Widefield Diamond Quantum Sensing with Neuromorphic Vision Sensors

Citation:  Du, Zhiyuan & Gupta, Madhav & Xu, Feng & Zhang, Kai & Zhang, Jiahua & Zhou, Yan & Liu, Yiyao & Wang, Zhenyu & Wong, Ngai & Li, Can & Chu, Zhiqin. (2024). Widefield Diamond Quantum Sensing with Neuromorphic Vision Sensors (Adv. Sci. 2/2024). Advanced Science. 11. 10.1002/advs.202470013.

Authors:  Zhiyuan Du, Madhav Gupta, Feng Xu, Kai Zhang, Jiahua Zhang, Yan Zhou, Yiyao Liu, Zhenyu Wang, Jörg Wrachtrup, Ngai Wong, Can Li and Zhiqin Chu.

Publication location: Advanced Science News

Year (date): 2023

D.O.I:  10.1002/advs.202304355

Abstract:  Despite increasing interest in developing ultrasensitive widefield diamond magnetometry for various applications, achieving high temporal resolution and sensitivity simultaneously remains a key challenge. This is largely due to the transfer and processing of massive amounts of data from the frame-based sensor to capture the widefield fluorescence intensity of spin defects in diamonds. In this study, a neuromorphic vision sensor to encode the changes of fluorescence intensity into spikes in the optically detected magnetic resonance (ODMR) measurements is adopted, closely resembling the operation of the human vision system, which leads to highly compressed data volume and reduced latency. It also results in a vast dynamic range, high temporal resolution, and exceptional signal-to background ratio. After a thorough theoretical evaluation, the experiment with an off-the-shelf event camera demonstrated a 13× improvement in temporal resolution with comparable precision of detecting ODMR resonance frequencies compared with the state-of the-art highly specialized frame-based approach. It is successfully deploy this technology in monitoring dynamically modulated laser heating of gold nanoparticles coated on a diamond surface, a recognizably difficult task using existing approaches. The current development provides new insights for high-precision and low-latency widefield quantum sensing, with possibilities for integration with emerging memory devices to realize more intelligent quantum sensors.

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Credits: USTUTT

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