{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Broadband polarization beam splitter using anisotropic metamaterial\n", "\n", "Polarization beam splitters (PBS) play a vital role in polarization diversity circuits to mitigate the strong polarization dependence of silicon nanophotonic devices. Among the various PBS structures, asymmetrical directional couplers are predominantly employed due to their superior overall performance. Notwithstanding, engineering an on-chip silicon PBS that offers a compact footprint, low loss, exceptional extinction ratio, and particularly, a broad bandwidth, all at once, remains a formidable challenge. The working bandwidth of directional couplers is inherently limited. \n", "\n", "Metamaterials offer an innovative method of manipulating optical responses and regulating light flow. Subwavelength grating (SWG), an anisotropic metamaterial (AM) formed by a one-dimensional array of deeply subwavelength nano-strips, exemplifies these characteristics. SWGs demonstrate strong anisotropy and flattened dispersion, making them extremely useful for polarization manipulation.\n", "\n", "In this notebook, we present an ultra-broadband PBS design that makes effective use of AM. The design is based on the research work `Xu, H., Dai, D., & Shi, Y. (2019). Ultra-broadband and ultra-compact on-chip silicon polarization beam splitter by using hetero-anisotropic metamaterials. Laser & Photonics Reviews, 13(4), 1800349.` [DOI: 10.1002/lpor.20180349](https://doi.org/10.1002/lpor.201800349).\n", "\n", "The design comprises three SWG sections symmetrically arranged to form a hetero-anisotropic slab, with two AM[100] sections sandwiching a central AM[010] section. The design also utilizes an adiabatic taper structure at the input/output ports, which serves as a converter between the standard channel waveguides and the SWGs. The design goal is to have the TE mode transmitted to the through port while the TM mode will be coupled to the cross port.\n", "\n", "\"Schematic\n", "\n", "For more examples utilizing SWGs for on-chip applications, please check out the [waveguide bragg gratings](https://www.flexcompute.com/tidy3d/examples/notebooks/BraggGratings/), [broadband polarizer](https://www.flexcompute.com/tidy3d/examples/notebooks/SWGBroadbandPolarizer/), and [exceptional coupling for waveguide crosstalk reduction](https://www.flexcompute.com/tidy3d/examples/notebooks/ZeroCrossTalkTE/)." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:24.697458Z", "iopub.status.busy": "2025-05-15T10:48:24.697288Z", "iopub.status.idle": "2025-05-15T10:48:26.507924Z", "shell.execute_reply": "2025-05-15T10:48:26.507554Z" } }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import tidy3d as td\n", "import tidy3d.web as web\n", "from tidy3d.plugins.mode import ModeSolver\n", "from tidy3d.plugins.mode.web import run as run_mode_solver" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Simulation Setup\n", "\n", "We will focus on the broadband capabilities of the designed PBS over a 200 nm spectrum, ranging from 1450 nm to 1650 nm. This range encapsulates the S-band, C-band, and L-band frequencies." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:26.509372Z", "iopub.status.busy": "2025-05-15T10:48:26.509039Z", "iopub.status.idle": "2025-05-15T10:48:26.511559Z", "shell.execute_reply": "2025-05-15T10:48:26.511202Z" } }, "outputs": [], "source": [ "lda0 = 1.55 # central wavelength\n", "freq0 = td.C_0 / lda0 # central frequency\n", "ldas = np.linspace(1.45, 1.65, 101) # wavelength range\n", "freqs = td.C_0 / ldas # frequency range\n", "fwidth = 0.5 * (np.max(freqs) - np.min(freqs)) # width of the source frequency range" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The three materials utilized are silicon, silicon oxide, and SU8. Both silicon and oxide are readily available in the [material library](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/material_library.html). In contrast, SU8 is modelled as a non-dispersive medium." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:26.512901Z", "iopub.status.busy": "2025-05-15T10:48:26.512662Z", "iopub.status.idle": "2025-05-15T10:48:26.515220Z", "shell.execute_reply": "2025-05-15T10:48:26.514858Z" } }, "outputs": [], "source": [ "si = td.material_library[\"cSi\"][\"Palik_Lossless\"]\n", "sio2 = td.material_library[\"SiO2\"][\"Palik_Lossless\"]\n", "\n", "n_su8 = 1.58\n", "su8 = td.Medium(permittivity=n_su8**2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Determine the geometric parameters. The thickness of the silicon layer is recorded to be 250 nm. The input and output single mode waveguides each have a width $w_{in}$ of 450 nm. The width of the [100] anisotropic metamaterial (AM[100]) $w_{100}$ is 650 nm. The junction between the single mode strip waveguide and the AM region takes on a taper structure, incorporating $n_{tp}=$10 grating periods. The periods $p$ for both the AM[100] and AM[010] are set at 250 nm. The duty cycles $f_{100}$ and $f_{010}$ are set to 0.7 for both metamaterials, with an option for fine-tuning later.\n", "\n", "\"Top" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:26.516779Z", "iopub.status.busy": "2025-05-15T10:48:26.516482Z", "iopub.status.idle": "2025-05-15T10:48:26.518745Z", "shell.execute_reply": "2025-05-15T10:48:26.518406Z" } }, "outputs": [], "source": [ "t = 0.25 # silicon layer thickness\n", "p = 0.25 # pitch of the swg\n", "w_in = 0.45 # input waveguide width\n", "w_100 = 0.65 # width of the AM[100]\n", "n_tp = 10 # number of periods in the taper region\n", "f_0 = 0.7 # initial duty cycle for the anisotropic metamaterial\n", "inf_eff = 1e3 # effective infinity\n", "buffer = 0.6 * lda0 # buffer spacing" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Mode Analysis\n", "\n", "To gain insight into the operational mechanism of the PBS design and to assist future design optimization, we start with a mode analysis. The effective refractive indices of the SWG AM are procured via the effective medium theory. The subsequent formulas elaborate on this:\n", "\n", "1. The ordinary refractive index, denoted as $n_o$, is governed by the formula:\n", " $$\n", " n_o^2 = f \\cdot n_{Si}^2 + (1 - f) \\cdot n_{SU8}^2\n", " $$\n", "\n", " Here, $f$ represents the SWG duty cycle, $n_{Si}$ stands for the refractive index of silicon, and $n_{SU8}$ indicates the refractive index of SU8.\n", "\n", "2. The extraordinary refractive index, denoted as $n_e$, is demonstrated as:\n", " $$\n", " \\frac{1}{n_e^2} = \\frac{f}{n_{Si}^2} + \\frac{1 - f}{n_{SU8}^2}\n", " $$\n", "\n", "3. The refractive index tensors for various configurations, specifically the anisotropic metamaterial [100] and [010], are depicted as such:\n", " $$\n", " n_{[100]} = \\text{diag}(n_{[100]}^{xx}, n_{[100]}^{yy}, n_{[100]}^{zz}) = \\text{diag}(n_e, n_o, n_o)\n", " $$\n", " Similarly,\n", " $$\n", " n_{[010]} = \\text{diag}(n_{[010]}^{xx}, n_{[010]}^{yy}, n_{[010]}^{zz}) = \\text{diag}(n_o, n_e, n_o)\n", " $$\n", "\n", "In this context, $n_o$ and $n_e$ are the ordinary and extraordinary refractive indices respectively. \n", "\n", "By applying the aforementioned refractive index tensors, a mode analysis is conducted on the effective mediums." