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<p>Ultrafast temperature field detection and identification is crucial for applications ranging from environmental sensing and biomedical monitoring to thermal management in advanced energy systems. Conventional temperature sensors—comprising discrete sensing arrays, data storage units, and external processors—suffer from high latency due to slow sensor response, repeated analog-to-digital conversions, and extensive data transmission inherent to von Neumann architectures. Here, we report a diamond array-based quantum sensor that integrates temperature sensing and real-time processing within a unified in-sensor computing (ISC) architecture. Exploiting the strong linear correlation between temperature and the zero-field splitting of nitrogen-vacancy (NV) color center centers in diamond, we realize a fixed-frequency temperature sensor with ultrafast response and tunable responsivity, enabled by multi-parameter microwave modulate. Matrix-vector multiplication of temperature intensity and responsivity, combined with Kirchhoff’s current summation, enables direct execution of neural-network-style computations on sensed data. The proposed system achieves a single-shot detection and identification latency of just 196.8 μs, as experimentally validated. This work demonstrates a scalable ISC-enabled quantum sensing paradigm, offering a promising route toward high-speed, low-power intelligent temperature field detection.</p><p></p>

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Temperature field ultrafast detection and identification quantum sensor based on diamond array

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月10日

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  • Wei Gao,
  • Jinyu Tai,
  • Zhiqiang Xiang,
  • Yunbo Shi,
  • Xin Li,
  • Huanfei Wen,
  • Fei Deng,
  • Zhonghao Li,
  • Zongmin Ma,
  • Hailong Wang,
  • Weixuan Zhang,
  • Zheng Lou,
  • Hao Guo,
  • Jun Tang,
  • Lili Wang,
  • Jun Liu

摘要

Ultrafast temperature field detection and identification is crucial for applications ranging from environmental sensing and biomedical monitoring to thermal management in advanced energy systems. Conventional temperature sensors—comprising discrete sensing arrays, data storage units, and external processors—suffer from high latency due to slow sensor response, repeated analog-to-digital conversions, and extensive data transmission inherent to von Neumann architectures. Here, we report a diamond array-based quantum sensor that integrates temperature sensing and real-time processing within a unified in-sensor computing (ISC) architecture. Exploiting the strong linear correlation between temperature and the zero-field splitting of nitrogen-vacancy (NV) color center centers in diamond, we realize a fixed-frequency temperature sensor with ultrafast response and tunable responsivity, enabled by multi-parameter microwave modulate. Matrix-vector multiplication of temperature intensity and responsivity, combined with Kirchhoff’s current summation, enables direct execution of neural-network-style computations on sensed data. The proposed system achieves a single-shot detection and identification latency of just 196.8 μs, as experimentally validated. This work demonstrates a scalable ISC-enabled quantum sensing paradigm, offering a promising route toward high-speed, low-power intelligent temperature field detection.