We analyse the near-infrared colour-magnitude diagram of a field including the giant molecular cloud G0.253+0.016 (a.k.a. The Brick) observed at high spatial resolution, with HAWK-I@VLT. The distribution of red clump stars in a line of sight crossing the cloud, compared with that in a direction just beside it, and not crossing it, allow us to

Spectroscopy of transiting exoplanets can be used to investigate their atmospheric properties and habitability. Combining radial velocity (RV) and transit data provides additional information on exoplanet physical properties. We detect a transiting rocky planet with an orbital period of 1.467 days around the nearby red dwarf star Gliese 486. The

GJ 9827 is a bright star hosting a planetary system with three transiting planets. As a multiplanet system with planets that sprawl within the boundaries of the radius gap between terrestrial and gaseous planets, GJ 9827 is an optimal target to study the evolution of the atmospheres of close-in planets with a common evolutionary history and their

Hydrodynamical simulations of galaxy formation and evolution attempt to fully model the physics that shapes galaxies. The agreement between the morphology of simulated and real galaxies, and the way the morphological types are distributed across galaxy scaling relations are important probes of our knowledge of galaxy formation physics. Here, we

In the light of more and more new instrumentation to get a deeper insight into the universe, tons of data are collected. While traditional machine-learning methods have been used in processing stellar spectral data, such large new datasets are better handled with Deep Learning (DL) techniques. In this work, we present a Deep Convolutional Neural

We construct an individual convolutional neural network architecture for each of the four stellar parameters effective temperature (Teff), surface gravity (log g), metallicity [M/H], and rotational velocity (v sin i). The networks are trained on synthetic PHOENIX-ACES spectra, showing small training and validation errors. We apply the trained