The effects of stochasticity on the luminosities of stellar populations are an often neglected but crucial element for understanding populations in the low mass or low star formation rate regime. To address this issue, we present SLUG, a new code to "Stochastically Light Up Galaxies". SLUG synthesizes stellar populations using a Monte Carlo technique that treats stochastic sampling properly including the effects of clustering, the stellar initial mass function, star formation history, stellar evolution, and cluster disruption. This code produces many useful outputs, including i) catalogs of star clusters and their properties, such as their stellar initial mass distributions and their photometric properties in a variety of filters, ii) two dimensional histograms of color-magnitude diagrams of every star in the simulation, iii) and the photometric properties of field stars and the integrated photometry of the entire simulated galaxy. After presenting the SLUG algorithm in detail, we validate the code through comparisons with SB99 in the well-sampled regime, and with observed photometry of Milky Way clusters. Finally, we demonstrate the SLUG's capabilities by presenting outputs in the stochastic regime. SLUG is publicly distributed through the website

Recent observations indicate a lower Hα to FUV ratio in dwarf galaxies than in brighter systems, a trend that could be explained by a truncated and/or steeper IMF in small galaxies. However, at low star formation rates (SFRs), the Hα to FUV ratio can vary due to stochastic sampling even for a universal IMF, a hypothesis that has, prior to this work, received limited investigation. Using slug, a fully stochastic code for synthetic photometry in star clusters and galaxies, we compare the Hα and FUV luminosity in a sample of ∼ 450 nearby galaxies with models drawn from a universal Kroupa IMF and a modified IMF, the integrated galactic initial mass function (IGIMF). Once random sampling and time evolution are included, a Kroupa IMF convolved with the cluster mass function reproduces the observed Hα distribution at all FUV luminosities, while a truncated IMF as implemented in current IGIMF models underpredicts the Hα luminosity by more than an order of magnitude at the lowest SFRs. We conclude that the observed luminosity is the result of the joint probability distribution function of the SFR, cluster mass function, and a universal IMF, consistent with parts of the IGIMF theory, but that a truncation in the IMF in clusters is inconsistent with the observations. Future work will examine stochastic star formation and its time dependence in detail to study whether random sampling can explain other observations that suggest a varying IMF.

Stellar population synthesis techniques for predicting the observable light emitted by a stellar population have extensive applications in numerous areas of astronomy. However, accurate predictions for small populations of young stars, such as those found in individual star clusters, star-forming dwarf galaxies, and small segments of spiral galaxies, require that the population be treated stochastically. Conversely, accurate deductions of the properties of such objects also requires consideration of stochasticity.Here we describe a comprehensive suite of modular, open-source software tools for tackling these related problems. These include: a greatly-enhanced version of the slug code introduced by da Silva et al. (2012), which computes spectra and photometry for stochastically-or deterministically-sampled stellar populations with nearly-arbitrary star formation histories, clustering properties, and initial mass functions; cloudy slug, a tool that automatically couples slug-computed spectra with the cloudy radiative transfer code in order to predict stochastic nebular emission; bayesphot, a generalpurpose tool for performing Bayesian inference on the physical properties of stellar systems based on unresolved photometry; and cluster slug and SFR slug, a pair of tools that use bayesphot on a library of slug models to compute the mass, age, and extinction of mono-age star clusters, and the star formation rate of galaxies, respectively. The latter two tools make use of an extensive library of pre-computed stellar population models, which are included the software. The complete package is available at http://www.slugsps.com.

The production rate of ionizing photons in young (≤ 8 Myr), unresolved stellar clusters in the nearby irregular galaxy NGC 4214 is probed using multi-wavelength Hubble Space Telescope WFC3 data. We normalize the ionizing photon rate by the cluster mass to investigate the upper end of the stellar initial mass function (IMF). We have found that within the uncertainties the upper end of the stellar IMF appears to be universal in this galaxy, and that deviations from a universal IMF can be attributed to stochastic sampling of stars in clusters with masses 10 3 M ⊙ . Furthermore, we have found that there does not seem to be a dependence of the maximum stellar mass on the cluster mass. We have also found that for massive clusters, feedback may cause an underrepresentation in Hα luminosities, which needs to be taken into account when conducting this type of analysis.

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