{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "81b358de",
   "metadata": {},
   "source": [
    "# Dispersion calculation in tapered waveguide"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c72bcc1",
   "metadata": {},
   "source": [
    "Integrated photonic waveguides provide a versatile platform for achieving a desired dispersion profile. By controlling the waveguide cross-section geometry, it is possible to obtain zero or near-zero waveguide dispersion across a wide range of wavelengths. This capability is crucial for various applications such as optical delay lines, modulators, and supercontinuum generators, as different spectral components associated with the propagation of short optical pulses can travel at different speeds causing signal distortion. In this example, we will build a CMOS-compatible tapered waveguide presented in `[1] N. Singh, D. Vermulen, A. Ruocco, N. Li, E. Ippen, F. X. Kärtner, and M. R. Watts. Supercontinuum generation in varying dispersion and birefringent silicon waveguide. Opt. Express 27(22), 31698-31712 (2019).`[DOI:10.1364/OE.27.031698](https://doi.org/10.1364/OE.27.031698), which demonstrates supercontinuum enhancement in varying dispersion waveguides. We will demonstrate how to utilize the `Tidy3D`'s [ModeSolver](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.mode.ModeSolver.html?highlight=modesolver) to compute the dispersion parameter (D) and the group-velocity dispersion (GVD) across the varying taper waveguide cross-section to replicate Figure 5 of [1].\n",
    "\n",
    "<img src=\"img/tapered_waveguide_dispersion.png\" width=\"400\" alt=\"Tapered Waveguide Schematic\">\n",
    "\n",
    "For more integrated photonic waveguide examples such as the [Dielectric waveguide with scale-invariant effective index](https://www.flexcompute.com/tidy3d/examples/notebooks/ScaleInvariantWaveguide/), please visit our [examples page](https://www.flexcompute.com/tidy3d/examples/).\n",
    "\n",
    "If you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101](https://www.flexcompute.com/fdtd101/) tutorials. Details on using `Tidy3D`'s [ModeSolver](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.mode.ModeSolver.html?highlight=modesolver) can be found [here](https://www.flexcompute.com/tidy3d/examples/notebooks/ModeSolver/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1f8ab3b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "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\n",
    "from tidy3d.plugins.mode import ModeSolver"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0f34afb",
   "metadata": {},
   "source": [
    "## Tapered Waveguide\n",
    "The tapered waveguide is 5 mm long and varies adiabatically from 0.500 $\\mu m$ to 1.100 $\\mu m$ in width. The rib cross-section has a total height of 0.380 $\\mu m$ and a slab thickness of 0.065 $\\mu m$. The waveguide is etched into a silicon thin film and is surrounded by a thick silica layer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4339417d",
   "metadata": {},
   "outputs": [],
   "source": [
    "taper_w_in = 0.5  # Input taper width (um).\n",
    "taper_w_out = 1.1  # Output taper width (um).\n",
    "taper_l = 5000  # Taper length (um).\n",
    "wg_h = 0.38  # Waveguide height (um).\n",
    "wg_slab = 0.065  # Waveguide slab thickness (um)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fc8c6f1",
   "metadata": {},
   "source": [
    "The group-velocity dispersion (GVD) variation will be computed along the taper length at the wavelength of 1.95 $\\mu m$. In addition, we will calculate the dispersion parameter (D) between the wavelength range of 1.2 $\\mu m$ and 2.8 $\\mu m$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "65f6f8db",
   "metadata": {},
   "outputs": [],
   "source": [
    "wl_min = 1.2  # Minimum wavelength in dispersion calculation.\n",
    "wl_max = 2.4  # Maximum wavelength in dispersion calculation.\n",
    "wl_steps = 21  # Number of wavelength points in mode calculation.\n",
    "\n",
    "wl_d = np.linspace(wl_min, wl_max, wl_steps)  # Wavelength range for D calculation.\n",
    "wl_gvd = np.asarray([1.95])  # Wavelength for GVD calculation."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eca1dda7",
   "metadata": {},
   "source": [
    "## Simulation Setup\n",
    "Now, we will build the tapered waveguide structure using a [`PolySlab`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PolySlab.html) and materials taken from the material library."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5b914131",
   "metadata": {},
   "outputs": [],
   "source": [
    "mat_si = td.material_library[\"cSi\"][\"Palik_Lossless\"]\n",
    "mat_sio2 = td.material_library[\"SiO2\"][\"Palik_Lossless\"]\n",
    "\n",
    "taper = td.Structure(\n",
    "    geometry=td.PolySlab(\n",
    "        vertices=[\n",
    "            [0, -taper_w_in / 2],\n",
    "            [taper_l, -taper_w_out / 2],\n",
    "            [taper_l, taper_w_out / 2],\n",
    "            [0, taper_w_in / 2],\n",
    "        ],\n",
    "        axis=2,\n",
    "        slab_bounds=(-wg_h / 2, wg_h / 2),\n",
    "    ),\n",
    "    medium=mat_si,\n",
    "    name=\"taper_core\",\n",
    ")\n",
    "\n",
    "slab = td.Structure(\n",
    "    geometry=td.Box(center=[0, 0, -wg_h / 2 + wg_slab / 2], size=[td.inf, td.inf, wg_slab]),\n",
