We present the validation of a transiting low-density exoplanet orbiting the M2.5 dwarf TOI 620 discovered by the NASA Transiting Exoplanet Survey Satellite (TESS) mission. We utilize photometric data from both TESS and ground-based follow-up observations to validate the ephemerides of the 5.09 day transiting signal and vet false-positive scenarios

The cosmic ionizing emissivity from star-forming galaxies has long been anchored to UV luminosity functions. Here, we introduce an emissivity framework based on Lyα emitters (LAEs), which naturally hones in on the subset of galaxies responsible for the ionizing background due to the intimate connection between production and escape of Lyα and LyC

We report the discovery of two transiting planets around the bright (V = 9.9 mag) main-sequence F7 star TOI-1670 by the Transiting Exoplanet Survey Satellite. TOI-1670 b is a sub-Neptune ( ${R}_{{\rm{b}}}={2.06}_{-0.15}^{+0.19}$ R ⊕) on a 10.9 day orbit, and TOI-1670 c is a warm Jupiter ( ${R}_{{\rm{c}}}={0.987}_{-0.025}^{+0.025}$ R Jup) on a 40.7

Since proposed by Bevis et al. in 1992, GNSS Meteorology has become a very competitive field, mainly because it provides a relatively cheap, extensive network of stations, with global and 365d/24h coverage. Therefore, the method has been widely validated by comparison with other reference techniques. A majority of the comparisons show both dry or

Large-scale surveys open the possibility to investigate Galactic evolution both chemically and kinematically; however, reliable stellar ages remain a major challenge. Detailed chemical information provided by high-resolution spectroscopic surveys of the stars in clusters can be used as a means to calibrate recently developed chemical tools for age

Context. The Gaia-ESO Survey (GES) is a large public spectroscopic survey that has collected, over a period of six years, spectra of ~10 5 stars. This survey provides not only the reduced spectra, but also the stellar parameters and abundances resulting from the analysis of the spectra. Aims: The GES dataflow is organised in 19 working groups