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A joint project led by Professor Zhiqin Chu, Professor Can Li and Professor Ngai Wong in the Department of Electrical and Electronic Engineering at the University of Hong Kong (HKU) has made a breakthrough in increasing the speed and resolution of wide-field quantum sensing, which for new opportunities in scientific research and practical applications.

Collaborating with scientists from mainland China and Germany, the team has successfully developed a breakthrough quantum sensing technology using a neuromorphic vision sensor, designed to mimic the human visual system. This sensor is capable of encoding changes in fluorescence intensity into spikes during optically detected magnetic resonance (ODMR) measurements. The key advantage of this approach is that it results in highly compressed data volumes and reduced latency, making the system more efficient than traditional methods. These advances in quantum sensing have the potential for a variety of applications in areas such as monitoring dynamic processes in biological systems.

The research paper has been published in the journal. Advanced Science Title “Widefield Diamond Quantum Sensing with Neuromorphic Vision Sensor.”

“Researchers around the world have devoted considerable effort to finding ways to improve the measurement accuracy and spatiotemporal resolution of camera sensors. But one fundamental challenge remains: handling the large amount of data in the form of image frames that the camera captures.” need to be transferred from the sensor. Further processing. This data transfer can significantly limit the spatial resolution, which is typically no higher than 100 fps due to the use of frame-based image sensors. We What it did was try to overcome the obstacle,” said Zhiyuan Du, the first author. Papers and PhD candidates in Electrical and Electronic Engineering Department

Du said his professor’s focus on quantum sensing inspired him and other team members to break new ground in the area. He is also passionate about combining sensing and computing.

“The latest development provides new insights for high-precision and low-latency wide-field quantum sensing, with potential for integration with emerging memory devices to realize more intelligent quantum sensors,” he added.

The team’s experience with the off-the-shelf event camera demonstrated a 13× improvement in temporal resolution, with comparable accuracy in detecting the ODMR resonance frequency with the state-of-the-art highly specialized frame-based approach. The new technology was successfully deployed in monitoring dynamically modulated laser heating of gold nanoparticles coated on a diamond surface. “It would be difficult to accomplish the same task using current methods,” Doe said.

Unlike conventional sensors that record light intensity levels, neuromorphic vision sensors convert light intensity into “spikes” similar to biological vision systems, resulting in spatial resolution (≈µs) and dynamic range ( >120 dB) improves. This approach is particularly effective in scenarios where image changes are infrequent, such as object tracking and autonomous vehicles, as it eliminates redundant static background signals.

“We expect that our successful demonstration of the proposed method will revolutionize wide-field quantum sensing, significantly improving performance at an affordable cost,” said Prof. Zhiqin Chu.

“It also brings sensor processing closer together with emerging memory-based electronic synapse devices,” said Professor Ken Lee.

“The technology’s potential for industrial applications should be further explored, such as studying dynamic changes in current in materials and identifying defects in microchips,” said Professor Ngai Wong.

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