{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "-"
}
},
"source": [
"# Layout design using gdstk\n",
"\n",
"In Tidy3D, complex structures can be defined via the third-party [gdstk](https://heitzmann.github.io/gdstk/) package. In this tutorial, we will illustrate how to use the package to define an integrated adiabatic coupler. For a tutorial on how to load a previously generated GDS file, please refer to [this](https://www.flexcompute.com/tidy3d/examples/notebooks/GDSImport) example.\n",
"\n",
"\n",
"\n",
"Note that this tutorial requires gdstk, so grab it with `pip install gdstk` before running the tutorial or uncomment the cell line below.\n",
"\n",
"Alternatively, the same layout design can be done using [Photonforge](https://www.flexcompute.com/photonforge/), our photonic design automation tool.\n",
"\n",
"We also provide a comprehensive list of other tutorials such as [how to define boundary conditions](https://www.flexcompute.com/tidy3d/examples/notebooks/BoundaryConditions/), [how to compute the S-matrix of a device](https://www.flexcompute.com/tidy3d/examples/notebooks/SMatrix/), [how to interact with tidy3d's web API](https://www.flexcompute.com/tidy3d/examples/notebooks/WebAPI/), and [how to define self-intersecting polygons](https://www.flexcompute.com/tidy3d/examples/notebooks/SelfIntersectingPolyslab/).\n",
"\n",
"If you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101](https://www.flexcompute.com/fdtd101/) tutorials. "
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# install gdstk\n",
"#!pip install gdstk\n",
"\n",
"# standard python imports\n",
"import os\n",
"\n",
"import gdstk\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"# tidy3d import\n",
"import tidy3d as td"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating the geometry with gdstk\n",
"\n",
"In this section, we will construct an integrated adiabatic coupler as in the title image in this notebook using `gdstk`. If you are only interested in importing an already existing GDSII file, please refer to [this](ttps://www.flexcompute.com/tidy3d/examples/notebooks/GDSImport) tutorial.\n",
"\n",
"We create a function that generates the coupler and returns the corresponding cell. The geometry is built by defining the cross-section of the device in the x-y plane. The cross section can be supplied at the `top`, `bottom`, or the `middle` of the device, specified by the parameter `reference_plane`. Here we choose to define the cross section on the base. There, the two arms of the device start at a distance `wg_spacing_in` apart, then come together at a coupling distance `wg_spacing_coup` for a certain length `coup_length`, and then split again into separate ports. In the coupling region, the field overlap results in energy exchange between the two waveguides. The cell also includes a rectangle around the whole device, which we will use as substrate later. The waveguides use GDS layer 1 and the rectangle layer 0.\n",
"\n",
"Here, we will only see how to define, export, and import such a device using `gdstk`. When importing the device, we can optionally dilate or erode its cross section via `dilation`. In a later example we will simulate the device and study the frequency dependence of the transmission into each of the ports."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [],
"source": [
"def make_coupler(\n",
" length: float,\n",
" wg_spacing_in: float,\n",
" wg_width: float,\n",
" wg_spacing_coup: float,\n",
" wg_spacing_side: float,\n",
" coup_length: float,\n",
" bend_length: float,\n",
") -> gdstk.Cell:\n",
" \"\"\"Make an integrated coupler using the gdstk RobustPath object.\"\"\"\n",
" input_length = length / 2 - coup_length / 2 - bend_length\n",
" if input_length <= 0:\n",
" raise ValueError(\"Device length must be larger than coupling length plus bending regions.\")\n",
"\n",
" delta = (wg_spacing_in - (wg_spacing_coup + wg_width)) / 2\n",
