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arXiv 2407.02467quant-ph
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超导量子处理器中利用稳定化噪声进行误差缓解

Error mitigation with stabilized noise in superconducting quantum processors

Youngseok Kim, Luke C. G. Govia, Andrew Dane, Ewout van den Berg, David M. Zajac, Bradley Mitchell, Yinyu Liu, Karthik Balakrishnan, George Keefe, Adam Stabile,… 展开作者

Youngseok Kim, Luke C. G. Govia, Andrew Dane, Ewout van den Berg, David M. Zajac, Bradley Mitchell, Yinyu Liu, Karthik Balakrishnan, George Keefe, Adam Stabile, Emily Pritchett, Jiri Stehlik, Abhinav Kandala

AI总结:

本文通过实验调节超导量子比特与缺陷二能级系统的相互作用以稳定噪声,从而提升噪声模型准确性和误差缓解的可靠性。

摘要:

容错前量子计算机已经证明,它们能够在超越经典计算暴力求解的规模上准确估计可观测量值。这一能力得益于误差缓解技术,而这些技术通常依赖于器件噪声的代表性模型。然而,学习并维护这些模型会因噪声在不可预测时间尺度上的波动而变得复杂,例如这种波动源于超导量子比特与缺陷二能级系统(TLS)之间的共振相互作用。此类相互作用不仅会影响器件整体性能的稳定性和一致性,还会影响噪声模型的准确性,从而导致可观测量估计错误。在这里,我们通过实验证明,调节量子比特-TLS相互作用有助于降低噪声不稳定性,并因此实现更可靠的误差缓解性能。这些实验为研究准静态噪声存在时的误差缓解性能提供了一个受控平台。我们预计,本文引入的能力对于在非平凡规模的固态处理器上探索量子应用将至关重要。

英文摘要:

Pre-fault tolerant quantum computers have already demonstrated the ability to estimate observable values accurately, at a scale beyond brute-force classical computation. This has been enabled by error mitigation techniques that often rely on a representative model on the device noise. However, learning and maintaining these models is complicated by fluctuations in the noise over unpredictable time scales, for instance, arising from resonant interactions between superconducting qubits and defect two-level systems (TLS). Such interactions affect the stability and uniformity of device performance as a whole, but also affect the noise model accuracy, leading to incorrect observable estimation. Here, we experimentally demonstrate that tuning of the qubit-TLS interactions helps reduce noise instabilities and consequently enables more reliable error-mitigation performance. These experiments provide a controlled platform for studying the performance of error mitigation in the presence of quasi-static noise. We anticipate that the capabilities introduced here will be crucial for the exploration of quantum applications on solid-state processors at non-trivial scales.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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