![](\"img/linear_taper.png\")
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"w_in = 10 # input waveguied width\n",
"w_out = 0.5 # output waveguide width\n",
"t_wg = 0.11 # waveguide thickness\n",
"inf_eff = 1e3 # effective infinity of the model\n",
"\n",
"# define the substrate structure\n",
"sub = td.Structure(\n",
" geometry=td.Box.from_bounds(rmin=(-inf_eff, -inf_eff, -inf_eff), rmax=(inf_eff, inf_eff, 0)),\n",
" medium=sio2,\n",
")\n",
"\n",
"# define a function to construct the simulation given the taper length\n",
"def linear_taper_sim(L_t):\n",
"\n",
" # vertices of the taper\n",
" vertices = [\n",
" [-inf_eff, w_in / 2],\n",
" [0, w_in / 2],\n",
" [L_t, w_out / 2],\n",
" [inf_eff, w_out / 2],\n",
" [inf_eff, -w_out / 2],\n",
" [L_t, -w_out / 2],\n",
" [0, -w_in / 2],\n",
" [-inf_eff, -w_in / 2],\n",
" ]\n",
"\n",
" # construct the taper structure using a PolySlab\n",
" linear_taper = td.Structure(\n",
" geometry=td.PolySlab(vertices=vertices, axis=2, slab_bounds=(0, t_wg)), medium=si\n",
" )\n",
"\n",
" # add a mode source that launches the TE0 mode at the input waveguide\n",
" mode_source = td.ModeSource(\n",
" center=(-lda0 / 2, 0, t_wg / 2),\n",
" size=(0, 1.2 * w_in, 6 * t_wg),\n",
" source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
" direction=\"+\",\n",
" mode_spec=td.ModeSpec(num_modes=1, target_neff=n_si),\n",
" mode_index=0,\n",
" )\n",
"\n",
" # add a field monitor to visualize the field distribution at z=t_wg/2\n",
" field_monitor = td.FieldMonitor(\n",
" center=(0, 0, t_wg / 2), size=(td.inf, td.inf, 0), freqs=[freq0], name=\"field\"\n",
" )\n",
"\n",
" # add a flux monitor to measure transmission to the output waveguide\n",
" flux_monitor = td.FluxMonitor(\n",
" center=(lda0 / 2 + L_t, 0, t_wg / 2),\n",
" size=(0, 2 * w_out, 6 * t_wg),\n",
" freqs=freqs,\n",
" name=\"flux\",\n",
" )\n",
"\n",
" # define simulation domain size\n",
" Lx = L_t + 2 * lda0\n",
" Ly = w_in + 2 * lda0\n",
" Lz = t_wg + 1.5 * lda0\n",
" sim_size = (Lx, Ly, Lz)\n",
"\n",
" run_time = 3e-12 # run time of the simulation\n",
"\n",
" # define simulation\n",
" sim = td.Simulation(\n",
" center=(L_t / 2, 0, t_wg),\n",
" size=sim_size,\n",
" grid_spec=td.GridSpec.auto(min_steps_per_wvl=20, wavelength=lda0),\n",
" structures=[linear_taper, sub],\n",
" sources=[mode_source],\n",
" monitors=[field_monitor, flux_monitor],\n",
" run_time=run_time,\n",
" boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()), # pml is used in all boundaries\n",
" symmetry=(0, -1, 0),\n",
" ) # a pec symmetry plane at y=0 can be used to reduce the grid points of the simulation\n",
" return sim"
]
},
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"id": "1e504189",
"metadata": {},
"source": [
"With the `linear_taper_sim` function defined, we can use it to construct a simulation batch. We aim to simulate taper lengths of 10 $\\mu m$, 20 $\\mu m$, 50 $\\mu m$, and 100 $\\mu m$.\n",
"\n",
"To visually verify the simulation setup, we can take a simulation from the batch and use the `plot` method."
