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arXiv 2401.02128quant-phcond-mat.mtrl-sci
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利用固态量子多传感器系统进行原子尺度结构分析的关联传感

Correlated sensing with a solid-state quantum multi-sensor system for atomic-scale structural analysis

Wentao Ji, Zhaoxin Liu, Yuhang Guo, Zhihao Hu, Jingyang Zhou, Siheng Dai, Yu Chen, Pei Yu, Mengqi Wang, Kangwei Xia, Fazhan Shi, Ya Wang, Jiangfeng Du

AI总结:

本文提出一种利用多量子传感器间信号关联的新型传感范式,通过三个氮-空位中心构成的量子静电计系统,实现了对金刚石中16个暗电子点缺陷的三维高精度定位及实时电荷动力学可视化,扩展了量子传感工具箱。

摘要:

开发从超高精度测量到复杂结构分析的卓越量子传感策略,是量子技术的核心。尽管利用量子资源(如传感器间的纠缠)来提升传感精度的策略已得到充分证明,但量子传感器间的信号关联却鲜少被利用。在此,我们开发了一种新型传感范式,利用多个量子传感器间的信号关联,来解析单个传感器无法解析的多目标重叠信号以及复杂结构构建难以处理的问题。我们以三个氮-空位(NV)中心作为量子静电计系统,通过从系综信号中解析出单个缺陷的涨落电场,展示了这种多传感器范式。我们通过类似GPS的定位方法,对金刚石中16个暗电子点缺陷的三维分布进行了成像,精度接近1.7 nm。此外,我们获取了单个点缺陷的实时电荷动力学,并可视化了该动力学如何引发著名的光谱扩散。该多传感器范式扩展了量子传感工具箱,为结构分析提供了新的可能性。

英文摘要:

Developing superior quantum sensing strategies ranging from ultra-high precision measurement to complex structural analysis is at the heart of quantum technologies. While strategies using quantum resources, such as entanglement among sensors, to enhance the sensing precision have been abundantly demonstrated, the signal correlation among quantum sensors is rarely exploited. Here we develop a novel sensing paradigm exploiting the signal correlation among multiple quantum sensors to resolve overlapping signals from multiple targets that individual sensors can't resolve and complex structural construction struggles with. With three nitrogen-vacancy centers as a quantum electrometer system, we demonstrate this multi-sensor paradigm by resolving individual defects' fluctuating electric fields from ensemble signals. We image the three-dimensional distribution of 16 dark electronic point-defects in diamond with accuracy approaching 1.7 nm via a GPS-like localization method. Furthermore, we obtain the real-time charge dynamics of individual point defects and visualize how the dynamics induce the well-known optical spectral diffusion. The multi-sensor paradigm extends the quantum sensing toolbox and offers new possibilities for structural analysis.

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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