FLAMINGO: calibrating large cosmological hydrodynamical simulations with machine learning
FLAMINGO: calibrating large cosmological hydrodynamical simulations with machine learning
To fully take advantage of the data provided by large-scale structure surveys, we need to quantify the potential impact of baryonic effects, such as feedback from active galactic nuclei (AGN) and star formation, on cosmological observables. In simulations, feedback processes originate on scales that remain unresolved. Therefore, they need to …