A panchromatic view of star cluster formation in a simulated dwarf galaxy starburst

TL;DR

This study uses high-resolution simulations and radiative transfer modeling to analyze star and star cluster formation in a dwarf galaxy starburst, comparing observational tracers and analyzing cluster properties at different distances.

Contribution

It introduces a comprehensive mock observational analysis of simulated star clusters, evaluating SFR tracers and the effects of crowding on cluster property estimates.

Findings

UV tracers better during quiescent phases

Aperture photometry overestimates cluster masses

Crowding affects cluster mass function slope estimates

Abstract

We present a photometric analysis of star and star cluster (SC) formation in a high-resolution simulation of a dwarf galaxy starburst that allows the formation of individual stars to be followed. Previous work demonstrated that the properties of the SCs formed in the simulation are in good agreement with observations. In this paper, we create mock spectral energy distributions and broad-band photometric images using the radiative transfer code SKIRT 9. We test several observational star formation rate (SFR) tracers and find that $24$ $\mu$m, total infrared and H$\alpha$ trace the underlying SFR during the (post)starburst phase, while UV tracers yield a more accurate picture of star formation during quiescent phases prior to and after the merger. We then place the simulated galaxy at distances of $10$ and $50$ Mpc and use aperture photometry at Hubble Space Telescope resolution to analyse the simulated SC population. During the starburst phase, a hierarchically forming set of SCs leads inaccurate source separation because of crowding. This results in estimated SC mass function slopes that are up to $\sim0.3$ shallower than the true slope of $\sim-1.9$ to $-2$ found for the bound clusters identified from the particle data in the simulation. The masses of the largest clusters are overestimated by a factor of up to $2.9$ due to unresolved clusters within the apertures. The aperture-based analysis also produces a relation between cluster formation efficiency and SFR surface density that is slightly flatter than that recovered from bound clusters. The differences are strongest in quiescent SF environments.