    "    medium=mat_si,\n",
    "    name=\"taper_slab\",\n",
    ")\n",
    "\n",
    "sim = td.Simulation(\n",
    "    center=(taper_l / 2, 0, 0),\n",
    "    size=(1.1 * taper_l, taper_w_out + wl_max, 3),\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=15, wavelength=wl_min),\n",
    "    structures=[taper, slab],\n",
    "    run_time=1e-12,\n",
    "    medium=mat_sio2,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.Periodic()),\n",
    "    symmetry=(0, -1, 0),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce9cd8ce",
   "metadata": {},
   "source": [
    "To ensure the simulation is correctly defined, we will visualize the permittivity distribution. As expected, we see the tapered waveguide profile along the `x`-direction and the rib cross-section in the `yz` plane."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "153fab40",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(12, 4))\n",
    "sim.plot(z=0, ax=ax[0])\n",
    "ax[0].set_aspect(\"auto\")\n",
    "\n",
    "sim.plot_eps(x=0, freq=td.C_0 / wl_gvd[0], ax=ax[1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa2b307e",
   "metadata": {},
   "source": [
    "As we need to run the mode solver several times, we will create a helper function called `build_mode`. This function takes the arguments `mode_pos_x`, `wl`, `num_modes`, and `group_index_step`, and builds the `ModeSolver`. We plan to use this function to conduct a sweep on the mode plane position along the tapered waveguide to calculate the parameters D and GVD."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0a8291e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def build_mode(\n",
    "    mode_pos_x: float = 0, wl: np.array = wl_d, num_modes: int = 1, group_index_step: float = 0.15\n",
    ") -> ModeSolver:\n",
    "    \"\"\"Builds a ModeSolver object.\"\"\"\n",
    "\n",
    "    freqs = td.C_0 / wl  # Mode frequencies.\n",
    "\n",
    "    # Mode specification.\n",
    "    mode_spec = td.ModeSpec(\n",
    "        num_modes=num_modes,\n",
    "        group_index_step=group_index_step,\n",
    "        num_pml=[7, 7],\n",
    "    )\n",
    "\n",
    "    # Build a mode solver.\n",
    "    mode_solver = ModeSolver(\n",
    "        simulation=sim,\n",
    "        plane=td.Box(center=(mode_pos_x, 0, 0), size=(0, td.inf, td.inf)),\n",
    "        mode_spec=mode_spec,\n",
    "        freqs=freqs,\n",
    "    )\n",
    "\n",
    "    return mode_solver"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0b88ee2",
   "metadata": {},
   "source": [
    "## Group Index Step Convergence\n",
    "According to `[2] G. Agrawal. Nonlinear Fiber Optics (5th Ed.), Academic Press (2013)`, the effects of fiber dispersion are addressed by expanding the mode-propagation constant $\\beta$ in a Taylor series around the angular frequency $\\omega$. As a result, the parameters $\\beta_{1}$ and $\\beta_{2}$ are directly linked to the mode's effective index $n_{eff}(\\omega)$ and its derivatives as\n",
    "\n",
    "$$\\beta_{1} = \\frac{1}{v_{g}} = \\frac{n_{g}}{c} = \\frac{1}{c}\\left(n_{eff} + \\omega\\frac{d n_{eff}}{d\\omega}\\right)$$\n",
    "\n",
    "and\n",
    "\n",
    "$$\\beta_{2} = \\frac{1}{c}\\left(2\\frac{d n_{eff}}{d\\omega} + \\omega\\frac{d^{2} n_{eff}}{d\\omega^{2}}\\right),$$\n",
    "\n",
    "where $c$ is the speed of light, $v_{g}$ is the group velocity, and $n_{g}$ is the group index. The first-order term $\\beta_{1}$ controls the speed at which the optical pulse envelope propagates, and the group velocity dispersion (GVD) parameter $\\beta_{2}$ represents dispersion of the group velocity and is responsible for pulse broadening. In practice, the dispersion parameter D, which is defined as $d\\beta_{1}/d\\lambda$, is also used to quantify dispersion. It is related to $\\beta_{2}$ by\n",
    "\n",
    "$$D = -\\frac{2\\pi c}{\\lambda^{2}}\\beta_{2},$$\n",
    "\n",
    "where $\\lambda$ is the light wavelength.\n",
    "\n",
    "When calculating dispersion using the Tidy3D ModeSolver, additional frequency points are included to improve the accuracy of the effective index numerical differentiation. The parameter `group_index_step` controls the proximity of these additional frequency points to the user-supplied frequencies. Before proceeding with the main analyses, we will verify the convergence of our dispersion calculation with respect to the `group_index_step` parameter.\n",
    "\n",
    "We will build a dictionary of ModeSolver instances to create a simulation batch as we run many mode solver calculations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f47196bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# List of group_index_step values.\n",
    "gis_values = [0.02, 0.05, 0.10, 0.15, 0.20]\n",
    "\n",
    "# Mode sweep over the group_index_step values.\n",
    "mode_gis = {}\n",
    "for gis in gis_values:\n",
    "    mode_gis[f\"gis={gis}\"] = build_mode(mode_pos_x=taper_l / 2, group_index_step=gis)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77ac29cd",
   "metadata": {},
   "source": [
    "Once the batch of ModeSolvers is created, we simply use the `run()` method to run the entire batch of tasks in parallel."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9756258e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6bacb58c5b3f4b9bb4074d6a6a40b994",
