{ "cells": [ { "cell_type": "markdown", "id": "0a854688", "metadata": {}, "source": [ "# Mode Solver\n", "\n", "Run this notebook in your browser using [Binder](https://mybinder.org/v2/gh/flexcompute-readthedocs/tidy3d-docs/readthedocs?labpath=docs%2Fsource%2Fnotebooks%2FModeSolver.ipynb).\n", "\n", "This tutorial shows how to use the mode solver plugin in tidy3d." ] }, { "cell_type": "code", "execution_count": 1, "id": "dfe126a8", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:41.650412Z", "iopub.status.busy": "2022-07-21T20:32:41.649884Z", "iopub.status.idle": "2022-07-21T20:32:42.602478Z", "shell.execute_reply": "2022-07-21T20:32:42.601980Z" }, "tags": [] }, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pylab as plt\n", "\n", "import tidy3d as td\n", "from tidy3d.constants import C_0\n", "import tidy3d.web as web\n", "\n", "from tidy3d.plugins import ModeSolver" ] }, { "cell_type": "markdown", "id": "56cfb817", "metadata": {}, "source": [ "## Setup\n", "\n", "We first set up the mode solver with information about our system. We start by setting parameters" ] }, { "cell_type": "code", "execution_count": 2, "id": "637d4748", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:42.604296Z", "iopub.status.busy": "2022-07-21T20:32:42.604171Z", "iopub.status.idle": "2022-07-21T20:32:42.607058Z", "shell.execute_reply": "2022-07-21T20:32:42.606625Z" }, "tags": [] }, "outputs": [], "source": [ "# size of simulation domain\n", "Lx, Ly, Lz = 6, 6, 6\n", "dl = .05\n", "\n", "# waveguide information \n", "wg_width = 1.5\n", "wg_height = 1.0\n", "wg_permittivity = 4.0\n", "\n", "# central frequency \n", "wvl_um = 2.0\n", "freq0 = C_0 / wvl_um\n", "fwidth = freq0 / 3\n", "\n", "# run_time in ps\n", "run_time = 1e-12\n", "\n", "# automatic grid specification\n", "grid_spec = td.GridSpec.auto(min_steps_per_wvl=20, wavelength=wvl_um)" ] }, { "cell_type": "markdown", "id": "97533832", "metadata": {}, "source": [ "Then we set up a simulation, in this case including a straight waveguide and default periodic boundary conditions." ] }, { "cell_type": "code", "execution_count": 3, "id": "a291bd49", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:42.608529Z", "iopub.status.busy": "2022-07-21T20:32:42.608344Z", "iopub.status.idle": "2022-07-21T20:32:42.691503Z", "shell.execute_reply": "2022-07-21T20:32:42.691149Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
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}, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "waveguide = td.Structure(\n", " geometry = td.Box(size=(wg_width, td.inf, wg_height)),\n", " medium = td.Medium(permittivity=wg_permittivity)\n", ")\n", "\n", "sim = td.Simulation(\n", " size=(Lx, Ly, Lz),\n", " grid_spec=grid_spec,\n", " structures=[waveguide],\n", " run_time = run_time,\n", ")\n", "\n", "ax = sim.plot(z=0)" ] }, { "cell_type": "markdown", "id": "6214a935", "metadata": {}, "source": [ "## Initialize Mode Solver\n", "\n", "With our system defined, we can now create our mode solver. We first need to specify on what plane we want to solve the modes using a `td.Box()` object." ] }, { "cell_type": "code", "execution_count": 4, "id": "2a92dc3e", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:42.693239Z", "iopub.status.busy": "2022-07-21T20:32:42.693051Z", "iopub.status.idle": "2022-07-21T20:32:42.695336Z", "shell.execute_reply": "2022-07-21T20:32:42.695080Z" }, "tags": [] }, "outputs": [], "source": [ "plane = td.Box(\n", " center=(0,0,0),\n", " size=(4, 0, 3.5)\n", ")" ] }, { "cell_type": "markdown", "id": "e2f289a9", "metadata": {}, "source": [ "The mode solver can now compute the modes given a `ModeSpec` object that specifies everything about the modes we're looking for, for example:\n", "\n", "- `num_modes`: how many modes to compute.