Bridging the Gap: Observations and Theory of Star Formation Meet on Large and Small Scales

The drive to understand galaxy formation and evolution over the lifetime of the universe has justified vast space-based and ground-based telescope facilities, as well as the development of new technologies. The details of star formation, and the modes by which that activity couples to the broader galactic environment, occurs on small spatial scales. These scales can only be traced with great sophistication in the local universe, as witnessed by observations using the Spitzer Space Telescope, the Herschel Space Observatory, the Stratospheric Observatory for Infrared Astronomy (SOFIA), and the Atacama Large Millimeter Array (ALMA). A critical realization of the last decade, however, is that the large scales and small scales are strongly coupled, and cannot be treated in isolation. At the same time, the scales studied in the local universe are "sub-grid" for the purpose of cosmological simulations that make valiant efforts to include the physics of star formation and its feedback to the local environment. The fundamental uncertainties in how this sub-grid physics is incorporated into the larger picture are by far the greatest limitation in understanding galaxy formation and evolution. The main goal of cosmological simulations is to understand the formation and evolution of the universe over a wide range of scales going from the Hubble volume to sub-light-year scales within galaxies. However, due to computational limitations, the physics of star formation in galaxies and the effects this process has on the formation and evolution of galaxies are often greatly simplified. For instance, accounting for the effect of stellar feedback in cosmological simulations is a crucial factor in galaxy formation and evolution. Without stellar feedback in galaxies, the gas would rapidly cool and collapse, converting all available gas into stars within a dynamical time. This consequence is in sharp conflict with observations—there are vastly fewer stars in our universe than the models would predict. Until recently, numerical simulations have been unable to regulate star formation efficiently enough to reproduce observations, with many consequences: models with too many stars also predict they form at the wrong times in the universe’s history, that there are the wrong abundances of heavy elements, that galaxies look nothing like the Milky Way, and even that the observable properties of dark matter are (apparently) discordant with new precision-cosmology measurements. All of these problems may, in fact, be due to the fundamental problem of understanding how small and large scales interact.