{ "cells": [ { "cell_type": "markdown", "id": "fe061c2b", "metadata": {}, "source": [ "# Inverse design of a 3D 2x2 MMI using Tidy3D" ] }, { "cell_type": "markdown", "id": "479cc68c-0a82-4fb2-ba8b-5016098ce27d", "metadata": {}, "source": [ "**Author: Prof. Tianyu Wang, Boston University**\n", "\n", "In this notebook, we show how to use Tidy3D to optimize a 2x2 balanced MMI by modifying the boundaries of a structure defined with a PolySlab. This is our first example illustrating inverse design for a multi-output port device with a specified output phase relationship.\n", "The epitaxy and device concept follow this paper (with modifications for better performance):\n", "\n", "`Ma, Yong, Seoijin Park, Liwei Wang, and Seng Tiong Ho. \"Ultracompact multimode interference 3-dB coupler with strong lateral confinement by deep dry etching.\" *IEEE Photonics Technology Letters 12*, no. 5 (2000): 492-494.` [DOI: 10.1109/68.841263](https://ieeexplore.ieee.org/document/841263)\n", "\n", "\"diagram\"" ] }, { "cell_type": "code", "execution_count": 1, "id": "b0b56115", "metadata": {}, "outputs": [], "source": [ "import matplotlib.pylab as plt\n", "import numpy as np\n", "\n", "import autograd as ag\n", "import autograd.numpy as anp\n", "\n", "import tidy3d as td\n", "import tidy3d.web as web" ] }, { "cell_type": "markdown", "id": "8b76491f", "metadata": {}, "source": [ "## Parameters and Materials" ] }, { "cell_type": "code", "execution_count": 2, "id": "4fc58484", "metadata": {}, "outputs": [], "source": [ "wg_sep = 0.5\n", "l_MMI = 12.0 # target MMI length\n", "w_wg = 1.0\n", "freq0 = 193414493734202.56 # central frequency for 1550 nm light\n", "fwidth = 6245676208333.328\n", "\n", "BCB_medium = td.Medium(\n", " name=\"BCB\",\n", " permittivity=1.45**2,\n", ")\n", "\n", "InP = td.Medium(\n", " name=\"InP\",\n", " permittivity=3.167**2,\n", ")\n", "Q1p3_medium = td.Medium(\n", " name=\"Q1p3\",\n", " permittivity=3.41**2,\n", ")\n", "\n", "wg_loc = (wg_sep + w_wg) / 2\n", "sim_box_cx = l_MMI / 2\n", "sim_box_cy = 0.0\n", "sim_box_cz = 2.25\n", "sim_box_lx = l_MMI + 3\n", "sim_box_ly = wg_sep + w_wg * 2 + 3\n", "sim_box_lz = 6.5" ] }, { "cell_type": "markdown", "id": "32901332", "metadata": {}, "source": [ "## Make Simulation\n", "Define a function that takes y coordinates (parameters to be designed) and returns a simulation object that can be submitted to the server." ] }, { "cell_type": "code", "execution_count": 3, "id": "18726bd3", "metadata": {}, "outputs": [], "source": [ "def make_sim(ys_half) -> td.Simulation:\n", " # fixed structures\n", " sub = td.Structure(\n", " geometry=td.Box(center=[0, 0, -5], size=[td.inf, td.inf, 10]),\n", " name=\"sub\",\n", " medium=InP,\n", " )\n", " wg1_1 = td.Structure(\n", " geometry=td.Box(center=[-2.5, wg_loc, 0.5], size=[5, w_wg, 1.0]),\n", " name=\"wg1_1\",\n", " medium=InP,\n", " )\n", " wg1_2 = td.Structure(\n", " geometry=td.Box(center=[-2.5, wg_loc, 1.325], size=[5, w_wg, 0.65]),\n", " name=\"wg1_2\",\n", " medium=Q1p3_medium,\n", " )\n", " wg1_3 = td.Structure(\n", " geometry=td.Box(center=[-2.5, wg_loc, 2.1], size=[5, w_wg, 0.9]),\n", " name=\"wg1_3\",\n", " medium=InP,\n", " )\n", " wg2_1 = td.Structure(\n", " geometry=td.Box(center=[-2.5, -wg_loc, 0.5], size=[5, w_wg, 1.0]),\n", " name=\"wg2_1\",\n", " medium=InP,\n", " )\n", " wg2_2 = td.Structure(\n", " geometry=td.Box(center=[-2.5, -wg_loc, 1.325], size=[5, w_wg, 0.65]),\n", " name=\"wg2_2\",\n", " medium=Q1p3_medium,\n", " )\n", " wg2_3 = td.Structure(\n", " geometry=td.Box(center=[-2.5, -wg_loc, 2.1], size=[5, w_wg, 0.9]),\n", " name=\"wg2_3\",\n", " medium=InP,\n", " )\n", " modesource_1 = td.ModeSource(\n", " name=\"modesource_1\",\n", " center=[-1, wg_loc, 1.325],\n", " size=[0, 2, 3.5],\n", " source_time=td.GaussianPulse(\n", " freq0=freq0,\n", " fwidth=fwidth,\n", " ),\n", " direction=\"+\",\n", " mode_spec=td.ModeSpec(num_modes=5, filter_pol=\"te\"),\n", " mode_index=0,\n", " )\n", " wg3_1 = td.Structure(\n", " geometry=td.Box(center=[l_MMI + 2.5, wg_loc, 0.5], size=[5, w_wg, 1.0]),\n", " name=\"wg3_1\",\n", " medium=InP,\n", " )\n", " wg3_2 = td.Structure(\n", " geometry=td.Box(center=[l_MMI + 2.5, wg_loc, 1.325], size=[5, w_wg, 0.65]),\n", " name=\"wg3_2\",\n", " medium=Q1p3_medium,\n", " )\n", " wg3_3 = td.Structure(\n", " geometry=td.Box(center=[l_MMI + 2.5, wg_loc, 2.1], size=[5, w_wg, 0.9]),\n", " name=\"wg3_3\",\n", " medium=InP,\n", " )\n", " wg4_1 = td.Structure(\n", " geometry=td.Box(center=[l_MMI + 2.5, -wg_loc, 0.5], size=[5, w_wg, 1.0]),\n", " name=\"wg4_1\",\n", " medium=InP,\n", " )\n", " wg4_2 = td.Structure(\n", " geometry=td.Box(center=[l_MMI + 2.5, -wg_loc, 1.325], size=[5, w_wg, 0.65]),\n", " name=\"wg4_2\",\n", " medium=Q1p3_medium,\n", " )\n", " wg4_3 = td.Structure(\n", " geometry=td.Box(center=[l_MMI + 2.5, -wg_loc, 2.1], size=[5, w_wg, 0.9]),\n", " name=\"wg4_3\",\n", " medium=InP,\n", " )\n", " modemonitor_3 = td.ModeMonitor(\n", " name=\"modemonitor_3\",\n", " center=[l_MMI + 1.0, wg_loc, 1.325], # [l_MMI + 0.1, wg_loc, 0.85],\n", " size=[0, 2, 3.5],\n", " freqs=[freq0],\n", " mode_spec=td.ModeSpec(num_modes=5, filter_pol=\"te\"),\n", " )\n", " modemonitor_4 = td.ModeMonitor(\n", " name=\"modemonitor_4\",\n", " center=[l_MMI + 1.0, -wg_loc, 1.325],\n", " size=[0, 2, 3.5],\n", " freqs=[freq0],\n", " mode_spec=td.ModeSpec(num_modes=5, filter_pol=\"te\"),\n", " )\n", "\n", " # Multimode waveguide structure to optimize.\n", " MMI = make_wg(ys_half)\n", "\n", " return td.Simulation(\n", " center=[sim_box_cx, sim_box_cy, sim_box_cz],\n", " size=[sim_box_lx, sim_box_ly, sim_box_lz],\n", " grid_spec=td.GridSpec.auto(wavelength=1.55, min_steps_per_wvl=10),\n", " run_time=50 * 1e-12,\n", " medium=BCB_medium,\n", " sources=[modesource_1],\n", " monitors=[modemonitor_3, modemonitor_4],\n", " structures=[\n", " sub,\n", " wg1_1,\n", " wg1_2,\n", " wg1_3,\n", " wg2_1,\n", " wg2_2,\n", " wg2_3,\n", " wg3_1,\n", " wg3_2,\n", " wg3_3,\n", " wg4_1,\n", " wg4_2,\n", " wg4_3,\n", " ]\n", " + MMI,\n", " )" ] }, { "cell_type": "markdown", "id": "6007fd53", "metadata": {}, "source": [ "The y coordinates for the MMI slab are defined as a set of points, and `make_sim(ys_half)` returns the polygon used in the simulation." ] }, { "cell_type": "code", "execution_count": 4, "id": "46d820a7", "metadata": {}, "outputs": [], "source": [ "# Fixed parameters\n", "num_points = 25\n", "x_start = 0\n", "x_half = l_MMI / 2\n", "xs_half = np.linspace(x_start, x_half, num_points)\n", "\n", "\n", "# Apply the symmetry\n", "def make_wg(ys_half) -> list[td.Structure]: # ys_half excludes the first point\n", " xs = anp.concatenate([xs_half, xs_half[1:] + x_half])\n", " ys_half = np.concatenate(([wg_sep / 2.0 + w_wg], ys_half))\n", " ys = anp.concatenate([ys_half, ys_half[:-1][::-1]])\n", " vertices = anp.concatenate(\n", " [\n", " anp.column_stack((xs, ys)),\n", " anp.column_stack((xs[::-1], -ys[::-1])),\n", " ]\n", " )\n", " MMIs = [\n", " td.Structure(\n", " geometry=td.PolySlab(vertices=vertices, slab_bounds=(0, 1.0), axis=2),\n", " medium=InP,\n", " ),\n", " td.Structure(\n", " geometry=td.PolySlab(vertices=vertices, slab_bounds=(1.0, 1.65), axis=2),\n", " medium=Q1p3_medium,\n", " ),\n", " td.Structure(\n", " geometry=td.PolySlab(vertices=vertices, slab_bounds=(1.65, 2.55), axis=2),\n", " medium=InP,\n", " ),\n", " ]\n", " return MMIs" ] }, { "cell_type": "markdown", "id": "f51d5961", "metadata": {}, "source": [ "## Extract the Output & Post-Processing\n", "* Define a function that measures the output intensities (for two ports) and fits them to our target (so the final loss function returns a single value regardless of the number of ports).\n", "* Mathematically, this is equivalent to the L2 loss of the output, treated as an N-dimensional complex vector, compared to the target output values." ] }, { "cell_type": "code", "execution_count": 5, "id": "a1a61e3c", "metadata": {}, "outputs": [], "source": [ "def measure_outputs_fit(\n", " sim_data: td.SimulationData,\n", ") -> float: # Smaller values are better.\n", " # For multiple outputs, measure all outputs.\n", " freq0 = sim_data.simulation.monitors[0].freqs[0]\n", " out1amp = (\n", " sim_data[\"modemonitor_3\"]\n", " .amps.sel(direction=\"+\", f=freq0, mode_index=0)\n", " .values.item()\n", " )\n", " out2amp = (\n", " sim_data[\"modemonitor_4\"]\n", " .amps.sel(direction=\"+\", f=freq0, mode_index=0)\n", " .values.item()\n", " )\n", " output_vec = anp.array([out1amp, out2amp])\n", " output_vec *= anp.exp(-1j * anp.angle(out1amp)) # Remove the common phase.\n", " return anp.sum(\n", " anp.abs(\n", " output_vec\n", " - anp.array([1 / anp.sqrt(2), 1 / anp.sqrt(2) * anp.exp(-1j * anp.pi / 2)])\n", " )\n", " ** 2\n", " )\n", " # Needs to be an array of size 1; a single scalar does not work." ] }, { "cell_type": "markdown", "id": "29a09f10", "metadata": {}, "source": [ "A function that takes raw parameters (any real number) and smoothly maps them into valid y values (between our self-specified minimum and maximum), along with a function that performs the inverse mapping." ] }, { "cell_type": "code", "execution_count": 6, "id": "f03bb312", "metadata": {}, "outputs": [], "source": [ "ys_half_min = 0.5\n", "ys_half_max = sim_box_ly / 2 - 1\n", "\n", "\n", "def get_ys_half(parameters: np.ndarray) -> np.ndarray:\n", " \"\"\"Convert arbitrary parameters to y values for the vertices (parameter range (-inf, inf) maps to ys_half range (ys_half_min, ys_half_max)).\"\"\"\n", " params_between_pm_1 = anp.tanh(np.pi * parameters)\n", " return (params_between_pm_1 + 1) / 2 * (ys_half_max - ys_half_min) + ys_half_min\n", "\n", "\n", "def get_params(ys_half: np.ndarray) -> np.ndarray:\n", " \"\"\"Inverse of the above mapping; recover parameters from ys.\"\"\"\n", " return (\n", " np.arctanh((ys_half - ys_half_min) * 2 / (ys_half_max - ys_half_min) - 1)\n", " / np.pi\n", " )\n", "\n", "\n", "params_test = 2 * (np.random.random((10,)) - 0.5)\n", "ys_test = get_ys_half(params_test)\n", "assert np.allclose(get_params(ys_test), params_test)" ] }, { "cell_type": "code", "execution_count": 7, "id": "1056d8d2", "metadata": {}, "outputs": [], "source": [ "def make_sim_params(parameters: np.ndarray) -> td.Simulation:\n", " \"\"\"Make the simulation out of raw parameters.\"\"\"\n", " ys_half = get_ys_half(parameters)\n", " return make_sim(ys_half)" ] }, { "cell_type": "code", "execution_count": 8, "id": "24a474b8", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ys_half_0 = anp.linspace((wg_sep + w_wg * 2) / 2, 0.8, num_points - 1) # Initial guess.\n", "params_0 = get_params(ys_half_0)\n", "sim = make_sim_params(params_0)\n", "sim.plot_3d()" ] }, { "cell_type": "markdown", "id": "6f74b5c7", "metadata": {}, "source": [ "## Penalty Function\n", "* Ensure the device is feasible for fabrication.\n", "* Similar to regularization in neural networks." ] }, { "cell_type": "code", "execution_count": 9, "id": "1f10d977", "metadata": {}, "outputs": [], "source": [ "from tidy3d.plugins.autograd.invdes import make_curvature_penalty\n", "\n", "curvature_penalty = make_curvature_penalty(min_radius=1.0)\n", "\n", "\n", "def penalty(params: np.ndarray) -> float:\n", " \"\"\"Compute penalty for a set of parameters.\"\"\"\n", " ys = get_ys_half(params)\n", " ys = np.concatenate(([wg_sep / 2.0 + w_wg], ys))\n", " points = anp.array([xs_half, ys]).T\n", " return curvature_penalty(points)" ] }, { "cell_type": "markdown", "id": "7de8d79b", "metadata": {}, "source": [ "## Objective Function\n", "The optimizer iteratively minimizes this objective, which combines the output measurement fit and the penalty term." ] }, { "cell_type": "code", "execution_count": 10, "id": "b3a2b7b3", "metadata": {}, "outputs": [], "source": [ "def objective(params) -> float:\n", " sim = make_sim_params(params)\n", " sim_data = web.run(sim, task_name=\"tidy3dMMIadj\")\n", " print(penalty(params))\n", " print(measure_outputs_fit(sim_data))\n", " return measure_outputs_fit(sim_data) + penalty(params)" ] }, { "cell_type": "code", "execution_count": 11, "id": "1e10eafc", "metadata": {}, "outputs": [], "source": [ "grad_fn = ag.value_and_grad(objective)" ] }, { "cell_type": "code", "execution_count": 12, "id": "e557f5d8", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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       "             a-41fa-88ce-48964d6a1e0e'.                                         \n",
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       "             execution details. Use 'web.real_cost(task_id)' to get the billed  \n",
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       "\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"
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15:52:37 -03 status = queued                                                    \n",
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       "\u001b[2;36m15:52:37 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                    \n"
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             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",
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       "\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",
