{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "24ab1cfc",
   "metadata": {},
   "source": [
    "# Solid Immersion Lens for Quantum Emitter Light Collection\n",
    "\n",
    "This notebook sets up a Tidy3D simulation of a solid immersion lens (SIL) for collecting light from a quantum emitter into an optical fiber. The SIL geometry is parameterized using a differentiable `TriangleMesh`, making it ready for gradient-based (autograd) optimization of the lens surface profile.\n",
    "\n",
    "The simulation includes:\n",
    "- A PEC boundary at −z as a metallic back-reflector\n",
    "- A SiO2 spacer layer on top of the reflector\n",
    "- A 200 nm emitter film with refractive index 1.8\n",
    "- A solid immersion lens (n=1.5) parameterized as concentric rings with adjustable heights\n",
    "- A collection optical fiber above the lens\n",
    "- Mode and flux monitors for computing coupling efficiency and Purcell factor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "616755c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import tempfile\n",
    "\n",
    "import autograd.numpy as anp\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import optax\n",
    "\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n",
    "from autograd import value_and_grad\n",
    "from autograd.scipy.signal import convolve\n",
    "from tidy3d.components.autograd import get_static\n",
    "from tidy3d.plugins.mode import ModeSolver\n",
    "from tidy3d.plugins.mode.web import run as run_mode_solver"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93742c8b",
   "metadata": {},
   "source": [
    "## Simulation Parameters\n",
    "\n",
    "The device stack is gold / SiO2 / emitter film / SIL. The quantum emitter sits at the mid-plane of a 200 nm film with refractive index 1.8, and a collection fiber is positioned above the SIL."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "a9aefb44",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Simulation wavelength.\n",
    "wl = 0.780  # Central wavelength (um).\n",
    "bw = 0.06  # Bandwidth (um).\n",
    "n_wl = 61  # Number of wavelength points.\n",
    "\n",
    "# SiO2 spacer.\n",
    "t_sio2 = 0.438  # SiO2 thickness (um).\n",
    "n_sio2 = 1.45  # SiO2 refractive index.\n",
    "\n",
    "# Emitter film.\n",
    "t_film = 0.200  # Film thickness (um).\n",
    "n_film = 1.80  # Film refractive index.\n",
    "\n",
    "# Solid immersion lens.\n",
    "n_sil = 1.50  # SIL refractive index.\n",
    "sil_radius = 2.5  # SIL base radius (um).\n",
    "\n",
    "# Match the same xy expanse used in example-bullseye-cavity.ipynb.\n",
    "bullseye_xy_radius = 3  # The simulation expanse\n",
    "\n",
    "# SIL mesh parameterization.\n",
    "num_rings = 64  # Number of concentric rings (design parameters).\n",
    "ring_segments = 64  # Angular segments per ring.\n",
    "smooth_sigma_frac = 0.02  # Smoothing kernel width fraction.\n",
    "\n",
    "# Height bounds for future optimization (um).\n",
    "min_height = 0.05\n",
    "max_height = 5\n",
    "\n",
    "# Collection fiber parameters (630HP).\n",
    "r_core = 2.0  # Fiber core radius (um).\n",
    "n_core = 1.455  # Core refractive index.\n",
    "n_clad = 1.45  # Cladding refractive index.\n",
    "d_cf = 2.15  # Distance from SIL peak to fiber face (um).\n",
    "\n",
    "# Simulation settings.\n",
    "run_time = 5e-12  # Simulation run time (s).\n",
    "use_pec_reflector = False  # PEC metallic back-reflector at z-minus."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f4b6f21",
   "metadata": {},
   "source": [
    "## Derived Quantities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "d6823515",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Wavelengths and frequencies.\n",
    "wl_max = wl + bw / 2\n",
    "wl_min = wl - bw / 2\n",
    "wl_range = np.linspace(wl_min, wl_max, n_wl)\n",
    "freq = td.C_0 / wl\n",
    "freqs = td.C_0 / wl_range\n",
    "freqw = 0.5 * (freqs[0] - freqs[-1])\n",
    "\n",
    "# Material definitions.\n",
    "mat_sio2 = td.Medium(permittivity=n_sio2**2)\n",
    "mat_film = td.Medium(permittivity=n_film**2)\n",
    "mat_sil = td.Medium(permittivity=n_sil**2)\n",
    "mat_core = td.Medium(permittivity=n_core**2)\n",
    "mat_clad = td.Medium(permittivity=n_clad**2)\n",
    "\n",
    "# Computational domain sizing.\n",
    "pml_spacing = 0.6 * wl\n",
    "eff_inf = 10\n",
    "\n",
    "# Z-axis layout (z=0 is the PEC reflector / SiO2 bottom surface).\n",
    "z_sio2_top = t_sio2\n",
    "z_film_top = z_sio2_top + t_film\n",
    "z_sil_base = z_film_top\n",
    "z_qd = z_sio2_top + 0.5 * t_film\n",
    "z_fiber_face = z_sil_base + sil_radius + d_cf\n",
    "if use_pec_reflector:\n",
    "    z_domain_min = 0.0\n",
    "else:\n",
    "    # Extend domain below SiO2 so at least 1 um of substrate sits before the PML.\n",
    "    z_domain_min = -(1.0 + pml_spacing)\n",
    "z_domain_max = z_fiber_face + pml_spacing\n",
    "\n",
    "size_z = z_domain_max - z_domain_min\n",
    "\n",
    "# Output directories.\n",
    "_NB_DIR = os.path.dirname(os.path.abspath(r\"g:\\My Drive\\product\\v1\\tidy3d\\solid_immersion_lens_v2\\inv_des_sil.ipynb\"))\n",
    "\n",
    "_STL_DIR = os.path.join(_NB_DIR, \"output\", \"stl\")\n",
    "\n",
    "_LOCAL_SIM_PATH = os.path.join(tempfile.gettempdir(), \"tidy3d_sil_opt.hdf5\")\n",
    "\n",
    "_PARAMS_DIR = os.path.join(_NB_DIR, \"output\", \"params\")# Simulation HDF5 downloads go to local temp (Google Drive can't handle HDF5 writes).\n",
    "\n",
    "os.makedirs(_STL_DIR, exist_ok=True)\n",
    "os.makedirs(_PARAMS_DIR, exist_ok=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a106a26",
   "metadata": {},
   "source": [
    "## SIL Mesh Construction\n",
    "\n",
    "The lens surface is parameterized as concentric rings in the x–y plane, each with an adjustable height along z. A Gaussian smoothing kernel ensures smooth transitions between adjacent rings. This parameterization is fully differentiable via autograd, enabling gradient-based optimization of the lens profile.\n",
    "\n",
    "The initial shape is a hemisphere of radius equal to `sil_radius`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "704f35f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def vertices_from_params(params):\n",
    "    \"\"\"Compute mesh vertices from ring height parameters.\"\"\"\n",
    "\n",
    "    def smooth_param_profile(params):\n",
    "        sigma = smooth_sigma_frac * len(params)\n",
    "        if sigma == 0:\n",
    "            return params\n",
    "        pad = max(1, int(4 * sigma))\n",
    "        x = anp.arange(-pad, pad + 1)\n",
    "        k = anp.exp(-0.5 * (x / sigma) ** 2)\n",
    "        k /= k.sum()\n",
    "        left_pad = params[1 : pad + 1][::-1]\n",
    "        right_pad = params[-pad - 1 : -1][::-1]\n",
    "        padded = anp.concatenate([left_pad, params, right_pad])\n",
    "        smoothed = convolve(padded, k, mode=\"valid\")\n",
    "        return smoothed\n",
    "\n",
    "    heights = smooth_param_profile(params)\n",
    "    theta = anp.linspace(0.0, 2.0 * anp.pi, ring_segments, endpoint=False)\n",
    "    cos_t = anp.cos(theta)\n",
    "    sin_t = anp.sin(theta)\n",
    "\n",
    "    rings = []\n",
    "\n",
    "    # Base ring at z = z_sil_base, radius = sil_radius (flat bottom edge).\n",
    "    X = sil_radius * cos_t\n",
    "    Y = sil_radius * sin_t\n",
    "    Z = anp.full(ring_segments, z_sil_base)\n",
    "    rings.append(anp.stack([X, Y, Z], axis=1))\n",
    "\n",
    "    # Top surface rings from innermost to outermost.\n",
    "    ring_radii = np.linspace(0.0, sil_radius, num_rings)\n",
    "    for radius, h in zip(ring_radii[1:], heights[1:]):\n",
    "        X = radius * cos_t\n",
    "        Y = radius * sin_t\n",
    "        Z = anp.full(ring_segments, z_sil_base + h)\n",
    "        rings.append(anp.stack([X, Y, Z], axis=1))\n",
    "\n",
    "    vertices = anp.concatenate(rings, axis=0)\n",
    "\n",
    "    # Top and bottom center vertices.\n",
    "    top_center = anp.array([[0.0, 0.0, z_sil_base + heights[0]]])\n",
    "    bottom_center = anp.array([[0.0, 0.0, z_sil_base]])\n",
    "    vertices = anp.concatenate([vertices, top_center, bottom_center], axis=0)\n",
    "\n",
    "    return vertices\n",
    "\n",
    "\n",
    "def build_faces():\n",
    "    \"\"\"Build triangle face connectivity for the SIL mesh.\"\"\"\n",
    "    faces = []\n",
    "\n",
    "    def ring_offset(i):\n",
    "        return i * ring_segments\n",
    "\n",
    "    K = num_rings - 1\n",
    "    top_center_idx = num_rings * ring_segments\n",
    "    bottom_center_idx = top_center_idx + 1\n",
    "\n",
    "    # Side wall: base ring <-> outermost top ring.\n",
    "    base = ring_offset(0)\n",
    "    outer = ring_offset(K)\n",
    "    for j in range(ring_segments):\n",
    "        jn = (j + 1) % ring_segments\n",
    "        faces.append([base + j, base + jn, outer + j])\n",
    "        faces.append([base + jn, outer + jn, outer + j])\n",
    "\n",
    "    # Center fan: top_center <-> innermost top ring.\n",
    "    inner_ring = ring_offset(1)\n",
    "    for j in range(ring_segments):\n",
    "        jn = (j + 1) % ring_segments\n",
    "        faces.append([top_center_idx, inner_ring + j, inner_ring + jn])\n",
    "\n",
    "    # Ring-by-ring: connect adjacent top rings.\n",
    "    for i in range(1, K):\n",
    "        r0 = ring_offset(i)\n",
    "        r1 = ring_offset(i + 1)\n",
    "        for j in range(ring_segments):\n",
    "            jn = (j + 1) % ring_segments\n",
    "            faces.append([r0 + j, r1 + j, r0 + jn])\n",
    "            faces.append([r0 + jn, r1 + j, r1 + jn])\n",
    "\n",
    "    # Bottom disk: fan from bottom_center to base ring.\n",
    "    base_start = ring_offset(0)\n",
    "    for j in range(ring_segments):\n",
    "        jn = (j + 1) % ring_segments\n",
    "        faces.append([bottom_center_idx, base_start + jn, base_start + j])\n",
    "\n",
    "    return anp.array(faces, dtype=int)\n",
    "\n",
    "\n",
    "FACE_ARRAY = build_faces()\n",
    "\n",
    "\n",
    "def mesh_from_params(params):\n",
    "    \"\"\"Create a TriangleMesh from ring height parameters.\"\"\"\n",
    "    vertices = vertices_from_params(params)\n",
    "    triangles = vertices[FACE_ARRAY]\n",
    "    mesh = td.TriangleMesh.from_triangles(triangles)\n",
    "    return mesh"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31e02926",
   "metadata": {},
   "source": [
    "## Simulation Setup\n",
    "\n",
    "The simulation uses:\n",
    "- A PEC boundary at −z as a metallic back-reflector\n",
    "- A SiO2 spacer layer\n",
    "- A 200 nm emitter film with index 1.8\n",
    "- The SIL (TriangleMesh) on top of the emitter film\n",
    "- A collection fiber (core + cladding) above the SIL\n",
    "- A point dipole source (Ey-polarized) at the film mid-plane\n",
    "- Mode and flux monitors for coupling efficiency computation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "6777a84d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_simulation(params, d_cf_override=None, t_sio2_override=None, pec_override=None):\n",
    "    \"\"\"Create a Simulation with the SIL and collection fiber.\"\"\"\n",
    "\n",
    "    _use_pec = use_pec_reflector if pec_override is None else pec_override\n",
    "    _d_cf = d_cf if d_cf_override is None else d_cf_override\n",
    "\n",
    "    _t_sio2 = t_sio2 if t_sio2_override is None else t_sio2_override\n",
    "    _t_sio2 = float(np.asarray(_t_sio2).item())\n",
    "    if _t_sio2 <= 0:\n",
    "        raise ValueError(f\"Invalid t_sio2={_t_sio2:.4f}: requires t_sio2 > 0\")\n",
    "\n",
    "    _z_sio2_top = _t_sio2\n",
    "    _z_film_top = _z_sio2_top + t_film\n",
    "    _z_sil_base = _z_film_top\n",
    "    _z_qd = _z_sio2_top + 0.5 * t_film\n",
    "    _z_fiber_face = _z_sil_base + sil_radius + _d_cf\n",
    "    if _use_pec:\n",
    "        _z_domain_min = 0.0\n",
    "    else:\n",
    "        _z_domain_min = -(1.0 + pml_spacing)\n",
    "    _z_domain_max = _z_fiber_face + pml_spacing\n",
    "    _size_z = _z_domain_max - _z_domain_min\n",
    "    _center_z = 0.5 * (_z_domain_min + _z_domain_max)\n",
    "\n",
    "    size_x = 2 * pml_spacing + max(2 * bullseye_xy_radius, 2 * r_core)\n",
    "    size_y = size_x\n",
    "\n",
    "    vertices = vertices_from_params(params)\n",
    "    dz = _z_sil_base - z_sil_base\n",
    "    if dz != 0:\n",
    "        vertices = vertices + anp.array([0.0, 0.0, dz])\n",
    "    triangles = vertices[FACE_ARRAY]\n",
    "    mesh = td.TriangleMesh.from_triangles(triangles)\n",
    "    sil_structure = td.Structure(geometry=mesh, medium=mat_sil, name=\"sil\")\n",
    "\n",
    "    mon_pos_z = _z_domain_max - pml_spacing / 2\n",
    "\n",
    "    dp_source = td.PointDipole(\n",
    "        center=(0, 0, _z_qd),\n",
    "        source_time=td.GaussianPulse(freq0=freq, fwidth=freqw),\n",
    "        polarization=\"Ey\",\n",
    "    )\n",
    "\n",
    "    field_monitor_xz = td.FieldMonitor(\n",
    "        center=(0, 0.05, _center_z),\n",
    "        size=(size_x, 0, _size_z),\n",
    "        freqs=[freq],\n",
    "        name=\"field_xz\",\n",
    "    )\n",
    "\n",
    "    mode_spec = td.ModeSpec(num_modes=1, target_neff=n_core)\n",
    "    mode_monitor = td.ModeMonitor(\n",
    "        center=(0, 0, mon_pos_z),\n",
    "        size=(size_x, size_y, 0),\n",
    "        freqs=freqs,\n",
    "        mode_spec=mode_spec,\n",
    "        name=\"mode_fiber\",\n",
    "    )\n",
