SLUG: A new way to Stochastically Light Up Galaxies

TL;DR

SLUG is a novel computational tool that simulates star cluster populations by stochastic sampling of the IMF, enabling realistic modeling of galaxy star formation and testing IMF variations.

Contribution

SLUG introduces a new stochastic sampling method for star clusters, improving the realism of synthetic galaxy star formation models.

Findings

Generates realistic star cluster distributions.

Provides a quantitative tool for testing IMF variations.

Addresses open problems in galaxy star formation studies.

Abstract

We present SLUG, a new code to "Stochastically Light Up Galaxies". SLUG populates star clusters by randomly drawing stars from an initial mass function (IMF) and then following their time evolution with stellar models and an observationally-motivated prescription for cluster disruption. For a choice of star formation history, metallicity, and IMF, SLUG outputs synthetic photometry for clusters and field stars with a proper treatment of stochastic star formation. SLUG generates realistic distributions of star clusters, demonstrating the range of properties that result from finite sampling of an IMF and a random distribution of ages. The simulated data sets provide a quantitative means to address open problems in studies of star formation in galaxies and clusters, such as a test for IMF variations that are suggested by the systematic deficiency in the H-alpha/UV ratio in outer disks or in dwarf galaxies. SLUG will be made publicly available through the website http://sites.google.com/site/runslug/.