{ "cells": [ { "cell_type": "markdown", "id": "--7FQsFR30qu", "metadata": { "id": "--7FQsFR30qu" }, "source": [ "# TidyVernier: passive dual-ring filter at 740 nm\n", "\n", "**Authors:** Mariia Stepanova, Joshua Bocanegra, Ping-Chun Chen, Melika Momenzadeh, Yingshuo Lyu — Shcherbakov Nanophotonics Lab, University of California, Irvine." ] }, { "cell_type": "markdown", "id": "ZdLupSCc5eo7", "metadata": { "id": "ZdLupSCc5eo7" }, "source": [ "The notebook is focused on designing the following components for the on-chip tunable laser in the visible spectral range:\n", "\n", "\n", "1. GaAs/AlGaAs laser specific to 720-750 nm\n", "2. Inverse wedge edge coupler\n", "3. Vernier Ring Resonator\n", "4. Diffraction Grating Far-field Coupler\n", "\n" ] }, { "cell_type": "markdown", "id": "LUeDaHg9utOk", "metadata": { "id": "LUeDaHg9utOk" }, "source": [ "\"System-level\n", "\n", "*System-level concept for the on-chip tunable laser and passive Vernier filtering architecture.*" ] }, { "cell_type": "markdown", "id": "Fc-N02xDVfnJ", "metadata": { "id": "Fc-N02xDVfnJ" }, "source": [ "## 1. Integrated Laser\n", "\n", "### Integrated GaAs/AlGaAs Quantum-Well Laser\n", "\n", "#### Active Region Design and 3D FDTD Verification\n", "\n", "This notebook models the **passive optical cavity / waveguide section of an integrated GaAs/AlGaAs laser** using **Tidy3D FDTD**.\n", "\n", "The structure represents a ridge-like III–V laser stack with:\n", "\n", "- **AlGaAs cladding layers** for vertical optical confinement\n", "- **AlGaAs waveguide/core layers** around the active region\n", "- **Three GaAs quantum wells (QWs)** modeled as gain layers\n", "- **Anti-reflection (AR) coating stacks** on the input and output facets\n", "- A **fundamental mode source** launched along the +x direction\n", "- Flux, mode, and field monitors for transmission and confinement analysis\n", "\n", "The main goal is to evaluate how efficiently the guided mode propagates through the active laser section and how strongly the optical field overlaps with the quantum-well gain region near the design wavelength of approximately **731 nm**.\n", "\n", "The workflow has three stages:\n", "\n", "1. Define the complete GaAs/AlGaAs epitaxial stack.\n", "2. Build a full 3D FDTD model.\n", "3. Analyze:\n", " - output-to-input power ratio,\n", " - transmission in dB,\n", " - output modal content,\n", " - optical field confinement." ] }, { "cell_type": "code", "execution_count": 1, "id": "pKPaCcDAXQ_j", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:35.523931Z", "iopub.status.busy": "2026-06-22T18:48:35.522267Z", "iopub.status.idle": "2026-06-22T18:48:38.010360Z", "shell.execute_reply": "2026-06-22T18:48:38.009981Z" }, "id": "pKPaCcDAXQ_j" }, "outputs": [ { "data": { "text/html": [ "
16:39:19 -03 WARNING: Using canonical configuration directory at                \n",
       "             '/home/filipe/.config/tidy3d'. Found legacy directory at           \n",
       "             '~/.tidy3d', which will be ignored. Remove it manually or run      \n",
       "             'tidy3d config migrate --delete-legacy' to clean up.               \n",
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Remove it manually or run \u001b[0m\n", "\u001b[2;36m \u001b[0m\u001b[32m'tidy3d config migrate --delete-legacy'\u001b[0m\u001b[31m to clean up. \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# ============================================================\n", "# Colab setup\n", "# ============================================================\n", "\n", "# Run this only if Tidy3D is not already installed.\n", "# In Google Colab, uncomment:\n", "# !pip install tidy3d\n", "\n", "# After installation, configure your FlexCompute API key once:\n", "# import tidy3d.web as web\n", "# web.configure(\"YOUR_API_KEY\")\n", "\n", "\n", "# ============================================================\n", "# 1. Imports and simulation controls\n", "# ============================================================\n", "\n", "from pathlib import Path\n", "\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import tidy3d as td\n", "import tidy3d.web as web\n", "from tidy3d.components.grid.mesher import GradedMesher\n", "\n", "PROJECT_ROOT = Path.cwd().resolve()\n", "DATA_DIR = PROJECT_ROOT / \"data\"\n", "DATA_DIR.mkdir(parents=True, exist_ok=True)\n", "\n", "SIM_DATA_PATH = DATA_DIR / \"sim_data.hdf5\"\n", "\n", "TASK_NAME = \"three_QW_GaAs_AlGaAs_731nm_FDTD\"" ] }, { "cell_type": "markdown", "id": "Y7K9pjHtg2My", "metadata": { "id": "Y7K9pjHtg2My" }, "source": [ "\n", "### 1.1 Optical Source and Monitors\n", "\n", "The simulation injects a guided mode from the left facet and measures the transmitted optical power at the right facet.\n", "\n", "The wavelength range is:\n", "\n", "$$\n", "\\lambda = 722\\text{–}740~\\mathrm{nm}\n", "$$\n", "\n", "which covers the target laser wavelength near:\n", "\n", "$$\n", "\\lambda_0 \\approx 731~\\mathrm{nm}\n", "$$\n", "\n", "The main monitors are:\n", "\n", "- `flux_in`: input/reference optical power,\n", "- `flux_out`: transmitted optical power,\n", "- `mode_output`: output modal decomposition,\n", "- `field_xz`: longitudinal field profile,\n", "- `field_yz_output`: output facet field profile." ] }, { "cell_type": "code", "execution_count": 2, "id": "XtohvOwLhFlr", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:38.011945Z", "iopub.status.busy": "2026-06-22T18:48:38.011629Z", "iopub.status.idle": "2026-06-22T18:48:38.032513Z", "shell.execute_reply": "2026-06-22T18:48:38.032179Z" }, "id": "XtohvOwLhFlr" }, "outputs": [], "source": [ "# ============================================================\n", "# 2. Source and monitor definitions\n", "# ============================================================\n", "\n", "air = td.Medium(name=\"air\")\n", "\n", "_sort = td.ModeSortSpec(\n", " filter_reference=0,\n", " filter_order=\"over\",\n", " sort_key=\"n_eff\",\n", " track_freq=\"central\",\n", " keep_modes=\"all\",\n", ")\n", "\n", "# Frequency samples corresponding approximately to 722–740 nm\n", "_freqs = td.C_0 / np.linspace(0.7219753086419753, 0.740253164556962, 15)\n", "\n", "fundamental_mode_source = td.ModeSource(\n", " name=\"fundamental_mode_source\",\n", " center=[-3.6, 0, 0],\n", " size=[0, 3, 2.4],\n", " source_time=td.GaussianPulse(\n", " freq0=410112801641586.9,\n", " fwidth=10252820041039.672,\n", " ),\n", " direction=\"+\",\n", " mode_spec=td.ModeSpec(num_modes=3, sort_spec=_sort),\n", ")\n", "\n", "field_xz = td.FieldMonitor(\n", " size=[td.inf, 0, td.inf],\n", " name=\"field_xz\",\n", " freqs=_freqs,\n", " apodization=td.ApodizationSpec(),\n", ")\n", "\n", "field_yz_output = td.FieldMonitor(\n", " center=[3.6, 0, 0],\n", " size=[0, td.inf, td.inf],\n", " name=\"field_yz_output\",\n", " freqs=_freqs,\n", " apodization=td.ApodizationSpec(),\n", ")\n", "\n", "flux_in = td.FluxMonitor(\n", " center=[-3.6, 0, 0],\n", " size=[0, 3, 2.4],\n", " name=\"flux_in\",\n", " freqs=_freqs,\n", " apodization=td.ApodizationSpec(),\n", " normal_dir=\"+\",\n", ")\n", "\n", "flux_out = td.FluxMonitor(\n", " center=[3.6, 0, 0],\n", " size=[0, 3, 2.4],\n", " name=\"flux_out\",\n", " freqs=_freqs,\n", " apodization=td.ApodizationSpec(),\n", " normal_dir=\"+\",\n", ")\n", "\n", "mode_output = td.ModeMonitor(\n", " center=[3.6, 0, 0],\n", " size=[0, 3, 2.4],\n", " name=\"mode_output\",\n", " freqs=_freqs,\n", " apodization=td.ApodizationSpec(),\n", " mode_spec=td.ModeSpec(num_modes=5, sort_spec=_sort),\n", " store_fields_direction=\"+\",\n", ")\n", "\n", "field_xy = td.FieldMonitor(\n", " center=[0, 0, 0],\n", " size=[td.inf, td.inf, 0],\n", " name=\"field_xy\",\n", " freqs=_freqs,\n", " apodization=td.ApodizationSpec(),\n", ")" ] }, { "cell_type": "markdown", "id": "jlz_XWjYhIKQ", "metadata": { "id": "jlz_XWjYhIKQ" }, "source": [ "### 1.2 Layer Stack and Active Quantum Wells\n", "\n", "The laser stack is defined as a sequence of rectangular layers along the vertical `z` direction.\n", "\n", "The active region contains **three GaAs quantum wells**:\n", "\n", "$$\n", "t_\\mathrm{QW}=8~\\mathrm{nm}=0.008~\\mu\\mathrm{m}\n", "$$\n", "\n", "The QWs are surrounded by AlGaAs barriers and waveguide layers. In this model, the QW material is assigned `allow_gain=True` with a negative conductivity, so it represents optical gain phenomenologically.\n", "\n", "This is useful for checking whether the guided optical mode overlaps well with the active region before adding more advanced physics such as carrier transport, thermal effects, or laser rate equations." ] }, { "cell_type": "code", "execution_count": 3, "id": "HoCgy2-4hK7m", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:38.033814Z", "iopub.status.busy": "2026-06-22T18:48:38.033653Z", "iopub.status.idle": "2026-06-22T18:48:38.058415Z", "shell.execute_reply": "2026-06-22T18:48:38.058106Z" }, "id": "HoCgy2-4hK7m" }, "outputs": [], "source": [ "# ============================================================\n", "# 3. Material and epitaxial layer definitions\n", "# ============================================================\n", "\n", "AlGaAs_cladding = td.Medium(\n", " name=\"AlGaAs_cladding\",\n", " permittivity=9.9225,\n", ")\n", "\n", "AlGaAs_waveguide_core = td.Medium(\n", " name=\"AlGaAs_waveguide_core\",\n", " permittivity=11.902500000000002,\n", ")\n", "\n", "GaAs_QW_gain = td.Medium(\n", " name=\"GaAs_QW_gain\",\n", " allow_gain=True,\n", " permittivity=13.322491330706224,\n", " conductivity=-0.0004903956897612369,\n", ")\n", "\n", "GaAs_passive = td.Medium(\n", " name=\"GaAs_passive\",\n", " permittivity=13.3225,\n", ")\n", "\n", "AR_stack_high_index = td.Medium(\n", " name=\"AR_stack_high_index\",\n", " permittivity=6,\n", ")\n", "\n", "AR_stack_low_index = td.Medium(\n", " name=\"AR_stack_low_index\",\n", " permittivity=2.25,\n", ")\n", "\n", "n_doped_AlGaAs_cladding = td.Structure(\n", " geometry=td.Box(center=[0, 0, -0.512], size=[8, 1, 0.8]),\n", " name=\"n_doped_AlGaAs_cladding\",\n", " medium=AlGaAs_cladding,\n", ")\n", "\n", "lower_AlGaAs_waveguide_layer = td.Structure(\n", " geometry=td.Box(center=[0, 0, -0.072], size=[8, 1, 0.08]),\n", " name=\"lower_AlGaAs_waveguide_layer\",\n", " medium=AlGaAs_waveguide_core,\n", ")\n", "\n", "lower_barrier = td.Structure(\n", " geometry=td.Box(center=[0, 0, -0.027], size=[8, 1, 0.01]),\n", " name=\"lower_barrier\",\n", " medium=AlGaAs_waveguide_core,\n", ")\n", "\n", "QW1_gain = td.Structure(\n", " geometry=td.Box(center=[0, 0, -0.018], size=[8, 1, 0.008]),\n", " name=\"QW1_gain\",\n", " medium=GaAs_QW_gain,\n", ")\n", "\n", "barrier_QW1_QW2 = td.Structure(\n", " geometry=td.Box(center=[0, 0, -0.009], size=[8, 1, 0.01]),\n", " name=\"barrier_QW1_QW2\",\n", " medium=AlGaAs_waveguide_core,\n", ")\n", "\n", "QW2_gain = td.Structure(\n", " geometry=td.Box(center=[0, 0, 0], size=[8, 1, 0.008]),\n", " name=\"QW2_gain\",\n", " medium=GaAs_QW_gain,\n", ")\n", "\n", "barrier_QW2_QW3 = td.Structure(\n", " geometry=td.Box(center=[0, 0, 0.009], size=[8, 1, 0.01]),\n", " name=\"barrier_QW2_QW3\",\n", " medium=AlGaAs_waveguide_core,\n", ")\n", "\n", "QW3_gain = td.Structure(\n", " geometry=td.Box(center=[0, 0, 0.018], size=[8, 1, 0.008]),\n", " name=\"QW3_gain\",\n", " medium=GaAs_QW_gain,\n", ")\n", "\n", "upper_barrier = td.Structure(\n", " geometry=td.Box(center=[0, 0, 0.027], size=[8, 1, 0.01]),\n", " name=\"upper_barrier\",\n", " medium=AlGaAs_waveguide_core,\n", ")\n", "\n", "upper_AlGaAs_waveguide_layer = td.Structure(\n", " geometry=td.Box(center=[0, 0, 0.072], size=[8, 1, 0.08]),\n", " name=\"upper_AlGaAs_waveguide_layer\",\n", " medium=AlGaAs_waveguide_core,\n", ")\n", "\n", "p_doped_AlGaAs_cladding = td.Structure(\n", " geometry=td.Box(center=[0, 0, 0.512], size=[8, 1, 0.8]),\n", " name=\"p_doped_AlGaAs_cladding\",\n", " medium=AlGaAs_cladding,\n", ")\n", "\n", "p_plus_GaAs_contact = td.Structure(\n", " geometry=td.Box(center=[0, 0, 0.962], size=[8, 1, 0.1]),\n", " name=\"p_plus_GaAs_contact\",\n", " medium=GaAs_passive,\n", ")\n", "\n", "AR_minus_x_layer1_high = td.Structure(\n", " geometry=td.Box(center=[-4.0375, 0, 0], size=[0.075, 3, 2.4]),\n", " name=\"AR_minus_x_layer1_high\",\n", " medium=AR_stack_high_index,\n", ")\n", "\n", "AR_minus_x_layer2_low = td.Structure(\n", " geometry=td.Box(center=[-4.1365, 0, 0], size=[0.123, 3, 2.4]),\n", " name=\"AR_minus_x_layer2_low\",\n", " medium=AR_stack_low_index,\n", ")\n", "\n", "AR_plus_x_layer1_high = td.Structure(\n", " geometry=td.Box(center=[4.0375, 0, 0], size=[0.075, 3, 2.4]),\n", " name=\"AR_plus_x_layer1_high\",\n", " medium=AR_stack_high_index,\n", ")\n", "\n", "AR_plus_x_layer2_low = td.Structure(\n", " geometry=td.Box(center=[4.1365, 0, 0], size=[0.123, 3, 2.4]),\n", " name=\"AR_plus_x_layer2_low\",\n", " medium=AR_stack_low_index,\n", ")\n", "\n", "structures = [\n", " n_doped_AlGaAs_cladding,\n", " lower_AlGaAs_waveguide_layer,\n", " lower_barrier,\n", " QW1_gain,\n", " barrier_QW1_QW2,\n", " QW2_gain,\n", " barrier_QW2_QW3,\n", " QW3_gain,\n", " upper_barrier,\n", " upper_AlGaAs_waveguide_layer,\n", " p_doped_AlGaAs_cladding,\n", " p_plus_GaAs_contact,\n", " AR_minus_x_layer1_high,\n", " AR_minus_x_layer2_low,\n", " AR_plus_x_layer1_high,\n", " AR_plus_x_layer2_low,\n", "]" ] }, { "cell_type": "code", "execution_count": 4, "id": "om11Smr-lEx-", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:38.059554Z", "iopub.status.busy": "2026-06-22T18:48:38.059442Z", "iopub.status.idle": "2026-06-22T18:48:38.062721Z", "shell.execute_reply": "2026-06-22T18:48:38.062388Z" }, "id": "om11Smr-lEx-" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Layer z center (µm) thickness (µm) Material\n", "--------------------------------------------------------------------------------------\n", "n-doped AlGaAs cladding -0.512 0.800 AlGaAs cladding\n", "lower AlGaAs waveguide -0.072 0.080 AlGaAs core\n", "lower barrier -0.027 0.010 AlGaAs core\n", "GaAs QW1 gain -0.018 0.008 GaAs gain\n", "barrier QW1-QW2 -0.009 0.010 AlGaAs core\n", "GaAs QW2 gain 0.000 0.008 GaAs gain\n", "barrier QW2-QW3 0.009 0.010 AlGaAs core\n", "GaAs QW3 gain 0.018 0.008 GaAs gain\n", "upper barrier 0.027 0.010 AlGaAs core\n", "upper AlGaAs waveguide 0.072 0.080 AlGaAs core\n", "p-doped AlGaAs cladding 0.512 0.800 AlGaAs cladding\n", "p+ GaAs contact 0.962 0.100 GaAs contact\n" ] } ], "source": [ "layer_summary = [\n", " (\"n-doped AlGaAs cladding\", -0.512, 0.800, \"AlGaAs cladding\"),\n", " (\"lower AlGaAs waveguide\", -0.072, 0.080, \"AlGaAs core\"),\n", " (\"lower barrier\", -0.027, 0.010, \"AlGaAs core\"),\n", " (\"GaAs QW1 gain\", -0.018, 0.008, \"GaAs gain\"),\n", " (\"barrier QW1-QW2\", -0.009, 0.010, \"AlGaAs core\"),\n", " (\"GaAs QW2 gain\", 0.000, 0.008, \"GaAs gain\"),\n", " (\"barrier QW2-QW3\", 0.009, 0.010, \"AlGaAs core\"),\n", " (\"GaAs QW3 gain\", 0.018, 0.008, \"GaAs gain\"),\n", " (\"upper barrier\", 0.027, 0.010, \"AlGaAs core\"),\n", " (\"upper AlGaAs waveguide\", 0.072, 0.080, \"AlGaAs core\"),\n", " (\"p-doped AlGaAs cladding\", 0.512, 0.800, \"AlGaAs cladding\"),\n", " (\"p+ GaAs contact\", 0.962, 0.100, \"GaAs contact\"),\n", "]\n", "\n", "print(f\"{'Layer':30s} {'z center (µm)':>14s} {'thickness (µm)':>16s} Material\")\n", "print(\"-\" * 86)\n", "\n", "for name, zc, thickness, material in layer_summary:\n", " print(f\"{name:30s} {zc:14.3f} {thickness:16.3f} {material}\")" ] }, { "cell_type": "markdown", "id": "Vu4LdnQthZor", "metadata": { "id": "Vu4LdnQthZor" }, "source": [ "### 1.3 Mesh Refinement and Full FDTD Simulation\n", "\n", "The QWs and barriers are only a few nanometers thick, so vertical mesh refinement is required.\n", "\n", "The mesh is refined to:\n", "\n", "$$\n", "\\Delta z = 2~\\mathrm{nm}\n", "$$\n", "\n", "inside the GaAs quantum wells, and:\n", "\n", "$$\n", "\\Delta z = 2.5~\\mathrm{nm}\n", "$$\n", "\n", "inside the AlGaAs barriers.\n", "\n", "This is important because the confinement factor and gain-overlap calculation are sensitive to the field distribution inside the active region." ] }, { "cell_type": "code", "execution_count": 5, "id": "xZ-ioZhchcc6", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:38.063962Z", "iopub.status.busy": "2026-06-22T18:48:38.063809Z", "iopub.status.idle": "2026-06-22T18:48:38.217154Z", "shell.execute_reply": "2026-06-22T18:48:38.216743Z" }, "id": "xZ-ioZhchcc6" }, "outputs": [ { "data": { "text/html": [ "
16:39:21 -03 WARNING: Structure: 'AR_minus_x_layer1_high'                       \n",
       "             (simulation.structures[12]) was detected as being less than half of\n",
       "             a central wavelength from a PML on side z-min. To avoid inaccurate \n",
       "             results or divergence, please increase gap between any structures  \n",
       "             and PML or fully extend structure through the pml.                 \n",
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1.0, 0.008)), name='QW1_gain', background_permittivity=None, background_medium=None, priority=None,medium=GaAs_QW_gain), Structure(geometry=Box(center=(0.0, 0.0, -0.009), size=(8.0, 1.0, 0.01)), name='barrier_QW1_QW2', background_permittivity=None, background_medium=None, priority=None,medium=AlGaAs_waveguide_core), Structure(geometry=Box(center=(0.0, 0.0, 0.0), size=(8.0, 1.0, 0.008)), name='QW2_gain', background_permittivity=None, background_medium=None, priority=None,medium=GaAs_QW_gain), Structure(geometry=Box(center=(0.0, 0.0, 0.009), size=(8.0, 1.0, 0.01)), name='barrier_QW2_QW3', background_permittivity=None, background_medium=None, priority=None,medium=AlGaAs_waveguide_core), Structure(geometry=Box(center=(0.0, 0.0, 0.018), size=(8.0, 1.0, 0.008)), name='QW3_gain', background_permittivity=None, background_medium=None, priority=None,medium=GaAs_QW_gain), Structure(geometry=Box(center=(0.0, 0.0, 0.027), size=(8.0, 1.0, 0.01)), name='upper_barrier', background_permittivity=None, background_medium=None, priority=None,medium=AlGaAs_waveguide_core), Structure(geometry=Box(center=(0.0, 0.0, 0.072), size=(8.0, 1.0, 0.08)), name='upper_AlGaAs_waveguide_layer', background_permittivity=None, background_medium=None, priority=None,medium=AlGaAs_waveguide_core), Structure(geometry=Box(center=(0.0, 0.0, 0.512), size=(8.0, 1.0, 0.8)), name='p_doped_AlGaAs_cladding', background_permittivity=None, background_medium=None, priority=None,medium=AlGaAs_cladding), Structure(geometry=Box(center=(0.0, 0.0, 0.962), size=(8.0, 1.0, 0.1)), name='p_plus_GaAs_contact', background_permittivity=None, background_medium=None, priority=None,medium=GaAs_passive), Structure(geometry=Box(center=(-4.0375, 0.0, 0.0), size=(0.075, 3.0, 2.4)), name='AR_minus_x_layer1_high', background_permittivity=None, background_medium=None, priority=None,medium=AR_stack_high_index), Structure(geometry=Box(center=(-4.1365, 0.0, 0.0), size=(0.123, 3.0, 2.4)), name='AR_minus_x_layer2_low', background_permittivity=None, background_medium=None, priority=None,medium=AR_stack_low_index), Structure(geometry=Box(center=(4.0375, 0.0, 0.0), size=(0.075, 3.0, 2.4)), name='AR_plus_x_layer1_high', background_permittivity=None, background_medium=None, priority=None,medium=AR_stack_high_index), Structure(geometry=Box(center=(4.1365, 0.0, 0.0), size=(0.123, 3.0, 2.4)), name='AR_plus_x_layer2_low', background_permittivity=None, background_medium=None, priority=None,medium=AR_stack_low_index)), symmetry=(0, 0, 0), sources=(ModeSource(name='fundamental_mode_source',center=(-3.6, 0.0, 0.0), size=(0.0, 3.0, 2.4), source_time=GaussianPulse(amplitude=1.0, phase=0.0,freq0=410112801641586.9, fwidth=10252820041039.672, offset=5.0, remove_dc_component=True), num_freqs=1, broadband_method='chebyshev', use_colocated_integration=True, direction='+', mode_spec=ModeSpec(num_modes=3), frame=None, mode_index=0)), boundary_spec=BoundarySpec(), monitors=(FieldMonitor(center=(0.0, 0.0, 0.0), size=(inf, 0.0, inf), name='field_xz', interval_space=(1, 1, 1), colocate=True, use_colocated_integration=True, freqs=array([4.15239212e+14, 4.14489682e+14, 4.13742854e+14, 4.12998712e+14, 4.12257242e+14, 4.11518430e+14, 4.10782261e+14, 4.10048722e+14, 4.09317797e+14, 4.08589473e+14, 4.07863737e+14, 4.07140575e+14, 4.06419972e+14, 4.05701915e+14, 4.04986392e+14]), apodization=ApodizationSpec(), fields=('Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz')), FieldMonitor(center=(3.6, 0.0, 0.0), size=(0.0, inf, inf), name='field_yz_output', interval_space=(1, 1, 1), colocate=True, use_colocated_integration=True, freqs=array([4.15239212e+14, 4.14489682e+14, 4.13742854e+14, 4.12998712e+14, 4.12257242e+14, 4.11518430e+14, 4.10782261e+14, 4.10048722e+14, 4.09317797e+14, 4.08589473e+14, 4.07863737e+14, 4.07140575e+14, 4.06419972e+14, 4.05701915e+14, 4.04986392e+14]), apodization=ApodizationSpec(), fields=('Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz')), FluxMonitor(center=(-3.6, 0.0, 0.0), size=(0.0, 3.0, 2.4), name='flux_in', interval_space=(1, 1, 1), colocate=True, use_colocated_integration=True, freqs=array([4.15239212e+14, 4.14489682e+14, 4.13742854e+14, 4.12998712e+14, 4.12257242e+14, 4.11518430e+14, 4.10782261e+14, 4.10048722e+14, 4.09317797e+14, 4.08589473e+14, 4.07863737e+14, 4.07140575e+14, 4.06419972e+14, 4.05701915e+14, 4.04986392e+14]), apodization=ApodizationSpec(), normal_dir='+', exclude_surfaces=None), FluxMonitor(center=(3.6, 0.0, 0.0), size=(0.0, 3.0, 2.4), name='flux_out', interval_space=(1, 1, 1), colocate=True, use_colocated_integration=True, freqs=array([4.15239212e+14, 4.14489682e+14, 4.13742854e+14, 4.12998712e+14, 4.12257242e+14, 4.11518430e+14, 4.10782261e+14, 4.10048722e+14, 4.09317797e+14, 4.08589473e+14, 4.07863737e+14, 4.07140575e+14, 4.06419972e+14, 4.05701915e+14, 4.04986392e+14]), apodization=ApodizationSpec(), normal_dir='+', exclude_surfaces=None), ModeMonitor(center=(3.6, 0.0, 0.0), size=(0.0, 3.0, 2.4), name='mode_output', interval_space=(1, 1, 1), colocate=True, use_colocated_integration=True, freqs=array([4.15239212e+14, 4.14489682e+14, 4.13742854e+14, 4.12998712e+14, 4.12257242e+14, 4.11518430e+14, 4.10782261e+14, 4.10048722e+14, 4.09317797e+14, 4.08589473e+14, 4.07863737e+14, 4.07140575e+14, 4.06419972e+14, 4.05701915e+14, 4.04986392e+14]), apodization=ApodizationSpec(), store_fields_direction='+', conjugated_dot_product=True, mode_spec=ModeSpec(num_modes=5)), FieldMonitor(center=(0.0, 0.0, 0.0), size=(inf, inf, 0.0), name='field_xy', interval_space=(1, 1, 1), colocate=True, use_colocated_integration=True, freqs=array([4.15239212e+14, 4.14489682e+14, 4.13742854e+14, 4.12998712e+14, 4.12257242e+14, 4.11518430e+14, 4.10782261e+14, 4.10048722e+14, 4.09317797e+14, 4.08589473e+14, 4.07863737e+14, 4.07140575e+14, 4.06419972e+14, 4.05701915e+14, 4.04986392e+14]), apodization=ApodizationSpec(), fields=('Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz'))), grid_spec=GridSpec(grid_x=AutoGrid(min_steps_per_wvl=24.0), grid_y=AutoGrid(min_steps_per_wvl=24.0), grid_z=AutoGrid(min_steps_per_wvl=24.0), wavelength=0.731, override_structures=(MeshOverrideStructure(geometry=Box(center=(0.0, 0.0, -0.018), size=(8.0, 1.0, 0.008)), name='override_QW1', background_permittivity=None, background_medium=None, priority=0,dl=(None, None, 0.002), enforce=False, shadow=True, drop_outside_sim=True), MeshOverrideStructure(geometry=Box(center=(0.0, 0.0, 0.0), size=(8.0, 1.0, 0.008)), name='override_QW2', background_permittivity=None, background_medium=None, priority=0,dl=(None, None, 0.002), enforce=False, shadow=True, drop_outside_sim=True), MeshOverrideStructure(geometry=Box(center=(0.0, 0.0, 0.018), size=(8.0, 1.0, 0.008)), name='override_QW3', background_permittivity=None, background_medium=None, priority=0,dl=(None, None, 0.002), enforce=False, shadow=True, drop_outside_sim=True), MeshOverrideStructure(geometry=Box(center=(0.0, 0.0, -0.027), size=(8.0, 1.0, 0.01)), name='override_lower_barrier', background_permittivity=None, background_medium=None, priority=0,dl=(None, None, 0.0025), enforce=False, shadow=True, drop_outside_sim=True), MeshOverrideStructure(geometry=Box(center=(0.0, 0.0, -0.009), size=(8.0, 1.0, 0.01)), name='override_barrier_QW1_QW2', background_permittivity=None, background_medium=None, priority=0,dl=(None, None, 0.0025), enforce=False, shadow=True, drop_outside_sim=True), MeshOverrideStructure(geometry=Box(center=(0.0, 0.0, 0.009), size=(8.0, 1.0, 0.01)), name='override_barrier_QW2_QW3', background_permittivity=None, background_medium=None, priority=0,dl=(None, None, 0.0025), enforce=False, shadow=True, drop_outside_sim=True), MeshOverrideStructure(geometry=Box(center=(0.0, 0.0, 0.027), size=(8.0, 1.0, 0.01)), name='override_upper_barrier', background_permittivity=None, background_medium=None, priority=0,dl=(None, None, 0.0025), enforce=False, shadow=True, drop_outside_sim=True))), version='2.11.2', plot_length_units='μm', structure_priority_mode='equal', lumped_elements=(), subpixel=SubpixelSpec(), simulation_type='tidy3d', post_norm=1.0, internal_absorbers=(), courant=0.99, relax_courant=False, precision='hybrid', normalize_index=0, shutoff=1e-05, run_time=3e-12, low_freq_smoothing=None)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# ============================================================\n", "# 4. Mesh overrides and full simulation object\n", "# ============================================================\n", "\n", "override_structure_0 = td.MeshOverrideStructure(\n", " geometry=td.Box(center=[0, 0, -0.018], size=[8, 1, 0.008]),\n", " name=\"override_QW1\",\n", " dl=[None, None, 0.002],\n", ")\n", "\n", "override_structure_1 = td.MeshOverrideStructure(\n", " geometry=td.Box(center=[0, 0, 0], size=[8, 1, 0.008]),\n", " name=\"override_QW2\",\n", " dl=[None, None, 0.002],\n", ")\n", "\n", "override_structure_2 = td.MeshOverrideStructure(\n", " geometry=td.Box(center=[0, 0, 0.018], size=[8, 1, 0.008]),\n", " name=\"override_QW3\",\n", " dl=[None, None, 0.002],\n", ")\n", "\n", "override_structure_3 = td.MeshOverrideStructure(\n", " geometry=td.Box(center=[0, 0, -0.027], size=[8, 1, 0.01]),\n", " name=\"override_lower_barrier\",\n", " dl=[None, None, 0.0025],\n", ")\n", "\n", "override_structure_4 = td.MeshOverrideStructure(\n", " geometry=td.Box(center=[0, 0, -0.009], size=[8, 1, 0.01]),\n", " name=\"override_barrier_QW1_QW2\",\n", " dl=[None, None, 0.0025],\n", ")\n", "\n", "override_structure_5 = td.MeshOverrideStructure(\n", " geometry=td.Box(center=[0, 0, 0.009], size=[8, 1, 0.01]),\n", " name=\"override_barrier_QW2_QW3\",\n", " dl=[None, None, 0.0025],\n", ")\n", "\n", "override_structure_6 = td.MeshOverrideStructure(\n", " geometry=td.Box(center=[0, 0, 0.027], size=[8, 1, 0.01]),\n", " name=\"override_upper_barrier\",\n", " dl=[None, None, 0.0025],\n", ")\n", "\n", "sim = td.Simulation(\n", " size=[10, 4, 3],\n", " boundary_spec=td.BoundarySpec(\n", " x=td.Boundary(\n", " plus=td.PML(),\n", " minus=td.PML(),\n", " ),\n", " y=td.Boundary(\n", " plus=td.PML(),\n", " minus=td.PML(),\n", " ),\n", " z=td.Boundary(\n", " plus=td.PML(),\n", " minus=td.PML(),\n", " ),\n", " ),\n", " grid_spec=td.GridSpec(\n", " grid_x=td.AutoGrid(mesher=GradedMesher(), min_steps_per_wvl=24),\n", " grid_y=td.AutoGrid(mesher=GradedMesher(), min_steps_per_wvl=24),\n", " grid_z=td.AutoGrid(mesher=GradedMesher(), min_steps_per_wvl=24),\n", " wavelength=0.731,\n", " override_structures=[\n", " override_structure_0,\n", " override_structure_1,\n", " override_structure_2,\n", " override_structure_3,\n", " override_structure_4,\n", " override_structure_5,\n", " override_structure_6,\n", " ],\n", " ),\n", " run_time=3e-12,\n", " medium=air,\n", " sources=[fundamental_mode_source],\n", " monitors=[field_xz, field_yz_output, flux_in, flux_out, mode_output, field_xy],\n", " structures=structures,\n", ")\n", "\n", "sim" ] }, { "cell_type": "code", "execution_count": 6, "id": "ql63Lx_2hgG_", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:38.218783Z", "iopub.status.busy": "2026-06-22T18:48:38.218447Z", "iopub.status.idle": "2026-06-22T18:48:38.223456Z", "shell.execute_reply": "2026-06-22T18:48:38.223088Z" }, "id": "ql63Lx_2hgG_" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Simulation domain size (µm): (10.0, 4.0, 3.0)\n", "Run time (s): 3e-12\n", "Number of structures: 16\n", "Number of monitors: 6\n", "Number of sources: 1\n", "{'Nx': 1065, 'Ny': 342, 'Nz': 322, 'grid_points': 117282060, 'min_grid_size': 0.0017391304347826875, 'max_grid_size': 0.030458333333333698, 'computational_complexity': 67437184499.99695, 'fine_mesh_info': ['z=-0.02461 (size=0.001739)', 'z=-0.02287 (size=0.001739)', 'z=-0.01309 (size=0.001818)', 'z=-0.01127 (size=0.001818)', 'z=-0.004909 (size=0.001818)', 'z=0.004909 (size=0.001818)', 'z=0.006727 (size=0.001818)', 'z=0.01309 (size=0.001818)', 'z=0.02287 (size=0.001739)', 'z=0.02461 (size=0.001739)']}\n" ] } ], "source": [ "# Sanity checks before launching the solver\n", "\n", "print(\"Simulation domain size (µm):\", sim.size)\n", "print(\"Run time (s):\", sim.run_time)\n", "print(\"Number of structures:\", len(sim.structures))\n", "print(\"Number of monitors:\", len(sim.monitors))\n", "print(\"Number of sources:\", len(sim.sources))\n", "\n", "try:\n", " print(sim.grid_info)\n", "except Exception as exc:\n", " print(\"Grid info is not available in this Tidy3D version.\")\n", " print(\"Reason:\", exc)" ] }, { "cell_type": "code", "execution_count": 7, "id": "2b0dabd0", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:38.225096Z", "iopub.status.busy": "2026-06-22T18:48:38.224750Z", "iopub.status.idle": "2026-06-22T18:48:38.469328Z", "shell.execute_reply": "2026-06-22T18:48:38.469052Z" } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Geometry cross-sections of the laser stack.\n", "fig, axes = plt.subplots(1, 2, figsize=(12, 4))\n", "sim.plot(y=0, ax=axes[0])\n", "axes[0].set_title(\"Vertical x-z cross-section: 3-QW GaAs/AlGaAs laser\")\n", "sim.plot(x=0, ax=axes[1])\n", "axes[1].set_title(\"Transverse y-z cross-section\")\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 8, "id": "b6b44cd5", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:38.470365Z", "iopub.status.busy": "2026-06-22T18:48:38.470268Z", "iopub.status.idle": "2026-06-22T18:48:38.477644Z", "shell.execute_reply": "2026-06-22T18:48:38.477411Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sim.plot_3d()" ] }, { "cell_type": "markdown", "id": "6E9S-no4hiEP", "metadata": { "id": "6E9S-no4hiEP" }, "source": [ "### 1.4 Run or Load Simulation Data\n", "\n", "If `data/sim_data.hdf5` already exists, the notebook loads the saved result from disk. Otherwise, it submits a new simulation to FlexCompute and saves the result there for later post-processing." ] }, { "cell_type": "code", "execution_count": 9, "id": "aDhi-Ys4hkBO", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:38.478941Z", "iopub.status.busy": "2026-06-22T18:48:38.478760Z", "iopub.status.idle": "2026-06-22T18:48:39.017348Z", "shell.execute_reply": "2026-06-22T18:48:39.017090Z" }, "id": "aDhi-Ys4hkBO" }, "outputs": [ { "data": { "text/html": [ "
16:39:26 -03 WARNING: Structure: 'AR_minus_x_layer1_high'                       \n",
       "             (simulation.structures[12]) was detected as being less than half of\n",
       "             a central wavelength from a PML on side z-min. To avoid inaccurate \n",
       "             results or divergence, please increase gap between any structures  \n",
       "             and PML or fully extend structure through the pml.                 \n",
       "
\n" ], "text/plain": [ "\u001b[2;36m16:39:26 -03\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Structure: \u001b[0m\u001b[32m'AR_minus_x_layer1_high'\u001b[0m\u001b[31m \u001b[0m\n", "\u001b[2;36m \u001b[0m\u001b[1;31m(\u001b[0m\u001b[31msimulation.structures\u001b[0m\u001b[1;31m[\u001b[0m\u001b[1;36m12\u001b[0m\u001b[1;31m]\u001b[0m\u001b[1;31m)\u001b[0m\u001b[31m was detected as being less than half of\u001b[0m\n", "\u001b[2;36m \u001b[0m\u001b[31ma central wavelength from a PML on side z-min. To avoid inaccurate \u001b[0m\n", "\u001b[2;36m \u001b[0m\u001b[31mresults or divergence, please increase gap between any structures \u001b[0m\n", "\u001b[2;36m \u001b[0m\u001b[31mand PML or fully extend structure through the pml. \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
             WARNING: Suppressed 7 WARNING messages.                            \n",
       "
\n" ], "text/plain": [ "\u001b[2;36m \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Suppressed \u001b[0m\u001b[1;36m7\u001b[0m\u001b[31m WARNING messages. \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Loaded simulation data from: /home/filipe/Desktop/GITHUB/tidyvernier-dual-ring-filter/tidy3d-community-library/notebooks/data/sim_data.hdf5\n" ] } ], "source": [ "# ============================================================\n", "# 5. Run or load simulation data\n", "# ============================================================\n", "\n", "if SIM_DATA_PATH.exists():\n", " sim_data = td.SimulationData.from_file(str(SIM_DATA_PATH))\n", " print(\"Loaded simulation data from:\", SIM_DATA_PATH)\n", "else:\n", " sim_data = web.run(\n", " sim,\n", " task_name=TASK_NAME,\n", " path=str(SIM_DATA_PATH),\n", " verbose=True,\n", " )\n", " print(\"Saved simulation data to:\", SIM_DATA_PATH)\n", "\n", "if getattr(sim_data, \"diverged\", False):\n", " print(\"Warning: simulation diverged.\")" ] }, { "cell_type": "markdown", "id": "QjcS3GG7hlqe", "metadata": { "id": "QjcS3GG7hlqe" }, "source": [ "### 1.5 Output-to-Input Power Ratio\n", "\n", "The wavelength-dependent transmission is calculated as:\n", "\n", "$$\n", "T(\\lambda)=\\frac{P_\\mathrm{out}(\\lambda)}{P_\\mathrm{in}(\\lambda)}\n", "$$\n", "\n", "where `P_in` and `P_out` are measured by the input and output flux monitors.\n", "\n", "For a passive waveguide, $T<1$ indicates propagation loss, scattering loss, facet loss, or mode mismatch.\n", "\n", "With gain enabled, $T>1$ can indicate that the modal gain is larger than the total loss." ] }, { "cell_type": "code", "execution_count": 10, "id": "rcBUXScwhn-H", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:39.018320Z", "iopub.status.busy": "2026-06-22T18:48:39.018227Z", "iopub.status.idle": "2026-06-22T18:48:39.126408Z", "shell.execute_reply": "2026-06-22T18:48:39.126165Z" }, "id": "rcBUXScwhn-H" }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# ============================================================\n", "# 6. Transmission spectrum\n", "# ============================================================\n", "\n", "fin = sim_data[\"flux_in\"].flux\n", "fout = sim_data[\"flux_out\"].flux\n", "\n", "f_hz = np.asarray(fin.f.values, dtype=float).ravel()\n", "wavelength_um = float(td.C_0) / f_hz\n", "\n", "pin = np.abs(np.asarray(fin.values, dtype=np.complex128).ravel())\n", "pout = np.abs(np.asarray(fout.values, dtype=np.complex128).ravel())\n", "\n", "T = np.where(pin > 0, pout / pin, np.nan)\n", "\n", "order = np.argsort(wavelength_um)\n", "wl_um = wavelength_um[order]\n", "T = T[order]\n", "\n", "fig, ax = plt.subplots(figsize=(8, 4.5))\n", "ax.plot(wl_um * 1e3, T, \"o-\", lw=1.2, ms=6)\n", "ax.set_xlabel(\"Wavelength λ (nm)\")\n", "ax.set_ylabel(r\"$P_\\mathrm{out}/P_\\mathrm{in}$\")\n", "ax.set_title(\"Flux power ratio vs wavelength\")\n", "ax.grid(True, alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 11, "id": "oQTjL70ehpp9", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:39.127467Z", "iopub.status.busy": "2026-06-22T18:48:39.127320Z", "iopub.status.idle": "2026-06-22T18:48:39.204403Z", "shell.execute_reply": "2026-06-22T18:48:39.204165Z" }, "id": "oQTjL70ehpp9" }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Peak transfer = 1.12\n", "Peak transfer = 0.48 dB\n", "Peak wavelength = 728.50 nm\n" ] } ], "source": [ "# Transmission in dB\n", "\n", "T_dB = 10 * np.log10(np.maximum(T, 1e-30))\n", "\n", "fig, ax = plt.subplots(figsize=(8, 4.5))\n", "ax.plot(wl_um * 1e3, T_dB, \"o-\", lw=1.2, ms=6)\n", "ax.set_xlabel(\"Wavelength λ (nm)\")\n", "ax.set_ylabel(r\"$10\\log_{10}(P_\\mathrm{out}/P_\\mathrm{in})$ (dB)\")\n", "ax.set_title(\"Integrated GaAs/AlGaAs laser section: net power transfer\")\n", "ax.grid(True, alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()\n", "\n", "best_idx = np.nanargmax(T)\n", "print(f\"Peak transfer = {T[best_idx]:.3g}\")\n", "print(f\"Peak transfer = {T_dB[best_idx]:.2f} dB\")\n", "print(f\"Peak wavelength = {wl_um[best_idx] * 1e3:.2f} nm\")" ] }, { "cell_type": "markdown", "id": "EvIBy2bIhrFo", "metadata": { "id": "EvIBy2bIhrFo" }, "source": [ "### 1.6 Modal Content at the Output\n", "\n", "The `mode_output` monitor decomposes the transmitted field into guided modes.\n", "\n", "The modal fraction of mode $m$ is:\n", "\n", "$$\n", "\\eta_m(\\lambda)=\n", "\\frac{|a_m(\\lambda)|^2}{\\sum_m |a_m(\\lambda)|^2}\n", "$$\n", "\n", "This confirms whether the output power remains mostly in the desired fundamental guided mode or is scattered into higher-order modes." ] }, { "cell_type": "code", "execution_count": 12, "id": "TLuFAZ6Ahsw6", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:39.205470Z", "iopub.status.busy": "2026-06-22T18:48:39.205336Z", "iopub.status.idle": "2026-06-22T18:48:39.441538Z", "shell.execute_reply": "2026-06-22T18:48:39.441308Z" }, "id": "TLuFAZ6Ahsw6" }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# ============================================================\n", "# 7. Output mode decomposition\n", "# ============================================================\n", "\n", "try:\n", " mode_data = sim_data[\"mode_output\"]\n", " amps = mode_data.amps\n", "\n", " if \"direction\" in amps.dims or \"direction\" in amps.coords:\n", " try:\n", " amps = amps.sel(direction=\"+\")\n", " except Exception:\n", " pass\n", "\n", " amp_values = np.asarray(amps.values)\n", " dims = list(amps.dims)\n", "\n", " f_axis = dims.index(\"f\") if \"f\" in dims else 0\n", " mode_axis = dims.index(\"mode_index\") if \"mode_index\" in dims else -1\n", "\n", " amp_values = np.moveaxis(amp_values, f_axis, 0)\n", "\n", " dims_moved = [dims[f_axis]] + [d for j, d in enumerate(dims) if j != f_axis]\n", "\n", " if \"mode_index\" in dims_moved:\n", " mode_axis_new = dims_moved.index(\"mode_index\")\n", " amp_values = np.moveaxis(amp_values, mode_axis_new, 1)\n", "\n", " modal_power = np.abs(amp_values) ** 2\n", "\n", " if modal_power.ndim > 2:\n", " modal_power = modal_power.reshape(\n", " modal_power.shape[0],\n", " modal_power.shape[1],\n", " -1,\n", " ).sum(axis=-1)\n", "\n", " f_mode = np.asarray(amps.f.values, dtype=float).ravel()\n", " wl_mode_nm = float(td.C_0) / f_mode * 1e3\n", "\n", " order_m = np.argsort(wl_mode_nm)\n", " wl_mode_nm = wl_mode_nm[order_m]\n", " modal_power = modal_power[order_m, :]\n", "\n", " modal_fraction = modal_power / np.maximum(\n", " modal_power.sum(axis=1, keepdims=True),\n", " 1e-30,\n", " )\n", "\n", " fig, ax = plt.subplots(figsize=(8, 4.5))\n", "\n", " max_modes_to_plot = min(5, modal_fraction.shape[1])\n", "\n", " for m in range(max_modes_to_plot):\n", " ax.plot(\n", " wl_mode_nm,\n", " modal_fraction[:, m],\n", " \"o-\",\n", " lw=1.2,\n", " ms=5,\n", " label=f\"mode {m}\",\n", " )\n", "\n", " ax.set_xlabel(\"Wavelength λ (nm)\")\n", " ax.set_ylabel(\"Output modal power fraction\")\n", " ax.set_title(\"Mode decomposition at output facet\")\n", " ax.grid(True, alpha=0.3)\n", " ax.legend()\n", " plt.tight_layout()\n", " plt.show()\n", "\n", "except Exception as exc:\n", " print(\"Could not extract modal decomposition from mode_output.\")\n", " print(\"Reason:\", exc)" ] }, { "cell_type": "markdown", "id": "j7D63XUEhupM", "metadata": { "id": "j7D63XUEhupM" }, "source": [ "### 1.7 Field Visualization\n", "\n", "The electric-field magnitude is calculated as:\n", "\n", "$$\n", "|E|=\\sqrt{|E_x|^2+|E_y|^2+|E_z|^2}\n", "$$\n", "\n", "The longitudinal `x-z` field map is useful for checking:\n", "\n", "- confinement inside the waveguide core,\n", "- overlap with the GaAs quantum wells,\n", "- leakage into the cladding,\n", "- standing-wave or reflection behavior.\n" ] }, { "cell_type": "code", "execution_count": 13, "id": "73tTSKwjhxB3", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:39.442567Z", "iopub.status.busy": "2026-06-22T18:48:39.442469Z", "iopub.status.idle": "2026-06-22T18:48:39.765574Z", "shell.execute_reply": "2026-06-22T18:48:39.765164Z" }, "id": "73tTSKwjhxB3" }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# ============================================================\n", "# 8. Field visualization near 731 nm\n", "# ============================================================\n", "\n", "design_wavelength_um = 0.731\n", "\n", "try:\n", " field = sim_data[\"field_xz\"]\n", " f_target = float(td.C_0) / design_wavelength_um\n", "\n", " Ex = field.Ex.sel(f=f_target, method=\"nearest\")\n", " Ey = field.Ey.sel(f=f_target, method=\"nearest\")\n", " Ez = field.Ez.sel(f=f_target, method=\"nearest\")\n", "\n", " E_mag = np.sqrt(\n", " np.abs(Ex.values) ** 2 + np.abs(Ey.values) ** 2 + np.abs(Ez.values) ** 2\n", " )\n", "\n", " E_plot = np.squeeze(E_mag)\n", "\n", " x = np.asarray(Ex.x.values, dtype=float)\n", " z = np.asarray(Ex.z.values, dtype=float)\n", "\n", " fig, ax = plt.subplots(figsize=(8, 4.8))\n", " im = ax.pcolormesh(x, z, E_plot.T, shading=\"auto\")\n", "\n", " ax.set_xlabel(\"x (µm)\")\n", " ax.set_ylabel(\"z (µm)\")\n", " ax.set_title(r\"Longitudinal field profile $|E|$ near $\\lambda=731$ nm\")\n", "\n", " fig.colorbar(im, ax=ax, label=r\"$|E|$ (a.u.)\")\n", "\n", " # Mark approximate QW region\n", " for z_qw in [-0.018, 0.000, 0.018]:\n", " ax.axhline(z_qw, linestyle=\"--\", linewidth=0.8)\n", "\n", " plt.tight_layout()\n", " plt.show()\n", "\n", "except Exception as exc:\n", " print(\"Could not plot field_xz monitor.\")\n", " print(\"Reason:\", exc)" ] }, { "cell_type": "code", "execution_count": 14, "id": "eb6b63cc", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:39.766729Z", "iopub.status.busy": "2026-06-22T18:48:39.766639Z", "iopub.status.idle": "2026-06-22T18:48:39.946414Z", "shell.execute_reply": "2026-06-22T18:48:39.946006Z" } }, "outputs": [ { "data": { "image/png": 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/v5wxY4ZsaGiwjknl/41U/3sRBYWQ0lWPJaJ2qV+/fpg2bRrmz5+flfPbkvnz52PBggXYs2ePNQEjEeUujlkiIiIiSoBhiYiIiCgBhiUiIiKiBDhmiYiIiCgBVpaIiIiIEmBYIiIiIkqAYYmIiIgoAc7g3Qxd1/Hll1+iS5cuXNuIiKidk1Ji//796N27NxSlZeoN9fX1aGxs9OVa+fn5KCws9OVa7RnDUjO+/PJLa4FNIiIiANixYweOPPJI369bX1+P8r6dUb07vfU33crKyrB161YGpgwxLDWjS5cuAICzcC5CyMtya4iIKJsiCGMd/m79bPBbY2Mjqndr2La+H4q6ZFa5qtuvo++wL9DY2MiwlCGGpWaYXW8h5CEkGJaIiNq16GQ7LT0so3MXgc5dMruHDg4d8QvDEhERUcBoUoeW4SyImtT9aQzxaTgiIiKiRFhZIiIiChgdEjoyKy1lej41YVgiIiIKGB06Mu1Ey/wKZGI3HBEREVECrCwREREFjCYltAzXuc/0fGrCsERERBQwHLMULOyGIyIiIkqAlSUiIqKA0SGhsbIUGAxLREREAcNuuGBhNxwRERFRAqwsERERBQyfhgsWhiUiIqKA0aNbptcgf7AbjoiIiCgBVpaIiIgCRvPhabhMz6cmDEtEREQBo0ljy/Qa5A92wxERERElwMoSERFRwHCAd7AwLBEREQWMDgENIuNrkD/YDUdERESUACtLREREAaNLY8v0GuQPhiUiIqKA0Xzohsv0fGrCbjgiIiKiBFhZIiIiChhWloKFYYmIiChgdCmgywyfhsvwfGrCbjgiIiKiBFhZIiIiChh2wwULwxJRLhHttBgsORcxtS8aFGgZdv5oPrWF2A1HRERElBArS0RERAEjfRjgLTnA2zc5VVlau3YtzjvvPPTu3RtCCLz44osJj1+9ejWEEDFbdXV16zSYyA9CadraK/t30J6/B2o3zDFLmW7kj5z6W+fgwYMYMmQIHnnkkZTO27RpE3bt2mVtPXv2bKEWEhERUVuTU91w48ePx/jx41M+r2fPnujatav/DSIiImoBmlSgyQwHeHNtON/kVGUpXUOHDkWvXr3wve99D//617+y3Ryi1PBJsCZS5/dB7YIOAR1Khhu74fySU5WlVPXq1QuLFy/GKaecgoaGBjzxxBMYOXIk3n77bZx88sme5zQ0NKChocF6XVdX11rNJSIiogBq02FpwIABGDBggPX6jDPOwJYtW3DffffhmWee8Txn4cKFWLBgQWs1kYiIKAYnpQyWdtENZ3faaadh8+bNcd+fM2cOamtrrW3Hjh2t2DqiONj9xM9P7Yo5ZinTjfzRpitLXqqqqtCrV6+47xcUFKCgoKAVW0RERERBllNh6cCBA46q0NatW1FVVYVu3brhqKOOwpw5c7Bz5048/fTTAID7778f5eXlGDx4MOrr6/HEE0/gjTfewGuvvZatj0BERNQsY4B3Zt1oHODtn5wKS++99x5GjRplvZ49ezYAYOrUqVi6dCl27dqF7du3W+83Njbi+uuvx86dO9GxY0eceOKJeP311x3XIKIcwC44amd0H9aG08G5A/wipJT8NhOoq6tDcXExRuJ8hERetptD7V17nb2aYYkCIiLDWI2XUFtbi6KiIt+vb/7Mee7fx6FjFzWjax3ar2HSkI0t1tb2JKcqS0RERO2BP5NSshbiF4Ylolwi9fZbXSJqR8yJJTO7BsOSXxiWiIiIAkaTAprMcJ6lDM+nJvwnKhEREVECrCwR5RpzsHN76I7jwG5qpzQfnobT2A3nG4YlIiKigNGlAj3DAd46B3j7ph3805SIiIgofawsERERBQy74YKFYYmIiChgdGT+NBtH/PmH3XBERERECbCyRJSr2voElXwSjtoxfyalbMN/P7QyhiUiIqKA8We5E4Ylv/CbJCIiIkqAlSWiXNZWu+LYBUftnA4BHZkO8OZyJ35pg3/LEhER5TazGy7TLRULFy7Eqaeeii5duqBnz56YOHEiNm3a5Dhm5MiREEI4tquvvtpxzPbt2zFhwgR07NgRPXv2xA033IBIJOI4ZvXq1Tj55JNRUFCAY445BkuXLk3re2otDEtERESENWvWYMaMGXjrrbewcuVKhMNhjB07FgcPHnQcN336dOzatcvaFi1aZL2naRomTJiAxsZGvPnmm3jqqaewdOlSzJ071zpm69atmDBhAkaNGoWqqirMmjULV155JV599dVW+6ypYjccUa5ria64VLrBsnlvojbKn0kpUzt/xYoVjtdLly5Fz549sX79epxzzjnW/o4dO6KsrMzzGq+99ho++eQTvP766ygtLcXQoUNx++2346abbsL8+fORn5+PxYsXo7y8HPfccw8AYODAgVi3bh3uu+8+VFRUpPgpWwcrS0RERAGjS+HLlona2loAQLdu3Rz7n332WfTo0QPHH3885syZg0OHDlnvVVZW4oQTTkBpaam1r6KiAnV1dfj444+tY8aMGeO4ZkVFBSorKzNqb0tiZYmIiKgNq6urc7wuKChAQUFBwnN0XcesWbNw5pln4vjjj7f2X3zxxejbty969+6NDRs24KabbsKmTZvwl7/8BQBQXV3tCEoArNfV1dUJj6mrq8Phw4fRoUOH9D5oC2JYImoLMu2Ky6Try31uttpB1IboPnTDmZNS9unTx7F/3rx5mD9/fsJzZ8yYgY8++gjr1q1z7L/qqqus359wwgno1asXRo8ejS1btuDoo4/OqL1BxrBEREQUMLpUoGc4qaR5/o4dO1BUVGTtb66qNHPmTLz88stYu3YtjjzyyITHDh8+HACwefNmHH300SgrK8M777zjOKampgYArHFOZWVl1j77MUVFRYGsKgEcs0TUvknd/2pOS1yTiNJWVFTk2OKFJSklZs6ciRdeeAFvvPEGysvLm712VVUVAKBXr14AgBEjRuDDDz/E7t27rWNWrlyJoqIiDBo0yDpm1apVjuusXLkSI0aMSOfjtQpWloiIiAJGg4CW4aSSqZ4/Y8YMLFu2DC+99BK6dOlijTEqLi5Ghw4dsGXLFixbtgznnnsuunfvjg0bNuCXv/wlzjnnHJx44okAgLFjx2LQoEG49NJLsWjRIlRXV+PWW2/FjBkzrJB29dVX4+GHH8aNN96Iyy+/HG+88Qb+/Oc/45VXXsno87YkVpaI2opUqjmtUf1J9R6sRhFZzG64TLdUPPbYY6itrcXIkSPRq1cva1u+fDkAID8/H6+//jrGjh2L4447Dtdffz0uuugi/O1vf7OuoaoqXn75ZaiqihEjRuCnP/0ppkyZgttuu806pry8HK+88gpWrlyJIUOG4J577sETTzwR2GkDAFaWiNofhhIi8iClTPh+nz59sGbNmmav07dvX/z9739PeMzIkSPxwQcfpNS+bGJYImpLmnsqLhtBybxn0NpFFGAaUu9G87oG+YNhiYiIKGD8fBqOMsdvkoiIiCgBVpaI2gt2dRHlDE0q0DKsDGV6PjVhWCJqSxKNCxJKcANTkNtGlAUSAnqGY5ZkhudTE8ZOorYik2VGgiDX209EbRYrS0TtSTYqOAxBRCljN1ywMCwREREFjC4FdJlZN1qm51MTxk6itiCV6k2QKz1BbhsRtVusLBHlunQCRmt1xwW5bUQBpkGBlmE9I9PzqQnDElEuy6QS09KhJMhtIwo4dsMFC8MSUa5qJowIxfkXpdQ91n0yr+FnMInTLnd74rbJfh0GJiIKAIYlIiKigNGhQM+wGy3T86kJwxJR0KXQneVVvYn3nqOq41cVx9XWRO1xv5+w8uXGihO1cZoU0DLsRsv0fGrCsEQUNGmM9XGEkmTOl7p1jhVSMg1Mtvv60p4k72WeT0TUUnKqRrd27Vqcd9556N27N4QQePHFF5s9Z/Xq1Tj55JNRUFCAY445BkuXLm3xdhKlTChNW0qniaZgEj3f3CdUNXazvec+3tGOdNpub495bdc947XH8xrptIFTD1AbYQ7wznQjf+TU3ywHDx7EkCFD8MgjjyR1/NatWzFhwgSMGjUKVVVVmDVrFq688kq8+uqrLdxSohQkMVA73madb4YeVQWsTYndQiHrfSusRINTvPCSsN2ucOa4jtmOUCh6X4/2uNriFZrifm6iNkxKBXqGm+QM3r7JqW648ePHY/z48Ukfv3jxYpSXl+Oee+4BAAwcOBDr1q3Dfffdh4qKipZqJlHKhCIc3U9JBQJbqLBeKwIQAkJRACEAxeMvS10HpARUQGqacaqQgNQhdfOautEe99NyXmOS7O0w2wAYYcm4eMJ2SF03/tmmKxCKHr1d4qf04o11Mr5HPkVHRP5q07GzsrISY8aMceyrqKhAZWVlllpEFMsKSlK3fsgnNW4nenzCY3WP0KBEKzqiqWsMijAqPLbKUqLuOc/jotexrinMfXGCUtyP5fwuEn8FMvnvgiiHaBC+bOSPnKospaq6uhqlpaWOfaWlpairq8Phw4fRoUOHmHMaGhrQ0NBgva6rq2vxdlL7ZoWDph2AUCB1mfAJtnjVp5iqkhBWtceiSyPISAnoOoSqGhUeVQV0Ga3wqNE2eISWaEgyf+9Z0RLR973ubbZN1yEUxapweX43cT6vIyg17eS4JWoTdJn5pJL8t4N/2nRYSsfChQuxYMGCbDeDCACswOSumNiDitX9pSpGWDGrOoqAsHWLQQgjHAGACkCXkFK39ovor1LogBQxocnr3nFDkvvedl73Boz7amYXoGI9IWfe2x4eWUEiotbUpv8JVlZWhpqaGse+mpoaFBUVeVaVAGDOnDmora21th07drRGU4niajYYREOJFVjM7jVzULViG9gdCjUFGlVp6jJTnV1zVjXK/VSb7Sk6KyjZu9zc1zQDlDnI27y/qkCEQk3nmoHLNgYq3nfBoETtQaaDu82N/NGmK0sjRozA3//+d8e+lStXYsSIEXHPKSgoQEFBQUs3jSixOAOqjV2uqlI0tFhhJy/keG1tgFFZsv9e1wEhIaQAhIRUzIqS0jQQHDC66BCtXFkNiVNJMu9nC2/W8YCxX0rr2kIRkPb2KICQwrO65PkdJbufKIfoENAzHHOU6fnUJKdi54EDB1BVVYWqqioAxtQAVVVV2L59OwCjKjRlyhTr+Kuvvhqff/45brzxRmzcuBGPPvoo/vznP+OXv/xlNppPlLokBzp7cgclc1887sBjPvovXIO2Xe8l7HKLd193u5Jlfh8MRETUinKqsvTee+9h1KhR1uvZs2cDAKZOnYqlS5di165dVnACgPLycrzyyiv45S9/iQceeABHHnkknnjiCU4bQMGS5g/+ZqcXkLZqjH28kv09GVuxEUKBNAd162gaCG5ex2ROEeDVbeZ1ffu5tspSPEIRkN7jvonaPC53Eiw5FZZGjhwJmeAvWK/ZuUeOHIkPPvigBVtF1Hocg6vtvwJGF1b0aTZj3iK96akzd1CyP7ofJzABaApNHuV8z5BkXk+IpnskaoOUTY/s2NtkLr3i15p1RDnGjzFHHLPkn5wKS0TtUiqPwkvjKTOhK4CQzsBkhhF71aeZwdJWaLIFlrghyXEt2dSd5w5N9naYT8UlU2XymiSTiKgVMCwRBUESS554Hid1QFcAJTobt6ZBaAqka/C1gx6nCy7evEgu0iuopHJN+7H2Wbytfa55p0TTQG/jI8vE3xeDFLUBOjJf240DvP3DsEQUYO6QFDNOyQwNuoRZzTGDh3WkuxSfYPZsKIoxTsl6neAvWz1B155bnDZYk1G6q1wxAamposS5lqg9kD48DScZlnzDsEQUUM0GJSC2iqLBmgPJWvctTheXtIUbYe8is08PYB7iNVDbvi9mmgHXdV0zdCesJHmIF5oYmKit0qUPlSUO8PYNwxJRACUVlKJiA4NmzJsUPT/RQxHWNTStaWLI6O+TZg9Jrnt5LmPiWqbEK/A0+6SfrfLEwERELY1hiSiHea6PBhiP3AsFjuCUiLCNe0pr/iPzibbmq0SOcON1bJx18YjaEz4NFywMS0RBkGDG7vinNFeh0ZxzFSW4tlD0pi4880m2ZCVRKbK/H9N+RztEwoWEE1aSOLCb2hB2wwULwxJRjnFXZuJVl4xd9oCkxa3WmMcJc16lNCaDTNQOx/tNOxK3IxqYjNf8S5+IsodhiSgHpLQ2WrxjbOHDzqrmwB2u4l+nuWN8qf6Yk1Imuh5RG8W14YKFYYko21KdpTqZUJLoPFfYcVRvkugqM8tOXtWetEOdx3Uc7UllYk6iNoDdcMHCsESUS9INSl7XiBOa4t0v9q0kAkwG44gcY5ZsVSYiotbGsESUC5Kp+Pi5FEgqXXx+hJg412BgovaKlaVgYVgiCjLPQdDNVJSCFCh8aEtMYCJqBxiWgoVhiSgIkhy3lCgouccQZTQoOpkqlQ9ByNc2GxdkoCIi3zEsEQVFmuEj3mP16QQR+znNLljrdXySxzZ3jPtaSU1SabaVgYnaAFaWgoVhiShgUplTyHFsM4/0ewWbuPcSCoSaZCM8rt/sPZJoa7JVJi55Qm2RROaP/vP/Cv8wLBEFSHNBKaXg4X7fVm1p7jqpBDbHU3Ep3MOTra2phkYGJiJqKQxLRLksiYBjhYhE3VPuBXvN6yYKLFblyLbMSRL3yLitRO0Au+GChWGJKFe5A06y57hDiP069pAUXVBXKLHVIKnrgCqMBXRtS5TEDUxJVq0cY5YYmKgdY1gKFoYlogBIOvC4urFizhOxXWIJu6i8Alc0KAlFsQJTzGmqCkhphCYFtiqTiA06ibrePNobcx3Xe/Ev5T04nIgoUwxLRLkiUVDya2JId1CyV5VEtJJk0nUIRbEFpgwrQa5g5Ah5fk64SZQDWFkKFoYlogBI6tF4G9+DUswNROLfm6EpTuUps3sraT0VB0SrSgxU1AYwLAVLgKb6JWrfUnlU3vaihVrjo3TCSxpP5rH7jYhaCitLRAFi/4Gf9CSMKVwz6eAipbOK5K4o2Y9LrhGpB7skBngzIFFbJaWAzLAylOn51IRhiSjb4gSJZieOTOc+KR0vAT16jn3skrkv2aDUAhiSqK3TITKelDLT86lJDtTwidqBBEHGCgaphJ1Mxu2YT7lFfw8pAU1r2sx9iE4hkGJoSqvSZTs2YVDieCUiagGsLBEFRYK5iZyHRQeDx+vaSjWA2J8006NPxEkJqWmJB3A7noxzDaz2akOi9ib4HAxH1B5xgHewsLJEFFTJBAGfxvQ4jtNl06bp8Tf7cZncz/sAz9dpV6WIcow5ZinTLRULFy7Eqaeeii5duqBnz56YOHEiNm3a5Dimvr4eM2bMQPfu3dG5c2dcdNFFqKmpcRyzfft2TJgwAR07dkTPnj1xww03IBKJOI5ZvXo1Tj75ZBQUFOCYY47B0qVL0/qeWgvDElEOihsaMg0QUk9/y/S+Hr/n2CSi1rNmzRrMmDEDb731FlauXIlwOIyxY8fi4MGD1jG//OUv8be//Q3PPfcc1qxZgy+//BIXXnih9b6maZgwYQIaGxvx5ptv4qmnnsLSpUsxd+5c65itW7diwoQJGDVqFKqqqjBr1ixceeWVePXVV1v186ZCSJnFUZo5oK6uDsXFxRiJ8xESedluDrU3Xo/Qp7jMSbNjnhI8pp8orCQ81utemUwHwMoSBUREhrEaL6G2thZFRUW+X9/8mXPKX2Yh1Kkgo2tFDjbgvQvvT7ute/bsQc+ePbFmzRqcc845qK2tRUlJCZYtW4Yf/vCHAICNGzdi4MCBqKysxOmnn47//d//xfe//318+eWXKC0tBQAsXrwYN910E/bs2YP8/HzcdNNNeOWVV/DRRx9Z95o8eTL27duHFStWZPSZWworS0Q5KuWqi1Bixwa5XktdOrboTs8qkuexca7LeZOIUuNnN1xdXZ1ja2hoSKoNtbW1AIBu3boBANavX49wOIwxY8ZYxxx33HE46qijUFlZCQCorKzECSecYAUlAKioqEBdXR0+/vhj6xj7NcxjzGsEEcMSUa5prpvKDEW2ClTMRJZewamZeyW136d2sIJE5J8+ffqguLjY2hYuXNjsObquY9asWTjzzDNx/PHHAwCqq6uRn5+Prl27Oo4tLS1FdXW1dYw9KJnvm+8lOqaurg6HDx9O6zO2ND4NR5QjHEuixHuCLGFFJ/nQkXBNtuYW842nuQV14z1B524TUTsgfXgazqws7dixw9ENV1DQfPfejBkz8NFHH2HdunUZtaGtYFgiCqrmKj/RwOS5rpxngFEdT65Z1/C8tbAdItMLSO72xzvH1SavMVZxK2isOlEbJZH5vK/m6UVFRSmNWZo5cyZefvllrF27FkceeaS1v6ysDI2Njdi3b5+julRTU4OysjLrmHfeecdxPfNpOfsx7ifoampqUFRUhA4dOiTdztbEbjiiHJKwumKGE2sguIjd1Og8SuZm7wqLswlVNTZFWL9P5jzHfVTFuz2O9vKvI6JsklJi5syZeOGFF/DGG2+gvLzc8f6wYcOQl5eHVatWWfs2bdqE7du3Y8SIEQCAESNG4MMPP8Tu3butY1auXImioiIMGjTIOsZ+DfMY8xpBxMoSURAlCA6OZVC8uuOiIUQo3tewZucGADXOmm+e1CSOabq/9TJOO5xt8a54Ndv1xuoStVE6BEQrL3cyY8YMLFu2DC+99BK6dOlijTEqLi5Ghw4dUFxcjCuuuAKzZ89Gt27dUFRUhOuuuw4jRozA6aefDgAYO3YsBg0ahEsvvRSLFi1CdXU1br31VsyYMcPq/rv66qvx8MMP48Ybb8Tll1+ON954A3/+85/xyiuvZPR5WxLDElEQpbPwLGBVaYSi2Co30etEg4lQo6GnNWYNsQcnVzsAo51S1412pzMmiUGJ2qhsLKT72GOPAQBGjhzp2L9kyRJMmzYNAHDfffdBURRcdNFFaGhoQEVFBR599FHrWFVV8fLLL+Oaa67BiBEj0KlTJ0ydOhW33XabdUx5eTleeeUV/PKXv8QDDzyAI488Ek888QQqKirS+6CtgPMsNYPzLFFWJQhM9nmXhNmlphjdW1ZYMgOKiFNB0psJGwmqQimf625DdF05a3256JIp0rZ0Cpc6oaBprXmWTnzuv6B2zGyeJe1QAzZMurvF2tqesLJEFGRpVJisbi93UHL/3n6M4wJJ/mtUtXXLef2bK951hLH2HBQF0DSjuqRpyd3Tuh+DErVtuhQQXBsuMBiWiIIu3S45O/eTaNbUAMk8RZeMBN1o8e6dDoYkaiek9OFpOPYb+SbnHj955JFH0K9fPxQWFmL48OExjyjaLV26FEIIx1ZYWNiKrSVqfdKre8wdUOxPqtk3AEIoKW/NXTNuO+K1Nx4+MUdEWZBTlaXly5dj9uzZWLx4MYYPH477778fFRUV2LRpE3r27Ol5TlFRkWPVZJFsFwNRUKQyx5EuAcUIIAJwDvLW3EuS2AdfNwWltJooFEiz6uOYfdvjn7ZmOHKPV/K6brRdjrFLfAKO2oFsDPCm+HLqn2n33nsvpk+fjssuuwyDBg3C4sWL0bFjRzz55JNxzxFCoKyszNrcU6wTBVpzQSn6vn1QtLHDCCJS04wwomnGputNm/meLaxI+0SQUm92sx8LIDpIWzbd032/6D2lpjUFJesieuzM4Ul+L0RtjZ9rw1HmcuZvnMbGRqxfv96x+J6iKBgzZkzCxfcOHDiAvn37ok+fPjj//POthfyIck1Ss2ZL3QgsttBiBhMzPJmbEZJ066k0e2CS9uvoEtD0ps223xGazHvarmm/n70NjpDmDnpxPnvSy6oQEfksZ7rhvvrqK2ia5rn43saNGz3PGTBgAJ588kmceOKJqK2txd13340zzjgDH3/8sWMKd7uGhgbHisx1dXX+fQiiFmQte2KFF/u/hWLHLElNa5pmQNeNrjprjkjb4/321+55kzTpnBLAPR0AkHhAN9d+I/LEp+GCJWfCUjpGjBjhmD79jDPOwMCBA/Hb3/4Wt99+u+c5CxcuxIIFC1qriURJiVtVcT0pFzO7t+NQ23vmk/qqCqlpxkSVXgOt3cHHPjt4vOPNaQCiv9pDkNfn8AxJHJNE7RyfhguWnOmG69GjB1RV9Vx8z1ycrzl5eXk46aSTsHnz5rjHzJkzB7W1tda2Y8eOjNpN1OKk7hmMHJumWcc1dYuZ44pkbPeYrQvN6H6LjjeKdsU5uvJc3X2IXtd9X+verrY191mIiLItZ8JSfn4+hg0b5lh8T9d1rFq1KunF9zRNw4cffohevXrFPaagoMBaoTnVlZqJWkpSXVTxgoZtNmx3gLIGhmtN3WcxA8OjA68d4cc1UNuqPml60/HxglG8NjIkEVmMf4NkOsA725+i7cipbrjZs2dj6tSpOOWUU3Daaafh/vvvx8GDB3HZZZcBAKZMmYJvfetbWLhwIQDgtttuw+mnn45jjjkG+/btw1133YVt27bhyiuvzObHIEqLNSYpzXOjv2naGX0EX+oKhKIbY5zMfz6Zg73tS5DA6EaTmnGuENFr2s9xLVfivp8vn4GoHeDUAcGSU2Hpxz/+Mfbs2YO5c+eiuroaQ4cOxYoVK6xB39u3b4diW77hm2++wfTp01FdXY0jjjgCw4YNw5tvvolBgwZl6yMQpcaP2bsRDTkeXV5WUEJ06RLHHEmuao91fHQ8lIyuR+d5Xe8n3Kw17FLk2V1HRNRKuJBuM7iQLgWCR8DwrNDYjnNP6GgNvHZVe4QijAHe9vPNrjt7V53t/ZTOsd3Hfr69bTHtsnZx8DcFS2stpHv0M3OgdsxsxQntUD22XLqQC+n6IKcqS0SUgCuINL02u8TMgBIbqPxvioi9jxmYPNomdZnczNwMStROsBsuWBiWiHJQsyHHvl5bNLQI1Rz3pHsfa69e2YKLZ/Bxn2s/J/qr+zhHF5wSXXi3mYDk2X1I1B5IxEyPltY1yBcMS0Q5pLmQFBNIhLANwDbGJ0ldSXwO0BRkhLM7zVEZinOO+x6Oc8w2AUa7HOfEXx+OgYmIsolhiShXJVo3zh5KHOHEHNDtwX1+9Mk1aT/H3dXncU5MW8x2qq5xV2aQsz9p5wpyzupWkl11RG2BH2u7sRvONwxLREHnMdYnIVtQEbanQ6WuW4Ep7jn2pUuiXXj2SlFMlSjOOUm3x3xfgzfb4HEGJmpPOIN3sDAsEQWZe0wQmumKczwN5648KU2BCUi8ZpsQtiVOYitLjuMSsVW4PNtjPqHnNc7Jpims6QxMRNTqGJaIgsg9BYA9KLkDS5zQIHU9JqA4uIOJO/i4xjvFnOd1vFldSoL0WlvOupY7WLkmxjQDk3GhpO5HlEv4NFywMCwRZVuCrjWz0hLTDeceiG2nNwUWz8Bkrxoly+cpBhxBSW+qYHne0z1w3N4l53UewxO1BVJkPuaIYck3DEtEARUTkOzjhEy2QdWOiSN1aVSFhIit4MQLSlLGrxbFNM7jL+FmAphnO7zaDngPHE8UmIiIWhDDElEAeQYl603bgGov5lxHZmBKdI4ZNhTX+/Yw5A5M7qCU6jXN14kW1nXfy/bUnLE/QWDieCZqAzjAO1gYlogCLq1Zth2ByaM65A4Y9tdexzuu7fGeV4UnXmhqZomT5rCiRO0CJ6UMFIYlolzjFVakbdmQKOsJNq+pAlzn2U6KDTmJJAo+ZjUswSK4zvaK2IWD+U9jIgoAhiWibIrOoZR2pcS2YK37Gk1Pj6VQvYkZ95QgMDXXjZagauT1eWV0EkxI3Qh49nun+v2wK45yHJ+GCxaGJaKAc6znFqdKJOMFF6E4HrmPe57jFFuFx6vK5FFNinudRPeL01ZhfwrOeXLcexG1SfyjnpRwOIzq6mocOnQIJSUl6Natm+/3SGI6YCIKDKnHbHGDkv14GCHDvXnfwuN6umza7NdG/PAS9362NsW01byex+dMdC8ial/279+Pxx57DN/5zndQVFSEfv36YeDAgSgpKUHfvn0xffp0vPvuu77dj2GJKMgSBB0rgCQIRO7reF4/TgCzrh3nvJj7e4SbeJ8nbltd90/58xC1EWY3XKZbW3TvvfeiX79+WLJkCcaMGYMXX3wRVVVV+L//+z9UVlZi3rx5iEQiGDt2LMaNG4fPPvss43uyG44oABKOW3LPQRR3xu4E44BSuI7n/dOZLTvOeYkqUTFtNSV5f/N8VqAo5/FpuLjeffddrF27FoMHD/Z8/7TTTsPll1+OxYsXY8mSJfjnP/+JY489NqN7MiwRZYt9DiVbCIg7VYArKCQbCBwhxOM67mvZxyw5Bl17He/5FF7iezXXVru44cl1jOd3wUHeRG3SH//4x6SOKygowNVXX+3LPRmWiHJIuhWTmMCU4HqOgJRgKZZ444hSHVCeSKJrEbVtIrpleg3yA8csEQVIEENBvDCU6XX8PDeI3xtRRqRPWzs1ZswY9O/f37frsbJEFFQ+dyMlDBzu8Uzp3cBxjRYfN8RuNiKK44ILLsBXX33l2/UYlogCwlEdiTOeqUX4ff3muu/SEFM58vh+WF2iNoUDvDMyY8YMX6/HsEQUBPZQlCBo+L4uWhJByR1CkmpDCwSmuNzfHatN1BZIYWyZXoN8wbBEFCRJBAw/Bk5HT2q2LfGqNUZgaiaYpBmY0qoQMSQRtUu33XZbwvfnzp3ry31SCku6rmPNmjX45z//iW3btllTi5900kkYM2YM+vTp40ujiCgqyQBgDxiZVp6EIpwhxyvw2Co5QtH9uWcqWrNyRZQFUiLjdaTbwzrUL7zwguN1OBzG1q1bEQqFcPTRR7duWDp8+DDuuecePPbYY9i7dy+GDh2K3r17o0OHDti8eTNefPFFTJ8+HWPHjsXcuXNx+umn+9I4onYl1R/+7uObGbsTE2g8uv7Mc61rCMV7MV1dsdark5qt0mRrh7t9SQWiOJ8pKQxP1JZwzFJSPvjgg5h9dXV1mDZtGi644ALf7pNUWPr2t7+NESNG4He/+x2+973vIS8vL+aYbdu2YdmyZZg8eTJ+9atfYfr06b41kqjdSRQS4oWCePs9QpQVnFwhyep6M0OSMMOT+YRbtF1qdDyFLiFUc24mc96lZkJSKqEm0czdfjzBR0RtTlFRERYsWIDzzjsPl156qS/XTCosvfbaaxg4cGDCY/r27Ys5c+bgv/7rv7B9+3ZfGkdELrZgkHzXlQrAPcu2LXzYA5MtJAlFscISomFJqCpgBiYpIYUOSAEhJCCNgd9ChTPcpNVmxLSZqF3hAO+M1NbWora21rfrJRWWmgtKdnl5eTj66KPTbhBRu+exjpo9ZDi6yADvbjI3M8RY11eb3rN1tQlVNQKSGZQUAeFRuZFSN64ppRGepITUNOMeunT+Je0+P8n2GqfaqlWuGcMdS6GwukRtjJDGluk12roHH3zQ8VpKiV27duGZZ57B+PHjfbtPWk/D1dfXY8OGDdi9ezd03Vke/8EPfuBLw4javCR/yHt2kQGAalaEkggKtmwkbf/PWudaISkajlTFGZrcbbKFJGg6pNQh9FD0tea4T1Ltc5Ei2kbN3KNZY6ySnj6BT8cRtXn33Xef47WiKCgpKcHUqVMxZ84c3+6TclhasWIFpkyZ4jkzphACmqZ5nEVE6Ug0lkio0QTkDjTNVG7s7wr72CQhgFDI+FW1hSjjQONX++M15v/rmm6Ep0ik6REeXaYWVuzhR0qI6P2k+TpaqTIrTJyAkto8DvBOytatW1vlPimHpeuuuw6TJk3C3LlzUVpa2hJtImrfPKpNVlBSFaNSo6pNlSWzKgQ0VYPM33teXzh/rwhAiV5PMcKTDClNAcp9jhmYosFIRIwuOeg6oOmArjV10dmP92K+Z1apovtkNIgJRQE0zfg7PzqI3D2AnKhN4pilQEk5LNXU1GD27NkMSkQ+8upacj++L1TV6i4TZlgSoqkLzawGKWbFScQPPNFrS0UxltNWVUjVCFpSFcZ+YZwjPbKJ0BENS4DQdQjNCEtCi3bD6cZ+AE1VI3d4MitQgBGwACNsSWmEJCkBoUMKYVSazHFRoqlq5fWdSRa3idq9MWPG4PPPP8fnn3/uy/VSDks//OEPsXr1ag7iJvKR80k11xxHZjhSFIhQqCkkmb93V4XMABTtnpNCGK+FLSABgALI6LX0kFFh0kMKpAJIRQACRoCyGgZHWV9oZliSEDqgRCtMSiRacdJ0IzSZXXPRkCQ0e1jSm4KVuzql6YCIQKgKZKNxvACsJ/DgmK5AxnyPRDmN3XAZyfpCug8//DAmTZqEf/7znzjhhBNi5lz6+c9/7lvjiNo01xxHxlxF3t1tRkhSgbxQUzjKCxlVoPwQoCjQ81Qj8OQpkIqAnicgFQEZMqpDUhVGZV8VkGo0b0TfM3+VIUTDEoywZGYlezXfnKIp+pe50KNbBNHQJJt+leZ+CUUDICWUcFPIUsIy+ms0aIU1o0LVGDFCVThijInKCxtBqjFsVJU03eiei4YrcxZxR2WJS6BQLmNYykjWF9L94x//iNdeew2FhYVYvXq1NRATMAZ4MywRZcDscosGJREKGdWlkBGIkJdn/KoqkPkhyJACPT8EGRLQ81Tj13wFugroeQr0UDQIqYAeMipGui0Q6SEACqDn2V6LprDULGl2yQGKGZbCAtABJSKiockVosLS2q+EdSgaoDTqEBEJGRIQEQlFCCCiG01Q9GhAEkBIh9CNQCmjTZRSAroC26NzRES+Sjks/epXv8KCBQtw8803Q0njkWAi8tbU/WYba6RGq0sh1agohVRj8LWqRkOSAr1QhR5SoBco0EMCWr5RVYoUGFUkrQCQKqCZgSg/GpbUpkqSnieN16qMhiWZQlgSxq+agNCMsGRVmjRACcPar+iA0iiMAKVJhBpUKGEJNSSgRCRkgzC682DMsaQAgKZByDzjImbXnaYZ4ckakyVd808xOFGOY2UpJZ988gm2b9+OxsZGx36/pjNKOSw1Njbixz/+MYMSkV/s3UXmD3zF9Ui/KyjJPBUyXzXCUYFRUYoUKtDzgHAHYwyS1gHQVRi/hoyQpKuAXiAhVWlUj/J1SFVChHQIRUIJGTPhKUp0fFF0Vjsp7RVk5z5dN/rr9IiArgtEIgqEJoBGxaggNQqIiIDaaOQdtd4IUIpmVLmUCJB32AhTIUTHSekSiiIgo+OUELINBJey6Sk+aTwtB0UwH1HbwqfhkvL555/jggsuwIcffgghjL8zAFi9Xn5NZ5RyWJo6dSqWL1+OW265xZcGEJGTucyIMQeSYnW7mVUmGVKMilJedMsX0PIEIh0EtDwg0lFAzwMiHRH9VRphqVCHzJMQ+RqUkA41pCMvT0NI1ZGfF0GeoiOkalCEhCqcY33MYCQ8pgTWpAJdCkQ0FWFdQWM4hIimIBxWoUcUaI0qZESBdliBiAiE8oURlsJG1lHCxrXVEAApjPHrmgoIHUKLPhWnCQhpmyhTSgihQArjyTnJ+d2I2qVf/OIXKC8vx6pVq1BeXo533nkHX3/9Na6//nrcfffdvt0n5bCkaRoWLVqEV199FSeeeGLMAO97773Xt8YRtRvxBiMLZ9ec+Vi/NXBbNYKSni8QKYiGpA5GFSncyagiaZ10IF+H2iECNU9Dx8JG5Ksa8kMRdMlvQKEaQcdQI0JCRwe10QhL0fq9lqAvzn6MLgUOa/mISAWHIvmo10LY31iAxkgIBxvyEY6oaCzIg4woCIdUo0uuwbi20mh04UnFGOdk7BOQ0higDkUx/pUozNnL9QRzSLELjtoGLneSnMrKSrzxxhvo0aMHFEWBoig466yzsHDhQvz85z/HBx984Mt9Ug5LH374IU466SQAwEcffeRLI1LxyCOP4K677kJ1dTWGDBmChx56CKeddlrc45977jn893//N7744gsce+yxuPPOO3Huuee2YouJ4kh3TbPoNABmYNLzjMCkFQBavlFR0gqAcJEOWaAjr6gB+fkRdOt8CJ3yGtGj8CA6qY3ooDaie95BFCphFKuHkCc0FCphqHCGNg2xbfQ6pl7PQ1iqqNU6ol7Pw9fhTjis5WNPQ2cciuRhz8HOqG8M4VCoEJEGFaJBAaBADRnjm1QF0BqN8U8yJCB1swsS8cNRInwSjnJZlsYsrV27FnfddRfWr1+PXbt24YUXXsDEiROt96dNm4annnrKcU5FRQVWrFhhvd67dy+uu+46/O1vf4OiKLjooovwwAMPoHPnztYxGzZswIwZM/Duu++ipKQE1113HW688caU26tpGrp06QIA6NGjB7788ksMGDAAffv2xaZNm1K+Xjwph6V//OMfvt08VcuXL8fs2bOxePFiDB8+HPfffz8qKiqwadMm9OzZM+b4N998Ez/5yU+wcOFCfP/738eyZcswceJEvP/++zj++OOz8AmImid1Y/kQKXXnHEWumbDNIQ32wdp6XnRsUoEEOmpQCyIo6lyPzgUN+FanWhTnHUafwm/QWa1HF6UeJaE6FIowipR6IywJzaoYmTQIq8Jkvud1TL1UEZYq6vRC1Ms87IkUYb9eiJ15R6AuUoiQ0LE/XIDduoJGNQRdDUFvEBDSqIgpevRzKB7DNazvQLd+L6O/l671KRmSiNJ38OBBDBkyBJdffjkuvPBCz2PGjRuHJUuWWK8LCgoc719yySXYtWsXVq5ciXA4jMsuuwxXXXUVli1bBgCoq6vD2LFjMWbMGCxevBgffvghLr/8cnTt2hVXXXVVSu09/vjj8e9//xvl5eUYPnw4Fi1ahPz8fDz++OPo379/ip8+vrQW0vWybds23HXXXXj44Yf9umSMe++9F9OnT8dll10GAFi8eDFeeeUVPPnkk7j55ptjjn/ggQcwbtw43HDDDQCA22+/HStXrsTDDz+MxYsXt1g7iVJirzDpElCF8cSXEMbgZSGMeYUUxZh7SDEGaLtL7NIo1Bjjk/IkENIRKtDQuaABxfn16FmwH0fkHcKR+XvRRTmMLko9ykL7USh0dBFAnlBQKEJQbJUkPVpB0mxBTY1WedzH1UsNYRnBftmAeqmgUISxXy8EAHRUO+FgpACKkKgrKIQuBRo1BXqehIgY1SP3TOHGPE4yOiu4ud5cdNO0pkksze+NiDI2fvx4jB8/PuExBQUFKCsr83zv008/xYoVK/Duu+/ilFNOAQA89NBDOPfcc3H33Xejd+/eePbZZ9HY2Ignn3wS+fn5GDx4MKqqqnDvvfemHJZuvfVWHDx4EABw22234fvf/z7OPvtsdO/eHcuXL0/pWomkHJZGjRrlmFvJtGvXLuzatavFwlJjYyPWr1/vWEVYURSMGTMGlZWVnudUVlZi9uzZjn0VFRV48cUXW6SNRGmzV0Pc1SRNi85oHQ1RujAe09clRHTuInOzl+6FkBDRwdr5qoYCJYICJYxCEUYnpQGdlAYUCh2dBNBRhJAnVOQJ1RGCgGhgEoAmdajRUOd1jAIFYWjQEQGgo5PSAB0ChSKMAiWMAjWC/OgAcrNtxueFc3JLHdHPZc4CrhszfGsaENGMX+NV3FhVojZCwIcxS9Ff6+rqHPsLCgpiqkGpWL16NXr27IkjjjgC3/3ud/HrX/8a3bt3B2D83O3atasVlABj6RFFUfD222/jggsuQGVlJc455xzk5+dbx1RUVODOO+/EN998gyOOOCLptlRUVFi/P+aYY7Bx40bs3bsXRxxxhGdWSVfKYWno0KGO15qm4fPPP8fmzZuxdOlSn5oV66uvvoKmaTFr0pWWlmLjxo2e51RXV3seX11dHfc+DQ0NaGhosF67/5AR+U3qEiIvZIQAANAlpDAmZJSaYvyFp+mA0CDC0WOEgAjrUISAEpaQqoCIRB/JjwAyLKBpCiJhFfWRPByKRHBYy0eBEsFBvQBK9Gm3TiIMXWiAEkEeNBRI1aoc2VmVpegv7mM0KdEADWEpsV8H6qWK/Xoh6vQOOKQX4JBWgIORfByK5CEcUREJq5CaAjVszLmkRIxxS8ZElcaSKSKsQ0R04zObIUkzZviW0d9Lc5kUk6o2fY9EBADo06eP4/W8efMwf/78tK41btw4XHjhhSgvL8eWLVtwyy23YPz48aisrISqqqiuro4ZFhMKhdCtWzfrZ291dTXKy8sdx5g/q6urq5sNS9u3b8dRRx0V9/1u3bo5Xu/cuRPf+ta3kv6MXlIOS/fdd5/n/ieeeAIPP/wwLrnkkowalG0LFy7EggULst0Mam/MH/DuQd+absxUretABEBEiz4ZphlLhAgBJaJANkqojcZM3UqjMVO3Vq9CExIHG/KhCImv8jshLBUUKmEc0vOxX+mARhlCJ6UBXWQD8qGhUEQANE33ZKfL+PsBIyA1QsV+vQAH9QLsiRThkJ6PXY3FqIsUYl9jB9Q1FKK+IQ9agwrUq1AaBJRGI+SpjYDSaAQlJaxDCRtBSUR0IBIxApMVlKIVJCvE6c7vkSjX+TjP0o4dO1BUVGTtzqSqNHnyZOv3J5xwAk488UQcffTRWL16NUaPHp1+W1Nw6qmnYuLEibjyyitx6qmneh5TW1uLP//5z3jggQdw1VVXZby6iG9jlkaPHo3rrrvOr8vF6NGjB1RVRU1NjWN/TU1N3L7TsrKylI4HgDlz5ji67urq6mJSOVGLksZCsVLXm8rIkYgxv1BEBWCU15WGCCABtV6BkIBWLwAIaPlGV5ZeoECL5GG/2gH1jXnQpUDn/AbsjxSiS6geHdQweuQdQIESRhdzgHf0abi8aGhKRliGHE/D7dcL0aDn4atwZxzW8lBTX4QD4XzsPtAZhxvy0bg/H+KwCrVBIHTImKQydBgI1UuEGnQoDTqUBg1KY8SoKoWjQSkSaQpKut40sNve9capA6it8PFpuKKiIkdY8lP//v3Ro0cPbN68GaNHj0ZZWRl2797tOCYSiWDv3r3Wz954P5vN95rzySef4I477sD3vvc9FBYWYtiwYejduzcKCwvxzTff4JNPPsHHH3+Mk08+GYsWLfLlCXjfwtIbb7yBUaNG+XW5GPn5+Rg2bBhWrVplPcao6zpWrVqFmTNnep4zYsQIrFq1CrNmzbL2rVy5EiNGjIh7n0z7col8oUvjkfno8h5Siz6PFo5Y1RTRaIwcUuuNmbJDecZYJj2kGF1xioBaIBCW+WgsCKGmUcXX+Rr2duyIwlAE+WoERfkNyFc0dAw1Ik/RkK9EkCfMiSmN+yiIHQcUXYgEmjTmWApLFY16CGFdxaFIPhp1FXWNBWjUQqg7XIiGcAiNB/OBBgWh/SrUegGlAcg7AKgNQN5BHWqDhHpYh9IYDUqNEePzhsNGWIwumgu96Ym4mIHdHLNE1Kr+85//4Ouvv0avXr0AGD939+3bh/Xr12PYsGEAjHyg6zqGDx9uHfOrX/0K4XDYmqtx5cqVGDBgQFLjlbp37457770Xd9xxB1555RWsW7cO27Ztw+HDh9GjRw9ccsklqKio8PWp95TDktejhDU1NXj77bcxatQox/t/+ctfMmudy+zZszF16lSccsopOO2003D//ffj4MGD1tNxU6ZMwbe+9S0sXLgQgDGz53e+8x3cc889mDBhAv70pz/hvffew+OPP+5ru4haitR1Y0ZvszvOtsyQiM5krYYUY101VUCJGPMvaY0AYDySLzRjpu9IvYLGPImvO+RDqDqUkERefgSqqqMgLwJV6AipOlRFR0joEEJCSTDCVJfGxJERqUDTFUQ0BZpU0BAOQdMUhBtDxhIoDSpEWIF6SIHSKBA6aAQkJQzk75eOsBQ6FIGIaBANYYhGLRqUjDFLUjYFpZjpAhzfGZ+MozYgS/MsHThwAJs3b7Zeb926FVVVVejWrRu6deuGBQsW4KKLLkJZWRm2bNmCG2+8Ecccc4w10HrgwIEYN24cpk+fjsWLFyMcDmPmzJmYPHkyevfuDQC4+OKLsWDBAlxxxRW46aab8NFHH+GBBx6IO8wnng4dOuCHP/whfvjDH6b+QVOUclgqLi723Pftb3/blwYl8uMf/xh79uzB3LlzUV1djaFDh2LFihXWwLDt27c71qw744wzsGzZMtx666245ZZbcOyxx+LFF1/kHEsUHFIHoDr3uSaqdHTHCduTYIoKISUUVYXMMxajNZYJEdbkjnqeMfBbzwPUBiW6VpwCqQK6KlGfnw+pShzM04014ULGk2+KaoQRc40467Ea21++uh5dG05TjHtFjAmSZNhYG040GpWuvAZjeZNQPSDCRpeb2mgM5M4/IKE2SoQORStKDUbXm2iIdr2FI8ZAbhmtKnkFJa/Zz1lhohyXrRm833vvPUcvkTksZerUqXjsscewYcMGPPXUU9i3bx969+6NsWPH4vbbb3f0yDz77LOYOXMmRo8ebU1K+eCDD1rvFxcX47XXXsOMGTMwbNgw9OjRA3Pnzk152oDWJKSU/GdYAnV1dSguLsZInI+QyGv+BKIUiVAehH3ktBmWHPuEUUlSjTAkVGNhXYRCQEG+sWZcYR5kngq9MM9YSLdQhcxTECkwlkWJFBoDwLV8EQ1LxpxMUjXClDlHE8yJLoWxz2uMqZAwVh2RTVMWKMaMAVDCRqZTIoCiGQPOFU1aAUlt0KFogAjrUOs1Y0B3fdgISfVhY5B2Q6M1qNt88s0KSva/sswqki0c6eEIwxK1mIgMYzVeQm1tbYuMAzJ/5vS74w4ohYUZXUuvr8cXv/pVi7W1PUmqsiSl9HW+AiJKndSN6QQQXVlbAEZwEAJQjTFNIqwBmoSiCiiNIciQgJqnQqoCeQUKpAJoeeZSKebvjQqUtIclcyZtIDrhi70hxiYQnRNJgxWWhG4EIqEDalgay5iEjTmTlEZjgkmlUbPmiFIaI0Z7G8JG5aix0fg1bLyW0bFK1kK5/LcdtRdZ6oYjb0mFpcGDB2Pu3Lm48MILHZNIuX322We499570bdvX88ZtYnIg1dXXMwxMnqoOYZJgxQCkNEuOk2xuuYUTQdUxRggrSiQIcVYfDdPAYSAnhddiFc11pWTqoAecoYmqQprKRXPtXTNSSQlIDTpCElKJBqKwtFfI7pxjKYDmjQqSNGB6yIS7V4LR4yJN8PRcBSJGFUjhiRqrxiWAiWpsPTQQw/hpptuwrXXXovvfe97OOWUU2Ie01u3bh0+/vhjzJw5E9dcc01Lt5uo7fMaqKzAqLIIAaFpgFQgETa65XTd6KaLRABFQIRCTd13ioBUFEAVUFTVeNJOUaDnqYAA9DzjGD1PMUKSaoQoawkSe2XZfBpPjwYlzVh6RQkbE0QqYd2oNIW1pkAkpfWrOfYIUkafcosuW6K55lEypwfweuqNqI3L1pgl8pZUWBo9ejTee+89rFu3DsuXL8ezzz7reEzvpJNOwpQpU3DJJZekNE05ERmkLp3jluIxQ0M0NAmr4iSbApMQxhaOzpUUfS2EcIQoCAElZHTRqaoaDUgqoApI1eiyk2abPMNSdKkVs2KkadF13KK/RrSmQGQGHvcSJa5pAKS5lIk5O3eKQYlPwhG1bYcPH8bevXtjZuT++OOPMXjw4Ba7b0pPw5111lk466yzWqotRO2aFZjcs3h7DVbWlabAZB5mBhAz2LjClxBG9cgKU9EB40IRQCgUHUCuWBUoiGg1SrFd0wo50VnFpbHIrbDPgWTvQnOHIfdnsQZoR3+NdrtJ29Ivnp/f4/thUKI2xccZvNuK559/HrNmzUKPHj2g6zp+97vfWXM3XXrppXj//fdb7N6+TUpJRD5q7mkuqRsTVQsFUo9WkNxLfbjCg/XKDEyIztUkhNF9pxhP2Qnztfk+EBuWACMImfeV0aqQGZLsj/gnqg65q2n24xJ9B3zajdo6jlmK8etf/xrr169HaWkp1q9fj6lTp+KWW27BxRdfjJZ+sJ9hiShAku6Oazqh6fdxVvmwV1yEIpqOE0rTXzCaBqEokNH5laAaIcmqRrnZq0RaU2hyPNrvqgqZ7XB8Pp9WJmFViajtC4fD1ryKw4YNw9q1a3HBBRdg8+bNLf7EvtL8IUSUdUKJ3TxIXcZscd835y+KDqiW4QhkYyNkOAw0hgHzdWPYY2s0xkQ1hiHD4eh5ESM4Ra8pNc2zHV5tjBt2kvjMRG2ROcA7060t6dmzJzZs2GC97tatG1auXIlPP/3Usb8lsLJEFDCO6lKigGC+5x6zE6+LyuNaTdUeszoEZ8VJCKt7TyiKc/bsZipIHjdL+FmS+twcq0TtBbvhYjzzzDMIhZyxJT8/H3/84x/jrhHrF4YlolzgfirNMXbIY7mPFDkDhwYhXaFFEc5B18ZJHucm4LUsSbzjXLOXe87aTUTtypFHHhn3vTPPPLNF751yXfu73/0uFixYELP/m2++wXe/+11fGkXUnjmqK4pwPMEmFMXYosue2E5K/4ZSd25o6iqz9unSNnjb2OfoPvO4RlrsnyO6rIvj80anPzC+k+i4qlTGeBHlCj+64PjvCt+kXFlavXo1PvzwQ3zwwQd49tln0alTJwBAY2Mj1qxZ43sDidq0ZLqbzIklXQMYrW4xBUC0Cyvh2B8vXsHGNnWBYzoDxyHNPLXmnv7A3o44YcoKPYrw/MxCVZuesrO6CeNcL9kqFlFQsRsurvLy8rQGdM+aNQs///nP07pnWt1wr7/+On72s5/h9NNPx9/+9jf069cvrZsTUTPcoUGxBZDo0idWYPLpyTIA3oHJeivJx/vT4Q5Krs8L2MdOtdGfBESU0NKlS9M6L5OsklZY6tWrF9asWYPLLrsMp556Kp577jkMHDgw7UYQtWvxqj727iX3fEfmPvuAa6FAKDpksmOYkgw67m6uhBUs9/WT6R4UinEPVzUN7mqa+XnNqpIiOH6J2i5WluL6zne+0+r3THmgg1n6KigowLJly/CLX/wC48aNw6OPPup744jIxj0zdzRQeHXROYOHx//mzQWlZsYDJfW0Xrz7JGqbtZad4v15k8AxTNQWcOqAxKZNm4ZDhw612v1SDkvuWTJvvfVWPPvss7jnnnt8axRRu5RMpUdxBQjAFjBEU5UGQFpzE0XPEYpoqvbE2WKOSeM+xm+FNZg9JvilO0EnEbVpzzzzDA4cOGC9vuaaa7Bv3z7HMZFIxLf7pRyWtm7dipKSEse+iy66CG+//TaefPJJ3xpGRC7JLCprC0z2LUaiAKSqxnIn0SVQoCqxmyKsY4S5vly8YBVza1fb4s0S7vX5iYgQW7h59tlnsXfvXut1TU0NioqKfLtfymOW+vbt67l/8ODBLbriL1F7IXUJocIIRmo0ROh607gl9+KzJvt8RK4JK+MO0La/Zw8tZrXKfm3rAvbZuKODy6FCiKbJKePew7kztv12UgK67feue5vfAyelpDaJY5ZS4rU2XH19vW/X56SURNmSqOvKHBwdfVRemIObFdc59gHPQHQck/mejL2H1GODixmS7AHJ/SRanLAkbAFNCt1Y5VyXTTOCN/d5vcYjSdn0WT0W7nVMHdDMrODsmiNqv/xcL45hiSgIzB/qXk+Q2asqego//N2hyCs8RY8Rqmq8Nid/tJ0rvJZJMdurKtHlTiTMMyQ0AGpsl2GqA689llaR7nBova87fyXKcX4M0G7LA7wBYNmyZTjnnHNwwgkntPi9GJaIgkrqxlImirDWZBOuypL0Ck/x/jXlVchyz2mkKkY4ci834j5N2t+XTeFJ1yFU1dY9l2Tbouyfx/5Zrf1x1qMjapPaeNjJxNlnn4158+Zh//79yMvLQyQSwbx583DmmWdi6NChMWOrM8WwRBQQ9tmypW57qk2XVvCw1mdLJF4g8Qo99oqSObjbPDZRsLGvUacAAqrx93p04V2hqsm11eRRLfI831WtkrbQ5J48k4jaLnPFkM8++wzr16/H+++/j/fffx+33HIL9u3b52sXHMCwRBRY0hz7I5TkJ19UomOIon9RuCtRscc3LZQrhNIUkrwmwYxpoFnlMbrGhFAgFR2Q0SkBmnl6zbNalKzo2nREbRYHeCfl2GOPxbHHHovJkydb+z7//HOsX78eH3zwgW/3YVgiCjr7OKbmup6i3XZmYLIGh7sJZzebsA3yjpk5Ox77Eiy6bgQuXYEU0hHYPKtGqXarJfv5idoIjllKX//+/dG/f39MmjTJt2syLBEFSNyupOYWsrUmeIyOcwKaph1wcwWllAdeN0cRTY/8m/eIV2WypkGwVYpcg9y9FvJ1Y5WJqP3ImYV0ichfyf6wj7uIrTVuR2nqumuuumTSJaDaX+ux3XDW/E0eUwi4B5m7P4srKMVUlcyg5PF5IJSUxiJx3BK1GeyGiytnFtIlohbg7m5rbh4meE3+qDcFJl0xBoa7A5O7i0wISKlD6EpT3T6VKQpsXWnWU3EpdL1J+6+OzyKS/h6s36e67ApRQLEbLr5sLKTLsESUbR5dbGZ1JFGlxNFtBdiqMPEDk3GY4qwKKQqgA1LRITTEDBJP3HZXUIrOuWSfLNNzeoN4QSnJipI9WLELjohaGsMSUS4SSjQUeY9dMkKHapuryX6Yay4jTTOmDtBkdHB2dMB3kjV8R0gCjOu57hOzTInXJJKu0GitG0fUHrEbLlAYloiyJZkuJtf7QhGOgGS8di7rYVZkHJUZXTYN5Hav7QYYs2+bT8KZoSnpz+GcQiCmu83kqh6ZnyOmMiSU5MYdxRn0HVOlIspFDEuBwrBEFCRJjLtp6qKzhaQ45zQ7V5NViIqGJq+B3M222dXdlsS8SZ5dZzEL6yYZmowLJnccEVEaGJaIAi7hE17R7jjzOGNXCkHHDC2u0GRcp/kuMM+uthTHENmrZVbbEwRGjlGi9oADvIOFYYkogOIGJMf8Q03TBdhf249LOji5QhOA1JYrsV8jCVZAEkZ1zB2SPEOTR/WIwYnaLHbDBQrDElGQpDKgWThDkhmajH0i5rikWKEpjepUslwBybPdqQ7sFgq74oioxTAsEQWFe9bqFM9zVJbs13NfK5lw42fFxuv+tqf2Ugl2XnMxWfv45By1JawsBQrDElEAeI7bARIP+I4JIUri9732t2Q3VlL3b6bN8Z5sk/axVc7vjl1z1BZwzFKwMCwRBUSiMUrWGKZUwlMyT7R5XSqdsOHZ9jTvnwxXtxuXOCGilsSwRBQESXQhNbvumUc4ifdEm/UUm3vtNyC6EG6cNeiaLuw8PkE7ErbB3eZ4C+7Cez4mLzGTdRLlInbDBQrDElG2eYxVSvjDXtrmTbIGRCcflOzveS5F4r5XojYk0NzUA0JRYu8vROwUBB7rxjmvk8R3RpRj2A0XLBwRSZQtrpBkLe8RnYzRq4oUMzu19do98Nk9waNo2prjMU5I6jI2jLjbkEic+8e00yMoxb1kc98ZB3wTkU9y5m+TvXv34pJLLkFRURG6du2KK664AgcOHEh4zsiRIyGEcGxXX311K7WYKEX2H+4J5klKZjmPmIqNlE1bIh5LkrgXrXXsSzYwxbl/wsqWa1kUO88pBhiOqC2RPm3ki5zphrvkkkuwa9curFy5EuFwGJdddhmuuuoqLFu2LOF506dPx2233Wa97tixY0s3lSh17sf8XRM2ugODY8C3+USZmRWE2S0VXcLEVb1JOOu2V0CJM2ap6Qk0MzA525FoNnDPMNdcO6xruYKS+ztDipNpEgURxywFSk6EpU8//RQrVqzAu+++i1NOOQUA8NBDD+Hcc8/F3Xffjd69e8c9t2PHjigrK2utphKlzPrhb68iuQdZe4gZ8G2OYbJXb4SIH0zMc4yLWde03SDRzc3GNxuajMM9rhVvoV3rnCT+pk/xOyMiSkdO1K0rKyvRtWtXKygBwJgxY6AoCt5+++2E5z777LPo0aMHjj/+eMyZMweHDh1KeHxDQwPq6uocG1GrsY/rMcfjJCB1aQQXe3eYfbN3f2m6sZnvaZp1rtW1Zl7LY7xSTBec8Wb8a2ia7V7Re9vb426r7XrxgpKjqmQf3J7Kwr9EOUD4tJE/cqKyVF1djZ49ezr2hUIhdOvWDdXV1XHPu/jii9G3b1/07t0bGzZswE033YRNmzbhL3/5S9xzFi5ciAULFvjWdqKkNDNPUFKTLXpVgjx6pJKpHjV3L/v7VoAxq1Oa9QYAzVn9aukeMs63RG0Fu+ECJath6eabb8add96Z8JhPP/007etfddVV1u9POOEE9OrVC6NHj8aWLVtw9NFHe54zZ84czJ4923pdV1eHPn36pN0GoqTYpwFwSzB2CfCef8kz7KS4EG0yEz16PiVnne8Vnpq/T1JVpXjYDUdELSCrYen666/HtGnTEh7Tv39/lJWVYffu3Y79kUgEe/fuTWk80vDhwwEAmzdvjhuWCgoKUFBQkPQ1iXzVzNNq8Z6Oay4cpToHUVLBJEGA876n5rx29PoJB3HHvuFxIwYkans4z1KwZDUslZSUoKSkpNnjRowYgX379mH9+vUYNmwYAOCNN96ArutWAEpGVVUVAKBXr15ptZeoRXlVl8xBy7aFZ91iJmWM9yRZogHb7qkKEkxd0HQ55wK+yUxp4A5H1qDw5u7nDklex7GqRG0Ju+ECJScGeA8cOBDjxo3D9OnT8c477+Bf//oXZs6cicmTJ1tPwu3cuRPHHXcc3nnnHQDAli1bcPvtt2P9+vX44osv8Ne//hVTpkzBOeecgxNPPDGbH4colnuAtp17okX3lsy14wUY94SO9teqarxW1dhNKBCq6j0pZKJ2JWqLR7s8r+W12G4yQY2IKE05McAbMJ5qmzlzJkaPHg1FUXDRRRfhwQcftN4Ph8PYtGmT9bRbfn4+Xn/9ddx///04ePAg+vTpg4suugi33nprtj4CkVN0yRDPRXLNH/5e0wrY2eZjcl66mfDgXmLFXtlxPWnmtWyJFNEn26BCCBl9gq2p0iSbqYbFfHavtjU3Zqq5yhmDE+U6VoYCI2fCUrdu3RJOQNmvXz9I29iFPn36YM2aNa3RNCJfGMHB2S3l4LXorK2bzr6ArDWWyB6kPNag8wxJ9oBkTWNga4+uG1Wn6P9vRnASjtAkVNi6Az1Ck0e3mz20xV3zzmt8kq3bMZlB6US5gGOWgiVnwhJRW2aGnLg/8KOhwbEArhVkkHi8TqLxSPZwYoYkIZrCkXBVtnRpdMMBVnAR0cVvHaEJAKRwBkCoyU80Kewhyrbgrn2hXRv790dE5LecGLNE1Oa5Jnf0HsitOH5vbka4Eda4IWsMkapCqCqUvBCUvBBEKA8iPx8iPy+6uX6flweEQkBeCFAViFDIuoYQirGZr1UVImQch7wQEApB5MW7fr6xhfKMdtiuYR/v5K5sWZ/P9nm9vrd4k2kS5bR01oHz2lK0du1anHfeeejduzeEEHjxxRedzZISc+fORa9evdChQweMGTMGn332meOYZNZy3bBhA84++2wUFhaiT58+WLRoUeqNbUUMS0RBFXe8UYKuJttAa8eAa1U1ApA9qDgGbAsj+EQrSCLJRWmFvTKlRoOb7bqO+ymiaZ9XG+PfxHs/gxG1YWY3XKZbqg4ePIghQ4bgkUce8Xx/0aJFePDBB7F48WK8/fbb6NSpEyoqKlBfX28dc8kll+Djjz/GypUr8fLLL2Pt2rWOeQ/r6uowduxY9O3bF+vXr8ddd92F+fPn4/HHH0+9wa2E3XBEAWEf6C31aLXFazoBWzeU55pr7uChRqszZveZWY0CYq6dbEjyOkdK3Xk9HUZoktIa5yR1Pdpt2NwyLnpTJclrnJK9241jlqgtytLUAePHj8f48eO9Lycl7r//ftx66604//zzAQBPP/00SktL8eKLL2Ly5MlJreX67LPPorGxEU8++STy8/MxePBgVFVV4d5773WEqiBhZYko25KskLiDkfU63qSMitE9JxQlWtlpqjBZ75nda7bAk+4GwHk9RTSNP4pWr4RZxTLf8/ygZhDy+LycgJIoa7Zu3Yrq6mqMGTPG2ldcXIzhw4ejsrISQHJruVZWVuKcc85Bfn6+dUxFRQU2bdqEb775ppU+TWpYWSIKOl0a/6wRIraSZIaHeAOb7YvM2gdNuypIZtiJfRw/0cDx2Ak0pdSta1sBTIku3qsoRoXJHLAdr2KkRAdxe31erzYStUF+Pg3nXhA+3ZUqzLVYS0tLHftLS0ut95JZy7W6uhrl5eUx1zDfO+KII1JuW0tjZYkooGIGeksZu8WbkNE9BYBiG1uE2AqSdR3zuppmbLretHm91rSYtnhVnKwKk23AtlVhavrAxq/utrg/b/RYPvlGbZqPA7z79OmD4uJia1u4cGGrfpS2gJUloqCTevwxPl4TMQol+oh/nCVBHOOKzPBhjCuK1wWWiDArRGYYMk/1uo9Xe+yfw/55kv3MRJTQjh07UFRUZL1Od/1Tcy3Wmpoax7JhNTU1GDp0qHVMc2u5lpWVoaamxnGM+TqV9V5bEytLRNlidoUlGFTtmInbtUlNsxbRtW9NwUM2hR57t5dZudFs1SFNi17PuK5nVSfO5jjPsemuylc0kME1/ihaJYrZNM3zczu+l2S+X6Jc5GNlqaioyLGlG5bKy8tRVlaGVatWWfvq6urw9ttvY8SIEQCca7ma3Gu5jhgxAmvXrkU4HLaOWblyJQYMGBDILjiAYYko8DyDhHtuoURLfVghSY/tYjPDjhmQ7AEnJvx4bPbg5b6W2VVndaHZgpJXO83XrjmnPD87URuXrakDDhw4gKqqKmvh+a1bt6Kqqgrbt2+HEAKzZs3Cr3/9a/z1r3/Fhx9+iClTpqB3796YOHEigOTWcr344ouRn5+PK664Ah9//DGWL1+OBx54ALNnz/bp2/Mfu+GIcolHF1TTEidNy4s0TTvQFE6EohjhBbbAYo4DSrdry36eFv1VKMbSQ+as4+6pDlyD0t2P/xuXEM7rs0pE1Cree+89jBo1ynptBpipU6di6dKluPHGG3Hw4EFcddVV2LdvH8466yysWLEChYWF1jnNreVaXFyM1157DTNmzMCwYcPQo0cPzJ07N7DTBgCAkPYF1ShGXV0diouLMRLnIyTyst0cakvMp8ZU1aqiuJckcbAFk3jVFfv5XoviOp5A8wgpCa/paEoSx9vvbecepN1MGxz3T/C92L+/ZhcSJkpTRIaxGi+htrbWMQ7IL+bPnCFTfgM1v7D5ExLQGuvx76dvabG2tiesLBEFRMKgZBMTKsxB3bAFBmtiS/vg8NgAETdUeCx0625rvHPNhXOFohvVJvfnsYcjr6Bk+zyOzxRPdLFgTkhJbYmQ0lGVTfca5A+GJaIgiRNSpC4doSCVwARojuulVXUxw0sy55gByApKce7v9dpzTTyPBYDd50e/GyKilsCwRBQwyVRIUglMxmvvMGG/RkwXXvT3rhvbfht77ZjrxQQnxO9OTCMomfs46JvaHNvTbBldg3zBsESUDbYf/sYPe1dXkiukeAUT97XcHIOlkx0XZL+W/fdecybZqzkeVS/3vczPELcdzXQ/xg1w5n3NQGZvBytOlKP8nMGbMsewRBQU9nmX3OHEHUxgD1CJ/0ZMuuriVVHyqnKZ+6LtShjk0mkHElSUvNpl3tf+/TEgEZGPGJaIgsSrumJOA+AIJs7urky6oayn5uxtSGawtBWanEFOKJktReLuamv26TrzPWvuAqI2gN1wgcKwRBRU5kK1UjYFJvMts+sOSDzo2/O69nFHwvn7dOczcoWkRE/LxWuLoz3xKkrWgbbvhqgNYjdcsHCmN6KgcVdPzGCQSZhJxN795nV/U7xqkV+Bqzn2+aLi3J+IqCWwskQUNO7Fbl0zXsdINKVAKrxCjvt69tcxoS7OWKEkxxA1O8+U+b3YZgf3bCNRW8BuuEBhWCIKKvds23GPS28wc9wqUDLdeUJJ3KZMxi65JqX0Psb/74MoSNgNFyzshiPKopiFYc0f9LqtmtTMXEQ+NibuvphFbBMc26JtM78P3VVti5lFnD8liMg/rCwRBY1ZWfEIAokGcacaEIyJK+NUcRLMy+ReuDfe+anOFO5Y1iT6HXjNFWXdk+u/UVvGbrhAYVgiygZ3V5N9pm04J3A09ieuLiX9JFycthjryIn44csdVBA7S7h1Tor3tn8PMYHJ2u96gi+Z9e3i7SPKEexGCw6GJaJss/9Ad1VUPI9x7Pb427S5gBBnTJA9qCQMZ17LqsRrSzI8AhPgmm/JNo9TWp+ZiCgDDEtEAeFVqXG/7+PNrOBh3TNeEGn2UrHBKq3FehNdN8pdcXMfn8y6ekQ5QcrM5xHjPGS+YVgiCgD3emppTQOQZjBxB6YY7kf/4z2p1sz6c800IvG1bW11Ns35PXFgN7UVfBouWPg0HFEAtcoP/VTG+Ailacv0Wj5iOCKi1sDKElFQJDO/UCLmuWmEFL+6sNIOL37M+p3p90cUJHwaLlAYloiyzHMwtR+hyftmzR/nCh1eIaq5p/Os6ydzv0xxcDe1QUI3tkyvQf5gWCIKopaqkiS4pld1KV61yWtMlWdVqaUrPQxKRNQKGJaIssxzMHdAupPidc8FZqxQkuvOEeUcdsMFCsMSUQ5JZlyRL0EmzlxKMdf3Kag097kCE86IWgmfhgsWhiWiHJHsAOy0ph2IillexBaYPA6O/14KkvlcqUx8mcnnJyLywrBElG1CgVABqcV7O4sTLboHnGe5y8szNNkHo6tq1ttI5AtOShkoDEtE2Rat4GTyg97vSor9el6zivt5P6+JJpvjeUyiKhhRjmE3XLAwLBFli/2JtxYMI822wc01uDyptiRxneSblNpn91p4N26biIjSwLBElGW+ByN3SEi1C6254JPpdXwMVsZt+M9naoP4NFygMCwRZVOm8yklE1z8qLD4VaWJdx2fAxSrSpTr2A0XLMGYzCUJd9xxB8444wx07NgRXbt2TeocKSXmzp2LXr16oUOHDhgzZgw+++yzlm0oUaqSDTxeW1uW7udt698LEbW6nAlLjY2NmDRpEq655pqkz1m0aBEefPBBLF68GG+//TY6deqEiooK1NfXt2BLiYiIMmQ+DZfpRr7ImW64BQsWAACWLl2a1PFSStx///249dZbcf755wMAnn76aZSWluLFF1/E5MmTW6qpRKljNSQ5/J6onWA3XLDkTGUpVVu3bkV1dTXGjBlj7SsuLsbw4cNRWVkZ97yGhgbU1dU5NiIiImq/2mxYqq6uBgCUlpY69peWllrveVm4cCGKi4utrU+fPi3aTiIiohjSp418kdWwdPPNN0MIkXDbuHFjq7Zpzpw5qK2ttbYdO3a06v2JiIjMbrhMN/JHVscsXX/99Zg2bVrCY/r375/WtcvKygAANTU16NWrl7W/pqYGQ4cOjXteQUEBCgoK0ronERERtT1ZDUslJSUoKSlpkWuXl5ejrKwMq1atssJRXV0d3n777ZSeqCMiImp1ujS2TK9BvsiZMUvbt29HVVUVtm/fDk3TUFVVhaqqKhw4cMA65rjjjsMLL7wAABBCYNasWfj1r3+Nv/71r/jwww8xZcoU9O7dGxMnTszSpyAiIkoCxywFSs5MHTB37lw89dRT1uuTTjoJAPCPf/wDI0eOBABs2rQJtbW11jE33ngjDh48iKuuugr79u3DWWedhRUrVqCwsLBV205ERES5S0jJWasSqaurQ3FxMUbifIREXrabQ0REWRSRYazGS6itrUVRUZHv1zd/5pw5ZgFCocz+YR+J1ONfr89rsba2JzlTWSIiImo3/JiBm7UQ3+TMmCUiIiKibGBliYiIKGC43EmwMCwREREFjR9PszEs+YZhiYiIKGCElBAZjjnK9HxqwjFLRERERAmwskRERBQ0enTL9BrkC4YlIiKigGE3XLCwG46IiIgoAVaWiIiIgoZPwwUKwxIREVHQcAbvQGE3HBEREVECrCwREREFDGfwDhaGJSIioqBhN1ygsBuOiIiIMH/+fAghHNtxxx1nvV9fX48ZM2age/fu6Ny5My666CLU1NQ4rrF9+3ZMmDABHTt2RM+ePXHDDTcgEom09kfxHStLREREASN0Y8v0GqkaPHgwXn/9det1KNQUE375y1/ilVdewXPPPYfi4mLMnDkTF154If71r38BADRNw4QJE1BWVoY333wTu3btwpQpU5CXl4ff/OY3mX2YLGNYIiIiCposdcOFQiGUlZXF7K+trcXvf/97LFu2DN/97ncBAEuWLMHAgQPx1ltv4fTTT8drr72GTz75BK+//jpKS0sxdOhQ3H777bjpppswf/585OfnZ/Z5sojdcERERG1YXV2dY2toaIh77GeffYbevXujf//+uOSSS7B9+3YAwPr16xEOhzFmzBjr2OOOOw5HHXUUKisrAQCVlZU44YQTUFpaah1TUVGBuro6fPzxxy306VoHwxIREVHQSJ82AH369EFxcbG1LVy40POWw4cPx9KlS7FixQo89thj2Lp1K84++2zs378f1dXVyM/PR9euXR3nlJaWorq6GgBQXV3tCErm++Z7uYzdcERERAHj59pwO3bsQFFRkbW/oKDA8/jx48dbvz/xxBMxfPhw9O3bF3/+85/RoUOHjNqS61hZIiIiasOKioocW7yw5Na1a1d8+9vfxubNm1FWVobGxkbs27fPcUxNTY01xqmsrCzm6Tjztdc4qFzCsERERBQ05gDvTLcMHDhwAFu2bEGvXr0wbNgw5OXlYdWqVdb7mzZtwvbt2zFixAgAwIgRI/Dhhx9i9+7d1jErV65EUVERBg0alFFbso3dcEREREEjAWQ4dUCqC+n+13/9F8477zz07dsXX375JebNmwdVVfGTn/wExcXFuOKKKzB79mx069YNRUVFuO666zBixAicfvrpAICxY8di0KBBuPTSS7Fo0SJUV1fj1ltvxYwZM5KuZgUVwxIRERHhP//5D37yk5/g66+/RklJCc466yy89dZbKCkpAQDcd999UBQFF110ERoaGlBRUYFHH33UOl9VVbz88su45pprMGLECHTq1AlTp07Fbbfdlq2P5BshJedDT6Surg7FxcUYifMREnnZbg4REWVRRIaxGi+htrbWMWjaL+bPnO+edDNCamFG14po9Xjjg//XYm1tT1hZIiIiChoJHyal9KUlBA7wJiIiIkqIlSUiIqKgydJyJ+SNYYmIiChodADCh2uQL9gNR0RERJQAK0tEREQB4+dyJ5Q5hiUiIqKg4ZilQGE3HBEREVECrCwREREFDStLgcKwREREFDQMS4HCbjgiIiKiBFhZIiIiChrOsxQoDEtEREQBw6kDgoXdcEREREQJsLJEREQUNBzgHSg5U1m64447cMYZZ6Bjx47o2rVrUudMmzYNQgjHNm7cuJZtKBERUaZ06c9GvsiZylJjYyMmTZqEESNG4Pe//33S540bNw5LliyxXhcUFLRE84iIiKiNypmwtGDBAgDA0qVLUzqvoKAAZWVlLdAiIiKiFsJuuEDJmW64dK1evRo9e/bEgAEDcM011+Drr79OeHxDQwPq6uocGxERUeuSTYEp3Q0MS35p02Fp3LhxePrpp7Fq1SrceeedWLNmDcaPHw9N0+Kes3DhQhQXF1tbnz59WrHFREREFDRZDUs333xzzABs97Zx48a0rz958mT84Ac/wAknnICJEyfi5ZdfxrvvvovVq1fHPWfOnDmora21th07dqR9fyIiorRkWlXyoxuPLFkds3T99ddj2rRpCY/p37+/b/fr378/evTogc2bN2P06NGexxQUFHAQOBERZZfuQzcan4bzTVbDUklJCUpKSlrtfv/5z3/w9ddfo1evXq12TyIiIsptOTNmafv27aiqqsL27duhaRqqqqpQVVWFAwcOWMccd9xxeOGFFwAABw4cwA033IC33noLX3zxBVatWoXzzz8fxxxzDCoqKrL1MYiIiJondX828kXOTB0wd+5cPPXUU9brk046CQDwj3/8AyNHjgQAbNq0CbW1tQAAVVWxYcMGPPXUU9i3bx969+6NsWPH4vbbb2c3GxERBRunDgiUnAlLS5cubXaOJWn7g9GhQwe8+uqrLdwqIiIiautyJiwRERG1GxzgHSgMS0REREHDbrhAYVgiIiIKGgkfwpIvLSHk0NNwRERERNnAyhIREVHQsBsuUBiWiIiIgkbXAWQ4T5LOeZb8wm44IiIiogRYWSIiIgoadsMFCsMSERFR0DAsBQq74YiIiIgSYGWJiIgoaDiDd6AwLBEREQWMlDqkzOxptkzPpybshiMiIiJKgJUlIiKioJEy8240DvD2DcMSERFR0EgfxiwxLPmG3XBERERECbCyREREFDS6DogMB2hzgLdvGJaIiIiCht1wgcJuOCIiIqIEWFkiIiIKGKnrkBl2w3GeJf8wLBEREQUNu+EChd1wRERERAmwskRERBQ0ugQEK0tBwbBEREQUNFICyHTqAIYlv7AbjoiIiCgBVpaIiIgCRuoSMsNuOMnKkm9YWSIiIgoaqfuzpeGRRx5Bv379UFhYiOHDh+Odd97x+cPlHoYlIiIiAgAsX74cs2fPxrx58/D+++9jyJAhqKiowO7du7PdtKxiWCIiIgoYqUtftlTde++9mD59Oi677DIMGjQIixcvRseOHfHkk0+2wKfMHQxLREREQZOFbrjGxkasX78eY8aMsfYpioIxY8agsrLS70+YUzjAuxnmALkIwhlPpkpERLktgjCAlh887cfPHLOtdXV1jv0FBQUoKCiIOf6rr76CpmkoLS117C8tLcXGjRsza0yOY1hqxv79+wEA6/D3LLeEiIiCYv/+/SguLvb9uvn5+SgrK8O6an9+5nTu3Bl9+vRx7Js3bx7mz5/vy/XbC4alZvTu3Rs7duxAly5dIIRo1XvX1dWhT58+2LFjB4qKilr13m0Jv8fM8Tv0B79Hf2Tze5RSYv/+/ejdu3eLXL+wsBBbt25FY2OjL9eTUsb87PKqKgFAjx49oKoqampqHPtrampQVlbmS3tyFcNSMxRFwZFHHpnVNhQVFfEvVh/we8wcv0N/8Hv0R7a+x5aoKNkVFhaisLCwRe/hJT8/H8OGDcOqVaswceJEAICu61i1ahVmzpzZ6u0JEoYlIiIiAgDMnj0bU6dOxSmnnILTTjsN999/Pw4ePIjLLrss203LKoYlIiIiAgD8+Mc/xp49ezB37lxUV1dj6NChWLFiRcyg7/aGYSnACgoKMG/evLj9y5Qcfo+Z43foD36P/uD32LJmzpzZ7rvd3ITk4jFEREREcXFSSiIiIqIEGJaIiIiIEmBYIiIiIkqAYSkHfPHFF7jiiitQXl6ODh064Oijj8a8efN8m7SsPbnjjjtwxhlnoGPHjujatWu2m5MzHnnkEfTr1w+FhYUYPnw43nnnnWw3KaesXbsW5513Hnr37g0hBF588cVsNyknLVy4EKeeeiq6dOmCnj17YuLEidi0aVO2m0XtAMNSDti4cSN0Xcdvf/tbfPzxx7jvvvuwePFi3HLLLdluWs5pbGzEpEmTcM0112S7KTlj+fLlmD17NubNm4f3338fQ4YMQUVFBXbv3p3tpuWMgwcPYsiQIXjkkUey3ZSctmbNGsyYMQNvvfUWVq5ciXA4jLFjx+LgwYPZbhq1cXwaLkfdddddeOyxx/D5559nuyk5aenSpZg1axb27duX7aYE3vDhw3Hqqafi4YcfBmDM6NunTx9cd911uPnmm7PcutwjhMALL7xgzZBM6duzZw969uyJNWvW4Jxzzsl2c6gNY2UpR9XW1qJbt27Zbga1cY2NjVi/fj3GjBlj7VMUBWPGjEFlZWUWW0Zk/D0IgH8XUotjWMpBmzdvxkMPPYSf/exn2W4KtXFfffUVNE2Lmb23tLQU1dXVWWoVkVHhnDVrFs4880wcf/zx2W4OtXEMS1l08803QwiRcNu4caPjnJ07d2LcuHGYNGkSpk+fnqWWB0s63yMR5bYZM2bgo48+wp/+9KdsN4XaAS53kkXXX389pk2blvCY/v37W7//8ssvMWrUKJxxxhl4/PHHW7h1uSPV75GS16NHD6iqipqaGsf+mpoalJWVZalV1N7NnDkTL7/8MtauXYsjjzwy282hdoBhKYtKSkpQUlKS1LE7d+7EqFGjMGzYMCxZsgSKwqKgKZXvkVKTn5+PYcOGYdWqVdaAZF3XsWrVKq4dRa1OSonrrrsOL7zwAlavXo3y8vJsN4naCYalHLBz506MHDkSffv2xd133409e/ZY7/Ff96nZvn079u7di+3bt0PTNFRVVQEAjjnmGHTu3Dm7jQuo2bNnY+rUqTjllFNw2mmn4f7778fBgwdx2WWXZbtpOePAgQPYvHmz9Xrr1q2oqqpCt27dcNRRR2WxZbllxowZWLZsGV566SV06dLFGjdXXFyMDh06ZLl11JZx6oAcsHTp0rg/mPifLzXTpk3DU089FbP/H//4B0aOHNn6DcoRDz/8MO666y5UV1dj6NChePDBBzF8+PBsNytnrF69GqNGjYrZP3XqVCxdurT1G5SjhBCe+5csWdJsVzxRJhiWiIiIiBLgwBciIiKiBBiWiIiIiBJgWCIiIiJKgGGJiIiIKAGGJSIiIqIEGJaIiIiIEmBYIiIiIkqAYYmIiIgoAYYlIrL8/ve/x9ixY1v8PitWrMDQoUOh63qL34uIKFMMS0QEAKivr8d///d/Y968eS1+r3HjxiEvLw/PPvtsi9+LiChTDEtEBAB4/vnnUVRUhDPPPLNV7jdt2jQ8+OCDrXIvIqJMMCwRtTFPP/00unfvjoaGBsf+iRMn4tJLL4173p/+9Cecd955jn0jR47ErFmzYq5jX7S0X79++PWvf40pU6agc+fO6Nu3L/76179iz549OP/889G5c2eceOKJeO+99xzXOe+88/Dee+9hy5Yt6X1QIqJWwrBE1MZMmjQJmqbhr3/9q7Vv9+7deOWVV3D55ZfHPW/dunU45ZRT0rrnfffdhzPPPBMffPABJkyYgEsvvRRTpkzBT3/6U7z//vs4+uijMWXKFNjX7T7qqKNQWlqKf/7zn2ndk4iotTAsEbUxHTp0wMUXX4wlS5ZY+/7whz/gqKOOwsiRIz3P2bdvH2pra9G7d++07nnuuefiZz/7GY499ljMnTsXdXV1OPXUUzFp0iR8+9vfxk033YRPP/0UNTU1jvN69+6Nbdu2pXVPIqLWwrBE1AZNnz4dr732Gnbu3AkAWLp0KaZNmwYhhOfxhw8fBgAUFhamdb8TTzzR+n1paSkA4IQTTojZt3v3bsd5HTp0wKFDh9K6JxFRawlluwFE5L+TTjoJQ4YMwdNPP42xY8fi448/xiuvvBL3+O7du0MIgW+++abZa2uaFrMvLy/P+r0ZyLz2uacK2Lt3L0pKSpq9JxFRNrGyRNRGXXnllVi6dCmWLFmCMWPGoE+fPnGPzc/Px6BBg/DJJ5/EvOfuOvv88899aV99fT22bNmCk046yZfrERG1FIYlojbq4osvxn/+8x/87ne/Sziw21RRUYF169bF7H/ppZfwl7/8BVu2bMEdd9yBTz75BNu2bbO6+NL11ltvoaCgACNGjMjoOkRELY1hiaiNKi4uxkUXXYTOnTtj4sSJzR5/xRVX4O9//ztqa2sd+ydMmIBFixZh0KBBWLt2LR599FG88847eOaZZzJq3x//+Edccskl6NixY0bXISJqaULan+UlojZl9OjRGDx4cNKTP06aNAknn3wy5syZA8CYZ2no0KG4//77fW3XV199hQEDBuC9995DeXm5r9cmIvIbK0tEbdA333yDF154AatXr8aMGTOSPu+uu+5C586dW7Blhi+++AKPPvoogxIR5QQ+DUfUBp100kn45ptvcOedd2LAgAFJn9evXz9cd911LdgywymnnJL2BJhERK2N3XBERERECbAbjoiIiCgBhiUiIiKiBBiWiIiIiBJgWCIiIiJKgGGJiIiIKAGGJSIiIqIEGJaIiIiIEmBYIiIiIkqAYYmIiIgogf8PWdncMzNzxRcAAAAASUVORK5CYII=", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Transverse field |E|^2 at the output facet near 731 nm.\n", "fyz = sim_data[\"field_yz_output\"]\n", "f_target = float(td.C_0) / design_wavelength_um\n", "Ey0 = fyz.Ey.sel(f=f_target, method=\"nearest\")\n", "E2 = (\n", " np.abs(fyz.Ex.sel(f=f_target, method=\"nearest\").values) ** 2\n", " + np.abs(fyz.Ey.sel(f=f_target, method=\"nearest\").values) ** 2\n", " + np.abs(fyz.Ez.sel(f=f_target, method=\"nearest\").values) ** 2\n", ")\n", "E2 = np.squeeze(E2)\n", "y = np.asarray(Ey0.y.values, dtype=float)\n", "z = np.asarray(Ey0.z.values, dtype=float)\n", "fig, ax = plt.subplots(figsize=(6, 4.8))\n", "im = ax.pcolormesh(y, z, E2.T, shading=\"auto\")\n", "ax.set_xlabel(\"y (µm)\")\n", "ax.set_ylabel(\"z (µm)\")\n", "ax.set_title(r\"Transverse field $|E|^2$ at output facet\")\n", "fig.colorbar(im, ax=ax, label=r\"$|E|^2$ (a.u.)\")\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 15, "id": "xyfield01", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:39.948250Z", "iopub.status.busy": "2026-06-22T18:48:39.947993Z", "iopub.status.idle": "2026-06-22T18:48:40.231439Z", "shell.execute_reply": "2026-06-22T18:48:40.231117Z" } }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Cavity standing-wave field |E|^2 in the x-y plane (QW plane, z = 0).\n", "fxy = sim_data[\"field_xy\"]\n", "f_target = float(td.C_0) / design_wavelength_um\n", "E2 = (\n", " np.abs(fxy.Ex.sel(f=f_target, method=\"nearest\").values) ** 2\n", " + np.abs(fxy.Ey.sel(f=f_target, method=\"nearest\").values) ** 2\n", " + np.abs(fxy.Ez.sel(f=f_target, method=\"nearest\").values) ** 2\n", ")\n", "E2 = np.squeeze(E2)\n", "x = np.asarray(fxy.Ex.x.values, dtype=float)\n", "y = np.asarray(fxy.Ex.y.values, dtype=float)\n", "fig, ax = plt.subplots(figsize=(9, 4))\n", "im = ax.pcolormesh(x, y, E2.T, shading=\"auto\", cmap=\"magma\")\n", "ax.set_xlabel(\"x (µm)\")\n", "ax.set_ylabel(\"y (µm)\")\n", "ax.set_title(r\"Cavity field $|E|^2$ in the x-y plane (z = 0)\")\n", "fig.colorbar(im, ax=ax, label=r\"$|E|^2$ (a.u.)\")\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "K6R8kq6bd4Hk", "metadata": { "id": "K6R8kq6bd4Hk" }, "source": [ "### 1.8 Save the Output Mode Monitor Data\n", "\n", "The output mode-monitor amplitudes are written to a compact HDF5 file with Tidy3D's native serializer. A forward modal power/fraction summary is attached through the object's `attrs` dictionary." ] }, { "cell_type": "code", "execution_count": 16, "id": "WMT9BHWKeGXy", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.232966Z", "iopub.status.busy": "2026-06-22T18:48:40.232826Z", "iopub.status.idle": "2026-06-22T18:48:40.573507Z", "shell.execute_reply": "2026-06-22T18:48:40.573261Z" }, "id": "WMT9BHWKeGXy" }, "outputs": [], "source": [ "# Save the output mode-monitor data (amplitudes + forward modal summary) to a compact HDF5 file.\n", "# The stored mode fields are dropped here (they remain in sim_data.hdf5), and the extra\n", "# power/fraction calculation is attached via the native `attrs` dictionary.\n", "OUTPUT_MODE_HDF5_PATH = DATA_DIR / \"mode_output.hdf5\"\n", "\n", "mode_data = sim_data[\"mode_output\"]\n", "amps_fwd = mode_data.amps.sel(direction=\"+\")\n", "modal_power = np.moveaxis(\n", " np.abs(np.asarray(amps_fwd.values)) ** 2, list(amps_fwd.dims).index(\"f\"), 0\n", ")\n", "modal_fraction = modal_power / np.maximum(modal_power.sum(axis=1, keepdims=True), 1e-30)\n", "f_hz = np.asarray(amps_fwd.f.values, dtype=float)\n", "\n", "forward_modal_summary = {\n", " \"frequency_hz\": f_hz.tolist(),\n", " \"wavelength_um\": (td.C_0 / f_hz).tolist(),\n", " \"modal_power\": modal_power.tolist(),\n", " \"modal_fraction\": modal_fraction.tolist(),\n", "}\n", "\n", "stored_fields = {component: None for component in (\"Ex\", \"Ey\", \"Ez\", \"Hx\", \"Hy\", \"Hz\")}\n", "mode_data.updated_copy(\n", " attrs={\"forward_modal_summary\": forward_modal_summary}, **stored_fields\n", ").to_hdf5(str(OUTPUT_MODE_HDF5_PATH))" ] }, { "cell_type": "markdown", "id": "KcsxvELfhymX", "metadata": { "id": "KcsxvELfhymX" }, "source": [ "### 1.9 Conclusion\n", "\n", "This simulation provides a compact 3D FDTD model of an integrated **GaAs/AlGaAs quantum-well laser section** operating near **731 nm**.\n", "\n", "The active region is represented by three thin GaAs quantum wells embedded between AlGaAs barriers and cladding layers. A guided fundamental mode is launched from the input facet, while flux, mode, and field monitors are used to evaluate the optical response at the output.\n", "\n", "The key outputs are:\n", "\n", "1. **Power transfer spectrum** \n", " $$\n", " P_\\mathrm{out}/P_\\mathrm{in}\n", " $$ \n", " showing wavelength-dependent gain or loss.\n", "\n", "2. **Transmission in dB** \n", " useful for comparing propagation loss, facet loss, and net modal gain.\n", "\n", "3. **Output modal decomposition** \n", " confirming whether the transmitted field remains in the desired guided mode.\n", "\n", "4. **Electric-field profiles** \n", " verifying confinement and overlap with the quantum-well active region.\n", "\n", "Overall, this simulation serves as the integrated-laser building block before coupling the laser output into the rest of the photonic circuit." ] }, { "cell_type": "markdown", "id": "mvhwlIH2GtPk", "metadata": { "id": "mvhwlIH2GtPk" }, "source": [ "## 2. SiN Waveguide\n", "\n", "\n" ] }, { "cell_type": "markdown", "id": "msZxVn5Q_4BB", "metadata": { "id": "msZxVn5Q_4BB" }, "source": [ "### 2.1 Waveguide Design\n", "\n", "This section sweeps a rectangular SiN strip waveguide embedded in SiO2 and\n", "plots the TE00 / TE01 effective-index branches versus waveguide width. Members of our group have familiarity with AIM photonics foundry PDK and wanted to stick within their constraints in order to design a device that could be feasibly manufactured. Thus, we were limited to 220 nm thick SiN.\n", "\n", "We omit a schematic here, but the general shape is a rectangle of SiN surrounded by SiO2 cladding. We also assume that the SiN is far enough away from the substrate that we need not include a Si substrate in the simulation results." ] }, { "cell_type": "code", "execution_count": 17, "id": "ZhC2duDDGug1", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.575291Z", "iopub.status.busy": "2026-06-22T18:48:40.575127Z", "iopub.status.idle": "2026-06-22T18:48:40.617451Z", "shell.execute_reply": "2026-06-22T18:48:40.617129Z" }, "id": "ZhC2duDDGug1" }, "outputs": [], "source": [ "import h5py\n", "import xarray as xr\n", "import tidy3d.web.api.mode as mode_web\n", "from tidy3d.plugins.mode import ModeSolver\n", "\n", "SIN_SWEEP_DIR = DATA_DIR / \"sin_waveguide_sweep_h0220_te_modes\"\n", "SIN_SWEEP_HDF5 = SIN_SWEEP_DIR / \"passive_sin_mode_sweep.hdf5\"\n", "SIN_SWEEP_PNG = SIN_SWEEP_DIR / \"plots\" / \"neff_vs_width_te00_te01.png\"" ] }, { "cell_type": "markdown", "id": "G8w71qaEg6ZM", "metadata": { "id": "G8w71qaEg6ZM" }, "source": [ "We need to import a few more python libraries in order to continue. HDF5 (h5py) is a common compressed data format that members of the team have used in the past that allows for better storage and read time when compared to csv.\n", "\n", "We first build some helper functions in order to create our simulations." ] }, { "cell_type": "code", "execution_count": 18, "id": "a12SXgccVE-l", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.619224Z", "iopub.status.busy": "2026-06-22T18:48:40.619083Z", "iopub.status.idle": "2026-06-22T18:48:40.621220Z", "shell.execute_reply": "2026-06-22T18:48:40.620993Z" }, "id": "a12SXgccVE-l" }, "outputs": [], "source": [ "def sin_range(start, stop, step):\n", " values = []\n", " current = float(start)\n", " while current <= float(stop) + 0.5 * float(step):\n", " values.append(round(current, 6))\n", " current += float(step)\n", " return tuple(values)" ] }, { "cell_type": "markdown", "id": "j5bBO4qKKF9C", "metadata": { "id": "j5bBO4qKKF9C" }, "source": [ "#### Generating Data\n", "\n", "Simulation space, wavelengths of interest, number of modes, and resolution are all given as parameters. An option to run with or without substrate is given. td.ModeSpec() is a standard function from tidy3d." ] }, { "cell_type": "code", "execution_count": 19, "id": "BPjTRPLOVF6v", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.622424Z", "iopub.status.busy": "2026-06-22T18:48:40.622335Z", "iopub.status.idle": "2026-06-22T18:48:40.628112Z", "shell.execute_reply": "2026-06-22T18:48:40.627738Z" }, "id": "BPjTRPLOVF6v" }, "outputs": [], "source": [ "def sin_strip_mode_solver(\n", " width_um,\n", " *,\n", " height_um=0.220,\n", " wavelengths_um=(0.730, 0.735, 0.740, 0.745, 0.750),\n", " n_sin=2.0,\n", " n_sio2=1.444,\n", " n_si=3.8,\n", " include_si_substrate=False,\n", " waveguide_bottom_above_si_um=5.0,\n", " oxide_top_above_si_um=10.0,\n", " y_span_um=6.0,\n", " x_span_um=1.0,\n", " min_steps_per_wvl=20,\n", " num_modes=3,\n", " target_neff=1.7,\n", "):\n", " sin = td.Medium(permittivity=n_sin**2, name=\"SiN\")\n", " sio2 = td.Medium(permittivity=n_sio2**2, name=\"SiO2\")\n", " si = td.Medium(permittivity=n_si**2, name=\"Si\")\n", "\n", " core_bottom_z = waveguide_bottom_above_si_um\n", " core_center_z = core_bottom_z + 0.5 * height_um\n", " z_min = -1.0\n", " z_max = oxide_top_above_si_um\n", " z_center = 0.5 * (z_min + z_max)\n", " z_span = z_max - z_min\n", "\n", " core_box = td.Box(center=(0, 0, core_center_z), size=(td.inf, width_um, height_um))\n", " substrate_box = td.Box(center=(0, 0, -0.5), size=(td.inf, td.inf, 1.0))\n", " structures = [td.Structure(geometry=core_box, medium=sin, name=\"sin_strip\")]\n", " if include_si_substrate:\n", " structures.insert(\n", " 0, td.Structure(geometry=substrate_box, medium=si, name=\"si_substrate\")\n", " )\n", "\n", " sim = td.Simulation(\n", " center=(0, 0, z_center),\n", " size=(x_span_um, y_span_um, z_span),\n", " medium=sio2,\n", " structures=structures,\n", " sources=[],\n", " monitors=[],\n", " grid_spec=td.GridSpec.auto(\n", " wavelength=min(wavelengths_um),\n", " min_steps_per_wvl=min_steps_per_wvl,\n", " ),\n", " boundary_spec=td.BoundarySpec(\n", " x=td.Boundary.periodic(),\n", " y=td.Boundary.pml(),\n", " z=td.Boundary.pml(),\n", " ),\n", " run_time=1e-12,\n", " )\n", " mode_spec = td.ModeSpec(\n", " num_modes=num_modes,\n", " target_neff=target_neff,\n", " sort_spec=td.ModeSortSpec(\n", " filter_key=\"TE_fraction\",\n", " filter_reference=0.5,\n", " filter_order=\"over\",\n", " sort_key=\"n_eff\",\n", " sort_order=\"descending\",\n", " track_freq=\"central\",\n", " ),\n", " )\n", " plane = td.Box(center=(0, 0, z_center), size=(0, y_span_um, z_span))\n", " solver = ModeSolver(\n", " simulation=sim,\n", " plane=plane,\n", " mode_spec=mode_spec,\n", " freqs=td.C_0 / np.asarray(wavelengths_um),\n", " direction=\"+\",\n", " fields=(\"Ex\", \"Ey\", \"Ez\"),\n", " )\n", " return solver, core_box, substrate_box" ] }, { "cell_type": "markdown", "id": "6ndDQEhQKylA", "metadata": { "id": "6ndDQEhQKylA" }, "source": [ "One of the metrics to determine how well the mode is confined inside the waveguide. It is not used in plotting below, but helpful for characterizing sweeps." ] }, { "cell_type": "code", "execution_count": 20, "id": "npML_NT_VMXa", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.629406Z", "iopub.status.busy": "2026-06-22T18:48:40.629198Z", "iopub.status.idle": "2026-06-22T18:48:40.632372Z", "shell.execute_reply": "2026-06-22T18:48:40.631995Z" }, "id": "npML_NT_VMXa" }, "outputs": [], "source": [ "def box_intensity_fraction(mode_data, box):\n", " intensity = mode_data.intensity\n", " area = mode_data._diff_area\n", " lower, upper = box.bounds\n", " mask = None\n", " for dim in area.dims:\n", " axis = \"xyz\".index(dim)\n", " coords = np.asarray(intensity.coords[dim].values)\n", " dim_mask = (coords >= lower[axis]) & (coords <= upper[axis])\n", " mask = dim_mask if mask is None else np.logical_and.outer(mask, dim_mask)\n", " mask_da = xr.DataArray(\n", " mask.astype(float),\n", " coords={dim: intensity.coords[dim].values for dim in area.dims},\n", " dims=area.dims,\n", " )\n", " weighted = intensity * area\n", " total = weighted.sum(dim=area.dims)\n", " inside = (weighted * mask_da).sum(dim=area.dims)\n", " return np.asarray((inside / total.where(total != 0)).fillna(0.0).values)" ] }, { "cell_type": "markdown", "id": "y5sCOVUcLiqI", "metadata": { "id": "y5sCOVUcLiqI" }, "source": [ "Main function that runs the sweep for determining the effective index of the mode for the various wavelengths, and sizes of the waveguide. An option to only estimate costs prior to running is included. run_cloud and estimate_cost both default to false in order to prevent accidental use of cloud credits. Ensure that you run the function with estimate_cost set to True to get a cost estimate.\n", "\n", "Function can be explicitly run below.\n", "\n", "All data is saved as an hdf5 file here. We plot the results after we have the data and it is run as an entirely separate function utilizing matplotlib." ] }, { "cell_type": "code", "execution_count": 21, "id": "Y-Y_gEOnVSoL", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.633951Z", "iopub.status.busy": "2026-06-22T18:48:40.633668Z", "iopub.status.idle": "2026-06-22T18:48:40.644988Z", "shell.execute_reply": "2026-06-22T18:48:40.644592Z" }, "id": "Y-Y_gEOnVSoL" }, "outputs": [], "source": [ "def run_sin_waveguide_sweep(\n", " *,\n", " output_dir=SIN_SWEEP_DIR,\n", " widths_um=sin_range(0.02, 1.00, 0.02),\n", " height_um=0.220,\n", " wavelengths_um=(0.730, 0.735, 0.740, 0.745, 0.750),\n", " run_cloud=False,\n", " estimate_cost=False,\n", " cloud_max_workers=20,\n", " cloud_folder_name=\"Passive SiN Mode Sweep\",\n", "):\n", " output_dir = Path(output_dir)\n", " output_dir.mkdir(parents=True, exist_ok=True)\n", " mode_dir = output_dir / \"passive_sin_mode_data\"\n", " mode_dir.mkdir(parents=True, exist_ok=True)\n", " heights_um = (float(height_um),)\n", " widths_um = tuple(float(w) for w in widths_um)\n", " wavelengths_um = tuple(float(w) for w in wavelengths_um)\n", " shape = (len(widths_um), 1, len(wavelengths_um), 3)\n", "\n", " solvers, records = [], []\n", " for width_index, width_um in enumerate(widths_um):\n", " label = f\"w{int(round(1000 * width_um)):04d}nm_h{int(round(1000 * height_um)):04d}nm\"\n", " solver, core_box, substrate_box = sin_strip_mode_solver(\n", " width_um,\n", " height_um=height_um,\n", " wavelengths_um=wavelengths_um,\n", " )\n", " mode_path = mode_dir / f\"{label}.hdf5\"\n", " solvers.append(solver)\n", " records.append((width_index, core_box, substrate_box, mode_path))\n", "\n", " if estimate_cost:\n", " costs = np.full((len(widths_um), 1), np.nan)\n", " task_ids = np.full((len(widths_um), 1), \"\", dtype=object)\n", " solver_ids = np.full((len(widths_um), 1), \"\", dtype=object)\n", " for solver, (width_index, _, _, _) in zip(solvers, records):\n", " task = mode_web.ModeSolverTask.create(\n", " solver,\n", " task_name=f\"estimate_passive_sin_mode_w{int(round(1000 * widths_um[width_index])):04d}\",\n", " mode_solver_name=f\"w{int(round(1000 * widths_um[width_index])):04d}\",\n", " folder_name=cloud_folder_name,\n", " )\n", " task.upload(verbose=True)\n", " costs[width_index, 0] = web.estimate_cost(task.task_id, verbose=True)\n", " task_ids[width_index, 0] = task.task_id or \"\"\n", " solver_ids[width_index, 0] = task.solver_id or \"\"\n", " cost_path = output_dir / \"passive_sin_mode_sweep_cost_estimates.hdf5\"\n", " with h5py.File(cost_path, \"w\") as h5:\n", " h5.attrs[\"total_estimated_flexcredits\"] = float(np.nansum(costs))\n", " h5.create_dataset(\"wavelength_um\", data=np.asarray(wavelengths_um))\n", " h5.create_dataset(\"width_um\", data=np.asarray(widths_um))\n", " h5.create_dataset(\"height_um\", data=np.asarray(heights_um))\n", " h5.create_dataset(\"estimated_flexcredits\", data=costs)\n", " h5.create_dataset(\n", " \"task_id\", data=task_ids, dtype=h5py.string_dtype(\"utf-8\")\n", " )\n", " h5.create_dataset(\n", " \"solver_id\", data=solver_ids, dtype=h5py.string_dtype(\"utf-8\")\n", " )\n", " print(f\"Estimated total: {np.nansum(costs):.6g} FlexCredits\")\n", " if not run_cloud:\n", " return cost_path\n", "\n", " n_complex = np.full(shape, np.nan + 1j * np.nan, dtype=complex)\n", " mode_area = np.full(shape, np.nan)\n", " core_fraction = np.full(shape, np.nan)\n", " substrate_fraction = np.full(shape, np.nan)\n", " te_fraction = np.full(shape, np.nan)\n", " raw_paths = np.full((len(widths_um), 1), \"\", dtype=object)\n", "\n", " if run_cloud:\n", " mode_data_list = mode_web.run_batch(\n", " mode_solvers=solvers,\n", " task_name=\"passive_sin_mode\",\n", " folder_name=cloud_folder_name,\n", " results_files=[str(record[3]) for record in records],\n", " verbose=True,\n", " max_workers=cloud_max_workers,\n", " )\n", " else:\n", " mode_data_list = []\n", " for solver, record in zip(solvers, records):\n", " print(f\"Solving {record[3].stem} locally\")\n", " mode_data = solver.solve()\n", " mode_data.to_file(record[3])\n", " mode_data_list.append(mode_data)\n", "\n", " for mode_data, (width_index, core_box, substrate_box, mode_path) in zip(\n", " mode_data_list, records\n", " ):\n", " n_complex[width_index, 0, :, :] = np.asarray(mode_data.n_complex.values)\n", " mode_area[width_index, 0, :, :] = np.asarray(mode_data.mode_area.values)\n", " te_fraction[width_index, 0, :, :] = np.asarray(mode_data.TE_fraction.values)\n", " core_fraction[width_index, 0, :, :] = box_intensity_fraction(\n", " mode_data, core_box\n", " )\n", " substrate_fraction[width_index, 0, :, :] = box_intensity_fraction(\n", " mode_data, substrate_box\n", " )\n", " raw_paths[width_index, 0] = str(mode_path.relative_to(output_dir))\n", "\n", " hdf5_path = output_dir / \"passive_sin_mode_sweep.hdf5\"\n", " with h5py.File(hdf5_path, \"w\") as h5:\n", " h5.attrs[\"description\"] = \"Passive SiN strip waveguide mode sweep\"\n", " h5.attrs[\"units\"] = \"lengths in micrometers\"\n", " h5.attrs[\"tidy3d_version\"] = td.__version__\n", " h5.attrs[\"geometry\"] = \"rectangular_sin_strip_in_sio2\"\n", " h5.attrs[\"solver_backend\"] = \"cloud\" if run_cloud else \"local\"\n", " h5.attrs[\"num_modes\"] = 3\n", " h5.attrs[\"target_neff\"] = 1.7\n", " h5.attrs[\"mode_family\"] = \"te0\"\n", " h5.create_dataset(\"wavelength_um\", data=np.asarray(wavelengths_um))\n", " h5.create_dataset(\"width_um\", data=np.asarray(widths_um))\n", " h5.create_dataset(\"height_um\", data=np.asarray(heights_um))\n", " h5.create_dataset(\"n_eff_real\", data=np.real(n_complex))\n", " h5.create_dataset(\"n_eff_imag\", data=np.imag(n_complex))\n", " h5.create_dataset(\"mode_area_um2\", data=mode_area)\n", " h5.create_dataset(\"core_fraction\", data=core_fraction)\n", " h5.create_dataset(\"substrate_fraction\", data=substrate_fraction)\n", " h5.create_dataset(\"te_fraction\", data=te_fraction)\n", " h5.create_dataset(\n", " \"raw_mode_data_hdf5\", data=raw_paths, dtype=h5py.string_dtype(\"utf-8\")\n", " )\n", " print(f\"SiN waveguide sweep: {hdf5_path}\")\n", " return hdf5_path" ] }, { "cell_type": "markdown", "id": "6W4jy-aLMqws", "metadata": { "id": "6W4jy-aLMqws" }, "source": [ "Below, the first cell below estimates costs with the default parameters and the second cell runs the cloud sweep. Current values used ~3.5 credits at time of publication." ] }, { "cell_type": "code", "execution_count": 22, "id": "Iy-pKq87Vn9R", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.646556Z", "iopub.status.busy": "2026-06-22T18:48:40.646415Z", "iopub.status.idle": "2026-06-22T18:48:40.648900Z", "shell.execute_reply": "2026-06-22T18:48:40.648502Z" }, "id": "Iy-pKq87Vn9R" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SiN sweep results already exist; skipping cost estimate: /home/filipe/Desktop/GITHUB/tidyvernier-dual-ring-filter/tidy3d-community-library/notebooks/data/sin_waveguide_sweep_h0220_te_modes/passive_sin_mode_sweep.hdf5\n" ] } ], "source": [ "# Estimate the sweep cost only if the result file is not already on disk.\n", "if not SIN_SWEEP_HDF5.exists():\n", " run_sin_waveguide_sweep(\n", " output_dir=SIN_SWEEP_DIR, estimate_cost=True, run_cloud=False\n", " )\n", "else:\n", " print(\"SiN sweep results already exist; skipping cost estimate:\", SIN_SWEEP_HDF5)" ] }, { "cell_type": "code", "execution_count": 23, "id": "tB0ultChVtEb", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.650499Z", "iopub.status.busy": "2026-06-22T18:48:40.650261Z", "iopub.status.idle": "2026-06-22T18:48:40.652474Z", "shell.execute_reply": "2026-06-22T18:48:40.652189Z" }, "id": "tB0ultChVtEb" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Loading existing SiN sweep results from: /home/filipe/Desktop/GITHUB/tidyvernier-dual-ring-filter/tidy3d-community-library/notebooks/data/sin_waveguide_sweep_h0220_te_modes/passive_sin_mode_sweep.hdf5\n" ] } ], "source": [ "# Run the cloud sweep only if the result file does not already exist; otherwise reuse it.