2018ApJ...861..107L

The implementation of star formation and stellar feedback in cosmological simulations plays a critical role in shaping galaxy properties. In the first paper of the series, we presented a new method to model star formation as a collection of star clusters. In this paper, we improve the algorithm by eliminating accretion gaps, boosting momentum feedback, and introducing a subgrid initial bound fraction, f_i, that distinguishes cluster mass from stellar particle mass. We perform a suite of simulations with different star formation efficiency per freefall time ε_ff and supernova momentum feedback intensity f_boost. We find that the star formation history of a Milky Way-sized galaxy is sensitive to f_boost, which allows us to constrain its value, f_boost~5, in the current simulation setup. Changing ε_ff from a few percent to 200% has little effect on global galaxy properties. However, on smaller scales, the properties of star clusters are very sensitive to ε_ff. We find that f_i increases with ε_ff and cluster mass. Through the dependence on f_i, the shape of the cluster initial mass function varies strongly with ε_ff. The fraction of clustered star formation and maximum cluster mass increase with the star formation rate surface density, with the normalization of both relations dependent on ε_ff. The cluster formation timescale systematically decreases with increasing ε_ff. Local variations in the gas accretion history lead to a 0.25 dex scatter for the integral cluster formation efficiency. Joint constraints from all the observables prefer the runs that produce a median integral efficiency of 16%.