]
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"
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" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: divide by zero encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n",
"/Users/twhughes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/numpy/linalg/linalg.py:2139: RuntimeWarning: invalid value encountered in det\n",
" r = _umath_linalg.det(a, signature=signature)\n"
]
}
],
"source": [
"t_slabs = np.linspace(t_wg, 0.4, 30) # range of slab waveguide thickness\n",
"n_eff = np.zeros(len(t_slabs)) # effective index of the slab waveguide\n",
"\n",
"for i, t_slab in enumerate(t_slabs):\n",
" # build the slab\n",
" slab = td.Structure(\n",
" geometry=td.Box.from_bounds(rmin=(-inf_eff, -inf_eff, 0), rmax=(inf_eff, inf_eff, t_slab)),\n",
" medium=si,\n",
" )\n",
"\n",
" # define simulation domain size\n",
" Lx = lda0\n",
" Ly = 0 \n",
" Lz = 10 * t_slab\n",
" sim_size = (Lx, Ly, Lz)\n",
"\n",
" # define simulation\n",
" sim = td.Simulation(\n",
" center=(0, 0, t_slab / 2),\n",
" size=sim_size,\n",
" grid_spec=td.GridSpec.auto(min_steps_per_wvl=50, wavelength=lda0),\n",
" structures=[slab, sub],\n",
" sources=[], # for mode solver, no source or monitor is needed\n",
" monitors=[],\n",
" run_time=1e-15,\n",
" boundary_spec=td.BoundarySpec.pml(z=True),\n",
" ) # pml is applied in z direction and\n",
" # periodic condition is applied in other directions\n",
"\n",
" # define a mode solver\n",
" mode_solver = ModeSolver(\n",
" simulation=sim,\n",
" plane=td.Box(center=(0, 0, t_slab / 2), size=(Lx, 0, Lz)),\n",
" mode_spec=td.ModeSpec(num_modes=1, target_neff=n_si),\n",
" freqs=[freq0],\n",
" )\n",
" # solve for the mode\n",
" mode_data = mode_solver.solve()\n",
"\n",
" # add the effective index to the n_eff array\n",
" n_eff[i] = np.array(mode_data.n_eff[0])"
]
},
{
"cell_type": "markdown",
"id": "80d5367c",
"metadata": {},
"source": [
"To order to obtain the waveguide thickness given an effective index, we perform a polynomial fitting using `Numpy`'s `polyfit` method to the effective index obtained from the previous step."
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "dfcd51c1",
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{
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],
"source": [
"job = web.Job(simulation=sim, task_name=\"luneburg_lens_taper\")\n",
"sim_data = job.run(path=\"data/simulation_data.hdf5\")"
]
},
{
"cell_type": "markdown",
"id": "96585808",
"metadata": {},
"source": [
"After the simulation is complete, we can visualize the field distribution. In the Luneburg lens region, the wave front converges into a focus and the coupling to the output waveguide is efficient."
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "1855adf3",
"metadata": {
"execution": {
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"outputs": [
{
"data": {
"text/plain": [
"![](\"img/semi_lens_taper.png\")
"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "4aafe94a",
"metadata": {
"execution": {
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},
"outputs": [],
"source": [
"t_wg = 0.26 # thickness of the waveguide\n",
"w_0 = 0.45 # width of the input waveguide\n",
"w_6 = 9 # width of the output waveguide\n",
"\n",
"# optimized design parameters\n",
"m_i = [3, 1.1, 0.01, 3, 0.32, 2.55]\n",
"w_i = [w_0, 1.7, 3.3, 9.06, 10, 3.19, w_6]\n",
"L_i = [1, 3.61, 0.05, 0.7, 3.11, 1.03]\n",
"\n",
"L_tot = np.sum(L_i) # total length of the device"
]
},
{
"cell_type": "markdown",
"id": "5d0141c0",
"metadata": {},
"source": [
"The width of each segment of the device is described by $w(x_i)=(w_i-w_{i+1})|\\frac{x_i-L_i}{L_i}|^{m_i}$, where $i=1,2,...,6$, $w_i$ is the width at the begining of each segment, $L_i$ is the length of each segment, and $m_i$ is the curvature of each segment. The optimized values of $w_i$, $L_i$, and $m_i$ are listed above.\n",
"\n",
"The structure of the deive will be constructed using a series of [PolySlabs](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.PolySlab.html?highlight=polyslab). The vertices are calculated from the above equation and the optimized parameters."
