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arXiv 2402.00536quant-ph
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基于机器学习与稳态自旋压缩的连续场追踪

Continuous field tracking with machine learning and steady state spin squeezing

Junlei Duan, Zhiwei Hu, Xingda Lu, Liantuan Xiao, Suotang Jia, Klaus Mølmer, Yanhong Xiao

AI总结:

本文结合光泵浦与连续量子非破坏测量,在热原子系综中实现约一天、-3.23 dB的稳态自旋压缩,并利用深度学习解码光信号以追踪连续波动磁场,在原子磁强计中验证了量子增强。

摘要:

纠缠在量子计量方案中起着至关重要的作用,然而在持续自旋纠缠条件下展示传感中的量子增强仍然是一项具有挑战性的工作。在此,我们结合光泵浦与连续量子非破坏测量,在 $\bm{4 \times 10^{10}}$ 个热原子中实现了持续的自旋压缩态。利用预测与回溯,维持了约一天的计量学相关的稳态压缩,压缩度为 $\bm{-3.23 \pm 0.24}$ dB。我们利用该系统追踪不同类型的连续时间波动磁场,并构建深度学习模型来解码来自光信号的测量记录。在我们的原子磁强计中验证了由稳态自旋压缩带来的量子增强。这些结果代表了在现实环境中应用长寿命量子纠缠资源方面的重要进展。

英文摘要:

Entanglement plays a crucial role in proposals for quantum metrology, yet demonstrating quantum enhancement in sensing with sustained spin entanglement remains a challenging endeavor. Here, we combine optical pumping and continuous quantum nondemolition measurements to achieve a sustained spin squeezed state with $\bm{4 \times 10^{10}}$ hot atoms. A metrologically relevant steady state squeezing of $\bm{-3.23 \pm 0.24}$ dB using prediction and retrodiction is maintained for about one day. We employ the system to track different types of continuous time-fluctuating magnetic fields, where we construct deep learning models to decode the measurement records from the optical signals. Quantum enhancement due to the steady spin squeezing is verified in our atomic magnetometer. These results represent important progress towards applying long-lived quantum entanglement resources in realistic settings.

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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