The Application of Machine Learning to AGN Classification
AUG 01, 2024
Abstract: A relatively new development in quasar and Seyfert research is the utilization of machine learning to expedite data collection and aid in analysis. This paper discusses a specific application of machine learning: to classify active galactic nuclei (AGN) as Seyfert type 1s, Seyfert type 2s, or quasars. Initially we focus on summarizing the development of research on the nuclei types from their discovery to present day. Then, our paper moves to a more focused discussion of the utilization of machine learning to classify AGN types. The importance of expedited AGN classification, as well as avenues for future research into the intersection of classification algorithms and AGNs, are discussed.
