Seminars and Colloquia at ESO Garching and on the campus

 In this study, we propose a data-driven and non-parametric approach to determine the continuum level in ALMA data. Our new method is based on a low-rank and sparse matrix decomposition technique. Here, a low-rank matrix is expressed with a small number of eigenvectors, whereas most elements of a sparse matrix are zero. We model the continuum emission as a low-rank component and lines as a sparse component based on their 3D structures. As a result, we demonstrated that our new method can reliably separate an ALCHEMI datacube into continuum and line components, including both emission and absorption lines. In this talk, I will introduce the basic concept and implementation of our new method and discuss its performance through comparisons with conventional continuum subtraction techniques. Finally, I will discuss the advantages of our method and its potential for future wideband observations.