{ "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", "\"Schematic\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" } }, "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", "\"Top" ] }, { "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", "iopub.status.busy": "2023-08-18T17:24:23.541070Z", "iopub.status.idle": "2023-08-18T17:24:23.560122Z", "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", "iopub.status.idle": "2023-08-18T17:24:23.580334Z", "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", "iopub.status.busy": "2023-08-18T17:24:23.601903Z", "iopub.status.idle": "2023-08-18T17:24:23.845203Z", "shell.execute_reply": "2023-08-18T17:24:23.844521Z" } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "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: 2.459162628532339, 2.43821523251537\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "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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tTXZ2tjHGmM8//9zUqVPHDB8+3MycOdNMmzbNtG3b1lSuXNkkJycbY4x57rnnTHh4uBk9erSZPXu2ee2110ydOnVM3bp1TXp6eqH1F2W7nJwcc//99xuHw2H69etn3n77bTN16lTz1FNPmZo1azrNa8yYMUaS6dChg3nzzTfN22+/bWJiYszIkSOtPk8//bRxOBzmH//4h/n444+tOz5f/Wu7K1+7iIgIM3XqVDNq1ChTpUoV06BBA+v1NZd/bVe1atVCX99rOX36tKlRo4apX7++eeutt8zkyZNNeHi4adWqVb56Jk6caCSZ559/3syfP9988cUXhY6blpZmateubTp37mz9Quz06dMmICDAREZGlsid1GfMmGEkmYceesjMnj3bxMTEGEnmtddeK/B1uHIu5vKv5SpVqmT+9re/mXfeecd06NDBVKpUyaxdu9ap37Zt24ynp6fTHca9vLxMt27dilTnM888Y+rUqZPvJpmSjLe3t7nvvvvMrFmzzJgxY4yvr6/x8/MzjRo1MvPnzzfmGvtQ3ryu/rVoYZ+H5s2bm0cffbRINQOFITwBJeDQoUMmJibG+Pv7G09PT3PrrbeaoUOHmqysLGOuE57M5VsTNGnSxFSuXNkEBASYIUOGOAWDH3/80fz1r381DRs2NF5eXqZmzZqmc+fOZuXKlVafpKQk07NnTxMcHGw8PDxMcHCwefjhh80PP/xwzdqLul12drZ54403TLNmzYynp6epUaOGad26tRk3bly+n93PmTPHhIeHW/06depkVqxYYa1PTU013bt3N9WqVTOSrJ+UFxSejDFm4cKF1ng1a9Y0jzzyiDl69KhTnxsJT8YYs3HjRtO+fXvj7e1tgoODzYgRI8zXX3+dr57z58+bv/zlL6Z69epG0jVvW/Dggw+aatWqmZ9++smpfenSpUaSeeONN65bV1G8++67pnHjxsbDw8M0bNjQTJkyJV9IKSw8Xbx40bz44osmMDDQeHp6mrZt25rExMQCn2f9+vWmQ4cOxsvLy/j7+5uhQ4eazMzMItW4fft2Iynf7S4kmdjYWNOnTx/j7e1tgoKCzPTp0018fLypUqWKeeKJJ4wpofC0Z88eI8lpvwGKw2G4zSoA4Cbo2rWrgoOD9eGHH1ptDodDcXFxBd5lvKQNHz5c69at07Zt2/i1HW4I1zwBAG6Kf/7zn1q4cKF1C4qb6cyZM3rvvfc0fvx4ghNuGLcqAADcFBEREYXel6q01apVS+fPny+T50bFw5EnAAAAGzjyBAAoM1x2i/KII08AAAA2EJ4AAABs4LRdEeXm5ur48eOqVq0av9QAAKCCMcbo3LlzCg4OvuYfUxfhqeiOHz/uMn/8FAAAlI4jR46obt261+xDeCqiatWqSZdfVF9f37IuBwAAlKDMzEyFhIRY3/fXQngqorxTdb6+voQnAAAqqKJcmsMF4wAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALDB5cLTunXr9MADDyg4OFgOh0NLliy5Zv81a9bI4XDkW1JTU536zZgxQw0aNJCXl5ciIiK0ZcuWUp4JAACoiFwuPF24cEGtWrXSjBkzbG23d+9enThxwlpuueUWa93ChQsVGxuruLg4bd++Xa1atVJ0dLROnjxZCjMAAAAVWaWyLuBq9913n+677z7b291yyy2qXr16gesmT56sQYMGacCAAZKk+Ph4LVu2THPmzNHIkSNvuGYAAPD74XJHnoorLCxMQUFBuvfee7Vx40arPTs7W9u2bVNUVJTV5ubmpqioKCUnJ5dRtQAAoLwq9+EpKChI8fHx+uyzz/TZZ58pJCRE99xzj7Zv3y5JOn36tHJychQQEOC0XUBAQL7roq6UlZWlzMxMpwUAAMDlTtvZ1bhxYzVu3Nh63KFDBx04cEBTpkzRhx9+WOxxJ0yYoHHjxpVQlQAAoKIo90eeCtKuXTvt379fklS7dm25u7srLS3NqU9aWpoCAwMLHWPUqFHKyMiwliNHjpR63QAAwPVVyPCUkpKioKAgSZKHh4dat26tpKQka31ubq6SkpIUGRlZ6Bienp7y9fV1WgAAAFzutN358+eto0aSdPDgQaWkpKhmzZqqV6+eRo0apWPHjumDDz6QJE2dOlWhoaFq1qyZLl26pPfee0+rVq3SN998Y40RGxur/v37q02bNmrXrp2mTp2qCxcuWL++AwAAKCqXC09bt25V586drcexsbGSpP79+yshIUEnTpzQ4cOHrfXZ2dl64YUXdOzYMVWpUkUtW7bUypUrncbo27evTp06pbFjxyo1NVVhYWFKTEzMdxE5AADA9TiMMaasiygPMjMz5efnp4yMDE7hAQBQwdj5nq+Q1zwBAACUFsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADY4HLhad26dXrggQcUHBwsh8OhJUuWXHebNWvW6M4775Snp6caNWqkhISEfH1mzJihBg0ayMvLSxEREdqyZUspzQAAAFRkLheeLly4oFatWmnGjBlF6n/w4EF1795dnTt3VkpKioYPH64nnnhCX3/9tdVn4cKFio2NVVxcnLZv365WrVopOjpaJ0+eLMWZAACAishhjDFlXURhHA6HPv/8c/Xq1avQPi+99JKWLVum7777zmrr16+f0tPTlZiYKEmKiIhQ27ZtNX36dElSbm6uQkJCNGzYMI0cObJItWRmZsrPz08ZGRny9fW94bkBAADXYed73uWOPNmVnJysqKgop7bo6GglJydLkrKzs7Vt2zanPm5uboqKirL6FCQrK0uZmZlOCwAAQLkPT6mpqQoICHBqCwgIUGZmpi5evKjTp08rJyenwD6pqamFjjthwgT5+flZS0hISKnNAQAAlB/lPjyVllGjRikjI8Najhw5UtYlAQAAF1CprAu4UYGBgUpLS3NqS0tLk6+vr7y9veXu7i53d/cC+wQGBhY6rqenpzw9PUutbgAAUD6V+yNPkZGRSkpKcmpbsWKFIiMjJUkeHh5q3bq1U5/c3FwlJSVZfQAAAIrK5cLT+fPnlZKSopSUFOnyrQhSUlJ0+PBh6fLptJiYGKv/U089pR9//FEjRozQ999/r5kzZ+qTTz7R888/b/WJjY3V7Nmz9T//8z/as2ePhgwZogsXLmjAgAFlMEMAAFCeudxpu61bt6pz587W49jYWElS//79lZCQoBMnTlhBSpJCQ0O1bNkyPf/88/rXv/6lunXr6r333lN0dLTVp2/fvjp16pTGjh2r1NRUhYWFKTExMd9F5AAAANfj0vd5ciXc5wkAgIrrd3WfJwAAgJuJ8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABtcMjzNmDFDDRo0kJeXlyIiIrRly5ZC+yYkJMjhcDgtXl5eTn2MMRo7dqyCgoLk7e2tqKgo7du37ybMBAAAVDQuF54WLlyo2NhYxcXFafv27WrVqpWio6N18uTJQrfx9fXViRMnrOXQoUNO6ydOnKhp06YpPj5emzdvVtWqVRUdHa1Lly7dhBkBAICKxOXC0+TJkzVo0CANGDBATZs2VXx8