{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Dispersive materials" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Introduction / Setup\n", "\n", "Here we show to to model dispersive materials in Tidy3D with an example showing transmission spectrum of a multilayer stack of slabs." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:52.181893Z", "iopub.status.busy": "2023-02-03T04:21:52.181610Z", "iopub.status.idle": "2023-02-03T04:21:53.216668Z", "shell.execute_reply": "2023-02-03T04:21:53.216202Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
[22:21:53] WARNING  This version of Tidy3D was pip installed from the 'tidy3d-beta' repository on   __init__.py:103\n",
       "                    PyPI. Future releases will be uploaded to the 'tidy3d' repository. From now on,                \n",
       "                    please use 'pip install tidy3d' instead.                                                       \n",
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           INFO     Using client version: 1.9.0rc1                                                  __init__.py:121\n",
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\n" ], "text/plain": [ "\u001b[2;36m \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO \u001b[0m Using client version: \u001b[1;36m1.9\u001b[0m.0rc1 \u001b]8;id=583827;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=441461;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#121\u001b\\\u001b[2m121\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# standard python imports\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "import tidy3d as td\n", "from tidy3d import web\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, let us define some basic parameters." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:53.219085Z", "iopub.status.busy": "2023-02-03T04:21:53.218817Z", "iopub.status.idle": "2023-02-03T04:21:53.222993Z", "shell.execute_reply": "2023-02-03T04:21:53.222569Z" }, "tags": [] }, "outputs": [], "source": [ "# Wavelength and frequency range\n", "lambda_range = (0.5, 1.5)\n", "lam0 = np.sum(lambda_range) / 2\n", "freq_range = (td.constants.C_0 / lambda_range[1], td.constants.C_0 / lambda_range[0])\n", "Nfreq = 333\n", "\n", "# frequencies and wavelengths of monitor\n", "monitor_freqs = np.linspace(freq_range[0], freq_range[1], Nfreq)\n", "monitor_lambdas = td.constants.C_0 / monitor_freqs\n", "\n", "# central frequency, frequency pulse width and total running time\n", "freq0 = monitor_freqs[Nfreq // 2]\n", "freqw = 0.3 * (freq_range[1] - freq_range[0])\n", "t_stop = 100 / freq0\n", "\n", "# Thicknesses of slabs\n", "t_slabs = [0.5, 0.2, 0.4, 0.3] # um\n", "\n", "# Grid resolution (cells per um)\n", "res = 150\n", "\n", "# space between slabs and sources and PML\n", "spacing = 1 * lambda_range[-1]\n", "\n", "# simulation size\n", "sim_size = Lx, Ly, Lz = (1.0, 1.0, 4 * spacing + sum(t_slabs))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Defining Materials (4 Ways)\n", "\n", "Here, we will illustrate defining materials in four different ways:\n", "\n", "1. Simple, lossless, dispersionless dielectric defined by a real-valued relative permittivity.\n", "2. Lossy material defined by real and imaginary part of the refractive index ($n$) and ($k$) at a given frequency. Values are exact only at that frequency, so this approach is only good for narrow-band simulations.\n", "3. Simple, lossless dispersive material (one-pole fitting) defined by the real part of the refractive index $n$ and the dispersion $\\mathrm{d}n/\\mathrm{d}\\lambda$ at a given frequency. The dispersion must be negative. This is a convenient approach to incorporate weakly dispersive materials in your simulations, as the values can be taken directly from [refractiveindex.info](https://refractiveindex.info/)\n", "4. Dispersive material imported from our pre-defined library of materials.\n", "\n", "More complicated dispersive materials [can also be defined](https://docs.flexcompute.com/en/v1.9.0rc2/api.html#dispersive-mediums) through dispersive models like Lorentz, Sellmeier, Debye, or Drude, if the model parameters are known. Finally, arbitrary dispersion data can also be fit, which is a the subject of [this tutorial](https://docs.flexcompute.com/en/v1.9.0rc2/notebooks/Fitting.html)." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:53.225021Z", "iopub.status.busy": "2023-02-03T04:21:53.224892Z", "iopub.status.idle": "2023-02-03T04:21:53.228174Z", "shell.execute_reply": "2023-02-03T04:21:53.227810Z" }, "tags": [] }, "outputs": [], "source": [ "# simple, lossless, dispersionless material (either epsilon or n)\n", "mat1 = td.Medium(permittivity=4.0)\n", "\n", "# lossy material with n & k values at a specified frequency or wavelength\n", "mat2 = td.Medium.from_nk(n=3.0, k=0.1, freq=freq0)\n", "\n", "# weakly dispersive material defined by dn_dwvl at a given frequency\n", "mat3 = td.Sellmeier.from_dispersion(n=2.0, dn_dwvl=-0.1, freq=freq0)\n", "\n", "# dispersive material from tidy3d library\n", "mat4 = td.material_library[\"BK7\"][\"Zemax\"]\n", "\n", "# put all together\n", "mat_slabs = [mat1, mat2, mat3, mat4]\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Create Simulation\n", "Now we set everything else up (structures, sources, monitors, simulation) to run the example." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, we define the multilayer stack structure." