{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "bc90c0990f1c3177",
   "metadata": {},
   "source": [
    "# Introduction to source gradients\n",
    "Source gradients make it possible to optimize systems in which one simulation produces the illumination for another.<br>\n",
    "This is useful for multi-stage photonic design problems such as two-level metasurfaces, where the stages can be used for tasks like wavefront pre-shaping, distributing phase control, or correcting aberrations. Without source gradients, a common workflow is to design each stage separately or to optimize a downstream stage under fixed upstream illumination, which makes end-to-end co-design difficult.<br>\n",
    "In this notebook, we demonstrate the idea with a two-level metalens: the first FDTD simulation generates a bridge field, that field is projected to the second stage as a differentiable custom source, and the second FDTD simulation focuses it to the final target. Because the projected source remains differentiable, gradients from the final objective can flow back through the bridge field into the first simulation.<br>\n",
    "This lets us co-optimize both metasurfaces without meshing the long free-space region between the two lenses or the long free-space region between the second lens and the focus inside one large FDTD domain.<br>\n",
    "For more metalens optimization notebooks, see\n",
    "- [Adjoint Optimization of a Metalens in Tidy3D](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd7Metalens/)\n",
    "- [Metalens in the visible frequency range](https://www.flexcompute.com/tidy3d/examples/notebooks/Metalens/)\n",
    "- [Design and shape optimization of a metalens-assisted waveguide taper](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd20MetalensWaveguideTaper/)\n",
    "- [Mid-IR metalens based on silicon nanopillars](https://www.flexcompute.com/tidy3d/examples/notebooks/MidIRMetalens/)\n",
    "\n",
    "For introductory notebooks on inverse design with Tidy3D, see\n",
    "- [Inverse design overview](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd0Overview/)\n",
    "- [Autograd, automatic differentiation, and adjoint optimization: basics](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd1Intro/)\n",
    "- [Inverse design quickstart - level 1](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd0Quickstart/)\n",
    "- [Inverse design quickstart - level 2](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd0QuickstartII/)\n",
    "\n",
    "<img src=\"./img/two_level_metalens.jpg\" style=\"width:30%;\">\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72baa936cd25e8db",
   "metadata": {},
   "source": [
    "## Setup\n",
    "We first import the packages needed for the optimization and for plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9e0515045716631d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:43:02.898799Z",
     "start_time": "2026-03-17T10:42:59.102920Z"
    }
   },
   "outputs": [],
   "source": [
    "import autograd.numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import tidy3d as td\n",
    "from autograd import value_and_grad\n",
    "from tidy3d import web\n",
    "from tidy3d.plugins.autograd import adam, optimize\n",
    "\n",
    "td.config.logging.level = \"ERROR\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "342f5980f537f330",
   "metadata": {},
   "source": "Next we define the basic physical and geometric parameters of the two-stage system."
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5fbde6e2791ae6fb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:43:02.911696Z",
     "start_time": "2026-03-17T10:43:02.908829Z"
    }
   },
   "outputs": [],
   "source": [
    "nm = 1e-3  # 1 nanometer in units of microns (for conversion)\n",
    "\n",
    "wavelength = 850 * nm  # free space central wavelength\n",
    "f0 = td.C_0 / wavelength  # central frequency\n",
    "fwidth = f0 / 20  # source pulse width\n",
    "\n",
    "diameter = 6.0  # diameter of each metalens\n",
    "height = 430 * nm  # pillar height\n",
    "period = 320 * nm  # lattice spacing\n",
    "\n",
    "radius_min = 50 * nm  # minimum pillar radius\n",
    "radius_max = period / 2 - 10 * nm  # maximum pillar radius\n",
    "\n",
    "buffer_z = wavelength / 2  # space above and below each metalens\n",
    "buffer_xy = wavelength  # buffer region in x and y\n",
    "\n",
    "n_si = 3.84  # refractive index of Si at 850 nm\n",
    "n_sio2 = 1.45  # refractive index of SiO2 at 850 nm\n",
    "\n",
    "air = td.Medium(permittivity=1.0)  # air background medium\n",
    "sio2 = td.Medium(permittivity=n_sio2**2)  # SiO2 substrate medium\n",
    "si = td.Medium(permittivity=n_si**2)  # Si pillar medium\n",
    "\n",
    "symmetry = (-1, 1, 0)  # symmetry across x and y\n",
    "run_time = 100 / fwidth  # simulation run time\n",
    "min_steps_per_wvl = 10  # minimum steps per wavelength"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "755947196426bbcd",
   "metadata": {},
   "source": [
    "We now define the derived distances used in the two-stage pipeline.<br>\n",
    "The first lens sends light to a bridge plane, and the second lens focuses from there to the final focal point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4b7ddb82c74e0c89",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:43:02.958346Z",
     "start_time": "2026-03-17T10:43:02.955173Z"
    }
   },
   "outputs": [],
   "source": [
    "sim_size_xy = diameter + 2 * buffer_xy  # simulation size in x and y for each lens stage\n",
    "sim_size_z = height + 2 * buffer_z  # simulation size in z for each lens stage\n",
    "sim_size = (sim_size_xy, sim_size_xy, sim_size_z)  # full simulation size tuple\n",
