quansys 4.0.0

Automated HFSS workflows for quantum circuit design and analysis

quansys

Automated HFSS workflows for quantum circuit design and analysis

quansys is a Python package that automates HFSS electromagnetic simulations for quantum circuit analysis. It provides structured workflows for parameter sweeps, quantum parameter extraction via Energy Participation Ratio (EPR) analysis, and cluster-based execution.

Features

• Structured Workflows: Automated prepare → build → simulate → aggregate pipeline
• Parameter Sweeps: Grid and custom parameter sweeps with caching and resumption
• Quantum Analysis: EPR-based quantum parameter extraction (χ matrix, dressed frequencies)
• CLI Interface: Command-line tools for simulation management and cluster execution
• Result Processing: Automatic JSON/CSV output generation for downstream analysis
• Extensible: Modular design supporting custom simulation types and builders

Documentation

Complete documentation is available at: hutorihunzu.github.io/quansys

Quick Start

Installation

Install from PyPI:

pip install quansys

Or install from source:

git clone https://github.com/hutorihunzu/quansys.git
cd quansys
pip install -e .

Basic Usage

1. Create a simulation configuration (config.yaml):

pyaedt_file_parameters:
  file_path: "my_design.aedt"
  non_graphical: true

builder:
  type: 'design_variable_builder'
  design_name: "HfssDesign1"

builder_sweep:
  - type: 'DictSweep'
    parameters:
      resonator_length: ["10mm", "12mm", "14mm"]

simulations:
  eigenmode:
    type: 'eigenmode'
    design_name: "HfssDesign1"
    setup_name: "Setup1"

2. Run the simulation:

quansys run config.yaml

3. Or use Python directly:

from quansys.workflow import WorkflowConfig, execute_workflow

config = WorkflowConfig.from_yaml("config.yaml")
execute_workflow(config)

Simulation Types

Eigenmode Analysis

Extract resonant frequencies and quality factors from electromagnetic eigenmodes:

from quansys.simulation import EigenmodeAnalysis

simulation = EigenmodeAnalysis(
    design_name="HfssDesign1",
    setup_name="Setup1",
    cores=8
)

Quantum EPR Analysis

Compute quantum circuit parameters using Energy Participation Ratio analysis:

from quansys.simulation import QuantumEPR, ConfigJunction

simulation = QuantumEPR(
    design_name="HfssDesign1",
    setup_name="Setup1",
    modes_to_labels={0: "resonator", 1: "transmon"},
    junctions_infos=[ConfigJunction(line_name='my_jj_line', inductance_variable_name='lj')]
)

Note: Quantum EPR analysis is based on the energy-participation-ratio method from: "Energy-participation quantization of Josephson circuits"

Cluster Support

quansys is designed for high-performance computing environments and is currently optimized for IBM LSF cluster systems. The CLI provides tools for:

• Job preparation and submission
• Resource allocation management
• Distributed execution across cluster nodes
• Result aggregation from multiple jobs

Cluster Requirement: This package is specifically tailored for IBM LSF clusters. Support for other cluster systems (SLURM, PBS, etc.) may be added in future releases.

Development

Dependencies

• HFSS/PyAEDT: Electromagnetic simulation engine
• QutIP: Quantum parameter calculations
• Typer: CLI interface
• Pydantic: Configuration validation
• Pandas/NumPy: Data processing

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes with appropriate tests
4. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Quantum EPR Analysis: Based on the energy-participation-ratio method developed in the pyEPR package. See: "Energy-participation quantization of Josephson circuits"
• HFSS Integration: Built on top of PyAEDT for ANSYS Electronics Desktop automation