Machine Learning-Based Pipeline for Pulsar Analysis (ML-PPA)

Future experiments, such as the Square Kilometer Array Observatory (SKAO), will produce huge data streams, which must be analyzed in real time for identifying the often small amounts of relevant information. One of the central tasks of the SKAO is the search for signals from pulsars. In view of the considerable data challenges, expertise in exploring large amounts of data is required. An interdisciplinary team of astronomers and computer scientists is developing a novel pipeline for analyzing and simulating pulsar signals. This article presents the status of the project and the methods used from a computer science perspective.