A Sparse-Event Simulation Engine to Model Coincidence-Based Ranging Architectures in Quantum Lidar

Non-classical radar and lidar systems have received substantial interest recently; however, while the many experimental demonstrations have provided deep physical knowledge of such systems, there remains a lack of effective system models to obtain fundamental metrics such as range resolution as a function of system parameters. This work introduces a high-fidelity simulation platform to mimic a certain type of quantum radar, specifically a recently proposed one based on temporal coincidences that arise due to entanglement. Specifically, the system measures coincidences between events related to a reference source and those related to the back-scattering of photons from targets. The large number of events – and their complex interaction with system components – makes a realistic simulation challenging. As an initial assessment, in this paper we develop a simulator to estimate the expected point spread function (PSF), and thereby the range resolution, considering various coincidence window time widths and system non-idealities. The estimate is based on the numerical computation of the correlation between the reference traces shifted along the time domain and traces of back-scattered photons (along with noise photons). The simulated results are comparable to available experimental results, illustrating the fidelity of the simulation engine. A crucial result is that, unlike a classical radar, the PSF and range resolution depends upon the environmental noise and multiple system parameters, not just the transmitted waveform.