\n", "\n", "- `target_neff`: float, default=None, initial guess for the effective index of the mode; if not specified, the modes with the largest real part of the effective index are computed.\n", "\n", "The full list of specification parameters can be found [here](https://docs.simulation.cloud/projects/tidy3d/en/latest/_autosummary/tidy3d.ModeSpec.html#tidy3d.ModeSpec)." ] }, { "cell_type": "code", "execution_count": 5, "id": "a87e86c0", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:42.696662Z", "iopub.status.busy": "2022-07-21T20:32:42.696526Z", "iopub.status.idle": "2022-07-21T20:32:42.698302Z", "shell.execute_reply": "2022-07-21T20:32:42.698068Z" }, "tags": [] }, "outputs": [], "source": [ "mode_spec = td.ModeSpec(\n", " num_modes=3,\n", " target_neff=2.0,\n", ")" ] }, { "cell_type": "markdown", "id": "dba7911a", "metadata": {}, "source": [ "We can also specify a list of frequencies at which to solvefor the modes." ] }, { "cell_type": "code", "execution_count": 6, "id": "fddf6735", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:42.699582Z", "iopub.status.busy": "2022-07-21T20:32:42.699456Z", "iopub.status.idle": "2022-07-21T20:32:42.701298Z", "shell.execute_reply": "2022-07-21T20:32:42.701055Z" } }, "outputs": [], "source": [ "num_freqs = 11\n", "f0_ind = num_freqs // 2\n", "freqs = np.linspace(freq0 - fwidth / 2, freq0 + fwidth / 2, num_freqs)" ] }, { "cell_type": "markdown", "id": "eb12573c", "metadata": {}, "source": [ "Finally, we can initialize the `ModeSolver`, and call the solve method." ] }, { "cell_type": "code", "execution_count": 7, "id": "a1656378", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:42.702573Z", "iopub.status.busy": "2022-07-21T20:32:42.702427Z", "iopub.status.idle": "2022-07-21T20:32:44.255434Z", "shell.execute_reply": "2022-07-21T20:32:44.255006Z" } }, "outputs": [], "source": [ "mode_solver = ModeSolver(\n", " simulation=sim,\n", " plane=plane,\n", " mode_spec=mode_spec,\n", " freqs=freqs,\n", ")\n", "mode_data = mode_solver.solve()" ] }, { "cell_type": "markdown", "id": "270eb533", "metadata": {}, "source": [ "## Visualizing Mode Data\n", "\n", "The `mode_info` object contains information about the effective index of the mode and the field profiles, as well as the `mode_spec` that was used in the solver. The effective index data and the field profile data is in the form of xarray DataArrays.\n", "\n", "We can for example plot the real part of the effective index for all three modes as follows." ] }, { "cell_type": "code", "execution_count": 8, "id": "e051faab", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:44.257474Z", "iopub.status.busy": "2022-07-21T20:32:44.257319Z", "iopub.status.idle": "2022-07-21T20:32:44.320003Z", "shell.execute_reply": "2022-07-21T20:32:44.319686Z" } }, "outputs": [ { "data": { "text/html": [ "
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<Figure size 432x288 with 1 Axes>\n",