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:26.519918Z", "iopub.status.busy": "2025-05-15T10:48:26.519790Z", "iopub.status.idle": "2025-05-15T10:48:26.620168Z", "shell.execute_reply": "2025-05-15T10:48:26.619812Z" } }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n_si = si.nk_model(frequency=freq0)[0] # refractive index of silicon\n", "\n", "# calculate effective refractive index tensors\n", "n_o = np.sqrt(f_0 * n_si**2 + (1 - f_0) * n_su8**2)\n", "n_e = np.sqrt(1 / (f_0 / n_si**2 + (1 - f_0) / n_su8**2))\n", "\n", "# create effective mediums\n", "n_o_medium = td.Medium(permittivity=n_o**2)\n", "n_e_medium = td.Medium(permittivity=n_e**2)\n", "am_100_medium = td.AnisotropicMedium(xx=n_e_medium, yy=n_o_medium, zz=n_o_medium)\n", "am_010_medium = td.AnisotropicMedium(xx=n_o_medium, yy=n_e_medium, zz=n_o_medium)\n", "\n", "# create waveguide structures\n", "n_010_example = 5 # use 5 periods for the AM[010] region width as an example\n", "am_010_waveguide = td.Structure(\n", " geometry=td.Box.from_bounds(\n", " rmin=(-inf_eff, -n_010_example * p / 2, 0), rmax=(inf_eff, n_010_example * p / 2, t)\n", " ),\n", " medium=am_010_medium,\n", ")\n", "\n", "am_100_waveguide_left = td.Structure(\n", " geometry=td.Box.from_bounds(\n", " rmin=(-inf_eff, -n_010_example * p / 2 - w_100, 0),\n", " rmax=(inf_eff, -n_010_example * p / 2, t),\n", " ),\n", " medium=am_100_medium,\n", ")\n", "am_100_waveguide_right = td.Structure(\n", " geometry=td.Box.from_bounds(\n", " rmin=(-inf_eff, n_010_example * p / 2, 0), rmax=(inf_eff, n_010_example * p / 2 + w_100, t)\n", " ),\n", " medium=am_100_medium,\n", ")\n", "\n", "# create box structure\n", "box = 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", "# create a simulation for the mode solver\n", "mode_solver_sim = td.Simulation(\n", " center=(0, 0, t / 2),\n", " size=(buffer, n_010_example * p + 2 * w_100 + 2 * buffer, t + 2 * buffer),\n", " grid_spec=td.GridSpec.auto(min_steps_per_wvl=25, wavelength=lda0),\n", " structures=[box, am_010_waveguide, am_100_waveguide_left, am_100_waveguide_right],\n", " run_time=1e-12,\n", " medium=su8,\n", ")\n", "\n", "# create a mode solver\n", "mode_solver = ModeSolver(\n", " simulation=mode_solver_sim,\n", " plane=td.Box(\n", " center=(0, 0, t / 2), size=(0, n_010_example * p + 2 * w_100 + 2 * buffer, t + 2 * buffer)\n", " ),\n", " mode_spec=td.ModeSpec(num_modes=6, target_neff=n_si),\n", " freqs=[freq0],\n", ")\n", "\n", "# plot the mode solving cross section\n", "mode_solver.plot()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To ensure accuracy in our process, we execute the server-side mode resolving and subsequently illustrate the mode properties. Utilizing the `TE (Ey) fraction` as a reference, we can discern that the initial two modes align with the first TE modes. Similarly, the third and fifth modes correspond to the first TM modes." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:26.640569Z", "iopub.status.busy": "2025-05-15T10:48:26.640398Z", "iopub.status.idle": "2025-05-15T10:48:45.071962Z", "shell.execute_reply": "2025-05-15T10:48:45.071588Z" } }, "outputs": [ { "data": { "text/html": [ "
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51.551.7686860.00.9507890.7893370.8758771.052157
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" ], "text/plain": [ " wavelength n eff k eff TE (Ey) fraction \\\n", "f mode_index \n", "1.934145e+14 0 1.55 2.266314 0.0 0.983015 \n", " 1 1.55 2.266245 0.0 0.982896 \n", " 2 1.55 1.960050 0.0 0.008933 \n", " 3 1.55 1.877059 0.0 0.979594 \n", " 4 1.55 1.848559 0.0 0.040657 \n", " 5 1.55 1.768686 0.0 0.950789 \n", "\n", " wg TE fraction wg TM fraction mode area \n", "f mode_index \n", "1.934145e+14 0 0.858241 0.817122 0.656643 \n", " 1 0.857676 0.817317 0.655515 \n", " 2 0.677584 0.977041 0.895533 \n", " 3 0.932495 0.854729 0.600591 \n", " 4 0.707929 0.921683 1.215859 \n", " 5 0.789337 0.875877 1.052157 " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mode_data = run_mode_solver(mode_solver, verbose=False)\n", "mode_data.to_dataframe()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot the field profiles for the initial two TE and TM modes. These results reproduce Fig. 2b in the cited [study](https://doi.org/10.1002/lpor.201800349). The TM0 and TM1 field profiles demonstrate coverage over both the AM[010] and AM[100] regions. In contrast, the even and odd TE super-modes are primarily concentrated in the AM[100] region, indicating a much smaller coupling strength." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:45.073097Z", "iopub.status.busy": "2025-05-15T10:48:45.072984Z", "iopub.status.idle": "2025-05-15T10:48:45.785035Z", "shell.execute_reply": "2025-05-15T10:48:45.784288Z" } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot the mode profiles\n", "fig, axes = plt.subplots(2, 2, figsize=(8, 4), tight_layout=True)\n", "mode_solver.plot_field(mode_index=2, field_name=\"Ez\", val=\"real\", vmin=-30, vmax=30, ax=axes[0, 0])\n", "axes[0, 0].set_title(\"Ez of the TM0 mode\")\n", "mode_solver.plot_field(mode_index=4, field_name=\"Ez\", val=\"real\", vmin=-30, vmax=30, ax=axes[0, 1])\n", "axes[0, 1].set_title(\"Ez of the TM1 mode\")\n", "mode_solver.plot_field(mode_index=1, field_name=\"Ey\", val=\"real\", vmin=-30, vmax=30, ax=axes[1, 1])\n", "axes[1, 1].set_title(\"Ey of the odd TE mode\")\n", "mode_solver.plot_field(mode_index=0, field_name=\"Ey\", val=\"real\", vmin=-30, vmax=30, ax=axes[1, 0])\n", "axes[1, 0].set_title(\"Ey of the even TE mode\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can calculate the coupling length for TE and TM modes using the formula $L_c = \\frac{\\lambda}{2(n_{eff}^0-n_{eff}^1)}$, where $n_{eff}^0$ and $n_{eff}^1$ denote the effective indices of the initial two modes. The results demonstrate that the coupling length for TM mode is approximately 7 μm, whilst the coupling length for TE mode is several orders of magnitude larger. Consequently, by designing the coupling region to roughly 7 μm, we can effectively couple the TM mode to the cross port. Conversely, the TE mode is directed solely to the through port, which results in the realization of the PBS functionality." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:45.786636Z", "iopub.status.busy": "2025-05-15T10:48:45.786499Z", "iopub.status.idle": "2025-05-15T10:48:45.791161Z", "shell.execute_reply": "2025-05-15T10:48:45.790529Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The coupling length for the TM mode is 6.95 μm.\n", "The coupling length for the TE mode is 11296.20 μm.\n" ] } ], "source": [ "# calculate TM mode coupling length\n", "n_tm0 = mode_data.n_eff.sel(mode_index=2).values[0]\n", "n_tm1 = mode_data.n_eff.sel(mode_index=4).values[0]\n", "print(f\"The coupling length for the TM mode is {lda0 / (2 * (n_tm0 - n_tm1)):.2f} μm.\")\n", "\n", "# calculate TE mode coupling length\n", "n_te0 = mode_data.n_eff.sel(mode_index=0).values[0]\n", "n_te1 = mode_data.n_eff.sel(mode_index=1).values[0]\n", "print(f\"The coupling length for the TE mode is {lda0 / (2 * (n_te0 - n_te1)):.2f} μm.\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Design Optimization\n", "\n", "For the final design configuration, it is crucial to pinpoint the exact coupling length that promotes the maximum coupling of the TM mode to the cross port. The determination of the coupling length is reliant upon the number of grating periods in the AM[100] region, i.e. $n_{100}$. Similarly, the width of the coupling region is governed by the number of grating periods in the AM[010] region, i.e. $n_{010}$. A parameter sweep of both aspects will be conducted to search for the optimal values. The duty cycles for both AM[100] and AM[010] are held at a constant 0.7 in this scenario to guarantee the minimal feature size. However, these values are open to precise adjustment at a later stage.