    "\n",
    "    flux_dip = td.FluxMonitor(\n",
    "        center=(0, 0, _center_z),\n",
    "        size=(0.8 * size_x, 0.8 * size_y, _size_z - pml_spacing),\n",
    "        freqs=freqs,\n",
    "        name=\"flux_dip\",\n",
    "    )\n",
    "\n",
    "    sio2_layer = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-size_x / 2 - eff_inf, -size_y / 2 - eff_inf,\n",
    "                  _z_domain_min - eff_inf),\n",
    "            rmax=(size_x / 2 + eff_inf, size_y / 2 + eff_inf, _z_sio2_top),\n",
    "        ),\n",
    "        medium=mat_sio2,\n",
    "    )\n",
    "\n",
    "    emitter_film = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-size_x / 2 - eff_inf, -size_y / 2 - eff_inf, _z_sio2_top),\n",
    "            rmax=(size_x / 2 + eff_inf, size_y / 2 + eff_inf, _z_film_top),\n",
    "        ),\n",
    "        medium=mat_film,\n",
    "    )\n",
    "\n",
    "    fiber_clad = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-size_x / 2 - eff_inf, -size_y / 2 - eff_inf, _z_fiber_face),\n",
    "            rmax=(size_x / 2 + eff_inf, size_y / 2 + eff_inf, _z_domain_max + eff_inf),\n",
    "        ),\n",
    "        medium=mat_clad,\n",
    "    )\n",
    "\n",
    "    fiber_center_z = 0.5 * (_z_fiber_face + _z_domain_max + eff_inf)\n",
    "    fiber_length = _z_domain_max + eff_inf - _z_fiber_face\n",
    "    fiber_core = td.Structure(\n",
    "        geometry=td.Cylinder(\n",
    "            radius=r_core,\n",
    "            center=(0, 0, fiber_center_z),\n",
    "            axis=2,\n",
    "            length=fiber_length,\n",
    "        ),\n",
    "        medium=mat_core,\n",
    "    )\n",
    "\n",
    "    sim = td.Simulation(\n",
    "        center=(0, 0, _center_z),\n",
    "        size=(size_x, size_y, _size_z),\n",
    "        medium=td.Medium(permittivity=1),\n",
    "        grid_spec=td.GridSpec.auto(min_steps_per_wvl=15, wavelength=wl),\n",
    "        structures=[sio2_layer, emitter_film, fiber_clad, fiber_core, sil_structure],\n",
    "        sources=[dp_source],\n",
    "        normalize_index=0,\n",
    "        monitors=[field_monitor_xz, mode_monitor, flux_dip],\n",
    "        boundary_spec=td.BoundarySpec(\n",
    "            x=td.Boundary.pml(),\n",
    "            y=td.Boundary.pml(),\n",
    "            z=td.Boundary(\n",
    "                minus=td.PECBoundary() if _use_pec else td.PML(),\n",
    "                plus=td.PML(),\n",
    "            ),\n",
    "        ),\n",
    "        symmetry=(1, -1, 0),\n",
    "        run_time=run_time,\n",
    "    )\n",
    "    return sim"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91e58f84",
   "metadata": {},
   "source": [
    "## Visualize the Simulation\n",
    "\n",
    "Initialize the SIL with a Cartesian oval surface profile — the analytically ideal refracting surface for coupling a point emitter into a Gaussian fiber mode. The oval satisfies a constant optical-path-length condition that maps the emitter's spherical wave to a collimated plane wave, eliminating spherical aberration for all rays within the TIR-limited aperture."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "c25dd1d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cartesian oval:  κ = 5.0,  ρ_max = 1.118 μm,  h_edge = 1.000 μm\n",
      "Critical angle   = 41.8°\n",
      "Emitter film top = 0.638 μm\n",
      "Emitter z        = 0.538 μm\n"
     ]
    }
   ],
   "source": [
    "# === Cartesian Oval Lens for Optimal Fiber Coupling ===\n",
    "#\n",
    "# The Cartesian oval eliminates spherical aberration by enforcing a constant\n",
    "# optical path length (OPL) for every ray from the point emitter to the\n",
    "# collimated output plane. For coupling into a single-mode fiber whose\n",
    "# Gaussian mode has a flat wavefront at the fiber face (z_R >> d_cf), the\n",
    "# optimal design collimates the emitter's spherical wave into a plane wave.\n",
    "#\n",
    "# OPL condition:   n_sil * sqrt(ρ² + z²) - n_out * z = (n_sil - n_out) * h\n",
    "#\n",
    "# Closed-form:     z(ρ) = [n_out·h + n_sil·√(h² - κρ²)] / (n_sil + n_out)\n",
    "#                  κ = (n_sil + n_out) / (n_sil - n_out)\n",
    "#\n",
    "# Valid aperture:  ρ ≤ ρ_max = h / √κ   (limited by total internal reflection)\n",
    "\n",
    "ring_radii = np.linspace(0.0, sil_radius, num_rings)\n",
    "h_apex = sil_radius\n",
    "\n",
    "n_out = 1.0\n",
    "kappa = (n_sil + n_out) / (n_sil - n_out)\n",
    "rho_max = h_apex / np.sqrt(kappa)\n",
    "\n",
    "discriminant = h_apex**2 - kappa * ring_radii**2\n",
    "in_aperture = discriminant >= 0\n",
    "oval_heights = np.where(\n",
    "    in_aperture,\n",
    "    (n_out * h_apex + n_sil * np.sqrt(np.maximum(discriminant, 0)))\n",
    "    / (n_sil + n_out),\n",
    "    0.0,\n",
    ")\n",
    "\n",
    "h_edge = n_out * h_apex / (n_sil + n_out)\n",
    "taper = h_edge - (h_edge - min_height) * (ring_radii - rho_max) / (sil_radius - rho_max)\n",
    "init_params = np.where(in_aperture, oval_heights, np.maximum(taper, min_height))\n",
    "\n",
    "theta_c = np.degrees(np.arcsin(n_out / n_sil))\n",
    "print(f\"Cartesian oval:  κ = {kappa:.1f},  ρ_max = {rho_max:.3f} μm,  h_edge = {h_edge:.3f} μm\")\n",
    "print(f\"Critical angle   = {theta_c:.1f}°\")\n",
    "print(f\"Emitter film top = {z_film_top:.3f} μm\")\n",
    "print(f\"Emitter z        = {z_qd:.3f} μm\")\n",
    "\n",
    "# init_params = np.array([2.6623397 , 2.6353512 , 2.5762963 , 2.5094512 , 2.4548113 ,\n",
    "#        2.417729  , 2.3731413 , 2.288861  , 2.3609178 , 2.4291139 ,\n",
    "#        2.4739783 , 2.3005333 , 2.4113936 , 2.5722444 , 2.66333   ,\n",
    "#        1.8571405 , 1.9002906 , 1.9994804 , 2.0997105 , 2.121043  ,\n",
    "#        1.992148  , 1.8380157 , 1.9888959 , 2.331807  , 2.436948  ,\n",
    "#        1.4891073 , 1.1165357 , 1.1380515 , 1.4260321 , 1.5764182 ,\n",
    "#        1.3656145 , 0.6193609 , 0.3750911 , 0.5133566 , 0.7549467 ,\n",
    "#        0.9513143 , 1.0200113 , 0.77997386, 0.3790514 , 0.458539  ,\n",
    "#        0.58106464, 0.54539514, 0.32169437, 0.09893914, 0.1696058 ,\n",
    "#        0.35921615, 0.39739528, 0.36803186, 0.4783354 , 0.62903315,\n",
    "#        0.6235232 , 0.22600067, 0.05      , 0.05      , 0.05      ,\n",
    "#        0.15269797, 0.24259725, 0.17233059, 0.05139003, 0.05      ,\n",
    "#        0.05      , 0.5704556 , 0.7359599 , 0.7268702 ])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "id": "1d13b96a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dome:  apex = 2.500 μm,  R_curv = 2.500 μm\n",
      "  Height at edge (ρ = 2.5): 0.0000 μm\n",
      "  min_height clamp: 0.05 μm\n"
     ]
    }
   ],
   "source": [
    "# === Simple Dome (Spherical Cap) Initial Profile ===\n",
    "#\n",
    "# A plain spherical cap with apex height `dome_height` and base radius\n",
    "# `sil_radius`.  The radius of curvature is computed so the dome meets\n",
    "# z = 0 at ρ = sil_radius and peaks at z = dome_height at ρ = 0.\n",
    "#\n",
    "#   R = (sil_radius² + dome_height²) / (2 · dome_height)\n",
    "#   z(ρ) = dome_height − R + √(R² − ρ²)\n",
    "\n",
    "dome_height = 2.5  # Apex height of the dome (μm).  Change as desired.\n",
    "\n",
    "ring_radii = np.linspace(0.0, sil_radius, num_rings)\n",
    "\n",
    "R_curv = (sil_radius**2 + dome_height**2) / (2 * dome_height)\n",
    "dome_heights = dome_height - R_curv + np.sqrt(np.maximum(R_curv**2 - ring_radii**2, 0.0))\n",
    "init_params = np.maximum(dome_heights, min_height)\n",
    "\n",
    "print(f\"Dome:  apex = {dome_height:.3f} μm,  R_curv = {R_curv:.3f} μm\")\n",
    "print(f\"  Height at edge (ρ = {sil_radius}): {float(dome_heights[-1]):.4f} μm\")\n",
    "print(f\"  min_height clamp: {min_height} μm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "c5631041",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x500 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "init_sim = get_simulation(init_params)\n",
    "\n",
    "fig = plt.figure(tight_layout=True, figsize=(14, 5))\n",
    "gs = fig.add_gridspec(2, 3)\n",
    "ax1 = fig.add_subplot(gs[:, 0])\n",
    "ax2 = fig.add_subplot(gs[0, 1])\n",
    "ax3 = fig.add_subplot(gs[1, 1])\n",
    "ax4 = fig.add_subplot(gs[:, 2])\n",
    "\n",
    "init_sim.plot_eps(z=z_sil_base + sil_radius / 2, ax=ax1, monitor_alpha=0)\n",
    "init_sim.plot(y=0, ax=ax2, monitor_alpha=0)\n",
    "init_sim.plot_eps(y=0, ax=ax3)\n",
    "\n",
    "hemisphere = np.sqrt(np.maximum(sil_radius**2 - ring_radii**2, 0.0))\n",
    "ax4.plot(ring_radii, hemisphere, \"k--\", alpha=0.5, label=\"Hemisphere\")\n",
    "ax4.plot(ring_radii, init_params, \"b-\", label=\"Init profile\")\n",
    "if \"rho_max\" in dir():\n",
    "    ax4.axvline(rho_max, color=\"gray\", ls=\":\", alpha=0.5, label=f\"$\\\\rho_{{max}}$ = {rho_max:.2f} μm\")\n",
    "ax4.set_xlabel(\"Radial position ρ (μm)\")\n",
    "ax4.set_ylabel(\"Height (μm)\")\n",
    "ax4.set_title(\"SIL surface profile\")\n",
    "ax4.legend(fontsize=9)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "672f97d4",
   "metadata": {},
   "source": [
    "## Output Fiber Mode\n",
    "\n",
    "Verify the correct optical fiber mode is used for the coupling efficiency calculation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "81ae5d02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">17:58:47 US Eastern Daylight Time </span>Mode solver created with                      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #808000; text-decoration-color: #808000\">task_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'fdve-a9217fd9-3ce3-4a96-b204-543b4b2e</span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #008000; text-decoration-color: #008000\">aea5'</span>,                                        \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #808000; text-decoration-color: #808000\">solver_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mo-82cf22b1-51f5-438f-9c01-07ca1455</span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #008000; text-decoration-color: #008000\">5681'</span>.                                        \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:58:47 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMode solver created with                      \n",
       "\u001b[2;36m                                  \u001b[0m\u001b[33mtask_id\u001b[0m=\u001b[32m'fdve-a9217fd9-3ce3-4a96-b204-543b4b2e\u001b[0m\n",
       "\u001b[2;36m                                  \u001b[0m\u001b[32maea5'\u001b[0m,                                        \n",
       "\u001b[2;36m                                  \u001b[0m\u001b[33msolver_id\u001b[0m=\u001b[32m'mo-82cf22b1-51f5-438f-9c01-07ca1455\u001b[0m\n",
       "\u001b[2;36m                                  \u001b[0m\u001b[32m5681'\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\">c:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\rich\\live.py:231\n",
       ": UserWarning: install \"ipywidgets\" for Jupyter support\n",
       "  warnings.warn('install \"ipywidgets\" for Jupyter support')\n",
       "</pre>\n"
      ],
      "text/plain": [
       "c:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\rich\\live.py:231\n",
       ": UserWarning: install \"ipywidgets\" for Jupyter support\n",
       "  warnings.warn('install \"ipywidgets\" for Jupyter support')\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\"></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\">17:58:50 US Eastern Daylight Time </span>Mode solver status: queued                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:58:50 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMode solver status: 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\">17:58:52 US Eastern Daylight Time </span>Mode solver status: running                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:58:52 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMode solver status: running                   \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\">17:59:00 US Eastern Daylight Time </span>Mode solver status: success                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:59:00 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMode solver status: 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"
    }
   ],
   "source": [
    "from scipy.optimize import curve_fit\n",
    "\n",
    "mode_spec = td.ModeSpec(num_modes=1, target_neff=n_core)\n",
    "mode_solver = ModeSolver(\n",
    "    simulation=init_sim,\n",
    "    plane=td.Box(\n",
    "        center=(0, 0, z_domain_max - pml_spacing / 2),\n",
    "        size=(td.inf, td.inf, 0),\n",
    "    ),\n",
    "    mode_spec=mode_spec,\n",
    "    freqs=[freq],\n",
    ")\n",
    "mode_fiber = run_mode_solver(mode_solver)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "83989c46",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MFD (x): 4.510 μm   MFD (y): 4.544 μm   MFD avg: 4.527 μm\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# --- Gaussian fit to extract MFD (log-linear regression – no iterative optimizer) ---\n",
    "import importlib as _il\n",
    "_np = _il.import_module('numpy')\n",
    "\n",
    "_Ey = mode_fiber.Ey.sel(mode_index=0, f=freq)\n",
    "x = _np.array(_Ey.x.values, dtype=_np.float64).ravel()\n",
    "y = _np.array(_Ey.y.values, dtype=_np.float64).ravel()\n",
    "\n",
    "# 1-D intensity cuts via xarray labelled indexing, squeezed to 1-D\n",
    "cut_x = _np.asarray(_np.abs(_Ey.sel(y=0, method='nearest').values)**2, dtype=_np.float64).ravel()\n",
