{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e134aabf",
   "metadata": {},
   "source": [
    "# Free-form chip-to-chip coupler"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0aa2f990",
   "metadata": {},
   "source": [
    "The efficient transfer of light between optical waveguides on separate chips is crucial for applications in photonic chip interfacing with optical interposers, flexible waveguide ribbons, and communication in multi-chip modules, as well as for connecting chips to optical printed circuit boards (PCBs). Historically, this inter-chip coupling has been achieved using mirrors or grating couplers. However, the mirror method faces challenges in achieving high coupling efficiency due to unavoidable wavefront distortions, while grating couplers suffer from inherent wavelength sensitivity. A new coupling scheme based on microfabricated free-form optical reflectors has been proposed, which offers low coupling loss, large bandwidth, high density, polarization diversity, and superior alignment tolerance.\n",
    "\n",
    "This notebook demonstrates the simulation and optimization of a free-form chip-to-chip coupler based on the work `S. Yu, H. Zuo, X. Sun, J. Liu, T. Gu and J. Hu, \"Optical Free-Form Couplers for High-density Integrated Photonics (OFFCHIP): A Universal Optical Interface,\" in Journal of Lightwave Technology, vol. 38, no. 13, pp. 3358-3365, 1 July, 2020.` [DOI: 10.1109/JLT.2020.2971724](https://doi.org/10.1109/JLT.2020.2971724). The coupler consists of two parabolic reflectors. The geometry is constructed using external CAD software and imported into `Tidy3D` for FDTD simulations. The initial design is based on ray optics where we assume the optical waveguide facets on both chips are located at the two focal points of the reflectors. This is not optimal due to the wave nature of light and the waveguide mode not being a point source so the positions of the waveguides are tuned to improve the insertion loss. Besides chip-to-chip coupling, this type of free-form couplers can also be used for fiber-to-chip coupling. \n",
    "\n",
    "<img src=\"img/freeform_coupler.png\" width=\"400\" alt=\"Schematic of the Free-form Coupler\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3d13ebf1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bbcd993-802b-4245-a903-7867fb14cd33",
   "metadata": {},
   "source": [
    "## Simulation Setup\n",
    "\n",
    "Define the simulation wavelength range to be 650 nm to 1050 nm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ef673905",
   "metadata": {},
   "outputs": [],
   "source": [
    "lda0 = 0.85  # central wavelength\n",
    "freq0 = td.C_0 / lda0  # central frequency\n",
    "ldas = np.linspace(0.65, 1.05, 21)  # wavelength range\n",
    "freqs = td.C_0 / ldas  # frequency range\n",
    "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))  # width of the source frequency"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce6cdf9d-5c88-48a8-9f77-5ab262f9606e",
   "metadata": {},
   "source": [
    "The free-form coupler is designed for low-contrast waveguide systems. Here we define the waveguide core and cladding materials."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0392af43",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_core = 1.543\n",
    "mat_core = td.Medium(permittivity=n_core**2)\n",
    "\n",
    "n_clad = 1.525\n",
    "mat_clad = td.Medium(permittivity=n_clad**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19141641-9dc7-4962-89dd-b07cf14985c5",
   "metadata": {},
   "source": [
    "Next, define geometric parameters for the waveguide as well as the coupler."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6cecbc9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "w_core = 2.3  # waveguide core width\n",
    "t_core = 2.3  # waveguide core thickness\n",
    "l_coupler = 40  # length of the coupler\n",
    "h_coupler = 45  # thickness of the coupler\n",
    "y_focus_1 = 0  # y coordinate of the coupler's first focus\n",
    "y_focus_2 = 25  # y coordinate of the coupler's second focus\n",
    "t_clad = (y_focus_2 - y_focus_1) / 2  # thickness of the cladding\n",
    "buffer_x = 10  # buffer spacing in x\n",
    "buffer_y = 5  # buffer spacing in y\n",
    "inf_eff = 1e3  # effective infinity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "684f23d6-6b8e-427e-b61e-39c514489e7a",
   "metadata": {},
   "source": [
    "For the best focusing performance, the free-form coupler has a parabolic shape. We used an external CAD package to create the geometry and import it into Tidy3D. The design principle is adopted from ray optics and can be found in standard optics textbooks. \n",
    "\n",