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\n" }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(1)\n", "n_eff = mode_data.n_eff # real part of the effective mode index\n", "n_eff.plot.line(x='f');" ] }, { "cell_type": "markdown", "id": "cf0d2045", "metadata": {}, "source": [ "The raw data can also be accessed." ] }, { "cell_type": "code", "execution_count": 9, "id": "356bc255", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:44.321774Z", "iopub.status.busy": "2022-07-21T20:32:44.321614Z", "iopub.status.idle": "2022-07-21T20:32:44.324796Z", "shell.execute_reply": "2022-07-21T20:32:44.324541Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "first mode effective index at freq0: n_eff = 1.77, k_eff = 0.00e+00\n" ] } ], "source": [ "n_complex = mode_data.n_complex # complex effective index as a DataArray\n", "n_eff = mode_data.n_eff.values # real part of the effective index as numpy array\n", "k_eff = mode_data.k_eff.values # imag part of the effective index as numpy array\n", "\n", "print(f'first mode effective index at freq0: n_eff = {n_eff[f0_ind, 0]:.2f}, k_eff = {k_eff[f0_ind, 0]:.2e}')" ] }, { "cell_type": "markdown", "id": "ac9ef151", "metadata": {}, "source": [ "The fields stored in `mode_data.fields` can be visualized using in-built xarray methods." ] }, { "cell_type": "code", "execution_count": 10, "id": "3b27d122", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:44.326486Z", "iopub.status.busy": "2022-07-21T20:32:44.326355Z", "iopub.status.idle": "2022-07-21T20:32:44.533637Z", "shell.execute_reply": "2022-07-21T20:32:44.533169Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
<Figure size 720x216 with 4 Axes>\n",
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\n" }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "field_data = mode_data.fields\n", "\n", "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(10, 3))\n", "abs(field_data.Ex.isel(mode_index=0, f=f0_ind)).plot(x='x', y='z', ax=ax1, cmap=\"magma\")\n", "abs(field_data.Ez.isel(mode_index=0, f=f0_ind)).plot(x='x', y='z', ax=ax2, cmap='magma')\n", "\n", "ax1.set_title('|Ex(x, y)|')\n", "ax1.set_aspect(\"equal\")\n", "ax2.set_title('|Ez(x, y)|')\n", "ax2.set_aspect(\"equal\")\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "f6a1a024", "metadata": {}, "source": [ "Alternatively, we can use the in-built ``plot_field`` method of ``mode_data``, which also allows us to overlay the structures in the simulation. The image also looks slightly different because we have set ``robust=True`` by default, which scales the colorbar to between the 2nd and 98th percentile of the data." ] }, { "cell_type": "code", "execution_count": 11, "id": "62c2f269", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:44.535260Z", "iopub.status.busy": "2022-07-21T20:32:44.535130Z", "iopub.status.idle": "2022-07-21T20:32:44.782981Z", "shell.execute_reply": "2022-07-21T20:32:44.782678Z" } }, "outputs": [ { "data": { "text/html": [ "
<Figure size 720x216 with 4 Axes>\n",
       "
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\n" }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(10, 3))\n", "mode_data.plot_field(\"Ex\", \"abs\", mode_index=0, freq=freq0, ax=ax1)\n", "mode_data.plot_field(\"Ez\", \"abs\", mode_index=0, freq=freq0, ax=ax2)\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "706a01ca", "metadata": {}, "source": [ "## Choosing the mode of interest\n", "\n", "We can also look at the other modes that were computed." ] }, { "cell_type": "code", "execution_count": 12, "id": "4345ce13", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:44.784726Z", "iopub.status.busy": "2022-07-21T20:32:44.784553Z", "iopub.status.idle": "2022-07-21T20:32:45.032951Z", "shell.execute_reply": "2022-07-21T20:32:45.032556Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
<Figure size 720x216 with 4 Axes>\n",
       "