" turn_angle = 2 * np.arctan(delta / bend_length)\n",
" bend_radius = bend_length / 2 / np.sin(turn_angle)\n",
"\n",
" coup = gdstk.RobustPath(\n",
" (-0.5 * length, wg_spacing_in / 2),\n",
" wg_width,\n",
" simple_path=True,\n",
" layer=1,\n",
" )\n",
" coup.segment((input_length, 0), relative=True)\n",
" coup.turn(bend_radius, -turn_angle)\n",
" coup.turn(bend_radius, turn_angle)\n",
" coup.segment((coup_length, 0), relative=True)\n",
" coup.turn(bend_radius, turn_angle)\n",
" coup.turn(bend_radius, -turn_angle)\n",
" coup.segment((0.5 * length, wg_spacing_in / 2))\n",
"\n",
" arm_cell = gdstk.Cell(\"COUPLER_ARM\")\n",
" arm_cell.add(coup)\n",
"\n",
" cell = gdstk.Cell(\"COUPLER\")\n",
" cell.add(gdstk.Reference(arm_cell))\n",
" cell.add(gdstk.Reference(arm_cell, x_reflection=True))\n",
"\n",
" substrate = gdstk.rectangle(\n",
" (-device_length / 2, -(wg_spacing_in + wg_width) / 2 - wg_spacing_side),\n",
" (device_length / 2, (wg_spacing_in + wg_width) / 2 + wg_spacing_side),\n",
" layer=0,\n",
" )\n",
" cell.add(substrate)\n",
" return cell"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can also define some structural parameters. We consider the sidewall of the device to be slanted, deviating from the vertical sidewall by `sidewall_angle`. Positive `sidewall_angle` values corresponds to a typical fabrication scenario where the base of the device is larger than the top."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"### Lengths in micrometers\n",
"\n",
"# Waveguide width\n",
"wg_width = 0.45\n",
"\n",
"# Waveguide separation in the beginning/end\n",
"wg_spacing_in = 4\n",
"\n",
"# Length of the coupling region\n",
"coup_length = 4\n",
"\n",
"# Angle of the sidewall deviating from the vertical ones, positive values for the base larger than the top\n",
"sidewall_angle = np.pi / 6\n",
"\n",
"# Reference plane where the cross section of the device is defined\n",
"reference_plane = \"bottom\"\n",
"\n",
"# Length of the bend region\n",
"bend_length = 6\n",
"\n",
"# Waveguide separation in the coupling region\n",
"wg_spacing_coup = 0.10\n",
"\n",
"# Waveguide separation in the coupling region\n",
"wg_spacing_side = 4.0\n",
"\n",
"# Total device length along propagation direction\n",
"device_length = 25"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Create a gds cell to add our structures to\n",
"coup_cell = make_coupler(\n",
" device_length,\n",
" wg_spacing_in,\n",
" wg_width,\n",
" wg_spacing_coup,\n",
" wg_spacing_side,\n",
" coup_length,\n",
" bend_length,\n",
")\n",
"\n",
"# Create a library for the cell and save it for future use\n",
"gds_path = \"coupler.gds\"\n",
"\n",
"if os.path.exists(gds_path):\n",
" os.remove(gds_path)\n",
"\n",
"lib = gdstk.Library()\n",
"lib.add(coup_cell, *coup_cell.dependencies(True))\n",
"lib.write_gds(gds_path)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Set up Geometries\n",
"\n",
"Next, we can construct tidy3d geometries from the GDS cell we just created, along with other information such as the axis, sidewall angle, and bounds of the \"slab\". When loading GDS cell as the cross section of the device, we can tune ``reference_plane`` to set the cross section to lie at ``bottom``, ``middle``, or ``top`` of the generated [Polyslab](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PolySlab.html) with respect to the axis. E.g. if ``axis=1``, ``bottom`` refers to the negative side of the y-axis, and ``top`` refers to the positive side of the y-axis. Additionally, we can optionally dilate or erode the cross section by setting `dilation`. A negative `dilation` corresponds to erosion.\n",
"\n",
"Note, we have to keep track of the `gds_layer` and `gds_dtype` used to define the GDS cell earlier, so we can load the right components."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# Define waveguide height\n",
"wg_height = 0.22\n",
"dilation = 0.02\n",
"\n",
"substrate_geo = td.Geometry.from_gds(\n",
" coup_cell,\n",
