | \u001b[39m0.259    \u001b[39m | \u001b[39m-0.5791  \u001b[39m | \u001b[39m0.8002   \u001b[39m | \u001b[39m0.4016   \u001b[39m | \u001b[39m0.3924   \u001b[39m | \u001b[39m0.6605   \u001b[39m |\n",
      "| \u001b[39m48       \u001b[39m | \u001b[39m0.09593  \u001b[39m | \u001b[39m-0.5623  \u001b[39m | \u001b[39m0.7689   \u001b[39m | \u001b[39m0.4404   \u001b[39m | \u001b[39m0.4795   \u001b[39m | \u001b[39m0.6131   \u001b[39m |\n",
      "| \u001b[39m49       \u001b[39m | \u001b[39m0.06088  \u001b[39m | \u001b[39m-0.6232  \u001b[39m | \u001b[39m0.8136   \u001b[39m | \u001b[39m0.4617   \u001b[39m | \u001b[39m0.3479   \u001b[39m | \u001b[39m0.6981   \u001b[39m |\n",
      "| \u001b[39m50       \u001b[39m | \u001b[39m0.1864   \u001b[39m | \u001b[39m-0.6742  \u001b[39m | \u001b[39m0.8025   \u001b[39m | \u001b[39m0.4417   \u001b[39m | \u001b[39m0.4322   \u001b[39m | \u001b[39m0.5883   \u001b[39m |\n",
      "| \u001b[39m51       \u001b[39m | \u001b[39m0.001129 \u001b[39m | \u001b[39m-0.7316  \u001b[39m | \u001b[39m0.8609   \u001b[39m | \u001b[39m0.8731   \u001b[39m | \u001b[39m0.7566   \u001b[39m | \u001b[39m0.7094   \u001b[39m |\n",
      "| \u001b[39m52       \u001b[39m | \u001b[39m0.2293   \u001b[39m | \u001b[39m-0.7121  \u001b[39m | \u001b[39m0.7631   \u001b[39m | \u001b[39m0.5474   \u001b[39m | \u001b[39m0.3747   \u001b[39m | \u001b[39m0.5568   \u001b[39m |\n",
      "| \u001b[39m53       \u001b[39m | \u001b[39m0.3059   \u001b[39m | \u001b[39m-0.6423  \u001b[39m | \u001b[39m0.8069   \u001b[39m | \u001b[39m0.5383   \u001b[39m | \u001b[39m0.4062   \u001b[39m | \u001b[39m0.5966   \u001b[39m |\n",
      "| \u001b[39m54       \u001b[39m | \u001b[39m0.06258  \u001b[39m | \u001b[39m-0.5826  \u001b[39m | \u001b[39m0.7606   \u001b[39m | \u001b[39m0.3205   \u001b[39m | \u001b[39m0.3611   \u001b[39m | \u001b[39m0.638    \u001b[39m |\n",
      "| \u001b[39m55       \u001b[39m | \u001b[39m0.207    \u001b[39m | \u001b[39m-0.7387  \u001b[39m | \u001b[39m0.8525   \u001b[39m | \u001b[39m0.4576   \u001b[39m | \u001b[39m0.4255   \u001b[39m | \u001b[39m0.6778   \u001b[39m |\n",
      "| \u001b[39m56       \u001b[39m | \u001b[39m0.04347  \u001b[39m | \u001b[39m-0.6178  \u001b[39m | \u001b[39m0.8528   \u001b[39m | \u001b[39m0.3955   \u001b[39m | \u001b[39m0.4493   \u001b[39m | \u001b[39m0.6773   \u001b[39m |\n",
      "| \u001b[39m57       \u001b[39m | \u001b[39m0.2797   \u001b[39m | \u001b[39m-0.6946  \u001b[39m | \u001b[39m0.8403   \u001b[39m | \u001b[39m0.5222   \u001b[39m | \u001b[39m0.4      \u001b[39m | \u001b[39m0.6144   \u001b[39m |\n",
      "| \u001b[39m58       \u001b[39m | \u001b[39m0.2402   \u001b[39m | \u001b[39m-0.7916  \u001b[39m | \u001b[39m0.827    \u001b[39m | \u001b[39m0.4341   \u001b[39m | \u001b[39m0.3574   \u001b[39m | \u001b[39m0.6185   \u001b[39m |\n",
      "| \u001b[39m59       \u001b[39m | \u001b[39m0.04937  \u001b[39m | \u001b[39m-0.836   \u001b[39m | \u001b[39m0.8689   \u001b[39m | \u001b[39m0.4237   \u001b[39m | \u001b[39m0.3393   \u001b[39m | \u001b[39m0.7152   \u001b[39m |\n",
      "| \u001b[39m60       \u001b[39m | \u001b[39m0.3044   \u001b[39m | \u001b[39m-0.7068  \u001b[39m | \u001b[39m0.8805   \u001b[39m | \u001b[39m0.6484   \u001b[39m | \u001b[39m0.3592   \u001b[39m | \u001b[39m0.4604   \u001b[39m |\n",
      "| \u001b[39m61       \u001b[39m | \u001b[39m0.0761   \u001b[39m | \u001b[39m-0.6435  \u001b[39m | \u001b[39m0.8796   \u001b[39m | \u001b[39m0.4544   \u001b[39m | \u001b[39m0.2933   \u001b[39m | \u001b[39m0.2807   \u001b[39m |\n",