    "cut_y = _np.asarray(_np.abs(_Ey.sel(x=0, method='nearest').values)**2, dtype=_np.float64).ravel()\n",
    "\n",
    "def _fit_gauss(r, data):\n",
    "    \"\"\"Fit A·exp(−2r²/w²)+C analytically via log-linear regression.\"\"\"\n",
    "    r = _np.asarray(r, dtype=_np.float64).ravel()\n",
    "    data = _np.asarray(data, dtype=_np.float64).ravel()\n",
    "    bg = float(0.5 * (data[:5].mean() + data[-5:].mean()))\n",
    "    d = data - bg\n",
    "    peak = float(d.max())\n",
    "    mask = d > 0.05 * peak\n",
    "    Y = _np.log(d[mask])\n",
    "    X = r[mask] ** 2\n",
    "    N = float(len(X))\n",
    "    sx  = float(X.sum());  sy  = float(Y.sum())\n",
    "    sxy = float((X * Y).sum());  sxx = float((X * X).sum())\n",
    "    b = (N * sxy - sx * sy) / (N * sxx - sx ** 2)\n",
    "    a = (sy - b * sx) / N\n",
    "    w = float(_np.sqrt(-2.0 / b))\n",
    "    A = float(_np.exp(a))\n",
    "    return w, A, bg\n",
    "\n",
    "w_x, Ax, Cx = _fit_gauss(x, cut_x)\n",
    "w_y, Ay, Cy = _fit_gauss(y, cut_y)\n",
    "mfd_x, mfd_y = 2 * w_x, 2 * w_y\n",
    "mfd_avg = (mfd_x + mfd_y) / 2.0\n",
    "\n",
    "print(f\"MFD (x): {mfd_x:.3f} μm   MFD (y): {mfd_y:.3f} μm   MFD avg: {mfd_avg:.3f} μm\")\n",
    "\n",
    "gauss_x = Ax * _np.exp(-2.0 * x**2 / w_x**2) + Cx\n",
    "gauss_y = Ay * _np.exp(-2.0 * y**2 / w_y**2) + Cy\n",
    "\n",
    "fig, axes = plt.subplots(1, 3, figsize=(14, 4), tight_layout=True)\n",
    "_Ey.real.plot(x=\"x\", y=\"y\", cmap=\"bwr\", ax=axes[0])\n",
    "axes[0].set_title(\"Fiber mode Ey (real)\")\n",
    "\n",
    "for ax, r, cut, gauss, mfd, lbl in [\n",
    "        (axes[1], x, cut_x, gauss_x, mfd_x, 'x'),\n",
    "        (axes[2], y, cut_y, gauss_y, mfd_y, 'y')]:\n",
    "    pk = float(cut.max())\n",
    "    ax.plot(r, cut / pk, 'k-', label='Mode')\n",
    "    ax.plot(r, gauss / pk, 'r--', label=f'Gauss (MFD={mfd:.2f} μm)')\n",
    "    ax.set_xlabel(f'{lbl} (μm)'); ax.set_ylabel('Normalized |Ey|²')\n",
    "    ax.set_title(f'{lbl}-cut ({(\"y\" if lbl==\"x\" else \"x\")}=0)')\n",
    "    ax.legend(fontsize=9)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26b52ff4",
   "metadata": {},
   "source": [
    "## Coupling Efficiency\n",
    "\n",
    "The figure-of-merit is the coupling efficiency: the fraction of emitted power that couples into the fundamental mode of the collection fiber."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "63963815",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_coupling_eff(sim_data):\n",
    "    \"\"\"Return the coupling efficiency vs. wavelength.\"\"\"\n",
    "    mode_amps = sim_data[\"mode_fiber\"].amps.sel(direction=\"+\", mode_index=0)\n",
    "    mode_power = np.squeeze(np.abs(mode_amps) ** 2)\n",
    "    dip_power = sim_data[\"flux_dip\"].flux\n",
    "    return mode_power / dip_power"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f31af0ff",
   "metadata": {},
   "source": [
    "## Run Simulation\n",
    "\n",
    "Run the forward simulation with the initial hemispherical SIL."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "0eb83902",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">21:16:52 US Eastern Daylight Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'SIL hemisphere'</span> with resource_id\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b'</span>   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                         \n",
       "</pre>\n"
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       "\u001b[2;36m21:16:52 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'SIL hemisphere'\u001b[0m with resource_id\n",
       "\u001b[2;36m                                  \u001b[0m\u001b[32m'fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b'\u001b[0m   \n",
       "\u001b[2;36m                                  \u001b[0mand task_type \u001b[32m'FDTD'\u001b[0m.                         \n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>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-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?tas</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">kId=fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b'</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>.                                             \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=299917;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=365451;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b\u001b\\\u001b[32mtas\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                                  \u001b[0m\u001b]8;id=365451;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b\u001b\\\u001b[32mkId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=299917;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=233735;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=299917;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b\u001b\\\u001b[32m-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b'\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                                  \u001b[0m.                                             \n"
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     "metadata": {},
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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>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/152fbf08-52d6-47df-93fd-6591068eb56a\" 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=167769;https://tidy3d.simulation.cloud/folders/152fbf08-52d6-47df-93fd-6591068eb56a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                       \n"
      ]
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     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">c:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\rich\\live.py:231\n",
       ": UserWarning: install \"ipywidgets\" for Jupyter support\n",
       "  warnings.warn('install \"ipywidgets\" for Jupyter support')\n",
       "</pre>\n"
      ],
      "text/plain": [
       "c:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\rich\\live.py:231\n",
       ": UserWarning: install \"ipywidgets\" for Jupyter support\n",
       "  warnings.warn('install \"ipywidgets\" for Jupyter support')\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\">21:16:54 US Eastern Daylight Time </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.172</span>. Minimum cost\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>depends on task execution details. Use        \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed    \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>FlexCredit cost after a simulation run.       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m21:16:54 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.172\u001b[0m. Minimum cost\n",
       "\u001b[2;36m                                  \u001b[0mdepends on task execution details. Use        \n",
       "\u001b[2;36m                                  \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed    \n",
       "\u001b[2;36m                                  \u001b[0mFlexCredit cost after a simulation run.       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">ERROR: </span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">error</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">=</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Exceed</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\"> the total storage limit.  </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">You can upgrade your license from your Account</span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">page to run this simulation; </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4000000022</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">;      </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">BAD_REQUEST [HTTP </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">400</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\"> POST                    </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #0000ff; text-decoration-color: #0000ff; text-decoration: underline\">https://tidy3d-api.simulation.cloud/tidy3d/tas</span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #0000ff; text-decoration-color: #0000ff; text-decoration: underline\">ks/fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b/s</span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #0000ff; text-decoration-color: #0000ff; text-decoration: underline\">ubmit</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">]                                        </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                                 \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;31mERROR: \u001b[0m\u001b[1;33merror\u001b[0m\u001b[1;31m=\u001b[0m\u001b[1;35mExceed\u001b[0m\u001b[1;31m the total storage limit.  \u001b[0m\n",
       "\u001b[2;36m                                  \u001b[0m\u001b[1;31mYou can upgrade your license from your Account\u001b[0m\n",
       "\u001b[2;36m                                  \u001b[0m\u001b[1;31mpage to run this simulation; \u001b[0m\u001b[1;36m4000000022\u001b[0m\u001b[1;31m;      \u001b[0m\n",
       "\u001b[2;36m                                  \u001b[0m\u001b[1;31mBAD_REQUEST \u001b[0m\u001b[1;31m[\u001b[0m\u001b[1;31mHTTP \u001b[0m\u001b[1;36m400\u001b[0m\u001b[1;31m POST                    \u001b[0m\n",
       "\u001b[2;36m                                  \u001b[0m\u001b[4;94mhttps://tidy3d-api.simulation.cloud/tidy3d/tas\u001b[0m\n",
       "\u001b[2;36m                                  \u001b[0m\u001b[4;94mks/fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b/s\u001b[0m\n",
       "\u001b[2;36m                                  \u001b[0m\u001b[4;94mubmit\u001b[0m\u001b[1;31m]\u001b[0m\u001b[1;31m                                        \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "WebError",
     "evalue": "error=Exceed the total storage limit. You can upgrade your license from your Account page to run this simulation; 4000000022; BAD_REQUEST [HTTP 400 POST https://tidy3d-api.simulation.cloud/tidy3d/tasks/fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b/submit]",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mWebError\u001b[0m                                  Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[181], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m sim_data \u001b[38;5;241m=\u001b[39m \u001b[43mweb\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43minit_sim\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtask_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mSIL hemisphere\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_LOCAL_SIM_PATH\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\tidy3d\\web\\api\\run.py:246\u001b[0m, in \u001b[0;36mrun\u001b[1;34m(simulation, task_name, folder_name, path, callback_url, verbose, progress_callback_upload, progress_callback_download, solver_version, worker_group, simulation_type, parent_tasks, local_gradient, max_num_adjoint_per_fwd, reduce_simulation, pay_type, priority, max_workers, lazy)\u001b[0m\n\u001b[0;32m    243\u001b[0m         path \u001b[38;5;241m=\u001b[39m DEFAULT_DATA_PATH\n\u001b[0;32m    244\u001b[0m     h, sim \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mnext\u001b[39m(\u001b[38;5;28miter\u001b[39m(h2sim\u001b[38;5;241m.\u001b[39mitems()))\n\u001b[0;32m    245\u001b[0m     data \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m--> 246\u001b[0m         h: \u001b[43mrun_autograd\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    247\u001b[0m \u001b[43m            \u001b[49m\u001b[43msimulation\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msim\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    248\u001b[0m \u001b[43m            \u001b[49m\u001b[43mtask_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtask_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    249\u001b[0m \u001b[43m            \u001b[49m\u001b[43mfolder_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfolder_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    250\u001b[0m \u001b[43m            \u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    251\u001b[0m \u001b[43m            \u001b[49m\u001b[43mcallback_url\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallback_url\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    252\u001b[0m \u001b[43m            \u001b[49m\u001b[43mverbose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    253\u001b[0m \u001b[43m            \u001b[49m\u001b[43mprogress_callback_upload\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprogress_callback_upload\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    254\u001b[0m \u001b[43m            \u001b[49m\u001b[43mprogress_callback_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprogress_callback_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    255\u001b[0m \u001b[43m            \u001b[49m\u001b[43msolver_version\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msolver_version\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    256\u001b[0m \u001b[43m            \u001b[49m\u001b[43mworker_group\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mworker_group\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    257\u001b[0m \u001b[43m            \u001b[49m\u001b[43msimulation_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msimulation_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    258\u001b[0m \u001b[43m            \u001b[49m\u001b[43mparent_tasks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparent_tasks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    259\u001b[0m \u001b[43m            \u001b[49m\u001b[43mlocal_gradient\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlocal_gradient\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    260\u001b[0m \u001b[43m            \u001b[49m\u001b[43mmax_num_adjoint_per_fwd\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmax_num_adjoint_per_fwd\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    261\u001b[0m \u001b[43m            \u001b[49m\u001b[43mreduce_simulation\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mreduce_simulation\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    262\u001b[0m \u001b[43m            \u001b[49m\u001b[43mpay_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpay_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    263\u001b[0m \u001b[43m            \u001b[49m\u001b[43mpriority\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpriority\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    264\u001b[0m \u001b[43m            \u001b[49m\u001b[43mlazy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlazy\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mlazy\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mis\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m    265\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    266\u001b[0m     }\n\u001b[0;32m    267\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    268\u001b[0m     key_prefix \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtask_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m_\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m task_name \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
