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arXiv 2408.01313quant-ph
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连续监测温度计的最优极限及其哈密顿结构

Optimal limits of continuously monitored thermometers and their Hamiltonian structure

Mohammad Mehboudi, Florian Meier, Marcus Huber, Harry J. D. Miller

AI总结:

研究通过连续监测探针,发现温度计精度与N线性相关,优于平衡温度计的log²N缩放,并揭示最优哈密顿结构为退化二能级系统。

摘要:

我们通过将N级探针与玻色子和费米子环境耦合,并对其进行连续监测,研究了在玻色子和费米子环境中温度计的 fundamental 和 practical 精度极限。我们的发现表明,最终的精度极限,由Fisher信息量度,与N线性相关,相较于平衡温度计的 scaling 仅为 log² N 提供了指数级改进。对于固定的哈密顿结构,我们开发了一种最大似然估计策略,将观测到的连续监测探针轨迹映射为温度估计,其误差最小。通过优化所有可能的哈密顿结构,我们发现最优配置是一个有效的二能级系统,其中两个能级的退化性随N增加而增加,这与平衡温度计中基态非退化性形成鲜明对比。我们的结果具有实际意义。首先,连续监测在多个平台上实验上是可行的,并且考虑了探针的准备时间,这在其他方法如准备和重置中常被忽视。其次,线性缩放对偏离最优哈密顿结构的有效二能级结构的偏差具有鲁棒性。此外,这种鲁棒性还扩展到初始对温度的无知情况。因此,在全局估计问题中,即使没有自适应策略,线性缩放仍然保持不变。

英文摘要:

We investigate the fundamental and practical precision limits of thermometry in bosonic and fermionic environments by coupling an $N$-level probe to them and continuously monitoring it. Our findings show that the ultimate precision limit, quantified by the Fisher information, scales linearly with $N$, offering an exponential improvement over equilibrium thermometry, where the scaling is only $\log^2 N$. For a fixed Hamiltonian structure, we develop a maximum likelihood estimation strategy that maps the observed continuously monitored trajectories of the probe into temperature estimates with minimal error. By optimizing over all possible Hamiltonian structures, we discover that the optimal configuration is an effective two-level system, with both levels exhibiting degeneracy that increases with $N$-a stark contrast to equilibrium thermometry, where the ground state remains non-degenerate. Our results have practical implications. First, continuous monitoring is experimentally feasible on several platforms and accounts for the preparation time of the probe, which is often overlooked in other approaches such as prepare-and-reset. Second, the linear scaling is robust against deviations from the effective two-level structure of the optimal Hamiltonian. Additionally, this robustness extends to cases of initial ignorance about the temperature. Thus, in global estimation problems, the linear scaling remains intact even without adaptive strategies.

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。

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