The astronomy group welcomes applications from postgraduates who wish to carry out research leading to the award of a Ph.D.
Applications are made using the online application form found here after registering a username and password. Further information on the admissions procedure is available from the postgraduate admissions tutor, Prof. Juan P. Garrahan. Once you have submitted your application, please also send a brief email containing your application ID to the astronomy admissions coordinator, Dr. Nina Hatch, confirming that you have applied.
Interviews for our STFC funded positions (for UK/EU students who meet the appropriate eligibility requirements) are normally held during the period from late February to early March each year. We therefore strongly encourage the submission of applications before January 31.
Overseas students may also be eligible for one of our international research scholarships, and should ensure their online application is submitted at least six weeks before the closing date for these schemes.
Examples of typical Ph.D. projects offered by the astronomy group may be found by following the research projects link on the right of this page. Further details regarding postgraduate funding opportunities are available at the links listed below, and more general information about being a postgraduate in the School of Physics and Astronomy may be obtained on our postgraduate study page.
In recent years there has been tremendous progress in identifying large samples of distant galaxies, but many crucial aspects of galaxy formation remain poorly understood. In particular, we still do not understand why star formation was abruptly quenched in many massive galaxies at high redshift. It is also unclear if the same processes are linked to the morphological transformation of galaxies, to produce the Hubble Sequence we see today. The aim of this project is to understand and unravel these key transformative processes. The project will involve a combination of deep imaging data from the Ultra-Deep Survey (the deepest infrared survey over ~1 sq degree, led by Nottingham), unique deep spectroscopy from the VLT VANDELS project, and forthcoming spectroscopy from the James Webb Space Telescope (JWST). Imaging will provide the morphological characteristics, while the spectra will allow us to understand the internal physical processes. Many unanswered questions remain. Are distant galaxies quenched by feedback from accreting black holes or massive stellar outflows? Is the morphological transformation related to the quenching of star formation? Do galaxy mergers play a role? By combining information obtained from multi-wavelength imaging and spectroscopy, the aim of this project is to solve these important problems, to finally understand the processes driving the evolution of distant galaxies.
The morphology, star-formation history, dynamics, and many other properties of galaxies depend strongly on where they formed and where they live. In other words, galaxies are affected by their environment. We have already studied in great detail the most extreme environments (cores of rich galaxy clusters), but milder environments such as the groups and the filamentary structures that feed galaxy clusters remain largely unexplored. We know that these environments must play an important role on galaxy evolution because many of the galaxies that fall into clusters have already been “pre-processed” by the time they arrive to the cluster core. In this project we will combine state-of-the-art numerical galaxy formation and evolution models with new and unique observational data taken with some of the most innovative astronomical instruments to, first, map these structures and identify the galaxies that inhabit them and, second, study their properties to find out how these environments affect their history.
Spiral arms are a familiar feature of galaxies, yet their origins are still poorly understood. A variety of mechanisms have been proposed, each predicting particular characteristics for the spiral patterns, as well as how they relate to a galaxy’s kinematics, star-formation, interstellar medium, and wider environment. Depending on which mechanism is at work, spiral arms may be superficial or significant, ephemeral or long-lived; meaningless or indicative. Small sets of nearby galaxies have provided support for many of the proposed mechanisms. However, in order to determine their relative importance across the galaxy population, it is essential to consider large, representative samples, spanning ranges of mass, environment and redshift. Measuring such detailed morphological features for large samples of galaxies is challenging. Recent advances have been made via two related paths: citizen science and deep (machine) learning. Thanks to the Galaxy Zoo project, we have visual information for hundreds of thousands of galaxies and the data to train the new generation of sophisticated computer vision models. This project will verify and build upon a variety of recent work, utilising data from the latest generation of wide-and-deep surveys (e.g. DECaLS and KiDS). Visual information will be used to construct automatic classifiers that can not only reproduce humans, but surpass them, by avoiding their characteristic biases. Using these abilities, this project will examine correlations between observed spiral arm characteristics and other galaxy properties. By comparing these multivariate distributions with expectations from physical models we will determine the prevalence of each spiral arm mechanism across the galaxy population and through cosmic time; reaching a conclusion on the role of spiral arms in galaxy evolution.