\n", "\n", "To start the parameter sweep process, we define a `make_sim` function. This function processes the design parameters and returns a Tidy3D [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html#tidy3d.Simulation). " ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:45.792714Z", "iopub.status.busy": "2025-05-15T10:48:45.792588Z", "iopub.status.idle": "2025-05-15T10:48:45.799153Z", "shell.execute_reply": "2025-05-15T10:48:45.798854Z" } }, "outputs": [], "source": [ "def make_sim(mode_index, n_100, n_010, f_100=f_0, f_010=f_0):\n", " \"\"\"\n", " Constructs and returns a simulation object given the design parameters.\n", "\n", " Args:\n", " mode_index (int): The index of the mode to excite in the simulation. mode_index=0 for TE and mode_index=1 for TM.\n", " n_100 (int): Number of SWG periods in AM[100].\n", " n_010 (int): Number of SWG periods in AM[010].\n", " f_100 (float, optional): Duty cycle for AM[100].\n", " f_010 (float, optional): Duty cycle for AM[010].\n", "\n", " Returns:\n", " td.Simulation\n", " \"\"\"\n", "\n", " l_c = p * n_100 - (1 - f_100) * p # coupling region length\n", " l_tp = p * n_tp # taper length\n", " y_0 = (\n", " n_010 * p / 2 + (1 - f_010) * p / 2 + w_100 / 2\n", " ) # y coordinate of the input waveguide center\n", "\n", " # create the swg structures in the coupling region\n", " am_geos = 0\n", " for i in range(n_010):\n", " am_geos += td.Box(\n", " center=(l_c / 2, (n_010 - 1) * p / 2 - i * p, t / 2), size=(l_c, p * f_010, t)\n", " )\n", "\n", " for i in range(n_100):\n", " am_geos += td.Box(center=(f_100 * p / 2 + i * p, y_0, t / 2), size=(p * f_100, w_100, t))\n", " am_geos += td.Box(center=(f_100 * p / 2 + i * p, -y_0, t / 2), size=(p * f_100, w_100, t))\n", "\n", " am_structure = td.Structure(geometry=am_geos, medium=si)\n", "\n", " # create the waveguide taper structures\n", " vertices = [\n", " (-inf_eff, y_0 + w_in / 2),\n", " (-inf_eff, y_0 - w_in / 2),\n", " (-l_tp - (1 - f_100) * p, y_0 - w_in / 2),\n", " (-(1 - f_100) * p, y_0),\n", " (-l_tp - (1 - f_100) * p, y_0 + w_in / 2),\n", " ]\n", "\n", " taper_in = td.PolySlab(vertices=vertices, axis=2, slab_bounds=(0, t))\n", " taper_out_bottom = taper_in.rotated(angle=np.pi, axis=2).translated(x=l_c, y=0, z=0)\n", " taper_out_top = taper_out_bottom.translated(x=0, y=2 * y_0, z=0)\n", "\n", " taper_geos = [taper_in, taper_out_bottom, taper_out_top]\n", " taper_structure = td.Structure(geometry=td.GeometryGroup(geometries=taper_geos), medium=si)\n", "\n", " # create the swg structures in the taper regions\n", " taper_widths = np.linspace(w_in, w_100, n_tp + 2)[1:-1]\n", " taper_am_geos = []\n", " for i in range(n_tp):\n", " taper_am = td.Box(\n", " center=(-l_tp + f_100 * p / 2 + i * p, y_0, t / 2), size=(f_100 * p, taper_widths[i], t)\n", " )\n", " taper_am_geos += [\n", " taper_am,\n", " taper_am.rotated(angle=np.pi, axis=2).translated(x=l_c, y=0, z=0),\n", " taper_am.rotated(angle=np.pi, axis=2).translated(x=l_c, y=2 * y_0, z=0),\n", " ]\n", " taper_am_structure = td.Structure(\n", " geometry=td.GeometryGroup(geometries=taper_am_geos), medium=si\n", " )\n", "\n", " # add a mode source as excitation\n", " mode_spec = td.ModeSpec(num_modes=2, target_neff=n_si)\n", " mode_source = td.ModeSource(\n", " center=(-l_tp - buffer / 2, y_0, t / 2),\n", " size=(0, 4 * w_in, 6 * t),\n", " source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n", " direction=\"+\",\n", " mode_spec=mode_spec,\n", " mode_index=mode_index,\n", " num_freqs=7, # use 7 frequency points since the simulation bandwidth is large\n", " )\n", "\n", " # add a mode monitor to measure transmission at the through port\n", " mode_through = td.ModeMonitor(\n", " center=(l_c + l_tp + buffer / 2, y_0, t / 2),\n", " size=mode_source.size,\n", " freqs=freqs,\n", " mode_spec=mode_spec,\n", " name=\"through\",\n", " )\n", "\n", " # add a mode monitor to measure transmission at the cross port\n", " mode_cross = td.ModeMonitor(\n", " center=(l_c + l_tp + buffer / 2, -y_0, t / 2),\n", " size=mode_source.size,\n", " freqs=freqs,\n", " mode_spec=mode_spec,\n", " name=\"cross\",\n", " )\n", "\n", " # add a field monitor to visualize field distribution at z=t/2\n", " field_monitor = td.FieldMonitor(\n", " center=(0, 0, t / 2),\n", " size=(td.inf, td.inf, 0),\n", " freqs=[freq0],\n", " interval_space=(2, 2, 1),\n", " name=\"field\",\n", " )\n", "\n", " run_time = 1.5e-12 # simulation run time\n", "\n", " # construct simulation\n", " sim = td.Simulation(\n", " center=(l_c / 2, 0, t / 2),\n", " size=(2 * l_tp + l_c + buffer * 2, n_010 * p + w_100 * 2 + 2 * buffer, 10 * t),\n", " grid_spec=td.GridSpec.auto(min_steps_per_wvl=25, wavelength=lda0),\n", " structures=[am_structure, taper_structure, taper_am_structure, box],\n", " sources=[mode_source],\n", " monitors=[mode_through, mode_cross, field_monitor],\n", " run_time=run_time,\n", " boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n", " medium=su8,\n", " )\n", "\n", " return sim" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The simulation setup is relatively complex due to the SWG structures. To validate the correctness of the setup, we construct a sample simulation and render its 3D visualization." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:45.800287Z", "iopub.status.busy": "2025-05-15T10:48:45.800202Z", "iopub.status.idle": "2025-05-15T10:48:45.833053Z", "shell.execute_reply": "2025-05-15T10:48:45.832731Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sim = make_sim(mode_index=1, n_100=30, n_010=5)\n", "sim.plot_3d()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visualize the grid to ensure that it's refined enough to resolve the small features." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:45.834381Z", "iopub.status.busy": "2025-05-15T10:48:45.834293Z", "iopub.status.idle": "2025-05-15T10:48:46.264832Z", "shell.execute_reply": "2025-05-15T10:48:46.264252Z" } }, "outputs": [ { "data": { "image/png": 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cunQJU6ZMwfr1661qHTp0QIcOHQCV7/k2bdoUkyZNwpIlS1BWVoauXbti06ZN2LlzJ9auXWv1Uuz06dPx7rvv4vTp01Z9yfPnzwf+WPAAYM2aNZb30StfVj579iwGDhwIk8mExx57DBs3bqz2cVRn0KBBmDFjBgoLCxEQEGBVy8/Px3333Ydhw4ahsLAQS5cuhb+/P3744Qf87//+L5599tlaz011tm3bhp49e9q850460nu7NRnb2bNnxciRI0Xjxo2F2WwWzZs3FxMnThQlJSVC/KnVqKp2JPFHa1Hr1q2Fl5eXCA4OFhMmTBBXrlyx1E+dOiWefvppERUVJXx8fMTtt98u7r33XvHFF19YzsnMzBSDBg0SYWFhwtvbW4SFhYmhQ4eKn376STG7vdeVlpaKl19+WbRt21aYzWbRsGFD0aVLFzFnzhxRUFBgde6qVatE586dLef16dNHbNu2zVLPyckR/fv3F/7+/gKApa3k1lajShs2bLCMd/vtt4thw4aJn3/+2eqc+Ph4Ub9+fZvHl5ycLOz5T3z37t3iL3/5i/D19RVhYWFiypQp4rPPPrPJ8/vvv4unnnpKNGjQQABQbDvq06dPtW1DycnJNWaqSXl5uVi4cKFo1qyZ8Pb2Fm3bthXvvfeezXmVbVinT5+2Oq7U1lSp8s/EkceRm5srbrvtNrFmzRqr482aNRPDhg0T48ePF/7+/uL2228XM2fOFJ9++qnw9/cX/fr1s8pwa6tddf9dVf6Z/7l9Lj8/X3h7e4u33367xrykHZNwxWscREQEABgzZgx++ukn7Ny503IsIiICffv21eRDNtLS0rB48WJkZ2e7bCc41R7f8yUicqHk5GTLb23TWllZGVJTUzFz5kwuvJLhe75ERC5055136vZxfl5eXjh37pwuP5uU8c6XiIhIY7ouvjt27MCAAQMQFhYGk8lk9Uvqq5OVlYV77rkHZrMZLVq0qPI9k2XLliEiIgI+Pj6IiYnBvn37XPQIiIhq78yZM5q830vy0nXxLS4uRseOHe1uXD99+jT69++Pe++9F4cPH8akSZPwzDPP4LPPPrOcU9kKkZycjIMHD6Jjx46Ii4uz/BpAIiIivUmz29lkMuGTTz7B4MGDqz1n6tSp2LJli9VvVXryySeRn5+PjIwM4I9fLN61a1e8+eabwB8fABAeHo7nn38e06ZN0+CREBERKTPUhqs9e/bYNOXHxcVh0qRJwB+/mefAgQOYPn26pe7h4YHY2FjFD9guKSmx+i1CFRUV+O2333DHHXfwF5ETEdUhQggUFRUhLCysVr/RrLYMtfjm5OTYfPh4cHAwCgsLce3aNVy5cgXl5eVVnqP00WgpKSmYM2eOy3ITEZGxnD9/Hk2bNnXZ+IZafF1l+vTpSExMtHxfUFCAO++8E8OXrIO3bz2rcwvzbn5ySkBQqM04amrOHs8VtYQeNz+5Jyoqyuaa7Oxsl9QWbtpXp+ZY6RojzL8s8+iKjFrOf+XxN78+X6uMstRc9bNeGtzN6XNc3TW///47/vrXv8Lf39+m7kyGWnxDQkJsPvUjNzcXAQEB8PX1haenJzw9Pas8JyQkpNpxzWZzlR/O7e1bD96+9a2Oefn4/lGrb3O+mpqzx3NFrfJJeOvvpnVlzcvHt07NsdI1Rph/WebRFRm1nP/K43rPldqaq36Wv7+/0+dY6Rpo8NnHhurz7d69OzIzM62Obdu