Impact of star formation models on the growth of simulated galaxies at high redshifts

Abstract: Star formation is a key process that governs the baryon cycle within galaxies, however, the question of how it controls their growth remains elusive due to modeling uncertainties. To understand the impact of star formation models on galaxy evolution, we performed cosmological zoom-in radiation-hydrodynamic simulations of a dwarf dark matter halo, with a virial mass of $M_{\rm vir} \sim 10^9\, M_\odot$ at $z=6$. We compared two different star formation models: a multi-freefall model combined with a local gravo-thermo-turbulent condition and a more self-consistent model based on a sink particle algorithm, where gas accretion and star formation are directly controlled by the gas kinematics. As the first study in this series, we used cosmological zoom-in simulations with different spatial resolutions and found that star formation is more bursty in the runs with the sink algorithm, generating stronger outflows than in the runs with the gravo-thermo-turbulent model. The main reason for the increased burstiness is that the gas accretion rates on the sinks are high enough to form stars on very short timescales, leading to more clustered star formation. As a result, the star-forming clumps are disrupted more quickly in the sink run due to more coherent radiation and supernova feedback. The difference in burstiness between the two star formation models becomes even more pronounced when the supernova explosion energy is artificially increased. Our results suggest that improving the modeling of star formation on small, sub-molecular cloud scales can significantly impact the global properties of simulated galaxies.