       "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\"></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\">22:19:48 CEST </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span> tasks.                      \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m22:19:48 CEST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m5\u001b[0m tasks.                      \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\">22:19:54 CEST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.029</span> for the whole batch.               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m22:19:54 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.029\u001b[0m for the whole batch.               \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>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>the Batch has completed.                                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after   \n",
       "\u001b[2;36m              \u001b[0mthe Batch has completed.                                          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5c36bde520e7464f96c0b19e33176c47",
       "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\">22:19:59 CEST </span>Batch complete.                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m22:19:59 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7319e48a2482401eb4fc943ce1dc0c91",
       "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\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#  Run the mode solvers in parallel.\n",
    "batch = web.Batch(simulations=mode_gis)\n",
    "batch_gis = batch.run(path_dir=\"data\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97af9daf",
   "metadata": {},
   "source": [
    "We can observe that a `group_index_step` value between 0.10 and 0.15 is enough to obtain a smooth dispersion curve, avoiding the numerical noise created in smaller `group_index_step` values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f0111c6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(12, 4), tight_layout=True)\n",
    "\n",
    "batch_gis[f\"gis={gis_values[0]}\"].intensity.isel(\n",
    "    f=batch_gis[f\"gis={gis_values[0]}\"].modes_info[\"f\"].size // 2, mode_index=0\n",
    ").plot(x=\"y\", y=\"z\", cmap=\"hot\", ax=ax[0])\n",
    "ax[0].set_title(\"Fundamental Mode - $|E|^{2}$\")\n",
    "ax[0].set_aspect(\"equal\")\n",
    "\n",
    "for gis, md in batch_gis.items():\n",
    "    ax[1].plot(\n",
    "        td.C_0 / md.modes_info[\"f\"].squeeze(drop=True).values,\n",
    "        md.modes_info[\"dispersion (ps/(nm km))\"].squeeze(drop=True).values,\n",
    "        label=gis,\n",
    "    )\n",
    "ax[1].set_ylabel(\"Dispersion (ps/(nm*km))\")\n",
    "ax[1].set_xlabel(\"Wavelength ($\\\\mu m$)\")\n",
    "ax[1].set_ylim([-1000, 1000])\n",
    "ax[1].set_xlim([wl_d[0], wl_d[-1]])\n",
    "ax[1].legend(title=\"group_index_step\")\n",
    "ax[1].grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05ff0569",
   "metadata": {},
   "source": [
    "## Dispersion Parameters Calculation\n",
    "Now, we are ready to calculate the dispersion parameters for the varying waveguide cross-sections along the taper length. To reproduce Figure 5(a) of [1], we will calculate the $\\beta_{2}$ parameter of GVD at the wavelength of 1.95 $\\mu m$ for waveguide cross-sections ranging from 0.5 $\\mu m$ to 1.1 $\\mu m$ in intervals of 0.2 $\\mu m$. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a4cbadd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_values_gvd = np.linspace(0.05, taper_l - 0.05, 13)\n",
    "\n",
    "# Mode simulations to calculate beta2 of GVD.\n",
    "mode_gvd = {}\n",
    "for x in x_values_gvd:\n",
    "    mode_gvd[f\"x={x:.2f}\"] = build_mode(mode_pos_x=x, wl=wl_gvd, group_index_step=0.15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "edaa9d92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "15bba85481314bc5915ec083f9df5ce9",
       "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\"></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\">22:20:42 CEST </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span> tasks.                     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m22:20:42 CEST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m13\u001b[0m tasks.                     \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\">22:20:56 CEST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.048</span> for the whole batch.               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m22:20:56 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.048\u001b[0m for the whole batch.               \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>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>the Batch has completed.                                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after   \n",
       "\u001b[2;36m              \u001b[0mthe Batch has completed.                                          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0b3613ac31ed4c0d95c02c55383fc89a",