    "\n",
    "focal_length = diameter  # focus location measured from the top surface of the second lens\n",
    "focal_distance = (\n",
    "    focal_length - buffer_z / 2\n",
    ")  # projection distance measured from the near-field monitor plane\n",
    "bridge_distance = (\n",
    "    0.5 * focal_distance\n",
    ")  # distance from the first near-field plane to the bridge plane\n",
    "\n",
    "source_center = (0, 0, -height / 2 - buffer_z / 2)  # plane-wave source location\n",
    "near_monitor_center = (0, 0, height / 2 + buffer_z / 2)  # near-field monitor location\n",
    "\n",
    "plane_size = diameter + buffer_xy  # transverse size of the bridge source plane\n",
    "bridge_source_center = source_center  # center of the custom source plane for level 2\n",
    "bridge_source_size = (plane_size, plane_size, 0)  # size of the custom source plane for level 2\n",
    "\n",
    "pulse = td.GaussianPulse(freq0=f0, fwidth=fwidth, phase=0)  # source time dependence"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27c2ac763dbd7a25",
   "metadata": {},
   "source": [
    "We divide the problem into two local FDTD simulations and two field-projection steps for the free-space propagation regions.<br>\n",
    "Before constructing the individual pieces, we first show an overview of the setup.<br>\n",
    "The sketch below shows the two local simulation boxes, the empty-space regions that are replaced by field projection, and the final focal point.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b200929d13b8319b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:43:03.105242Z",
     "start_time": "2026-03-17T10:43:03.006666Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x620 with 1 Axes>"
      ]
     },
     "jetTransient": {
      "display_id": null
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.patches import Rectangle\n",
    "\n",
    "\n",
    "def plot_two_stage_setup():\n",
    "    sim1_center_z = 0.0\n",
    "    sim1_start_z, sim1_end_z = sim1_center_z - sim_size_z / 2, sim1_center_z + sim_size_z / 2\n",
    "\n",
    "    bridge_plane_z = near_monitor_center[2] + bridge_distance\n",
    "\n",
    "    # Align the source plane of simulation 2 with the projected bridge plane.\n",
    "    sim2_center_z = bridge_plane_z - source_center[2]\n",
    "    sim2_start_z, sim2_end_z = sim2_center_z - sim_size_z / 2, sim2_center_z + sim_size_z / 2\n",
    "\n",
    "    lens1_start_z = -height / 2\n",
    "    lens2_start_z, lens2_end_z = sim2_center_z - height / 2, sim2_center_z + height / 2\n",
    "\n",
    "    # The focus is measured from the top of metalens 2.\n",
    "    focus_z = sim2_center_z + near_monitor_center[2] + focal_distance\n",
    "\n",
    "    y_bottom, y_top = -diameter / 2, diameter / 2\n",
    "    y_center = 0.0\n",
    "    y_margin_bottom, y_margin_top = 1.0, 2.0\n",
    "    projection_label_y = y_bottom - 0.55\n",
    "    focal_arrow_y = y_top + 1.25\n",
    "    focal_text_y = y_top + 0.8\n",
    "    line_ymin, line_ymax = y_bottom - 0.3, y_top\n",
    "\n",
    "    fig, ax = plt.subplots(figsize=(12, 6.2), tight_layout=True)\n",
    "\n",
    "    sim_color = \"#dbe9f4\"\n",
    "    lens_color = \"#2f5d62\"\n",
    "    projection_color = \"#f7dcc3\"\n",
    "\n",
    "    ax.add_patch(\n",
    "        Rectangle(\n",
    "            (sim1_start_z, y_bottom),\n",
    "            sim_size_z,\n",
    "            diameter,\n",
    "            facecolor=sim_color,\n",
    "            edgecolor=\"black\",\n",
    "            linewidth=1.2,\n",
    "        )\n",
    "    )\n",
    "    ax.add_patch(\n",
    "        Rectangle(\n",
    "            (sim2_start_z, y_bottom),\n",
    "            sim_size_z,\n",
    "            diameter,\n",
    "            facecolor=sim_color,\n",
    "            edgecolor=\"black\",\n",
    "            linewidth=1.2,\n",
    "        )\n",
    "    )\n",
    "\n",
    "    ax.add_patch(\n",
    "        Rectangle(\n",
    "            (lens1_start_z, y_bottom), height, diameter, facecolor=lens_color, edgecolor=\"none\"\n",
    "        )\n",
    "    )\n",
    "    ax.add_patch(\n",
    "        Rectangle(\n",
    "            (lens2_start_z, y_bottom), height, diameter, facecolor=lens_color, edgecolor=\"none\"\n",
    "        )\n",
    "    )\n",
    "\n",
    "    ax.add_patch(\n",
    "        Rectangle(\n",
    "            (sim1_end_z, y_bottom),\n",
    "            sim2_start_z - sim1_end_z,\n",
    "            diameter,\n",
    "            facecolor=projection_color,\n",
    "            edgecolor=\"tab:red\",\n",
    "            linewidth=1.2,\n",
    "            linestyle=\"--\",\n",
    "            alpha=0.45,\n",
    "        )\n",
    "    )\n",
    "    ax.add_patch(\n",
    "        Rectangle(\n",
    "            (sim2_end_z, y_bottom),\n",
    "            focus_z - sim2_end_z,\n",
    "            diameter,\n",
    "            facecolor=projection_color,\n",
    "            edgecolor=\"tab:red\",\n",
    "            linewidth=1.2,\n",
    "            linestyle=\"--\",\n",
    "            alpha=0.45,\n",
    "        )\n",
    "    )\n",
    "\n",
    "    ax.annotate(\n",
    "        \"\",\n",
    "        xy=(source_center[2] - 0.2, y_center),\n",
    "        xytext=(source_center[2] - 1.0, y_center),\n",
    "        arrowprops=dict(arrowstyle=\"->\", lw=2, color=\"tab:blue\"),\n",
    "    )\n",
    "    ax.text(\n",
    "        source_center[2] - 1.05,\n",
    "        y_center,\n",
    "        \"Plane-Wave Source\",\n",
    "        ha=\"right\",\n",
    "        va=\"center\",\n",
    "        color=\"tab:blue\",\n",
    "    )\n",
