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arXiv 2511.03411cond-mat.mtrl-sci
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NV色心的统计成像揭示金刚石中缺陷的簇状形成

Statistical imaging of NV centers reveals clustered defect formation in diamond

CUNY- The City College of New York(纽约市立大学学院);CUNY-Graduate Center(纽约市立大学研究生院)

Jason Shao, Richard Monge, Tom Delord, Carlos A. Meriles

AI总结:

本研究利用共振光致发光激发成像实现金刚石中NV色心的统计分析,发现其呈非泊松簇状分布,为金刚石缺陷研究及量子应用提供了可扩展方法。

摘要:

金刚石中NV⁻色心在低温下的尖锐光学共振为材料表征提供了强大的新能力,但提取最详细信息通常需要对单个传感器进行仔细校准,这限制了可扩展性。在这项工作中,我们使用共振光致发光激发成像在大视场范围内光学分辨并监测数百个单个NV色心,实现了具有亚衍射分辨率的空间分布统计分析。这种多路复用、非破坏性方法允许量子传感器对其所处的材料平台进行表征。针对化学气相沉积(CVD)生长的金刚石,我们发现其与随机分布存在显著偏差,包括出现意外高比例的由两个或更多NV色心组成的紧密间距簇。这些发现表明存在非泊松形成动力学,并指向空间相关的缺陷产生机制。除了为金刚石生长和NV色心形成提供见解外,我们的方法还能规模化识别天然存在的NV簇——这些构型有望用于纠缠辅助量子信息协议和关联传感——并为在单发射器水平上对各种材料基体进行结构和电子缺陷分析开辟了途径。

英文摘要:

The sharp optical resonances of NV- centers in diamond at cryogenic temperatures offer powerful new capabilities for material characterization, but extracting the most detailed information typically requires careful calibration of individual sensors, limiting scalability. In this work, we use resonant photoluminescence excitation imaging to optically resolve and monitor hundreds of individual NVs across large fields of view, enabling statistical analysis of their spatial distribution with sub-diffraction resolution. This multiplexed, non-destructive approach allows quantum sensors to characterize the material platform they inhabit. Focusing on CVD-grown diamond, we uncover significant deviations from random distributions, including an unexpectedly high occurrence of closely spaced clusters comprising two or more NVs. These findings suggest non-Poissonian formation dynamics and point to spatially correlated defect generation mechanisms. Beyond offering insight into diamond growth and NV center formation, our approach enables the scalable identification of naturally occurring NV clusters - configurations that are promising for entanglement-assisted quantum information protocols and correlated sensing - and establishes a path toward structural and electronic defect analysis in various material hosts at the single-emitter level.

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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