2zfJJHd7e3ujSpYvVORUVFcjMzOSneRARkTR0XXx///13HD58GIcPHwb+aCU6fPiw5TeyTJ8+HSNHjrScP378eJw6dQpTpkzBsWPHsHz5cnzwwQdWn/CSmJiIlStX4t1338XRo0cxYcIEFBcXY/To0To8QiIiIlu6vuy8f/9+3HvvvZbvK993jY+Px+rVq3Hx4kWrX40WGRmJLVu2YPLkyXj99dfRtGlTvP3221af9TlkyBBcunQJSUlJyMnJQadOnZCRkWGzCYuIiEgvui6+ffv2Vfzg6Kp+A0zfvn1x6NAhxXETEhKQkJDgcL7CvIuW9yIqFf2aW+35amrOHs8VtbNnq70EZxWKjtScOV+yzKPajEaYf1nm0RUZtZz/yuMFuRdqlVGWmqt+Vk3zVZtaTdcUFxdXW3cmQ73nS0RE5A4MtdtZawFBoVXuvgOAwOAm1V6npubs8ZxZa9asGQCgRYsW1V7j7Jr/HRfq1BwrHTfS/Msyj87MqMf8Byrcbcsyj0o1Z4/XrFkzp89xdceLioqqHcuZeOdLRESkMS6+REREGuPiS0REpDEuvkRERBrjhisFbDW6yQitLko1WeZRbUYjzL8s8+iKjGw1sr/GViP78c6XiIhIY7zzVcBWo5uM1OqiVNN7HtVmNNL8yzKPzszIViP9nwdsNSIiIiKHcfElIiLSGBdfIiIijXHxJSIi0hg3XClgq9FNRmh1UarJMo9qMxph/mWZR1dkZKuR/TW2GtmPd75EREQa452vArYa3WSkVhelmt7zqDajkeZflnl0Zka2Gun/PGCrERERETmMiy8REZHGuPgSERFpjIsvERGRxrjhSgFbjW4yQquLUk2WeVSb0QjzL8s8uiIjW43sr7HVyH688yUiItIY73wVsNXoJiO1uijV9J5HtRmNNP+yzKMzM7LVSP/nAVuNiIiIyGFcfImIiDTGxZeIiEhjfM9XAXc732SE3bZKNVnmUW1GI8y/LPPoiozc7Wx/jbud7cc7XyIiIo3xzlcBdzvfZKTdtko1vedRbUYjzb8s8+jMjNztrP/zgLudiYiIyGFcfImIiDTGxZeIiEhjXHyJiIg0xg1XCthqdJMRWl2UarLMo9qMRph/WebRFRnZamR/ja1G9uOdLxERkcZ456uArUY3GanVRamm9zyqzWik+ZdlHp2Zka1G+j8P2GpEREREDuPiS0REpDEuvkRERBrj4ktERKQxbrhSwFajm4zQ6qJUk2Ue1WY0wvzLMo+uyMhWI/trbDWyH+98iYiINMY7XwVsNbrJSK0uSjW951FtRiPNvyzz6MyMbDXS/3nAViMiIiJyGBdfIiIijXHxJSIi0hgXXyIiIo1xw5UCthrdZIRWF6WaLPOoNqMR5l+WeXRFRrYa2V9jq5H9eOdLRESkMd75KmCr0U1GanVRquk9j2ozGmn+ZZlHZ2Zkq5H+zwO2GhEREZHDuPgSERFpjIsvERGRxrj4EhERaYwbrhSw1egmI7S6KNVkmUe1GY0w/7LMoysystXI/hpbjezHO18iIiKN8c5XAVuNbjJSq4tSTe95VJvRSPMvyzw6MyNbjfR/HrDViIiIiBzGxZeIiEhjXHyJiIg0xvd8FXC3801G2G2rVJNlHtVmNML8yzKPrsjI3c7217jb2X688yUiItIY73wVcLfzTUbabatU03se1WY00vzLMo/OzMjdzvo/D7jbmYiIiBzGxZeIiEhjXHyJiIg0pvviu2zZMkRERMDHxwcxMTHYt2+f4vlpaWm466674Ovri/DwcEyePBnXr193aEwiIiIt6brhasOGDUhMTER6ejpiYmKQlpaGuLg4HD9+HEFBQTbnv//++5g2bRpWrVqFHj164KeffsKoUaNgMpmQmpqqakwlbDW6yQitLko1WeZRbUYjzL8s8+iKjGw1sr/GViP76Xrnm5qairFjx2L06NFo06YN0tPTUa9ePaxatarK87/++mv07NkTTz31FCIiItCvXz8MHTrU6s62tmMSERFpTbc739LSUhw4cADTp0+3HPPw8EBsbCz27NlT5TU9evTAe++9h3379qFbt244deoUtm7dihEjRqgeEwBKSkpQUlJi+b6wsBBgq5GFkVpdlGp6z6PajEaaf1nm0ZkZ2Wqk//PAHVuNdFt8L1++jPLycgQHB1sdDw4OxrFjx6q85qmnnsLly5fRq1cvCCFw48YNjB8/Hi+99JLqMQEgJSUFc+bMccrjIiIiqonuG65qIysrCwsXLsTy5ctx8OBBfPzxx9iyZQvmzZvn0LjTp09HQUGB5ev8+fNOy0xERHQr3e58GzVqBE9PT+TmWr/Rnpubi5CQkCqvmTVrFkaMGIFnnnkGANC+fXsUFxdj3LhxmDFjhqoxAcBsNsNsNjvlcREREdVEtztfb29vdOnSBZmZmZZjFRUVyMzMRPfu3au85urVq/DwsI7s6ekJABBCqBqTiIhIa7q2GiUmJiI+Ph7R0dHo1q0b0tLSUFxcjNGjRwMARo4ciSZNmiAlJQUAMGDAAKSmpqJz586IiYnByZMnMWvWLAwYMMCyCNc0Zm2w1egmI7S6KNVkmUe1GY0w/7LMoysystXI/hpbjeyn6+I7ZMgQXLp0CUlJScjJyUGnTp2QkZFh2TB17tw5qzvdmTNnwmQyYebMmbhw4QIaN26MAQMGYMGCBXaPSUREpDfdP9UoISEBCQkJVdaysrKsvr/tttuQnJyM5ORk1WPWBluNbjJSq4tSTe95VJvRSPMvyzw6MyNbjfR/Hrhjq5GhdjsTERG5Ay6+REREGuPiS0REpDEuvkRERBrTfcOVzNhqdJMRWl2UarLMo9qMRph/WebRFRnZamR/ja1G9uOdLxERkcZ456uArUY3GanVRamm9zyqzWik+ZdlHp2Zka1G+j8P2GpEREREDuPiS0REpDEuvkRERBrj4ktERKQxbrhSwFajm4zQ6qJUk2Ue1WY0wvzLMo+uyMhWI/trbDWyH+98iYiINMY7XwVsNbrJSK0uSjW951FtRiPNvyzz6MyMbDXS/3nAViMiIiJyGBdfIiIijXHxJSIi0hjf81XA3c43GWG3rVJNlnlUm9EI8y/LPLoiI3c721/jbmf78c6XiIhIY7zzVcDdzjcZabetUk3veVSb0UjzL8s8OjMjdzvr/zzgbmciIiJyGBdfIiIijXHxJSIi0hgXXyIiIo1xw5UCthrdZIRWF6WaLPOoNqMR5l+WeXRFRrYa2V9jq5H9eOdLRESkMd75KmCr0U1GanVRquk9j2ozGmn+ZZlHZ2Zkq5H+zwO2GhEREZHDuPgSERFpjIsvERGRxrj4EhERaYwbrhSw1egmI7S6KNVkmUe1GY0w/7LMoysystXI/hpbjezHO18iIiKN8c5XAVuNbjJSq4tSTe95VJvRSPMvyzw6MyNbjfR/HrDViIiIiBzGxZeIiEhjXHyJiIg0xsWXiIhIY9xwpYCtRjcZodVFqSbLPKrNaIT5l2UeXZGRrUb219hqZD/e+RIREWmMd74K2Gp0k5FaXZRqes+j2oxGmn9Z5tGZGdlqpP/zgK1GRERE5DAuvkRERBrj4ktERKQxLr5EREQa44YrBWw1uskIrS5KNVnmUW1GI8y/LPPoioxsNbK/xlYj+3HxVfDS4G7w9/e3Olb5B1e5A9LRmrPHc2VGLU36n3vq5BwrXaOl2s6/LPPoyoxamvt4j2pz6D2PSjVX/ix3w8VXQVRUFAICAqqsabXtXaaaLDnU1mTJYfSMSjVZcjCjvjVZcqjJyFYjIiIiN8XFl4iISGNcfImIiDTG93wVZGdnV7vhqiqu2HknQ02WHGprsuQwekalmiw5mFHfmiw5HMnID1YgIiJyU7zzVcDdznLmUFuTJYfRMyrVZMnBjPrWZMmhJiN3OxMREbkpLr5EREQa4+JLRESkMS6+REREGuOGKwVsNZIrh9qaLDmMnlGpJksOZtS3JksORzKy1YiIiMhN8c5XAVuN5MyhtiZLDqNnVKrJkoMZ9a3JkkNNRrYaERERuSkuvkRERBrj4ktERKQxLr5EREQa44YrBWw1kiuH2posOYyeUakmSw5m1LcmSw5HMtaZVqNly5YhIiICPj4+iImJwb59+xTPz8/Px8SJExEaGgqz2YxWrVph69atDo1JRESkJV3vfDds2IDExESkp6cjJiYGaWlpiIuLw/HjxxEUFGRzfmlpKR544AEEBQXhww8/RJMmTXD27Fk0aNBA9ZhK2GokZw61NVlyGD2jUk2WHMyob02WHGoy1olWo9TUVIwdOxajR49GmzZtkJ6ejnr16mHVqlVVnr9q1Sr89ttv2LRpE3r27ImIiAj06dMHHTt2VD0mERGR1nRbfEtLS3HgwAHExsb+N4yHB2JjY7Fnz54qr/n000/RvXt3TJw4EcHBwWjXrh0WLlyI8vJy1WMCQElJCQoLC62+iIiIXEW3xffy5csoLy9HcHCw1fHg4GDk5ORUec2pU6fw4Ycfory8HFu3bsWsWbPw6quvYv78+arHBICUlBQEBgZavsLDw53yGImIiKqi+4ar2qioqEBQUBDeeustdOnSBUOGDMGMGTOQnp7u0LjTp09HQUGB5ev8+fNOy0xERHQr3TZcNWrUCJ6ensjNzbU6npubi5CQkCqvCQ0NhZeXFzw9PS3H7r77buTk5KC0tFTVmABgNpthNpttjrPVSK4camuy5DB6RqWaLDmYUd+aLDkcyej2rUbe3t7o0qULMjMzLccqKiqQmZmJ7t27V3lNz549cfLkSVRUVFiO/fTTTwgNDYW3t7eqMYmIiLSma6tRYmIi4uPjER0djW7duiEtLQ3FxcUYPXo0AGDkyJFo0qQJUlJSAAATJkzAm2++iRdffBHPP/88Tpw4gYULF+KFF16we8zaYKuRnDnU1mTJYfSMSjVZcjCjvjVZcqjJqFWrka6L75AhQ3Dp0iUkJSUhJycHnTp1QkZGhmXD1Llz5+Dh8d+b8/DwcHz22WeYPHkyOnTogCZNmuDFF1/E1KlT7R6zNiavyYK3b32rYwW5FwAAgcG2L12oqTl7vLqa0ej5ZcnhzvllyWH0jEbPX9M1Zdev2Rx3Bd1/vWRCQgISEhKqrGVlZdkc6969O7755hvVYxIREenNULudiYiI3AEXXyIiIo3p/rKzzArzLsLLx9fqWNGvudWer6bm7PHqakalmiw5jJ5RqSZLDmbUtyZLDkcylpVcr7buTLzzJSIi0hjvfBUEBIXa7HauFBjcpNrr1NScPV5dzahUkyWH0TMq1WTJwYz61mTJoSajVrudeedLRESkMS6+REREGuPiS0REpDG+56uAu53lyqG2JksOo2dUqsmSgxn1rcmSw5GM3O1MRETkpmp953v69Gns3LkTZ8+exdWrV9G4cWN07twZ3bt3h4+Pj2tS6oS7neXMobYmSw6jZ1SqyZKDGfWtyZJDTUbpfrfz2rVr8frrr2P//v0IDg5GWFgYfH198dtvvyE7Oxs+Pj4YNmwYpk6dimbNmrk2NRERkYHZtfh27twZ3t7eGDVqFD766COEh4db1UtKSrBnzx6sX78e0dHRWL58OR5//HFXZSYiIjI0uxbfRYsWIS4urtq62WxG37590bdvXyxYsABnzpxxZkYiIiK3Ytfiq7Tw3uqOO+7AHXfc4UgmIiIit6a61SgvLw95eXmoqKiwOt6hQwdn5JICW43kyqG2JksOo2dUqsmSgxn1rcmSw5GMWrUa1XrxPXDgAOLj43H06FEIIQAAJpMJQgiYTCaUl5e7IicREZHbqPXi+/TTT6NVq1Z45513EBwcDJPJ5JpkEmCrkZw51NZkyWH0jEo1WXIwo741WXKoyShdq1GlU6dO4aOPPkKLFi1ck4iIiMjN1fo3XN1///347rvvXJOGiIioDqj1ne/bb7+N+Ph4/PDDD2jXrh28vLys6gMHDnRmPiIiIrdT68V3z5492L17N/7zn//Y1LjhioiIqGa1Xnyff/55DB8+HLNmzUJwcLBrUkmCrUZy5VBbkyWH0TMq1WTJwYz61mTJ4UhGaT/V6Ndff8XkyZPdfuElIiJylVrf+T766KPYvn07oqKiXJNIImw1kjOH2posOYyeUakmSw5m1LcmSw41GaVtNWrVqhWmT5+OXbt2oX379jYbrl544QVn5iMiInI7qnY7+/n54auvvsJXX31lVTOZTFx8iYiIalDrxff06dOuSUJERFRH1HrDVXUuXryIxYsXO2s4IiIit6XqdztX5ezZs9i3bx+mTJnijFxSYKuRXDnU1mTJYfSMSjVZcjCjvjVZcjiSUdpPNbpy5YrV9+Xl5Th16hSOHj2K5cuXOzMbERGRW6r14vvJJ59UeXzBggXYtGkTnn32WWfkkgJbjeTMobYmSw6jZ1SqyZKDGfWtyZJDTUatWo2c9p7v0KFDkZWV5azhiIiI3JbTFt/vvvsOnTt3dtZwREREbqvWLzsnJibaHMvNzcXmzZvRv39/q3pqaqrjCYmIiNxMrRffQ4cOVXm8a9euyMvLQ15eHvDHL9wgIiIiW7VefLdv3+6aJBJiq5FcOdTWZMlh9IxKNVlyMKO+NVlyOJJR2k81IiIiIsfYdef74IMPYvbs2fjLX/6ieF5RURGWL18OPz8/TJw40VkZdcNWIzlzqK3JksPoGZVqsuRgRn1rsuRQk1GqTzV6/PHH8be//Q2BgYEYMGAAoqOjERYWBh8fH1y5cgVHjhzBrl27sHXrVvTv3x9LlixxfXIiIiKDsmvxHTNmDIYPH46NGzdiw4YNeOutt1BQUAD8sbGqTZs2iIuLw7fffou7777b1ZmJiIgMze4NV2azGcOHD8fw4cMBAAUFBbh27RruuOMOm8/0JSIiourVerdzpcDAQAQGBjo3jWS421muHGprsuQwekalmiw5mFHfmiw5HMnI3c5ERERuSvWdb13A3c5y5lBbkyWH0TMq1WTJwYz61mTJoSaj4T5YgYiIiOzDxZeIiEhjtV584+PjsWPHDtekISIiqgNqvfgWFBQgNjYWLVu2xMKFC3HhwgXXJCMiInJTtd5wtWnTJly6dAlr1qzBu+++i+TkZMTGxmLMmDEYNGiQW/X8stVIrhxqa7LkMHpGpZosOZhR35osORzJKHWrUePGjZGYmIjvvvsOe/fuRYsWLTBixAiEhYVh8uTJOHHihPOTEhERuQmHWo0uXryIbdu2Ydu2bfD09MRDDz2E77//Hm3atMHixYsxefJk5yXVAVuN5MyhtiZLDqNnVKrJkoMZ9a3JkkNNRmlbjcrKyvDRRx/h4YcfRrNmzbBx40ZMmjQJv/zyC95991188cUX+OCDDzB37lzXJCYiIjK4Wt/5hoaGoqKiAkOHDsW+ffvQqVMnm3PuvfdeNGjQwFkZiYiI3EqtF9/XXnsNjz/+OHx8fKo9p0GDBjh9+rSj2YiIiNxSrRffESNGuCYJERFRHcHf7ayArUZy5VBbkyWH0TMq1WTJwYz61mTJ4UhGqVuNiIiISD3e+Spgq5GcOdTWZMlh9IxKNVlyMKO+NVlyqMkobasREREROYaLLxERkca4+BIREWmMiy8REZHGuOFKAVuN5MqhtiZLDqNnVKrJkoMZ9a3JksORjGw1IiIiclMmIYTQO8SyZcuwZMkS5OTkoGPHjli6dCm6detW43Xr16/H0KFDMWjQIGzatMlyXAiB5ORkrFy5Evn5+ejZsydWrFiBli1b2pWnsLAQgYGBKCgoQEBAgFXt5MmTAIAWLVrYXKem5uzx6mpGo+eXJYc755clh9EzGj1/TdcUFRXhnnvuqfLvf2fS/c53w4YNSExMRHJyMg4ePIiOHTsiLi4OeXl5itedOXMGf//739G7d2+b2uLFi/HGG28gPT0de/fuRf369REXF4fr17V5OYGIiEiJ7otvamoqxo4di9GjR6NNmzZIT09HvXr1sGrVqmqvKS8vx7BhwzBnzhw0b97cqiaEQFpaGmbOnIlBgwahQ4cO+Ne//oVffvnF6u6YiIhIL7ouvqWlpThw4ABiY2P/G8jDA7GxsdizZ0+1182dOxdBQUEYM2aMTe306dPIycmxGjMwMBAxMTGKYxIREWlF193Oly9fRnl5OYKDg62OBwcH49ixY1Ves2vXLrzzzjs4fPhwlfWcnBzLGLeOWVm7VUlJCUpKSizfFxYW1vqxEBER2ctQrUZFRUUYMWIEVq5ciUaNGjlt3JSUFMyZM8fmeHZ2Nvz9/a2OnT17ttpx1NScPV5dzahUkyWH0TMq1WTJwYz61mTJ4UjG4uLiauvOpOvi26hRI3h6eiI317rvKjc3FyEhITbnZ2dn48yZMxgwYIDlWEVFBQDgtttuw/Hjxy3X5ebmIjQ01GrMTp06VZlj+vTpSExMtHxfWFiI8PBwJzxCIiIiW7ouvt7e3ujSpQsyMzMxePBg4I/FNDMzEwkJCTbnt27dGt9//73VsZkzZ6KoqAivv/46wsPD4eXlhZCQEGRmZloW28LCQuzduxcTJkyoMofZbIbZbLY5HhUVVe1W86q2qTtSc/Z4dTWjUk2WHEbPqFSTJQcz6luTJYeajEVFRdWO5Uy6v+ycmJiI+Ph4REdHo1u3bkhLS0NxcTFGjx4NABg5ciSaNGmClJQU+Pj4oF27dlbXN2jQAACsjk+aNAnz589Hy5YtERkZiVmzZiEsLMyywBMREelJ98V3yJAhuHTpEpKSkpCTk4NOnTohIyPDsmHq3Llz8PCo3absKVOmoLi4GOPGjUN+fj569eqFjIwM+Pj4uOhREBER2U/3xRcAEhISqnyZGQCysrIUr129erXNMZPJhLlz52Lu3LlOy0hEROQsUiy+suJuZ7lyqK3JksPoGZVqsuRgRn1rsuRwJKNWu511/w1XREREdQ3vfBVwt7OcOdTWZMlh9IxKNVlyMKO+NVlyqMmo1W5n3vkSERFpjIsvERGRxrj4EhERaYyLLxERkca44UoBW43kyqG2JksOo2dUqsmSgxn1rcmSw5GMbDUiIiJyU7zzVcBWIzlzqK3JksPoGZVqsuRgRn1rsuRQk5GtRkRERG6Kiy8REZHGuPgSERFpjIsvERGRxrjhSgFbjeTKobYmSw6jZ1SqyZKDGfWtyZLDkYxsNSIiInJTvPNVwFYjOXOorcmSw+gZlWqy5GBGfWuy5FCTka1GREREbop3vgomr8mCt299q2MFuRcAAIHBtu8bqKk5e7y6mtHo+WXJ4c75Zclh9IxGz1/TNWXXr9kcdwXe+RIREWmMiy8REZHG+LKzgsK8i/Dy8bU6VvRrbrXnq6k5e7y6mlGpJksOo2dUqsmSgxn1rcmSw5GMZSXXq607E+98iYiINMY7XwUBQaE2G64qBQY3qfY6NTVnj1dXMyrVZMlh9IxKNVlyMKO+NVlyqMnIDVdERERuiosvERGRxrj4EhERaYyLLxERkca44UoBW43kyqG2JksOo2dUqsmSgxn1rcmSw5GMbDUiIiJyU7zzVcBWIzlzqK3JksPoGZVqsuRgRn1rsuRQk5GtRkRERG6Kiy8REZHGuPgSERFpjO/5KuBuZ7lyqK3JksPoGZVqsuRgRn1rsuRwJCN3OxMREbkp3vkq4G5nOXOorcmSw+gZlWqy5GBGfWuy5FCTkbudiYiI3BQXXyIiIo1x8SUiItIYF18iIiKNccOVArYayZVDbU2WHEbPqFSTJQcz6luTJYcjGdlqRERE5KZ456uArUZy5lBbkyWH0TMq1WTJwYz61mTJoSYjW42IiIjcFBdfIiIijXHxJSIi0hgXXyIiIo1xw5UCthrJlUNtTZYcRs+oVJMlBzPqW5MlhyMZ2WpERETkpnjnq4CtRnLmUFuTJYfRMyrVZMnBjPrWZMmhJiNbjYiIiNwUF18iIiKNcfElIiLSGBdfIiIijXHDlQK2GsmVQ21NlhxGz6hUkyUHM+pbkyWHIxnZakREROSmeOergK1GcuZQW5Mlh9EzKtVkycGM+tZkyaEmI1uNiIiI3BQXXyIiIo1x8SUiItIYF18iIiKNccOVArYayZVDbU2WHEbPqFSTJQcz6luTJYcjGdlqRERE5KZ456uArUZy5lBbkyWH0TMq1WTJwYz61mTJoSYjW42IiIjclBSL77JlyxAREQEfHx/ExMRg37591Z67cuVK9O7dGw0bNkTDhg0RGxtrc74QAklJSQgNDYWvry9iY2Nx4sQJDR4JERFRzXRffDds2IDExEQkJyfj4MGD6NixI+Li4pCXl1fl+VlZWRg6dCi2b9+OPXv2IDw8HP369cOFCxcs5yxevBhvvPEG0tPTsXfvXtSvXx9xcXG4fl2bN9KJiIiU6P6eb2pqKsaOHYvRo0cDANLT07FlyxasWrUK06ZNszl/7dq1Vt+//fbb+Oijj5CZmYmRI0dCCIG0tDTMnDkTgwYNAgD861//QnBwMDZt2oQnn3zS7mzc7SxXDrU1WXIYPaNSTZYczKhvTZYcjmSsE7udS0tLceDAAcTGxv43kIcHYmNjsWfPHrvGuHr1KsrKynD77bcDAE6fPo2cnByrMQMDAxETE2P3mERERK6k653v5cuXUV5ejuDgYKvjwcHBOHbsmF1jTJ06FWFhYZbFNicnxzLGrWNW1m5VUlKCkpISy/eFhYUAdztLm0NtTZYcRs+oVJMlBzPqW5Mlh5qM3O1sh0WLFmH9+vX45JNP4OPjo3qclJQUBAYGWr7Cw8OdmpOIiOjPdF18GzVqBE9PT+TmWr8Gn5ubi5CQEMVrX3nlFSxatAiff/45OnToYDleeV1txpw+fToKCgosX+fPn3fgURERESnTdfH19vZGly5dkJmZaTlWUVGBzMxMdO/evdrrFi9ejHnz5iEjIwPR0dFWtcjISISEhFiNWVhYiL1791Y7ptlsRkBAgNUXERGRq+i+2zkxMRHx8fGIjo5Gt27dkJaWhuLiYsvu55EjR6JJkyZISUkBALz88stISkrC+++/j4iICMv7uH5+fvDz84PJZMKkSZMwf/58tGzZEpGRkZg1axbCwsIwePBgXR8rERERZFh8hwwZgkuXLiEpKQk5OTno1KkTMjIyLBumzp07Bw+P/96gr1ixAqWlpXjsscesxklOTsbs2bMBAFOmTEFxcTHGjRuH/Px89OrVCxkZGbV+X5itRnLlUFuTJYfRMyrVZMnBjPrWZMnhSEatWo10X3wBICEhAQkJCVXWsrKyrL4/c+ZMjeOZTCbMnTsXc+fOdVpGIiIiZ5Fi8ZUVW43kzKG2JksOo2dUqsmSgxn1rcmSQ01GthoRERG5KS6+REREGuPiS0REpDEuvkRERBrjhisFbDWSK4famiw5jJ5RqSZLDmbUtyZLDkcy1olPNSIiIqqLeOergK1GcuZQW5Mlh9EzKtVkycGM+tZkyaEmo1atRiYhhNDkJxlIYWEhAgMDUVBQYPN7nk+ePAkAaNGihc11amrOHq+uZjR6fllyuHN+WXIYPaPR89d0TVFREe65554q//53Jr7sTEREpDEuvkRERBrj4ktERKQxbrhSkJ2dDX9/f6tjZ8+erfZ8NTVnj1dXMyrVZMlh9IxKNVlyMKO+NVlyOJKxuLi42roz8c6XiIhIY7zzVRAVFVXtbreqdso5UnP2eHU1o1JNlhxGz6hUkyUHM+pbkyWHmoxFRUXVjuVMvPMlIiLSGBdfIiIijXHxJSIi0hgXXyIiIo1xw5UCthrJlUNtTZYcRs+oVJMlBzPqW5MlhyMZ2WpERETkpnjnq4CtRnLmUFuTJYfRMyrVZMnBjPrWZMmhJiNbjYiIiNwUF18iIiKNcfElIiLSGN/zVcDdznLlUFuTJYfRMyrVZMnBjPrWZMnhSEbudiYiInJTvPNVwN3OcuZQW5Mlh9EzKtVkycGM+tZkyaEmI3c7ExERuSkuvkRERBrj4ktERKQxLr5EREQa44YrBWw1kiuH2posOYyeUakmSw5m1LcmSw5HMrLViIiIyE3xzlcBW43kzKG2JksOo2dUqsmSgxn1rcmSQ01GthoRERG5KS6+REREGuPLzgomr8mCt299q2MFuRcAAIHBtm/aq6k5e7y6mtHo+WXJ4c75Zclh9IxGz1/TNWXXr9kcdwXe+RIREWmMd74KCvMuwsvH1+pY0a+51Z6vpubs8epqRqWaLDmMnlGpJksOZtS3JksORzKWlVyvtu5MvPMlIiLSGO98FQQEhdq851spMLhJtdepqTl7vLqaUakmSw6jZ1SqyZKDGfWtyZJDTUa+50tEROSmuPgSERFpjIsvERGRxrj4EhERaYwbrhSw1UiuHGprsuQwekalmiw5mFHfmiw5HMnIViMiIiI3xTtfBWw1kjOH2posOYyeUakmSw5m1LcmSw41GdlqRERE5Ka4+BIREWmMiy8REZHGuPgSERFpjBuuFLDVSK4camuy5DB6RqWaLDmYUd+aLDkcychWIyIiIjfFO18FbDWSM4famiw5jJ5RqSZLDmbUtyZLDjUZ2WpERETkprj4EhERaYyLLxERkca4+BIREWmMG64UsNVIrhxqa7LkMHpGpZosOZhR35osORzJyFYjIiIiN8U7XwVsNZIzh9qaLDmMnlGpJksOZtS3JksONRnZakREROSmuPgSERFpjIsvERGRxqR4z3fZsmVYsmQJcnJy0LFjRyxduhTdunWr9vyNGzdi1qxZOHPmDFq2bImXX34ZDz30kKUuhEBycjJWrlyJ/Px89OzZEytWrEDLli1rlYu7neXKobYmSw6jZ1SqyZKDGfWtyZLDkYx1Zrfzhg0bkJiYiOTkZBw8eBAdO3ZEXFwc8vLyqjz/66+/xtChQzFmzBgcOnQIgwcPxuDBg/HDDz9Yzlm8eDHeeOMNpKenY+/evahfvz7i4uJw/bo2k0pERKRE9zvf1NRUjB07FqNHjwYApKenY8uWLVi1ahWmTZtmc/7rr7+OBx98EP/4xz8AAPPmzcO2bdvw5ptvIj09HUIIpKWlYebMmRg0aBAA4F//+heCg4OxadMmPPnkk3Zn425nOXOorcmSw+gZlWqy5GBGfWuy5FCTsU7sdi4tLcWBAwcQGxv730AeHoiNjcWePXuqvGbPnj1W5wNAXFyc5fzTp08jJyfH6pzAwEDExMRUOyYREZGWdL3zvXz5MsrLyxEcHGx1PDg4GMeOHavympycnCrPz8nJsdQrj1V3zq1KSkpQUlJi+b6goAAAUHrtqs25lf8qKr1W7JSas8erqxmNnl+WHO6cX5YcRs9o9Pw1XVNWcrMuhLCpO5PuLzvLICUlBXPmzLE5/t4/huqSh4iI9PXrr78iMDDQZePruvg2atQInp6eyM213n2Wm5uLkJCQKq8JCQlRPL/yf3NzcxEaGmp1TqdOnaocc/r06UhMTLR8n5+fj2bNmuHcuXMunXx3UlhYiPDwcJw/fx4BAQF6xzEEzlntcc5qj3NWOwUFBbjzzjtx++23u/Tn6Lr4ent7o0uXLsjMzMTgwYMBABUVFcjMzERCQkKV13Tv3h2ZmZmYNGmS5di2bdvQvXt3AEBkZCRCQkKQmZlpWWwLCwuxd+9eTJgwocoxzWYzzGazzfHAwEA+WWspICCAc1ZLnLPa45zVHuesdjw8XLslSveXnRMTExEfH4/o6Gh069YNaWlpKC4utux+HjlyJJo0aYKUlBQAwIsvvog+ffrg1VdfRf/+/bF+/Xrs378fb731FgDAZDJh0qRJmD9/Plq2bInIyEjMmjULYWFhlgWeiIhIT7ovvkOGDMGlS5eQlJSEnJwcdOrUCRkZGZYNU+fOnbP6F0iPHj3w/vvvY+bMmXjppZfQsmVLbNq0Ce3atbOcM2XKFBQXF2PcuHHIz89Hr169kJGRAR8fH10eIxERkRVBNq5fvy6Sk5PF9evX9Y5iGJyz2uOc1R7nrPY4Z7Wj1XyZhKv3UxMREZEV3X+9JBERUV3DxZeIiEhjXHyJiIg0VmcW32XLliEiIgI+Pj6IiYnBvn37FM/fuHEjWrduDR8fH7Rv3x5bt261qgshkJSUhNDQUPj6+iI2NhYnTpxw8aPQTm3ma+XKlejduzcaNmyIhg0bIjY21uZ8d58vqHiOVVq/fj1MJpNNKxznzFZ+fj4mTpyI0NBQmM1mtGrVyua/TbV/DkZR28eXlpaGu+66C76+vggPD8fkyZNtPuHNnedsx44dGDBgAMLCwmAymbBp06Yar8nKysI999wDs9mMFi1aYPXq1TbnODxnLt3OJYn169cLb29vsWrVKvHjjz+KsWPHigYNGojc3Nwqz9+9e7fw9PQUixcvFkeOHBEzZ84UXl5e4vvvv7ecs2jRIhEYGCg2bdokvvvuOzFw4EARGRkprl27puEjc43aztdTTz0lli1bJg4dOiSOHj0qRo0aJQIDA8XPP/9sOced50uomLNKp0+fFk2aNBG9e/cWgwYNsqpxzqyVlJSI6Oho8dBDD4ldu3aJ06dPi6ysLHH48GHVYxpNbR/f2rVrhdlsFmvXrhWnT58Wn332mQgNDRWTJ09WPabRbN26VcyYMUN8/PHHAoD45JNPFM8/deqUqFevnkhMTBRHjhwRS5cuFZ6eniIjI8NyjjPmrE4svt26dRMTJ060fF9eXi7CwsJESkpKlec/8cQTon///lbHYmJixLPPPiuEEKKiokKEhISIJUuWWOr5+fnCbDaLdevWuexxaKW283WrGzduCH9/f/Huu+8KUQfmS6icsxs3bogePXqIt99+W8THx1stvpwzWytWrBDNmzcXpaWlThvTaGr7+CZOnCjuu+8+q2OJiYmiZ8+eqsc0MnsW3ylTpoi2bdtaHRsyZIiIi4uzfO+MOXP7l535sYW1o2a+bnX16lWUlZVZfjeqO88XHJizuXPnIigoCGPGjLGpcc5sffrpp+jevTsmTpyI4OBgtGvXDgsXLkR5ebnqMY1EzePr0aMHDhw4YHlJ9NSpU9i6dSseeugh1WO6u5r+/nfWnOn+G65cTZaPLTQKNfN1q6lTpyIsLMzy5HTn+YLKOdu1axfeeecdHD58uMo658zWqVOn8OWXX2LYsGHYunUrTp48ieeeew5lZWVITk52ynNXZmoe31NPPYXLly+jV69eEELgxo0bGD9+PF566SXVY7q76v7+LywsxLVr13DlyhWnzJnb3/mSthYtWoT169fjk08+4a/zrEZRURFGjBiBlStXolGjRnrHMYyKigoEBQXhrbfeQpcuXTBkyBDMmDED6enpekeTVlZWFhYuXIjly5fj4MGD+Pjjj7FlyxbMmzdP72h1ntvf+crysYVGoWa+Kr3yyitYtGgRvvjiC3To0MFy3J3nCyrmLDs7G2fOnMGAAQMsxyoqKgAAt912G44fP845q0JoaCi8vLzg6elpOXb33XcjJycHpaWlDj13jUDN45s1axZGjBiBZ555BgDQvn17y++9nzFjhtvPmRrV/f0fEBAAX19feHp6OmXO3P7O988fW1ip8mMLKz+G8FaVH1v4Z9V9bGGlyo8trG5Mo1AzXwCwePFizJs3DxkZGYiOjraqufN8QcWctW7dGt9//z0OHz5s+Ro4cCDuvfdeHD58GOHh4ZyzKvTs2RMnT560/EMFAH766SeEhobC29tb9XPXKNQ8vqtXr9p8NF7lP16EEG4/Z2rU9Pe/0+asVlvFDGr9+vXCbDaL1atXiyNHjohx48aJBg0aiJycHCGEECNGjBDTpk2znL97925x2223iVdeeUUcPXpUJCcnV9lq1KBBA7F582bx//7f/xODBg1ymzaQ2s7XokWLhLe3t/jwww/FxYsXLV9FRUVW57jrfAkVc3arW3c7C86ZzZydO3dO+Pv7i4SEBHH8+HHx73//WwQFBYn58+fbPabR1XbOkpOThb+/v1i3bp04deqU+Pzzz0VUVJR44okn7B7T6IqKisShQ4fEoUOHBACRmpoqDh06JM6ePSuEEGLatGlixIgRlvMrW43+8Y9/iKNHj4ply5ZV2Wrk6JzVicVXCCGWLl0q7rzzTuHt7S26desmvvnmG0utT58+Ij4+3ur8Dz74QLRq1Up4e3uLtm3bii1btljVKyoqxKxZs0RwcLAwm83i/vvvF8ePH9fs8bhabearWbNmAoDNV3JysuUcd58voeI59mdVLb6cM9s5+/rrr0VMTIwwm82iefPmYsGCBeLGjRt2j+kOajNnZWVlYvbs2SIqKkr4+PiI8PBw8dxzz4krV67YPabRbd++vcq/nyrnKT4+XvTp08fmmk6dOglvb2/RvHlz8c9//tNmXEfnjJ9qREREpDG3f8+XiIhINlx8iYiINMbFl4iISGNcfImIiDTGxZeIiEhjXHyJiIg0xsWXiIhIY1x8iYiINMbFl6gOeuedd9CvXz+X/5yMjAx06tTJ6vcxExEXX6I65/r165g1axaSk5Nd/rMefPBBeHl5Ye3atS7/WURGwsWXqI758MMPERAQgJ49e2ry80aNGoU33nhDk59FZBRcfIkM6tKlSwgJCcHChQstx77++mt4e3vbfCTan61fv97qs4QBoG/fvpg0aZLVscGDB2PUqFGW7yMiIjB//nyMHDkSfn5+aNasGT799FNcunQJgwYNgp+fHzp06ID9+/dbjTNgwADs378f2dnZTnjURO6Biy+RQTVu3BirVq3C7NmzsX//fhQVFWHEiBFISEjA/fffX+11u3btsvnMZXu99tpr6NmzJw4dOoT+/ftjxIgRGDlyJIYPH46DBw8iKioKI0eOxJ8/r+XOO+9EcHAwdu7cqepnErkjLr5EBvbQQw9h7NixGDZsGMaPH4/69esjJSWl2vPz8/NRUFCAsLAw1T/v2WefRcuWLZGUlITCwkJ07doVjz/+OFq1aoWpU6fi6NGjyM3NtbouLCwMZ8+eVfUzidwRF18ig3vllVdw48YNbNy4EWvXroXZbK723GvXrgEAfHx8VP2sDh06WP5/cHAwAKB9+/Y2x/Ly8qyu8/X1xdWrV1X9TCJ3xMWXyOCys7Pxyy+/oKKiAmfOnFE894477oDJZMKVK1dqHLe8vNzmmJeXl+X/m0ymao/d2lr022+/oXHjxnY8GqK6gYsvkYGVlpZi+PDhGDJkCObNm4dnnnnG5q7zz7y9vdGmTRscOXLEpnbrS8WnTp1ySsbr168jOzsbnTt3dsp4RO6Aiy+Rgc2YMQMFBQV44403MHXqVLRq1QpPP/204jVxcXHYtWuXzfHNmzfj448/RnZ2NhYsWIAjR47g7NmzuHDhgkMZv/nmG5jNZnTv3t2hcYjcCRdfIoPKyspCWloa1qxZg4CAAHh4eGDNmjXYuXMnVqxYUe11Y8aMwdatW1FQUGB1vH///li8eDHatGmDHTt2YPny5di3bx/WrFnjUM5169Zh2LBhqFevnkPjELkTk/hzTwAR1QmPP/447rnnHkyfPh34o8+3U6dOSEtLc+rPuXz5Mu666y7s378fkZGRTh2byMh450tUBy1ZsgR+fn4u/zlnzpzB8uXLufAS3YJ3vkTksjtfIqoaF18iIiKN8WVnIiIijXHxJSIi0hgXXyIiIo1x8SUiItIYF18iIiKNcfElIiLSGBdfIiIijXHxJSIi0hgXXyIiIo39f6hdDvkHeIV2AAAAAElFTkSuQmCC", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax = sim.plot(z=t / 2, monitor_alpha=0)\n", "sim.plot_grid(z=t / 2, ax=ax)\n", "ax.set_xlim(0, 1)\n", "ax.set_ylim(0, 1)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The purpose of this notebook is solely for demonstration, thus, we will only be exploring a limited parameter space. For a more extensive exploration, a similar procedure can be adopted.\n", "\n", "Prior to initiating a [Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html) of simulations, it is important to get an estimate of the potential FlexCredit cost. This helps users by keeping them informed about possible expenses associated with the simulations and protects against accidental misuse of credits." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:48:46.266106Z", "iopub.status.busy": "2025-05-15T10:48:46.266006Z", "iopub.status.idle": "2025-05-15T10:50:04.801528Z", "shell.execute_reply": "2025-05-15T10:50:04.800665Z" } }, "outputs": [ { "data": { "text/html": [ "
19:03:59 CEST Maximum FlexCredit cost: 12.141 for the whole batch.              \n",
       "
\n" ], "text/plain": [ "\u001b[2;36m19:03:59 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m12.141\u001b[0m for the whole batch. \n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# parameter sweep ranges\n", "n_100_list = list(range(24, 36, 2))\n", "n_010_list = list(range(5, 7, 1))\n", "\n", "# create simulations\n", "sims = {\n", " f\"mode_index={mode_index}; n_100={n_100}; n_010={n_010};\": make_sim(mode_index, n_100, n_010)\n", " for mode_index in [0, 1]\n", " for n_100 in n_100_list\n", " for n_010 in n_010_list\n", "}\n", "\n", "# create batch\n", "batch = web.Batch(simulations=sims, verbose=True)\n", "_ = batch.estimate_cost()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Run the batch of simulations and verify the real cost. This cost is typically significantly reduced compared to the estimated one because of early shutoff." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2025-05-15T10:50:04.804226Z", "iopub.status.busy": "2025-05-15T10:50:04.803996Z", "iopub.status.idle": "2025-05-15T10:51:16.914557Z", "shell.execute_reply": "2025-05-15T10:51:16.913402Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "43e0a77f7f014206b1878c16f3e84f57", "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": [
       "
              Started working on Batch containing 24 tasks.                     \n",
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      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m24\u001b[0m tasks.                     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:04:22 CEST Maximum FlexCredit cost: 12.141 for the whole batch.              \n",
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      ],
      "text/plain": [
       "\u001b[2;36m19:04:22 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m12.141\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",
       "              the Batch has completed.                                          \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[0mthe Batch has completed.                                          \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6ad62aa08c52498084783a2ba5b003ef",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:07:22 CEST Batch complete.                                                   \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:07:22 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "62117967de644d239a02b232cf290d5c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
19:07:46 CEST Total billed flex credit cost: 5.630.                             \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:07:46 CEST\u001b[0m\u001b[2;36m \u001b[0mTotal billed flex credit cost: \u001b[1;36m5.630\u001b[0m.                             \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "batch_results = batch.run(path_dir=\"data\")\n",
    "_ = batch.real_cost()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Result Visualization\n",
    "\n",
    "Let's now move towards visualization of our results. We begin by extracting and plotting the transmission at the central frequency as a function of both $n_{010}$ and $n_{100}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:51:17.182196Z",
     "iopub.status.busy": "2025-05-15T10:51:17.182072Z",
     "iopub.status.idle": "2025-05-15T10:51:17.185871Z",
     "shell.execute_reply": "2025-05-15T10:51:17.185456Z"
    }
   },
   "outputs": [],
   "source": [
    "def cal_transmission_at_freq0(mode_index, n_010):\n",
    "    \"\"\"\n",
    "    Calculates the transmission at the central frequency as a function of n_100 for a given mode index\n",
    "    and n_010\n",
    "\n",
    "    Args:\n",
    "        mode_index (int): The index of the mode for which transmission is calculated. mode_index=0 for TE and mode_index=1 for TM.\n",
    "        n_010 (int): The number of periodic elements along the y-direction.\n",
    "\n",
    "    Returns:\n",
    "        tuple[list[float], list[float]]: A tuple containing two lists:\n",
    "            - `cross`: Power transmission values to the cross port.\n",