vKpUqaI5c+YUuo3D4VBgYKC1BAQEWOuMMZo6dapGjx6tnj17qmXLlvrggw90/PhxLVmy5CbNCgAAVBQuFZ6ys7O1bds2RUVFWW1ubm6KiopScnJyodudP39e9evXV0hIiHr27Kldu3ZZ6w4ePKjU1FSnMf38/BQREXHNMQEAAAriUuHp9OnTysnJcTpyJEkBAQFKTU0tcJvGjRtrzpw5Wrp0qT766CPl5uaqQ4cOOnr0qCRZ29kZU5KysrKUmZnptAAAALhUeCqOyMhIxcTEKCwsTJ06ddLixYvl7++vd95554bGnTBhgvz8/KwlJCSkxGoGAADll0uFp9q1a8vd3V1paWlO7WlpaQoMDCzSGJUrV1Z4eLj2798vSdZ2dsccNWqUMjIyrOXIkSPFmBEAAKhoXCo8eXh4qHXr1kpKSrLacnNzlZSUpMjIyCKNkZOTo507dyooKEiSFBoaqsDAQKcxMzMztXnz5muO6enpKV9fX6cFAACgUlkXcLXY2Fj1799fbdq0Ubt27TR16lRduHBBAwYMkCTFxMSoTp06mjBhgiTp1VdfVfv27dWoUSOlp6dr0qRJOnTokJ544gnp8i/xhg8frvHjx+u2225TaGioxowZo+DgYPXq1atM5woAAMoflwtPffv21alTpzR27FilpqYqLCxMiYmJ1gXfhw8flpvb/x0wO3v2rAYNGqTU1FTVqFFDrVu31qZNm9S0aVOrz4gRI3ThwgUNHjxY6enp6tixoxITE/PdTBMAAOB6HMYYU9ZFlAeZmZny8/NTRkYGp/AAAKhg7HzPu9Q1TwAAAK6O8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsKGSnc65ublau3at1q9fr0OHDumXX36Rv7+/wsPDFRUVpZCQkNKrFAAAwAUU6cjTxYsXNX78eIWEhOj+++/Xv//9b6Wnp8vd3V379+9XXFycQkNDdf/99+vbb78t/aoBAADKSJGOPN1+++2KjIzU7Nmzde+996py5cr5+hw6dEjz589Xv3799PLLL2vQoEGlUS8AAECZchhjzPU67dmzR3fccUeRBvz11191+PBhNWzYsCTqcxmZmZny8/NTRkaGfH19y7ocAABQgux8zxfptF1Rg5MkVa5cucIFJwAAgDy2LhjPc+nSJf33v//VyZMnlZub67SuR48eJVUbAACAy7EdnhITExUTE6PTp0/nW+dwOJSTk1NStQEAALgc2/d5GjZsmPr06aMTJ04oNzfXaSE4AQCAis72kae0tDTFxsYqICCgdCoCcFMMmZNU1iW4jFl/7VrWJUjl9D1xldcOuJlsH3l66KGHtGbNmtKpBgAAwMXZPvI0ffp09enTR+vXr1eLFi3y3fPp2WefLcn6AAAAXIrt8PTxxx/rm2++kZeXl9asWSOHw2GtczgchCcAAFCh2Q5PL7/8ssaNG6eRI0fKzY2/KwwAAH5fbKef7Oxs9e3bl+AEAAB+l2wnoP79+2vhwoWlUw0AAICLs33aLicnRxMnTtTXX3+tli1b5rtgfPLkySVZHwAAgEuxHZ527typ8PBwSdJ3331XGjUBAAC4LNvhafXq1aVTCQAAQDlQYld9Hzp0SM8880xJDQcAAOCSbB956ty5s9O9nfKcOHFCJ06c0PTp00uqNgAAAJdjOzyFhYU5Pc7JydGPP/6o/fv3KyEhoSRrAwAAcDm2w9OUKVMKbH/vvfc0ffp0PfLIIyVRFwAAgEsqsWueunbtqpSUlJIaDgAAwCWVWHhatWqVOnfuXFLDAQAAuCTbp+0efPDBfG1paWnavHmzOnfu7LR+8eLFN14hAACAC7Ednvz8/Apsu/3220uqJgAAAJdlOzzNnTu3dCoBAAAoB4p0zZMxpvQrAQAAKAeKFJ6aNWumBQsWKDs7+5r99u3bpyFDhuj111+/oaJmzJihBg0ayMvLSxEREdqyZcs1+y9atEhNmjSRl5eXWrRooeXLlzutN8Zo7NixCgoKkre3t6KiorRv374bqhEAAPw+FSk8vf3223rzzTcVGBiovn37atKkSZo3b54+++wzvffee4qNjVW7du0UFhYmX19fDRkypNgFLVy4ULGxsYqLi9P27dvVqlUrRUdH6+TJkwX237Rpkx5++GENHDhQO3bsUK9evdSrVy+nP1o8ceJETZs2TfHx8dq8ebOqVq2q6OhoXbp0qdh1AgCA3yeHsXFObsOGDVq4cKHWr1+vQ4cO6eLFi6pdu7bCw8MVHR2tRx55RDVq1LihgiIiItS2bVvrz7zk5uYqJCREw4YN08iRI/P179u3ry5cuKCvvvrKamvfvr3CwsIUHx8vY4yCg4P1wgsv6MUXX5QkZWRkKCAgQAkJCerXr1+R6srMzJSfn58yMjLk6+t7Q3MEXMGQOUllXYLLmPXXrmVdglRO3xNXee2AG2Xne97WBeMdO3ZUx44db7S+QmVnZ2vbtm0aNWqU1ebm5qaoqCglJycXuE1ycrJiY2Od2qKjo7VkyRJJ0sGDB5WamqqoqChrvZ+fnyIiIpScnFzk8AQAAKDi/NquNJ0+fVo5OTkKCAhwag8ICND3339f4DapqakF9k9NTbXW57UV1qcgWVlZysrKsh5nZmYWY0YAAKCicanw5EomTJigcePGlXUZQKnhdIvr4T0ByocS+/MsJaF27dpyd3dXWlqaU3taWpoCAwML3CYwMPCa/fP+aWdMSRo1apQyMjKs5ciRI8WeFwAAqDhcKjx5eHiodevWSkr6v4smc3NzlZSUpMjIyAK3iYyMdOovSStWrLD6h4aGKjAw0KlPZmamNm/eXOiYkuTp6SlfX1+nBQAAwOVO28XGxqp///5q06aN2rVrp6lTp+rChQsaMGCAJCkmJkZ16tTRhAkTJEnPPfecOnXqpLfeekvdu3fXggULtHXrVr377ruSJIfDoeHDh2v8+PG67bbbFBoaqjFjxig4OFi9evUq07kCAIDyx3Z46tKlizp16qS4uDin9rNnz6p3795atWrVDRXUt29fnTp1SmPHjlVqaqrCwsKUmJhoXfB9+PBhubn93wGzDh06aP78+Ro9erT+/ve/67bbbtOSJUvUvHlzq8+IESN04cIFDR48WOnp6erYsaMSExPl5eV1Q7UCAIDfH1v3edLlWwfUqlVLd911l+bNm6eqVatKl68hCg4OVk5OTmnVWqa4zxMAABWXne/5Yl3ztHLlSqWmpqp9+/b66aefilsnAABAuVOs8BQUFKS1a9eqRYsWatu2rdasWVPylQEAALgg2+HJ4XBIl3+NNn/+fD333HP6wx/+oJkzZ5ZGfQAAAC7F9gXjV18iNXr0aN1xxx3q379/SdYFAADgkmyHp4MHD8rf39+prXfv3mrSpIm2bt1akrUBAAC4HNvhqX79+gW2N2vWTM2aNSuJmgAAAFyWS91hHAAAwNURngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAG1wqPBljNHbsWAUFBcnb21tRUVHat2/fNbd55ZVX5HA4nJYmTZo49bl06ZKGDh2qWrVqycfHR71791ZaWlopzwYAAFRELhWeJk6cqGnTpik+Pl6bN29W1apVFR0drUuXLl1zu2bNmunEiRPWsmHDBqf1zz//vL788kstWrRIa9eu1fHjx/Xggw+W8mwAAEBFVKmsC8hjjNHUqVM1evRo9ezZU5L0wQcfKCAgQEuWLFG/fv0K3bZSpUoKDAwscF1GRobef/99zZ8/X126dJEkzZ07V3fccYe+/fZbtW/fvpRmBAAAKiKXOfJ08OBBpaamKioqymrz8/NTRESEkpOTr7ntvn37FBwcrFtvvVWPPPKIDh8+bK3btm2bfv31V6dxmzRponr16l1z3KysLGVmZjotAAAALhOeUlNTJUkBAQFO7QEBAda6gkRERCghIUGJiYmaNWuWDh48qLvvvlvnzp2zxvXw8FD16tVtjTthwgT5+flZS0hIyA3OEAAAVARlFp7mzZsnHx8fa/n111+LNc59992nPn36qGXLloqOjtby5cuVnp6uTz755IbqGzVqlDIyMqzlyJEjNzQeAACoGMrsmqcePXooIiLCepyVlSVJSktLU1BQkNWelpamsLCwIo9bvXp13X777dq/f78kKTAwUNnZ2UpPT3c6+pSWllbodVKS5OnpKU9PT9vzAgAAFVuZHXmqVq2aGjVqZC1NmzZVYGCgkpKSrD6ZmZnavHmzIiMjizzu+fPndeDAASuAtW7dWpUrV3Yad+/evTp8+LCtcQEAAORK1zw5HA4NHz5c48eP1xdffKGdO3cqJiZGwcHB6tWrl9Wva9eumj59uvX4xRdf1Nq1a/XTTz9p06ZN+tOf/iR3d3c9/PDD0uWLzgcOHKjY2FitXr1a27Zt04ABAxQZGckv7QAAgG0uc6sCSRoxYoQuXLigwYMHKz09XR07dlRiYqK8vLysPgcOHNDp06etx0ePHtXDDz+sM2fOyN/fXx07dtS3334rf39/q8+UKVPk5uam3r17KysrS9HR0Zo5c+ZNnx8AACj/HMYYU9ZFlAeZmZny8/NTRkaGfH19y7ocAABQgux8