BroadbandDirectionalCoupler.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "36ff66e5",
   "metadata": {},
   "source": [
    "# Broadband directional coupler"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05954108",
   "metadata": {},
   "source": [
    "In the rapidly evolving field of silicon integrated photonics, the directional coupler (DC) stands out as a crucial building block for a multitude of applications, such as optical signal processing, sensing, and communication systems. As a passive device, a DC allows for the precise manipulation and distribution of light between two parallel waveguides within close proximity, enabling highly efficient and compact coupling with minimal loss. This elegant, yet simple structure capitalizes on the waveguiding properties of silicon, leveraging the evanescent coupling between the propagating modes to achieve precise control over the flow of optical power, thereby playing a pivotal role in shaping the future of photonic integrated circuits.\n",
    "\n",
    "Conventional compact DCs often face limitations in terms of narrow bandwidth, while broadband designs tend to require a significantly larger footprint. This document explores a design for compact, broadband DCs, as proposed in `Zeqin Lu, Han Yun, Yun Wang, Zhitian Chen, Fan Zhang, Nicolas A. F. Jaeger, and Lukas Chrostowski, \"Broadband silicon photonic directional coupler using asymmetric-waveguide based phase control,\" Opt. Express 23, 3795-3808 (2015)`, [DOI: 10.1364/OE.23.003795](https://doi.org/10.1364/OE.23.003795). The key innovation in this design, as compared to traditional DCs, lies in its incorporation of an asymmetric-waveguide-based phase control section. To demonstrate a concrete example, we will design a 2x2 DC for the TE mode, with a 50%/50% (-3 dB) splitting ratio, operating within the 1500 nm to 1600 nm range. Different polarizations and splitting ratios can be achieved in a similar design process.\n",
    "\n",
    "Initially, we employ the transfer matrix method (TMM) to model the DC in a semi-analytical manner. TMM necessitates the calculation of effective indices for various waveguide configurations, for which we utilize Tidy3D's [waveguide plugin](https://www.flexcompute.com/tidy3d/examples/notebooks/WaveguidePluginDemonstration/), as it offers a convenient means of performing mode analysis. TMM provides a computationally efficient and accurate preliminary estimation of the ideal design parameters, which are then further optimized using rigorous 3D FDTD simulations. \n",
    "\n",
    "<img src=\"img/broadband_DC_1.png\" width=\"500\" alt=\"Schematic of the DC\">\n",
    "\n",
    "For more integrated photonic examples such as the [8-Channel mode and polarization de-multiplexer](https://www.flexcompute.com/tidy3d/examples/notebooks/8ChannelDemultiplexer/), the [broadband bi-level taper polarization rotator-splitter](https://www.flexcompute.com/tidy3d/examples/notebooks/BilevelPSR/), and the [90 degree optical hybrid](https://www.flexcompute.com/tidy3d/examples/notebooks/90OpticalHybrid/), please visit our [examples page](https://www.flexcompute.com/tidy3d/examples/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2dccd831",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:24:22.153290Z",
     "iopub.status.busy": "2023-08-18T17:24:22.152697Z",
     "iopub.status.idle": "2023-08-18T17:24:23.538790Z",
     "shell.execute_reply": "2023-08-18T17:24:23.538195Z"
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   "outputs": [],
   "source": [
    "import gdstk\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n",
    "from tidy3d.plugins import waveguide"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e767be29",
   "metadata": {},
   "source": [
    "## Transfer Matrix Method (TMM) Analysis "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41c9cdc2",
   "metadata": {},
   "source": [
    "The broadband DC primarily consists of a symmetric coupler, an asymmetric phase control section, and another symmetric coupler. The three sections are connected via linear tapers. The inputs and outputs are from 90 degree circular bends. \n",
    "\n",
    "We can use TMM to analyze this system. Assuming the input and output fields on the waveguide are $E_1$, $E_2$, $E_3$, and $E_4$, each section of the DC can be represented by a matrix. That is, we can write down the following equation that connects the input and output fields:\n",
    "\n",
    "$\\begin{bmatrix}E_3\\\\E_4\\end{bmatrix} = C \\cdot P_t \\cdot P \\cdot P_t \\cdot C \\cdot \\begin{bmatrix} E_1\\\\E_2 \\end{bmatrix}$.\n",
    "\n",
    "$C =\\begin{bmatrix}t & -jk\\\\-jk & t\\end{bmatrix} e^{-j\\frac{\\pi}{\\lambda}(n_++n_-)L_1}$ represents the symmetric coupler. $t$ and $k$ are the transmission and coupling coefficients given by $t = cos(\\frac{\\pi\\Delta n_{eff}}{\\lambda}L_1) $ and $k = sin(\\frac{\\pi\\Delta n_{eff}}{\\lambda}L_1) $, where $\\Delta n_{eff}=n_+-n_-$. $n_+$ and $n_-$ are the effective indices of the symmetric and anti-symmetric modes, which we will determine from mode analysis using the [waveguide plugin](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.waveguide.RectangularDielectric.html). \n",
    "\n",
    "$P = \\begin{bmatrix}e^{-j\\frac{2\\pi n_1}{\\lambda}L_2} & 0\\\\0 & e^{-j\\frac{2\\pi n_2}{\\lambda}L_2}\\end{bmatrix}$ represents the asymmetric phase control section. Here $n_1$ and $n_2$ are the effective indices of the lowest order modes, which correspond to modes confined in the top waveguide and bottom waveguide, respectively. We will determine $n_1$ and $n_2$ from mode analysis too.\n",
    "\n",
    "Lastly, $P_t = \\begin{bmatrix}e^{-j\\theta_{t1}} & 0\\\\0 & e^{-j\\theta_{t2}}\\end{bmatrix}$ approximately represents the linear tapers. $\\theta_{t1}$ and $\\theta_{t2}$ are the phase shifts in the top and bottom tapers, which we will determine numerically from quick FDTD simulations. \n",
    "\n",
    "In the [reference](https://opg.optica.org/oe/fulltext.cfm?uri=oe-23-3-3795), a small propagation loss of 2.7 dB/cm is also considered. Since this is a small factor, we choose to ignore it in the analysis without a significant loss of accuracy. \n",
    "\n",
    "After we perform the TMM calculation, we can determine the power splitting ratio by $\\eta_{cross} = \\frac{|E_4|^2}{|E_3|^2+|E_4|^2}$ and $\\eta_{through} = \\frac{|E_3|^2}{|E_3|^2+|E_4|^2}$, assuming the input field is $\\begin{bmatrix}E_1\\\\0\\end{bmatrix}$.\n",
    "\n",
    "\n",
    "<img src=\"img/broadband_DC_2.png\" width=\"700\" alt=\"Top view of the DC\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc4c6b5f",
   "metadata": {},
   "source": [
    "We are interested in the wavelength range of 1500 nm to 1600 nm. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "41aad3b8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:24:23.541364Z",
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     "shell.execute_reply": "2023-08-18T17:24:23.559535Z"
    }
   },
   "outputs": [],
   "source": [
    "lda0 = 1.55  # central wavelength\n",
    "ldas = np.linspace(1.5, 1.6, 101)  # wavelength range of interest\n",
    "freq0 = td.C_0 / lda0  # central frequency\n",
