Compact All-Fiber Quantum-Inspired LiDAR with > 100dB Noise Rejection and Single Photon Sensitivity

TL;DR

This paper presents a novel all-fiber, quantum-inspired LiDAR system that achieves over 100dB noise rejection and single-photon sensitivity using classical light sources, bridging quantum advantages with classical power levels.

Contribution

The authors develop a high-power classical LiDAR prototype that mimics quantum correlations, enabling superior noise rejection while maintaining single-photon sensitivity, and introduce a new chaotic quantum frequency conversion technique.

Findings

Achieves >100dB in-band noise rejection with 100ms integration.

Maintains sensitivity to single-photon signals despite high noise rejection.

Proposes a novel chaotic quantum frequency conversion method for quantum state manipulation.

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 correlations. 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 degrees 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.