    "\n",
    "    ax.text(\n",
    "        sim1_center_z,\n",
    "        y_top + 0.25,\n",
    "        \"Metalens 1\\n(FDTD Sim Level 1)\",\n",
    "        ha=\"center\",\n",
    "        va=\"bottom\",\n",
    "        fontsize=11,\n",
    "    )\n",
    "    ax.text(\n",
    "        sim2_center_z,\n",
    "        y_top + 0.25,\n",
    "        \"Metalens 2\\n(FDTD Sim Level 2)\",\n",
    "        ha=\"center\",\n",
    "        va=\"bottom\",\n",
    "        fontsize=11,\n",
    "    )\n",
    "\n",
    "    ax.text((sim1_end_z + sim2_start_z) / 2, y_center, \"Field Projection\", ha=\"center\", va=\"center\")\n",
    "    ax.text((sim2_end_z + focus_z) / 2, y_center, \"Field Projection\", ha=\"center\", va=\"center\")\n",
    "\n",
    "    ax.plot(\n",
    "        [sim2_start_z, sim2_start_z],\n",
    "        [line_ymin, line_ymax],\n",
    "        color=\"tab:red\",\n",
    "        linestyle=\"--\",\n",
    "        linewidth=1.5,\n",
    "    )\n",
    "    ax.plot(\n",
    "        [focus_z, focus_z], [line_ymin, line_ymax], color=\"tab:red\", linestyle=\"--\", linewidth=1.5\n",
    "    )\n",
    "    ax.text(\n",
    "        sim2_start_z,\n",
    "        projection_label_y,\n",
    "        \"Projection Plane\",\n",
    "        ha=\"center\",\n",
    "        va=\"top\",\n",
    "        color=\"tab:red\",\n",
    "    )\n",
    "    ax.text(\n",
    "        focus_z,\n",
    "        projection_label_y,\n",
    "        \"Projection Plane\",\n",
    "        ha=\"center\",\n",
    "        va=\"top\",\n",
    "        color=\"tab:red\",\n",
    "    )\n",
    "\n",
    "    ax.plot(focus_z, y_center, marker=\"o\", markersize=7, color=\"gold\", markeredgecolor=\"black\")\n",
    "    ax.text(focus_z + 0.15, y_center, \"Focus\", ha=\"left\", va=\"center\")\n",
    "\n",
    "    ax.annotate(\n",
    "        \"\",\n",
    "        xy=(lens2_end_z, focal_arrow_y),\n",
    "        xytext=(focus_z, focal_arrow_y),\n",
    "        arrowprops=dict(arrowstyle=\"<->\", lw=1.4, color=\"black\"),\n",
    "    )\n",
    "    ax.text(\n",
    "        (lens2_end_z + focus_z) / 2,\n",
    "        focal_text_y,\n",
    "        f\"focal length = {focal_length:.2f} um\",\n",
    "        ha=\"center\",\n",
    "        va=\"bottom\",\n",
    "    )\n",
    "\n",
    "    ax.set_xlim(source_center[2] - 1.25, focus_z + 1.1)\n",
    "    ax.set_ylim(y_bottom - y_margin_bottom, y_top + y_margin_top)\n",
    "    ax.set_xlabel(\"z (um)\")\n",
    "    ax.set_yticks([])\n",
    "    ax.spines[[\"left\", \"right\", \"top\"]].set_visible(False)\n",
    "    ax.set_aspect(\"equal\", adjustable=\"box\")\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "plot_two_stage_setup()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76b6c28e2f01b907",
   "metadata": {},
   "source": [
    "## Create the Two Metasurfaces\n",
    "We use circular Si pillars on an SiO2 substrate. Symmetry allows us to model only one quadrant of each metasurface in the simulation.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "187cba44cb06509",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:43:03.124553Z",
     "start_time": "2026-03-17T10:43:03.121140Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Independent cylinders per lens: 69\n",
      "Physical cylinders per lens: 241\n",
      "focal_length = 6.00 um\n",
      "bridge_distance = 2.89 um\n",
      "focal_distance = 5.79 um\n"
     ]
    }
   ],
   "source": [
    "def get_cylinder_centers(diameter, spacing, full_circle=False):\n",
    "    r_eff = diameter / 2 - spacing / 2\n",
    "    coords = np.arange(0.0, r_eff, spacing)\n",
    "    if full_circle:\n",
    "        positive_coords = coords[coords > 0]\n",
    "        coords = np.concatenate((-positive_coords[::-1], coords))\n",
    "    x_grid, y_grid = np.meshgrid(coords, coords)\n",
    "    points = np.vstack((x_grid.ravel(), y_grid.ravel())).T\n",
    "    mask = x_grid**2 + y_grid**2 <= r_eff**2\n",
    "    points = points[mask.ravel()]\n",
    "    if full_circle:\n",
    "        return points\n",
    "    return points[(points[:, 0] >= -1e-12) & (points[:, 1] >= -1e-12)]\n",
    "\n",
    "\n",
    "centers_quarter = get_cylinder_centers(diameter, period, full_circle=False)\n",
    "centers_full = get_cylinder_centers(diameter, period, full_circle=True)\n",
    "\n",
    "print(f\"Independent cylinders per lens: {len(centers_quarter)}\")\n",
    "print(f\"Physical cylinders per lens: {len(centers_full)}\")\n",
    "print(f\"focal_length = {focal_length:.2f} um\")\n",
    "print(f\"bridge_distance = {bridge_distance:.2f} um\")\n",
    "print(f\"focal_distance = {focal_distance:.2f} um\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65a15b805b7f375b",
   "metadata": {},
   "source": "Let's visualize the pillar center coordinates across the full circular aperture."
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ec9d99b591bb9de5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:43:03.290794Z",
     "start_time": "2026-03-17T10:43:03.231967Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "jetTransient": {
      "display_id": null
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, tight_layout=True)\n",
    "ax.scatter(*centers_full.T, s=8)\n",
    "ax.add_artist(plt.Circle((0, 0), diameter / 2, color=\"black\", fill=False))\n",
    "ax.set_xlabel(\"x (um)\")\n",
    "ax.set_ylabel(\"y (um)\")\n",
    "ax.set_aspect(\"equal\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "846b3e44db85d784",
   "metadata": {},
   "source": "Next we define the substrate, the aperture structures, and a helper that turns optimization parameters into grouped cylinder geometries."
