PROBING THE BARYONIC CYCLE OF GALAXIES THROUGH STELLAR POPULATION ANALYSES
The growth of dark matter halos is to first-order the main driver of galaxy formation in our standard cosmological model. Yet, complex and highly non-linear baryonic processes take over at the centers of these halos, leading to the diversity of galaxies observed in the Universe today. The coupling between baryonic and dark matter physics is central
Improvement of farside activity detection with machine learning techniques and applications
Hasta ahora, la única formar de monitorizar de manera consistente el hemisferio del Sol no visible (farside de aquí en adelante) desde la Tierra es el uso de métodos heliosísmicos. Estos métodos interpretan las oscilaciones del hemisferio visible (nearside de aquí en adelante) para inferir la actividad del farside, que es de gran importancia en las
UNCOVERING THE PHYSICS OF GALAXIES WITH SELF-SUPERVISED DEEP LEARNING
As surveys grow, the challenge is how to explore and interpret the increasing quantity of data. For this, removing the observational biases and reducing the dimensionality of the data are fundamental. A promising avenue to do this is a self-supervised deep learning algorithm called contrastive learning. Contrastive learning is especially effective