    "freqs = td.C_0 / ldas  # frequency range of interest\n",
    "fwidth = 0.4 * (np.max(freqs) - np.min(freqs))  # frequency width of the source"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a027789e",
   "metadata": {},
   "source": [
    "The silicon layer is 220 nm. The waveguide width and gap size in the symmetric coupler are 500 nm and 200 nm, respectively.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8cc7ec56",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:24:23.562386Z",
     "iopub.status.busy": "2023-08-18T17:24:23.562219Z",
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     "shell.execute_reply": "2023-08-18T17:24:23.579823Z"
    }
   },
   "outputs": [],
   "source": [
    "w_sc = 0.5  # width of waveguides in the symmetric coupler section\n",
    "h_si = 0.22  # thickness of the silicon layer\n",
    "gap_sc = 0.2  # gap size between the waveguides in the symmetric coupler section"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60f8be20",
   "metadata": {},
   "source": [
    "To define the media, we directly use the dispersive medium model of silicon and oxide from Tidy3D's [material library](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/material_library.html) for convenience. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "de4b86dc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:24:23.582412Z",
     "iopub.status.busy": "2023-08-18T17:24:23.582246Z",
     "iopub.status.idle": "2023-08-18T17:24:23.600018Z",
     "shell.execute_reply": "2023-08-18T17:24:23.599455Z"
    }
   },
   "outputs": [],
   "source": [
    "# define silicon and silicon dioxide media from material library\n",
    "si = td.material_library[\"cSi\"][\"Li1993_293K\"]\n",
    "sio2 = td.material_library[\"SiO2\"][\"Horiba\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fdf1ec5",
   "metadata": {},
   "source": [
    "Now we use the [waveguide plugin](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.waveguide.RectangularDielectric.html) to perform the mode analysis on the symmetric coupler. Alternatively, one can use the [ModeSolver](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.mode.ModeSolver.html) plugin to do the same analysis. The [waveguide plugin](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.waveguide.RectangularDielectric.html) just provides a fast and convenient way of setting up the mode analysis for dielectric waveguides. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "64f4ad0c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:24:23.602038Z",
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     "shell.execute_reply": "2023-08-18T17:24:23.844521Z"
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   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define the symmetric coupler section\n",
    "symmetric_coupler = waveguide.RectangularDielectric(\n",
    "    wavelength=lda0,\n",
    "    core_width=(w_sc, w_sc),\n",
    "    core_thickness=h_si,\n",
    "    core_medium=si,\n",
    "    clad_medium=sio2,\n",
    "    gap=gap_sc,\n",
    "    grid_resolution=40,\n",
    "    mode_spec=td.ModeSpec(num_modes=5, precision=\"double\"),\n",
    ")\n",
    "\n",
    "# plot the cross section\n",
    "symmetric_coupler.plot_structures(x=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25d4c6bd",
   "metadata": {},
   "source": [
    "The effective indices of different modes can be directly calculated. The corresponding mode profiles can be visualized. Here we focus on the two lowest order modes, which are the symmetric and anti-symmetric modes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f6ac9551",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:24:23.847840Z",
     "iopub.status.busy": "2023-08-18T17:24:23.847662Z",
     "iopub.status.idle": "2023-08-18T17:24:38.311635Z",
     "shell.execute_reply": "2023-08-18T17:24:38.311069Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Effective indices: 2.4591626285320944, 2.4382152325151867\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compute the effective indices for the symmetric and anti-symmetric modes\n",
    "n_p = symmetric_coupler.n_eff.values[0][0]\n",
    "n_m = symmetric_coupler.n_eff.values[0][1]\n",
    "del_n = n_p - n_m\n",
    "print(f\"Effective indices: {n_p}, {n_m}\")\n",
    "\n",
    "# plot the mode profiles\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4), tight_layout=True)\n",
    "\n",
    "symmetric_coupler.plot_field(\"Ey\", mode_index=0, ax=ax1)\n",
    "symmetric_coupler.plot_field(\"Ey\", mode_index=1, ax=ax2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2b25d5e",
   "metadata": {},
   "source": [
    "After obtaining $n_+$ and $n_-$, we will calculate $n_1$ and $n_2$ in a similar fashion for the phase control section, where the waveguide widths are 600 nm and 400 nm. The gap is 300 nm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "95794c46",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:24:38.313583Z",
     "iopub.status.busy": "2023-08-18T17:24:38.313398Z",
     "iopub.status.idle": "2023-08-18T17:24:38.486481Z",
     "shell.execute_reply": "2023-08-18T17:24:38.485952Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w_top = 0.6  # width of the top waveguide in the phase control section\n",
    "w_bottom = 0.4  # width of the bottom waveguide in the phase control section\n",
    "gap_pc = 0.3  # gap size in the phase control section\n",
    "\n",
    "# define the phase control section\n",
    "phase_control = waveguide.RectangularDielectric(\n",
    "    wavelength=lda0,\n",
    "    core_width=(w_top, w_bottom),\n",
    "    core_thickness=h_si,\n",
    "    core_medium=si,\n",
    "    clad_medium=sio2,\n",
    "    gap=gap_pc,\n",
    "    grid_resolution=40,\n",
    "    mode_spec=td.ModeSpec(num_modes=2, precision=\"double\"),\n",
    ")\n",
    "\n",
    "# plot the cross section\n",
    "phase_control.plot_structures(x=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a91d6a5d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:24:38.488603Z",
     "iopub.status.busy": "2023-08-18T17:24:38.488459Z",
     "iopub.status.idle": "2023-08-18T17:24:49.772566Z",
     "shell.execute_reply": "2023-08-18T17:24:49.771964Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Effective indices: 2.568245448653179, 2.217684204007138\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compute the effective indices for the first two modes\n",
    "n_1 = phase_control.n_eff.values[0][0]\n",
    "n_2 = phase_control.n_eff.values[0][1]\n",
    "print(f\"Effective indices: {n_1}, {n_2}\")\n",
    "\n",
    "# plot the mode profiles\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4), tight_layout=True)\n",
    "\n",
    "phase_control.plot_field(\"Ey\", mode_index=0, ax=ax1)\n",
    "phase_control.plot_field(\"Ey\", mode_index=1, ax=ax2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50fa4702",
   "metadata": {},
   "source": [