      "| \u001b[39m62       \u001b[39m | \u001b[39m0.2577   \u001b[39m | \u001b[39m-0.7314  \u001b[39m | \u001b[39m0.8167   \u001b[39m | \u001b[39m0.6713   \u001b[39m | \u001b[39m0.3653   \u001b[39m | \u001b[39m0.4545   \u001b[39m |\n",
      "| \u001b[39m63       \u001b[39m | \u001b[39m0.003973 \u001b[39m | \u001b[39m-0.6534  \u001b[39m | \u001b[39m0.4818   \u001b[39m | \u001b[39m0.9379   \u001b[39m | \u001b[39m0.1868   \u001b[39m | \u001b[39m0.9214   \u001b[39m |\n",
      "| \u001b[39m64       \u001b[39m | \u001b[39m0.2642   \u001b[39m | \u001b[39m-0.6335  \u001b[39m | \u001b[39m0.8656   \u001b[39m | \u001b[39m0.7031   \u001b[39m | \u001b[39m0.3425   \u001b[39m | \u001b[39m0.443    \u001b[39m |\n",
      "| \u001b[39m65       \u001b[39m | \u001b[39m0.2023   \u001b[39m | \u001b[39m-0.6883  \u001b[39m | \u001b[39m0.9274   \u001b[39m | \u001b[39m0.7084   \u001b[39m | \u001b[39m0.345    \u001b[39m | \u001b[39m0.3905   \u001b[39m |\n",
      "| \u001b[39m66       \u001b[39m | \u001b[39m0.2385   \u001b[39m | \u001b[39m-0.6441  \u001b[39m | \u001b[39m0.8423   \u001b[39m | \u001b[39m0.6453   \u001b[39m | \u001b[39m0.3966   \u001b[39m | \u001b[39m0.4068   \u001b[39m |\n",
      "| \u001b[39m67       \u001b[39m | \u001b[39m0.115    \u001b[39m | \u001b[39m-0.6291  \u001b[39m | \u001b[39m0.8525   \u001b[39m | \u001b[39m0.6278   \u001b[39m | \u001b[39m0.2939   \u001b[39m | \u001b[39m0.4472   \u001b[39m |\n",
      "| \u001b[39m68       \u001b[39m | \u001b[39m0.009544 \u001b[39m | \u001b[39m-0.6876  \u001b[39m | \u001b[39m0.6745   \u001b[39m | \u001b[39m0.6504   \u001b[39m | \u001b[39m0.7635   \u001b[39m | \u001b[39m0.534    \u001b[39m |\n",
      "| \u001b[39m69       \u001b[39m | \u001b[39m0.1545   \u001b[39m | \u001b[39m-0.6343  \u001b[39m | \u001b[39m0.8937   \u001b[39m | \u001b[39m0.7117   \u001b[39m | \u001b[39m0.4213   \u001b[39m | \u001b[39m0.4706   \u001b[39m |\n",
      "| \u001b[39m70       \u001b[39m | \u001b[39m0.1657   \u001b[39m | \u001b[39m-0.6473  \u001b[39m | \u001b[39m0.8122   \u001b[39m | \u001b[39m0.7514   \u001b[39m | \u001b[39m0.3606   \u001b[39m | \u001b[39m0.3789   \u001b[39m |\n",
      "| \u001b[39m71       \u001b[39m | \u001b[39m0.09981  \u001b[39m | \u001b[39m-0.6858  \u001b[39m | \u001b[39m0.8804   \u001b[39m | \u001b[39m0.7599   \u001b[39m | \u001b[39m0.3      \u001b[39m | \u001b[39m0.4805   \u001b[39m |\n",
      "| \u001b[39m72       \u001b[39m | \u001b[39m0.2367   \u001b[39m | \u001b[39m-0.7438  \u001b[39m | \u001b[39m0.8586   \u001b[39m | \u001b[39m0.541    \u001b[39m | \u001b[39m0.3547   \u001b[39m | \u001b[39m0.5173   \u001b[39m |\n",
      "| \u001b[39m73       \u001b[39m | \u001b[39m0.1969   \u001b[39m | \u001b[39m-0.5551  \u001b[39m | \u001b[39m0.9023   \u001b[39m | \u001b[39m0.7058   \u001b[39m | \u001b[39m0.3568   \u001b[39m | \u001b[39m0.3739   \u001b[39m |\n",
      "| \u001b[39m74       \u001b[39m | \u001b[39m0.003964 \u001b[39m | \u001b[39m-0.867   \u001b[39m | \u001b[39m0.5866   \u001b[39m | \u001b[39m0.3316   \u001b[39m | \u001b[39m0.3515   \u001b[39m | \u001b[39m0.2023   \u001b[39m |\n",
      "| \u001b[39m75       \u001b[39m | \u001b[39m0.2389   \u001b[39m | \u001b[39m-0.7877  \u001b[39m | \u001b[39m0.7523   \u001b[39m | \u001b[39m0.3      \u001b[39m | \u001b[39m0.4788   \u001b[39m | \u001b[39m0.7533   \u001b[39m |\n",
