Led by P. Arnalte-Mur and M. Stefanon, this research line studies cosmic expansion, dark energy, and galaxy formation using data from J-PAS, Euclid, and JWST. The CS group participates in major international collaborations combining ground-based projects (e.g., J-PAS) with space missions like Euclid and JWST (MINERVA, UNCOVER, FRESCO). The team has extensive experience analyzing large-scale structure through photometric redshift surveys, developing tools to measure galaxy clustering and its evolution with environment and time. Their work revealed small-scale deviations matching halo models, refining structure formation knowledge. They also pioneered statistical methods to extract cosmological parameters from large datasets, including baryon acoustic oscillation detection and growth rate estimation using multivariate analyses. These are supported by synthetic galaxy catalogs created with HOD methods and the PINOCCHIO code, crucial for validating surveys. Another focus is galaxy populations across cosmic time, with a particular emphasis on the first billion years of the Universe. We explore galaxy assembly focusing on both statistical studies (e.g., luminosity and stellar mass functions), and detailed analysis of individual sources (e.g., stellar population age gradients, kinematics, dust content). Moreover, the group has significant expertise in the identification of robust candidates of (bright) galaxies in the epoch of reionization. This research is complemented by wide-area photometric analyses (e.g., J-PAS) quantifying the luminosity function and evolution of bright galaxies over the past 6 billion years, notably applied to Lyman-alpha emitters in narrow-band surveys like miniJ-PAS. The group also leads in ML applications to astronomy, exemplified by zELDA, a public Python package combining radiative transfer simulations and neural networks to model Lyman-alpha emission profiles. 

Senior researchers: P. Arnalte-Mur, V. J. Martínez, M. Stefanon