Wavelet-Based Quantum Sensing of Geomagnetic Fluctuations With Multiple NV Ensembles

Chou-Wei Kiang;Jean-Fu Kiang
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Abstract

Nitrogen-vacancy (NV) ensembles are viable magnetometers to be implemented on nanosatellites for monitoring geomagnetic fluctuations, which are credible precursors for predicting earthquakes at short notice. In this work, a Haar wavelet-based quantum sensing method is proposed to reconstruct the time-varying waveform of geomagnetic fluctuations in the very low frequency band. To collect different frequency components of fluctuations waveform at once, we propose a schematic to employ multiple NV ensembles (NVEs), with each controlled by an independent microwave source. Berry sequences are applied on one set of NVEs to extract the scaling coefficients from accumulated geometric phases to reconstruct near-dc components of a waveform. Spin-echo sequences are applied to another set of NVEs to extract the Haar wavelet coefficients from the dynamic phases to reconstruct high-frequency components. The efficacy of the proposed sensing protocol implemented on multiple NVEs is validated by reconstructing a waveform of geomagnetic fluctuations from a DEMETER satellite dataset through simulations. Each NVE is assumed to contain $N = 10^{8}$ uncorrelated NV centers. The application of a Berry sequence to each NVE can achieve the maximum detectable magnetic field of over $460 \ \mu$T, resolving the issues of phase ambiguity and hyperfine-induced detuning if conventional Ramsey sequence were applied. The feasibility of the proposed simulation scenario considering spin-bath noise within an NVE is justified by simulations. The effects of wavelet scales, Rabi frequency in Berry sequence, and number of NV centers in each NVE are analyzed. The proposed NVE quantum sensors operated with the proposed sensing protocol can be installed on nanosatellites to monitor global geomagnetic fluctuations, with sub-$\mu$s temporal resolution in the near future.
基于小波的多NV系综地磁波动量子传感
氮空位(NV)集合是一种可行的磁力计,将在纳米卫星上实施,用于监测地磁波动,而地磁波动是在短时间内预测地震的可靠前兆。本文提出了一种基于Haar小波的量子传感方法,用于重建地磁波动在极低频段的时变波形。为了同时收集波动波形的不同频率成分,我们提出了一个使用多个NV集成(nve)的示意图,每个nve由一个独立的微波源控制。在一组nve上应用Berry序列,从累积的几何相位中提取尺度系数,重建波形的近直流分量。将自旋回波序列应用于另一组nve,从动态相位提取Haar小波系数,重构高频分量。通过模拟重建DEMETER卫星数据集的地磁波动波形,验证了该传感方案在多个nve上实现的有效性。假设每个NVE包含$N = 10^{8}$不相关的NV中心。对每个NVE应用Berry序列可以实现超过$460 \ \mu$T的最大可检测磁场,解决了使用常规Ramsey序列时的相位模糊和超细诱导失谐问题。通过仿真验证了该方法的可行性。分析了小波尺度、Berry序列中的Rabi频率和每个NVE中NV中心数的影响。按照拟议传感协议运行的拟议NVE量子传感器可安装在纳米卫星上,以监测全球地磁波动,在不久的将来,其时间分辨率将低于5 μ m。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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