Editorial activity - Applications of signal processing in astrophysics and cosmology

We live in an epoch where the frontiers of our investigation and comprehension of fundamental physics depend largely on the light coming from the sky, that is, on the study of galactic and extra-galactic radiation. Watching the sky, in principle, we have access to the highest energies conceivable, generated by the laws of nature in extreme conditions, such as nearby black holes or even close to the origin of the universe itself. For example, in the microwave band, the extra-Galactic radiation is dominated by a markedly isotropic component, obeying a black body spectrum characterized by a temperature of about 2.726 Kelvin. That is the relic of the Big Bang, originated just 300 000 years after the initial starting point of the universe. This radiation, namely the cosmic microwave background (CMB) radiation, today is the most important observable we have to access the mysterious physics of the Big Bang itself. The latter is telling us about the unknown fundamental interactions and particles, the physics of spacetime, and the nature of quantum gravity, and represents the only way to address those issues in physics today. Electronics hardware technology has reached in these very recent years the capability to study the tiniest details of the CMB, carrying the image of the primordial stage of cosmic geometry, structure, and composition. Such a fantastic challenge is ongoing in this verymoment, while several CMB detectors are operating and advanced probes are being designed for the forthcoming decades. Many breakthroughs in physics are made possible by the use of the most advanced data analysis techniques. The present datasets obtained in astrophysical and cosmological observations are huge, and cover the entire electromagnetic spectrum, dealing with very different processes, from gamma and X-rays of the high-energy astrophysics of compact stars or black holes, to the microwave and infrared emission from the whole large-scale universe. This variety of the observational techniques and signals to deal with represents a formidable challenge for signal processing.We need state-ofthe-art techniques that can analyse, summarise, and extract the necessary information from this ocean of data. To continue with the example above, the microwave sky is dominated by the CMB radiation, but several processes contribute to the total emission, coming for instance fromall the processes occurring along the line of sight, such as the emission from other galaxies or clusters of those, as well as from the diffuse gas in our own Galaxy. Each of these processes are most relevant in different contexts in astrophysics and cosmology. Recently, the astrophysics field has benefited a great deal from the rich research work going on source separation in the signal processing field. Source separation aims at the recovery of the various different components fromthemultiband observations exploiting the differences between them, induced by their independent physical origins. Despite the mutual interest, the two disciplines suffer from lack of a common publication ground, implying that the results produced in one of them are not immediately visible in the other. The aim of the present issue is to provide a unified platform that would strengthen the bridge between signal processing and astrophysics and cosmology and enable the sharing of information. We would like to provide astrophysicists and cosmologists with a spectrum of the most advanced signal processing techniques and the signal processing community an exposure to various vital real problems in analysing astrophysics data that await solution. Finally, our aim is to provide a reference for present and future literature, in the widest possible context, accounting for various applications and algorithms proposed. Indeed, as the reader may see, the topics we collected range from solar physics, thus on the scale of stars, to the reconstructuon of the most ambitious signal from the Big Bang, with the reconstruction of the CMB pattern on all sky. The methods presented in the issue range from transform domain analysis of such wavelets to data mining techniques.