The R2D2 Deep Neural Network Series Paradigm for Fast Precision Imaging in Radio Astronomy

The author introduces the novel deep learning approach of the R2D2 algorithm to address scalability challenges in radio astronomy imaging, combining elements of PnP algorithms and matching pursuit. The core thesis is that R2D2 offers high precision and fast imaging capabilities through a series of residual images generated by DNNs.