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d2a776291b035353",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:43:03.344976Z",
     "start_time": "2026-03-17T10:43:03.324930Z"
    }
   },
   "outputs": [],
   "source": [
    "substrate = td.Structure(\n",
    "    geometry=td.Box.from_bounds(\n",
    "        rmin=(-td.inf, -td.inf, -1000),\n",
    "        rmax=(td.inf, td.inf, -height / 2),\n",
    "    ),\n",
    "    medium=sio2,\n",
    ")\n",
    "\n",
    "aperture = [\n",
    "    td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-td.inf, -td.inf, -height / 2),\n",
    "            rmax=(td.inf, td.inf, -height / 2 + 0.2),\n",
    "        ),\n",
    "        medium=td.PECMedium(),\n",
    "    ),\n",
    "    td.Structure(\n",
    "        geometry=td.Cylinder(\n",
    "            center=(0, 0, 0),\n",
    "            radius=diameter / 2 + buffer_xy / 4,\n",
    "            length=height,\n",
    "        ),\n",
    "        medium=air,\n",
    "    ),\n",
    "]\n",
    "\n",
    "\n",
    "def params_to_radii(params):\n",
    "    return radius_min + (radius_max - radius_min) / (1 + np.exp(-params))\n",
    "\n",
    "\n",
    "def make_cylinders(params):\n",
    "    radii = params_to_radii(params)\n",
    "    geometries = []\n",
    "    for radius, (x_pos, y_pos) in zip(radii, centers_quarter):\n",
    "        geometries.append(td.Cylinder(center=(x_pos, y_pos, 0), radius=radius, length=height))\n",
    "    return td.Structure(\n",
    "        geometry=td.GeometryGroup(geometries=geometries),\n",
    "        medium=si,\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adcdfbe849f6c13b",
   "metadata": {},
   "source": [
    "## Define the Source and Monitors\n",
    "Level 1 is illuminated by a plane wave. The field just above level 1 is projected to the bridge plane and reused as the source of level 2. After level 2, we project to the focal point and to a few visualization planes instead of extending the FDTD domain through the free-space propagation region.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4d4bc8c430bc6a7d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:43:03.434682Z",
     "start_time": "2026-03-17T10:43:03.390485Z"
    }
   },
   "outputs": [],
   "source": [
    "level1_source = td.PlaneWave(\n",
    "    source_time=pulse,\n",
    "    size=(td.inf, td.inf, 0),\n",
    "    center=source_center,\n",
    "    direction=\"+\",\n",
    "    pol_angle=0,\n",
    ")\n",
    "\n",
    "level1_near_monitor = td.FieldMonitor(\n",
    "    center=near_monitor_center,\n",
    "    size=(td.inf, td.inf, 0),\n",
    "    freqs=[f0],\n",
    "    name=\"level1_near\",\n",
    "    colocate=False,\n",
    ")\n",
    "\n",
    "level2_near_monitor = td.FieldMonitor(\n",
    "    center=near_monitor_center,\n",
    "    size=(td.inf, td.inf, 0),\n",
    "    freqs=[f0],\n",
    "    name=\"level2_near\",\n",
    "    colocate=False,\n",
    ")\n",
    "\n",
    "\n",
    "def make_symmetric_axis(span, spacing):\n",
    "    half_steps = max(1, int(np.floor((span / 2) / spacing)))\n",
    "    max_coord = half_steps * spacing\n",
    "    return np.linspace(-max_coord, max_coord, 2 * half_steps + 1)\n",
    "\n",
    "\n",
    "def make_positive_axis(span, spacing):\n",
    "    num_steps = max(1, int(np.floor(span / spacing)))\n",
    "    return spacing * np.arange(0, num_steps + 1, dtype=float)\n",
    "\n",
    "\n",
    "# sampling of the projected bridge field\n",
    "bridge_grid_spacing = period\n",
    "\n",
    "# finer sampling used for visualization plots\n",
    "plot_grid_spacing = period / 5\n",
    "\n",
    "# transverse span of the final field plots\n",
    "focus_span = 2.0\n",
    "\n",
    "# x coordinates on the bridge plane\n",
    "bridge_x = make_symmetric_axis(plane_size, bridge_grid_spacing)\n",
    "\n",
    "# y coordinates on the bridge plane\n",
    "bridge_y = make_symmetric_axis(plane_size, bridge_grid_spacing)\n",
    "\n",
    "# x coordinates on the final focal plane\n",
    "focus_x = make_symmetric_axis(focus_span, plot_grid_spacing)\n",
    "\n",
    "# y coordinates on the final focal plane\n",
    "focus_y = make_symmetric_axis(focus_span, plot_grid_spacing)\n",
    "\n",
    "# transverse coordinate of the axial cross section\n",
    "axial_y = make_symmetric_axis(focus_span, plot_grid_spacing)\n",
    "\n",
    "# propagation coordinate of the axial cross section\n",
    "axial_z = make_positive_axis(focal_distance + buffer_z, plot_grid_spacing)[1:]\n",
    "\n",
    "# monitor used to project from level 1 to the bridge plane\n",
    "bridge_monitor = td.FieldProjectionCartesianMonitor(\n",
    "    center=level1_near_monitor.center,\n",
    "    size=level1_near_monitor.size,\n",
    "    freqs=level1_near_monitor.freqs,\n",
    "    name=\"bridge_projection\",\n",
    "    x=bridge_x,\n",
    "    y=bridge_y,\n",
    "    proj_axis=2,\n",
    "    proj_distance=bridge_distance,\n",
    "    far_field_approx=False,\n",
    "    custom_origin=level1_near_monitor.center,\n",
    ")\n",
    "\n",
    "# monitor used to evaluate on-axis focusing after level 2\n",
    "focus_point_monitor = td.FieldProjectionAngleMonitor(\n",
    "    center=level2_near_monitor.center,\n",
    "    size=level2_near_monitor.size,\n",
    "    freqs=level2_near_monitor.freqs,\n",
    "    name=\"focus_point_projection\",\n",
    "    phi=[0],\n",
    "    theta=[0],\n",
    "    proj_distance=focal_distance,\n",
    "    far_field_approx=False,\n",
    "    custom_origin=level2_near_monitor.center,\n",
    ")\n",
    "\n",
    "# monitor used to visualize the projected focal plane after level 2\n",
    "focus_plane_monitor = td.FieldProjectionCartesianMonitor(\n",
    "    center=level2_near_monitor.center,\n",
    "    size=level2_near_monitor.size,\n",
    "    freqs=level2_near_monitor.freqs,\n",
    "    name=\"focus_plane_projection\",\n",
    "    x=focus_x,\n",
    "    y=focus_y,\n",
    "    proj_axis=2,\n",
    "    proj_distance=focal_distance,\n",
    "    far_field_approx=False,\n",
    "    custom_origin=level2_near_monitor.center,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a03b7a556b963e0",
   "metadata": {},
   "source": [
    "## Build the Simulations\n",
    "Each lens uses the same geometry template. We keep each FDTD domain short and connect the stages with field projection, so the free-space gap between the two lenses does not need to be meshed explicitly.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a9735488dc64520b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:43:03.484267Z",
     "start_time": "2026-03-17T10:43:03.480214Z"
    }
   },
   "outputs": [],
   "source": [
    "boundary_spec = td.BoundarySpec.all_sides(td.PML())\n",
    "grid_spec = td.GridSpec.auto(min_steps_per_wvl=min_steps_per_wvl)\n",
    "\n",
    "\n",
    "def make_level1_sim(params):\n",
    "    structures = [substrate, *aperture]\n",
    "    if params is not None:\n",