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:53.230271Z", "iopub.status.busy": "2023-02-03T04:21:53.230110Z", "iopub.status.idle": "2023-02-03T04:21:53.233176Z", "shell.execute_reply": "2023-02-03T04:21:53.232821Z" }, "tags": [] }, "outputs": [], "source": [ "slabs = []\n", "slab_position = -Lz / 2 + 2 * spacing\n", "for t, mat in zip(t_slabs, mat_slabs):\n", " slab = td.Structure(\n", " geometry=td.Box(\n", " center=(0, 0, slab_position + t / 2),\n", " size=(td.inf, td.inf, t),\n", " ),\n", " medium=mat,\n", " )\n", " slabs.append(slab)\n", " slab_position += t\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We must now define the excitation conditions and field monitors. We will excite the slab using a normally incident (along z) planewave, polarized along the x direciton." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:53.235178Z", "iopub.status.busy": "2023-02-03T04:21:53.235057Z", "iopub.status.idle": "2023-02-03T04:21:53.237732Z", "shell.execute_reply": "2023-02-03T04:21:53.237395Z" }, "tags": [] }, "outputs": [], "source": [ "# Here we define the planewave source, placed just in advance (towards negative z) of the slab\n", "source = td.PlaneWave(\n", " source_time=td.GaussianPulse(freq0=freq0, fwidth=freqw),\n", " size=(td.inf, td.inf, 0),\n", " center=(0, 0, -Lz / 2 + spacing),\n", " direction=\"+\",\n", " pol_angle=0,\n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we define the field monitor, placed just past (towards positive z) of the stack." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:53.239768Z", "iopub.status.busy": "2023-02-03T04:21:53.239610Z", "iopub.status.idle": "2023-02-03T04:21:53.242285Z", "shell.execute_reply": "2023-02-03T04:21:53.241900Z" }, "tags": [] }, "outputs": [], "source": [ "# We are interested in measuring the transmitted flux, so we set it to be an oversized plane.\n", "monitor = td.FluxMonitor(\n", " center=(0, 0, Lz / 2 - spacing),\n", " size=(td.inf, td.inf, 0),\n", " freqs=monitor_freqs,\n", " name=\"flux\",\n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, define the boundary conditions to use PMLs along z and the default periodic boundaries along x and y" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:53.244212Z", "iopub.status.busy": "2023-02-03T04:21:53.244056Z", "iopub.status.idle": "2023-02-03T04:21:53.246475Z", "shell.execute_reply": "2023-02-03T04:21:53.246116Z" }, "tags": [] }, "outputs": [], "source": [ "boundary_spec = td.BoundarySpec(x=td.Boundary.periodic(), y=td.Boundary.periodic(), z=td.Boundary.pml())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now it is time to define the simulation object." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:53.248371Z", "iopub.status.busy": "2023-02-03T04:21:53.248225Z", "iopub.status.idle": "2023-02-03T04:21:53.252205Z", "shell.execute_reply": "2023-02-03T04:21:53.251842Z" }, "tags": [] }, "outputs": [], "source": [ "sim = td.Simulation(\n", " center=(0, 0, 0),\n", " size=sim_size,\n", " grid_spec=td.GridSpec.auto(min_steps_per_wvl=40),\n", " structures=slabs,\n", " sources=[source],\n", " monitors=[monitor],\n", " run_time=t_stop,\n", " boundary_spec=boundary_spec,\n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plot The Structure\n", "\n", "Let's now plot the permittivity profile to confirm that the structure was defined correctly." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First we use the `Simulation.plot()` method to plot the materials only, which assigns a different color to each slab without knowledge of the material properties." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:53.254229Z", "iopub.status.busy": "2023-02-03T04:21:53.254093Z", "iopub.status.idle": "2023-02-03T04:21:53.372842Z", "shell.execute_reply": "2023-02-03T04:21:53.372409Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
           INFO     Auto meshing using wavelength 0.7500 defined from sources.                     grid_spec.py:510\n",
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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sim.plot(x=0)\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we use `Simulation.plot_eps()` to vizualize the permittivity of the stack. However, because the stack contains dispersive materials, we need to specify the `freq` of interest as an argument to the plotting tool. Here we show the permittivity at the lowest and highest frequences in the range of interest. Note that in this case, the real part of the permittivity (being plotted) only changes slightly between the two frequencies on the dispersive material. However, for other materials with more dispersion, the effect can be much more prominent." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:53.375610Z", "iopub.status.busy": "2023-02-03T04:21:53.375418Z", "iopub.status.idle": "2023-02-03T04:21:53.739798Z", "shell.execute_reply": "2023-02-03T04:21:53.739314Z" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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p2rZtayZOnFjug3ArajBjfvo4iA4dOpikpCTTrFkzM378+IA/nu+++86MHTvWtGvXziQnJ5v09HTTv39/s3z5ct86K1asMNdcc43JysoyDofDZGVlmRtuuMFs377dsvbqbufxeMwjjzxiOnbsaJxOp2nUqJHp2rWrmTFjRrmPOnjppZdMly5dfOv17dvXLFu2zHf7/v37zZAhQ0yDBg2q9UG4b7zxhm9/6enplh+Ee6bqNJgxxnz22WfmkksuMSkpKSYrK8v86U9/MkuXLi1Xz4kTJ8yNN95oGjZsWOUH4V577bWmQYMG5vvvvw9Y/s477xhJ5pFHHqmyrup4/vnnTfv27Y3D4TDt2rUzTzzxRMDHcRhTeYOdOnXK/PGPfzSZmZnG6XSa7t27m/fff7/C+/nkk09Mr169THJyssnIyDATJ040brc7JI8BwNmDTCQTK0ImVizOmCqeAwAAAABqqNqv6QQAAADsYugEAABA2DF0AgAAIOwYOgEAABB2DJ0AAAAIO4ZOAAAAhF3YvnsdP/F6vfrxxx/VoEEDW1+hFS7GGBUUFCgrK6vc98BWR1FRkTwejxwOh5KTk8NQIQDgbFNbM1EiFyOBoTPMfvzxR9/XSdVGeXl5atGiRVDbFBUVKSUlRZKUmZmpXbt20WAAgCrV9kyUyMVwYugMswYNGkiS/vrXv/p+rojH4/F9H23Dhg3lcDjCWldBQYH+9Kc/WdZUGY/H4/t5//798ng8NBcAoErVzUS78vPzfd/VnpGREdTZVHIx/Bg6w6zsD75BgwZKS0urcB2Px6PCwkLf7adPn1ZaWlrYB8+f1wcAQLhVJxPtKigoUEJCgtLT01VcXKzTp0+rcePGQT9VTi6GD28kijKPx6PDhw8rKSlJTZo0UZMmTZSUlKTDhw8HHDnVRjQmAKA2KCgokNvtlsvlUuPGjdWkSROdPn1aR44ckdfrjVgd5KI1hs4o+vnAWXY0Fh8fr8aNG9eJwZPmAgBE288HzrKnxh0OR1QGT3LRGkNnlFQ0cJapK4MnzQUAiKaKBs4y0Rg8yUVrDJ1RYDVwlgn34GmMqfE+aC4AQLRYDZxlIj14kovWGDojrDoDZ5lwDZ5er9f3TvmaoLkAANFQnYGzTCQHT3LRGu9ej5CSkhIVFhbq2LFjSkxMlMvlUklJSbW2dblcOnbsmA4ePKhGjRopKSnJdh3GGB07dqzWPmUPADj7lZSU2M6hwsJCnThxQqmpqXI6ndXeT1paWkCWnjkgnj592lY9qD6GzgjxeDwqLS2V0+mUw+HwfY5YdaWkpPg+WsnhcNj6tgRjjDwej+Lj40Py+Wgc0QEA7CgpKVFRUZGt7U6fPq369esrISEh6H2kpqbK4/HI7XbL4XAE5FhpaWnQ9ZyJXLTG0Bkh1157rVwuV7TL8HG73brnnntqtA+aCwBgx7Bhw2pVJko/5eLdd99do32Qi9YYOiMkPT29VjVYYmLN/+lpLgCAHbUtEyVyMRJ4IxEAAADCjqETtnFEBwCAH7lojaETAAAAYcfQCds4ogMAwI9ctMbQCdtoLgAA/MhFawydsI3mAgDAj1y0xtAJ22guAAD8yEVrDJ2wjeYCAMCPXLTG0AkAAICwY+iEbRzRAQDgRy5aY+iEbTQXAAB+5KI1hk4AAACEHUMnbOOIDgAAP3LRGkMnbKO5AADwIxetMXTCNpoLAAA/ctEaQycAAADCjqETtnFEBwCAH7lojaETttFcAAD4kYvWGDphG80FAIAfuWiNoRO20VwAAPiRi9YYOi3MmTNHnTt3lsvlksvlUk5Ojt57771ol1Vr0FwAEFvIRWvkojWGTgstWrTQww8/rPXr12vdunUaMGCArrnmGm3ZsiXapQEAEHHkImqCodPC0KFDddVVV+ncc8/Veeedp1mzZik1NVWrV6+Odml1UmlpqR544AG1adNGKSkpateunf7yl7/IGBPt0gAA1UAuhk4sZmJitAuoK0pLS/XWW2+psLBQOTk5la5XXFys4uJi33W32x2J8qIi2KcRHnnkEc2ZM0f//Oc/1bFjR61bt0633HKL0tLSdOedd4apSgBAOFQnF2MpE6XgcjEWM5GhswqbNm1STk6OioqKlJqaqoULF+qCCy6odP3c3FzNmDEjghVGT7BD5+eff65rrrlGQ4YMkSS1bt1a//rXv/Tll1+GozwAQBgEk4uxlIlScLkYi5nI0+tVaN++vTZu3Kg1a9Zo/PjxGj16tLZu3Vrp+lOnTlV+fr7vkpeXF8FqI6usudxud8Dl50e1P9erVy+tWLFC27dvlyT97//+rz799FMNHjw4YjUDAGommFyMpUyUgsvFWMxEznRWweFw6JxzzpEkde3aVWvXrtXf//53zZ07t8L1nU6nnE5nJEuMmrLmys7ODlg+ffp0Pfjgg+XWnzJlitxutzp06KCEhASVlpZq1qxZGjlyZCTKBQCEQDC5GEuZKAWXi7GYiQydQfJ6vZWeyYtVeXl5crlcvuuV/Q/mzTff1GuvvaYFCxaoY8eO2rhxoyZNmqSsrCyNHj06UuUCAEKIXCyvOrkYi5nI0Glh6tSpGjx4sFq2bKmCggItWLBAq1at0tKlS6NdWq1QdkRX9nltVbn33ns1ZcoUjRgxQpLUqVMn/fDDD8rNzT1rGwwAzibkorVgcjEWM5Gh08LBgwc1atQo7du3T2lpaercubOWLl2qyy+/PNql1QrBvpHo5MmTio8PfBlxQkKCvF5vKMsCAIQJuWgtmFyMxUxk6LTw4osvRruEWi3YoXPo0KGaNWuWWrZsqY4dO2rDhg16/PHHNXbs2DBVCAAIJXLRWjC5GIuZyNAJ24IdOp966ik98MADmjBhgg4ePKisrCz9/ve/17Rp08JUIQAAkRNMLsZiJjJ0ImIaNGig2bNna/bs2dEuBQCAqIrFTORzOgEAABB2DJ2wLdin1wEAOJuRi9YYOmEbzQUAgB+5aI2hE7bRXAAA+JGL1hg6YRvNBQCAH7lojaETttFcAAD4kYvWGDphG80FAIAfuWiNoRMAAABhx9AJ2ziiAwDAj1y0xtAJ22guAAD8yEVrDJ0AAAAIO4ZO2MYRHQAAfuSiNYZO2EZzAQDgRy5aY+gEAABA2DF0wjaO6AAA8CMXrTF0wjaaCwAAP3LRGkMnbKO5AADwIxetMXTCNpoLAAA/ctEaQydso7kAAPAjF60lRruAmOE5JnlKo12Fn8cd7QoAALGqtmWiRC5GAENnpOQtkhqkRLsKv4JTNd4FR3QAAFtqWyZK5GIE8PQ6AAAAwo6hE7ZxRAcAgB+5aI2hE7bRXAAA+JGL1nhNZ6RkD5NcrmhX4ed2S5pUo13QXAAAW2pbJkrkYgQwdFrIzc3V22+/rW3btiklJUW9evXSI488ovbt2we/M0cjyVGLGsyRUONd0FwAEFtClou1LRMlcjECeHrdwkcffaSJEydq9erVWrZsmU6fPq1BgwapsLAw2qUBABBx5CJqgqHTwvvvv68xY8aoY8eOuuiiizR//nzt3r1b69evj3ZptUKwR3StW7dWXFxcucvEiRPDVCEAIJTIRWvkojWeXg9Cfn6+JCk9PT3KldQOwTbX2rVrVVrq/zDgzZs36/LLL9fw4cNDXRoAIALIxUDkojWGzmryer2aNGmSevfurQsvvLDS9YqLi1VcXOy77nafvd9wEGxzZWRkBFx/+OGH1a5dO/Xt2zeUZQEAIqA6uRhLmSiRi1Xh6fVqmjhxojZv3qzXX3/dcr3c3FylpaX5LtnZ2RGqMPLKmsvtdgdcfv4/mMp4PB69+uqrGjt2LC+8BoA6qDq5GEuZKJGLVWHorIbbb79dixcv1sqVK9WiRQvLdadOnar8/HzfJS8vL0JVRk92dnbA/1Ryc3Or3GbRokU6fvy4xowZE/4CAQAhVd1cjMVMlMjFyvD0ugVjjO644w4tXLhQq1atUps2barcxul0yul0RqC62iMvL0+un33eWnUe/4svvqjBgwcrKysrnKUBAEIo2FyMxUyUyMXKMHRamDhxohYsWKB33nlHDRo00P79+yVJaWlpSklJiXJ10Vd2+t/lcgU0V1V++OEHLV++XG+//Xa4SgMAhAG5aI1ctMbT6xbmzJmj/Px89evXT82bN/dd3njjjWiXVivYfc3JvHnz1LRpUw0ZMiTEFQEAwolctEYuWuNMpwVjTLRLqNXsNJfX69W8efM0evRoJSby5wcAdQm5aI1ctMaZTthmp7mWL1+u3bt3a+zYsWGoCACA6CEXrZ3dIzXCyk5zDRo0iCNlAMBZiVy0xplOAAAAhB1DJ2w7Wz+8FgAAO8hFawydsI3mAgDAj1y0xtAJ22guAAD8yEVrDJ0AAAAIO4ZO2MYRHQAAfuSiNYZOAAAAhB1DJ2zjiA4AAD9y0RpDJ2yjuQAA8CMXrTF0wjaaCwAAP3LRGkMnbKO5AADwIxetMXTCNpoLAAA/ctEaQydso7kAAPAjF60xdAIAACDsGDphG0d0AAD4kYvWGDoBAAAQdgydsI0jOgAA/MhFawydsI3mAgDAj1y0xtAJ22guAAD8yEVrDJ0AAAAIO4ZO2MYRHQAAfuSiNYZO2EZzAQDgRy5aY+iEbTQXAAB+5KI1hk7YRnMBAOBHLlpj6IRtNBcAAH7kojWGTgAAAIQdQ2cVPv74Yw0dOlRZWVmKi4vTokWLol1SrcERHQDEFjLRGrlojaGzCoWFhbrooov0zDPPRLuUs8LevXt10003qXHjxkpJSVGnTp20bt26aJcFAKgGMjG0Yi0TE6NdQG03ePBgDR48ONpl1ErBHtEdO3ZMvXv3Vv/+/fXee+8pIyND3377rRo1ahSmCgEAoUQmWgsmF2MxExk6YVuwQ+cjjzyi7OxszZs3z7esTZs2oS4LAICoCCYXYzETeXo9xIqLi+V2uwMuZ6uy5jrz8RYXF1e4/rvvvqtu3bpp+PDhatq0qbp06aIXXnghkiUDACIoljJRCi4XYzETGTpDLDc3V2lpab5LdnZ2tEsKm7Lmys7ODnjMubm5Fa7/3Xffac6cOTr33HO1dOlSjR8/Xnfeeaf++c9/RrJsAECExFImSsHlYixmIk+vh9jUqVM1efJk33W3233WN1leXp5cLpfvutPprHA9r9erbt266aGHHpIkdenSRZs3b9Zzzz2n0aNHR6RWAEDkxGImStXLxVjMRIbOEHM6nZUOXWebsiM6l8sV0FyVad68uS644IKAZeeff77+/e9/h6U+AEB0xVImSsHlYixmIkNnFU6cOKEdO3b4ru/atUsbN25Uenq6WrZsGcXKoi/YNxL17t1b33zzTcCy7du3q1WrVqEsCwAQJmSitWByMRYzkaGzCuvWrVP//v1918ueJhg9erTmz58fpapqh2CHzrvvvlu9evXSQw89pN/+9rf68ssv9fzzz+v5558PU4UAgFAiE60Fk4uxmIkMnVXo16+fjDHRLqNWCnbo7N69uxYuXKipU6dq5syZatOmjWbPnq2RI0eGqUIAQCiRidaCycVYzESGTkTU1VdfrauvvjraZQAAEHWxlol8ZBIAAADCjqETtgX79DoAAGczctEaQydso7kAAPAjF60xdMI2mgsAAD9y0RpvJIqQ7du3KzU1Ndpl+Jw4caLG+6C5AAB2bNu2rVZlokQuRgJnOmEbzQUAgB+5aI2hEwAAAGHH0AnbOKIDAMCPXLTG0AnbaC4AAPzIRWsMnbCN5gIAwI9ctMbQCQAAgLBj6IRtHNEBAOBHLlpj6AQAAEDYMXTCNo7oAADwIxetMXTCNpoLAAA/ctEaQydso7kAAPAjF63x3esRsmHDBqWkpES7DJ9Tp07VeB80FwDAji+++KJWZaJELkYCZzphG80FAIAfuWiNoRO20VwAAPiRi9YYOgEAABB2DJ2wjSM6AAD8yEVrDJ0AAAAIO4ZO2MYRHQAAfuSiNYZO2EZzAQDgRy5aY+iEbTQXAAB+5KI1hk4AAACEHUMnbOOIDgAAP3LRGkNnNTzzzDNq3bq1kpOT1bNnT3355ZfRLqlWCLa5HnzwQcXFxQVcOnToENQ+vF6vXnrppaC2AQCEDplYuUjnYl3LRIbOKrzxxhuaPHmypk+frq+++koXXXSRrrjiCh08eDDapUWdnSO6jh07at++fb7Lp59+GtT28fHxmjt3btD3CwCoOTLRWqRzsa5lYp0YOgcMGKAZM2aUW37s2DENGDAgrPf9+OOPa9y4cbrlllt0wQUX6LnnnlO9evXq1JFFuNhprsTERGVmZvouTZo0CXof3bp109NPPx30dgBwtohWLpKJ1qKRi3UpE+vE0Llq1So9/fTTGjZsmAoLC33LPR6PPvroo7Ddr8fj0fr16zVw4EDfsvj4eA0cOFBffPFF2O63rihrLrfbHXApLi6udJtvv/1WWVlZatu2rUaOHKndu3cHfb979uzR448/rtatW+vGG29Ubm6uFi9ebPtxAEBdE41cJBOrFo1crEuZWCeGTklavny59u/fr0suuUTff/99RO7z8OHDKi0tVbNmzQKWN2vWTPv3769wm+Li4nJ/bGe77OxspaWl+S65ubkVrtezZ0/Nnz9f77//vubMmaNdu3apT58+KigoCOr+3nnnHX333XfavHmz7rrrLmVkZGj58uWheCgAUGdEOhfJxOqLZC7WqUw0dUBcXJw5cOCAKSoqMjfccINp0qSJWblypdm/f7+Jj48P2/3u3bvXSDKff/55wPJ7773X9OjRo8Jtpk+fbiTVmUt+fn7Qv5f8/Hwjydx9991GksnLyzP5+fm+S1FRUbX2c+zYMeNyucw//vEPy/Uuu+wy85///Kfc8tLS0qBrB4CzQTRyMRYysS7kYl3OxDpxprPsdLXT6dSCBQt011136corr9Szzz4b1vtt0qSJEhISdODAgYDlBw4cUGZmZoXbTJ06Vfn5+b5LXl5eWGuMprJ/F5fLFXBxOp3V2r5hw4Y677zztGPHDsv11q1bp9atW0uSfvjhB9/yf/zjH7r55pvtFQ8AdVg0cpFMrFokcrEuZ2KdGDqNMQHX77//fr322mt67LHHwnq/DodDXbt21YoVK3zLvF6vVqxYoZycnAq3cTqd5f7YzlY1/TyyEydOaOfOnWrevLnleh6PRw0aNJAkderUSd99950kqVevXgH/NgAQK6KRi2Ri1SKRi3U5ExOjXUB17Nq1SxkZGQHLfvOb36hDhw5at25dWO978uTJGj16tLp166YePXpo9uzZKiws1C233BLW+60Lgm2uP/7xjxo6dKhatWqlH3/8UdOnT1dCQoJuuOEGy+3OPfdcffnll2rQoIEKCwuVn58vSWrQoIGOHj1qu34AqKuilYtkorVI5GJdzsQ6MXS2atWqwuUdO3ZUx44dw3rf119/vQ4dOqRp06Zp//79uvjii/X++++XeyF1LAq2ufbs2aMbbrhBR44cUUZGhi699FKtXr263P84z3THHXdo3Lhxat26tTp37qwXX3xRTz/9tD755BP+HQDEpGjlIploLRK5WJczsU4MndF2++236/bbb492GbVOsM31+uuv27qf3/3ud0pPT9f27ds1btw4jRgxQm3bttW+ffv4dwGACCMTKxeJXKzLmcjQiTrh2muv9f383nvvaeHChfJ4PBoxYkQUqwIAIPLqaiYydEbIs88+q5SUlGiX4XPq1ClNmDChRvuo6Qum7UpMTNTw4cOjct8AgJqrbZko1d1crEuZWCfevY7aKVpDJwAAtRG5aI2hE7bRXAAA+JGL1hg6AQAAEHYMnbCNIzoAAPzIRWsMnQAAAAg7hk7YxhEdAAB+5KI1hk7YRnMBAOBHLlpj6IRtNBcAAH7kojWGTthGcwEA4EcuWmPohG00FwAAfuSiNYZOAAAAhB1DJ2zjiA4AAD9y0RpDJ2yjuQAA8CMXrTF0AgAAIOwYOmEbR3QAAPiRi9YYOmEbzQUAgB+5aI2hE7bRXAAA+JGL1hg6AQAAEHYMnbCNIzoAAPzIRWuJ0S4gVowcOVIulyvaZfi43W5NmDChRvuguQAAdtS2TJTIxUjgTCdso7kAAPAjF60xdMI2mgsAAD9y0RpDJ2yjuQAA8CMXrTF0AgAAIOwYOgEAABB2DJ2wraZPIzz88MOKi4vTpEmTQlMQAABRVJNcjIVMZOi0MGvWLPXq1Uv16tVTw4YNo11OrVOT5lq7dq3mzp2rzp07h7AiAEC4kIlVs5uLsZKJDJ0WPB6Phg8frvHjx0e7lFrJbnOdOHFCI0eO1AsvvKBGjRqFuCoAQDiQiVWzk4uxlIkMnRZmzJihu+++W506dYp2KbVSWXO53e6AS3FxseV2EydO1JAhQzRw4MBIlAkACAEysWp2cjGWMpFvJAqx4uLigD8ut9sdxWoiIzs7O+D69OnT9eCDD1a47uuvv66vvvpKa9eujUBlAIBoisVMlKqfi7GWiQydIZabm6sZM2ZEu4yIKDuiy8vLC/g6M6fTWeH6eXl5uuuuu7Rs2TIlJydHpEYAQPTEUiZKweViLGZizD29PmXKFMXFxVletm3bZnv/U6dOVX5+vu+Sl5cXwuprl7LmcrlcAZfKhs7169fr4MGD+uUvf6nExEQlJibqo48+0pNPPqnExESVlpZGsnwAiHlkYmgFk4uxmIkxd6bznnvu0ZgxYyzXadu2re39O53OSoeus02wL5i+7LLLtGnTpoBlt9xyizp06KD77rtPCQkJoSwPAFAFMjG0gsnFWMzEmBs6MzIylJGREe0yzgrBDp0NGjTQhRdeGLCsfv36aty4cbnlAIDwIxNDK5hcjMVMjLmhMxi7d+/W0aNHtXv3bpWWlmrjxo2SpHPOOUepqanRLQ4AgAgiE1FTDJ0Wpk2bpn/+85++6126dJEkrVy5Uv369YtSVWeXVatWRbsEAEA1kInhd7ZnYsy9kSgY8+fPlzGm3IXm+klNvwYTAFB3kIlVIxetMXTCNpoLAAA/ctEaQydso7kAAPAjF60xdMI2mgsAAD9y0RpDJ2yjuQAA8CMXrTF0wjaaCwAAP3LRGkMnAAAAwo6hE7ZxRAcAgB+5aI2hE7bRXAAA+JGL1hg6YRvNBQCAH7lojaETAAAAYcfQCds4ogMAwI9ctMbQCQAAgLBj6IRtHNEBAOBHLlpj6IRtNBcAAH7kojWGTthGcwEA4EcuWmPohG00FwAAfuSiNYZO2EZzAQDgRy5aY+gEAABA2DF0wjaO6AAA8CMXrTF0wjaaCwAAP3LRGkMnAAAAwo6hE7ZxRAcAgB+5aI2hE7bRXAAA+JGL1hg6YRvNBQCAH7lojaETAAAAYcfQCds4ogMAwI9ctMbQCduCba45c+aoc+fOcrlccrlcysnJ0XvvvRem6gAAiCxy0RpDJ2wLtrlatGihhx9+WOvXr9e6des0YMAAXXPNNdqyZUuYKgQAIHLIRWsMnZX4/vvvdeutt6pNmzZKSUlRu3btNH36dHk8nqjV9O2Rb/XtkW+jdv9nCra5hg4dqquuukrnnnuuzjvvPM2aNUupqalavXp1mCoEAIRCbczE/KJ8rf9xvTyl0avhTOSitcRoF1Bbbdu2TV6vV3PnztU555yjzZs3a9y4cSosLNSjjz4a8Xq8xqux74xVXFycVo1Zpfi46B8v1OS1K6WlpXrrrbdUWFionJycEFYFAAi12paJkrRg0wI9sfoJvTD0BfVt3TcqNZyJXLTG0FmJK6+8UldeeaXvetu2bfXNN99ozpw5UWmwjfs3anf+binup59/2fyXEa+hMm63O+C60+mU0+mscN1NmzYpJydHRUVFSk1N1cKFC3XBBRdEokwAgE21LRONMVr87WIdKDygZd8tqzVDZxlysWLRP11Wh+Tn5ys9Pd1yneLiYrnd7oBLKCzbuUzFpcUqLinWsp3LQrLPUMnOzlZaWprvkpubW+m67du318aNG7VmzRqNHz9eo0eP1tatWyNYLQAgFKKZiTuP7dTXh75WUnyS/vPtf2rVU+wSuVgZznRW044dO/TUU09VeUSXm5urGTNmhPS+vcarxdsXKyk+SZK05Nslurf3vVF/ir3saYS8vDy5XC7f8sqO5iTJ4XDonHPOkSR17dpVa9eu1d///nfNnTs3vMUCAEImmpko/XQi5uTpk8pMzdTBwoP6Iu+LWnG2k1y0FnNnOqdMmaK4uDjLy7Zt2wK22bt3r6688koNHz5c48aNs9z/1KlTlZ+f77vk5eXVuOayp9YbOBuogbOBfsj/Qf+7/39rvN+aKmuuso96KLtYNdeZvF6viouLw1UiAMBCXczEsqfW4+PilZyYrBJviZZ9VzueASQXrcXcmc577rlHY8aMsVynbdu2vp9//PFH9e/fX7169dLzzz9f5f6tXrdhV9lT600Sm0iSjp46qg92fqAuzbuE9H6CFewLpqdOnarBgwerZcuWKigo0IIFC7Rq1SotXbo0TBUCAKzUxUwse2rd5fzpTGJyYrL+8+1/NK3vNDkSHCG9r2CRi9ZibujMyMhQRkZGtdbdu3ev+vfvr65du2revHmKj4/OieFl3y1TUUmRjhUdkyQVlRRp2XfLdN+l90WlnjLBNtfBgwc1atQo7du3T2lpaercubOWLl2qyy+/PEwVAgCs1MVM/OSHT3TCc0IJ8QmKj4tX4elCeY1XX+37Spe0uCQqNZUhF63F3NBZXXv37lW/fv3UqlUrPfroozp06JDvtszMzIjWcvcld+vVTa/qo+8/kiQNPnewbup0U0RrCIUXX3wx2iUAAGyoTZk45Lwh+vrw11r49ULtO7FP7Rq107XnX1urPtWlumItFxk6K7Fs2TLt2LFDO3bsUIsWLQJuM8YEvT93iVsqsVdLn7Z9tLtgt1Z9v0qS9KvWv1Kftn1+2qdNNdm2DN8xCwCxoTZlYrIzWXf2ulP//vrfMsaovqO+bs+5XUWmSEUlRfZ2KnIxEhg6KzFmzJgqX+cSjFX5q1TPW8/29ltOblGxt9j38/Ljy2tUz8mCkzXaXqK5ACBW1LZMPOk5qZOlJ1ViSnS05GiNM1EiFyOBobOOiI+Ll5Hx/Vwb0FwAgGiIU5zi4+MVFxenhPiEaJfjQy5aY+isI3La5chT4vH9XBvQXACAaEhxpOjWPrfqx+M/6vzm50e7HB9y0RpDZx3hTHJq0IWDol0GAAC1wsUtL9bFLS+OdhkIAkNnhPRL6xfw7QTR5o4PzVeRAQAQrNqWiRK5GAkMnRHiSnTJlViLGiwE//I8jQAAsKPWZaJELkZA7XhHCuokmgsAAD9y0RpDJ2yjuQAA8CMXrTF0wjaaCwAAP3LRGkMnbKO5AADwIxetMXTCNpoLAAA/ctEaQycAAADCjqETtnFEBwCAH7lojaETttFcAAD4kYvWGDoBAAAQdgydsI0jOgAA/MhFawydsI3mAgDAj1y0xtAJAACAsGPohG0c0QEA4EcuWmPohG00FwAAfuSiNYZO2EZzAQDgRy5aY+iEbTQXAAB+5KI1hk7YRnMBAOBHLlpj6AQAAEDYMXTCNo7oAADwIxetMXQCAAAg7Bg6YVuwR3S5ubnq3r27GjRooKZNm2rYsGH65ptvwlQdAACRFUwuxmImMnTCtmCHzo8++kgTJ07U6tWrtWzZMp0+fVqDBg1SYWFhmCoEACBygsnFWMzExGgXUJv9+te/1saNG3Xw4EE1atRIAwcO1COPPKKsrKxol1YrBDt0vv/++wHX58+fr6ZNm2r9+vX61a9+FcrSAAAhRiZWLZhcjMVM5Eynhf79++vNN9/UN998o3//+9/auXOnrrvuumiXVWvU9AXT+fn5kqT09PRQlAMACCMysWo1ycVYyETOdFq4++67fT+3atVKU6ZM0bBhw3T69GklJSVFsbLaxe12B1x3Op1yOp2W23i9Xk2aNEm9e/fWhRdeGM7yAAAhQCZWX7C5GCuZyJnOajp69Khee+019erVi+b6/8qO6LKzs5WWlua75ObmVrntxIkTtXnzZr3++uvhLhMAEGJkYsXs5mKsZCJnOqtw33336emnn9bJkyd1ySWXaPHixZbrFxcXq7i42Hf9zKOds0lZc+Xl5cnlcvmWV3WW8/bbb9fixYv18ccfq0WLFmGtEQAQOmSiNTu5GEuZGHNnOqdMmaK4uDjLy7Zt23zr33vvvdqwYYM++OADJSQkaNSoUTLGVLr/3NzcgKOb7OzsSDysqChrLpfLFXCprLmMMbr99tu1cOFCffjhh2rTpk0kywUAnIFMDK1gcjEWMzHOWP21nIUOHTqkI0eOWK7Ttm1bORyOcsv37Nmj7Oxsff7558rJyalw24qO6rKzs5Wfnx9w1BNtbrdbaWlptuoq2/bLL79Ujx49qr2PCRMmaMGCBXrnnXfUvn173/K0tDSlpKQE/RgAADVDJvpFOhdjMRNj7un1jIwMZWRk2NrW6/VKUkADnak6b6KJVXPmzJEk9evXL2D5vHnzNGbMmMgXBAAxjkyMnljMxJgbOqtrzZo1Wrt2rS699FI1atRIO3fu1AMPPKB27dpVekQHazF2Uh0AzhpkYujFYibG3Gs6q6tevXp6++23ddlll6l9+/a69dZb1blzZ3300Ucctf1/Nf2cTgBA3UAmVg+5aI0znZXo1KmTPvzww2iXUavRXAAQG8jE6iEXrXGmE7bRXAAA+JGL1hg6YRvNBQCAH7lojaETttFcAAD4kYvWGDoBAAAQdgydsI0jOgAA/MhFawydsI3mAgDAj1y0xtAJ22guAAD8yEVrDJ0AAAAIO4ZO2MYRHQAAfuSiNYZOAAAAhB1DJ2zjiA4AAD9y0RpDJ2yjuQAA8CMXrTF0wjaaCwAAP3LRGkMnbKO5AADwIxetMXTCNpoLAAA/ctEaQydso7kAAPAjF60xdAIAACDsGDphG0d0AAD4kYvWGDoBAAAQdgydsI0jOgAA/MhFa4nRLiBWHD16VCUlJdEuw8ftdtd4HzQXAMCO2paJErkYCQydEbJo0SKlpKRIkowx8ng8MsbI4XAoPr7iE85er1cej0dxcXFyOBwh/WM+depUjfdBcwEA7Ph5JtpV3YwsKSnR6dOnlZSUpMTEyscecjH8GDojJDExUcnJyb7rycnJOnbsmE6cOKFGjRopKSkpYP3Tp0/L7XYrMTFRjRo1Cvkf8unTp0O6PwAAquvMTLQrKSlJx44dU2lpaYVZWVhYqMLCQqWmpqp+/fqW+yIXw4+hM0ISExPlcDgCljVt2lRHjhxRfn6+mjRp4rvd4/EoPz9fTqdTjRs3rvRMaE3rqSmO6AAAdlSUiXY4HA4lJSXp8OHDcrvdAZlZUFCgkydPqmHDhmrQoEG1aqopctEabySKovj4eDVu3NjXMB6PRx6PR4cPH1ZSUlLYBs5QobkAANHmcDjUpEkTnT59WkeOHJHX61VBQYHcbrdcLle1Bs5QIRet1d6JJkb8fPA8dOiQDh06VCcGTslec3388ccaOnSosrKyFBcXp0WLFoW+MABATPn54Llv376oDJxS8LkYa5lYu6eaGBEfHy+Xy+W77nK5av3AKdkbOgsLC3XRRRfpmWeeCUNFAIBY5XA45HQ6fdereg1nOASbi7GWibymsxbweDw6cuSI781ER44cCXiNZ21lZ+gcPHiwBg8eHIZqAACxrKCgQEVFRUpOTlZxcbGOHDkS8WcNg83FWMvE2n867Sz389dwNmnSRE2aNAl4jScAALD289dwNm7cuNxrPFE7cKYzzIwxkn5qiDOdPn1ax48fV2JiourVq+dbJykpSYWFhdq9e7caNmxY7uOUQqHsQ3DL6rPjxIkTAfsq43Q6A57iAABAss5Eu8o+Fql+/fryer3Kz8+X9NPT7cePH1dhYaEaNmxY5VlIcjH8GDrD7MiRI5KkP/3pT1GupGJHjhxRWlpaUNs4HA5lZmbqggsuUGpqqrKzswNunz59uh588MEQVgkAOBvU9kyUyMVwYugMs/T0dEnS7t27g/4jPpPb7VZ2drby8vIC3nhkR35+vlq2bOmrLxjJycnatWuX71uVzjx65GgOAFCR2pqJErkYCQydYVb2Aua0tLSQNIX007vbQ7Uvuy+wTk5ODsm3SQAAYkdtz0SJXAwnhk5E1IkTJ7Rjxw7f9V27dmnjxo1KT09Xy5Yto1gZAACRFWuZyNCJiFq3bp369+/vuz558mRJ0ujRozV//vwoVQUAQOTFWiYydIaZ0+nU9OnTQ/J6jtq6r2D069evRu8MBADUXbU5x6KRi7GWiXEmlh4tAAAAooIPhwcAAEDYMXQCAAAg7Bg6AQAAEHYMnSF29OhRjRw5Ui6XSw0bNtStt97q+1qsyvTr109xcXEBl8TERPXs2VNffvml5bZvvfWWOnTooOTkZHXq1En/+c9/fLc988wzat26tZKTk6vc1/z588vVwOeNAQBqKlS52KxZsxplokQuRhtDZ4iNHDlSW7Zs0bJly7R48WJ9/PHHuu2226rcbty4cXruuefkcDj0xBNP6PPPP9dFF12kK664QgcPHqxwm88//1w33HCDbr31Vm3YsEHDhg3TsGHDtHnzZr3xxhuaPHmypk+frq+++qrKfUk/fcDuvn37fJcffvjB9u8BAADJfi4OGDDAl4mrVq3S4MGDbWeiJHKxNjAIma1btxpJZu3atb5l7733nomLizN79+6tdLu+ffuau+66y/To0cNMnDjRt7y0tNRkZWWZ3NzcCrf77W9/a4YMGRKwrGfPnub3v/990PuaN2+eSUtLq87DBACgWmqSi82aNQtZJhpjyMVagDOdIfTFF1+oYcOG6tatm2/ZwIEDFR8frzVr1lhu++qrr+rLL7/Uu+++q6lTp+rkyZOKj4/XwIED9cUXX1R6fwMHDgxYdsUVV+izzz7T+vXrA26ral/ST9+M0KpVK2VnZ+uaa67Rli1bqvOwAQCokN1c9Hq9OnDggF5++WVdeOGFmjp1qoqKimxl4hdffCGPx0Mu1gIMnSG0f/9+NW3aNGBZYmKi0tPTtX///kq3u/HGG/Xkk09KksaOHatXXnlFN910kySpWbNmlW67f/9+NWvWLGBZs2bNtG/fPpWWllZ4W2X7at++vV566SW98847evXVV+X1etWrVy/t2bPH+kEDAFAJu7l49dVXS5KeffZZTZ061ZeLdjJx//79Onz4MLlYCzB0VsOUKVPKvZj4zMu2bdts7/+2225Tv379JP10VPbyyy9r4cKF2rlzZ4geQdVycnI0atQoXXzxxerbt6/efvttZWRkaO7cuRGrAQBQN4Q7F8tOvLRr104jR4705eLx48dD9AiqRi6GHl+DWQ333HOPxowZY7lO27ZtlZmZWe4FySUlJTp69KgyMzMtt2/SpIkSEhJ04MABXX755ZKkHTt26MCBA5Vum5mZqQMHDgQsO3DggJo3b67jx49XeFtVdZRJSkpSly5dtGPHjmqtDwCIHeHOxZ9noiT17NlTkrRr166gMzEzM7Pc/s68vTrIxZrjTGc1ZGRkqEOHDpYXh8OhnJwcHT9+XOvXr/dt++GHH8rr9foapjIOh0Ndu3bVihUrtHHjRkk/nfZfsWKFcnJyKtwmJydHK1asCFi2bNky9e7d27evMl6v13JfZyotLdWmTZvUvHnzaq0PAIgd4c7Fn2eiJF8u/t///V/QmZiTk1NufxK5GBXRfifT2ebKK680Xbp0MWvWrDGffvqpOffcc80NN9zgu33Pnj2mffv2Zs2aNcYYY3bs2GFmzpxp1q1bZ5566imTlJRkMjIyTLdu3cxtt91mGjZsaPbv32+MMebmm282U6ZM8e3rs88+M4mJiebRRx81X3/9tZk+fbpJSkoymzZtMq+//rpxOp1m/vz5ZuvWrVXua8aMGWbp0qVm586dZv369WbEiBEmOTnZbNmyJRK/NgDAWcpuLj700EPG4XCYu+66y7Ro0cJkZmbazkRjDLlYCzB0htiRI0fMDTfcYFJTU43L5TK33HKLKSgo8N2+a9cuI8msXLnSGGPM7t27za9+9SuTnp5unE6nadKkiXG5XMbhcJgePXqY1atX+7bt27evGT16dMD9vfnmm+a8884zDofDdOzY0SxZssR321NPPWVatmxZrX1NmjTJt26zZs3MVVddZb766qvQ/nIAADGnJrmYmJhoEhMTTUJCgunatWuNMtEYcjHa4owxJtpnWwEAAHB24zWdAAAACDuGTgAAAIQdQycAAADCjqETAAAAYcfQCQAAgLBj6AQAAEDYMXQCAAAg7Bg6AQAAEHYMnQAAAAg7hk4AAACEHUMnAAAAwo6hs5Z7+eWX1bhxYxUXFwcsHzZsmG6++eYoVQUAQHSQi3UXQ2ctN3z4cJWWlurdd9/1LTt48KCWLFmisWPHRrEyAAAij1ysuxg6a7mUlBTdeOONmjdvnm/Zq6++qpYtW6pfv37RKwwAgCggF+suhs46YNy4cfrggw+0d+9eSdL8+fM1ZswYxcXFRbkyAAAij1ysm+KMMSbaRaBqXbt21XXXXadBgwapR48e+v7775WdnR3tsgAAiApyse5JjHYBqJ7f/e53mj17tvbu3auBAwfSWACAmEYu1j2c6awj8vPzlZWVpZKSEr388su6/vrro10SAABRQy7WPbyms45IS0vTb37zG6WmpmrYsGHRLgcAgKgiF+sehs46ZO/evRo5cqScTme0SwEAIOrIxbqFp9frgGPHjmnVqlW67rrrtHXrVrVv3z7aJQEAEDXkYt3EG4nqgC5duujYsWN65JFHaCwAQMwjF+smznQCAAAg7HhNJwAAAMKOoRMAAABhx9AJAACAsGPoBAAAQNgxdAIAACDsGDoBAAAQdgydAAAACDuGTgAAAIQdQycAAADC7v8BVcW1dOgObg8AAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot the permittivity at a few frequencies\n", "freqs_plot = (freq_range[0], freq_range[1])\n", "fig, axes = plt.subplots(1, len(freqs_plot), tight_layout=True, figsize=(12, 4))\n", "for ax, freq_plot in zip(axes, freqs_plot):\n", " sim.plot_eps(x=0, freq=freq_plot, ax=ax)\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also take a look at the source to make sure it's defined correctly over our frequency range of interst." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:53.742085Z", "iopub.status.busy": "2023-02-03T04:21:53.741916Z", "iopub.status.idle": "2023-02-03T04:21:54.141949Z", "shell.execute_reply": "2023-02-03T04:21:54.141440Z" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Check probe and source\n", "ax1 = sim.sources[0].source_time.plot(times=np.linspace(0, sim.run_time, 1001))\n", "ax1.set_xlim(0, 1e-13)\n", "ax2 = sim.sources[0].source_time.plot_spectrum(times=np.linspace(0, sim.run_time, 1001))\n", "ax2.fill_between(\n", " freq_range, [-8e-16, -8e-16], [8e-16, 8e-16], alpha=0.4, color=\"g\", label=\"mesure\"\n", ")\n", "ax2.legend()\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Run the simulation\n", "\n", "We will submit the simulation to run as a new project." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T04:21:54.144287Z", "iopub.status.busy": "2023-02-03T04:21:54.144146Z", "iopub.status.idle": "2023-02-03T04:22:51.532938Z", "shell.execute_reply": "2023-02-03T04:22:51.532089Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