This project will verify and build upon a variety of recent work, utilising data from the latest generation of wide-and-deep surveys (e.g. DECaLS and KiDS). Visual information will be used to construct automatic classifiers that can not only reproduce humans, but surpass them, by avoiding their characteristic biases. Using these abilities, this project will examine correlations between observed spiral arm characteristics and other galaxy properties. By comparing these multivariate distributions with expectations from physical models we will determine the prevalence of each spiral arm mechanism across the galaxy population and through cosmic time; reaching a conclusion on the role of spiral arms in galaxy evolution.
Today we know that galaxies are assembled hierarchically, by the accretion of smaller sub-systems. These mergers and interactions shape galaxies in ways not yet fully understood. The details of these processes are largely erased in the inner regions of galaxies. Fortunately, clues are preserved in galaxy outskirts, in the form of low surface brightness substructures and the faint population of small stellar companions: globular clusters and dwarf galaxies. Most previous studies of the population of companion systems have typically been limited to targeted observations of massive, nearby ellipticals. However, the latest generation of large surveys achieve the combination of depth and resolution required to detect small stellar systems at significant distances. This opens up the possibility of studying the companion populations for large, statistically-representative samples of galaxies: spanning a range of morphology, mass and environment. This project will develop novel techniques to automatically extract and characterise small companion objects and substructures in multi-band imaging provided by the latest galaxy surveys, such as DECaLS and KiDS. This will also be valuable preparation for exploiting the potential of the next generation of surveys by facilities such as LSST and Euclid. With the resulting measurements, we will be able study the variation of the companion population as a function of galaxy properties. The ultimate goal is to use the properties of the companion population to constrain fundamental questions regarding the assembly and interaction histories of galaxy.
This project will collaboratively develop novel techniques to automatically extract and characterise small companion objects and substructures in multi-band imaging provided by the latest galaxy surveys, such as DECaLS and KiDS. This will also be valuable preparation for exploiting the potential of the next generation of surveys by facilities such as LSST and Euclid. With the resulting measurements, we will be able study the variation of the companion population as a function of galaxy properties. The ultimate goal is to use the properties of the companion population to constrain fundamental questions regarding the assembly and interaction histories of galaxy.
The intergalactic medium forms the link between galaxy formation and cosmology; its spatial distribution is sometimes referred to as the cosmic web due to the filamentary network that intergalactic gas and dark matter traces on large scales. Detailed spectroscopic observations of the cosmic web -- as seen in absorption in the spectra of distant, background quasars -- therefore play a vital role in understanding the structural, chemical and thermal evolution of baryons across cosmic time. Unlocking and interpreting this rich source of information using high fidelity cosmological hydrodynamical simulations of intergalactic gas is the goal of this project. You will use the state-of-the-art Sherwood simulation suite (www.nottingham.ac.uk/astronomy/sherwood) to investigate the properties of intergalactic structure throughout cosmic time, and predict the observational signatures expected in the spectra of the most distant quasars and galaxies yet discovered.
We currently do not understand the nature of dark matter, yet we can detect it in great abundance in the nearby universe where it makes up 90% of all mass. What we would like to understand is how dark matter has evolved through cosmic time. This will reveal not only how dark matter itself was assembled in the universe, which we know very little about, but also how dark matter is related to the process of galaxy formation.
To address this our group has recently obtained spectroscopy of distant galaxies when the universe was only a few Gyr old with the VLT using the SINFONI instrument. This data will provide internal kinematics for these young galaxies, which in turn will reveal their internal dynamics from which not only early kinematic properties can be measured, but also their total dark matter content. By comparing the dark matter to stellar masses with galaxies at a variety of distances, we will be able to determine how dark matter has assembled with galaxies. This is furthermore a major test of the CDM paradigm for understanding how galaxies and the universe assembled.
Massive galaxies are the brightest systems in the universe, and thus the easiest to study. They are also the type of galaxies where we have the most theoretical models on their formation, yet observationally we still do not know how they and their dark matter halos formed. While we know a great deal about massive galaxies, some of their unexplored features include their outer diffuse regions, and their satellite galaxies, neither of which have been studied in any detail. Diffuse light around massive galaxies have longer dynamical time-scales than denser regions, and thus allow us to probe the history of galaxy formation, in particular how it relates to their satellite galaxies, which merge with the central to build up their masses. The problem is that it is very difficult to study these galaxies and regions, as they are very faint and have a low surface brightness.
