论文标题
单次歧视过程矩阵的策略
Strategies for single-shot discrimination of process matrices
论文作者
论文摘要
因果关系的主题最近获得了吸引量子信息研究。这项工作研究了过程矩阵之间单次歧视的问题，这是定义因果结构的通用方法。我们为正确区分的最佳概率提供了精确的表达。此外，我们提出了一种使用凸锥结构理论来实现这种表达的另一种方法。我们还将歧视任务表示为半决赛编程。因此，我们创建了SDP来计算过程矩阵之间的距离，并根据痕量标准对其进行量化。作为有价值的副产品，该计划发现了歧视任务的最佳实现。我们还找到了两个可以完美区分的过程矩阵。但是，我们的主要结果是考虑与量子梳相对应的过程矩阵的歧视任务。我们研究在歧视任务中应使用哪种策略，自适应或非信号。我们证明，无论您选择哪种策略，区分两个过程矩阵（量子梳子）的可能性都是相同的。
The topic of causality has recently gained traction quantum information research. This work examines the problem of single-shot discrimination between process matrices which are an universal method defining a causal structure. We provide an exact expression for the optimal probability of correct distinction. In addition, we present an alternative way to achieve this expression by using the convex cone structure theory. We also express the discrimination task as semidefinite programming. Due to that, we have created the SDP calculating the distance between process matrices and we quantify it in terms of the trace norm. As a valuable by-product, the program finds an optimal realization of the discrimination task. We also find two classes of process matrices which can be distinguished perfectly. Our main result, however, is a consideration of the discrimination task for process matrices corresponding to quantum combs. We study which strategy, adaptive or non-signalling, should be used during the discrimination task. We proved that no matter which strategy you choose, the probability of distinguishing two process matrices being a quantum comb is the same.
