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Multiphysics Numerical Methods for Designing Multiplexed Superconducting Qubit Readout Chains

Samuel T. Elkin, Michael Haider, Thomas E. Roth

Published May 18, 2025• 0 citations
Publisher

Abstract

Superconducting qubits require rapid and high-fidelity multiplexed readout to enable effective quantum computers. However, predicting the fidelity of the physical implementation of a readout chain is challenging, limiting the success of experimental devices. While analytical tools are currently used to support these design efforts, mapping their outputs into a physical design is difficult and prone to error. In this work, we use multiphysics numerical methods to model the effect of individual component values on fidelity, which can more easily guide the design of a physical device geometry. This procedure is utilized here to optimize a pair of key capacitance values, but it is applicable to broader parameterization of a readout chain.

DOI
10.23919/aces66556.2025.11052562

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quant-pharXiv:2511.20774•Nov 27, 2025
Superconducting qubits require rapid and high-fidelity multiplexed readout to enable effective quantum computers. However, predicting the fidelity of the physical implementation of a readout chain is challenging, limiting the success of experimental devices. While analytical tools are currently used to support these design efforts, mapping their outputs into a physical design is difficult and prone to error. In this work, we use multiphysics numerical methods to model the effect of individual component values on fidelity, which can more easily guide the design of a physical device geometry. This procedure is utilized here to optimize a pair of key capacitance values, but it is applicable to broader parameterization of a readout chain.
Superconducting qubits require rapid and high-fidelity multiplexed readout to enable effective quantum computers. However, predicting the fidelity of the physical implementation of a readout chain is challenging, limiting the success of experimental devices. While analytical tools are currently used to support these design efforts, mapping their outputs into a physical design is difficult and prone to error. In this work, we use multiphysics numerical methods to model the effect of individual component values on fidelity, which can more easily guide the design of a physical device geometry. This procedure is utilized here to optimize a pair of key capacitance values, but it is applicable to broader parameterization of a readout chain.
Fast, high-fidelity readout of qubits is crucial in quantum computing. Quantum error correction in particular requires the repeated measurement of subsets of qubits without perturbing any others. Achieving this goal in a multiplexed readout architecture has been challenging, mainly due to the crosstalk of readout signals. In this work, individual Purcell filters are used for each readout resonator to protect the qubits from untargeted readout signals, and from radiative decay. By implementing this scheme, which could find broad use in near-term multiqubit devices, the authors demonstrate the $s\phantom{\rule{0}{0ex}}i\phantom{\rule{0}{0ex}}m\phantom{\rule{0}{0ex}}u\phantom{\rule{0}{0ex}}l\phantom{\rule{0}{0ex}}t\phantom{\rule{0}{0ex}}a\phantom{\rule{0}{0ex}}n\phantom{\rule{0}{0ex}}e\phantom{\rule{0}{0ex}}o\phantom{\rule{0}{0ex}}u\phantom{\rule{0}{0ex}}s$ readout of up to five qubits.
Qubit readout is a critical part of any quantum computer including the superconducting-qubit-based one. The readout fidelity is affected by the readout pulse width, readout pulse energy, resonator design, qubit design, qubit-resonator coupling, and the noise generated along the readout path. It is thus important to model and predict the fidelity based on various design parameters along the readout path. In this work, a simulation methodology for superconducting qubit readout fidelity is proposed and implemented using Matlab and Ansys HFSS to allow co-optimization in the readout path. As an example, parameters are taken from an actual superconducting-qubit-based quantum computer. Without any calibrations, the model is able to predict the readout error of the system as a function of the readout pulse power. It is found that the system can still maintain high fidelity even if the input power is reduced by 7 dB. This can be used to guide the design and optimization of a superconducting qubit readout system.
Superconducting quantum computing hardware relies on classical radio-frequency (RF) electronic circuits to control and measure quantum states. As the complexity of quantum computers increases, the significance of the classical circuitry component grows, necessitating the development of accurate models for its design and optimization. This study presents an analytical model that quantifies the influence of circuit nonidealities on readout fidelity in superconducting quantum computing systems. This model considers a wide range of nonidealities typically encountered in the readout chain, encompassing frequency, amplitude, phase inaccuracies, impedance mismatch, quantum noise, and amplifier noise. It further predicts the combined impact of these nonidealities on fidelity. The model’s precision and efficacy are confirmed through numerical quantum-classical co-simulation. The highest observed relative mismatch is roughly 3.5%, but most errors remain below 1%. Such a model can significantly aid in designing and optimizing practical quantum computers.
High-fidelity numerical methods that model the physical layout of a device are essential for the design of many technologies. For methods that characterize electromagnetic effects, these numerical methods are referred to as computational electromagnetics (CEM) methods. Although the CEM research field is mature, emerging applications can still stress the capabilities of the techniques in use today. The design of superconducting circuit quantum devices falls in this category due to the unconventional material properties and important features of the devices covering nanometer to centimeter scales. Such multiscale devices can stress the fundamental properties of CEM tools which can lead to an increase in simulation times, a loss in accuracy, or even cause no solution to be reliably found. While these challenges are being investigated by CEM researchers, knowledge about them is limited in the broader community of users of these CEM tools. This review is meant to serve as a practical introduction to the fundamental aspects of the major CEM techniques that a researcher may need to choose between to model a device, as well as provide insight into what steps they may take to alleviate some of their challenges. Our focus is on highlighting the main concepts without rigorously deriving all the details, which can be found in many textbooks and articles. After covering the fundamentals, we discuss more advanced topics related to the challenges of modeling multiscale devices with specific examples from superconducting circuit quantum devices. We conclude with a discussion on future research directions that will be valuable for improving the ability to successfully design increasingly more sophisticated superconducting circuit quantum devices. Although our focus and examples are taken from this area, researchers from other fields will still benefit from the details discussed here.