SLUG - Stochastically Lighting Up Galaxies. II: Quantifying the Effects of Stochasticity on Star Formation Rate Indicators

Abstract: The integrated light of a stellar population, measured through photometric filters that are sensitive to the presence of young stars, is often used to infer the star formation rate (SFR) for that population. However, these techniques rely on an assumption that star formation is a continuous process, whereas in reality stars form in discrete spatially- and temporally-correlated structures. This discreteness causes the light output to undergo significant time-dependent fluctuations, which, if not accounted for, introduce systematic errors in the inferred SFRs due to the intrinsic distribution of luminosities at any fix SFR. We use SLUG, a code that Stochastically Lights Up Galaxies, to simulate galaxies undergoing stochastic star formation. We then use these simulations to present a quantitative analysis of these effects and provide tools for calculating probability distribution functions of SFRs given a set of observations. We show that, depending on the SFR tracer used, stochastic fluctuations can produce non-trivial errors at SFRs as high as 1 M/yr, and biases >0.5 dex at the lowest SFRs. We emphasize that due to the stochastic behavior of blue SFR tracers, one cannot assign a deterministic single value to the SFR of an individual galaxy, but we suggest methods by which future analyses that rely on integrated-light indicators can properly account for these stochastic effects.