Presentation #302.06 in the session Computation, Data Handling, Image Analysis — iPoster Session.
The next-generation Very Large Array (ngVLA) is a proposed large area radio array planned for the 2030s. The ngVLA will have the capability to resolve the surfaces of nearby stars, both spatially and temporally, using a combination of milliarcsecond-scale resolution and sensitivity to thermal radio emission. Here, we present stellar imaging with the ngVLA using two image reconstruction methods – CLEAN techniques and regularized maximum likelihood (RML) methods – to evaluate the capabilities of a new update to the configuration, the Revision D (Rev D) Main Array, as compared to the previous Revision C (Rev C) configuration. We find that, for the CLEAN reconstructions, the Rev D configuration improves the synthesized beam, resulting in better reconstructions due to the improved uniformity of coverage and circular symmetry. This result demonstrates that Rev D can enhance imaging capability for non-uniform weighting. However, the synthesized beam in both Rev C and Rev D configurations is highly non-Gaussian in robust and natural weightings, which limits the fidelity of image reconstructions. The RML methods result in similar or better performance for both configurations with image quality comparable to or better than CLEAN reconstructions in uniform weighting without adopting any uv-weighting. RML methods are an attractive choice over CLEAN for both array configurations. This work is financially supported by the ngVLA Community Studies program, coordinated by the National Radio Astronomy Observatory (NRAO), which is a facility of the National Science Foundation (NSF) operated under cooperative agreement by Associated Universities, Inc.