MeerKAT and the upcoming SKA will drastically increase our horizon for direct measurements of neutral hydrogen (HI) in the Universe providing new insights on the baryonic content of galaxies across cosmic times. We recently acquired deep U-band MeerKAT observations of the COSMOS field. With these data and with the use of 21 cm stacking techniques, we will measure the HI mass of large samples...
Galaxy physical properties are not randomly scattered throughout a multi-dimensional parameter space, but instead follow distinct clustering ("scaling relations") that reflect their formation path and the associated astrophysical processes.
In this presentation I will describe two examples - both relevant to science with SKA-MID - of how these interrelations between different galaxy...
We will show of the first results of the full box of the phoebos simulation.
Vision foundation models, which have demonstrated significant potential in many multimedia applications, are often underutilized in the natural sciences. This is primarily due to mismatches between the nature of domain-specific scientific data and the typical training data used for foundation models, leading to distribution shifts. Scientific data often differ substantially in structure and...
Physics-Informed Neural Networks (PINNs) have emerged as a powerful tool for solving differential equations by integrating physical laws into the learning process. This work leverages PINNs to simulate gravitational collapse, a critical phenomenon in astrophysics and cosmology. We introduce the Schrödinger-Poisson Informed Neural Network (SPINN) which solve nonlinear Schrödinger-Poisson (SP)...