z7vMaTsAAIDygPAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbXCo8LV68WN26dVOtWrXkcDiUkpJSpO0WLVqkJk2ayMvLSy1atNDy5cud1htjNHbsWAUFBcnb21tRUVHat29fKc0CAABUZC4Vni5cuKCOHTvqjTfeKPI2mzZt0sMPP6yBAwdqx44d6tWrl3r16qXvvvvO6jNx4kRNmzZN8fHx2rx5s6pWraro6GhdunSplGYCAAAqKocxxpR1EVf76aefFBoaqh07digsLOyaffv27asLFy7oq6++strat2+vsLAwxcfHyxij4OBgvfDCC3rxxRclSRkZGQoICFBCQoL69etXpJoyMzPl5+enjIwM+fr63uAMAQCAK7HzPe9SR56KIzk5WVFRUU5t0dHRSk5OliQdPHhQqampTn38/PwUERFh9QEAACiqSmVdwI1KTU1VQECAU1tAQIBSU1Ot9XlthfUpSFZWlrKysqzHmZmZJVw5AAAoj8rsyNO8efPk4+NjLevXry+rUgo0YcIE+fn5WUtISEhZlwQAAFxAmYWnHj16KCUlxVratGlTrHECAwOVlpbm1JaWlqbAwEBrfV5bYX0KMmrUKGVkZFjLkSNHilUfAACoWMosPFWrVk2NGjWyFm9v72KNExkZqaSkJKe2FStWKDIyUpIUGhqqwMBApz6ZmZnavHmz1acgnp6e8vX1dVoAAABc6pqnn3/+WYcPH9bx48clSXv37pUuHz3KO0oUExOjOnXqaMKECZKk5557Tp06ddJbb72l7t27a8GCBdq6daveffddSZLD4dDw4cM1fvx43XbbbQoNDdWYMWMUHBysXr16ldlcAQBA+eRSv7b74osvFB4eru7du0uS+vXrp/DwcMXHx1t9Dh8+rBMnTliPO3TooPnz5+vdd99Vq1at9Omnn2rJkiVq3ry51WfEiBEaNmyYBg8erLZt2+r8+fNKTEyUl5fXTZ4hAAAo71zyPk+uiPs8AQBQcf2u7vMEAABwMxGeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABpcKT4sXL1a3bt1Uq1YtORwOpaSkXHebhIQEORwOp8XLy8upjzFGY8eOVVBQkLy9vRUVFaV9+/aV4kwAAEBF5VLh6cKFC+rYsaPeeOMNW9v5+vrqxIkT1nLo0CGn9RMnTtS0adMUHx+vzZs3q2rVqoqOjtalS5dKeAYAAKCiq1TWBVzpsccekyT99NNPtrZzOBwKDAwscJ0xRlOnTtXo0aPVs2dPSdIHH3yggIAALVmyRP369SuBygEAwO+FSx15Kq7z58+rfv36CgkJUc+ePbVr1y5r3cGDB5WamqqoqCirzc/PTxEREUpOTi50zKysLGVmZjotAAAA5T48NW7cWHPmzNHSpUv10UcfKTc3Vx06dNDRo0clSampqZKkgIAAp+0CAgKsdQWZMGGC/Pz8rCUkJKSUZwIAAMqDMgtP8+bNk4+Pj7WsX7++WONERkYqJiZGYWFh6tSpkxYvXix/f3+98847N1TfqFGjlJGRYS1Hjhy5ofEAAEDFUGbXPPXo0UMRERHW4zp16pTIuJUrV1Z4eLj2798vSda1UGlpaQoKCrL6paWlKSwsrNBxPD095enpWSI1AQCAiqPMjjxVq1ZNjRo1shZvb+8SGTcnJ0c7d+60glJoaKgCAwOVlJRk9cnMzNTmzZsVGRlZIs8JAAB+P1zq13Y///yzDh8+rOPHj0uS9u7dK10+epR3BCkmJkZ16tTRhAkTJEmvvvqq2rdvr0aNGik9PV2TJk3SoUOH9MQTT0iXf4k3fPhwjR8/XrfddptCQ0M1ZswYBQcHq1evXmU2VwAAUD65VHj64osvNGDAAOtx3m0E4uLi9Morr0iSDh8+LDe3/ztgdvbsWQ0aNEipqamqUaOGWrdurU2bNqlp06ZWnxEjRujChQsaPHiw0tPT1bFjRyUmJua7mSYAAMD1OIwxpqyLKA8yMzPl5+enjIwM+fr6lnU5AACgBNn5ni/3tyoAAAC4mQhPAAAANhCeAAAAbHCpC8ZdWd6lYfyZFgAAKp687/eiXApOeCqic+fOSRJ/pgUAgArs3Llz8vPzu2Yffm1XRLm5uTp+/LiqVasmh8NR6s+XmZmpkJAQHTlypEL+uo/5lX8VfY7Mr/yr6HNkfiXLGKNz584pODjY6ZZIBeHIUxG5ubmpbt26N/15fX19K+ROkYf5lX8VfY7Mr/yr6HNkfiXnekec8nDBOAAAgA2EJwAAABsITy7K09NTcXFx8vT0LOtSSgXzK/8q+hyZX/lX0efI/MoOF4wDAADYwJEnAAAAGwhPAAAANhCeAAAAbCA83QS//vqrXnrpJbVo0UJVq1ZVcHCwYmJidPz48etuO2PGDDVo0EBeXl6KiIjQli1bnNZfunRJQ4cOVa1ateTj46PevXsrLS2tFGdTuMWLF6tbt26qVauWHA6HUlJSrrtNQkKCHA6H0+Ll5eXUxxijsWPHKigoSN7e3oqKitK+fftKcSYFK878JGnRokVq0qSJvLy81KJFCy1fvtxpvavMrzh1vPLKK/nevyZNmjj1caXP6PX2p6uVl/cuj535lad9T5LWrVunBx54QMHBwXI4HFqyZMl1t1mzZo3uvPNOeXp6qlGjRkpISMjXx+5norTYnd+aNWvyvX8Oh0OpqalO/VxlfhMmTFDbtm1VrVo13XLLLerVq5f27t173e1cdh80KHXp6ekmKirKLFy40Hz//fcmOTnZtGvXzrRu3fqa2y1YsMB4eHiYOXPmmF27dplBgwaZ6tWrm7S0NKvPU089ZUJCQkxSUpLZunWrad++venQocNNmFV+H3zwgRk3bpyZPXu2kWR27Nhx3W3mzp1rfH19zYkTJ6wlNTXVqc/rr79u/Pz8zJIlS8z//u//mh49epjQ0FBz8eLFUpxNfsWZ38aNG427u7uZOHGi2b17txk9erSpXLmy2blzp9XHVeZXnDri4uJMs2bNnN6/U6dOOfVxlc9oUfanK5Wn984UY37lad8zxpjly5ebl19+2SxevNhIMp9//vk1+//444+mSpUqJjY21uzevdu8/fbbxt3d3SQmJlp97L5mpcnu/FavXm0kmb179zq9hzk5OVYfV5pfdHS0mTt3rvnuu+9MSkqKuf/++029evXM+fPnC93GlfdBwlMZ2bJli5FkDh06VGifdu3amaFDh1qPc3JyTHBwsJkwYYIxl0NZ5cqVzaJFi6w+e/bsMZJMcnJyKc+gcAcPHrQVnvz8/Apdn5ubawIDA82kSZOstvT0dOPp6Wk+/vjjEqvZDjvz+/Of/2y6d+/u1BYREWGefPJJY1xofsWtIy4uzrRq1arQ9a70Gb3e/nS18vLe5bE7v/K47+UpSrgYMWKEadasmVNb3759TXR0tPXY7mt2s9gJT2fPni20j6vOzxhjTp48aSSZtWvXFtrHlfdBTtuVkYyMDDkcDlWvXr3A9dnZ2dq2bZuioqKsNjc3N0VFRSk5OVmStG3bNv36669OfZo0aaJ69epZfcqD8+fPq379+goJCVHPnj21a9cua93BgweVmprqNEc/Pz9FRESUizkmJyc71S5J0dHRVu2uMr8bqWPfvn0KDg7WrbfeqkceeUSHDx+21rnKZ7Qo+9PVyst7p2LOT7/zfa+4r5mrCQsLU1BQkO69915t3LjRanf1+WVkZEiSatasWWgfV94HCU9l4NKlS3rppZf08MMPF/r3ek6fPq2cnBwFBAQ4tQcEBFjntFNTU+Xh4ZEvgF3Zx9U1btxYc+bM0dKlS/XRRx8pNzdXHTp00NGjR6XLc9TlOV2pvMwxNTX1uu+hXGB+xa0jIiJCCQkJSkxM1KxZs3Tw4EHdfffdOnfunDWuK3xGi7I/Xa28vHcq5vx+r/teZmamLl68WKzXzJUEBQUpPj5en332mT777DOFhITonnvu0fbt26VifiZultzcXA0fPlx33XWXmjdvXmg/V94HCU+lYN68efLx8bGW9evXW+t+/fVX/fnPf5YxRrNmzSrTOm/EteZoR2RkpGJiYhQWFqZOnTpp8eLF8vf31zvvvFPiNdtRUvNzVVfP79dffy3WOPfdd5/69Omjli1bKjo6WsuXL1d6ero++eSTEq8ZJctV9z0UTePGjfXkk0+qdevW6tChg+bMmaMOHTpoypQpZV3adQ0dOlTfffedFixYUNalFFulsi6gIurRo4ciIiKsx3Xq1JGuCE6HDh3SqlWrrvlXomvXri13d/d8v0pKS0tTYGCgJCkwMFDZ2dlKT093+j/7K/uUlsLmeKMqV66s8PBw7d+/X7o8R12eU1BQkNUvLS1NYWFhJfKcBSmp+QUGBl73PZQLzC8rK6tE6qhevbpuv/12p/evrD6jVyrK/nQ1V33vClKc+V3NVfa9klLY++fr6ytvb2+5u7vf8Gvmatq1a6cNGzZIJfSZKA3PPPOMvvrqK61bt05169a9Zl9X3gc58lQKqlWrpkaNGlmLt7e3FZz27dunlStXqlatWtccw8PDQ61bt1ZSUpLVlpubq6SkJEVGRkqSWrdurcqVKzv12