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\n" }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "mode_index = 1\n", "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(10, 3))\n", "mode_data.plot_field(\"Ex\", \"abs\", mode_index=mode_index, freq=freq0, ax=ax1)\n", "mode_data.plot_field(\"Ez\", \"abs\", mode_index=mode_index, freq=freq0, ax=ax2);\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "411d2a62", "metadata": {}, "source": [ "This looks like an Ez-dominant mode. Finally, next-order mode has mixed polarization." ] }, { "cell_type": "code", "execution_count": 13, "id": "d2bb0c31", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:45.034494Z", "iopub.status.busy": "2022-07-21T20:32:45.034370Z", "iopub.status.idle": "2022-07-21T20:32:45.282127Z", "shell.execute_reply": "2022-07-21T20:32:45.281659Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
<Figure size 720x216 with 4 Axes>\n",
       "
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\n" }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "mode_index = 2\n", "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(10, 3))\n", "mode_data.plot_field(\"Ex\", \"abs\", mode_index=mode_index, freq=freq0, ax=ax1)\n", "mode_data.plot_field(\"Ez\", \"abs\", mode_index=mode_index, freq=freq0, ax=ax2);\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "2e220cf2", "metadata": {}, "source": [ "## Exporting Results\n", "\n", "This looks promising!\n", "\n", "Now we can choose the mode specifications to use in our mode source and mode monitors. These can be created separately, can be exported directly from the mode solver, for example:" ] }, { "cell_type": "code", "execution_count": 14, "id": "32d20a0b", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:45.283796Z", "iopub.status.busy": "2022-07-21T20:32:45.283681Z", "iopub.status.idle": "2022-07-21T20:32:45.286975Z", "shell.execute_reply": "2022-07-21T20:32:45.286718Z" }, "tags": [] }, "outputs": [], "source": [ "# Makes a modal source with geometry of `plane` with modes specified by `mode_spec` and a selected `mode_index`\n", "source_time = td.GaussianPulse(freq0=freq0, fwidth=fwidth)\n", "mode_src = mode_solver.to_source(mode_index=2, source_time=source_time, direction='-')\n", "\n", "# Makes a mode monitor with geometry of `plane`.\n", "mode_mon = mode_solver.to_monitor(name='mode', freqs=freqs)\n", "# Offset the monitor along the propagation direction\n", "mode_mon = mode_mon.copy(update=dict(center = (0, -2, 0)))" ] }, { "cell_type": "code", "execution_count": 15, "id": "4cd19f9a", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:45.288336Z", "iopub.status.busy": "2022-07-21T20:32:45.288168Z", "iopub.status.idle": "2022-07-21T20:32:45.360659Z", "shell.execute_reply": "2022-07-21T20:32:45.360298Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
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Ih3xRAyJfVCGKI8b4iirByRdViGKINb6iSnAgX1Qh8kC+qAUhX1QhwiNf1AKRL6oQYZEvqhBCjDlRjuDkiypEWOSLmgFmdrWZPWxmt/e7jXxRhQiPfFGz4W+BCwbZQL6oQoSnLL6ohSY4d/8O0PejAvr1RQ1R+6YkJyaZWOOr6BHcQMgXVYjiiDG+xj7Bmdk2M7vFzG45ePDgsuvLF1WIcMgXNWPcfbu7b3X3rXNzc31tI19UIcIhX9QxQL6oQoRDvqh9YGafBf4P8DQzu9/M3pylvnxRhQhHDL6ohd7o6+5vCL2P9k5qPfpYN+4KkQ2h40u+qH2g2lIhwiFfVCGEKICJGMGptlSIcMgXtUBUWypEOOSLWiDyRRUiHPJFLRD5ogoRDvmiFoh8UYUIh3xRC0S+qEKEQ76oAZEvqhDFEWN8RZXg5IsqRDHEGl9RJTiQL6oQeSBf1IKQL6oQ4ZEvaoHIF1WIsMgXVQghxpwoR3DyRRUiLPJFLQj5ogoRHvmiFoR8UYUIj3xRC0C+qEIUQ6zxFVWCky+qEMURY3xFleD6Qb6oQoRDvqhjgHxRhQiHfFHHAPmiChEO+aL2gZldYGZ3mdndZva+rPXliypEOGLwRS0sQs2sCnwCeBWwGXiDmW3Oej+qLRUiHHnVhg/LspUMZvZ7wDXu/ujQe+nOC4C73X1Xup+/By4CfpbxfkpZW3rd7uuKbkJXHj5lZ6Z6jy08