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       "\u001b[2;36m             \u001b[0mTerminating the Python script will not stop the job running on the \n",
       "\u001b[2;36m             \u001b[0mcloud.                                                             \n"
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15:52:41 -03 status = preprocess                                                \n",
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15:52:46 -03 starting up solver                                                 \n",
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       "\u001b[2;36m15:52:46 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
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15:52:47 -03 running solver                                                     \n",
       "
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      ],
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       "\u001b[2;36m15:52:47 -03\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
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     "metadata": {},
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       "
15:52:55 -03 early shutoff detected at 4%, exiting.                             \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m15:52:55 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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15:52:56 -03 status = postprocess                                               \n",
       "
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      "text/plain": [
       "\u001b[2;36m15:52:56 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
      ]
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     "metadata": {},
     "output_type": "display_data"
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    {
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6f03fbcc5b7d42a89a8276b391e20ade",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
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     "metadata": {},
     "output_type": "display_data"
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15:52:59 -03 status = success                                                   \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m15:52:59 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
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    },
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     "data": {
      "text/html": [
       "
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     "metadata": {},
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    {
     "data": {
      "text/html": [
       "
15:53:01 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-c73169d2-d5d\n",
       "             a-41fa-88ce-48964d6a1e0e'.                                         \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m15:53:01 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=375229;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c73169d2-d5da-41fa-88ce-48964d6a1e0e\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=275164;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c73169d2-d5da-41fa-88ce-48964d6a1e0e\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=375229;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c73169d2-d5da-41fa-88ce-48964d6a1e0e\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=1179;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c73169d2-d5da-41fa-88ce-48964d6a1e0e\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=375229;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c73169d2-d5da-41fa-88ce-48964d6a1e0e\u001b\\\u001b[4;34m-c73169d2-d5d\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=375229;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c73169d2-d5da-41fa-88ce-48964d6a1e0e\u001b\\\u001b[4;34ma-41fa-88ce-48964d6a1e0e'\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": "04769da57cdc4e47b8f6033d2de151d5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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      "text/html": [
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       "
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      ],
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:53:05 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:53:05 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 1.1914871495818756e-11\n",
      "Autograd ArrayBox with value 1.0845485202207426\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Started working on Batch containing 1 tasks.                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:53:10 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:53:10 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a37f3b43f0f94dcd9555b11ddffd07ce",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:53:37 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m15:53:37 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
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    },
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       "
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    },
    {
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2d36baa7cc36463e99faa52002cc28e1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
     "metadata": {},
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    },
    {
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      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 1\n",
      "\tJ = 1.0845e+00\n",
      "\tgrad_norm = 7.2962e+00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
15:53:39 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d' and task_type 'FDTD'.  \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:53:39 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d'\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-5c6049e9-a00\n",
       "             4-438c-9369-ffc6c8f0367d'.                                         \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=399036;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=474297;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=399036;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=349821;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=399036;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[32m-5c6049e9-a00\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=399036;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[32m4-438c-9369-ffc6c8f0367d'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Task folder: 'default'.                                            \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=145859;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6b87d0e883424a35b19c43cb6a3a0ce0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:53:42 -03 Estimated FlexCredit cost: 1.176. 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;36m15:53:42 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "382c0a14e33b4fcd802aaa08d29ef407",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:53:46 -03 status = queued                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m15:53:46 -03\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": "968e9e95f0bd464f97f46ec8195a8b6b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:54:31 -03 status = preprocess                                                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:54:31 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:54:37 -03 starting up solver                                                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:54:37 -03\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": "728c1e64cff84e369e71ba2accb6280c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:54:50 -03 early shutoff detected at 4%, exiting.                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:54:50 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
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    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
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15:54:51 -03 status = postprocess                                               \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:54:51 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8ebeece1d8f6476395899065a3b11005",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:54:54 -03 status = success                                                   \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m15:54:54 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:54:56 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a00\n",
       "             4-438c-9369-ffc6c8f0367d'.                                         \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:54:56 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=291448;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=265139;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=291448;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=58219;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=291448;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[4;34m-5c6049e9-a00\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=291448;https://tidy3d.simulation.cloud/workbench?taskId=fdve-5c6049e9-a004-438c-9369-ffc6c8f0367d\u001b\\\u001b[4;34m4-438c-9369-ffc6c8f0367d'\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": "aee3bfbe6e444b73b2bde592f4da5707",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:54:59 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:54:59 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 0.0\n",
      "Autograd ArrayBox with value 0.8062529734229864\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Started working on Batch containing 1 tasks.                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:55:05 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:55:05 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "738624c8e4404de69a187d3a1e534eb3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:57:38 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m15:57:38 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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       "
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       "
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      ],
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       "\n"
      ]
     },
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    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d5e2e5f4386c47b5bc3cafa14da1ed0d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 2\n",
      "\tJ = 8.0625e-01\n",
      "\tgrad_norm = 6.0516e+00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
15:57:40 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-c5b56090-c581-4636-a43e-2358a903aa44' and task_type 'FDTD'.  \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:57:40 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-c5b56090-c581-4636-a43e-2358a903aa44'\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-c5b56090-c58\n",
       "             1-4636-a43e-2358a903aa44'.                                         \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=648990;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=787753;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=648990;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=310073;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=648990;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[32m-c5b56090-c58\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=648990;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[32m1-4636-a43e-2358a903aa44'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Task folder: 'default'.                                            \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=606829;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0840d4b9e0b84636aab1e9e6996a100f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:57:43 -03 Estimated FlexCredit cost: 1.176. 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;36m15:57:43 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7f89bacd57d048d2b2c4a677b7e0723c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:57:47 -03 status = queued                                                    \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:57:47 -03\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": "d61275b4013a4a3ebccec1d93d6ac333",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:59:08 -03 status = preprocess                                                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:59:08 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:59:13 -03 starting up solver                                                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:59:13 -03\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": "e785d333f3ae435db343029ebd7a13bc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:59:27 -03 early shutoff detected at 4%, exiting.                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:59:27 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "
