The projects

Dying young and frustrated? Finding the youngest radio galaxies 

Supervisor:  Joe Callingham (J.R.Callingham@uva.nl)

Project type:  Observational Astrophysics

Our understanding of how a radio galaxy evolves remains embarrassingly incomplete. In particular, astronomers struggle to understand the first stages of radio galaxy evolution, with far too many small radio galaxy precursors identified relative to the number of giant radio galaxies. One competing idea is that these galaxies are not small due to youth but because they are confined to small scales by a dense environment. In this project, we will use the International LOFAR telescope, in particular data produced by the LOFAR all-sky survey (LoTSS) and its lowest frequency counterpart, to select the newest young radio galaxy candidates. You will also reduce data from the Australia Telescope Compact Array. Such observations will allow you to test whether their radio spectra is consistent with these sources being a young galaxies or if the sources have stopped growing due to interaction with a dense environment. Additionally, you will also look at the high-resolution data projects coming from the international baselines of LOFAR. In this project, you will gain experience in using Python, supercomputers in reducing LOFAR data, and Bayesian reasoning in model differentiation.  Some python coding experience is a positive.

Why are you so bright radio star? 

Supervisor:  Joe Callingham (J.R.Callingham@uva.nl)

Project type:  Observational Astrophysics, Theoretical Astrophysics

Magnetospheric processes seen on gas giants such as aurorae and circularly polarized radio emission have recently been detected coming from radio stars. This is unexpected. In this project, you will characterise the types of stars we have detected, understand the origin of their radio emission, and model the type of magnetic fields that are necessary to drive such emission. Through you will gain experience in using Python, supercomputers in reducing LOFAR and GMRT data, and will complete regular visits to ASTRON (Netherlands Institute for Radio Astronomy). The project is flexible in taking it in a theoretical or observational route.  Some python coding experience is a positive.

X-ray messages from the accretion disk around a supermassive black hole 

Supervisor:  Elisa Costantini ( E.Costantini@sron.nl)

Project type:  Observational Astrophysics

Active galaxies host at their center a massive black hole that accretes matter under the form of an accretion disk. The energies involved are so high that the accretion disk shines bright in the X-rays. This provides us with precious tools to understand how accretion, and the whole environment near the black hole, behaves. In this project you will study the spectral and timing properties of brand new data just acquired from the ESA satellite XMM-Newton of a bright active galaxy. 

Mining for Massive Stars with Gaia, MeerKAT & ASKAP

Supervisors:  Mitchel Stoop (m.p.stoop@uva.nl) + Jakob van den Eijnden (a.j.vandeneijnden@uva.nl) + Lex Kaper/Alex de Koter

Project type:  Observational Astrophysics

Massive stars are born with a mass exceeding ~ 8 solar masses. They only make up a small fraction of all stars in the night sky, but they play a central role in a wide range of astrophysical processes. Massive stars have abundant ultraviolet radiation and will end their life in a powerful supernova. Every year, a massive star gradually ejects the mass-equivalent of Earth as hot plasma into space, known as a stellar wind. The energy supplied by these processes will shape their birth regions and the surrounding interstellar medium. To better understand such processes often requires combining data from multiple telescopes.

In this project, you will use the revolutionary Gaia space telescope and state-of-the-art radio telescopes (MeerKAT in South Africa and ASKAP in Australia). Gaia has observed more than 2 billion stars to accurately determine their position, motion, distance, and optical flux. MeerKAT and ASKAP have recently performed the deepest radio-frequency surveys of the Southern sky. You will search in (and combine) data from Gaia, MeerKAT, and ASKAP to systematically identify massive stars and search for their radio emission. This will give new insights into stellar winds at unprecedented sensitivity and scale and allow us to better understand the influence of massive stars on larger scales.

Searching for transient and variable radio sources in “Big Data”

Supervisor: Antonia Rowlinson ( b.a.rowlinson@uva.nl)

Project type:  Observational Astrophysics, Applied Data Science

Since ancient times, astronomers have been interested in the changing astronomical sky. Variability studies initially started in optical, finding sources like supernovae and variable stars. As new facilities came online, astronomers were able to extend their studies to multiple wavelengths – from gamma-ray to radio. We now know that our Universe is highly dynamic and the sources we observe enable us to probe fundamental physics.

We have now entered the information age, where multi-wavelength facilities are able to obtain vast amounts of data. It is no longer feasible for us to manually search images for variability. Various teams have been developing pipelines and filtering strategies to manage this big data. 

 In this project, we will use a large radio image dataset, containing many snapshot images, and process them through our LOFAR Transient’s Pipeline. We will develop a method to automatically reject extended sources from the analysis steps as these interfere with our statistics and give false positive detections. We will then quantify transient and variable behaviour in the field and further analyse transient candidates to determine their progenitors.  Knowledge of Python would be very useful. 