bt3rw4fPmz1KS0FzbEk5OTkaOfOndaOEBoaqsDAQKc5ZmZmavPmzaU6x5KaX2RkpFPtkrRixQqrdleZX9OmTUukjvPnz+vAgQPW+1eWn9ErFWV/upqrvncFKc78ruYq+15Jud77VxKvmatJSUmx3j9Xm58xRs8884w+//xzrVq1SqGhodfdxqX3wVK9HB3GGGOys7NNjx49TN26dU1KSorTz0qzsrKsfl26dDFvv/229XjBggXG09PTJCQkmN27d5vBgweb6tWrO/2c+KmnnjL16tUzq1atMlu3bjWRkZEmMjLyps/RGGPOnDljduzYYZYtW2YkmQULFpgdO3aYEydOWH0ee+wxM3LkSOvxuHHjzNdff20OHDhgtm3bZvr162e8vLzMrl27rD6vv/66qV69ulm6dKn573//a3r27FkmP5cuzvw2btxoKlWqZN58802zZ88eExcXV+BPbV1hfkWp4+rP6AsvvGDWrFljDh48aDZu3GiioqJM7dq1zcmTJ60+rvIZvd7+VJ7fu+LMrzzte8YYc+7cObNjxw6zY8cOI8lMnjzZ7Nixw/rF8siRI81jjz1m9c+7VcHf/vY3s2fPHjNjxowCb1Vwvf/Guur8pkyZYpYsWWL27dtndu7caZ577jnj5uZmVq5c6ZLzGzJkiPHz8zNr1qxx+g785ZdfrD7laR8kPN0EeT9tL2hZvXq11a9+/fomLi7Oadu3337b1KtXz3h4eJh27dqZb7/91mn9xYsXzdNPP21q1KhhqlSpYv70pz85fZnfTHPnzi1wjlfOqVOnTqZ///7W4+HDh1vzCwgIMPfff7/Zvn2707i5ublmzJgxJiAgwHh6epquXbuavXv33tS5mWLOzxhjPvnkE3P77bcbDw8P06xZM7Ns2TKn9a4yv6LUcfVntG/fviYoKMh4eHiYOnXqmL59+5r9+/c7beNKn9Fr7U/l+b3LY2d+5WnfM1f8NP/qJW9O/fv3N506dcq3TVhYmPHw8DC33nqrmTt3br5xr/ff2JvF7vzeeOMN07BhQ+Pl5WVq1qxp7rnnHrNq1ap847rK/Ar7DrzyPSlP+6Dj8qQAAABQBFzzBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALCB8ATgd+v9999Xt27dSv15EhMTFRYWptzc3FJ/LgClj/AE4Hfp0qVLGjNmjOLi4kr9uf7whz+ocuXKmjdvXqk/F4DSR3gC8Lv06aefytfXV3fddddNeb7HH39c06ZNuynPBaB0EZ4AlGsffPCBatWqpaysLKf2Xr166bHHHit0uwULFuiBBx5warvnnns0fPjwfOM8/vjj1uMGDRpo/PjxiomJkY+Pj+rXr68vvvhCp06dUs+ePeXj46OWLVtq69atTuM88MAD2rp1qw4cOHCDMwZQ1ghPAMq1Pn36KCcnR1988YXVdvLkSS1btkx//etfC91uw4YNatOmTbGec8qUKbrrrru0Y8cOde/eXY899phiYmL06KOPavv27WrYsKFiYmJ05d9dr1evngICArR+/fpiPScA10F4AlCueXt76y9/+Yvmzp1rtX300UeqV6+e7rnnngK3SU9PV0ZGhoKDg4v1nPfff7+efPJJ3XbbbRo7dqwyMzPVtm1b9enTR7fffrteeukl7dmzR2lpaU7bBQcH69ChQ8V6TgCug/AEoNwbNGiQvvnmGx07dkySlJCQoMcff1wOh6PA/hcvXpQkeXl5Fev5WrZsaf17QECAJKlFixb52k6ePOm0nbe3t3755ZdiPScA11GprAsAgBsVHh6uVq1a6YMPPlC3bt20a9cuLVu2rND+tWrVksPh0NmzZ687dk5OTr62ypUrW/+eF9AKarv61gQ///yz/P39izgrAK6KI08AKoQnnnhCCQkJmjt3rqKiohQSElJoXw8PDzVt2lS7d+/Ot+7qU20//vhjidR36dIlHThwQOHh4SUyHoCyQ3gCUCH85S9/0dGjRzV79uxrXiieJzo6Whs2bMjXvnTpUi1evFgHDhzQa6+9pt27d+vQoUPWKcHi+vbbb+Xp6anIyMgbGgdA2SM8AagQ/Pz81Lt3b/n4+KhXr17X7T9w4EAtX75cGRkZTu3du3fXxIkT1bRpU61bt04zZ87Uli1b9OGHH95QfR9//LEeeeQRValS5YbGAVD2HObK39ICQDnWtWtXNWvWrMg3o+zTp4/uvPNOjRo1Srp8n6ewsDBNnTq1ROs6ffq0GjdurK1btyo0NLRExwZw83HkCUC5d/bsWX3++edas2aNhg4dWuTtJk2aJB8fn1KtTZJ++uknzZw5k+AEVBD82g5AuRceHq6zZ8/qjTfeUOPGjYu8XYMGDTRs2LBSrU2S2rRpU+wbcgJwPZy2AwAAsIHTdgAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2/H8ed7iEVbla9gAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "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: 2.5682454486522666, 2.2176841960818794\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "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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", 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" ] }, "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": [ "
19:24:51 CEST Created task 'top_taper' with task_id                             \n",
       "              'fdve-a3a97cc7-8f49-45e8-9e99-bb4ea38b9b2f' and task_type 'FDTD'. \n",
       "
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              View task using web UI at                                         \n",
       "              'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a3a97cc7-8f\n",
       "              49-45e8-9e99-bb4ea38b9b2f'.                                       \n",
       "
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              Task folder: 'default'.                                           \n",
       "
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      ],
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/html": [
       "
19:24:53 CEST Maximum FlexCredit cost: 0.039. Minimum cost depends on task      \n",
       "              execution details. Use 'web.real_cost(task_id)' to get the billed \n",
       "              FlexCredit cost after a simulation run.                           \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m19:24:53 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.039\u001b[0m. Minimum cost depends on task      \n",
       "\u001b[2;36m              \u001b[0mexecution details. Use \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"
    },
    {
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19:24:54 CEST status = queued                                                   \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m19:24:54 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              To cancel the simulation, use 'web.abort(task_id)' or             \n",
