This Thesis explores the use of independent dynamical probes (multiple populations, gravitational lensing) to infer the prope1ties of Dark Matter (DM) haloes and investigate scenarios of galaxy formation. It begins with a study of the virial properties (flattening and global anisotropy) of stellar populations in different DM profiles. General theorems are presented, with some application to the Milky Way potential (DM flattening and density profile) as probed by the thick disk, stellar halo and rotation curve. A powerful outcome of virial methods applied to multiple populations is the distinction between DM cusps or cores in nearby dwaif Spheroidal galaxies, in particular Seu lptor and Fornax. Modelling based upon the Jeans equations is reformulated so that it involves just the direct observables (surface density and velocity dispersion), which enables a simultaneous exploration of photometric and dynamical prope1ties. This is applied to different systems. First, probes of DM in early-type galaxy gravitational lenses are devised and the mass-bias underliying some common assumptions in the literature is quantified. Second, when studying the Globular Cluster (GC) system of the nearby Elliptical M87, this new approach yields information on the GC subpopulations, the luminous mass and DM profile. Inference on the GC orbital structure is discussed, with an eye to the processes of assembly and evolution that my have produced it. The general aim of this Thesis is the development of simple, yet flexible and robust, methods to study DM profiles in spheroidal or ellipsoidal galaxies of different sizes and masses. The combined treatment of photometry and dynamics yields appreciable insight even when the data are not enough to justify more elaborate modelling techniques.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:648136 |
Date | January 2013 |
Creators | Agnello, Adriano |
Publisher | University of Cambridge |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://www.repository.cam.ac.uk/handle/1810/265616 |
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