The new generation of radio interferometers is characterized by high sensitivity, wide fields
of view and large fractional bandwidth. To synthesize the deepest images enabled by the …

Galaxy clusters are the most massive gravitationally bound structures in the Universe,
comprising thousands of galaxies and pervaded by a diffuse, hot intracluster medium (ICM) …

We propose a new imaging technique for radio and optical/infrared interferometry. The
proposed technique reconstructs the image from the visibility amplitude and closure phase …

This thoroughly updated new edition presents state of the art sparse and multiscale image
and signal processing. It covers linear multiscale geometric transforms, such as wavelet …

We propose a new technique for radio interferometry to obtain superresolution full-
polarization images in all four Stokes parameters using sparse modeling. The proposed …

The far-infrared (FIR) regime is one of the few wavelength ranges where no astronomical
data with sub-arcsecond spatial resolution exist yet. Neither of the medium-term satellite …

We introduce a new class of iterative image reconstruction algorithms for radio
interferometry, at the interface of convex optimization and deep learning, inspired by plug …

We introduce the first AI-based framework for deep, super-resolution, wide-field radio
interferometric imaging and demonstrate it on observations of the ESO 137-006 radio …

It is a classic problem to estimate continuous-time sparse signals, like point sources in a
direction-of-arrival problem, or pulses in a time-of-flight measurement. The earliest …

In the context of next-generation radio telescopes, like the Square Kilometre Array (SKA), the
efficient processing of large-scale data sets is extremely important. Convex optimization …