       "              'web.delete(task_id)' or abort/delete the task in the web UI.     \n",
       "              Terminating the Python script will not stop the job running on the\n",
       "              cloud.                                                            \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\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[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the web UI.     \n",
       "\u001b[2;36m              \u001b[0mTerminating the Python script will not stop the job running on the\n",
       "\u001b[2;36m              \u001b[0mcloud.                                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7bda50613e494b4bbc87d95b45145ec4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
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     },
     "metadata": {},
     "output_type": "display_data"
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19:27:31 CEST status = preprocess                                               \n",
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       "\u001b[2;36m19:27:31 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                               \n"
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     "metadata": {},
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     "metadata": {},
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19:27:35 CEST starting up solver                                                \n",
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      ],
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       "\u001b[2;36m19:27:35 CEST\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "
              running solver                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "56fee892c2fd41d68890f51c5d76fe2c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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19:27:49 CEST early shutoff detected at 84%, exiting.                           \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m19:27:49 CEST\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": [
       "
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      ],
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     },
     "metadata": {},
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              status = postprocess                                              \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                              \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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       "version_major": 2,
       "version_minor": 0
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      "text/plain": [
       "Output()"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
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19:27:51 CEST status = success                                                  \n",
       "
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      ],
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       "\u001b[2;36m19:27:51 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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      "text/html": [
       "
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     },
     "metadata": {},
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19:27:53 CEST View simulation result at                                         \n",
       "              'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a3a97cc7-8f\n",
       "              49-45e8-9e99-bb4ea38b9b2f'.                                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m19:27:53 CEST\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                         \n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=549790;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a3a97cc7-8f49-45e8-9e99-bb4ea38b9b2f\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=347727;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a3a97cc7-8f49-45e8-9e99-bb4ea38b9b2f\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=549790;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a3a97cc7-8f49-45e8-9e99-bb4ea38b9b2f\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=688535;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a3a97cc7-8f49-45e8-9e99-bb4ea38b9b2f\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=549790;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a3a97cc7-8f49-45e8-9e99-bb4ea38b9b2f\u001b\\\u001b[4;34m-a3a97cc7-8f\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=549790;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a3a97cc7-8f49-45e8-9e99-bb4ea38b9b2f\u001b\\\u001b[4;34m49-45e8-9e99-bb4ea38b9b2f'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:27:55 CEST loading simulation from data/simulation_data.hdf5                 \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m19:27:55 CEST\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": [