    "In fact, simply putting the waveguide facet at the focus of the parabolic coupler will not result in optimal coupling efficiency since the waveguide mode is not a point source. Therefore, the position of the coupler needs to be fine-tuned for optimal coupling efficiency. To do so, we create a function `make_structures(adjustable_spacing)` that defines the simulation structures giving the offset spacing in the $x$ direction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "43e37304",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_structures(adjustable_spacing):\n",
    "    # import coupler geometry from a stl file\n",
    "    coupler_geometry = td.TriangleMesh.from_stl(\n",
    "        filename=\"misc/chip_to_chip_coupler.stl\",\n",
    "    )\n",
    "\n",
    "    # define coupler structure\n",
    "    coupler = td.Structure(geometry=coupler_geometry, medium=mat_core)\n",
    "\n",
    "    # define the structures for additional offset in x\n",
    "    adjust_in = td.Structure(\n",
    "        geometry=td.Box(\n",
    "            center=(adjustable_spacing / 2, 0, 0),\n",
    "            size=(abs(adjustable_spacing), 2 * t_clad, td.inf),\n",
    "        ),\n",
    "        medium=mat_clad if adjustable_spacing > 0 else mat_core,\n",
    "    )\n",
    "\n",
    "    adjust_out = td.Structure(\n",
    "        geometry=td.Box(\n",
    "            center=(l_coupler - adjustable_spacing / 2, y_focus_2, 0),\n",
    "            size=(abs(adjustable_spacing), 2 * t_clad, td.inf),\n",
    "        ),\n",
    "        medium=mat_clad if adjustable_spacing > 0 else mat_core,\n",
    "    )\n",
    "\n",
    "    # define the input waveguide structure\n",
    "    waveguide_in = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-inf_eff, -t_core / 2, -w_core / 2),\n",
    "            rmax=(adjustable_spacing, t_core / 2, w_core / 2),\n",
    "        ),\n",
    "        medium=mat_core,\n",
    "    )\n",
    "\n",
    "    # define the output waveguide structure\n",
    "    waveguide_out = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(l_coupler - adjustable_spacing, y_focus_2 - t_core / 2, -w_core / 2),\n",
    "            rmax=(inf_eff, y_focus_2 + t_core / 2, w_core / 2),\n",
    "        ),\n",
    "        medium=mat_core,\n",
    "    )\n",
    "\n",
    "    # define the input waveguide cladding structure\n",
    "    clad_in = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-inf_eff, -inf_eff, -inf_eff), rmax=(adjustable_spacing, t_clad, inf_eff)\n",
    "        ),\n",
    "        medium=mat_clad,\n",
    "    )\n",
    "\n",
    "    # define the output waveguide cladding structure\n",
    "    clad_out = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(l_coupler - adjustable_spacing, y_focus_2 - t_clad, -inf_eff),\n",
    "            rmax=(inf_eff, inf_eff, inf_eff),\n",
    "        ),\n",
    "        medium=mat_clad,\n",
    "    )\n",
    "\n",
    "    if adjustable_spacing != 0:\n",
    "        return [coupler, adjust_in, adjust_out, clad_in, clad_out, waveguide_in, waveguide_out]\n",
    "    else:\n",
    "        return [coupler, clad_in, clad_out, waveguide_in, waveguide_out]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4175b6b-7efd-452c-81bd-ed006686a5ad",
   "metadata": {},
   "source": [
    "Next we define the source and monitors. Then put everything into a Tidy3D [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html) object. To facilitate parameter sweep to optimize the coupling efficiency, we put everything into a function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "201cbd15",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_sim(adjustable_spacing):\n",
    "    # add a mode source as excitation\n",
    "    mode_spec = td.ModeSpec(num_modes=1, target_neff=n_core)\n",
    "    mode_source = td.ModeSource(\n",
    "        center=(adjustable_spacing - 0.9 * buffer_x, 0, 0),\n",
    "        size=(0, 5 * t_core, 5 * w_core),\n",
    "        source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "        direction=\"+\",\n",
    "        mode_spec=mode_spec,\n",
    "        mode_index=0,\n",
    "        num_freqs=7,\n",
    "    )\n",
    "\n",
    "    # add a mode monitor to measure transmission at the output waveguide\n",
    "    mode_monitor = td.ModeMonitor(\n",
    "        center=(l_coupler - adjustable_spacing + 0.9 * buffer_x, y_focus_2, 0),\n",
    "        size=mode_source.size,\n",
    "        freqs=freqs,\n",
    "        mode_spec=mode_spec,\n",
    "        name=\"mode\",\n",
    "    )\n",
    "\n",
    "    # add a field monitor to visualize field distribution at z=t/2\n",
    "    field_monitor = td.FieldMonitor(\n",
    "        center=(0, 0, 0), size=(td.inf, td.inf, 0), freqs=[freq0], name=\"field\"\n",
    "    )\n",
