We combine near-infrared imaging in two bands from the Hubble Space Telescope with archival observations of molecular gas to study SDSS J160705.16+533558.6 (J1607), an extremely luminous broad-line quasar at z = 3.65 that is also bright in the submillimeter. Via subtraction of the quasar point-spread function, we show that its host galaxy is

Cherenkov Telescope Array Observatory (CTAO) is the next-generation ground-based $\gamma$-ray observatory operating in the energy range from $20\, \mathrm{GeV}$ up to $300\, \mathrm{TeV}$, with two sites in La Palma (Spain) and Paranal (Chile). It will consist of telescopes of three sizes, covering different parts of the large energy range. We

V Sge is a peculiar, highly luminous long-period (12.34 h) binary star that can display a supersoft X-ray emitting component when in the faint phase of its $V \approx 10-13$ mag variability range. Apparently undergoing Eddington-limited accretion from its more massive secondary, it is in a very rare, short-lived evolutionary phase towards the

Context. Post-facto image restoration techniques are essential for improving the quality of ground-based astronomical observations, which are affected by atmospheric turbulence. Multi-object, multi-frame blind deconvolution (MOMFBD) methods are widely used in solar physics to achieve diffraction-limited imaging. Aims. We present torchmfbd, a new

Context. Super-Earths and mini-Neptunes are missing from our Solar System, yet they appear to be the most abundant planetary types in our Galaxy. A detailed characterization of key planets within this population is important for understanding the formation mechanisms of rocky and gas giant planets and the diversity of planetary interior structures

Context. Understanding the origin of stars within a galaxy, namely whether they formed in situ or were accreted from other galaxies (ex situ), is key to constraining its evolution. When they are spatially resolved, these components provide crucial insights into the mass assembly history of a galaxy. Aims. We predict the spatial distribution of the