The DIANOGA simulations of galaxy clusters: characterizing star formation in proto-clusters

TL;DR

This study uses cosmological hydrodynamical simulations to analyze star formation in galaxy proto-clusters, revealing underpredictions of starburst activity and gas fractions compared to observations, with implications for modeling galaxy evolution.

Contribution

It provides a detailed comparison between simulated and observed star formation rates in proto-clusters, highlighting limitations in current models and the robustness of results against parameter variations.

Findings

Simulations underpredict star formation rates in proto-cluster cores.

Main sequence normalization is underestimated by a factor of ~3.

Results are stable across different star formation model parameters.

Abstract

We studied the star formation rate (SFR) in cosmological hydrodynamical simulations of galaxy (proto-)clusters in the redshift range $0<z<4$, comparing them to recent observational studies; we also investigated the effect of varying the parameters of the star formation model on galaxy properties such as SFR, star-formation efficiency, and gas fraction. We analyze a set of zoom-in cosmological hydrodynamical simulations centred on twelve clusters. The simulations are carried out with the GADGET-3 TreePM/SPH code which includes various subgrid models to treat unresolved baryonic physics, including AGN feedback. Simulations do not reproduce the high values of SFR observed within protoclusters cores, where the values of SFR are underpredicted by a factor $\gtrsim 4$ both at $z\sim2$ and $z\sim 4$. The difference arises as simulations are unable to reproduce the observed starburst population and is worsened at $z\sim 2$ because simulations underpredict the normalization of the main sequence of star forming galaxies (i.e., the correlation between stellar mass and SFR) by a factor of $\sim 3$. As the low normalization of the main sequence seems to be driven by an underestimated gas fraction, it remains unclear whether numerical simulations miss starburst galaxies due to a too low predicted gas fractions or too low star formation efficiencies. Our results are stable against varying several parameters of the star formation subgrid model and do not depend on the details of the AGN feedback.