CLEANing Cygnus A deep and fast with R2D2

arXiv:2309.03291v3 Announce Type: replace-cross
Abstract: A novel deep learning paradigm for synthesis imaging by radio interferometry in astronomy was recently proposed, dubbed "Residual-to-Residual DNN series for high-Dynamic range imaging" (R2D2). In this work, we start by shedding light on R2D2's algorithmic structure, interpreting it as a learned version of CLEAN with minor cycles substituted with a deep neural network (DNN) whose training is iteration-specific. We then proceed with R2D2's first demonstration on real data, for monochromatic intensity imaging of the …

abstract arxiv astronomy astro-ph.im cleaning cs.lg deep learning dnn dynamic eess.iv eess.sp imaging light novel paradigm radio residual series synthesis type work