Resilience of Quantum Random Access Memory to Generic Noise
Resilience of Quantum Random Access Memory to Generic Noise
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DOI：
10.1103/prxquantum.2.020311
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发表时间：
2021-04-29
期刊：
影响因子：
9.7
通讯作者：
Jiang, Liang
中科院分区：
文献类型：
--
作者：
Hann, Connor T.;Lee, Gideon;Jiang, Liang
量子随机存取存储器(QRAM)-存储经典数据但允许重叠执行查询的存储器-是实现许多量子算法所必需的。虽然QRAM的幼稚实现非常容易受到退相干的影响，因此不可伸缩，但有人认为，桶-队QRAM体系结构[Giovannetti等人，Phys..莱特牧师。100,160501(2008年)]对噪声具有很强的弹性，查询的不保真性仅随内存大小对数扩展。然而，在先前的分析中，这种有利的缩放直接源于人为噪声模型的使用，因此留下了一个悬而未决的问题，即实验实现是否真的会享受到所谓的缩放优势。在这项工作中，我们全面地研究了退相干对QRAM的影响。我们的主要结果是证明这种有利的不保真度缩放对于任意错误通道(例如，包括去极化噪声和相干错误)有效。我们的证明将这种噪声弹性的起源确定为存储器组件之间的有限纠缠，并且它还揭示了在保持噪声弹性的同时可以进行显著的结构简化。我们用一种新的有效模拟噪声QRAM电路的经典算法对这些结果进行了数值验证。我们的发现表明，QRAM可以在现实中嘈杂的设备中使用现有的硬件来实现，并且高保真查询是可能的，而不需要量子纠错。此外，我们还证明了当使用量子纠错时，桶-队结构的优点仍然存在，在这种情况下，该方案提供了更高的硬件效率和对逻辑错误的恢复能力。
Quantum random access memory (QRAM)-memory which stores classical data but allows queries to be performed in superposition-is required for the implementation of numerous quantum algorithms. While naive implementations of QRAM are highly susceptible to decoherence and hence not scalable, it has been argued that the bucket-brigade QRAM architecture [Giovannetti et al., Phys. Rev. Lett. 100, 160501 (2008)] is highly resilient to noise, with the infidelity of a query scaling only logarithmically with the memory size. In prior analyses, however, this favorable scaling followed directly from the use of contrived noise models, thus leaving open the question of whether experimental implementations would actually enjoy the purported scaling advantage. In this work, we study the effects of decoherence on QRAM in full generality. Our main result is a proof that this favorable infidelity scaling holds for arbitrary error channels (including, e.g., depolarizing noise and coherent errors). Our proof identifies the origin of this noise resilience as the limited entanglement among the memory's components, and it also reveals that significant architectural simplifications can be made while preserving the noise resilience. We verify these results numerically using a novel classical algorithm for the efficient simulation of noisy QRAM circuits. Our findings indicate that QRAM can be implemented with existing hardware in realistically noisy devices, and that high-fidelity queries are possible without quantum error correction. Furthermore, we also prove that the benefits of the bucket-brigade architecture persist when quantum error correction is used, in which case the scheme offers improved hardware efficiency and resilience to logical errors.