    "            - `through`: Power transmission values to the through port.\n",
    "    \"\"\"\n",
    "    cross = [\n",
    "        np.abs(\n",
    "            batch_results[f\"mode_index={mode_index}; n_100={n_100}; n_010={n_010};\"][\"cross\"]\n",
    "            .amps.sel(mode_index=mode_index, direction=\"+\")\n",
    "            .sel(f=freq0, method=\"nearest\")\n",
    "            .values\n",
    "        )\n",
    "        ** 2\n",
    "        for n_100 in n_100_list\n",
    "    ]\n",
    "\n",
    "    through = [\n",
    "        np.abs(\n",
    "            batch_results[f\"mode_index={mode_index}; n_100={n_100}; n_010={n_010};\"][\"through\"]\n",
    "            .amps.sel(mode_index=mode_index, direction=\"+\")\n",
    "            .sel(f=freq0, method=\"nearest\")\n",
    "            .values\n",
    "        )\n",
    "        ** 2\n",
    "        for n_100 in n_100_list\n",
    "    ]\n",
    "\n",
    "    return cross, through"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:51:17.187126Z",
     "iopub.status.busy": "2025-05-15T10:51:17.186928Z",
     "iopub.status.idle": "2025-05-15T10:51:17.190499Z",
     "shell.execute_reply": "2025-05-15T10:51:17.189940Z"
    }
   },
   "outputs": [],
   "source": [
    "# hex codes of the colors used for plotting\n",
    "colors = {\n",
    "    \"TM_cross\": \"#dc0154\",\n",
    "    \"TM_through\": \"#f5a67a\",\n",
    "    \"TE_cross\": \"#aaa3f0\",\n",
    "    \"TE_through\": \"#3130bc\",\n",
    "}\n",
    "\n",
    "\n",
    "def plot_transmission_at_freq0(cross, through, n_010, mode, ax):\n",
    "    \"\"\"\n",
    "    Plots the transmission values for cross and through ports at the central frequency as a function of n_100\n",
    "\n",
    "    Args:\n",
    "        cross (list[float]): List of transmission values for the cross port.\n",
    "        through (list[float]): List of transmission values for the through port.\n",
    "        n_010 (int): Number of periods in the AM[010]\n",
    "        mode (str): Input mode type (e.g., \"TE\" or \"TM\").\n",
    "        ax: Matplotlib Axes object on which to plot.\n",
    "    \"\"\"\n",
    "    ax.plot(n_100_list, cross, color=colors[f\"{mode}_cross\"], linewidth=2, label=\"Cross port\")\n",
    "    ax.plot(n_100_list, through, color=colors[f\"{mode}_through\"], linewidth=2, label=\"Through port\")\n",
    "    ax.set_title(f\"n_010={n_010}; {mode.upper()} input\")\n",
    "    ax.set_ylim(-0.05, 1.05)\n",
    "    ax.set_aspect(aspect=5)\n",
    "    ax.set_xlabel(\"n_100\")\n",
    "    ax.set_ylabel(\"Transmission\")\n",
    "    ax.legend()\n",
    "    ax.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The outcome replicates a portion of Figure 3 from the cited [paper](https://doi.org/10.1002/lpor.201800349). It is evident that the optimal outcome is achieved with $n_{100}=30$ and $n_{010}=5$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:51:17.191759Z",
     "iopub.status.busy": "2025-05-15T10:51:17.191514Z",
     "iopub.status.idle": "2025-05-15T10:51:30.722471Z",
     "shell.execute_reply": "2025-05-15T10:51:30.722176Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for n_010 in n_010_list:\n",
    "    fig, axes = plt.subplots(1, 2, figsize=(8, 5), sharex=True)\n",
    "\n",
    "    # TM\n",
    "    cross_tm, through_tm = cal_transmission_at_freq0(1, n_010)\n",
    "    plot_transmission_at_freq0(cross_tm, through_tm, n_010, \"TM\", axes[0])\n",
    "\n",
    "    # TE\n",
    "    cross_te, through_te = cal_transmission_at_freq0(0, n_010)\n",
    "    plot_transmission_at_freq0(cross_te, through_te, n_010, \"TE\", axes[1])\n",
    "\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we generate the transmission spectra plots for both TE and TM input simulations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:51:30.723812Z",
     "iopub.status.busy": "2025-05-15T10:51:30.723713Z",
     "iopub.status.idle": "2025-05-15T10:51:30.727087Z",
     "shell.execute_reply": "2025-05-15T10:51:30.726852Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_spectra(sim_data):\n",
    "    \"\"\"\n",
    "    Calculates the power spectra for the through and cross ports\n",
    "    from simulation data.\n",
    "\n",
    "    Args:\n",
    "        sim_data: td.SimulationData\n",
    "\n",
    "    Returns:\n",
    "        tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:\n",
    "            - Power spectrum for mode_index=0 at the through port.\n",
    "            - Power spectrum for mode_index=0 at the cross port.\n",
    "            - Power spectrum for mode_index=1 at the through port.\n",
    "            - Power spectrum for mode_index=1 at the cross port.\n",
    "    \"\"\"\n",
    "    return (\n",
    "        np.abs(sim_data[\"through\"].amps.sel(mode_index=0, direction=\"+\").values) ** 2,\n",
    "        np.abs(sim_data[\"cross\"].amps.sel(mode_index=0, direction=\"+\").values) ** 2,\n",
    "        np.abs(sim_data[\"through\"].amps.sel(mode_index=1, direction=\"+\").values) ** 2,\n",
    "        np.abs(sim_data[\"cross\"].amps.sel(mode_index=1, direction=\"+\").values) ** 2,\n",
    "    )\n",
    "\n",
    "\n",
    "def plot_spectra(sim_data, mode, field_component, field_vmin, field_vmax):\n",
    "    \"\"\"\n",
    "    Plots the spectra and field distribution for a given simulation result.\n",
    "\n",
    "    Parameters:\n",
    "        sim_data: Simulation data object.\n",
    "        mode: \"TE\" or \"TM\".\n",
    "        field_component: Field component to plot (e.g., \"Hz\", \"Ez\").\n",
    "        field_vmin: Minimum value for field plot colormap.\n",
    "        field_vmax: Maximum value for field plot colormap.\n",
    "    \"\"\"\n",
    "    # extract spectra\n",
    "    te_through, te_cross, tm_through, tm_cross = get_spectra(sim_data)\n",
    "\n",
    "    # choose the correct data based on mode\n",
    "    if mode == \"TE\":\n",
    "        through = te_through\n",
    "        cross = te_cross\n",
    "        title = \"TE input\"\n",
    "    elif mode == \"TM\":\n",
    "        through = tm_through\n",
    "        cross = tm_cross\n",
    "        title = \"TM input\"\n",
    "    else:\n",
    "        raise ValueError(\"Invalid mode. Use 'TE' or 'TM'.\")\n",
    "\n",
    "    # create figure\n",
    "    fig, axes = plt.subplots(2, 1, figsize=(5, 7))\n",
    "\n",
    "    # plot spectra\n",
    "    axes[0].plot(\n",
    "        ldas,\n",
    "        10 * np.log10(through),\n",
    "        color=colors[f\"{mode}_through\"],\n",
    "        linewidth=2,\n",
    "        label=\"Through port\",\n",
    "    )\n",
    "    axes[0].plot(\n",
    "        ldas, 10 * np.log10(cross), color=colors[f\"{mode}_cross\"], linewidth=2, label=\"Cross port\"\n",
    "    )\n",
    "    axes[0].set_title(title)\n",
    "    axes[0].set_ylim(-50, 2)\n",
    "    axes[0].set_xlabel(\"Wavelength (μm)\")\n",
    "    axes[0].set_ylabel(\"Transmission (dB)\")\n",
    "    axes[0].legend()\n",
    "    axes[0].grid()\n",
    "\n",
    "    # plot field distribution\n",
    "    sim_data.plot_field(\n",
    "        \"field\", field_component, \"real\", vmin=field_vmin, vmax=field_vmax, ax=axes[1]\n",
    "    )\n",
    "\n",
    "    # adjust layout and display\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The results show a great PBS performance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:51:30.728243Z",
     "iopub.status.busy": "2025-05-15T10:51:30.728148Z",
     "iopub.status.idle": "2025-05-15T10:51:31.333542Z",