       "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\">22:21:07 CEST </span>Batch complete.                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m22:21:07 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "408d7b629cb54b00a2af225c6b7c07d2",
       "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\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#  Run the mode solvers in parallel.\n",
    "batch = web.Batch(simulations=mode_gvd)\n",
    "batch_gvd = batch.run(path_dir=\"data\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e557576a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Mode simulations to calculate beta2 of GVD.\n",
    "data_gvd = []\n",
    "for _, md in batch_gvd.items():\n",
    "    d = md.modes_info[\"dispersion (ps/(nm km))\"].squeeze(drop=True).values\n",
    "    beta2 = -((d * wl_gvd**2) / (2 * np.pi * td.C_0)) * 1e12\n",
    "    data_gvd.append(beta2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "491f3675",
   "metadata": {},
   "source": [
    " Afterward, considering seven positions along the taper length, we will calculate the dispersion parameter D for wavelengths ranging from 1.2 $\\mu m$ to 2.4 $\\mu m$. We will use this data to plot Figure 5(b) of [1].   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d73b5800",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_values_d = np.linspace(0.05, taper_l - 0.05, 7)\n",
    "\n",
    "# Mode simulations to calculate D.\n",
    "mode_d = {}\n",
    "for x in x_values_d:\n",
    "    mode_d[f\"x={x:.2f}\"] = build_mode(mode_pos_x=x, group_index_step=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "dec1e641",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "892b02561df446599b0d9509b4fe9119",
       "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\"></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\">22:21:41 CEST </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7</span> tasks.                      \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m22:21:41 CEST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m7\u001b[0m tasks.                      \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\">22:21:50 CEST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.041</span> for the whole batch.               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m22:21:50 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.041\u001b[0m for the whole batch.               \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>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after   \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>the Batch has completed.                                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after   \n",
       "\u001b[2;36m              \u001b[0mthe Batch has completed.                                          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "166212efadde4aefa11f094d91223738",
       "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\">22:21:56 CEST </span>Batch complete.                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m22:21:56 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f649a5bf48c14f43a91bc73e39a417c8",
       "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\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#  Run the mode solvers in parallel.\n",
    "batch = web.Batch(simulations=mode_d)\n",
    "batch_d = batch.run(path_dir=\"data\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b228c76d",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_d = []\n",
    "for _, md in batch_d.items():\n",
    "    data_d.append(md.modes_info[\"dispersion (ps/(nm km))\"].squeeze(drop=True).values)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8706e021",
   "metadata": {},
   "source": [
    "Lastly, we will plot GVD and D dispersion parameters. We can observe a good agreement between the simulations and Figure 5(a-b)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2e054e76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(12, 4), tight_layout=True)\n",
    "\n",
    "# GVD\n",
    "ax[0].plot(x_values_gvd / 1000, data_gvd, \"ok-\")\n",
    "ax[0].set_ylabel(\"$\\\\beta_{2}$ ($ps^{2}/m$)\")\n",
    "ax[0].set_xlabel(\"Mode Plane X-Position (mm)\")\n",
    "ax[0].set_ylim([-1, 1])\n",
    "ax[0].set_xlim([0, 5])\n",
    "ax[0].grid()\n",
    "\n",
    "# D\n",
    "for l, d in zip(x_values_d, data_d):\n",
    "    ax[1].plot(wl_d, d, \"-o\", label=f\"{l / 1000:.2f} mm\")\n",
    "ax[1].set_ylabel(\"D ($ps/(nm \\\\cdot km)$)\")\n",
    "ax[1].set_xlabel(\"Wavelength ($\\\\mu m$)\")\n",
    "ax[1].set_ylim([-210, 600])\n",
    "ax[1].set_xlim([1.2, 2.4])\n",
    "ax[1].legend(title=\"X-Position\")\n",
    "ax[1].grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2a917981-461c-4345-a321-2cc854082669",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "applications": [
   "Passive photonic integrated circuit components"
  ],
  "description": "This notebook demonstrates how to perform dispersion calculation using the Tidy3D Mode Solver.",
  "feature_image": "./img/tapered_waveguide_dispersion.png",
  "features": [
   "Mode analysis"
  ],
  "kernelspec": {
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  "title": "Dispersion calculation in tapered waveguide using Tidy3D | Flexcompute"
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