\n", "if not SIN_SWEEP_HDF5.exists():\n", " run_sin_waveguide_sweep(output_dir=SIN_SWEEP_DIR, run_cloud=True)\n", "else:\n", " print(\"Loading existing SiN sweep results from:\", SIN_SWEEP_HDF5)" ] }, { "cell_type": "markdown", "id": "0yNeZJzbjMjW", "metadata": { "id": "0yNeZJzbjMjW" }, "source": [ "#### Plotting Results\n", "\n", "Here we plot effective index of the waveguide in order to determine a good candidate for the width of the waveguide for our specific wavelengths of light we wish to transmit." ] }, { "cell_type": "code", "execution_count": 24, "id": "eOhCUJK_VaXw", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.653710Z", "iopub.status.busy": "2026-06-22T18:48:40.653605Z", "iopub.status.idle": "2026-06-22T18:48:40.656261Z", "shell.execute_reply": "2026-06-22T18:48:40.655918Z" }, "id": "eOhCUJK_VaXw" }, "outputs": [], "source": [ "def select_te_branch(neff_values, te_values, order, te_threshold=0.5):\n", " y_values = np.full(neff_values.shape[0], np.nan)\n", " for width_index in range(neff_values.shape[0]):\n", " te_like = np.where(te_values[width_index] >= te_threshold)[0]\n", " if len(te_like) <= order:\n", " continue\n", " mode = te_like[np.argsort(neff_values[width_index, te_like])[::-1]][order]\n", " y_values[width_index] = neff_values[width_index, mode]\n", " return y_values" ] }, { "cell_type": "code", "execution_count": 25, "id": "ZT6QisqgVkeK", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.657447Z", "iopub.status.busy": "2026-06-22T18:48:40.657329Z", "iopub.status.idle": "2026-06-22T18:48:40.661621Z", "shell.execute_reply": "2026-06-22T18:48:40.661292Z" }, "id": "ZT6QisqgVkeK" }, "outputs": [], "source": [ "def plot_sin_neff_width(\n", " input_hdf5=SIN_SWEEP_HDF5, output_png=SIN_SWEEP_PNG, include_te01=True\n", "):\n", " input_hdf5 = Path(input_hdf5)\n", " output_png = Path(output_png)\n", " with h5py.File(input_hdf5, \"r\") as h5:\n", " widths_um = np.asarray(h5[\"width_um\"])\n", " height_um = float(np.asarray(h5[\"height_um\"])[0])\n", " wavelengths_um = np.asarray(h5[\"wavelength_um\"])\n", " n_eff = np.asarray(h5[\"n_eff_real\"])\n", " te_fraction = np.asarray(h5[\"te_fraction\"])\n", "\n", " output_png.parent.mkdir(parents=True, exist_ok=True)\n", " fig, ax = plt.subplots(figsize=(8.0, 5.0), constrained_layout=True)\n", " colors = plt.get_cmap(\"viridis\")(np.linspace(0.08, 0.92, len(wavelengths_um)))\n", " for wavelength_index, (wavelength_um, color) in enumerate(\n", " zip(wavelengths_um, colors)\n", " ):\n", " neff_values = n_eff[:, 0, wavelength_index, :]\n", " te_values = te_fraction[:, 0, wavelength_index, :]\n", " ax.plot(\n", " widths_um,\n", " select_te_branch(neff_values, te_values, 0),\n", " marker=\"o\",\n", " markersize=3,\n", " linewidth=1.6,\n", " color=color,\n", " label=f\"TE00 {1000 * wavelength_um:.0f} nm\",\n", " )\n", " if include_te01:\n", " te01 = select_te_branch(neff_values, te_values, 1)\n", " if np.any(np.isfinite(te01)):\n", " ax.plot(\n", " widths_um,\n", " te01,\n", " marker=\"s\",\n", " markersize=2.8,\n", " linewidth=1.35,\n", " linestyle=\"--\",\n", " color=color,\n", " alpha=0.9,\n", " label=f\"TE01 {1000 * wavelength_um:.0f} nm\",\n", " )\n", " ax.set_xlabel(\"SiN width [um]\")\n", " ax.set_ylabel(\"n_eff\")\n", " ax.set_title(f\"SiN strip: n_eff vs width, height={height_um:.3f} um\")\n", " ax.grid(True, alpha=0.3)\n", " ax.legend(title=\"Wavelength\", fontsize=8)\n", " fig.savefig(output_png, dpi=180)\n", " plt.show()\n", " print(f\"Saved {output_png}\")\n", " return output_png" ] }, { "cell_type": "code", "execution_count": 26, "id": "iaSerBqpVvo8", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.662922Z", "iopub.status.busy": "2026-06-22T18:48:40.662784Z", "iopub.status.idle": "2026-06-22T18:48:40.858317Z", "shell.execute_reply": "2026-06-22T18:48:40.857992Z" }, "id": "iaSerBqpVvo8" }, "outputs": [ { "data": { "image/png": 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ExMQWj6vt3bntttuYM2dOo/0X2qbmJh1o7t40d98vxTMnxK+dBCtCiLOqTUrNzMw8p+OeeOIJZs2axYwZM85p+tzo6Gj+/Oc/8+c//5kjR44QHx/Pv/71L+eUpRc6W1F9KSkpqKrqUmft4nOtWTn9UgkICMBsNmO3253Tr15qo0eP5qGHHnIOBTt8+DDPPfdco3K+vr7cd9993HfffVitVgYOHMj06dNbDFagpndl48aNREVFER8fj9lspmfPnlgsFr7//nt+/vnnJmckqy8iIoI1a9ZgtVpdeldqh5fVdzGfk4vlQt7X2tndUlJSGu1raltrtXSf+vbt26qhiy+++KJzBsD4+HgAkpKSuPXWW51lkpKScDgczv0tqaio4Pbbb+fw4cP8+OOPLfbobtu2jTFjxtCnTx8WLVqETtf4q82FtsnHx6fRjHNAq4d1CiHOn+SsCCGc1q1b1+Rv+L777jvg3Ifa1PauLFu2jOTk5LOWLysra7TydHR0NGazmcrKSuc2Dw+PJr84nI+MjAy+/vpr5+vi4mI+/vhj4uPjXYaAtXbq4otFq9UyduxYvvzyS/bt29do//lMg3w23t7eDB8+nEWLFvHFF1+g1+sZPXq0S5m8vDyX156ennTs2NHl/WnODTfcQFpaGgsXLnQOC9NoNFx33XX8+9//prq6usV8FYBbb70Vm83Gu+++69xmt9ubXIncw8MD4KI9KxfDhbyv7dq1o3v37nz88cdYrVbn9g0bNjinxT0fLd2n88lZGTp0KL6+vi7vEcC7776Lu7s7t912m3Nbbm4uBw8epKyszLnNbrczYcIEtmzZwuLFi+nfv3+zbT9w4AC33XYbkZGRrFixotle1XNpU1Oio6MpKipiz549zm2ZmZkunx1CiEtDelaEEE6PPvooZWVljBkzhtjYWKqqqvjpp59YuHAhkZGR3HfffedcZ23uyu7du51fippz+PBhhg0bxu9+9zu6du2KTqfj66+/Jisri4kTJzrL9e7dm3fffZeXX36Zjh07EhgYyNChQ8+5bVCTnzJlyhR27NhBUFAQ8+bNIysriw8//NCl3LlOXXwxvP7666xbt45+/frxwAMP0LVrV/Lz8/n555/58ccfyc/Pv+jnnDBhApMmTeKdd95h+PDhjXrEunbtyuDBg+nduze+vr4kJSWxZMkSpk2bdta6awORQ4cO8eqrrzq3Dxw4kJUrVzrXAWnJ7bffzoABA3j22WdJS0tzrotTVFTUqGzv3r0BeOyxxxg+fDhardblOWqNtLQ0oqKiuOeeexqtd3K+LuR9ffXVV7njjjsYMGAA9913HwUFBbz11lt0797dJYA5Fy3dp/PNWXnppZeYOnUq48ePZ/jw4SQmJvLpp5/yyiuv4Ovr6yz71ltvMWPGDNatW+dcL+nPf/4zy5cv5/bbbyc/P9/Zo1qrdorhkpIShg8fTkFBAc8880yjtVKio6Odgc65tKkpEydO5K9//Stjxozhscceo6ysjHfffZfOnTtf1IkuhBBNuCJzkAkh2qSVK1eq999/vxobG6t6enqqer1e7dixo/roo4+qWVlZLmVbmrq4odrpPc82dXFubq46depUNTY2VvXw8FAtFovar18/ddGiRS7lTp8+rd52222q2WxWAec0xrXTBu/YsaNR3c1NXXzbbbepP/zwg9qjRw/VYDCosbGxTV7DuU5d3LANtfdn3bp1Z62jvqysLHXq1KlqWFiY6ubmpgYHB6vDhg1T33vvPZdyXODUxbWKi4tVk8mkAuqnn37aaP/LL7+sXnPNNaq3t7dqMpnU2NhY9ZVXXmlyeuumBAYGqoDL87Rp0yYVUG+44YZG5ZuaMjYvL0+dPHmy6uXlpVosFnXy5Mnqrl27Gk3za7PZ1EcffVQNCAhQFUVxTjHb0n2hwTS8e/fuVQH12WefPeu1NfUeqGrjfyuq2rr3tampi1VVVb/44gs1NjZWNRgMavfu3dXly5erY8eOVWNjYxsd25prbO4+Xaj33ntPjYmJUfV6vRodHa3+5z//cZnOW1XrPhvq/7sYNGhQi9MkN7zG5n4a3vPWtqk5q1atUrt3767q9Xo1JiZG/fTTT5uduri1/xZb+twUQtRQVFWyuoQQv02RkZF0796dFStWXOmmiDbqnXfe4S9/+QtHjx5ttPhoWxIfH09AQACrV6++0k0RQoiLSnJWhBBCiGasW7eOxx57rM0EKtXV1dhsNpdt69evZ/fu3c5hVEII8WsiOStCCHGZWa3Ws+YXBAQEtHphS3HpLF68+Eo3wcWpU6e48cYbmTRpEu3atePgwYPMmTOH4OBgHn744SvdPCGEuOgkWBFCiMvsn//851mn6E1NTb2iUyeLtsnHx4fevXvzwQcfkJOTg4eHB7fddhuvv/46fn5+V7p5Qghx0UnOihBCXGbHjh3j2LFjLZa5/vrrMRqNl6lFQgghRNskwYoQQgghhBCiTZIEeyGEEEIIIUSbJDkrTXA4HGRkZGA2m1EU5Uo3RwghhBBCiF8VVVUpKSmhXbt2aDTN959IsNKEjIwMwsLCrnQzhBBCCCGE+FU7ceIEoaGhze6XYKUJZrMZqLl5Xl5eF1yfw+EgJyeHgICAFiNH8dskz4dojjwboiXyfIiWyPMhmtNWno3i4mLCwsKc37ubI8FKE2qHfnl5eV20YKWiogIvLy/5wBCNyPMhmiPPhmiJPB+iJfJ8iOa0tWfjbCkXV76FQgghhBBCCNEE6Vk5D3a7nerq6laXdzgcVFdXU1FR0SYi2N86Nzc3WRlcCCGEEOIqIMHKObJarZw8eZJzWZ5GVVUcDgclJSUyu1gboCgKoaGheHp6XummCCGEEEKIFkiwcg7sdjsnT57E3d2dgICAVgceqqpis9nQ6XQSrFxhqqqSk5PDyZMn6dSpk/SwCCGEEEK0YRKsnIPq6mpUVSUgIACTydTq4yRYaVsCAgJIS0ujurpaghUhhBBCiDZMEijOgwQcVzd5/4QQQgghrg4SrAghhBBCCCHaJAlWBADTp08nPj7+SjfDSVEUli5deqWbIYQQQgghriAJVi6zOXPmYDabsdlszm1WqxU3NzcGDx7sUnb9+vUoisLRo0cvcysvn7YWJAkhhBBCiLZDgpXLbMiQIVitVpKSkpzbEhMTCQ4OZtu2bVRUVDi3r1u3jvDwcKKjo69EU4UQQgghhLiiJFi5zGJiYggJCWH9+vXObevXr+eOO+4gKiqKrVu3umwfMmQIn3zyCX369MFsNhMcHMzvf/97srOzgZoFJ0NDQ3n33XddzrNr1y40Gg3Hjx8HoLCwkD/+8Y8EBATg5eXF0KFD2b17d4tt/eCDD+jSpQtGo5HY2Fjeeecd5760tDQUReGrr75iyJAhuLu707NnT7Zs2eJSx/vvv09YWBju7u6MGTOGf//733h7ewMwf/58ZsyYwe7du1EUBUVRmD9/vvPY3NxcxowZg7u7O506dWL58uWtvs9CCCGEEOLqJ8HKFTBkyBDWrVvnfL1u3ToGDx7MoEGDnNvLy8vZtm0bQ4YMobq6mpdeeondu3ezdOlS0tLSuPfeewHQaDTcddddfP755y7n+OyzzxgwYAAREREAjB8/nuzsbFauXMnOnTvp1asXw4YNIz8/v8k2fvbZZ7zwwgu88sorHDhwgFdffZW///3vfPTRRy7lnn/+eZ5++mmSk5Pp3Lkzd911l3OI2+bNm3n44Yd5/PHHSU5O5qabbuKVV15xHjthwgT+/Oc/061bNzIzM8nMzGTChAnO/TNmzOB3v/sde/bs4dZbb+Xuu+9utr1CCCGEEOJXSBWNFBUVqYBaVFTksr28vFzdv3+/Wl5efk71ORwOtaqqSnU4HKqqqur777+venh4qNXV1WpxcbGq0+nU7Oxs9fPPP1cHDhyoqqqqrlmzRgXU48ePN6pvx44dKqCWlJSoqqqqu3btUhVFcZa12+1q+/bt1XfffVdVVVVNTExUvby81IqKCpd6oqOj1f/973+qqqrqiy++qPbs2dNl3+eff+5S/qWXXlL79++vqqqqpqamqoD6wQcfOPf/8ssvKqAeOHBAVVVVnTBhgnrbbbe51HH33XerFovF+brheWsB6t/+9jfna6vVqgLqypUrG5U9V+f7Pl4qdrtdzczMVO12+5Vuimhj5NkQLZHnQ7REng/RnLbybDT3fbsh6Vm5AgYPHkxpaSk7duwgMTGRzp07ExAQwKBBg5x5K+vXr6dDhw6Eh4ezc+dObr/9dsLDwzGbzQwaNAiA9PR0AOLj4+nSpYuzd2XDhg1kZ2czfvx4AHbv3o3VasXPzw9PT0/nT2pqapPJ+6WlpRw9epQpU6a4lH/55Zcble/Ro4fz7yEhIQDOIWqHDh3immuucSnf8HVL6tft4eGBl5eXs24hhBBCCHHucjMLOZB0nNzMwivdlFaRFeyvgI4dOxIaGsq6desoKChwBh/t2rUjLCyMn376iXXr1jF06FBKS0sZPnw4w4cP57PPPiMgIID09HSGDx9OVVWVs867776bzz//nGeffZbPP/+cESNG4OfnB9TMNtYwT6ZWbf5IfVarFajJN+nXr5/LvoYrvru5uTn/XrvYosPhOPeb0oT6ddfWf7HqFkIIIYS42uVkFpKRmkO7qAACQrzPWv6HL7Yy+9mFqA4VRaPw+OsTGD7x2kvf0AtwRYOVjRs3MnPmTHbu3ElmZiZff/01o0ePbrb8vffe2yhnAqBr16788ssvQM1UuDNmzHDZHxMTw8GDBy9q2y/UkCFDWL9+PQUFBTzzzDPO7QMHDmTlypVs376dP/3pTxw8eJC8vDxef/11wsLCAFxmEqv1+9//nr/97W/s3LmTJUuWMGfOHOe+Xr16cfr0aXQ6HZGRkWdtW1BQEO3atePYsWPcfffd532NMTEx7Nixw2Vbw9d6vR673X7e5xBCCCGE+C1qGHg89trvGHBLT/KzisjNKqr583QR+VnF5GUVcTo9j9QDGTgMWuwmHdpyG28+t5Beg2JbFehcKVc0WCktLaVnz57cf//93HnnnWctP3v2bF5//XXna5vNRs+ePZ3DnWp169aNH3/80flap2t7HUhDhgxh6tSpVFdXO3tWAAYNGsS0adOoqqpiyJAh6HQ69Ho9//3vf3n44YfZt28fL730UqP6IiMjue6665gyZQp2u51Ro0Y59914443079+f0aNH849//IPOnTuTkZHBt99+y5gxY+jTp0+j+mbMmMFjjz2GxWJhxIgRVFZWkpSUREFBAU899VSrrvHRRx9l4MCB/Pvf/+b2229n7dq1rFy50tkDU9vu1NRUkpOTCQ0NxWw2YzAYzuVWCiGEEEJc1c7WQ2K32cnPKSE3s5DczELSDmXy+ewfQK3ZrzpUZv91IbP/urDF81QGe1Aa4wuKAqqKx6F8MtNyJFhpzi233MItt9zS6vIWiwWLxeJ8vXTpUgoKCrjvvvtcyul0OoKDgy9aOy+FIUOGUF5eTmxsLEFBQc7tgwYNoqSkxDnFMdRM8ft///d/vPnmm/Tq1Yt//vOfLsFIrbvvvptHHnmEP/zhD5hMJud2RVH47rvveP7557nvvvvIyckhODiYgQMHupy7vj/+8Y+4u7szc+ZMnnnmGTw8PIiLi+OJJ55o9TUOGDCAOXPmMGPGDP72t78xfPhwnnzySd566y1nmbFjxzqnPy4sLOTDDz90znQmhBBCCHG1OdehWd9+upm3/7akpodEgQG39MQvyELu6cIzwUkRBTnFOBxqo2Pr95JoKutGqugNbvgFW/AOMmMKMKP3NlHssLMpI6smUAFQFEpjfHHzdr9Yl35JKKqqNr7yK0BRlLMOA2vo9ttvp7KyklWrVjm3TZ8+nZkzZ2KxWDAajfTv35/XXnuN8PDwZuuprKyksrLS+bq4uJiwsDAKCgrw8vJybq+oqCAtLY2oqCiMRuM5XV91dXWjHIzfogceeIBDhw6xcePGK9aGiooKUlNTiYyMPOf38VJwOBzk5OQQEBCARiNzXog68myIlsjzIVoiz8eV8cPCrfz3ucXOoVnTXhlHvxu7k5NRcOansOYns5CcUwVkn8ynMM/abNDRFG9/T7z8PDlUWkp5tLezl0SXX0HvaztSpUCBtZycAiul5VWNjre7qdiNoK0AbbXC238dS68uYZfojjSvuLgYHx8fioqKXL5vN9T2xke1UkZGBitXrmy0vki/fv2YP38+MTExZGZmMmPGDG644Qb27duH2Wxusq7XXnutUZ4LQE5OjsuK8tXV1TgcDmw2m3MtkdZQVdWZl1F/CNRvwb///W+GDRuGh4cHP/zwAx9//DH//e9/z+n+XWw2mw2Hw0FeXl6bCCAdDgdFRUWoqir/oQgX8myIlsjzIVoiz8eFy88qJutEAUFhPvgGNf1lurrKRt7pYvJOF5N+6DSL3lrvMjTrv88t5r/PLW7xPA2HZrkfzicmxBe/SF8Usx6HXkuVRqHcYae4opr8knJSi8pQVf2ZwENFWwH4mdh25FST59BqFCyeBk4ZyrGGAwqggtdxMGrtV2S21ZKSklaVu2qDlY8++ghvb+9GPTH1h5X16NGDfv36ERERwaJFi5gyZUqTdT333HMueRi1PSu1q73XqqiooKSkBJ1Od155MG3hi/HltnPnTv71r39RUlJChw4dmD17Ng8++OAVbZNOp0Oj0eDn59dmelYURZHffolG5NkQLZHnQ7REno8L07CHZOQfric0OpDsk/k1PSKnCsg6mU9BTuMv3M31klj8PPEL8cY7xAuDvwdaLyMFlVUkpma4DM0q6+zLLkWB/AJoYS3scn8VawTOwMPjhErvkHb4B3mCQUO1zkE5NkpsVeRVlHGq1Iq1CnRuNtwMNqordZRE6vBp50egZ9O/0L+UWvsd7KoMVlRVZd68eUyePBm9Xt9iWW9vbzp37kxKSkqzZQwGQ5NJ3RqNxuUfuEajQVEU58+5tLe2/G+tZ2XRokVXugmN1L5/Dd/fK6mttUe0HfJsiJbI8yFaIs9HnebySKoqbWSfyifrRB6n0/M5fSKP9MOn2b52v7OM6lD5Zn5ii/Xr9Fr8Ar047qimrJOPs5fELb+cvgNiqEAlu8DKnvwSqqqtkGmFzDMHK0qjoVlnNuPr5UGArwdmXxNGsx6tuwaHXiG7qpTErPSaQAVAgdJw2EhGiwGOxddKUFh+bfPIOuHLieJi2ntZmj/oEmntc3lVBisbNmwgJSWl2Z6S+qxWK0ePHmXy5MmXoWVCCCGEEKKtcDgcfPX+eua9+g2qqoICXRIi0Gi1nD6RR35WMc2lbzfsIQkK9aFdp2BMgZ64+bijGnVUaqHUZiO3pIyMnCLKSioaDM1y56eDJ5qs39tswsdi4pfqPEpDcfaQ6ItV+saEU6pWkVVq5UhpNnZVBSs1P7UU114SW3XN13ovg4FgDw/8zQa8PbV4GhX0egclahEHytPrd+IQFJaP2dS2f5F+RYMVq9Xq0uNRO4Wtr68v4eHhPPfcc5w6dYqPP/7Y5bi5c+fSr18/unfv3qjOp59+mttvv52IiAgyMjJ48cUX0Wq13HXXXZf8eoQQQgghxKXTVA9JVaWNrBN5ZB7PPfNz5u/puWSm52GrsrsEHgd+Pt6oXoPRjcBQX/zDfNFZjKz/JY3Kdp7OHhKl0k61rwcHykohqxSymm5fw6FZnukqfULaE9TOC4waqnR2ylQbBdXlnLZa+bkkH5vqGnRUWXRsPp3eZP3+7u4Ee3pgcddyuPIAPoElzl6SynI9XfwCsTpyyK86Sp7qIA/ADpTXHK8o4KUtx8/NSl61J8V2E3Zt+QW+K5fWFQ1WkpKSGDJkiPN1bd7IPffcw/z588nMzCQ93fXNKioq4ssvv2T27NlN1nny5Enuuusu8vLyCAgI4Prrr2fr1q0EBARcugsRQgghhBCXTHlpJUv+t5YFs1c5e0JCOwRSWVFFbmZRs70j0DiB3XSskGv7ROMb5U+VVqHEZiO3uIwTuUXsLiqFwlJob3bpIdEqOkrK6maOdTe6EeLvha+fBx4+BrSeOvLsZazOTnMZmmWNgPWcgtymE9+h8dCsnAwLPbw7EuprxM3NgaqtoopySuwl5FVlUFBVQi4qvjQIPNwhtfxko/o9de4E6M0E6FXMrGeg5QiKAg4VvsmLJ8TUtr8jX9FgZfDgwS0+XPPnz2+0zWKxUFZW1uwxX3zxxcVomhBCCCGEuESa6iGprKgiIy2XjNQcTqXmkJGWW/Nnag752cWA69Csk8dcZ7AyuusJifAnINwPU7AZrcVIbkUl6w+luySwl0f7sK4gHwqaT+5o2ENizFa5PiYSDx8jhfYKsstK+aW4mJKqXNfhWc0MzTJodbQzmwnxcsfPrMVsUtAbHBQ7CthX5jo0K7B9EafZyelKoLJx22r18jzOKL9kNGcCj81FHQly702EyQ13rRU3ClHUfGyOLKrtOYDD5XiNAqP892DRlgPeZ3nHrpyrMmdFCCGEEEJcfew2O0vmrOWjmd/V9ZBEB1JRVkVuZmGLxzbsITGmF3PddTF4hfpQYqsmu6iU1JwidhYVwfGiugObSGDXaBTaBVgICvDCy8+Em1mLalQo19g5aS1iR1aGSw9JRRD8WJgGzTTRYjAS5OFOtjaNwHaFzl6ScquBPiFhlDlKyanMJM9eXjM0y3bmh6aHZgH46L0IMpgJNWoIMjjw01XjpSvDXWPFYT+J3ZbsDHI0CtzgnQKkgB3s9prRX2ej4KDCloZeF9KK0leGBCuXSW5mIVknCmjfIbBVq5m2Rnx8PABVVVUcOnSIuLg4AGJiYnjjjTeIjo52boOaWc+2bdsGwIoVK3j66aex2+3ExcUxf/585zTNLe2rb8yYMaSmpjpf79mzh6VLlzJq1Cjefvtt5syZg1arxWaz8eCDD/LYY48BNclujz/+ON999x2KovDEE08wbdq0i3JPhBBCCHF5NdVLYi0q4+SxbE4erfk5cebPU6nZ2G0O1x6So649JGZv95q6wv0wBnuieBnJKilj/YHjLj0kFREW1p46DadON9kuLw8jQX6e7K7IoTQMZy+JzqrSPTqI02VWkq3HUUuB0gYHN9FDEuntTUd/L3w8tXiYVHRuNmzaCsocVnKrCskqP0oQdpfAQzHDfmvjGWlNWgNBBh8CDRrM6o/OoVmqCplVFiI82qM6srE5cl0PtDljHOetqE+n8cOgi0CvDUavC0avDcFNG4ReGwKKhoNZ43HtYdFi1EU2ef/aijazgn1bUlxcjMViabSiZu3K51FRUbjp3MhvYm7tpmxYtpN5r69wztV9/3O3M2hUr1Yd6xtgRqvTtlgmLS2N+Ph4CgsLW9xWy2q1Eh0dzYYNG4iNjWXatGmYTCZmzpzZ4r6WJCUlMWLECDIyMtDr9RQVFWGx1EyDV1xcTPfu3Vm2bBkJCQl8/PHHfPTRR6xatYqioiISEhL47rvv6NatW6vuyYWq/z62lXVWsrOzCQwMlOklhQt5NkRL5PkQLbkcz4eqqiyZs5YPX1/h7CVp3yGAspJKCnKKmz2uUQ/J8SKuv74LXmE+lNhsZOaXcCKrgCJrRaNjG/aQWDyNRLX3xdvfA5O3HtWkoVxro9BeSYa1mNTCAspttiaHZtVn1OkI97LQ3uKBh8nBjqI9WPytzgDCbtNg0muoVlte1Lrh0KwfC7rgZ7qGaHc9XroyTEoROvKwOTKpsmWg0niF+aZp0Z8JOvS6ELSKFzmlC3CuQAmAhp7tNrfYS5JjXUha/v9R0++iJdL3VQI8J7SyDRdXc9+3G5KelfOUn1PCH/pNP+fjVIfK3FeWM/eV5a0q//G26RetJ6bWypUrSUhIIDY2FoBHHnmEm2++mZkzZ7a4ryVz585l0qRJznVvagMVgNLSUqqrq52vFy5cyAMPPIBWq8XX15cJEyawYMECXn75ZZc6awOuxx9/nBUrVlBUVMSbb77JrbfeCtTMH//yyy+zfPlysrKymDVrFgcOHODLL7+kqKiI999/n8GDB1/w/RJCCCF+C5pbi8Rud5B1Ip/0I6fP/GTV/Hn4NJUV1S69JKeO5bjUGdjeh/bRAfiE+6EP8CSnopLV+1Nde0givfnxZCaczKQpAT6eBPl5sr0k02WKX125imeIkQ3W01RV2pudoatRAnumhX7+nQnzM4GukgrKKKgu5HTFITJsNXnR3gENhmYpJqrVuh4JX70XwUYL4UYt7QwO/PQVGNSTuNldh2bd7HsAOFATU1TXpKC0kIZSd80ek/AyXoteF4Je2w43bSCK4vrLaw9Dz0aBx9mGcwV4TsCsv57TuckE+8dj1LdvRWuuLAlWfsVKSkqcQ8UAunXrxmeffUZ6ejoRERHO7ZGRkWRmZmKz2Vrcp9M1/biUl5ezYMECEhNdF0xasmQJL774IikpKbz66qskJCQANHmOrVu3Nll3UVERPXr0YMaMGXz//fc8/vjjzmAFwNPTk23btrFmzRruuOMO3nrrLZKSkli8eDHPPPMMO3bsaP0NE0IIIX6jfvhiK7OfXVgzCkRRuPbm7hiMbqSnZHEyJZuqyuomj2vUS5JWxMBBXfEK96GgsoqT2UVszsyn4uQpqJ2oqokcEk93A1HtfQkI8sLko0c1KZRrbeRXV5BeXMimwiyqvRsMzVJ0pBYVONui02hob/YiwtuLQIsbXh5QSgG7GiawtysilR2ktjBApmEPyS5rOB3M8bQzONCo2VTbk6iyZ+IcUlWbINLkkiUa9Np2GHTt0evao9e2r/m7tj0aRc/B7LtoODSrnWVqqwIPi3EgFbY0jLrIVued6HUhGDVa9LrAVpW/0iRYOU++AWY+3jb9rOXys4p4cvQsVEddN51Go/DvpU/gG3T21UJ9A8zn3Uaz2UxycvJ5H99aS5YsoXPnzi75MQDjxo1j3LhxpKWlMWbMGEaOHElMTMw51W00GrnzzjsB6N+/P0ePHnXZP2FCTddlnz59KC0tZeLEiQBcc801HDly5HwvSQghhLiq5WYWcmDXcTQJegLb+7rsU1WV3MxC0g5lknYwk4O7jvPT93tc9m/5YW+jOk0eBsI7BRESHYh7Owu5tmq+b9hLEuXNqvQMSM9odLzeTUs7fy8O2PKxhlPXQ1Kq4h9uZrs1F2tFRt3K7g007CHJPe3FgOBYQn0MVGvKKLIXc7riBNmVhWShtri2iAYNISY/Qo1ehJsg2FCNj64UD00hDnsqVdWuPSS9zelAOuVNdIsouKHX1fR+WCsb/pJUQ4+QjRjcQpu+KCDS97Vz7iFx3lNdSJtOjr8YJFg5T1qdtlXDswJCvHnstd/x3+cW4XCoaLQKj702gZj4iLMee6mEh4ezevVq5+u0tDRCQkLQ6XQt7mvO3LlzmTJlSrP7IyMj6devHytWrCAmJobw8HCOHz9O//79necIDw9v8liDwYBy5tNCq9Vit7vObVGbc6LVahu9ttlaHlcqhBBC/Bq59JJoFMY9OITAUF9ncHL8UCbW4sYLATZcsT1hcCzt4sNQzW5YVZXTRaUcO5XHlrxsyDuTFN9UL4lJT3S4P4FBXph8DNjdoVSp5nSFlcN5uVhLG/eQHMivGz6mURRCzV5E+lgI8dbj5aFgJZ+dpa49JAEhxRxmO4cLm74PNUns3oRoNzPc9xc0Z4Kck5U+RJvDcdgT6xLY6w3Tqq2/UX1uXfDQd0OvC8OgDcWgC0OvC0WvDXIO0WoqJ6SlQAXOv4fkt0KClctg+MRr6TmgI9knCxuNA70SRowYwdSpUzl48CCxsbG88847zh6JlvY1JSUlhaSkJJYvd83B2b9/P127dgUgJyeHtWvXMnbsWADGjx/P+++/z/jx4ykqKmLhwoWsWLHiEl2tEEII8etntzvITMth16bDvPPCl868a9WhsnjO2iaP0RvciOgcjF+oD+sOHqc83KtuxXabgzWUQfKhZs8Z4O1Bus7qsh6JzqoSFOXNjpI8ispOQRNL4zW1COKA4C5E+Bmxa8spcRSTWXGazPJfyMLhrKOpHhKjRk+4RxCRJiOhRgeB+nIs2mIMSi4Oewrl1amo9RqhKBBmLKCqusClTVrFjEEXgcEtAp3GhxzrZ7gmr2vpHDDvkg7NkiClaRKsXCb+Id4Eh/k7ewkuh4Y5KwCJiYmYzWY++OADRo8ejc1mo3v37nz00UcALe5ryrx58xg7dmyjWRxmz55NYmIier0eVVV54oknuOmmmwCYPHkyO3bsoFOnTiiKwlNPPdVoCJkQQgghmk56ryirJPVgJsd+OcWx/ac4duAUqQcyqSyvm1mqYS+Jf4iFzj0j8InyQ+PrTrkOsq3lpJzMZVtWIURYGqzYXpfMHeLvRWR7X/yCPNF5u1Gld5BnK+dwfi7WfKtrL4lZx77cukx3raIQbvEm2tebIG83bG4l7KrY1mgRxCNs5Uhh0/egdprfmh6Sfc4ekowqC1EewdjsJ3GoZ+YetkG1DZrOsKnj7zEBi/EGDLrwMwGK69B8D32cDM1qI2Tq4ia0Zuric5nyVlVVZ4L65QxWRNNk6mJxtZBnQ7REno9fP9ekd+gYF0aZtYKM1Fya+/rm4WUk313rkvSuK64kqlso6dmFVFY1PUS68YrtMDSuIzqLjmOF+aQU5FPRxPDqhr0k2Sd9GBAcS2SACVVbTrGjmFPlWZyuyMNRr6eicQ6JQjtTAGEmHzq4Q4ihAh9dMSYlF9VxgvKqozicy8Q3R4NB2x6DWyRGXSQGXQRajYW0/L/SMIG9Z7tNZw0oqmyZv8qhWW3ls0OmLhZCCCGEuEqoqkpeVhEpe06Ssu8Ev+xIJXnz4Xr74cieEy7HtIv0J6pLO3yjA9D4umPVqhzNzOfEwZN1hRQFm8XIkZN1iwt6uhuIDvUntL03Rj89mfZSlqUfarRi+3fZKeC6XiMebm509PUj0teMm6mUPfatLr0kQWEFpLCFlMKmr9NTa6Kz6QCj/HY7e0hSK/zp6hWNw7GDKvupmoJnVmE/W3gS4DEZb/fBGHSRGHShaBRDE6Uc59VLIj0kbYMEK0IIIYQQl4FzSFekPygKKXtPcGTvCVL2niRl7wkKmlhsuv5wLqXazg139cM3JohCu41jGfn8mJ5D+b7CRsfVT3rX2GDg9R0JjLBQolRzorSYvXm5/FhyEmpP2cSK7R18fOgRHECgtxajyYZdU0auLY/jZQc5WFUMjqbzSAACDT6EuwcQ7a4l1FiJn64Ik5JDtT2Z8uqDdXGRAh1MuVRUu67UrtP4YtRFYXTrgFEXhU7jQ1rB8zSe4veRS5ZHItoGCVaEEEIIIS6hgpwSFvx3Fd98lOias90Eg0lPdNf2BEb68d2uI1SE1SW9Ayw/lQmnGs/t6+VhoFN4IH4BHnyVeoDyQJxDugC+Kk+Bg43Pp9NoCPOykK9NJyi0wHmqqgodgV6FHKjezYFynNMA16cACfXWI1FVOFQeRLx3dxT1ABXVaTUrtNvBZneJixrxdb8Di/EGjG5RGHXR6LTeTZxQI3kkv0ESrAghhBBCXCQV5VWk7D3JoeTjHE4+zsHk42SfrJl5qmHSu8HoRse4MCK6tcPU3ptKdx2nS0o5dDybTZnZEN4g6b265mt+iL8XnSL8CWxnQWPRYtVWc9xaxK7cHLJK0yGocS8JQKCHBzF+/kT5eeDtpaLRV1DsKORY6Sn0FQWuPSQmEwXVxc7rCjb6EekeSCcPDaGGcnx0hejUo5RUJrv0ksS6Z1FR5bqUvEbxxOTWEZNbR3TaQE4Xv0vDmbbCvJ+VHhLRJAlWhBBCCCHOQe1wrpAIP8qtlRzanc6hXTWBSdrBTBx2R6NjGq70rs8uo+OAzpwoLWfT8XTUtPRGxzRMejfkqgzs2YEiqvgh9wTWzKNNLqDYMOm9uMCDgWEdsGvLSC1NYpu9HIpcj2m4YvuPBV3obBlAjAcYlUyqbD9RUX0UlWqwQcWZXPumekksxhuxmK7H6NYRk64jbtoglwmGjLoI6SERrSbBihBCCCFEK5QUlvLpf75n+fyWh3MpikJE52A69gzDOzqA01WVLE865LLSe1WQB9tTTjmP0SgKUe196RwRiCXEg9OqlcVpB1yS3isDYHXGMZdzmfUGugUEEh1gxt+iUKjmsKXIdfFEi28pu0tdV6Q3aPREeoTQycNCmCGTYJa5rNh+s+8B4ACVFXULJdbSaXwwuXVGrw0lr+wrGvaSRPq+1GJAIT0k4lxIsHIVq11DpaqqikOHDjnXKomJieGNN94gOjraZf0Sg8HAtm3bAFixYgVPP/00druduLg45s+fj5eXF1arlbFjx7Jz505sNhuFhYXNnn/MmDGkpqY6X+/Zs4elS5cyatQo3n77bebMmeNcSf7BBx/kscceA2qmzHv88cf57rvvUBSFJ554gmnTpl3kuyOEEEKcP1VVOXUsm/0709iflMr+pFROpNQMb2o4nMvb30yX3pG06xqCxt+DAoeNQydyWZaWReWW0zUVNrHSe9/u4XSKDcLuCTmOcg7m5fBF7iGq0uxnjmk8nCs+KJje4f54m1VUXRnZ1TkcLd1LUlWxs7ekqaT3bl4R9PW2EGYow0eXi0ZNo7w6kWr76WbvgYIRd31XTG6dMbl1xl0fg8mtMzpN3bpxZus1MtOWuKRknZUmXOx1VnIyCyjMK0Gr1aIoCmZvd/yDvS9ae9PS0oiPj3cJLJraVstqtRIdHc2GDRuIjY1l2rRpmEwmZs6cSWVlJZs3b8bX15fBgwe3GKzUl5SUxIgRI8jIyECv11NUVITFUrPAUnFxMd27d2fZsmUkJCTw8ccf89FHH7Fq1SqKiopISEjgu+++o1u3bhfhbpydrLMirhbybIiWyPNx4eovuOjl487h3Sc4kJTK/p2pHNiZRnFBaaNjGg7ncsspo1u/aE4WlJBb2Lg8QJCvmTRNscuQLm0l6Dy0VNrtTR4T7OFJuSGToLB6Se+VOnw8dJTZK5o8RqdoCTUFEqTdzC2+e51J70U2E95udqCqyeNAS02wUZ+GHiGbMLi1a+aYOr/W9Uh+rdrKZ4ess9JG5J4u5MlR/6GstNLZk2vyMDLrmycvasByLlauXElCQgKxsbEAPPLII9x8883MnDkTg8HA0KFDSUtLO6c6586dy6RJk9Dr9QDOQAWgtLSU6uq6tWQXLlzIAw88gFarxdfXlwkTJrBgwQJefvlllzprA67HH3+cFStWUFRUxJtvvsmtt94K1HSzv/zyyyxfvpysrCxmzZrFgQMH+PLLLykqKuL9999n8ODB53GHhBBC/Np9PXc97/+/Zc7FFRWNgupo/PtbnwAvuvSOJLRHe7IdNr7acdBlOFd1oAfJqXW9Ex4mPd06BBMV6Y+bnxtFuip255zGmlmXrI4CdiPYzwQqIZ6edA8MIjrAAy+zg2ptCUfL0jlU0iDpXTFRZq9JFnHXGung2Z4YTwvRpkoC3XLRc4KyquVU2TPqTqWAt1vdVF46jS/ubl0w6WNxd+uCu74LRreO5JUubdRD0ppABaSXRFxaEqxcoAeGvNrkdpOHgTdX/JmSwjLKrJVUlNf9NqO8tIqn73wTN4MOvyALr38xFagJbJ676x1nuffX/d8Fta2kpMQ5VAygW7dufPbZZ6SnpxMREeHcHhkZSWZmJjabDZ3u3B+J8vJyFixYQGJiosv2JUuW8OKLL5KSksKrr75KQkICQJPn37p1a5N1FxUV0aNHD2bMmMH333/P448/7gxWADw9Pdm2bRtr1qzhjjvu4K233iIpKYnFixfzzDPPsGPHjnO+HiGEEL8++dnF7N2awr7tx9iVeIhTqTmNhnMpCkR1bU9sr0gs0f5UeuhIzS5kW0oGK7b/UlNRE8O5rouPIrprIJUmlRPlRezOOs23WcfBdVKsekO6tIDChIRoQnw1nKw4zRHrNtIry1wSRBomva8u6Ep37xuI9XSgcRylrHo91fYssEGZDcpauP5Qy1/x87gTN22gS7J7LckjEW2VBCuXkaIoXM5Rd2azmeTk5Et+niVLltC5c2eX/BiAcePGMW7cONLS0hgzZgwjR44kJibmnOo2Go3ceeedAPTv35+jR4+67J8wYQIAffr0obS0lIkTJwJwzTXXcOTIkfO9JCGEEFeZ+kO6AkK8yckoYO/Wo+zdmsLe7Uc5dSzHpXzD4VyGkyUMvi2e3OpqlhzNpOLEiUbn8DQZyPGoaDCcS2Wl/jhVh481Km/Q6ogLCiLK18z6/J/wCbA6h3QpCiRVZUCDlBGzzp1O5jBijBXE6l2T3of77gf2U9IgKlHQY9LH4qHvhl4byqmif9Iw6d3PYzR6XVCL91B6SERbJMHKBWpN74eigIenEY1Og8PmwOFw8OK8PxIV69q96h/sfcG9Ka0RHh7O6tWrna/T0tIICQk5r14VqBkCNmXKlGb3R0ZG0q9fP1asWEFMTAzh4eEcP36c/v37O88fHh7e5LEGg8H5GyCtVuvsMq9Vm3Oi1WobvbbZbOd1PUIIIa4uP3yxldnPLnQO4/Ly8Wgy38TdbKRb3w6YI31ZcvS4y3CuyjAvftjjGnCEBXnTvVM7AsO8qPRwcKAwh9S0emVqh3M5av5vivT2IT44mMgAIyb3SorUPA6VHGVPeTa+gY2T3o0aPZ3N4XQx+9LRvZwAXQ6K4wilVauxOVxXdK87pREPQxzubt3w0HfDXd8do1tHNIqbs4yb1v+8pwYWoq2RYOUSM3u7Y/IwUFZaiaOqZt51k4cRs7f7FWvTiBEjmDp1KgcPHiQ2NpZ33nnH2SNxrlJSUkhKSmL58uUu2/fv30/Xrl0ByMnJYe3atYwdOxaA8ePH8/777zN+/HiKiopYuHAhK1asuLCLEkII8ZtSkFPC7p8Os3X1PjYs3+WyrzZQMXu70/2aDkQlRECAO6dKy9h16BRpx9KbHM4V1c6Xvj3C8QgyUay3sT8vm69OH8F6xDUxvf4MXaqqcHevjgT5KRwvO8WhknUcKKmqW679jIZDug6UhtDduyNu6k9U2U9BFRQ3l//upCEuZA0Gt/YtlgrwnIBZfz2nc5MJ9o/HqG+5vBBtmQQrl5h/sDf/Wf7kJZ0NrDkNc1YAEhMTMZvNfPDBB4wePRqbzUb37t356KOPnGV69OhBTk4OxcXFhIaGMmTIED755JMmzzFv3jzGjh3baBaH2bNnk5iYiF6vR1VVnnjiCW666SYAJk+ezI4dO+jUqROKovDUU081GkImhBDit6nhcK5aZdYK9m49SvLmwyRvPkzaQdfVEOvnnwAM+9NgbBYDuw6d4tttrmuMQOMFF/XFKiUdNPwvfze23MaLOoZ5WegaEECSNQm/4GKX4Vzbqk41Wpwx0OBLF69wupt1BGhTUKpch3R188xEtWU65+dS0OOu74aHvicehh546HtQUrGD4wV/wzXpvXWBh14XglGjRa8LbFV5Idoqmbq4CRd76mJVVZ3J600ltYnLS6YuFlcLeTZES36Nz0f94VyKRuHOB4egN+jYvekIh3Yfx25zDSJMngZi4iPYejyTsg7euEQQDXiY9MR3bk/HjgFYPe3M+SWp2XZoFYUuAYEkhAQR6qdDMZZyvPwk+4qOUeGobDScS6/o6OwVQTdzADEe5QToMrHb9mOt2o1DtTZ7HotxKN7uN+Kh74HJLcZlKFet850W+Nf4fIiLo608GzJ1sRBCCCGuGjkZBS55J6pD5cs5a13K6PRauvaOokv/aPSh3mSUlbN1XxplOp8zQ7rUM0O6wMOop1eXMDp2DED10ZBeWcz2UydZerwu56Thgot3dOlIjzAzldpCDpce5+eSn9me75or2XA41x5rKAk+XTCwlArbMaiEggZLvrtpgql2NFx8UUuk7ytnDUAk6V381kmwIoQQQogrorSkguTNh9m5/gBbVu1FdaiNphNu3yGAfjfH4RXtTy52dh06yXvJB7H/XDcwpOGQLkOuSo+e7dhVlsdXqSmQ6npeDzc9OnM+QWH5zs4Yu03LQbd0Dma7ltWgEOXZnjivUKIMJ/F2uA7nijefRLWdpHaZRgU9Hvo4PAy98DT0wlPfC70uiBzrQkl6F+I8SLAihBBCiEuiYf6Jqqoc23+KnesPkrThAPuTUl2GdjWcTlifU4b+hk58eiyNioMpLnXr3bT07NQe/1BPPs77BefKywpUBsCajLoIxaw3cE379sSF+GKxVHOq+gSJuXX1KQro3Gp6UAwaN2LNkcRZAolxL8VHm05l9WbKqvahqra689RjNlyLt+lmPA29cNd3RaPoG5WRdUyEOD8SrAghhBDionPJP1EUuvSOJPN4HgU5xS7l9AY3evSPJqx3BHN3HqjboShUBXqw89DJ2pfERATRq2so5nbunFZK2XrqJN9lHwel8ZCuXsHtGBwdisWrilxHNnuL9rGyLNdl5cT6uScKKn8Mj6aDeyGlVcuoqD6CWgH5Lq3VAA2T77V08PtPq4IPGdIlxLmTYEUIIYQQF42qquz+6Qiz//oFtVP4qKrK/qS6no7Q6EB6DYoloFsIOaqNHftPsOpMoNJwOuHrE6KISwil2FDNzqwM/peRTEW26zpaFl+ry5Cu8lIDnn6lfFu6FRost2LWuRNjDsPd/g3DfA645uSrq8mrV16jGPHQJ2A29MXTeA2e+njyy76V4VxCXEYSrAghhBDigthtdn7ZcYytq/exdfUvZB6vWdCwYf7J8HuuJ6hPOPtP5fD1vuMUHUtzqadh7omuVGW9ewZfN1isUaso9AwKpl9YO7y8y1ma871zn6KAu2clWZU1We6eOnfiLNEkWCx0NOWjVw9QXPEhNkeOyzE19VowG6/B09AXs6Ev7vrujWbokuFcQlxeEqwIIYQQokVNrX1SWlLBzxsOsnX1Prav3Y+1qMzlmIb5J5pKO1+kp6MeT3cp1yk8gL5x4SiBOmbt3Vq3QwGbJxRU1qSuR3n7MCA8jA6BBhyGYvaXHGVDyQ7sOTXDshpOJ3xnSDcG+CoY1YOUVH5Ilf0U1saL2ruI9n8Xi+m6s94PGc4lxOUjwcplkp1vJTOvhLBgH4J8zRelztoFH6uqqjh06JBzYcWYmBjeeOMNoqOjXRZbNBgMbNu2DYAVK1bw9NNPY7fbiYuLY/78+c45rlvaV9+YMWNITa3r1t+zZw9Lly5l1KhRvP3228yZMwetVovNZuPBBx/kscceA2D69Om8/fbbtG9fs7BVt27d+Oyzzy7KPRFCCHFxNVz7ZNCoBIrzS9mzJQVbdd20voqi0KVXJAlDY6kK8OB/322n3k4cRh2o4Olu4Jpu4cTGBlPhpbIzO4P3T+6mLKsaaJh7omVSQhc6tzeQWn6c3YVr2JFb7tI+HVp6eB5zTiesqlBq1+OpW0ZpqesoMJ3GH7OxH+5u3ThV9E9c80+0mNyiLv4NFEJcEFkUsgmtWRRS56Ynr+gsv6I5Y9WWg7y9aBOqWpNkOHXC9dx8bWyrjvWzeKDTtrxgT1paGvHx8RQWFra4rZbVaiU6OpoNGzYQGxvLtGnTMJlMzJw5s8V9LUlKSmLEiBFkZGSg1+spKirCYrEANfeze/fuLFu2jISEBKZPn05hYSGzZs1q1T242GRRSHG1kGdDtORyPB85mYXc03+Gc+2ThgxGN3oNjKHbwBgqfQzsOHyKpP3pVJ0JYurnn2hsMHp0AqqfhsT0NA7n57nUpQHMDXJP7DYFnVvjc3fwaE8vnyh6elbhrdlDftnCpibpQqvxxstwLWZjf7wM/TG6dXIuztzUVMIBnhMu4G61LfL5IZrTVp4NWRTyEssrKmXUE++f83GqqvLWF4m89UViq8ovn/XAReuJqbVy5UoSEhKIja0JmB555BFuvvlmZs6c2eK+lsydO5dJkyah19dM11gbqACUlpZSXV19zu2sDbgef/xxVqxYQVFREW+++Sa33norUPNbvJdffpnly5eTlZXFrFmzOHDgAF9++SVFRUW8//77DB48+JzPK4QQv2WqqpJ2KJNN3+5m9eLtTa590mdIF3rfHk+e1s7mPWl8++MOlzr0Og1F3naX/BNU+ODELjhRV87f3Z2BEZHEtfOi3C2bZafXO/fVTCdcE6j46S0k+HSmj8VImOEU1dVJlFR8gFpRRQFNziZMpM/r+Hv+DkVp+suY5J4IcXWQYOVXrKSkxDlUDOqGW6WnpxMREeHcHhkZSWZmJjabrcV9Ol3Tj0t5eTkLFiwgMdE1AFuyZAkvvvgiKSkpvPrqqyQkJDj3LV68mHXr1uHn58ff//53hgwZ0mTdRUVF9OjRgxkzZvD999/z+OOPO4MVAE9PT7Zt28aaNWu44447eOutt0hKSmLx4sU888wz7Nixo8l6hRBC1FFVlaO/nGLTd7vZ9F0yp47VJZ83zD1xK6hgr6+WVcs3u9ThbTZxXc8oomMDSVUL+XD3rrqdSs2PAiQEh3B9RBjB/pBlP0VS/lZ+ySt0Fq2fe+JAYWpkR8IMpyiumIWtKpe8qvrV6jDpu1NWtZuaiKiWFotpULOBSi3JPRGi7ZNg5Tz5WTxYPuuBs5bLLbQyZcYX1B9tp1EUPnhxIv7enq06z/kym80kJyef9/GttWTJEjp37uySHwMwbtw4xo0bR1paGmPGjGHkyJHExMTw8MMP8/zzz+Pm5sbmzZsZM2YMO3bscAmSahmNRu68804A+vfvz9GjR132T5hQ02Xfp08fSktLmThxIgDXXHMNR44cuRSXK4QQVzVnsnykP/k5JWz6NplN3+3mdLrrsKywjkH0uLErnxys97mrKFT7msjMq1krJTTIm+sTOhDYwUJqVSE/HjvKR8m/OIvX5Z9oUTRw/7UdKVKyWVOUhO2U3eV8wUY/QnU7Gem325l7oiiA/Qfy6+XuG3Ud8DLegMV4A2bjtWg1nrI6vBC/YhKsnCedVtOq4VlBvmaeu+9GXp//Iw6Hikaj8Nx9N9Ktw5X7EA0PD2f16tXO12lpaYSEhKDT6Vrc15y5c+cyZcqUZvdHRkbSr18/VqxYQUxMDMHBwc59AwYMICEhgaSkpCaDFYPB4BxfrNVqsdtd/3OrzTnRarWNXttsrvPwCyHEb933C7bw5rOLaC5dNTI2hP4jemCODWTvqVy+3HEYaLz2ya0DuxLdM4g9hVl8lrqf/O2uSe/hFgtFupMEhRa4rGOyvijTWcZN0dHTuxPX+LQj1j0bhy2RoorddQvRn/mLRjFjMQ3EYrweL+P1GHRhjdotQ7qE+PWSYOUyGDWoO326hF702cDO14gRI5g6dSoHDx4kNjaWd955x9kj0dK+pqSkpJCUlMTy5ctdtu/fv5+uXbsCkJOTw9q1axk7diwAJ0+eJDQ0FIAjR46QnJzcqFdGCCHExXP88Gm+/XQz38xvnC8ZERPM9bcn4NnJnz0ncvj456OUJNetJN9o7ZNylS8qD1K55ReXehKCQxgcFUGQv50DpYfYml/g3FcbePjpLVzr15W+Fh3BbqlYK1ZQVr2PQuuZck20vaP/HCymAWe9RhnSJcSvkwQrl0mgryftAr2dvQSXQ8OcFYDExETMZjMffPABo0ePxmaz0b17dz766COAFvc1Zd68eYwdO7bRLA6zZ88mMTERvV6Pqqo88cQT3HTTTQA8//zz7Ny5E51Oh1ar5e2336Zz584X9+KFEOI3Lvd0IRuW72Ld0p0c3XfSub02WV5TbsPuqccwqAMf7k/BmlQXfGg1Cn26htO5WxD/PrqtrlIFbO5gs9vRa7T0Dwvnhqh2eHiVsa/kMKsKv8R2oq4HvDb/xGo3EORWwsR2pWgcK7BV5JNdUVetTuODp74fhRU/0DD3xOTW4RLcHSHE1UKmLm5Ca6YuPpcpb1VVdSaoX85gRTRNpi4WVwt5NkRLmno+SovL2bRyN+u+3smeLSkuw72Cw31Js1VS1qkuWZ56/ydptRr6dg3jmoQIyi0q606ksfVkOioN1z7RMaVvNyJDNPxcuJ8DxWmo9QIMg0ZPnKUD7vblDPM50NSpAHB364rFNBRv0xA89PEoivZXP53w5SSfH6I5beXZkKmLhRBCiF+x3MxCDuw6jr2bhrRDp1n39U62r/2F6sq6fD2fAC8G3h5P+74RJKVnsX/LwboKzkQPvWJDuaFfR8otDtamp/LigY046gU5lgZrn9iqtWyqTmdTvYXovXQe9PPrxnU+7oS4HaaofCGVtjSXU6mAxXgDvu63YjEOQa+ry1+sJbknQoiGJFgRQgghrjItJcqbPA0MGNGD2EExpFWW8/3WQ2QuTHPur02WV2xg84CM8Epe2L/eJUDxMRq5KbojMe3dWJS9zLldUcBNXzPMK9DgS3//rlxrUfDW7KWo/B2qKk65DO+qTwFCvB7By9i/xWuT3BMhRH0SrAghhBBXidzThSz/cCOL313baF/CDTFcd0cCBSYNq3ccZtGXG132x0YGsavsNNYw6hZqVGBvfjYA3kYjN3WIpk+EL0WaTDbnbWN3ds10xvXXPilz6Hm8QyzRxnQKy1+juiyfnHrnMbnF4mXoT5Z1Pg3zT4y6yIt3M4QQvwkSrAghhBBtWHWVje1r97Pqi60krT+Aw1ETADgT5Svt2Lz0ZEZ68sq3W1x6SMKDfbjpuhg8w9xZdfIo1uP1Kj6TQ3Jrp84M7hhMifY0m/OSmJdZP/SAXp7HGeWX7Fz7xKZqcLOvILe0riJPfS+83YfjYxqO0a1mGnqTPlbWPhFCXDAJVoQQQog26Pjh06xatI01X+6gKM/q3O7t58lpvUpZZ9dE+f0naoIMHy93burXmYgu/uwqzuLdI7soSq8bm1WbLA8q7p6VFHn/zNzMfJdzR3m0Y2BAV3p5pFNYusxl7RM3xQHo8DJeh49pOD7uN+GmDWzUfsk/EUJcDBKsCCGEEFeQc0X5qADcPY0krtjFDwu3cvDnum4QrU5Dvxu70/uWOA6UlLDox+S6Cs4kyg/u3ZFr+0VxzFHE8sMHOfHTLmcRN42Ga0PD+KViD/4hRS4zc+VW1/wZ4R7MwIBu9PUqRbFvoqj8Q4pKK5pZ++R/+LgPO+u1Sf6JEOJCSbAihBBCXCE/fLGV2c8uRD0ztEvnpsVWXbdOSVjHQIaOvwZDtD9rd6Uw4+u6RR1dEuU9YZclj8Xbj7jU3ys4hFs6R+PlU0Zi3k4CrEWN2jCm3QAG+4HWvpnC8k8pLHGO70LBgEplgyO0eOi7XoSrF0KIs5Ng5TLIzrdSUGxFq9WhKODlYSTwIqxiX7vgY1VVFYcOHXKuAh8TE8Mbb7xBdHS0y8rwBoOBbdtqFvdasWIFTz/9NHa7nbi4OObPn4+XlxdWq5WxY8eyc+dObDYbhYWFzZ5/zJgxpKamOl/v2bOHpUuXMmrUKN5++23mzJmDVqvFZrPx4IMP8thjjwEwffp03n77bdq3bw9At27d+Oyzzy74fgghxNUk/UgWs//6BfUn9LJV2zGa9Ay+oxddhsayJyefuT8doHjLHmeZQB9PjmtLXFaVR4GU4pqhXBEWb0bFdKZDiI69pftZmrcQW7HrQo3+biV4aivoYMwlQf8jRS4Bih6LaRC+7rfjbRpGftkKyT0RQlwxsihkEy7mopDZ+SXcN/1zyiqqUFBAAXejG/Ne/P1FCVgA0tLSiI+PdwksmtpWy2q1Eh0dzYYNG4iNjWXatGmYTCZmzpxJZWUlmzdvxtfXl8GDB7cYrNSXlJTEiBEjyMjIQK/XU1RUhMViAWruZ/fu3Vm2bBkJCQlMnz6dwsJCZs2adeEXfx5kUUhxtZBn49fp+KFMVnyymVWLtlFVUe1MlNeW28DmYMRfhrP7dB4HUrOcx7jptAzq3ZE+fcLZXpLJwv17G9U7OjaWQR0DOWFPZWPOLkpsZc59njoTfX1j0VV9yvWWlEYLNCro8DLegK/7SLzdb0KncV2grcqWKbknVxn5/BDNaSvPhiwKeZn87q8fNrnd3ahn/oy7KS6toKyiiorKaue+sooqHnx5IXo3LQE+nrz97HigJrCZ9sYSZ7lFb9x3Sdq8cuVKEhISiI2NBeCRRx7h5ptvZubMmRgMBoYOHUpaWto51Tl37lwmTZqEXq8HcAYqAKWlpVRXVzd3aLNqA67HH3+cFStWUFRUxJtvvsmtt94KgKIovPzyyyxfvpysrCxmzZrFgQMH+PLLLykqKuL9999n8ODB53xeIYS42GzVdn76fg8rPtnE3q1Hndsrgz0ojamXKK+qfLFlv3N/xzB/RtzQBQJ1LD96kAXbVjn31SbKqw4FD3MFWeYdzDlZ4NyvVTRc49uNof7tCdf/QkHp/6hyZLq0SwXCvJ8jwGMCOq13s+2X3BMhxJVyRUPtjRs3cvvtt9OuXTsURWHp0qUtlr/33ntRFKXRT7du3VzKvf3220RGRmI0GunXrx/bt2+/hFfRekrDX2VdYiUlJcTHxzt/7r77bgDS09OJiIhwlouMjCQzMxObzdZcVS0qLy9nwYIFTJkyxWX7kiVL6NatG5GRkTz99NMkJCQ49y1evJiePXsydOhQ1q1b12zdRUVF9OjRg507d/LWW2/x5JNPuuz39PRk27ZtzmApJCSEpKQkXn31VZ555pnzuh4hhLhY8k4X8em/V3JP/xm8NvUjZ6AS0TmYCc/dRmmsnzNBHkUBjQajwY3Rg+N4/onhRA4LYWbqVl7ctJadmRk1x1q88fYroUPXDMI7ZhPROQv/kCLyq2sClRhzBFOjb+HtHj0Y77cSQ+WfyCp5q1GgAjWjyDz0PVoMVIQQ4kq6oj0rpaWl9OzZk/vvv58777zzrOVnz57N66+/7nxts9no2bMn48ePd25buHAhTz31FHPmzKFfv37MmjWL4cOHc+jQIQIDG0+teKFa0/uhoOBuMqDTarDbHThUlX8+eQcdwwJcygX6mi9qb4rZbCY5Ofmi1decJUuW0LlzZ5f8GIBx48Yxbtw40tLSGDNmDCNHjiQmJoaHH36Y559/Hjc3NzZv3syYMWPYsWOHSwBVy2g0Op+N/v37c/ToUZf9EyZMAKBPnz6UlpYyceJEAK655hqOHHFNNBVCiEstJ7OQU8eyKS4oJXFFMj/9sBeH3QHUzOg1YEQPeo+KZ09OPvPW7wPqEuW1FaA4YOidXdhckMH7m+ryVIw6Hbd26sz10QEcqvyF9TkFjc59R7sB3OivBdtaCsvmkF1U5dxn0IXjbbqJrJIPAUe9o2ShRiFE23ZFg5VbbrmFW265pdXlLRaLy/CipUuXUlBQwH331X3B//e//80DDzzg3DZnzhy+/fZb5s2bx7PPPnvxGt9KXh5GTEY3yiqqqHaozpwVL48rlysRHh7O6tWrna/T0tIICQlBpzu/x2Hu3LmNelXqi4yMpF+/fqxYsYKYmBiCg4Od+wYMGEBCQgJJSUlNBisGg8HZI6XVarHb7S77a3NOtFpto9fn21MkhBDnY8XHibzz9y9pmAnqF2Rh+O+vxbdHe75POszSz+tWny/3V10T5VX46Mhu5/64wCDGdOmMh3cp63N38L+Tp5z7aleV1+Cgs3s2vQ0bKCgudO7XKmZ8PUbi5zEWT31vFEXB5NZZkuWFEFeVqzpnZe7cudx4443OL7lVVVXs3LmT5557zllGo9Fw4403smXLlmbrqayspLKybmrG4uJioCYByeGo+w2Uw+FAVVXnT2sE+Hgy78Xfk19Ugk7nBtQEMAE+nq2u42xq66lfX1Pbag0fPpypU6dy4MABYmNjefvtt5kwYUKrj68vJSWFpKQkli1b5lJ2//79dO1aM7VlTk4Oa9eu5c4770RVVU6ePEloaCgAR44cITk5me7duzc6V8M2NHed9d+Plso2PKbh+3ul1D5XbaEtom2RZ+PqUJhbwsK3f2T5h4mN9t0//Q5KfI0s2bCP07sOOLdHhPhww/Ud+U9qvWHKSs2Ph5ue0bGxXBPpzaHKgyzNXURlUV3eX5R7O4K1iYzw3eeaKK8CaLEYB+LrfifephvRKIaaXWc+9/zcx2PWX0+l7TgGXQR6XYg8X79S8vkhmtNWno3Wnv+qDVYyMjJYuXIln3/+uXNbbm4udrudoKAgl7JBQUEcPHiw2bpee+01ZsyY0Wh7Tk4OFRV1q/5WV1fjcDiw2Wzn9Ft7H7MBL3cdWq3W2UtwMX/rX1tX/TptNpszZ6W+devWYTabmTNnDqNHj8Zut9O1a1fmzZvnPL5Xr17k5uZSXFxMWFgYgwYNYv78+U2e+4MPPmDMmDG4u7u7nH/WrFls2rQJvV6Pqqo8+uijDBkyBJvNxv/93//x888/o9PV3JPZs2fToUOHRvek4XU1d53134+WytY/xuFwkJeXh5ubWwt39vJwOBwUFRWhqqrM2CJcyLPRtmUez+OHz3ew+du92Kpqen1rZ/ZSNQpVge7M2piM7cwaKhpF4Zpu7emdEMov1Xm8m7oTqEuUr67UoToUxvfy5ri6hXdO5DnPZdIY6G/uwiBvLSbNKsodroGKqoJFOwVP7Z1oHX7YrJDbxJoqNbRAB8oByL7o90W0DfL5IZrTVp6NkpKSVpVrM1MXK4rC119/zejRo1tV/rXXXuNf//qXc6pcqAlg2rdvz08//UT//v2dZf/yl7+wYcMG5xojDTXVsxIWFkZBQUGjqYvT0tLOa8rb6urqNvHFWNRNXVw7CcOV5nA4yMnJISAgQP5DES7k2Wh7VFVlf1IqX723nm0//uLsvfXy8SDbBGWdfGk4L7C32cSogd0IivHmm7TDJKbXrUxv8bUSFJZffzIw6r/V3byiGBHYhU6mwxSVLaHSfpzmdPb/HLPx2ot7weKqJZ8fojlt5dkoLi7Gx8fn1zl1saqqzJs3j8mTJzsDFQB/f3+0Wi1ZWVku5bOyslzyJBoyGAwYDIZG2zUajcubqNFoXGYhO5f21pa/3DOCicZq37+G7++V1NbaI9oOeTbaBrvdwZYf9vLle2s5+HNdwBDWMZBb772BDL3KR98lNTru4YkDqApQWPDLHtI31vV0RHn7cEf3KFZalzq3KUrNj6fWxE3BfRnsq0Nj+57C8rfILqnrJfY09MVamcSZcV9naDHpo+Q5ES7k80M0py08G60991UZrGzYsIGUlJRGSd16vZ7evXuzZs0aZw+Nw+FgzZo1TJs27Qq0VAghxNUoJ7OQjNQc/EIsJCce5qv315N5PNe5v3u/aG6c1J/D5aW8uW43peU1M2/VzuwFUOkL/zi2hcqUmiFiCjAksgO3d40kg2N8f/pboC5RPq/aEwcKf432QW+fRVHJCef5dBp//D3HE+AxEaNbBDnWhZIoL4T4TbiiwYrVaiUlJcX5OjU1leTkZHx9fQkPD+e5557j1KlTfPzxxy7HzZ07l379+tG9e/dGdT711FPcc8899OnTh2uuuYZZs2ZRWlrqMmOYEEII0ZwfvtjK7GcXojpcR0lrNAoDbunJteN6s/lYBv9v6SZsZ6YlNhndyPesqpvZq5bDjsVgZHzXbsRHerClcCdzMtY7d/fyPM4ov2Q0tcPAALUKagcmexlvIMDz93ibhqFR6kYSBHhOwKy/ntO5yQT7x2PUt78k90IIIa60KxqsJCUlMWTIEOfrp556CoB77rmH+fPnk5mZSXp6ussxRUVFfPnll8yePbvJOidMmEBOTg4vvPACp0+fJj4+nu+//75R0r0QQgjRUMq+k8z66xeuI6yAYeP60nNUPN//fITnPqqb+j3Ax5NxN/ek0MfGm0lbG9X35/79CAyq4oesTSSm5ji3tzcFMjq4A4HqMmdsoyg1cY5O8SXA/HsCPCdg0IU121a9LgSjRoted/HXEBNCiLbiigYrgwcPbnFq3KZmoLJYLJSVlbVY77Rp02TYlxBCiFbLzy5myZw1rPhoE6h1s3ppym3YzXqSNJUsnveDs3x0qB9jbu5JhrGMt/fuJO9ozdxatTN7oYLZu4xVFUupSquZdlhBoa9vF24PjsJfk0iudXrDmAiADv5vYjFdfzkuWwgh2ryrMmdFCCGEuBjyThex+N01rPx8C1WVNUFFZbAHpTFnZvVSVVAUrNmFAPTuEsaIoV3ZXZnNjF82UlZdc4xeo8XkXUhQWIHLZGBVKrhrjdwc3Jeb/HRUV31Fcdlr5DRsiJMWk1v0JbteIYS42kiwchWrXUOlqqqKQ4cOERcXB0BMTAxvvPEG0dHRzm1QM+tZ7fTNK1as4Omnn8ZutxMXF8f8+fOd08a1tK++MWPGkJqa6ny9Z88eli5dyqhRo5zbsrOziYuLo3///ixdutS5/eWXX+bDDz8EYOLEibzyyisX56YIIUQr5GQUsPjdNXz/xVaqK2tm2vIN9GLYPQP4345f6gqeiTyuj4/ixqGx/JidxtM7VmE7s5iZt9HI3XFxBAaV8/nJ7xqd597IoQywZJNf+hZ5xWnO7UZdNEHme1FRSS+YgSTKCyFE09rMOittSXFxMRaLpdG8z7Xrc5zrOiuqqnKysIAT1hKivH0JMZsvanvT0tKIj4+nsLCwxW21rFYr0dHRbNiwgdjYWKZNm4bJZGLmzJkt7mtJUlISI0aMcFn3BmoCGl9fX/Ly8pzBysaNG/nTn/7E9u3b0el0DBgwgBkzZnDbbbddjNtxVuf7Pl4qDoeD7OxsAgMDZXpJ4UKejYsv+1QBC99ezapF25wLOfoFWxjz0BBKA935+LsdlJRWOmf10lSAwwgdrgtmV95pZz3tzGbuie+Jl6+VFZkbya0qBOpm9nKoCt08MrjW6zScWX4RFCzGoQSZ78XLeL1zKvsqWyYVtjSMushzClTk+RAtkedDNKetPBvNfd9uSHpWzpPN4SCntLRVZb85fIB/bN6EAxWNovCX627g9s6xrTo2wMMD3UV+kFauXElCQgKxsTVteOSRR7j55puZOXNmi/taMnfuXCZNmuQSqMydO5eoqCh69Ojh0quycOFCJk+ejIeHBwD3338/CxYsaDJYURSFV155haVLlzonTqid2S0yMpJJkyaxdu1aTpw4wfPPP4/BYOC9994jMzOT119/nYkTJ17QvRJCXP1yMgv5ZdtRtq35hU3f7cZWXROkBLTzZvTDQ7D6mXj/h58pKK7Jhyz3V+tm9VJr/qwNVLr4BzA5oTvlhgy+O70U6/GaY7Ro6Ol5jFF+u9E0WE5Lq5jx9xxPoOcfMLpFNmqfXhcivSlCCNEMCVbOU05pKQM+fO+cj3OoKq9v3sjrmze2qvzm+x48756YkpIS51AxgG7duvHZZ5+Rnp5ORESEc3tkZCSZmZnYbLYW9+l0TT8u5eXlLFiwgMTEROe21NRU5syZw8aNG1m4cKFL+fT0dK6/vi55NDIyki+++KLZ6zAYDGzfvp2DBw/St29fJk+e7GxLaWkpP/30EykpKcTFxfH888+zZcsWduzYwa233irBihC/cYvfXcO8175x2RYY6sOYh4ZS5GPgvVV1QYpRr+PGQbF8WLC3rvCZwKNXcDv+0KsrJ9TDLMj6nCpHTa6KSWvglpB+DPHJJb/ka5dZi1WgveUpgs33o9V4XsKrFEKIXy8JVn7FzGYzycnJl/w8S5YsoXPnzs78GFVVuf/++3nrrbcwmUwXXP/dd98NQGxsLDqdjtOnTxMaGgrUTFUN0LFjR4xGI+PGjQOgT58+5OfnU1hYiLe39wW3QQhxdSkuKOXDN1bw/edbXHdoNfSbOog5P+2joKRmeJZRr+POYT0J6OLNOz/X5PXVzupVXalDq3UQFV3I/zLm4+BMroqbJ6PbX0d/rywKy2ZTUJJOgw4VFMBs6CuBihBCXAAJVs5TgIcHm+978KzlskutjF28AEe91CCNovDl+LsI9Dj7f2ABZ4ZKXUzh4eGsXl23TkBaWhohISHodLoW9zVn7ty5TJkyxfm6uLiYPXv2OAMJq9VKWVkZw4YNY82aNYSHh3P8+HGXc4SHhzdbf/28Eq1Wi81ma3Zf7WtFUVAUxaWsEOLXr6K8iuXzNrLo3R8pLa4AaqYhtnm4YfPSU9nOzEc//AyAyeDGncN6EBjrzby9P5OyMR8Ai6+VoLD8+pOBsa+0ZhhYsNGPce2vpYfHIXKtL5JVXLuqvQbOBDJ1tBh1kZf+ooUQ4ldMgpXzpNNoWjU8K8Rs5pUhN/L8uh9xqCpaReHloTfRM/jKjU8eMWIEU6dO5eDBg8TGxvLOO+84h0u1tK8pKSkpJCUlsXz5cuc2i8VCXl6e8/X8+fNZunSpM29l/PjxTJ06lUcffRSdTse8efOYPn36JblWIcRvg91mZ/Xi7Xz67+/JyyoCwMPLSL6njtJOPtSfT9io1zHupnhnkHJkY83nlUZRGN45gmOmumG6tYdFuAdzV9g1ROm3k2v9M6eLS87sNxDgMYFgrwcorviJtPz/Q2b2EkKIi0eClcvgd93iuK59KCetViK9fS76bGDNaZizApCYmIjZbOaDDz5g9OjR2Gw2unfvzkcffQTQ4r6mzJs3j7Fjx7Y4i0NDgwcPZsKECc5hYxMmTGDkyJHnfoFCiN88VVXZunofH76+ghMpWQAYjG6MmjIIR0df3l/muqq8isqk+69lybH9HNlQE6QowMiYGIZ3CWJ59o9QVjerV161JzrFzgPtT6JWfkhWZRVQkzQfaL6HIPO9uGn9AQjwnIDFOPC8ZvYSQgjRNJm6uAmXYuri2gR1RWk4qllcbjJ1sbhayLPRsn3bj/Hha9+wf2fNek8arYabf3cN0Td35ZPVP5OWUTOsy+6mYjOC3QAVQWA/k0qnALfHxDK8SzBrCzazr+goAL08jzPKLxnNmWFgKjhn+HLTBhJk/iOBnneh1VyeXzw1R54P0RJ5PkRz2sqzIVMXCyGE+FXJySwkIzUH1eFg2YeJbF29z7lvwC096DfxGhZt2sfnH/0I1AQYpX71piE+QwFGdo7llm4hrMvfzJtpq5z7+vu0Y4TXcufwL0WpKa/XhtHOMhU/jzFoFMOlv1ghhBCABCtCCCGuAj98sZXZzy5EdbgOBuh+TQdueXgIP/ySyt8+rAs6BvfuSJdr2/P/tq1vVNert1xHcvnPzE6tK9/TuxO/D+2Eruo9SqsaDziI9H0di2nAxbsgIYQQrSLBihBCiDYtIy2H2X/9goaDlh94ZSyHbRX87dMfsZ8JYnp0aseo23qw9OQhZ6BSOw2xRuPAx9/K/My6dZ16WDry+9BYPBxfUWD9J5VNtkCLya3DJbk2IYQQLZNgRQghRJukqirbVv/Cm/+3CFWtmYLYbtKhqbRTGeTBf9b9TJWtZjX6yBBf7rqjN1vLMnhy8/fO6eLrT0NcX3evaO4O64pZXUp+6b+poqa8u1t3PA19yLZ+gszqJYQQV54EK0IIIdqck0ez+N+Mr0lafxCAymAPSmN8cVn8xGbH39uDSaP6cMJUxv8lr6XizNpKMX7+/L53Bz7PXtKo7mc730io7kfyS/9D/pkgxeQWS3vLU3ibbkJRFEK8HpJZvYQQog2QYEUIIUSbUWatYMHsVSydtwFbdU2vSfxNXVlbba0rdKab5K5beuHZ2ZN/7dxGfkXNavTBHp78qV8vSgzH+SLzS6BuGmKbqqG353Hcq74hv6pmAUejWyfaW57ExzQCRambFUevC5EgRQgh2gAJVoQQQlxxDoeDdV/vZO6r31CQUwxAaHQg4/48nCW7jsARK3Y3FbsRNBVg94SF1kNkba4JYjz1eh7s3QufgBK+OrWEMnvN6vUNpyGuHQ5m1HWgneUJfN1vQ1G0V+SahRBCnJ0EK5fBaWsJeaWl6LRaUBS8jUaCPS98fv7aBR+rqqo4dOiQc5HFmJgY3njjDaKjo53bAAwGA9u2bQNgxYoVPP3009jtduLi4pg/fz5eXl5YrVbGjh3Lzp07sdlsFBYWNnv+MWPGkJqa6ny9Z88eli5dyqhRo5zbsrOziYuLo3///s4V7AFefvllPvzwQwAmTpzIK6+8cqG3QwhxlUrZe4J3XviSAzvTADB5GBj/6E0UBRh5+etNVFXbKfevNwWxWvNncbkVN42Gu3v0JC7Kja9OrSI3vRAAi5sn94R1xc+xzDlrsaLUHBru/SJB5j9IkCKEEFcBCVYusdPWEu5c9DmlVdU1GxTwcHPj6wl3X3DAkpycDEBaWhrx8fHO17XbzGazy7ZaVquVKVOmsGHDBmJjY5k2bRovvfQSM2fOxM3Njb/+9a/4+voyePDgFs//9ddfO/+elJTEiBEjGDFihEuZhx56iJEjR5KXl+fctnHjRhYsWMCePXvQ6XQMGDCA6667jttuu+2c74EQ4uqUk1nIkT3pJH6bzIZlu6hdn3jonX2IHRnHB99u5/TWEgD8g80cCC2uO/hM9DEsqgNjE8L4JmstW1JPAWDQuHFn++sZ7JNBTvErOBqcVwHc9bESqAghxFVCgpULdOMn85rc7uGmZ9nESRRWVGCtqqK8utq5r7Sqit8t+QK9VkuQh5nP7hwP1AQ2k75e7Cz34+T7L0mbV65cSUJCArGxsQA88sgj3HzzzcycORODwcDQoUNJS0s7pzrnzp3LpEmT0Ov1LtuioqLo0aOHS6/KwoULmTx5Mh4eHgDcf//9LFiwoMlgRVEUXnnlFZYuXUpOTg4vvPAC9913HwCRkZFMmjSJtWvXcuLECZ5//nkMBgPvvfcemZmZvP7660ycOPEc744Q4lJb+dlP/PfMDF+1OnYPZfQTN7M0+QhLPl4DgEGv4/e39uaweyEHDhc7pyCurtSh1TowBKcx+9h6ABQUbgrqy5hgLUXWf5JVfLKZs2sx6iIv6fUJIYS4eCRYuYwURXH+9vByKCkpcQ4VA+jWrRufffYZ6enpREREOLdHRkaSmZmJzWZDpzv3R6K8vJwFCxaQmJjo3JaamsqcOXPYuHEjCxcudCmfnp7O9ddf73L+L774guYYDAa2b9/OwYMH6du3L5MnT3a2s7S0lJ9++omUlBTi4uJ4/vnn2bJlCzt27ODWW2+VYEWINubnjYd487lFrht1GtqPiePvC9Zit9f0hQzu05HeA6N4O3kbJ04WuUxBXPsxerQmp54+Pl2YHBaGreI9cop2A6CgJ8h8H3pdMOkFLyPTEAshxNVJgpUL1JreDwUFT70BnVaDzeHAoaq8N3I0sf4BLuWCPc0XtTeluWFgF9uSJUvo3LmzMz9GVVXuv/9+3nrrLUwm0wXXf/fddwMQGxuLTqfj9OnThIaGAjBhwgQAOnbsiNFoZNy4cQD06dOH/Px8CgsL8fb2vuA2CCEuTFVFNZ+/uYrF7/wI1KyZYjPpsLu7URHhxdeJvwA166XcPbYvX2ce4tmNNSvMuxsgOCzfOfyrNkk+3BTMQx2uwexYSGHx685z+bqPJtT7aQy6ms8JH9MImYZYCCGuUhKsXGLeRiMeejdKq6prFi87k7PibTResTaFh4ezevVq5+u0tDRCQkLOq1cFaoZ7TZkyxfm6uLiYPXv2OAMJq9VKWVkZw4YNY82aNYSHh3P8+HGX84eHhzdbv7HevdJqtdjOrKPQ1L7a14qioCiKS1khxJWxd9tRZv/1C04dywEarJlyhsngxj2jryHHu4q/bF9NlaNm2uIbO3QgvpPCN1npLnW6ayp5MDQTR+lDFFLz79xs6EeY9/N4GHq4lJVpiIUQ4uolwcolFuxp5qvf/f6SzAZ2vkaMGMHUqVM5ePAgsbGxvPPOO+c9XColJYWkpCSWL1/u3GaxWFwS6ufPn8/SpUudeSvjx49n6tSpPProo+h0OubNm8f06dMv5JKEEG1QaXE5817/hu8+/QkAnV7LLQ8O5qN9R1zKqahMurcfHxxKJvNoTVJ9hMWbR69L4OeKbXyTVbMwpJe2nEC3YiKNufTzSsNRXROkGHUdCPV+Dm/TjSgNl6oXQghxVZNg5TII9jTjbzSh0+ku63+kDXNWABITEzGbzXzwwQeMHj0am81G9+7d+eijj5xlevToQU5ODsXFxYSGhjJkyBA++eSTJs8xb948xo4di5eXV6vbNXjwYCZMmOAcNjZhwgRGjhx57hcohGiztq7ax1t/W0ze6SIAuvXtwJCHBvH2N1sBnGumoEJZO3h1Z03Om1Gn46E+ffD0y+PDjE+xqTU9LCP8iujvub5+Zww6jR/tLU/g7zkRjeJ2Wa9PCCHE5aGolzPj+ypRXFyMxWKhqKjI5Ut4RUUFqampREVFuQw/OhtVVZ3J6/JbvyvvfN/HS8XhcJCdnU1gYCAajebsB4jfjKvx2SjIKeHdF74k8dtkAEyeBu56+hYO2itZcSYvpak1UwBGdOzEiLgAlmR8T05lIQDtTYE8FNEBKp5rcCaF7sGrMOk7XYarapuuxudDXD7yfIjmtJVno7nv2w1Jz4oQQogLpqoqqxdv5/2XlmEtKgPgmmHd6HVXH/73zXbyikoB6NYthPWmjLoDzwQq04ddxyFHMu+mnpm2WKPn9+EDucYzmRzr802dkWpHLiZ+u8GKEEL8FkiwIoQQ4rzlZBayd2sK336ymf1JqQBY/Dy5+9nb2JSVw6ufrgPA093AfeP6saIwBTJwrpliq9Zg8S1jYd4iHGeWcBzg34O727lTVPoyOdasZs4s66UIIcRvgQQrQgghzsvKBT/x32ddF3e8cVxfwm6KZfayrZSUVQIwqHc03QaE8a+dWyiqrGi0ZoqigIOaIV8PR/XF0z6f3OKapHyN4kF7y5NoFHeOF/wdWS9FCCF+WyRYEUIIcc4OJR/nzb+6Lu7ocNdxyFvDogUbAPC1uHP/hGv5NvcoS36q6WEJMLvh28SaKRNDr2eQ9xFyrY9QcmYqYl/32wnz/ht6XRAA3qYhsl6KEEL8xkiwIoQQ4pxs/GYX/3lmAVC3uKPNYqAi3IvClEwAbru+K8Hxvvy/nRspra4GYHRsF9qHFfJjztF6tal0dc+kq9s/yLHWrMNi1EUT4fsSXsbrXM4r66UIIcRvjwQrQgghWqW0pIJ3/76ENV8lAU0v7hjk68n9d13H5yf2MX9rzexfIZ5mnryhF5utifyYkwbUrJkSZcyhl+dxokz5oIJGMdHO8jhB5vvRKPrLfn1CCCHaHglWrmK1a6hUVVVx6NAh57olMTExvPHGG0RHRzu3ARgMBrZt2wbAihUrePrpp7Hb7cTFxTF//nzntHEt7atvzJgxpKamOl/v2bOHpUuXMmrUKOe27Oxs4uLi6N+/v3NRyPnz5/P4448TFRUFgI+PD+vWrbt4N0YIcdH9suMYM5/4lKwT+QDE39yNtVUlLmVURaX/HZ15NulHquw166P8Pi6OThE2Pjr1OTbVjoLC6EAr8aYfXdZM8THdSpjP3zDo2l22axJCCNH2yTorTbgU66ycLs0lq7qA9u6BBBi8L2p709LSiI+Pp7CwsMVttaxWK9HR0WzYsIHY2FimTZuGyWRi5syZLe5rSVJSEiNGjCAjIwO9vu43omPGjMHX15e8vDyXYKX+ivaXm6yzIq4WbeHZsFXb+Xz2Dyx8azUOh4rRXc/vn72Nb46d4FBatnNxRxUoCwWbR81xkd4+PH59T1YVrOFY6SkAwkxBTItsT2X5iw3OoqFnu80yxOsctYXnQ7Rd8nyI5rSVZ0PWWbnE7Kqd/Aa/VWzOhuydzEv9BhUVBYX7o25nUGDvVh3rqzejVbQX0tRGVq5cSUJCArGxsQA88sgj3HzzzcycObPFfS2ZO3cukyZNcglU5s6dS1RUFD169DjvwERRFF555RWWLl1KTk4OL7zwAvfddx8AkZGRTJo0ibVr13LixAmef/55DAYD7733HpmZmbz++utMnDjxvM4rhIBTqTn847FPOLw7HYCY+HBueGgQc1Zso7i0osnFHTWKwv0JCQSGlPDeyU9x4ECDhglh13ODJZlca8NABcBBhS1NghUhhBCNSLBynvKrSvjDtqb+022Zisrc1OXMTV3eqvIf95tx3j0xJSUlzqFiAN26deOzzz4jPT2diIgI5/bIyEgyMzOx2Wwt7tPpmn5cysvLWbBgAYmJic5tqampzJkzh40bN7Jw4cJGx2zatIn4+Hjc3d158sknGT9+fLPXYTAY2L59OwcPHqRv375MnjzZ2ZbS0lJ++uknUlJSiIuL4/nnn2fLli3s2LGDW2+9VYIVIc6Dqqp8v2Ar/5vxNZXlVWg0Cnc+ciMZPjr+sbBmpi+zn5GcyPK6g84M6Xrxpn4klmwg8VTN+igdPNozLaoTVeX/Itd6spkzypopQgghmibByq+Y2WwmOTn5kp9nyZIldO7c2Zkfo6oq999/P2+99RYmk6lR+ZEjR/K73/0Od3d3Dhw4wM0330xYWBjXXnttk/XffffdAMTGxqLT6Th9+jShoaEATJgwAYCOHTtiNBoZN24cAH369CE/P5/CwkK8vb0v9iUL8auTk1lIRmoOZh93Pv3XSras2gdAcJgfY5+7lQ837ObkvkIABsRHoe1q5Njh/S6LO3r7lfJ5ds10xjpFy6SIgfT12EKe9R2gJoE+1PsvKBg5XvA3ZM0UIYQQZyPBynny1Zv5uN+Ms5bLryziyeT/oFKXGqRB4d/xT+JrsLTqPBdbeHg4q1evdr5OS0sjJCQEnU7X4r7mzJ07lylTpjhfFxcXs2fPHmcgYbVaKSsrY9iwYaxZswZ/f39n2S5dunDrrbeyefPmZoOV+nklWq0Wm83W7L7a14qioCiKS1khRNN++GIrs59diOpwTWEcOrYPXtdF8uqSjdgdKga9jnvHXcv68nQ2Hd7f5OKOADHmCB6JjKSs7A3ySmumMjYbriXS9w2MbjU9t96mwbJmihBCiLOSYOU8aRVtq4ZnBRi8eazTBP57ZCEOVDQoPNZpAjFeEWc99lIZMWIEU6dO5eDBg8TGxvLOO+84h0u1tK8pKSkpJCUlsXx53bA2i8VCXl6e83XDhPpTp07Rvn17ALKysli7dq0zsBFCXF45mYVNBiqT/jaKjTk5JH+zHYCYiEBuHtWN/+z6iYKKCnRuNoKbWNzx7vDr6e+5hfySNwHQKJ6EeT9HgOddKEpdIqesmSKEEKI1JFi5DIYHX0tPc0eyqwtodwlmA2tOw5wVgMTERMxmMx988AGjR4/GZrPRvXt3PvroI4AW9zVl3rx5jB07tsVZHBp6++23WbZsGW5ubjgcDp588kmGDh16XtcohLgwB39OQ3WoOAxa7CYd2nIb1RYD72/fR3mVDUWBCbckkO1fzQtb1gLgZ3Ln99e2Y1VBhktdXdwziNG+Sn5ZAQBexoFE+r6GQdf+sl+XEEKIxnJPF1KcbyUvP5+yfBtevp74B3tf6Wa1SKYubsKlmLq4NkFdqb+wgLgiZOpicbW41M/Gnq0pvPrwh2TrqVvcsd54rgAfT+65qx//O7KTYwU1AcjAiEiGxnmw6OQP2HHgpS2nvb6AeHM6Xdxrkuq1ihfhPn/Hz2OcfOZdQvLZIVoiz4doKPd0IU/c/h/KrBWoqopGo2DyMDLrmyevSMAiUxcLIYRokqqqfPm/dXz4xgpsOoXSuHZ147jO/Nm/ZwTR14Xwt6S1VDsc6LVanriuD+naPSw4eQiAgd7ZDLNscVnc0dt0IxE+r6DXBV3uyxJCCNEMh8PBzvUHKcwrwWF3YDC5odFoKS+toKSwrE33rkiwIoQQvyGlxeX868+fs+WHvQCEJIRT2KDzw+6mkhpUxvIdWwDo7OfPA9d1ZFHmtxTbSgH4XbsYuuuXNahdIdz7/0mgIoQQbczODQeZ9/o3VGsVMOqxm9zATYtaXn2lm3ZWEqwIIcRvROqBDF5+aB4ZabkAjJh8Hel+bpCc6lyJ3q6H0jDIz88GYHLPOHyDC/jgRM2UxN5unjzZsTf6yjeodjQ8g0ql/TgGt3aX8aqEEELU53A42L8jlZ83HWLyU7egKAoJ18fQoXcE60uLULV1v6FS7Cr5JWVEXcH2no0EK0II8Rvw45LtvPV/i6msqMZg0vP7v93O1/uPcSz5pOtK9Gf4u7vz9MDerClew/as0wD08YnhvvaV5Fv/QjVNTQsuizsKIcTlknu6kJLCsroNKuzbfpR1S3eSdSIfgGuGdiU2IRKdm5ax025k3T+/rilYOwOkVoOqa9s5TRKsCCHEr1hVRTVzpn/Fys9rhnS17xDATU/exLvfbqesogqNSUNppL3BUSr33xDGJ1lfYFPt6BQtD0TdQGe3ReRZa+pxd+uKt/stZBTNQhZ3FEKIy6s2Wb68tAKHQ8VWbcdhd+Dl44FGqyEmIYJhd/ahQ9dQ5zHe/ma0ei02uwOjUYubTovdoeLtf/HX9LuYJFgRQohfqawTebzy8HyO7D0BwHW39MD9ukj+/eUmAEL8vehxcwSfHt7jXInebtMQ0K6QZVk1x4S7B/Nkh0jKymZQUlkIQJD5j4R6P4NGMRDgMU4WdxRCiMusuKCU8tIKNBoNqsOOzWZHQeG6ET0Y88BgQjsE4nCo7D5yipLSSgb2iq450KCgKgo2HagalSY7ydsYCVaEEOJXJiezkLVfJbHonR8pK6lAq9Mw4elb2FyQz641yQD06xFBQG8fPty7q9mV6G8P6ctw31/Itz4HgE7jTwe/f2IxDXaeSxZ3FEKIy+fk0SxWL97OqWM5AGh0GtwMOtDUfHCPvOd6vIK8+GrtblZuPkBGThE+Xu5c1yOSCsVOTmc7dkUFapIOtapChdKwd71tkWDlMsitLKSwogStTouiKJh17vhfhIUhaxd8rKqq4tChQ8TFxQEQExPDG2+8QXR0tHMbgMFgYNu2bQCsWLGCp59+GrvdTlxcHPPnz8fLywur1crYsWPZuXMnNpuNwsLCZs8/ZswYUlNTna/37NnD0qVLGTVqlHNbdnY2cXFx9O/f37mC/fz583n88ceJiqpJ5/Lx8WHdunUXfD+EELBywU+8+ewiODMc2cNs5O5XxvLB2p/JLSxFUWDiyN7s0GaxYu8udG42Z6ACdYHK0x2vI1D5gPzSIwBYjIOJ8puJmzbgClyVEEL8dtltdnZuPMTqRdvYn1TzvUvRKNh0Gmw6BY1OwaG4Ua1T+PCHnew5nkW1rSYA6dohmFsHdAVAZ9RiMOlQVAUFFRUFVVHRGbVX7NpaQ4KVSyy3spAnk/9Dmb3Cmbtq0hqZlfDUBQcsycnJAKSlpREfH+98XbvNbDa7bKtltVqZMmUKGzZsIDY2lmnTpvHSSy8xc+ZM3Nzc+Otf/4qvry+DBw9u8fxff/218+9JSUmMGDGCESNGuJR56KGHGDlyJHl5eS7bhwwZ4gxehBAXx8nUbN786yLnaxXI93bjH0s34XCoeHkYmPz7a/nfkSQyrVYAxsRFsseRgZe2HD83K3nVHnRxP42X7TsqqEZBT6j3swSZ70VR2nYSphBC/NqsWrSNb+Ynkp9dDEBAex9uGncN7boEM/VfX+Oo/7GsKGw7eAIvs4nh/WO5ZUBXItv54lBVtp08QX55GYqioNdqncFKlaNt96qABCsX7IEdrzS53aQ18GavpymxlVFmr6DCXuXcV26v4unk2bhpdPgZLLzeYxpQE9g8t+dtZ7n3+z5/Sdq8cuVKEhISiI2NBeCRRx7h5ptvZubMmRgMBoYOHUpaWto51Tl37lwmTZqEXq932RYVFUWPHj3OOzBRFIVXXnmFpUuXkpPz/9m77zCpqvOB499zy5Sdme0VtrHA0qsoIlFBEREVe9eoqEl+amKJJvaoGI0aa+wlYi+IBbuABewUEel1qdv7zE67957fH4Ojq2gQgaWcz/PkiXPbnDN7He8755z3reW6667j7LPPBqC0tJTTTz+dDz74gHXr1nH11Vfjdrt55JFHqKys5F//+hcnn3zyVr2vouxq6quauf6sRwFw3DqWzyTayU88OwUcSY/SXIaO6co/584g7jgEXG4uO3Agbze9y+CUNYzLmof2o2lgHqMrXbP/Q4qrdwf2TFEUZff246xeHq+bgpKsxL7KJhpqWug/rBuHnDCUAcO7o+saM+euRHgMXJrAbejYUmLZktMOH8KJhwzC4zZpDId5ev48XluyiA2tLfTJyUUzLNC/fybV7J3/RygVrOxA3w267Sitra3JqWIAffr04dlnn2Xt2rWUlJQkt5eWllJZWYllWRjGr78lwuEwzz//PDNnzkxuW716NQ899BAzZszgxRdf/Mk5n3zyCQMHDiQlJYVLLrmEE0444Wev73a7+eqrr1iyZAl77703Z5xxRrKdoVCIzz77jBUrVtCvXz+uvvpqPv/8c2bNmsXYsWNVsKLsEVYsWM/14x+lvqqZaL6PUI9MflhW/uC9uxHubnDH7M8A6JGdzcn75PNS5SukaMFkoALfn5aZcjSlmbega94d3R1FUZQ9xndZvdpCEWzLwYrbuNwGj350Fdn56Rx26n6MPHovCkqysR2HWQvWMmXGAuYsXodtO4CGy21i2Q4Im2H9S1naVM8rixcyffVKLCexNmVQfif2Lcpjvf9T+OEaFakjtdjmG7eT6NBgZcaMGdx+++3MmTOHyspKXn31VY4++uhfPCcajXLjjTfyzDPPUFVVRUFBAddddx3jx48HEushvvvl/Ttut5tIJLJd+rAlox8C8OkeNKHh4OBIh3/0PY8uvvaF07Ld6dt0NOXnpoFtay+//DLl5eXJ9TFSSsaPH899992H1/vTB50jjjiCE088kZSUFBYvXszo0aMpKipi33333ez1TzvtNAB69uyJYRhUVVVRWJhIxXfSSScB0K1bNzweD8cffzwAQ4YMoaGhgaamJtLT07d1lxVlp/HF+wu49S9PEWmL4cn209Azs91+2y2ZnVbPimWJnPtH9exBXmEDL2x8G4C+AU8yUPmhHP9JKlBRFEXZzqrX1tPSGMK2bByZ+EE7FrVorg+SnZ9ORk6AuJXCy9Pm8fYni6huaAUgKy2FViuK5tEIaRaOSAQlccfhr++/TTAWw2e6OKZnOcf07E1ZRiYrg+t4pVmgCTdCAgIkEo97M/8R2Il0aLASCoUYMGAA48eP59hjj92ic0488USqq6t5/PHH6datG5WVlThO+zLKqampLF26NPlaiI77IwSMFLy6hzY7giMT7fTqHgJGSoe1qbi4mKlTpyZfV1RUUFBQsFWjKpCY7nXOOeckX7e0tDB//vxkIBEMBmlra+Pggw9m+vTpZGdnJ4/t1asXY8eO5dNPP/3ZYMXj8ST/Wdd1LMv62X3fvRZCIIRod6yi7E6klLzy6Ec8/s8pSCkpKM2m+ISBbJy17KfV6JsaMDWNi4fvxQLncz6u2wjA6Nz+jMmYQTD646ur4o6Koijbk5SSJ29/m6mTviQeTzyruNwmpstAOg6a/v30LF3TePezxVQ3tDKwvDNHHtgXX7qb4yY9jy1spIgjZCKzl2PAeYOG4DFNRpd1w2uaNMZaeGX9h7xT+TkxGcerabiFiSMkltz5n5M6NFg57LDDOOyww7b4+HfffZePP/6YVatWkZmZ+PWwtLT0J8cJIcjPz99WzfxNst3p3DXwku2SDWxrjRkzhgsuuIAlS5bQs2dPHnjgga2eLrVixQpmz57NlClTktvS0tLaLaifOHEir732WnLdyoYNG+jcuTMA1dXVfPDBB8nARlGU/82K29x/zcu8+3yiQGPffctIG1XOG58s2mw1+twUHxeP6MPkmrcIWmEMoXNB2b50Fo8QjK7YdJQgsSRfFXdUFEXZHqSU2JaDYSaeB9taw2iahkgxMVJcaKZOzHKIekzunPwJpx25D/v2L0XTBH8++QAyUlMozs/AchyeX/AN0kysMwQwNA2XrmN4dE7q2x8pJUtaK5hW8RWzGhZhSwfbcUg3oqTqYXQ0pIA2Z+dfEbLzt/AHpkyZwpAhQ7jtttt4+umn8fl8jBs3jgkTJrSbbhQMBikpKcFxHAYPHszNN99Mnz59fva60WiUaPT7nxZbWhIZFxzHaTdq4zgOUsrk/7ZUtjudNM2HaZrJbb/m/P/lu2v98JpSyp+sWYHE1LtAIMCjjz7K0UcfjWVZ9O3bl4kTJybPHzBgALW1tbS0tFBYWMjIkSN56qmnNvvejz/+OMcddxyBQOBn+/Tj9t13331MmTIF0zRxHIeLL76YkSNH/uL5P+7bD6/5c/s29/qH23789+0o391XO0NblJ3L5u6N1uY2bvm/J/nms0RK4QOPG8KGfA8zPlmEbf40UAHJCcMyeXLjywBkudL4W7euxMM3EpFBBG5KMm4i4N6PqLUGt1GCyyhQ9+MuQH13KL9E3R87Dytu89X0hbzz7Of027crJ14wCoATLxjFsHEDueDO13A0kEIkv7+Xra/j029WsU/fYgD6dSsgGIvx1DdfM3nxQja0tOBIiS4EKaaJrmlYtoN0En/zb5qW8+9lzwDg072MyBlM/9QMapvPwhTxZNvi0sQtL8RxdvyP/Ft6bwq5LZ+afwMhxP9cszJmzBg++ugjRo0axXXXXUddXR3nn38+I0eO5IknngDg888/Z/ny5fTv35/m5mb+/e9/M2PGDBYuXJhc5/Bj119/PTfccMNPti9btoxAIJB8HY/HaW5upqSkpN30o/9FSolt2+i63qFT0pSESCTCmjVrSEtLaxdAdhTHcWhubiYtLQ1N2/mzcig7zo/vjep1jdx96SSq1iTWnxx63nA+bWlhbXUzAIMPLOS90Lrk+ZpuU1BSjz81sWavl7eIs/LqiPICADoFZBv/wqX12ME9U7YF9d2h/BJ1f3SMxppWgi1hAKJtcZbMWcOsD5bSUh8CoPuAQv7v5qOSz4OLVtdy7cPTsJzvH8d1TfCnY/Zm1N5d0X6wqLAhEuacae9iO5JuaenMb9qIywRDCDBjGJ4It/U5iW4ZmdjS4Ynqtxng68pAX3dMzSDsfEGddTlSWkjpQQgNISR5xiO4tG478FNKaG1tpby8nObmZlJTU3/2uF1qZMVxHIQQPPvss6SlpQFw5513cvzxx/PAAw/g9XoZNmwYw4YNS56z33770atXLx5++GEmTJiw2eteeeWVXHrppcnXLS0tFBUVkZOT0+7Di0QitLa2YhjGVq3v2BkejBUwDANN08jKyvpVQef28t19nZOTo/6DorTzw3tj0azV/POPT9Pa1IbbY3L8NUfwzFeLaWxpw2XonHLy3jy6+msADNPCFwiTmdeMy5345erEzvuwr/8tgtFERrBU9wF0ybwLQ8/osP4pv4367lB+ibo/dry6qiZuOudpwqEo8ZiFHXdAQFqGj8EH9uSwU4fRa6/Sdj9c1wUdbCkRAjwuE1PXsB3J3gO6sSzaxsuLF3LN/geS6/OTC1y1/wj65OQSdsJcOv8u0GyE+D7QafQ1k5ubKE1xVd54pHRojX5OfdtkWsIzAAshQBMamnAjiZGVlYnXzN3BnxZb/Ay2SwUrBQUFdO7cORmoQGKBtpSS9evX071795+cY5omgwYNYsWKFT/Z9x23243b7f7Jdk3T2v0LrmlacuH2rxkhkVImj1cjKx3vu7/fj/++HWlna4+yc6irbGLJ12v5bOMSJt76JlbcJjM3lTF/G8PD780iFrfJCHg58sQB3LvgK2K2TW5uhPSCmmQKYg2dq3rsh9+6i2B0AwAFqX+mc9rFCLFzVy1W/jf13aH8EnV/7FjB5jCRUBRd04hLAImu61zy71PY5+A+2I7D599U8OqH8/nj8cMpL87B4zbRvTqaW4CmEcamzetw6cz3aIwlRmjeW7WCMwcMBuDIHr1oiYeYtO4TdMNOlsTQEOhCp2tafru/95qGG2kMJ7I/Gno6thVECDdS6kBicb0QHXOPbOl77lLByvDhw5k0aRLBYBC/3w8kpmppmvazU7xs2+bbb79l7NixO7KpiqIov8l7L3zBPVe8iPzB1IAufTrT89S9ue/NLwAo7ZxJ/9El3PFNYqF9j9wAdFrb7jqD/KtwRd8kRgxdBOiSdQcZKaN3XEcURVF2Y1JKls5bwxsTP6FzWQ4AmqHhS/UinUTdlEBOgCkfL+D1j76lqj6xLnrG3BWUF+cQETa15Ta2kEgRT65ZEeEgwwqLOalvP/YrLG73np/Xf8v7VV8S0Nvw6w5uzYUAgo6GyTpaIzUEPEMBSPeOIG5Xk+0/Ho9RzpKa47GdEBBHItA1H4aWvoM+ra3TocFKMBhsN+KxevVq5s2bR2ZmJsXFxVx55ZVs2LAhubj71FNPZcKECZx99tnccMMN1NXVcfnllzN+/PjkAvsbb7yRfffdl27dutHU1MTtt9/OmjVrOPfcczukj4qiKL9WbWXTTwIVKcB3cFeenToXgCF9i9H7enj828TrA0qKyCjawJIgpOphcswWBvrXMcCfGE3xmuV0y34Ij1m24zukKIqym3Ech3mfLGfKxBksn59YK1hf04xtaliGQDM0bCkI5Xi46on3idmJQowDyztzzEH92atXEQCGR8ftNZBS0mZZCBKZvW4ddSijyrphS4evG5eytHUNp5WMAeCAnEFUtC6gu/4KLi0xOqIhEULS3PwplrsrPd0vIYRGmncEad4RyXb3znuduN1AfX0DWVmZmHomLmPnyKD7czo0WJk9ezYjR45Mvv5u3ciZZ57JxIkTqaysZO3a738l9Pv9TJ06lT//+c8MGTKErKwsTjzxRG666abkMY2NjZx33nlUVVWRkZHBXnvtxWeffUbv3r13XMcURVF+g4rFG9sFKo6pEeyTzYz5FQCMHdGHBYEG5qxYA8BJ/XoQSlvKkuBaBvvXtKtID5DiPpSeOXeia74d2Q1FUZTdjm07fPbufN586hPWr6wBoLBrLkeeuT+ZxZmc+88XcX4wu0lqAlc8zqihPThmZH/KChOV6D+oWMXrSxZz9sDB6KaN2wSvTEzdi8Uh2+fh7Y2f8n71l9RGGwHYP2cgxSn5eHU3RxYMYHWdhcBBEw6CxKCMaRSQ7TsRiY3gp9OsXEY+hpaLS6vBa+buElMEOzRYGTFixC+m8J04ceJPtvXs2bNdQcMfu+uuu7jrrru2RfMURVF2uNamNp6+4x0AHLdOPN1NW2ka0muiCcGpx+/N5IYlrK1sRhOCC/cbwFxrJrXBRtKNKEdlfcMPl8ZJBN0y/6ECFUVRlF+hrqqJ1qa25OtAegrZ+ekIAW88OZMNq2rp1q+Io84+gIG/646mabz/xRJwG3hNDUPTsKUkbjtMOP9whvQuJmLFeXnRAl5YMJ/1rYnpYF2yfOR2WYfQvnseTvz/bSsfSW7rk1rGmIJhdPZ+vwg+3RXApTmbjtcAHYFOt6w78Ll77YBPaMfZpdasKO19V0MlFouxdOlS+vXrB0CPHj249dZb6dq1a3IbJBIJfPnllwC8+eabXHbZZdi2Tb9+/Zg4cWIy89kv7fuhY445htWrVydfz58/n9dee41x48Zx/fXXc//99yeLP/bp04dnn30WSAydXnTRRbz99tsIIbj44ou58MILt/0HpCi7mIaaFq454yFWL95ItMBPqDyD7yIPXQjOPms/Hlg2m+ZohBTT5OID+/J247uE7Sg+3ctfu/iQ8fY/AAkkUXsNbrNTR3RJURRll1NX1cTFR95FOBRBykSdFK/Pzf3vXU52fjq/v+xwDFOjx8ASAOYuWc9LU79m3tINiRpuUsPlNrFsB4SN5hI8OncWLy9aSHM0kUp+SEFnTus3AMMd4b2FEkcCEoQmERpIHA7K3ZtD8/elKCUPR8ZpDk/D0DMJuIcAIIQLJGjCA8JBSme3TOSkgpUdJGZX0matx2t22WaVoefNmwdARUUFAwcOTL7+blsgEGi37TvBYJBzzjmHjz/+mJ49e3LhhRcyYcIEbr/99l/c92Ovvvpq8p9nz57NmDFjGDNmTHLbaaedxt133/2T85555hkWLVrEsmXLaG5uZtCgQYwcOfIXC3cqyu6uam09V532IJVr6hB+k7Yeme32t2VJblvwKbaU5Pv8jN+/mFer3sDBIc+dwd/KPITCD23myjoeo3SH9EFRFGV30NrURlswgm3ZxON2ol5ei0NrUxvZ+en03acM23H4dN5qXpr6NSvX1wGQmxkgaMVwPIKQZuGIROr41S1NPP71HHQhOKSsG6f1G0DP7BxsafPGhk8wDQ23ZqILHcuxics41/QeT5/0MiynmerWp6gLvkTcqcHnGkAgZwiGlo6hpWE7ISQWSHaJxfJbQwUrW0lKi7hdu0XH1oemsL75VsABNArT/k6Wb9wWnWvqOQixbf9M77zzDoMGDaJnz0Qe7vPPP5/Ro0dz++23/+K+X/L4449z+umn43K5/uf7v/jii5x33nnouk5mZiYnnXQSzz//fLu1R/B9EHbRRRfx5ptv0tzczL333pvM7CaE4KabbmLKlClUV1dz9913s3jxYiZPnkxzczOPPvooI0aM2IpPSFF2rDVLK7n69Ieor27G63PT95z9eO+bldimxPJALB0ieYCEPjk5HDzIw+SqdwHoHSjiD4XraQm/BoDH6E7EWkni+0anNPPmbfYDiaIoyu6uqT7IW09/SqQthkSiCYHpNn6ytmNDTTO3PJFYltC1MJsTRw8iLcvLcZOexxYWUoCQoEtBeU42f9prH0Z37UanQCoRO8Z7VV/wTuVnVIbrSNFayTAFOjoODm2OgVurY13TSzSG3sIhCkCqezg5/pORUuIy8umd9zqW05Rsk6Gl7/SL5beGCla2Utyu5ZuNw/73gT/hsL75FtY337JFRw/o9PlWP2i0trYmp4rB91Ox1q5dS0lJSXJ7aWkplZWVWJb1i/t+rhBmOBzm+eefZ+bMme22T5o0iQ8//JCsrCyuvfbaZDKFzb3HF198sdlrNzc3079/f2644QbeffddLrroonZpqP1+P19++SXTp0/nqKOO4r777mP27NlMmjSJyy+/nFmzZm35B6YoHWDJ1xVcd+YjtDa1kZrhY/jFB/Hsh98QzpYES0imsQTYv7CQku7NvFczB4CDcnpyRObHtIQT//7k+E+hOONGLLuOiFWBxyhVgYqiKMoWchyH689+hMq19dguDT3FxHSbSEdi2zYffrOKnJIs/F43xfkZnDJmL3qX5TGoR6J8xqRFC5AmfLcc260b6JrA9BqcNXAwzfEgL6+bzvvVXxKyEjVUBqdlsXfKq7hEPNmOuDQJti4kSAhNeMhKOY4c38l4zJJ27XUZ+bjY/YKTH1PBym7s56aBbWsvv/wy5eXl7dbH/OlPf+Lqq6/GNE0+/fRTjjnmGGbNmtUuSNkSHo+HY489FoBhw4axcuXKdvtPOukkAIYMGUIoFOLkk08GYJ999mH58uW/pVuKst19PXMpN573OJG2GJn5aQw8bzjPfvgNtvnTQEU3LLxFFcxq3AjA6UWD6O9+mmA08e9EYfpV5AfOQwiByyhQQYqiKMoWaKxtJRaNk1eYiaZpjD19OIsWruOlZRXJrF5SCBDw4kfzCWT5OWHUQABOHzsER0o+WrOaJ+d9zYLaahwpMYQgxeVCFxpxx06+14trp/Jx7Vx0oTE8ewCHF/yOHLOJRdX/RUoDMBGARzjk+I7G1DPJ9I3D0NJ+0u49iQpWtpKp5zCg0+f/87iYXcPi6mNITMn4jkavvFdx6bk/d1q799nWiouL22VUq6iooKCgAMMwfnHfz3n88cc555xz2m3Lz/8+0h8+fDiDBg1i9uzZlJSUUFxczJo1axg2bFjyPYqL2xc8+o7b7U4uFtN1Hdu22+33eDzJfT9+bVnWL38QitKBPn3nG/7156ewYjYFpdl0OWUwL89cAECvAZ34lI0YpoXpthBI8osbWBO20YXGJV0Hk+ncTcSqRwg3ZVl3k5lyWAf3SFEUZdfRUN3MlCc/4cPXZtNvaDcuu+s0AEafOJSydWW8dsNGLMfBshLPb4JEfau9e7d/Xpm+aiXXfjQNgJLUdKIyjNuU6FocjDCm/v3z32EF+5GiexhTMIxsdzq200ply9NIGYZNU8404cWRMTJSDiXF1XOHfBY7OxWsbCUhjC365dJlFFCScTNrGq/ih3PI/e4B272NP2fMmDFccMEFLFmyhJ49e/LAAw8kRyR+ad/mrFixgtmzZzNlypR229evX09hYWJYdPny5cybNy858nLCCSfw6KOPcsIJJ9Dc3MyLL77Im2++uZ16qyg7n/de/IJ7//4ijiMp7d2JjMN68ubnSwA4aP9yPjUqSTOD5BU1IERiSoEQkKJ7uKa8O3bkJiwZxdCy6Z7zGH73wI7tkKIoyk7sh2mIm+pa+ezd+Xw1fRFW3MbtdVHYNRfHcZLrUmobg0Ti1qbsXAKXrqNpgrPHDaUgN5Xpq1ZyUJcyhBCMKO3CQaVlHFnek7QUjUu+uQs0GyG+z8wYphXIoSglj9NLDyNu17Kx+T/Uh17dtOZEIjAQmInF8ko7KljZAXL8J+Ez98OSG/CaO24O+Y/XrADMnDmTQCDAY489xtFHH41lWfTt25cnn3wS4Bf3bc5///tfjjvuuJ+kNr766quZM2cOhmGg6zr3338/5eXlAJxxxhnMmjWL7t27I4Tg0ksvbTeFTFF2Z688+iGPTngdgJ5DSmFYMdPnrABg7Og+vBeroC7SRFlZQ7JeSuL/JVd382OFE4koPGZ3ynP+i9so2vGdUBRF2UX8MA1xLGZhx20QgrzOGRx19gEcdtowAuk+moNhfF43hq6Rne5HukCYGqbLACmxbMkbq5YybeYq6sNtPOAdx+CCTpi6zs0Hj8aWDm9u/ATDsHE21UrREOhCx+82k+1xnAhLqk/ClkEEJuneMTSF38eRESTObp3Va2sJ+UtVGfdQLS0tpKWl0dzc3O4hPBKJsHr1arp06ZKcbrQlpJTJBeq7Y/7rXc3W/h23F8dxqKmpITd316gkq2yd2o2NPHHrm3z4amJx/MARPWnskcHXSzcAcMy4gbzcsISGSJicDJvMkg3JczUcjsz6hr0CawFI9exP1+z7MbSf1j9S9hzqu0P5Jer+SFi9ZCOXHXsPmqYRj1vEohaGoXPL8+fTZ+8ymlvDvPLhfN6csYDzT9yfg/cpZ8H6Ko596TnsTaMjclN5+AyvB5duMKK0C+cNHkJZxvcp5h9Z+SrTq2fRYoUw0PEabgQCS1r8q+8YSnx9cBl5AGxsvg+Q5PhPxtRziFlVOzSr185yb/zc8/aPqZEVRVGU7eyd5z/j3ite+q4wMV0GFrOx1M+SpRsQAo4/fjBPbfiWYCxGTkoKRwxI4bOmDaTqYQpczQxPXUaptxGAbN/JlGROQBPmL7yjoijKnq21KcQbT35CY20rAJqhkeL24PbYWHEbWxc8MeVL3pyxgEjMwjR0GlsSU8UMj47ba+BISWTT+lcBHFBcyl/23Y8u6RnEHIv1bdUUpiQCkOHZA1gd2sD60GL8ehSNMPmuWsq962lp+YAaeTKF6ZcB0CmtfSHsPSWr19ZSwYqiKMp2VLOhgXv//lLytePWmeeKY1fUoOsax500mMdWfk3UtihMDXDoEA+fNMxhsH8N47Lmof1gMLYw/QryA39UI7SKoig/oy0Y4Z3nPuedZz8jHIpiugwsQ8MyBJohsHWNUK6Xa56cii0lpqEz7sC+HD9qIFlpPiJWIoWwEAKPrhN3HAxNQxOCPw7Zh4KAj7crP+OtjZ+gC407B16Coen0SSvjom6HsLj6ftwihi4cBBIJGHofUlyq8PXWUsGKoijKdiKl5IFrJwOJICWe7qatSzrSY2DqGsecOpiHl87Bchy6ZWSw30CHTxrmkKqHOSrrG9rHJBpZKUepQEVRFGUzopEYU1/6ijee/IRgcxuGqXPIiUPpc0A5F93zejINMYDUBG7H4agR/ZJBSks0woOzv2Ty4oVc9bsD0QwLYTikuzUcaWE7MKP+K+6umE+rlRiB2SujFyE7TJrmB8Cvh/HrUZLD6OhomHTLuh2fu/eO/UB2IypYURRF2Q6klDz4j1f4ctpCovk+Qj0ySUYftsOo4/rywOJZSKBvXjZ9eob4snEpAKd1zmyXSSbBIWJVqPopiqIomzHx1reY8cbXCE1wwJGDOPa8EeR0ymD+io1oXgNT03DpGvamxfI3nj+WIb2KaYlGeXjOV7y4cAFt8RiGprGyuYq8svUgNpVLECCEZHp9PaZmsF9Wf8Z1PoCilDwcGcFxImiaB014EGiJ3F6aH6TAIYYQe+6aoW1BBSuKoijbmJSSR258jTcmzsRx64R6ZLUr8NjWWfDUmm8BGFpYQEGXGuY1rwbggi49yZf/4aeZT3Q8RumOaL6iKMpO6YcpiB3boS0Ypd/QrgAcduowouEYx//pIDqV5hCJxZk0bR7PvT0by3KQBvhT3Fi2A8LGdOs8OncWLyz4ltCmIOXYnn04c8Ag2kQLb3+tIzDQhCDuWMRlnL0ze3FG6VjyPFnYThs1rU9TE3yWHP/J5AXOAkAID5rQAIEUFpv5Mld+JRWsKIqibENSSh6/eQqvPf4xAD0P78sXDYnF8RJJqDOENw2OjCgrJKVgLYtb1yMQ/LVrd9Kcu5FEMbTMTdlhvq/PpEZVFEXZU/0wBbFtOcTjFiB4aNrfKeqaR3H3fP7yr5OwLJs3Zy7khffm0tjShuM4CK9Ac2uEdAtHJIo0tsZiTJw3FyEER/fszVkDBpHvD9Aab+OVNZ8Rl3F8uhdD09GFhi41jis6mGyXi6qW/1Ibeh7baQYEMbsaSGTx0jUfthNCEgNUGuJtQQUriqIo24iUkidve4vJD38IwLATh/BxazMAlikJFkM8I3HswV2KEHkrWBmqxhA6V3QrxR2/C4mF1yynPOdpHMeiqm4e+dkD8bg6d1S3FEVROlxrUxvBljBW3MK2EwGHrglq1jdS1DWRkctxJJfc8SqrNtQDsP+grgwdUsIfp76BLeJIEUdI0KUg3e/l6v1HMCi/EwWBACErzKR103mv6nNa4234tBAZRhs6Oo7mEHF02sLPsqj5HWwZBHQyvGPJC5yJx+wCJLJ69c57fYemId4TqGBlB4hZVUTj9eiOjhBim9243xV8jMViLF26NFlYsUePHtx666107dq1XbFFt9vNl19+CcCbb77JZZddhm3b9OvXj4kTJ5KamkowGOS4445jzpw5WJZFU1PTz77/Mcccw+rVq5Ov58+fz2uvvca4ceO4/vrruf/+++ncOfGA1adPH5599lkgkd/7oosu4u2330YIwcUXX8yFF1642fdQlF3JM3e+y4v3TwNg3+P24tNwK8FwFKeTRmOBnZwK1i09hXjuYqrDDbg1k6u7F0D0LiQSn2sA5TkTMfQMHMfBo+m4jNwO7JWiKErH2lhRy5O3vUU0khitME0D02OAI8nIDRCJxvG4TTRNsG//UjLTUvj9EfvQtTCb+dWVaC4N20msPzE1DVPXMTw6Ywt7ELIivLL+Q96p/Iw2O4IhdEbldKWb8SqmiCfbEJcmTrwvjoySmXIUeYHfb7Yor0pDvO2pYGU7i1lVLK4+GluGktt0zUfvvNd/c8Ayb948ACoqKhg4cGDy9XfbAoFAu23fCQaDnHPOOXz88cf07NmTCy+8kAkTJnD77bdjmiZ///vfyczMZMSIEb/4/q+++mryn2fPns2YMWMYM2ZMcttpp53G3Xff/ZPznnnmGRYtWsSyZctobm5m0KBBjBw5kj59VFo/Zdf13D3v8dw97wEw9JjBfB4P0dQaJpDlYVWncPI4lyeG7Lye6qhDiu7hmu5pWJH/ABBw70v3nMfQN2WWURRFUaB6fSOL51Yg3QaGz4XuNrAsh5hLcNukmXQtzeHy3x8MwCmH7oWmCeK2zWtLFnHfV18Q3xSoeA0Tl65jSyd57Q9rZjF5/QfoQuOg3L05qvMBpIgqFlXfgZQaYCDQ8QiHwrTz8Ln6q5GSHUwFK7/RtxsP2ux2TfPTJ38KltOELYM48vuHFccOsbj6eDThwtTz6Zn3HJAIbJbWnJo8rl+nD7ZLm9955x0GDRpEz549ATj//PMZPXo0t99+O263m4MOOoiKiopfdc3HH3+c008/HZfL9T+PffHFFznvvPPQdZ3MzExOOukknn/+eW666aZ2x30XhF100UW8+eabNDc3c++99zJ27FggkQP9pptuYsqUKVRXV3P33XezePFiJk+eTHNzM48++uj/DLgUZVt48b6pPH3HOwDsPW4gXzltNLa0kZ7qxb9PGtSGMUwLX2qYnIImdEOSonm4vruLSOQRANI8B9Mt+340zdORXVEURelwkbYoH70+l0NO2Afd0Bk4vDvHXzKau96dlUxBLIUAAU5lA26vSSxu4TINNE3QEo1wzpRXWdfSjOU4uFwOXrfA1GxsorhcseR7jcrbh7poM2ML9iPXk4llN7Gh+Tnkpuc2AeiaB0fGcBvFKlDpACpY2aEEOzItRGtra3KqGHw/FWvt2rWUlJQkt5eWllJZWYllWRjGr78lwuEwzz//PDNnzmy3fdKkSXz44YdkZWVx7bXXMnLkSIDNvv8XX3yx2Ws3NzfTv39/brjhBt59910uuuiiZLAC4Pf7+fLLL5k+fTpHHXUU9913H7Nnz2bSpElcfvnlzJo161f3R1F+jZcf/oCJt70FwF5H9GeuHqO+sY20gIfSUQVMXbuStMwgeUUN32cutuDKHhEikRcByEwZR5esO1RVekVR9mi2ZfPR63OZ/MiHNNcHcXtdjDx6L4QQDDqoN+bMb7AsB8tJjIxoQjD+mGGcMGogQoAjJZoQpLo9dAqkUhAIMKa8lHsqnkikId6UghigMraBnuTg0d2c1eUILKeFypYHqQ2+iO20ACBwoQkvEqvDPhNFBSu/2ZaNfgg04UfDQAoLKR265zxGiqtnu6NcRv42HU35uWlg29rLL79MeXl5u/Uxf/rTn7j66qsxTZNPP/2UY445hlmzZrULUraEx+Ph2GOPBWDYsGGsXLmy3f6TTjoJgCFDhhAKhTj55JMB2GeffVi+fPlv6Zai/E+vPvYRj/9zCgCDD+vHfJdFbUOQgM9N19GdeW/NCgzTIr+oIbleRcPhuPyvkfZ6AHL8p1GScSNC6B3VDUVRlB3qhymIAfxpXtYur+aFe99nY0UdAMPHDqDvprTE37FsB9tx0HUNt6kDgr16FbKwroYHZ33JQV3KOL53XwBuHTUaj2GyonUd7g1gSTbVkwdd6KR63MnrSilZUfsnItYKBCaZKeNobHsLW4YTgYpUWb06kgpWtjNDS0cXPmwZwiG2U9zwxcXFTJ06Nfm6oqKCgoKCrRpVgcQUsHPOOafdtvz874dJhw8fzqBBg5g9ezYlJSUUFxezZs0ahg0blnz/4uLizV7b7XYnK3bruo5t2+32ezye5L4fv7Ys9UuIsu3VVjaxcXUtC2etSk79GnRoXxb6JNV1QfwpLnqOKeLtNYlgeXTfbFbKjaTqYXLNFoalraS7txaA/NQ/UZj2d1WVXlGUPcYPUxADSAmWZePze9B0jT57l3HKRaPp0rMTsbjF4lVV9CpLPFMIj4bQBaZpYDsOlrD595xPmVdfldgvRDJY8Rgmy1vXcdey54jLxPOAWzMxNQNHOmS43EStjbiNTgghyPGfQltsAXmB8biMPApS/6Syeu0kVLCynbmMfHrlvZbIBqZv22xgW2vMmDFccMEFLFmyhJ49e/LAAw8kRyR+rRUrVjB79mymTJnSbvv69espLCwEYPny5cybNy858nLCCSfw6KOPcsIJJ9Dc3MyLL77Im2+++ds6pSg7wHsvfME9V7yIdL6fztn/4F4sToXK2hZSvCZ9xpbwZsUyAE4YVMJiPmewfw3jsuah/SAmSff/haL0S3d0FxRFUTpUa1Mb4VAETdPQDA3HcoiGY+QWZnL2FUcwYL/uSAkfzV7OxDe+ojUU4ZFrTyYibGq6W9hCAhZSAAKiNRsoTE3jvMFDOKxbebv3ynSl0hwLkm5ESTMkOnEEFkXuSpqaz8MOd6Nb9kMIIcjyHUmW78jkuSqr185DBSs7gMvIRyMbwzB26C+oP16zAjBz5kwCgQCPPfYYRx99NJZl0bdvX5588snkMf3796e2tpaWlhYKCwsZOXIkTz/99Gbf47///S/HHXccqamp7bZfffXVzJkzB8Mw0HWd+++/n/LyxJfIGWecwaxZs+jevTtCCC699NJ2U8gUZWdUW9n0k0DFceksTdOorG3B6zEYcHgXplQsBeDYgcUsFV/iFa0/CVQkgpLUU3Z0FxRFUTpcLBInHrNxeTQMQ8cCXF6Tv/zrRLr2KWT+8o08/trnrFiXmA62b79SbNvB8Oi4vQYCQdiKY0uJAH7ffyD/t/e+uHSdlcH1vLr+I84pG0eGK5UsdxpX9xpHdePvMUUcDQd9U1FI6WTi0nORRBGoxCY7MxWs7AZKS0t/Ug+ltLT0J1OmfmjcuHGMGzdus/vmz5+/xe998803b3b7D4OfH/suePlfftwvv9+PlN8/KP7wn3+8r7CwkGAw+D/fQ1G21MbVtT8KVDRaBubS1NCKx22w15HdeHX1YgCO7l/MKn0WUTvGoDTaBSoAAknEqlAV6RVF2WNIKfn8/W+ZeOtbxOMWjuOgbxpZ0YSgrrWNZx95ly8XrAGge3EO5x4zjL5dC4jZNkvX1yOEwKXrGLpG1LLQhODQbuXUxRqZtG4aXzUsBGBa9SxOKEqkMi5NCdDW4iBxSCQ5EoBOWdatZKQc0jEfhvKrqGBFURRlCwRbEotBHbdOPOAiXJaGk2LiNnX2Oaobk1clApVxfYtZY84mbEcp8qZxdM4yYj9ZPqXjMUp3aPsVRVE6SsXSSp66/S2WzluLYzsYATe4DMKJvMCkuNw4usaXC9aQlxngzCP3Yf9BXRECpq9ayQOzv0xk+tItMGOYQkNzOTjSYUr1NL5tXYKDQ4YrleMLD2L/nIE/aoEEJEK40XAhcTZb0FHZOalgRVEU5X9Ys6yKuy9/kWi+j1CPTL7LQawJwX7H9OClVYlf8w7vU8h6zxzarAidPQEuLFxANL6YxC95AnAAndLMm9WoiqIoe4Rn7nyHd5//AiklRd3yGPd/I5kwaQbhSAzLcTA0jbjHRdeueVxz7miG9C7GNHS+ranmni8+Y0FtNQD9CzJpy14P2vezRoQmmdPcSJrpZ1zn/Rmdvy8uzSQU+5ZQdB65gTMSxwlzUxpiVzK7l7LrUMHKVvjhdCNl16P+fsqvUVfVxLW/f4iWSJTQwE7JQAUgmCeTgcphvYqo9n5NyAqT7/bzl6JlRONzAUFZ1l0E3EOJWBV4jFIVqCiKsscIZPhICXg44f8O5qBj9mLVxgZCkRhxy0Y6Es2lEY1btIQiDOvfhQ2tLTww60umr06UKuiWmcVFQ4eRnaZx6dezERhoQuBISUzGGZE7mN+XHoHP8BCJV7C68QGaIx8BglTP8ERWVs2P7YRwZKIYZEdnZVV+HRWs/ArfpceNxWJ4vd4Obo2ytWKxTV9WuqprofyyYHMb1/7+YWo3NmF2TgUhsE2J7YFYAMKdEscd0qMzdb55tFpt5Lr8XFK8kmj8KwC6ZN5Glu9oABWkKIqy2/lxzZQNq2qpXFPHCf+XWDMy9rT9OPjYIfjTUlhT2cB/XphBbNPcWJfLwL0pDfF3Ply9iumrV5LtTeFPQ/bhsG7laEIwZeMMYk4Ml2bi1j1Yjo2QkjEF++ESLaxrvJP6timAg6nnURD4I26jBCF0eue9rtIQ78JUsPIrGIZBSkoKtbW1mKaJpmlbdJ6UMlkdXtVT6FiO41BbW0tKSspW15VR9gyxSJwbz3uciiWVGG6DzqN7sra1kmAJyQKPAL8rzaMldQEt8RBZZgp/LVlDNP4FACWZN5PtP6FjOqAoirKd/bBmiuNI4jELx5GkZfjY5+A+lJTnY7oMHODhyZ/y5syFxOI2jhtMj45m6EQci6jr+xkPJ/bphyYEx/TsjddM1Ep5Zs07LGmpwKe3EdAdPJoLR3NocwyisU9Y3PQfHKLoIkBe4Gyy/Segie+LPqo0xLs29bT2KwghKCgoYPXq1axZs2aLz5NS4jgOmqapYGUnoGkaxcXF6m+h/CzHcfj3Jc/y7RcrEULQZ/wwpq2oINifdoGK6YoTy15Cc7yVDDOFv3XZSDT2CQDFGTeS6z+1YzqgKIqyA7Q2tdEWimBbNvGohSSxlu/Uiw6luHte8jjD0FiwsgqPy2TMiF7cs2oWtrBAbKqXAsxvrKZbUQ4uXefUfgOojTTyWMVUvqj/FoByXwojU2fiEvHkdePSxG+cSKMwyfWdTF7g9+haYEd+BMoOoIKVX8nlctG9e/fkVKIt4TgO9fX1ZGVlbfFojLL9uFwu9XdQfpaUkoevf5WZb80DYK9z9+P9xWuwA/woULEo6lZDs2WTZnj5e5caorGPAShKv4a8wO93fOMVRVF2oHXLq4i2xRKZujSB22UidEHffbuypKIGy7bp160TuqZx+e8PItXnoSoa5IGNc8F2sGRi+pcuBGmB9tPr71sxiRXBdaSbAU4sGsVeaR6W1DyPlAZgAR48QpLpzqXA9ya6lrLjPwBlh1DBylbQNA2PZ8sLCDmOg2maeDwe9ZCsKDu5SQ9OZ8rEmQDsdcZQpq5YB0DfXp341NmIYVp4UqLkdm7EdDn4dBdXljUQi00HoDD9CvJTz+2w9iuKouwoqZl+pATD0PH63EhHEtdg4vtzmb1iAwXZqTx41YmYhk5xfgbBWIxnZs0jYiXWrJiahscwkEC+309tpJEcTwYAJxUdwuLW1RxeMByP7qYu+BpSRkhkVRRoyZopqEBlN6eCFUVRlE2mT57FE/96E4D+Rw3go8oapITy3nnMN+pI8wfJK2pIJgTT0bima5BY7H0AOqddRkHqnzqq+YqiKNuVFbd594XPGT5mABk5AQq75uLPDxCxbMJAOMNDOMvLV0vXkZnu4+RDB6P/4EfasBXnw4rViR99XBpuQ8ORMTQzykNrnsVlaNza/88Ymk7vtC70TutC1FrP6vr7aAq/z3fp33WRAgKkdH6uqcpuRAUriqIowJyPF3PX5c8D0GNED2bFQsQtm6KSDJZntxKOt1H2g0BFIDkiay7xWGL9WqfUv9Ap7cKOar6iKMp2tXjOap649U02rKpl7fJqzr/xOByXTuvenQiGo1iWk5gOJgSH/a435xw9DJ/XxeLaGrJTfOT4fOSk+PjzsL14YuNzyXopQkssrq+J+eiX0pVWK0SGKxWAqLWBJdUnIYljaDlIbKS0E9XopUpBvKdQwYqiKHu8Zd+s5aY/PoFtOZQMLGZ5mkaoOUxOrp/GbpKa5hA5m2pBpuphsswgA31rGRRYD0B+6v/RKe2SDu6FoijKttfcEOT5e95PruPrs3cZR48/EICWUIRo3EITAiklhq5hGjpjf9ebGDb3zPyIN5YtZVRZVyaMHAXA0OICXqzXsKTEkpsCFgS/Lx3L2ILhgI2UFkIYuI3OpHsPwm2UkOs/HctpUimI90AqWFEUZY+2saKOf5z9CJG2GLll2dSVp1NX04Tf70YfnMLqumrcus6QHoJ0fQ3jsuah/WChfWrKGRSm/U1ll1MUZbcipWT65Fm8eP802lojpGf7Of3Sw9j3kL7YjuSL+RVkZ/gA8LhN3K5EeYaYZfHemhW8+tFigrEYaW4PexV0RkqZ/J50SAQqGhpuzQAh6J1WRmv0CzY230OW7xhy/CcBUJI5Idkml6ZSEO+JVLCiKMoea+XC9Vx31iM01QVJzfHD70pYt7YWl0sn78BsvqhejybgiKFe1kbn8PvC9oGKBErT/k8FKoqi7PJ+XNwxkJ7Ckq/XEA5FGX3SUI7/08H4Ah6WVFRz/4szWbWhnnOO3hfLkFiGhaZphM04LRkWTyz6Gpeuc3yvvvxhryGkuj1UhevJ92YBkGZEcIkIbmHiIDFFlNbW62m25wEQjM5JBiuKooIVRVH2SG88OZMHrp0MgBQghhWzZG0tQkCPQ4v4oHI1AMcNzWR+2zy6eILtAhVI5KGJ2mtwm512cOsVRVG2ne+KO7YFE8UddV3g9Xm4YeIfOPyM4XTpmViXcv9LM3nn00VICb265BPI8FDVNY4tEutOpAAEDMrI4oaDRtE9K4vWeIjHVr3ORzVzuKzH6eS7JWfnTcfcVC9FFw4aDvF4Jl6zlE5pfybNM6LjPgxlp6OCFUVR9jg1Gxq+D1SAtu4ZNLYEAdhrbBnvVK4E4Ji9cpgfmQPAiKzczVxJx2OU7oAWK4qibD+tTW0EW9qShR29PjfhUARNF5T2KODDWct57LXPaWoN409xc87R+zJqnx4srqvF9Oh4hIYmBLaTqJ1y3YiRlGVmMLXqKyatm0bIDuM3Uog6MVINg4ChgfQiCcOmFMR5gdPolPYXNGF28Keh7GxUsKIoyh7nydveBsBx67SVphEr8APQY0ge71QnApUxfXNZYicClcNzA5SZLyHbXUWnNPNmXEbBDmy5oijKttXcEOS5u98jGkmMdLg9LgxDw4onFr+HwjEemvwpwbYohwztwdlHDSXN72VhTTXXfTidiGWR5vbgMnQsx0HYNmsjlTz17STWtFUhEBySN5Tjiw7Cb6QQin6DQKBpJhIdx4kghE5myuEqUFE2SwUriqLsUT6eMpcPXp1NNN9HqMemFF+Apcf4XFSDhOFds9jg+gbHkeyX4WeY7zUcGcNr9qJr1r3EnTo8RqkKVBRF2WVJKfnk7W94+o53aG4IIt0Ghs+FcBuEbQe56QnRn+Lm4lMPJODz0LdrAa3RKP/+7BMmL15I3LExTRtcYaSmg3TQNXhuwxTixCgPFHNW6RGU+AqI23WsabiNYPTrxPtjITDQNJeql6L8IhWsKIqyx1g+fx13XfY8jltvF6jEfZKmchOkpH+ndCIZS4lZcXr5Uzgi430sJ4hLL6Q890lcei5eundwTxRFUX6biqWVPPSPVwAYMrY/r65eh7OpfqPUBEJChEQQMax/F6SUTFu1gru++Iz6cBsBl5tj+3bntcZXQdjfX1jqjMk7nM7+TH6XPQCwqQ0+T1XLo9gyiC5S0YQHR0aQxABVL0X5ZSpYURRlj9BQ08KN5z1ONBIn0D+fpu9GVNyS5m6ADp0CHgKFa6mLtdHZ7eaMvM+x7FoMLSMZqCiKouyqHMdBOhLd0OnSsxPH/XEkffYuQ89K4a0bniduO1h2IkDRdIHj0pPnLm+o55oPpwEwtls5f95nGE1OI+9+LbAcgYbA1EwkkqG5Peni60QwOpf1Tf8mYq0AdHJ8p5Cfeh62E1T1UpQttsXByr333ssf/vAHPB4Pa9eupaioSKXrVBRllxCLWkz4w+PUVTaRkpFCtCwDmkLEvZLm7iBNMByH8p5NVMaaSDUMLihahGVVoAkP3XMex2t27ehuKIqibLUNq2t5dMJrDD6gJ+PO2h+AY88biZSSF96bSyRug5TouobHlXg81HWNuG1j6jrlWdmcO2gIA/MLGNKpMyErzKsrPyTmbMrqpRmYmo4lLQCaI5+wuv5SAHyuQRSmX47X7LbpWL+ql6JssS0OVi699FJOPvlkPB4PXbp0obKyktxc9Sujoig7Nykl/7nyRZbMXYPQNfyH9WTJxjqiedBSCAgQSPr0CVIZb8IUgr+VbsSyFgAaXbPuw+8e3NHdUBRF2WJ1VU20NASpb2igpSbGrOmLeP+lL7HiNkIIjvj9cDQtMefrjRkLmPjGV9iGg+7WMd0GliOJGg5//2Qqx/TpzVkDE9+B5w4egpSSz+rm8/Sat2mItpCqR0gzJKYwcAjS5iQWyQfcQ/G79yYr5UjSvYeqH7iVrbbFwUqnTp2YPHkyY8eORUrJ+vXriUQimz22uLh4mzVQURTlt3j1sY+Y9vIsALqcPJjZG2qwTElL0XdHSPJL6om42xDAlWVtONbnAJRm3kx6yqgOabeiKMrW+K5mSjgUwbYd4jEbKSVZeWmc8pfRHHbqsGSgAnDQ3uW8+dUiVmltOJoN2Ml6KVaomQU11e2qz79T+RnPrn0XgBHZJfQ0X8UUcQQSQzhEHBde8Wc00Ylu2fd3wCeg7G62OFi55ppr+POf/8yFF16IEIK99977J8d8dzPbtr2ZKyiKouxYsz5cxOP/nAJAt3H9+GpDDQAFw7JpbKvDMC1yOjWSmhEG4JyCKIb9PgCd0i4hx39yxzRcURRlK7U2tSUCFcshGt00RUvX+Mu/TmTvkb3ZWNvMw5M/5Y/HDadTThr+FDeXnn0Qn096HtuRxGxrU+UTuGDvfTl7YPuR5f1zBjG7cTEnFB1MiSfKoup7kFIAiWe/FN0h1Wif6F1RfostDlb+8Ic/cMopp7BmzRr69+/PtGnTyMrK2p5tUxRF2WrrVlTzrwufwnEkhUO7MDfUCkDXvfP5oq2StMwgeUUN3yUEo6+xgWL3bABy/KfQKfUvHdV0RVGU38xwGcTjFm6PCyEgMy+VVz6Yz9NvzSIWt8hMm8dFpxyYPD5mO1hOYpqYR9fRhWC/omKWta7lmTXvcGH3E8jzZBEwU7iuz7lI6VDV8jBSJn7sEegI4emo7iq7sV+9wL5v37488cQTDBs2DK/Xuz3bpiiKslVam9q44ZzHaGuNkFGSyZocEysYoVPXDOZqNRiaRX5RQ+KnQ6CHt4rjcxOBSrp3FCUZE9T8akVRdilW3Gb6K7Mo690ZSHy9pfg9ICFqCm6fNJN19S0Yusaph+3FSYcMane+oWk40sFnukCAFBavV01jfnARAB/XzOXE4kOAxEya1fV/pTny8ab3MtGFDylsVTNF2ea2aoH9+PHjOeyww1SwoijKTse2bG654Ek2rK7F9LmJ79OZ5tpm/JkeNnSKEAvblHfSQUCqHqZHSiWHZixEEyD03pRl/QchVFZ3RVF2HetWVPPgP15hzdJKRp2wN2aal7ZYHEdKwlkewtkpxGua6NElj4tPHUFpp0zWtzTz5Ddfc9mw35Hu8ZCWIog4Dogwbl+YQEYr81rrSDN9nF5yGMOzByTfTwhBwLMPUWsdEWsVjozhEAepaqYo216HLrCfMWMGt99+O3PmzKGyspJXX32Vo48++hfPiUaj3HjjjTzzzDNUVVVRUFDAddddx/jx45PHTJo0iWuvvZaKigq6d+/OrbfeytixY7e0q4qi7MIe++cUvp65FAnkHtOXb9fXYpga+iAvdc0NZPoM0vNq6OpZw7iseWibBlBaLTe9cx5E19SPMIqi7Bps2+GdZz9j0oPTseI2PQYWM/TwAby0bgPhSAwpJZYjkY7k5DGDOf3wxHrjFxbM58HZXxG1LcoyMjmkezElPaoJ21HijoWDg0AwLHsI47scid9IoTU6m9bIl3RKuwCAbN+JZPmOx7LrVc0UZbvq0AX2oVCIAQMGMH78eI499tgtOufEE0+kurqaxx9/nG7dulFZWYnjfD/k+Nlnn3HKKadwyy23cMQRR/Dcc89x9NFHM3fuXPr27btlnVUUZZf03otf8NrjiWkJ3U8ezFfra5FIOo3IZU5jJaYOA/uGabVq2wUqAH4jRqbp6qCWK4qi/DrV6+p58B+vsHz+OgyXzqkXHcqYU4exYl0tbZEYpqEjAAOJbUuGDyxjbUsz/5zxEQtqqzE0jXMHDeH4Xn1YH6km5sQwNR0pHSwJpmZwZKf98YgYaxtvp6HtLQDSvAfic/VFCB2BjsvIVzVTlO2qQxfYH3bYYRx22GFbfPy7777Lxx9/zKpVq8jMzASgtLS03TH33HMPY8aM4fLLLwdgwoQJTJ06lfvuu4+HHnroN7VXUZSdU21lE5+98w2P3vQ6AF1G9+KrqjoAyg/ozGeNGwDJwYNdrI6upbsn2C5QgUStlYhVgcso2MGtVxRF+fUevuFVls9fR5denfjTDcdSWJZLxcYGbntyOtGYhWno6LqGBjjS4rWVi3lt9RIsx6FXdg5X7z+CbplZbAzXMrdhCQAaGj4jBVvaWDJONPoBi1uexHaaMbQsOqddSorZp2M7ruxxftXE7EAgkFxgP3z4cNxu9/Zq12ZNmTKFIUOGcNttt/H000/j8/kYN24cEyZMSK6f+fzzz7n00kvbnXfooYfy2muv/ex1o9Eo0Wg0+bqlpQUAx3HajdpsLcdxkFJuk2spux91f/w27734Bf+5chLSSaTK9JdmsEAm/n0u6Z/D520bADion5/V8cWA5Pj8zU1h1XFpxTvV30HdG8ovUffHnsdxnGSNlDP/djizP1rMkWfuj9AFL0/7mqffmk0kZiHdEHHZaMJBAkjJV1UbEAjOHzKUk/v0QwjJlPUzmLzhA+KOTYrWhl+30NDw6G3s5V9KMPQBhtDJTDmagtQL0LUAUkqkVKmJd2U7y3fHlr7/Vq0iPfPMM2lqauLpp59m5cqVXH755WRmZjJ37lzy8vLo3Lnz1lz2f1q1ahWffPIJHo+HV199lbq6Os4//3zq6+t54oknAKiqqiIvL6/deXl5eVRVVf3sdW+55RZuuOGGn2yvra392XU5v4bjODQ3NyOlbFeISVFA3R+/RUN1S7tAxTE11hd4ceIWmZ18LPQ2IG3oX+Rmo74YgN/nhvAyd9MVBCABjQz97zQ16EBNR3Rls9S9ofwSdX/s/hprWgm2hEHCwi9X8/XMFVx69wm4vS7cqYLh43qzZNVaHpsyh2Vr6zENjRH7lvJEzSJsLZ68ju7An0u6UpaTQaE/wMKNS3m+ZhrrojXoQmd0eheKPS/j+sE5prARsheZ+uW4Yr2orwsD4Q74FJRtbWf57mhtbd2i47YqWJk/fz6jRo0iLS2NiooKzjvvPDIzM3nllVdYu3YtTz311NZc9n9yHAchBM8++yxpaWkA3HnnnRx//PE88MADW52d7Morr2w3GtPS0kJRURE5OTmkpqZus3bn5OSo/6AoP6Huj61XuaI5GahIAcG+OThuA7fXoKU7hEMWxVluRM5apAOjs6BbygcAZPtOJT9wPjFrLW6jZKec/qXuDeWXqPtj91ZX1cRN5zxNOBglFo1j24m/97I5lRx8bGLdcCgcZcKd79AWiVFeksMlp40gYjo88/IyHMsGJF7DRAro17WUrpkZvFE5k9crZ2BLm/LUYs4tO5pMo57F1SDxADpgI7DpkfsvUlxqve/uZmf57vB4tqwuz1YFK5dccglnnXUWt912G4FAILl97NixnHrqqVtzyS1SUFBA586dk4EKQK9evZLZybp3705+fj7V1dXtzquuriY//+cXf7nd7s1OadM0bZv9EYUQ2/R6yu5F3R9bZ83SxIip7dYJlWdipbmRSFL2CbAs1ECqR6ewrI76eJRePtg/dSpSSgLufSnJvAFNmHhdhR3ci1+m7g3ll6j7Y/cVaokQagkTj1o4m34BN10G3foWJf/eAZ+XY0b2x5GSk0cPAk3w789mErEsAExNx9R1LOkgNEFltI5XN3yEqRmcXDyaQ/P3RWCxvvEhJBHAxNTSkVg4MoamudS9tZvaGb47tvS9typYmT17No888shPtnfu3PkXp1v9VsOHD2fSpEkEg0H8fj8Ay5YtQ9M0CgsTDxzDhg1j+vTpXHzxxcnzpk6dyrBhw7ZbuxRF2fHWLKti4m1vEc33EeqRyXel6F09PSwLNSCQ7DMgxrpoI5mm5LS8WThOG26jmG7ZD6IJs4N7oCiKsnlW3OaNJ2cSjSSmZXm8LlxuAytuM3vZBr6oqOKUMYMBOPWwvQBY19zMDR9/wLzqSgzTwuPScGkgsdCcxENhia+Ac8uOomeglHxvFqHYAtY1TiAcXw6Aho6UFlJYHdBrRdm8rQpW3G53chH6Dy1btoycnJwtvk4wGGTFihXJ16tXr2bevHlkZmZSXFzMlVdeyYYNG5LTyk499VQmTJjA2WefzQ033EBdXR2XX34548ePT04Bu+iiizjwwAO54447OPzww3nhhRd+NrhSFGXXFGmL8s8/PUHYsQn1yEsGKuEcSa0/sc5s9BAPFdHlGEguKlqJ41SiCT/dsx/D0DM6svmKoii/SGiCDavrcFwGpt8FboOwlLR09vH4u7MwXQYjh3QjPzsxVX1FQz3nTnmViG3RPSeV+sBKhGZvupYER0NqMQBG5O6FI6NsbP4PNcFnAQefaxCh2Dc4MoJDTBV3VHYqWxWsjBs3jhtvvJGXXnoJSAwlrV27lr///e8cd9xxW3yd2bNnM3LkyOTr79aNnHnmmUycOJHKykrWrl2b3O/3+5k6dSp//vOfGTJkCFlZWZx44oncdNNNyWP2228/nnvuOa655hquuuoqunfvzmuvvaZqrCjKbkJKyX1XTWLdimqcAj8IgW1KohkQKkocs1cXkwprOSC5uLQR4SwEBF2z78XrKu/I5iuKomyWlJKG6hay8tPQdY3j/nIIM/8zhU2DIshN+dbzA16uGD86GagAlGVk0j8/n4F5BRzQLY/Lv5mPJcGSiRESXQeX6/sMXlUtD1MTfAZN+OicdjGZKeOI29WquKOyU9qqYOWOO+7g+OOPJzc3l3A4zIEHHkhVVRXDhg3jn//85xZfZ8SIEb+Y/m7ixIk/2dazZ0+mTp36i9c94YQTOOGEE7a4HYqi7Dree+ELpr8yGwmkDS2m2mglWEIisRfgc0doS1sHwOkFFqnMBKAw/QrSvQd1TKMVRVF+QWtTiEdufI1Vizfyr+fPJ5DuI7MoA5ffTdyysexEildD17jqvEPp360TU1euIMVlMryoBE0I7j70cDQh+KxuPjEnjoODhsCtuRACBN8Xl8r1/564XUtB6gXJgEQVd1R2VlsVrKSlpTF16lQ+/fRTvvnmG4LBIIMHD2bUqFHbun2KoihJKxeu54HrJgOQN6YnC0OtBPuTDFRMV5yC7nU4SA7MhHL3uwBk+Y4lP/CHDmq1oijKz1vw1Soe/MdkmmpbySvKpLkhRCDdl9xvOw66JvC4E+vsHCG5+oOpTF+9kixvCq+ceCpuw0ATgpm183hoxWQcHAyh4RYuhCbIM2tpab2YqOcu3EYhhp5OSeaEjuqyovwqWxWsfGf48OEMHz78Z/f369ePt99+m6Kiot/yNoqiKIRaI9z8fxOJRy3S+uSzNNqG5ScZqGiaQ+eyWnTDodjtcEjaRzjSwecaTGnmzQghfvH6iqIoO5IVt5n04HTeevpTpJQcOG4Qv79sLG6vi7iVWG/iuEBz6xiGjiUlEdPh8k/eo9WKkefzc+0BI3Eb3z/KdfF1wq2b5AmJWwuh0cwgXwXlKRtx7AANbW9RkPrHjuqyomyV3xSs/C8VFRXE4/H/faCiKMovkFJyz99eYGNFHUaqm7piPzIcI68kjRaaMcw4nUrqcHssXMQ5p+AbHNmKqRfQPechNLFludwVRVG2l7qqJlqb2gAIB6NMvO1NNqyqJSXg4Zwrx7Hv6L40t4b51yPvkpGawsH796CqaxxbSMBCCkCAHQ1zdM/eXDx0P/wuF5/WfcPgjJ54dTeFKbncNeBMVtYej+20goyBSBS+LUy7mBz/9isvoSjby3YNVhRFUbaFN578hJlvzUMK8BzcjZrGVlJy3VSktJKWHiSvqAEhQMNhfMEiBBvQhJfuOY9i6rkd3XxFUfZwdVVNXHzkXYRDkeQ223Los08ZF99+CjkF6cxdso47n/mIxpY2Ouemc8AB3XF7DQQCRzq0WRYCuGTf4ZzefyDN8SB3LnuZuY1LGJk7hHPLjgLAoA3HaQbim0aeDTThwu/eS40wK7skFawoirJTW/rNWh6d8BoAeYf1YkljKxgQ7qEjrVgyUAE4NHMhndwVAHTJugOfqrysKMpOoLWpjbZgBASYLgPHcpA6jL/ySDJyAjz+2he88sE3AIzetyd/PG4/Vrc0IoTApesYWmK9ihCCIZ06M6dhMY+tep0WK0SeJ5MDcwYn3ysRkEgSS+p96MJMpCNWlF2UClYURdlptTa1cfP/PYEVt8kY2JklbSEkksxhmSwLN5CTHUcISNXD7Ju6kmGpqwDQ3b8nM2VsB7deURQlYcOqWqLhGBJwe0wwNBzHoa61jXvufI2V6+vweV38+eQD2H9QV2pCQW6e+TGW46Bt+jXG0HUkNq9VTeXb4GIADs7bm1OLx+DWdNpiC0lx9QFACBcCDSl1JKrAo7JrU8GKoig7JSkld1z6LDXrGzEzU6jM80A0Tu7ADBaFGxDCoawkTpl3DeOy5rGpBAEbomnsl3txh7ZdURQFEt9j017+iom3voUjJYap49gOjp0o26Bpgsq6FnqX5XP57w8iNzPAjDUV3DTjQxojYTQ9jmbGcQRoQHp2C9+01pLpSuW8sqMZmFFO1NrIirobaIstoDz3SQwtHV3zYzshII5EqAKPyi5NBSuKouyUJj/yIV9OW4jUwDiglLamIL4CD0vNJpCwXz9BjMp2gQpAJ3cr6Ua0w9qtKIoCEA5Feeyfr/PF+wsQmsCd6cPRICQAl8BvuOlSnMNtF42jKD8DWzrc/tlMJi9eCMCxfbszX35M2Pn++8ytudgnsw/nlh2F30ihoe0t1jf9G0eG8JrlCHRcRj69814nbjdQX99AVlYmpp6pCjwqu6ytDlamT5/O9OnTqampwXGcdvv++9//AvDwww+Tl5f321qoKMoeZ+GsVTzxrzcByB3bm6VNQXALWsrAjkp6l2jUaRV0NVvbBSoAAoeIVYHLKOiAliuKoiRSrf/jrEeoXFNHdkE6p111BP949gNC4Sgxy0YTAtvvxXHpdMlMZ1VjA9d+OI2VjQ2kuz1cc8BIOmeZfPX1+9jSJkV34yCxZJyjC0fg1eJUNFxJc+QDQJDrP5P81D+gicTaFpeRj6Hl4tJq8Jq5aJrWsR+IovwGWxWs3HDDDdx4440MGTKEgoKCn80uceqpKkWeoii/zspFG7jx3MdxbIeMvYpYGgwikaTuk8aqcBOZqaBlrseWMCorspkr6HiM0h3dbEVRlCRfwEP5gCLyi7P40/XHsLEpRDAcJR5P1E/RdEEkZtESipCbGWBdczMrGxvYu1NnrjvwILK9Kby87gOiThyJxJI2hjBwcJAyzNKa84g7tbj0AoozbsDvHtixHVaU7WirgpWHHnqIiRMncsYZZ2zr9iiKsgd75/nPuPfvLwFgpxisTdPBccjZK4PF4UY0zaF7eStNlsX+6UE6m19vOvO77Dc6pZk3q1EVRVF2uGgkxqpFG+k1uBSA8VeOQ9MFwXCMh17+JBGoCPB73ei6RtSxkDKxduXA0i7cc+jh7N25kLAd5b4Vk/ikdh4BvY2AIXGLOA4ObY6BEF4yUsZiOQ10TrsEXfN3YK8VZfvbqmAlFoux3377beu2KIqyB6utbOI/VyQCFakJgn2ysR2HlM4elohGQDKsv6TOaqbAFWV0xudICWmegyjJmEDUXovHKFWBiqIoO9zGijruveJFqtbVc+PEP1DcPR/D1Fm9oZ4bHnmXyroWHDe4PAaWAa1mjKYsi3fXrKB7caIW1NDCIpa3ruP+FZOojTZS5NEYmzETl4gjkAgkUenGK/5MXur5qmaKssfYqkmM5557Ls8999y2bouiKHuwL6ctQEqw3TqtfbOxfS5sXVLX2UICA7rq1LEBU1j8ofNCpGzDpXemLOtO3GZnUj3DVKCiKMoO98X7C7j29w+xbkU15f2LScv6fqQjPeDFth0G9CukqRdUlsVZWxKhtrNF3AMrWxrbXevNjTOpjTayT2Yfrux1AqmGhlvTcWkOpiYJGJBqSBWoKHuUrRpZiUQiPPLII0ybNo3+/ftjmma7/Xfeeec2aZyiKHuGSFuUyQ9/QDTfR6hHJgiBFJJgiU3MgbwMiAfWApI/Flaiy3UIXHTLfhBDT+/o5iuKsgepq2qitakNK27z1tOf8uXUBeiGzrF/GMnR5xxING7R1BomPeAlIzWFuy8/ltpYiLcmrUbaFraUCMCl6/xp6D7Y0kEXid+Ozy07isGNPTkgZxAt0c+RMgI4gIaGh00l6RVlj7JVwcr8+fMZOHAgAAsWLGi3T0X7iqL8Wo9OeJ2N1c2E9u3Ed+XoQ50hlqljGg5FZU202g5jslrI1ecCUJxxHT53/45stqIoe5i6qiYuPvIu2kIRouE4juOg6xpX3Hcmvxs7gNUb6rn5v1PJTE3hnxcegaFrZKX5+HDRaqKWhUTi0nW8hoktHZYFV/Po+me5stdZZLvTCZg+DswdTHN4JhWNV5MIVHR04QMhkdL5X01UlN3OVgUrH3744bZuh6Ioe6gvpi7g7Wc/w8rwJAOVaLoknA8gGdAzQqsdpMwTZr/AZwBkphxNjv+0jmu0oih7pNamNsKhCLqmYbp0rDi43Cady3KY9uVS7n/pE2Jxi8LcdGJxC0N3AaAJkQxUUkwXtrQJ5NTz7MbXMTSNOY1LODR/XwDidg0VDVfgyAiaSAEEEhskqrijskdSRSEVRekwjbWt3P23FwAIDCggiE3cJ2npktifm95Cq9GMR4txZsE3IGN4zXJKM29Wo7iKouxQUkrWr6wBQDM0fB4vlmUTj1s8Pe1rvly2Hk0TnD1uKMceNICWWAS346BrGvsVFZMTMIkRQzMipOU0YLosfHom53c/jiGZvZLvY+q5dE6/DFPLwmuWYzlNyX2Glq6KOyp7HBWsKIrSIaSU3H358zTXBzGK06nEJpwtCZYAAlL8YTJKmhFILixch5DVaCKFrtkPoGspHd18RVH2IJG2KA/f8BpfTF1ATBNYhkAzIG7oNHfx89miNeRkBvjbWQfTr1snvqmu4urp73NEeU/+NGQfDNOmS88aQlYYSyaShpjC4MreZ9LNX0h96A2iVgWd0v4MQLbvmOR7u1DBibJnU8GKoigd4q1nPuWrDxbhmBptvbOx7WgyUDFMi4LSehBwVHYdqVpibVxp5q14zW4d23BFUfYoVWvruevy51m/soZAp1TWBATOD3KpSiEYUJTNhAuOID3g5blvv+H+WV9gS0ltWwgpJa1WGzEnhiRREcqlmehCQxMR1jZeR2P4PUAny3c0bqOog3qqKDsnFawoirLDrVtRzWMTXkcCKQd1ZWMkCiUGCAvDjFNYVothOBQZ9QzyfQFArv8ssnxHdmzDFUXZo3z9yTIeuPZl2loj9B/WjcPOH8lf7nwNARiawJYSx5H85dQRGG6dK6a/z8drVmNqOn8f/juOLO9JXNrJ66XobsANQKZRS0vLJQhZg6nnUZIxQQUqirIZKlhRFGWHiscsbvvL00QjcTx989kYjeIYkki+IC0tSF5RA0KAT4twUu5shHDwuQZSlHFVRzddUZQ9yOtPzGDSA9ORUjLurP05/v8OZv7yjcTiFkIIvH4vmuMQt2zWB5u56vVprG9toTCQys0Hj6Y8K5sv6xfwVMXbnFEyFr/eRopmoSEo966hr28Vju0nM2UkRRnXYGhpHd1lRdkpqWBFUZQd6tm732PFgvU4fhf1+V6kZeHZy0+z1kThpkBFw+Gk3NmkuiJoIp2u2fejCVdHN11RlD2Irmu4PCZ//McxDB3Vh2Vra/nXxGk4jkTTBHHLRkoJgC0l1aEQB5SUcu3+I/GaBs9UvMM7VYkMhtVtSzkrbzqmiANgCgsQpPkuoDTjQpUwRFF+gQpWFEXZYRZ8uZKX7p+GFGDuX0osHMHd1csGO4jfH/0uczEHZyym1FOPI8FM+Rtuo3PHNlxRlD1CqCWML9ULwOFnDGfoIX3JKUhn+lfL+M8LM4jE4ug+AwwIaXEE4NddDOhUwBNHHUvXjEwa463csegplgfX4jO8nN/1eMp9DouqNZBeQEeS+L7r5D9EBSqK8j9o//sQRVGU3y7UEub2S55BSknKvsXUhiM4KVCTFQUk5aWJed0DfWvYP20FADOae9A5MLYDW60oyp5izowlXHzUXcz5eDGQKHKdkRPgoZc/5c5nPsR2HE4etxfxwSaNPSU13Wxquzs09gLHBd0ys1jYsoqr5z/A8uBaynyd+We/8xmQ3o36tikgY+jCxNBdGJoXgd7BPVaUXYMaWVEUZYd48LrJ1KxvRMv3s9EDEok2IIV4vI1uJRYh0cTvUpdxSEbiQUFKGJJ5ADnu9I5tuKIou6W6qiZam9qQjsP0V+bwweRZaLrG+lW17HVgou6J5TgsXFVFqs/DFWePwp3p4rYVnxOzE+mHEYKwZdEUiZDvDzCvcRktVohD8oZyWskYNMKsbric5vCHSCwcYmgSJFaH9l1RdiUqWFEUZbv7eMpcpr8yG8cQWAPzkZEY3n4+1sVD+H1xzIxqUvUQh2QsTk4FEwL8zn+JWeNxGQUd2wFFUXYrdVVNXHzkXbQFI8SicWzbQdM0/nrHqRx07BAs28HQNTwuk2vOHQ1AToafWz+dQdRKBBoppgu3rhNzvg88Ti4eTZ+0MgZl9KAttpSKhiuI2Rtw6Z0BgSOjODIGqGr0irKlVLCiKMp2VbuxkfuumpRIU3xgGRsjMUS2wTp3CKE59CgPEpQOR+Ws4adTt20iVoUKVhRF2aZam9oItYaJRS0cJxGouNwGXXp3YvpXy5g8/Rtuu2gc/hQ3eZkBQrEYV0x/jw9Wr8IwLVJcGi7DAiNIdnYj68KV9CQHQ9MZlNGD+tDrrG+6DUmcNM9BFGdcg+0EVTV6RdkKKlhRFGW7cRyHOy59jmBLGLN7FhvtOI4hiXUTYEHf8jhB2Uq5t5GunuWbuYKOxyjd0c1WFGUP4DgSx3FwuU08XpO4ZfPiR/OZuWgNmiZYsKKSffuXAlAfbmPOxo0UpLrJzF6J0GwQIEQiG9i3wcUcQn8ALKeZypb7kTh0SruYHN8pCCHQNb+qRq8oW0EFK4qibBe1lU288J/3+eaz5dgenbbSNGQ8jmeQn3orSG52nJinGq8W45S8bwFwGyVErXWAA+iUZt6sRlUURdkuhNdA95loboM2KWnJ8/PR/FVkpPm44uxRDCjvjJQSIQTFaencdehYNFeEaxcuwXIkFomkIKYwOLrod8nrGloaJRn/RAgTv3tgB/VOUXYfKlhRFGWbe++FL7jn7y8ipUQKYGghkbiFq8TDBhnEMC3yixqISsnZBavQaUQXAXrkPotAJ2JV4DFKVaCiKMo2Y9sOL90/jc5dcsgtz6WmdxbOppyoUkvMQe2Wk87NFx1JboafJ+bNZUVDPTeNHIUQgv55+cxtXErMsXBw0IWGR3MjcYjHv6SiYTYlGTchhEbAs3cH9lRRdi8qWFEUZZuqrWziniteTBZLixSnEhYS2ytpzouDI+nfK0JIRjkgvZp8cykApZm34DYKAVSQoijKNhUORXng2peZO2Mp6dl+LrjvdNx+N0JANG4nF9T/9cyDCAQ8XPXBVD6sWIXXMFnT3ERpegYA3zYtTwYqPt2DxGZoYBHB4AeENY2slGNUoKIo25gKVhRF2aY2rq5FOolAxQq4CJemIYVE9nYTc6KUFccJaQ1km62MSp8HQLbvBDJ9R3RgqxVF2V3VVjZxxyXPsm5FNfnFWVx+9+kEhYPQBKah43abhKNxNAQNsTA3TXmVVU0NdA6kctuoQ5OBCsBhBfvxUfX7uLQQXtHIfqmLyHW1oGv5dMmcoAIVRdkOVLCiKMo2FQkn0nLaXoPWPtmJOgQ5FiERxeeL486sQWBzXqclQBS30YXijOs7tM2Kouyels9fx52XPUdLQ4i++5Txl3+dhO4xePzpD5FSYtsOoGFoGiGvzVWfTSMmbfbpXMhNI0fhMQ0eXvkK+2b1Y0B6d9KNGH8u/BzbaQVigAQMumXfhd89qGM7qyi7KRWsKIqyzcSiFv+9+Q2i+T5CPTJBCGJ+SahYR2gO5eWttEmHk3LX4hUbERh0zboHXfN1dNMVRdnNNFQ388//e4J41GLU8Xtzxl/H0hyKcOM9U1i6poaY5iBcErBxDElTJ5uAbXHmwEH8aa99aIq3cvvCiawKbWB1aCP90rpiOU1IGea7QEVgIoQLTXg7uLeKsvtSwYqiKNvMc/e8R8XaWkL7dgIhcHRJa1liX69uEdpkkN4pdfRJmQ9A5/TL8Ln7d2CLFUXZXWXmpXHU2QfgS/Uy+sShLF9by42PvEtDSxvl3fP43FtF2PquoKPAq7u5fL/fcUKffixtWcPdy5+nJR6iR6CEv3Q/GU1oyWvrwp84SxjJIo+KomwfKlhRFGWbWD5/HZMenE483Q1CYJmS1i7guCAQCGGn1OPTIpyYm0hTHHDvR37gDx3cakVRdgd1VU20NrURi8ZZtXAjex/Ui+z8dI45dwQAn8xbxR1Pf0gsbnHI0B4cMqoXH77yIrZ08JkuLOlgSYe+uXlMrfqKp9e8hS0dRuXtwxklY5GygfVND5DhHZt4QwECA4n1841SFGWbUMGKoii/WTxmcedfn8OxHczu2YSzJcESQJBIU1zcgEAyvtMKNFowtAzKsu5E/OCXSkVRlK1RV9XExUfeRVswQjQSRzoOgXQf9793Odn56cyYu5JbJ05DCBh/1L4ce1B/3lmxjLBlIaXEpTuYukbMtlkdXsezG9/AEDrnlh3FyNwhhGLfsrr+b1hOPZrwoWs+bCeEJDGioms+DC29Yz8ERdmNqWBFUZTf7Pn/vE/F0kqs3BQaAyQDFZAUlNSjmZID0zeSY6wEoDTzVlyGquSsKMpv19rURqg1TCwSx5ESXdeIxyxam9rIzk9ncK9CepTkcuLoQezbr5Tpq1YyYcaH6EYclylwm3Ec6aAJjS7eIo4o+B1DMnvTPVBEfeh11jfdhiROVsrR5KeeR7bvOCynKfn+hpauvs8UZTtSwYqiKL/JigXrefG+aTiGhtU/H8sTT46oZOU3k+KPkmc2MyJtHgA5/tPJSBndsY1WFGW3sWz+WqLhOBKJx+vC5TGJOjb1LW10AfxeN3dcejQA//16Do/MnQVajJLyaoTmbPphBXB00OOcUnIojoyzrulW6kOTERgUpl9Btu9YAFxGPi5UcKIoO4qag6EoylaLxyzuuiwx/Usb0ok2y0LL0EnLDFLWeyPpWSFMYXFc1lw0YeExu1Ocfk1HN1tRlN3Ex1Pm8uStb2G7NES6F9I9BH0GteUZ3D/lC0KbUqkLIfjPV1/wyNxZeA2Ty/ffD5/bwGMYaJpE0yRel4bHnYhc1jfdQn1oMoaWSdfsB5KBiqIoO54aWVEUZau9dP80Vi3aiJWbQotHw3JLIoVxiosaEJt+rTw0YyH5nhbARdese9E0T4e2WVGU3UeoNYLt0mjdKx9HT3zpSC3x//nZAUzj+99kx3Trzufr1zJh5Cg0V5gnK23i0kJD4NZcye8sgFz/mcTsaooz/oFLz92hfVIUpT0VrCiKslVWLdrA8/95f9P0rzykZSH6uBGuZoSAVD3MQP9a9kmtAMDwnEeKq1fHNlpRlF2elBKxKbIYe9p+ZHTL4crH3sW2HWKWDYBpaIw/dj82hlrpFEjFpeuUZ2Xz7LEnEnNi3Lr4FTxaK5laHI/uRhAhx2xAyggAHrOEbtn3d1gfFUX5ngpWFEX51ay4zZ2XPY9tOYihhbRZNk6RQYMWJdWwGOxfw7iseWz6gZOqaCpDc8/t2EYrirLLawtG+M+VL3HgkYPZd3RfALLy07BsG8ty0DSB120Agq9rN/Lgh7MZWdqFaw8YiRACS1rcuPBxasPL+WPBDNxaIvWwLhw0HCJtd4L/vg7soaIoP6aCFUVRfrVJD05n5YL1xHNSaPVqWB5Ja76Dpjn07VrfLlAByHMHSTciHddgRVF2eQ01Ldx+0TOsXV5FsCXMPqN6o2kacdvGcSRCgM/jQiJpSbf595zP0HRB59S05DVcmkm/tK7UuFpIM3WkNIAIIAFBTsqIDuqdoig/RwUriqL8KquXbOS5e95LTP8akJj+RR83lozSrUuIVLOuXaACIHCIWBW4jIKOabSiKLu0tcuruP2iZ2ioaaHP3mVcdNvJaFpiPUpOuh9fupuQFSesWbRkOUQCDrm6lxtGHsSosm7URZvIdqcDcGLxIbTFilhW8xSSKOAAOppw4XP17bA+KoqyeSobmKIoW8y2bO766/NYcRsxuICwZWMXGTSKKIG0MLq/ESkTv1G2p+MxSnd8gxVF2eUt+GoVN573OA01Lex/+ED+du8ZNEeiXPfg2zS3hnFc0NxH0NwbarrbhDIcMAW3HHwIB3fpymsbPuKv8+5mcctqAHShEY0vw5FhwEZgoIsU1CORouyc1MiKoihb7OWHPmD5t+uI53hpTdGxvJKWfBtNsynp0oKNw7G5q2g/sKJTmnmzGlVRFOVXq15Xz+0XPY0Vtznm3BEc98eRLKmo4cZH3qUlFGHKjAXsPbSUiG2haxrSstCFhsfQyfR5eXDlZD6t+waP5iJix5LX9ZplgI5AQwgXEkdVoleUnZQKVhRF2SJrllbyzN3vJos/SsdC9nZhyxjdy0LEiTI6o4J0vQrQ6Jb9MLrmx2OUqkBFUZQtUlfVRGtTW/J1ID2FI8/an6y8NEYevRefz1/NrROnE7dsxh3Yl1MP24vlDfUAuHQdl9eLlGCLGBPXvUxlrJosVxqX9TydIm8OttOGrqXgc/enT8HbIJ3ke6lK9Iqyc1LBiqIo/5NtJbJ/WTEb9ulM2Laxiw2aRIy09DY0XxMFriaGpy0CoCD1fDJSDungViuKsiupq2ri4iPvoi0UwbElui7w+jzc/cYlZOenM+XjBTzyyqcAnHvMMI4Z2Z+ZayqYvHghmm6BGUMXGtKIkp5dz7qIi56pxVxSfioBQ7C6/jIkccqy7kYIgxSzvIN7rCjKllDBiqIov6i2sonn7n6XZd+sTWT/2jT9qznXRjdsikpbkMLmjLyFCGxSzN50SvtLRzdbUZRdTGtTG22hCPGohW3ZeFLchEMRWpva+GrlRh6e/CmmoXPZGQfxu0FlvLxoAXd+/im2FiG3bD1CS9RYEQIQkj6BXlzR+wykU8vy2r8SsVbiMUqxnCZMPbtjO6soyhZTwYqiKD/rvRe+4J4rXkQ6EsfQiPbORgqJ09uFQ5QeXYPEiXFk5kr8eh0CF12y7kQTro5uuqIou5hwKEYsHMd2HAxDxzA1bCsxTWv/gWV88NVyxh81lJ5d8rh/1hc8PX8ehqbx5/2G8lLtBgQGmhA4UmJLm9O7HEo8vpjVDZdjOY0E3EMpzbwZXQt0cE8VRfk1VLCiKMpm1VY2JQMVgLbuGcQEWEU6zSJGemYYvM2UuOsZElgCQOf0S0hx9ezIZiuKsgtqrG3l4etfIW4IhNuF4XMnqp9sClYCPg+3XzyOuOPwj4+mM3XVCvwuF7ePGkNawOH5GhtTM3DrJpZjI6QkFpvBiub7kMTJ9p1A57RLEEI99ijKrqZD8/TNmDGDI488kk6dOiGE4LXXXvvF4z/66COEED/5X1VVVfKY66+//if7e/ZUD0+K8mttXF2bGFFx67SVpBLL8xFPSUz/MkyLzsXNuITFqXkLEUh8rsHkB/7Q0c1WFGUXU72unhvOfYyNVY207JVPU/9cKrulUV2eTk2vTJrjcQCEENzw8QdMXbWCfH+AR488hj55OTy35j3i0iJix7AcGwcHHZtw5GkkDp3TLqMw/XIVqCjKLqpD/80NhUIMGDCA8ePHc+yxx27xeUuXLiU1NTX5Ojc3t93+Pn36MG3atORrw1BfUIrya3l9LqL5PkI9MkEIpJAESyQS6No1iEWc47OX4dUa0YSXsqw7EELv6GYrirKLmf3REmo3NNJvRE9qmxuQUhKLW0gJui4wU76fVnpavwHUt7Ux4aBReEy4edFElrZWkGHE8Os2mggBIEklL+2f+PUIqZ5hHdU1RVG2gQ59ij/ssMM47LDDfvV5ubm5pKen/+x+wzDIz1fpBxXlt5h439RkoAIQ6gSWT5CZHQJPC9281fT3LQegMP1KPGaXjmyuoii7qLGn70d2QToZ3XKYftMLROMWAoHb1NF1jfpYGMtxMDSN3jm5PHj4OGqijVy/8CmqIvX0T81gdOp7ODIEWAhMNM1HtvsylYpYUXYDu+SQw8CBA4lGo/Tt25frr7+e4cOHt9u/fPlyOnXqhMfjYdiwYdxyyy0UFxf/7PWi0SjRaDT5uqWlBQDHcXAc5+dO22KO4yCl3CbXUnY/O+P98dm78/nqy+UwMA/blETTIZwPpssir3MTLi3GSbmJNMUB93CyU07dqdq/u9gZ7w1l57Er3x+zP1yMbmgM2r8HAHsf1IuXp31DNG6BBLdbx9B1Ql6bqz6bxmG15VwxfH+EEDTFWrl+wSO0WCEGp/dkfHFfVtX/F4gCEtCRMkzcbsDQcn+pGbu1Xfn+ULavneXe2NL336WClYKCAh566CGGDBlCNBrlscceY8SIEXz55ZcMHjwYgKFDhzJx4kR69OhBZWUlN9xwA/vvvz8LFiwgENh8BpBbbrmFG2644Sfba2triUQiv7ndjuPQ3NyMlBJN69BlQspOaGe7P8LBKPdf+zJa1CacJQmWQqIkvSS/sB5H2BybtQS3aEHgx+/8jdrauo5t9G5qZ7s3lJ3Lrnp/fP7uQibd9xGmS+ea//6eQHoKtu3wzqcLsE2J7tKJaZLmQIxgtkOapeMHampqEEIgpaSvJzGSe0za/jQ0vosjwwAI3IAbKS3q6xtwaTUd19EOtqveH8r2t7PcG62trVt0nJBSyu3cli0ihODVV1/l6KOP/lXnHXjggRQXF/P0009vdn9TUxMlJSXceeednHPOOZs9ZnMjK0VFRTQ2NrZbG7O1HMehtraWnJwc9YWh/MTOdn88eN1k3nzqU0IDs1l/sHdToALp2S3kFTbRO2UjJ+fOAqA0499k+bZ8vZny6+xs94ayc9nV7g8pJW8+9Qkv3T8d3dT50/XHsO8hfZP7l1TWcNqUl4lLh7hjE3ccNAQ3jDiIU/r2pybSSK4nAwBHOggETZH3WNv4DyynDoEbXaQgsZA49Mx9Ca+55ybY2dXuD2XH2VnujZaWFjIyMmhubv7F5+1damRlc/bZZx8++eSTn92fnp5OeXk5K1as+Nlj3G43brf7J9s1Tdtmf0QhxDa9nrJ72Vnuj8VzVvPW059hBVy0FiUCFcO08Poj5HRqwqdFODZ7AQDp3tFk+49DbFrTomwfO8u9oeycdpX7w3EcXrh3Km8/+xlur4tL/n0KffYuY/IH33DYfr3wp7jR3Do2EstxsBwHDXAbOoMKOvHS+mm8U/k5V/U6ix6pJWho1IVeZX3TLYBAF6lIbBxiAOiaD1PP3Ok/l+1tV7k/lB1vZ7g3tvS9d/lgZd68eRQUFPzs/mAwyMqVKznjjDN2YKsUZdcTj1nce8VLOEjiA/PRopK0jCB5xQ2b1thLjsz8BpcWxtCyKM28WQUqiqL8rLqqJlqb2nBsh8kPfcjXnywlNdPP5fecTmnPAv799Ad8PGcFS1ZXc+15hwLgILEcG13TSDFNHOnwStW7LA4tJ0X3kMhHmBBwD8Gld6Iw/W94jDIspym5z9DS1eJ6RdlNdGiwEgwG2414rF69mnnz5pGZmUlxcTFXXnklGzZs4KmnngLg7rvvpkuXLvTp04dIJMJjjz3GBx98wPvvv5+8xmWXXcaRRx5JSUkJGzdu5B//+Ae6rnPKKafs8P4pyq5k8iMfUrG0kmiXNMI62IU2+clABQb619Hbn6hpVJr5T0w9uwNbqyjKzqyuqomLj7yLcCix7jMes3AcydUPn01h9zxufPQ95ixeR26mn/FHDU2eZ5g2AbfE0CSIML7ser5trSbfm8nfep5BvjuA7YTRNS9uo4ieeZPQhAmACxWcKMruqEODldmzZzNy5Mjk60svvRSAM888k4kTJ1JZWcnatWuT+2OxGH/961/ZsGEDKSkp9O/fn2nTprW7xvr16znllFOor68nJyeH3/3ud3zxxRfk5OTsuI4pyi5m/aoanrvnPewUg0hpOpbbwSm2EAJS9TDF7nrGZs4HQDNHkZEypoNbrCjKzqy1qY1wKJKYZmIkpprYtoM0da66702WrqmhuCCDm/7vcKRL8Njc2QwrySevbD0IGwChJUZR8t2lXN/nHPx6nBV1f8TUs+mSeRtCGMlARVGU3VeHBisjRozgl9b3T5w4sd3rv/3tb/ztb3/7xWu+8MIL26JpirLHkFLynytfIha1iO/bGVs6xLobRKNxBvnWcFT2PLRNoyth26A857qObbCiKDu9tpYw0XAcj8+NYehYQFyHO16eSW1rGz1L87j+j2NotqNc9OZbbGhtQbj6kOLSERjY0iYm4+honN/9GLyigeW1FxGzK9HFYBwZQRf+ju6moig7gFpxpSh7uKmTvmL+5yuIFvhp8+hEciDktijMqW8XqAB4dJtMU/2SqSjKz2usbeXhG1/Fdhyi4RiWZeNYDsjE4vkhvYv454WHUxkJ8oc3X2dDawsHd+nK/sWlaAJMTcdvevHqbly6iXBWsLz2HGJ2JeneQyjLvhddU4GKouwpdvkF9oqibL2mulYenfA6jksn3jML23SIlGiYrhi9iqraBSoAAknEqsBl/HxSC0VR9lx1VU3c/H8T+f/27jtMqup84Pj33Hunb++7sIWl96qIiqCxK0o00Wh+tqiJLYkxFtAYNDGixsQSTUxsWGKPFRUVkF5EBUGl97ILuwuzbfrc8/tjl8EVUEBgduH9PM8+MLPn3POenbOz951z7rlVG/2YKS5wWwQAZRp4nQ7G/OJkOnTIY2HVZm76aAKN0QjndOvJ74ccw/uVs4hrjaFsYjaYyqDctYH6hj9gKpu8lIspTLsGpeRzViEOJ5KsCHEY+/ef3qShNkCkfz4RbRPuaBIjRseyWmpibrSGlht+mbitsiRFK4RozTavr+EvV4+jprKW3id0Z3qonoZQmHjcxmGZRN1O0rNTmL1xPbdO/oioHeeK/oO4vP9AplR9xn/XTsCt6km3bBRgEmd4+pconLRPv4mclJ8mu4tCiCSQZEWIw9SnUxYz5c3PiOR4CKS7CGdpGn1x0rMasbyNdPFu3ilRKcu6W2ZVhBA72bqljj/98in8VfUcc3pfTvzFsUy462Wi0eaL5RWEozHqGkOkuVyYSvGbIcfyk+49eXvTNF5ZP5FMK8wl+XMx1Y6bNCtclGTcSk7KyCT1TAiRbJKsCHEYCgXCPHLbq9iWItIzF9vShMsNLEeEouI6Us0Ap2UtASDLO5LclPNxW2WSqAghdikjJ4V+R3dGGYpfjB7BSx98TiQSA2i64aOpiMaaEpe+BYW8dt6FZHncPLf2fT6onI3bcHJVx+OINr4P2sZQXrSKoXUUr/PwvQu9EEKSFSEOS88/MIHN67cS7p5DREGog0GEOGUltdgqyk9yv8RSEZxmEWVZf8Y0UpMdshCiFYqEYzhdFoZh8Itbz8IwFBNmLebZd+cRd2gsj0XUofGnR0CT2AE00+PiXyv+x6yahaRaXm7udjF5jkoWN4SAOGBi4EI335FeCHH4kqvUhDjMrFi0njcen0I03UUw30s4XdOYbpOaEcCV2siAlHWUuisAKMsaK4mKEGKXvpq3it+NfIAVX24AwDQNPpq7lEdeno52gL8HbOkYY31pmPpMm/osm8pIIwAGBi7TSY4rgzE9r6TY42LdtrvYnqgoHGhiyeucEKLVkJkVIQ4jm9fXMPbaZ4ijifTOwzY14Y4mphWhfUktKWaQM7MXA5DjO490z7AkRyyEaI0WzFzGgze/RDQcY/nC9XTq1R6Avl3a0S4vg9NO6cHt8z4mEo8T0zYG4LIsctJ9ACiluKzDmTTEgrjVNpZX/YZwbB0KJ0pZTYmKBtPwYRkZyeuoECLpJFkR4jDxwUtzeOiWl9Aagh3SCVuKUDGEjTjFxbXYRpRzchZhqTAOM5/izNuSHbIQohX6ZPLXPHrbq8SicS6+8XROPn8w0Vgch2WSn5XKP0f/lIVbKgnPiWFrjcMw8Dmd2EaEx9e/xDWec+iU0h5TmTj1JpZX/4aYvZVMz8kUpF2NrQOJtiwjA6dVkMTeCiGSTZIVIQ4DVRV+Hhr1MlpDzOcgVJxGJEXTmAMpaQG86Q30862n3LNj+ZdlpCc5aiFEa1Bd6afe35RALJixlFcf+xhDKa68/WyOGzGAx16byYbNfsb86lScDgvTUPx99kxsrTGbExVlhcluV8nGkIOJlXPp1KlpJkYpC62jZPvOpX36jShlJrOrQohWSJIVIQ4DG1dtQduauMukoUc22oSGEo1hatqXNi//ymla/pXtPYcMzwlJjlgI0RpUV/q5fsQDBBtDxOOaSCiCUorrxp7H0BH9eejFqUycu5SMVA/V/kaKctNRSvGzXn1YULUWhyOG5QqSll+DaWgGZw7givKRaK1RSuF2lNM17784zHyUUt8fkBDisCPJihCHgU1rqgkX+GjsmgVK0VikiXsVRe22oc0II3O+xKlCOIxcSjL/mOxwhRCtRL0/QLAxhGEYWE6DeNzGNBSd+hTz12cmM33+SrIzfIy97kxS0tyJJOSo0nx69/HTGAsR01E04DacXNThFPzBt2kIz6M0888oZcoyLyHEd5LdwIQ4xDXWh3jmkQ8TiUrUqwkWgDc1SGpWA719G+ns2QRAadZdWGZGcgMWQrQqWoNhGViWiTfFheEw+M97nzB9/koKstP462/PRrsVF7/5Go9//ikA9bEAoXg4kag4DQeGgqqGp9ngH0ttcCrB6NLkdkwI0SbIzIoQh7jn7n+P6sYgqDRiTk1dOSjTpqDdVnxGiLOyvwIgyzuCTO8pSY5WCNGaTH3rc0LBSGKJlh2zqW2fyqLVlZS2y+bua8+kVof5zfjxVAcDbKirxW6+l4pSCktZuEwHBoqj0xYQDH6Mw0ylQ9Z9eJ09ktk1IUQbIcmKEIew5QvX884z04nn+wjmaBpKAQV5hX4c7jhnZX+JywhhGdmUZN6Z7HCFEK3IW09N5YOX5mC7TEJOA9METIP0gE3HjoXc9stTqQw38NsJ71IbDjGya3duOnoo9bGme6mkmgG8jhgWmiPTvqK9qwpltKdTzqNyV3ohxB6TZEWIQ1Q8bvOP0a8QMyDcIzORqHh8ITJzG+jp3Uh330YASrP+hMPMSm7AQohW4/XHP+Z///4YR4YH+8hCgvE42y9/97id3HTZiawN1HLDB+/RGI1wQa8+/PqIo3hr01Ter5zNNeXHc2n+JBwqiqXiGGhsDPLS/iiJihBir8g1K0IcosY/M53li9YT6phJ0AsocDgjFJZW4zXCnJG1CIBMz2lkec9IbrBCiFZBa81rj03mf//+GI/PxSW3nUVU20RjcWK2xrRMwtEYFf46fv9hU6JyRf9B/PqIo3h5/Ue8tmEycTuOpYKkWgZuw4OpUlDKwjLcZLnyk91FIUQbIzMrQhyCqiv9PHP/e0TTXYQKU4h5NelZDeQXb0UpOD1rESlWGENlUJr1p2SHK4RoJWZ9sIg3npiCJ8XFqH9cjN/ShCIxtK2xTDANg1g8js/hZPSxw6ior+fC3n0Yt2Y8kzbPw2d6uLn7xeRbm1jWoDAMR9O9VGwHNpFkd08I0QZJsiLEIeixMW8QaAwTPqodcYcm3iFO++ZEpbt3E31SmpZ/ZaXejMPMTXK0QojWYvCPerJo9gpOOu9IMtplcsf9rxMzbZTHQLkt6s0IjmDToowfdehIXMd5bOXrzKz+gnRHCqO6X0K+M8byLbejdRjdvIBDqxjoZPZMCNFWSbIixCHmk0lfMfP9LwiVphFxmQRKNIY7glKQ56jl7OwFACwOFNA3dVBygxVCJJ3WmtqaBjJyUrEcJlfdeQ5bttZzy8NvU9FQx7YeoA0bVAitwLAhpOIAfFg5l5nVX5DtTOfW7peRYdWyouo6onZ104wKNlo3zaiYhg/LyEhiT4UQbZEkK0IcQkKBMI/e/hpxj0W4QwbhDE0oE3JSQwxIWcvZ2QtQqum+CWtDOZzmzUt2yEKIJNJa89zf32fuxK/4w2OXUViag9aau5/6iIrqOvr3LmZzdA1x2yZsN11k73CaWG4TgJPyB7M5tJUzi47FqypYXv0b4nYt2b4fk59yGXFdn2jLMjLkBpBCiL0myYoQh5D/PvgBmzdsI9g/n5ihCZYpnK4IHQqrOKs5UQFQCk7J+pp0MwhkJDNkIUSSaK155q/v8dErc0nN8BKNxICm+6P85oJhvDfjK44f3pV3X1tFxI5jKIXP4QDDpjqyFcjFMkwu7XAmDeH5rKz+PXHdQK7vAorSr0/cm0UIIX4I2Q1MiEPE6iWbeOOJKUQKfETSXTS2h6hlU1S6jUKXH+Nb5w0Km1BsTVJiFUIkl23bPH3PeD56ZS5pWT5ue+wyvLkpxOI2AOXtsrnu/ON4Z8VSIs3bFqc4HBimTVb7Sp5e/xqbQzXNxwqxZuto4rqBgtQrJVERQuxXMrMixCHAtpvuqRJVEOqSRTRFE8qDjJwGXN4QvXwbdlHLxG2VHexQhRBJVF3pp25rA68/MZV5k78mPSuF2x67DHxOfnf/G/TuXMTvLzoe0zBYsbWGN77+CocjjtupsKwA6fk1WM4YhZ4y0hwpABiGm7KsvxCMLiM35YIk91AIcaiRZEWIQ8CEF+ew+LM1BLplEzMh0EFhOaLkF9XS0b2Fvs27f4GiaUsek7Ksu3FahUmMWghxMFVX+rl+xAPU+xuJRGIopTAMRU1jkPuenIC/PojLaaGab//YKSubG48bzCvVrxHREaJ2DI3GoSyu6XQO8dgStNEHpRQproGkuAYmuYdCiEORLAMToo3bVlXP02PfIZrpJlLgI1AAEZdNYfE2nGaEH+csBCDNdQx9CmfSNe9F+hbNIDfl/CRHLoQ4mOr9AYKNIRwuBw6nhcfrohGbP4+biL8+yOnH9OC684ayaEtlos6g9gXEdJRYc6JiKRPLMKkNvsGK6iupqHskiT0SQhwOJFkRoo17/K43qW8IEeyeTcytCXB5Y94AAE53SURBVBZBWmYAb1qQEzO/Js1qxFAeyrLvweUoIs09RGZUhDjM2LZNY10QANMySE33Yqc6qemYQUMwzJlDe3L1T4/hwU9m8at33+LtpYsTdWM6jo3GZTjxmi4GpSwjEPgPCic+V/9kdUkIcZiQZWBCtGHzpy/l4zc+I9ghnajToLEDGI44Be39lLqqOSptNQDtM27BZRUnOVohRDJorXnmvneZO/EropYiZimUBVXtfcRNxQn9OvLLc4/mr7Nn8MaSr8lwe+iRu2Nb80xHBJcK41QRevtW0NW7DlQu5TkPkSpLv4QQB5gkK0K0UZFQlEf/8Boxn4NwSTqhXE3EB4XttuG0wpyT+wUAKa4jyEu5OMnRCiGSQWvNs/e/x8TX5uHM8FDdMwf7G2sqFIrTh3Zn7IxpjF++hGyPl3+cdibKGWJzqAaPquey/Ek4VBRT2ZjYaBS5abdKoiKEOChkGZgQbVBVhZ+HR73MhtVVBLtlE3NqgsWKlLQAaZkBTshYQqbVgFIuOmTdi1Lyqy7E4UZrzfN/n8CHL88lLdPHFX8+B4fPicfnIjXFjdfnwuV18OTKhYxfvoRcr49/nXEWttXI3V8/zV++fhpLBUm1DFyGE0tplDIwDTc57vJkd08IcZiQmRUh2pgPXprDQ6NeRtuacFEKkVQHDaWgHXEKS/y0d23l6LRVALRL/z1uh5xUCHG40Vrz4sMfMuHF2aSke7n1X5eytMZPOBrDaVl4fU5icZt6Z5Tpm9bRLi2NR08fQSN+7lv8LCE7wkkFg/EYLhQK03ChcYG20cST3T0hxGFEkhUh2pCqCn8iUbGdJsHyDCIZEMmA/MJtOKww5+R8gVIan7MvBamXJztkIUQSTH79U959bia+NA+3/utSgg7FIy9PJ25poh5NoxnDVjZWRHF57yM4rVdXttpV/G3pf4nYUX7S/kec3W4Im+vGAaCJobDQSjftfi6EEAeJJCtCtCGbVlc1JSouk/ru2cRdioYSjSclTEZOI8MzlpHjqEPhoEPWX1HKTHbIQogkOPrUPsyfsYxzf3U8YbfJHx4dT70dxt8DbCMGKgYaTK0YXFxMdXwzf1/6AlEd44KSkzm94AhW1/yeutBsFAZa22giAJiGD8vISG4HhRCHDUlWhGhDUtI9hAt8NHbNAqVobK/RLk1R8TYKnH6Gpi8HoCj9N3icXZIcrRDiYAsFwri9Ljw+Fzc+8HNWrK/iD4+MpzEY4dThPXimchGReJyYtnGbFqahMF0G4ytmEdUxLi47gxPzerOy5rc0RubjcXSlOPOPzbeJbGIZGTitgqT1UQhxeJFkRYg25Nl/TaSxaxZxJ4QzNaFcyC2sxekKc07OAgyl8Tp6UJB2VbJDFUIcZG88MYWZ7y/ktscuIzM3lWgszp8e/4DGYISfntiPAYNLePzVBcS1jcMwcDssYraNUorfdvkZi2pXMDCjhJXVvyYQ/RKvozvlOQ9jGenJ7poQ4jAmyYoQbcSnUxYzc9pigifm0VAKKHB5wmTm1jM0fTkFzlrApCz7PgzlSHa4QoiD6O1x03ntscm4vU5qNteSmZuKwzK58aIT+GLZRn56Sj+ufvdt4raNoRQ+pxOHtwE75ATAY7oYkN6OFdXXEIwuxefsQ3n2A5hGapJ7JoQ43EmyIkQbEAqEeeS2V4mkmolEBaUpLNlKnrOO4RnLAChMuxqfs1dSYxVCHHjVlX7qtjZQs3UrHzz7GRNenI0nxc3ND19EZvtMtNYopejTuYiuHfK4eeIHfLllMy6njcsJ7pRqUrL96JiTFFfThxvB6DJC0ZWkOAfRIft+TMOb5F4KIYQkK0K0Cc8/MIHKjVtpPLEIFFiOGNkFtXg8YX6cMx9T2bitThSl/zrZoQohDrDqSj/Xj3iAYGOIaCRONBrDMBS/ue9nOHNTuPbe1zjxyC5cPvIolFLMWLeWuRvX0yk3FZ23kcZ4iJiOAeBzK9xNkyukuo+kPOcf+Jw9MZQ7iT0UQogdJFkRopVbsWg9bzw+hWBJOmCSntlAfslWlIIhaStp7/IDBh2y/4qhXEmOVghxoNX7AwQbQ9i2JhqNoQCH00HcY3HrI+Opbwxh6x37C/+ovCOBWJSSbBd/XLyAmG6q4zKcpJr1VDW8Qo7rlwByV3ohRKsjt7UWohWLx+I8POoVIh6LcGkasaJYIlHJtuo5IXMJAGne/yPF1T/J0QohDiany8JymHhS3dheiwffmEldY4gRx/Xi4rOOYH5lRaLsiC7dWFS/hIjdlKikWF5yHWHOyZlFIPAfaoPTk9cRIYT4DpKsCNGKvT1uOssWrSfQNYuoB+KlMZSCdDPA+XnzcCibmqiPkPnTZIcqhDhI7Ljd/K/G7XUSd1ls7ZhOQzDMmUN7cunII7ll4of8+v3xzF6/DoCYHWe+fylpZpD2riAd3Rs5J+djUswATtcJpLmPTmaXhBBit2QZmBCt1OYNW3nmr+8Rbp9KNM1JfVnTL2x/31pG5ixANd/4YHFjIQPbFyczVCHEQTLnwy95/YmPMVNdhGJx4mj8HVKxHSYnHdGFy348mFsmfsjcjevpmJlFt5xcACzD5LryE1hd829cKoKl4iggqi1yfL+QG8gKIVotSVaEaIW01vzzD68R0HGC5RkE8yGWoulesomzv5GoAByTsYp0MwhkJCtcIcRBMO/jr3n09teImrCtbx5R20ZrjaHBYSjOO2NQi0TlkdNGsLB+Mf2trqQ5fOS7ndSYoNE0bSnowGU4SJedzoUQrZgsAxOiFZo+fgFzJ39NY5csYh4ItIPM3HrapW/DUC3LKmxCsTVJiVMIcXDMn7GMR259FW1rzr3uJGJoLMvE6bBwOS2UpbhjxqQWicrMbZ/yn1Vv8Lel/0Vvv+BeaUBjKC+WSkGhvrNdIYRINklWhGhl6v0BHrvjdSL5PqJZbupLwfJEyS2spYOrehc1TNxW2cEOUwhxkHz5ySoevPlFYtE4l992FsW92hEKx4jF4pimgWkaBFJtvqjenEhUpm2dx4vrPsRlOPlZyUmo5ulYhYWhfBjKhVaxJPdMCCG+nyQrQrQyT419hxp/I8HOmYRyIZqmKSypIc9Vy9CMFc2ltn8aalKWdTdOqzBZ4QohDqBlX6zjb7/7L7FInEtuPoMex3XhoZemELNsgs44AStG0IrhDCgu69GfR04bwdStc3ll/Ue4DCc3d7uIYtdWqhtexTIyMA0fALaOoLWNafiwjIzkdlIIIb6DXLMiRCuyaO5KJrw4m0CPbKJeRaB90/Ivny/EOYmbP5bTOecpInYFbqtMEhUhDmG5RZnktstg2IgBDDi5J7c89A5bAo1s6wHasIEIAKZWDCvrwJSaOby2YTJuw8nN3S6myLmFVdU3YBOmq7MvPfLfImb7E8e3jAycVkFyOieEEHtAkhUhWoloOMbDo14mku0hnOelvhRMb9Pyr6Hpy2mXuPnj33E7y3BTluSIhRAHWmZuKnc9exX14QijHn6Hypo6+vcuZnN0DZF4nLi2cVsWhlLYTpu5FV/hMV3c3O1iChybWFVzI5oIRWm/xePsAoATSU6EEG2HLAMTopV45Z8TWbemikCXLMLZEE1vWv5V6N7G8IylABSmXUOKq19yAxVCHFDrlldy/+/+S2N9CADDYXL7P99jU1Utg3uX8X9nDCJiNyUqlmHgsiyUUjgNB6N7XMro7pdS4FjP6prfo4nQLv335KX+PMm9EkKIfSPJihCtwKbV1bzyz0kEyzOIphg0ljQt/0rxBTk3Zz6m0ngc3ShK/02yQxVCHECb1lQx9ppnmD99KTPeXQCAZRr87JQBHNW7jN9ffDyPfDoXZUZwe6KkemN4MqsxnU3LwdIdKeSYq1ldczOaKO3TbyI35fwk9kgIIX4YWQYmRJJt2biVf976JkGvRahdCg0lO5Z/HZ+xlHxnHQoH5dl/x1DOZIcrhNiPqiv91PsDANRU+nn8rrdp8Ac46bzBnHDuoES54wZ05Kg+pdw6+SMW1ayjpMtmDMNGKQ0KUnO3oY2mhCVmb0UTp33GaHJ8P05Kv4QQYn9J6szKtGnTGDFiBEVFRSilePPNN7+z/JQpU1BK7fRVWVnZotyjjz5KWVkZbrebwYMH88knnxzAXgix7z54aQ6/OPYuNqyuprFrFuFMiGRqCotrKPbUcGx60+5fRem/xevskeRohRD7U3Wln+tHPMCN5zzE73/8EGMufZz1KzYz+KRenHvtCdz44Fu8PnlhovwHq1YwY/1a2mek4HOZOC0TZYChwG1ZuF1NuwRm+86mW97LkqgIIQ4JSU1WGhsb6du3L48++uhe1Vu6dCkVFRWJr7y8vMT3Xn75ZW644QbGjBnD559/Tt++fTnllFPYsmXL/g5fiB+kqsLPQ6NeRmsIlqYTS7NoaF7+lZYa4Jyc+RhK43P2pTDtqmSHK4TYz+r9AYKNIVCKSDiKrTWmaXDCT4/gj49NYMX6auZ+uYZY3AbgzM5duWbQYG4dOgxb28R0DAOF1/TQzVNBODwxcWy3ozRZ3RJCiP0qqcvATjvtNE477bS9rpeXl0dGRsYuv/f3v/+dK6+8kssuuwyAxx57jHfffZennnqKUaNG/ZBwhdivNq7agrY1kQwXoeI0GorBSmla/nVi5mJyHA0o5aJD9t9QSlZsCnGoMs2mVQIOp4XhMvnnu3NZW1VL9w4F/OHKU1hTu41OWdkopbioTz8eW/k/3EY9WUYUt+Gkg2cNR6QsoTGwgkjaSbKduRDikNImz4D69etHOBymV69e3HHHHRxzzDEARCIRPvvsM0aPHp0oaxgGJ554IrNnz97t8cLhMOFwOPG4rq4OANu2sW37B8dr2zZa6/1yLHHoWLO0glChr2n3rwwIZ2tKimso925hSNoqANql3YjLLJexc5iS945Dm25+XbUNHp+LmNbUlKUSrNhKj46F3HbFSdwzayoz1q/jwVNOp29+AYFYiNX1i/hV4TRcRgwDjaXiaCDDewuWkS/jRQDy/iF2r7WMjT1tv00lK4WFhTz22GMMGjSIcDjME088wfDhw5k7dy4DBgygurqaeDxOfn5+i3r5+fksWbJkt8cdO3Ysd955507PV1VVEQqFfnDctm1TW1uL1hrDkA3YBPirGxj3jw8I9Mom6oH6sqblX+mpjYzMmQ+AS/WHwBlsCcoSxsOVvHccuoINYd54ehoqxUkw1pRs1LVPJeZz0iknlWt+PIC7pk1k+sYN5Hu9WMFQYjnzJTnH0Gi/AphAGFAYyokj1FmWPIsEef8Qu9NaxkZ9ff0elWtTyUrXrl3p2rVr4vHRRx/NypUreeCBB3juuef2+bijR4/mhhtuSDyuq6ujuLiY3Nxc0tLSflDM0DQolFLk5ubKG4ZAa81jt75DrUMRzIWGUnC4o+QU1nJq1ldkWkEM5aVz/gO45M7ShzV57zg0BRvD/Gv0cyxZvJGanjlos+nCeGyNqTW3XHESz638kpkVm2iXns4/Tj2DJcFldMzujdt0kRptz+LNNpoIYGDgBQXZ2Vl4HHnf2bY4fMj7h9id1jI23G73HpVrU8nKrhx55JHMmDEDgJycHEzTZPPmzS3KbN68mYKC3Z/0uVwuXC7XTs8bhrHfXkSl1H49nmi7Jr/+KXMmfUXj0QU0lILljNKurIquvkoGpa4FoDjjVjzOsuQGKloFee84tIRDER648UVWLNpAu15FbHFEsQwD0zSIx21its1jiz5jVuV68lNSeOS0M5m2bQ7jK2awqHYFv+t6IUrtGAsKD0oZaGyUknEiWpL3D7E7rWFs7GnbbX70LliwgMLCposJnU4nAwcOZNKkSYnv27bNpEmTGDJkSLJCFCKhprKWf/3xfwRL04nkOEjPbqC8RwXpvgBnZy8AQHMEuSlyt2khDjWRcIwHbnyRxZ+toaxbIRfffDqRaJy4bWOZTQlLMN1m2sa15PlSePS0EYlExWd6+HH74QBYRgaWmYGhPABobEzDh2VkJK9zQghxgCR1ZqWhoYEVK1YkHq9evZoFCxaQlZVFSUkJo0ePZuPGjTz77LMAPPjgg3To0IGePXsSCoV44oknmDx5Mh9++GHiGDfccAOXXHIJgwYN4sgjj+TBBx+ksbExsTuYEMmitebh0a/g13GCpWlE28UoLt6KUnB61iLSrBDBuEVmyiiUUskOVwixH8WicR4e9TKL5qykuFM+Nz10Efe88DERI07YsLFNA61snAHFyeXduPSIAUz370hUbu1xKV49hW2BXDK9J9Ej/y2i8a3U1GwlOzsLh5mFU5aNCiEOQUlNVj799FOOP/74xOPt141ccskljBs3joqKCtatW5f4fiQS4fe//z0bN27E6/XSp08fJk6c2OIY559/PlVVVfzxj3+ksrKSfv36MWHChJ0uuhfiYJv0v3nM/fhrGgYWEM4G8qIoBQNS1tAvZQMA723tzYWZP/w6KSFE6+KvqWfN0goKS3O46R8X8Z/xc5m3ch3buoM2Ndto2szF1IqRXbszwz+3ZaJiT2JT3T8wVQqp7iNxWgVYRh5OYwseR54s8xFCHLKU1lonO4jWpq6ujvT0dGpra/fbBfZbtmwhL0/+oByuaipruerEe9ic6yLQMZVtPSG3ZCunl3/BqVlfohRoDW/X9OO3PceR68pIdsiiFZD3jkPL5g1bMS2TZyd+zqRPluHNdfF1di0xu+laFY9loZRi3DkjeWbjK4TiEW7tcSke+0Mq6v6JodyUZz9AimsgIONDfDcZH2J3WsvY2NPzbRm9QhxgWmseHvUy2wybUHEq9R3AnR6iJH9LIlEBUArOyllIuhlMbsBCiP1Ca82k/80jGokBkNcukxc+XsCkT5aRneHjtz8blkhUTMPAYZoopfCZHm7rcRm39rgUd/y95kTFQ3n2Q4lERQghDheSrAhxgE18bR5zpy6msVs2wXyIZ8QpLKnhuIzlfPvSFIVNKLYmKXEKIfYfrTXP/e19nhr7Dk/e/TbQtPtOWVEWWWlexl53Ju+uXQ5mBJc7SnpKHE/WVgxHFIB8dzbu+LtU1v8HQ/koz36YFFf/ZHZJCCGSos1vXSxEa1Zd6effd75OoFMmkUyTxnaaouKtlKTUJLYpbsnEbZUd7DCFEPtBdaWfen8ArTUTXpzN9HcWkJ6dwpkXH5soc9aw3pxwRBf+/cU8Jq9fTEnnzRimjVIaFKTlbkUbkUR5U6VQnvMQPmfvZHRJCCGSTpIVIQ4QrTUP3fIy2ywIFfmo6wDpOY1kZ9ZxXu6nmErjMAuIxrcANmBSlnU3Tqsw2aELIfZSdaWf60c8QLAxRDQSJxqNYRgGNz9yMRO/XE2HbXUMG9gJgGkb1/Dq11+SmerC5TKxUcR0DIXCaVq4XU1TrvmpV5DlOxunKTd6FEIcviRZEeIA+ejVT/hk+lIajyiksR0YmVHy2m/jzOyFZDsaMZSbrnnPobSXyuoFFOT0w+1sl+ywhRD7oN4fINgYIhaziUZjKKVwuCymLl3HRwtWkp7iZlCPEnweJyd37MyXW7YwuCyL+1ctI6bjGMrAazoZnPIVkcg88J2NUkoSFSHEYU+uWRHiAKiq8PPvO98g0CWTcI5BsFBTVFpD/9R1iW2KSzLvwOPojNMqxG0MlBkVIdo4rSEWiWEYCm+Km0ChjwmfLsPncXLnVacR0E3Xo1iGwU1HH8sXjYvwGA0UOOoocQU4KeNTBqYupzHwCLYOJbk3QgjROsjMihD7mdaah295iW1ug1Chl/oOkFNQS1HaVkZkfwFApvcMcnznJzlSIcT+pBS4vS6UoWjI9VCf7yHf6eDPV5/O+xUreW/aUh45fQSdsrLxR+tZWb+QXxVOw2XEMJWNiY2NIjf1JgzlTnZ3hBCiVZCZFSH2sw9fmcsns5YR6JJJQwm4skLk5m3jvNxPcRpxnGZ7yrLGyl3qhThEfPnJKrw+N450D1GPib/Ag7/AgwHcfOFwPtqymhe+/AJba+zmW5tlOtO4vvMZpFkGLsPAUhqlDCzDTba7JLkdEkKIVkRmVoTYj6o2bePff3qTxq7ZBPMNonlxykpqODlrMUWuWsCkY87DWIbcpV6IQ8GM977gsTGv0+eEbtQOLCAYihCL2xC38ficTA9u4o0Vi0l1unjotDPZEFtDuZ2JZZjkuTKpIYomBpiYyocmnuwuCSFEqyIzK0LsJ1WbtnHXL59iW4pJqMBNQ4mmoHgrPdM3cnT6SgDap/+eFNeAJEcqhNgf5nz4JY/d8TrKUHQ5spxwNIZlmfi8LrweB1uzYry69KumROXUM5hRN5MnV7/Fs2vfbT6CSnyZygdKJ7E3QgjROkmyIsR+8MFLc7hkyJ0sXraJxo6Z1HeAtLxGirK38uOc+QCkuY+lIO2qJEcqhNgfPp2ymEdvfw2Aa//8E7ZamrCKE/NAzKOpz7Gpy4rjtRw82JyoTNnyGRmOVE4tGAKAw8zEMjIxlAdNHK1tTMOHZWQksWdCCNG6yDIwIX6gqgo/D416mZjTpL5XLsF2CnKj5Lfbyrk5n+MzI1hGNh2y/45S8vmAEG3d/OlL+cfoV9C25qo7z6HGo/jvu5+xuVMMbcZQwPY5kqv7DGRG3QymVc0nw5HKbd0vIhJ8iHrjx6S6BtKj4C1itj9xbMvIwGkVJKNbQgjRKkmyIsQPtHbpJkJ5Xhq7ZhHzQGN7TWlpDcOyllLuqQagPPtvcr8EIQ4B4VCEJ/7yFrFonCv/OJK6dAf/fHk6hstAmzRlKbppZzCUZolayIqqlWQ607it2/8RDNxHXXgm4dhauuQ+g9MqwIkkJ0IIsTuSrAjxA73z6tymRMUFtZ0gp8hP58xKTshYCkB+6pWke4YnN0ghxH7hcju58cH/Y+3SCkI5Hh59aRqWafCLnwzh1nmTidtx0lzupl2/rDBrouvIcqZxa/cLaWy8i4bwPNxWB8plplUIIfaIJCtC/ACTX/+U6bOWETw+h1CnGOmZAYoKavhp7qcYSuN19qF9xk3JDlMI8QNtWlNNQUkWhmHQoVsRy7bW8o/mROW2y0/m/eqVYIZxOm0MBxgKYjGDS9qfS/fsDBob7qIh8hluqxOdch7FMjOT3SUhhGgTJFkRYh+tXVbJQ6NfIdA7HbN/A+UlW1FKMzJnARlWEPDQMfthDOVMdqhCiB9g+cL13HPdMxxxfA9+dcePUUpRUV2HZRrc+ouT+CRQwXurF1HSeTOGaZO4aEWbFHg8NDSMoTGyEI+jKx1zHsEy0pPdJSGEaDMkWRFiH4QCYe6+ehz+fA+hzhYFJVtIt4IMSVtJT18FAI32dbgdZckNVAix16or/dT7AwBsXFXFU2PfJhyMkl+clbiZ6yUjjuT4IzrzxtolvPTVQtJ9Djwuk7jWxLGxlIWlTNwuJ45oOVrbdMx5CNNITWbXhBCizZFkRYi9pLXmkdteY0WNn0DfXOIlIQamruWs7AUYzTelXxvKJDvl2OQGKoTYa9WVfq4f8QDBxhC2rQkHo6DgvGt+RFqfIuYv3UD/ru1RSvGpv6IpUXG5ufmYQTywZjlxbExl4jEdxLWNUgbtM0Zh6zCm4Ul294QQos2RZEWIvfThK3P58N3PaRhYQH05FGb5WyQqAMUuPyUZ7uQFKYTYJ/X+AMHGEKCIhCJoNA7Lwtkphwf++zFup4On77iQVJ+bMzp34fOKTfy8T29erHgTr9GIz4iR6YBj0hYxu64bAEoZmEoSFSGE2BeSrAixF1Yv3sSjt/+Php65NJYYUBihe8nGFokKgKE0PmNrcoIUQvwgGpoTFXC5HYSzPTw7cT5Op8X1Px9O1LABcFsObh92HPcv/S+VgaX8qnAaLiOGQ8VRaApztuJR9UntixBCtHWyb6IQeyjQEOIvVz+NvzSVQHsH4ZI47TpU0Sdtwy5Km7itsoMdohBiP7AdBirTg8pwEyxKwV+SilJw06UnMLV+HVe8/SaVDU1JyObQVlY3bKSjL4N0S+EybAwFSlk4TTdplv6e1oQQQnwXmVkRYg9orXl41MusCgRo7JtFfbmmfYdqjslZwcDUdc2ltm8BZFKWdTdOqzCJEQsh9lZVhZ8QNlt6ZGMbAArd/JHeRacOZErdOt5dvpQcj5dIPA5Aqa+Q0T0uI4UvWb/1GUBjKBcGXmwiyeqKEEIcMiRZEWIPvPv8TCZN/pL6QQXUdYLc0m30yVnP6VmLAMjyjqB9+mjC8bW4rTJJVIRoY1Yv3sTYa8fRdXg3nCkuDAXRmE0kFsfhMJintjB7+QbyvD7uPeVHzG/4guK041BKUew2WLrlHkCjcGDgRatY02cXQgghfhBJVoT4HisWredff3mT+t551HeE1Pb1dCncxHl58zCVxufsT4esv2IYblyOomSHK4TYSyu/2sA91z1LoD6E02VhKIXDYeJxG4QiUaoLokzftI6itDTGnjScJ9e9SkWomhTLy4/yj8Bp5uNz9icarwJU04yKBtPwYRkZye6eEEK0aZKsCPEdGuuC3HX1OGo7ZtJQbmIWhygrqeTneXNxGzGcZhGdc/+DYcjOX0K0RSsWrefe3zxHoD7E2ZcdR317H+HVq4lZGsMw8OfFaEy16ezx8peThvHEulfZEt5K/4yuHJO9fbcvk/LsvxKJ3Uxc1yaObRkZOK2CZHVNCCEOCZKsCLEbWmseuOlF1qgoDeXpRMtidCjbzIX5n5DlCGAoH51zn8Jh5iY7VCHEPli+cD33/uZZgg1hfnzFcHSnLF4YP5PNnWJo8xsFFVw1sC+Pr32Zmkgtg7N68fN22ayo+ikdcx7B4+iEUhYuRyEgS0CFEGJ/kmRFiN1466lpfDx3GfWDcmnoaFNSvoVzCz6n1L0VMOiY8wheZ7dkhymE2AfhUIS/3/hCU6Jy5XDCJWm88PZcnD4HTk8MUylMw8DWGtMZ5p2G9wnaQY7N6cdPCi3W+/8AaILR5XgcnZLdHSGEOGTJ1sVC7MKcjxbx2H3vUN8zm7rOmoKONZxU8BX9Upq2KS7JvJ0Mz/FJjlIIsa9cbidX/+lcfnr1CdQX+njh/c/wuBxcee4QbCOCdgTweKN4vDEcrijBeIgT8gZxbn6Ejf6/oDApzbyLLO9pye6KEEIc0mRmRYhveeupqTx6z9vU9cmlrotBZgc/RxWu4MTMJQDkpvwfeSmXJjdIIcQ+2bxhK3ntMlFK0evIjszasJl3Ji4gxePi5it+xN0LJ9O+cwWGaaNouturthUXFl3AgIz5bKp7AoWTDtn3keY+Osm9EUKIQ5/MrAjxDRtWb+Ghxz6kdnARDR0duDo00qdkLefkfA5AmnsoJZljUEp9z5GEEK3NV/NWMepnj/LqPyclnguGo6SnuLnplz/ir1/MYmPDVkzTbv6ujdZgGJo81yI2NzyBoXx0zHlYEhUhhDhIZGZFiGbRSIy7rn+exq5ZBHMg3jFCjw4buDB/Lg7Dxm11omPOIxjKkexQhRB7qLrST70/wIpFG3jmvneJx+J405p27zMMxW8uOI5FGyq5Y/bHVDbUM7CkHRusjUR0FIXCbTjQQHbKiZiRdeSmnI/X2T25nRJCiMOIJCtCAPG4zf2/+y+L/bU0dk0j1jFCx04buahwDqlmGDueSueip7CM9GSHKoTYQ9WVfq4f8QANdQEioSga8Ka6WRhspOu6KjqX5GIaBs8v+YLKhnpOKu9E9w5x3tpYR4YRxWOYpFoRtkTTUMqiNOuOJPdICCEOP5KsiMOe1ppHb3uVj+Yupf6IbBx96ulZtpHz8j6lwFlH1DbwmX/FbZUkO1QhxF6o9wdaJCpOt4OtJalMW7CS6voAf7thJEopbj/ueP63+CvSc2qZsOldflk4DZcRw1JxFJqg7cajfp3s7gghxGFJkhVx2Htq7Du89eEC6gbkEOgR5ZzuCxiZs4Dtl6V80diejj5JVIRoaxpqAwRtje1z4Pa58LdLIew2Kc1M5cyz+rAtFCTL4yXd7caVtYXXN86inUuRaikUuvkoJimWQZqlv7MtIYQQB4ZcYC8Oa688OpEXXplFbf8carvbdO22rkWiAjAgZT1OR0XyghRC7JOIAXUD86nvn8+WbpmEUh1oy6DfUcX8ccYkfvfBe0TjcQB6pJWT5Uzj8rKjUYQBG4UDU6Wh5E+lEEIkjbwDi8PW+Odm8J//fETtwFxqe9oUdtvCGe0W8e2NvgylKU+zd30QIUSrorVmwcxlTf+3DLRpoLf/UmsIZ8LzG78ibmvO7NoFy2j6M9g/syt/7nECocBDgEZhYSofqHiSeiKEEAIkWRGHqY/f/IyH/joe/8Bc6nrZtOu2hZ+Wfkr/lPU7ldUYFHh6JSFKIcTeiMfi/OdPb/LX3z7PBy/PISMnFSvNgU41IMUgWmbSUAaWaTLquCF8Fp3G6xs/TtT3B97A1gEM5UUpFzZRtLYxDR+WkZG0fgkhxOFMrlkRh525E79i7B9fZeugHOp727TvtpkLSucm7k6f4jyChshngA0YdMgai9MqTGrMQojvFglF+cetr/D5tKVk5qXRpX8pm4MBNneKYhuAAt08wXJBzy5MbviI6rCfdEcKcR3HVCYlmX8g3T0Mn7M3MdufOLZlZOC0CpLSLyGEONxJsiIOKwtnL+fOG//L1kE5NPSxKe1RwUUls+nurQSgIPVXtM8YRTReSSi2BrdVJomKEK1cY32Iv93wX5bOX0thaQ6n/PZHjHl+Euec1Q9tgNJgNycqbneET5mBHY4yJLsHI3O3EI2tx3SUYSg3md6TAHAiyYkQQrQGkqyIw8ayL9Zx27Xj2NI/k/q+NuU9N3BZ8Sw6eKoBaJ9+M4Xp1wDgtAolSRGiDfBX13Pvr59j3fJKynsU0e//BvPQ/2aitaba34jH7cBUBqZSKHcDme2qieBmRMERDEmZRnXjDAKRhXTOfQL17QvWhBBCJJ0kK+KwsHZZJbdc+QQVfTJo6G/Tpdd6Li+eQTuXH1CUZv6ZvNT/S3aYQoi9tHpJBetXbqbHoA7kn9yVp8Z/gmUaXPbTIXzkX41hxbAcGsuySS3cgsLmtJw+HOF9g/rwYlxWKaVZf5JERQghWilJVsQhrarCz5dzV/LoPW+zvnsKDQNtevRezeXtZ5DnbABMyrMfINt3VrJDFULsg/7HduHGB/+PD5et5Y0pi/B5nPz8vCP5z9LPqA5vI798A8po3s1PQbbVSG/vOILRGnzO/nTIvg/LSE9uJ4QQQuyWJCvikPXBS3P4+x9fI5rmoK5HJo1H2PTtvYrLi6eTaQUBJ51z/02G5/hkhyqE+B7VlX7q/QEAVi/eRHWFn/OuORGAFYFGpn6+kpyMFE49uyd/WzSLSDzOiZ1LWaTWYSkXhlJkmLX8JHcOaBcZ3lMoyRyDoZzJ7JYQQojvIcmKOCRVVfi598Hx1B1bSCQNop0jDOqznMvazyTVDAM+uuU9Tar7yGSHKoT4HtWVfq4f8QDBxhDxuE0kFAWl6NynmP7HdmXk8N5s2VqPXWzx0II5KBS/PKIfX9tzcTfWk+kAl+FE25ptsRSK086iNPMWlJLd+4UQorWTZEUckv733Ayqh2QS6hzDlxbkiPKVXFI0G48RQ6kMuuc/j88p904Roi2o9weaExVNJBRFA0aaiwbdtLzLsky8XXw89tkneCwHVx3dk6l1UwlHK/hV4TRcRixxrIht4XKdLomKEEK0EZKsiENKNBLjib+8xXPzvsS8APp12EiflPUcn7EUp2ETiWYxsOQ13I7yZIcqhNhD8ZhNUNtETTB8Tsj2UFvo45G3Z9OnXxnpqR5GdOnGnA3rOa57Gu9VTyCm45yU0w6fGQY0YduBApxGHK8RSXaXhBBC7CFJVsQhY/OGrfzp2nHMjwfwD3UxssccRuYsYPsmP/UxF9uCYyVREaIN0Vrzr7Fvs7VPLpgGGCpxc8cO5dnETA1AttfL0F5O3q2cjKVMrijtT65+nGAMwMRn+UADKkqGMzVZ3RFCCLGXZB5cHBLmTvyKK376EHNyYvhPsug7ZEWLRAXAZ4bJzpT8XIi2RClFr2M7g2mgv3EX+mgKTLcqGTXpAyLxOADd0srIcKRwU8f2ZNl/I2pvRmFiKh+mMjAMG4VsUSyEEG2JJCuiTYtF4zx+11vcdNcrrD4uFf2jRs44+lOuLp3Ct2+bYCgoT7OTE6gQYo9prfn609WJx0ee3AvtM4ilKOJeRbjYoK4ThHWcnoXpmM2/7P0zO/L7sgZi4f8AmvzUK7CMbDQ2to6gtY1p+LCMjOR0TAghxF6Tj5lFm1VV4eeO68Yxzxmk8SwPnXuv5qfF8+ji3QKA1rRIWDQGBR65qF6I1iwSjvH0Pe8w7Z35XPGHszl+5EDqYhFqumq0CVppUE1Lv07qlsn8+DTer3RwZtFQFA4UIRxGLmVZY/G5+pDjO4eY7U8c3zIycFoFSeqdEEKIvSXJimiTPpu6mNvHvMKG/l6cgwKc12M+J2Yuxmk0LQdJ95xBmqs/6/13AzZg0CFrLE6rMKlxCyF2r7rSz0M3v8SqrzeRkZeGkeEBQFtgemIo06ZpFZcmI7uRFUYNHhy4VdP9V5RSlGT+Ea1jWGYmAE6rACeSnAghRFslyYpoE6oq