15:59:28 -03 status = postprocess                                               \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:59:28 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ad5edb65e00747ce992c4c56f080e7da",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:59:31 -03 status = success                                                   \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:59:31 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:59:33 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c58\n",
       "             1-4636-a43e-2358a903aa44'.                                         \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:59:33 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=82016;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=325238;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=82016;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=773619;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=82016;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[4;34m-c5b56090-c58\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=82016;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c5b56090-c581-4636-a43e-2358a903aa44\u001b\\\u001b[4;34m1-4636-a43e-2358a903aa44'\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": "a7d238d993b8429fa624117319f39fec",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:59:36 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:59:36 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 1.310412275269257e-11\n",
      "Autograd ArrayBox with value 0.5603121752719921\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
15:59:37 -03 Started working on Batch containing 1 tasks.                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m15:59:37 -03\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
15:59:43 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m15:59:43 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "67d0c26963094a4ba49abffa2b298b93",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:00:28 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:00:28 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8b90ba52e8ab420db03e1b9bb146c901",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "
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      ],
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      ],
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 3\n",
      "\tJ = 5.6031e-01\n",
      "\tgrad_norm = 5.5494e+00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:00:30 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-6bef01f7-f407-481b-a1ee-e62926e630ff' and task_type 'FDTD'.  \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:00:30 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-6bef01f7-f407-481b-a1ee-e62926e630ff'\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-6bef01f7-f40\n",
       "             7-481b-a1ee-e62926e630ff'.                                         \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=60343;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=16790;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=60343;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=568484;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=60343;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[32m-6bef01f7-f40\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=60343;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[32m7-481b-a1ee-e62926e630ff'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Task folder: 'default'.                                            \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=926002;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8852cbaaada04a6e9a23a38dae354e1c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
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     "output_type": "display_data"
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      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:00:34 -03 Estimated FlexCredit cost: 1.176. 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;36m16:00:34 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2d684d8902b4481f8b89721a5d9f6e5f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:00:38 -03 status = queued                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:00:38 -03\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": "29518d73048d449d9e2ee8ad8aa4af32",
       "version_major": 2,
       "version_minor": 0
      },
      "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": [
       "
16:00:50 -03 starting up solver                                                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:00:50 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:00:51 -03 running solver                                                     \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:00:51 -03\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "751a731797d54b5fa840afb4d1767c15",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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16:01:09 -03 early shutoff detected at 4%, exiting.                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:01:09 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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       "\n"
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     },
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    },
    {
     "data": {
      "text/html": [
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16:01:10 -03 status = success                                                   \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:01:10 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
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     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f40\n",
       "             7-481b-a1ee-e62926e630ff'.                                         \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=500145;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=905710;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=500145;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=573500;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=500145;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[4;34m-6bef01f7-f40\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=500145;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6bef01f7-f407-481b-a1ee-e62926e630ff\u001b\\\u001b[4;34m7-481b-a1ee-e62926e630ff'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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       "Output()"
      ]
     },
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     "output_type": "display_data"
    },
    {
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      "text/html": [
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      ],
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       "
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      ],
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:01:13 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:01:13 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 0.00010287196003832341\n",
      "Autograd ArrayBox with value 0.37841807407707767\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Started working on Batch containing 1 tasks.                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:01:19 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:01:19 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "807446c290e242b7a23eab2f2d0f3760",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:01:49 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:01:49 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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    {
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      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d51673e849d047f59c6456bfd7ff32af",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 4\n",
      "\tJ = 3.7852e-01\n",
      "\tgrad_norm = 4.1899e+00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:01:52 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9' and task_type 'FDTD'.  \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:01:52 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9'\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-43d8518f-8b0\n",
       "             d-4a70-82a3-8f1236af0bd9'.                                         \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=764528;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=847230;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=764528;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=901160;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=764528;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[32m-43d8518f-8b0\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=764528;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[32md-4a70-82a3-8f1236af0bd9'\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=531911;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1b21ef3f216d4087a378898e660c1777",
       "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": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:01:55 -03 Estimated FlexCredit cost: 1.176. 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;36m16:01:55 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8fee8551ec814089a7341c3cfeb719c0",
       "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": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:02:00 -03 status = queued                                                    \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:02:00 -03\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": "6354ffe4b31e42e98ab2a4aeda2e5ef3",
       "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": [
       "
16:02:12 -03 starting up solver                                                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:02:12 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:02:13 -03 running solver                                                     \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:02:13 -03\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2655e4119fc947c7ae331206db1a5117",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:02:24 -03 early shutoff detected at 4%, exiting.                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:02:24 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "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": "b6a97d754c1e4576b0ccf5c5bfccacd2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:02:28 -03 status = success                                                   \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:02:28 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:02:30 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0\n",
       "             d-4a70-82a3-8f1236af0bd9'.                                         \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:02:30 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=906984;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=178670;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=906984;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=904754;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=906984;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[4;34m-43d8518f-8b0\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=906984;https://tidy3d.simulation.cloud/workbench?taskId=fdve-43d8518f-8b0d-4a70-82a3-8f1236af0bd9\u001b\\\u001b[4;34md-4a70-82a3-8f1236af0bd9'\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": "bd675c17732e48abb499cbe67eed521a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:02:33 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:02:33 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 0.011128271649457282\n",
      "Autograd ArrayBox with value 0.24685722901208346\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Started working on Batch containing 1 tasks.                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:02:39 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:02:39 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "486bb67bbeb44b438de6a503452580f5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:06:15 -03 Batch complete.                                                    \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:06:15 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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       "model_id": "801cf676790a4ca881ab54e61cfdc0c8",
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       "version_minor": 0
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      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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     "data": {
      "text/html": [
       "
