{ "cells": [ { "cell_type": "markdown", "id": "02533116-7df1-4fda-9018-92b3a311a3aa", "metadata": { "tags": [] }, "source": [ "# Q3D Capacitance Matrix of a MultiPlanar Design with pyaedt\n", "\n", "A `MultiPlanar` design reads its layers from a layer-stack file: for each layer, its z position, thickness, material and whether it is filled. The pyaedt renderers use that stack to build the 3D model in Ansys.\n", "\n", "**Note:** this may work only with the full (paid) version of Ansys, not the student version. This issue is fixable and requires more testing. Please run the notebook and test it out on student license, if you're interested to make a contribution!" ] }, { "cell_type": "markdown", "id": "q3d-badges", "metadata": {}, "source": [ "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/qiskit-community/qiskit-metal/blob/main/docs/tut/4-Analysis/pyaedt-multiplanar/Q3D-pyaedt-multiplanar.ipynb)\n", "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/qiskit-community/qiskit-metal/main?labpath=docs%2Ftut%2F4-Analysis%2Fpyaedt-multiplanar%2FQ3D-pyaedt-multiplanar.ipynb)" ] }, { "cell_type": "markdown", "id": "3b36ee18", "metadata": {}, "source": [ "> 💡 **Desktop GUI or inline.** `metal.gui(design)` opens the desktop `MetalGUI` when Qt and a display are available and falls back to an inline viewer (Colab, Binder, a server) with the same API, so `gui.rebuild()` and `gui.screenshot()` work in both. See [1.1 Quick start](https://qiskit-community.github.io/qiskit-metal/tut/1-Overview/1.1-Quick-start.html) and [`docs/headless-usage.rst`](https://qiskit-community.github.io/qiskit-metal/headless-usage.html).\n", ">\n", "> Everything up to and including the layout runs anywhere. The rest drives Ansys through pyaedt (Q3D: setup, analysis, capacitance matrix per pass); those cells need Ansys Electronics Desktop and are shown here without outputs." ] }, { "cell_type": "markdown", "id": "simulation-pathways", "metadata": {}, "source": [ "> 🧭 **Other simulation pathways.** This notebook uses Ansys, which needs a license. Without one, the same kind of result can come from the open-source ElmerFEM path for capacitance (tutorial 4.19) or the pip-installable gmsh + scikit-fem solver for eigenmodes, couplings and capacitance (tutorials 4.43–4.45); AWS Palace is available through SQDMetal, with a native integration in progress. [Simulation pathways](https://qiskit-community.github.io/qiskit-metal/simulation-pathways.html) summarizes what each solver computes, how to install it, and which tutorials use it." ] }, { "cell_type": "code", "execution_count": 2, "id": "4556b9a4-4431-4c31-b02f-24247c89a41f", "metadata": {}, "outputs": [], "source": [ "import qiskit_metal as metal\n", "from qiskit_metal import Dict\n", "from qiskit_metal.designs.design_multiplanar import MultiPlanar\n", "from qiskit_metal.renderers.renderer_ansys_pyaedt.q3d_renderer_aedt import QQ3DPyaedt" ] }, { "cell_type": "markdown", "id": "98703b6d-638a-4fcd-92ed-443a5169ac46", "metadata": {}, "source": [ "## Layer stack\n", "\n", "The layer stack is a CSV file with one row per layer and datatype." ] }, { "cell_type": "code", "execution_count": 3, "id": "87b9784b-f9d9-412c-8894-5a26ff6aef4f", "metadata": { "tags": [] }, "outputs": [], "source": [ "# The example stack ships with the tutorials, in docs/tut/resources/.\n", "ls_file_path = \"../../resources/layer_stack_data_example_1.csv\"\n", "\n", "multiplanar_design = MultiPlanar(\n", " metadata={}, overwrite_enabled=True, layer_stack_filename=ls_file_path\n", ")" ] }, { "cell_type": "markdown", "id": "282a5872-956d-4e98-92f8-ba3a5493451d", "metadata": {}, "source": [ "## Multi-Planar design has default of chip named main. If there is more than one, add information to multiplanar design." ] }, { "cell_type": "code", "execution_count": 4, "id": "e4985b4d-3b23-4bda-91ae-25876fd689a0", "metadata": {}, "outputs": [], "source": [ "multiplanar_design._chips[\"qubit_chip\"] = Dict()\n", "multiplanar_design._chips.qubit_chip.size = Dict(\n", " center_x=\"0.0mm\",\n", " center_y=\"0.0mm\",\n", " size_x=\"4mm\",\n", " size_y=\"7mm\",\n", ")\n", "\n", "\n", "# Override the default values size for chip=='main'.