    "To perform the TMM analysis, we still need to obtain $\\theta_{t1}$ and $\\theta_{t2}$. This can be done by setting up FDTD simulations for the tapers. To get the phase shift, we place one [ModeMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeMonitor.html) right before the taper and another [ModeMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModeMonitor.html) right after the taper. The phase difference calculated from the mode amplitudes is the phase shift we are looking for. Since the tapers are only 1 $\\mu m$ in length, the FDTD simulations are very fast.\n",
    "\n",
    "First, let's do the top taper that transitions from a 500 nm waveguide to a 600 nm waveguide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fd2a853f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:24:49.775054Z",
     "iopub.status.busy": "2023-08-18T17:24:49.774897Z",
     "iopub.status.idle": "2023-08-18T17:24:49.796044Z",
     "shell.execute_reply": "2023-08-18T17:24:49.795521Z"
    }
   },
   "outputs": [],
   "source": [
    "L_t = 1  # length of the tapers\n",
    "l = 10  # length of the straight waveguide\n",
    "\n",
    "# define vertices\n",
    "vertices = [(-l, 0), (L_t + l, 0), (L_t + l, w_top), (L_t, w_top), (0, w_sc), (-l, w_sc)]\n",
    "\n",
    "# define the top taper structure\n",
    "taper_top = td.Structure(\n",
    "    geometry=td.PolySlab(\n",
    "        vertices=vertices,\n",
    "        axis=2,\n",
    "        slab_bounds=(-h_si / 2, h_si / 2),\n",
    "    ),\n",
    "    medium=si,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9faea023",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:24:49.798519Z",
     "iopub.status.busy": "2023-08-18T17:24:49.798373Z",
     "iopub.status.idle": "2023-08-18T17:24:50.016716Z",
     "shell.execute_reply": "2023-08-18T17:24:50.016123Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# simulation domain size\n",
    "Lx = L_t + l / 2\n",
    "Ly = 5 * w_sc\n",
    "Lz = 9 * h_si\n",
    "\n",
    "# define a mode source that injects te mode\n",
    "mode_spec = td.ModeSpec(num_modes=1, target_neff=3.47)\n",
    "mode_source = td.ModeSource(\n",
    "    center=(-l / 5, w_sc / 2, 0),\n",
    "    size=(0, Ly, 4 * h_si),\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",
    "# define a mode monitor to measure the phase before the taper\n",
    "mode_monitor_1 = td.ModeMonitor(\n",
    "    center=(0, w_sc / 2, 0),\n",
    "    size=(0, Ly, 4 * h_si),\n",
    "    freqs=freqs,\n",
    "    mode_spec=mode_spec,\n",
    "    name=\"mode_1\",\n",
    ")\n",
    "\n",
    "# define a mode monitor to measure the phase after the taper\n",
    "mode_monitor_2 = td.ModeMonitor(\n",
    "    center=(L_t, w_top / 2, 0),\n",
    "    size=(0, Ly, 4 * h_si),\n",
    "    freqs=freqs,\n",
    "    mode_spec=mode_spec,\n",
    "    name=\"mode_2\",\n",
    ")\n",
    "\n",
    "run_time = 4e-13  # simulation run time\n",
    "\n",
    "# define a simulation\n",
    "sim = td.Simulation(\n",
    "    center=(0, w_sc / 2, 0),\n",
    "    size=(Lx, Ly, Lz),\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=20, wavelength=lda0),\n",
    "    structures=[taper_top],\n",
    "    sources=[mode_source],\n",
    "    monitors=[mode_monitor_1, mode_monitor_2],\n",
    "    run_time=run_time,\n",
    "    medium=sio2,\n",
    ")\n",
    "\n",
    "# plot simulation\n",
    "sim.plot(z=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "71c60cd6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:24:50.019115Z",
     "iopub.status.busy": "2023-08-18T17:24:50.018961Z",
     "iopub.status.idle": "2023-08-18T17:26:01.607027Z",
     "shell.execute_reply": "2023-08-18T17:26:01.606376Z"
    }
   },
   "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\">17:58:14 Eastern Standard Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'top_taper'</span> with task_id            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b'</span> and  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:58:14 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'top_taper'\u001b[0m with task_id            \n",
       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b'\u001b[0m and  \n",
       "\u001b[2;36m                               \u001b[0mtask_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-21eef95a-2a4d-47ee-bc37-edeedbb0834b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b'</span></a>.     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=293190;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=619830;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=293190;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=443988;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=293190;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\u001b\\\u001b[32m-21eef95a-2a4d-47ee-bc37-edeedbb0834b'\u001b[0m\u001b]8;;\u001b\\.     \n"
      ]
     },
     "metadata": {},
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    },
    {
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">17:58:22 Eastern Standard Time </span>status = queued                                  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:58:22 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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       "Output()"
      ]
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     "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\">17:58:26 Eastern Standard Time </span>status = preprocess                              \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:58:26 Eastern Standard 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\">17:58:33 Eastern Standard Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.039</span>. 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;36m17:58:33 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.039\u001b[0m. 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>starting up solver                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \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\">                               </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> or \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>abort/delete the task in the web UI. Terminating \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>the Python script will not stop the job running  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>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 or \n",
       "\u001b[2;36m                               \u001b[0mabort/delete the task in the web UI. Terminating \n",
       "\u001b[2;36m                               \u001b[0mthe Python script will not stop the job running  \n",
       "\u001b[2;36m                               \u001b[0mon the cloud.                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">17:59:10 Eastern Standard Time </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">84</span>%, exiting.          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:59:10 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m84\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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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>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": {
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       "model_id": "",
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">17:59:15 Eastern Standard Time </span>status = success                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:59:15 Eastern Standard 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\">17:59:16 Eastern Standard 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-21eef95a-2a4d-47ee-bc37-edeedbb0834b\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:59:16 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                        \n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=607489;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=45622;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=607489;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=301836;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=607489;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21eef95a-2a4d-47ee-bc37-edeedbb0834b\u001b\\\u001b[4;34m-21eef95a-2a4d-47ee-bc37-edeedbb0834b'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m     \n"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
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       "model_id": "9aae40771d6f4569a9a46cb4d8bfd004",
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">17:59:17 Eastern Standard Time </span>loading simulation from data/simulation_data.hdf5\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:59:17 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/simulation_data.hdf5\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"top_taper\")\n",
    "sim_data = job.run(path=\"data/simulation_data.hdf5\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2afb87ea",
   "metadata": {},
   "source": [
    "Compute and plot $\\theta_{t1}$. As expected, the phase shift is linear. Note that the phase is only significant mod 2$\\pi$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "477b3a7f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:26:02.847293Z",
     "iopub.status.busy": "2023-08-18T17:26:02.847160Z",
     "iopub.status.idle": "2023-08-18T17:26:03.020429Z",
     "shell.execute_reply": "2023-08-18T17:26:03.019898Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# phase at the first monitor\n",
    "phase_1 = np.angle(sim_data[\"mode_1\"].amps.sel(mode_index=0, direction=\"+\"))\n",
    "\n",
    "# phase at the second monitor\n",
    "phase_2 = np.angle(sim_data[\"mode_2\"].amps.sel(mode_index=0, direction=\"+\"))\n",
    "\n",
    "# phase shift at the top taper\n",
    "theta_t1 = phase_2 - phase_1\n",
    "\n",
    "plt.plot(ldas, np.unwrap(theta_t1))\n",
    "plt.xlabel(r\"$\\lambda (\\mu m)$\")\n",
    "plt.ylabel(\"Phase shift\")\n",
    "plt.xlim(1.5, 1.6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99074deb",
   "metadata": {},
   "source": [
    "Similarly, we simulate the taper that transitions from a 500 nm waveguide to a 300 nm waveguide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "eb2a75e0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:26:03.022431Z",
     "iopub.status.busy": "2023-08-18T17:26:03.022285Z",
     "iopub.status.idle": "2023-08-18T17:26:03.232286Z",
     "shell.execute_reply": "2023-08-18T17:26:03.231661Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define vertices\n",
    "vertices = [(-l, 0), (L_t + l, 0), (L_t + l, w_bottom), (L_t, w_bottom), (0, w_sc), (-l, w_sc)]\n",
    "\n",
    "# define the bottom taper structure\n",
    "taper_bottom = td.Structure(\n",
    "    geometry=td.PolySlab(\n",
    "        vertices=vertices,\n",
    "        axis=2,\n",
    "        slab_bounds=(-h_si / 2, h_si / 2),\n",
    "    ),\n",
    "    medium=si,\n",
    ")\n",
    "\n",
    "# copy previous simulation and update the structure\n",
    "sim = sim.copy(update={\"structures\": [taper_bottom]})\n",
    "sim.plot(z=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb906ac6",
   "metadata": {},
   "source": [
    "Compute and plot $\\theta_{t2}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5b2f6267",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:26:03.235103Z",
     "iopub.status.busy": "2023-08-18T17:26:03.234826Z",
     "iopub.status.idle": "2023-08-18T17:27:45.900957Z",
     "shell.execute_reply": "2023-08-18T17:27:45.900371Z"
    }
   },
   "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\">                               </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'bottom_taper'</span> with task_id         \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3'</span> and  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'bottom_taper'\u001b[0m with task_id         \n",
       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3'\u001b[0m and  \n",
       "\u001b[2;36m                               \u001b[0mtask_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-57a68fa9-6867-4d11-a985-e98592cdf6b3\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3'</span></a>.     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=292069;https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=276058;https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=292069;https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=116125;https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=292069;https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\u001b\\\u001b[32m-57a68fa9-6867-4d11-a985-e98592cdf6b3'\u001b[0m\u001b]8;;\u001b\\.     \n"
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       "Output()"
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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": {},
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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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">17:59:19 Eastern Standard Time </span>status = queued                                  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:59:19 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                  \n"
      ]
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     "metadata": {},
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    },
    {
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       "Output()"
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     "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\">17:59:23 Eastern Standard Time </span>status = preprocess                              \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m17:59:23 Eastern Standard 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": {},
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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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">17:59:29 Eastern Standard Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.039</span>. 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;36m17:59:29 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.039\u001b[0m. 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": {},
