Open AccessTesting Algorithms for Identifying Source Confusion in the H i-MaNGA Survey
Author(s) -
Griffin Shapiro,
David V. Stark,
Karen L. Masters
Publication year - 2022
Publication title -
research notes of the aas
Language(s) - English
Resource type - Journals
ISSN - 2515-5172
DOI - 10.3847/2515-5172/ac4743
Subject(s) - confusion , galaxy , astrophysics , flagging , telescope , physics , brightness , astronomy , metric (unit) , surface brightness , source counts , sample (material) , algorithm , computer science , geography , cartography , psychology , operations management , redshift , psychoanalysis , economics , thermodynamics
Astronomical observations of neutral atomic hydrogen (H i ) are an important tracer of several key processes of galaxy evolution, but face significant difficulties with terrestrial telescopes. Among these is source confusion, or the inability to distinguish between emission from multiple nearby sources separated by distances smaller than the telescope’s spatial resolution. Confusion can compromise the data for the primary target if the flux from the secondary galaxy is sufficient. This paper presents an assessment of the confusion-flagging methods of the H i -MaNGA survey, using higher-resolution H i data from the Westorbork Synthesis Radio Telescope-Apertif survey. We find that removing potentially confused observations using a confusion probability metric—calculated from the relationship between galaxy color, surface brightness, and H i content—successfully eliminates all significantly confused observations in our sample, although roughly half of the eliminated observations are not significantly confused.