\n", "multiplanar_design.chips.main.size[\"size_x\"] = \"2mm\"\n", "multiplanar_design.chips.main.size[\"size_y\"] = \"2mm\"" ] }, { "cell_type": "code", "execution_count": 5, "id": "aee98fa4-5791-426a-8098-eca96de2ca1e", "metadata": {}, "outputs": [ { "output_type": "execute_result", "metadata": {}, "data": { "text/plain": "{'main': {'size': {'center_x': '0.0mm',\n 'center_y': '0.0mm',\n 'size_x': '2mm',\n 'size_y': '2mm'}},\n 'qubit_chip': {'size': {'center_x': '0.0mm',\n 'center_y': '0.0mm',\n 'size_x': '4mm',\n 'size_y': '7mm'}}}" }, "execution_count": 5 } ], "source": [ "multiplanar_design.chips" ] }, { "cell_type": "code", "execution_count": 6, "id": "3faa626f-3df7-4452-9ada-77264cd87305", "metadata": {}, "outputs": [], "source": [ "# Remember, the layers may not always be unique, since there can be multiple datatypes.\n", "ls_unique = multiplanar_design.ls.is_layer_data_unique()" ] }, { "cell_type": "markdown", "id": "03443c7c-eeb1-42aa-8bd3-5eaa52dbfb1e", "metadata": {}, "source": [ "## Open the GUI on the MultiPlanar design" ] }, { "cell_type": "code", "execution_count": 7, "id": "b30d9881-6ae2-4153-ac22-38845e3b0ffd", "metadata": {}, "outputs": [], "source": [ "gui = metal.gui(multiplanar_design)" ] }, { "cell_type": "markdown", "id": "fde66a1a-8c3d-4bc2-aaa6-fda162f3c44c", "metadata": { "tags": [] }, "source": [ "## Add all components to design. \n", "\n", "### Note the layer number and chip names are used when adding components to design. " ] }, { "cell_type": "code", "execution_count": 8, "id": "1cb28265-f90a-4785-9ac8-e6cbef7df99e", "metadata": { "tags": [] }, "outputs": [ { "output_type": "display_data", "metadata": { "image/png": { "width": 500 } }, "data": { "image/png": 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", "text/plain": "" } } ], "source": [ "from qiskit_metal.qlibrary.qubits.transmon_pocket import TransmonPocket\n", "from qiskit_metal.qlibrary.terminations.open_to_ground import OpenToGround\n", "from qiskit_metal.qlibrary.tlines.meandered import RouteMeander\n", "from qiskit_metal.qlibrary.tlines.mixed_path import RouteMixed\n", "from qiskit_metal.qlibrary.qubits.transmon_concentric import TransmonConcentric\n", "\n", "# As precaution, remove any components already previously to design.\n", "multiplanar_design.delete_all_components()\n", "\n", "\n", "qubit_cpw_otg_layer = 2\n", "qubit_chip_name = \"qubit_chip\"\n", "\n", "\n", "q1 = TransmonPocket(\n", " multiplanar_design,\n", " \"Q1\",\n", " options=dict(\n", " pad_width=\"425 um\",\n", " pocket_height=\"650um\",\n", " layer=qubit_cpw_otg_layer,\n", " chip=qubit_chip_name,\n", " # orientation='44',\n", " orientation=\"0\",\n", " connection_pads=dict(readout=dict(loc_W=+1, loc_H=+1, pad_width=\"200um\")),\n", " ),\n", ")\n", "\n", "otg = OpenToGround(\n", " multiplanar_design,\n", " \"open_to_ground\",\n", " options=dict(\n", " pos_x=\"1.75mm\",\n", " pos_y=\"0um\",\n", " orientation=\"0\",\n", " layer=qubit_cpw_otg_layer,\n", " chip=qubit_chip_name,\n", " ),\n", ")\n", "\n", "route_meaander = RouteMeander(\n", " multiplanar_design,\n", " \"readout\",\n", " Dict(\n", " layer=qubit_cpw_otg_layer,\n", " chip=qubit_chip_name,\n", " total_length=\"3 mm\",\n", " hfss_wire_bonds=True,\n", " fillet=\"90 um\",\n", " lead=dict(start_straight=\"100um\"),\n", " pin_inputs=Dict(\n", " start_pin=Dict(component=\"Q1\", pin=\"readout\"),\n", " end_pin=Dict(component=\"open_to_ground\", pin=\"open\"),\n", " ),\n", " ),\n", ")\n", "\n", "##############################################################################\n", "optionsQ = dict(\n", " pad_width=\"425 um\",\n", " pocket_height=\"650um\",\n", " layer=qubit_cpw_otg_layer,\n", " chip=qubit_chip_name,\n", " orientation=\"-44\",\n", " # orientation='0',\n", " connection_pads=dict( # Qbits defined to have 4 pins\n", " a=dict(loc_W=+1, loc_H=+1),\n", " b=dict(loc_W=-1, loc_H=+1, pad_height=\"30um\"),\n", " c=dict(loc_W=+1, loc_H=-1, pad_width=\"200um\"),\n", " d=dict(loc_W=-1, loc_H=-1, pad_height=\"50um\"),\n", " ),\n", ")\n", "\n", "q2 = TransmonPocket(\n", " multiplanar_design, \"Q2\", options=dict(pos_x=\"-1.5mm\", pos_y=\"+0.0mm\", **optionsQ)\n", ")\n", "\n", "##############################################################################\n", "concentric_options = dict(\n", " # chip='main',\n", " pos_x=\"400um\",\n", " pos_y=\"900um\",\n", " # layer='1', # default is 1, this is just for example. This component does NOT have option for layer.\n", " pocket_w=\"1500um\", # transmon pocket width\n", " pocket_h=\"900um\", # transmon pocket height\n", ")\n", "\n", "# Create a new Concentric Transmon object with name 'Q1'\n", "qc1 = TransmonConcentric(multiplanar_design, \"cc_qubit\", options=concentric_options)\n", "\n", "\n", "gui.rebuild()\n", "gui.autoscale()\n", "gui.screenshot()" ] }, { "cell_type": "markdown", "id": "7c11b9c3-030d-432e-9b93-59096dcd7420", "metadata": {}, "source": [ "## Start the Q3D renderer for Ansys by passing arguments to QQ3DPyaedt.\n", "## The default will use default names for Ansys ProjectName and Ansys DesignName." ] }, { "cell_type": "code", "execution_count": 9, "id": "401c0b56-5a54-4ea9-873b-854ef9be26cd", "metadata": { "tags": [] }, "outputs": [], "source": [ "multi_q3d = QQ3DPyaedt(multiplanar_design)\n", "\n", "# Example of passing names for project and design.\n", "# multi_q3d_1 = QQ3DPyaedt(multiplanar_design, \"q3d_project_1\", \"q3d_design_1\")" ] }, { "cell_type": "code", "execution_count": 10, "id": "c0898fc3-639b-496e-a60d-feeb2c5ae954", "metadata": {}, "outputs": [ { "output_type": "execute_result", "metadata": {}, "data": { "text/plain": "{'name': 'QQ3DPyaedt_setup',\n 'AdaptiveFreq': '5.0',\n 'SaveFields': 'False',\n 'Enabled': 'True',\n 'MaxPass': '15',\n 'MinPass': '2',\n 'MinConvPass': '2',\n 'PerError': '0.5',\n 'PerRefine': '30',\n 'AutoIncreaseSolutionOrder': 'True',\n 'SolutionOrder': 'High',\n 'Solver_Type': 'Iterative'}" }, "execution_count": 10 } ], "source": [ "\"\"\"Create a solution setup in Ansys Q3D. If user does not provide\n", " arguments, they will be obtained from QQ3DPyaedt.default_setup dict.\n", "\n", "Args:\n", " name (str, optional): Name of solution setup. Defaults to None.\n", " AdaptiveFreq (float, optional): Adaptive frequency in GHz. Defaults to None.\n", " SaveFields (bool, optional): Whether or not to save fields. Defaults to None.\n", " Enabled (bool, optional): Whether or not setup is enabled. Defaults to None.\n", " MaxPass (int, optional): Maximum number of passes. Defaults to None.\n", " MinPass (int, optional): Minimum number of passes. Defaults to None.\n", " MinConvPass (int, optional): Minimum number of converged passes. Defaults to None.\n", " PerError (float, optional): Error tolerance as a percentage. Defaults to None.\n", " PerRefine (int, optional): Refinement as a percentage. Defaults to None.\n", " AutoIncreaseSolutionOrder (bool, optional): Whether or not to increase solution order automatically. Defaults to None.\n", " SolutionOrder (str, optional): Solution order. Defaults to None.\n", " Solver_Type (str, optional): Solver type. Defaults to None.\n", "\"\"\"\n", "\n", "QQ3DPyaedt.default_setup" ] }, { "cell_type": "code", "execution_count": null, "id": "3e51ce91-008d-47a3-8f7e-4f6dd4947d01", "metadata": { "tags": [ "requires-ansys" ] }, "outputs": [], "source": [ "# Use all default values.\n", "multi_q3d.add_q3d_setup()\n", "\n", "# Reduce MaxPass when running notebook as an example.