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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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>starting up solver                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \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\">                               </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> or \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>abort/delete the task in the web UI. Terminating \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>the Python script will not stop the job running  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>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 or \n",
       "\u001b[2;36m                               \u001b[0mabort/delete the task in the web UI. Terminating \n",
       "\u001b[2;36m                               \u001b[0mthe Python script will not stop the job running  \n",
       "\u001b[2;36m                               \u001b[0mon the cloud.                                    \n"
      ]
     },
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       "Output()"
      ]
     },
     "metadata": {},
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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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">18:00:06 Eastern Standard Time </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">84</span>%, exiting.          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m18:00:06 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m84\u001b[0m%, exiting.          \n"
      ]
     },
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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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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>status = postprocess                             \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                             \n"
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       "Output()"
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     "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\">18:00:11 Eastern Standard Time </span>status = success                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m18:00:11 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                 \n"
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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"
      ],
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     },
     "metadata": {},
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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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View simulation result at                        \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                        \n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=867861;https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=245806;https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=867861;https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=698108;https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=867861;https://tidy3d.simulation.cloud/workbench?taskId=fdve-57a68fa9-6867-4d11-a985-e98592cdf6b3\u001b\\\u001b[4;34m-57a68fa9-6867-4d11-a985-e98592cdf6b3'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m     \n"
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       "Output()"
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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\"></pre>\n"
      ],
      "text/plain": []
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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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
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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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">18:00:12 Eastern Standard Time </span>loading simulation from data/simulation_data.hdf5\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m18:00:12 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/simulation_data.hdf5\n"
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    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"bottom_taper\")\n",
    "sim_data = job.run(path=\"data/simulation_data.hdf5\")\n",
    "\n",
    "# calculate phase shift\n",
    "phase_1 = np.angle(sim_data[\"mode_1\"].amps.sel(mode_index=0, direction=\"+\"))\n",
    "phase_2 = np.angle(sim_data[\"mode_2\"].amps.sel(mode_index=0, direction=\"+\"))\n",
    "theta_t2 = phase_2 - phase_1\n",
    "\n",
    "plt.plot(ldas, np.unwrap(theta_t2))\n",
    "plt.xlabel(r\"$\\lambda (\\mu m)$\")\n",
    "plt.ylabel(\"Phase shift\")\n",
    "plt.xlim(1.5, 1.6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09f10e0f",
   "metadata": {},
   "source": [
    "Now that we have calculated $n_+$, $n_-$, $n_1$, $n_2$, $\\theta_{t1}$, and $\\theta_{t2}$, we are ready to assemble the matrices and calculate $\\eta_{cross}$. First, we focus on the wavelength of 1550 nm and explore $\\eta_{cross}$ as a function of $L_1$ and $L_2$. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c421aead",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:27:47.608648Z",
     "iopub.status.busy": "2023-08-18T17:27:47.608509Z",
     "iopub.status.idle": "2023-08-18T17:27:47.725510Z",
     "shell.execute_reply": "2023-08-18T17:27:47.724909Z"
    }
   },
   "outputs": [],
   "source": [
    "# input field vector\n",
    "E_in = np.array([[0], [1]])\n",
    "\n",
    "N_L1 = 100  # number of L_1 points\n",
    "N_L2 = 50  # number of L_2 points\n",
    "L_1_array = np.linspace(4, 20, N_L1)\n",
    "L_2_array = np.linspace(1, 6, N_L2)\n",
    "\n",
    "eta_cross_1550 = np.zeros((N_L1, N_L2))\n",
    "\n",
    "# compute the taper matrix\n",
    "P_t = np.array([[np.exp(-1j * theta_t1[50]), 0], [0, np.exp(-1j * theta_t2[50])]]) * np.exp(-0.5)\n",
    "\n",
    "for i, L_1 in enumerate(L_1_array):\n",
    "    for j, L_2 in enumerate(L_2_array):\n",
    "        # compute the transmission coefficient\n",
    "        t = np.cos(np.pi * del_n * L_1 / lda0)\n",
    "        # compute the coupling coefficient\n",
    "        k = np.sin(np.pi * del_n * L_1 / lda0)\n",
    "        # compute the symmetric coupler matrix\n",
    "        C = np.exp(-1j * np.pi * (n_p + n_m) * L_1 / lda0) * np.array([[t, -1j * k], [-1j * k, t]])\n",
    "        # compute the phase control section matrix\n",
    "        P = np.array(\n",
    "            [\n",
    "                [np.exp(-1j * 2 * np.pi * n_1 * L_2 / lda0), 0],\n",
    "                [0, np.exp(-1j * 2 * np.pi * n_2 * L_2 / lda0)],\n",
    "            ]\n",
    "        )\n",
    "        # compute the output field vector by tmm\n",
    "        E_out = np.dot(C, np.dot(P_t, np.dot(P, np.dot(P_t, np.dot(C, E_in)))))\n",
    "\n",
    "        # total transmission\n",
    "        T = np.abs(E_out[0, 0]) ** 2 + np.abs(E_out[1, 0]) ** 2\n",
    "        # power transmitted to the cross port\n",
    "        eta_cross_1550[i, j] = np.abs(E_out[0, 0]) ** 2 / T"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6844319d",
   "metadata": {},
   "source": [
    "Plot $\\eta_{cross}$ as a function of $L_1$ and $L_2$. Since we are looking for a specific power splitting ratio, we add contours to the plot. For a desirable splitting ratio, one only needs to pick design parameters on the specific contour. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ed1a9fbb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:27:47.727557Z",