yt5DDx79f3ZqDetWbch0H9ft3pepXtZcPH9x0U1YknH2Re2nVOuJwI/M7CfA1cAN7u5D7/EY64H72v6/H3hh50pmtg3YBoyUyUWc3PXLb/PLA3dTsRrgmBmveMblRTdLRMKyU1R3/wPgqcCngEuBfzKzj5jZUwK3rbX/7e6+1d23zs3NDaXRXvs2Pz+v+9giwnEqVmOqOkOtMoO7bs0ZN0LH1yhafRXbu7ub2UPAQ0AdOBn4gpnd6O7vGXLfDwDtc40z0vcypds5gdY5g5jPw43rtOXGX30rU70Vh2+m1niYKV+Ju+MOp/7q3Ez3cfH8eZnqTRKh4yu4L6qZvcPMfgz8KfBd4Fnu/rvA84DXDr1n+BHwVDN7splNA78NfHkEvROQL6oQ4YjBF7WfEdw64GJ3v6f9TXdvmtmFw+7Y3etm9nbgBqAKXO3udwyr18kgtW/D/NLIF1VMMnnEVxajwGUTnLt/cIllI10yc/evAV8bRaMbw9S+DdKRLf3Z2dmsmixENOQVX/JF7YJ8UYUIh3xRAyJfVCGKI8b4iirByRdViGKINb6iSnAgX1Qh8kC+qAUhX1QhwiNf1AKRL6oQYZEvqhBCjDlRjuDkiypEWOSLWhDyRRUiPPJFLQj5ogoRHvmiFoB8UYUohljjK6oEJ1/UyeBQ41Eeb+zh8cYemhw5bpnD0WWPN/bQ8HoxjZxAYoyvKC8yLMWgBb6j1Nap2D579h65n68+8j4qVgWg6U2m7Nj3YsCXHk6e6NvwIzxvzZt4xtyrimjqRJJnfKnYvgfyRY2XueoTqFiNGiuYtlWsqKymaok9o5kxU1nNtK1i2lZRtSlOnjqz4BZPHvJFHQPkixontcoM62eeyxE/tOR6Ta9Tocap00/PqWWiHfmijgHyRY2Ts1a+FDNbcp1Ff5yNs+cencqK/JEv6hig2tL4eNL0FsBoeqPnOhWrsmn2xfk1SnQlel/UMqDa0rhoTVPvP/xjZuxEJzVNT8eLcfZFLf0ITsTJUtNUTU9Fv0zECE61pfHRPk3tTGSano4XedSGD0vpR3CqLY2T9qupNZxPn/oAm6cWND0dM/KqDR+WQhKcmb3OzO4ws6aZbQ21H/mixk1rmvrcmcNsnTnMK1Ye1PR0jIjBF7WoEdztwMXAd0LtIHTtm3xRw9Oapr5y9gCLDq9eeZCqVTQ9HQPyiK9MbuUaessRcPed7n5XKP3QtW8tfd3oG5ZaZYaNM8/m5SsPsqdRZZU1eNa0a3paMHnFl0q1uiBf1HLxitVnUjOnjlE15/VrTtH0tEDki5piZt80s9u7vC4aUGebmd1iZrccOHBAvqgTxstmHjl6qf/xpnHB7F4MnfssghjjK9htIu5+fkY624HtABs3bvReHZBl7VsIfTE4Feo8u/Yj9tVX0vRDLFqF+Yqz3nZxv59ddPMmiljjK7o5lnxRJ4dNdhdV6tQqa3CazFRWUaHBlsr3i25a6ZEv6giY2WvM7H7gRcBXzeyGfrfNq/ZNtavFc07le1RoMGWzVG2KaZtjgVmeU/2upqmBkS/qCLj79cD1w26fR+2baleLpUKdZ1W/z2FWYlbh5KmNADSAFTymaWpg5IsqREBa09Nml99gTVNFv0SZ4Npr3+bn5zMvuwqtL5anNT3thqap4Wn5osYeX9ElOPmilp/26Wk3GkyxgsdZb7tybtnkIF/UgpAvavlZanraQtPUsMgXtQDkizoZLDU9baFpar7EGl9RJTj5opaf5aanLTRNzZ8Y4yuqBNcPoWvf2vX1uKTsOdUeYIbD1DjCNIdYwWNUaZk7Oyt4jGkOMc0hplhkU+XOQts7aeQZX1kkuVI+0bdf89hRa+v27duXVZNFykN+Jp888qGjU9RX1D7H6fYvNNJDtUKDvzlyRdv6Gwtp5ySTV3xlcQNwKRMchK99ky9qKIz7/KlH/zvkqxI7+7bl97gel1Q0ecRXu/6wlG6K2o58UYUIh3xRxwDVlgoRDvmijgGqLRUiHPJFFUKIApiIEZx8UYUIh3xRC0S1pUKEQ76oBSJfVCHCIV/UApEvqhDhkC9qgcgXVYhwyBe1QOSLKkQ45IsaEHeXL6oQBRFjfEWV4MysZydlWfsWQl+ImIk1vqJKcCBfVCHyQL6oI2BmHzWzO81sh5ldb2Zr+91WvqhChKcsvqhFjeBuBLa4+znAz4Erlln/ONpr33bv3p1554TWF2Lcafmixh5fRRk/f6Pt3+8Dv1VEO6Lm7u1Ft6ArL63uzFTvDPsnTraHaXoFA5pW5aXVr2S6D+7+52z1subsbUW3IFrGoRb1MuBzvRaa2TZgG3D0juY8at9UuzoeVGhiQMUcAMOLbdCE0PJFhbjjK9gU1cy+aWa3d3ld1LbOlUAduLaXjrtvd/et7r51bm5OvqgTxgKzHPKVHPSTOOhrqDNVdJMmgrL4ogYbwbn7+UstN7NLgQuB89y975/l5WrfRvkl6Ke2bmxGcmM6bbn5O9/KVG+T3cmc7WeBlYCz0g9yc+PCTPdxydnnZapXBnr5osYWX0VdRb0AeA/wm+7+eL/byRdViGKINb6Kuor6cWA1cKOZ3WpmV/WzkXxRhSiOGOOrqKuoZ4fSHnS4O0pt3ezsbFbNFiIK8owvFdv3IHTtW0tfj0sSk0he8ZXFSK6UCQ7C177NzMgXVUwuecRXFkmutAkO5IsqREhCx1e7/rCUPkJVWypEOPKqDR+WcahkCE5o30YhJpnQ8aVHlgshRBcmYgSn2lIhwiFf1AJRbakQ4ZAvaoHIF1WIcMgXtUDkiypEOOSLWiDyRRUiHDH5opbuIkPo2rd2fZ3DC8M6e4gKyfR/2jr72Jm3B4/+t9fnqaMfmrzIM76yuEgRVYJr+aL2+uBZ1L4ttW2nvhJc9jzR7uPtU1dQTw9NwznSlsCcCm+bej8AUyzy9cYlfLfx6kLaOmnkHV9ZENUUVb6o5edX/kTqTHGEGRZYyWFW0Tj6FF/jEHMssJIFVlJnivubTym0vZNCrPEVVYID+aKWnTrT/Kz5PFaw9HNQq9Q5wjT3+lNzatlkIV/Ugsir9k21q8VxW/OlNJc5NGd4nB2NF+FUc2rVZFEWX9SozsG1yKP2TbWrxbGruRmnQoUGzR4JrEmVHc0X59yyyaHliwpxx1d0IzhRfpabpmp6KvolygTXXvs2Pz+fedlVaH2xPEtNUzU9DU/LFzX2+IouwckXdTLY1dxMM52mdqLpaXjK4osaXYLLq/YthL7onzrT7OwyTdX0NB96+aLGFl9F+aL+FzPbkVoGfsPMTu9nO/miThbdpqmanhZDrPFV1Ajuo+5+jrs/B/gK8IF+NpIv6mTRbZqq6WlxxBhfhSQ4d9/f9u8qwLPSHrSTRqmt0+OSwtI5TdX0tHjyjK8sklxh5+DM7I/M7D7gEvocwfWLfFHLQ/s0VdPT8SAmX1Rzz2zwdLyw2TeBJ3VZdKW7f6ltvSuAFe7+wR4624BtAGvXrn3ee9/73r7b0Gw2qdfr1Gq1Eyz+llrWL/V6ndWrVzM9Pd1Vf3FxseuyQdrfS2Nc9e/