Context. Jets and outflows are associated with young stellar objects across the stellar mass spectrum, from brown dwarf protostars to massive Ae/Be stars. Frequently the jet morphology is spatially discontinuous because of the temporal variability of the ejection from the driving source. Images covering a wide field of view around the jet-driving

Internetwork (IN) magnetic fields are highly dynamic, short-lived magnetic structures that populate the interior of supergranular cells. Since they emerge all over the Sun, these small-scale fields bring a substantial amount of flux, and therefore energy, to the solar surface. Because of this, IN fields are crucial for understanding the quiet Sun

The Zeeman effect is of limited utility for probing the magnetism of the quiet solar chromosphere. The Hanle effect in some spectral lines is sensitive to such magnetism, but the interpretation of the scattering polarization signals requires taking into account that the chromospheric plasma is highly inhomogeneous and dynamic (i.e., that the

We present the spectroscopic analysis of 333 OB-type stars extracted from VLT-MUSE observations of the central 30 × 30 pc of NGC 2070 in the Tarantula Nebula on the Large Magellanic Cloud, the majority of which are analysed for the first time. The distribution of stars in the spectroscopic Hertzsprung-Russell diagram (sHRD) shows 281 stars in the

Context. The JAXA asteroid sample return mission Hayabusa2 reached its target (162173) Ryugu in June 2018 and released the European (CNES-DLR) lander MASCOT in October 2018. MASCOT successfully landed on the surface, and the Hayabusa2 Optical Navigation Camera system has been able to image parts of the MASCOT trajectory. Aims: This work builds on

Large-scale sky surveys have played a transformative role in our understanding of astrophysical transients, only made possible by increasingly powerful machine learning-based filtering to accurately sift through the vast quantities of incoming data generated. In this paper, we present a new real-bogus classifier based on a Bayesian convolutional