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "a7a76f40",
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"execution": {
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"outputs": [
{
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\n",
"text/plain": [
"\n",
"\n"
],
"text/plain": [
"\n",
"\u001b[?25h"
]
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"source": [
"job = web.Job(simulation=sim, task_name=\"semi_lens_beam_expander\")\n",
"sim_data = job.run(path=\"data/simulation_data.hdf5\")"
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{
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"source": [
"Plot the field distribution."
]
},
{
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"execution_count": 24,
"id": "f260899d",
"metadata": {
"execution": {
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"iopub.status.busy": "2023-02-03T04:58:08.748506Z",
"iopub.status.idle": "2023-02-03T04:58:09.618062Z",
"shell.execute_reply": "2023-02-03T04:58:09.617758Z"
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"↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/6.3 kB • ? • -:--:--\n↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/6.3 kB • ? • -:--:--\n", "text/plain": "\r\u001b[2K\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m0.0%\u001b[0m • \u001b[32m0.0/6.3 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m-:--:--\u001b[0m\n\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m0.0%\u001b[0m • \u001b[32m0.0/6.3 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m-:--:--\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "13cde12aae6e4a7d8cc04f510823a647": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_aaf3d30a43de4104a148c34dd9696e79", "msg_id": "", "outputs": [ { "data": { "text/html": "
🏃 Finishing 'semi_lens_beam_expander'...\n🏃 Finishing 'semi_lens_beam_expander'...\n", "text/plain": "\r\u001b[2K\u001b[32m🏃 \u001b[0m \u001b[1;32mFinishing 'semi_lens_beam_expander'...\u001b[0m\n\u001b[32m🏃 \u001b[0m \u001b[1;32mFinishing 'semi_lens_beam_expander'...\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "13df8713ace248069f8c7c9adb4f49ca": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "157b2b0df52f4608a7660c92063b2ea4": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_2b1e3422f2664acbbbe19d6c8621202d", "msg_id": "", "outputs": [ { "data": { "text/html": "
🚶 Starting 'semi_lens_beam_expander'...\n🚶 Starting 'semi_lens_beam_expander'...\n", "text/plain": "\r\u001b[2K\u001b[32m🚶 \u001b[0m \u001b[1;32mStarting 'semi_lens_beam_expander'...\u001b[0m\n\u001b[32m🚶 \u001b[0m \u001b[1;32mStarting 'semi_lens_beam_expander'...\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "1c27716ca03543ae99cf78bb55d63568": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_13df8713ace248069f8c7c9adb4f49ca", "msg_id": "", "outputs": [ { "data": { "text/html": "
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↓ monitor_data.hdf5 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 99.6% • 60.2/60.5 MB • 8.5 MB/s • 0:00:01\n↓ monitor_data.hdf5 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 99.6% • 60.2/60.5 MB • 8.5 MB/s • 0:00:01\n", "text/plain": "\r\u001b[2K\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m \u001b[35m99.6%\u001b[0m • \u001b[32m60.2/60.5 MB\u001b[0m • \u001b[31m8.5 MB/s\u001b[0m • \u001b[36m0:00:01\u001b[0m\n\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m \u001b[35m99.6%\u001b[0m • \u001b[32m60.2/60.5 MB\u001b[0m • \u001b[31m8.5 MB/s\u001b[0m • \u001b[36m0:00:01\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "2b1e3422f2664acbbbe19d6c8621202d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "2c1d236a3bf24607b611dddb90f2251f": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "3dde3987b9704376bc1dcfdbf2f03cee": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "3de6246ad2bf4012b6ad991bd50f32d5": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_89d79f19f4544995b053e5170eab71bc", "msg_id": "", "outputs": [ { "data": { "text/html": "
↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/6.2 kB • ? • -:--:--\n↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/6.2 kB • ? • -:--:--\n", "text/plain": "\r\u001b[2K\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m0.0%\u001b[0m • \u001b[32m0.0/6.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m-:--:--\u001b[0m\n\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m0.0%\u001b[0m • \u001b[32m0.0/6.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m-:--:--\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "44252167ce8f417680ebd0747ed4c6aa": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "4b813c7757514f30bc85261e30855dae": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_77c45c22b8f149bb938dee454e427c94", "msg_id": "ee333ce2-2f1ad261c3ea4382a71b7280_12020_9", "outputs": [ { "data": { "text/html": "