The Dark Energy Survey (DES) on the Blanco 4m telescope at Cerro-Tololo Observatory in Chile will cover 5000 square degrees of the sky, and is an ideal data set to investigate these related questions. The student on this project will led the effort towards finding the faintest satellite galaxies, as well as investigate the faint outer parts of galaxies which have not yet been explored. The project will involve collaborating with the DES team, including observational trips to Chile, and leading other follow up individual projects on various telescopes. The result of this will be a better understanding of how satellite and central galaxies have formed in the universe.
The James Webb space telescope will launch in the beginning of 2021, providing a revolution in our understanding of the first galaxies within the first 500 Million years after the Big Bang. This update to the Hubble Space Telescope will allow us to probe the very first galaxies in a way that we are unable to do today. Nottingham is part of the team with guaranteed early data from JWST. The student hired for this project will at first lead some preparatory work using data we are acquiring with the Very Large Telescope (VLT) in Chile to determine the best targets for JWST. After launch the student will then take on a leadership role in investigating the stellar populations, ages, structure and star formation rates of the first galaxies. This will ultimately be interpreted in terms of theories of galaxies formation to test and exclude different ideas for how the first generations of galaxies and star formed.
Our group plays a key role in the gravitational lensing element of the Herschel-ATLAS survey carried out by the Herschel Space Observatory. H-ATLAS is rapidly increasing the number of known strong lens systems with a continual stream of new detections at significantly higher redshifts than existing lens samples reach. This allows astronomers to probe deeper into the young Universe when galaxy evolution was in its early stages. These new lens systems are presently being followed up by the ground-breaking ALMA telescope in Chile which offers incredibly high resolution and sensitivity. This, in combination with the fact that the lenses themselves give a magnified image of the background source galaxy enables analysis of high redshift galaxies at a level of precision that is impossible to obtain otherwise. The project being offered is to carry out lens modelling of the ALMA observations to learn about both the foreground galaxy doing the lensing and the background galaxy being lensed. The project includes the possibility of developing lens modelling techniques.
Strong gravitational lensing is now recognised as one of the most powerful methods for measuring the amount and distribution of dark matter and baryonic mass in galaxies. Such measurements are key for the understanding of galaxy formation and evolution but there are presently only around 150 strong galaxy lens systems known and most of these are at low redshifts where the pace of galaxy evolution has significantly slowed. This situation is expected to improve dramatically in the near future with new higher redshift lens samples containing tens of thousands of lenses resulting from two forthcoming facilities: The Large Synoptic Survey Telescope which comes online in 2019 and the Euclid satellite due for launch in 2020. Our group has developed a technique that has now become the 'industry standard' for modelling strong lenses but the method is too labour intensive for scaling up to the large datasets anticipated. This project is therefore concerned with tackling this challenge directly by developing methods for the automatic detection and modelling of strong lens systems in large survey data.
Most galaxies in the Universe live in groups or clusters, making such large-scale structure critical both for studies of cosmology and of galaxy evolution. This project builds on a successful research program working at the interface between simulations (Pearce) and observations (Gray) to understand the physical processes that influence these objects and the galaxies inhabiting them. Students will exploit state-of-the-art N-body and hydrodynamic simulations, galaxy evolution models, and large imaging and spectrographic surveys to study the properties of large scale structure in both the real and mock universes. Comparison of both approaches allows us to simultaneously test the model physics, gain insight into the data, and understand the ultimate limitations of our measurements. Our goals include understanding group and cluster assembly (and implications for large cosmological surveys) as well as distentangling the interplay between galaxy properties and their environments.
In 1998, the discovery that the expansion of the Universe was accelerating lead to the suggestion that almost 70% of the Universe is made of a mysterious “dark energy”. Almost nothing about this substance is known; it may be a new type of field, or a property of space itself, or perhaps Einstein's theory of gravity, general relativity, may fail on cosmological scales. All of these theoretical models can be precisely fit by the supernovae data that measures the acceleration of the Universe, so these observations, and other geometric cosmological measurements, cannot distinguish between these models.
