JESSNet: Joint dEconvolution and Sparse Separation Network for HI 21 cm foreground cleaning
This work introduces JESSNet, a beam-aware, mask-compatible foreground-cleaning framework for single-dish intensity mapping, and introduces three main extensions: a multiscale angular decomposition with scale-dependent mixing matrices and channel selection, a learned spherical-wavelet''learnlet''sparse regularization o...