Restoring Information from Sparse Single Photon Detection Events for Experiments in Quantum Optics

The precise analysis and control of quantum systems are critical for assessing their potential in advanced quantum technologies. Many characterization methods and prospective quantum applications rely on the detection of single photons and are therefore often time-consuming and resource-intensive. In this work, we adapt a statistical Monte Carlo (MC) simulation method, originally used in astrophysics and high-energy physics [1], to retrieve information from undersampled experimental data.