      "| \u001b[39m76       \u001b[39m | \u001b[39m0.04023  \u001b[39m | \u001b[39m-0.797   \u001b[39m | \u001b[39m0.7835   \u001b[39m | \u001b[39m0.3      \u001b[39m | \u001b[39m0.4151   \u001b[39m | \u001b[39m0.8371   \u001b[39m |\n",
      "=====================================================================================\n"
     ]
    }
   ],
   "source": [
    "optimizer.maximize(init_points=init_points, n_iter=n_iter)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b89b286f",
   "metadata": {},
   "source": [
    "## Analyzing the Results\n",
    "\n",
    "We extract the optimizer history, track the best observed loss, and visualize how the search converges toward high-efficiency gratings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2d05ffdf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization complete.\n",
      "Best parameters: {'first_gap_si': np.float64(-0.6933388041768698), 'gap_si': np.float64(0.7992416233438039), 'gap_sin': np.float64(0.5135103145142313), 'width_si': np.float64(0.3983180007432449), 'width_sin': np.float64(0.5781958117277934)}\n",
      "Best objective (power): 0.3425821844561507\n",
      "Best objective (dB): 4.65\n"
     ]
    }
   ],
   "source": [
    "best = optimizer.max\n",
    "\n",
    "results = optimizer.res\n",
    "iterations = np.arange(1, len(results) + 1)\n",
    "targets = np.asarray([res[\"target\"] for res in results], dtype=float)\n",
    "targets = np.maximum(targets, 1e-12)\n",
    "coupling_loss_db = -10 * np.log10(targets)\n",
    "best_loss = np.minimum.accumulate(coupling_loss_db)\n",
    "\n",
    "best_loss_db = -10 * np.log10(max(best[\"target\"], 1e-12))\n",
    "\n",
    "print(\"Optimization complete.\")\n",
    "print(f\"Best parameters: {best['params']}\")\n",
    "print(f\"Best objective (power): {best['target']}\")\n",
    "print(f\"Best objective (dB): {best_loss_db:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4606275e",
   "metadata": {},
   "source": [
    "## Interpreting the Optimization Progress\n",
    "\n",
    "The scatter points show every simulation the optimizer evaluated, while the red curve tracks the best coupling loss found so far. Early iterations explore widely; later ones cluster near promising regions as the surrogate model focuses on exploitation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1d91747f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 4))\n",
    "ax.scatter(iterations, coupling_loss_db, label=\"Samples\")\n",
    "ax.plot(iterations, best_loss, color=\"red\", label=\"Best so far\")\n",
    "ax.set_xlabel(\"Iteration\")\n",
    "ax.set_ylabel(\"Coupling loss (dB)\")\n",
    "ax.set_title(\"Bayesian optimization progress\")\n",
    "ax.legend()\n",
    "plt.grid(True, alpha=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "135ed68e",
   "metadata": {},
   "source": [
    "## Visualizing the Optimized Design\n",
    "\n",
    "We reconstruct the best-performing structure, inspect its geometry, and analyze the spectral response to confirm the optimizer's progress."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d8151e0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "best_params = {name: float(value) for name, value in best[\"params\"].items()}\n",
    "best_widths_si = np.full(num_elements, best_params[\"width_si\"])\n",
    "best_gaps_si = np.full(num_elements, best_params[\"gap_si\"])\n",
    "best_widths_sin = np.full(num_elements, best_params[\"width_sin\"])\n",
    "best_gaps_sin = np.full(num_elements, best_params[\"gap_sin\"])\n",
