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Title: Understanding the large-scale dynamics of the interstellar medium in barred galaxies
Author: Sormani, Mattia Carlo
ISNI:       0000 0004 6352 9374
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2015
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We study the large-scale dynamics of the interstellar medium in barred galaxies. The interest in doing this is two-fold. On the one hand, the hydrodynamic flow is the source of many interesting physical phenomena, such as shocks and spiral arms. On the other hand, it is a powerful tool to constrain the characteristics of individual galaxies. Approximately half of this thesis is devoted to understanding the general characteristics of the gas dynamics. There are two key ingredients. The first is ballistic closed orbits. We investigate the connection between closed orbits and the full hydrodynamic flow. We show how they also form the basis to explain bar-driven spiral arms. The second key ingredient is shocks. These can arise at the transition between different families of closed orbits, or when the spiral arms become too strong. Under certain conditions, shocks become hydrodynamically unstable and produce density fluctuations that may have an observational counterpart in the form of asymmetries in the Milky Way molecular gas distribution. We also explore systematically how the gas flow is affected by a change in the parameters that characterise the bar, such as its length, strength and pattern speed. Through the study of the gas dynamics, inferences can be made about the structure of galaxies. We have compared our models with observations of the Milky Way. First, we revisit and refine the Binney et al (1991) model, one of the most successful models for the gas flow in the Galaxy. Then, we present new models that while preserving the good properties of the previous model can also correct its main shortcomings. These models can qualitatively account for most of the observational signatures of the Galactic bar and allow us to constrain its characteristics, such as its pattern speed, length and strength. However, we show that is difficult to find a model that accounts for all the important observational features simultaneously due to the high dimensionality of parameter space involved. We argue that automatic fitting method are necessary. To this end, we develop a new quantitative method to fit Milky Way longitude-velocity diagrams that is based on feature matching.
Supervisor: Magorrian, John Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available