学术文献库

Recent years have seen growing interest in post-processing cosmological simulations with radiative transfer codes to predict observable fluxes for simulated galaxies. However, this can be slow, and requires a number of assumptions in cases where simulations do not resolve the ISM. Zoom-in simulations better resolve the detailed structure of the ISM and the geometry of stars and gas, however statistics are limited due to the computational cost of simulating even a single halo. In this paper, we make use of a set of high resolution, cosmological zoom-in simulations of massive M_star>10^10.5M_sol at z=2), star-forming galaxies from the FIRE suite. We run the SKIRT radiative transfer code on hundreds of snapshots in the redshift range 1.5<z<5 and calibrate a power law scaling relation between dust mass, star formation rate and 870um flux density. The derived scaling relation shows encouraging consistency with observational results from the sub-millimeter-selected AS2UDS sample. We extend this to other wavelengths, deriving scaling relations between dust mass, stellar mass, star formation rate and redshift and sub-millimeter flux density at observed-frame wavelengths between 340um and 870um. We then apply the scaling relations to galaxies drawn from EAGLE, a large box cosmological simulation. We show that the scaling relations predict EAGLE sub-millimeter number counts that agree well with previous results that were derived using far more computationally expensive radiative transfer techniques. Our scaling relations can be applied to other simulations and semi-analytical or semi-empirical models to generate robust and fast predictions for sub-millimeter number counts.