A Review of Research on Pulsar Candidate Recognition Based on Machine Learning

Abstract

Abstract The pulsar is a highly magnetized rotating neutron star that provides the first indirect evidence for the existence of gravitational waves and also provides the possibility to reveal extreme phenomena in neutron star astrophysics. Therefore, the identification of pulsars in the universe is a prerequisite for the study of pulsars and gravitational waves. At present, a large number of pulsar searches have produced millions of pulsar candidates. In the face of these large-scale data, if only relying on manual visual classification by experts in related fields, it will be a huge project. Since the emergence of machine learning, its theory and technology have become increasingly mature, and has been successfully applied to astronomical research fields such as pulsar candidate screening. This paper introduces the related machine learning theory of pulsar candidate recognition firstly, and then reviews the research status of pulsar candidate recognition based on machine learning in recent years. Finally, we discuss and prospect the identification of pulsars in the future.