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 5\n",
      "\tJ = 2.5799e-01\n",
      "\tgrad_norm = 7.5265e+00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:06:17 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a' and task_type 'FDTD'.  \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:06:17 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a'\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-dcd07df4-86c\n",
       "             e-4393-ba7e-9b5b7e78317a'.                                         \n",
       "
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      ],
      "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=219346;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=976054;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=219346;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=834471;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=219346;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[32m-dcd07df4-86c\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=219346;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[32me-4393-ba7e-9b5b7e78317a'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Task folder: 'default'.                                            \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=49393;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "53c5defa57a84389bd578448874387e6",
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      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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      "text/html": [
       "
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      ],
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       "\n"
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    {
     "data": {
      "text/html": [
       "
16:06:20 -03 Estimated FlexCredit cost: 1.176. 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;36m16:06:20 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6ec4513948d4404289c143172ddeb304",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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       "
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       "
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       "
16:06:24 -03 status = queued                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:06:24 -03\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"
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       "Output()"
      ]
     },
     "metadata": {},
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       "
16:06:31 -03 status = preprocess                                                \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:06:31 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
      ]
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      "text/html": [
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     "metadata": {},
     "output_type": "display_data"
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    {
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       "
16:06:36 -03 starting up solver                                                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:06:36 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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16:06:37 -03 running solver                                                     \n",
       "
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      ],
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       "\u001b[2;36m16:06:37 -03\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
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     "metadata": {},
     "output_type": "display_data"
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       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:06:46 -03 early shutoff detected at 4%, exiting.                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:06:46 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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      "text/html": [
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16:06:47 -03 status = postprocess                                               \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:06:47 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "Output()"
      ]
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16:06:50 -03 status = success                                                   \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:06:50 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:06:52 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86c\n",
       "             e-4393-ba7e-9b5b7e78317a'.                                         \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:06:52 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=461320;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=51415;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=461320;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=909503;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=461320;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[4;34m-dcd07df4-86c\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=461320;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dcd07df4-86ce-4393-ba7e-9b5b7e78317a\u001b\\\u001b[4;34me-4393-ba7e-9b5b7e78317a'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
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      "text/html": [
       "
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       "
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      ],
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:06:55 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:06:55 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 3.5963767960258645e-07\n",
      "Autograd ArrayBox with value 0.14899286550021512\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Started working on Batch containing 1 tasks.                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:07:01 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:07:01 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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16:07:25 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:07:25 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
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    {
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       "Output()"
      ]
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "
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      ],
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       "
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      ],
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 6\n",
      "\tJ = 1.4899e-01\n",
      "\tgrad_norm = 2.0224e+00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:07:27 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-3a6a074c-4a00-4191-ac06-8f499c04196c' and task_type 'FDTD'.  \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:07:27 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-3a6a074c-4a00-4191-ac06-8f499c04196c'\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-3a6a074c-4a0\n",
       "             0-4191-ac06-8f499c04196c'.                                         \n",
       "
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      ],
      "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=619490;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=821049;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=619490;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=706822;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=619490;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[32m-3a6a074c-4a0\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=619490;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[32m0-4191-ac06-8f499c04196c'\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=990194;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "aa87f19b428e44b49631de47dd7eecfd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     "metadata": {},
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      "text/html": [
       "
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       "
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      ],
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:07:30 -03 Estimated FlexCredit cost: 1.176. 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;36m16:07:30 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "09c53429f4c4486f844d741d0b14e380",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
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     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:07:34 -03 status = queued                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:07:34 -03\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"
    },
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       "model_id": "be16cac261a84b3aa67125422b9831e3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
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    },
    {
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      "text/html": [
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16:07:39 -03 status = preprocess                                                \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:07:39 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
      ]
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     "output_type": "display_data"
    },
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      "text/html": [
       "
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     "metadata": {},
     "output_type": "display_data"
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    {
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      "text/html": [
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16:07:44 -03 starting up solver                                                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:07:44 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             running solver                                                     \n",
       "
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      ],
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       "\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": "9583a54067de4f1fae56c09fe3e365b9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:08:00 -03 early shutoff detected at 4%, exiting.                             \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:08:00 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "\n"
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    },
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      "text/html": [
       "
             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": {
       "model_id": "021bc8648ba44a938a3c766c26a4073d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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16:08:04 -03 status = success                                                   \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:08:04 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
     "metadata": {},
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    },
    {
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      "text/html": [
       "
16:08:06 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a0\n",
       "             0-4191-ac06-8f499c04196c'.                                         \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:08:06 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=168927;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=705367;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=168927;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=443364;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=168927;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[4;34m-3a6a074c-4a0\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=168927;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3a6a074c-4a00-4191-ac06-8f499c04196c\u001b\\\u001b[4;34m0-4191-ac06-8f499c04196c'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:08:09 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:08:09 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 1.7070064538075662e-06\n",
      "Autograd ArrayBox with value 0.1026582001009208\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Started working on Batch containing 1 tasks.                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:08:15 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:08:15 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cd38a00d3ce54db7adf04a314433abfa",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:08:41 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:08:41 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
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    },
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     "data": {