Diffuse X-ray emission from stellar cluster Westerlund 1

Supervisors: Jacco Vink (j.vink@uva.nl), Manan Agarwal (m.agarwal@uva.nl)

Project type:  Observational Astrophysics

There is a renewed interest in the high-energy emission from stellar clusters as they may be important sources of cosmic rays. This was recently confirmed by gamma-ray observations from LHAASO and H.E.S.S. indicating that particles are being accelerated to TeV energies. The idea is that the energy for the cosmic-ray acceleration comes from the shock-heated gas from the stars, which then leads to a fast shock wave (the collective cluster wind), which then accelerates the particles. However, there are various estimates of the energy in the hot gas of the cluster.

 For this project the student will analyze a recent very deep observation of the  Westerlund 1 cluster obtained by the Chandra X-ray observatory. The X-ray emission from the stars will then be separated from the diffuse gas surrounding the stars, and then spectral analysis will be performed using state of the art non-ionization equilibrium codes. Important it to deduce the available thermal energy in the gas, which needs to be compared to the energy need to explain the gamma-ray flux from Westerlund 1.

Using machine learning to emulate Comptonized emission around black holes

Supervisors:  Ben Ricketts (B.J.Ricketts@uva.nl), Daniela Huppenkothen (D.Huppenkothen@uva.nl)

Project type:  Theoretical astrophysics, Applied Data science

Highly energized electron gas close to an accreting black hole (known as the “corona” or crown of the black hole) emit high-energy photons in a process called Comptonization. This process heats up the electron gas as well as up scatters photons to higher energies as they collide with electrons in the gas. The resulting emission cannot be modelled analytically, necessitating costly simulations which presents difficulties when trying to model the emission we see from black hole systems. This project aims to use machine learning to model these simulations by learning the relationship between input parameters that describe the gas’ geometry and properties and the escaping emission. No knowledge of machine learning or Comptonization is required. Knowledge of python is required due to the coding required in this project. This project can focus on extending the machine learning to learn more complex outputs or making the coronal simulation more complex depending on what you are most interested in.

Hunting the mysterious companion of 25 Ori, a rapidly rotating Be star
Supervisors: Julia Bodensteiner  (j.bodensteiner@uva.nl ) & Alex de Koter

Project type:  Observational Astrophysics
20% of the galactic B-type stars are so-called classical Be stars, that is rapidly rotating stars surrounded by a circumstellar decretion disk, which causes strong emission lines in their spectra (and hence led to their name). Despite their prevalence, many questions are still open about Be stars, which include the origin of their high rotation rates. A recent, exiting hypothesis is that Be stars could be post-interaction binaries, where transfer of mass and momentum of a (now dim or even unseen) companion has spun them up to high enough speeds that they can form a disk around their equator. 
If Be stars truly form through mass transfer, many of them should still be in a binary system with the donor star, that could either be an envelope-stripped star or, if it had time to evolve, a compact object. As detecting such companions directly in the stellar spectra is very difficult, only a handful of Be binary systems are known. To better understand the potential binary history of Be stars, more such post-interaction binaries have to be detected and characterized.
In this project, the student will look at 25 Ori, a bright Be star of spectral type B1Ve. While no companion has been detected around 25 Ori so far, time series of optical spectra show variability that could indicate a hidden companion. You will use these spectra as well as python codes to investigate the variability in the spectrum, to measure the motion of Be star, to identify possible signatures of the hidden companion, and, if detected, investigate the companion’s properties.

Magnetic mountains: location is everything

Supervisor: Oliver Porth (O.J.G.Porth@uva.nl)

Project type:  Theoretical Astrophysics, Computational Astrophysics

Some of the brightest galactic X-ray sources are the so-called X-ray binaries.  Here the energetic radiation is emitted by heated gas which revolves around and falls towards a compact object (a black hole or a neutron star).  In contrast to black holes, neutron stars have a hard surface and roughly 50% of the observed radiation is thought to be released when matter crashes into the stellar surface.  There are many open questions about how matter lands and spreads over the star and answering them is key to understanding how the different classes of neutron stars evolve in our universe.  
One aspect of this problem is the formation of magnetically supported mountains on the stellar surfaces.  In essence, as matter falls onto the star, it cannot expand sideways due to the strong magnetic field (ionized gas cannot cross field lines) and it piles up as a mountain.  The expected mountain heights are <~100 m and they will eventually collapse when the magnetic support fails.  The properties of the mountains (how high, how massive) are not only interesting for the X-ray emission from the surface, the mountain on the rapidly rotating star could also be an important gravitational wave source.  

In a bachelor project last year [https://scripties.uba.uva.nl/search?id=record_54590], we have already numerically investigated how mountains grow in a very simplified 'slab' geometry.  In this project, we want to explore the more realistic case of a spherical star which will allow us to compare properties of mountains forming at different locations on the star.  When does the mountain collapse?  What is the maximum height and mass you can support?  How does this depend on the rotation of the star, the geometry of the magnetic field and the properties of the dense matter?   This project will be intense, but its a great start into numerical simulations using (magneto-) hydrodynamics and for getting a flavor of front line questions in theoretical astrophysics.  

