Continuous field tracking with machine learning and steady state spin squeezing

TL;DR

This paper demonstrates sustained spin squeezing in a large atomic ensemble using optical pumping and continuous measurements, enabling long-term quantum-enhanced magnetic field sensing with deep learning decoding.

Contribution

It introduces a method to maintain steady spin squeezing over a day in a hot atomic ensemble, advancing quantum metrology applications.

Findings

Achieved steady spin squeezing of -3.23 dB in 4x10^10 atoms.

Maintained quantum-enhanced sensing for about one day.

Used deep learning to decode measurement signals for magnetic field tracking.

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.