Institute for Astronomy

Milky Way & Local Group PhD Projects

Research projects on offer in our Milky Way & Local Group Galaxies research group.

Galactic Archaeology of Local Volume Galaxies with Euclid

Annette Ferguson

Within the hierarchical framework for structure formation, merger and accretion events drive the growth of dark matter halos and the galaxies that form within them. The low surface brightness peripheral regions of galaxies are predicted to contain a gold mine of information about the nature, frequency and timing of these events but the lack of suitable data has greatly hindered analyses to date.

The optimal way to study these elusive regions is via wide-area star count studies – a technically challenging approach that has thus far only been applied to a small handful of external galaxies.  However, with the successful launch of ESA’s Euclid mission in July 2023, we now have an unprecedented opportunity to obtain the deep, panoramic and high-resolution maps of nearby galaxies that are required for stellar halo analyses. In particular, Euclid data will allow this approach to be applied to all galaxies within the survey footprint out to a distance of at least 5 Mpc.

This PhD project will exploit the first major data release from Euclid (early 2025) to uncover the archaeological record in the stellar halos of the nearest galaxies in the Local Volume. It will involve mapping the distribution of luminous red giant branch stars and globular star clusters, the most accessible tracers of old stellar populations, over >100 kpc scales. A primary focus will be the M81 Group (D=3.6 Mpc) which contains a Milky Way analogue, several LMC-like systems and several tens of low-mass dwarf galaxies, the properties of which are particularly sensitive to the nature of dark matter and the physics of galaxy formation. The Euclid data will be complemented by a variety of other ground-based datasets, some of which are already in hand and others will be proposed for during the PhD thesis (with opportunities to go on observing trips).

With knowledge of the galactic archaeological record in a significant sample of nearby galaxies, a range of science questions can be addressed about the detailed way in which galaxies across the stellar mass spectrum build up their mass and transform over time. The observations will also be used to compare to the predictions of high-resolution simulations of galaxy formation within a cosmological context, allowing exploration of where improvements in the input physics may be warranted.

Uncovering disequilibrium in the Milky Way with Machine Learning

Jorge PenarrubiaAneesh Naik, and Michael Petersen

Our Galaxy, the Milky Way (MW), is currently undergoing a major collision with the Large Magellanic Cloud (LMC), a large satellite galaxy visible to the naked eye. In part due to the observations of the Gaia satellite, we have only just begun to understand this process in the last 5 years. In particular, the LMC is far more massive than previously thought, and so the impact of its infall on the Milky Way itself is far bigger than previously thought.

The overarching goal of this PhD project is to arrive at a quantitative understanding of the impact the LMC is having on the kinematics and dynamics of the stars in the Milky Way disc. The student will apply state-of-the-art unsupervised deep learning tools to large-scale simulations of the MW-LMC interaction to measure and map out the imprints of the LMC on the simulated disc stars. A first generation of such simulations is already available, but the student will have opportunities to run their own simulations. Subsequently, the student will be able to perform a statistical comparison with observed data from the Gaia satellite in order to search for the same imprints of disequilibrium in the real MW disc.

The work described above will cover the first 1-1.5 years of the PhD.  Following this, there are several 'downstream' science goals and potential future directions:

  • Dynamical analyses of the disc stars (for example, analyses estimating the local density of dark matter) typically assume equilibrium. This assumption is incorrect, and likely introduces some systematic bias into the analysis. The student will be able to quantify this bias, leading to better-informed estimates of the local dark matter density.
  • LMCs of different masses and sizes would impart different imprints on the stellar kinematics. So, one could invert the problem and use the observations to 'weigh' the LMC.
  • The machinery developed by the student to measure disequilibria in the MW disc could be used for other disequilibrium sources beyond the LMC, e.g., past mergers or internal processes like the MW bar.

This PhD will be primarily computational, involving simulations, machine learning, and the statistical analysis of large, complex datasets (simulated and observed).

Unlocking the physics of environmental quenching in the Virgo galaxy cluster

Ruben Sanchez-Janssen

Galaxies are not uniformly distributed in the Universe but span a wide range of densities from the cores of rich clusters to groups, filaments, and voids. Galaxy clusters are mainly composed of quiescent objects, while star-forming systems are dominant in less dense environments. This is especially true at low galaxy masses, where the scarcity of truly isolated quiescent dwarfs indicates that internal processes are not sufficient to completely halt star formation and that environmental 'quenching' must take place. Different gravitational and hydrodynamical mechanisms have been proposed to operate in clusters, but the relative contribution of each process to shaping quiescent cluster dwarfs still is hotly debated.

The goal of this PhD project is to finally resolve this tension by studying a mass-limited sample of dwarf galaxies in the Virgo cluster which are in transition from being star-forming to quiescent. Virgo is the nearest galaxy cluster and the dominant mass concentration in the local Universe, which makes it the ideal laboratory to study the perturbing mechanisms that shape cluster dwarfs with unrivalled detail. The student will take advantage of extremely deep optical/infrared imaging to uncover the presence of residual star formation in the inner regions of thousands of Virgo dwarf galaxies. In addition to modelling these pan-chromatic spectral energy distributions, the student will exploit integral-field spectroscopy from the WEAVE instrument for a representative subsample of ~20 dwarfs in transition. This unique dataset will allow us to study the properties of the star-forming gas and, critically, characterise and model their stellar populations--did quenching occur on short or long timescales? What do the stellar kinematics tell us about the role of tidal interactions?

This project is poised to make the next leap forward in our understanding of the physical mechanisms driving environmental quenching in low-mass (Virgo) cluster galaxies. At the same time, the student will develop expertise in the analysis of modern datasets (integral-field spectroscopy and multi-wavelength imaging), thus positioning them to optimally exploit similar data from upcoming surveys such as Rubin/LSST.