Dissertation projects for the MSc by Research in Astronomy and Astrophysics
Below are some of the MSc(R) projects for this coming year. However, we encourage prospective MSc(R) students to speak with as many of our academic staff, as early as possible, to find out what we do and to see if there are possible MSc(R) projects available - this list is unlikely to be comprehensive and research projects can quickly become out-of-date.
Note that supervisors and projects should be decided within the first 1-2 weeks of the first semester and they should inform the MSc(R) course director, Laura Wolz.
Supervisors: Albert Zijlstra, Iain McDonald
The GAIA satellite is in the process of mapping the precise position and motion of nearly every star in the Milky Way. It is measuring the parallax of every star and uses this to obtain an accurate distance. The GAIA DR3 catalogue (2020) contains 2 billion stars. An example of its use is at 'Our solar neighbourhood' video.
The current project aims at creating accurate 3-d HR diagrams (the third dimension being the location in the Milky Way) by deriving the temperature and luminosity for each star it this catalogue. This requires combining available photometry for each star from other catalogues, and fitting model atmospheres to the spectral energy distribution.
The results can be used to identify stars of particular interest, for instance stars with circumstellar dust fro their formation or their final evolution, or the study of interstellar extinction. Depending on the interest of the student, the focus can be on the software development or on the analysis.
Supervisor: Chris Conselice
This project will focus on discovering the earliest galaxies that formed in the universe and measuring their basic properties with the James Webb Space Telescope (JWST). Astronomers have long sought to find the earliest galaxies and to use them to determine how galaxies first formed. We can currently see galaxies back to when the universe was around 500 Million years old. We are, however, still learning about these galaxies and their basic properties such as their masses, sizes, and luminosities.
This project will use new and simulated data to search for and locate massive galaxies in the first billion years of the universe's history using JWST imaging. The project will involve using this imaging to discover these systems and then to make catalogues of objects. From this it will be possible to measure the masses of these galaxies and their number densities, putting constraints on the formation and galaxies and their role in the evolution of the universe.
Once we have identified the candidate distant galaxies using the Webb imaging, the student will characterise these systems in terms of the number of galaxies, their sizes, star formation rates, and masses. From this data, we can compare with theory to determine the processes driving the earliest galaxy formation.
This project can be done with a computer using preferably python coding.
Supervisor: Neal Jackson
Gravitational lenses are systems in which a background object is multiply imaged by the action of the gravitational field of a foreground galaxy. Gravitational lensing is important because it allows us magnified views of distant objects in the Universe, and also because it allows us to investigate mass distributions in galaxies independent of their light emission.
We are currently involved in a number of projects with major radio facilities (e-MERLIN and LOFAR) and planning for future surveys, including Euclid. Accordingly, there are a number of areas in which students could become involved:
- We are conducting LOFAR observations of a number of gravitational lenses to explore the properties of lensing galaxies. Because lenses give us multiple lines of sight through the galaxy, this allows us to deduce the effect of the lensing galaxy on the radio signal that propagates through it.
- We are currently conducting a survey called LBCS which provides calibrators for the analysis of the long baselines of LOFAR, which use the international stations outside the Netherlands. There are opportunities to get involved with the development of interferometric pipelines for the reduction of LOFAR-LB data.
- We have a number of projects involving radio observations of both radio-loud and radio-quiet lenses in order to study both lensing galaxies and the lensed sources (the latter are visible thanks to the magnification of the lensing galaxy).
- We are involved in a science working group of Euclid which is investigating the use of Euclid-discovered gravitational lenses for the study of galaxy evolution. The student will assist with the simulation of the scientific output from such a survey.
Intensity Mapping of the Neutral Hydrogen gas (HI) is a new cosmological survey type to observe the matter distribution. It uses the integrated 21cm emission of the HI gas in the radio wavelength to map the largest scales of the matter distribution with radio telescopes. The resulting HI intensity maps trace the underlying structure and therefore can be used to test cosmology, for example, by measuring the expansion rate of the Universe via Baryon Acoustic Oscillation (BAO) detection.
