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arXiv 2602.21076quant-ph
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通过顺流而行来纠正相干量子错误

Correcting coherent quantum errors by going with the flow

Sandia National Laboratories(桑迪亚国家实验室);Quantinuum

Wayne M. Witzel, Anand Ganti, Tzvetan S. Metodi

AI总结:

通过被动误差校正策略,有效抑制相干误差累积,实现与泡利噪声模型相近的量子比特性能。

摘要:

量子误差校正(QEC)代码的性能取决于所假设的噪声模型。独立的泡利噪声,在每个量子操作后应用,是一种简单的噪声模型,易于在稳定子码的背景下模拟和理解。尽管这种噪声模型是人为的,但它等同于独立的、随机的、无偏的量子比特旋转。那么,空间上或时间上相关的量子比特旋转呢?这种噪声模型适用于全局操作(例如NMR或ESR)、共同的控制源(例如激光)或缓慢漂移(例如电荷或磁噪声)在各种量子比特技术中。在最坏的情况下,这些错误可以相加并产生后校正失败率,该失败率随着错误校正循环次数的增加而增加。然而,我们证明,除非在执行QEC时采取主动纠正措施,否则这种最坏情况一般不会出现。也就是说,通过使用虚拟泡利框架更新(“被动”误差校正)而不是物理纠正(“主动”误差校正),相干错误不会显著累积。以随机泡利框架开始也有优势。事实上,通过扰动理论论证和支持的数值模拟,我们证明,在使用这些“懒惰”策略时,对于相关的单量子比特哈密顿量噪声模型(即全局偏移量子比特旋转),在距离3以上的逻辑量子比特性能,本质上与具有相同过程保真度的泡利噪声模型的性能相同。在更一般的电路噪声模型中,相关性可能在综合征提取轮次内相加,但被动误差校正中的泡利框架随机化在多个轮次中减轻了这种影响。

英文摘要:

The performance of a given quantum error correction (QEC) code depends upon the noise model that is assumed. Independent Pauli noise, applied after each quantum operation, is a simplistic noise model that is easy to simulate and understand in the context of stabilizer codes. Although such a noise model is artificial, it is equivalent to independent, random, unbiased qubit rotations. What about spatially or temporally correlated qubit rotations? Such a noise model is applicable to global operations (e.g., NMR or ESR), common control sources (e.g., lasers), or slow drift (e.g., charge or magnetic noise) in various qubit technologies. In the worst case, such errors can combine constructively and result in a post-correction failure rate that increases with the number of error correction cycles. However, we show that this worst case does not generally arise unless taking active corrective actions while performing QEC. That is, by employing virtual Pauli frame updates ("passive" error correction) rather than physical corrections ("active" error correction), coherent errors do not compound appreciably. Starting in a random Pauli frame is also advantageous. In fact, through perturbation theory arguments and supporting numerical simulations, we show that the logical qubit performance beyond distance 3 for correlated single-qubit Hamiltonian noise models (i.e., global errant qubit rotations), when employing these "lazy" strategies, essentially matches the performance of Pauli noise model with the same process fidelity (fidelity after one application). In a more general circuit model of noise, correlations may add constructively within syndrome extraction rounds but Pauli frame randomization from passive error correction mitigates this effect across multiple rounds.

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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