探测无后选的测量后纠缠

Samuel J. Garratt, Ehud Altman
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引用次数: 0

摘要

我们研究的问题是观测大量测量产生的量子集体现象。这些现象在传统实验中很难观测到,因为为了区分测量和消相干的影响,必须对测量结果集进行后选择,而测量结果集的天生概率在测量次数中呈指数级小。避免这种指数级 "后选择问题 "的非常规方法是在实验数据和经典计算机模拟结果之间建立交叉相关。然而,这些交叉相关通常与物理量没有明确的关系。我们首先展示了如何将经典阴影纳入这一框架,从而构建量子信息论交叉相关。然后,我们确定了既能上限值又能下限值测量平均冯-诺依曼纠缠熵的交叉相关,以及能下限值测量平均纯度和纠缠负性的交叉相关。这些界限表明,可以通过实验来约束测量后的纠缠,而无需进行后选择。为了说明我们的技术,我们考虑了如何用它来观察哈尔随机量子电路中测量诱导的纠缠转变。我们使用精确的数值计算作为量子模拟的替代,为了突出经典记忆的根本局限性,我们在有限的键维度上通过张量网络计算构建了交叉相关。我们的结果揭示了测量诱导临界的特征,使用量子模拟器可以在多项式时间和多项式经典记忆中观察到这一特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Probing Postmeasurement Entanglement without Postselection

Probing Postmeasurement Entanglement without Postselection
We study the problem of observing quantum collective phenomena emerging from large numbers of measurements. These phenomena are difficult to observe in conventional experiments because, in order to distinguish the effects of measurement from dephasing, it is necessary to postselect on sets of measurement outcomes with Born probabilities that are exponentially small in the number of measurements performed. An unconventional approach, which avoids this exponential “postselection problem”, is to construct cross-correlations between experimental data and the results of simulations on classical computers. However, these cross-correlations generally have no definite relation to physical quantities. We first show how to incorporate classical shadows into this framework, thereby allowing for the construction of quantum information-theoretic cross-correlations. We then identify cross-correlations that both upper and lower bound the measurement-averaged von Neumann entanglement entropy, as well as cross-correlations that lower bound the measurement-averaged purity and entanglement negativity. These bounds show that experiments can be performed to constrain postmeasurement entanglement without the need for postselection. To illustrate our technique, we consider how it could be used to observe the measurement-induced entanglement transition in Haar-random quantum circuits. We use exact numerical calculations as proxies for quantum simulations and, to highlight the fundamental limitations of classical memory, we construct cross-correlations with tensor-network calculations at finite bond dimension. Our results reveal a signature of measurement-induced criticality that can be observed using a quantum simulator in polynomial time and with polynomial classical memory.
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