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Major Merger between a Classical Dwarf Irregular Galaxy and its Massive Ultra-Faint Satellite

Presentation #336.05 in the session Galaxies incl. the Milky Way.

Published onJul 01, 2023
Major Merger between a Classical Dwarf Irregular Galaxy and its Massive Ultra-Faint Satellite

Dark matter, an elusive form of matter that does not emit nor interact with electromagnetic radiation, can be observed only through its gravitational influence on the visible matter in galaxies and the large-scale structure of the Universe. One of the best ways we can study dark matter is through the kinematics of dwarf galaxies, due to their high relative dark matter content. Dwarf galaxies are classified based on their low mass, with classical dwarf irregular galaxies having stellar masses typically around 105-108 Msun, and the even more dark matter-dominated “ultra-faint” galaxies having M* < 105 Msun. Because the stellar kinematics of dwarf galaxies is the best tool, we have to model their dark matter content, any external influence on the stellar motion is also extremely important to model. Major mergers in dwarf galaxies (anything with at least a 1:10 mass ratio between the central and the satellite) can impact stellar kinematics in dwarf galaxies, and so properly predicting these effects has major implications for our understanding of dark matter and its role in shaping dwarf galaxy kinematics. We study one such major merger in a high-resolution cosmological Zoom-in simulation of a dwarf galaxy (M* ~ 106 Msun) merging with its massive ultra-faint satellite (M* ~ 105 Msun) using the FIRE-2 simulations (Hopkins et al. 2018). We perform mock observations of the simulation before, during, and after the merger, and make testable predictions for the circular rotation, the velocity dispersion, and the stellar age gradient of classical dwarf spheroidal galaxies that may have undergone a similar collision. With these predictions, astronomers will be better equipped to disentangle the effects of dark matter and mergers on dwarf galaxies, allowing them to construct more accurate dark matter models.

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