Source Count Distribution

Source count distribution (SCD) analysis aims to determine the number density of faint, unresolved sources as a function of their brightness, a crucial task in fields like astronomy. Current research focuses on leveraging machine learning, particularly deep learning architectures like convolutional neural networks, to extract SCDs from complex observational data, often incorporating spectral information to improve accuracy and extend analysis to fainter sources than previously possible. These advancements enable more precise characterization of astronomical populations and improve our understanding of phenomena like extragalactic gamma-ray sources, impacting cosmological models and related fields.