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[22:21:56] INFO     Maximum FlexUnit cost: 0.106                                                      webapi.py:253\n",
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[22:22:21] INFO     status = preprocess                                                               webapi.py:274\n",
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[22:22:27] INFO     starting up solver                                                                webapi.py:278\n",
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[22:22:38] INFO     running solver                                                                    webapi.py:284\n",
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       "\u001b[2;36m[22:22:48]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m early shutoff detected, exiting.                                                  \u001b]8;id=540344;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=851387;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#295\u001b\\\u001b[2m295\u001b[0m\u001b]8;;\u001b\\\n"
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           INFO     status = postprocess                                                              webapi.py:301\n",
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = postprocess                                                              \u001b]8;id=647427;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=407094;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#301\u001b\\\u001b[2m301\u001b[0m\u001b]8;;\u001b\\\n"
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       "model_id": "347174a308ed433c8d1ad312bd173dcc",
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       "Output()"
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     "output_type": "display_data"
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       "
[22:22:49] INFO     status = success                                                                  webapi.py:307\n",
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       "\u001b[2;36m[22:22:49]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = success                                                                  \u001b]8;id=717449;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=810931;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#307\u001b\\\u001b[2m307\u001b[0m\u001b]8;;\u001b\\\n"
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       "\n",
       "\u001b[?25h\r",
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       "
[22:22:50] INFO     Billed FlexUnit cost: 0.030                                                       webapi.py:311\n",
       "
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      ],
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       "\u001b[2;36m[22:22:50]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Billed FlexUnit cost: \u001b[1;36m0.030\u001b[0m                                                       \u001b]8;id=296324;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=90817;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#311\u001b\\\u001b[2m311\u001b[0m\u001b]8;;\u001b\\\n"
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     "data": {
      "text/html": [
       "
           INFO     downloading file \"output/monitor_data.hdf5\" to \"data/sim_data.hdf5\"               webapi.py:593\n",
       "
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      ],
      "text/plain": [
       "\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[32m\"data/sim_data.hdf5\"\u001b[0m               \u001b]8;id=960803;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=101200;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#593\u001b\\\u001b[2m593\u001b[0m\u001b]8;;\u001b\\\n"
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       "Output()"
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "
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      "text/plain": [
       "\n",
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "
[22:22:51] INFO     loading SimulationData from data/sim_data.hdf5                                    webapi.py:415\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[22:22:51]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m loading SimulationData from data/sim_data.hdf5                                    \u001b]8;id=215341;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=769803;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#415\u001b\\\u001b[2m415\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data = web.run(sim, task_name=\"dispersion\", path=\"data/sim_data.hdf5\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Postprocess and Plot\n",
    "\n",