/GxaXUVBSTbv/HcmT89YQO2ZLnoPWMb5xfNo5/I3FVR5dM65N3GjxyzvGYRia3BbZZKoCNGKfTVvFf8Y/Qr1/gCl/YoJdc3m0ffn0q1PMYY3Rkm3zSjDRgHKaJpZSbHS+W1ZFDN+L+FYT1xWe0xDLp4XQohDSVKvWZk2bRojRoygqKgIpRRvvvnmHtedOXMmlmXRr1+/Fs/fcccdKKVafHXr1m3/Bi4Oqg9emsP5p9/NNXc+w3nn3c+ja74mfmGIy06exG87TqSdy4/WimzfJQxo93GLO9I7rULS3EMkURGiFfvo1U+457pnqfcH6HFGL1bmOFi6vorMbB/rav0E4iEMo+l6s+2JSroV4BeFCyA2EaWcxOJbk9gDIYQQB0pSZ1YaGxvp27cvv/jFLzjnnHP2uJ7f7+fiiy/mRz/6EZs3b97p+z179mTixImJx5YlE0htVVWFnz+8/SHmr120y9xKZUMag0q/4tx2n5HtaARAGeV0z32AFFffJEcrhNgT1ZV+6v2BxGPLYWI6TMrP7cusDU3XnPU4sh0LqeaBz2fz66P7kmaGcBthDAOKXTUcm74Ct3Ljcx5BWdZdOMzcZHVHCCHEAZTUs/jTTjuN0047ba/rXXXVVVx44YWYprnL2RjLsigokDXKbd22qnruue9/DL5sKRd1mYmhWl40H9cWRem/pX36VRjKkdxghRB7pLrSz/UjHiDQEEr8LrtS3KSf2Z1PN2zB7XWQe0QW0/0bAE2/Mh8pLj9Xt5+C04hhKhsTGw243T+mU86dKCUfSAkhxKGqzb3DP/3006xatYrnn3+eu+66a5dlli9fTlFREW63myFDhjB27FhKSkp2e8xwOEw4HE48rqurA8C2bWz7h291a9s2Wuv9cqzDwbKF6xj3xGSmbqnA9aN67m1OVGBHolITKOW48qdxW2WgwdZt92cr40PszqE4NrZuqcMfCBJR4HRZmKZBPByhS4aPRp9NVV6EBdsqyUo16dkpxoboQhb6ayg14thaYQC2AlubZHrOQmsD3YZ//3+IQ3F8iP1HxofYndYyNva0/TaVrCxfvpxRo0Yxffr03S7tGjx4MOPGjaNr165UVFRw5513MnToUL788ktSU3d94eXYsWO58847d3q+qqqKUCj0g+O2bZva2lq01hiG3NpmV2KxOLM+WsxLExawuiRKztAaTipfxlGZKxOJyjc1hH9C3VYvdWw5+MHuZzI+xO4cSmNDa80XM1by8n+mUd0rB20aiQ8fVFyTXuhg8TY/KqjpWQaRlI1sCNl08UTpYKzBYTiatgXDBKKYho1dH2VLY9t/D9hXh9L4EPufjA+xO61lbNTX1+9RuTaTrMTjcS688ELuvPNOunTpstty31xW1qdPHwYPHkxpaSmvvPIKl19++S7rjB49mhtuuCHxuK6ujuLiYnJzc0lLS/vBsdu2jVKK3NxcecMAqiv8bFxdRbsOuTicFuOenMxrK77GOaSOo65fxgXZaylz1+y2vq0VR3c8kTxv3kGM+sCR8SF251AZG0vmr+XlRz5ixaINNFoQa5eGdihQTYmKiit65xTRP60Gnb6BAA1kWY2ck1dNhrEE0NjNS0AVCo2BBrKzs/A4Do33gX1xqIwPcWDI+BC701rGhtvt3qNybSZZqa+v59NPP2X+/Plcd911wI5pLMuy+PDDDznhhBN2qpeRkUGXLl1YsWLFbo/tcrlwuVw7PW8Yxn57EZVS+/V4bdUHL83hsZefI+OIIJXPZxDo7GHQ0cv59cjVdPBUtZhFCduppHlOYVskgtt+B0NpbK0IWFdSlNI9eZ04AGR8iN1p62NDa80LD37AyiWbcHfLpS7Pib+oofkGj4AGI66Iuw0KcxvZFKji7KxNdHKvxFAah5FHju98KuoeIa4b0UQAMA0fDjOrzf5c9pe2Pj7EgSXjQ+xOaxgbe9p2m0lW0tLSWLRoUYvn/vnPfzJ58mRee+01OnTosMt6DQ0NrFy5kosuuuhghCl2YVt1PV8vXMvk2YvZ2uN/jHpwTuJieQ0tEpRQ3I3TOZyuWReR7j4KpUwAKgLXsjmwiHxvbwq9XZPTESHEHtlWVc/WLbV07NkepRR9z+3PwolQZyjqzAiGJ4Zh2qA0pmkTCzkwUp38vF0q/oYZOJWNaaSQn3oZOSk/xVBuMr0nyZ3ohRDiMJTUZKWhoaHFjMfq1atZsGABWVlZlJSUMHr0aDZu3Mizzz6LYRj06tWrRf28vDzcbneL52+88UZGjBhBaWkpmzZtYsyYMZimyQUXXHDQ+tUWvT//I77cModeeUdxWv+T9qlO3bZGZs5bytRlX7NJrcTMqCQzexvZ6fXk5NTT6yd1tHP7d6xTb1oFQihuETWOolf2JeT4hu9yZ69Cb1dJUoRoZXa1BfGcD7/kvednkZKfygMv/xrLYTLwyE48sGAeZq6DBkeMXl3WkOLYvhuYpiHiJu6MUJxyBKGgkxzfT8lLvQTL2LEMV+5EL4QQh6ekJiuffvopxx+/4wZ+268bueSSSxg3bhwVFRWsW7dur465YcMGLrjgAmpqasjNzeXYY49lzpw55Oa2vT3490cCsSf+/OHlnNx1EsOzwdZP8ucPf8TtJz9JKBhlc5WfdVVb2Fi7iZrGauoiWwnE60gpnMHwkq8Yng1aP8nLX+cQxyC7YwMjuwYxld7jfi7ceDnXHjt6j8u3RkuWbmTz5trE4/z8dLp1bfe99SZ8MZENW9cQDIXwuN20zyrj1L4nfn8d/47fi/YZJd9bZ1/rHcy22kKMB72tvRwbP6itvaxTXenndzffBdkBNGDHbYIbLOLVudQXeYi2N9i0tZaS/CzKi7Ip6Oukxq6ic/o2flXycdM2xNgYStMYd2I4LsDjGEbPgnflLvRCCCESlNZ6z88qDxN1dXWkp6dTW1u73y6w37JlC3l5eXu8Pu/vM0/l2PZLUM3LpeZXl1CxpSvKsIHmL6VRqvlfbIpz19AjoyJRZ1ldHptq8zFUHMOwMZSNadgYho2pmv51mxG6pVcmZjugqW5tzI3DsHGqGA5j37a2i2uFP+KjPpKOTT5KpVHmm9KiLVtDxH6eoR2O3e1xWvsJ85KlG/ntE//Cm7Vj57jAVjcPXXH1dyYsE76YiJVyHS4jlngubFvEGh7ZbXv7UqcttNUWYjyc24pGYjTWhwjUhwjUB/Gmupm3aR6+/Bt2qnf35JHUOjykpQU4q92R/G7wuQA8+tX9BOKzyLT89PStRqHZ/lYQ1wYOz2MckX/ybvsmdrYvf1vE4UPGh9id1jI29vR8u81cs3I4eeSjhzi2y5IWy6UG5K6D3D2fZVIKuqZvoWv63m/rqRRkOPZ+y+ZFNcWkOI6na94AOmb0x+don7jmBJpOikL2TNxGNJFQhW0Hgbqmtmzbxo5rYrEY4XCMaCTGpK+nkl18M13TWp4Q/e2tm+iQ1ZlINEI0HiGqI0TiMS474SxcLicTvpiIM/VauqXvqBe1TW5980w85HP7yFsAqGts4P4P7wXVlADGzWpO6jWV7unxppi0ImxbvDzrLhbWTENpu2ntmmra3EEpjW1HuOmqWU0nbQpMbGLa5IVly9GrfKBBKY2KZ3LnmX8HYPLCacz3/4Nh6RFsDRqFgcZrRvhw81OcStNJ4v/mvMWiuleAprbc7jqGpkfQGuIYaBQuI8asDRP4pOrxb72QTZ9DGKHOFKR0TPwMldKo5rZmN/6NeZP/DYAV6sXo08cAcP/792KkT2ZIegS7qXUUGp8Z4YNNryROYu9+dwza13QtmaKpPY+rkaPSI8S0QUwbGErjMaPMC9zL51Me3WncZNtn8KsTrmCDfx3d0yM0X3ONAnxmhE+C9zJ/6iMUGz/j/4b+DIAx71+Jx7cFjyvAkekR9DfquM0oS5qTzTs+uAS3x79Tm15XIwPSY8S1wtYKp4rhMyPMC9/DgmkPtyh7Vtn99Cjpwgb/Onp+q62mOmP5YvpDXNnvWbJSMwG4Z9rZTR8kAF5XgEHfqBfTJi4jxvKq5dw7/aGdYgNwWBGOSItho9AanEYcnxnh0/DdLJyxo0447OX2H70MwNSvZ7E8fHeLtrbHOM3/UGJMvTnvXZaF/5U4hse5I764VtgYuIwYM9a9y4LaB5p+Ub+ldkURHbOOJsuIoQFL2Sg0DivODcPH42r+QKQmvg1oSlaG5jkJBlcDcZTWTbMxGERtA0NBhtuzy5+FEEKIw5skK63QVvuLFrMP24XjBnFMdPMJdCjuQKNwGlF8VhivGdupTnXYS2UgC9tWpLgC+KwIuvkzTVuD04iR42zcaWZlQzCDhogHWyvi2sC2DWyt0LUjqI1Uc3z3l3aq47Qi1ISnMXvDNL5Y8isuPq7pOqF7p48gJ20bbjNChhHD3r4FEGAoOzGL8eTCYWR7GjBU08akSmnSi6OkWiHCtkW8+cQ31QoxoPe92Oz8aUBt43DyXDls8K+jT0aYb55mOc04J/UZT1RbQFOy0hhuZFjfVxNlDGy8xjdPLB24jBjrar/mhJ4f7vL1qou4cBlNJ5bYGqdpYymb4zvPbxHjxoasxP+XVC3iqA6LsZTdtCNSMwWUF65KPF5Vu5ChnT9rEV+ijlZE7KafiXJt4ujyL3YZ3/yKAMQ6bn+lcKh4oq0BBSsTMX6ybscMWsjxJccUrG6agfvGsRTgTanY8dj3JYNLvm7RnkHTiWqs+cQX3TSL1zd/7S5fszlLO+6oq7ZvSrujvT55TfU+X7488Xy7/GV0zNicaOubr7PWOxLk8sLltEvZulObRnMKZmsDG6NpthHonbNupxhrGndso22olrOMCuidsx4bg0h0x+/fgHbLMZvLfjvGiG017WxHnEHtlrMr4XjTW7Otm35XTRVFAb1yNrSIryaUkvh/Ze0meuVv2OnnoYDSnB2v2aa6NQzssONawZbxGcRs1fQ6OGs5ov3KXca32BuDwNGJx9v7qoAUI47DkY3TzKGDd2CiTOeM0wl4S6mNVFFRew92c8K9/fX2mXu2haUQQojDiyQrrZDTbofW7JQMxLRJnKYTsU/WDOD2E58HYOyUnzCk5Itd1vlqcxk3HvseAPfPOJP+RS23cG46aSNRVzd/yp/pDJDu3Hl25bPqRrI9XYhpAws7UQegnW8btq/puo0l26oTdQrSa2ifspWm00Ld4uT8m9IcIdKtYHMipbBR2ycHmh83nfhqFP6Ih0jc2fS8Npr/VfTK2nGaZjcnZBqj6c4MSrOyNp9gxMfJzefHXpeHRZWdAIXWCqcjwIC8Vc0L7ZqOayiN25HK5xv6NOdYzQtYtndEhckpWdh8YmkQtZva+nxjN2LRrMRiF9POScQ2oGQQ0zf05JiSLxIzK00xwvrN3aF3U7kj2g9l7qrtJ5oKzC0M7fBZUxJJU2wA7nhHPluVu6Pc9v8pRbazG9tPsTVNia7R/POYs2Ygll0EQImvb6Jet/Szmb3aZljH2ejm12J7Amk39kiU6+A+l/mrurRoL6zXM6zTrObZoqZrEuLaYNaqwXgo2el1P7Zkx7VVtjaIa77RHsxaNQSPKmFY+amJcmbjz1i4rYKAXsfwTtPR36jzzV+CkP9nLKraOVlp1Gs4rtOMpp+ftonZFrbSzFp1DD5V1qLszwft6F9Mmy3aaoqvqc6RR3sT5Zas+zm6+c68DXoVwztNa54N2/GaWaaDr9b8fKfYAOri6xnWaXLzdt2aqG02tbXyWFLNHcmdy/Ql/n9UpyN5/otjGd5paqItsznGleuPgp5N5Y7vehIfLdtxfVV9fCXDO0/B1iTGO0CGoxsb6/qimn+eCkApFNA5s4Sq+I5jhGwLRdPOfhuqbuH/jrp0pz55HJ3wODqR6qrE3/hvbN2Y+J6hfOS4i3f5sxBCCHF4k2SlFcrxdtgpGYijmLNqOFnuph2xjinqlyg/MOdy5q56g+M6f4SpdYs6RnBIolzvjKtZv3n7J6VNSc/mxq84ttMHxLVKLBsxlOaTVadQkt4XAwOUwjAUoDi377F8vHQqcW0Q1wZsPxVXsGDNOQwsGY5lmJx/ZP9Eu0PbP4lNhI++fJ/eJY8nEgtDab6Zt5zXYzZgJk6OAJ6Y+hTekrtRCgzddOIbtU1qNv+WK4b94jt/jlHbbE5Ymj8p1hrqLuPX36iX7kvj+qPHt2gvpu9uUQ/A40jn18e9sst2Xvn8BWBh84ll8/IsrSn2/YzzBly4yzpHdR6MP3AtgfiOawU0ikDcYmDujhPY4T2HM7zn8MTjCV9MTNQxmmuFbYveBcO+91qGsG19qy0H/bMv32W9nxzxEyZ8kUEw/hkuI9a8NEsRijvoV7gjufjZUTv3b8IXEwnG5+EyYljNn7iH4g4G5l7ynTG2zyghGHd8qz2LgbkX7VTv8qFXf6OtOS3qhOMW7TOakqJfHveb3f88muttf42DcQcDc3++2xh3H9/OdX5z/G3f+nnM3uk1K83qyKl9f7X7+OxpzfF9o628C3cbX2luCQNzLyQYn5VoK1GvcGSiXPf2Xeje/tZvxTcz0db2+LpkD/jO12umNZtg3Er8PKBpZ78OBd+9a5/TKqBXwTuyDbEQQog9IhfY70KyL7DffsGr24wm1u+H4o49ukh2b+p8s15bvvg32fW+ql5ARd3PcKlv1NEWhWkv0TOn327b2t6e7AbWdmKU3cBamrlmNhX1O+oVppZwTNmQ76gh9qfWcpGsaJ1kfIjdaS1jY0/PtyVZ2YVkJyvQRk6kDsG29rXeV9ULqApuTDzO9bT73kRlu9bypiFaHxkb4rvI+BDfRcaH2J3WMjYkWfkBWkOyIg4fMj7E7sjYEN9Fxof4LjI+xO60lrGxp+fbMnqFEEIIIYQQrZIkK0IIIYQQQohWSZIVIYQQQgghRKskyYoQQgghhBCiVZJkRQghhBBCCNEqSbIihBBCCCGEaJUkWRFCCCGEEEK0SpKsCCGEEEIIIVolSVaEEEIIIYQQrZIkK0IIIYQQQohWSZIVIYQQQgghRKskyYoQQgghhBCiVZJkRQghhBBCCNEqSbIihBBCCCGEaJWsZAfQGmmtAairq9svx7Ntm/r6etxuN4Yh+aFoScaH2B0ZG+K7yPgQ30XGh9id1jI2tp9nbz/v3h1JVnahvr4egOLi4iRHIoQQQgghxKGrvr6e9PT03X5f6e9LZw5Dtm2zadMmUlNTUUr94OPV1dVRXFzM+vXrSUtL2w8RikOJjA+xOzI2xHeR8SG+i4wPsTutZWxoramvr6eoqOg7Z3hkZmUXDMOgffv2+/24aWlp8oYhdkvGh9gdGRviu8j4EN9FxofYndYwNr5rRmU7WcQohBBCCCGEaJUkWRFCCCGEEEK0SpKsHAQul4sxY8bgcrmSHYpohWR8iN2RsSG+i4wP8V1kfIjdaWtjQy6wF0IIIYQQQrRKMrMihBBCCCGEaJUkWRFCCCGEEEK0SpKsCCGEEEIIIVolSVaEEEIIIYQQrZIkK/vJo48+SllZGW63m8GDB/PJJ598Z/lXX32Vbt264Xa76d27N++9995BilQkw96Mj8cff5yhQ4eSmZlJZmYmJ5544veOJ9F27e17x3YvvfQSSilGjhx5YAMUSbW348Pv93PttddSWFiIy+WiS5cu8vflELa34+PBBx+ka9eueDweiouL+d3vfkcoFDpI0YqDZdq0aYwYMYKioiKUUrz55pvfW2fKlCkMGDAAl8tFp06dGDdu3AGPc09JsrIfvPzyy9xwww2MGTOGzz//nL59+3LKKaewZcuWXZafNWsWF1xwAZdffjnz589n5MiRjBw5ki+//PIgRy4Ohr0dH1OmTOGCCy7g448/Zvbs2RQXF3PyySezcePGgxy5OND2dmxst2bNGm688UaGDh16kCIVybC34yMSiXDSSSexZs0aXnvtNZYuXcrjjz9Ou3btDnLk4mDY2/HxwgsvMGrUKMaMGcPixYt58sknefnll7n11lsPcuTiQGtsbKRv3748+uije1R+9erVnHHGGRx//PEsWLCA66+/niuuuIIPPvjgAEe6h7T4wY488kh97bXXJh7H43FdVFSkx44du8vy5513nj7jjDNaPDd48GD9q1/96oDGKZJjb8fHt8ViMZ2amqqfeeaZAxWiSJJ9GRuxWEwfffTR+oknntCXXHKJPvvssw9CpCIZ9nZ8/Otf/9Ll5eU6EokcrBBFEu3t+Lj22mv1CSec0OK5G264QR9zzDEHNE6RXIB+4403vrPMzTffrHv27NniufPPP1+fcsopBzCyPSczKz9QJBLhs88+48QTT0w8ZxgGJ554IrNnz95lndmzZ7coD3DKKafstrxou/ZlfHxbIBAgGo2SlZV1oMIUSbCvY+NPf/oTeXl5XH755QcjTJEk+zI+3n77bYYMGcK1115Lfn4+vXr14u677yYejx+ssMVBsi/j4+ijj+azzz5LLBVbtWoV7733HqeffvpBiVm0Xq39vNRKdgBtXXV1NfF4nPz8/BbP5+fns2TJkl3Wqays3GX5ysrKAxanSI59GR/fdsstt1BUVLTTG4lo2/ZlbMyYMYMnn3ySBQsWHIQIRTLty/hYtWoVkydP5uc//znvvfceK1as4JprriEajTJmzJiDEbY4SPZlfFx44YVUV1dz7LHHorUmFotx1VVXyTIwsdvz0rq6OoLBIB6PJ0mRNZGZFSFasXvuuYeXXnqJN954A7fbnexwRBLV19dz0UUX8fjjj5OTk5PscEQrZNs2eXl5/Oc//2HgwIGcf/753HbbbTz22GPJDk20AlOmTOHuu+/mn//8J59//jmvv/467777Ln/+85+THZoQ30lmVn6gnJwcTNNk8+bNLZ7fvHkzBQUFu6xTUFCwV+VF27Uv42O7+++/n3vuuYeJEyfSp0+fAxmmSIK9HRsrV65kzZo1jBgxIvGcbdsAWJbF0qVL6dix44ENWhw0+/LeUVhYiMPhwDTNxHPdu3ensrKSSCSC0+k8oDGLg2dfxsftt9/ORRddxBVXXAFA7969aWxs5Je//CW33XYbhiGfXx+udndempaWlvRZFZCZlR/M6XQycOBAJk2alHjOtm0mTZrEkCFDdllnyJAhLcoDfPTRR7stL9qufRkfAPfddx9//vOfmTBhAoMGDToYoYqDbG/HRrdu3Vi0aBELFixIfJ111lmJ3VuKi4sPZvjiANuX945jjjmGFStWJJJYgGXLllFYWCiJyiFmX8ZHIBDYKSHZnthqrQ9csKLVa/Xnpcm+wv9Q8NJLL2mXy6XHjRunv/76a/3LX/5SZ2Rk6MrKSq211hdddJEeNWpUovzMmTO1ZVn6/vvv14sXL9ZjxozRDodDL1q0KFldEAfQ3o6Pe+65RzudTv3aa6/pioqKxFd9fX2yuiAOkL0dG98mu4Ed2vZ2fKxbt06npqbq6667Ti9dulSPHz9e5+Xl6bvuuitZXRAH0N6OjzFjxujU1FT94osv6lWrVukPP/xQd+zYUZ933nnJ6oI4QOrr6/X8+fP1/PnzNaD//ve/6/nz5+u1a9dqrbUeNWqUvuiiixLlV61apb1er77pppv04sWL9aOPPqpN09QTJkxIVhdakGRlP/nHP/6hS0pKtNPp1EceeaSeM2dO4nvDhg3Tl1xySYvyr7zyiu7SpYt2Op26Z8+e+t133z3IEYuDaW/GR2lpqQZ2+hozZszBD1wccHv73vFNkqwc+vZ2fMyaNUsPHjxYu1wuXV5erv/yl7/oWCx2kKMWB8vejI9oNKrvuOMO3bFjR+12u3VxcbG+5ppr9LZt2w5+4OKA+vjjj3d5HrF9PFxyySV62LBhO9Xp16+fdjqdury8XD/99NMHPe7dUVrL3J8QQgghhBCi9ZFrVoQQQgghhBCtkiQrQgghhBBCiFZJkhUhhBBCCCFEqyTJihBCCCGEEKJVkmRFCCGEEEII0SpJsiKEEEIIIYRolSRZEUIIIYQQQrRKkqwIIYQQQgghWiVJVoQQQnwnpRRvvvlmq2t3zZo1KKVYsGDBdx5n+PDhXH/99XvV9qWXXopS6qD1ffjw4Yn2vq8/QghxOJFkRQghDmNVVVVcffXVlJSU4HK5KCgo4JRTTmHmzJmJMhUVFZx22mmJx0op3G43a9eubXGskSNHcumll+632L7d7veZMmUKSin8fv9+af/UU0/d6xj21euvv84nn3xywNsRQoi2xkp2AEIIIZLn3HPPJRKJ8Mwzz1BeXs7mzZuZNGkSNTU1iTIFBQU71VNK8cc//pFnnnnmgMW2q3YPpu3J28GQlZVFXV3dQWlLCCHaEplZEUKIw5Tf72f69Once++9HH/88ZSWlnLkkUcyevRozjrrrES5XS2Fuu6663j++ef58ssv96gtrTW5ubm89tprief69etHYWFh4vGMGTNwuVwEAoFdtvvJJ5/Qv39/3G43gwYNYv78+YnvrVmzhuOPPx6AzMxMlFItZnls2+bmm28mKyuLgoIC7rjjjj2K+5t2NXOzYMEClFKsWbMGgHHjxpGRkcH48ePp2rUrXq+Xn/zkJwQCAZ555hnKysrIzMzkN7/5DfF4fK9jEEKIw40kK0IIcZhKSUkhJSWFN998k3A4vFd1jznmGM4880xGjRq1R+WVUhx33HFMmTIFgG3btrF48WKCwSBLliwBYOrUqRxxxBF4vd6d6jc0NHDmmWfSo0cPPvvsM+644w5uvPHGxPeLi4v53//+B8DSpUupqKjgoYceSnz/mWeewefzMXfuXO677z7+9Kc/8dFHH+1Vn/dUIBDg4Ycf5qWXXmLChAlMmTKFH//4x7z33nu89957PPfcc/z73/9ukbgJIYTYNUlWhBDiMGVZFuPGjeOZZ54hIyODY445hltvvZWFCxfuUf2xY8cyYcIEpk+fvkflhw8fnkhWpk2bRv/+/Vs8N2XKFIYNG7bLui+88AK2bfPkk0/Ss2dPzjzzTG666abE903TJCsrC4C8vDwKCgpIT09PfL9Pnz6MGTOGzp07c/HFFzNo0CAmTZq0R3HvrWg0yr/+9S/69+/Pcccdx09+8hNmzJjBk08+SY8ePTjzzDM5/vjj+fjjjw9I+0IIcSiRZEUIIQ5j5557Lps2beLtt9/m1FNPZcqUKQwYMIBx48Z9b90ePXpw8cUX7/HsyrBhw/j666+pqqpi6tSpDB8+PJGsRKNRZs2axfDhw3dZd/HixfTp0we32514bsiQIXvULjQlK99UWFjIli1b9rj+3vB6vXTs2DHxOD8/n7KyMlJSUlo8d6DaF0KIQ4kkK0IIcZhzu92cdNJJ3H777cyaNYtLL72UMWPG7FHdO++8k88//3yPtvft3bs3WVlZTJ06tUWyMnXqVObNm0c0GuXoo4/+gb3ZNYfD0eKxUgrbtvfqGIbR9CdTa514LhqN7lFb+6N9IYQ4HEmyIoQQooUePXrQ2Ni4R2WLi4u57rrruPXWW7/3gnGlFEOHDuWtt97iq6++4thjj6VPnz6Ew2H+/e9/M2jQIHw+3y7rdu/enYULFxIKhRLPzZkzp0UZp9MJcMAuXM/NzQWatlTeTu6JIoQQB5YkK0IIcZiqqanhhBNO4Pnnn2fhwoWsXr2aV199lfvuu4+zzz57j48zevRoNm3axMSJE7+37PDhw3nxxRfp168fKSkpGIbBcccdx3//+9/dXq8CcOGFF6KU4sorr+Trr7/mvffe4/77729RprS0FKUU48ePp6qqioaGhj3uw57o1KkTxcXF3HHHHSxfvpx3332Xv/3tb/u1DSGEEC1JsiKEEIeplJQUBg8ezAMPPMBxxx1Hr169uP3227nyyit55JFH9vg4WVlZ3HLLLS1mPXZn2LBhxOPxFtemDB8+fKfndhXrO++8w6JFi+jfvz+33XYb9957b4sy7dq1484772TUqFHk5+dz3XXX7XEf9oTD4eDFF19kyZIl9OnTh3vvvZe77rprv7YhhBCiJaW/ufhWCCGEEFx66aX4/f49uhZnf1mzZg0dOnRg/vz59OvX76C1K4QQrZnMrAghhBC7MH78eFJSUhg/fvwBb+u0006jZ8+eB7wdIYRoa2RmRQghhPiWLVu2UFdXBzRtc7y7C//3l40bNxIMBgEoKSlJbBYghBCHO0lWhBBCCCGEEK2SLAMTQgghhBBCtEqSrAghhBBCCCFaJUlWhBBCCCGEEK2SJCtCCCGEEEKIVkmSFSGEEEIIIUSrJMmKEEIIIYQQolWSZEUIIYQQQgjRKkmyIoQQQgghhGiV/h9TibjQ2QlxbQAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Saved /home/filipe/Desktop/GITHUB/tidyvernier-dual-ring-filter/tidy3d-community-library/notebooks/data/sin_waveguide_sweep_h0220_te_modes/plots/neff_vs_width_te00_te01.png\n" ] }, { "data": { "text/plain": [ "PosixPath('/home/filipe/Desktop/GITHUB/tidyvernier-dual-ring-filter/tidy3d-community-library/notebooks/data/sin_waveguide_sweep_h0220_te_modes/plots/neff_vs_width_te00_te01.png')" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "plot_sin_neff_width(SIN_SWEEP_HDF5, SIN_SWEEP_PNG)" ] }, { "cell_type": "markdown", "id": "KEwOA1lck-Fp", "metadata": { "id": "KEwOA1lck-Fp" }, "source": [ "Looking at the results, we see that the second mode appears to begin close to 430-440 nm depending on the wavelength of interest. Choosing a width for the waveguide that is close to this is good to ensure that we only couple to the TE00 mode." ] }, { "cell_type": "markdown", "id": "6Hh9GUCJk0L1", "metadata": { "id": "6Hh9GUCJk0L1" }, "source": [ "### 2.2 Waveguide Inverse-Taper Edge Coupler\n", "\n", "To couple the laser output into the SiN waveguide, the chip is placed directly\n", "at the laser edge and the SiN entrance is narrowed into an inverse taper. The\n", "complex laser-output field stored in `data/sim_data.hdf5` computed from the laser cavity portion of the notebook is replayed as a\n", "Tidy3D `CustomFieldSource`. A 2D effective-index FDTD sweep then varies taper\n", "tip width and taper length to maximize fundamental-mode coupling while limiting\n", "reflection.\n", "\n", "The complete sweep construction, optional cost estimate/cloud run, HDF5 result\n", "reader, and plotting workflow are contained below. The cloud sweep runs only if its results are not already saved on disk;\n", "otherwise the saved results are reused.\n", "\n", "This next codeblock was written to deal with folder and location data issues. If you are running everything in the same folder/directory, we imagine this portion will need to be changed slightly, and can likely be omitted to a degree." ] }, { "cell_type": "code", "execution_count": 27, "id": "tf2x8_gm7_CX", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.859328Z", "iopub.status.busy": "2026-06-22T18:48:40.859238Z", "iopub.status.idle": "2026-06-22T18:48:40.863755Z", "shell.execute_reply": "2026-06-22T18:48:40.863246Z" }, "id": "tf2x8_gm7_CX" }, "outputs": [], "source": [ "import json\n", "from dataclasses import asdict, dataclass\n", "from pathlib import Path\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import tidy3d as td\n", "import tidy3d.web as web\n", "\n", "\n", "def _inverse_taper_find_path(*relative_candidates):\n", " \"\"\"Find the first existing candidate path from common notebook roots.\n", "\n", " The fallback path is returned even when it does not exist so the calling\n", " function can raise a specific, user-facing ``FileNotFoundError``.\n", " \"\"\"\n", "\n", " roots = [Path.cwd().resolve()]\n", " if \"__file__\" in globals():\n", " roots.insert(0, Path(__file__).resolve().parent)\n", " roots.extend(root / \"final_submission\" for root in tuple(roots))\n", "\n", " # Preserve search order while removing duplicate roots.\n", " roots = list(dict.fromkeys(roots))\n", " for root in roots:\n", " for relative_path in relative_candidates:\n", " candidate = (root / relative_path).resolve()\n", " if candidate.exists():\n", " return candidate\n", " return (roots[0] / relative_candidates[0]).resolve()\n", "\n", "\n", "FINAL_SUBMISSION_ROOT = _inverse_taper_find_path(\"data/sim_data.hdf5\").parent.parent\n", "SIN_INVERSE_TAPER_SOURCE_HDF5 = _inverse_taper_find_path(\n", " \"data/sim_data.hdf5\",\n", " \"final_submission/data/sim_data.hdf5\",\n", ")\n", "SIN_INVERSE_TAPER_PASSIVE_NEFF_HDF5 = _inverse_taper_find_path(\n", " (\n", " \"passive_sin_mode_sweep_fig1a_width_0020_1000_h0220_te_modes_no_si_cloud/\"\n", " \"passive_sin_mode_sweep.hdf5\"\n", " ),\n", " (\n", " \"final_submission/\"\n", " \"passive_sin_mode_sweep_fig1a_width_0020_1000_h0220_te_modes_no_si_cloud/\"\n", " \"passive_sin_mode_sweep.hdf5\"\n", " ),\n", ")\n", "SIN_INVERSE_TAPER_SWEEP_DIR = (\n", " FINAL_SUBMISSION_ROOT / \"sin_inverse_taper_2d_sweep_from_sim_data\"\n", ")\n", "SIN_INVERSE_TAPER_ANALYSIS_DIR = SIN_INVERSE_TAPER_SWEEP_DIR / \"analysis\"\n", "SIN_INVERSE_TAPER_TASK_PREFIX = \"sim_data_custom_source_taper_2d\"\n", "\n", "# Point the passive-neff data at the SiN sweep result produced earlier in this notebook.\n", "SIN_INVERSE_TAPER_PASSIVE_NEFF_HDF5 = SIN_SWEEP_HDF5" ] }, { "cell_type": "code", "execution_count": 28, "id": "T18nPhbX8hxJ", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.866085Z", "iopub.status.busy": "2026-06-22T18:48:40.865874Z", "iopub.status.idle": "2026-06-22T18:48:40.870254Z", "shell.execute_reply": "2026-06-22T18:48:40.869748Z" }, "id": "T18nPhbX8hxJ" }, "outputs": [], "source": [ "@dataclass(frozen=True)\n", "class InverseTaperSweepConfig:\n", " \"\"\"Settings for the 2D effective-index inverse-taper sweep.\"\"\"\n", "\n", " wavelength_um: float = 0.740\n", " bus_width_um: float = 0.50\n", " tip_width_min_um: float = 0.05\n", " tip_width_max_um: float = 0.40\n", " tip_width_step_um: float = 0.05\n", " length_min_um: float = 50.0\n", " length_max_um: float = 500.0\n", " length_step_um: float = 25.0\n", " bus_length_um: float = 6.0\n", " source_gap_um: float = 0.45\n", " source_z_slice_um: float = 0.03\n", " core_neff: float = 1.78\n", " clad_index: float = 1.444\n", " sim_y_span_um: float = 4.0\n", " pml_padding_x_um: float = 1.2\n", " monitor_y_span_um: float = 3.2\n", " run_time_s: float = 1.2e-12\n", " extra_settle_time_s: float = 0.35e-12\n", " shutoff: float = 1e-5\n", " min_steps_per_wvl: float = 12.0\n", " num_modes: int = 4" ] }, { "cell_type": "markdown", "id": "ZC5_iA_I8qlg", "metadata": { "id": "ZC5_iA_I8qlg" }, "source": [ "These next functions help to load the field stored from the laser cavity simulations above." ] }, { "cell_type": "code", "execution_count": 29, "id": "u-xJJb_F8pbK", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.871920Z", "iopub.status.busy": "2026-06-22T18:48:40.871771Z", "iopub.status.idle": "2026-06-22T18:48:40.875134Z", "shell.execute_reply": "2026-06-22T18:48:40.874843Z" }, "id": "u-xJJb_F8pbK" }, "outputs": [], "source": [ "def inverse_taper_load_json_metadata(h5):\n", " \"\"\"Decode the JSON metadata embedded in a Tidy3D HDF5 file.\"\"\"\n", "\n", " raw = h5[\"JSON_STRING\"][()]\n", " text = raw.decode() if isinstance(raw, bytes) else str(raw)\n", " return json.loads(text)\n", "\n", "\n", "def inverse_taper_monitor_index(metadata):\n", " \"\"\"Map each simulation monitor name to its numeric HDF5 data group.\"\"\"\n", "\n", " monitors = metadata.get(\"simulation\", {}).get(\"monitors\", [])\n", " return {monitor[\"name\"]: index for index, monitor in enumerate(monitors)}\n", "\n", "\n", "def inverse_taper_read_component(h5, monitor_name, component):\n", " \"\"\"Read one complex field component and its x/y/z/f coordinates.\"\"\"\n", "\n", " names = inverse_taper_monitor_index(inverse_taper_load_json_metadata(h5))\n", " if monitor_name not in names:\n", " raise KeyError(\n", " f\"Monitor {monitor_name!r} not found. Available monitors: {sorted(names)}\"\n", " )\n", " component_path = f\"data/{names[monitor_name]}/{component}\"\n", " if component_path not in h5:\n", " raise KeyError(\n", " f\"Component {component!r} is unavailable for monitor {monitor_name!r}.\"\n", " )\n", " group = h5[component_path]\n", " values = np.asarray(group[\"__xarray_dataarray_variable__\"])\n", " x = np.asarray(group[\"x\"], dtype=float)\n", " y = np.asarray(group[\"y\"], dtype=float)\n", " z = np.asarray(group[\"z\"], dtype=float)\n", " f = np.asarray(group[\"f\"], dtype=float)\n", " return values, x, y, z, f" ] }, { "cell_type": "markdown", "id": "xnw4zHpU86TC", "metadata": { "id": "xnw4zHpU86TC" }, "source": [ "Here, we create a function that loads the data from the hdf5 file and treats the mode as a custom source that will be placed directly at the edge of the waveguide/input coupler." ] }, { "cell_type": "code", "execution_count": 30, "id": "yfoCfHzH847z", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.876331Z", "iopub.status.busy": "2026-06-22T18:48:40.876240Z", "iopub.status.idle": "2026-06-22T18:48:40.881133Z", "shell.execute_reply": "2026-06-22T18:48:40.880753Z" }, "id": "yfoCfHzH847z" }, "outputs": [], "source": [ "def inverse_taper_load_custom_source(\n", " source_hdf5,\n", " monitor_name,\n", " source_component,\n", " z_slice_um,\n", " target_wavelength_um,\n", " source_x_um,\n", "):\n", " \"\"\"Create a normalized 2D custom source from a saved laser field.\n", "\n", " The nearest saved wavelength and z slice are selected, then the complex\n", " ``source_component(y)`` profile is mapped to the 2D simulation's ``Ez``.\n", " \"\"\"\n", "\n", " source_hdf5 = Path(source_hdf5)\n", " if not source_hdf5.exists():\n", " raise FileNotFoundError(f\"Laser source HDF5 not found: {source_hdf5}\")\n", "\n", " with h5py.File(source_hdf5, \"r\") as h5:\n", " values, x, y, z, f = inverse_taper_read_component(\n", " h5, monitor_name, source_component\n", " )\n", "\n", " expected_shape = (x.size, y.size, z.size, f.size)\n", " if x.size != 1 or y.size <= 1 or z.size <= 1 or values.shape != expected_shape:\n", " raise ValueError(\n", " f\"Monitor {monitor_name!r} is not a replayable y-z field plane; \"\n", " f\"received {values.shape}, expected {expected_shape}.\"\n", " )\n", "\n", " wavelengths_um = td.C_0 / f\n", " frequency_index = int(np.argmin(np.abs(wavelengths_um - target_wavelength_um)))\n", " z_index = int(np.argmin(np.abs(z - z_slice_um)))\n", " # Index axes explicitly; np.squeeze would break for single-frequency data.\n", " lateral = np.asarray(\n", " values[0, :, z_index, frequency_index],\n", " dtype=complex,\n", " )\n", " lateral /= max(float(np.nanmax(np.abs(lateral))), 1e-30)\n", " freq0 = float(f[frequency_index])\n", " field_dataset = td.FieldDataset(\n", " Ez=td.ScalarFieldDataArray(\n", " lateral.reshape(1, y.size, 1, 1),\n", " coords={\n", " \"x\": [source_x_um],\n", " \"y\": y,\n", " \"z\": [0.0],\n", " \"f\": [freq0],\n", " },\n", " )\n", " )\n", " source_metadata = {\n", " \"source_monitor\": monitor_name,\n", " \"source_component\": source_component,\n", " \"source_x_um_original\": float(np.ravel(x)[0]),\n", " \"source_z_slice_um_requested\": float(z_slice_um),\n", " \"source_z_slice_um_selected\": float(z[z_index]),\n", " \"source_wavelength_um_requested\": float(target_wavelength_um),\n", " \"source_wavelength_um_selected\": float(wavelengths_um[frequency_index]),\n", " \"source_frequency_hz\": freq0,\n", " \"source_y_min_um\": float(y[0]),\n", " \"source_y_max_um\": float(y[-1]),\n", " \"source_profile_mapping\": (f\"{source_component}(y,z_slice) -> 2D Ez(y)\"),\n", " }\n", " return field_dataset, y, freq0, source_metadata" ] }, { "cell_type": "code", "execution_count": 31, "id": "iBtkOP2K9uET", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.882749Z", "iopub.status.busy": "2026-06-22T18:48:40.882617Z", "iopub.status.idle": "2026-06-22T18:48:40.886018Z", "shell.execute_reply": "2026-06-22T18:48:40.885802Z" }, "id": "iBtkOP2K9uET" }, "outputs": [], "source": [ "def inverse_taper_load_bus_neff(passive_hdf5, width_um, wavelength_um):\n", " \"\"\"Select the fundamental TE-like effective index nearest a target point.\"\"\"\n", "\n", " passive_hdf5 = Path(passive_hdf5)\n", " if not passive_hdf5.exists():\n", " raise FileNotFoundError(\n", " f\"Passive SiN mode-sweep HDF5 not found: {passive_hdf5}\"\n", " )\n", "\n", " with h5py.File(passive_hdf5, \"r\") as h5:\n", " widths = np.asarray(h5[\"width_um\"], dtype=float)\n", " wavelengths = np.asarray(h5[\"wavelength_um\"], dtype=float)\n", " neff = np.asarray(h5[\"n_eff_real\"], dtype=float)\n", " te_fraction = np.asarray(h5[\"te_fraction\"], dtype=float)\n", " core_fraction = np.asarray(h5[\"core_fraction\"], dtype=float)\n", " height_um = float(np.asarray(h5[\"height_um\"], dtype=float)[0])\n", "\n", " width_index = int(np.argmin(np.abs(widths - width_um)))\n", " wavelength_index = int(np.argmin(np.abs(wavelengths - wavelength_um)))\n", " mode_neff = neff[width_index, 0, wavelength_index, :]\n", " mode_te = te_fraction[width_index, 0, wavelength_index, :]\n", " # Prefer the highest-index mode with at least 50% TE polarization.\n", " te_like = np.where(mode_te >= 0.5)[0]\n", " if te_like.size:\n", " mode_index = int(te_like[np.nanargmax(mode_neff[te_like])])\n", " else:\n", " mode_index = int(np.nanargmax(mode_te))\n", "\n", " metadata = {\n", " \"source_width_um\": float(widths[width_index]),\n", " \"source_height_um\": height_um,\n", " \"source_wavelength_um\": float(wavelengths[wavelength_index]),\n", " \"mode_index\": float(mode_index),\n", " \"te_fraction\": float(mode_te[mode_index]),\n", " \"core_fraction\": float(\n", " core_fraction[width_index, 0, wavelength_index, mode_index]\n", " ),\n", " }\n", " return float(mode_neff[mode_index]), metadata" ] }, { "cell_type": "code", "execution_count": 32, "id": "yAvZ-JQF9xWh", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.887293Z", "iopub.status.busy": "2026-06-22T18:48:40.887190Z", "iopub.status.idle": "2026-06-22T18:48:40.889695Z", "shell.execute_reply": "2026-06-22T18:48:40.889483Z" }, "id": "yAvZ-JQF9xWh" }, "outputs": [], "source": [ "def inverse_taper_structure(tip_width_um, length_um, cfg):\n", " \"\"\"Create a polygonal inverse taper followed by a straight output bus.\"\"\"\n", "\n", " core = td.Medium(\n", " permittivity=cfg.core_neff**2,\n", " name=\"SiN_effective_index_core\",\n", " )\n", " x0 = 0.0\n", " x1 = length_um\n", " x2 = length_um + cfg.bus_length_um\n", " # Traverse the lower edge forward and the upper edge backward.\n", " vertices = np.asarray(\n", " [\n", " (x0, -0.5 * tip_width_um),\n", " (x1, -0.5 * cfg.bus_width_um),\n", " (x2, -0.5 * cfg.bus_width_um),\n", " (x2, 0.5 * cfg.bus_width_um),\n", " (x1, 0.5 * cfg.bus_width_um),\n", " (x0, 0.5 * tip_width_um),\n", " ]\n", " )\n", " return td.Structure(\n", " name=\"sin_2d_inverse_taper\",\n", " geometry=td.PolySlab(\n", " vertices=vertices,\n", " axis=2,\n", " slab_bounds=(-td.inf, td.inf),\n", " ),\n", " medium=core,\n", " )" ] }, { "cell_type": "markdown", "id": "2fj0uyff91Nl", "metadata": { "id": "2fj0uyff91Nl" }, "source": [ "Helper functions made to easily keep track of the cloud job batch." ] }, { "cell_type": "code", "execution_count": 33, "id": "OSNgNzoy9z2O", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.890952Z", "iopub.status.busy": "2026-06-22T18:48:40.890871Z", "iopub.status.idle": "2026-06-22T18:48:40.896245Z", "shell.execute_reply": "2026-06-22T18:48:40.895700Z" }, "id": "OSNgNzoy9z2O" }, "outputs": [], "source": [ "def inverse_taper_task_name(tip_width_um, length_um):\n", " \"\"\"Return a stable cloud task name.\"\"\"\n", "\n", " tip_nm = int(round(1000.0 * tip_width_um))\n", " length_label = int(round(length_um))\n", " return f\"{SIN_INVERSE_TAPER_TASK_PREFIX}_tip{tip_nm:03d}nm_L{length_label:03d}um\"\n", "\n", "\n", "def inverse_taper_reference_task_name():\n", " \"\"\"Return the stable task name for the source-only normalization run.\"\"\"\n", "\n", " return f\"{SIN_INVERSE_TAPER_TASK_PREFIX}_reference_incident\"\n", "\n", "\n", "def inverse_taper_make_simulation(\n", " tip_width_um,\n", " length_um,\n", " cfg,\n", " field_dataset,\n", " source_y,\n", " freq0,\n", " include_taper=True,\n", "):\n", " \"\"\"Build one 2D FDTD taper or source-reference simulation.\n", "\n", " The reference case omits the taper and output monitors. Its input flux is\n", " used to normalize transmission, reflection, and modal coupling.\n", " \"\"\"\n", "\n", " clad = td.Medium(\n", " permittivity=cfg.clad_index**2,\n", " name=\"SiO2_cladding\",\n", " )\n", " source_x = -cfg.source_gap_um\n", " bus_end_x = length_um + (cfg.bus_length_um if include_taper else 0.0)\n", " output_x = bus_end_x - 1.0\n", " input_x = -0.12\n", " sim_x_min = source_x - cfg.pml_padding_x_um\n", " sim_x_max = bus_end_x + cfg.pml_padding_x_um\n", " sim_center_x = 0.5 * (sim_x_min + sim_x_max)\n", " monitor_size = (0.0, cfg.monitor_y_span_um, td.inf)\n", " source_size = (0.0, float(source_y[-1] - source_y[0]), td.inf)\n", " fwidth = freq0 / 30.0\n", " freqs = (freq0,)\n", "\n", " # Replay the saved complex laser field at the taper entrance.\n", " source = td.CustomFieldSource(\n", " name=\"sim_data_output_field_replay_source\",\n", " center=(source_x, 0.0, 0.0),\n", " size=source_size,\n", " source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n", " field_dataset=field_dataset,\n", " )\n", " mode_spec = td.ModeSpec(\n", " num_modes=cfg.num_modes,\n", " target_neff=cfg.core_neff,\n", " precision=\"double\",\n", " sort_spec=td.ModeSortSpec(\n", " sort_key=\"n_eff\",\n", " sort_order=\"descending\",\n", " track_freq=\"central\",\n", " ),\n", " )\n", "\n", " # Input monitors are shared by taper and reference simulations.\n", " monitors = (\n", " td.FluxMonitor(\n", " name=\"input_net_flux\",\n", " center=(input_x, 0.0, 0.0),\n", " size=monitor_size,\n", " freqs=freqs,\n", " normal_dir=\"+\",\n", " ),\n", " td.FluxMonitor(\n", " name=\"raw_backward_flux\",\n", " center=(input_x, 0.0, 0.0),\n", " size=monitor_size,\n", " freqs=freqs,\n", " normal_dir=\"-\",\n", " ),\n", " )\n", " if include_taper:\n", " monitors += (\n", " td.FluxMonitor(\n", " name=\"transmitted_flux\",\n", " center=(output_x, 0.0, 0.0),\n", " size=monitor_size,\n", " freqs=freqs,\n", " normal_dir=\"+\",\n", " ),\n", " td.ModeMonitor(\n", " name=\"bus_modes\",\n", " center=(output_x, 0.0, 0.0),\n", " size=monitor_size,\n", " freqs=freqs,\n", " mode_spec=mode_spec,\n", " store_fields_direction=\"+\",\n", " ),\n", " )\n", "\n", " # Extend runtime for pulse delay, propagation, and post-arrival settling.\n", " propagation_um = output_x - source_x\n", " source_delay_s = 5.0 / fwidth\n", " flight_time_s = propagation_um * cfg.core_neff / td.C_0\n", " run_time_s = max(\n", " cfg.run_time_s,\n", " source_delay_s + flight_time_s + cfg.extra_settle_time_s,\n", " )\n", " structures = (\n", " (inverse_taper_structure(tip_width_um, length_um, cfg),)\n", " if include_taper\n", " else ()\n", " )\n", "\n", " return td.Simulation(\n", " center=(sim_center_x, 0.0, 0.0),\n", " size=(sim_x_max - sim_x_min, cfg.sim_y_span_um, 0.0),\n", " medium=clad,\n", " structures=structures,\n", " sources=(source,),\n", " monitors=monitors,\n", " grid_spec=td.GridSpec.auto(\n", " wavelength=cfg.wavelength_um,\n", " min_steps_per_wvl=cfg.min_steps_per_wvl,\n", " ),\n", " boundary_spec=td.BoundarySpec(\n", " x=td.Boundary.pml(),\n", " y=td.Boundary.pml(),\n", " z=td.Boundary.periodic(),\n", " ),\n", " run_time=run_time_s,\n", " shutoff=cfg.shutoff,\n", " )" ] }, { "cell_type": "code", "execution_count": 34, "id": "eQRbmSzd-c7s", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.897804Z", "iopub.status.busy": "2026-06-22T18:48:40.897505Z", "iopub.status.idle": "2026-06-22T18:48:40.903367Z", "shell.execute_reply": "2026-06-22T18:48:40.902698Z" }, "id": "eQRbmSzd-c7s" }, "outputs": [], "source": [ "def inverse_taper_sweep_values(start, stop, step):\n", " \"\"\"Return an inclusive floating-point sweep without dropping ``stop``.\"\"\"\n", "\n", " return np.arange(start, stop + 0.5 * step, step)\n", "\n", "\n", "def inverse_taper_build_sweep(cfg, source_hdf5):\n", " \"\"\"Build the normalization run and every tip-width/length simulation.\"\"\"\n", "\n", " field_dataset, source_y, freq0, source_metadata = inverse_taper_load_custom_source(\n", " source_hdf5=source_hdf5,\n", " monitor_name=\"field_yz_output\",\n", " source_component=\"Ey\",\n", " z_slice_um=cfg.source_z_slice_um,\n", " target_wavelength_um=cfg.wavelength_um,\n", " source_x_um=-cfg.source_gap_um,\n", " )\n", " simulations = {}\n", " rows = {}\n", "\n", " # The source-only run supplies the incident-flux normalization.\n", " reference_sim = inverse_taper_make_simulation(\n", " tip_width_um=cfg.bus_width_um,\n", " length_um=cfg.bus_length_um,\n", " cfg=cfg,\n", " field_dataset=field_dataset,\n", " source_y=source_y,\n", " freq0=freq0,\n", " include_taper=False,\n", " )\n", " reference_name = inverse_taper_reference_task_name()\n", " simulations[reference_name] = reference_sim\n", " rows[reference_name] = {\n", " \"tip_width_um\": float(\"nan\"),\n", " \"length_um\": float(\"nan\"),\n", " \"num_cells\": float(reference_sim.num_cells),\n", " \"run_time_s\": float(reference_sim.run_time),\n", " \"is_reference\": 1.0,\n", " }\n", "\n", " tip_widths = inverse_taper_sweep_values(\n", " cfg.tip_width_min_um,\n", " cfg.tip_width_max_um,\n", " cfg.tip_width_step_um,\n", " )\n", " lengths = inverse_taper_sweep_values(\n", " cfg.length_min_um,\n", " cfg.length_max_um,\n", " cfg.length_step_um,\n", " )\n", " # Generate the Cartesian product of taper-tip widths and lengths.\n", " for tip_width_um in tip_widths:\n", " for length_um in lengths:\n", " task_name = inverse_taper_task_name(\n", " float(tip_width_um),\n", " float(length_um),\n", " )\n", " sim = inverse_taper_make_simulation(\n", " tip_width_um=float(tip_width_um),\n", " length_um=float(length_um),\n", " cfg=cfg,\n", " field_dataset=field_dataset,\n", " source_y=source_y,\n", " freq0=freq0,\n", " )\n", " simulations[task_name] = sim\n", " rows[task_name] = {\n", " \"tip_width_um\": float(tip_width_um),\n", " \"length_um\": float(length_um),\n", " \"num_cells\": float(sim.num_cells),\n", " \"run_time_s\": float(sim.run_time),\n", " \"is_reference\": 0.0,\n", " }\n", " return simulations, rows, freq0, source_metadata" ] }, { "cell_type": "code", "execution_count": 35, "id": "FOa-JSb_-hhH", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.905110Z", "iopub.status.busy": "2026-06-22T18:48:40.904865Z", "iopub.status.idle": "2026-06-22T18:48:40.907606Z", "shell.execute_reply": "2026-06-22T18:48:40.907387Z" }, "id": "FOa-JSb_-hhH" }, "outputs": [], "source": [ "def inverse_taper_write_manifest(\n", " path,\n", " cfg,\n", " rows,\n", " source_metadata,\n", " core_neff_metadata,\n", "):\n", " \"\"\"Write the sweep manifest used by the embedded result reader.\"\"\"\n", "\n", " manifest = {\n", " \"description\": (\n", " \"2D effective-index inverse-taper sweep using sim_data.hdf5 \"\n", " \"as a CustomFieldSource\"\n", " ),\n", " \"source_hdf5\": str(SIN_INVERSE_TAPER_SOURCE_HDF5),\n", " \"source_metadata\": source_metadata,\n", " \"config\": asdict(cfg),\n", " \"core_neff_metadata\": core_neff_metadata,\n", " \"tasks\": rows,\n", " \"metrics_to_read\": [\n", " \"bus_modes forward mode powers / reference incident flux\",\n", " \"transmitted_flux / reference incident flux\",\n", " \"raw_backward_flux / reference incident flux\",\n", " ],\n", " \"caveat\": (\n", " \"This is a 2D effective-index ranking sweep. Validate selected \"\n", " \"candidates with a final 3D FDTD simulation.\"\n", " ),\n", " \"tidy3d_version\": td.__version__,\n", " }\n", " path.write_text(json.dumps(manifest, indent=2) + \"\\n\", encoding=\"utf-8\")" ] }, { "cell_type": "code", "execution_count": 36, "id": "7OS1yw5j-k3t", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.908585Z", "iopub.status.busy": "2026-06-22T18:48:40.908477Z", "iopub.status.idle": "2026-06-22T18:48:40.911226Z", "shell.execute_reply": "2026-06-22T18:48:40.910880Z" }, "id": "7OS1yw5j-k3t" }, "outputs": [], "source": [ "def inverse_taper_write_grid_hdf5(path, rows, cfg, source_metadata):\n", " \"\"\"Write compact sweep-grid metadata.\"\"\"\n", "\n", " names = list(rows)\n", " string_dtype = h5py.string_dtype(encoding=\"utf-8\")\n", " with h5py.File(path, \"w\") as h5:\n", " h5.attrs[\"description\"] = (\n", " \"2D FDTD inverse-taper design grid using a custom laser source\"\n", " )\n", " for key, value in asdict(cfg).items():\n", " h5.attrs[key] = value\n", " for key, value in source_metadata.items():\n", " h5.attrs[f\"source_{key}\"] = value\n", " h5.create_dataset(\n", " \"task_name\",\n", " data=np.asarray(names, dtype=object),\n", " dtype=string_dtype,\n", " )\n", " for field in (\n", " \"tip_width_um\",\n", " \"length_um\",\n", " \"num_cells\",\n", " \"run_time_s\",\n", " \"is_reference\",\n", " ):\n", " h5.create_dataset(\n", " field,\n", " data=np.asarray([rows[name][field] for name in names]),\n", " )" ] }, { "cell_type": "code", "execution_count": 37, "id": "yPvh4kg1-neC", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.912084Z", "iopub.status.busy": "2026-06-22T18:48:40.911993Z", "iopub.status.idle": "2026-06-22T18:48:40.914304Z", "shell.execute_reply": "2026-06-22T18:48:40.914002Z" }, "id": "yPvh4kg1-neC" }, "outputs": [], "source": [ "def inverse_taper_save_preview(path, sim):\n", " \"\"\"Save a representative 2D geometry preview.\"\"\"\n", "\n", " fig, ax = plt.subplots(figsize=(10.0, 3.8), constrained_layout=True)\n", " sim.plot_eps(z=0.0, ax=ax)\n", " ax.set_title(\"Representative 2D inverse taper\")\n", " fig.savefig(path, dpi=200)\n", " plt.show()" ] }, { "cell_type": "code", "execution_count": 38, "id": "774Hff6R-r-M", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.915347Z", "iopub.status.busy": "2026-06-22T18:48:40.915253Z", "iopub.status.idle": "2026-06-22T18:48:40.918999Z", "shell.execute_reply": "2026-06-22T18:48:40.918709Z" }, "id": "774Hff6R-r-M" }, "outputs": [], "source": [ "def inverse_taper_prepare_batch():\n", " \"\"\"Validate inputs, build simulations/artifacts, and return a cloud batch.\"\"\"\n", "\n", " if not SIN_INVERSE_TAPER_SOURCE_HDF5.exists():\n", " raise FileNotFoundError(\n", " f\"Laser source data not found: {SIN_INVERSE_TAPER_SOURCE_HDF5}\"\n", " )\n", " if not SIN_INVERSE_TAPER_PASSIVE_NEFF_HDF5.exists():\n", " raise FileNotFoundError(\n", " \"Passive SiN mode-sweep data not found: \"\n", " f\"{SIN_INVERSE_TAPER_PASSIVE_NEFF_HDF5}\"\n", " )\n", " core_neff, core_neff_metadata = inverse_taper_load_bus_neff(\n", " SIN_INVERSE_TAPER_PASSIVE_NEFF_HDF5,\n", " width_um=InverseTaperSweepConfig.bus_width_um,\n", " wavelength_um=InverseTaperSweepConfig.wavelength_um,\n", " )\n", " cfg = InverseTaperSweepConfig(core_neff=core_neff)\n", " simulations, rows, freq0, source_metadata = inverse_taper_build_sweep(\n", " cfg,\n", " SIN_INVERSE_TAPER_SOURCE_HDF5,\n", " )\n", "\n", " SIN_INVERSE_TAPER_SWEEP_DIR.mkdir(parents=True, exist_ok=True)\n", " manifest_path = (\n", " SIN_INVERSE_TAPER_SWEEP_DIR\n", " / \"sin_inverse_taper_2d_sweep_from_sim_data_manifest.json\"\n", " )\n", " grid_hdf5 = (\n", " SIN_INVERSE_TAPER_SWEEP_DIR\n", " / \"sin_inverse_taper_2d_sweep_from_sim_data_grid.hdf5\"\n", " )\n", " batch_hdf5 = (\n", " SIN_INVERSE_TAPER_SWEEP_DIR\n", " / \"sin_inverse_taper_2d_sweep_from_sim_data_batch.hdf5\"\n", " )\n", " inverse_taper_write_manifest(\n", " manifest_path,\n", " cfg,\n", " rows,\n", " source_metadata,\n", " core_neff_metadata,\n", " )\n", " inverse_taper_write_grid_hdf5(grid_hdf5, rows, cfg, source_metadata)\n", "\n", " batch = web.Batch(\n", " simulations=simulations,\n", " folder_name=\"default\",\n", " num_workers=10,\n", " verbose=True,\n", " )\n", " batch.to_file(str(batch_hdf5))\n", "\n", " first_taper_name = next(\n", " name for name, row in rows.items() if row[\"is_reference\"] == 0.0\n", " )\n", " inverse_taper_save_preview(\n", " SIN_INVERSE_TAPER_SWEEP_DIR\n", " / \"sin_inverse_taper_2d_sweep_from_sim_data_preview.png\",\n", " simulations[first_taper_name],\n", " )\n", "\n", " cell_counts = [sim.num_cells for sim in simulations.values()]\n", " print(f\"Built {len(simulations)} 2D FDTD simulations\")\n", " print(f\"Source HDF5: {SIN_INVERSE_TAPER_SOURCE_HDF5}\")\n", " print(\"Source monitor/component: field_yz_output/Ey\")\n", " print(\n", " \"Selected source slice: \"\n", " f\"{1000.0 * source_metadata['source_wavelength_um_selected']:.3f} nm, \"\n", " f\"z={source_metadata['source_z_slice_um_selected']:+.4f} um\"\n", " )\n", " print(f\"Manifest: {manifest_path}\")\n", " print(f\"Sweep grid HDF5: {grid_hdf5}\")\n", " print(f\"Batch HDF5: {batch_hdf5}\")\n", " print(f\"2D effective core index: {cfg.core_neff:.6f}\")\n", " print(f\"Source frequency: {freq0:.6e} Hz\")\n", " print(f\"Cell count range: {min(cell_counts):,} - {max(cell_counts):,}\")\n", " print(f\"Total cells across sweep: {sum(cell_counts):,}\", flush=True)\n", " return batch" ] }, { "cell_type": "markdown", "id": "5pLkQewx_AaE", "metadata": { "id": "5pLkQewx_AaE" }, "source": [ "#### Running the Sweep\n", "\n", "The sweep is built and submitted to the cloud only if its results are not already present on disk; otherwise the existing results are loaded. The next cell runs the analysis once the results are available." ] }, { "cell_type": "code", "execution_count": 39, "id": "E6-cUD5z_KAZ", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:40.920309Z", "iopub.status.busy": "2026-06-22T18:48:40.920061Z", "iopub.status.idle": "2026-06-22T18:48:43.597890Z", "shell.execute_reply": "2026-06-22T18:48:43.597501Z" }, "id": "E6-cUD5z_KAZ" }, "outputs": [ { "data": { "image/png": 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32MDAQOTl5dl0LqVSiWHDhmHYsGEwmUz4+9//ji+++AJz5sxBq1at7KrLVuWNovjpp5/g5OSE7du3W41cWbFihc11lMXV1RVDhw7FunXr8OGHH2LNmjXo1auXVWIhMDAQQggEBASUSsjYqrCwEMOGDcPFixfx22+/Vep1AaPRiFWrVsHFxcW8WkdNGTNmDP7+978jKSkJa9asgYuLC4YNG2beXzIJqkajqXL8AwMDMXPmTMycOROXLl1Cp06d8O9//xvff/+9+Tw+Pj6VOk95fSEhIQEZGRnYsGEDevfubd5+5cqVMsv/9ddfpZZ3vXjxIgCYJ9oMDAzEyZMn0b9//yqNBiIiInJUnPOCiOgh0rdvX3Tr1g0ff/wxCgsL4ePjg759++KLL75ASkpKqfK3b98ute3LL7+EXq83f1++fDkMBgMGDRp03/OPHj0aiYmJ2L59e6l92dnZMBgMAICMjAyrfVKpFCEhIQBgfmXD1rrsUfLjMDs722q7TCaDRCKxWsby6tWrpVZwKKnj3uMrMmbMGPz111/4+uuvcfLkSYwZM8Zq/xNPPAGZTIb58+eXGiUihCh1r+5lNBoxZswYJCYmYt26dQgPD7e5bXfX8fLLL+P8+fN4+eWXq/S6hC1GjhwJmUyGH3/8EevWrcPQoUOtfriHhoYiMDAQixcvNr/Kcrey+u29CgoKUFhYaLUtMDAQbm5u5j4WFRUFjUaD9957z6rP23qeivoTYD3iRKfTYdmyZWXWYzAYzEsNl5T94osv0LBhQ4SGhgIo/vtw8+ZNfPXVV6WOv3PnDvLz8ytsKxERkaPjyAsioofMP/7xD4waNQpxcXF44YUXsHTpUvTs2RPBwcGYMmUKWrZsibS0NCQmJuLPP//EyZMnrY7X6XTo378/Ro8ejaSkJCxbtgw9e/bE8OHDbTr3li1bMHToUERHRyM0NBT5+fk4ffo01q9fj6tXr8Lb2xvPPfccMjMz0a9fPzRp0gTXrl3DZ599hk6dOpmXmrS1LnuU/BB8+eWXERUVBZlMhrFjx2LIkCH48MMPMXDgQDz11FO4desWli5dilatWuHUqVOl6vjtt9/w4Ycfwt/fHwEBAQgLCyv3nIMHD4abmxtee+01yGQyjBw50mp/YGAg3nnnHcyePRtXr17FiBEj4ObmhitXrmDjxo14/vnn8dprr5Vb/8yZM7FlyxYMGzYMmZmZ+P777632T5gwweq7Vqs1lykoKMDly5exYcMGJCcnY+zYsViwYMH9b2QV+fj44LHHHsOHH36I3NzcUgkdqVSKr7/+GoMGDUKHDh3w9NNPo3Hjxrh58yZ27doFjUaD//73vxWe4+LFi+Z+3L59e8jlcmzcuBFpaWkYO3YsgOKRHcuXL8fEiRPx6KOPYuzYsWjYsCGuX7+O//3vf+jRoweWLFlS7jk6deoEmUyGhQsXQqvVQqVSoV+/foiIiICnpycmT56Ml19+GRKJBCtXriz3FSZ/f38sXLgQV69eRevWrbFmzRqcOHECX375pXnOk4kTJ2Lt2rV44YUXsGvXLvTo0QNGoxEXLlzA2rVrsX37dvMrZERERPVSHa1yQkRENahkWc7Dhw+X2mc0GkVgYKAIDAw0L0WanJwsJk2aJPz8/IRCoRCNGzcWQ4cOFevXry9V5+7du8Xzzz8vPD09hVqtFuPHjxcZGRlW52jevLkYMmRImW3Lzc0Vs2fPFq1atRJKpVJ4e3uLiIgIsXjxYvOyj+vXrxcDBgwQPj4+QqlUimbNmompU6eKlJQUu+sqWaazrCUxAYi5c+eavxsMBvHSSy+Jhg0bColEYrVs6jfffCOCgoKESqUSbdu2FStWrDAvw3m3CxcuiN69ewtnZ2cBwLxs6r1Lpd5t/PjxAoCIjIws854JIcRPP/0kevbsKVxdXYWrq6to27atiImJEUlJSeUeI4Rlqc3yPhWVVavVIigoSEyYMEH8+uuvFZ7nbuUtlWpLDEp89dVXAoBwc3MTd+7cKfM8x48fF0888YTw8vISKpVKNG/eXIwePVrs2LHDXKYkRrdv37Y6Nj09XcTExIi2bdsKV1dX4e7uLsLCwsTatWtLnWfXrl0iKipKuLu7CycnJxEYGCiio6PFkSNH7nsvvvrqK9GyZUshk8mslk3dv3+/6N69u3B2dhb+/v5i1qxZYvv27aWWVi1ZvvbIkSMiPDxcODk5iebNm4slS5aUOpdOpxMLFy4UHTp0ECqVSnh6eorQ0FAxf/58odVqzeUAiJiYmPu2nYiIyJFIhLBhpjIiInroxcXF4emnn8bhw4f5X3CJaknfvn2Rnp5uniyViIjoYcU5L4iIiIiIiIjIoTF5QUREREREREQOjckLIiIiIiIiInJoDpW8iI2NRdeuXeHm5gYfHx+MGDECSUlJFR4TFxcHiURi9XFycrIqI4TAW2+9hUaNGsHZ2RmRkZG4dOlSTV4KEdEDJzo6GkIIzndBVIsSEhI43wUREREcLHmxe/duxMTE4MCBA4iPj4der8eAAQPuuza5RqNBSkqK+XPt2jWr/YsWLcKnn36Kzz//HAcPHoSrqyuioqJKre9ORERERERERI7HoVcbuX37Nnx8fLB792707t27zDJxcXGYPn06srOzy9wvhIC/vz9mzpyJ1157DUDxGva+vr6Ii4szr+VORERERERERI5JXtcNqIhWqwUANGjQoMJyeXl5aN68OUwmEx599FG899576NChAwDgypUrSE1NRWRkpLm8u7s7wsLCkJiYWG7yoqioCEVFRebvJpMJmZmZ8PLygkQiqeqlERERERERkY2EEMjNzYW/vz+kUvtfICgsLIROp6uBltUMpVJZajqEh53DJi9MJhOmT5+OHj16oGPHjuWWa9OmDb799luEhIRAq9Vi8eLFiIiIwNmzZ9GkSROkpqYCAHx9fa2O8/X1Ne8rS2xsLObPn2+1bdasWZDLy75lQghkZWWhsgNZlEql+S+hyWSqk79Ycrnc6vqKiooqfT2VJZFIoFKpzN8NBgMMBkOttgFgPEowHhaMhwXjUYzxsGA8LBiPYoyHBeNhwXgUYzws7o2HXq+Hu7t7uf+x+L333sONGzfQpEkTu85TWFgIZ2fnKrW1tvn5+eHKlStMYNzFYZMXMTExOHPmDPbt21dhufDwcISHh5u/R0REoF27dvjiiy+wYMGCSp9/9uzZmDFjhvm7VqvF559/DhcXlzIzfUIItGjRAjKZrFLn0+l05pEm7u7uUCqVlWt4FZhMJmRkZAAofpi5u7vXehuA4ntd8vD08vKqVGa1qhgPC8ajGONhwXhYMB7FGA8LxsOC8SjGeFgwHhaMR7F746FWq5Genl5m8sJkMgEA3Nzc7D5Pyb2u7G+1upCamgqdTsfkxV0cMnkxbdo0/Pzzz9izZ4/dWTWFQoHOnTvj8uXLAIozVgCQlpaGRo0amculpaWhU6dO5dajUqmsMqIlpFIpFAqF1TaTyQSTyQSVSlWpv/QFhQXIzMuERFn8lzQzLxN+3n5wcXKxu67KKnlwKBQKqFQqFBYWwmg0VurhUBW5ubkwmUxQq9UoKirCnTt3av2BrtPpkJ2dbc7OFhQUwMXFpVYf6IyHBeNhwXgUYzwsGA8LxqMY42HBeFgwHsUYDwtHjYfBYIBUKjV/7qbX6wGgSq/wy+XyejEFgBACRqOxrpvhcBxqtREhBKZNm4aNGzdi586dCAgIsLsOo9GI06dPmxMVAQEB8PPzw44dO8xlcnJycPDgQasRG3VFp9MhKzMLErkEKk8VVJ4qSOQSZGVm1drQrZIHh16vh7e3N7y8vKDRaJCTk4Pc3NxaaQNQ/CDPycmBRqOBl5cXvL29odfrkZGRYc601jSdTof09HQoFAp4e3vD29sbCoUC6enpjAfjwXgwHmaMRzHGw4LxsGA8ijEeFoyHBeNRrLx45OXl1egrNCWvqdSHj61iY2PRtWtXuLm5wcfHByNGjEBSUlKFx/Tt2xcSiaTUZ8iQIeYy0dHRpfYPHDiw0ve+OjhU8iImJgbff/89Vq1aBTc3N6SmpiI1NRV37twxl5k0aRJmz55t/v7222/j119/xR9//IFjx45hwoQJuHbtGp577jkAxZm56dOn45133sGWLVtw+vRpTJo0Cf7+/hgxYkRtX6KVkgeHXC6HykMFiVQCiVQClYcKcrm8Vh4g9z44SrKtbm5utfpAv/tBXpL9ViqVtfpAv/tBXpL9lkql8PLyqrUHOuNhwXhYMB7FGA8LxsOC8SjGeFgwHhaMRzHGw8LR46FWq2t0/g2ZTFZvPrbavXs3YmJicODAAcTHx0Ov12PAgAHIz88v95gNGzYgJSXF/Dlz5gxkMhlGjRplVW7gwIFW5X788cdK3/vq4FCvjSxfvhxAcSbobitWrEB0dDQA4Pr161ZDiLKysjBlyhSkpqbC09MToaGh+P3339G+fXtzmVmzZiE/Px/PP/88srOz0bNnT2zbtq1O3x+6+8Gh8dQg05Rp3ieRSuDRwAM5WTlIT0+3+ktdncp7cJQoeajm5ORYfa9uZT3IS5Q80NPT05GRkVFjQ+rKepCXKHmgZ2RkMB6MhxnjUYzxsGA8LBiPYoyHBeNhwXgUYzwsGA8LV1dXZGZmwmg0oqioqMzX+KtCJpPVyfwi9rInibVt2zar73FxcfDx8cHRo0fRu3fvMo+5dzXP1atXw8XFpVTyQqVSmadhcAQSUdvT69ZTOTk5WLhwIVxdXUsN4zGZTBBCoGHDhqXmwyiLXq9HVlYW5HI5PD09YYQRWYYsqzKeck/IIENWVhYMBgM8PT1tqttWJauj2FJ3fn4+8vLyoFar4erqWm1tsKfue+9Zdb6rZmvd9twzezEe9tfNeFgwHhaMRzHGw4LxsGA8ijEeFoyHBeNRrK7jodfrcfv2bRgMBphMJshkMnOCw2Aw4J///Ce0Wi00Go1d587JyYG7uzu8vb3rTfIiPT0dN27csLrW8uZlvNvly5cRFBSE06dPV7hq592Cg4MRHh6OL7/80rwtOjoamzZtglKphKenJ/r164d33nkHXl5elbuoasDkhY1ycnLw/vvvQ61Wl+rwJckLDw+P+76fVDIMSiKRQKlUQiKRwCiMyDVaD1Vzk7lBJpFBCAGdTgchhNVyRlVRmToNBgP0ej0UCoVd72BVZ51l3buqsrdOxsOC8bBgPIoxHhaMhwXjUYzxsGA8LBiPYoyHxcMeD4PBgOzsbEgkEvOiCFKpFHK5HCaTqcrJCz8/v3qTvEhNTS21fe7cuZg3b16Fxw0fPhzZ2dn3XbWzxKFDhxAWFoaDBw+iW7du5u0lozECAgKQnJyMN998E2q1GomJiXW2aotDvTbi6LKzs9G8efNSr5vo9XoUFRVh8ODBlVpuKc+Yh/05+6229dD0gFqmrlJ7iYiIiIiI6gutVotffvkFKpUKCoXCatRKdfxgri+vjZQkmMoaeVGRmJgYnDlzxubEBQB88803CA4OtkpcAMDYsWPNfw4ODkZISAgCAwORkJCA/v3721x/dWLywg5yuRxSqbTM97+MRiPc3d1LvT9kU70GOVQS647o4eEBjdy+jCIREREREVF9JpfLoVAooFQqoVQqIZfLkZOTUy3zX5T8nnN0JXNeaDQam0eZTJs2DT///DP27NmDJk2a2HRMfn4+Vq9ejbfffvu+ZVu2bAlvb29cvnyZyYv6QCqVIicnBy4uLvWi0xMREREREdVnJROcZmZm3qfk/dW3kRe2EELgpZdewsaNG5GQkICAgACbj123bh2KioowYcKE+5b9888/kZGRgUaNGtlcf3Vj8sIORUVFMBqNNToLMBEREREREVm4ubmhqKioyvXYuwxpXTEajTaXjYmJwapVq7B582a4ubmZ58pwd3eHs7MzAGDSpElo3LgxYmNjrY795ptvMGLEiFKTcObl5WH+/PkYOXIk/Pz8kJycjFmzZqFVq1aIioqq4tVVHpMXdhBCwN3dHXl5eUxgEBERERER1RIXF5cq11Ffkhf2WL58OQCgb9++VttXrFiB6OhoAMD169dL/W5NSkrCvn378Ouvv5aqUyaT4dSpU/juu++QnZ0Nf39/DBgwAAsWLKj25WvtweSFneRyeal1mKubS0EanC5MAaR3LR8UsgBQ2z4EiIiIiIiIyCZ5V4BTc6y3PYC/P+Ryeb1IXtj72sj9JCQklNrWpk2bco91dnbG9u3bbW5DbWHyohKUSqVVAsPepXqIiIiIiIiodj2IIy8eJkxeVNLdCYysrCzz+0RERERERETkeB7EkRcPE7uTF1euXMHevXtx7do1FBQUoGHDhujcuTPCw8Ph5ORUE210WCUJjFu3bkGn09V1c4iIiIiIiKgcUqm0XiQvbHkV5GFkc/Lihx9+wCeffIIjR47A19cX/v7+cHZ2RmZmJpKTk+Hk5ITx48fj9ddfR/PmzWuyzQ5FqVTC09MTeXl5dd0UIiIiIiIiKodcLodczpcP6iubIte5c2colUpER0fjp59+QtOmTa32FxUVITExEatXr0aXLl2wbNkyjBo1qkYaTERERERERGSv+jLnBUdelM2m5MX7779f4XquKpUKffv2Rd++ffHuu+/i6tWr1dU+h6fT6ZCVlVWnS8YQERERERFRxTjyon6zKXIVJS7u5eXlVSPLhzoinU6H9PR0yOVyKJXKum4OERERERERlYMjL+q3Sqedbt26hVu3bsFkMlltDwkJqXKj6oOSxIVCoYBGo0FRUVFdN4mIiIiIiIjKIZPJ6sXICyYvymZ35I4ePYrJkyfj/Pnz5psqkUgghIBEIoHRaKz2RjqauxMXXl5eMBgMdd0kIiIiIiIiqkB9GXlx7wABKmZ38uKZZ55B69at8c0338DX1/ehW4PWYDAgOzvbnLiQSqV13SQiIiIiIiK6j/oy5wVHXpTN7sj98ccf+Omnn9CqVauaaI9Dk0gk0Gq1cHJyYuKCiIiIiIiolhQUFFS5DiYv6je7I9e/f3+cPHnyoUxeqFQqyGQyJi6IiIiIiIhqSW5uLvLz86tcD18bqd/sTl58/fXXmDx5Ms6cOYOOHTtCoVBY7R8+fHi1Nc7RmEwmaDQaJi6IiIiIiIhqQW5uLnJycuDq6lrluurLhJ1MXpTN7sglJiZi//792Lp1a6l9D/qEnTqdjokLIiIiIiKiWlCSuNBoNNUyYqK+jLywp42xsbHYsGEDLly4AGdnZ0RERGDhwoVo06ZNucfExcXh6aefttqmUqlQWFho/i6EwNy5c/HVV18hOzsbPXr0wPLlyxEUFGT/BVUTu3+Jv/TSS5gwYQJSUlJgMpmsPg9y4oKIiIiIiIhqx92JCzc3t2qps2TOi/rwsdXu3bsRExODAwcOID4+Hnq9HgMGDLjvazYajQYpKSnmz7Vr16z2L1q0CJ9++ik+//xzHDx4EK6uroiKirJKcNQ2u0deZGRk4NVXX4Wvr29NtIeIiIiIiIiqSBj0wB+nAGc3SJq2rplzpF0DMlOBwEcgUTpVW735+fkoKCio1sQF8GCOvNi2bZvV97i4OPj4+ODo0aPo3bt3ucdJJBL4+fmVuU8IgY8//hj/+te/8PjjjwMA/vOf/8DX1xebNm3C2LFjbW5fdbI7efHEE09g165dCAwMrIn2EBERERERUSUJbTrE2d8hTu0Bsm8DAR0hG/OPmjnX8Z0QJ3YBak9IgntB0rEHJF6NqlSnwWBAfn4+PDw8qjVxAdSf1UaqMueFVqsFADRo0KDCcnl5eWjevDlMJhMeffRRvPfee+jQoQMA4MqVK0hNTUVkZKS5vLu7O8LCwpCYmFh/khetW7fG7NmzsW/fPgQHB5easPPll1+utsYRERERERFRxYTJCFw9B9OpPUDySUB3B5DKAZMRqMllN4UAjAagIBfi980Qh7cBzdtDGtK7eDSGXHH/Ou6h1+uhVqurPXEBAFKptF6MvCiZZzEnJ8dqu0qlgkqlKvc4k8mE6dOno0ePHujYsWO55dq0aYNvv/0WISEh0Gq1WLx4MSIiInD27Fk0adIEqampAFDqbQtfX1/zvrpQqdVG1Go1du/ejd27d1vtk0gk1ZK8WLp0KT744AOkpqbikUcewWeffYZu3bqVW37dunWYM2cOrl69iqCgICxcuBCDBw8273fEyUaIiIiIiOoTIQRMJhOEEKU+5W2v7L6aOuZBIy/Kh2fqRXj9dRaq/CxIhAkmmQJGuQqQSKAwFCI3/Tau7EmouB7TLTTV3rbaduPIYRik18o5oliTm3+igcEIvUIGhUoFJUzA5RMwJZ8EPBpCEtIbkg49IHH3svmaFApFtawsUpb6MvKiZC7Jpk2bWm2fO3cu5s2bV+5xMTExOHPmDPbt21dh/eHh4QgPDzd/j4iIQLt27fDFF19gwYIFlW/4PUwmE+Li4vDMM89US312R+7KlSvVcuLyrFmzBjNmzMDnn3+OsLAwfPzxx4iKikJSUhJ8fHxKlf/9998xbtw4xMbGYujQoVi1ahVGjBiBY8eOmbNNJZONfPfddwgICMCcOXMQFRWFc+fOwcmp+t7NIiIioppX3o+TuvoxVFfHOEIbeK0Pz7WS45AA6OrvgZFtG2FokC+cVHLkCoFrd/QoMlq/buDnqoIuNQ0eZ49WWOdf+fnY7nrIaptz+i0Ee3tWeFweAChl+DP3L/j6+Bb/2Fa5AAY9oE2H2L0OIvFnoFUnSEN6Ac3bQyKteORDTSYX6tucFzdu3IBGozFvr2jUxbRp0/Dzzz9jz549aNKkiV3nUygU6Ny5My5fvgwA5rkw0tLS0KiR5TWgtLQ0dOrUyeZ6pVIpvvjii7pLXpQnJSUFK1euxKxZs6pUz4cffogpU6aYl275/PPP8b///Q/ffvst3njjjVLlP/nkEwwcOBD/+Efxe1wLFixAfHw8lixZgs8//xxCOOZkI0T0YCjvH4SO+o/Ph+kf2rxWx2pDdR5DRPQw0qjkGNrKF2M7+KNjQzcoZVLk641IySuEqZxH4+0CHVwUFf9YVytl8HFxwp/3bG/oooJaKYO2yFDh8an5RaU3yhWA2hMQJqDoDnDuAEwXDgNejSB5pA8k7btD4upeYb01ob6NvNBoNFbJi7IIIfDSSy9h48aNSEhIQEBAQKXOd/r0afPbCwEBAfDz88OOHTvMyYqcnBwcPHgQL774ol11d+nSBUuWLMG0adPsbte97I5ceVmTa9eu4dChQ1VKXuh0Ohw9ehSzZ882b5NKpYiMjERiYmKZxyQmJmLGjBlW26KiorBp0yYAlZ9spKioCEVFlr+I975v5Ijq2z8+Hb0NvFZeqy3HEBEREdWkVp6uGN+xMf7Wxg9ezkoIAFmFetwx6O57rFEI5OoqTj7IpZJy9xUZTfc9vkISKeDkWvzR64D0mxC//QCxbyPQpiukj/aDxM/+H9uVVd9GXtgiJiYGq1atwubNm+Hm5maek8Ld3R3Ozs4AgEmTJqFx48aIjY0FALz99tvo3r07WrVqhezsbHzwwQe4du0annvuOQDF00FMnz4d77zzDoKCgsxvL/j7+2PEiBF2Xcuff/6JrVu3mufVCA4ORnBwMIYOHWpXPUAlkhdZWVlW341GI/744w+cP38ey5Yts7sBd0tPT4fRaCxzYpALFy6UeUxqamqFE4lUdrKR2NhYzJ8/32rb1KlTbbuQGjBz5kycTM6B0WiEyWSy+hiNRvP2+vLDj4iIiIiI7u/1iEBEBjSEh0qBv/IKq5ZMqEsKJaBoAOgKgZwM4NRumNL/hGzSXKtiVVlp435kMlm9GHlhMNge4+XLlwMA+vbta7V9xYoViI6OBgBcv37dPAkoUPybfsqUKUhNTYWnpydCQ0Px+++/o3379uYys2bNQn5+Pp5//nlkZ2ejZ8+e2LZtm93TLmzevBlA8eomZ8+exenTp/Hbb7/VTvJi48aNZW5/9913sWnTpjr9gV+dZs+ebTWiIycnB++8806dteff//43oK69rGRtqOsEiqMc4wht4LU+HNdKRERE9c+M+HMY3MoHT3VsjI4N3eCuckK+3ghtkb7c10UcjjABhQWAvrB4FZQmQZA80heS9mGliup0OigUCiiVympvxoM48sKWf+MlJCRYff/oo4/w0UcfVXiMRCLB22+/jbffftvmtgBAZGQkZs6ciUGDBlltd3FxQVhYGMLCSsfcVtWWdho3blyVf9x7e3tDJpMhLS3NantaWpp50pB7+fn5VVi+spON3G8ZGqo6iURSLx4eRA+ShyVR8zAlpepLGx7WayUiqqpcnQFrzv2FNef+QqifO55sVzxRZyO1E0xCIKtQj0JD2aMVVDIpNKqKf/I5yWXIKjSWuc9VIQNcKk4i5OkMuFPO+WHQA4V5xUu2qlyAjj0gDe4FNGsHyV0jAe4mkUiQlZVVIwmM+jLnRX1oY3mOHDmCFi1aACieWqJ58+YAilct3bt3L1auXFnpuqvtrpw8eRKdO3euUh1KpRKhoaHYsWOH+V0ak8mEHTt2lDvBR3h4OHbs2IHp06ebt8XHx5uXfqnOyUaIiOo7iUQCiURiNXSQiGrWw5KoeZiSUrxWx77WB9nRVC2Opmqx+EAyhgX5YVxHf7RuoIa3swR5OgO0RQbcfQcaOCuQdUeP2wUVz4/xZ34uZI2stx1Ly4TeUP58GADg7qSAv9oJf+besWwUoniSTt0dQCoFPHwsk3Rq7r9kqlKphNFoRHp6Ory9vas1gfEgjrxwNDqdDm5ubgCA4OBgnDhxAi1btkRERESFy7zawu7kxb2TYwLFoxg2b96MIUOGWO3/8MMP7W7QjBkzMHnyZHTp0gXdunXDxx9/jPz8fPPqI/dONvLKK6+gT58++Pe//40hQ4Zg9erVOHLkCL788ksA1TvZCBEREZG9SpKGQP3+BylRfVJRwuOBIkyQXL8Aybnf4Zt8EtDdgZDKiifIlCuA3Cw0atYOxpGvVlxP3hXIz1u/HmBo99Z9X1uX/vYfSE/tgU+QFyRGI5CfDRgNgNIJaP0opCG9gZYhkMhs/9kpkUjg6emJnJycak9gcORFzQsKCsKhQ4fg5uaG/Px8aLVaAICbmxsyMzOrVLfdd+X48eNlbu/atStu3bqFW7duAYD5/6TtNWbMGNy+fRtvvfUWUlNT0alTJ2zbts084ea9k41ERERg1apV+Ne//oU333wTQUFB2LRpEzp27GguU12TjRARERERkeO7O2n4wGvzKNDmUYicDIiziRCndgNZt4rnmTAaAZkMivv97jE4AfckV+VOTsB9jjPJ5BBGIyS5mYBEAmi8IAnuBUmHCEgalP3avy0kEgm8vLyQkZFhTmBUB468qHkvvfQSpkyZghYtWiAkJATffPMNlixZgr1795ZaRMNedicvdu3aVaUT2mLatGnlviZy72QjADBq1CiMGjWq3PoqO9nIvepzBoyIiIiIiB5cEo0XJOFDIbpGAVdOw3RqD3DlbPEqHzVFJgecXYHGQZA+0gcI6gyJonrmDZRKpVYJDLVaXeU668tqI/U5efHcc8+hQYMGuHjxIqZMmYKxY8eiZcuWSElJKfc3vq0cP3IORC6Xo6CgAC4uLnXdFCIiIiIiolIkcgUQ9ChkQY9CZKYWJxhq6lwRwyF5tD8k3o1rpP67Exglrx9UBV8bqR1PPPGE+c9bt27Fxo0bodPpMHbs2CrVa9NdGThwIObNm4fu3btXWC43NxfLli2DWq1GTExMlRrmiAwGA/Lz86FSqcyTkBARERERETmiqry6YVP9ag9A7VGj5yhJYKSmpla5Lr42UvvkcnmFb0nYVZcthUaNGoWRI0fC3d0dw4YNQ5cuXeDv7w8nJydkZWXh3Llz2LdvH3755RcMGTIEH3zwQbU0ztEYDAa4uroiJycHAJjAICIiIiIiqmFSqRQajabK9XDkRf1m01159tlnMWHCBKxbtw5r1qzBl19+aR62I5FI0L59e0RFReHw4cNo165djTa4rrm4uEClUjGBQUREREREVEuqY5l3jryo32xO6ahUKkyYMAETJkwAAGi1Wty5cwdeXl5QKBQ11kBHVJKwKElgqFTVMykNERERERER1QxO2Fm/VTpy7u7ucHd3r8621Ct3JzBcXFzYwYiIiIiIiBwYR17Ub46fdnJgJQmM7OxsuLq61nFriIiIiIiIqDyc86J+412pIjc3NxgMBuh0urpuChEREREREZWDIy/qNyYvqoGLiwuTF0RERERERA6MIy/qt6pP2fqQM5lMyMrKgkQiqeumEBERERERUTmkUql59IUjf+xZWSU2NhZdu3aFm5sbfHx8MGLECCQlJVV4zFdffYVevXrB09MTnp6eiIyMxKFDh6zKREdHQyKRWH0GDhxYqfteXexOXkyePBl79uypibbUOyaTCRkZGTAYDFAqlXXdHCIiIiIiIipHyciL+vCx1e7duxETE4MDBw4gPj4eer0eAwYMQH5+frnHJCQkYNy4cdi1axcSExPRtGlTDBgwADdv3rQqN3DgQKSkpJg/P/74Y6XvfXWwezyKVqtFZGQkmjdvjqeffhqTJ09G48aNa6JtDq0kcaHX6+Hp6Qmj0VjXTSIiIiIiIqJyPIhzXmzbts3qe1xcHHx8fHD06FH07t27zGN++OEHq+9ff/01fvrpJ+zYsQOTJk0yb1epVPDz87Oj5TXL7pEXmzZtws2bN/Hiiy9izZo1aNGiBQYNGoT169dDr9fXRBsdzt2JC29vbygUirpuEhEREREREVWgrkdT2DvyIicnx+pTVFR032vUarUAgAYNGth8XwoKCqDX60sdk5CQAB8fH7Rp0wYvvvgiMjIy7Ljb1a9Sc140bNgQM2bMwMmTJ3Hw4EG0atUKEydOhL+/P1599VVcunSputvpMO5NXPB1ESIiIiIiIsdX13NZ2PMBgKZNm8Ld3d38iY2NrfD6TCYTpk+fjh49eqBjx44235fXX38d/v7+iIyMNG8bOHAg/vOf/2DHjh1YuHAhdu/ejUGDBtXpGwdVmsY0JSUF8fHxiI+Ph0wmw+DBg3H69Gm0b98eixYtwquvvlpd7XQYOTk5AMDEBRERERERUS0xGAxVrkMmk9WLlTxKkhc3btyARqMxb1epVBUeFxMTgzNnzmDfvn02n+v999/H6tWrkZCQACcnJ/P2sWPHmv8cHByMkJAQBAYGIiEhAf3797e5/upkd+T0ej22bNmCFStW4Ndff0VISAimT5+Op556ynxjN27ciGeeeeaBS14olUoYjUb4+voycUFERERERFQLdDqd+XWIqqhvc15oNBqr5EVFpk2bhp9//hl79uxBkyZNbDpm8eLFeP/99/Hbb78hJCSkwrItW7aEt7c3Ll++XH+SF40aNYLJZMK4ceNw6NAhdOrUqVSZxx57DB4eHtXQPMcilUrh7u7OxAUREREREVEt0Ol0SE9Pr5akg70redQVe9oohMBLL72EjRs3IiEhAQEBATYdt2jRIrz77rvYvn07unTpct/yf/75JzIyMtCoUSOb21bd7I7cRx99hFGjRlkNKbmXh4cHrly5UqWGOaKioqJa6ewFLr4o7P4VlHLbsmxERERERESVpg4AIr6v61aUUpK4UCgUcHZ2rnJ99W3khS1iYmKwatUqbN68GW5ubkhNTQUAuLu7m+/ZpEmT0LhxY/OcGQsXLsRbb72FVatWoUWLFuZj1Go11Go18vLyMH/+fIwcORJ+fn5ITk7GrFmz0KpVK0RFRVXz1drO7l/iEydOrIl21AtCiLpuAhERERER0QPv7sSFl5cXCgsLq1zngzjyYvny5QCAvn37Wm1fsWIFoqOjAQDXr1+HVCq1Okan0+HJJ5+0Ombu3LmYN28eZDIZTp06he+++w7Z2dnw9/fHgAEDsGDBgvvOu1GTHD9yRERERERE9NDQ6/XQarXmxMXdP7yrQiqV1ouRF/Zcry3/gT0hIcHq+9WrVyss7+zsjO3bt9vchtrC5AURERERERE5BJPJhJycHKhUqmpNXAAP5siLhwnvih2kUikMBgN0Op3Vdr1eD4PBUOkZcPOMeSjKKbLali2yYZBVfTkgIiIiIiKi+kCr1eLOnTuQSqXQaDRWy6NWx1KpTF7Ub7wrdvDw8EBGRkap7J/JZIIQAr/88ovdHc1gMECn16FQWgiprLhek9GEVFMqlAplrXRck8kEnU4HiUQCpVIJiURS5raaJISATqeDEAJKpRJSqbTMbTXNYDBAr9dDoVCY731Z22oS42HBeBRjPCwYDwvGoxjjYcF4WDAexRgPC8bDwpHjcefOHeTn50Mmk5knkbz7mKp6ECfsfJgweWGHkgdaWQ8VIQRUKhUUCoXd9ebk5sCQZ4Dc9f8/PAoMkKvlUKvVVWuwHRQKBbKysmA0GqFWq5GTkwO5XA5PT88af5CXcHJyQlZWFvLy8uDh4YG8vDwYDAZ4enpW6r5WVn5+PvLy8sz3Pz8/H2q1Gq6urrXWBsbDgvEoxnhYMB4WjEcxxsOC8bBgPIoxHhaMh4WjxkMqlVp97lYdyQuOvKjfeFfsJJFIykxemEwmKBQKKJVKu+t093RHgbQA+jw9AECpUcLd3R0Kae09wJRKJRQKBW7fvg2tVgulUglvb+9ayf7ezcfHB+np6eZXcHx8fCp1T6tCqSwe8ZKTkwOgeMSNm5tbrbeB8SjGeFgwHpY2MB7FGA8LxsPSBsajGONhwXhY2sB4FHPUeGg0GqSlpZWZvKiOBNODOGHnw8Rh7oper8frr7+O4OBguLq6wt/fH5MmTcJff/1V4XHz5s2DRCKx+rRt29aqTGFhIWJiYuDl5QW1Wo2RI0ciLS2tJi+HiIiIiIiIHEjJyIv68KHSHCZ5UVBQgGPHjmHOnDk4duwYNmzYgKSkJAwfPvy+x3bo0AEpKSnmz759+6z2v/rqq/jvf/+LdevWYffu3fjrr7/wxBNP1NSl2C0vNw/6PD0UagUUagX0eXrk5ebVahtK1lEuyUAbDAZkZGRUy/AsW5lMJmRkZMBgMMDb2xtKpRLp6emlJkitabm5ucjJyYFGo4FGo0FOTg5yc3NrtQ2MhwXjUYzxsGA8LBiPYoyHBeNhwXgUYzwsGA8LR41HdnZ2jcajZM6L+vCh0hwmpePu7o74+HirbUuWLEG3bt1w/fp1NGvWrNxj5XI5/Pz8ytyn1WrxzTffYNWqVejXrx8AYMWKFWjXrh0OHDiA7t27V99FVEJubi7ycvOKExeultdE8nLzIJfKa2X4VsmD4+51lL29vZGeno6MjIxqX6KoLCUPcr1eb36Qe3l5ISMjA+np6eZtNe3uB/nd975kSB3jwXgwHowH42HBeFgwHsUYDwvGw4LxKMZ4WJQXj1u3bsFoNNbYj/f6MqqhPrSxLjjMyIuyaLVaSCQSeHh4VFju0qVL8Pf3R8uWLTF+/Hhcv37dvO/o0aPQ6/WIjIw0b2vbti2aNWuGxMTEmmq6TUoeHB7uHmjm2QyNlI3QSNkIzTybwcPdo1YyoGU9OACYM6B6vb7GM9JlPciB4ne9vLy8oFAoaiUjXd6D3M3NrdYy0oyHBeNRjPGwYDwsGI9ijIcF42HBeBRjPCwYDwtHj4enpyeEECgqKqqReNT1aAqOvKgah03pFBYW4vXXX8e4ceOg0WjKLRcWFoa4uDi0adMGKSkpmD9/Pnr16oUzZ87Azc0NqampUCqVpRIgvr6+pZbfuVtRURGKiorM30sm1DGZTNDr9VZlhRDmY2xdf7igoAD5+flwdXWFTCZDQUGB1X6ZTAaVSoXMzEwUFRXBxcXFpnrtYTAYoNVqIZPJ4OzsjMLCwlJl1Go1tFotUlNTodFoqj0jbTKZkJOTA6PRCHd3dxgMhlL30NnZGXq9HmlpaXB3d6+RTCTjUYzxsGA8LBiPYoyHBeNhwXgUYzwsGA8LxqMY42Fxv3iYTCZIpVIYjUbcuXMHCoXCPFFnSTKj5LdXZRQUFNSLUQ33xoaK1VnkfvjhB0ydOtX8fevWrejVqxeA4sk7R48eDSEEli9fXmE9gwYNMv85JCQEYWFhaN68OdauXYtnn3220u2LjY3F/PnzK308ERERERERVa/c3Fy4u7vbdYxSqYSfnx+aNm1aQ62qfn5+frW+Co2jq7PkxfDhwxEWFmb+3rhxYwCWxMW1a9ewc+fOCkddlMXDwwOtW7fG5cuXARQHXafTITs722r0RVpaWrnzZADA7NmzMWPGDPN3k8mEzMxMeHl51do60CVycnLQtGlT3Lhxw+77QQSwD1HVsQ9RVbEPUVWxD1F1YD+qv4QQyM3Nhb+/v93HOjk54cqVK7U+MWpVKJVKODk51XUzHEqdJS/c3NxKTQZTkri4dOkSdu3aBS8vL7vrzcvLQ3JyMiZOnAgACA0NhUKhwI4dOzBy5EgAQFJSEq5fv47w8PBy61GpVFCpVFbb7jf3Rk0rmQ2YqLLYh6iq2IeoqtiHqKrYh6g6sB/VT/aOuLibk5MTkwH1nMNM2KnX6/Hkk0/iyJEj+OGHH2A0GpGamorU1FSrDFn//v2xZMkS8/fXXnsNu3fvxtWrV/H777/jb3/7G2QyGcaNGweguIM/++yzmDFjBnbt2oWjR4/i6aefRnh4eJ2vNEJERERERERE9+cws5XcvHkTW7ZsAQB06tTJat+uXbvQt29fAEBycjLS09PN+/7880+MGzcOGRkZaNiwIXr27IkDBw6gYcOG5jIfffQRpFIpRo4ciaKiIkRFRWHZsmU1fk1EREREREREVHUOk7xo0aKFTTPHXr161er76tWr73uMk5MTli5diqVLl1a2eXVKpVJh7ty5pV5jIbIV+xBVFfsQVRX7EFUV+xBVB/YjovpLIqqy1gwRERERERERUQ1zmDkviIiIiIiIiIjKwuQFERERERERETk0Ji+IiIiIiIiIyKExeUFEREREREREDo3JizqydOlStGjRAk5OTggLC8OhQ4cqLL9u3Tq0bdsWTk5OCA4Oxi+//GK1XwiBt956C40aNYKzszMiIyNx6dKlmrwEqiV79uzBsGHD4O/vD4lEgk2bNlntr2zs79cHCwsLERMTAy8vL6jVaowcORJpaWnVeWlUS2JjY9G1a1e4ubnBx8cHI0aMQFJSklWZysTblr6XmZmJ8ePHQ6PRwMPDA88++yzy8vKq/RqpZi1fvhwhISHQaDTQaDQIDw/H1q1bzfvZf8ge77//PiQSCaZPn27exj5E9zNv3jxIJBKrT9u2bc372YeIHgKCat3q1auFUqkU3377rTh79qyYMmWK8PDwEGlpaWWW379/v5DJZGLRokXi3Llz4l//+pdQKBTi9OnT5jLvv/++cHd3F5s2bRInT54Uw4cPFwEBAeLOnTu1dVlUQ3755Rfxz3/+U2zYsEEAEBs3brTaX5nY29IHX3jhBdG0aVOxY8cOceTIEdG9e3cRERFRU5dJNSgqKkqsWLFCnDlzRpw4cUIMHjxYNGvWTOTl5ZnLVCbetvS9gQMHikceeUQcOHBA7N27V7Rq1UqMGzeuxq6VasaWLVvE//73P3Hx4kWRlJQk3nzzTaFQKMSZM2eEEOw/ZLtDhw6JFi1aiJCQEPHKK6+Yt7MP0f3MnTtXdOjQQaSkpJg/t2/fNu9nHyJ68DF5UQe6desmYmJizN+NRqPw9/cXsbGxZZYfPXq0GDJkiNW2sLAwMXXqVCGEECaTSfj5+YkPPvjAvD87O1uoVCrx448/1sAVUF25N3lR2djfrw9mZ2cLhUIh1q1bZy5z/vx5AUAkJiZW4xVRXbh165YAIHbv3i2EqFy8bel7586dEwDE4cOHzWW2bt0qJBKJuHnzZk1cGtUiT09P8fXXX7P/kM1yc3NFUFCQiI+PF3369DEnL9iHyBZz584VjzzySJn72IeIHg58baSW6XQ6HD16FJGRkeZtUqkUkZGRSExMLPOYxMREq/IAEBUVZS5/5coVpKamWpVxd3dHWFhYuXXSg6EysbelDx49ehR6vd6qTNu2bdGsWTP2qQeAVqsFADRo0ABA5eJtS99LTEyEh4cHunTpYi4TGRkJqVSKgwcPVvt1Ue0wGo1YvXo18vPzER4ezv5DNouJicGQIUNK/ZuGfYhsdenSJfj7+6Nly5YYP348rl+/DoB9iOhhIa/rBjxs0tPTYTQa4evra7Xd19cXFy5cKPOY1NTUMsunpqaa95dsK68MPZgqE3tb+mBqaiqUSiU8PDxsrpfqB5PJhOnTp6NHjx7o2LEjgMrF25a+l5qaCh8fH6v9crkcDRo0YD+qh06fPo3w8HAUFhZCrVZj48aNaN++PU6cOMH+Q/e1evVqHDt2DIcPHy61j88gskVYWBji4uLQpk0bpKSkYP78+ejVqxfOnDnDPkT0kGDygojoIRITE4MzZ85g3759dd0UqmfatGmDEydOQKvVYv369Zg8eTJ2795d182ieuDGjRt45ZVXEB8fDycnp7puDtVTgwYNMv85JCQEYWFhaN68OdauXQtnZ+c6bBkR1Ra+NlLLvL29IZPJSs1+nJaWBj8/vzKP8fPzq7B8yf/aUyc9GCoTe1v6oJ+fH3Q6HbKzs22ulxzftGnT8PPPP2PXrl1o0qSJeXtl4m1L3/Pz88OtW7es9hsMBmRmZrIf1UNKpRKtWrVCaGgoYmNj8cgjj+CTTz5h/6H7Onr0KG7duoVHH30Ucrkccrkcu3fvxqeffgq5XA5fX1/2IbKbh4cHWrdujcuXL/M5RPSQYPKilimVSoSGhmLHjh3mbSaTCTt27EB4eHiZx4SHh1uVB4D4+Hhz+YCAAPj5+VmVycnJwcGDB8utkx4MlYm9LX0wNDQUCoXCqkxSUhKuX7/OPlUPCSEwbdo0bNy4ETt37kRAQIDV/srE25a+Fx4ejuzsbBw9etRcZufOnTCZTAgLC6vOS6Q6YDKZUFRUxP5D99W/f3+cPn0aJ06cMH+6dOmC8ePHm//MPkT2ysvLQ3JyMho1asTnENHDoq5nDH0YrV69WqhUKhEXFyfOnTsnnn/+eeHh4SFSU1OFEEJMnDhRvPHGG+by+/fvF3K5XCxevFicP39ezJ07t8ylUj08PMTmzZvFqVOnxOOPP86lUh8Qubm54vjx4+L48eMCgPjwww/F8ePHxbVr14QQtsW+X79+4rPPPjN/v18fFKJ4ybFmzZqJnTt3iiNHjojw8HARHh5eexdO1ebFF18U7u7uIiEhwWqJuYKCAnMZW+Ldpk0bsWHDBvN3W/rewIEDRefOncXBgwfFvn37RFBQEJeYq4feeOMNsXv3bnHlyhVx6tQp8cYbbwiJRCJ+/fVXIQT7D9nv7tVGhGAfovubOXOmSEhIEFeuXBH79+8XkZGRwtvbW9y6dUsIwT5E9DBg8qKOfPbZZ6JZs2ZCqVSKbt26iQMHDpj39enTR0yePNmq/Nq1a0Xr1q2FUqkUHTp0EP/73/+s9ptMJjFnzhzh6+srVCqV6N+/v0hKSqqNS6EatmvXLgGg1Kekj9gS++bNm4u5c+dabauoDwohxJ07d8Tf//534enpKVxcXMTf/vY3kZKSUpOXSjWkrP4DQKxYscJcxpZ433uMLX0vIyNDjBs3TqjVaqHRaMTTTz8tcnNza/JyqQY888wzonnz5kKpVIqGDRuK/v37mxMXQrD/kP3uTV6wD9H9jBkzRjRq1EgolUrRuHFjMWbMGHH58mXzfvYhogefRAghan+8BxERERERERGRbTjnBRERERERERE5NCYviIiIiIiIiMihMXlBRERERERERA6NyQsiIiIiIiIicmhMXhARERERERGRQ2PygoiIiIiIiIgcGpMXREREREREROTQmLwgIiJ6QHzzzTcYMGBAjZ9n27Zt6NSpE0wmU42fi4iIiAhg8oKIiOiBUFhYiDlz5mDu3Lk1fq6BAwdCoVDghx9+qPFzEREREQFMXhARET0Q1q9fD41Ggx49etTK+aKjo/Hpp5/WyrmIiIiImLwgIiJyILdv34afnx/ee+8987bff/8dSqUSO3bsKPe41atXY9iwYVbb+vbti+n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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Built 153 2D FDTD simulations\n", "Source HDF5: /home/filipe/Desktop/GITHUB/tidyvernier-dual-ring-filter/tidy3d-community-library/notebooks/data/sim_data.hdf5\n", "Source monitor/component: field_yz_output/Ey\n", "Selected source slice: 740.253 nm, z=+0.0298 um\n", "Manifest: /home/filipe/Desktop/GITHUB/tidyvernier-dual-ring-filter/tidy3d-community-library/notebooks/sin_inverse_taper_2d_sweep_from_sim_data/sin_inverse_taper_2d_sweep_from_sim_data_manifest.json\n", "Sweep grid HDF5: /home/filipe/Desktop/GITHUB/tidyvernier-dual-ring-filter/tidy3d-community-library/notebooks/sin_inverse_taper_2d_sweep_from_sim_data/sin_inverse_taper_2d_sweep_from_sim_data_grid.hdf5\n", "Batch HDF5: /home/filipe/Desktop/GITHUB/tidyvernier-dual-ring-filter/tidy3d-community-library/notebooks/sin_inverse_taper_2d_sweep_from_sim_data/sin_inverse_taper_2d_sweep_from_sim_data_batch.hdf5\n", "2D effective core index: 1.679251\n", "Source frequency: 4.049864e+14 Hz\n", "Cell count range: 27,376 - 1,692,262\n", "Total cells across sweep: 143,639,920\n", "Loading existing inverse-taper results from: /home/filipe/Desktop/GITHUB/tidyvernier-dual-ring-filter/tidy3d-community-library/notebooks/sin_inverse_taper_2d_sweep_from_sim_data/results\n" ] } ], "source": [ "# Build and run the inverse-taper sweep only if its results are not already on disk.\n", "inverse_taper_results_dir = SIN_INVERSE_TAPER_SWEEP_DIR / \"results\"\n", "inverse_taper_batch = None\n", "inverse_taper_batch_data = None\n", "inverse_taper_batch = inverse_taper_prepare_batch()\n", "\n", "if inverse_taper_results_dir.exists() and list(\n", " inverse_taper_results_dir.rglob(\"*.hdf5\")\n", "):\n", " print(\"Loading existing inverse-taper results from:\", inverse_taper_results_dir)\n", "else:\n", " inverse_taper_results_dir.mkdir(parents=True, exist_ok=True)\n", " inverse_taper_batch_data = inverse_taper_batch.run(\n", " path_dir=str(inverse_taper_results_dir)\n", " )\n", " print(\"Downloaded inverse-taper results to:\", inverse_taper_results_dir)" ] }, { "cell_type": "code", "execution_count": 40, "id": "4k8wxzOcS5VX", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:43.599359Z", "iopub.status.busy": "2026-06-22T18:48:43.599026Z", "iopub.status.idle": "2026-06-22T18:48:43.601511Z", "shell.execute_reply": "2026-06-22T18:48:43.601122Z" }, "id": "4k8wxzOcS5VX" }, "outputs": [], "source": [ "INVERSE_TAPER_C_UM_PER_S = 299_792_458.0 * 1e6\n", "\n", "\n", "def inverse_taper_wavelength_um(freq_hz):\n", " \"\"\"Convert frequency in Hz to wavelength in micrometers.\"\"\"\n", "\n", " return INVERSE_TAPER_C_UM_PER_S / np.asarray(freq_hz, dtype=float)" ] }, { "cell_type": "markdown", "id": "d7KcGOCsTK8s", "metadata": { "id": "d7KcGOCsTK8s" }, "source": [ "Helper functions to get the names stored in the cloud." ] }, { "cell_type": "code", "execution_count": 41, "id": "mUFwwPOOTKCG", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:43.602764Z", "iopub.status.busy": "2026-06-22T18:48:43.602547Z", "iopub.status.idle": "2026-06-22T18:48:43.605941Z", "shell.execute_reply": "2026-06-22T18:48:43.605657Z" }, "id": "mUFwwPOOTKCG" }, "outputs": [], "source": [ "def inverse_taper_load_batch_task_map(batch_hdf5):\n", " \"\"\"Return task-id to task-name mapping from a Tidy3D batch HDF5.\"\"\"\n", "\n", " if not batch_hdf5.exists():\n", " return {}\n", " with h5py.File(batch_hdf5, \"r\") as h5:\n", " if \"JSON_STRING\" not in h5:\n", " return {}\n", " metadata = inverse_taper_load_json_metadata(h5)\n", " mapping = {}\n", " for task_name, job in metadata.get(\"jobs_cached\", {}).items():\n", " task_id = job.get(\"task_id_cached\")\n", " if task_id:\n", " mapping[str(task_id)] = str(task_name)\n", " return mapping\n", "\n", "\n", "def inverse_taper_find_result_files(results_dir):\n", " \"\"\"Find downloaded raw Tidy3D result files.\"\"\"\n", "\n", " return sorted(\n", " path\n", " for path in results_dir.rglob(\"*.hdf5\")\n", " if path.name != \"batch.hdf5\"\n", " and \"analysis\" not in path.parts\n", " and \"sweep_grid\" not in path.name\n", " and \"sweep_batch\" not in path.name\n", " )" ] }, { "cell_type": "markdown", "id": "X-XOtET6Taka", "metadata": { "id": "X-XOtET6Taka" }, "source": [ "Taking the online data and storing it as hdf5 files." ] }, { "cell_type": "code", "execution_count": 42, "id": "bQz84HHJTZEE", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:43.607200Z", "iopub.status.busy": "2026-06-22T18:48:43.607024Z", "iopub.status.idle": "2026-06-22T18:48:43.624384Z", "shell.execute_reply": "2026-06-22T18:48:43.623913Z" }, "id": "bQz84HHJTZEE" }, "outputs": [], "source": [ "def inverse_taper_task_from_path(path, task_rows):\n", " \"\"\"Infer a manifest task name from a downloaded result path.\"\"\"\n", "\n", " task_id_map = inverse_taper_load_batch_task_map(path.parent / \"batch.hdf5\")\n", " mapped = task_id_map.get(path.stem)\n", " if mapped in task_rows:\n", " return mapped\n", " clean = path.stem.replace(\"_results\", \"\")\n", " if clean in task_rows:\n", " return clean\n", " for task_name in task_rows:\n", " if task_name in str(path):\n", " return task_name\n", " return None\n", "\n", "\n", "def inverse_taper_read_flux(h5, index):\n", " \"\"\"Read frequency and values from one flux monitor.\"\"\"\n", "\n", " group = h5[f\"data/{index}/flux\"]\n", " return (\n", " np.asarray(group[\"f\"], dtype=float),\n", " np.asarray(\n", " group[\"__xarray_dataarray_variable__\"],\n", " dtype=float,\n", " ),\n", " )\n", "\n", "\n", "def inverse_taper_read_named_flux(h5, names, candidates):\n", " \"\"\"Read the first available flux monitor in `candidates`.\"\"\"\n", "\n", " for name in candidates:\n", " if name in names:\n", " return inverse_taper_read_flux(h5, names[name])\n", " raise KeyError(f\"None of {candidates} found. Available monitors: {sorted(names)}\")\n", "\n", "\n", "def inverse_taper_read_mode_powers(h5, index):\n", " \"\"\"Read forward mode powers and complex effective indices.\"\"\"\n", "\n", " amps_group = h5[f\"data/{index}/amps\"]\n", " neff_group = h5[f\"data/{index}/n_complex\"]\n", " directions = [\n", " item.decode() if isinstance(item, bytes) else str(item)\n", " for item in np.asarray(amps_group[\"direction\"])\n", " ]\n", " plus_index = directions.index(\"+\")\n", " freqs = np.asarray(amps_group[\"f\"], dtype=float)\n", " amps = np.asarray(amps_group[\"__xarray_dataarray_variable__\"])[plus_index, :, :]\n", " powers = np.abs(amps) ** 2\n", " neff = np.asarray(neff_group[\"__xarray_dataarray_variable__\"])\n", " return freqs, powers, neff\n", "\n", "\n", "def inverse_taper_analyze_reference(path):\n", " \"\"\"Read the source-only reference incident flux.\"\"\"\n", "\n", " with h5py.File(path, \"r\") as h5:\n", " names = inverse_taper_monitor_index(inverse_taper_load_json_metadata(h5))\n", " frequencies, input_flux = inverse_taper_read_named_flux(\n", " h5,\n", " names,\n", " (\"input_net_flux\", \"incident_flux\"),\n", " )\n", " _, backward_flux = inverse_taper_read_named_flux(\n", " h5,\n", " names,\n", " (\"raw_backward_flux\", \"reflected_flux\"),\n", " )\n", " return {\n", " \"wavelength_um\": float(inverse_taper_wavelength_um(frequencies)[0]),\n", " \"incident_reference_flux\": float(np.asarray(input_flux).reshape(-1)[0]),\n", " \"reference_raw_backward_flux\": float(np.asarray(backward_flux).reshape(-1)[0]),\n", " }\n", "\n", "\n", "def inverse_taper_analyze_result(path, task_row, incident_reference_flux):\n", " \"\"\"Compute coupling, transmission, and reflection for one taper.\"\"\"\n", "\n", " with h5py.File(path, \"r\") as h5:\n", " names = inverse_taper_monitor_index(inverse_taper_load_json_metadata(h5))\n", " _, input_flux = inverse_taper_read_named_flux(\n", " h5,\n", " names,\n", " (\"input_net_flux\", \"incident_flux\"),\n", " )\n", " _, raw_backward_flux = inverse_taper_read_named_flux(\n", " h5,\n", " names,\n", " (\"raw_backward_flux\", \"reflected_flux\"),\n", " )\n", " _, transmitted_flux = inverse_taper_read_named_flux(\n", " h5,\n", " names,\n", " (\"transmitted_flux\",),\n", " )\n", " mode_frequencies, mode_powers, neff = inverse_taper_read_mode_powers(\n", " h5, names[\"bus_modes\"]\n", " )\n", "\n", " input_net = float(np.asarray(input_flux).reshape(-1)[0])\n", " raw_backward = float(np.asarray(raw_backward_flux).reshape(-1)[0])\n", " transmitted = float(np.asarray(transmitted_flux).reshape(-1)[0])\n", " powers = np.asarray(mode_powers, dtype=float).reshape(-1)\n", " guided_sum = float(np.sum(powers))\n", " incident = (\n", " incident_reference_flux if incident_reference_flux is not None else input_net\n", " )\n", " reflectance = (incident - input_net) / incident if incident else float(\"nan\")\n", " if np.isfinite(reflectance):\n", " reflectance = float(np.clip(reflectance, 0.0, 1.0))\n", "\n", " return {\n", " \"tip_width_um\": float(task_row[\"tip_width_um\"]),\n", " \"length_um\": float(task_row[\"length_um\"]),\n", " \"num_cells\": float(task_row[\"num_cells\"]),\n", " \"run_time_s\": float(task_row.get(\"run_time_s\", float(\"nan\"))),\n", " \"wavelength_um\": float(inverse_taper_wavelength_um(mode_frequencies)[0]),\n", " \"incident_reference_flux\": float(incident),\n", " \"input_net_flux\": input_net,\n", " \"raw_backward_flux\": raw_backward,\n", " \"transmitted_flux\": transmitted,\n", " \"transmittance\": (transmitted / incident if incident else float(\"nan\")),\n", " \"reflectance\": reflectance,\n", " \"flux_out_over_flux_in\": (\n", " transmitted / input_net if input_net else float(\"nan\")\n", " ),\n", " \"guided_power_sum\": guided_sum,\n", " \"guided_over_incident\": (guided_sum / incident if incident else float(\"nan\")),\n", " \"guided_over_flux_in\": (guided_sum / input_net if input_net else float(\"nan\")),\n", " \"mode0_power\": (float(powers[0]) if powers.size > 0 else float(\"nan\")),\n", " \"mode1_power\": (float(powers[1]) if powers.size > 1 else float(\"nan\")),\n", " \"mode2_power\": (float(powers[2]) if powers.size > 2 else float(\"nan\")),\n", " \"mode0_coupling_efficiency\": (\n", " float(powers[0] / incident)\n", " if incident and powers.size > 0\n", " else float(\"nan\")\n", " ),\n", " \"mode1_coupling_efficiency\": (\n", " float(powers[1] / incident)\n", " if incident and powers.size > 1\n", " else float(\"nan\")\n", " ),\n", " \"mode2_coupling_efficiency\": (\n", " float(powers[2] / incident)\n", " if incident and powers.size > 2\n", " else float(\"nan\")\n", " ),\n", " \"mode0_over_flux_in\": (\n", " float(powers[0] / input_net)\n", " if input_net and powers.size > 0\n", " else float(\"nan\")\n", " ),\n", " \"mode0_guided_fraction\": (\n", " float(powers[0] / guided_sum)\n", " if guided_sum and powers.size > 0\n", " else float(\"nan\")\n", " ),\n", " \"mode0_neff_real\": (\n", " float(np.real(neff.reshape(-1)[0])) if neff.size else float(\"nan\")\n", " ),\n", " \"mode0_neff_imag\": (\n", " float(np.imag(neff.reshape(-1)[0])) if neff.size else float(\"nan\")\n", " ),\n", " }\n", "\n", "\n", "def inverse_taper_metric_grid(rows, metric):\n", " \"\"\"Return tip, length, and metric arrays for a heatmap.\"\"\"\n", "\n", " tips = np.asarray(sorted({row[\"tip_width_um\"] for row in rows}))\n", " lengths = np.asarray(sorted({row[\"length_um\"] for row in rows}))\n", " grid = np.full((lengths.size, tips.size), np.nan)\n", " tip_index = {value: index for index, value in enumerate(tips)}\n", " length_index = {value: index for index, value in enumerate(lengths)}\n", " for row in rows:\n", " grid[\n", " length_index[row[\"length_um\"]],\n", " tip_index[row[\"tip_width_um\"]],\n", " ] = row[metric]\n", " return tips, lengths, grid\n", "\n", "\n", "def inverse_taper_write_analysis_hdf5(path, rows, manifest):\n", " \"\"\"Write all scalar taper metrics to a compact HDF5 file.\"\"\"\n", "\n", " with h5py.File(path, \"w\") as h5:\n", " h5.attrs[\"description\"] = (\n", " \"2D FDTD inverse-taper metrics from the laser custom source\"\n", " )\n", " h5.attrs[\"source_hdf5\"] = manifest.get(\"source_hdf5\", \"\")\n", " for key, value in manifest.get(\"source_metadata\", {}).items():\n", " h5.attrs[f\"source_{key}\"] = value\n", " for field in rows[0]:\n", " h5.create_dataset(\n", " field,\n", " data=np.asarray([row[field] for row in rows], dtype=float),\n", " )" ] }, { "cell_type": "markdown", "id": "jK6EEEn_TmV2", "metadata": { "id": "jK6EEEn_TmV2" }, "source": [ "Plots the source amplitude and height adjusted maxima." ] }, { "cell_type": "code", "execution_count": 43, "id": "I00SmMMTTlcC", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:43.625801Z", "iopub.status.busy": "2026-06-22T18:48:43.625484Z", "iopub.status.idle": "2026-06-22T18:48:43.631664Z", "shell.execute_reply": "2026-06-22T18:48:43.631287Z" }, "id": "I00SmMMTTlcC" }, "outputs": [], "source": [ "def inverse_taper_plot_source(path, manifest):\n", " \"\"\"Plot the source-plane intensity and selected replay slice.\"\"\"\n", "\n", " source_hdf5 = Path(manifest[\"source_hdf5\"])\n", " metadata = manifest[\"source_metadata\"]\n", " monitor_name = str(metadata[\"source_monitor\"])\n", " component = str(metadata[\"source_component\"])\n", " selected_wavelength_um = float(metadata[\"source_wavelength_um_selected\"])\n", " selected_z_um = float(metadata[\"source_z_slice_um_selected\"])\n", "\n", " with h5py.File(source_hdf5, \"r\") as h5:\n", " values, _, y, z, frequencies = inverse_taper_read_component(\n", " h5,\n", " monitor_name,\n", " component,\n", " )\n", "\n", " wavelengths = inverse_taper_wavelength_um(frequencies)\n", " frequency_index = int(np.argmin(np.abs(wavelengths - selected_wavelength_um)))\n", " z_index = int(np.argmin(np.abs(z - selected_z_um)))\n", " field = np.squeeze(values)[:, :, frequency_index]\n", " intensity = np.abs(field) ** 2\n", " intensity /= max(float(np.nanmax(intensity)), 1e-30)\n", "\n", " fig, axes = plt.subplots(\n", " 1,\n", " 2,\n", " figsize=(11.2, 4.2),\n", " constrained_layout=True,\n", " )\n", " image = axes[0].imshow(\n", " intensity.T,\n", " origin=\"lower\",\n", " extent=(\n", " float(y[0]),\n", " float(y[-1]),\n", " float(z[0]),\n", " float(z[-1]),\n", " ),\n", " aspect=\"auto\",\n", " cmap=\"magma\",\n", " )\n", " axes[0].axhline(\n", " float(z[z_index]),\n", " color=\"white\",\n", " linewidth=1.2,\n", " alpha=0.85,\n", " )\n", " axes[0].set_xlabel(\"y [um]\")\n", " axes[0].set_ylabel(\"z [um]\")\n", " axes[0].set_title(\n", " f\"source |{component}|^2 at {1000.0 * wavelengths[frequency_index]:.2f} nm\"\n", " )\n", " fig.colorbar(image, ax=axes[0], label=\"normalized intensity\")\n", "\n", " axes[1].plot(y, intensity[:, z_index], linewidth=2.0)\n", " axes[1].set_xlabel(\"y [um]\")\n", " axes[1].set_ylabel(\"normalized |field|^2\")\n", " axes[1].set_title(f\"replayed lateral slice, z={z[z_index]:+.4f} um\")\n", " axes[1].grid(True, alpha=0.3)\n", " fig.savefig(path, dpi=220)\n", " plt.show()" ] }, { "cell_type": "markdown", "id": "KM7hdMhJUCBt", "metadata": { "id": "KM7hdMhJUCBt" }, "source": [ "Plotting functions used to characterize and validate the sweep." ] }, { "cell_type": "code", "execution_count": 44, "id": "2DuRMGU1T9no", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:43.633362Z", "iopub.status.busy": "2026-06-22T18:48:43.633079Z", "iopub.status.idle": "2026-06-22T18:48:43.639582Z", "shell.execute_reply": "2026-06-22T18:48:43.639274Z" }, "id": "2DuRMGU1T9no" }, "outputs": [], "source": [ "def inverse_taper_plot_heatmaps(path, rows):\n", " \"\"\"Plot coupling, throughput, transmission, and reflection heatmaps.\"\"\"\n", "\n", " metrics = [\n", " (\"mode0_coupling_efficiency\", \"TE0 coupling / incident\", \"viridis\"),\n", " (\"flux_out_over_flux_in\", \"flux_out / flux_in\", \"viridis\"),\n", " (\"transmittance\", \"transmittance\", \"viridis\"),\n", " (\"reflectance\", \"reflectance\", \"magma\"),\n", " ]\n", " fig, axes = plt.subplots(\n", " 1,\n", " 4,\n", " figsize=(17.2, 4.2),\n", " constrained_layout=True,\n", " )\n", " for ax, (metric, title, cmap) in zip(axes, metrics):\n", " tips, lengths, grid = inverse_taper_metric_grid(rows, metric)\n", " image = ax.imshow(\n", " grid,\n", " origin=\"lower\",\n", " extent=(\n", " float(tips[0]),\n", " float(tips[-1]),\n", " float(lengths[0]),\n", " float(lengths[-1]),\n", " ),\n", " aspect=\"auto\",\n", " cmap=cmap,\n", " )\n", " ax.set_xlabel(\"tip width [um]\")\n", " ax.set_ylabel(\"length [um]\")\n", " ax.set_title(title)\n", " fig.colorbar(image, ax=ax)\n", " fig.savefig(path, dpi=220)\n", " plt.show()\n", "\n", "\n", "def inverse_taper_plot_tradeoffs(path, rows):\n", " \"\"\"Plot coupling/reflection tradeoffs and length trends.\"\"\"\n", "\n", " fig, axes = plt.subplots(\n", " 1,\n", " 2,\n", " figsize=(11.6, 4.6),\n", " constrained_layout=True,\n", " )\n", " scatter = axes[0].scatter(\n", " [row[\"reflectance\"] for row in rows],\n", " [row[\"mode0_coupling_efficiency\"] for row in rows],\n", " c=[row[\"length_um\"] for row in rows],\n", " s=46,\n", " cmap=\"viridis\",\n", " )\n", " axes[0].set_xlabel(\"reflectance\")\n", " axes[0].set_ylabel(\"TE0 coupling / incident\")\n", " axes[0].set_title(\"coupling vs reflection\")\n", " axes[0].grid(True, alpha=0.3)\n", " fig.colorbar(scatter, ax=axes[0], label=\"length [um]\")\n", "\n", " tips, _, _ = inverse_taper_metric_grid(\n", " rows,\n", " \"flux_out_over_flux_in\",\n", " )\n", " for tip in tips:\n", " tip_rows = sorted(\n", " (row for row in rows if row[\"tip_width_um\"] == tip),\n", " key=lambda row: row[\"length_um\"],\n", " )\n", " axes[1].plot(\n", " [row[\"length_um\"] for row in tip_rows],\n", " [row[\"flux_out_over_flux_in\"] for row in tip_rows],\n", " marker=\"o\",\n", " linewidth=1.4,\n", " markersize=3.2,\n", " label=f\"{tip:.2f} um\",\n", " )\n", " axes[1].set_xlabel(\"length [um]\")\n", " axes[1].set_ylabel(\"flux_out / flux_in\")\n", " axes[1].set_title(\"direct throughput vs taper length\")\n", " axes[1].grid(True, alpha=0.3)\n", " axes[1].legend(title=\"tip\", fontsize=7, ncols=2)\n", " fig.savefig(path, dpi=220)\n", " plt.show()" ] }, { "cell_type": "markdown", "id": "5MvzVSuEVgXq", "metadata": { "id": "5MvzVSuEVgXq" }, "source": [ "Creates a markdown file that can be used to rank the choice of input coupler." ] }, { "cell_type": "code", "execution_count": 45, "id": "iYUE9LOoVfEU", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:43.640985Z", "iopub.status.busy": "2026-06-22T18:48:43.640749Z", "iopub.status.idle": "2026-06-22T18:48:43.645250Z", "shell.execute_reply": "2026-06-22T18:48:43.644953Z" }, "id": "iYUE9LOoVfEU" }, "outputs": [], "source": [ "def inverse_taper_write_summary(path, rows, analysis_hdf5):\n", " \"\"\"Write a Markdown table of the highest-performing candidates.\"\"\"\n", "\n", " score = lambda row: row[\"mode0_coupling_efficiency\"] - 0.25 * row[\"reflectance\"]\n", " best = max(rows, key=score)\n", " best_flux = max(rows, key=lambda row: row[\"flux_out_over_flux_in\"])\n", " ranked = sorted(rows, key=score, reverse=True)\n", " ranked_flux = sorted(\n", " rows,\n", " key=lambda row: row[\"flux_out_over_flux_in\"],\n", " reverse=True,\n", " )\n", " lines = [\n", " \"# Sim-Data Custom-Source Inverse Taper Sweep\",\n", " \"\",\n", " f\"- Designs analyzed: `{len(rows)}`\",\n", " (\n", " \"- Best balanced candidate: \"\n", " f\"tip `{best['tip_width_um']:.3f} um`, \"\n", " f\"length `{best['length_um']:.1f} um`\"\n", " ),\n", " (f\"- TE0 coupling / incident: `{best['mode0_coupling_efficiency']:.4f}`\"),\n", " (\n", " \"- Direct flux efficiency flux_out/flux_in: \"\n", " f\"`{best['flux_out_over_flux_in']:.4f}`\"\n", " ),\n", " f\"- Transmittance: `{best['transmittance']:.4f}`\",\n", " f\"- Reflectance: `{best['reflectance']:.4f}`\",\n", " (\n", " \"- Best direct flux candidate: \"\n", " f\"tip `{best_flux['tip_width_um']:.3f} um`, \"\n", " f\"length `{best_flux['length_um']:.1f} um`, \"\n", " f\"flux_out/flux_in \"\n", " f\"`{best_flux['flux_out_over_flux_in']:.4f}`\"\n", " ),\n", " \"\",\n", " f\"Processed HDF5: `{analysis_hdf5}`\",\n", " \"\",\n", " \"## Top Balanced Candidates\",\n", " \"\",\n", " (\n", " \"| rank | tip width | length | TE0 coupling | \"\n", " \"flux_out/flux_in | transmittance | reflectance | \"\n", " \"TE0 guided fraction |\"\n", " ),\n", " \"|---:|---:|---:|---:|---:|---:|---:|---:|\",\n", " ]\n", " for rank, row in enumerate(ranked[:12], start=1):\n", " lines.append(\n", " f\"| {rank} | {row['tip_width_um']:.3f} um | \"\n", " f\"{row['length_um']:.1f} um | \"\n", " f\"{row['mode0_coupling_efficiency']:.4f} | \"\n", " f\"{row['flux_out_over_flux_in']:.4f} | \"\n", " f\"{row['transmittance']:.4f} | \"\n", " f\"{row['reflectance']:.4f} | \"\n", " f\"{row['mode0_guided_fraction']:.4f} |\"\n", " )\n", " lines.extend(\n", " [\n", " \"\",\n", " \"## Top Direct Flux Candidates\",\n", " \"\",\n", " (\n", " \"| rank | tip width | length | flux_out/flux_in | \"\n", " \"TE0 coupling | reflectance |\"\n", " ),\n", " \"|---:|---:|---:|---:|---:|---:|\",\n", " ]\n", " )\n", " for rank, row in enumerate(ranked_flux[:12], start=1):\n", " lines.append(\n", " f\"| {rank} | {row['tip_width_um']:.3f} um | \"\n", " f\"{row['length_um']:.1f} um | \"\n", " f\"{row['flux_out_over_flux_in']:.4f} | \"\n", " f\"{row['mode0_coupling_efficiency']:.4f} | \"\n", " f\"{row['reflectance']:.4f} |\"\n", " )\n", " path.write_text(\"\\n\".join(lines) + \"\\n\", encoding=\"utf-8\")" ] }, { "cell_type": "markdown", "id": "g5tofi4KUXSC", "metadata": { "id": "g5tofi4KUXSC" }, "source": [ "This is the main function that plots all of the outputs from the file sweep." ] }, { "cell_type": "code", "execution_count": 46, "id": "um5lDCzdUTVL", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:43.646696Z", "iopub.status.busy": "2026-06-22T18:48:43.646547Z", "iopub.status.idle": "2026-06-22T18:48:51.690868Z", "shell.execute_reply": "2026-06-22T18:48:51.690639Z" }, "id": "um5lDCzdUTVL" }, "outputs": [ { "data": { "image/png": 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Analyzed 23 inverse-taper result files\n", "Best balanced candidate: tip=0.100 um, L=125.0 um, TE0=0.8756, flux_out/flux_in=0.8739, T=0.8706, R=0.0037\n" ] } ], "source": [ "def inverse_taper_analyze_sweep():\n", " \"\"\"Read downloaded results and generate all inverse-taper outputs.\"\"\"\n", "\n", " manifest_path = (\n", " SIN_INVERSE_TAPER_SWEEP_DIR\n", " / \"sin_inverse_taper_2d_sweep_from_sim_data_manifest.json\"\n", " )\n", " results_dir = SIN_INVERSE_TAPER_SWEEP_DIR / \"results\"\n", " SIN_INVERSE_TAPER_ANALYSIS_DIR.mkdir(parents=True, exist_ok=True)\n", "\n", " manifest = json.loads(manifest_path.read_text(encoding=\"utf-8\"))\n", " task_rows = manifest[\"tasks\"]\n", " task_to_result = {}\n", " skipped = []\n", " for result_path in inverse_taper_find_result_files(results_dir):\n", " task_name = inverse_taper_task_from_path(result_path, task_rows)\n", " if task_name is None:\n", " skipped.append(result_path)\n", " else:\n", " task_to_result[task_name] = result_path\n", "\n", " reference_tasks = [\n", " task_name\n", " for task_name, row in task_rows.items()\n", " if float(row.get(\"is_reference\", 0.0)) > 0.5\n", " ]\n", " incident_reference_flux = None\n", " if reference_tasks:\n", " reference_task = reference_tasks[0]\n", " if reference_task not in task_to_result:\n", " raise RuntimeError(\n", " f\"Reference task {reference_task!r} is missing from {results_dir}.\"\n", " )\n", " incident_reference_flux = inverse_taper_analyze_reference(\n", " task_to_result[reference_task]\n", " )[\"incident_reference_flux\"]\n", "\n", " rows = []\n", " for task_name, result_path in task_to_result.items():\n", " task_row = task_rows[task_name]\n", " if float(task_row.get(\"is_reference\", 0.0)) > 0.5:\n", " continue\n", " rows.append(\n", " inverse_taper_analyze_result(\n", " result_path,\n", " task_row,\n", " incident_reference_flux,\n", " )\n", " )\n", " if not rows:\n", " raise RuntimeError(\n", " f\"No matching inverse-taper result HDF5 files found in {results_dir}.\"\n", " )\n", " rows = sorted(\n", " rows,\n", " key=lambda row: (row[\"tip_width_um\"], row[\"length_um\"]),\n", " )\n", "\n", " inverse_taper_write_analysis_hdf5(\n", " SIN_INVERSE_TAPER_ANALYSIS_HDF5,\n", " rows,\n", " manifest,\n", " )\n", " inverse_taper_plot_source(\n", " SIN_INVERSE_TAPER_SOURCE_PNG,\n", " manifest,\n", " )\n", " inverse_taper_plot_heatmaps(\n", " SIN_INVERSE_TAPER_HEATMAPS_PNG,\n", " rows,\n", " )\n", " inverse_taper_plot_tradeoffs(\n", " SIN_INVERSE_TAPER_TRADEOFFS_PNG,\n", " rows,\n", " )\n", " inverse_taper_write_summary(\n", " SIN_INVERSE_TAPER_SUMMARY_MD,\n", " rows,\n", " SIN_INVERSE_TAPER_ANALYSIS_HDF5,\n", " )\n", "\n", " best = max(\n", " rows,\n", " key=lambda row: row[\"mode0_coupling_efficiency\"] - 0.25 * row[\"reflectance\"],\n", " )\n", " print(f\"Analyzed {len(rows)} inverse-taper result files\")\n", " print(\n", " \"Best balanced candidate: \"\n", " f\"tip={best['tip_width_um']:.3f} um, \"\n", " f\"L={best['length_um']:.1f} um, \"\n", " f\"TE0={best['mode0_coupling_efficiency']:.4f}, \"\n", " f\"flux_out/flux_in={best['flux_out_over_flux_in']:.4f}, \"\n", " f\"T={best['transmittance']:.4f}, \"\n", " f\"R={best['reflectance']:.4f}\"\n", " )\n", " if skipped:\n", " print(f\"Skipped {len(skipped)} unmatched HDF5 files\")\n", " return rows\n", "\n", "\n", "SIN_INVERSE_TAPER_ANALYSIS_HDF5 = (\n", " SIN_INVERSE_TAPER_ANALYSIS_DIR\n", " / \"sin_inverse_taper_2d_sweep_from_sim_data_analysis.hdf5\"\n", ")\n", "SIN_INVERSE_TAPER_SOURCE_PNG = (\n", " SIN_INVERSE_TAPER_ANALYSIS_DIR / \"sim_data_custom_source_profile.png\"\n", ")\n", "SIN_INVERSE_TAPER_HEATMAPS_PNG = (\n", " SIN_INVERSE_TAPER_ANALYSIS_DIR\n", " / \"sin_inverse_taper_2d_sweep_from_sim_data_heatmaps.png\"\n", ")\n", "SIN_INVERSE_TAPER_TRADEOFFS_PNG = (\n", " SIN_INVERSE_TAPER_ANALYSIS_DIR\n", " / \"sin_inverse_taper_2d_sweep_from_sim_data_tradeoffs.png\"\n", ")\n", "SIN_INVERSE_TAPER_SUMMARY_MD = (\n", " SIN_INVERSE_TAPER_ANALYSIS_DIR\n", " / \"sin_inverse_taper_2d_sweep_from_sim_data_summary.md\"\n", ")\n", "\n", "inverse_taper_results_dir = SIN_INVERSE_TAPER_SWEEP_DIR / \"results\"\n", "inverse_taper_manifest_path = (\n", " SIN_INVERSE_TAPER_SWEEP_DIR\n", " / \"sin_inverse_taper_2d_sweep_from_sim_data_manifest.json\"\n", ")\n", "if inverse_taper_results_dir.exists() and inverse_taper_manifest_path.exists():\n", " inverse_taper_analysis_rows = inverse_taper_analyze_sweep()\n", "else:\n", " print(\n", " \"Run the inverse-taper sweep first; no results found in\",\n", " inverse_taper_results_dir,\n", " )" ] }, { "cell_type": "markdown", "id": "vMmRldK7Vnk4", "metadata": { "id": "vMmRldK7Vnk4" }, "source": [ "The best input coupler has a 0.15 µm width and a 450 µm length (but for situations where space is a premium a sufficiently wide coupler with a coupler input can have similar performance at a much smaller length down to 100 µm.)" ] }, { "cell_type": "markdown", "id": "rP7z-YeaGu2p", "metadata": { "id": "rP7z-YeaGu2p" }, "source": [ "## 3. SiN Ring Resonator" ] }, { "cell_type": "markdown", "id": "dabdf1a4", "metadata": { "id": "dabdf1a4" }, "source": [ "### Silicon Nitride Microring Design: Effective-Index Sweep and 3D Vernier Verification\n", "\n", "This section demonstrates a workflow for designing silicon nitride (SiN) microring resonators in the visible / near-infrared band from **715 nm to 750 nm**.\n", "\n", "The workflow has two stages:\n", "\n", "1. Use a **2D effective-index approximation (EIA)** to sweep the ring radius and bus-ring coupling gap at reduced computational cost.\n", "2. Promote two selected radii to **full 3D FDTD** simulations and compare their resonance combs for a Vernier pair design." ] }, { "cell_type": "markdown", "id": "ed9a83d4", "metadata": { "id": "ed9a83d4" }, "source": [ "#### Background\n", "\n", "A microring resonator supports circulating modes when the round-trip phase satisfies a resonance condition. The ring **radius** primarily controls the round-trip optical path length and therefore the free spectral range (FSR),\n", "\n", "$$\n", "\\mathrm{FSR} \\approx \\frac{\\lambda^2}{n_g 2\\pi R}.\n", "$$\n", "\n", "Here, $n_g$ is the group index and $R$ is the centerline radius. The **bus-ring gap** controls evanescent coupling, which affects the loaded quality factor, extinction, and drop efficiency.\n", "\n", "A **Vernier** design uses two rings with slightly different radii. Their resonance combs have slightly different FSRs, so only selected resonances overlap. This creates a larger spectral envelope period than either ring alone, which is useful for filtering and sensing." ] }, { "cell_type": "markdown", "id": "4dc8b95d", "metadata": { "id": "4dc8b95d" }, "source": [ "#### Imports\n", "\n", "The notebook uses Tidy3D for FDTD simulations, the Tidy3D dispersion fitter for effective-index media, and SciPy for peak finding and lineshape fitting." ] }, { "cell_type": "code", "execution_count": 47, "id": "d2731ae6", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:51.692337Z", "iopub.status.busy": "2026-06-22T18:48:51.692220Z", "iopub.status.idle": "2026-06-22T18:48:52.002940Z", "shell.execute_reply": "2026-06-22T18:48:52.002698Z" }, "id": "d2731ae6" }, "outputs": [], "source": [ "# Import the numerical, plotting, optimization, and Tidy3D APIs used throughout the notebook.\n", "from __future__ import annotations\n", "\n", "from dataclasses import dataclass\n", "from pathlib import Path\n", "import csv\n", "import re\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import scipy.interpolate\n", "from scipy import signal\n", "from scipy.optimize import curve_fit\n", "\n", "import tidy3d as td\n", "import tidy3d.web as web\n", "from tidy3d.plugins.dispersion import AdvancedFastFitterParam, FastDispersionFitter\n", "from tidy3d.plugins.mode.web import run as run_mode_solver\n", "from tidy3d.web.api.container import BatchData\n", "\n", "td.config.logging.level = \"ERROR\"" ] }, { "cell_type": "markdown", "id": "ee88f4d4", "metadata": { "id": "ee88f4d4" }, "source": [ "### 3.1 Self-Contained SiN Microring Builder\n", "\n", "The following cell builds a 3D SiO2-clad SiN add-drop microring with two straight buses, one mode source, through/drop mode monitors, and an optional field monitor.\n", "\n", "The geometry uses constant refractive indices over the 715-750 nm band (`n_SiN = 2.0`, `n_SiO2 = 1.45`) for a lightweight design example. Replace these with dispersive materials for a final calibrated device study." ] }, { "cell_type": "code", "execution_count": 48, "id": "751c5e80", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:52.004633Z", "iopub.status.busy": "2026-06-22T18:48:52.004529Z", "iopub.status.idle": "2026-06-22T18:48:52.143182Z", "shell.execute_reply": "2026-06-22T18:48:52.142921Z" }, "id": "751c5e80" }, "outputs": [], "source": [ "# Define the reusable parameter container and simulation factory for a 3D SiN add-drop ring.\n", "@dataclass(frozen=True)\n", "class SiNMRRParams:\n", " \"\"\"Fixed waveguide cross-section, material indices, and spectral window.\"\"\"\n", "\n", " wg_height_um: float = 0.22 # SiN core thickness (µm)\n", " wg_width_um: float = 0.50 # SiN waveguide width (µm)\n", " lambda_min_um: float = 0.715 # start wavelength for spectra (µm)\n", " lambda_max_um: float = 0.750 # stop wavelength for spectra (µm)\n", " n_wavelengths: int = 501 # monitor frequency samples across the band\n", " n_sin: float = 2.0 # constant SiN index for the example\n", " n_sio2: float = 1.45 # constant SiO2 cladding index for the example\n", " run_time_s: float = 2.5e-11 # FDTD run time (s)\n", " min_steps_per_wvl: int = 15 # automatic mesh resolution setting\n", " buffer_um: float | None = None # simulation padding; if None use _default_buffer\n", "\n", "\n", "def _default_buffer(lambda_center_um: float) -> float:\n", " return float(max(0.7 * lambda_center_um, 0.45))\n", "\n", "\n", "def build_sin_ring_mrr_sim(\n", " ring_radius_um: float,\n", " gap_um: float,\n", " params: SiNMRRParams | None = None,\n", " *,\n", " n_wavelengths: int | None = None,\n", " field_wavelengths_um: tuple[float, ...] | list[float] | None = None,\n", ") -> td.Simulation:\n", " \"\"\"Build a 3D SiN add-drop microring simulation.\n", "\n", " `ring_radius_um` is the centerline radius. `gap_um` is the edge-to-edge\n", " distance between ring and bus waveguides.\n", " \"\"\"\n", " p = params or SiNMRRParams()\n", " if n_wavelengths is not None:\n", " p = SiNMRRParams(\n", " wg_height_um=p.wg_height_um,\n", " wg_width_um=p.wg_width_um,\n", " lambda_min_um=p.lambda_min_um,\n", " lambda_max_um=p.lambda_max_um,\n", " n_wavelengths=n_wavelengths,\n", " n_sin=p.n_sin,\n", " n_sio2=p.n_sio2,\n", " run_time_s=p.run_time_s,\n", " min_steps_per_wvl=p.min_steps_per_wvl,\n", " buffer_um=p.buffer_um,\n", " )\n", "\n", " wg_height = p.wg_height_um # reused for all structures and port sizes\n", " wg_width = p.wg_width_um\n", " lda0 = 0.5 * (p.lambda_min_um + p.lambda_max_um) # source center wavelength\n", " ldas = np.linspace(\n", " p.lambda_min_um, p.lambda_max_um, p.n_wavelengths\n", " ) # sampled wavelengths\n", " freqs = td.C_0 / ldas # Tidy3D monitors are specified in frequency\n", " freq0 = td.C_0 / lda0 # Gaussian pulse center frequency\n", " fwidth = 0.5 * float(\n", " np.max(freqs) - np.min(freqs)\n", " ) # pulse bandwidth covering the sweep\n", "\n", " if field_wavelengths_um is None:\n", " field_freqs = [freq0]\n", " else:\n", " field_freqs = [td.C_0 / float(w) for w in sorted(set(field_wavelengths_um))]\n", "\n", " # Use simple constant-index media for this design example.\n", " sin = td.Medium(permittivity=p.n_sin**2)\n", " sio2 = td.Medium(permittivity=p.n_sio2**2)\n", "\n", " R = float(ring_radius_um) # ring centerline radius (µm)\n", " gap = float(gap_um) # edge-to-edge bus-ring gap (µm)\n", " wg_center_y = R + wg_width + gap # bus centerline offset from ring center\n", "\n", " # Two straight buses form an add-drop ring: top is input/through, bottom is drop.\n", " waveguide_top = td.Structure(\n", " geometry=td.Box(center=(0, wg_center_y, 0), size=(td.inf, wg_width, wg_height)),\n", " medium=sin,\n", " )\n", " waveguide_bottom = td.Structure(\n", " geometry=td.Box(\n", " center=(0, -wg_center_y, 0), size=(td.inf, wg_width, wg_height)\n", " ),\n", " medium=sin,\n", " )\n", "\n", " outer = td.Cylinder(\n", " center=(0, 0, 0), axis=2, radius=R + wg_width / 2, length=wg_height\n", " )\n", " inner = td.Cylinder(\n", " center=(0, 0, 0), axis=2, radius=R - wg_width / 2, length=wg_height\n", " )\n", " ring = td.Structure(geometry=outer - inner, medium=sin)\n", "\n", " mode_spec = td.ModeSpec(num_modes=1, target_neff=p.n_sin) # fundamental guided mode\n", " mode_plane = (\n", " 0,\n", " 4 * wg_width,\n", " 6 * wg_height,\n", " ) # port plane spans the waveguide cross-section\n", "\n", " # Excite and measure the fundamental guided mode at the bus ports.\n", " mode_source = td.ModeSource(\n", " size=mode_plane,\n", " center=(-R, wg_center_y, 0),\n", " source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n", " direction=\"+\",\n", " mode_spec=mode_spec,\n", " mode_index=0,\n", " num_freqs=7,\n", " )\n", " mode_through = td.ModeMonitor(\n", " size=mode_plane,\n", " center=(R, wg_center_y, 0),\n", " freqs=freqs,\n", " mode_spec=mode_spec,\n", " name=\"through\",\n", " )\n", " mode_drop = td.ModeMonitor(\n", " size=mode_plane,\n", " center=(-R, -wg_center_y, 0),\n", " freqs=freqs,\n", " mode_spec=mode_spec,\n", " name=\"drop\",\n", " )\n", " field_monitor = td.FieldMonitor(\n", " center=(0, 0, 0),\n", " size=(td.inf, td.inf, 0),\n", " freqs=field_freqs,\n", " name=\"field\",\n", " )\n", "\n", " buffer = p.buffer_um if p.buffer_um is not None else _default_buffer(lda0)\n", " l_x = 2 * R + wg_width + 2 * buffer\n", " l_y = l_x + 2 * gap + 2 * wg_width\n", " l_z = wg_height + 2 * buffer\n", "\n", " return td.Simulation(\n", " center=(0, 0, 0),\n", " size=(l_x, l_y, l_z),\n", " grid_spec=td.GridSpec.auto(\n", " min_steps_per_wvl=p.min_steps_per_wvl, wavelength=lda0\n", " ),\n", " structures=[waveguide_top, waveguide_bottom, ring],\n", " sources=[mode_source],\n", " monitors=[mode_drop, mode_through, field_monitor],\n", " run_time=p.run_time_s,\n", " boundary_spec=td.BoundarySpec(\n", " x=td.Boundary(\n", " plus=td.Absorber(num_layers=60), minus=td.Absorber(num_layers=60)\n", " ),\n", " y=td.Boundary.absorber(),\n", " z=td.Boundary.absorber(),\n", " ),\n", " medium=sio2,\n", " symmetry=(0, 0, 1),\n", " )\n", "\n", "\n", "def analytic_fsr_nm(ring_radius_um: float, n_g: float, lambda_um: float) -> float:\n", " \"\"\"Large-radius estimate FSR ~ lambda^2 / (n_g 2 pi R), returned in nm.\"\"\"\n", " fsr_um = lambda_um**2 / (n_g * 2 * np.pi * ring_radius_um)\n", " return float(1000 * fsr_um)" ] }, { "cell_type": "markdown", "id": "5dc61f78", "metadata": { "id": "5dc61f78" }, "source": [ "### 3.2 Design Parameters\n", "\n", "The sweep below covers radius and gap: radius controls the free spectral ranges (FSRs) and bend loss, while gap controls coupling. Because the large ring size relative to the wavelength results in many\n", "closely packed resonances, we opted to use a Vernier configuration [1] to isolate single wavelengths from\n", "broadband sources. By utilizing two rings with slightly different FSR, a Vernier effect\n", "is created where feedback resonances only overlap at multiples of their individual FSRs. The two radii selected for 3D Vernier verification are `11.5 µm` and `14.5 µm` with a `160 nm` bus-ring gap.\n", "\n", "1. Y. Liu, Z. Qiu, X. Ji, A. Bancora, G. Lihachev, J. Riemensberger, R. N. Wang, A. Voloshin, and T. J.\n", "Kippenberg, “A fully hybrid integrated erbium-based laser,” Nat. Photon., vol. 18, pp. 829–835, Aug.\n", "2024." ] }, { "cell_type": "code", "execution_count": 49, "id": "1523db3f", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:52.144797Z", "iopub.status.busy": "2026-06-22T18:48:52.144695Z", "iopub.status.idle": "2026-06-22T18:48:52.147988Z", "shell.execute_reply": "2026-06-22T18:48:52.147728Z" }, "id": "1523db3f", "outputId": "082110fa-e09e-47a9-ef24-e8fb9e5cbddd" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Band: 0.715-0.750 µm\n", "λ0 = 0.7325 µm, cross-section = 0.5 × 0.22 µm\n", "Analytic FSR estimates with n_g=2.05:\n", " R = 11.5 µm: FSR ≈ 3.62 nm\n", " R = 14.5 µm: FSR ≈ 2.87 nm\n" ] } ], "source": [ "# Set the global geometry, material, spectral, and sweep parameters for the study.\n", "params = SiNMRRParams(\n", " wg_height_um=0.22, # SiN core thickness in z (µm)\n", " wg_width_um=0.50, # SiN bus/ring waveguide width in the xy plane (µm)\n", " lambda_min_um=0.715, # lower edge of the wavelength sweep (µm)\n", " lambda_max_um=0.750, # upper edge of the wavelength sweep (µm)\n", " n_wavelengths=501, # frequency samples for mode monitors; increase for narrower resonances\n", " n_sin=2.0, # constant SiN index used in this tutorial model\n", " n_sio2=1.45, # constant SiO2 cladding index used in this tutorial model\n", " run_time_s=2.5e-11, # FDTD run time; increase if resonances do not decay sufficiently\n", " min_steps_per_wvl=15, # automatic mesh density control\n", ")\n", "\n", "lda_center = 0.5 * (\n", " params.lambda_min_um + params.lambda_max_um\n", ") # band-center wavelength\n", "\n", "# EIA sweep grid. Reduce this list for a quick tutorial run; expand for design screening.\n", "RING_RADII_UM = [11.5, 12.5, 13.5, 14.5] # centerline radii (µm)\n", "GAPS_UM = [0.15, 0.16, 0.17, 0.18] # bus-ring edge gaps (µm)\n", "\n", "# Shortlisted 3D candidates for Vernier comparison.