The most promising route to reveal the nature of dark energy is to measure the rate at which structures form in the Universe. The growth of structures, such as groups and clusters of galaxies, is a battle between the expansion rate of the Universe, which acts to suppress the growth of density fluctuations, and the gravitational attraction of matter, which accelerates it. Observing the growth rate of structures, therefore, allows us to measure the expansion rate and test the theory of gravity on large scales. However, observing the growth rate of structures is extremely difficult; only 3 methods are commonly used, all of which have severe systematic uncertainties that may prevent precision measurements of the growth of structure. In this project, you will use data from cosmological simulations to design a new method that will precisely measure the growth rate of galaxy clusters in the early Universe using the velocities of the surrounding galaxies and the weak gravitational lensing signal. Measuring this growth rate will lead not only to the information about the nature of dark energy, but also gives clues to the nature of dark matter and the mass of neutrinos.
In our Universe structure forms hierarchically, with small objects merging to make larger ones. The end state of this process are the largest bound structures in the Universe, giant clusters of thousands of galaxies. These enormous objects are used as the testing ground for theories of galaxy formation and evolution because of their highly complex environment and long history. In this project we aim to catch these giants prior to and in the process of formation, using deep observations to identify galaxies which will eventually form galaxy clusters by the present day. This will allow us to answer such questions as how important a large dark matter halo is to the physics of galaxy transformation and what is the connection between large scale environment and local galaxy formation. To do this we will couple the latest generation of large astrophysical simulations of the Universe to our ongoing deep observation programme, using insights obtained from the full evolutionary history contained within the simulations to shed light on our observational data. We require a student with interests both in high performance computing and large observational programmes.
It is now quite well established that the distinct components of galaxies -- primarily their bulges and disks -- have different stories to tell about the evolution of these systems. To study these components separately in order to learn how they formed, we need detailed spectral mapping across the entire face of each galaxy, which can now be obtained using integral field unit (IFU) spectrographs. The World-leading project to do this is the Mapping Nearby Galaxies at APO (MaNGA) programme, which is one of the components of the on-going Sloan Digital Sky Survey. MaNGA will produce a huge IFU spectral data set for 10,000 galaxies, allowing their kinematics and chemical properties to be studied in unprecedented detail. As members of this elite programme, we have complete access to all the data, and at this stage in the project we can play a key role in shaping the over-all science programme. PhD students involved in this project will have the opportunity to work with data of a quantity and quality that has never been obtained before, and will interact with the leading scientists in this field from all over the World, to establish their own longer-term research careers.
It is now well established that all massive galaxies host a supermassive black hole, but at any given time most of them are relatively dormant. Only a few per cent of galaxies contain luminous Active Galactic Nuclei (AGN), and it is unclear if this activity is stochastic or triggered by particular events in the evolution of the host. Furthermore, does the AGN itself play a role in regulating star formation, as many galaxy formation models predict? In this project we will adopt a novel approach to understanding AGN activity in the Universe. Using the latest data from deep multi-wavelength surveys we will search for AGN by identifying galaxies with characteristic features in their spectral energy distributions (e.g. strong X-ray emission, or the presence of hot dust), while simultaneously using HST images of the galaxies to separate the central nuclei from their more extended hosts. For low-luminosity AGN in particular, which are poorly understood, this approach will allow us to disentangle the light from star formation and the central accreting black holes. The overall goals are to develop new techniques for identifying AGN in deep survey data, and to understand the links between AGN activity and the wider process of galaxy formation and evolution.
Computer generated mock observations underpin the interpretation of modern astrophysics. Ongoing and future large survey programmes such as the Dark Energy Survey, Euclid and PanStarrs rely upon such models to train and validate their search algorithms and data extraction techniques. In Nottingham we lead the Mocking Astrophysics project (www.mockingastrophysics.org) which aims to provide verified model skies to these large programmes. Mocking Astrophysics has projects ranging across the entire spectrum of mock catalogue production, from comparing initial conditions generators through Tier-0 production simulation on the world's largest supercomputers to detailed analysis and mock galaxy catalogue production and mock observation using current observational software pipelines. We are looking for a computationally literate student to join of international project team which is gearing up for the launch of the Euclid satellite in 2020.