    "        structures.append(make_cylinders(params))\n",
    "    return td.Simulation(\n",
    "        size=sim_size,\n",
    "        structures=structures,\n",
    "        sources=[level1_source],\n",
    "        monitors=[level1_near_monitor],\n",
    "        run_time=run_time,\n",
    "        boundary_spec=boundary_spec,\n",
    "        grid_spec=grid_spec,\n",
    "        symmetry=symmetry,\n",
    "    )\n",
    "\n",
    "\n",
    "def projection_to_field_dataset(projected_fields):\n",
    "    fields_cartesian = projected_fields.fields_cartesian\n",
    "    z_values = fields_cartesian.coords[\"z\"].values\n",
    "    z_values = z_values - z_values[0]\n",
    "    coords = {\n",
    "        \"x\": fields_cartesian.coords[\"x\"].values,\n",
    "        \"y\": fields_cartesian.coords[\"y\"].values,\n",
    "        \"z\": z_values,\n",
    "        \"f\": fields_cartesian.coords[\"f\"].values,\n",
    "    }\n",
    "    field_components = {}\n",
    "    for field_name in (\"Ex\", \"Ey\", \"Ez\", \"Hx\", \"Hy\", \"Hz\"):\n",
    "        field_data = fields_cartesian[field_name]\n",
    "        field_components[field_name] = td.ScalarFieldDataArray(\n",
    "            field_data.data,\n",
    "            coords=coords,\n",
    "            dims=field_data.dims,\n",
    "        )\n",
    "    return td.FieldDataset(**field_components)\n",
    "\n",
    "\n",
    "def make_bridge_source(sim_data_level1):\n",
    "    projector = td.FieldProjector.from_near_field_monitors(\n",
    "        sim_data=sim_data_level1,\n",
    "        near_monitors=[level1_near_monitor],\n",
    "        normal_dirs=[\"+\"],\n",
    "        pts_per_wavelength=None,\n",
    "        origin=level1_near_monitor.center,\n",
    "    )\n",
    "    projected_bridge_fields = projector.project_fields(bridge_monitor, verbose=False)\n",
    "    bridge_dataset = projection_to_field_dataset(projected_bridge_fields)\n",
    "    return td.CustomFieldSource(\n",
    "        center=bridge_source_center,\n",
    "        size=bridge_source_size,\n",
    "        source_time=pulse,\n",
    "        field_dataset=bridge_dataset,\n",
    "    )\n",
    "\n",
    "\n",
    "def make_level2_sim(params, bridge_source):\n",
    "    structures = [substrate, *aperture]\n",
    "    if params is not None:\n",
    "        structures.append(make_cylinders(params))\n",
    "    return td.Simulation(\n",
    "        size=sim_size,\n",
    "        structures=structures,\n",
    "        sources=[bridge_source],\n",
    "        monitors=[level2_near_monitor],\n",
    "        run_time=run_time,\n",
    "        boundary_spec=boundary_spec,\n",
    "        grid_spec=grid_spec,\n",
    "        symmetry=symmetry,\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d97d9f7d324adde",
   "metadata": {},
   "source": "Let's inspect the geometry of one lens before starting the optimization."
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d98c54ad87e4d445",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:43:03.811036Z",
     "start_time": "2026-03-17T10:43:03.535378Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 3 Axes>"
      ]
     },
     "jetTransient": {
      "display_id": null
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "params0_level1 = np.zeros(len(centers_quarter))\n",
    "params0_level2 = np.zeros(len(centers_quarter))\n",
    "params0 = np.concatenate((params0_level1, params0_level2))\n",
    "\n",
    "sim0 = make_level1_sim(params0_level1)\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(14, 5))\n",
    "\n",
    "sim0.plot(x=0, ax=ax1)\n",
    "sim0.plot(y=0, ax=ax2)\n",
    "sim0.plot(z=-height / 2, ax=ax3)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "681d2f19cc2dc596",
   "metadata": {},
   "source": [
    "## Objective Function\n",
    "We now define the two-stage optimization pipeline:<br>\n",
    "The first simulation generates the bridge source, the second simulation focuses the field, and the final objective is the projected on-axis power at the focal point. The projection step also removes the need to simulate the full free-space propagation distance from the second lens to the focus with FDTD. The normalized objective reported below is this on-axis power divided by the empty-device value, while the focused power itself is not normalized to the total input power. Because the bridge source is differentiable, this chained setup still supports an end-to-end gradient.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8d0e23465d8a1cf3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:43:09.280100Z",
     "start_time": "2026-03-17T10:43:03.821428Z"
    }
   },
   "outputs": [],
   "source": [
    "def split_params(params_all):\n",
    "    return params_all[: len(centers_quarter)], params_all[len(centers_quarter) :]\n",
    "\n",
    "\n",
    "def run_two_level(params_level1, params_level2, tag):\n",
    "    # Run the first simulation with the plane-wave source.\n",
    "    sim_level1 = make_level1_sim(params_level1)\n",
    "    sim_data_level1 = web.run(\n",
    "        sim_level1, task_name=f\"intro_source_gradients_level1_{tag}\", verbose=False\n",
    "    )\n",
    "\n",
    "    # Project the first near field to the bridge plane and reuse it as a custom source.\n",
    "    bridge_source = make_bridge_source(sim_data_level1)\n",
    "\n",
    "    # Run the second simulation with the projected bridge field as illumination.\n",
    "    sim_level2 = make_level2_sim(params_level2, bridge_source)\n",
    "    sim_data_level2 = web.run(\n",
    "        sim_level2, task_name=f\"intro_source_gradients_level2_{tag}\", verbose=False\n",
    "    )\n",
    "    return sim_data_level1, sim_data_level2\n",
    "\n",
    "\n",
    "def measure_focal_power(sim_data_level2):\n",
    "    projector = td.FieldProjector.from_near_field_monitors(\n",
    "        sim_data=sim_data_level2,\n",
    "        near_monitors=[level2_near_monitor],\n",
    "        normal_dirs=[\"+\"],\n",
    "        pts_per_wavelength=None,\n",
    "        origin=level2_near_monitor.center,\n",
    "    )\n",
    "    projected_focus = projector.project_fields(focus_point_monitor, verbose=False)\n",
    "    return np.sum(np.real(projected_focus.power.values))\n",
    "\n",
    "\n",
    "def J_absolute(params_all):\n",
    "    params_level1, params_level2 = split_params(params_all)\n",
    "    _, sim_data_level2 = run_two_level(params_level1, params_level2, tag=\"opt\")\n",
    "    return measure_focal_power(sim_data_level2)\n",
    "\n",
    "\n",
    "_, sim_data_empty = run_two_level(None, None, tag=\"empty\")\n",
    "J_empty = float(measure_focal_power(sim_data_empty))\n",
    "\n",
    "\n",
    "def J(params_all):\n",
    "    return J_absolute(params_all) / J_empty\n",
    "\n",
    "\n",
    "dJ = value_and_grad(J)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eacb0ff9e20e1629",
   "metadata": {},
   "source": "We can now evaluate the initial objective value and the initial gradient norm."
