In time-correlated single-photon counting (TCSPC), photons that arrive during the detector and timing electronics dead times are missed, causing distortion of the detection time distribution. Conventional wisdom holds that TCSPC should be performed with detections in fewer than 5% of illumination cycles to avoid substantial distortion. This requires attenuation and leads to longer acquisition times if the incident flux is too high. Through the example of ranging with a single-photon lidar system, this work demonstrates that accurately modeling the sequence of detection times as a Markov chain allows for measurements at much higher incident flux without attenuation. Our probabilistic model is validated by the close match between the limiting distribution of the Markov chain and both simulated and experimental data, so long as issues of calibration and afterpulsing are minimal. We propose an algorithm that corrects for the distortion in detection histograms caused by dead times without assumptions on the form of the transient light intensity. Our histogram correction yields substantially improved depth imaging performance, and modest additional improvement is achieved with a parametric model assuming a single depth per pixel. We show results for depth and flux estimation with up to 5 photoelectrons per illumination cycle on average, facilitating an increase in time efficiency of more than two orders of magnitude. The use of identical TCSPC equipment in other fields suggests that our modeling and histogram correction could likewise enable high-flux acquisitions in fluorescence lifetime microscopy or quantum optics applications.

中文翻译：

---

高通量单光子激光雷达

在与时间相关的单光子计数（TCSPC）中，错过了在检测器期间到达的光子和计时电子设备的死区时间，从而导致检测时间分布失真。传统观点认为，应在少于5％的照明周期进行检测的情况下执行TCSPC，以免产生实质性的失真。如果入射通量太大，则需要衰减并导致更长的采集时间。通过单光子激光雷达系统的测距示例，这项工作表明，准确地建立检测时间序列的马尔可夫链模型可以在更高的入射通量下进行测量而不会产生衰减。我们的概率模型通过马尔可夫链的极限分布与模拟和实验数据之间的紧密匹配而得到验证，只要校准和后脉冲问题最小。我们提出了一种算法，该算法可以校正死区时间导致的检测直方图中的失真，而无需假设瞬态光强度的形式。我们的直方图校正可显着改善深度成像性能，并且在假设每个像素只有一个深度的参数模型中可获得适度的额外改​​进。我们展示了平均深度和光通量估计的结果，平均每个照明周期最多有5个光电子，从而使时间效率提高了两个数量级以上。在其他领域使用相同的TCSPC设备表明，我们的建模和直方图校正同样可以在荧光寿命显微镜或量子光学应用中实现高通量采集。我们提出了一种算法，该算法可以校正死区时间导致的检测直方图中的失真，而无需假设瞬态光强度的形式。我们的直方图校正可显着改善深度成像性能，并且在假设每个像素只有一个深度的参数模型中可获得适度的额外改​​进。我们展示了平均深度和光通量估计的结果，每个照明周期平均最多有5个光电子，这有助于将时间效率提高两个数量级以上。在其他领域使用相同的TCSPC设备表明，我们的建模和直方图校正同样可以在荧光寿命显微镜或量子光学应用中实现高通量采集。我们提出了一种算法，该算法可以校正死区时间导致的检测直方图中的失真，而无需假设瞬态光强度的形式。我们的直方图校正可显着改善深度成像性能，并且在假设每个像素只有一个深度的参数模型中可获得适度的额外改​​进。我们展示了平均深度和光通量估计的结果，每个照明周期平均最多有5个光电子，这有助于将时间效率提高两个数量级以上。在其他领域使用相同的TCSPC设备表明，我们的建模和直方图校正同样可以在荧光寿命显微镜或量子光学应用中实现高通量采集。