L_t=10: status = success ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00\nL_t=20: status = success ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00\nL_t=50: status = success ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00\nL_t=100: status = running ━━━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━ 57% -:--:--\nL_t=10: status = success ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00\nL_t=20: status = success ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00\nL_t=50: status = success ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00\nL_t=100: status = running ━━━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━ 57% -:--:--\n", "text/plain": "\r\u001b[2K\u001b[1A\u001b[2K\u001b[1A\u001b[2K\u001b[1A\u001b[2KL_t=10: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nL_t=20: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nL_t=50: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nL_t=100: status = running \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m 57%\u001b[0m \u001b[36m-:--:--\u001b[0m\nL_t=10: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nL_t=20: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nL_t=50: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nL_t=100: status = running \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m 57%\u001b[0m \u001b[36m-:--:--\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "539c0d5945de440e8a7c46732fdf61b8": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_908f17b51fec41fa952aa7c1c7ce8e0b", "msg_id": "", "outputs": [ { "data": { "text/html": "
↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/6.2 kB • ? • -:--:--\n↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/6.2 kB • ? • -:--:--\n", "text/plain": "\r\u001b[2K\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m0.0%\u001b[0m • \u001b[32m0.0/6.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m-:--:--\u001b[0m\n\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m0.0%\u001b[0m • \u001b[32m0.0/6.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m-:--:--\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "5ca478d518414ac28329cadef910eae4": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_44252167ce8f417680ebd0747ed4c6aa", "msg_id": "", "outputs": [ { "data": { "text/html": "
↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100.0% • 38.0/38.0 kB • ? • 0:00:00\n↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100.0% • 38.0/38.0 kB • ? • 0:00:00\n", "text/plain": "\r\u001b[2K\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m38.0/38.0 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m38.0/38.0 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "5f000cd2d6b1419f9f6193e7f45ddb40": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "6639069fd083489b9fcb48385ccdfc2f": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_d827da4984044c81a67412492b66fe00", "msg_id": "", "outputs": [ { "data": { "text/html": "
↓ monitor_data.hdf5 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸━━━━━━ 84.8% • 6.8/8.0 MB • 6.9 MB/s • 0:00:01\n↓ monitor_data.hdf5 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸━━━━━━ 84.8% • 6.8/8.0 MB • 6.9 MB/s • 0:00:01\n", "text/plain": "\r\u001b[2K\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━━━━━━\u001b[0m \u001b[35m84.8%\u001b[0m • \u001b[32m6.8/8.0 MB\u001b[0m • \u001b[31m6.9 MB/s\u001b[0m • \u001b[36m0:00:01\u001b[0m\n\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━━━━━━\u001b[0m \u001b[35m84.8%\u001b[0m • \u001b[32m6.8/8.0 MB\u001b[0m • \u001b[31m6.9 MB/s\u001b[0m • \u001b[36m0:00:01\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "74d8bf022c724c0a82fee4b5e077a4d2": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "77c45c22b8f149bb938dee454e427c94": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "7dd315ef7a074bc9a5eccc9fc37253cd": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "8083f93d51224baf8d978180d3cbe501": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_2c1d236a3bf24607b611dddb90f2251f", "msg_id": "", "outputs": [ { "data": { "text/html": "