      "File \u001b[1;32mc:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\tidy3d\\web\\api\\autograd\\autograd.py:270\u001b[0m, in \u001b[0;36mrun\u001b[1;34m(simulation, task_name, folder_name, path, callback_url, verbose, progress_callback_upload, progress_callback_download, solver_version, worker_group, simulation_type, parent_tasks, local_gradient, max_num_adjoint_per_fwd, reduce_simulation, pay_type, priority, lazy)\u001b[0m\n\u001b[0;32m    249\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(simulation, td\u001b[38;5;241m.\u001b[39mSimulation) \u001b[38;5;129;01mand\u001b[39;00m is_valid_for_autograd(simulation):\n\u001b[0;32m    250\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m _run(\n\u001b[0;32m    251\u001b[0m         simulation\u001b[38;5;241m=\u001b[39msimulation,\n\u001b[0;32m    252\u001b[0m         task_name\u001b[38;5;241m=\u001b[39mtask_name,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    267\u001b[0m         lazy\u001b[38;5;241m=\u001b[39mlazy,\n\u001b[0;32m    268\u001b[0m     )\n\u001b[1;32m--> 270\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mwebapi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    271\u001b[0m \u001b[43m    \u001b[49m\u001b[43msimulation\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msimulation\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    272\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtask_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtask_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    273\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfolder_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfolder_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    274\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    275\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcallback_url\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallback_url\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    276\u001b[0m \u001b[43m    \u001b[49m\u001b[43mverbose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    277\u001b[0m \u001b[43m    \u001b[49m\u001b[43mprogress_callback_upload\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprogress_callback_upload\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    278\u001b[0m \u001b[43m    \u001b[49m\u001b[43mprogress_callback_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprogress_callback_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    279\u001b[0m \u001b[43m    \u001b[49m\u001b[43msolver_version\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msolver_version\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    280\u001b[0m \u001b[43m    \u001b[49m\u001b[43mworker_group\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mworker_group\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    281\u001b[0m \u001b[43m    \u001b[49m\u001b[43msimulation_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msimulation_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    282\u001b[0m \u001b[43m    \u001b[49m\u001b[43mparent_tasks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparent_tasks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    283\u001b[0m \u001b[43m    \u001b[49m\u001b[43mreduce_simulation\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mreduce_simulation\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    284\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpay_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpay_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    285\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpriority\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpriority\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    286\u001b[0m \u001b[43m    \u001b[49m\u001b[43mlazy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlazy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    287\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\tidy3d\\web\\api\\connect_util.py:42\u001b[0m, in \u001b[0;36mwait_for_connection.<locals>.decorator.<locals>.web_fn_wrapped\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m     40\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m (time\u001b[38;5;241m.\u001b[39mtime() \u001b[38;5;241m-\u001b[39m time_start) \u001b[38;5;241m<\u001b[39m timeout:\n\u001b[0;32m     41\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m---> 42\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m web_fn(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m     43\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m (ConnErr, \u001b[38;5;167;01mConnectionError\u001b[39;00m, NewConnectionError, ReadTimeout, JSONDecodeError):\n\u001b[0;32m     44\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m warned_previously:\n",
      "File \u001b[1;32mc:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\tidy3d\\web\\api\\webapi.py:402\u001b[0m, in \u001b[0;36mrun\u001b[1;34m(simulation, task_name, folder_name, path, callback_url, verbose, progress_callback_upload, progress_callback_download, solver_version, worker_group, simulation_type, parent_tasks, reduce_simulation, pay_type, priority, lazy)\u001b[0m\n\u001b[0;32m    389\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m restored_path:\n\u001b[0;32m    390\u001b[0m     task_id \u001b[38;5;241m=\u001b[39m upload(\n\u001b[0;32m    391\u001b[0m         simulation\u001b[38;5;241m=\u001b[39msimulation,\n\u001b[0;32m    392\u001b[0m         task_name\u001b[38;5;241m=\u001b[39mtask_name,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    400\u001b[0m         reduce_simulation\u001b[38;5;241m=\u001b[39mreduce_simulation,\n\u001b[0;32m    401\u001b[0m     )\n\u001b[1;32m--> 402\u001b[0m     \u001b[43mstart\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    403\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtask_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    404\u001b[0m \u001b[43m        \u001b[49m\u001b[43msolver_version\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msolver_version\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    405\u001b[0m \u001b[43m        \u001b[49m\u001b[43mworker_group\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mworker_group\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    406\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpay_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpay_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    407\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpriority\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpriority\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    408\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    409\u001b[0m     monitor(task_id, verbose\u001b[38;5;241m=\u001b[39mverbose)\n\u001b[0;32m    410\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[1;32mc:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\tidy3d\\web\\api\\connect_util.py:42\u001b[0m, in \u001b[0;36mwait_for_connection.<locals>.decorator.<locals>.web_fn_wrapped\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m     40\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m (time\u001b[38;5;241m.\u001b[39mtime() \u001b[38;5;241m-\u001b[39m time_start) \u001b[38;5;241m<\u001b[39m timeout:\n\u001b[0;32m     41\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m---> 42\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m web_fn(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m     43\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m (ConnErr, \u001b[38;5;167;01mConnectionError\u001b[39;00m, NewConnectionError, ReadTimeout, JSONDecodeError):\n\u001b[0;32m     44\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m warned_previously:\n",
      "File \u001b[1;32mc:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\tidy3d\\web\\api\\webapi.py:694\u001b[0m, in \u001b[0;36mstart\u001b[1;34m(task_id, solver_version, worker_group, pay_type, priority)\u001b[0m\n\u001b[0;32m    692\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m task:\n\u001b[0;32m    693\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTask not found.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m--> 694\u001b[0m \u001b[43mtask\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msubmit\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    695\u001b[0m \u001b[43m    \u001b[49m\u001b[43msolver_version\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msolver_version\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    696\u001b[0m \u001b[43m    \u001b[49m\u001b[43mworker_group\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mworker_group\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    697\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpay_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpay_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    698\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpriority\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpriority\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    699\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\tidy3d\\web\\core\\task_core.py:624\u001b[0m, in \u001b[0;36mSimulationTask.submit\u001b[1;34m(self, solver_version, worker_group, pay_type, priority)\u001b[0m\n\u001b[0;32m    621\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    622\u001b[0m     protocol_version \u001b[38;5;241m=\u001b[39m http_util\u001b[38;5;241m.\u001b[39mget_version()\n\u001b[1;32m--> 624\u001b[0m \u001b[43mhttp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpost\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    625\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtidy3d/tasks/\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtask_id\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m/submit\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m    626\u001b[0m \u001b[43m    \u001b[49m\u001b[43m{\u001b[49m\n\u001b[0;32m    627\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msolverVersion\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43msolver_version\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    628\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mworkerGroup\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mworker_group\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    629\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mprotocolVersion\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mprotocol_version\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    630\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43menableCaching\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mweb\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43menable_caching\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    631\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpayType\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mpay_type\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    632\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpriority\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mpriority\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    633\u001b[0m \u001b[43m    \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    634\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\tidy3d\\web\\core\\http_util.py:186\u001b[0m, in \u001b[0;36mhttp_interceptor.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    183\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m:\n\u001b[0;32m    184\u001b[0m         \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[1;32m--> 186\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m WebError(err_msg)\n\u001b[0;32m    188\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m resp\u001b[38;5;241m.\u001b[39mtext:\n\u001b[0;32m    189\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "\u001b[1;31mWebError\u001b[0m: error=Exceed the total storage limit. You can upgrade your license from your Account page to run this simulation; 4000000022; BAD_REQUEST [HTTP 400 POST https://tidy3d-api.simulation.cloud/tidy3d/tasks/fdve-c6da3e6d-adee-4c70-8ca3-c4f39f95a74b/submit]"
