Context. Large-amplitude oscillations (LAOs) are often detected in filaments. Using multi-wavelength observations, their origin can be traced back to the interaction with eruptions and jets. Aims: We present two different case studies as observational evidence in support of 2.5D numerical magnetohydrodynamics (MHD) experiments that show that the

Context. The project called INvestigating Stellar Population In RElics (INSPIRE) is based on VLT/X-shooter data from the homonymous on-going ESO Large Program. It targets 52 ultra-compact massive galaxies at 0.1 < z < 0.5 with the goal of constraining their kinematics and stellar population properties in great detail and of analysing their relic

The LIGO/Virgo detected a gravitational wave (GW) event, named GW200224_222234 (also known as S200224ca) and classified as a binary-black hole coalescence, on 2020 February 24. Given its relatively small localization skymap (71 deg 2 for a 90% credible region; revised to 50 deg 2 in GWTC-3), we performed target-of-opportunity observations using the

We present BISTRO Survey 850 μm dust emission polarization observations of the L1495A-B10 region of the Taurus molecular cloud, taken at the James Clerk Maxwell Telescope (JCMT). We observe a roughly triangular network of dense filaments. We detect nine of the dense starless cores embedded within these filaments in polarization, finding that the

We present a catalog of about 25,000 images of massive (M ⋆ ≥ 10 9 M ⊙) galaxies at redshifts 3 ≤ z ≤ 6 from the TNG50 cosmological simulation, tailored for observations at multiple wavelengths carried out with JWST. The synthetic images were created with the SKIRT radiative transfer code, including the effects of dust attenuation and scattering

Next-generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Machine-learning methods are increasingly becoming the most efficient tools to handle this enormous amount of data, because they are often faster and more accurate than