↓ monitor_data.hdf5 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸━ 96.4% • 13.4/13.9 MB • 5.3 MB/s • 0:00:01\n↓ monitor_data.hdf5 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸━ 96.4% • 13.4/13.9 MB • 5.3 MB/s • 0:00:01\n", "text/plain": "\r\u001b[2K\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━\u001b[0m \u001b[35m96.4%\u001b[0m • \u001b[32m13.4/13.9 MB\u001b[0m • \u001b[31m5.3 MB/s\u001b[0m • \u001b[36m0:00:01\u001b[0m\n\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━\u001b[0m \u001b[35m96.4%\u001b[0m • \u001b[32m13.4/13.9 MB\u001b[0m • \u001b[31m5.3 MB/s\u001b[0m • \u001b[36m0:00:01\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "8561600403954d08a302dab489a61cdd": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "89d79f19f4544995b053e5170eab71bc": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "908f17b51fec41fa952aa7c1c7ce8e0b": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "a40b0f2cb6774c148830a0b5da147df4": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_3dde3987b9704376bc1dcfdbf2f03cee", "msg_id": "", "outputs": [ { "data": { "text/html": "
↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/6.2 kB • ? • -:--:--\n↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0% • 0.0/6.2 kB • ? • -:--:--\n", "text/plain": "\r\u001b[2K\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m0.0%\u001b[0m • \u001b[32m0.0/6.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m-:--:--\u001b[0m\n\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m0.0%\u001b[0m • \u001b[32m0.0/6.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m-:--:--\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "aab69e21a0e349069a3fafbdd1bd7eb6": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_e8059321ac614bdf96351a5bd2f3f4ba", "msg_id": "", "outputs": [ { "data": { "text/html": "
↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100.0% • 41.3/41.3 kB • ? • 0:00:00\n↑ simulation.json ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100.0% • 41.3/41.3 kB • ? • 0:00:00\n", "text/plain": "\r\u001b[2K\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m41.3/41.3 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.json\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m41.3/41.3 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "aaf3d30a43de4104a148c34dd9696e79": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "c08b5b49201e4ee19e8ee8a619d37872": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_8561600403954d08a302dab489a61cdd", "msg_id": "ee333ce2-2f1ad261c3ea4382a71b7280_12020_2673", "outputs": [ { "data": { "text/html": "
% done (field decay = 1.96e-03) ━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 24% -:--:--\n% done (field decay = 1.96e-03) ━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 24% -:--:--\n", "text/plain": "\r\u001b[2K% done (field decay = 1.96e-03) \u001b[38;2;249;38;114m━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m 24%\u001b[0m \u001b[36m-:--:--\u001b[0m\n% done (field decay = 1.96e-03) \u001b[38;2;249;38;114m━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m 24%\u001b[0m \u001b[36m-:--:--\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "c39c33ecc8924d35b7469ba8f8952eb0": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_f8b32bd8d95a4e99bf94b8c223b943eb", "msg_id": "", "outputs": [ { "data": { "text/html": "
🏃 Starting 'luneburg_lens_taper'...\n🏃 Starting 'luneburg_lens_taper'...\n", "text/plain": "\r\u001b[2K\u001b[32m🏃 \u001b[0m \u001b[1;32mStarting 'luneburg_lens_taper'...\u001b[0m\n\u001b[32m🏃 \u001b[0m \u001b[1;32mStarting 'luneburg_lens_taper'...\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "cd2702af1ab547088f1eb687a1ec3de2": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_5f000cd2d6b1419f9f6193e7f45ddb40", "msg_id": "", "outputs": [ { "data": { "text/html": "
% done (field decay = 8.10e-06) ━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━ 44% 0:01:42\n% done (field decay = 8.10e-06) ━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━ 44% 0:01:42\n", "text/plain": "\r\u001b[2K% done (field decay = 8.10e-06) \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m 44%\u001b[0m \u001b[36m0:01:42\u001b[0m\n% done (field decay = 8.10e-06) \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m 44%\u001b[0m \u001b[36m0:01:42\u001b[0m" }, "metadata": {}, "output_type": "display_data" } ], "tabbable": null, "tooltip": null } }, "d827da4984044c81a67412492b66fe00": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "e8059321ac614bdf96351a5bd2f3f4ba": { "model_module": "@jupyter-widgets/base", "model_module_version": 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"right": null, "top": null, "visibility": null, "width": null } }, "ea656d911f7d4787bac367f933143ab9": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, 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