71YFj/7hj3sCtCmbHr7jUsjaq1Hn76R/jiE8xZYt8YfcbeGDxzMz0ATacsrrr+zH2f1b6u3fvplpd+ockdHy1a1x55ZU/dvetg2oEq2Rw9/P7XPVa4GtA1wTn7tuB7QDr16/3Wm2wJlcqlaNfZGvber1OvV4/7r1hOemkk074lcqy/KSb1jjrN/Ye/4trzQa1+mHqtRV4pXrsvcbx7/XUY5qfLzyDZ87u4FBzJfc1zsKrxwJmVH2ANWvW9FwWW/9npf/oo4/2FRuh46ulP/T2I+19SMys/STKRcCdofZVq9WYnp5mcXHxaMd3fiGjEHttbGh9r1Sp11ZQqx/Gmo2uCWk5fnboHKbsCDsPbcE7Dtks9Jci9v4PrR86vlr6Q28/cguG40/M7GlAE7gHeGvInbU6ujWfn5mZyaTzW8ReGxta/1gSOgRAvTY7UPK5Z+HJPFI/lZ2HtwTRX47Y+z+0fuj4GkWrkATn7q8tYr8iThrU+OTD7yy6GSJConyayKC0hs2tX63WnD6rX5k8fCFj1j82bZwFyHQKmYd+7P0fWj90fNXr9aG3ja5Ua1A6zwl0njMYldhrY0Prd54T6zxnNu76sfd/aP3Q8dXSH5ZSJ7heJzyz+hIajUbUtbGh9Xud8M8qCYXWj73/Q+uHjq92/WEpbYJb7mrOqF9CvV6n0WhEWxsbWn+5q5mjJqHQ+rH3f2j9POIri6uxpUxw/Xb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}, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# In-plane field monitor, slightly offset along x\n", "monitor = td.FieldMonitor(\n", " center=(0, 0, 0.1),\n", " size=(td.inf, td.inf, 0),\n", " freqs=[freq0],\n", " name='field'\n", ")\n", "\n", "sim = td.Simulation(\n", " size=(Lx, Ly, Lz),\n", " grid_spec=grid_spec,\n", " run_time=run_time,\n", " boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n", " structures=[waveguide],\n", " sources=[mode_src],\n", " monitors=[monitor, mode_mon]\n", ")\n", "\n", "sim.plot(z=0);" ] }, { "cell_type": "code", "execution_count": 16, "id": "a4250bd4", "metadata": { "execution": { "iopub.execute_input": "2022-07-21T20:32:45.362032Z", "iopub.status.busy": "2022-07-21T20:32:45.361883Z", "iopub.status.idle": "2022-07-21T20:33:25.911385Z", "shell.execute_reply": "2022-07-21T20:33:25.910680Z" } }, "outputs": [ { "data": { "text/html": [ "
[16:32:45] INFO     Using Tidy3D credentials from stored file                      auth.py:74\n",
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[16:32:47] INFO     Uploaded task 'mode_simulation' with task_id                webapi.py:120\n",
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[16:32:54] INFO     Maximum flex unit cost: 0.20                                webapi.py:244\n",
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       "
           INFO     status = postprocess                                        webapi.py:292\n",
       "
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = postprocess                                        \u001b]8;id=923282;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=64800;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#292\u001b\\\u001b[2m292\u001b[0m\u001b]8;;\u001b\\\n"
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       "                    \"data/simulation_data.hdf5\"                                              \n",
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      ],
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m downloading file \u001b[32m\"output/monitor_data.hdf5\"\u001b[0m to              \u001b]8;id=710794;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=73264;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#574\u001b\\\u001b[2m574\u001b[0m\u001b]8;;\u001b\\\n",
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       "
[16:33:25] INFO     loading SimulationData from data/simulation_data.hdf5       webapi.py:398\n",
       "
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       "\u001b[2;36m[16:33:25]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m loading SimulationData from data/simulation_data.hdf5       \u001b]8;id=608797;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=634589;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#398\u001b\\\u001b[2m398\u001b[0m\u001b]8;;\u001b\\\n"