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a167763466009f3d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T10:44:14.473183Z",
     "start_time": "2026-03-17T10:43:09.292220Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "baseline focused power = 0.0413\n",
      "initial normalized objective = 0.637\n",
      "initial focused power = 0.0263\n",
      "initial gradient norm = 0.331\n"
     ]
    }
   ],
   "source": [
    "value0, gradient0 = dJ(params0)\n",
    "print(f\"baseline focused power = {J_empty:.4f}\")\n",
    "print(f\"initial normalized objective = {value0:.3f}\")\n",
    "print(f\"initial focused power = {value0 * J_empty:.4f}\")\n",
    "print(f\"initial gradient norm = {np.linalg.norm(gradient0):.3f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99faadf82b00333b",
   "metadata": {},
   "source": [
    "## Optimization\n",
    "We optimize both metasurfaces end-to-end. During optimization, we track the objective value and the gradient norm.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "740881de648d5922",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T11:05:44.704857Z",
     "start_time": "2026-03-17T10:44:14.780165Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 1\n",
      "\tnormalized objective = 0.637\n",
      "\tfocused power = 0.0263\n",
      "\tgradient norm = 0.331\n",
      "step = 2\n",
      "\tnormalized objective = 1.493\n",
      "\tfocused power = 0.0616\n",
      "\tgradient norm = 0.418\n",
      "step = 3\n",
      "\tnormalized objective = 2.240\n",
      "\tfocused power = 0.0924\n",
      "\tgradient norm = 0.643\n",
      "step = 4\n",
      "\tnormalized objective = 2.765\n",
      "\tfocused power = 0.1141\n",
      "\tgradient norm = 0.997\n",
      "step = 5\n",
      "\tnormalized objective = 3.245\n",
      "\tfocused power = 0.1339\n",
      "\tgradient norm = 0.544\n",
      "step = 6\n",
      "\tnormalized objective = 3.563\n",
      "\tfocused power = 0.1470\n",
      "\tgradient norm = 0.571\n",
      "step = 7\n",
      "\tnormalized objective = 3.919\n",
      "\tfocused power = 0.1617\n",
      "\tgradient norm = 0.741\n",
      "step = 8\n",
      "\tnormalized objective = 4.090\n",
      "\tfocused power = 0.1688\n",
      "\tgradient norm = 1.379\n",
      "step = 9\n",
      "\tnormalized objective = 4.407\n",
      "\tfocused power = 0.1819\n",
      "\tgradient norm = 1.093\n",
      "step = 10\n",
      "\tnormalized objective = 4.696\n",
      "\tfocused power = 0.1938\n",
      "\tgradient norm = 0.867\n",
      "step = 11\n",
      "\tnormalized objective = 4.907\n",
      "\tfocused power = 0.2025\n",
      "\tgradient norm = 0.709\n",
      "step = 12\n",
      "\tnormalized objective = 5.172\n",
      "\tfocused power = 0.2134\n",
      "\tgradient norm = 0.708\n",
      "step = 13\n",
      "\tnormalized objective = 5.301\n",
      "\tfocused power = 0.2188\n",
      "\tgradient norm = 0.505\n",
      "step = 14\n",
      "\tnormalized objective = 5.404\n",
      "\tfocused power = 0.2230\n",
      "\tgradient norm = 0.611\n",
      "step = 15\n",
      "\tnormalized objective = 5.522\n",
      "\tfocused power = 0.2279\n",
      "\tgradient norm = 0.483\n",
      "step = 16\n",
      "\tnormalized objective = 5.620\n",
      "\tfocused power = 0.2319\n",
      "\tgradient norm = 0.506\n",
      "step = 17\n",
      "\tnormalized objective = 5.653\n",
      "\tfocused power = 0.2333\n",
      "\tgradient norm = 0.638\n",
      "step = 18\n",
      "\tnormalized objective = 5.705\n",
      "\tfocused power = 0.2354\n",
      "\tgradient norm = 0.577\n",
      "step = 19\n",
      "\tnormalized objective = 5.702\n",
      "\tfocused power = 0.2353\n",
      "\tgradient norm = 0.630\n",
      "step = 20\n",
      "\tnormalized objective = 5.757\n",
      "\tfocused power = 0.2376\n",
      "\tgradient norm = 0.521\n"
     ]
    }
   ],
   "source": [
    "num_steps = 20\n",
    "learning_rate = 1e-1\n",
    "\n",
    "optimizer = adam(learning_rate=learning_rate)\n",
    "\n",
    "\n",
    "def print_step(_params, gradient, _state, step_index, objective_value):\n",
    "    value = float(objective_value)\n",
    "    print(f\"step = {step_index + 1}\")\n",
    "    print(f\"\tnormalized objective = {value:.3f}\")\n",
    "    print(f\"\tfocused power = {value * J_empty:.4f}\")\n",
    "    print(f\"\tgradient norm = {np.linalg.norm(gradient):.3f}\")\n",
    "\n",
    "\n",
    "params, _, opt_history = optimize(\n",
    "    J,\n",
    "    params0=np.copy(params0),\n",
    "    optimizer=optimizer,\n",
    "    num_steps=num_steps,\n",
    "    callback=print_step,\n",
    "    direction=\"max\",\n",
    ")\n",
    "J_history = opt_history[\"objective_fn_val\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "502ee7ba51923af2",
   "metadata": {},
   "source": "The objective history below shows the normalized focusing enhancement over the optimization iterations."
