论文标题
实时反馈控制协助的关键量子计量学
Critical quantum metrology assisted by real-time feedback control
论文作者
论文摘要
我们研究了临界量子计量学，这是通过贝叶斯推论理论的镜头接近量子临界点的多体系统中参数的估计。我们首先得出一个不做的结果，指出任何非自适应测量策略都不会利用足够多的粒子$ n $来利用量子关键增强（即超过射击限制的精度）。然后，我们考虑可以克服这种不做结果的不同自适应策略，并在估算（i）使用一维旋转链链的磁场和（ii）Bose-Hubbard Square晶格中的耦合强度时说明了它们的性能。我们的结果表明，即使有少数测量和实质性的不确定性，具有实时反馈控制的自适应策略也可以实现子噪声缩放。
We investigate critical quantum metrology,that is the estimation of parameters in many-body systems close to a quantum critical point, through the lens of Bayesian inference theory. We first derive a no-go result stating that any non-adaptive measurement strategy will fail to exploit quantum critical enhancement (i.e. precision beyond the shot-noise limit) for a sufficiently large number of particles $N$ whenever our prior knowledge is limited. We then consider different adaptive strategies that can overcome this no-go result, and illustrate their performance in the estimation of (i) a magnetic field using a probe of 1D spin Ising chain and (ii) the coupling strength in a Bose-Hubbard square lattice. Our results show that adaptive strategies with real-time feedback control can achieve sub-shot noise scaling even with few measurements and substantial prior uncertainty.
