Exploring IMF Sampling Effects on Star Formation and Metallicity in Ultra-Faint Dwarf Galaxies (2411.17862v1)

Abstract: We examine the impact of various Initial Mass Function (IMF) sampling methods on the star formation and metal enrichment histories of Ultra-Faint Dwarf (UFD) galaxy analogs. These analogs are characterized by $M_{\rm vir}\sim10^8 M_\odot$ and $M_{\ast}\lesssim10^5 M_\odot$ at $z=0$, utilizing high-resolution cosmological hydrodynamic zoom-in simulations with a gas particle mass resolution of $\sim63 M_\odot$. Specifically, we evaluate three IMF sampling techniques: the burst model, stochastic IMF sampling, and individual IMF sampling. Our results demonstrate that the choice of IMF sampling method critically affects stellar feedback dynamics, particularly supernova (SN) feedback, thus impacting the star formation and metallicity characteristics of UFD analogs. We find that simulations with stochastic IMF sampling yield UFD analogs with 40\% to 70\% higher stellar masses than those using the burst model, due to a less immediate suppression of star formation by SNe. The individual IMF method results in even greater stellar masses, 8\% to 58\% more than stochastic runs, as stars form individually and continuously. Star formation is most continuous with individual sampling, followed by stochastic, and least with the burst model, which shows the longest quenching periods. Furthermore, the individual sampling approach achieves higher metallicity stars, aligning well with observed values, unlike the lower metallicities (about 1 dex less) found in the burst and stochastic methods. This difference is attributed to the continuous star formation in individual sampling, where gas metallicity shaped by previous SN events is immediately reflected in stellar metallicity. These findings emphasize the essential role of choosing appropriate IMF sampling methods for accurately modeling the star formation and chemical evolution of UFD galaxies.