{ "cells": [ { "cell_type": "markdown", "id": "23c04350", "metadata": {}, "source": [ "## Optimized photonic crystal cavity\n", "\n", "In this notebook, we will simulate an optimized version of the commonly used L3 photonic crystal cavity composed of three missing holes in a hexagonal lattice of holes in a silicon slab. The design we use was optimized in the paper [A full degree-of-freedom photonic crystal spatial light modulator](https://www.nature.com/articles/s41566-022-01086-9) to simultaneously have a very high quality factor and far-field emission strongly localized around the cavity normal direction." ] }, { "cell_type": "code", "execution_count": 1, "id": "fa696798", "metadata": { "execution": { "iopub.execute_input": "2023-02-03T03:31:19.011197Z", "iopub.status.busy": "2023-02-03T03:31:19.010877Z", "iopub.status.idle": "2023-02-03T03:31:20.692674Z", "shell.execute_reply": "2023-02-03T03:31:20.692246Z" } }, "outputs": [ { "data": { "text/html": [ "
[21:31:19] WARNING This version of Tidy3D was pip installed from the 'tidy3d-beta' repository on __init__.py:103\n", " PyPI. Future releases will be uploaded to the 'tidy3d' repository. From now on, \n", " please use 'pip install tidy3d' instead. \n", "\n" ], "text/plain": [ "\u001b[2;36m[21:31:19]\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING \u001b[0m This version of Tidy3D was pip installed from the \u001b[32m'tidy3d-beta'\u001b[0m repository on \u001b]8;id=98440;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=511687;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#103\u001b\\\u001b[2m103\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[2;36m \u001b[0m PyPI. Future releases will be uploaded to the \u001b[32m'tidy3d'\u001b[0m repository. From now on, \u001b[2m \u001b[0m\n", "\u001b[2;36m \u001b[0m please use \u001b[32m'pip install tidy3d'\u001b[0m instead. \u001b[2m \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
INFO Using client version: 1.9.0rc1 __init__.py:121\n", "\n" ], "text/plain": [ "\u001b[2;36m \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO \u001b[0m Using client version: \u001b[1;36m1.9\u001b[0m.0rc1 \u001b]8;id=457610;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=884155;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#121\u001b\\\u001b[2m121\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from os.path import join\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "import tidy3d as td\n", "from tidy3d.plugins import ResonanceFinder\n", "from tidy3d import web\n" ] }, { "cell_type": "markdown", "id": "1c81b043", "metadata": {}, "source": [ "### Initialize geometry\n", "\n", "We will read in hole positions and radii from file, in units of lattice constant. The holes are only defined in one quadrant so we have to use symmetry later on when defining the simulation. If symmetry is not applied in the simulation, we have to expand the hole list to append holes in the other quadrants. Note also that the holes correspond to a *periodic* arrangement of cavities, as for the spatial light modulator structure studied in the paper." ] }, { "cell_type": "code", "execution_count": 2, "id": "fc301459", "metadata": { "execution": { "iopub.execute_input": "2023-02-03T03:31:20.695293Z", "iopub.status.busy": "2023-02-03T03:31:20.694989Z", "iopub.status.idle": "2023-02-03T03:31:20.699560Z", "shell.execute_reply": "2023-02-03T03:31:20.699095Z" } }, "outputs": [], "source": [ "holes_file = np.loadtxt(join(\"misc\", \"optimized_L3_holes.txt\"))\n", "xs, ys, rs = holes_file.T # in units of um\n" ] }, { "cell_type": "code", "execution_count": 