     "iopub.status.busy": "2023-08-18T17:27:47.727406Z",
     "iopub.status.idle": "2023-08-18T17:27:48.096562Z",
     "shell.execute_reply": "2023-08-18T17:27:48.096056Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the power transmitted to the cross port as a function of L_1 and L_2\n",
    "cp = plt.contour(\n",
    "    L_2_array,\n",
    "    L_1_array,\n",
    "    eta_cross_1550,\n",
    "    levels=10,\n",
    "    colors=\"black\",\n",
    "    linestyles=\"dashed\",\n",
    "    linewidths=1,\n",
    ")\n",
    "plt.clabel(cp, inline=1, fontsize=10)\n",
    "cp = plt.contourf(L_2_array, L_1_array, eta_cross_1550, levels=100, vmin=0, vmax=1, cmap=\"bwr\")\n",
    "plt.xlabel(r\"$L_2 (\\mu m)$\")\n",
    "plt.ylabel(r\"$L_1 (\\mu m)$\")\n",
    "plt.title(\"Transmission to cross port\")\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "187383d2",
   "metadata": {},
   "source": [
    "In this case, we aim for a 50%/50% splitting ratio. Since we want the DC to work in a wide wavelength range, we also need to calculate $\\eta_{cross}$ at other wavelengths to make sure the same splitting ratio is maintained. Here we skip explicitly showing this step to avoid making the notebook excessively long. \n",
    "\n",
    "From this analysis, the optimal $L_1$ and $L_2$ are found to be 12.8 $\\mu m$ and 4.4 $\\mu m$. Now we fix $L_1$ and $L_2$ and calculate $\\eta_{cross}$ as a function of wavelength."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "64de03ca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:27:48.100431Z",
     "iopub.status.busy": "2023-08-18T17:27:48.100226Z",
     "iopub.status.idle": "2023-08-18T17:27:48.123865Z",
     "shell.execute_reply": "2023-08-18T17:27:48.123440Z"
    }
   },
   "outputs": [],
   "source": [
    "L_1 = 12.8  # optimal L_1 from the tmm analysis\n",
    "L_2 = 4.4  # optimal L_2 from the tmm analysis\n",
    "\n",
    "# compute power transmitted to the cross port as a function of wavelength\n",
    "eta_cross_ldas = np.zeros(len(ldas))\n",
    "for i, lda in enumerate(ldas):\n",
    "    t = np.cos(np.pi * del_n * L_1 / lda)\n",
    "    k = np.sin(np.pi * del_n * L_1 / lda)\n",
    "    C = np.exp(-1j * np.pi * (n_p + n_m) * L_1 / lda) * np.array([[t, -1j * k], [-1j * k, t]])\n",
    "\n",
    "    P = np.array(\n",
    "        [\n",
    "            [np.exp(-1j * 2 * np.pi * n_1 * L_2 / lda), 0],\n",
    "            [0, np.exp(-1j * 2 * np.pi * n_2 * L_2 / lda)],\n",
    "        ]\n",
    "    )\n",
    "\n",
    "    E_out = np.dot(C, np.dot(P_t, np.dot(P, np.dot(P_t, np.dot(C, E_in)))))\n",
    "\n",
    "    T = np.abs(E_out[0, 0]) ** 2 + np.abs(E_out[1, 0]) ** 2\n",
    "    eta_cross_ldas[i] = np.abs(E_out[0, 0]) ** 2 / T"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c30801d8",
   "metadata": {},
   "source": [
    "Plot $\\eta_{cross}$ as a function of wavelength. Here we can see if we define +- 1 dB as the bandwidth, the bandwidth is larger then 100 nm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d747859c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:27:48.125803Z",
     "iopub.status.busy": "2023-08-18T17:27:48.125603Z",
     "iopub.status.idle": "2023-08-18T17:27:48.247677Z",
     "shell.execute_reply": "2023-08-18T17:27:48.247121Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the power transmitted to the cross port as a function of wavelength\n",
    "plt.axhline(y=-3, color=\"r\", linestyle=\"--\", linewidth=3, label=\"Ideal\")\n",
    "plt.plot(ldas, 10 * np.log10(eta_cross_ldas), linewidth=3, label=\"TMM\")\n",
    "plt.legend()\n",
    "plt.xlim(1.5, 1.6)\n",
    "plt.ylim(-6, 0)\n",
    "plt.xlabel(r\"$\\lambda (\\mu m)$\")\n",
    "plt.ylabel(\"Transmission to cross port (dB)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa617412",
   "metadata": {},
   "source": [
    "## 3D FDTD"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "050fbb8f",
   "metadata": {},
   "source": [
    "The TMM analysis is only meant for an estimation of the optimal design parameters since TMM doesn't account for crucial details that can only be captured in a rigorous full wave simulation. Starting from the TMM analysis, we can further optimize $L_1$ and $L_2$ using 3D FDTD simulations. This can be done by performing a grid search (parameter sweeping), [adjoint optimization](https://www.flexcompute.com/tidy3d/examples/notebooks/AdjointPlugin1Intro/), or other gradient-free optimization around the initial values. Since parameter sweeping and adjoint optimization have been demonstrated in various examples such as the [MMI](https://www.flexcompute.com/tidy3d/examples/notebooks/MMI1x4/) and the [mode converter](https://www.flexcompute.com/tidy3d/examples/notebooks/AdjointPlugin3InverseDesign/), we won't do it again here but only report the final optimized design.\n",
    "\n",
    "After some further optimization, we determine that the optimal $L_1$ and $L_2$ are 12.4 $\\mu m$ and 4.7 $\\mu m$, which is not far from the TMM estimation of 12.8$\\mu m$ and 4.4 $\\mu m$. Now we demonstrate the FDTD simulation on the optimized device. To define the DC structures, we use Tidy3D's built-in [PolySlab](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PolySlab.html). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6f0a7b51",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:27:48.249721Z",
     "iopub.status.busy": "2023-08-18T17:27:48.249578Z",
     "iopub.status.idle": "2023-08-18T17:27:48.271595Z",
     "shell.execute_reply": "2023-08-18T17:27:48.271032Z"
    }
   },
   "outputs": [],
   "source": [
    "L_1 = 12.4  # optimal L_1 from the 3d fdtd analysis\n",
    "L_2 = 4.7  # optimal L_2 from the 3d fdtd analysis\n",
    "\n",
    "# define vertices of the top waveguide\n",
    "vertices = [\n",
    "    (L_2 / 2 + L_t + L_1, 0),\n",
    "    (L_2 / 2 + L_t + L_1, w_sc),\n",
    "    (L_2 / 2 + L_t, w_sc),\n",
    "    (L_2 / 2, w_top),\n",
    "    (-L_2 / 2, w_top),\n",
    "    (-L_2 / 2 - L_t, w_sc),\n",
    "    (-L_2 / 2 - L_t - L_1, w_sc),\n",
    "    (-L_2 / 2 - L_t - L_1, 0),\n",
    "]\n",
    "\n",
    "# define the top waveguide\n",
    "DC_top = td.Structure(\n",
    "    geometry=td.PolySlab(\n",
    "        vertices=vertices,\n",
    "        axis=2,\n",
    "        slab_bounds=(-h_si / 2, h_si / 2),\n",
    "    ),\n",
    "    medium=si,\n",
    ")\n",
    "\n",
    "# define vertices of the bottom waveguide\n",
    "vertices = [\n",
    "    (L_2 / 2 + L_t + L_1, -gap_sc - w_sc),\n",
    "    (L_2 / 2 + L_t + L_1, -gap_sc),\n",
    "    (L_2 / 2 + L_t, -gap_sc),\n",
    "    (L_2 / 2, -gap_pc),\n",
    "    (-L_2 / 2, -gap_pc),\n",
    "    (-L_2 / 2 - L_t, -gap_sc),\n",
    "    (-L_2 / 2 - L_t - L_1, -gap_sc),\n",
    "    (-L_2 / 2 - L_t - L_1, -gap_sc - w_sc),\n",
    "]\n",
    "\n",
    "# define the bottom waveguide\n",
    "DC_bottom = td.Structure(\n",
    "    geometry=td.PolySlab(\n",
    "        vertices=vertices,\n",
    "        axis=2,\n",
    "        slab_bounds=(-h_si / 2, h_si / 2),\n",
    "    ),\n",
