Fast radio bursts (FRBs) last for much less than the blink of eye and originate in distant galaxies, billions of lightyears away. We are still trying to understand what produces the FRBs. The hyper-magnetic neutron stars known as magnetars are a leading contender, but can they explain the variety of different FRBs we have observed? Some FRBs repeat, whereas others apparently do not. Some FRBs are found near star-forming regions in their host galaxies, whereas others live where only old stars are expected. This is confusing, and suggests that there may be multiple types of FRB sources. Recent years saw the discovery of longer-than-typical FRBs with durations up to a few seconds. Are they a distinct class of bursts or are they produced by the same sources and physical processes?

OBJECTIVE: This project aims to find longer-duration FRBs using data from the CHIME and/or LOFAR telescopes. You'll get access to prerecorded data sets and will work on the visualization tools and algorithms to first identify and then characterize astrophysical bursts.

PREREQUISITES: No prior knowledge of the field is required but experience with programming in Python or another language is strongly preferred.

RESOURCES: This project can be performed using a consumer laptop that runs Python; you will get remote access to one of our compute clusters for more demanding processing tasks. We will lend a laptop computer if need be.

Radio transient astronomy has taken off during the past decade, thanks to excellent new radio telescopes coming online and increases in computational power. Exciting detections of strange sources that still need identifying have been made including the Galactic Burster, a LOFAR transient, dispersed transients by AARTFAAC and recently an MWA discovery of a possible unusually slow magnetar. Each detection leads to the chance of discovering a whole new population of transient sources. In this project you will take data obtained by survey experiments from a world class radio telescope, either LOFAR or MeerKAT, and search for new transient sources on timescales ranging from seconds to months. You will process these data using our successful transient detection pipeline and help develop new techniques with our team.

OBJECTIVE: The key goal of this project is to search for and identify transient and variable sources in a radio image dataset by applying existing techniques developed for other datasets. The second objective is to develop and trial new techniques to filter transient candidates. The student will learn to process radio images and how to handle systematic effects in these data.

PREREQUISITES: Some knowledge of Python is preferred.

RESOURCES: The student will be connecting to computer resources in Amsterdam, so a standard computer or laptop is sufficient. Linux or OS operating system is ideal; however, there will be alternative options for Windows users.

Neutron stars contain matter at supranuclear densities – conditions that may lead to quark deconfinement and the formation of stable states of strange matter.  We study this by measuring neutron star mass and radius, which depend directly on the nature of the matter in the stellar core.  There are several ways to do this, but our group specializes in using relativistic ray-tracing to model X-ray emission from the neutron star surface. We use data from rotation-powered and accretion-powered X-ray pulsars, as well as for neutron stars that undergo Type I X-ray bursts (triggered by explosions in an accreted ocean).
  Recently we have working intensively on mass-radius measurement for bursting stars where the burning is detectably non-uniform.  Part of the surface gets hotter than the rest (for reasons that are not yet understood), such that the X-ray emission varies as the star spins.  But what happens if the hot spot forms, for example, at the rotational pole?  We would not see any pulsation, but the emission across the stellar surface would still be non-uniform.  Could this bias attempts to recover mass and radius?

OBJECTIVE: The objective of this project is to investigate potential bias in the mass and radius measured for bursting neutron stars, caused by the presence of non-uniform burning, for cases where we are unable to detect this directly via the presence of pulsations.   You will generate simulated X-ray burst data for a range of ‘undetectable hot spots’, and then analyse them to recover mass and radius, using the modeling techniques that are currently standard in the field. By comparing the recovered values to the input values, you will quantify the degree to which measurements may be biased by non-uniform surface emission.  Your results will directly impact both current analysis, and observing plans for future X-ray telescopes like Athena.

PREREQUISITES: No prior knowledge of the field is required, but experience with programming in Python and working in a Linux environment would be useful.


RESOURCES: A standard laptop is sufficient, ideally with Linux or OS operating system; but if necessary we can provide a laptop.  You will also make use of our local cluster.

When two neutron stars merge, they emit across the full electromagnetic spectrum, as well as in other messengers such as gravitational waves, neutrinos, and cosmic rays. The processes that govern the merger and give rise to all this emission are extremely complex, and even when a set of computer simulations has been done, are still hard to understand. An essential tool to help us understand the complex outcomes and processes is visualization of the simulations.

OBJECTIVE: This project will be focussed on visualizing simulation data from binary neutron-star merger simulations. These simulations include general relativity, gas dynamics, nuclear and neutrino effects, and magnetic fields. You will use a visualization software that we develop in the group and look into finding the best way to visualize the physics happening in these extreme collisions. This will include looking at how heavy elements like gold can be made and how electromagnetic radiation in the form of kilonovae and gamma-ray bursts can be generated.

PREREQUISITES: Knowledge in coding with Python.

RESOURCES: A normal computer/laptop should suffice, with a working Python installation.

Observations have shown that field stars are not always single; many develop in pairs and/or higher-order systems. The ones that reside in close binaries are of particular interest because, apart from the intrinsic stellar properties, the evolution depends sensitively on the interactions between the system’s stellar components. Among the various interaction processes, mass transfer (MT), in which one star (donor) transfers mass to its companion (accretor) via Roche-lobe overflow (RLOF), will have by far the greatest impact on the system's subsequent evolution.
Mass transfer in close binaries has been the focus of many studies during the last decades. However, the majority of them is constrained in analytical models which are based on various assumptions. Common assumptions are that the donor's spin velocity is equal to the orbit's angular velocity, i.e. the donor is synchronous with the orbit, that the mass transfer occurs instantaneously and the all mass ends on the accretor star. Despite the various insights of previous analytical studies, the hydrodynamical nature of the problem demands hydrodynamical simulations in order to reveal the details and the future of the mass stream.

OBJECTIVE: The main objective of this project is to describe qualitatively and quantitatively the dynamical behaviour of the mass stream in the case of sub-synchronous, synchronous and super-synchronous donors. To do this, the student will perform hydrodynamical simulations of mass transferring binaries, analyse the system's orbital evolution and compare the results with recent studies using different techniques. The student will learn the basic principles of Smooth Particle Hydrodynamics (SPH) techniques and get valuable experience in computational astrophysics.

PREREQUISITES: Rudimentary knowledge in coding with Python is beneficial. Some basic experience with Linux is also helpful, but not required.

RESOURCES: The student will be connecting to computer resources in Amsterdam, so a standard computer or laptop is sufficient. Linux or OS operating system is ideal

OB runaway stars are massive stars moving with a high space velocity away from the place where they were born. Two scenarios have been proposed to explain how they were ejected: (i) through dynamical interactions in a young and dense stellar cluster; (ii) due to a supernova in a massive binary system. A massive star has a significant impact on its environment via its intense UV radiation field, dense stellar wind and powerful supernova. Thus, when they move out of the Galactic plane into lower density regions, they are expected to play an important role in the thermal and chemical evolution of the Galaxy.

OBJECTIVE: Thanks to the unique astrometric dataset that is currently being produced by the ESA Gaia satellite, a large number of OB runaways has been identified. The aim of this project is to trace back known OB runaways to their birth location, measure the time it took to travel to their current position (kinematical age), and investigate whether they have been ejected by the dynamical interaction or binary supernova scenario.

PREREQUISITES: Some experience with Python would be helpful.

RESOURCES: The student will use a terminal in the student room and access the Gaia Data Release 3 database through the ESA Gaia archive.