相干态的自适应辨识
Adaptive identification of coherent states
摘要：
我们提出了有效的光学相干态$|α\rangle$的表征方法。我们根据收集的数据自适应地随机选择测量设置。我们的算法将估计分为两个不同的步骤：（i）在第一次检测到真空状态之前，选择测量设置的概率与使用该设置检测真空成比例，这使得使用太相似的测量设置不太可能两次;以及（ii）在第一次检测到真空之后，我们将测量集中在最有可能检测到真空的区域。在步骤（i）[（ii）]中，真空（光子）的检测对$α$的后验概率分布的形状具有显著更大的影响。非自适应计划相比，我们的方法使测量拍摄的数量需要达到一定程度的准确性小约由一个因素成比例的面积描述的初始不确定性的$α$在相空间。虽然该算法对于读出误差不是直接鲁棒的，但是我们通过在步骤（i）中引入重复测量来实现。
英文摘要：
We present methods for efficient characterization of an optical coherent state $|α\rangle$. We choose measurement settings adaptively and stochastically, based on data while it is collected. Our algorithm divides the estimation into two distinct steps: (i) before the first detection of a vacuum state, the probability of choosing a measurement setting is proportional to detecting vacuum with the setting, which makes using too similar measurement settings twice unlikely; and (ii) after the first detection of vacuum, we focus measurements in the region where vacuum is most likely to be detected. In step (i) [(ii)] the detection of vacuum (a photon) has a significantly larger effect on the shape of the posterior probability distribution of $α$. Compared to nonadaptive schemes, our method makes the number of measurement shots required to achieve a certain level of accuracy smaller approximately by a factor proportional to the area describing the initial uncertainty of $α$ in phase space. While this algorithm is not directly robust against readout errors, we make it such by introducing repeated measurements in step (i).
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