Application of Machine Learning Techniques in Astronomy: Predicting H2 Column Density from Molecular Line Data

Yoshito Shimajiri  (Kyushu Kyoritsu University)

In recent years, the application of machine learning has been gaining attention in astronomical research. In our study, we developed a machine learning model to predict the H2 column density using only molecular line data. We discuss the advantages and disadvantages of this model. Finally, we introduce the SURFING project, an ongoing JCMT large program.