    "Once the simulation has completed, we can download the results and load them into the simulation object."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we compute the transmitted flux and plot the transmission spectrum."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:22:52.667467Z",
     "iopub.status.busy": "2023-02-03T04:22:52.667358Z",
     "iopub.status.idle": "2023-02-03T04:22:52.773275Z",
     "shell.execute_reply": "2023-02-03T04:22:52.772940Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Retrieve the power flux through the monitor plane.\n",
    "transmission = sim_data[\"flux\"].flux\n",
    "plt.plot(monitor_lambdas, transmission, color=\"k\")\n",
    "plt.xlabel(\"wavelength (um)\")\n",
    "plt.ylabel(\"transmitted flux\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In Tidy3D, results are normalized by default. In some cases, and largely depending on the required accuracy, a normalizing run may still be needed. Here, we show how to do such a normalizing run by simulating an empty simulation with the exact same source and monitor but none of the structures."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:22:52.775624Z",
     "iopub.status.busy": "2023-02-03T04:22:52.775435Z",
     "iopub.status.idle": "2023-02-03T04:23:16.817024Z",
     "shell.execute_reply": "2023-02-03T04:23:16.816428Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
           INFO     Auto meshing using wavelength 0.7500 defined from sources.                     grid_spec.py:510\n",
       "
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Auto meshing using wavelength \u001b[1;36m0.7500\u001b[0m defined from sources.                     \u001b]8;id=649382;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py\u001b\\\u001b[2mgrid_spec.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=961700;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py#510\u001b\\\u001b[2m510\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[22:22:53] INFO     Created task 'docs_dispersion_norm' with task_id                                  webapi.py:120\n",
       "                    'b8530c35-cc27-410a-b64c-947cd268f3e9'.                                                        \n",
       "
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       "\u001b[2;36m[22:22:53]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Created task \u001b[32m'docs_dispersion_norm'\u001b[0m with task_id                                  \u001b]8;id=925214;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=350481;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#120\u001b\\\u001b[2m120\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m         \u001b[32m'b8530c35-cc27-410a-b64c-947cd268f3e9'\u001b[0m.                                           \u001b[2m             \u001b[0m\n"
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       "Output()"
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    },
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     "data": {
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       "
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       "
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       "\n",
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    {
     "data": {
      "text/html": [
       "
[22:22:55] INFO     Maximum FlexUnit cost: 0.025                                                      webapi.py:253\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[22:22:55]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Maximum FlexUnit cost: \u001b[1;36m0.025\u001b[0m                                                      \u001b]8;id=142003;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=776955;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#253\u001b\\\u001b[2m253\u001b[0m\u001b]8;;\u001b\\\n"
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       "
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      ],
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[22:23:04] INFO     starting up solver                                                                webapi.py:278\n",
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[22:23:10] INFO     running solver                                                                    webapi.py:284\n",
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[22:23:14] INFO     early shutoff detected, exiting.                                                  webapi.py:295\n",
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           INFO     status = postprocess                                                              webapi.py:301\n",
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = postprocess                                                              \u001b]8;id=368039;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=487502;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#301\u001b\\\u001b[2m301\u001b[0m\u001b]8;;\u001b\\\n"
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[22:23:15] INFO     status = success                                                                  webapi.py:307\n",
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       "\u001b[2;36m[22:23:15]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = success                                                                  \u001b]8;id=491939;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=154180;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#307\u001b\\\u001b[2m307\u001b[0m\u001b]8;;\u001b\\\n"
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           INFO     Billed FlexUnit cost: 0.025                                                       webapi.py:311\n",
