论文标题
最佳环境本地化
Optimal environment localization
论文作者
论文摘要
量子通道模拟许多物理过程。因此,量子通道之间的假设检验是量子信息理论中的基本任务。在这里,我们考虑了通道位置查找的范式情况,目的是确定目标量子通道在背景通道序列中的位置。我们考虑了具有相同透射率(或增益)但不同级别的环境噪声的高斯通道,我们在骨骼系统的设置中探索了这一模型。因此,问题的目的是检测目标环境在许多相同的背景环境中的位置,所有这些都作用于输入多模式系统。我们得出了影响这个多ARINISING问题的最终误差概率的界限,并找到了量子优势的分析条件,而不是涉及经典输入状态的协议。我们还设计了一个明确的协议,该协议在最终误差概率上给出数值界限,并且经常实现量子优势。最后,我们考虑该模型用于热成像任务(在较冷的背景中找到较温暖的像素)和量子通信(用于以一系列线或频率频谱的方式定位不同级别的噪声)。
Quantum channels model many physical processes. For this reason, hypothesis testing between quantum channels is a fundamental task in quantum information theory. Here we consider the paradigmatic case of channel position finding, where the aim is to determine the position of a target quantum channel within a sequence of background channels. We explore this model in the setting of bosonic systems, considering Gaussian channels with the same transmissivity (or gain) but different levels of environmental noise. Thus the goal of the problem becomes detecting the position of a target environment among a number of identical background environments, all acting on an input multi-mode system. We derive bounds for the ultimate error probability affecting this multi-ary discrimination problem and find an analytic condition for quantum advantage over protocols involving classical input states. We also design an explicit protocol that gives numerical bounds on the ultimate error probability and often achieves quantum advantage. Finally, we consider direct applications of the model for tasks of thermal imaging (finding a warmer pixel in a colder background) and quantum communication (for localizing a different level of noise in a sequence of lines or a frequency spectrum).