The South African Square Kilometre Array pathfinder MeerKAT is an interferometric array consisting of 64 dishes, which can be used in so-called single dish mode for HI intensity mapping observations. There are many observational challenges to overcome in order to detect the HI signal, such as subtracting astrophysical foregrounds and terrestrial radio frequency interference (RFI). In this project, we will examine the RFI present in the pilot HI intensity mapping data from MeerKAT in order to understand its statistical properties. We will then model the RFI in telescope simulations and test different methods to subtract them.
We will investigate the impact of the RFI properties and removal methods on the resulting HI intensity maps and the cosmological constraints.
Some programming experience in python or similar is essential, background in radio astronomy desirable.
Looking for the techno-signatures of advanced technical civilisations via anomalies in astronomical data
Supervisor: Michael Garrett
This project will search for anomalies in publicly available astronomical data that may be generated by the activities of an energy-intensive extraterrestrial civilisation. These so-called "techno-signatures" may take various forms but we will focus on unusual excess emission in the infrared domain due to the generation of waste-heat, in addition to other outliers e.g. discrepancies in spectroscopic v astrometric distances, excess stellar emission in the radio domain etc.
It may be possible to introduce some Machine Learning and AI aspects into the project. We will choose a well-defined topic with the aim of publishing the results in a refereed journal (see: Extending the Breakthrough Listen nearby star survey to other stellar objects in the field for a recent example).
Prior knowledge: it would be useful if the student has some background in astronomy and astrophysics but this is not essential. The student should be prepared to use software tools to interrogate large astronomical data sets, and to write python scripts to analyse the data.
Supervisor: Paddy Leahy
POSSUM is one of several surveys being conducted with the ASKAP telescope, which is revolutionary in that it is the first aperture synthesis telescope equipped with “PAFs”, essentially the radio equivalent of a CCD chip. This gives it a very large field of view for a high-frequency telescope, about 36 square degrees, about 150 times more sky area than visible to the VLA at any one time. This makes it ideal for large, deep radio surveys, and POSSUM will cover 75% of the sky, in full polarization and over a 300 MHz bandwidth. POSSUM is an international project and is currently in its pilot phase. Its aim is to measure Faraday rotation, which depends on the magnetic field between the radio source and the Earth. There are all sorts of specific science goals but this MSc project is to study the magnetic field immediately surrounding the radio lobes of radio galaxies. These lobes are bubbles of relativistic plasma embedded in the 100-million kelvin gas that surround galaxies, especially in clusters of galaxies. We can isolate the magnetic fields in this gas from the rest of the line of sight because the field direction and strength, and hence the amount of Faraday rotation, varies with position across the lobes. The best targets are the radio lobes with largest apparent size, > 5 arcmin, for which ASKAP gives detailed maps. Typically there are only one or two objects so large in each ASKAP field. In 2021-2 POSSUM isl carrying out “Phase II pilot” observations of about 10 fields, which should yield 10 to 15 objects to analyse for the project. Routine data analysis is done automatically for the whole survey, so you will start with calibrated images. Your job is:
- To find a well-defined group of targets to analyse, by inspecting the images: these objects are so big that they don’t show up in automatic catalogues: they tend to be registered as several different sources and are most easily recognised by eye. The images are BIG, so this will take a week or two, plus probably a week or so of training.
- Do some literature research on each object: most of them will be known AGNs, with basic data catalogued such as magnitude of the galaxy and in many cases a redshift and therefore distance. Typically there is not much known about the radio source itself, although there are some exceptions which have been the subject of earlier studies.
- For each target, extract a cut-out from the data “cube” of maps at 288 different frequencies, including the target and some empty sky surrounding it to analyse the noise properties, and run the POSSUM RMTools code to make a Faraday analysis of the cutout. This yields maps showing the Faraday Rotation Measure (RM) in each pixel, along with estimates of the intrinsic polarization direction, fractional polarization, and information about the spread of RM within the pixel (“Faraday dispersion”).
