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arXiv 2402.18548quant-phcond-mat.stat-mech
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噪声随机电路中条件互信息的普适传播

Universal Spreading of Conditional Mutual Information in Noisy Random Circuits

Su-un Lee, Changhun Oh, Yat Wong, Senrui Chen, Liang Jiang

AI总结:

研究了带噪声的一维随机量子电路中条件互信息的演化,发现局部噪声与置乱酉算子共同作用导致其超线性传播并突破光锥,通过粗粒化方法解析验证了其普适标度律。

摘要:

我们研究了条件互信息在一般开放量子系统中的演化,重点关注一维随机电路中穿插局部噪声的情况。与无噪声电路中条件互信息以线性方式传播且受限于光锥不同,我们发现错误率为 $p$ 的噪声随机电路表现出超线性的条件互信息传播,在临界电路深度 $t_c \propto p^{-1}$ 处发散并远远超出光锥。我们证明,这种快速传播的内在机制是局部噪声与置乱酉算子的共同作用,它们选择性地移除短程关联,同时保留长程关联。为了解析地描述噪声随机电路中条件互信息的动力学,我们引入了一种粗粒化方法,并通过数值模拟验证了我们的理论结果。此外,我们确定了支配条件互信息传播的普适标度律。

英文摘要:

We study the evolution of conditional mutual information in generic open quantum systems, focusing on one-dimensional random circuits with interspersed local noise. Unlike in noiseless circuits, where conditional mutual information spreads linearly while being bounded by the lightcone, we find that noisy random circuits with an error rate $p$ exhibit superlinear propagation of conditional mutual information, which diverges far beyond the lightcone at a critical circuit depth $t_c \propto p^{-1}$. We demonstrate that the underlying mechanism for such rapid spreading is the combined effect of local noise and a scrambling unitary, which selectively removes short-range correlations while preserving long-range correlations. To analytically capture the dynamics of conditional mutual information in noisy random circuits, we introduce a coarse-graining method, and we validate our theoretical results through numerical simulations. Furthermore, we identify a universal scaling law governing the spreading of conditional mutual information.

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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