We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, in which SNe are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their

Future data provided by the Euclid mission will allow us to better understand the cosmic history of the Universe. A metric of its performance is the figure-of-merit (FoM) of dark energy, usually estimated with Fisher forecasts. The expected FoM has previously been estimated taking into account the two main probes of Euclid, namely the three

The TESS mission searches for transiting exoplanets by monitoring the brightness of hundreds of thousands of stars across the entire sky. M-type planet hosts are ideal targets for this mission due to their smaller size and cooler temperatures, which makes it easier to detect smaller planets near or within their habitable zones. Additionally, M