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ac84c343989ec5db",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T11:05:44.895176Z",
     "start_time": "2026-03-17T11:05:44.788626Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "jetTransient": {
      "display_id": null
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(J_history)\n",
    "plt.xlabel(\"Iterations\")\n",
    "plt.ylabel(\"Normalized Objective\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "535ad6ed53e44a5e",
   "metadata": {},
   "source": [
    "## Final Designs\n",
    "We first look at the optimized pillar layouts for the two metasurfaces.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ae0a32853a0d07b8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T11:05:45.577311Z",
     "start_time": "2026-03-17T11:05:44.915591Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1100x500 with 2 Axes>"
      ]
     },
     "jetTransient": {
      "display_id": null
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def expand_design_with_symmetry(centers, radii):\n",
    "    seen = set()\n",
    "    full_centers = []\n",
    "    full_radii = []\n",
    "    for (x_pos, y_pos), radius in zip(centers, radii):\n",
    "        for sign_x in (-1.0, 1.0):\n",
    "            for sign_y in (-1.0, 1.0):\n",
    "                x_coord = float(sign_x * x_pos)\n",
    "                y_coord = float(sign_y * y_pos)\n",
    "                key = (round(x_coord, 12), round(y_coord, 12))\n",
    "                if key in seen:\n",
    "                    continue\n",
    "                seen.add(key)\n",
    "                full_centers.append((x_coord, y_coord))\n",
    "                full_radii.append(float(radius))\n",
    "    return full_centers, full_radii\n",
    "\n",
    "\n",
    "def plot_design(axis, radii, title):\n",
    "    centers_plot, radii_plot = expand_design_with_symmetry(centers_quarter, radii)\n",
    "    for (x_coord, y_coord), radius in zip(centers_plot, radii_plot):\n",
    "        axis.add_patch(plt.Circle((x_coord, y_coord), radius, facecolor=\"black\", edgecolor=\"none\"))\n",
    "    axis.add_patch(plt.Circle((0, 0), diameter / 2, color=\"black\", fill=False, linewidth=1.0))\n",
    "    span = diameter / 2 + period\n",
    "    axis.set_xlim(-span, span)\n",
    "    axis.set_ylim(-span, span)\n",
    "    axis.set_xlabel(\"x (um)\")\n",
    "    axis.set_ylabel(\"y (um)\")\n",
    "    axis.set_title(title)\n",
    "    axis.set_aspect(\"equal\")\n",
    "\n",
    "\n",
    "params_level1_after, params_level2_after = split_params(params)\n",
    "\n",
    "radii_level1_after = params_to_radii(params_level1_after)\n",
    "radii_level2_after = params_to_radii(params_level2_after)\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(11, 5), tight_layout=True)\n",
    "\n",
    "plot_design(axes[0], radii_level1_after, \"Level 1 design\")\n",
    "plot_design(axes[1], radii_level2_after, \"Level 2 design\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "998d1676a11f2723",
   "metadata": {},
   "source": [
    "## Projected Fields\n",
    "To visualize the result, we rerun the optimized two-stage system and project the fields to the bridge plane, to the focal plane, and to an axial plane through the focus. These projections again let us inspect the long-distance propagation without enlarging the FDTD domain.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2d640ec6c15eea00",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T11:06:29.322245Z",
     "start_time": "2026-03-17T11:05:45.590098Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final focused power = 0.2392\n",
      "final normalized objective = 5.796\n"
     ]
    }
   ],
   "source": [
    "def project_bridge_plane(sim_data_level1):\n",
    "    projector = td.FieldProjector.from_near_field_monitors(\n",
    "        sim_data=sim_data_level1,\n",
    "        near_monitors=[level1_near_monitor],\n",
    "        normal_dirs=[\"+\"],\n",
    "        pts_per_wavelength=min_steps_per_wvl,\n",
    "        origin=level1_near_monitor.center,\n",
    "    )\n",
    "    return projector.project_fields(bridge_monitor, verbose=False)\n",
    "\n",
    "\n",
    "def project_focus_plane(sim_data_level2):\n",
    "    projector = td.FieldProjector.from_near_field_monitors(\n",
    "        sim_data=sim_data_level2,\n",
    "        near_monitors=[level2_near_monitor],\n",
    "        normal_dirs=[\"+\"],\n",
    "        pts_per_wavelength=min_steps_per_wvl,\n",
    "        origin=level2_near_monitor.center,\n",
    "    )\n",
    "    return projector.project_fields(focus_plane_monitor, verbose=False)\n",
    "\n",
    "\n",
    "def project_focus_axial_plane(sim_data_level2):\n",
    "    axial_monitor = td.FieldProjectionCartesianMonitor(\n",
    "        center=level2_near_monitor.center,\n",
    "        size=level2_near_monitor.size,\n",
    "        freqs=level2_near_monitor.freqs,\n",
    "        name=\"focus_axial_projection\",\n",
    "        x=axial_y,\n",
    "        y=axial_z,\n",
    "        proj_axis=0,\n",
    "        proj_distance=0,\n",
    "        far_field_approx=False,\n",
    "        custom_origin=level2_near_monitor.center,\n",
    "    )\n",
    "    projector = td.FieldProjector.from_near_field_monitors(\n",
    "        sim_data=sim_data_level2,\n",
    "        near_monitors=[level2_near_monitor],\n",
    "        normal_dirs=[\"+\"],\n",
    "        pts_per_wavelength=min_steps_per_wvl,\n",
    "        origin=level2_near_monitor.center,\n",