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   "source": [
    "job = web.Job(simulation=sim, task_name='mode_simulation')\n",
    "sim_data = job.run(path='data/simulation_data.hdf5')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acac7b19",
   "metadata": {},
   "source": [
    "We can now plot the in-plane field and the modal amplitudes. Since we injected mode 2 and we just have a straight waveguide, all the power recorded by the modal monitor is in mode 2, going backwards."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4d8425d3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-21T20:33:26.177944Z",
     "iopub.status.busy": "2022-07-21T20:33:26.177845Z",
     "iopub.status.idle": "2022-07-21T20:33:26.442674Z",
     "shell.execute_reply": "2022-07-21T20:33:26.442273Z"
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   },
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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(10, 4))\n",
    "sim_data.plot_field(\"field\", \"Ez\", freq=freq0, ax=ax[0])\n",
    "sim_data['mode']['amps'].sel(direction='-').abs.plot.line(x='f', ax=ax[1]);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3a50f61",
   "metadata": {},
   "source": [
    "## Storing server-side computed modes\n",
    "\n",
    "We can also use a `ModeFieldMonitor` to store the modes as they are computed server-side. This is illustrated below. We will also request in the mode specification that the modes are filtered by their `tm` polarization. In this particular simulation, TM refers to `Ez` polarization. The effect of the filtering is that modes with a `tm` polarization fraction larger than or equal to 0.5 will come first in the list of modes (while still ordered by decreasing effective index). After that, the set of predominantly `te`-polarized modes (`tm` fraction < 0.5) follow."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4cb3fdb9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-21T20:33:26.444547Z",
     "iopub.status.busy": "2022-07-21T20:33:26.444363Z",
     "iopub.status.idle": "2022-07-21T20:33:26.449536Z",
     "shell.execute_reply": "2022-07-21T20:33:26.449129Z"
    }
   },
   "outputs": [],
   "source": [
    "mode_spec = mode_spec.copy(update=dict(filter_pol = \"tm\"))\n",
    "\n",
    "# Update mode source to use the highest-tm-fraction mode\n",
    "mode_src = mode_src.copy(update=dict(mode_spec = mode_spec))\n",
    "mode_src = mode_src.copy(update=dict(mode_index = 0))\n",
    "\n",
    "# Update mode monitor to use the tm_fraction ordered mode_spec\n",
    "mode_mon = mode_mon.copy(update=dict(mode_spec = mode_spec))\n",
    "\n",
    "# New monitor to record the modes computed at the mode decomposition monitor location\n",
    "mode_solver_mon = td.ModeFieldMonitor(\n",
    "    center=mode_mon.center, \n",
    "    size=mode_mon.size,\n",
    "    freqs=mode_mon.freqs,\n",
    "    mode_spec=mode_spec,\n",
    "    name=\"mode_fields\"\n",
    ")\n",
    "\n",
    "sim = td.Simulation(\n",
    "    size=(Lx, Ly, Lz),\n",
    "    grid_spec=grid_spec,\n",
    "    run_time=run_time,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "    structures=[waveguide],\n",
    "    sources=[mode_src],\n",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1)\n",
    "n_eff = sim_data[\"mode\"].n_eff # real part of the effective mode index\n",
    "n_eff.plot.line(x='f');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37483bc2",
