arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1910.14014quant-ph
收藏

传感器网络中最优量子增强的多参数压缩

Multiparameter squeezing for optimal quantum enhancements in sensor networks

Manuel Gessner, Augusto Smerzi, Luca Pezzè

摘要:

压缩目前代表了在各种连续和离散变量设置和技术应用中对单个参数进行量子增强精度测量的领先策略。然而,许多重要的物理问题,包括成像和现场传感需要同时测量多个未知参数。多参量量子精密测量的发展仍然受到寻找饱和灵敏度界和可行估计策略的固有困难的阻碍。在这里,我们推导出多参数压缩的一般操作概念,识别计量有用的状态和最佳估计策略。当应用到自旋或连续变量系统,我们的结果推广了广泛使用的自旋或正交压缩参数。多参数压缩提供了一个实用和通用的概念,铺平了道路的发展,量子增强估计的多个相位,梯度和领域,并为有效的表征多模量子态在原子和光学传感器网络。

英文摘要:

Squeezing currently represents the leading strategy for quantum enhanced precision measurements of a single parameter in a variety of continuous- and discrete-variable settings and technological applications. However, many important physical problems including imaging and field sensing require the simultaneous measurement of multiple unknown parameters. The development of multiparameter quantum metrology is yet hindered by the intrinsic difficulty in finding saturable sensitivity bounds and feasible estimation strategies. Here, we derive the general operational concept of multiparameter squeezing, identifying metrologically useful states and optimal estimation strategies. When applied to spin- or continuous-variable systems, our results generalize widely-used spin- or quadrature-squeezing parameters. Multiparameter squeezing provides a practical and versatile concept that paves the way to the development of quantum-enhanced estimation of multiple phases, gradients, and fields, and for the efficient characterization of multimode quantum states in atomic and optical sensor networks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