Related papers: Evaluation of the ngVLA Revision D array configura…

This document describes some of the fundamental astrophysical problems that require observing capabilities at millimeter- and centimeter wavelengths well beyond those of existing, or already planned, telescopes. The results summarized in…

Long-slit echellograms of the high excitation planetary nebula NGC1501, reduced according to the methodology developed by Sabbadin et al. (2000a, b), allowed us to obtain the ``true'' distribution of the ionized gas in the eight nebular…

In this Chapter we examine the role of the ngVLA to further our understanding of the different manifestations of convective or turbulence-driven stellar activity on red giant and supergiant stars. The combination of high spatial resolution…

Radio interferometry enables high-resolution imaging of astronomical radio sources by synthesizing a large effective aperture from an array of antennas and solving a deconvolution problem to reconstruct the image. Deep learning has emerged…

Radio continuum observations have proven to be a workhorse in our understanding of the star formation process (i.e., stellar birth and death) from galaxies both in the nearby universe and out to the highest redshifts. In this article we…

Episodic accretion may be a common occurrence in the evolution of young pre-main sequence stars and has important implications for our understanding of star and planet formation. Many fundamental aspects of what drives the accretion…

The Global mm-VLBI Array (GMVA) has demonstrated the ability to resolved what may be the general relativistic shadow of the supermassive black hole in M87 at 86 GHz, as well as delineate the inner jet to $\sim 1$~mas distance. We…

Real-SR endeavors to produce high-resolution images with rich details while mitigating the impact of multiple degradation factors. Although existing methods have achieved impressive achievements in detail recovery, they still fall short…

Radio interferometric imaging has long relied on the CLEAN algorithm, valued for its speed, robustness, and integration with calibration pipelines. However, next-generation facilities such as the ngVLA, SKA, and ALMAs Wideband Sensitivity…

Deep continuum surveys at radio wavelengths are able to cover large areas, yield high angular resolution, and do not suffer from dust extinction, thus providing a robust way to measure the star formation history of the universe. However,…

High angular resolution images obtained with a hypertelescope can strongly constrain the radiative-hydrodynamics simulations of red supergiant (RSG) stars, in terms of intensity contrast, granulation size and temporal variations of the…

Scene reconstruction from unorganized RGB images is an important task in many computer vision applications. Multi-view Stereo (MVS) is a common solution in photogrammetry applications for the dense reconstruction of a static scene. The…

The ngVLA is a new interferometric radio astronomy facility with transformative capabilities, being developed by the National Radio Astronomy Observatory. It combines two orders of magnitude in frequency coverage, over 1.2 - 116 GHz, with…

Radio-astronomical observations are increasingly contaminated by interference, and suppression techniques become essential. A powerful candidate for interference mitigation is adaptive spatial filtering. We study the effect of spatial…

Supervised deep learning approaches can artificially increase the resolution of microscopy images by learning a mapping between two image resolutions or modalities. However, such methods often require a large set of hard-to-get…

The science case and associated science requirements for a next-generation Very Large Array (ngVLA) are described, highlighting the five key science goals developed out of a community-driven vision of the highest scientific priorities in…

We report the results of a simulation and reconstruction of observations of a young stellar object (YSO) jet with the LINC-NIRVANA (LN) interferometric instrument, which will be mounted on the Large Binocular Telescope (LBT). This…

In recent years, Diffusion Models have become the new state-of-the-art in deep generative modeling, ending the long-time dominance of Generative Adversarial Networks. Inspired by the Regularization by Denoising principle, we introduce an…

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…

The exponential growth of astronomical datasets provides an unprecedented opportunity for humans to gain insight into the Universe. However, effectively analyzing this vast amount of data poses a significant challenge. Astronomers are…