     ]
    }
   ],
   "source": [
    "sim_data = web.run(init_sim, task_name=\"SIL hemisphere\", path=_LOCAL_SIM_PATH)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "af0975c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "coup_eff = get_coupling_eff(sim_data)\n",
    "\n",
    "f, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4), tight_layout=True)\n",
    "ax1.plot(wl_range, coup_eff, \"-k\")\n",
    "ax1.set_xlabel(\"Wavelength (um)\")\n",
    "ax1.set_ylabel(\"Coupling Efficiency\")\n",
    "ax1.set_xlim(wl - bw / 2, wl + bw / 2)\n",
    "ax1.set_title(f\"Peak CE = {float(np.max(coup_eff)):.4f}\")\n",
    "sim_data.plot_field(\"field_xz\", \"E\", \"abs^2\", ax=ax2)\n",
    "ax2.set_aspect(\"auto\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2ad0dd0",
   "metadata": {},
   "source": [
    "## Fiber Position Sweep\n",
    "\n",
    "Sweep the fiber-to-SIL gap distance (`d_cf`) using the Cartesian oval profile to find the fiber position that maximizes coupling efficiency at 780 nm. This is done with cheap forward simulations before running the autograd optimization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "id": "5166b87c",
   "metadata": {},
   "outputs": [],
   "source": [
    "run_position_sweep = 0\n",
    "if run_position_sweep:\n",
    "    # Fiber position sweep configuration.\n",
    "    d_cf_values = np.linspace(2.15 - 0.5, 2.15 + 0.5, 7)  # 9 points from 1.65 to 2.65 um\n",
    "\n",
    "    np.arange(3 * wl, 5 * wl, wl / 4)\n",
    "    if len(d_cf_values) > 20:\n",
    "        raise ValueError(\"Too many d_cf values; reduce the number of points or increase the step size.\")\n",
    "\n",
    "\n",
    "    # Use the Cartesian oval profile (already computed as init_params) for each d_cf.\n",
    "    # Clamp heights so the SIL never exceeds the fiber face.\n",
    "    sweep_ce = []\n",
    "    sweep_sims = []\n",
    "    for d_cf_val in d_cf_values:\n",
    "        clamped_params = np.clip(init_params, min_height, sil_radius + d_cf_val)\n",
    "        sim_i = get_simulation(clamped_params, d_cf_override=d_cf_val)\n",
    "        sweep_sims.append(sim_i)\n",
    "\n",
    "    # Submit all sims as a batch.\n",
    "    batch = web.Batch(simulations={f\"dcf_{i:02d}\": s for i, s in enumerate(sweep_sims)})\n",
    "    batch_data = batch.run()\n",
    "\n",
    "    # Extract CE at 780 nm for each d_cf.\n",
    "    for i, d_cf_val in enumerate(d_cf_values):\n",
    "        sd = batch_data[f\"dcf_{i:02d}\"]\n",
    "        mode_amps = sd[\"mode_fiber\"].amps.sel(direction=\"+\", mode_index=0)\n",
    "        mode_power = np.abs(mode_amps.sel(f=freq, method=\"nearest\").values) ** 2\n",
    "        dip_power = sd[\"flux_dip\"].flux.sel(f=freq, method=\"nearest\").values\n",
    "        sweep_ce.append(float(mode_power / dip_power))\n",
    "\n",
    "    sweep_ce = np.array(sweep_ce)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "eaf48e5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "if run_position_sweep:\n",
    "    # Find optimal d_cf and update globals.\n",
    "    d_cf_opt = d_cf_values[np.argmax(sweep_ce)]\n",
    "    print(f\"Optimal d_cf = {d_cf_opt:.3f} μm  (CE = {np.max(sweep_ce):.4f})\")\n",
    "\n",
    "    fig, ax = plt.subplots(1, 1, figsize=(7, 4), tight_layout=True)\n",
    "    ax.plot(d_cf_values, sweep_ce, \"o-\", markersize=4)\n",
    "    ax.axvline(d_cf_opt, color=\"r\", ls=\"--\", alpha=0.7, label=f\"$d_{{cf}}^*$ = {d_cf_opt:.2f} μm\")\n",
    "    ax.set_xlabel(\"Fiber gap d_cf (μm)\")\n",
    "    ax.set_ylabel(\"Coupling efficiency at 780 nm\")\n",
    "    ax.set_title(\"Fiber Position Sweep (Cartesian Oval)\")\n",
    "    ax.legend()\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "64124657",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Lock in the optimal fiber position for all subsequent cells.\n",
    "d_cf = 2.15\n",
    "z_fiber_face = z_sil_base + sil_radius + d_cf\n",
    "z_domain_max = z_fiber_face + pml_spacing\n",
    "size_z = z_domain_max - z_domain_min"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19271e48",
   "metadata": {},
   "source": [
    "## Substrate Thickness Sweep\n",
    "\n",
    "Sweep the SiO2 substrate thickness (`t_sio2`) while keeping the current lens profile and fiber position fixed, then lock in the value that maximizes coupling efficiency at 780 nm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "bef5cbf4",
   "metadata": {},
   "outputs": [],
   "source": [
    "substrate_thickness_sweep = 0\n",
    "\n",
    "if substrate_thickness_sweep:\n",
    "    t_sio2_values = np.linspace(0.25, 0.75, 9)\n",
    "\n",
    "    base_params = np.clip(init_params, min_height, min(max_height, sil_radius + d_cf))\n",
    "\n",
    "    sweep_ce_t_sio2 = []\n",
    "    sweep_sims_t_sio2 = []\n",
    "    for t_sio2_val in t_sio2_values:\n",
    "        sim_i = get_simulation(base_params, t_sio2_override=t_sio2_val)\n",
    "        sweep_sims_t_sio2.append(sim_i)\n",
    "\n",
    "    batch_t_sio2 = web.Batch(\n",
    "        simulations={f\"tsio2_{i:02d}\": s for i, s in enumerate(sweep_sims_t_sio2)}\n",
    "    )\n",
    "    batch_t_sio2_data = batch_t_sio2.run()\n",
    "\n",
    "    for i, t_sio2_val in enumerate(t_sio2_values):\n",
    "        sd = batch_t_sio2_data[f\"tsio2_{i:02d}\"]\n",
    "        mode_amps = sd[\"mode_fiber\"].amps.sel(direction=\"+\", mode_index=0)\n",
    "        mode_power = np.abs(mode_amps.sel(f=freq, method=\"nearest\").values) ** 2\n",
    "        dip_power = sd[\"flux_dip\"].flux.sel(f=freq, method=\"nearest\").values\n",
    "        sweep_ce_t_sio2.append(float(mode_power / dip_power))\n",
    "\n",
    "    sweep_ce_t_sio2 = np.array(sweep_ce_t_sio2)\n",
    "\n",
    "    t_sio2_opt = t_sio2_values[np.argmax(sweep_ce_t_sio2)]\n",
    "    t_sio2 = float(t_sio2_opt)\n",
    "    z_sio2_top = t_sio2\n",
    "    z_film_top = z_sio2_top + t_film\n",
    "    z_sil_base = z_film_top\n",
    "    z_qd = z_sio2_top + 0.5 * t_film\n",
    "    z_fiber_face = z_sil_base + sil_radius + d_cf\n",
    "    z_domain_max = z_fiber_face + pml_spacing\n",
    "    size_z = z_domain_max - z_domain_min\n",
    "\n",
    "    print(f\"Optimal t_sio2 = {t_sio2_opt:.4f} μm  (CE = {np.max(sweep_ce_t_sio2):.4f})\")\n",
    "\n",
    "    fig, ax = plt.subplots(1, 1, figsize=(7, 4), tight_layout=True)\n",
    "    ax.plot(t_sio2_values, sweep_ce_t_sio2, \"o-\", markersize=4)\n",
    "    ax.axvline(t_sio2_opt, color=\"r\", ls=\"--\", alpha=0.7, label=f\"$t_{{SiO_2}}^*$ = {t_sio2_opt:.3f} μm\")\n",
    "    ax.set_xlabel(\"Substrate thickness t_sio2 (μm)\")\n",
    "    ax.set_ylabel(\"Coupling efficiency at 780 nm\")\n",
    "    ax.set_title(\"Substrate Thickness Sweep\")\n",
    "    ax.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0979304c",
   "metadata": {},
   "source": [
    "## Gradient-Based Optimization\n",
    "\n",
    "Optimize the SIL ring-height profile to maximize fiber coupling efficiency using Tidy3D's autograd support with an optax Adam optimizer. The fiber position is fixed at the optimal `d_cf` found above. Heights are clipped after each step so the SIL can touch but never exceed the fiber face."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "5d888dd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def objective(params):\n",
    "    \"\"\"Compute the peak fiber mode power (differentiable via autograd).\n",
    "\n",
    "    We maximize mode power rather than coupling efficiency (mode_power / dip_power)\n",
    "    because FluxMonitor cannot produce adjoint sources for gradient computation.\n",
    "    Since the SIL surface is far from the emitter, it does not significantly affect\n",
    "    total dipole emission, so maximizing mode power is a practical proxy for\n",
    "    maximizing coupling efficiency.\n",
    "    \"\"\"\n",
    "    sim = get_simulation(params)\n",
    "    sim_data = web.run(sim, task_name=\"sil_opt\", verbose=False, path=_LOCAL_SIM_PATH)\n",
    "    mode_amps = sim_data[\"mode_fiber\"].amps.sel(direction=\"+\", mode_index=0)\n",
    "    mode_power = anp.abs(mode_amps.values) ** 2\n",
    "    return anp.max(mode_power)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "806e5a19",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step 01/45: mode_power = 103.201367, ||∇|| = 2.8387e+02\n",
      "Step 02/45: mode_power = 362.992526, ||∇|| = 4.9708e+02\n",
      "Step 03/45: mode_power = 677.005507, ||∇|| = 5.9006e+02\n",
      "Step 04/45: mode_power = 913.388215, ||∇|| = 4.9684e+02\n",
      "Step 05/45: mode_power = 1058.741722, ||∇|| = 3.8518e+02\n",
      "Step 06/45: mode_power = 1116.547465, ||∇|| = 3.3578e+02\n",
      "Step 07/45: mode_power = 1138.006381, ||∇|| = 3.2917e+02\n",
      "Step 08/45: mode_power = 1148.915107, ||∇|| = 2.9940e+02\n",
      "Step 09/45: mode_power = 1141.769604, ||∇|| = 3.2856e+02\n",
      "Step 10/45: mode_power = 1144.648102, ||∇|| = 3.5650e+02\n",
      "Step 11/45: mode_power = 1173.249193, ||∇|| = 3.4403e+02\n",
      "Step 12/45: mode_power = 1216.019798, ||∇|| = 3.1146e+02\n",
      "Step 13/45: mode_power = 1257.813473, ||∇|| = 2.9129e+02\n",
      "Step 14/45: mode_power = 1292.994902, ||∇|| = 2.9375e+02\n",
      "Step 15/45: mode_power = 1328.528546, ||∇|| = 2.7900e+02\n",
      "Step 16/45: mode_power = 1359.614178, ||∇|| = 2.2742e+02\n",
      "Step 17/45: mode_power = 1379.718487, ||∇|| = 1.7688e+02\n",
      "Step 18/45: mode_power = 1382.698660, ||∇|| = 1.8230e+02\n",
      "Step 19/45: mode_power = 1378.531498, ||∇|| = 2.1515e+02\n",
      "Step 20/45: mode_power = 1376.071459, ||∇|| = 2.3966e+02\n",
      "Step 21/45: mode_power = 1377.856230, ||∇|| = 2.4701e+02\n",
      "Step 22/45: mode_power = 1383.827030, ||∇|| = 2.3647e+02\n",
      "Step 23/45: mode_power = 1391.582601, ||∇|| = 2.1733e+02\n",
      "Step 24/45: mode_power = 1399.176503, ||∇|| = 1.9660e+02\n",
      "Step 25/45: mode_power = 1412.032595, ||∇|| = 1.8390e+02\n",
      "Step 26/45: mode_power = 1429.628122, ||∇|| = 1.7247e+02\n",
      "Step 27/45: mode_power = 1442.695879, ||∇|| = 1.5774e+02\n",
      "Step 28/45: mode_power = 1454.938871, ||∇|| = 1.4198e+02\n",
      "Step 29/45: mode_power = 1466.151028, ||∇|| = 1.3190e+02\n",
      "Step 30/45: mode_power = 1475.264613, ||∇|| = 1.3278e+02\n",
      "Step 31/45: mode_power = 1485.196647, ||∇|| = 1.4282e+02\n",
      "Step 32/45: mode_power = 1494.787646, ||∇|| = 1.4810e+02\n",
      "Step 33/45: mode_power = 1506.208289, ||∇|| = 1.4030e+02\n",
      "Step 34/45: mode_power = 1519.583615, ||∇|| = 1.1955e+02\n",
      "Step 35/45: mode_power = 1532.182109, ||∇|| = 9.4809e+01\n",
      "Step 36/45: mode_power = 1539.568887, ||∇|| = 8.6617e+01\n",
      "Step 37/45: mode_power = 1541.344269, ||∇|| = 1.0216e+02\n",
      "Step 38/45: mode_power = 1540.464463, ||∇|| = 1.2308e+02\n",
      "Step 39/45: mode_power = 1541.125691, ||∇|| = 1.3554e+02\n",
      "Step 40/45: mode_power = 1543.464203, ||∇|| = 1.3152e+02\n",
      "Step 41/45: mode_power = 1551.114455, ||∇|| = 1.1451e+02\n",
      "Step 42/45: mode_power = 1556.994528, ||∇|| = 9.3259e+01\n",
      "Step 43/45: mode_power = 1563.007094, ||∇|| = 8.2228e+01\n",
      "Step 44/45: mode_power = 1569.922907, ||∇|| = 8.1662e+01\n",
      "Step 45/45: mode_power = 1575.743726, ||∇|| = 8.5391e+01\n"
     ]
    }
   ],
   "source": [
    "# Optimization configuration.\n",
    "num_steps = 45\n",
    "learning_rate = 0.1\n",
    "\n",
    "# Initialize from the Cartesian oval, clamped so SIL never exceeds the fiber face.\n",
    "params = np.clip(init_params, min_height, min(max_height, sil_radius + d_cf)).astype(float)\n",
    "optimizer = optax.adam(learning_rate=learning_rate)\n",
    "opt_state = optimizer.init(params)\n",
    "val_and_grad_fn = value_and_grad(objective)\n",
    "\n",
    "# Optimization loop.\n",
    "history = []\n",
    "for step in range(1, num_steps + 1):\n",
    "    value, grad = val_and_grad_fn(params)\n",
    "    history.append(float(value))\n",
    "    grad_norm = float(np.linalg.norm(grad))\n",
    "    print(f\"Step {step:02d}/{num_steps}: mode_power = {float(value):.6f}, ||∇|| = {grad_norm:.4e}\")\n",
    "\n",
    "    # Maximize by negating gradient.\n",
    "    updates, opt_state = optimizer.update(-grad, opt_state, params)\n",
    "    params = optax.apply_updates(params, updates)\n",
    "    # Keep heights within physical bounds and prevent fiber overlap.\n",
    "    params = anp.clip(params, min_height, min(max_height, sil_radius + d_cf))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1a3fd05",
   "metadata": {},
   "source": [
    "## Optimization Results\n",
    "\n",
    "Convergence history, optimized lens profile, and field distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "c74b64ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.7957325  3.6015952  2.8804846  2.7388644  2.8584878  2.8408155\n",
      " 2.9300768  3.1253731  3.1616764  3.0100484  2.8015068  2.6035569\n",
      " 2.4531732  2.535381   2.9014757  2.9748905  2.4863043  2.1240332\n",
      " 2.478168   3.1428552  3.1113372  2.661268   2.5235898  2.4765387\n",
      " 1.9520289  1.7339753  2.7133787  3.4660995  1.7226913  0.64236337\n",
      " 1.1467525  2.3278089  2.7500808  2.3945968  1.535236   0.65786266\n",