3, "id": "b447677a", "metadata": { "execution": { "iopub.execute_input": "2023-02-03T03:31:20.701930Z", "iopub.status.busy": "2023-02-03T03:31:20.701762Z", "iopub.status.idle": "2023-02-03T03:31:20.704872Z", "shell.execute_reply": "2023-02-03T03:31:20.704513Z" } }, "outputs": [], "source": [ "# Periodicity in units of PhC periods in x and y directions\n", "nx, ny = 32, 32\n", "\n", "# Lattice constant of the PhC in micron\n", "alattice = 0.4\n", "\n", "# Regular PhC lattice parameters\n", "r_hole = 0.1 # radius of holes in regular PhC region\n", "d_slab = 0.22 # slab thickness\n", "n_slab = 3.4757 # refractive index of the slab\n", "\n", "# Materials - air and silicon\n", "air = td.Medium()\n", "si = td.Medium(permittivity=n_slab**2)\n", "\n", "# Simulation domain size (micron)\n", "size_z = 6\n", "sim_size = [(nx + 1) * alattice, (ny + 1) * alattice * np.sqrt(3) / 2, size_z]\n" ] }, { "cell_type": "code", "execution_count": 4, "id": "f82c55d6", "metadata": { "execution": { "iopub.execute_input": "2023-02-03T03:31:20.706988Z", "iopub.status.busy": "2023-02-03T03:31:20.706845Z", "iopub.status.idle": "2023-02-03T03:31:20.722052Z", "shell.execute_reply": "2023-02-03T03:31:20.721667Z" } }, "outputs": [], "source": [ "# Initialize structures\n", "slab = td.Structure(\n", " geometry=td.Box(center=[0, 0, 0], size=[td.inf, td.inf, d_slab]), medium=si\n", ")\n", "\n", "holes_group = []\n", "# Add all provided optimized holes\n", "for x, y, r in zip(xs, ys, rs):\n", " holes_group.append(td.Cylinder(center=[x, y, 0], radius=r, length=d_slab))\n", "\n", "# Pad with regular PhC holes outside of the optimized region\n", "xmax_opt = np.amax(np.int64(xs / alattice))\n", "ymax_opt = np.amax(np.int64(ys / alattice * 2 / np.sqrt(3)))\n", "nx_pos, ny_pos = nx // 2 + 1, ny // 2 + 1\n", "for iy in range(ny_pos):\n", " for ix in range(nx_pos):\n", " if ix > xmax_opt or iy > ymax_opt:\n", " xp = ix + (iy % 2) * 0.5\n", " yp = iy * np.sqrt(3) / 2\n", " holes_group.append(\n", " td.Cylinder(center=[xp, yp, 0], radius=r_hole, length=d_slab)\n", " )\n", "\n", "holes = td.Structure(geometry=td.GeometryGroup(geometries=holes_group), medium=air)\n" ] }, { "cell_type": "markdown", "id": "682713be", "metadata": {}, "source": [ "### Initialize source\n", "\n", "We will be looking for the fundamental mode of the L3 cavity, so we use a y-polarized source at the center of the cavity." ] }, { "cell_type": "code", "execution_count": 5, "id": "ad414ec3", "metadata": { "execution": { "iopub.execute_input": "2023-02-03T03:31:20.724206Z", "iopub.status.busy": "2023-02-03T03:31:20.724052Z", "iopub.status.idle": "2023-02-03T03:31:21.081711Z", "shell.execute_reply": "2023-02-03T03:31:21.081246Z" } }, "outputs": [ { "data": { "text/plain": [ "
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\n", "\n" ], "text/plain": [ "\n", "\u001b[?25h" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sim_data = web.run(sim, task_name=\"L3_opt\")\n" ] }, { "cell_type": "markdown", "id": "27256e0e", "metadata": {}, "source": [ "### Analyze data\n", "\n", "First, we can examine the raw time series data and we can also compute the spectrum corresponding to it." ] }, { "cell_type": "code", "execution_count": 10, "id": "f8604b88", "metadata": { "execution": { "iopub.execute_input": "2023-02-03T03:34:29.100061Z", "iopub.status.busy": "2023-02-03T03:34:29.099832Z", "iopub.status.idle": "2023-02-03T03:34:29.982511Z", "shell.execute_reply": "2023-02-03T03:34:29.981712Z" } }, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Spectrum')" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
\n", " | decay | \n", "Q | \n", "amplitude | \n", "phase | \n", "error | \n", "
---|---|---|---|---|---|
freq | \n", "\n", " | \n", " | \n", " | \n", " | \n", " |
1.915336e+14 | \n", "6.955702e+08 | \n", "865075.124478 | \n", "12193.271309 | \n", "-0.094253 | \n", "0.002133 | \n", "