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