      " 0.5565963  1.0868295  1.3645165  1.2717543  1.2382777  1.2575331\n",
      " 1.4273942  1.6254028  1.7057337  1.5371319  1.3350819  1.6053576\n",
      " 2.5779068  3.4789388  0.18058585 0.05       0.9618319  1.5583732\n",
      " 0.93738097 0.76973593 1.1050149  1.633205   1.0345849  0.6338103\n",
      " 2.2522395  2.0028248  0.05       0.05      ]\n"
     ]
    }
   ],
   "source": [
    "print(params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "97635908",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial CE = 103.2014\n",
      "Final   CE = 1575.7437\n",
      "Improvement = 1472.5424\n"
     ]
    }
   ],
   "source": [
    "# Convergence plot.\n",
    "fig, ax = plt.subplots(1, 1, figsize=(7, 4), tight_layout=True)\n",
    "ax.plot(np.arange(1, len(history) + 1), history, \"o-\", linewidth=2, markersize=4)\n",
    "ax.set_xlabel(\"Optimization Step\")\n",
    "ax.set_ylabel(\"Peak Coupling Efficiency\")\n",
    "ax.set_title(\"Optimization Convergence\")\n",
    "plt.show()\n",
    "\n",
    "print(f\"Initial CE = {history[0]:.4f}\")\n",
    "print(f\"Final   CE = {history[-1]:.4f}\")\n",
    "print(f\"Improvement = {history[-1] - history[0]:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "a4f22272",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">00:03:28 US Eastern Daylight Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'SIL optimized'</span> with resource_id \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b'</span>   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:03:28 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'SIL optimized'\u001b[0m with resource_id \n",
       "\u001b[2;36m                                  \u001b[0m\u001b[32m'fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b'\u001b[0m   \n",
       "\u001b[2;36m                                  \u001b[0mand 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-7ce01e20-5607-4c66-8093-2d8359cd6b2b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?tas</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">kId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b'</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>.                                             \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=606741;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=681380;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[32mtas\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                                  \u001b[0m\u001b]8;id=681380;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[32mkId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=606741;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=325135;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=606741;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[32m-7ce01e20-5607-4c66-8093-2d8359cd6b2b'\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                                  \u001b[0m.                                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/152fbf08-52d6-47df-93fd-6591068eb56a\" 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=924475;https://tidy3d.simulation.cloud/folders/152fbf08-52d6-47df-93fd-6591068eb56a\u001b\\\u001b[32m'default'\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\">c:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\rich\\live.py:231\n",
       ": UserWarning: install \"ipywidgets\" for Jupyter support\n",
       "  warnings.warn('install \"ipywidgets\" for Jupyter support')\n",
       "</pre>\n"
      ],
      "text/plain": [
       "c:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\rich\\live.py:231\n",
       ": UserWarning: install \"ipywidgets\" for Jupyter support\n",
       "  warnings.warn('install \"ipywidgets\" for Jupyter support')\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\">00:03:30 US Eastern Daylight Time </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.177</span>. Minimum cost\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>depends on task execution details. Use        \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed    \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>FlexCredit cost after a simulation run.       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:03:30 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.177\u001b[0m. Minimum cost\n",
       "\u001b[2;36m                                  \u001b[0mdepends on task execution details. Use        \n",
       "\u001b[2;36m                                  \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed    \n",
       "\u001b[2;36m                                  \u001b[0mFlexCredit cost after a simulation run.       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">00:03:31 US Eastern Daylight Time </span>status = queued                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:03:31 US Eastern Daylight Time\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                 \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or <span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </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   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>the job running on the cloud.                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                                 \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use                 \n",
       "\u001b[2;36m                                  \u001b[0m\u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or \u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m \n",
       "\u001b[2;36m                                  \u001b[0mor abort/delete the task in the web UI.       \n",
       "\u001b[2;36m                                  \u001b[0mTerminating the Python script will not stop   \n",
       "\u001b[2;36m                                  \u001b[0mthe job running on the cloud.                 \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\">00:03:37 US Eastern Daylight Time </span>status = preprocess                           \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:03:37 US Eastern Daylight Time\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\">00:03:41 US Eastern Daylight Time </span>starting up solver                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:03:41 US Eastern Daylight Time\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\">                                  </span>running solver                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                                 \u001b[0m\u001b[2;36m \u001b[0mrunning 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\">00:03:53 US Eastern Daylight Time </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>%, exiting.        \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:03:53 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\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\">                                  </span>status = postprocess                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                                 \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                          \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\">00:04:02 US Eastern Daylight Time </span>status = success                              \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:04:02 US Eastern Daylight Time\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\">00:04:04 US Eastern Daylight Time </span>View simulation result at                     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?tas</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">kId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b'</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                             \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:04:04 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                     \n",
       "\u001b[2;36m                                  \u001b[0m\u001b]8;id=952709;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=584142;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[4;34mtas\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                                  \u001b[0m\u001b]8;id=584142;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[4;34mkId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=952709;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=27825;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=952709;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7ce01e20-5607-4c66-8093-2d8359cd6b2b\u001b\\\u001b[4;34m-7ce01e20-5607-4c66-8093-2d8359cd6b2b'\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                                  \u001b[0m\u001b[4;34m.\u001b[0m                                             \n"
      ]
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     "output_type": "display_data"
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    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></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\">00:04:06 US Eastern Daylight Time </span>Loading simulation from                       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>C:\\Users\\chris\\AppData\\Local\\Temp\\tidy3d_sil_o\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>pt.hdf5                                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:04:06 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from                       \n",
       "\u001b[2;36m                                  \u001b[0mC:\\Users\\chris\\AppData\\Local\\Temp\\tidy3d_sil_o\n",
       "\u001b[2;36m                                  \u001b[0mpt.hdf5                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Final simulation with optimized parameters.\n",
    "opt_sim = get_simulation(params)\n",
    "opt_sim_data = web.run(opt_sim, task_name=\"SIL optimized\", path=_LOCAL_SIM_PATH)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "d735deb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimal d_cf = 2.150 μm\n",
      "Optimized peak CE = 0.0873\n"
     ]
    }
   ],
   "source": [
    "# Optimized coupling efficiency spectrum and field profile.\n",
    "opt_ce = get_coupling_eff(opt_sim_data)\n",
    "\n",
    "fig, axes = plt.subplots(1, 3, figsize=(16, 4), tight_layout=True)\n",
    "\n",
    "# CE spectrum comparison.\n",
    "axes[0].plot(wl_range, coup_eff, \"--k\", alpha=0.5, label=\"Initial (Cartesian oval)\")\n",
    "axes[0].plot(wl_range, opt_ce, \"-b\", label=\"Optimized\")\n",
    "axes[0].set_xlabel(\"Wavelength (μm)\")\n",
    "axes[0].set_ylabel(\"Coupling Efficiency\")\n",
    "axes[0].set_xlim(wl - bw / 2, wl + bw / 2)\n",
    "axes[0].set_title(f\"Peak CE: {float(np.max(opt_ce)):.4f}\")\n",
    "axes[0].legend(fontsize=9)\n",
    "\n",
    "# Field distribution.\n",
    "opt_sim_data.plot_field(\"field_xz\", \"E\", \"abs^2\", ax=axes[1])\n",
    "axes[1].set_aspect(\"auto\")\n",
    "axes[1].set_title(\"Optimized |E|²\")\n",
    "\n",
    "# Lens profile comparison.\n",
    "smoothed_params = np.array(params)  # final optimized params\n",
    "axes[2].plot(ring_radii, hemisphere, \"k--\", alpha=0.4, label=\"Hemisphere\")\n",
    "axes[2].plot(ring_radii, np.clip(init_params, min_height, sil_radius + d_cf), \"b--\", alpha=0.5, label=\"Cartesian oval (init)\")\n",
    "axes[2].plot(ring_radii, smoothed_params, \"r-\", label=\"Optimized\")\n",
    "axes[2].axhline(sil_radius + d_cf, color=\"gray\", ls=\":\", alpha=0.5, label=f\"fiber face = {sil_radius + d_cf:.2f} μm\")\n",
    "axes[2].set_xlabel(\"Radial position ρ (μm)\")\n",
    "axes[2].set_ylabel(\"Height (μm)\")\n",
    "axes[2].set_title(\"SIL Surface Profile\")\n",
    "axes[2].legend(fontsize=9)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "print(f\"Optimal d_cf = {d_cf:.3f} μm\")\n",
    "print(f\"Optimized peak CE = {float(np.max(opt_ce)):.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "id": "564e62f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved 64 optimized ring heights to 'g:\\My Drive\\product\\v1\\tidy3d\\solid_immersion_lens_v2\\output\\params\\sil_params.npy'\n"
     ]
    }
   ],
   "source": [
    "# Save optimized parameters.\n",
    "_params_path = os.path.join(_PARAMS_DIR, \"sil_params.npy\")\n",
    "np.save(_params_path, get_static(params))\n",
    "print(f\"Saved {num_rings} optimized ring heights to '{_params_path}'\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbb225fa",
   "metadata": {},
   "source": [
    "## Purcell Factor Calculation\n",
    "\n",
    "The Purcell factor ($F_p = P_{cav}/P_{bulk}$) is the ratio between the dipole power emitted in the SIL device and in a homogeneous reference medium matching the emitter film. We compute $P_{bulk}$ both analytically and via a normalization simulation.\n",
    "\n",
    "Analytically: $P_{bulk} = \\frac{\\omega^2}{12\\pi} \\frac{\\mu_0 n}{c}$, using the film index $n = 1.8$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "dc22a057",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Analytical P_bulk in the homogeneous emitter film.\n",
    "p_bulk_a = ((2 * np.pi * freqs) ** 2 / (12 * np.pi)) * (td.MU_0 * n_film / td.C_0)\n",
    "\n",
    "# Correction for symmetry image charges.\n",
    "p_bulk_a = p_bulk_a * 2 ** (2 * np.sum(np.abs(init_sim.symmetry)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31f48216",
   "metadata": {},
   "source": [
    "### Normalization Simulation\n",
    "\n",
