论文标题
纠缠增强了嵌入多个阶段的参数的估计
Entanglement Enhanced Estimation of a Parameter Embedded in Multiple Phases
论文作者
论文摘要
量子增强的传感有望使用非经典探针和测量值提高感应任务的性能,而测量结果比最佳的经典方案所需的场景调制光子要少得多,从而授予有关广泛物理系统的先前无法访问的信息。我们提出了一个通用的分布式传感框架,该框架使用纠缠量子探测器来估计一个场景参数编码,该场景参数在一个相位阵列中编码,其功能依赖性依赖于该参数由实际系统的物理学确定。接收器使用激光光源通过量子键入的多目标挤压 - 维库姆灯来探测相位,从而估算所需的场景参数。纠缠抑制了整个相位阵列的集体量子真空噪声。我们报告了仅取决于光学探针和测量系统的物理模型的CramérRao结合的简单分析表达式,并且我们表明我们的结构化接收器渐近地使量子cramér-rao在无损情况下结合。我们的方法使海森伯格在估计有关总探针能量以及调制阶段数量方面的场景参数方面的精度有限。此外,我们研究了系统中均匀损失的影响,并研究量子和经典cramér-rao边界的行为。我们将框架应用于诸如射频阶梯式阵列方向雷达等示例,原子力显微镜的光束置换跟踪和基于光纤的温度级级计。
Quantum-enhanced sensing promises to improve the performance of sensing tasks using non-classical probes and measurements that require far fewer scene-modulated photons than the best classical schemes, thereby granting previously-inaccessible information about a wide range of physical systems. We propose a generalized distributed sensing framework that uses an entangled quantum probe to estimate a scene-parameter encoded within an array of phases, with a functional dependence on that parameter determined by the physics of the actual system. The receiver uses a laser light source enhanced by quantum-entangled multi-partite squeezed-vacuum light to probe the phases and thereby estimate the desired scene-parameter. The entanglement suppresses the collective quantum vacuum noise across the phase array. We report simple analytical expressions for the Cramér Rao bound that depend only on the optical probes and the physical model of the measured system, and we show that our structured receiver asymptotically saturates the quantum Cramér-Rao bound in the lossless case. Our approach enables Heisenberg limited precision in estimating a scene-parameter with respect to total probe energy, as well as with respect to the number of modulated phases. Furthermore, we study the impact of uniform loss in our system and examine the behavior of both the quantum and the classical Cramér-Rao bounds. We apply our framework to examples as diverse as radio-frequency phased-array directional radar, beam-displacement tracking for atomic-force microscopy, and fiber-based temperature gradiometry.