TQEA: Temporal Quantum Error Analysis
TQEA: Temporal Quantum Error Analysis
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TQEA：时间量子误差分析
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Qiang Guan
中科院分区：
文献类型：
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作者：
Betis Baheri;Daniel T. Chen;B. Fang;S. Stein;V. Chaudhary;Y. Mao;Shuai Xu;Ang Li;Qiang Guan
在机器学习、数值科学模拟和金融等许多领域对量子计算机需求的增长，促使量子计算机产生更稳定、更不易出错的结果。然而，减轻每个量子器件内部噪声的影响仍然是当前的挑战。在本文中，我们调查的时间行为的噪声中尺度量子（NISQ）计算机的校准数据和个别设备的特性的基础上的错误。特别是，我们收集了超过90天的IBM-Q机器的校准数据，并比较了不同处理器类型、量子拓扑和量子卷的量子错误鲁棒性。我们通过比较2019-2021年期间四台IBM量子计算机的量子误差数据来分析老化效应，结果显示，随着时间的推移，只有一台计算机的误差显著增长。在这项研究中，我们简单地分析收集到的数据，并运行时间测试分析，以观察IBM-Q计算机的行为。
The growth of need of quantum computers in many domains such as machine learning, numerical scientific simulation and finance has urged the quantum computers to produce more stable and less error-prone results. However, to mitigate the impact of the noise inside each quantum device remains a present challenge. In this paper, we investigate the temporal behavior of noisy intermediate-scale quantum (NISQ) computer errors based on calibration data and the characteristics of individual devices. In particular, we collect calibration data of IBM-Q machines over 90 days and compare the quantum error robustness across processor types, quantum topology and quantum volumes. We analyze the aging effect by comparing the quantum error data from four IBM quantum computers during 2019-2021 showing that only one computer experienced significant error growth overtime. In this study, we simply analyze the collected data and run temporal test analysis to observe the behaviour of IBM-Q computers.