    "A homogeneous reference simulation with the emitter embedded in the $n=1.8$ film provides the numerical $P_{bulk}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "8eeffabf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dp_source_bulk = td.PointDipole(\n",
    "    center=(0, 0, z_qd),\n",
    "    source_time=td.GaussianPulse(freq0=freq, fwidth=freqw),\n",
    "    polarization=\"Ey\",\n",
    ")\n",
    "\n",
    "flux_dip_bulk = td.FluxMonitor(\n",
    "    center=(0, 0, 0.5 * (z_domain_min + z_domain_max)),\n",
    "    size=(init_sim.size[0] * 0.8, init_sim.size[1] * 0.8, init_sim.size[2] - pml_spacing),\n",
    "    freqs=freqs,\n",
    "    name=\"flux_dip_bulk\",\n",
    ")\n",
    "\n",
    "bulk_device = init_sim.copy(\n",
    "    update={\n",
    "        \"structures\": [],\n",
    "        \"sources\": [dp_source_bulk],\n",
    "        \"monitors\": [flux_dip_bulk],\n",
    "        \"medium\": mat_film,\n",
    "        \"symmetry\": init_sim.symmetry,\n",
    "        \"boundary_spec\": td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "    }\n",
    ")\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(10, 5))\n",
    "bulk_device.plot_eps(z=z_qd, ax=ax1)\n",
    "bulk_device.plot_eps(y=0, ax=ax2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "e89c389c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">00:04:09 US Eastern Daylight Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'bulk sim'</span> with resource_id      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374'</span>   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:04:09 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'bulk sim'\u001b[0m with resource_id      \n",
       "\u001b[2;36m                                  \u001b[0m\u001b[32m'fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374'\u001b[0m   \n",
       "\u001b[2;36m                                  \u001b[0mand 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-53e2ba45-17eb-4a4d-9040-57bfbbd36374\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?tas</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">kId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374'</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>.                                             \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=43231;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=923913;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[32mtas\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                                  \u001b[0m\u001b]8;id=923913;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[32mkId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=43231;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=194469;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=43231;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[32m-53e2ba45-17eb-4a4d-9040-57bfbbd36374'\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                                  \u001b[0m.                                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/152fbf08-52d6-47df-93fd-6591068eb56a\" 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=549580;https://tidy3d.simulation.cloud/folders/152fbf08-52d6-47df-93fd-6591068eb56a\u001b\\\u001b[32m'default'\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\">c:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\rich\\live.py:231\n",
       ": UserWarning: install \"ipywidgets\" for Jupyter support\n",
       "  warnings.warn('install \"ipywidgets\" for Jupyter support')\n",
       "</pre>\n"
      ],
      "text/plain": [
       "c:\\Users\\chris\\miniconda3\\envs\\tidy3d-env-271\\lib\\site-packages\\rich\\live.py:231\n",
       ": UserWarning: install \"ipywidgets\" for Jupyter support\n",
       "  warnings.warn('install \"ipywidgets\" for Jupyter support')\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\">00:04:11 US Eastern Daylight Time </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.168</span>. Minimum cost\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>depends on task execution details. Use        \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed    \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>FlexCredit cost after a simulation run.       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:04:11 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m0.168\u001b[0m. Minimum cost\n",
       "\u001b[2;36m                                  \u001b[0mdepends on task execution details. Use        \n",
       "\u001b[2;36m                                  \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed    \n",
       "\u001b[2;36m                                  \u001b[0mFlexCredit cost after a simulation run.       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">00:04:12 US Eastern Daylight Time </span>status = queued                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:04:12 US Eastern Daylight Time\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                 \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or <span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </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   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>the job running on the cloud.                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                                 \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use                 \n",
       "\u001b[2;36m                                  \u001b[0m\u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or \u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m \n",
       "\u001b[2;36m                                  \u001b[0mor abort/delete the task in the web UI.       \n",
       "\u001b[2;36m                                  \u001b[0mTerminating the Python script will not stop   \n",
       "\u001b[2;36m                                  \u001b[0mthe job running on the cloud.                 \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\">00:04:24 US Eastern Daylight Time </span>starting up solver                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:04:24 US Eastern Daylight Time\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\">                                  </span>running solver                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                                 \u001b[0m\u001b[2;36m \u001b[0mrunning 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\">00:04:28 US Eastern Daylight Time </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>%, exiting.        \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:04:28 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\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\">                                  </span>status = postprocess                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                                 \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                          \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\">00:04:29 US Eastern Daylight Time </span>status = success                              \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:04:29 US Eastern Daylight Time\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\">00:04:31 US Eastern Daylight Time </span>View simulation result at                     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?tas</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">kId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374'</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                             \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:04:31 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                     \n",
       "\u001b[2;36m                                  \u001b[0m\u001b]8;id=717156;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=131483;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[4;34mtas\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                                  \u001b[0m\u001b]8;id=131483;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[4;34mkId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=717156;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=787292;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=717156;https://tidy3d.simulation.cloud/workbench?taskId=fdve-53e2ba45-17eb-4a4d-9040-57bfbbd36374\u001b\\\u001b[4;34m-53e2ba45-17eb-4a4d-9040-57bfbbd36374'\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                                  \u001b[0m\u001b[4;34m.\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\"></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\">00:04:32 US Eastern Daylight Time </span>Loading simulation from                       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>C:\\Users\\chris\\AppData\\Local\\Temp\\tidy3d_sil_o\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                                  </span>pt.hdf5                                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m00:04:32 US Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from                       \n",
       "\u001b[2;36m                                  \u001b[0mC:\\Users\\chris\\AppData\\Local\\Temp\\tidy3d_sil_o\n",
       "\u001b[2;36m                                  \u001b[0mpt.hdf5                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data_bulk = web.run(bulk_device, task_name=\"bulk sim\", path=_LOCAL_SIM_PATH)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "599470ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p_cav = sim_data[\"flux_dip\"].flux\n",
    "p_bulk_s = sim_data_bulk[\"flux_dip_bulk\"].flux\n",
    "\n",
    "purcell_s = p_cav / p_bulk_s\n",
    "purcell_a = p_cav / p_bulk_a\n",
    "\n",
    "f, ax1 = plt.subplots(1, 1, figsize=(6, 4), tight_layout=True)\n",
    "ax1.plot(wl_range, purcell_s, \"-k\", label=\"simulation\")\n",
    "ax1.plot(wl_range, purcell_a, \"--r\", label=\"analytic\")\n",
    "ax1.set_xlabel(\"Wavelength (um)\")\n",
    "ax1.set_ylabel(\"Purcell Factor\")\n",
    "ax1.set_xlim(wl - bw / 2, wl + bw / 2)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "a5b407c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" 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\" ></div>\n",
       "    <script>\n",
       "        \n",
       "        /**\n",
       "        * Simulation Viewer Injector\n",
       "        *\n",
       "        * Monitors the document for elements being added in the form:\n",
       "        *\n",
       "        *    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"{...}\" />\n",
       "        *\n",
       "        * This script will then inject an iframe to the viewer application, and pass it the simulation data\n",
       "        * via the postMessage API on request. The script may be safely included multiple times, with only the\n",
       "        * configuration of the first started script (e.g. viewer URL) applying.\n",
       "        *\n",
       "        */\n",
       "        (function() {\n",
       "            const TARGET_CLASS = \"simulation-viewer\";\n",
       "            const ACTIVE_CLASS = \"simulation-viewer-active\";\n",
       "            const VIEWER_URL = \"https://tidy3d.simulation.cloud/simulation-viewer\";\n",
       "\n",
       "            class SimulationViewerInjector {\n",
       "                constructor() {\n",
       "                    for (var node of document.getElementsByClassName(TARGET_CLASS)) {\n",
       "                        this.injectViewer(node);\n",
       "                    }\n",
       "\n",
       "                    // Monitor for newly added nodes to the DOM\n",
       "                    this.observer = new MutationObserver(this.onMutations.bind(this));\n",
       "                    this.observer.observe(document.body, {childList: true, subtree: true});\n",
       "                }\n",
       "\n",
       "                onMutations(mutations) {\n",
       "                    for (var mutation of mutations) {\n",
       "                        if (mutation.type === 'childList') {\n",
       "                            /**\n",
       "                            * Have found that adding the element does not reliably trigger the mutation observer.\n",
       "                            * It may be the case that setting content with innerHTML does not trigger.\n",
       "                            *\n",
       "                            * It seems to be sufficient to re-scan the document for un-activated viewers\n",
       "                            * whenever an event occurs, as Jupyter triggers multiple events on cell evaluation.\n",
       "                            */\n",
       "                            var viewers = document.getElementsByClassName(TARGET_CLASS);\n",
       "                            for (var node of viewers) {\n",
       "                                this.injectViewer(node);\n",
       "                            }\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "\n",
       "                injectViewer(node) {\n",
       "                    // (re-)check that this is a valid simulation container and has not already been injected\n",
       "                    if (node.classList.contains(TARGET_CLASS) && !node.classList.contains(ACTIVE_CLASS)) {\n",
       "                        // Mark node as injected, to prevent re-runs\n",
       "                        node.classList.add(ACTIVE_CLASS);\n",
       "\n",
       "                        var uuid;\n",
