Compact all-fiber quantum-inspired LiDAR with over 100 dB noise rejection and single photon sensitivity

Han Liu (), Changhao Qin, Georgios Papangelakis, Meng Lon Iu and Amr S. Helmy
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Han Liu: University of Toronto
Changhao Qin: University of Toronto
Georgios Papangelakis: University of Toronto
Meng Lon Iu: University of Toronto
Amr S. Helmy: University of Toronto

Nature Communications, 2023, vol. 14, issue 1, 1-8

Abstract: Abstract Entanglement and correlation of quantum light can enhance LiDAR sensitivity in the presence of strong background noise. However, the power of such quantum sources is fundamentally limited to a stream of single photons and cannot compete with the detection range of high-power classical LiDAR transmitters. To circumvent this, we develop and demonstrate a quantum-inspired LiDAR prototype based on coherent measurement of classical time-frequency correlation. This system uses a high-power classical source and maintains the high noise rejection advantage of quantum LiDARs. In particular, we show that it can achieve over 100dB rejection (with 100ms integration time) of indistinguishable (with statistically identical properties in every degree of freedom) in-band noise while still being sensitive to single photon signals. In addition to the LiDAR demonstration, we also discuss the potential of the proposed LiDAR receiver for quantum information applications. In particular, we propose the chaotic quantum frequency conversion technique for coherent manipulation of high dimensional quantum states of light. It is shown that this technique can provide improved performance in terms of selectivity and efficiency as compared to pulse-based quantum frequency conversion.

Date: 2023
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DOI: 10.1038/s41467-023-40914-6

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