   "metadata": {},
   "source": [
    "Now the fundamental Ez-polarized mode is injected, and as before it is the only one that the mode monitor records any intensity in."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "c169a724",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-21T20:34:12.701824Z",
     "iopub.status.busy": "2022-07-21T20:34:12.701693Z",
     "iopub.status.idle": "2022-07-21T20:34:12.944205Z",
     "shell.execute_reply": "2022-07-21T20:34:12.943737Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
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     },
     "metadata": {},
     "output_type": "display_data"
    },
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     "data": {
      "text/html": [
       "
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    {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(10, 4))\n",
    "sim_data.plot_field(\"field\", \"Ez\", freq=freq0, ax=ax[0])\n",
    "sim_data['mode']['amps'].sel(direction='-').abs.plot.line(x='f', ax=ax[1]);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e9e49c1",
   "metadata": {},
   "source": [
    "We can also have a look at the mode fields stored in the `ModeFieldMonitor` either directly using xarray methods as above, or using the Tidy3D `SimulationData` in-built field plotting. Note that here we have to specificall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ebe430c7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-21T20:34:12.945815Z",
     "iopub.status.busy": "2022-07-21T20:34:12.945682Z",
     "iopub.status.idle": "2022-07-21T20:34:13.207483Z",
     "shell.execute_reply": "2022-07-21T20:34:13.207176Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
<AxesSubplot:title={'center':'cross section at y=-2.00'}, xlabel='x', ylabel='z'>\n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mAxesSubplot:\u001b[0m\u001b[1;33mtitle\u001b[0m\u001b[39m=\u001b[0m\u001b[1;39m{\u001b[0m\u001b[32m'center'\u001b[0m\u001b[39m:\u001b[0m\u001b[32m'cross section at \u001b[0m\u001b[32my\u001b[0m\u001b[32m=-2.00'\u001b[0m\u001b[1;39m}\u001b[0m\u001b[39m, \u001b[0m\u001b[33mxlabel\u001b[0m\u001b[39m=\u001b[0m\u001b[32m'x'\u001b[0m\u001b[39m, \u001b[0m\u001b[33mylabel\u001b[0m\u001b[39m=\u001b[0m\u001b[32m'z'\u001b[0m\u001b[1m>\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
<Figure size 864x288 with 4 Axes>\n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 864x288 with \u001b[0m\u001b[1;36m4\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(12, 4))\n",
    "sim_data.plot_field(\"mode_fields\", \"Ex\", freq=freq0, val=\"abs\", mode_index=0, ax=ax[0])\n",
    "sim_data.plot_field(\"mode_fields\", \"Ez\", freq=freq0, val=\"abs\", mode_index=0, ax=ax[1]);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c1f64f9",
   "metadata": {},
   "source": [
    "## Notes / Considerations\n",
    "\n",
    "- This mode solver runs locally, which means it does not require credits to run.\n",
    "- It also means that the mode solver does not use subpixel-smoothening, even if this is specified in the simulation. On the other hand, when the modes are stored in a `ModeFieldMonitor` during a simulation run, the subpixel averaging is applied. Therefore, the latter results may not perfectly match those from a local run, and are more accurate.\n",
    "- Symmetries are applied if they are defined in the simulation and the mode plane center sits on the simulation center.  "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
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