- The hard bit is then to try to make sense of the results. You will look for patterns, e.g. marked asymmetry between the RMs of the two lobes (Laing-Garrington effect), which is likely due to the lobe on the far side of the galaxy having more gas in front of it, and there are also claims of systematic ripples in RM across each lobe, although these are not always seen. We can do some pencil-and-paper theoretical analysis to assess proposed explanations, such as the numerical simulations by Hardcastle and Krause. The overall aim is to learn more about the magnetic fields in the intergalactic gas and how that interacts with the jets from the AGN.
Supervisor: Eamonn Kerins
Projects are available to work within the Spectroscopy and Photometry of Exoplanet Atmospheres Research Network (SPEARNET). SPEARNET is a new Manchester-led international survey, involving colleagues at Manchester, Open University, NARIT (Thailand) and ARIES (India). We are using a globally-distributed network of optical and IR telescopes, from 0.5m to 8m aperture, to undertake multi-epoch, multi-wavelength observations of exoplanet transits.
The multi-wavelength observations are used to measure the transmission spectrum of the atmospheres of Hot Jupiters and Neptunes. SPEARNET has developed an innovative automated selection scheme to choose our targets, a world-leading transit fitting code to analyse the data and construct transmission spectra, and novel machine-learning techniques to speed up retrieval of spectral models.
The goal of SPEARNET is to provide a testbed for how to conduct optimal, objectively-selected statistical studies of exoplanet atmospheres in an era where, thanks to missions such as NASA TESS, ESA PLATO and ESA ARIEL, we expect to have far more targets than we are able to follow up from the ground. Projects are available to work on analysing data as we gather it. You’ll be using and writing software in Python, so experience of, and enjoyment of, using Python is an advantage.
Supervisor: Patrick Leahy
Co-supervisors: Ian Browne and Peter Wilkinson
After many decades of radio astronomy activity are there any exciting discoveries to be made? Perhaps! An American experiment, ARCADE-2, consisting of carefully calibrated antennas flown on a balloon to get above most of the Earth’s atmosphere, claims that there is an unexplained radio background emission which only becomes visible at low radio frequencies (See Singal et al., for a summary of a conference on the current status).
L-BASS is a Manchester project designed to test whether or not this claim of an unexplained background emission is really true. L-BASS will produce a very accurately calibrated map of the sky at a frequency around 1.4 GHz (in the L-Band) and as well as confronting the ARCADE-2 controversy our map will have impact on the astrophysics of the Milky Way.
The mapping will be done using two 3m-long horn antennas at Jodrell Bank. The whole receiving system was deployed in January 2022; by September 2022 we will be collecting science data. The first part of the project will involve contributing to the observing, data collection and particularly the quality control of the time-stream data.
The second part of the project will involve applying corrections for temperature effects and then converting the data into a map of the relative brightness of the northern sky. In parallel work the L-BASS team will be developing an absolute calibration system based on a cryogenically-cooled reference resistor. By the end of the project we expect to be able to apply the absolute calibration to the map of the sky.
The project will offer training in the fundamental techniques of radio astronomy and sophisticated map-making techniques.
Supervisor: Rowan Smith
The gas of all galaxies is intrinsically turbulent in nature, which has profound implications for how they convert gas into stars. While idealised turbulence is well understood, how well it compares to real turbulent motions in the interstellar medium (ISM) is unknown.
In this project we will use innovative simulations of gas in galaxies like our own Milky Way to investigate how well the turbulence can be described by standard indicators such as the Mach number. We will then investigate how such simulations would appear in emission using synthetic emission to predict the best diagnostics for observers to use to understand the nature of turbulence in real observations of the ISM.
Supervisors: Lucio Piccirillo, Mark McCulloch
After almost 100 years since the beginning of radio-astronomy, the field has experienced a huge technological surge in terms of capability of detecting weaker and weaker radio signals, with higher spatial resolution and broader spectral coverage. Technology has improved in terms of imaging capabilities especially with big interferometers - like ALMA - or many imaging arrays at the focal plane of single telescopes. Modern radio astronomy has improved mostly in terms of larger and larger instruments (FAST as a single dish and SKA as interferometer, just to cite two examples). A corresponding improvement in the noise of the radio receiver has not happened mostly because amplification systems are not fully optimized for radio-astronomy.
