论文标题
通过不完美的误差校正增强分布式感测
Enhancing distributed sensing with imperfect error correction
论文作者
论文摘要
纠缠已显示出通过分布式量子传感协议增强传感器网络中信息处理任务的希望。由于噪声在传感器网络中无处不在，因此需要基于Gottesman，Kitaev和Preskill（GKP）状态的误差校正方案来增强性能，如[New J. Phys所示。 22，022001（2020）]假设传感器和完美的GKP状态之间存在均匀的噪声。在这里，我们将性能增强的分析扩展到了异质噪声模型中有限的挤压GKP状态。首先，我们研究了GKP-Two-Two-Mode-Squeezing代码的不同串联方案。尽管以前的作品中的传统顺序串联方案确实改善了对噪声的抑制，但我们提出了一个平衡的串联方案，在存在有限的GKP挤压的情况下，在存在有限的串联方案中表现优于顺序方案。然后，我们将这些结果应用于分布式量子传感的两个特定任务（参数估计和假设测试），以了解不完善的压缩和性能之间的权衡。对于以前的任务，我们考虑了一个能量受限的方案，并提供了一种最佳的方式，可以在传感器之间分配有限的GKP状态的能量。对于后一个任务，我们表明，通过逼近逼真的有限挤压GKP代码的串联，误差概率仍然可以大大降低。
Entanglement has shown promise in enhancing information processing tasks in a sensor network, via distributed quantum sensing protocols. As noise is ubiquitous in sensor networks, error correction schemes based on Gottesman, Kitaev and Preskill (GKP) states are required to enhance the performance, as shown in [New J. Phys. 22, 022001 (2020)] assuming homogeneous noise among sensors and perfect GKP states. Here, we extend the analyses of performance enhancement to finite squeezed GKP states in a heterogeneous noise model. To begin with, we study different concatenation schemes of GKP-two-mode-squeezing codes. While traditional sequential concatenation schemes in previous works do improve the suppression of noise, we propose a balanced concatenation scheme that outperforms the sequential scheme in presence of finite GKP squeezing. We then apply these results to two specific tasks in distributed quantum sensing -- parameter estimation and hypothesis testing -- to understand the trade-off between imperfect squeezing and performance. For the former task, we consider an energy-constrained scenario and provide an optimal way to distribute the energy of the finite squeezed GKP states among the sensors. For the latter task, we show that the error probability can still be drastically lowered via concatenation of realistic finite squeezed GKP codes.
