We present the first optical-UV spectral systematic analysis of 30 Type 1 active galactic nuclei selected in the far-infrared and X-ray in the Lockman-SpReSO Survey. The sample of faint objects (m B = 19.6–21.8) covers a large redshift range of 0.33 >z > 4.97 with a high signal-to-noise ratio (∼21 on average). A detailed spectral analysis based on

The ExoLife Finder (ELF) is a groundbreaking ground-based facility that will transform exoplanet research through direct imaging and characterisation of terrestrial exoplanets. Our mission is to identify biomarkers within their atmospheres, and we are poised to achieve unparalleled performance levels by leveraging cutting-edge technologies. A

Chemical properties of stellar populations are a key observable that can be used to shed light on the assembly history of galaxies across cosmic time. In this study, we investigate the distribution and origin of chemical elements in different stellar components of simulated Milky Way-like galaxies in relation to their mass assembly history, stellar

Context. Despite the ever-increasing number of known exoplanets, no uncontested detections have been made of their satellites, known as exomoons. Aims. The quest to find exomoons is at the forefront of exoplanetary sciences. Certain space-born instruments are thought to be suitable for this purpose. We show the progress made with the CHaracterising

Hydrogen 21-cm Line Intensity Mapping offers the unique opportunity to access the Dark Ages and trace the formation and evolution of the large scale structure of the Universe prior to star and galaxy formation. In this work we investigate the potential of future Earth- and Moon-based 21-cm surveys to constrain the growth of structures during the

Reflectance spectroscopy remains a cornerstone of remote mineralogical analysis of airless bodies. However, traditional spectral unmixing techniques face limitations when dealing with nonlinear mixing, instrument-specific noise, or spectral coverage constraints. To overcome these, we have developed a suite of robust convolutional neural network