It is well known that any coherent amplifier has an unavoidable intrinsic noise dictated by quantum mechanics: the noise in any coherent amplifier cannot be less than the so called “quantum noise” which is of the order of hv/2k. Current best amplifiers are at the level of 5-10 times this noise. In this project, we attack the problem of further reducing the noise in High Electron Mobility Transistors, which are the base of a very popular transistor in use in radio astronomy, by researching the causes of the extra noise with the aim of approaching further the quantum noise limit.
The student will be integrated into a research laboratory where he/she will work with other students and staff and will be involved mostly in experimental physics.
The student will learn a set of experimental skills about the fundamentals of radio astronomy electronics, low temperature physics, vacuum techniques and quantum noise in non-linear systems.
Supervisor: Patrick Weltevrede
MeerKAT is an array of 64 very sensitive radio dishes, that will become part of the Square Kilometre Array. Using MeerKAT the Thousand Pulsar Array project (which is one of the projects of MeerTime) has obtained high fidelity data for over 1200 pulsars. Our research group is actively exploiting this data to study the emission variability of pulsars on timescales comparable to the rotation period. Although pulsars, rotating neutron stars acting as cosmic lighthouses, are renowned to produce extremely stable clock-like signals that can rival atomic clocks in some cases, most pulsars show very significant variability in their pulse shapes. For about one third of the sample the pulse-to-pulse variability of the emission so-called drifting subpulses are have been detected. This means that within the envelope of the time-averaged pulse, the pulses detected for individual stellar rotations appear to progressively shift. This drift is a manifestation of periodic changes in the shape of the pulsar beam. The physical reasons for this are currently poorly understood.
In this data-driven project you will analyse MeerKAT data for a pulsar which shows abrupt changes in the drift direction, which is highly unusual. This work will build on work on another pulsar for which this effect has been seen by MeerKAT (this work has been submitted). The two key aims are to quantify the properties of the drifting subpulses, and compare the two pulsars to understand what sets them apart from pulsars showing more regular drifting subpulses. This may help understanding the physical mechanism driving these periodicities in pulsar magnetospheres.
Supervisor: Anna Scaife
Unlike standard neural networks, which provide a point-wise prediction for each test sample, Bayesian neural networks provide a posterior probability distribution. This probability distribution can then be used to quantify the relative uncertainty/confidence with which each prediction is being made. However, the calibration of these uncertainties can be improved/degraded by making changes to the neural network model. In this project the student will investigate whether the introduction of different types of equivariance to isometries of the 2-d Euclidean group (i.e. the image plane) in the convolutional layers of a CNN affects the calibration of uncertainties when making predictions of radio galaxy classification in astrophysics. This project is suited to a student with a background in physics, maths or computer science. Existing experience with deep learning models is useful but not essential. The project will run in Python, using the PyTorch deep-learning library.
Supervisor: Rebecca Bowler
At the cutting-edge of Astronomy research is the study of the formation and evolution of the first galaxies. Through breakthrough observations in the past 30 years it has been possible to identify galaxies within the first billion years after the Big Bang. These galaxies are selected and studied based on their rest-frame UV emission from young stars. This light is redshifted into the near-infrared (~ 1 micron) where it is detected with telescopes like Hubble and James Webb. Despite the many recent advances in the understanding of early galaxies based on this rest-frame UV light, there are clear issues with having such a restricted view of the multi-wavelength emission from galaxies (e.g. [1, 2]).
The goal of this project is to use sub-mm or radio observations to identify dust-obscured star-formation in the early universe. Sub-mm observations measure the emission from cold dust in galaxies, providing an estimate of the obscured star-formation. Radio observation on the other hand provide an independent measure of the star-formation rate via synchrotron emission that is not affected by dust obscuration. The student will be analysing new data from either ALMA  or the Square Kilometre Array pathfinder MeerKat  to calculate the obscured star-formation rate in galaxies at redshifts in excess of 4.
The project will be computational and involve a combination of writing new code and using established astronomy software. Coding in python is recommended due to the considerable astronomy modules that are freely available. It would be useful if the student had a background in astronomy and astrophysics but this is not essential.