Continuous field tracking with machine learning and steady state spin squeezing

• URL: http://arxiv.org/abs/2402.00536v1
• Date: Thu, 1 Feb 2024 12:04:04 GMT
• Title: Continuous field tracking with machine learning and steady state spin squeezing
• Authors: Junlei Duan, Zhiwei Hu, Xingda Lu, Liantuan Xiao, Suotang Jia, Klaus M{\o}lmer, Yanhong Xiao
• Abstract summary: We combine optical pumping and continuous quantum nondemolition measurements to achieve a sustained spin squeezed state with $bm4 times 1010$ 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.
• Score: 4.969887562291159
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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