Abstract
Mapping galaxy mass distribution is an important means of understanding galaxy morphologyand the nature of dark matter haloes, and therefore build up our knowledge of galaxy
formation and evolution. Analytical and numerical dynamical models are powerful methods
to model galaxy mass distributions based on galaxy stellar kinematics, and are strengthened
by including gaseous kinematics.
In this thesis, I start my research with using descriptive analytical models to identify thin-disc
components in galaxies. I kinematically classify the sample into disc-dominated, non-disc-dominated
and disc-free galaxies and measure the dynamical mass for disc-dominated galaxies
to study their mass budget. I find a dichotomy of lenticular galaxies in my classification, which
is explained by the deficiency of molecular gas. Realising the limitation of analytical models,
I continue my research with numerical models. I develop an orbit-based method with stellar
kinematics modelled by the Schwarzschild technique, and cold gas (H I ) assumed as a thin disc
aligned with stars. The application of this method to early-type galaxy NGC 2974 shows that
including extended cold gas kinematics significantly narrows down the measurement of the
dark matter inner slope. I then further generalise this method to be adapted for galaxies with
misaligned stellar and gas discs and apply the generalised method to early-type NGC 3626.
The results suggest that with very extended cold gas discs out to 10 Rₑ, there is a chance to
determine the overall shape of dark matter halo and even distinguish between different halo
models. I finally model a larger sample of galaxies which have two-aperture stellar kinematics
using the Schwarzschild technique to study their orbital components and dark matter profiles
across a wider mass range. The dark matter fraction is typically 40%-70% at 3 Rₑ, and I find
no clear trends between the dark matter fraction and stellar mass.
Date of Award | 1 Dec 2021 |
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Original language | English |
Awarding Institution |
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Supervisor | Anne-Marie Weijmans (Supervisor) |
Access Status
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