       "
"
      ]
     },
     "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": [
       "
"
      ]
     },
     "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": [
       "
              Created task 'bottom_taper' with task_id                          \n",
       "              'fdve-540042b7-76b5-426f-986a-b6abf723420c' and task_type 'FDTD'. \n",
       "
\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-540042b7-76b5-426f-986a-b6abf723420c'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m. \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              View task using web UI at                                         \n",
       "              'https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76\n",
       "              b5-426f-986a-b6abf723420c'.                                       \n",
       "
\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=611437;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=467539;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=611437;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=27999;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=611437;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[32m-540042b7-76\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=611437;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[32mb5-426f-986a-b6abf723420c'\u001b[0m\u001b]8;;\u001b\\.                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              Task folder: 'default'.                                           \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=328856;https://tidy3d.simulation.cloud/folders/folder-7a0ee478-ee62-43e0-9a9e-26a06b299b0a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                           \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6aef283742d442d5b7fe49d9859f6cda",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:27:57 CEST Maximum FlexCredit cost: 0.038. Minimum cost depends on task      \n",
       "              execution details. Use 'web.real_cost(task_id)' to get the billed \n",
       "              FlexCredit cost after a simulation run.                           \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:27:57 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.038\u001b[0m. Minimum cost depends on task      \n",
       "\u001b[2;36m              \u001b[0mexecution details. Use \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": [
       "
19:27:58 CEST status = queued                                                   \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:27:58 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              To cancel the simulation, use 'web.abort(task_id)' or             \n",
       "              'web.delete(task_id)' or abort/delete the task in the web UI.     \n",
       "              Terminating the Python script will not stop the job running on the\n",
       "              cloud.                                                            \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\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[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the web UI.     \n",
       "\u001b[2;36m              \u001b[0mTerminating the Python script will not stop the job running on the\n",
       "\u001b[2;36m              \u001b[0mcloud.                                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0aa3c80b438a42c4bfe15b98b8ff266d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:29:05 CEST starting up solver                                                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:29:05 CEST\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              running solver                                                    \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f76027f518c6400ea0f98ca46d1e3e95",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:29:18 CEST early shutoff detected at 84%, exiting.                           \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:29:18 CEST\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": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:29:19 CEST status = success                                                  \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:29:19 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              View simulation result at                                         \n",
