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Noise-resilient single-pixel compressive sensing with single photon counting

Physics

Noise-resilient single-pixel compressive sensing with single photon counting

L. Li, S. Kumar, et al.

This groundbreaking research by Lili Li, Santosh Kumar, Yong Meng Sua, and Yu-Ping Huang explores the degradation of single-pixel optical classifiers due to compressive sensing challenges and photon-counting noise. By implementing quantum parametric mode sorting, this team achieves an impressive 94% classification accuracy amidst extreme noise, showcasing a novel approach to enhance single-photon sensing in demanding environments.

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