deep21: a deep learning method for 21 cm foreground removal
deep21: a deep learning method for 21 cm foreground removal
Abstract We seek to remove foreground contaminants from 21 cm intensity mapping observations. We demonstrate that a deep convolutional neural network (CNN) with a UNet architecture and three-dimensional convolutions, trained on simulated observations, can effectively separate frequency and spatial patterns of the cosmic neutral hydrogen (HI) signal from foregrounds in …