       "              'https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76\n",
       "              b5-426f-986a-b6abf723420c'.                                       \n",
       "
\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=877653;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=218717;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=877653;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=436845;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=877653;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[4;34m-540042b7-76\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=877653;https://tidy3d.simulation.cloud/workbench?taskId=fdve-540042b7-76b5-426f-986a-b6abf723420c\u001b\\\u001b[4;34mb5-426f-986a-b6abf723420c'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fd083225d76345ae855c38ba43db5599",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:29:20 CEST loading simulation from data/simulation_data.hdf5                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:29:20 CEST\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/simulation_data.hdf5                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "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": [
       "
"
      ]
     },
     "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": [
       "
"
      ]
     },
     "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/Autograd1Intro/), 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/Autograd3InverseDesign/), 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": [
       "
"
      ]
     },
     "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": [
       "
19:29:21 CEST Created task 'full_structure' with task_id                        \n",
       "              'fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002' and task_type 'FDTD'. \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:29:21 CEST\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-faf8fd20-68e4-4c2e-a162-2651f3a7a002'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m. \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              View task using web UI at                                         \n",
       "              'https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68\n",
       "              e4-4c2e-a162-2651f3a7a002'.                                       \n",
       "
\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=112531;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=164156;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=112531;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=79430;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=112531;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[32m-faf8fd20-68\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=112531;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[32me4-4c2e-a162-2651f3a7a002'\u001b[0m\u001b]8;;\u001b\\.                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              Task folder: 'default'.                                           \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=258155;https://tidy3d.simulation.cloud/folders/folder-7a0ee478-ee62-43e0-9a9e-26a06b299b0a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                           \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b52e6c3e4f164a79b242e0917aef792b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:29:22 CEST Maximum FlexCredit cost: 0.436. Minimum cost depends on task      \n",
       "              execution details. Use 'web.real_cost(task_id)' to get the billed \n",
       "              FlexCredit cost after a simulation run.                           \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:29:22 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.436\u001b[0m. Minimum cost depends on task      \n",
       "\u001b[2;36m              \u001b[0mexecution details. Use \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": [
       "
19:29:23 CEST Maximum FlexCredit cost: 0.436. Minimum cost depends on task      \n",
       "              execution details. Use 'web.real_cost(task_id)' to get the billed \n",
