论文标题
优化有限数据的连续变量纠缠检测
Optimizing detection of continuous variable entanglement for limited data
论文作者
论文摘要
我们探讨了基于Husimi $ Q $ - 分布的连续变量系统的一类纠缠标准的优势，而实验数据很少。这些标准的一般性允许将它们优化为给定的纠缠状态和实验设置。我们考虑了粗粒度测量值或有限探测器分辨率的情况，其中仅在相空间中的点网格上知道Husimi $ Q $分布的值，并显示纠缠标准如何适应此情况。此外，我们研究了实验测量等同于从Husimi分布中绘制独立样品的情况。在这里，我们自定义纠缠标准，以最大程度地提高给定有限数量样品的检测的统计意义。在这两种情况下，优化都可以明确改善检测状态类别和检测的信噪比。
We explore the advantages of a class of entanglement criteria for continuous variable systems based on the Husimi $Q$-distribution in scenarios with sparse experimental data. The generality of these criteria allows optimizing them for a given entangled state and experimental setting. We consider the scenario of coarse grained measurements, or finite detector resolution, where the values of the Husimi $Q$-distribution are only known on a grid of points in phase space, and show how the entanglement criteria can be adapted to this case. Further, we examine the scenario where experimental measurements amount to drawing independent samples from the Husimi distribution. Here, we customize our entanglement criteria to maximize the statistical significance of the detection for a given finite number of samples. In both scenarios optimization leads to clear improvements enlarging the class of detected states and the signal-to-noise ratio of the detection, respectively.