\n", "multi_q3d.add_q3d_setup(name=\"fun_test\", MaxPass=3)" ] }, { "cell_type": "markdown", "id": "938c363f-98c3-4c02-98fe-1d2f017d4b30", "metadata": {}, "source": [ "## Render the multi-planar design using the similar convention as planar-design to identify ports." ] }, { "cell_type": "code", "execution_count": null, "id": "5558b1a3-be2a-41bc-9c91-aa44b7130851", "metadata": { "tags": [ "requires-ansys" ] }, "outputs": [], "source": [ "multi_q3d.render_design(\n", " selection=[\"Q1\"], box_plus_buffer=True, open_pins=[(\"Q1\", \"readout\")]\n", ")\n", "\n", "\n", "############# Below are samples of different rendering arguments.\n", "\n", "# multi_q3d.render_design(selection=['Q1', 'Q2', 'cc_qubit'],\n", "# box_plus_buffer=True,\n", "# open_pins=[('Q1', 'readout'), ('Q2', 'a'), ('Q2', 'b'),\n", "# ('Q2', 'd')])\n", "\n", "\n", "# multi_q3d.render_design(selection=['mult_planar_readout'])\n", "\n", "# multi_q3d.render_design(selection=['readout'])\n", "\n", "# multi_q3d.render_design(selection=[], box_plus_buffer=False)\n", "\n", "# multi_q3d.render_design(selection=['Q1', 'readout'], box_plus_buffer=True)\n", "\n", "# multi_q3d.render_design(selection=[], box_plus_buffer=False)" ] }, { "cell_type": "markdown", "id": "7a256cef-d4b2-4469-8477-9291a5ec89a1", "metadata": {}, "source": [ "## Select the name to analyze. Presently, we have two to choose from. The default=='QQ3DPyaedt_setup' and 'fun_test'." ] }, { "cell_type": "code", "execution_count": null, "id": "69004c7c-801c-4dff-a9a5-634d053c7f1c", "metadata": { "tags": [ "requires-ansys" ] }, "outputs": [], "source": [ "multi_q3d.analyze_setup(\"fun_test\")" ] }, { "cell_type": "markdown", "id": "9756795c-81a6-4bf7-a25f-7b698cc8c1dd", "metadata": {}, "source": [ "## Get the result of analyze_setup.\n", "### You can get the capacitance matrix in pandas dataframes format, for the AdaptiveFreq in GHz which was 5.0 in our example." ] }, { "cell_type": "code", "execution_count": null, "id": "b7d0186d-8ea5-4ebc-9085-8e80e0b19802", "metadata": { "tags": [ "requires-ansys" ] }, "outputs": [], "source": [ "cap_data = multi_q3d.get_capacitance_all_passes(\"fun_test\")" ] }, { "cell_type": "code", "execution_count": null, "id": "2c604f1c-4b5a-43c4-84a6-50a6cdae6937", "metadata": { "tags": [ "requires-ansys" ] }, "outputs": [], "source": [ "# For Freq==5.0\n", "all_cap_data = cap_data[5.0]\n", "all_cap_data" ] }, { "cell_type": "code", "execution_count": null, "id": "85c8f5ce-0e62-49ed-8b56-fc605e555cd2", "metadata": { "tags": [ "requires-ansys" ] }, "outputs": [], "source": [ "# For 1st pass\n", "pass_1 = cap_data[5.0][1]\n", "pass_1" ] }, { "cell_type": "code", "execution_count": null, "id": "2369b99b-26c9-4c84-aa42-c0409499fd34", "metadata": { "tags": [ "requires-ansys" ] }, "outputs": [], "source": [ "# For 2nd pass\n", "pass_2 = cap_data[5.0][2]\n", "pass_2" ] }, { "cell_type": "code", "execution_count": null, "id": "4d7203e5-2d45-4d64-b365-111434fc97c7", "metadata": { "tags": [ "requires-ansys" ] }, "outputs": [], "source": [ "# For 3rd pass\n", "pass_3 = cap_data[5.0][3]\n", "pass_3" ] }, { "cell_type": "code", "execution_count": 11, "id": "0b40dcec-d9e6-4041-b72a-91ae5443e94a", "metadata": {}, "outputs": [], "source": [ "# 4th pass does not exist, since we limited passes to three passes.\n", "# pass_4 = cap_data[5.0][4]\n", "# pass_4" ] }, { "cell_type": "code", "execution_count": null, "id": "2516e435-75ee-4e6e-8406-d5708748dba7", "metadata": { "tags": [ "requires-ansys" ] }, "outputs": [], "source": [ "# Will disconnect Metal from Ansys, and leave Ansys open.\n", "# multi_q3d.close()\n", "\n", "# # If the python script closes, the OS will most likely close Ansys.\n", "\n", "# Will close Ansys.\n", "# multi_q3d.force_exit_ansys()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" } }, "nbformat": 4, "nbformat_minor": 5 }