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    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "283895507a5e456386030c20f93f4c8b",
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
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       "
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      ],
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 7\n",
      "\tJ = 1.0266e-01\n",
      "\tgrad_norm = 1.6868e+00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:08:43 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6' and task_type 'FDTD'.  \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:08:43 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6'\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-8af7a8f3-cd7\n",
       "             2-46d0-b33f-dfee24f4a8f6'.                                         \n",
       "
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      ],
      "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=792366;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=223544;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=792366;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=740714;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=792366;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[32m-8af7a8f3-cd7\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=792366;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[32m2-46d0-b33f-dfee24f4a8f6'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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             Task folder: 'default'.                                            \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=686007;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "842c9be00af849e9a3f33cc63341238c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
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      "text/html": [
       "
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    {
     "data": {
      "text/html": [
       "
16:08:46 -03 Estimated FlexCredit cost: 1.176. 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;36m16:08:46 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "31b5e81bcaf3437f8045aa4dc12dc714",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
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       "
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       "
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       "\n"
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       "
16:08:51 -03 status = queued                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:08:51 -03\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"
      ]
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       "model_id": "d12b3ffacbe14209a09430b8b3c33e2a",
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       "version_minor": 0
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       "Output()"
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       "
16:08:55 -03 status = preprocess                                                \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:08:55 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
      ]
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      "text/html": [
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16:09:00 -03 starting up solver                                                 \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:09:00 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
      ]
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16:09:01 -03 running solver                                                     \n",
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       "\u001b[2;36m16:09:01 -03\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
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     "metadata": {},
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       "model_id": "5acb5ab6275c440491179e59d428626c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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       "
16:09:19 -03 early shutoff detected at 4%, exiting.                             \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:09:19 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
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     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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16:09:20 -03 status = postprocess                                               \n",
       "
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      ],
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       "\u001b[2;36m16:09:20 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
      ]
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     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b6c2e4b81f594aed99ecb01ec84b4fbd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
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     "metadata": {},
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    {
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      "text/html": [
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16:09:21 -03 status = success                                                   \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:09:21 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
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     "output_type": "display_data"
    },
    {
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      "text/html": [
       "
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     "metadata": {},
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      "text/html": [
       "
16:09:23 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd7\n",
       "             2-46d0-b33f-dfee24f4a8f6'.                                         \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:09:23 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=773230;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=28958;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=773230;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=596271;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=773230;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[4;34m-8af7a8f3-cd7\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=773230;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8af7a8f3-cd72-46d0-b33f-dfee24f4a8f6\u001b\\\u001b[4;34m2-46d0-b33f-dfee24f4a8f6'\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": "9c408143f37743f296be75755afa6bfb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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      "text/html": [
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       "
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      ],
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:09:26 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:09:26 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 0.0005682527800021411\n",
      "Autograd ArrayBox with value 0.06247049438086219\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Started working on Batch containing 1 tasks.                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:09:32 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:09:32 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "04488a0568eb4825a5551d9ae3a36b2a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:09:52 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:09:52 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
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    {
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3a654da921cc4adfa9fdf63e92e748ea",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 8\n",
      "\tJ = 6.3039e-02\n",
      "\tgrad_norm = 1.8994e+00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:09:55 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e' and task_type 'FDTD'.  \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:09:55 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e'\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-158a2c9d-4aa\n",
       "             a-49bd-af41-6b93bae1b97e'.                                         \n",
       "
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      ],
      "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=685840;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=480393;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=685840;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=955000;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=685840;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[32m-158a2c9d-4aa\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=685840;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[32ma-49bd-af41-6b93bae1b97e'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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             Task folder: 'default'.                                            \n",
       "
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      ],
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=501032;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9d97341628a045b9a8cb8674576e3594",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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      "text/html": [
       "
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       "
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      ],
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       "\n"
      ]
     },
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    },
    {
     "data": {
      "text/html": [
       "
16:09:58 -03 Estimated FlexCredit cost: 1.176. 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;36m16:09:58 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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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       "Output()"
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       "
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16:10:02 -03 status = queued                                                    \n",
       "
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      ],
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       "\u001b[2;36m16:10:02 -03\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": {},
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       "model_id": "9348829ae20742e9bf37655878d9b899",
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       "Output()"
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16:10:07 -03 status = preprocess                                                \n",
       "
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       "\u001b[2;36m16:10:07 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
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      "text/html": [
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16:10:12 -03 starting up solver                                                 \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:10:12 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
      ]
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             running solver                                                     \n",
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
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     "metadata": {},
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       "Output()"
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16:10:30 -03 early shutoff detected at 4%, exiting.                             \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:10:30 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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16:10:31 -03 status = postprocess                                               \n",
       "
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       "\u001b[2;36m16:10:31 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
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     "metadata": {},
     "output_type": "display_data"
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     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ad5ad0248969444eade9820290e5a4ab",
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       "version_minor": 0
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       "Output()"
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      "text/html": [
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16:10:34 -03 status = success                                                   \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:10:34 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
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     "metadata": {},
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    },
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     "data": {
      "text/html": [
       "
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    {
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      "text/html": [