" gds_layer=0,\n",
" gds_dtype=0,\n",
" axis=2,\n",
" slab_bounds=(-4, 0),\n",
" reference_plane=reference_plane,\n",
")\n",
"\n",
"arms_geo = td.Geometry.from_gds(\n",
" coup_cell,\n",
" gds_layer=1,\n",
" gds_dtype=0,\n",
" axis=2,\n",
" slab_bounds=(0, wg_height),\n",
" sidewall_angle=sidewall_angle,\n",
" dilation=dilation,\n",
" reference_plane=reference_plane,\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's plot the base and the top of the coupler waveguide arms to make sure it looks ok. The base of the device should be larger than the top due to a positive `sidewall_angle`."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"f, ax = plt.subplots(2, 1, figsize=(15, 6), tight_layout=True)\n",
"arms_geo.plot(z=0.0, ax=ax[0])\n",
"arms_geo.plot(z=wg_height, ax=ax[1])\n",
"\n",
"ax[0].set_ylim(-5, 5)\n",
"_ = ax[1].set_ylim(-5, 5)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Set up Structures\n",
"\n",
"To make use of these new geometries, we need to load them into a `td.Simulation` as `td.Structures` with material properties.\n",
"\n",
"We'll define the substrate and waveguide mediums and then link them up with the Polyslabs."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# Permittivity of waveguide and substrate\n",
"wg_n = 3.48\n",
"sub_n = 1.45\n",
"medium_wg = td.Medium(permittivity=wg_n**2)\n",
"medium_sub = td.Medium(permittivity=sub_n**2)\n",
"\n",
"# Substrate\n",
"substrate = td.Structure(geometry=substrate_geo, medium=medium_sub)\n",
"\n",
"# Waveguides\n",
"arms = td.Structure(geometry=arms_geo, medium=medium_wg)\n",
"\n",
"structures = [substrate, arms]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Set up Simulation\n",
"\n",
"Now let's set up the rest of the Simulation."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# Spacing between waveguides and PML\n",
"pml_spacing = 1.0\n",
"\n",
"# Simulation size\n",
"sim_size = list(arms_geo.bounding_box.size)\n",
"sim_size[0] -= 4 * pml_spacing\n",
"sim_size[1] += 2 * pml_spacing\n",
"sim_size[2] = wg_height + 2 * pml_spacing\n",
"\n",
"sim_center = list(arms_geo.bounding_box.center)\n",
"sim_center[2] = 0\n",
"\n",
"# grid size in each direction\n",
"dl = 0.020\n",
"\n",
"### Initialize and visualize simulation ###\n",
"sim = td.Simulation(\n",
" size=sim_size,\n",
" center=sim_center,\n",
" grid_spec=td.GridSpec.uniform(dl=dl),\n",
" structures=structures,\n",
" run_time=2e-12,\n",
" boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note: `Tidy3D` is warning us that our Simulation does not contain sources. In this case, since we are using the simulation as a demonstration and are not running any simulations, we may safely ignore this warning throughout this notebook."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plot Simulation Geometry\n",
"\n",
"Let's take a look at the simulation all together with the PolySlabs added. Here the angle of the sidewall deviating from the vertical direction is 30 degree."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(17, 5))\n",
"\n",
"sim.plot(z=wg_height / 2, lw=1, edgecolor=\"k\", ax=ax1)\n",
"sim.plot(x=0.1, lw=1, edgecolor=\"k\", ax=ax2)\n",
"\n",
"ax2.set_xlim([-3, 3])\n",
"_ = ax2.set_ylim([-1, 1])"
]
}
],
"metadata": {
"description": "This notebook demonstrates how to create Tidy3D geometries with gdstk for FDTD simulations.",
"feature_imag": "",
"feature_image": "N/A",
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"keywords": "gds, import, 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": "3.11.2"
},
"title": "GDS File Creation in Tidy3D | Flexcompute"
},
"nbformat": 4,
"nbformat_minor": 4
}
![\"Schematic](\"img/splitter.png\")
\n",
"\n",
"Note that this tutorial requires gdstk, so grab it with `pip install gdstk` before running the tutorial or uncomment the cell line below.\n",
"\n",
"Alternatively, the same layout design can be done using [Photonforge](https://www.flexcompute.com/photonforge/), our photonic design automation tool.\n",
