Adaptive Robust High-Precision Atomic Gravimetry

TL;DR

This paper introduces an adaptive Bayesian quantum estimation protocol for atomic gravimeters, significantly enhancing their precision, dynamic range, and noise robustness for practical sensing applications.

Contribution

It develops a novel adaptive measurement protocol that improves precision scaling and robustness in atomic gravimetry without requiring multiple fringe scans.

Findings

Achieves over 5-fold precision improvement in transportable gravimeters

Enhances measurement scaling to $ ilde{T}^{-2}$ or better

Increases robustness against environmental noise

Abstract

Atomic gravimeters are the most accurate sensors for measuring gravity, yet a significant challenge lies in achieving high precision while also maintaining high dynamic range and robustness. Here, we develop a protocol for achieving robust high-precision atomic gravimetry based upon adaptive Bayesian quantum estimation. Our protocol incorporates a sequence of interferometry measurements taken with short to long interrogation times and offers several crucial advantages. Firstly, it enables a high dynamic range without the need to scan multiple fringes for pre-estimation, making it more efficient than the conventional frequentist method. Secondly, it improves robustness against noise, allowing for a significant improvement in measurement precision in noisy environments. The enhancement can be more than 5 times for a transportable gravimeter [Sci. Adv. 5, eaax0800 (2019)] and up to an order of magnitude for a state-of-the-art fountain gravimeter [Phys. Rev. A 88, 043610 (2013)]. Notably, by optimizing the interferometry sequence, our approach can improve the scaling of the measurement precision ($\Delta g_{est}$) versus the total interrogation time ($\tilde{T}$) to $\Delta g_{est} \propto \tilde{T}^{-2}$ or even better, in contrast to the conventional one $\Delta g_{est} \propto \tilde{T}^{-0.5}$. Our approach offers superior precision, increased dynamic range, and enhanced robustness, making it highly promising for a range of practical sensing applications.