     "shell.execute_reply": "2025-05-15T10:51:31.333312Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot TE simulation results\n",
    "sim_data_te = batch_results[\"mode_index=0; n_100=30; n_010=5;\"]\n",
    "plot_spectra(\n",
    "    sim_data=sim_data_te,\n",
    "    mode=\"TE\",\n",
    "    field_component=\"Hz\",\n",
    "    field_vmin=-0.5,\n",
    "    field_vmax=0.5,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:51:31.334789Z",
     "iopub.status.busy": "2025-05-15T10:51:31.334680Z",
     "iopub.status.idle": "2025-05-15T10:51:31.964399Z",
     "shell.execute_reply": "2025-05-15T10:51:31.963986Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot TM simulation results\n",
    "sim_data_tm = batch_results[\"mode_index=1; n_100=30; n_010=5;\"]\n",
    "plot_spectra(\n",
    "    sim_data=sim_data_tm,\n",
    "    mode=\"TM\",\n",
    "    field_component=\"Ez\",\n",
    "    field_vmin=-50,\n",
    "    field_vmax=50,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we determine the polarization extinction ratio (PER) specifically for the TM input scenario."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-15T10:51:31.965340Z",
     "iopub.status.busy": "2025-05-15T10:51:31.965255Z",
     "iopub.status.idle": "2025-05-15T10:51:32.017352Z",
     "shell.execute_reply": "2025-05-15T10:51:32.017108Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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       "
"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, _, tm_through, tm_cross = get_spectra(sim_data_tm)\n",
    "\n",
    "per_tm = 10 * np.log10(tm_cross / tm_through)\n",
    "\n",
    "plt.plot(ldas, per_tm, c=\"red\", linewidth=2)\n",
    "plt.title(\"Polarization Extinction Ratio (PER) for TM Input\")\n",
    "plt.ylim(0, 50)\n",
    "plt.xlabel(\"Wavelength (μm)\")\n",
    "plt.ylabel(\"PER_TM (dB)\")\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Final Remarks\n",
    "\n",
    "This notebook demonstrates the design process of a broadband PBS based on SWG AM. The result shows low loss and large bandwidth. However, ideally we would like to have a flat polarization extinction ratio. As demonstrated in the referenced paper, this can be achieved by further fine-tuning the duty cycle of the AM[100]. We don't demonstrate this part in this notebook and leave this part for the readers as an exercise. Readers are encouraged to explore additional opportunities to optimize the design by introducing apodization or using inverse design optimization, for example."
   ]
  }
 ],
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  "applications": [
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  ],
  "description": "This notebook demonstrates how to model a broadband polarization beam splitter (PBS) based on anisotropic metamaterial in Tidy3D FDTD.",
  "feature_image": "./img/pbs_swg_am.png",
  "features": [
   "Mode analysis",
   "Parameter sweep"
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  "keywords": "integrated photonics, polarization beam splitter, PBS, subwavelength grating, SWG, anisotropic metamaterial, waveguide, Tidy3D, FDTD",
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       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_3568ec7f047f4cf6bc5d08918a0b4f66",
       "msg_id": "",
       "outputs": [
        {
         "data": {
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mode_index=0; n_100=24; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:16\nmode_index=0; n_100=24; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:16\nmode_index=0; n_100=26; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:15\nmode_index=0; n_100=26; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:15\nmode_index=0; n_100=28; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:15\nmode_index=0; n_100=28; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:15\nmode_index=0; n_100=30; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:14\nmode_index=0; n_100=30; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:14\nmode_index=0; n_100=32; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:14\nmode_index=0; n_100=32; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:14\nmode_index=0; n_100=34; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:13\nmode_index=0; n_100=34; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:13\nmode_index=1; n_100=24; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:13\nmode_index=1; n_100=24; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:13\nmode_index=1; n_100=26; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:13\nmode_index=1; n_100=26; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:12\nmode_index=1; n_100=28; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:12\nmode_index=1; n_100=28; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:12\nmode_index=1; n_100=30; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:12\nmode_index=1; n_100=30; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:11\nmode_index=1; n_100=32; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:11\nmode_index=1; n_100=32; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:11\nmode_index=1; n_100=34; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:11\nmode_index=1; n_100=34; n_0... → success       ━━━━━━━━━━━━━━━━━━━━ 100% 0:00:10\n
\n",
          "text/plain": "mode_index=0; n_100=24; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:16\u001b[0m\nmode_index=0; n_100=24; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:16\u001b[0m\nmode_index=0; n_100=26; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:15\u001b[0m\nmode_index=0; n_100=26; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:15\u001b[0m\nmode_index=0; n_100=28; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:15\u001b[0m\nmode_index=0; n_100=28; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:15\u001b[0m\nmode_index=0; n_100=30; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:14\u001b[0m\nmode_index=0; n_100=30; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:14\u001b[0m\nmode_index=0; n_100=32; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:14\u001b[0m\nmode_index=0; n_100=32; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:14\u001b[0m\nmode_index=0; n_100=34; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:13\u001b[0m\nmode_index=0; n_100=34; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:13\u001b[0m\nmode_index=1; n_100=24; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:13\u001b[0m\nmode_index=1; n_100=24; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:13\u001b[0m\nmode_index=1; n_100=26; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:13\u001b[0m\nmode_index=1; n_100=26; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:12\u001b[0m\nmode_index=1; n_100=28; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:12\u001b[0m\nmode_index=1; n_100=28; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:12\u001b[0m\nmode_index=1; n_100=30; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:12\u001b[0m\nmode_index=1; n_100=30; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:11\u001b[0m\nmode_index=1; n_100=32; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:11\u001b[0m\nmode_index=1; n_100=32; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:11\u001b[0m\nmode_index=1; n_100=34; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:11\u001b[0m\nmode_index=1; n_100=34; n_0... → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:10\u001b[0m\n"
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