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一种基于卡尔曼滤波器的方法用于改进温度传感的NV金刚石数据融合

A Kalman Filter Based Approach to NV Diamond Data Fusion For Improved Temperature Sensing

Shraddha Rajpal, Qiaochu Guo, Brendon A. McCullian, Tyrus Berry, Zeeshan Ahmed

arXiv 2607.22410首次发表:更新:

AI 中文总结

研究利用热启动卡尔曼滤波方法融合金刚石中氮空位(NV)中心的光探测磁共振(ODMR)和全光测量两种模态进行温度传感,使精度提高57%,实现了低延迟下的高长期精度,为高精度NV金刚石温度传感提供可行方案。

AI 中文摘要

金刚石中的氮空位(NV)中心已被证明能够使用多种模态进行高灵敏度温度测量。独立的光探测磁共振(ODMR)可提供可靠的温度估计,尽管延迟较高,而全光测量提供毫秒级分辨率,但长期精度较差。在这项工作中,我们展示了一种热启动卡尔曼滤波方法,该方法融合了这两种模态,使精度提高了57%。融合估计在较低延迟下实现了更高的长期精度,为实现自校正、高精度NV金刚石温度传感方案提供了一条可行途径。

英文摘要

Nitrogen-vacancy (NV) centers in diamond have been demonstrated to enable highly sensitive temperature measurements using multiple modalities. Standalone optically detected magnetic resonance (ODMR) provides robust temperature estimates, albeit with high latency, whereas all-optical measurements provide millisecond resolution but suffer from poorer long-term accuracy. In this work, we demonstrate a hot-start Kalman filtering approach that fuses the two modalities, leading to a 57% improvement in accuracy. The fused estimate achieves higher long-term accuracy with lower latency, demonstrating a viable route toward implementing self-correcting, high-precision NV-diamond temperature sensing schemes.

Comments16 pages, 3 figures, 2 tables

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