Using Contour Trees in the Analysis and Visualization of Radio Astronomy Data Cubes

The current generation of radio and millimeter telescopes, particularly the Atacama Large Millimeter Array (ALMA), offers enormous advances in observing capabilities. While these advances represent an unprecedented opportunity to advance scientific understanding, the increased complexity in the spatial and spectral structure of even a single spectral line is hard to interpret. The complexity present in current ALMA data cubes therefore challenges not only the existing tools for fundamental analysis of these datasets, but also users’ ability to explore and visualize their data. We have performed a feasibility study for applying forms of topological data analysis and *e-mail: [email protected] †e-mail: [email protected] ‡e-mail: [email protected] §e-mail: [email protected] ¶e-mail: [email protected] ||e-mail: [email protected] **e-mail: [email protected] ††e-mail: [email protected] visualization never before tested by the ALMA community. Through contour tree-based data analysis, we seek to improve upon existing data cube analysis and visualization workflows, in the forms of improved accuracy and speed in extracting features. In this paper, we review our design process in building effective analysis and visualization capabilities for the astrophysicist users. We summarize effective design practices, in particular, we identify domain-specific needs of simplicity, integrability and reproducibility, in order to best target and service the large astrophysics community.