    "\n",
    "    # simulation domain box\n",
    "    sim_box = td.Box.from_bounds(\n",
    "        rmin=(adjustable_spacing - buffer_x, y_focus_1 - buffer_y, -2 * w_core),\n",
    "        rmax=(l_coupler - adjustable_spacing + buffer_x, y_focus_2 + buffer_y, 2 * w_core),\n",
    "    )\n",
    "\n",
    "    run_time = 1e-12  # simulation run time\n",
    "\n",
    "    # define simulation\n",
    "    sim = td.Simulation(\n",
    "        center=sim_box.center,\n",
    "        size=sim_box.size,\n",
    "        grid_spec=td.GridSpec.auto(min_steps_per_wvl=10, wavelength=lda0),\n",
    "        structures=make_structures(adjustable_spacing),\n",
    "        sources=[mode_source],\n",
    "        monitors=[mode_monitor, field_monitor],\n",
    "        run_time=run_time,\n",
    "        boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "        symmetry=(0, 0, -1),\n",
    "    )\n",
    "\n",
    "    return sim"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd330955-3129-46be-8faf-89867772f54e",
   "metadata": {},
   "source": [
    "Visualize the simulation using an arbitrary parameter to verify everything is set up properly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9b376ce9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim = make_sim(adjustable_spacing=2)\n",
    "sim.plot(z=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ccf2a71-4a75-4dce-af7b-faf75e68e0a9",
   "metadata": {},
   "source": [
    "## Parameter Sweep\n",
    "\n",
    "Now we are ready to perform the parameter sweep and monitor the coupling efficiency as a function of the $x$ offset. Since this is just a simple parameter sweep over one variable, we will use the batch feature in Tidy3D. For more complex parameter sweep and design parameter space exploration, we recommend using Tidy3D's [design plugin](https://www.flexcompute.com/tidy3d/examples/notebooks/Design/) as demonstrated in this [example](https://www.flexcompute.com/tidy3d/examples/notebooks/AllDielectricStructuralColor/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1bda9791",
   "metadata": {},
   "outputs": [],
   "source": [
    "# parameter sweep range\n",
    "adjustable_spacing_list = np.linspace(-1, 4, 6)\n",
    "\n",
    "# create a batch and run it\n",
    "sims = {\n",
    "    f\"{adjustable_spacing:.1f} μm\": make_sim(adjustable_spacing)\n",
    "    for adjustable_spacing in adjustable_spacing_list\n",
    "}\n",
    "batch = web.Batch(simulations=sims, verbose=False)\n",
    "batch_results = batch.run(path_dir=\"data\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1d51c34-e961-47ca-902d-c55ad0f8805b",
   "metadata": {},
   "source": [
    "From the plotted results, we see that the coupling efficiency is around 0.5 dB for 3 or 4 μm offset in the $x$ direction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "85248ba1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# extract and plot coupling efficiencies from all simulations\n",
    "for adjustable_spacing in adjustable_spacing_list:\n",
    "    sim_data = batch_results[f\"{adjustable_spacing} μm\"]\n",
    "    T = np.abs(sim_data[\"mode\"].amps.sel(direction=\"+\").values) ** 2\n",
    "\n",
    "    plt.plot(ldas, 10 * np.log10(T), linewidth=2, label=f\"{adjustable_spacing} μm\")\n",
    "\n",
    "plt.xlabel(\"Wavelength (μm)\")\n",
    "plt.ylabel(\"Coupling efficiency (dB)\")\n",
    "plt.xlim(min(ldas), max(ldas))\n",
    "plt.ylim(-3, 0)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cba54d64-617c-43a4-b45e-6947fbf308e8",
   "metadata": {},
   "source": [
    "Finally, visualize the field intensity distribution for the optimal coupling efficiency. \n",
    "\n",
    "Additional optimization can be done by further fine tuning the parabolic reflector shape. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d5fa825e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "batch_results[\"3.0 μm\"].plot_field(\n",
    "    field_monitor_name=\"field\", field_name=\"E\", val=\"abs^2\", eps_alpha=0.2, vmin=0, vmax=200\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "66ce4344-fe23-4959-bb33-f11d5b6092f2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "applications": [
   "Passive photonic integrated circuit components"
  ],
  "description": "This notebook demonstrates how to model a free-form coupler in Tidy3D FDTD.",
  "feature_image": "./img/freeform_coupler.png",
  "features": [
   "STL component",
   "Parameter sweep"
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "integrated photonics, coupler, waveguide, Tidy3D, FDTD",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.2"
  },
  "title": "Free-form Chip-to-chip Coupler Modeling in Tidy3D | Flexcompute"
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
