Expanding the SQuADDS database for superconducting quantum device design
POSTER
Abstract
The Superconducting Quantum Device Design and Simulation (SQuADDS) database is an open-source platform developed to provide a large set of ready-made, accurately simulated device designs. It connects device layout information, electromagnetic simulations, and extracted Hamiltonian parameters into a unified framework, providing a foundation for design benchmarking and machine learning–based device prediction. Simulated devices are based on experimentally-measured devices, providing a validation for simulation data. However, most entries currently consist of cross-style transmon qubits coupled to transmission line resonators. While this geometry is well characterized, it represents a part of the larger device architecture used in superconducting quantum research.This project aims to broaden the designs represented in SQuADDS by modeling and simulating new transmon and resonator modalities. These include different transmon geometries, quasi-lumped-element resonators, spiral resonators, tunable couplers, and a variety of coupling element geometries. Adding these new designs to SQuADDS requires adjusting simulation settings and updating the circuit models that were originally built to only account for one style of device. Expanding the database in this way creates a more flexible structure that allows users to better find a design that fits their needs. It also provides a more extensive dataset mapping between layout and simulation results, providing stronger benchmarks for future simulations and more training data for AI models. With more diverse qubit and resonator designs included, SQuADDS becomes a better tool for studying how device structure affects performance, improving simulation reliability, and supporting data-driven design of superconducting qubits.
*Devices were fabricated and provided by the Superconducting Qubits at Lincoln Laboratory (SQUILL) Foundry at MIT Lincoln Laboratory, with funding from the Laboratory for Physical Sciences (LPS) Qubit Collaboratory. This work was supported by the Army Research Office under LPS Qubit Collaboratory grant W911NF-25-1-0255.
Presenters
-
Ethan Y Zheng
- University of Southern California