    "    )\n",
    "    return projector.project_fields(axial_monitor, verbose=False)\n",
    "\n",
    "\n",
    "sim_data_level1_after, sim_data_level2_after = run_two_level(\n",
    "    params_level1_after,\n",
    "    params_level2_after,\n",
    "    tag=\"final\",\n",
    ")\n",
    "final_on_axis_power = float(measure_focal_power(sim_data_level2_after))\n",
    "\n",
    "bridge_plane_data = project_bridge_plane(sim_data_level1_after)\n",
    "focus_plane_data = project_focus_plane(sim_data_level2_after)\n",
    "axial_plane_data = project_focus_axial_plane(sim_data_level2_after)\n",
    "\n",
    "print(f\"final focused power = {final_on_axis_power:.4f}\")\n",
    "print(f\"final normalized objective = {final_on_axis_power / J_empty:.3f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e6e8f97a0eecd74",
   "metadata": {},
   "source": [
    "Now we visualize the projected field intensity at three locations: the bridge plane between the two lenses, the focal plane, and the axial cross section through the focus.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "461ab0db9444b42d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-17T11:13:00.316764Z",
     "start_time": "2026-03-17T11:12:59.970321Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x450 with 6 Axes>"
      ]
     },
     "jetTransient": {
      "display_id": null
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bridge_power = np.squeeze(np.real(bridge_plane_data.power.values))\n",
    "focus_power = np.squeeze(np.real(focus_plane_data.power.values))\n",
    "axial_power = np.squeeze(np.real(axial_plane_data.power.values))\n",
    "axial_z_plot = axial_plane_data.z + buffer_z / 2\n",
    "\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(14, 4.5), tight_layout=True)\n",
    "\n",
    "mesh1 = ax1.pcolormesh(\n",
    "    bridge_plane_data.x,\n",
    "    bridge_plane_data.y,\n",
    "    bridge_power.T,\n",
    "    shading=\"auto\",\n",
    "    cmap=\"magma\",\n",
    ")\n",
    "ax1.set_xlabel(\"x (um)\")\n",
    "ax1.set_ylabel(\"y (um)\")\n",
    "ax1.set_title(\"Projected Bridge-Plane Power\")\n",
    "ax1.set_aspect(\"equal\")\n",
    "fig.colorbar(mesh1, ax=ax1, label=\"power metric (a.u.)\")\n",
    "\n",
    "mesh2 = ax2.pcolormesh(\n",
    "    focus_plane_data.x,\n",
    "    focus_plane_data.y,\n",
    "    focus_power.T,\n",
    "    shading=\"auto\",\n",
    "    cmap=\"magma\",\n",
    ")\n",
    "ax2.set_xlabel(\"x (um)\")\n",
    "ax2.set_ylabel(\"y (um)\")\n",
    "ax2.set_title(\"Projected Focus-Plane Power\")\n",
    "ax2.set_aspect(\"equal\")\n",
    "fig.colorbar(mesh2, ax=ax2, label=\"power metric (a.u.)\")\n",
    "\n",
    "mesh3 = ax3.pcolormesh(\n",
    "    axial_plane_data.y,\n",
    "    axial_z_plot,\n",
    "    axial_power.T,\n",
    "    shading=\"auto\",\n",
    "    cmap=\"magma\",\n",
    ")\n",
    "ax3.axhline(focal_length, color=\"white\", linestyle=\"--\", linewidth=1.5)\n",
    "ax3.text(\n",
    "    0,\n",
    "    focal_length + 0.05,\n",
    "    \"focal plane\",\n",
    "    color=\"white\",\n",
    "    ha=\"center\",\n",
    "    va=\"bottom\",\n",
    ")\n",
    "ax3.set_xlabel(\"y (um)\")\n",
    "ax3.set_ylabel(\"z relative to Metalens 2 (um)\")\n",
    "ax3.set_title(\"Projected Axial Power\")\n",
    "ax3.set_aspect(\"equal\")\n",
    "fig.colorbar(mesh3, ax=ax3, label=\"power metric (a.u.)\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7e4476f52476f7b",
   "metadata": {},
   "source": [
    "## Conclusions\n",
    "This example shows how source gradients can propagate through a multi-stage workflow in which one simulation generates the source for another.<br>\n",
    "The field projector is used both to couple the two metasurfaces and to evaluate the final focusing performance, while the optimization still sees the whole pipeline as a single differentiable objective.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6a7ed048185a524",
   "metadata": {},
   "source": [
    "For more related case studies, see the<br>\n",
    "* [Gradient Checking Notebook](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd2GradientChecking/).<br>\n",
    "* [Inverse Design Notebook](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd3InverseDesign/).<br>\n",
    "* [Metalens Notebook](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd7Metalens/).<br>\n",
    "* [Metasurface Notebook](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd13Metasurface/).<br>\n",
    "* [Metalens Waveguide Taper Notebook](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd20MetalensWaveguideTaper/).<br>\n",
    "* [Fiber Lens Notebook](https://www.flexcompute.com/tidy3d/examples/notebooks/Autograd28FiberLens/)\n"
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Metamaterials, gratings, and other periodic structures",
   "Lenses"
  ],
  "description": "This notebook demonstrates how to optimize a two-level metalens system in Tidy3D FDTD by projecting the near field from one metasurface to a bridge plane, reusing it as a differentiable source for a second simulation, and backpropagating the final focusing objective through the full chain.",
  "feature_image": "./img/two_level_metalens.jpg",
  "features": [
   "Adjoint inverse design",
   "Far field projection"
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "source gradients, metalens, metasurface, inverse design, adjoint optimization, field projection, custom field source, Tidy3D, FDTD",
  "title": "Introduction to source gradients"
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
