Single-photon light detection and ranging (LiDAR) is an optical imaging and sensing technique that combines single-photon detection, computational imaging algorithms, and related techniques1. It actively emits laser pulses from the system to the object and exploits the single-photon detectors to record the time-of-flight of echo photons, where the time-of-flight measurements are processed to obtain 3D information. Single-photon LiDAR can achieve exceptional potential for precise imaging and remote sensing through its picosecond-level temporal resolution and single-photon sensitivity, attracting widespread attention in research and applications2. Recent developments have witnessed remarkable progress in LiDAR techniques and imaging algorithms. The photon-efficient imaging algorithms enable the processing of LiDAR data to precisely reconstruct the 3D image using as low as one photon per pixel3,4. The advanced single-photon LiDAR systems can deliver detailed 3D images at kilometer range5, obtain the image of targets tens or hundreds of kilometers away6,7, or reconstruct the targets that are not in the line-of-sight8,9. These progresses provide exciting new prospects for the widespread LiDAR applications.

The detectors in the previous single-photon LiDAR systems can only distinguish whether there are photons or not (i.e., threshold detection2), but cannot resolve the exact number of photons. This makes it difficult to accurately extract signal photons flooded by the strong noise photons. In addition, the threshold detection will lose the statistical information of photon numbers, which prevents the LiDAR from reaching the standard quantum limit10 (SQL) set by the photon-number statistics.

In a paper in Light: Science & Applications11, Haochen Li et al., propose a photon-number-resolving (PNR) single-photon LiDAR and show the capability to approach the SQL of the amplitude measurement of the light field. To do so, they develop a superconducting nanowire single-photon detector (SNSPD) array to realize PNR detection for up to 16 photons through spatial multiplexing, and design an active photon number filter (APNF) to adaptive select the effective photon number content and construct temporal gate (see Fig. 1). The APNF is design to adaptive select the effective photon number content and construct temporal gate to filter out noise events according to the statistic distribution of photon numbers.

Fig. 1: Schematic diagram of the proposed method. Schematic diagram of the LiDAR system with photon-number-resolving (PNR) detection.
figure 1

The data is obtained by the transceiver, detected by the superconducting nanowire single-photon detector (SNSPD) array, and processed by the active photon number filter (APNF) algorithm

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Tested in the outdoor experiments, the proposed LiDAR system is capable to reconstruct the complex structure of a distributed pylon nearly noise-free over a standoff distance of 900 meters. The photon statistic measuring capability of the LiDAR is quantified by comparing the Fisher information of detection with the quantum Fisher information determined by the quantum fluctuation of coherent light. The results indicate that the proposed LiDAR can approach the SQL of the amplitude measurement of the light field within a large dynamic range, enabling faster and more accurate target measurement and materials identification in various scenarios.

Note that the single-photon LiDAR is believe to be particularly useful in the photon-starved situation with much less than one photon detection (per pulse period). This is indeed the scenario in the long-range target detection3,4,5,6,7, biology imaging12, non-line-of-sight imaging8,9 and so forth1,2. The proposed PNR approach will lose its advantage, but it may be valuable in the high-flux case13.

Recently, the emerging technologies such as single-photon avalanche diode, quantum light source, integrated photonics, and machine learning have been accelerating the advancement of single-photon LiDAR12,13,14,15,16. Overall, the successful integration of two advanced technologies, SNSPD array and the tailored computational imaging algorithm, has made it possible to realize target reconstruction approaching the SQL in the daytime. In the future, the PNR detection is expected to provide a new perspective for optical imaging and sensing.