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arXiv:2509.18482

Characterizing Noise in Controlling Superconducting Qubits

Yuanzheng Paul Tan, Yung Szen Yap, Nguyen, Long Hoang, Rangga P. Budoyo, Bore, Patrick, Kun Hee Park, Christoph Hufnagel, Rainer Dumke

Published Sep 23, 2025• 0 citations
arXivHTMLPDF

Abstract

Meaningful quantum computing is currently bottlenecked by the error rates of current generation Noisy Intermediate Scale Quantum (NISQ) devices. To improve the fidelity of the quantum logic gates, it is essential to recognize the contributions of various sources of errors, including background noise. In this work, we investigate the effects of noise when applied to superconducting qubit control pulses to observe the dependency of the gate fidelity with the signal-to-noise ratio (SNR). We propose a model on how the noise of the control electronics interacts with the qubit system and demonstrate a method for characterizing the noise environment of the qubit control.

DOI
10.48550/arxiv.2509.18482

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Meaningful quantum computing is currently bottlenecked by the error rates of current generation Noisy Intermediate Scale Quantum (NISQ) devices. To improve the fidelity of the quantum logic gates, it is essential to recognize the contributions of various sources of errors, including background noise. In this work, we investigate the effects of noise when applied to superconducting qubit control pulses to observe the dependency of the gate fidelity with the signal-to-noise ratio (SNR). We propose a model on how the noise of the control electronics interacts with the qubit system and demonstrate a method for characterizing the noise environment of the qubit control.
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Quantum devices in the noisy intermediate-scale quantum (NISQ) era are highly susceptible to different types of quantum noise, which directly impact the reliability of experimental results. This work provides a characterization of error behavior arising from quantum noises on IBM's superconducting quantum processor, offering practical insights for algorithm design, benchmarking, and error-mitigation strategies on a real superconducting quantum processor in the NISQ era. The study begins with the measurement of the basis state, without applying any gate, to quantify state-preparation and measurement (SPAM) errors. Additionally, the errors are further quantified due to the application of single-qubit Pauli-X, two-qubit CNOT gate and other multi-qubit Controlled-X gates. Each circuit was executed with 1024 shots, and the percentage error between the expected and observed outputs was computed. The results show that the single-qubit Pauli-X gate exhibits relatively low errors in comparison with the two-qubit CNOT gate, whereas other multi-qubit Controlled-X gates lead to significantly higher deviations. This work also analyzes the noise effect of a fourqubit Controlled-X gate being implemented using a three-qubit Controlled-X gate with an extra auxiliary qubit, and the result shows a significant reduction in the error rate.
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Abstract The effects of noise are one of the most important factors to consider when it comes to quantum computing in the noisy intermediate-scale quantum computing (NISQ) era that we are currently in. Therefore, it is important not only to gain more knowledge about the noise sources appearing in current quantum computing hardware in order to suppress and mitigate their contributions, but also to evaluate whether a given quantum algorithm can achieve reasonable results on a given hardware. To accomplish this, we need noise models that can describe the real hardware with sufficient accuracy. Here, we present a noise model that has been evaluated on superconducting hardware platforms and could be adapted to other common architectures such as trapped-ion or neutral atom devices. We then benchmark our model by simulating a 20-qubit superconducting quantum computer, and compare the accuracy of our model to similar approaches from the literature and demonstrate an improvement in the overall prediction accuracy.
Abstract Superconducting qubits are currently a leading platform for developing a scalable quantum computer. However, random and uncontrollable noises from the environment during the design and measurement of qubits lead to limitations in qubit coherence time and gate fidelity, which is a major challenge in current state of the art for superconducting quantum computing. To advance superconducting qubits technologies, it is essential to understand and mitigate environmentally-induced errors. This requires modeling superconducting qubits as open quantum systems coupled to their surroundings. The present study aims to provide useful open quantum system approaches to analyze and quantify the interaction between superconducting qubits and their environments. We provide an accessible introduction to open quantum system formalism for newcomers to the field. For experts, we discuss recently developed methods for analyzing superconducting qubit dynamics under realistic noises. We outline how these techniques provide quantitative insights into decoherence mechanisms and how they can guide design improvements to enhance qubit coherence time. This self-contained review of open quantum system approaches can be used to model, understand, and improve superconducting qubit performance in the presence of unavoidable environmental noises.