       "
16:10:36 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aa\n",
       "             a-49bd-af41-6b93bae1b97e'.                                         \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:10:36 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=919404;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=608599;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=919404;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=875899;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=919404;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[4;34m-158a2c9d-4aa\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=919404;https://tidy3d.simulation.cloud/workbench?taskId=fdve-158a2c9d-4aaa-49bd-af41-6b93bae1b97e\u001b\\\u001b[4;34ma-49bd-af41-6b93bae1b97e'\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": "352edd693f7242b4af13619e2f0c5f58",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
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      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:10:39 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:10:39 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 0.0025670907016877046\n",
      "Autograd ArrayBox with value 0.025802648174640674\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Started working on Batch containing 1 tasks.                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:10:45 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:10:45 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "model_id": "f751e01eecfa4091ab7b5a246a858dd0",
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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     "data": {
      "text/html": [
       "
16:11:14 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:11:14 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
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    },
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     "data": {
      "text/html": [
       "
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    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "939cb0fa207b4c0a9c93555275385409",
       "version_major": 2,
       "version_minor": 0
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       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/html": [
       "
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      ],
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     },
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      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 9\n",
      "\tJ = 2.8370e-02\n",
      "\tgrad_norm = 2.9723e+00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:11:17 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-3948ac76-6fda-4504-9def-8bd506173fe8' and task_type 'FDTD'.  \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:11:17 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-3948ac76-6fda-4504-9def-8bd506173fe8'\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-3948ac76-6fd\n",
       "             a-4504-9def-8bd506173fe8'.                                         \n",
       "
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      ],
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=291656;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=144824;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=291656;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=616172;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=291656;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[32m-3948ac76-6fd\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=291656;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[32ma-4504-9def-8bd506173fe8'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "
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      ],
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=986536;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "model_id": "0deab3ad6ac849c78026517685630ca9",
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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       "
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      ],
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       "\n"
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     },
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    },
    {
     "data": {
      "text/html": [
       "
16:11:20 -03 Estimated FlexCredit cost: 1.176. 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;36m16:11:20 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "df5e457619874016a9a5e9b7834f0607",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
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       "
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      ],
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      ]
     },
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    },
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     "data": {
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16:11:24 -03 status = queued                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:11:24 -03\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": {
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       "Output()"
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      "text/html": [
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16:11:42 -03 starting up solver                                                 \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:11:42 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
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             running solver                                                     \n",
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      ],
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
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     "metadata": {},
     "output_type": "display_data"
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    {
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       "model_id": "337b1657f78f453e891daf1701bc4aa7",
       "version_major": 2,
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      "text/plain": [
       "Output()"
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     },
     "metadata": {},
     "output_type": "display_data"
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    {
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      "text/html": [
       "
16:11:54 -03 early shutoff detected at 4%, exiting.                             \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:11:54 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
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     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7266cd489dd2408d92cd1dd02e169b15",
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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    {
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      "text/html": [
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16:11:58 -03 status = success                                                   \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:11:58 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
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    },
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       "
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      "text/html": [
       "
16:12:00 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fd\n",
       "             a-4504-9def-8bd506173fe8'.                                         \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:12:00 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=120139;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=181888;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=120139;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=141;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=120139;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[4;34m-3948ac76-6fd\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=120139;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3948ac76-6fda-4504-9def-8bd506173fe8\u001b\\\u001b[4;34ma-4504-9def-8bd506173fe8'\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": "d53f24b40fec41c38987428f23654181",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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       "
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      ],
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       "\n"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:12:03 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:12:03 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 0.00011907159155895129\n",
      "Autograd ArrayBox with value 0.008102693176776206\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Started working on Batch containing 1 tasks.                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:12:09 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:12:09 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5da3dfa1ef234ea3a6ef88c139863766",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:13:02 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:13:02 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
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    },
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       "
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "295136a13b094ced9cbcda06240086db",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 10\n",
      "\tJ = 8.2218e-03\n",
      "\tgrad_norm = 4.5009e-01\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:13:04 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e' and task_type 'FDTD'.  \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:13:04 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e'\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-d8a2e404-c3f\n",
       "             d-434b-8c2f-6e7963b0782e'.                                         \n",
       "
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      ],
      "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=454399;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=458580;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=454399;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=432353;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=454399;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[32m-d8a2e404-c3f\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=454399;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[32md-434b-8c2f-6e7963b0782e'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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             Task folder: 'default'.                                            \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=703207;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7d32c107e28949fe922c937f29d06706",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:13:07 -03 Estimated FlexCredit cost: 1.176. 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;36m16:13:07 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d2819b068fc146409394b715a2ae2b70",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:13:11 -03 status = queued                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:13:11 -03\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": "4592018f7a5248bfa983c0f52f89a90a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:13:46 -03 status = preprocess                                                \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:13:46 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:13:52 -03 starting up solver                                                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:13:52 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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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": "028c1fe1f4f94d7bb247d5b6040198d4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:14:11 -03 early shutoff detected at 4%, exiting.                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:14:11 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
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    },
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "325f0bf00d2a493e94449067a6adf700",
       "version_major": 2,
       "version_minor": 0
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       "Output()"
      ]
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16:14:15 -03 status = success                                                   \n",
       "
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      ],
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       "\u001b[2;36m16:14:15 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
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    },
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     "data": {
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       "
