Ansys export

Once the simulation object is created, call function export_ansys_json to export the geometry as GDSII file and meta-data in json format. Parameter ansys_tool determines whether to use HFSS (‘hfss’) or Q3D Extractor (‘q3d’). HFSS eigenmode simulations are done with ‘eigenmode’, this is used for pyEPR as well:

from kqcircuits.simulations.export.ansys.ansys_export import export_ansys_json, copy_ansys_scripts_to_directory, export_ansys_bat, export_ansys
path = "C:\\Your\\Path\\Here\\"
json = export_ansys_json(simulation, path, ansys_tool='hfss')

Performing simulations requires Ansys-scripts, which are located at scripts/simulations/ansys/. Usually, it’s convenient to copy this folder to the export path by calling copy_ansys_scripts_to_directory:

copy_ansys_scripts_to_directory(path)

You can create a Windows batch file for running multiple simulations in a row by calling function export_ansys_bat. The first argument is a list of exported json filenames:

bat = export_ansys_bat([json], path)

Alternatively, you can call export_ansys to cover last three steps. This exports multiple simulations that are stored in a list, copies the Ansys-scripts into the folder, and creates the Windows batch file:

bat = export_ansys([simulation], path, ansys_tool='hfss')

Ansys scripts

The folder scripts/simulations/ansys/ contains several IronPython scripts to run simulations in Ansys Electronics Desktop. Scripts support HFSS and Q3D Extractor frameworks.

The scripts are developed and tested with Ansys Electronic Desktop 2022 R2 on Windows x64.

The primary use case is to estimate capacitive couplings between different elements in the layout, where each element of interest has a port in the simulation. The capacitances are represented as a matrix, where the Cij is the capacitance between two ports i and j, and Cii is the capacitance between port i and ground.

Main scripts

  • import_simulation_geometry.py

    Argument: path to json file exported by export_ansys_json.

    Creates a new project, imports the geometry, defines ports/nets and materials, and sets up the analysis setup.

  • create_capacitive_pi_model.py

    No argument.

    Adds solution variables and reports for a PI model between all ports/nets in the current design.

    The variables yy_i_j give the scalar admittance between port i and j, or the admittance from port i to ground if i==j. The yy-variables are created only in HFSS.

    Similarly, the variables C_i_j give the capacitance between ports and from ports to ground, assuming a purely capacitive model. This assumption is valid as long as the resulting C_i_j are constant over frequency.

  • export_solution_data.py

    No argument.

    Exports data from the solutions. projectname_CMatrix.txt contains the elements C_i_j in fF (at 1 GHz in HFSS). projectname_results.json contains all C_i_j and yy_i_j elements for all frequencies in the solution. In case of HFSS, projectname_SMatrix.s2p contains the S-parameters.

  • import_and_simulate.py

    Argument: path to json file exported by export_ansys_json.

    Performs the full simulation sequence including running the three other scripts, saving the project, and running the simulation.

Additional scripts for use cases other than capacitive coupling exist. These are enabled in import_and_simulate.py with a list of strings as parameters to export_ansys, e.g., to enable exporting Time Domain Reflectometry (TDR) and non-de-embedded Touchstone (.sNp) files:

export_ansys(..., simulation_flags=['tdr', 'snp_no_deembed'])

The optional scripts are listed below.

Optional scripts

  • export_snp_no_deembed.py

    No argument.

    Disables de-embedding and exports the \(S\)-matrix network data to a Touchstone (.sNp) file.

    Works only in HFSS.

  • export_tdr.py

    No argument.

    Creates a Time Domain Reflectometry report using TDRZt(port) for all ports and exports the data to a .csv.

    Works only in HFSS.

pyEPR

pyEPR is supported for HFSS eigenmode simulations. A simulation needs to be created with ansys_tool=eigenmode and simulation_flags=['pyepr']. An example simulation is found at klayout_package/python/scripts/simulations/xmons_direct_coupling_pyepr.py. See pyEPR_example.ipynb in the KQCircuits-Examples repository for an example on using pyEPR itself.

TLS-limited \(T_1\) estimation with EPR

Do as in pyEPR but additionally include intermediate_processing_command='python "scripts/t1_estimate.py"'. This will run t1_estimate.py between queued simulations and compute the electrical participations in the lossy interfaces. See double_pads_sim.py for an example and N. Savola, ‘Design and modelling of long-coherence qubits using energy participation ratios’, Master’s thesis, Aalto University, 2023, for details on the method.