    "    medium=si,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69167a13",
   "metadata": {},
   "source": [
    "The input and output waveguides are connected to circular bends, which can be most conveniently defined using `gdstk`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6f236968",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:27:48.273580Z",
     "iopub.status.busy": "2023-08-18T17:27:48.273439Z",
     "iopub.status.idle": "2023-08-18T17:27:48.304676Z",
     "shell.execute_reply": "2023-08-18T17:27:48.304082Z"
    }
   },
   "outputs": [],
   "source": [
    "R = 5  # bend radius\n",
    "\n",
    "cell = gdstk.Cell(\"bends\")  # define a gds cell\n",
    "\n",
    "# define the first input waveguide bend\n",
    "bend_1 = gdstk.FlexPath((L_2 / 2 + L_t, w_sc / 2), w_sc, layer=1, datatype=0)\n",
    "bend_1.horizontal(L_2 / 2 + L_t + L_1)\n",
    "bend_1.arc(R, -np.pi / 2, 0)\n",
    "bend_1.vertical(2 * l)\n",
    "cell.add(bend_1)\n",
    "\n",
    "# define the second input waveguide bend\n",
    "bend_2 = bend_1.copy()\n",
    "bend_2.mirror((0, 0), (0, 1))\n",
    "cell.add(bend_2)\n",
    "\n",
    "# define the third input waveguide bend\n",
    "bend_3 = bend_1.copy()\n",
    "bend_3.mirror((0, -gap_sc / 2), (1, -gap_sc / 2))\n",
    "cell.add(bend_3)\n",
    "\n",
    "# define the forth input waveguide bend\n",
    "bend_4 = bend_2.copy()\n",
    "bend_4.mirror((0, -gap_sc / 2), (1, -gap_sc / 2))\n",
    "cell.add(bend_4)\n",
    "\n",
    "# define the waveguide bend tidy3d geometries\n",
    "bends_geo = td.PolySlab.from_gds(\n",
    "    cell,\n",
    "    gds_layer=1,\n",
    "    axis=2,\n",
    "    slab_bounds=(-h_si / 2, h_si / 2),\n",
    ")\n",
    "\n",
    "# define the waveguide bend tidy3d structures\n",
    "bends = [td.Structure(geometry=bend_geo, medium=si) for bend_geo in bends_geo]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b41cd2e",
   "metadata": {},
   "source": [
    "Define source, monitors, and simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4c2446bb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:27:48.307400Z",
     "iopub.status.busy": "2023-08-18T17:27:48.307157Z",
     "iopub.status.idle": "2023-08-18T17:27:48.692954Z",
     "shell.execute_reply": "2023-08-18T17:27:48.692434Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define a mode source that injects te mode\n",
    "mode_source = td.ModeSource(\n",
    "    center=(-L_2 / 2 - L_t - L_1 - R, -R - l / 10, 0),\n",
    "    size=(4 * w_sc, 0, 4 * h_si),\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",
    "# define a mode monitor to measure the transmission to cross port\n",
    "mode_monitor_cross = td.ModeMonitor(\n",
    "    center=(L_2 / 2 + L_t + L_1 + R, R + l / 10, 0),\n",
    "    size=(4 * w_sc, 0, 4 * h_si),\n",
    "    freqs=freqs,\n",
    "    mode_spec=mode_spec,\n",
    "    name=\"mode_cross\",\n",
    ")\n",
    "\n",
    "# define a mode monitor to measure the transmission to through port\n",
    "mode_monitor_through = td.ModeMonitor(\n",
    "    center=(L_2 / 2 + L_t + L_1 + R, -R - l / 10, 0),\n",
    "    size=(4 * w_sc, 0, 4 * h_si),\n",
    "    freqs=freqs,\n",
    "    mode_spec=mode_spec,\n",
    "    name=\"mode_through\",\n",
    ")\n",
    "\n",
    "# define a field monitor to visualize mode propagation\n",
    "field_monitor = td.FieldMonitor(size=(td.inf, td.inf, 0), freqs=[freq0], name=\"field\")\n",
    "\n",
    "run_time = 2e-12  # simulation run time\n",
    "\n",
    "# simulation domain size\n",
    "Lx = 2 * L_1 + 2 * L_t + L_2 + 2 * R + l / 4\n",
    "Ly = 2 * R + l / 4\n",
    "Lz = 9 * h_si\n",
    "\n",
    "# define a simulation\n",
    "sim = td.Simulation(\n",
    "    size=(Lx, Ly, Lz),\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=15, wavelength=lda0),\n",
    "    structures=bends + [DC_top, DC_bottom],\n",
    "    sources=[mode_source],\n",
    "    monitors=[mode_monitor_cross, mode_monitor_through, field_monitor],\n",
    "    run_time=run_time,\n",
    "    medium=sio2,\n",
    "    symmetry=(0, 0, 1),\n",
    ")\n",
    "\n",
    "ax = sim.plot(z=0)\n",
    "ax.set_aspect(\"auto\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59aa08eb",
   "metadata": {},
   "source": [
    "Submit the simulation job to the server. Before running the simulation, we can get a cost estimation using `estimate_cost`. This prevents us from accidentally running large jobs that we set up by mistake. The estimated cost is the maximum cost corresponding to running all the time steps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a62cc71e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:27:48.694880Z",
     "iopub.status.busy": "2023-08-18T17:27:48.694737Z",
     "iopub.status.idle": "2023-08-18T17:27:54.084791Z",
     "shell.execute_reply": "2023-08-18T17:27:54.083656Z"
    }
   },
   "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\">18:00:13 Eastern Standard Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'full_structure'</span> with task_id       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d'</span> and  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m18:00:13 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'full_structure'\u001b[0m with task_id       \n",
       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d'\u001b[0m and  \n",
       "\u001b[2;36m                               \u001b[0mtask_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-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d'</span></a>.     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=762558;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=147097;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=762558;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=621902;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=762558;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\u001b\\\u001b[32m-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d'\u001b[0m\u001b]8;;\u001b\\.     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">18:00:15 Eastern Standard Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.437</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;36m18:00:15 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.437\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"
    }
   ],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"full_structure\")\n",
    "estimated_cost = web.estimate_cost(job.task_id)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "219d6dc6",
   "metadata": {},
   "source": [
    "The cost is reasonably so we can run the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "4f5e638d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:27:54.100126Z",
     "iopub.status.busy": "2023-08-18T17:27:54.099989Z",
     "iopub.status.idle": "2023-08-18T17:29:33.933405Z",
     "shell.execute_reply": "2023-08-18T17:29:33.932864Z"
    }
   },
   "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\">18:00:16 Eastern Standard Time </span>status = queued                                  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m18:00:16 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                  \n"
      ]