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      "text/html": [
       "
16:14:17 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3f\n",
       "             d-434b-8c2f-6e7963b0782e'.                                         \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:14:17 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=256756;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=327277;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=256756;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=649583;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=256756;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[4;34m-d8a2e404-c3f\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=256756;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d8a2e404-c3fd-434b-8c2f-6e7963b0782e\u001b\\\u001b[4;34md-434b-8c2f-6e7963b0782e'\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": "32f0f8ccffeb40fa8f851ca938ec87f5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/html": [
       "
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      ],
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       "
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      ],
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       "\n"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "
16:14:20 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:14:20 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 0.002349891506344505\n",
      "Autograd ArrayBox with value 0.003916633263534279\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Started working on Batch containing 1 tasks.                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:14:26 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:14:26 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3d0d5f8ec7f543d5bb09b86f30bb977e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "
16:15:11 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:15:11 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
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    },
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c912da52c1e447fab180015b48639885",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
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    },
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       "
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      ],
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       "
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      ],
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 11\n",
      "\tJ = 6.2665e-03\n",
      "\tgrad_norm = 2.7466e+00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:15:14 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd' and task_type 'FDTD'.  \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:15:14 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd'\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-a6ed8466-0ab\n",
       "             2-454a-ba98-d0bdfd6858dd'.                                         \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=122387;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=561597;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=122387;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=403555;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=122387;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[32m-a6ed8466-0ab\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=122387;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[32m2-454a-ba98-d0bdfd6858dd'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/html": [
       "
             Task folder: 'default'.                                            \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=602723;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "21f38b542c3d42658a47532578d05f49",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:15:17 -03 Estimated FlexCredit cost: 1.176. 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;36m16:15:17 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "69137b4d52cc48f59bcfe459adc2efdb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:15:20 -03 status = queued                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:15:20 -03\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": "b7e964dc53e54d54843cc3b739a97e2d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:15:29 -03 status = preprocess                                                \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:15:29 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:15:35 -03 starting up solver                                                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:15:35 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             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": "e754e2130b834d4aa83468a5c84e705a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:15:46 -03 early shutoff detected at 4%, exiting.                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:15:46 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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       "
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       "\n"
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     },
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    },
    {
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16:15:47 -03 status = success                                                   \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:15:47 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab\n",
       "             2-454a-ba98-d0bdfd6858dd'.                                         \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=392603;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=713340;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=392603;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=224123;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=392603;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[4;34m-a6ed8466-0ab\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=392603;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a6ed8466-0ab2-454a-ba98-d0bdfd6858dd\u001b\\\u001b[4;34m2-454a-ba98-d0bdfd6858dd'\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": "d8c123f9e1a345e8b30171344cad6c7f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     "metadata": {},
     "output_type": "display_data"
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     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:15:50 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:15:50 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 0.0003520986322037858\n",
      "Autograd ArrayBox with value 0.004899877599120619\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:15:51 -03 Started working on Batch containing 1 tasks.                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:15:51 -03\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:15:56 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:15:56 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "61299025e9ee4077a72b10ef68fde10e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:16:23 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:16:23 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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     "data": {
      "text/html": [
       "
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      ],
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       "
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       "\n"
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     },
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     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "695ac9ec6fe845b79c15716b397a261a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 12\n",
      "\tJ = 5.2520e-03\n",
      "\tgrad_norm = 6.3671e-01\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:16:25 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-dac97da6-64a9-46d4-b078-f80977589ce2' and task_type 'FDTD'.  \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:16:25 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-dac97da6-64a9-46d4-b078-f80977589ce2'\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-dac97da6-64a\n",
       "             9-46d4-b078-f80977589ce2'.                                         \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=234563;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=272014;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=234563;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=515029;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=234563;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[32m-dac97da6-64a\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=234563;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[32m9-46d4-b078-f80977589ce2'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Task folder: 'default'.                                            \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=535795;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5c1f2ecefdf341d781d6446113af4647",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:16:29 -03 Estimated FlexCredit cost: 1.176. 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;36m16:16:29 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5fb5ad0cea2c41faa174464d56780776",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:16:32 -03 status = queued                                                    \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:16:32 -03\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": "7cc94e7271b643b3aa392f5057ab2da7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:16:48 -03 starting up solver                                                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:16:48 -03\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": "519fa2f0a148483cb0be19fc08790f13",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:17:07 -03 early shutoff detected at 4%, exiting.                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:17:07 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             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
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:17:11 -03 status = success                                                   \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:17:11 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:17:13 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a\n",
       "             9-46d4-b078-f80977589ce2'.                                         \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:17:13 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=859755;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=68667;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=859755;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=140439;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=859755;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[4;34m-dac97da6-64a\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=859755;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dac97da6-64a9-46d4-b078-f80977589ce2\u001b\\\u001b[4;34m9-46d4-b078-f80977589ce2'\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": "5bbc8c41525c447cbe3c201f19907d4a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
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    },
    {
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      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "
16:17:16 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:17:16 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 0.00011586847629584113\n",
      "Autograd ArrayBox with value 0.0078057860869055334\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Started working on Batch containing 1 tasks.                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:17:22 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:17:22 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0d06dc46c77e4ec092c936fda9f60e1d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:17:44 -03 Batch complete.                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:17:44 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
      ]
     },
     "metadata": {},
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    },
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      "text/html": [
       "
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    {
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "209d9d19204b44a5aae8d6854d48c451",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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       "
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       "
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      ],
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step = 13\n",
      "\tJ = 7.9217e-03\n",
