论文标题
优化实用传感器中相位和噪声的量子增强贝叶斯多参数估计
Optimizing quantum-enhanced Bayesian multiparameter estimation of phase and noise in practical sensors
论文作者
论文摘要
在测量未知数量的情况下，实现量子增强的性能，需要为实践场景开发合适的方法，包括噪声和有限资源的可用性。在这里，我们报告了不合标准的量子限制贝叶斯多参数估计的优化，在这种情况下，参数的子集描述了实验光子传感器中不可避免的噪声过程。我们探讨估计的优化如何变化，具体取决于哪些参数是感兴趣或被视为滋扰的参数。我们的结果表明，在嘈杂设备中优化多参数方法是一个重要的工具，可以充分利用超出标准量子限制的实用传感器的潜力。
Achieving quantum-enhanced performances when measuring unknown quantities requires developing suitable methodologies for practical scenarios, that include noise and the availability of a limited amount of resources. Here, we report on the optimization of sub-standard quantum limit Bayesian multiparameter estimation in a scenario where a subset of the parameters describes unavoidable noise processes in an experimental photonic sensor. We explore how the optimization of the estimation changes depending on which parameters are either of interest or are treated as nuisance ones. Our results show that optimizing the multiparameter approach in noisy apparata represents a significant tool to fully exploit the potential of practical sensors operating beyond the standard quantum limit for broad resources range.