"\n",
"We also provide a comprehensive list of other tutorials such as [how to define boundary conditions](https://www.flexcompute.com/tidy3d/examples/notebooks/BoundaryConditions/), [how to compute the S-matrix of a device](https://www.flexcompute.com/tidy3d/examples/notebooks/SMatrix/), [how to interact with tidy3d's web API](https://www.flexcompute.com/tidy3d/examples/notebooks/WebAPI/), and [how to define self-intersecting polygons](https://www.flexcompute.com/tidy3d/examples/notebooks/SelfIntersectingPolyslab/).\n",
"\n",
"If you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101](https://www.flexcompute.com/fdtd101/) tutorials. "
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# install gdstk\n",
"#!pip install gdstk\n",
"\n",
"# standard python imports\n",
"import os\n",
"\n",
"import gdstk\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"# tidy3d import\n",
"import tidy3d as td"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating the geometry with gdstk\n",
"\n",
"In this section, we will construct an integrated adiabatic coupler as in the title image in this notebook using `gdstk`. If you are only interested in importing an already existing GDSII file, please refer to [this](ttps://www.flexcompute.com/tidy3d/examples/notebooks/GDSImport) tutorial.\n",
"\n",
"We create a function that generates the coupler and returns the corresponding cell. The geometry is built by defining the cross-section of the device in the x-y plane. The cross section can be supplied at the `top`, `bottom`, or the `middle` of the device, specified by the parameter `reference_plane`. Here we choose to define the cross section on the base. There, the two arms of the device start at a distance `wg_spacing_in` apart, then come together at a coupling distance `wg_spacing_coup` for a certain length `coup_length`, and then split again into separate ports. In the coupling region, the field overlap results in energy exchange between the two waveguides. The cell also includes a rectangle around the whole device, which we will use as substrate later. The waveguides use GDS layer 1 and the rectangle layer 0.\n",
"\n",
"Here, we will only see how to define, export, and import such a device using `gdstk`. When importing the device, we can optionally dilate or erode its cross section via `dilation`. In a later example we will simulate the device and study the frequency dependence of the transmission into each of the ports."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [],
"source": [
"def make_coupler(\n",
" length: float,\n",
" wg_spacing_in: float,\n",
" wg_width: float,\n",
" wg_spacing_coup: float,\n",
" wg_spacing_side: float,\n",
" coup_length: float,\n",
" bend_length: float,\n",
") -> gdstk.Cell:\n",
" \"\"\"Make an integrated coupler using the gdstk RobustPath object.\"\"\"\n",
" input_length = length / 2 - coup_length / 2 - bend_length\n",
" if input_length <= 0:\n",
" raise ValueError(\"Device length must be larger than coupling length plus bending regions.\")\n",
"\n",
" delta = (wg_spacing_in - (wg_spacing_coup + wg_width)) / 2\n",
" turn_angle = 2 * np.arctan(delta / bend_length)\n",
" bend_radius = bend_length / 2 / np.sin(turn_angle)\n",
"\n",
" coup = gdstk.RobustPath(\n",
" (-0.5 * length, wg_spacing_in / 2),\n",
" wg_width,\n",
" simple_path=True,\n",
" layer=1,\n",
" )\n",
" coup.segment((input_length, 0), relative=True)\n",
" coup.turn(bend_radius, -turn_angle)\n",
" coup.turn(bend_radius, turn_angle)\n",
" coup.segment((coup_length, 0), relative=True)\n",
" coup.turn(bend_radius, turn_angle)\n",
" coup.turn(bend_radius, -turn_angle)\n",
" coup.segment((0.5 * length, wg_spacing_in / 2))\n",
"\n",
" arm_cell = gdstk.Cell(\"COUPLER_ARM\")\n",
" arm_cell.add(coup)\n",
"\n",
" cell = gdstk.Cell(\"COUPLER\")\n",
" cell.add(gdstk.Reference(arm_cell))\n",
" cell.add(gdstk.Reference(arm_cell, x_reflection=True))\n",