      "\tgrad_norm = 6.0158e-01\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:17:46 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
       "             'fdve-65dbff02-c404-4d86-89ce-99a952761ec6' and task_type 'FDTD'.  \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:17:46 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-65dbff02-c404-4d86-89ce-99a952761ec6'\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-65dbff02-c40\n",
       "             4-4d86-89ce-99a952761ec6'.                                         \n",
       "
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      ],
      "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=106560;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=543145;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=106560;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=443447;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=106560;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[32m-65dbff02-c40\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=106560;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[32m4-4d86-89ce-99a952761ec6'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Task folder: 'default'.                                            \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=140362;https://tidy3d.simulation.cloud/folders/folder-f9e994c1-6315-4b44-af3a-c2cb1435b23a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "46d4d21b785542edbc3742c1dfcf2c40",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:17:50 -03 Estimated FlexCredit cost: 1.176. 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;36m16:17:50 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5aaf48327047470e87c42d679839f907",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:17:54 -03 status = queued                                                    \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:17:54 -03\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": "4be8ae3f634c40af8f1161a7e2500091",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:18:40 -03 status = preprocess                                                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:18:40 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:18:45 -03 starting up solver                                                 \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:18:45 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:18:46 -03 running solver                                                     \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:18:46 -03\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4ff8d675674b45f5ac40c44d3b4334c7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:19:03 -03 early shutoff detected at 4%, exiting.                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:19:03 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m4\u001b[0m%, exiting.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
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     },
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16:19:04 -03 status = postprocess                                               \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:19:04 -03\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_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:19:08 -03 status = success                                                   \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:19:08 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:19:10 -03 View simulation result at                                          \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c40\n",
       "             4-4d86-89ce-99a952761ec6'.                                         \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:19:10 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=313523;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=731274;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=313523;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=873533;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=313523;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[4;34m-65dbff02-c40\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=313523;https://tidy3d.simulation.cloud/workbench?taskId=fdve-65dbff02-c404-4d86-89ce-99a952761ec6\u001b\\\u001b[4;34m4-4d86-89ce-99a952761ec6'\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": "ded3446857324d16bbe0485d6ac8fb26",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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      ],
      "text/plain": []
     },
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     "output_type": "display_data"
    },
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      "text/html": [
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       "
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      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:19:12 -03 Loading simulation from simulation_data.hdf5                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:19:12 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 0.00025578170972243784\n",
      "Autograd ArrayBox with value 0.012093082778784616\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:19:13 -03 Started working on Batch containing 1 tasks.                       \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m16:19:13 -03\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m1\u001b[0m tasks.                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:19:27 -03 Maximum FlexCredit cost: 1.208 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:19:27 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.208\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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     "output_type": "stream",
     "text": [
      "step = 14\n",
      "\tJ = 1.2349e-02\n",
      "\tgrad_norm = 9.2290e-01\n"
     ]
    },
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16:19:56 -03 Created task 'tidy3dMMIadj' with resource_id                       \n",
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       "\u001b[2;36m16:19:56 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tidy3dMMIadj'\u001b[0m with resource_id                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-cdfa82e1-3be3-46e8-8b5a-e26b91d43291'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
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       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-cdfa82e1-3be\n",
       "             3-46e8-8b5a-e26b91d43291'.                                         \n",
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       "\u001b[2;36m             \u001b[0m\u001b]8;id=672138;https://tidy3d.simulation.cloud/workbench?taskId=fdve-cdfa82e1-3be3-46e8-8b5a-e26b91d43291\u001b\\\u001b[32m3-46e8-8b5a-e26b91d43291'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
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16:20:08 -03 Estimated FlexCredit cost: 1.176. 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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      ],
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       "\u001b[2;36m16:20:08 -03\u001b[0m\u001b[2;36m \u001b[0mEstimated FlexCredit cost: \u001b[1;36m1.176\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"
      ]
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     "metadata": {},
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       "             '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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       "\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",
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       "\u001b[2;36m             \u001b[0mTerminating the Python script will not stop the job running on the \n",
       "\u001b[2;36m             \u001b[0mcloud.                                                             \n"
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16:20:16 -03 status = preprocess                                                \n",
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16:20:21 -03 starting up solver                                                 \n",
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       "\u001b[2;36m16:20:21 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
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16:20:22 -03 running solver                                                     \n",
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       "             3-46e8-8b5a-e26b91d43291'.                                         \n",
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       "\u001b[2;36m             \u001b[0m\u001b]8;id=807897;https://tidy3d.simulation.cloud/workbench?taskId=fdve-cdfa82e1-3be3-46e8-8b5a-e26b91d43291\u001b\\\u001b[4;34m3-46e8-8b5a-e26b91d43291'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
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16:20:36 -03 Loading simulation from simulation_data.hdf5                       \n",
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       "\u001b[2;36m16:20:36 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from simulation_data.hdf5                       \n"
      ]
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autograd ArrayBox with value 0.00046923602303622434\n",
      "Autograd ArrayBox with value 0.016732958016607083\n"
     ]
    },
    {
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
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    {
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     "output_type": "stream",
     "text": [
      "step = 15\n",
      "\tJ = 1.7202e-02\n",
      "\tgrad_norm = 1.2442e+00\n"
     ]
    }
   ],
   "source": [
    "import optax\n",
    "import pickle\n",
    "\n",
    "td.config.logging_level = \"ERROR\"\n",
    "\n",
    "# Hyperparameters\n",
    "num_steps = 15\n",
    "learning_rate = 0.01\n",
    "\n",
    "# Initialize the Adam optimizer with the starting parameters.\n",
    "params = np.array(params_0).copy()\n",
    "schedule = optax.piecewise_constant_schedule(\n",
    "    init_value=learning_rate, boundaries_and_scales={10: 0.5}\n",
    ")\n",
    "optimizer = optax.adam(\n",
    "    learning_rate=schedule,\n",
    "    b1=0.9,  # beta1\n",
    "    b2=0.99,  # beta2: default 0.999\n",
    "    eps=1e-8,\n",
    ")\n",
    "# optimizer = optax.sgd(learning_rate=learning_rate)\n",
    "opt_state = optimizer.init(params)\n",
    "\n",
    "# Store history.\n",
    "objective_history = []\n",
    "param_history = [params]\n",
    "\n",
    "for i in range(num_steps):\n",
    "    # Compute the gradient and current objective function value.\n",
    "    value, gradient = grad_fn(params)\n",
    "\n",
    "    # Convert NaNs to 0 (infinite radius of curvature) and multiply all values by -1 to maximize the objective.\n",
    "\n",
    "    # Outputs.\n",
    "    print(f\"step = {i + 1}\")\n",
    "    print(f\"\\tJ = {value:.4e}\")\n",
    "    print(f\"\\tgrad_norm = {np.linalg.norm(gradient):.4e}\")\n",
    "\n",
    "    # Compute and apply the optimizer updates based on the gradient.\n",
    "    updates, opt_state = optimizer.update(gradient, opt_state, params)\n",
    "    params = optax.apply_updates(params, updates)\n",
    "    params = np.array(params)\n",
    "\n",
    "    # Save history.\n",
    "    objective_history.append(value)\n",
    "    param_history.append(params)\n",
    "\n",
    "checkpoint = {\n",
    "    \"params\": params,\n",
    "    \"opt_state\": opt_state,\n",
    "    \"objective_history\": objective_history,\n",
    "    \"param_history\": param_history,\n",
    "    \"last_step\": num_steps,\n",
    "}\n",
    "\n",
    "with open(\"checkpoint.pkl\", \"wb\") as f:\n",
    "    pickle.dump(checkpoint, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "247f0e4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "params_best = param_history[-1]\n",
    "ax = plt.plot(objective_history)\n",
    "plt.xlabel(\"iteration number\")\n",
    "plt.ylabel(\"objective function\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df084b0b-4d5c-4b76-bf04-486ebe4af6f6",
   "metadata": {},
   "source": [
    "We observe that the objective function decreases, indicating that adjoint optimization improves the MMI performance over successive iterations. The device is also more compact than the one reported in the reference, underscoring the power of inverse design."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "53a439fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_best = make_sim_params(param_history[-1])\n",
    "ax = sim_best.plot(z=0.01)\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Passive photonic integrated circuit components"
  ],
  "description": "This notebook demonstrates how to perform inverse design of a 3D 2x2 multimode interference coupler using Tidy3D.",
  "feature_image": "./img/autogradMMI.png",
  "features": [
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