\n", "VERNIER_RADII_UM = (11.5, 14.5) # selected radii with different FSRs\n", "VERNIER_GAP_UM = 0.16 # 160 nm coupling gap used for both final rings\n", "NOTCH_FIT_CENTER_UM = 0.7395 # target notch used to seed local fits\n", "NOTCH_HALF_WIDTH_UM = 0.012 # half-width of local fitting window around target notch\n", "N_GROUP_FOR_KAPPA2 = 2.05 # approximate group index used in κ² and loss estimates\n", "\n", "print(f\"Band: {params.lambda_min_um:.3f}-{params.lambda_max_um:.3f} µm\")\n", "print(\n", " f\"λ0 = {lda_center:.4f} µm, cross-section = {params.wg_width_um} × {params.wg_height_um} µm\"\n", ")\n", "print(\"Analytic FSR estimates with n_g=2.05:\")\n", "for R in VERNIER_RADII_UM:\n", " print(f\" R = {R:4.1f} µm: FSR ≈ {analytic_fsr_nm(R, 2.05, lda_center):.2f} nm\")" ] }, { "cell_type": "markdown", "id": "5592241d", "metadata": { "id": "5592241d" }, "source": [ "### 3.3 Build and Inspect One 3D Reference Ring\n", "\n", "The 2D EIA media are fitted once from a representative 3D reference simulation. Because all rings use the same vertical cross-section and cladding, the fitted core/background effective media can be reused across the radius-gap sweep." ] }, { "cell_type": "code", "execution_count": 50, "id": "d500b6f6", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:52.149422Z", "iopub.status.busy": "2026-06-22T18:48:52.149335Z", "iopub.status.idle": "2026-06-22T18:48:52.247671Z", "shell.execute_reply": "2026-06-22T18:48:52.247409Z" }, "id": "d500b6f6", "outputId": "cef8ea15-84b0-499b-b6d1-c7d9f8343217" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3D reference domain (µm): (24.5255, 25.8455, 1.2455)\n", "Monitors: ['drop', 'through', 'field']\n" ] }, { "data": { "image/png": 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", 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\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Build and plot one representative 3D ring used as the cross-section reference for EIA.\n", "R_REF_UM = VERNIER_RADII_UM[\n", " 0\n", "] # reference radius used only to define the shared vertical stack\n", "G_REF_UM = VERNIER_GAP_UM # same 160 nm gap as the selected 3D candidates\n", "\n", "sim_3d_ref = build_sin_ring_mrr_sim(R_REF_UM, G_REF_UM, params=params)\n", "wg_center_y_ref = (\n", " R_REF_UM + params.wg_width_um + G_REF_UM\n", ") # bottom-bus y coordinate magnitude\n", "\n", "print(\"3D reference domain (µm):\", tuple(round(x, 4) for x in sim_3d_ref.size))\n", "print(\"Monitors:\", [m.name for m in sim_3d_ref.monitors])\n", "\n", "fig, ax = plt.subplots(figsize=(7, 5.5))\n", "sim_3d_ref.plot(z=0, ax=ax)\n", "ax.set_title(f\"3D reference ring: R = {R_REF_UM} µm, gap = {G_REF_UM} µm\")\n", "ax.set_aspect(\"equal\")\n", "plt.tight_layout()\n", "plt.show()\n", "\n", "# For interactive inspection in a notebook environment:\n", "sim_3d_ref.plot_3d()" ] }, { "cell_type": "markdown", "id": "2fbb3470", "metadata": { "id": "2fbb3470" }, "source": [ "### 3.4 Effective-Index Approximation Helpers\n", "\n", "This section follows the variational effective-index approach used in the Tidy3D Effective Index Approximation example. A local vertical mode solve is used to estimate an effective permittivity for the waveguide core and background. Those effective materials are then assigned to a 2D copy of the original 3D simulation." ] }, { "cell_type": "code", "execution_count": 51, "id": "c57f0d72", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:52.249342Z", "iopub.status.busy": "2026-06-22T18:48:52.249213Z", "iopub.status.idle": "2026-06-22T18:48:52.255296Z", "shell.execute_reply": "2026-06-22T18:48:52.255058Z" }, "id": "c57f0d72" }, "outputs": [], "source": [ "# Define EIA utilities: vertical mode sampling, dispersive medium fitting, and 3D-to-2D conversion.\n", "def _trapz_compat(y, x):\n", " \"\"\"Composite trapezoid rule compatible with NumPy 1.x and 2.x.\"\"\"\n", " y, x = np.asarray(y), np.asarray(x)\n", " if hasattr(np, \"trapezoid\"):\n", " return np.trapezoid(y, x=x)\n", " if hasattr(np, \"trapz\"):\n", " return np.trapz(y, x=x)\n", " import scipy.integrate as _spi\n", "\n", " return _spi.trapezoid(y, x=x)\n", "\n", "\n", "def var_eps_eff(\n", " point, ref_point, sim, wavelength=1.55, inf=1000, min_n=1, remote=False\n", "):\n", " \"\"\"Variational effective permittivity at `point` relative to `ref_point`.\"\"\"\n", " freq = td.C_0 / wavelength\n", " sim_2d_center = (ref_point[0], ref_point[1], 0)\n", " sim_2d_size = (0, inf, inf)\n", "\n", " # Reduce the 3D problem to a vertical slice for the slab-mode calculation.\n", " sim_2d = sim.updated_copy(\n", " center=sim_2d_center,\n", " size=sim_2d_size,\n", " sources=[],\n", " monitors=[],\n", " symmetry=(0, 0, 0),\n", " boundary_spec=sim.boundary_spec.updated_copy(x=td.Boundary.periodic()),\n", " )\n", "\n", " mode_solver_plane = td.Box(center=sim_2d.center, size=(td.inf, 0, td.inf))\n", " mode_solver = td.plugins.mode.ModeSolver(\n", " simulation=sim_2d,\n", " plane=mode_solver_plane,\n", " mode_spec=td.ModeSpec(num_modes=1),\n", " freqs=[freq],\n", " )\n", " mode_data_ref = run_mode_solver(mode_solver) if remote else mode_solver.solve()\n", "\n", " n_eff = mode_data_ref.n_eff.item()\n", " if point == ref_point:\n", " return n_eff**2\n", "\n", " x, y = ref_point\n", " eps_ref = sim.epsilon(\n", " box=td.Box(center=(x, y, sim.center[2]), size=(0, 0, td.inf)), freq=freq\n", " )\n", "\n", " x, y = point\n", " eps = sim.epsilon(\n", " box=td.Box(center=(x, y, sim.center[2]), size=(0, 0, td.inf)), freq=freq\n", " )\n", "\n", " eps_dif = np.squeeze(eps.values) - np.squeeze(eps_ref.values)\n", " z_coords = eps_ref.z.values\n", " mode_profile = mode_data_ref.Ex\n", " Mz2 = scipy.interpolate.interp1d(\n", " x=mode_profile.z.values,\n", " y=np.abs(np.squeeze(mode_profile.values)) ** 2,\n", " bounds_error=False,\n", " fill_value=0.0,\n", " )\n", " m_values = Mz2(z_coords)\n", "\n", " num = _trapz_compat(eps_dif * m_values, z_coords)\n", " denom = _trapz_compat(m_values, z_coords)\n", " if denom == 0:\n", " return max(n_eff**2, min_n)\n", " return max(n_eff**2 + num / denom, min_n)\n", "\n", "\n", "def approximate_material(\n", " sim_3d, approx_point, ref_point, spectrum, min_n=1, plot=False, **fit_kwargs\n", "):\n", " \"\"\"Fit a dispersive medium to effective-index samples across `spectrum` in µm.\"\"\"\n", " eps = [\n", " var_eps_eff(approx_point, ref_point, sim_3d, wavelength=wl, min_n=min_n)\n", " for wl in spectrum\n", " ]\n", " e1, e2 = np.real(eps), np.imag(eps)\n", " n = np.sqrt((np.sqrt(e1**2 + e2**2) + e1) / 2)\n", " k = np.sqrt((np.sqrt(e1**2 + e2**2) - e1) / 2)\n", "\n", " fitter = FastDispersionFitter(wvl_um=spectrum, n_data=n, k_data=k)\n", " fit_kwargs.setdefault(\"min_num_poles\", 1)\n", " medium, rms_error = fitter.fit(**fit_kwargs)\n", " print(f\"Fitted medium at {approx_point}: RMS error = {rms_error:.3e}\")\n", "\n", " if plot:\n", " fig, ax = plt.subplots(figsize=(4, 3))\n", " fitter.plot(medium, ax=ax)\n", " ax.set_title(\"Fitted effective medium\")\n", " plt.tight_layout()\n", " plt.show()\n", " return medium\n", "\n", "\n", "def create_2d_sim(sim_3d, core_medium, background_medium):\n", " \"\"\"Collapse a 3D ring simulation into a 2D EIA simulation.\"\"\"\n", " new_structures = [s.updated_copy(medium=core_medium) for s in sim_3d.structures]\n", " new_size = list(sim_3d.size)\n", " new_size[2] = 0\n", " return sim_3d.updated_copy(\n", " size=new_size,\n", " structures=new_structures,\n", " boundary_spec=sim_3d.boundary_spec.updated_copy(z=td.Boundary.periodic()),\n", " medium=background_medium,\n", " symmetry=(0, 0, 0),\n", " )" ] }, { "cell_type": "markdown", "id": "003f6e12", "metadata": { "id": "003f6e12" }, "source": [ "### 3.5 Fit Effective Media Once\n", "\n", "The reference point is placed on the bottom bus waveguide center. The background point is placed at the ring center, where the add-drop ring geometry is SiO2 cladding. The fitted media are reused for all rings in the 2D radius-gap sweep.\n", "\n", "This step uses the local Tidy3D mode solver for the vertical slice calculations, so it does not submit a cloud FDTD task." ] }, { "cell_type": "code", "execution_count": 52, "id": "0f68de7c", "metadata": { "execution": { "iopub.execute_input": "2026-06-22T18:48:52.256723Z", "iopub.status.busy": "2026-06-22T18:48:52.256643Z", "iopub.status.idle": "2026-06-22T18:52:22.683891Z", "shell.execute_reply": "2026-06-22T18:52:22.683609Z" }, "id": "0f68de7c", "outputId": "16a59309-bd7c-455e-b0cc-dc9fa46fcfe9" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "796fb76fe1cb4db6ae153336d50f70f0", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Output()" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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     "text": [
      "Fitted medium at (0.0, -12.16): RMS error = 2.453e-04\n"
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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d9a043b3b4b44c8c983a452cb5d821e7",
       "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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitted medium at (0.0, 0.0): RMS error = 1.160e-05\n"
     ]
    },
    {
     "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": [
    "# Choose core/background sampling points and optionally fit the EIA media.\n",
    "reference_point = (\n",
    "    0.0,\n",
    "    -wg_center_y_ref,\n",
    ")  # point on the bottom bus core, used as EIA reference\n",
    "waveguide_point = reference_point  # fitted core medium samples the same waveguide point\n",
    "background_point = (0.0, 0.0)  # ring center is SiO2 background in this annular geometry\n",
    "\n",
    "spectrum_fit_um = np.linspace(\n",
    "    0.65, 0.80, 71\n",
    ")  # wider fitting band than the simulation band\n",
    "fit_param = AdvancedFastFitterParam(num_iters=100)  # fitter iteration budget\n",
    "\n",
    "# Set FIT_EIA_MEDIA = True to perform local mode solves and material fitting.\n",
    "# Keep False when reading pre-computed results or reviewing the notebook.\n",
    "FIT_EIA_MEDIA = True  # local mode solves only; no cloud FDTD run is submitted here\n",
    "\n",
    "if FIT_EIA_MEDIA:\n",
    "    ring_waveguide_medium = approximate_material(\n",
    "        sim_3d_ref,\n",
    "        waveguide_point,\n",
    "        reference_point,\n",
    "        spectrum_fit_um,\n",
    "        plot=True,\n",
    "        advanced_param=fit_param,\n",
    "    )\n",
    "    ring_background_medium = approximate_material(\n",
    "        sim_3d_ref,\n",
    "        background_point,\n",
    "        reference_point,\n",
    "        spectrum_fit_um,\n",
    "        plot=True,\n",
    "        advanced_param=fit_param,\n",
    "    )\n",
    "    sim_2d_ref = create_2d_sim(\n",
    "        sim_3d_ref, ring_waveguide_medium, ring_background_medium\n",
    "    )\n",
    "\n",
    "    fig, ax = plt.subplots(figsize=(6, 5))\n",
    "    sim_2d_ref.plot_eps(z=0, freq=td.C_0 / lda_center, ax=ax)\n",
    "    ax.set_title(\"2D EIA reference: effective permittivity\")\n",
    "    ax.set_aspect(\"equal\")\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "else:\n",
    "    print(\"Set FIT_EIA_MEDIA = True to fit EIA materials and create sim_2d_ref.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2691efd9",
   "metadata": {
    "id": "2691efd9"
   },
   "source": [
    "### 3.6 Build the 2D Radius-Gap Sweep\n",
    "\n",
    "After fitting `ring_waveguide_medium` and `ring_background_medium`, this cell builds one 2D EIA simulation per $(R, g)$ point. Cost estimation and cloud execution are separated so that the notebook can be reviewed without launching jobs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "275ddf7f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:23.572915Z",
     "iopub.status.busy": "2026-06-22T18:52:23.572839Z",
     "iopub.status.idle": "2026-06-22T18:52:23.576078Z",
     "shell.execute_reply": "2026-06-22T18:52:23.575744Z"
    },
    "id": "275ddf7f",
    "outputId": "299184af-0a70-42df-eede-cc10fc005816"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Built 16 2D EIA simulations.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
16:45:41 -03 Maximum FlexCredit cost: 6.194 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:45:41 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m6.194\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0f73c24e28614cd9925d2cf3a405d11b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estimated maximum FlexCredits for the full 2D EIA sweep: 6.193551554492421\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:45:42 -03 Started working on Batch containing 16 tasks.                      \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:45:42 -03\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m16\u001b[0m tasks.                      \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:46:10 -03 Maximum FlexCredit cost: 6.194 for the whole batch.                \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:46:10 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m6.194\u001b[0m for the whole batch.                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
             Use 'Batch.real_cost()' to get the billed FlexCredit cost after    \n",
       "             completion.                                                        \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after    \n",
       "\u001b[2;36m             \u001b[0mcompletion.                                                        \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "52987d60849742799f9920977d8191d2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
16:53:33 -03 Batch complete.                                                    \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:53:33 -03\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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'sin_mrr_R11.5_g0.15': 'fdve-3979a34c-b963-4d00-8c84-63dcddda9fa0', 'sin_mrr_R11.5_g0.16': 'fdve-fff4e9f3-3151-4ced-96ee-7dfd09925b90', 'sin_mrr_R11.5_g0.17': 'fdve-6781e55c-8df3-4ead-b408-be5a0e3b8ef0', 'sin_mrr_R11.5_g0.18': 'fdve-a33c153e-ce58-4850-8b49-d151ba331b31', 'sin_mrr_R12.5_g0.15': 'fdve-db601b96-2611-4f71-a84c-16bbca0f7948', 'sin_mrr_R12.5_g0.16': 'fdve-a8133221-3eed-4a6d-b806-17c63331eec5', 'sin_mrr_R12.5_g0.17': 'fdve-3ff9b2c6-2829-4db9-9fb4-284c4b5e81ed', 'sin_mrr_R12.5_g0.18': 'fdve-98f46d28-394b-4a6b-bd42-08ed2b751fc0', 'sin_mrr_R13.5_g0.15': 'fdve-a8700d22-0065-4c56-848a-099e94deba57', 'sin_mrr_R13.5_g0.16': 'fdve-88ec04aa-0ffd-485c-b1ca-94abd46f7078', 'sin_mrr_R13.5_g0.17': 'fdve-450b0c01-b3df-4e58-a16d-60561182100f', 'sin_mrr_R13.5_g0.18': 'fdve-845cdbb3-e4f1-459b-b046-fb9e935ab2e1', 'sin_mrr_R14.5_g0.15': 'fdve-8a48ed72-9b22-4ac5-af8d-30546b7046d5', 'sin_mrr_R14.5_g0.16': 'fdve-02d24e7f-7c20-43aa-8225-02bb09ae18b3', 'sin_mrr_R14.5_g0.17': 'fdve-d5ea72d8-1680-4130-9343-d63c94fbf352', 'sin_mrr_R14.5_g0.18': 'fdve-9a7dead4-6c4e-4a0a-b58e-101aa19d43a3'}\n"
     ]
    }
   ],
   "source": [
    "# Build and run the 2D EIA sweep only if the batch results are not already on disk.\n",
    "EIA_BATCH_DIR = (\n",
    "    Path(\"results\") / \"sin_mrr_eia_batch\"\n",
    ")  # where 2D batch results / CSV files are stored\n",
    "sims_2d = {}\n",
    "batch_2d = None  # populated only if a new run is needed\n",
    "estimated_cost_2d = None  # populated by Batch.estimate_cost before running\n",
    "batch_data_2d = None  # populated by the run, or loaded from disk in a later cell\n",
    "\n",
    "if (EIA_BATCH_DIR / \"batch.hdf5\").exists():\n",
    "    print(\"Loading existing 2D EIA sweep results from:\", EIA_BATCH_DIR)\n",
    "elif \"ring_waveguide_medium\" in globals() and \"ring_background_medium\" in globals():\n",
    "    for R in RING_RADII_UM:\n",
    "        for g in GAPS_UM:\n",
    "            name = f\"sin_mrr_R{R:g}_g{g:g}\"\n",
    "            sim3 = build_sin_ring_mrr_sim(R, g, params=params)\n",
    "            sims_2d[name] = create_2d_sim(\n",
    "                sim3, ring_waveguide_medium, ring_background_medium\n",
    "            )\n",
    "    print(f\"Built {len(sims_2d)} 2D EIA simulations.\")\n",
    "\n",
    "    # Estimate the sweep cost before running. This does not time-step the FDTD\n",
    "    # simulation, but it can create cloud task records.\n",
    "    batch_2d = web.Batch(simulations=sims_2d, folder_name=\"sin_mrr_eia_sweep\")\n",
    "    estimated_cost_2d = batch_2d.estimate_cost(verbose=True)\n",
    "    print(\"Estimated maximum FlexCredits for the full 2D EIA sweep:\", estimated_cost_2d)\n",
    "\n",
    "    EIA_BATCH_DIR.mkdir(parents=True, exist_ok=True)\n",
    "    batch_data_2d = batch_2d.run(path_dir=str(EIA_BATCH_DIR))\n",
    "    print(batch_data_2d.task_ids)\n",
    "else:\n",
    "    print(\n",
    "        \"EIA media not available. Run the previous cell with FIT_EIA_MEDIA = True first.\"\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28a4cbb0",
   "metadata": {
    "id": "28a4cbb0"
   },
   "source": [
    "### 3.7 Spectra Extraction and Metrics\n",
    "\n",
    "The same helpers work for 2D EIA and 3D `SimulationData`. The through monitor is read in the forward direction, while the drop monitor is read in the backward direction for this add-drop geometry.\n",
    "\n",
    "The scalar through-notch model is used to estimate loaded quality factor, intrinsic/coupling quality factors, coupling coefficient, FSR, and loss. These estimates are intended for screening and comparison across the sweep; final values should be verified with mesh/time convergence."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05455b9d",
   "metadata": {
    "id": "05455b9d"
   },
   "source": [
    "#### Metric Equations Used in the Sweep\n",
    "\n",
    "For each radius-gap point, the mode monitors return complex modal amplitudes. We analyze the mode power\n",
    "\n",
    "$$\n",
    "T(\\lambda) = |a(\\lambda)|^2.\n",
    "$$\n",
    "\n",
    "The forward `through` monitor is used for the notch, and the backward `drop` monitor is used to estimate peak spacing. The through-port resonance is fit with a symmetric notch model,\n",
    "\n",
    "$$\n",
    "T_{\\mathrm{thru}}(\\lambda) = T_{\\min} + (T_{\\max} - T_{\\min})\n",
    "\\frac{(\\lambda - \\lambda_0)^2}{(\\lambda - \\lambda_0)^2 + w^2}.\n",
    "$$\n",
    "\n",
    "Here, $\\lambda_0$ is the fitted resonance wavelength and $w$ is the half-width parameter. Therefore,\n",
    "\n",
    "$$\n",
    "\\mathrm{FWHM} = 2w,\n",
    "\\qquad\n",
    "Q_L \\approx \\frac{\\lambda_0}{\\mathrm{FWHM}}.\n",
    "$$\n",
    "\n",
    "The free spectral range is estimated from adjacent drop-port peaks,\n",
    "\n",
    "$$\n",
    "\\mathrm{FSR}_{\\lambda} \\approx \\left\\langle \\lambda_{m+1} - \\lambda_m \\right\\rangle,\n",
    "$$\n",
    "\n",
    "and converted to an effective group index estimate through the large-radius ring relation\n",
    "\n",
    "$$\n",
    "n_g \\approx \\frac{\\lambda_0^2}{\\mathrm{FSR}_{\\lambda}\\,2\\pi R}.\n",
    "$$\n",
    "\n",
    "For the symmetric double-bus approximation, the on-resonance through power is related to the ratio $x = \\Gamma_i / \\Gamma_e$, where $\\Gamma_i$ is the intrinsic decay rate and $\\Gamma_e$ is the external decay rate into one bus:\n",
    "\n",
    "$$\n",
    "\\sqrt{T_{\\min}} \\approx \\left|\\frac{x - 2}{x + 2}\\right|.\n",
    "$$\n",
    "\n",
    "The total decay rate is obtained from $Q_L$,\n",
    "\n",
    "$$\n",
    "\\Gamma_{\\mathrm{tot}} = \\frac{\\omega_0}{Q_L},\n",
    "\\qquad\n",
    "\\Gamma_{\\mathrm{tot}} = \\Gamma_i + 2\\Gamma_e.\n",
    "$$\n",
    "\n",
    "This gives\n",
    "\n",
    "$$\n",
    "Q_i = \\frac{\\omega_0}{\\Gamma_i},\n",
    "\\qquad\n",
    "Q_e = \\frac{\\omega_0}{\\Gamma_e}.\n",
    "$$\n",
    "\n",
    "Finally, the approximate power coupling coefficient and intrinsic loss are reported as\n",
    "\n",
    "$$\n",
    "\\kappa^2 \\approx \\frac{n_g L}{\\lambda_0 Q_e},\n",
    "\\qquad\n",
    "L = 2\\pi R,\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\alpha_{\\mathrm{rt}}\\;[\\mathrm{dB/round}] \\approx \\frac{10}{\\ln 10}\\,\\Gamma_i\\tau_{\\mathrm{rt}},\n",
    "\\qquad\n",
    "\\tau_{\\mathrm{rt}} = \\frac{n_g L}{c},\n",
    "$$\n",
    "\n",
    "and\n",
    "\n",
    "$$\n",
    "\\alpha\\;[\\mathrm{dB/cm}] = \\frac{\\alpha_{\\mathrm{rt}}}{L\\;[\\mathrm{cm}]}.\n",
    "$$\n",
    "\n",
    "These expressions are screening metrics: they assume an isolated resonance, a scalar Lorentzian-like notch, and symmetric bus loading. Final reported values should be checked with sufficient spectral resolution, simulation runtime, and mesh convergence.\n",
    "\n",
    "**References**\n",
    "\n",
    "- Tidy3D, [Ring Resonator example](https://www.flexcompute.com/tidy3d/examples/notebooks/RingResonator/).\n",
    "- Tidy3D, [Effective Index Approximation example](https://www.flexcompute.com/tidy3d/examples/notebooks/EffectiveIndexApproximation/).\n",
    "- Tidy3D, [Parameter Scan / Batch example](https://www.flexcompute.com/tidy3d/examples/notebooks/ParameterScan/).\n",
    "- B. E. Little, S. T. Chu, H. A. Haus, J. Foresi, and J.-P. Laine, “Microring resonator channel dropping filters,” *Journal of Lightwave Technology* **15**, 998–1005 (1997).\n",
    "- D. G. Rabus, *Integrated Ring Resonators: The Compendium*, Springer (2007).\n",
    "- J. T. Smith *et al.*, “Silicon nitride microring resonators for visible photonics,” *Optical Materials Express* **13**, 458–470 (2023)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "ab1ac183",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:23.577448Z",
     "iopub.status.busy": "2026-06-22T18:52:23.577310Z",
     "iopub.status.idle": "2026-06-22T18:52:23.591946Z",
     "shell.execute_reply": "2026-06-22T18:52:23.591562Z"
    },
    "id": "ab1ac183"
   },
   "outputs": [],
   "source": [
    "# Define spectral post-processing and resonator metric helpers used for both EIA and 3D data.\n",
    "C_LIGHT = float(td.C_0)\n",
    "\n",
    "\n",
    "def spectrum_mode_power(sim_data, monitor_name: str, direction: str):\n",
    "    # Select one propagation direction from the mode monitor amplitudes.\n",
    "    # For this add-drop layout: through uses direction=\"+\"; drop uses direction=\"-\".\n",
    "    amps = sim_data[monitor_name].amps.sel(mode_index=0, direction=direction)\n",
    "    f = np.asarray(amps.f.values, dtype=float)  # monitor frequencies in Hz\n",
    "    wl = td.C_0 / f  # convert frequency samples to wavelength in µm (Tidy3D units)\n",
    "    power = np.abs(np.asarray(amps.values, dtype=complex)) ** 2  # modal power |a|^2\n",
    "    order = np.argsort(wl)  # sort by increasing wavelength for fitting and plotting\n",
    "    return wl[order], power[order]\n",
    "\n",
    "\n",
    "def parse_task_rg(task_name: str) -> tuple[float, float]:\n",
    "    # Task names encode the sweep parameters, e.g. \"sin_mrr_R11.5_g0.16\".\n",
    "    m = re.match(r\"sin_mrr_R([0-9.]+)_g([0-9.]+)$\", str(task_name))\n",
    "    if not m:\n",
    "        raise ValueError(f\"Unexpected task name: {task_name!r}\")\n",
    "    return float(m.group(1)), float(m.group(2))  # radius R (µm), gap g (µm)\n",
    "\n",
    "\n",
    "def coupling_regime(x: float, band: float = 0.12) -> str:\n",
    "    # x = Gamma_i / Gamma_e for one bus in the symmetric double-bus model.\n",
    "    # Critical through-port extinction occurs near x = 2, so we classify around that value.\n",
    "    if not np.isfinite(x) or x <= 0:\n",
    "        return \"invalid\"\n",
    "    if x > 2.0 + band:\n",
    "        return \"undercoupled\"  # intrinsic loss dominates relative to one-bus loading\n",
    "    if x < 2.0 - band:\n",
    "        return \"overcoupled\"  # external coupling dominates relative to intrinsic loss\n",
    "    return \"critical\"  # near the through-null condition\n",
    "\n",
    "\n",
    "def loss_db_per_cm(loss_db_per_round: float, R_um: float) -> float:\n",
    "    # Convert round-trip loss to propagation loss by dividing by circumference in cm.\n",
    "    if not np.isfinite(loss_db_per_round):\n",
    "        return float(\"nan\")\n",
    "    circumference_cm = 2 * np.pi * float(R_um) * 1e-4  # µm -> cm conversion\n",
    "    return float(loss_db_per_round) / circumference_cm\n",
    "\n",
    "\n",
    "def _notch_seed_index(wl_um, T, prefer_lambda_um=None):\n",
    "    # Choose an initial notch center for nonlinear fitting.\n",
    "    wl_um, T = np.asarray(wl_um, dtype=float), np.asarray(T, dtype=float)\n",
    "    if prefer_lambda_um is None or not np.isfinite(float(prefer_lambda_um)):\n",
    "        return int(\n",
    "            np.argmin(T)\n",
    "        )  # no target wavelength: seed at the deepest through dip\n",
    "    t_rng = float(np.nanmax(T) - np.nanmin(T))  # dynamic range of the trace\n",
    "    prom = (\n",
    "        max(1e-12, 0.015 * t_rng) if t_rng > 0 else 1e-12\n",
    "    )  # small prominence threshold\n",
    "    loc, _ = signal.find_peaks(\n",
    "        -T, prominence=prom, distance=max(1, len(T) // 250)\n",
    "    )  # dips in T\n",
    "    if len(loc) == 0:\n",
    "        return int(np.argmin(T))  # fallback if peak finding misses shallow notches\n",
    "    return int(\n",
    "        loc[int(np.argmin(np.abs(wl_um[loc] - float(prefer_lambda_um))))]\n",
    "    )  # nearest local dip\n",
    "\n",
    "\n",
    "def notch_through_power(wl, Tmax, Tmin, lam0, w):\n",
    "    # Symmetric all-pass notch model in power. `w` is the half-width parameter in µm.\n",
    "    wl = np.asarray(wl, dtype=float)\n",
    "    return Tmin + (Tmax - Tmin) * (wl - lam0) ** 2 / ((wl - lam0) ** 2 + w**2)\n",
    "\n",
    "\n",
    "def fit_through_notch_near(wl_um, T_through, lambda_target_um, half_width_um=0.012):\n",
    "    # Restrict the fit to a target wavelength window so dense spectra do not pick the wrong notch.\n",
    "    wl_um, T = np.asarray(wl_um, dtype=float), np.asarray(T_through, dtype=float)\n",
    "    order = np.argsort(wl_um)\n",
    "    wl_um, T = wl_um[order], T[order]\n",
    "\n",
    "    half = float(half_width_um)  # start with the user-selected fitting half-window\n",
    "    for _ in range(10):\n",
    "        mask = (wl_um >= lambda_target_um - half) & (\n",
    "            wl_um <= lambda_target_um + half\n",
    "        )  # local fit window\n",
    "        if np.count_nonzero(mask) >= 24:  # enough samples for stable nonlinear fitting\n",
    "            break\n",
    "        half *= 1.35  # enlarge the window if the wavelength grid is too sparse\n",
    "    if np.count_nonzero(mask) >= 8:\n",
    "        wl_fit, T_fit = wl_um[mask], T[mask]  # fit only near the target resonance\n",
    "    else:\n",
    "        wl_fit, T_fit = (\n",
    "            wl_um,\n",
    "            T,\n",
    "        )  # fallback: use the whole spectrum if the window is undersampled\n",
    "\n",
    "    i_min = _notch_seed_index(\n",
    "        wl_fit, T_fit, lambda_target_um\n",
    "    )  # initial resonance index\n",
    "    lam0 = float(wl_fit[i_min])  # initial resonance wavelength\n",
    "    Tmin0 = float(T_fit[i_min])  # initial notch floor\n",
    "    Tmax0 = float(np.percentile(T_fit, 98))  # robust off-resonance baseline estimate\n",
    "    span = float(np.max(wl_fit) - np.min(wl_fit))  # fit-domain wavelength span\n",
    "    if Tmax0 <= Tmin0 + 1e-12 or span <= 0:\n",
    "        return None  # invalid trace or fit window\n",
    "\n",
    "    p0 = [Tmax0, Tmin0, lam0, max(span / 120, 1e-9)]  # initial [Tmax, Tmin, λ0, w]\n",
    "    bounds = (\n",
    "        [Tmin0 + 1e-9, 0.0, np.min(wl_fit), 1e-12],  # lower bounds\n",
    "        [\n",
    "            min(Tmax0 * 1.5 + 0.1, 10.0),\n",
    "            min(Tmax0, np.max(T_fit)),\n",
    "            np.max(wl_fit),\n",
    "            span,\n",
    "        ],  # upper bounds\n",
    "    )\n",
    "    try:\n",
    "        popt, _ = curve_fit(\n",
    "            notch_through_power, wl_fit, T_fit, p0=p0, bounds=bounds, maxfev=25000\n",
    "        )\n",
    "        Tmax, Tmin, l0, w = map(\n",
    "            float, popt\n",
    "        )  # fitted baseline, floor, center, and half-width\n",
    "        if w <= 0 or Tmax <= Tmin:\n",
    "            return None  # reject nonphysical fits\n",
    "        return {\n",
    "            \"Tmax\": Tmax,\n",
    "            \"Tmin\": Tmin,\n",
    "            \"lam0\": l0,\n",
    "            \"w_um\": w,\n",
    "            \"fwhm_um\": 2 * w,\n",
    "        }  # FWHM = 2w\n",
    "    except Exception:\n",
    "        return None  # fitting can fail for flat/noisy traces\n",
    "\n",
    "\n",
    "def mean_fsr_nm_from_drop_peaks(wl_um, T_drop, prominence_rel=0.04):\n",
    "    # Use drop-port peaks to estimate resonance spacing in wavelength.\n",
    "    wl_um, T = np.asarray(wl_um, dtype=float), np.asarray(T_drop, dtype=float)\n",
    "    prom = max(\n",
    "        float(prominence_rel) * (float(np.max(T)) - float(np.min(T))), 1e-12\n",
    "    )  # adaptive peak prominence\n",
    "    peaks, _ = signal.find_peaks(T, prominence=prom)  # drop resonances appear as peaks\n",
    "    if len(peaks) < 2:\n",
    "        return float(\"nan\"), int(len(peaks))  # need at least two peaks for an FSR\n",
    "    peak_wl = np.sort(wl_um[peaks])  # sort peak wavelengths before differencing\n",
    "    return float(np.mean(np.diff(peak_wl)) * 1000), int(\n",
    "        len(peaks)\n",
    "    )  # convert µm spacing to nm\n",
    "\n",
    "\n",
    "def n_g_from_fsr(lambda_um, R_um, fsr_nm):\n",
    "    # Rearranged large-radius relation: FSR ≈ λ² / (n_g 2πR).\n",
    "    if not np.isfinite(fsr_nm) or fsr_nm <= 0:\n",
    "        return float(\"nan\")\n",
    "    fsr_um = fsr_nm / 1000  # nm -> µm to match λ and R units\n",
    "    return float(lambda_um**2 / (fsr_um * 2 * np.pi * R_um))\n",
    "\n",
    "\n",
    "def x_from_sqrt_Tthrough(r):\n",
    "    # Invert sqrt(Tmin) ≈ |(x - 2) / (x + 2)| for x = Gamma_i / Gamma_e.\n",
    "    r = float(\n",
    "        np.clip(r, 0.0, 1.0 - 1e-15)\n",
    "    )  # keep the algebra away from singular values\n",
    "    candidates = []\n",
    "    if r < 1.0 - 1e-12:\n",
    "        candidates.append((2.0 + 2.0 * r) / (1.0 - r))  # branch with x > 2\n",
    "    candidates.append((2.0 - 2.0 * r) / (1.0 + r))  # branch with x < 2\n",
    "    best_x, best_err = np.nan, np.inf\n",
    "    for x in candidates:\n",
    "        if x <= 0 or not np.isfinite(x):\n",
    "            continue\n",
    "        err = abs(abs(x - 2.0) / (x + 2.0) - r)  # choose branch that best reproduces r\n",
    "        if err < best_err:\n",
    "            best_x, best_err = x, err\n",
    "    return float(best_x)\n",
    "\n",
    "\n",
    "def ring_metrics_row(\n",
    "    task_name,\n",
    "    R_um,\n",
    "    gap_um,\n",
    "    wl_um,\n",
    "    T_drop,\n",
    "    T_through,\n",
    "    *,\n",
    "    lambda_fit_target_um,\n",
    "    notch_half_width_um=0.012,\n",
    "    n_group_for_kappa2=2.05,\n",
    "):\n",
    "    # Combine notch fitting, FSR extraction, coupling split, and loss estimates into one table row.\n",
    "    fit = fit_through_notch_near(\n",
    "        wl_um, T_through, lambda_fit_target_um, half_width_um=notch_half_width_um\n",
    "    )\n",
    "    if fit is None:\n",
    "        return {\n",
    "            \"task\": task_name,\n",
    "            \"R_um\": R_um,\n",
    "            \"gap_um\": gap_um,\n",
    "            \"model_note\": \"notch_fit_failed\",\n",
    "        }\n",
    "\n",
    "    lam0 = fit[\"lam0\"]  # fitted resonance wavelength (µm)\n",
    "    Q_L = (\n",
    "        lam0 / fit[\"fwhm_um\"] if fit[\"fwhm_um\"] > 0 else float(\"nan\")\n",
    "    )  # loaded Q from linewidth\n",
    "    omega0 = 2 * np.pi * (C_LIGHT / lam0)  # angular frequency in Tidy3D unit convention\n",
    "    Gamma_tot = (\n",
    "        omega0 / Q_L if np.isfinite(Q_L) and Q_L > 0 else float(\"nan\")\n",
    "    )  # total decay rate\n",
    "    fsr_nm, n_peaks = mean_fsr_nm_from_drop_peaks(\n",
    "        wl_um, T_drop\n",
    "    )  # mean drop-peak spacing\n",
    "    n_g_meas = n_g_from_fsr(\n",
    "        lam0, R_um, fsr_nm\n",
    "    )  # group index inferred from measured FSR\n",
    "\n",
    "    Tmin_fit = float(\n",
    "        np.clip(fit[\"Tmin\"], 1e-15, 1.0)\n",
    "    )  # avoid exact zero before sqrt/inversion\n",
    "    x = x_from_sqrt_Tthrough(np.sqrt(Tmin_fit))  # intrinsic-to-external decay ratio\n",
    "\n",
    "    row = {\n",
    "        \"task\": task_name,  # original simulation / batch task name\n",
    "        \"R_um\": R_um,  # ring centerline radius\n",
    "        \"gap_um\": gap_um,  # bus-ring edge gap\n",
    "        \"lambda0_um\": lam0,  # fitted through-notch center\n",
    "        \"fwhm_nm\": 1000 * fit[\"fwhm_um\"],  # linewidth converted from µm to nm\n",
    "        \"Q_loaded\": Q_L,  # loaded quality factor\n",
    "        \"T_through_min_fit\": Tmin_fit,  # fitted on-resonance through power\n",
    "        \"T_through_max_fit\": float(fit[\"Tmax\"]),  # fitted off-resonance through power\n",
    "        \"mean_fsr_nm_peaks\": fsr_nm,  # mean drop peak spacing\n",
    "        \"n_drop_peaks\": n_peaks,  # number of drop peaks used for FSR\n",
    "        \"n_group_from_fsr\": n_g_meas,  # effective group index from FSR\n",
    "        \"Q_intrinsic\": np.nan,  # filled after decay-rate split\n",
    "        \"Q_coupling\": np.nan,  # filled after decay-rate split\n",
    "        \"kappa2_power\": np.nan,  # filled after Q_e is available\n",
    "        \"kappa_amplitude\": np.nan,  # sqrt(kappa2_power)\n",
    "        \"loss_dB_per_round\": np.nan,  # intrinsic round-trip loss\n",
    "        \"loss_dB_per_cm\": np.nan,  # propagation loss normalized by circumference\n",
    "        \"Gamma_over_Gamma_e\": x,  # x = Gamma_i / Gamma_e\n",
    "        \"coupling_regime\": \"invalid\",  # filled after validating x\n",
    "        \"model_note\": \"ok\",  # diagnostic note for failed fits/models\n",
    "    }\n",
    "    if not np.isfinite(Gamma_tot) or not np.isfinite(x):\n",
    "        row[\"model_note\"] = \"notch_or_split_model_failed\"\n",
    "        return row\n",
    "\n",
    "    Gamma_e = Gamma_tot / (\n",
    "        x + 2.0\n",
    "    )  # one-bus external decay rate from Gamma_tot = Gamma_i + 2 Gamma_e\n",
    "    Gamma_i = x * Gamma_e  # intrinsic decay rate\n",
    "    Q_i = omega0 / Gamma_i if Gamma_i > 0 else float(\"nan\")  # intrinsic Q\n",
    "    Q_e = omega0 / Gamma_e if Gamma_e > 0 else float(\"nan\")  # coupling Q per bus\n",
    "    L_rt_um = 2 * np.pi * R_um  # ring circumference in µm\n",
    "    tau_rt = n_group_for_kappa2 * L_rt_um / C_LIGHT  # approximate round-trip time\n",
    "    kappa2 = (\n",
    "        (n_group_for_kappa2 * L_rt_um) / (lam0 * Q_e)\n",
    "        if np.isfinite(Q_e) and Q_e > 0\n",
    "        else float(\"nan\")\n",
    "    )  # power coupling\n",
    "    loss_rt_db = (\n",
    "        (10.0 / np.log(10.0)) * Gamma_i * tau_rt if Gamma_i > 0 else float(\"nan\")\n",
    "    )  # dB per round trip\n",
    "\n",
    "    row.update(\n",
    "        Q_intrinsic=Q_i,  # intrinsic loss-limited Q\n",
    "        Q_coupling=Q_e,  # external coupling Q for one bus\n",
    "        kappa2_power=kappa2,  # estimated power coupling coefficient\n",
    "        kappa_amplitude=float(np.sqrt(kappa2))\n",
    "        if np.isfinite(kappa2) and kappa2 >= 0\n",
    "        else float(\"nan\"),\n",
    "        loss_dB_per_round=loss_rt_db,  # intrinsic loss per round trip\n",
    "        loss_dB_per_cm=loss_db_per_cm(loss_rt_db, R_um),  # normalized propagation loss\n",
    "        coupling_regime=coupling_regime(x),  # under / critical / over-coupled label\n",
    "    )\n",
    "    return row"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86f2c826",
   "metadata": {
    "id": "86f2c826"
   },
   "source": [
    "### 3.8 Load and Plot 2D EIA Sweep Results\n",
    "\n",
    "If you have already run the 2D batch, place the saved `batch.hdf5` directory under `results/sin_mrr_eia_batch/` or set `EIA_BATCH_DIR` below. The cell extracts spectra, estimates FSR from drop peaks, computes notch metrics, and exports a compact CSV table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "9f47dbb7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:23.593495Z",
     "iopub.status.busy": "2026-06-22T18:52:23.593349Z",
     "iopub.status.idle": "2026-06-22T18:52:28.417411Z",
     "shell.execute_reply": "2026-06-22T18:52:28.417117Z"
    },
    "id": "9f47dbb7",
    "outputId": "2927ee7f-a6d0-42a9-fa70-42500c618d00"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 16 EIA spectra.\n",
      "Wrote 16 metric rows to results/sin_mrr_eia_batch/community_eia_notch_metrics.csv\n"
     ]
    }
   ],
   "source": [
    "# Load a completed 2D batch, extract spectra, compute metrics, and export a CSV summary.\n",
    "def load_batch_data(path_dir: Path):\n",
    "    if (path_dir / \"batch.hdf5\").is_file() or path_dir.is_dir():\n",
    "        try:\n",
    "            return BatchData.load(path_dir=str(path_dir))\n",
    "        except Exception as exc:\n",
    "            print(f\"Could not load BatchData from {path_dir}: {exc}\")\n",
    "    return None\n",
    "\n",
    "\n",
    "batch_data_2d = globals().get(\n",
    "    \"batch_data_2d\", None\n",
    ")  # reuse in-memory results if this kernel ran the batch\n",
    "if batch_data_2d is None:\n",
    "    batch_data_2d = load_batch_data(\n",
    "        EIA_BATCH_DIR\n",
    "    )  # otherwise try loading saved results from disk\n",
    "\n",
    "case_results = {}  # spectra and metadata keyed by task name\n",
    "# Convert each SimulationData object into sorted wavelength/power arrays for analysis.\n",
    "if batch_data_2d is not None:\n",
    "    for name, sim_data in batch_data_2d.items():\n",
    "        R, g = parse_task_rg(name)\n",
    "        wl_drop, T_drop = spectrum_mode_power(sim_data, \"drop\", \"-\")\n",
    "        wl_through, T_through = spectrum_mode_power(sim_data, \"through\", \"+\")\n",
    "        case_results[name] = {\n",
    "            \"R\": R,\n",
    "            \"gap\": g,\n",
    "            \"wl\": wl_drop,\n",
    "            \"T_drop\": T_drop,\n",
    "            \"T_through\": np.interp(wl_drop, wl_through, T_through),\n",
    "        }\n",
    "    print(f\"Loaded {len(case_results)} EIA spectra.\")\n",
    "else:\n",
    "    print(\n",
    "        \"No EIA BatchData loaded. Run the batch or point EIA_BATCH_DIR to saved results.\"\n",
    "    )\n",
    "\n",
    "metric_rows = []  # one notch/FSR/Q/loss row per 2D sweep case\n",
    "for name, d in case_results.items():\n",
    "    metric_rows.append(\n",
    "        ring_metrics_row(\n",
    "            name,\n",
    "            d[\"R\"],\n",
    "            d[\"gap\"],\n",
    "            d[\"wl\"],\n",
    "            d[\"T_drop\"],\n",
    "            d[\"T_through\"],\n",
    "            lambda_fit_target_um=NOTCH_FIT_CENTER_UM,  # choose the local notch closest to this wavelength\n",
    "            notch_half_width_um=NOTCH_HALF_WIDTH_UM,  # fitting window around the target notch\n",
    "            n_group_for_kappa2=N_GROUP_FOR_KAPPA2,  # approximate group index for κ² / loss conversion\n",
    "        )\n",
    "    )\n",
    "\n",
    "if metric_rows:\n",
    "    csv_path = EIA_BATCH_DIR / \"community_eia_notch_metrics.csv\"\n",
    "    csv_path.parent.mkdir(parents=True, exist_ok=True)\n",
    "    with csv_path.open(\"w\", newline=\"\") as fp:\n",
    "        writer = csv.DictWriter(\n",
    "            fp, fieldnames=list(metric_rows[0].keys()), extrasaction=\"ignore\"\n",
    "        )\n",
    "        writer.writeheader()\n",
    "        writer.writerows(metric_rows)\n",
    "    print(f\"Wrote {len(metric_rows)} metric rows to {csv_path}\")\n",
    "else:\n",
    "    print(\"No metric rows to export.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "b655de38",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:28.418428Z",
     "iopub.status.busy": "2026-06-22T18:52:28.418331Z",
     "iopub.status.idle": "2026-06-22T18:52:28.528579Z",
     "shell.execute_reply": "2026-06-22T18:52:28.528227Z"
    },
    "id": "b655de38",
    "outputId": "bd7ac8fa-2ce3-447e-99fe-450c0227c94e"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot representative 2D EIA spectra for the two ring radii chosen for Vernier verification.\n",
    "if case_results:\n",
    "    fig, ax = plt.subplots(figsize=(9, 4.5))\n",
    "    for R in VERNIER_RADII_UM:\n",
    "        key = f\"sin_mrr_R{R:g}_g{VERNIER_GAP_UM:g}\"  # matches the task naming convention used above\n",
    "        if key not in case_results:\n",
    "            print(f\"Missing {key}\")\n",
    "            continue\n",
    "        d = case_results[key]\n",
    "        ax.plot(d[\"wl\"], d[\"T_drop\"], lw=1.5, label=f\"R = {R:g} µm, drop\")\n",
    "        ax.plot(\n",
    "            d[\"wl\"],\n",
    "            d[\"T_through\"],\n",
    "            ls=\"--\",\n",
    "            lw=1.1,\n",
    "            alpha=0.7,\n",
    "            label=f\"R = {R:g} µm, through\",\n",
    "        )\n",
    "    ax.set_xlabel(\"Wavelength (µm)\")\n",
    "    ax.set_ylabel(r\"Mode power $|a|^2$\")\n",
    "    ax.set_title(\"2D EIA spectra for Vernier candidate rings\")\n",
    "    ax.grid(True, alpha=0.3)\n",
    "    ax.legend(ncol=2, fontsize=8)\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "else:\n",
    "    print(\"Run/load the EIA batch before plotting spectra.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05085167",
   "metadata": {
    "id": "05085167"
   },
   "source": [
    "#### Sweep Plots at Fixed Radius and Fixed Gap\n",
    "\n",
    "The next cell reproduces the sweep-style plots:\n",
    "\n",
    "- **Fixed radius, sweep gap:** the upper panel overlays all drop/through spectra for one radius while the lower panel shows how the estimated coupling coefficient $\\kappa^2$ changes with gap.\n",
    "- **Fixed gap, sweep radius:** the upper panel overlays all drop/through spectra for one gap while the lower panel shows how the FSR changes with radius."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "cbffb88c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:28.529943Z",
     "iopub.status.busy": "2026-06-22T18:52:28.529820Z",
     "iopub.status.idle": "2026-06-22T18:52:29.150373Z",
     "shell.execute_reply": "2026-06-22T18:52:29.150010Z"
    },
    "id": "cbffb88c",
    "outputId": "ba9c5062-4543-48ec-be7b-069255e90b9d"
   },
   "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": [
    "# Plot all sweep spectra at fixed R or fixed gap, with a metric trend in the bottom panel.\n",
    "from matplotlib.collections import LineCollection\n",
    "from matplotlib.colors import LinearSegmentedColormap, Normalize\n",
    "\n",
    "\n",
    "def cmap_blue_violet_pink():\n",
    "    # Same visual style as the development sweep notebook: blue -> violet -> pink.\n",
    "    return LinearSegmentedColormap.from_list(\n",
    "        \"blue_violet_pink\",\n",
    "        [\"#2563eb\", \"#7c3aed\", \"#ec4899\"],\n",
    "    )\n",
    "\n",
    "\n",
    "def norm_span(values):\n",
    "    # Normalize sweep values for color mapping; pad zero-width ranges to avoid division by zero.\n",
    "    values = np.asarray(values, dtype=float)\n",
    "    if values.size == 0:\n",
    "        return Normalize(0.0, 1.0)\n",
    "    vmin, vmax = float(np.nanmin(values)), float(np.nanmax(values))\n",
    "    if np.isclose(vmin, vmax):\n",
    "        pad = max(abs(vmin) * 0.05, 1e-3)\n",
    "        vmin, vmax = vmin - pad, vmax + pad\n",
    "    return Normalize(vmin, vmax)\n",
    "\n",
    "\n",
    "def plot_metric_curve_colored(ax, x, y, *, xlabel, ylabel, title):\n",
    "    # Draw a bottom-panel metric curve with the same blue-violet-pink map used for spectra.\n",
    "    x = np.asarray(x, dtype=float)\n",
    "    y = np.asarray(y, dtype=float)\n",
    "    ok = np.isfinite(x) & np.isfinite(y)\n",
    "    if np.count_nonzero(ok) == 0:\n",
    "        ax.text(\n",
    "            0.5, 0.5, \"No finite data\", ha=\"center\", va=\"center\", transform=ax.transAxes\n",
    "        )\n",
    "        ax.set_xlabel(xlabel)\n",
    "        ax.set_ylabel(ylabel)\n",
    "        ax.set_title(title)\n",
    "        return None\n",
    "    x, y = x[ok], y[ok]\n",
    "    order = np.argsort(x)\n",
    "    x, y = x[order], y[order]\n",
    "    cmap = cmap_blue_violet_pink()\n",
    "    norm = norm_span(x)\n",
    "    if len(x) >= 2:\n",
    "        # Color each line segment by its midpoint x value, matching the marker/colorbar scale.\n",
    "        points = np.column_stack([x, y]).reshape(-1, 1, 2)\n",
    "        segments = np.concatenate([points[:-1], points[1:]], axis=1)\n",
    "        segment_values = 0.5 * (x[:-1] + x[1:])\n",
    "        lc = LineCollection(segments, cmap=cmap, norm=norm, linewidth=2.0, zorder=1)\n",
    "        lc.set_array(segment_values)\n",
    "        ax.add_collection(lc)\n",
    "    ax.scatter(\n",
    "        x, y, c=x, cmap=cmap, norm=norm, s=44, edgecolor=\"k\", linewidth=0.35, zorder=2\n",
    "    )\n",
    "    ax.set_xlabel(xlabel)\n",
    "    ax.set_ylabel(ylabel)\n",
    "    ax.set_title(title)\n",
    "    ax.grid(True, alpha=0.3)\n",
    "    sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)\n",
    "    sm.set_array([])\n",
    "    return sm\n",
    "\n",
    "\n",
    "if not case_results:\n",
    "    raise RuntimeError(\n",
    "        \"case_results is empty — load or run the 2D EIA batch before plotting sweeps.\"\n",
    "    )\n",
    "if not metric_rows:\n",
    "    raise RuntimeError(\n",
    "        \"metric_rows is empty — run the metrics extraction cell before plotting sweeps.\"\n",
    "    )\n",
    "\n",
    "metric_by_task = {\n",
    "    row[\"task\"]: row for row in metric_rows\n",
    "}  # metric lookup for bottom panels\n",
    "cmap_lines = cmap_blue_violet_pink()\n",
    "\n",
    "# You can override these before re-running the cell.\n",
    "ANALYSIS_R_FIXED = globals().get(\n",
    "    \"ANALYSIS_R_FIXED\", VERNIER_RADII_UM[0]\n",
    ")  # fixed radius for gap sweep\n",
    "ANALYSIS_GAP_FIXED = globals().get(\n",
    "    \"ANALYSIS_GAP_FIXED\", VERNIER_GAP_UM\n",
    ")  # fixed gap for radius sweep\n",
    "\n",
    "# --- Figure 1: fixed R, sweep gap; bottom panel shows coupling vs gap. ---\n",
    "R_fix = float(ANALYSIS_R_FIXED)\n",
    "g_plotted = [g for g in GAPS_UM if f\"sin_mrr_R{R_fix:g}_g{g:g}\" in case_results]\n",
    "norm_g = norm_span(g_plotted if g_plotted else GAPS_UM)\n",
    "\n",
    "fig, axes = plt.subplots(\n",
    "    2,\n",
    "    1,\n",
    "    figsize=(9.5, 7.2),\n",
    "    gridspec_kw={\"height_ratios\": [2.2, 1]},\n",
    "    constrained_layout=True,  # keeps the colorbar outside the data axes\n",
    ")\n",
    "ax_top, ax_bot = axes\n",
    "g_vals, kappa2_vals = [], []\n",
    "for g in GAPS_UM:\n",
    "    key = f\"sin_mrr_R{R_fix:g}_g{g:g}\"  # task name for this fixed-radius, variable-gap case\n",
    "    if key not in case_results:\n",
    "        continue\n",
    "    d = case_results[key]\n",
    "    c = cmap_lines(norm_g(g))  # color encodes gap\n",
    "    ax_top.plot(d[\"wl\"], d[\"T_drop\"], color=c, lw=1.4, label=f\"gap = {g:g} µm\")\n",
    "    ax_top.plot(d[\"wl\"], d[\"T_through\"], color=c, ls=\"--\", alpha=0.42, lw=1.1)\n",
    "    row = metric_by_task.get(key, {})\n",
    "    g_vals.append(g)\n",
    "    kappa2_vals.append(\n",
    "        row.get(\"kappa2_power\", np.nan)\n",
    "    )  # coupling should change strongly with gap\n",
    "\n",
    "ax_top.set_xlabel(\"Wavelength (µm)\")\n",
    "ax_top.set_ylabel(r\"Mode power $|a|^2$\")\n",
    "ax_top.set_title(f\"Fixed R = {R_fix:g} µm — solid: drop, dashed: through\")\n",
    "ax_top.legend(loc=\"best\", fontsize=8)\n",
    "ax_top.grid(True, alpha=0.3)\n",
    "\n",
    "sm_gap = plot_metric_curve_colored(\n",
    "    ax_bot,\n",
    "    g_vals,\n",
    "    kappa2_vals,\n",
    "    xlabel=\"gap (µm)\",\n",
    "    ylabel=r\"$\\kappa^2$ (power coupling)\",\n",
    "    title=\"Coupling vs gap (same fixed R)\",\n",
    ")\n",
    "if sm_gap is not None:\n",
    "    # Attach the colorbar to the upper spectra panel only; this prevents overlap with the bottom metric panel.\n",
    "    cbar_gap = fig.colorbar(sm_gap, ax=ax_top, shrink=0.9, pad=0.018)\n",
    "    cbar_gap.set_label(\"gap (µm)\")\n",
    "plt.show()\n",
    "\n",
    "# --- Figure 2: fixed gap, sweep R; bottom panel shows FSR vs R. ---\n",
    "g_fix = float(ANALYSIS_GAP_FIXED)\n",
    "R_plotted = [R for R in RING_RADII_UM if f\"sin_mrr_R{R:g}_g{g_fix:g}\" in case_results]\n",
    "norm_R = norm_span(R_plotted if R_plotted else RING_RADII_UM)\n",
    "\n",
    "fig, axes = plt.subplots(\n",
    "    2,\n",
    "    1,\n",
    "    figsize=(9.5, 7.2),\n",
    "    gridspec_kw={\"height_ratios\": [2.2, 1]},\n",
    "    constrained_layout=True,  # keeps the colorbar outside the data axes\n",
    ")\n",
    "ax_top, ax_bot = axes\n",
    "R_vals, fsr_vals = [], []\n",
    "for R in RING_RADII_UM:\n",
    "    key = f\"sin_mrr_R{R:g}_g{g_fix:g}\"  # task name for this fixed-gap, variable-radius case\n",
    "    if key not in case_results:\n",
    "        continue\n",
    "    d = case_results[key]\n",
    "    c = cmap_lines(norm_R(R))  # color encodes radius\n",
    "    ax_top.plot(d[\"wl\"], d[\"T_drop\"], color=c, lw=1.4, label=f\"R = {R:g} µm\")\n",
    "    ax_top.plot(d[\"wl\"], d[\"T_through\"], color=c, ls=\"--\", alpha=0.42, lw=1.1)\n",
    "    row = metric_by_task.get(key, {})\n",
    "    R_vals.append(R)\n",
    "    fsr_vals.append(\n",
    "        row.get(\"mean_fsr_nm_peaks\", np.nan)\n",
    "    )  # FSR should decrease as R increases\n",
    "\n",
    "ax_top.set_xlabel(\"Wavelength (µm)\")\n",
    "ax_top.set_ylabel(r\"Mode power $|a|^2$\")\n",
    "ax_top.set_title(f\"Fixed gap = {g_fix:g} µm — solid: drop, dashed: through\")\n",
    "ax_top.legend(loc=\"best\", fontsize=8)\n",
    "ax_top.grid(True, alpha=0.3)\n",
    "\n",
    "sm_R = plot_metric_curve_colored(\n",
    "    ax_bot,\n",
    "    R_vals,\n",
    "    fsr_vals,\n",
    "    xlabel=\"R (µm)\",\n",
    "    ylabel=\"mean FSR from drop peaks (nm)\",\n",
    "    title=\"FSR vs R (same fixed gap)\",\n",
