Fermi Gamma-ray Space Telescope

Classification and Ranking of Fermi LAT Gamma-ray Sources using Machine Learning Techniques

Pablo Saz Parkinson
(Jason Fan (Department of Physics & Laboratory for Space Research, The University of Hong Kong), Philip Yu (Department of Statistics and Actuarial Science, The University of Hong Kong), Graziano Chiaro (INAF-IASF, Milano))

Abstract:

In our previous work (Saz Parkinson et al. 2016, Chiaro et al. 2016), we applied a number of machine learning techniques to classify and rank gamma-ray sources from the Fermi Large Area Telescope (LAT) Third Source Catalog (3FGL). We examine some of the predictions made in our past work and present some preliminary results on our new analyses, as applied to the recently-released LAT 8-year Point Source List (FL8Y).