       "                        if (window.crypto && window.crypto.randomUUID) {\n",
       "                            uuid = window.crypto.randomUUID();\n",
       "                        } else {\n",
       "                            uuid = \"\" + Math.random();\n",
       "                        }\n",
       "\n",
       "                        var frame = document.createElement(\"iframe\");\n",
       "                        frame.width = node.dataset.width || 800;\n",
       "                        frame.height = node.dataset.height || 800;\n",
       "                        frame.style.cssText = `width:${frame.width}px;height:${frame.height}px;max-width:none;border:0;display:block`\n",
       "                        frame.src = VIEWER_URL + \"?uuid=\" + uuid;\n",
       "\n",
       "                        var postMessageToViewer;\n",
       "                        postMessageToViewer = event => {\n",
       "                            if(event.data.type === 'viewer' && event.data.uuid===uuid){\n",
       "                                frame.contentWindow.postMessage({ type: 'jupyter', uuid, value: node.dataset.simulation, fileType: 'hdf5'}, '*');\n",
       "\n",
       "                                // Run once only\n",
       "                                window.removeEventListener('message', postMessageToViewer);\n",
       "                            }\n",
       "                        };\n",
       "                        window.addEventListener(\n",
       "                            'message',\n",
       "                            postMessageToViewer,\n",
       "                            false\n",
       "                        );\n",
       "\n",
       "                        node.appendChild(frame);\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            if (!window.simulationViewerInjector) {\n",
       "                window.simulationViewerInjector = new SimulationViewerInjector();\n",
       "            }\n",
       "        })();\n",
       "    \n",
       "    </script>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_3d_sim = opt_sim.copy(\n",
    "    update={\n",
    "        \"structures\": opt_sim.structures,\n",
    "        \"sources\": opt_sim.sources,\n",
    "        \"monitors\": [],\n",
    "        \"medium\": opt_sim.medium,\n",
    "        \"boundary_spec\": td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "    }\n",
    ")\n",
    "\n",
    "plot_3d_sim.plot_3d()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8b03fb31",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "67060b05",
   "metadata": {},
   "source": [
    "## Export Lens + Support Structures to STL\n",
    "\n",
    "Combine the optimized SIL lens with support structures for nano-3D printing:\n",
    "\n",
    "1. **Spacer cylinder** — sits on the topmost film, constrains the fiber-to-film distance.  \n",
    "   OD = 200 µm, ID = 50 µm, height = `sil_radius + d_cf` (≈ 4.65 µm).\n",
    "2. **Alignment cylinder** — guides the fiber laterally.  \n",
    "   OD = 200 µm, ID = 126 µm, height = 100 µm.\n",
    "3. **Conical taper** — funnels the fiber into the alignment bore.  \n",
    "   OD = 200 µm, ID tapers from 126 → 200 µm, height = 75 µm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "id": "06e67d49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Spacer height (film top → fiber face): 4.650 μm\n",
      "\n",
      "Exported STL → g:\\My Drive\\product\\v1\\tidy3d\\solid_immersion_lens_v2\\output\\stl\\sil_with_supports (2).stl\n",
      "  Z-shift applied: -0.638 μm  (bottom now at z=0)\n",
      "  Lens:         8192 faces\n",
      "  Spacer:       1024 faces  (200.0 OD × 50.0 ID × 4.65 μm)\n",
      "  Alignment:    1024 faces  (200.0 OD × 126.0 ID × 100.0 μm)\n",
      "  Taper:        1024 faces  (200.0 OD, ID 126.0→200.0 μm × 75.0 μm)\n",
      "  Total:       11264 faces\n",
      "  Z range:    [0.000, 179.650] μm\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# --- Export Optimized Lens + Support Structures to STL ---\n",
    "\n",
    "import subprocess, sys\n",
    "\n",
    "try:\n",
    "    import trimesh\n",
    "except ImportError:\n",
    "    subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", \"trimesh\"])\n",
    "    import trimesh\n",
    "\n",
    "# Spacer height = distance from topmost film to fiber face.\n",
    "spacer_height = sil_radius + d_cf\n",
    "print(f\"Spacer height (film top → fiber face): {spacer_height:.3f} μm\")\n",
    "\n",
    "# Support structure dimensions (all in μm).\n",
    "SPACER_OD, SPACER_ID = 200.0, 50.0\n",
    "ALIGN_OD, ALIGN_ID   = 200.0, 126.0\n",
    "ALIGN_HEIGHT          = 100.0\n",
    "TAPER_OD              = 200.0\n",
    "TAPER_HEIGHT          = 75.0\n",
    "N_SEG                 = 128\n",
    "\n",
    "\n",
    "def make_annular_cylinder(r_out, r_in, h, z_base, n=128):\n",
    "    \"\"\"Watertight annular cylinder mesh.\"\"\"\n",
    "    theta = np.linspace(0, 2 * np.pi, n, endpoint=False)\n",
    "    c, s = np.cos(theta), np.sin(theta)\n",
    "    v = np.zeros((4 * n, 3))\n",
    "    v[:n]       = np.c_[r_out*c, r_out*s, np.full(n, z_base)]\n",
    "    v[n:2*n]    = np.c_[r_out*c, r_out*s, np.full(n, z_base + h)]\n",
    "    v[2*n:3*n]  = np.c_[r_in*c,  r_in*s,  np.full(n, z_base)]\n",
    "    v[3*n:]     = np.c_[r_in*c,  r_in*s,  np.full(n, z_base + h)]\n",
    "    f = []\n",
    "    ob, ot, ib, it = 0, n, 2*n, 3*n\n",
    "    for j in range(n):\n",
    "        jn = (j + 1) % n\n",
    "        f += [[ob+j, ot+j, ob+jn], [ob+jn, ot+j, ot+jn]]   # outer wall\n",
    "        f += [[ib+j, ib+jn, it+j], [ib+jn, it+jn, it+j]]    # inner wall\n",
    "        f += [[ot+j, it+j, ot+jn], [ot+jn, it+j, it+jn]]    # top ring\n",
    "        f += [[ob+j, ob+jn, ib+j], [ob+jn, ib+jn, ib+j]]    # bottom ring\n",
    "    return trimesh.Trimesh(vertices=v, faces=np.array(f))\n",
    "\n",
    "\n",
    "def make_conical_taper(r_out, r_in_bot, r_in_top, h, z_base, n=128):\n",
    "    \"\"\"Annular frustum with constant OD and linearly tapered ID.\"\"\"\n",
    "    r_in_top = min(r_in_top, r_out - 0.1)  # avoid degenerate zero-width ring\n",
    "    theta = np.linspace(0, 2 * np.pi, n, endpoint=False)\n",
    "    c, s = np.cos(theta), np.sin(theta)\n",
    "    v = np.zeros((4 * n, 3))\n",
    "    v[:n]       = np.c_[r_out*c,    r_out*s,    np.full(n, z_base)]\n",
    "    v[n:2*n]    = np.c_[r_out*c,    r_out*s,    np.full(n, z_base + h)]\n",
    "    v[2*n:3*n]  = np.c_[r_in_bot*c, r_in_bot*s, np.full(n, z_base)]\n",
    "    v[3*n:]     = np.c_[r_in_top*c, r_in_top*s, np.full(n, z_base + h)]\n",
    "    f = []\n",
    "    ob, ot, ib, it = 0, n, 2*n, 3*n\n",
    "    for j in range(n):\n",
    "        jn = (j + 1) % n\n",
    "        f += [[ob+j, ot+j, ob+jn], [ob+jn, ot+j, ot+jn]]\n",
    "        f += [[ib+j, ib+jn, it+j], [ib+jn, it+jn, it+j]]\n",
    "        f += [[ot+j, it+j, ot+jn], [ot+jn, it+j, it+jn]]\n",
    "        f += [[ob+j, ob+jn, ib+j], [ob+jn, ib+jn, ib+j]]\n",
    "    return trimesh.Trimesh(vertices=v, faces=np.array(f))\n",
    "\n",
    "\n",
    "# --- Build lens mesh from optimized parameters ---\n",
    "lens_verts = np.array(vertices_from_params(params))\n",
    "lens_faces = np.array(FACE_ARRAY)\n",
    "lens_mesh = trimesh.Trimesh(vertices=lens_verts, faces=lens_faces)\n",
    "\n",
    "# --- Build support structures ---\n",
    "z_base_support = z_film_top\n",
    "\n",
    "spacer = make_annular_cylinder(\n",
    "    SPACER_OD / 2, SPACER_ID / 2, spacer_height, z_base_support, N_SEG\n",
    ")\n",
    "alignment = make_annular_cylinder(\n",
    "    ALIGN_OD / 2, ALIGN_ID / 2, ALIGN_HEIGHT,\n",
    "    z_base_support + spacer_height, N_SEG\n",
    ")\n",
    "taper = make_conical_taper(\n",
    "    TAPER_OD / 2,       # outer radius (constant)\n",
    "    ALIGN_ID / 2,       # inner radius at bottom (matches alignment bore)\n",
    "    TAPER_OD / 2,       # inner radius at top (wide opening)\n",
    "    TAPER_HEIGHT,\n",
    "    z_base_support + spacer_height + ALIGN_HEIGHT, N_SEG\n",
    ")\n",
    "\n",
    "# --- Combine all parts and shift so bottom face sits at z=0 ---\n",
    "combined = trimesh.util.concatenate([lens_mesh, spacer, alignment, taper])\n",
    "z_shift = combined.bounds[0, 2]  # current minimum z\n",
    "combined.apply_translation([0, 0, -z_shift])\n",
    "\n",
    "# Save to output/stl/ with auto-increment to avoid overwrites.\n",
    "_dst_base = \"sil_with_supports\"\n",
    "_dst = os.path.join(_STL_DIR, _dst_base + \".stl\")\n",
    "_counter = 1\n",
    "while os.path.exists(_dst):\n",
    "    _dst = os.path.join(_STL_DIR, f\"{_dst_base} ({_counter}).stl\")\n",
    "    _counter += 1\n",
    "combined.export(_dst)\n",
    "\n",
    "print(f\"\\nExported STL → {_dst}\")\n",
    "print(f\"  Z-shift applied: -{z_shift:.3f} μm  (bottom now at z=0)\")\n",
    "print(f\"  Lens:       {len(lens_mesh.faces):>6} faces\")\n",
    "print(f\"  Spacer:     {len(spacer.faces):>6} faces  ({SPACER_OD} OD × {SPACER_ID} ID × {spacer_height:.2f} μm)\")\n",
    "print(f\"  Alignment:  {len(alignment.faces):>6} faces  ({ALIGN_OD} OD × {ALIGN_ID} ID × {ALIGN_HEIGHT} μm)\")\n",
    "print(f\"  Taper:      {len(taper.faces):>6} faces  ({TAPER_OD} OD, ID {ALIGN_ID}→{TAPER_OD} μm × {TAPER_HEIGHT} μm)\")\n",
    "print(f\"  Total:      {len(combined.faces):>6} faces\")\n",
    "print(f\"  Z range:    [{combined.bounds[0,2]:.3f}, {combined.bounds[1,2]:.3f}] μm\")\n",
    "\n",
    "# --- Schematic cross-section visualization (shifted to z=0 origin) ---\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 7), tight_layout=True)\n",
    "\n",
    "z_sp_bot = z_base_support - z_shift\n",
    "z_sp_top = z_sp_bot + spacer_height\n",
    "z_al_top = z_sp_top + ALIGN_HEIGHT\n",
    "z_ta_top = z_al_top + TAPER_HEIGHT\n",
    "\n",
    "\n",
    "def draw_wall(ax, r_out, r_in_b, r_in_t, zb, zt, color, label=None):\n",
    "    \"\"\"Draw cross-section walls of an annular/tapered section.\"\"\"\n",
    "    for sgn in [1, -1]:\n",
    "        xs = sgn * np.array([r_in_b, r_out, r_out, r_in_t])\n",
    "        zs = [zb, zb, zt, zt]\n",
    "        ax.fill(xs, zs, color=color, alpha=0.5,\n",
    "                label=label if sgn == 1 else None)\n",
    "\n",
    "\n",
    "# Full-scale view\n",
    "draw_wall(ax1, SPACER_OD/2, SPACER_ID/2, SPACER_ID/2,\n",
    "          z_sp_bot, z_sp_top, \"orange\", \"Spacer\")\n",
    "draw_wall(ax1, ALIGN_OD/2, ALIGN_ID/2, ALIGN_ID/2,\n",
    "          z_sp_top, z_al_top, \"green\", \"Alignment\")\n",
    "draw_wall(ax1, TAPER_OD/2, ALIGN_ID/2, TAPER_OD/2 - 0.1,\n",
    "          z_al_top, z_ta_top, \"red\", \"Taper\")\n",
    "profile_z = np.array(params) + z_sil_base - z_shift\n",
    "z_lens_base = z_sil_base - z_shift\n",
    "ax1.fill_between(ring_radii, z_lens_base, profile_z,\n",
    "                 color=\"blue\", alpha=0.6, label=\"Lens\")\n",
    "ax1.fill_between(-ring_radii, z_lens_base, profile_z,\n",
    "                 color=\"blue\", alpha=0.6)\n",
    "ax1.set_xlabel(\"x (μm)\")\n",
    "ax1.set_ylabel(\"z (μm)\")\n",
    "ax1.set_title(\"Full Assembly Cross-Section\")\n",
    "ax1.legend(loc=\"upper right\", fontsize=9)\n",
    "ax1.set_aspect(\"equal\")\n",
    "\n",
    "# Zoomed view near the lens\n",
    "draw_wall(ax2, SPACER_OD/2, SPACER_ID/2, SPACER_ID/2,\n",
    "          z_sp_bot, z_sp_top, \"orange\", \"Spacer\")\n",
    "ax2.fill_between(ring_radii, z_lens_base, profile_z,\n",
    "                 color=\"blue\", alpha=0.6, label=\"Lens\")\n",
    "ax2.fill_between(-ring_radii, z_lens_base, profile_z,\n",
    "                 color=\"blue\", alpha=0.6)\n",
    "ax2.axhline(z_sp_top, color=\"gray\", ls=\":\", alpha=0.6, label=\"Fiber face\")\n",
    "ax2.set_xlim(-30, 30)\n",
    "ax2.set_ylim(z_lens_base - 0.5, z_sp_top + 1)\n",
    "ax2.set_xlabel(\"x (μm)\")\n",
    "ax2.set_ylabel(\"z (μm)\")\n",
    "ax2.set_title(\"Lens + Spacer Base (zoomed)\")\n",
    "ax2.legend(loc=\"upper right\", fontsize=9)\n",
    "ax2.set_aspect(\"equal\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "id": "35173be0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exported lens-only STL → g:\\My Drive\\product\\v1\\tidy3d\\solid_immersion_lens_v2\\output\\stl\\sil_lens_only (2).stl\n",
      "  Faces: 8192\n",
      "  Z range: [0.000, 3.491] μm\n"
     ]
    }
   ],
   "source": [
    "# --- Export optimized lens only (no support structures) ---\n",
    "_lens_verts = np.array(vertices_from_params(params))\n",
    "_lens_mesh = trimesh.Trimesh(vertices=_lens_verts, faces=np.array(FACE_ARRAY))\n",
    "\n",
    "# Shift so bottom face sits at z=0\n",
    "_z_shift = _lens_mesh.bounds[0, 2]\n",
    "_lens_mesh.apply_translation([0, 0, -_z_shift])\n",
    "\n",
    "# Save to output/stl/ with auto-increment to avoid overwrites.\n",
    "_dst_base = \"sil_lens_only\"\n",
    "_dst = os.path.join(_STL_DIR, _dst_base + \".stl\")\n",
    "_counter = 1\n",
    "while os.path.exists(_dst):\n",
    "    _dst = os.path.join(_STL_DIR, f\"{_dst_base} ({_counter}).stl\")\n",
    "    _counter += 1\n",
    "_lens_mesh.export(_dst)\n",
    "\n",
    "print(f\"Exported lens-only STL → {_dst}\")\n",
    "print(f\"  Faces: {len(_lens_mesh.faces)}\")\n",
    "print(f\"  Z range: [{_lens_mesh.bounds[0,2]:.3f}, {_lens_mesh.bounds[1,2]:.3f}] μm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe5e3276",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "205fc736",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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