       "              FlexCredit cost after a simulation run.                           \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:29:23 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.436\u001b[0m. Minimum cost depends on task      \n",
       "\u001b[2;36m              \u001b[0mexecution details. Use \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": [
       "
19:29:24 CEST status = queued                                                   \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:29:24 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              To cancel the simulation, use 'web.abort(task_id)' or             \n",
       "              'web.delete(task_id)' or abort/delete the task in the web UI.     \n",
       "              Terminating the Python script will not stop the job running on the\n",
       "              cloud.                                                            \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\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[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the web UI.     \n",
       "\u001b[2;36m              \u001b[0mTerminating the Python script will not stop the job running on the\n",
       "\u001b[2;36m              \u001b[0mcloud.                                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "460e9ef423b9485092f11a7c23fdf20d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:29:29 CEST status = preprocess                                               \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:29:29 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:29:34 CEST starting up solver                                                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:29:34 CEST\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              running solver                                                    \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8d257bce31484e6b8a4158784a9a21d4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:30:35 CEST early shutoff detected at 76%, exiting.                           \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:30:35 CEST\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": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
              status = postprocess                                              \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                              \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "476ce363bf53413bb170614c1b7e9e65",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:30:37 CEST status = success                                                  \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:30:37 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:30:39 CEST View simulation result at                                         \n",
       "              'https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68\n",
       "              e4-4c2e-a162-2651f3a7a002'.                                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:30:39 CEST\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                         \n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=433761;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=184383;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=433761;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=276098;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=433761;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[4;34m-faf8fd20-68\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=433761;https://tidy3d.simulation.cloud/workbench?taskId=fdve-faf8fd20-68e4-4c2e-a162-2651f3a7a002\u001b\\\u001b[4;34me4-4c2e-a162-2651f3a7a002'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "54dd0f7c11904dc38edba7f15b2bfec9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:30:43 CEST loading simulation from data/simulation_data.hdf5                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:30:43 CEST\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",
     "iopub.status.busy": "2023-08-18T17:29:35.898541Z",
     "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": [
       "
"
      ]
     },
     "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": [
       "
"
      ]
     },
     "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()"
   ]
  }
 ],
 "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": ".venv",
   "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": "3.13.5"
  },
  "title": "Broadband Directional Coupler Modeling | Flexcompute",
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