"\n",
" substrate = gdstk.rectangle(\n",
" (-device_length / 2, -(wg_spacing_in + wg_width) / 2 - wg_spacing_side),\n",
" (device_length / 2, (wg_spacing_in + wg_width) / 2 + wg_spacing_side),\n",
" layer=0,\n",
" )\n",
" cell.add(substrate)\n",
" return cell"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can also define some structural parameters. We consider the sidewall of the device to be slanted, deviating from the vertical sidewall by `sidewall_angle`. Positive `sidewall_angle` values corresponds to a typical fabrication scenario where the base of the device is larger than the top."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"### Lengths in micrometers\n",
"\n",
"# Waveguide width\n",
"wg_width = 0.45\n",
"\n",
"# Waveguide separation in the beginning/end\n",
"wg_spacing_in = 4\n",
"\n",
"# Length of the coupling region\n",
"coup_length = 4\n",
"\n",
"# Angle of the sidewall deviating from the vertical ones, positive values for the base larger than the top\n",
"sidewall_angle = np.pi / 6\n",
"\n",
"# Reference plane where the cross section of the device is defined\n",
"reference_plane = \"bottom\"\n",
"\n",
"# Length of the bend region\n",
"bend_length = 6\n",
"\n",
"# Waveguide separation in the coupling region\n",
"wg_spacing_coup = 0.10\n",
"\n",
"# Waveguide separation in the coupling region\n",
"wg_spacing_side = 4.0\n",
"\n",
"# Total device length along propagation direction\n",
"device_length = 25"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Create a gds cell to add our structures to\n",
"coup_cell = make_coupler(\n",
" device_length,\n",
" wg_spacing_in,\n",
" wg_width,\n",
" wg_spacing_coup,\n",
" wg_spacing_side,\n",
" coup_length,\n",
" bend_length,\n",
")\n",
"\n",
"# Create a library for the cell and save it for future use\n",
"gds_path = \"coupler.gds\"\n",
"\n",
"if os.path.exists(gds_path):\n",
" os.remove(gds_path)\n",
"\n",
"lib = gdstk.Library()\n",
"lib.add(coup_cell, *coup_cell.dependencies(True))\n",
"lib.write_gds(gds_path)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Set up Geometries\n",
"\n",
"Next, we can construct tidy3d geometries from the GDS cell we just created, along with other information such as the axis, sidewall angle, and bounds of the \"slab\". When loading GDS cell as the cross section of the device, we can tune ``reference_plane`` to set the cross section to lie at ``bottom``, ``middle``, or ``top`` of the generated [Polyslab](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.PolySlab.html) with respect to the axis. E.g. if ``axis=1``, ``bottom`` refers to the negative side of the y-axis, and ``top`` refers to the positive side of the y-axis. Additionally, we can optionally dilate or erode the cross section by setting `dilation`. A negative `dilation` corresponds to erosion.\n",
"\n",
"Note, we have to keep track of the `gds_layer` and `gds_dtype` used to define the GDS cell earlier, so we can load the right components."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# Define waveguide height\n",
"wg_height = 0.22\n",
"dilation = 0.02\n",
"\n",
"substrate_geo = td.Geometry.from_gds(\n",
" coup_cell,\n",
" gds_layer=0,\n",
" gds_dtype=0,\n",
" axis=2,\n",
" slab_bounds=(-4, 0),\n",
" reference_plane=reference_plane,\n",
")\n",
"\n",
"arms_geo = td.Geometry.from_gds(\n",
" coup_cell,\n",
" gds_layer=1,\n",
" gds_dtype=0,\n",
" axis=2,\n",
" slab_bounds=(0, wg_height),\n",
" sidewall_angle=sidewall_angle,\n",
" dilation=dilation,\n",
" reference_plane=reference_plane,\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's plot the base and the top of the coupler waveguide arms to make sure it looks ok. The base of the device should be larger than the top due to a positive `sidewall_angle`."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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",
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