Assembling the big picture of nearby galaxies

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Galaxies are the building blocks of the universe, the place where stars and planets are born. The inner life of galaxies is complex: stars are formed from dense, cold gas, spend their finite lifetimes fusing hydrogen into helium and heavier elements, and then die, returning some of the processed material to space where the cycle begins again. There is a complicated interplay between stars, interstellar gas and dust, the haloes of dark matter that surround galaxies and the giant black holes that live at their centres. The rate of new star formation depends on the physical properties of the gas, which in turn depend on the past history of star formation, which affects and can be affected by the central black hole. In establishing the stories of galaxies, important questions include whether models can reconstruct unique past histories, how the formation of new stars varies within galaxies, and how the mass and star formation of galaxies can best be measured. The huge variations in pressure, temperature, and density in the various galaxy components mean that different parts of galaxies absorb and emit light at many different wavelengths. While astronomers previously tended to specialize in observations made at a particular wavelength, it is now clear that we need a multi-wavelength approach to assemble the full picture of how galaxies arrived at their present diversity of states. In nearby galaxies the available observations can probe both the present and past of these complex ecosystems in exquisite detail, but only if we can find new and better ways to manage and exploit the data. This program will develop the tools and techniques to compare the internal structures of galaxies to each other and to the increasingly-sophisticated models which describe the interplay between stars, gas, dust, black holes, and dark matter. This will enable the derivation of detailed histories of nearby galaxies, an important part of the quest to understand the Milky Way's---and our own---place in the universe. The tools and training developed in this program will be transferable to other applications and enable astrophysicists to contribute to other areas of "Big Data" science.