    "best_first_gap_si = best_params[\"first_gap_si\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f3191db5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "best_sim = make_simulation(\n",
    "    best_widths_si,\n",
    "    best_gaps_si,\n",
    "    best_widths_sin,\n",
    "    best_gaps_sin,\n",
    "    first_gap_si=best_first_gap_si,\n",
    "    include_field_monitor=True,\n",
    ")\n",
    "ax = best_sim.plot(y=0)\n",
    "ax.set_title(\"Cross-section of the optimized grating (y=0)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ef0bcf39",
   "metadata": {},
   "outputs": [],
   "source": [
    "best_data = web.run(best_sim, task_name=\"gc_bopt_final\", verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3bd4eae3",
   "metadata": {},
   "outputs": [],
   "source": [
    "power_da = get_mode_monitor_power(best_data)\n",
    "freqs = power_da.coords[\"f\"].values\n",
    "wavelengths = td.C_0 / freqs\n",
    "power = np.squeeze(power_da.data)\n",
    "power_db = 10 * np.log10(power)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0ad87dab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 4))\n",
    "ax.plot(wavelengths, power_db)\n",
    "ax.set_xlabel(\"Wavelength (µm)\")\n",
    "ax.set_ylabel(\"Transmission (dB)\")\n",
    "ax.set_title(\"Mode monitor spectrum (optimized design)\")\n",
    "ax.grid(True, alpha=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1984bbfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = best_data.plot_field(\"field_monitor\", \"Ey\", \"abs^2\")\n",
    "ax.set_title(\"Field intensity |Ey|^2 for the optimized design\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2c434de",
   "metadata": {},
   "source": [
    "The optimized geometry increases overlap between the free-space beam and the guided mode, yielding a stronger steady-state field inside the silicon nitride layer. In the next notebook we leverage this design as the starting point for gradient-based refinement."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "303207c7",
   "metadata": {},
   "source": [
    "## Exporting the Best Design\n",
    "\n",
    "We serialize the best uniform grating parameters so the adjoint notebook can continue from this design without rerunning the Bayesian search."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "00274144",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved best design to /home/yannick/flexcompute/worktrees/seminar_notebooks/docs/notebooks/2025-10-09-invdes-seminar/results/gc_bayes_opt_best.json\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "from pathlib import Path\n",
    "\n",
    "export_path = Path(\"./results/gc_bayes_opt_best.json\")\n",
    "export_path.parent.mkdir(parents=True, exist_ok=True)\n",
    "\n",
    "export_payload = {\n",
    "    \"width_si\": best_params[\"width_si\"],\n",
    "    \"gap_si\": best_params[\"gap_si\"],\n",
    "    \"width_sin\": best_params[\"width_sin\"],\n",
    "    \"gap_sin\": best_params[\"gap_sin\"],\n",
    "    \"first_gap_si\": best_params[\"first_gap_si\"],\n",
    "    \"target_power\": float(best[\"target\"]),\n",
    "    \"coupling_loss_db\": float(best_loss_db),\n",
    "}\n",
    "\n",
    "with export_path.open(\"w\", encoding=\"utf-8\") as f:\n",
    "    json.dump(export_payload, f, indent=2)\n",
    "\n",
    "print(f\"Saved best design to {export_path.resolve()}\")"
   ]
  }
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