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Billed FlexUnit cost: \u001b[1;36m0.025\u001b[0m                                                       \u001b]8;id=155523;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=195871;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#311\u001b\\\u001b[2m311\u001b[0m\u001b]8;;\u001b\\\n"
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       "
           INFO     downloading file \"output/monitor_data.hdf5\" to \"data/sim_data.hdf5\"               webapi.py:593\n",
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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[32m\"data/sim_data.hdf5\"\u001b[0m               \u001b]8;id=775531;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=647473;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#593\u001b\\\u001b[2m593\u001b[0m\u001b]8;;\u001b\\\n"
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       "\n",
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    {
     "data": {
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       "
[22:23:16] INFO     loading SimulationData from data/sim_data.hdf5                                    webapi.py:415\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[22:23:16]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m loading SimulationData from data/sim_data.hdf5                                    \u001b]8;id=701083;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=736689;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#415\u001b\\\u001b[2m415\u001b[0m\u001b]8;;\u001b\\\n"
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   "source": [
    "sim_norm = sim.copy(update={\"structures\": []})\n",
    "\n",
    "sim_data_norm = web.run(\n",
    "    sim_norm, task_name=\"docs_dispersion_norm\", path=\"data/sim_data.hdf5\"\n",
    ")\n",
    "transmission_norm = sim_data_norm[\"flux\"].flux\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:23:17.156654Z",
     "iopub.status.busy": "2023-02-03T04:23:17.156542Z",
     "iopub.status.idle": "2023-02-03T04:23:17.299431Z",
     "shell.execute_reply": "2023-02-03T04:23:17.299052Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(monitor_lambdas, transmission, label=\"with structure\")\n",
    "plt.plot(monitor_lambdas, transmission_norm, label=\"no structure\")\n",
    "plt.plot(monitor_lambdas, transmission / transmission_norm, \"k--\", label=\"normalized\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"wavelength (um)\")\n",
    "plt.ylabel(\"fraction of transmitted power (normalized)\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that since the flux monitor already takes the source power into account, the normalizing run has no visible effect on the results."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analytical Comparison\n",
    "\n",
    "We will use a transfer matrix method (TMM) [code](https://github.com/sbyrnes321/tmm) to compare tidy3d transmission to a semi-analytical result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:23:17.301873Z",
     "iopub.status.busy": "2023-02-03T04:23:17.301707Z",
     "iopub.status.idle": "2023-02-03T04:23:17.304652Z",
     "shell.execute_reply": "2023-02-03T04:23:17.304299Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# import TMM package\n",
    "import tmm\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:23:17.306703Z",
     "iopub.status.busy": "2023-02-03T04:23:17.306544Z",
     "iopub.status.idle": "2023-02-03T04:23:17.354077Z",
     "shell.execute_reply": "2023-02-03T04:23:17.353734Z"
    }
   },
   "outputs": [],
   "source": [
    "# prepare list of thicknesses including air boundaries\n",
    "d_list = [np.inf] + t_slabs + [np.inf]\n",
    "\n",
    "# convert the complex permittivities at each frequency to refractive indices\n",
    "n_list1 = np.sqrt(mat1.eps_model(monitor_freqs))\n",
    "n_list2 = np.sqrt(mat2.eps_model(monitor_freqs))\n",
    "n_list3 = np.sqrt(mat3.eps_model(monitor_freqs))\n",
    "n_list4 = np.sqrt(mat4.eps_model(monitor_freqs))\n",
    "\n",
    "# loop through wavelength and record TMM computed transmission\n",
    "transmission_tmm = []\n",
    "for i, lam in enumerate(monitor_lambdas):\n",
    "\n",
    "    # create list of refractive index at this wavelength including outer material (air)\n",
    "    n_list = [1, n_list1[i], n_list2[i], n_list3[i], n_list4[i], 1]\n",
    "\n",
    "    # get transmission at normal incidence\n",
    "    T = tmm.coh_tmm(\"s\", n_list, d_list, 0, lam)[\"T\"]\n",
    "    transmission_tmm.append(T)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:23:17.356188Z",
     "iopub.status.busy": "2023-02-03T04:23:17.356032Z",
     "iopub.status.idle": "2023-02-03T04:23:17.464312Z",
     "shell.execute_reply": "2023-02-03T04:23:17.463879Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(monitor_lambdas, transmission_tmm, label=\"TMM\")\n",
    "plt.plot(monitor_lambdas, transmission / transmission_norm, \"k--\", label=\"Tidy3D\")\n",
    "plt.xlabel(\"wavelength ($\\mu m$)\")\n",
    "plt.ylabel(\"Transmitted\")\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
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   "execution_count": null,
   "metadata": {},
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   "source": []
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% done (field decay = 7.93e-10) ━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━  16% -:--:--\n% done (field decay = 7.93e-10) ━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━  16% -:--:--
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