     },
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      },
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       "Output()"
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     "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\">18:00:19 Eastern Standard Time </span>status = preprocess                              \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m18:00:19 Eastern Standard 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\">18:00:25 Eastern Standard Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.437</span>. 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;36m18:00:25 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.437\u001b[0m. 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>starting up solver                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \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\">                               </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> or \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>abort/delete the task in the web UI. Terminating \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>the Python script will not stop the job running  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>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 or \n",
       "\u001b[2;36m                               \u001b[0mabort/delete the task in the web UI. Terminating \n",
       "\u001b[2;36m                               \u001b[0mthe Python script will not stop the job running  \n",
       "\u001b[2;36m                               \u001b[0mon the cloud.                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d0eda29f79854da8b4134e3e8ca93a6e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">18:01:31 Eastern Standard Time </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">76</span>%, exiting.          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m18:01:31 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m76\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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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>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": {
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       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">18:01:37 Eastern Standard Time </span>status = success                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m18:01:37 Eastern Standard 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\">                               </span>View simulation result at                        \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                        \n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=442390;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=255183;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                               \u001b[0m\u001b]8;id=442390;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=426071;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=442390;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d\u001b\\\u001b[4;34m-c5c7ae60-dabc-49c5-b2a2-9fd940ccee4d'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m     \n"
      ]
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       "Output()"
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     },
     "metadata": {},
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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": []
     },
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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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">18:01:40 Eastern Standard Time </span>loading simulation from data/simulation_data.hdf5\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m18:01:40 Eastern Standard Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/simulation_data.hdf5\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data = job.run(path=\"data/simulation_data.hdf5\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "373a985c",
   "metadata": {},
   "source": [
    "After the simulation is complete, we plot the splitting ratio and compare it to the ideal case. From the plot, we can see that the designed DC maintains a -3 dB splitting ratio very well across the wavelength range of interest. The bandwidth is larger than 100 nm. As a comparison, [traditional DCs](https://tidy3d.simulation.cloud/workbench?taskId=pa-45ba95c2-3ced-4331-8ea3-01c49041f516) have a much smaller working bandwidth."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b8731f7d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:29:35.898677Z",
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     "iopub.status.idle": "2023-08-18T17:29:36.056282Z",
     "shell.execute_reply": "2023-08-18T17:29:36.055764Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculate transmission to cross port\n",
    "amp_cross = sim_data[\"mode_cross\"].amps.sel(mode_index=0, direction=\"+\")\n",
    "T_cross = np.abs(amp_cross) ** 2\n",
    "\n",
    "# calculate transmission to through port\n",
    "amp_through = sim_data[\"mode_through\"].amps.sel(mode_index=0, direction=\"-\")\n",
    "T_through = np.abs(amp_through) ** 2\n",
    "\n",
    "T_total = T_cross + T_through  # total transmitted power\n",
    "\n",
    "plt.axhline(y=-3, color=\"r\", linestyle=\"--\", linewidth=3, label=\"Ideal\")\n",
    "plt.plot(ldas, 10 * np.log10(T_cross / T_total), linewidth=3, label=\"FDTD\")\n",
    "plt.xlabel(r\"$\\lambda (\\mu m)$\")\n",
    "plt.ylabel(\"Transmission to cross port (dB)\")\n",
    "plt.xlim(1.5, 1.6)\n",
    "plt.ylim(-6, 0)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b45cb6a",
   "metadata": {},
   "source": [
    "Finally, visualize the power distribution at the central wavelength, which confirms the even splitting of power."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "170af679",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:29:36.058087Z",
     "iopub.status.busy": "2023-08-18T17:29:36.057946Z",
     "iopub.status.idle": "2023-08-18T17:29:37.774733Z",
     "shell.execute_reply": "2023-08-18T17:29:37.774198Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sim_data.plot_field(field_monitor_name=\"field\", field_name=\"E\", val=\"abs^2\", vmin=0, vmax=4000)\n",
    "ax.set_aspect(\"auto\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b7b145b2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "applications": [
   "Passive photonic integrated circuit components"
  ],
  "description": "This notebook demonstrates how to model a broadband directional coupler in Tidy3D FDTD.",
  "feature_image": "./img/broadband_DC_1.png",
  "features": [
   "Mode analysis",
   "GDS component"
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "silicon photonics, PIC, integrated photonics, broadband direction coupler, 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": "3.11.0"
  },
  "title": "Broadband Directional Coupler Modeling | Flexcompute",
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       "msg_id": "",
       "outputs": [
        {
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