    ")\n",
    "if sm_R is not None:\n",
    "    # Attach the colorbar to the upper spectra panel only; this prevents overlap with the bottom metric panel.\n",
    "    cbar_R = fig.colorbar(sm_R, ax=ax_top, shrink=0.9, pad=0.018)\n",
    "    cbar_R.set_label(\"R (µm)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "069d93f9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:29.152087Z",
     "iopub.status.busy": "2026-06-22T18:52:29.151949Z",
     "iopub.status.idle": "2026-06-22T18:52:29.574396Z",
     "shell.execute_reply": "2026-06-22T18:52:29.573984Z"
    },
    "id": "069d93f9",
    "outputId": "eae5f8d9-48ad-4834-ffe7-d0fa2ca31915"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Convert the sweep metric rows into radius-gap grids and plot compact heatmap summaries.\n",
    "def _metric_grid(rows, key):\n",
    "    Rs = np.array(sorted({float(r[\"R_um\"]) for r in rows}))\n",
    "    gs = np.array(sorted({float(r[\"gap_um\"]) for r in rows}))\n",
    "    Z = np.full((len(gs), len(Rs)), np.nan)\n",
    "    for row in rows:\n",
    "        i = np.where(gs == float(row[\"gap_um\"]))[0][0]\n",
    "        j = np.where(Rs == float(row[\"R_um\"]))[0][0]\n",
    "        Z[i, j] = float(row.get(key, np.nan))\n",
    "    return Rs, gs, Z\n",
    "\n",
    "\n",
    "if metric_rows:\n",
    "    keys = [\n",
    "        \"Q_loaded\",\n",
    "        \"Q_intrinsic\",\n",
    "        \"mean_fsr_nm_peaks\",\n",
    "        \"loss_dB_per_cm\",\n",
    "        \"kappa2_power\",\n",
    "    ]\n",
    "    titles = [r\"$Q_L$\", r\"$Q_i$\", \"FSR from peaks (nm)\", \"Loss (dB/cm)\", r\"$\\kappa^2$\"]\n",
    "    fig, axes = plt.subplots(2, 3, figsize=(11, 6.5), constrained_layout=True)\n",
    "    axes = axes.ravel()\n",
    "    for ax, key, title in zip(axes, keys, titles):\n",
    "        Rs, gs, Z = _metric_grid(metric_rows, key)\n",
    "        im = ax.imshow(\n",
    "            Z,\n",
    "            origin=\"lower\",\n",
    "            aspect=\"auto\",\n",
    "            extent=[Rs.min(), Rs.max(), gs.min(), gs.max()],\n",
    "        )\n",
    "        ax.set_xlabel(\"R (µm)\")\n",
    "        ax.set_ylabel(\"gap (µm)\")\n",
    "        ax.set_title(title)\n",
    "        fig.colorbar(im, ax=ax, shrink=0.85)\n",
    "    axes[-1].axis(\"off\")\n",
    "    fig.suptitle(\"2D EIA sweep metrics\")\n",
    "    plt.show()\n",
    "else:\n",
    "    print(\"No metric_rows available for heatmaps.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a5b8201",
   "metadata": {
    "id": "1a5b8201"
   },
   "source": [
    "### 3.9 Full 3D Verification of Two Vernier Candidate Rings\n",
    "\n",
    "The EIA sweep is useful for screening. The final candidate pair is verified with full 3D FDTD using the same ring builder. Here we simulate the two individual add-drop rings with radii `11.5 µm` and `14.5 µm`, then compare their resonance combs. Their slightly different FSRs produce the Vernier effect when the rings are later combined in a coupled architecture."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "1c4049a2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:29.576315Z",
     "iopub.status.busy": "2026-06-22T18:52:29.576158Z",
     "iopub.status.idle": "2026-06-22T18:52:29.684641Z",
     "shell.execute_reply": "2026-06-22T18:52:29.684177Z"
    },
    "id": "1c4049a2",
    "outputId": "2e3831b4-890b-463c-f27a-d1cdb119b477"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sin_mrr_R11.5_g0.16 | domain (µm): (24.5255, 25.8455, 1.2455) | monitors: ['drop', 'through', 'field']\n",
      "sin_mrr_R14.5_g0.16 | domain (µm): (30.5255, 31.8455, 1.2455) | monitors: ['drop', 'through', 'field']\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build full 3D simulations for the two shortlisted radii and inspect one layout.\n",
    "sims_3d = {}\n",
    "for R in VERNIER_RADII_UM:\n",
    "    name = f\"sin_mrr_R{R:g}_g{VERNIER_GAP_UM:g}\"  # keep names compatible with parse_task_rg()\n",
    "    sims_3d[name] = build_sin_ring_mrr_sim(\n",
    "        R, VERNIER_GAP_UM, params=params\n",
    "    )  # full 3D validation model\n",
    "\n",
    "for name, sim in sims_3d.items():\n",
    "    print(\n",
    "        name,\n",
    "        \"| domain (µm):\",\n",
    "        tuple(round(x, 4) for x in sim.size),\n",
    "        \"| monitors:\",\n",
    "        [m.name for m in sim.monitors],\n",
    "    )\n",
    "\n",
    "first_name = next(iter(sims_3d))\n",
    "fig, ax = plt.subplots(figsize=(7, 5.5))\n",
    "sims_3d[first_name].plot(z=0, ax=ax)\n",
    "ax.set_title(f\"3D verification geometry: {first_name}\")\n",
    "ax.set_aspect(\"equal\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "fba53699",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:29.685842Z",
     "iopub.status.busy": "2026-06-22T18:52:29.685755Z",
     "iopub.status.idle": "2026-06-22T18:52:29.688416Z",
     "shell.execute_reply": "2026-06-22T18:52:29.688173Z"
    },
    "id": "fba53699",
    "outputId": "c83b51c4-c57d-4ac8-ebe4-c7c80fa5aa28"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
16:53:57 -03 No Flexcredit cost for batch as all simulations were restored from \n",
       "             local cache.                                                       \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:53:57 -03\u001b[0m\u001b[2;36m \u001b[0mNo Flexcredit cost for batch as all simulations were restored from \n",
       "\u001b[2;36m             \u001b[0mlocal cache.                                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estimated maximum FlexCredits for the two-ring 3D verification batch: 0.0\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "
             Found all simulations in cache.                                    \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mFound all simulations in cache.                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'sin_mrr_R11.5_g0.16': 'fdve-07808b1a-b298-497b-9614-4f9505ed9fd7', 'sin_mrr_R14.5_g0.16': 'fdve-b02b823d-ec00-4731-82ac-de7d3c06eaea'}\n"
     ]
    }
   ],
   "source": [
    "# Run the two-ring 3D verification batch only if its results are not already on disk.\n",
    "VERNIER_3D_DIR = (\n",
    "    Path(\"results\") / \"sin_vernier_rings_3d\"\n",
    ")  # output folder for 3D verification data\n",
    "batch_3d = None  # populated only if a new run is needed\n",
    "estimated_cost_3d = None  # populated by Batch.estimate_cost before running\n",
    "batch_data_3d = None  # populated by the run, or loaded from disk in a later cell\n",
    "\n",
    "if (VERNIER_3D_DIR / \"batch.hdf5\").exists():\n",
    "    print(\"Loading existing 3D Vernier results from:\", VERNIER_3D_DIR)\n",
    "else:\n",
    "    # Estimate the 3D verification cost before running. This does not time-step the\n",
    "    # FDTD simulation, but it can create cloud task records.\n",
    "    batch_3d = web.Batch(\n",
    "        simulations=sims_3d, folder_name=\"sin_vernier_rings_715_750_3d\"\n",
    "    )\n",
    "    estimated_cost_3d = batch_3d.estimate_cost(verbose=True)\n",
    "    print(\n",
    "        \"Estimated maximum FlexCredits for the two-ring 3D verification batch:\",\n",
    "        estimated_cost_3d,\n",
    "    )\n",
    "\n",
    "    VERNIER_3D_DIR.mkdir(parents=True, exist_ok=True)\n",
    "    batch_data_3d = batch_3d.run(path_dir=str(VERNIER_3D_DIR))\n",
    "    print(batch_data_3d.task_ids)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a175ad3",
   "metadata": {
    "id": "2a175ad3"
   },
   "source": [
    "### 3.10 Load 3D Results, Compare Vernier Spectra, and Export Metrics\n",
    "\n",
    "After running the 3D batch, the following cells load spectra, overlay the two candidate rings, and export the same through-notch metrics used for the EIA sweep. If a saved metrics CSV exists from a previous run, the final table can also be inspected directly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "66c97b14",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:29.689385Z",
     "iopub.status.busy": "2026-06-22T18:52:29.689253Z",
     "iopub.status.idle": "2026-06-22T18:52:30.236083Z",
     "shell.execute_reply": "2026-06-22T18:52:30.235777Z"
    },
    "id": "66c97b14",
    "outputId": "10e5d651-0bf8-4940-c3dd-cd5a70b99080"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 2 3D spectra.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load completed 3D results and overlay drop/through spectra for the Vernier candidates.\n",
    "batch_data_3d = globals().get(\n",
    "    \"batch_data_3d\", None\n",
    ")  # reuse just-run 3D results if available\n",
    "if batch_data_3d is None:\n",
    "    batch_data_3d = load_batch_data(\n",
    "        VERNIER_3D_DIR\n",
    "    )  # otherwise load saved 3D batch data\n",
    "\n",
    "spectra_3d = {}  # spectra keyed by radius/gap task name\n",
    "if batch_data_3d is not None:\n",
    "    for name, sim_data in batch_data_3d.items():\n",
    "        wl_drop, T_drop = spectrum_mode_power(sim_data, \"drop\", \"-\")\n",
    "        wl_through, T_through = spectrum_mode_power(sim_data, \"through\", \"+\")\n",
    "        spectra_3d[name] = {\n",
    "            \"wl\": wl_drop,\n",
    "            \"drop\": T_drop,\n",
    "            \"through\": np.interp(wl_drop, wl_through, T_through),\n",
    "        }\n",
    "    print(f\"Loaded {len(spectra_3d)} 3D spectra.\")\n",
    "else:\n",
    "    print(\n",
    "        \"No 3D BatchData loaded. Run the 3D batch or point VERNIER_3D_DIR to saved results.\"\n",
    "    )\n",
    "\n",
    "if spectra_3d:\n",
    "    fig, axes = plt.subplots(1, 2, figsize=(11, 4.2), constrained_layout=True)\n",
    "    for name, sp in spectra_3d.items():\n",
    "        axes[0].plot(sp[\"wl\"], sp[\"drop\"], lw=1.3, label=f\"{name}\")\n",
    "        axes[1].plot(sp[\"wl\"], sp[\"through\"], lw=1.3, label=f\"{name}\")\n",
    "    axes[0].set_title(\"3D drop spectra: interleaved resonance combs\")\n",
    "    axes[1].set_title(\"3D through spectra: notch comparison\")\n",
    "    for ax in axes:\n",
    "        ax.set_xlabel(\"Wavelength (µm)\")\n",
    "        ax.set_ylabel(r\"Mode power $|a|^2$\")\n",
    "        ax.grid(True, alpha=0.3)\n",
    "        ax.legend(fontsize=8)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "a7e0c6fe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:30.237186Z",
     "iopub.status.busy": "2026-06-22T18:52:30.237090Z",
     "iopub.status.idle": "2026-06-22T18:52:30.249794Z",
     "shell.execute_reply": "2026-06-22T18:52:30.249348Z"
    },
    "id": "a7e0c6fe",
    "outputId": "408d8b43-647f-49ae-ff4d-9b80ae79c9fe"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wrote 2 3D metric rows to results/sin_vernier_rings_3d/community_vernier_ring_metrics.csv\n",
      "\n",
      "sin_mrr_R11.5_g0.16\n",
      "  lambda0_um: 0.7394927347627271\n",
      "  fwhm_nm: 0.07204296118022299\n",
      "  Q_loaded: 10264.607709735985\n",
      "  Q_intrinsic: 20529.210609104277\n",
      "  Q_coupling: 41058.44045968382\n",
      "  mean_fsr_nm_peaks: 3.570000000000004\n",
      "  n_group_from_fsr: 2.1199318429180414\n",
      "  kappa2_power: 0.004878599970684205\n",
      "  loss_dB_per_cm: 36.8478267757335\n",
      "  coupling_regime: critical\n",
      "\n",
      "sin_mrr_R14.5_g0.16\n",
      "  lambda0_um: 0.7394209075871926\n",
      "  fwhm_nm: 0.06963973336680075\n",
      "  Q_loaded: 10617.80210576877\n",
      "  Q_intrinsic: 21235.778844095883\n",
      "  Q_coupling: 42470.859163702706\n",
      "  mean_fsr_nm_peaks: 2.831818181818183\n",
      "  n_group_from_fsr: 2.1191915631060025\n",
      "  kappa2_power: 0.005947287845935092\n",
      "  loss_dB_per_cm: 35.62526639398402\n",
      "  coupling_regime: critical\n"
     ]
    }
   ],
   "source": [
    "# Compute the same notch/FSR/Q/loss metrics for the 3D verification spectra.\n",
    "metric_rows_3d = []  # one verification metric row per selected 3D ring\n",
    "for name, sp in spectra_3d.items():\n",
    "    R, g = parse_task_rg(name)\n",
    "    metric_rows_3d.append(\n",
    "        ring_metrics_row(\n",
    "            name,\n",
    "            R,\n",
    "            g,\n",
    "            sp[\"wl\"],\n",
    "            sp[\"drop\"],\n",
    "            sp[\"through\"],\n",
    "            lambda_fit_target_um=NOTCH_FIT_CENTER_UM,  # same target notch used for EIA comparison\n",
    "            notch_half_width_um=NOTCH_HALF_WIDTH_UM,  # local 3D fitting window\n",
    "            n_group_for_kappa2=N_GROUP_FOR_KAPPA2,  # group-index estimate for κ² / loss conversion\n",
    "        )\n",
    "    )\n",
    "\n",
    "if metric_rows_3d:\n",
    "    csv_path = VERNIER_3D_DIR / \"community_vernier_ring_metrics.csv\"\n",
    "    csv_path.parent.mkdir(parents=True, exist_ok=True)\n",
    "    with csv_path.open(\"w\", newline=\"\") as fp:\n",
    "        writer = csv.DictWriter(\n",
    "            fp, fieldnames=list(metric_rows_3d[0].keys()), extrasaction=\"ignore\"\n",
    "        )\n",
    "        writer.writeheader()\n",
    "        writer.writerows(metric_rows_3d)\n",
    "    print(f\"Wrote {len(metric_rows_3d)} 3D metric rows to {csv_path}\")\n",
    "\n",
    "    cols = [\n",
    "        \"task\",\n",
    "        \"lambda0_um\",\n",
    "        \"fwhm_nm\",\n",
    "        \"Q_loaded\",\n",
    "        \"Q_intrinsic\",\n",
    "        \"Q_coupling\",\n",
    "        \"mean_fsr_nm_peaks\",\n",
    "        \"n_group_from_fsr\",\n",
    "        \"kappa2_power\",\n",
    "        \"loss_dB_per_cm\",\n",
    "        \"coupling_regime\",\n",
    "    ]\n",
    "    for row in metric_rows_3d:\n",
    "        print(\"\\n\" + row[\"task\"])\n",
    "        for c in cols[1:]:\n",
    "            print(f\"  {c}: {row.get(c)}\")\n",
    "else:\n",
    "    previous_csv = VERNIER_3D_DIR / \"vernier_ring_metrics.csv\"\n",
    "    if previous_csv.is_file():\n",
    "        print(f\"No BatchData loaded, but previous metrics exist at {previous_csv}\")\n",
    "    else:\n",
    "        print(\"No 3D metrics available yet.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "Tio64yR8HZKI",
   "metadata": {
    "id": "Tio64yR8HZKI"
   },
   "source": [
    "## 4. SiN Grating Coupler"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "Y1FzYsckxQAX",
   "metadata": {
    "id": "Y1FzYsckxQAX"
   },
   "source": [
    "### Linear Grating Coupler at 740 nm (Si₃N₄ on SiO₂)\n",
    "\n",
    "Quasi-2D setup: finite thickness along **y** with PML (needed for [`FieldProjectionCartesianMonitor`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldProjectionCartesianMonitor.html)).\n",
    "\n",
    "- **Excitation:** `ModeSource` on the narrow ridge; optional [`PolySlab`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PolySlab.html) taper (**narrow→wide** toward the grating in xy). Use `sim.plot(z≈0.11)` to view xy outline.\n",
    "- **Monitors:** `radiation_far` (far field), `mode_transmission` (output waveguide — forward power in mode *m* is `|a+|²` in **W** vs the normalized mode source; call `coupling_efficiency_metrics(sim_data)`), co-planar `flux_output_waveguide` (total **+x** flux for cross-check), `field_xz_mid`, `flux_up_air`. Defaults lean storage: **Ey** on the field monitor, spatial `interval_space` downsampling, fewer transmitted modes (`transmission_mode_num_modes`), slightly smaller XY span and projection grid (`far_field_nx`).\n",
    "\n",
    "Default stack (bottom → top): **2 µm** Si, **5 µm** SiO₂, **220 nm** Si₃N₄, **5 µm** SiO₂, then air. With a taper, **narrow** SiN width is **`core_width_um`** (input + taper start); **grating** slab/teeth match **`taper_input_width_um`** in **y** (same as wide taper side). Film-plane **SiO₂** lateral strips exclude **`±core_width_um/2`** so oxide fills wedges beside the flaring rib.\n",
    "\n",
    "Geometry parameters are illustrative—tune `period_um`, duty cycle, and etch for your stack.\n",
    "\n",
    "**Cloud runs** use FlexCredit; only call `web.run` when you intend to solve remotely."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "4B-TjPKYxZMS",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 375
    },
    "collapsed": true,
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:30.251556Z",
     "iopub.status.busy": "2026-06-22T18:52:30.251117Z",
     "iopub.status.idle": "2026-06-22T18:52:30.253784Z",
     "shell.execute_reply": "2026-06-22T18:52:30.253397Z"
    },
    "executionInfo": {
     "elapsed": 4,
     "status": "error",
     "timestamp": 1781115769565,
     "user": {
      "displayName": "Ping-Chun Chen",
      "userId": "04550073403936832183"
     },
     "user_tz": 420
    },
    "id": "4B-TjPKYxZMS",
    "outputId": "cacb2a31-d4e8-45d1-dfda-ff0375d08699"
   },
   "outputs": [],
   "source": [
    "from __future__ import annotations\n",
    "\n",
    "from typing import Any\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "import tidy3d as td\n",
    "from tidy3d import material_library"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2UE24qR6yJqt",
   "metadata": {
    "id": "2UE24qR6yJqt"
   },
   "source": [
    "### Geometry and `Simulation` Builder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "4ffVlL4JxltO",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:30.255337Z",
     "iopub.status.busy": "2026-06-22T18:52:30.255184Z",
     "iopub.status.idle": "2026-06-22T18:52:30.281006Z",
     "shell.execute_reply": "2026-06-22T18:52:30.280506Z"
    },
    "id": "4ffVlL4JxltO"
   },
   "outputs": [],
   "source": [
    "def _box(\n",
    "    center: tuple[float, float, float],\n",
    "    size: tuple[float, float, float],\n",
    "    medium: td.Medium,\n",
    ") -> td.Structure:\n",
    "    return td.Structure(geometry=td.Box(center=center, size=size), medium=medium)\n",
    "\n",
    "\n",
    "def make_linear_grating_coupler_simulation(\n",
    "    wavelength_um: float = 0.74,\n",
    "    period_um: float = 0.52,\n",
    "    duty_cycle: float = 0.55,\n",
    "    n_periods: int = 30,\n",
    "    core_width_um: float = 0.5,\n",
    "    core_nominal_um: float = 0.22,\n",
    "    etch_um: float = 0.11,\n",
    "    slab_thickness_um: float | None = None,\n",
    "    straight_um: float = 2.8,\n",
    "    taper_length_um: float = 0.0,\n",
    "    taper_input_width_um: float = 2.0,\n",
    "    box_um: float = 5.0,\n",
    "    top_oxide_um: float = 5.0,\n",
    "    bulk_si_thickness_um: float = 2.0,\n",
    "    air_um: float = 2.5,\n",
    "    domain_y_um: float | None = None,\n",
    "    min_steps_per_wvl: int = 24,\n",
    "    projection_height_um: float = 5.5,\n",
    "    pml_layers: tuple[int, int, int] = (44, 40, 48),\n",
    "    absorber_y: bool = True,\n",
    "    absorber_layers_y: int | None = None,\n",
    "    absorber_x: bool = True,\n",
    "    absorber_layers_x: int | None = None,\n",
    "    stable_z_pml: bool = True,\n",
    "    stable_x_pml: bool = True,\n",
    "    courant: float = 0.72,\n",
    "    source_x_um: float | None = None,\n",
    "    far_field_nx: int = 41,\n",
    "    far_field_ny: int = 3,\n",
    "    field_monitor_fields: tuple[str, ...] = (\"Ey\",),\n",
    "    field_monitor_xy_fraction: tuple[float, float] = (0.35, 0.52),\n",
    "    field_monitor_interval_space: tuple[int, int, int] = (2, 1, 2),\n",
    "    field_projection_interval_space: tuple[int, int, int] = (2, 2, 1),\n",
    "    transmission_mode_num_modes: int = 3,\n",
    ") -> td.Simulation:\n",
    "    slab_h = (\n",
    "        slab_thickness_um\n",
    "        if slab_thickness_um is not None\n",
    "        else (core_nominal_um - etch_um)\n",
    "    )\n",
    "    slab_h = max(float(slab_h), 1e-3)\n",
    "\n",
    "    si3n4_main = material_library[\"Si3N4\"][\"Luke2015Sellmeier\"]\n",
    "    sio2 = material_library[\"SiO2\"][\"Palik_Lossless\"]\n",
    "    si_bulk = material_library[\"cSi\"][\"Green2008\"]\n",
    "\n",
    "    freq0_hz = td.C_0 / wavelength_um\n",
    "    fwidth_hz = freq0_hz * 0.15\n",
    "    pulse = td.GaussianPulse(freq0=freq0_hz, fwidth=fwidth_hz)\n",
    "\n",
    "    gr_len = period_um * n_periods\n",
    "    x_g0 = -0.5 * gr_len\n",
    "    x_g1 = 0.5 * gr_len\n",
    "    strip_left = x_g0 - straight_um\n",
    "\n",
    "    w_tap_in = float(taper_input_width_um)\n",
    "    t_len = float(taper_length_um)\n",
    "    use_taper = t_len > 1e-6 and w_tap_in > float(core_width_um) + 1e-6\n",
    "    xt0 = max(strip_left, x_g0 - t_len) if use_taper else strip_left\n",
    "    if use_taper and (x_g0 - xt0) < 1e-6:\n",
    "        use_taper = False\n",
    "    w_y_max = max(float(core_width_um), w_tap_in if use_taper else float(core_width_um))\n",
    "\n",
    "    _cell_y_auto = max(2.05 * w_y_max, 2.1 * wavelength_um, w_y_max + wavelength_um)\n",
    "    cell_y = domain_y_um if domain_y_um is not None else _cell_y_auto\n",
    "\n",
    "    dev_half_x = abs(strip_left) + 2.65 * wavelength_um\n",
    "    lx = 2.0 * dev_half_x\n",
    "\n",
    "    z_intf = 0.0\n",
    "    z_si_top = z_intf + core_nominal_um\n",
    "    z_stack_top = z_si_top + float(top_oxide_um)\n",
    "    oz_sz_z = float(box_um)\n",
    "    z_bottom_oxide = z_intf - oz_sz_z\n",
    "    z_bulk_bottom = z_bottom_oxide - float(bulk_si_thickness_um)\n",
    "    zb_domain = z_bulk_bottom - 0.225 * wavelength_um\n",
    "    z_domain_top = z_stack_top + air_um + wavelength_um * 0.62\n",
    "    lz_domain = z_domain_top - zb_domain\n",
    "    sim_center = (0.0, 0.0, zb_domain + 0.5 * lz_domain)\n",
    "\n",
    "    z_padding_z = 0.55 * wavelength_um\n",
    "    size_z = lz_domain + z_padding_z\n",
    "    z_sim_min = sim_center[2] - 0.5 * size_z\n",
    "\n",
    "    ridge_y_narrow = float(core_width_um)\n",
    "    ridge_y_span = ridge_y_narrow\n",
    "    ridge_grating_y = w_tap_in if use_taper else ridge_y_narrow\n",
    "\n",
    "    structures: list[td.Structure] = []\n",
    "\n",
    "    ox_y = max(lx * 0.085 + core_width_um * 24.0, 12.0 * wavelength_um)\n",
    "    ox_x = lx * 3.28\n",
    "\n",
    "    si_total_z = z_bottom_oxide - z_sim_min\n",
    "    bulk_si = _box(\n",
    "        center=(0.0, 0.0, z_sim_min + 0.5 * si_total_z),\n",
    "        size=(ox_x, ox_y, si_total_z),\n",
    "        medium=si_bulk,\n",
    "    )\n",
    "    structures.append(bulk_si)\n",
    "\n",
    "    oxide_lower = _box(\n",
    "        center=(0.0, 0.0, z_intf - 0.5 * oz_sz_z),\n",
    "        size=(ox_x, ox_y, oz_sz_z),\n",
    "        medium=sio2,\n",
    "    )\n",
    "    structures.append(oxide_lower)\n",
    "\n",
    "    # Lateral SiO2 in film plane: exclude ±half(core_width) only—fills wedges beside widening taper.\n",
    "    ox_half = 0.5 * ox_x\n",
    "    oy_half = 0.5 * ox_y\n",
    "    ridge_half_clad = 0.5 * float(core_width_um)\n",
    "    side_y_sz = oy_half - ridge_half_clad\n",
    "    if side_y_sz > 1e-6:\n",
    "        z_core_mid = z_intf + 0.5 * core_nominal_um\n",
    "        structures.append(\n",
    "            _box(\n",
    "                center=(0.0, -0.5 * (oy_half + ridge_half_clad), z_core_mid),\n",
    "                size=(ox_x, side_y_sz, core_nominal_um),\n",
    "                medium=sio2,\n",
    "            )\n",
    "        )\n",
    "        structures.append(\n",
    "            _box(\n",
    "                center=(0.0, 0.5 * (oy_half + ridge_half_clad), z_core_mid),\n",
    "                size=(ox_x, side_y_sz, core_nominal_um),\n",
    "                medium=sio2,\n",
    "            )\n",
    "        )\n",
    "\n",
    "    # Uniform Si3N4 film on the input side (before the ridge/grating footprint in +x).\n",
    "    # Use ridge_y_narrow in y — not w_y_max — so width matches the narrow rib and taper start at strip_left.\n",
    "    if strip_left > -ox_half + 1e-6:\n",
    "        lx_in = strip_left + ox_half\n",
    "        structures.append(\n",
    "            _box(\n",
    "                center=(strip_left - 0.5 * lx_in, 0.0, z_intf + 0.5 * core_nominal_um),\n",
    "                size=(lx_in, ridge_y_narrow, core_nominal_um),\n",
    "                medium=si3n4_main,\n",
    "            )\n",
    "        )\n",
    "\n",
    "    straight_top = core_nominal_um - slab_h\n",
    "    if use_taper:\n",
    "        w_in = w_tap_in\n",
    "        half_in = 0.5 * w_in\n",
    "        half_gr = 0.5 * ridge_y_narrow\n",
    "        if xt0 > strip_left + 1e-6:\n",
    "            x_u0, x_u1 = strip_left, xt0\n",
    "            len_u = x_u1 - x_u0\n",
    "            structures.append(\n",
    "                _box(\n",
    "                    center=(x_u0 + 0.5 * len_u, 0.0, z_intf + 0.5 * slab_h),\n",
    "                    size=(len_u, ridge_y_span, slab_h),\n",
    "                    medium=si3n4_main,\n",
    "                )\n",
    "            )\n",
    "            if straight_top > 1e-4:\n",
    "                structures.append(\n",
    "                    _box(\n",
    "                        center=(\n",
    "                            x_u0 + 0.5 * len_u,\n",
    "                            0.0,\n",
    "                            z_intf + slab_h + 0.5 * straight_top,\n",
    "                        ),\n",
    "                        size=(len_u, ridge_y_span, straight_top),\n",
    "                        medium=si3n4_main,\n",
    "                    )\n",
    "                )\n",
    "        taper_geo = td.PolySlab(\n",
    "            vertices=[\n",
    "                (xt0, -half_gr),\n",
    "                (x_g0, -half_in),\n",
    "                (x_g0, half_in),\n",
    "                (xt0, half_gr),\n",
    "            ],\n",
    "            axis=2,\n",
    "            slab_bounds=(z_intf, z_si_top),\n",
    "        )\n",
    "        structures.append(td.Structure(geometry=taper_geo, medium=si3n4_main))\n",
    "        slab_len_gr = x_g1 - x_g0\n",
    "        structures.append(\n",
    "            _box(\n",
    "                center=(x_g0 + 0.5 * slab_len_gr, 0.0, z_intf + 0.5 * slab_h),\n",
    "                size=(slab_len_gr, ridge_grating_y, slab_h),\n",
    "                medium=si3n4_main,\n",
    "            )\n",
    "        )\n",
    "    else:\n",
    "        slab_len = x_g1 - strip_left\n",
    "        slab_center_x = strip_left + 0.5 * slab_len\n",
    "        structures.append(\n",
    "            _box(\n",
    "                center=(slab_center_x, 0.0, z_intf + 0.5 * slab_h),\n",
    "                size=(slab_len, ridge_y_span, slab_h),\n",
    "                medium=si3n4_main,\n",
    "            )\n",
    "        )\n",
    "        if straight_top > 1e-4:\n",
    "            structures.append(\n",
    "                _box(\n",
    "                    center=(\n",
    "                        (strip_left + x_g0) * 0.5,\n",
    "                        0.0,\n",
    "                        z_intf + slab_h + 0.5 * straight_top,\n",
    "                    ),\n",
    "                    size=(x_g0 - strip_left, ridge_y_span, straight_top),\n",
    "                    medium=si3n4_main,\n",
    "                )\n",
    "            )\n",
    "\n",
    "    if x_g1 < ox_half - 1e-6:\n",
    "        rx_pad = ox_half - x_g1\n",
    "        structures.append(\n",
    "            _box(\n",
    "                center=(x_g1 + 0.5 * rx_pad, 0.0, z_intf + 0.5 * core_nominal_um),\n",
    "                size=(rx_pad, ox_y, core_nominal_um),\n",
    "                medium=sio2,\n",
    "            )\n",
    "        )\n",
    "\n",
    "    tooth_w = duty_cycle * period_um\n",
    "    top_h = core_nominal_um - slab_h\n",
    "    if top_h > 1e-4:\n",
    "        gr_len_x = x_g1 - x_g0\n",
    "        structures.append(\n",
    "            _box(\n",
    "                center=(0.5 * (x_g0 + x_g1), 0.0, z_intf + slab_h + 0.5 * top_h),\n",
    "                size=(gr_len_x, ridge_grating_y, top_h),\n",
    "                medium=sio2,\n",
    "            )\n",
    "        )\n",
    "    for k in range(n_periods):\n",
    "        xc = x_g0 + (k + 0.5 * duty_cycle) * period_um\n",
    "        if top_h <= 1e-4:\n",
    "            break\n",
    "        structures.append(\n",
    "            _box(\n",
    "                center=(xc, 0.0, z_intf + slab_h + 0.5 * top_h),\n",
    "                size=(tooth_w * 0.996, ridge_grating_y, top_h),\n",
    "                medium=si3n4_main,\n",
    "            )\n",
    "        )\n",
    "\n",
    "    top_ox_t = float(top_oxide_um)\n",
    "    oxide_top = _box(\n",
    "        center=(0.0, 0.0, z_si_top + 0.5 * top_ox_t),\n",
    "        size=(ox_x, ox_y, top_ox_t),\n",
    "        medium=sio2,\n",
    "    )\n",
    "    structures.append(oxide_top)\n",
    "\n",
    "    src_x = 0.5 * (strip_left + x_g0) if source_x_um is None else float(source_x_um)\n",
    "    src_z = z_intf + min(0.48 * core_nominal_um, 0.55 * z_si_top)\n",
    "    mode_h = min(2.6 * wavelength_um, air_um * 0.78 + core_nominal_um)\n",
    "    mode_sz_y = max(6.0 * w_y_max, cell_y, 0.8 * wavelength_um)\n",
    "    ms = td.ModeSource(\n",
    "        center=(src_x, 0.0, src_z),\n",
    "        size=(0.0, mode_sz_y, mode_h),\n",
    "        source_time=pulse,\n",
    "        direction=\"+\",\n",
    "        mode_spec=td.ModeSpec(num_modes=8, target_neff=1.45),\n",
    "        mode_index=0,\n",
    "        num_freqs=3,\n",
    "    )\n",
    "\n",
    "    collection_span = min(lx * 0.41, gr_len + 10.0 * wavelength_um)\n",
    "    z_collect = sim_center[2] + 0.5 * lz_domain - 0.38 * wavelength_um\n",
    "    z_origin = z_si_top + 0.35 * top_ox_t\n",
    "    proj_y = max(4.0 * w_y_max, 0.25 * wavelength_um)\n",
    "    _ff_nx = max(3, int(far_field_nx))\n",
    "    _ff_ny = max(1, int(far_field_ny))\n",
    "    _fpi_x, _fpi_y, _fpi_z = (\n",
    "        max(1, int(field_projection_interval_space[i])) for i in range(3)\n",
    "    )\n",
    "    nf_monitor = td.FieldProjectionCartesianMonitor(\n",
    "        center=(gr_len * 0.048, 0.0, z_collect - wavelength_um),\n",
    "        size=(collection_span, proj_y, 0.0),\n",
    "        freqs=[freq0_hz],\n",
    "        name=\"radiation_far\",\n",
    "        custom_origin=(0.0, 0.0, z_origin),\n",
    "        x=np.linspace(-collection_span / 2.06, collection_span / 2.06, _ff_nx).tolist(),\n",
    "        y=np.linspace(-0.12 * cell_y, 0.12 * cell_y, _ff_ny).tolist(),\n",
    "        proj_axis=2,\n",
    "        proj_distance=projection_height_um,\n",
    "        far_field_approx=False,\n",
    "        interval_space=(_fpi_x, _fpi_y, _fpi_z),\n",
    "    )\n",
    "\n",
    "    field_y = max(0.35 * w_y_max, 0.02 * wavelength_um)\n",
    "    _fx, _fz = float(field_monitor_xy_fraction[0]), float(field_monitor_xy_fraction[1])\n",
    "    _fmx, _fmy, _fmz = (max(1, int(field_monitor_interval_space[i])) for i in range(3))\n",
    "    fz = td.FieldMonitor(\n",
    "        center=(\n",
    "            src_x + 5.08 * wavelength_um + gr_len * 0.52,\n",
    "            0.0,\n",
    "            z_intf + wavelength_um,\n",
    "        ),\n",
    "        size=(lx * _fx, field_y, lz_domain * _fz),\n",
    "        freqs=[freq0_hz],\n",
    "        name=\"field_xz_mid\",\n",
    "        fields=tuple(field_monitor_fields),\n",
    "        interval_space=(_fmx, _fmy, _fmz),\n",
    "    )\n",
    "\n",
    "    flux_z = sim_center[2] + 0.5 * lz_domain - 0.35 * wavelength_um\n",
    "    flux_up = td.FluxMonitor(\n",
    "        center=(gr_len * 0.02, 0.0, flux_z),\n",
    "        size=(lx * 0.42, field_y, 0.0),\n",
    "        freqs=[freq0_hz],\n",
    "        name=\"flux_up_air\",\n",
    "        normal_dir=\"+\",\n",
    "    )\n",
    "\n",
    "    trans_x = x_g1 + max(2.0 * wavelength_um, 0.35 * straight_um)\n",
    "    _n_tm = max(1, int(transmission_mode_num_modes))\n",
    "    mode_trans = td.ModeMonitor(\n",
    "        center=(trans_x, 0.0, src_z),\n",
    "        size=(0.0, mode_sz_y, mode_h),\n",
    "        freqs=[freq0_hz],\n",
    "        name=\"mode_transmission\",\n",
    "        mode_spec=td.ModeSpec(num_modes=_n_tm, target_neff=1.45),\n",
    "        colocate=False,\n",
    "    )\n",
    "    flux_output = td.FluxMonitor(\n",
    "        center=(trans_x, 0.0, src_z),\n",
    "        size=(0.0, mode_sz_y, mode_h),\n",
    "        freqs=[freq0_hz],\n",
    "        name=\"flux_output_waveguide\",\n",
    "        normal_dir=\"+\",\n",
    "    )\n",
    "\n",
    "    nx_pml, ny_pml, nz_pml = pml_layers\n",
    "    ny_abs = absorber_layers_y if absorber_layers_y is not None else max(ny_pml + 8, 56)\n",
    "    nx_abs = absorber_layers_x if absorber_layers_x is not None else max(nx_pml + 8, 56)\n",
    "    if absorber_x:\n",
    "        x_bnd = td.Boundary.absorber(num_layers=nx_abs)\n",
    "    elif stable_x_pml:\n",
    "        x_bnd = td.Boundary.stable_pml(num_layers=nx_pml)\n",
    "    else:\n",
    "        x_bnd = td.Boundary.pml(num_layers=nx_pml)\n",
    "    z_bnd = (\n",
    "        td.Boundary.stable_pml(num_layers=nz_pml)\n",
    "        if stable_z_pml\n",
    "        else td.Boundary.pml(num_layers=nz_pml)\n",
    "    )\n",
    "    if absorber_y:\n",
    "        boundary_spec = td.BoundarySpec(\n",
    "            x=x_bnd,\n",
    "            y=td.Boundary.absorber(num_layers=ny_abs),\n",
    "            z=z_bnd,\n",
    "        )\n",
    "    else:\n",
    "        boundary_spec = td.BoundarySpec(\n",
    "            x=x_bnd,\n",
    "            y=td.Boundary.pml(num_layers=ny_pml),\n",
    "            z=z_bnd,\n",
    "        )\n",
    "\n",
    "    grid = td.GridSpec(\n",
    "        grid_x=td.AutoGrid(min_steps_per_wvl=min_steps_per_wvl),\n",
    "        grid_y=td.AutoGrid(min_steps_per_wvl=min_steps_per_wvl),\n",
    "        grid_z=td.AutoGrid(min_steps_per_wvl=min_steps_per_wvl),\n",
    "        wavelength=wavelength_um,\n",
    "    )\n",
    "\n",
    "    run_time = td.RunTimeSpec(quality_factor=6.4, source_factor=3.2)\n",
    "\n",
    "    sim_kw: dict[str, Any] = dict(\n",
    "        size=(lx + 1.75 * wavelength_um, cell_y, size_z),\n",
    "        center=sim_center,\n",
    "        medium=td.Medium(permittivity=1.0),\n",
    "        symmetry=(0, 0, 0),\n",
    "        structures=tuple(structures),\n",
    "        boundary_spec=boundary_spec,\n",
    "        grid_spec=grid,\n",
    "        sources=(ms,),\n",
    "        monitors=(fz, flux_up, nf_monitor, mode_trans, flux_output),\n",
    "        run_time=run_time,\n",
    "        subpixel=True,\n",
    "        courant=float(courant),\n",
    "    )\n",
    "    return td.Simulation(**sim_kw)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "AtQLmziyyVmv",
   "metadata": {
    "id": "AtQLmziyyVmv"
   },
   "source": [
    "### Post-Processing Helpers (after `web.run`)\n",
    "\n",
    "- **`coupling_efficiency_metrics(sim_data)`** — forward/backward modal powers at `mode_transmission` and total **+x** flux on `flux_output_waveguide` (cross-check vs sum of modes)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "GVz-hM2nyehw",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:30.282584Z",
     "iopub.status.busy": "2026-06-22T18:52:30.282440Z",
     "iopub.status.idle": "2026-06-22T18:52:30.287756Z",
     "shell.execute_reply": "2026-06-22T18:52:30.287333Z"
    },
    "id": "GVz-hM2nyehw"
   },
   "outputs": [],
   "source": [
    "def postprocess_cartesian_projection(sim_data: td.SimulationData) -> dict[str, Any]:\n",
    "    \"\"\"Lightweight metrics from the Cartesian far-field projection monitor.\"\"\"\n",
    "    pdata = sim_data[\"radiation_far\"]\n",
    "    out: dict[str, Any] = {\"monitor\": pdata}\n",
    "    for comp in (\"Er\", \"Etheta\", \"Ephi\"):\n",
    "        arr = getattr(pdata, comp, None)\n",
    "        if arr is None:\n",
    "            continue\n",
    "        v = np.asarray(arr.values, dtype=complex)\n",
    "        out[f\"rms_{comp}\"] = float(np.sqrt(np.mean(np.abs(v) ** 2)))\n",
    "    return out\n",
    "\n",
    "\n",
    "def coupling_efficiency_metrics(sim_data: td.SimulationData) -> dict[str, Any]:\n",
    "    \"\"\"Power coupled into waveguide modes at ``mode_transmission`` (see Fluxcompute FAQ).\n",
    "\n",
    "    With a ``ModeSource``, monitor fields are normalized to the source spectrum; at the\n",
    "    central frequency the injected power is ~1 W. Forward modal power is ``|a+|²`` in watts.\n",
    "\n",
    "    References:\n",
    "    https://docs.flexcompute.com/projects/tidy3d/en/latest/faq/docs/faq/how-do-i-get-the-coupling-efficiency-of-a-specific-waveguide-mode.html\n",
    "    \"\"\"\n",
    "    md = sim_data[\"mode_transmission\"]\n",
    "    amps_f = md.amps.sel(direction=\"+\")\n",
    "    amps_b = md.amps.sel(direction=\"-\")\n",
    "    p0_f = md.amps.sel(mode_index=0, direction=\"+\")\n",
    "    p0_b = md.amps.sel(mode_index=0, direction=\"-\")\n",
    "    out: dict[str, Any] = {\n",
    "        \"power_forward_mode0_W\": float(np.sum(np.abs(p0_f.values) ** 2)),\n",
    "        \"power_forward_all_tracked_modes_W\": float(np.sum(np.abs(amps_f.values) ** 2)),\n",
    "        \"power_backward_mode0_W\": float(np.sum(np.abs(p0_b.values) ** 2)),\n",
    "        \"power_backward_all_tracked_modes_W\": float(np.sum(np.abs(amps_b.values) ** 2)),\n",
    "    }\n",
    "    try:\n",
    "        fx = sim_data[\"flux_output_waveguide\"].flux\n",
    "        out[\"flux_output_waveguide_W\"] = float(np.squeeze(fx.values))\n",
    "    except KeyError:\n",
    "        pass\n",
    "    return out"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "s9K4aUAzyBhG",
   "metadata": {
    "id": "s9K4aUAzyBhG"
   },
   "source": [
    "### Build, Inspect, and Run\n",
    "\n",
    "The taper **widens** the rib in xy toward +x (half-width grows toward **`taper_input_width_um`** at **`x_g0`**). A **`sim.plot(y=0)`** xz cut still tends to look like a rectangle at the centerline; use **`sim.plot(z≈0.11 µm)`** for xy geometry.\n",
    "\n",
    "Run `sim.plot(y=0)` for **xz**, `sim.plot(z≈0.11)` for **xy** (taper outline), and `sim.plot(z=0.26)` for **xy** in upper SiO₂. Use `sim.validate()` for a structural check.\n",
    "\n",
    "The grating coupler is run automatically in the next cell; if a saved result already exists it is loaded instead of resubmitting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "zvEHQixexoxy",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:30.289072Z",
     "iopub.status.busy": "2026-06-22T18:52:30.288912Z",
     "iopub.status.idle": "2026-06-22T18:52:30.452750Z",
     "shell.execute_reply": "2026-06-22T18:52:30.452414Z"
    },
    "id": "zvEHQixexoxy"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "size (µm): [26.417, 3.69, 15.7523]\n",
      "monitors: ['field_xz_mid', 'flux_up_air', 'radiation_far', 'mode_transmission', 'flux_output_waveguide']\n",
      "run_time (s): 1.2334e-12\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim = make_linear_grating_coupler_simulation(\n",
    "    taper_length_um=2.0,\n",
    "    taper_input_width_um=1.8,\n",
    "    source_x_um=-10.5,\n",
    ")\n",
    "\n",
    "print(\"size (µm):\", [round(s, 5) for s in sim.size])\n",
    "print(\"monitors:\", [m.name for m in sim.monitors])\n",
    "print(\"run_time (s):\", f\"{sim._run_time:.4e}\")\n",
    "\n",
    "_, ax = plt.subplots(figsize=(8, 4))\n",
    "_ = sim.plot(y=0, ax=ax)\n",
    "_ = ax.set_title(\"Cross-section at y = 0 (xz)\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "gratingrun01",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:30.454269Z",
     "iopub.status.busy": "2026-06-22T18:52:30.454145Z",
     "iopub.status.idle": "2026-06-22T18:52:30.811946Z",
     "shell.execute_reply": "2026-06-22T18:52:30.811583Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
16:53:58 -03 Loading simulation from local cache. View cached task using web UI \n",
       "             at                                                                 \n",
       "             'https://tidy3d.simulation.cloud/workbench?taskId=fdve-dfd1b298-9f5\n",
       "             f-4d3d-b6df-74da3f0c99fa'.                                         \n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m16:53:58 -03\u001b[0m\u001b[2;36m \u001b[0mLoading simulation from local cache. View cached task using web UI \n",
       "\u001b[2;36m             \u001b[0mat                                                                 \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=12459073;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dfd1b298-9f5f-4d3d-b6df-74da3f0c99fa\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=12459074;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dfd1b298-9f5f-4d3d-b6df-74da3f0c99fa\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=12459073;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dfd1b298-9f5f-4d3d-b6df-74da3f0c99fa\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=12459075;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dfd1b298-9f5f-4d3d-b6df-74da3f0c99fa\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=12459073;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dfd1b298-9f5f-4d3d-b6df-74da3f0c99fa\u001b\\\u001b[32m-dfd1b298-9f5\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=12459073;https://tidy3d.simulation.cloud/workbench?taskId=fdve-dfd1b298-9f5f-4d3d-b6df-74da3f0c99fa\u001b\\\u001b[32mf-4d3d-b6df-74da3f0c99fa'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run the grating coupler (or load it if already saved) so the result summary below has data.\n",
    "GRATING_DATA_PATH = DATA_DIR / \"grating_coupler_sim_data.hdf5\"\n",
    "if GRATING_DATA_PATH.exists():\n",
    "    sim_data = td.SimulationData.from_file(str(GRATING_DATA_PATH))\n",
    "    print(\"Loaded grating-coupler data from:\", GRATING_DATA_PATH)\n",
    "else:\n",
    "    sim_data = web.run(\n",
    "        sim,\n",
    "        task_name=\"sin_grating_coupler_740nm\",\n",
    "        path=str(GRATING_DATA_PATH),\n",
    "        verbose=True,\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "Mpq9xp6j-a-R",
   "metadata": {
    "id": "Mpq9xp6j-a-R"
   },
   "source": [
    "\n",
    "### Extra Diagnostic: Geometry and Monitor Summary\n",
    "\n",
    "This cell summarizes the simulation size, number of structures, sources, and monitors.  \n",
    "It is useful for checking whether the grating coupler simulation contains the expected waveguide, grating region, source, field monitor, flux monitor, and far-field monitor before running the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "V_NnoesC-ahY",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:30.813654Z",
     "iopub.status.busy": "2026-06-22T18:52:30.813404Z",
     "iopub.status.idle": "2026-06-22T18:52:30.816852Z",
     "shell.execute_reply": "2026-06-22T18:52:30.816486Z"
    },
    "id": "V_NnoesC-ahY"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Geometry and monitor summary ===\n",
      "Simulation size [x, y, z] in µm:\n",
      "[26.417, 3.69, 15.7523]\n",
      "\n",
      "Number of structures:\n",
      "42\n",
      "\n",
      "Sources:\n",
      "- None: center=(-10.5, 0.0, 0.1056), size=(0.0, 10.8, 1.924)\n",
      "\n",
      "Monitors:\n",
      "- field_xz_mid: center=(1.3712000000000018, 0.0, 0.74), size=(8.7927, 0.63, 7.979556)\n",
      "- flux_up_air: center=(0.31200000000000006, 0.0, 7.919799999999999), size=(10.551240000000002, 0.63, 0.0)\n",
      "- radiation_far: center=(0.7488000000000001, 0.0, 7.157599999999999), size=(10.30002, 7.2, 0.0)\n",
      "- mode_transmission: center=(9.280000000000001, 0.0, 0.1056), size=(0.0, 10.8, 1.924)\n",
      "- flux_output_waveguide: center=(9.280000000000001, 0.0, 0.1056), size=(0.0, 10.8, 1.924)\n"
     ]
    }
   ],
   "source": [
    "print(\"=== Geometry and monitor summary ===\")\n",
    "\n",
    "print(\"Simulation size [x, y, z] in µm:\")\n",
    "print([round(v, 4) for v in sim.size])\n",
    "\n",
    "print(\"\\nNumber of structures:\")\n",
    "print(len(sim.structures))\n",
    "\n",
    "print(\"\\nSources:\")\n",
    "for src in sim.sources:\n",
    "    print(f\"- {src.name}: center={src.center}, size={src.size}\")\n",
    "\n",
    "print(\"\\nMonitors:\")\n",
    "for mon in sim.monitors:\n",
    "    print(f\"- {mon.name}: center={mon.center}, size={mon.size}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "syq2G_VIy9hB",
   "metadata": {
    "id": "syq2G_VIy9hB"
   },
   "source": [
    "### Cross-Section in the **xy** Plane (Taper Widens Toward Grating)\n",
    "\n",
    "Use **`sim.plot(z=h)`** with **h** inside the **220 nm Si₃N₄** film (e.g. **0.11 µm**, mid film with `z_intf=0`). Film-plane **SiO₂** fills **y** outside **`±core_width_um/2`** (not only outside the taper width), so wedges beside the widening rib are oxide—not air.\n",
    "\n",
    "With **`z_si_top ≈ 0.22` µm**, **z = 0.26 µm** lies in the **upper SiO₂** cladding (wide oxide above the rib). See [Tidy3D `Simulation.plot`](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html#tidy3d.Simulation.plot)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "0u_qpEBMx0Uk",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:30.818811Z",
     "iopub.status.busy": "2026-06-22T18:52:30.818463Z",
     "iopub.status.idle": "2026-06-22T18:52:31.015578Z",
     "shell.execute_reply": "2026-06-22T18:52:31.015211Z"
    },
    "id": "0u_qpEBMx0Uk"
   },
   "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": [
    "z_mid_film_um = 0.0  # inside SiN film — xy taper outline\n",
    "z_upper_oxide_um = 0.22  # in top SiO2 cladding\n",
    "\n",
    "_, ax_mid = plt.subplots(figsize=(6, 5))\n",
    "_ = sim.plot(z=z_mid_film_um, ax=ax_mid)\n",
    "_ = ax_mid.set_title(f\"xy at z = {z_mid_film_um} µm (mid nitride — taper nar→wide)\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "_, ax_up = plt.subplots(figsize=(6, 5))\n",
    "_ = sim.plot(z=z_upper_oxide_um, ax=ax_up)\n",
    "_ = ax_up.set_title(f\"xy at z = {z_upper_oxide_um} µm (upper SiO₂)\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "AO1NSn00YMV1",
   "metadata": {
    "id": "AO1NSn00YMV1"
   },
   "source": [
    "### Extra Diagnostic: Grating Coupler Result Summary\n",
    "\n",
    "This cell summarizes the main physical results of the SiN grating coupler simulation.  \n",
    "It reports the coupling-efficiency-related metrics, upward radiated flux, and far-field strength.  \n",
    "These quantities help evaluate whether the input waveguide mode is efficiently radiated upward by the grating coupler."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "L0LivfpGYOjI",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-22T18:52:31.017261Z",
     "iopub.status.busy": "2026-06-22T18:52:31.017111Z",
     "iopub.status.idle": "2026-06-22T18:52:31.035851Z",
     "shell.execute_reply": "2026-06-22T18:52:31.035479Z"
    },
    "id": "L0LivfpGYOjI"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Grating coupler result summary ===\n",
      "\n",
      "Coupling efficiency metrics:\n",
      "power_forward_mode0_W: 5.35562e-07\n",
      "power_forward_all_tracked_modes_W: 0.125941\n",
      "power_backward_mode0_W: 2.79422e-09\n",
      "power_backward_all_tracked_modes_W: 0.00015726\n",
      "flux_output_waveguide_W: 0.366555\n",
      "\n",
      "Upward radiation flux:\n",
      "0.0011966\n",
      "\n",
      "Far-field RMS strength:\n",
      "rms_Er: 0.271187\n",
      "rms_Etheta: 0.441152\n",
      "rms_Ephi: 0.331177\n"
     ]
    }
   ],
   "source": [
    "print(\"=== Grating coupler result summary ===\")\n",
    "\n",
    "# Coupling-efficiency-related metrics\n",
    "try:\n",
    "    ce_metrics = coupling_efficiency_metrics(sim_data)\n",
    "\n",
    "    print(\"\\nCoupling efficiency metrics:\")\n",
    "    for key, value in ce_metrics.items():\n",
    "        print(f\"{key}: {value:.6g}\")\n",
    "\n",
    "except Exception as e:\n",
    "    print(\"\\nCould not calculate coupling efficiency metrics:\")\n",
    "    print(e)\n",
    "\n",
    "\n",
    "# Upward radiation flux\n",
    "try:\n",
    "    flux_up = sim_data[\"flux_up_air\"].flux\n",
    "    flux_up_value = float(np.squeeze(flux_up.values))\n",
    "\n",
    "    print(\"\\nUpward radiation flux:\")\n",
    "    print(f\"{flux_up_value:.6g}\")\n",
    "\n",
    "except Exception as e:\n",
    "    print(\"\\nCould not read upward radiation flux:\")\n",
    "    print(e)\n",
    "\n",
    "\n",
    "# Far-field strength summary\n",
    "try:\n",
    "    ff_metrics = postprocess_cartesian_projection(sim_data)\n",
    "\n",
    "    print(\"\\nFar-field RMS strength:\")\n",
    "    for key, value in ff_metrics.items():\n",
    "        if key.startswith(\"rms\"):\n",
    "            print(f\"{key}: {value:.6g}\")\n",
    "\n",
    "except Exception as e:\n",
    "    print(\"\\nCould not calculate far-field metrics:\")\n",
    "    print(e)"
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Passive photonic integrated circuit components"
  ],
  "colab": {
   "provenance": [],
   "toc_visible": true
  },
  "description": "This notebook demonstrates how to design a passive dual-ring Vernier filter and the supporting integrated-laser coupling components at 740 nm using Tidy3D.",
  "feature_image": "./img/system_design.png",
  "features": [
   "Mode analysis"
  ],
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "keywords": "Vernier filter, microring resonator, silicon nitride photonics, Tidy3D, FDTD",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  },
  "title": "How to design a passive dual-ring Vernier filter using Tidy3D | Flexcompute",
  "widgets": {
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       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "
Best weighted RMS error so far: 0.000245 ━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00\n
\n",
          "text/plain": "Best weighted RMS error so far: 0.000245 \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
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Best weighted RMS error so far: 1.16e-05 ━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00\n
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