A method to correct the temporal drift of single photon detectors, based on asynchronous quantum ghost imaging

Single photon detection and timing gathered increasing interest in the last few years due to both its necessity in the field of quantum sensing and the advantages of single quanta detection in the field of low level light imaging. While simple bucket detectors are mature enough for commercial applications, more complex imaging detectors are still a field of research with mostly prototype level detectors. A major problem in these detectors is the implementation of in-pixel timing circuitry, especially for two-dimensional imagers. One of the most promising approaches is the use of voltage controlled ring resonators in every pixel. Each of those is running independently, based on a voltage supplied by a global reference. However, this yields the problem that across the chip the supply voltage can change, which in turn changes the period of the ring resonator. Due to additional parasitic effects, this problem can worsen with increasing measurement time, leading to a drift of the timing information. We present here a method to identify and correct such temporal drifts of single photon detectors, based on asynchronous quantum ghost imaging. We also show the effect of this correction on a recent QGI measurement from our group.

Histogram-less LiDAR through SPAD response linearization

We present a new method to acquire the 3D information from a SPAD-based direct-Time-of-Flight (d-ToF) imaging system which does not require the construction of a histogram of timestamps and can withstand high flux operation regime. The proposed acquisition scheme emulates the behavior of a SPAD detector with no distortion due to dead time, and extracts the Tof information by a simple average operation on the photon timestamps ensuring ease of integration in a dedicated sensor and scalability to large arrays. The method is validated through a comprehensive mathematical analysis, whose predictions are in agreement with a numerical Monte Carlo model of the problem. Finally, we show the validity of the predictions in a real d-ToF measurement setup under challenging background conditions well beyond the typical pile-up limit of 5% detection rate up to a distance of 3.8 m.