Go with the flow -- the fate of high-energy particles in black hole flares

Supervisor:  Oliver Porth (O.J.G.Porth@uva.nl)

Project type:  Theoretical Astrophysics, Computational Astrophysics

The galactic center black hole (SgrA*) is known for its daily flaring activity in IR, X-ray and radio bands.  During a large flare, the X-ray flux can increase by up to 100 fold for timescales of less than an hour.  There is strong evidence that the rapid flares come from the direct vicinity of the supermassive black hole and the flares are caused by synchrotron emission from relativistic electrons.  Similar behavior is found in other accreting black holes, but the vicinity of the Galactic center makes it a perfect test-bed for our theoretical models.  Furthermore, thanks to the Event Horizon Telescope, we can directly image the black hole shadow which gives us a great handle on the properties of the accretion flow (and its only a matter of time until we catch a flare in an EHT observation).  

To model these flares, it is commonly assumed that the emitting particles remain confined to a spherical blob that is put on an orbit around the black hole.  Since they navigate through a turbulent accretion flow however, a key question is whether in nature the particles will actually remain together for the observed duration of the flare (~50 minutes) or whether they will be diffused and sheared out in the flow.  In this project, you will investigate what happens to the emitting particles by injecting tracer particles into a general relativistic magnetohydrodynamic simulation (GRMHD) of the accretion flow.  Tracing particle trajectories allows us to challenge the simple model assumptions and see for example when particles simply co-rotate and when they are ejected into an outflow (jet). 
A clear outcome of the project would be an understanding how long 'the flaring region' exists as a function of the initial size of the blob but there are a number of interesting questions we could address, for example how many protons get mixed into the particle acceleration region or how the properties of the particle cloud depend on parameters of the system such as black hole spin.  
The idea of the project is that you will work with a set of pre-existing GRMHD simulations and you will re-run parts of the simulations with injected test-particles.  You will design the injection recipes and analyze the particle data.  As part of the project, you will learn to operate state-of-the-art numerical codes on parallel compute clusters which should prepare you for computational projects in the future.  To do this project, you should be excited about computational methods and not be afraid to enter uncharted territory!  

An analytical model for a gaseous disk around B-type stars

Supervisors: Alex de Koter (a.dekoter@uva.nl ) & Julia Bodensteiner

Project type:  Observational Astrophysics

Be-stars are an enigmatic group of B stars that show emission lines in their optical spectrum (hence the suffix e). It is well established that the emission originates from a circumstellar gaseous disk. However, little is known about the origin and properties of this disk. Recent breakthroughs suggest that the Be phenomenon is associated with binary interactions: a more massive primary star transfers mass- and angular momentum to a close companion that starts to outshine the primary, spins up and creates a circumstellar disk.

For some Be stars it is observed that the disk is transient, i.e., it disappears and reappears over time. We have recently collected multi-object spectroscopy of three such systems (V519 Per, HD 165285, BD+62300) in the context of the HONEYBees Survey with the Mercator telescope. The goal of this project is to constrain the mass of the Be-disk, which may be give clues as to the disk’s origin.

The student will isolate the disk emission in spectral lines by comparing epochs when the star featured a disk and when not. Then, the student will use python and jupyter notebooks to develop an analytical disk model that allows to predict spectral line emission and use this model to estimate the disk mass.

A novel mass-determination method for young clusters

Supervisors: Mitchel Stoop & Alex de Koter (a.dekoter@uva.nl )

Project type:  Observational Astrophysics

Young galactic clusters are probes of the present-day star-forming activity of the Milky-Way galaxy and for an important part control the dynamical and thermal state of the galactic disk. To estimate how much star formation takes place it is essential to be able to determine the masses of newly formed clusters.  In the literature, several methods are employed to constrain clusters masses, however, each has their drawbacks.  Here, we propose to pursue a completely novel idea to measure cluster masses using astrometric data obtained with the revolutionary Gaia space telescope.

Gaia has observed more than 2 billion stars to accurately determine their position, motion, distance, and optical flux. This makes Gaia ideal to study the dynamics of stellar populations.

In this project, the student will analyze 15 young massive Galactic clusters in the Milky Way (including the famous clusters M8, M16, M17, and M20). For each of these systems, a set of reliable cluster members has already been identified. Using the transverse velocity properties of these stars and application of the virial theorem allows for a new way to ‘weigh’ the mass of the entire cluster.

The student will process Gaia DR3 data using python and jupyter notebooks. Cluster masses will also be assessed with common methodologies to confront to the new method. Literature will be consulted to collect previous mass-estimate attempts, to include in this comparison.

Exploring fast radio burst variability with machine learning

Supervisors:  Dirk Kuiper (d.kuiper@uva.nl), Daniela Huppenkothen (d.huppenkothen@uva.nl) and Ziggy Pleunis (z.pleunis@uva.nl)

Project type:  Applied Data Science, Observational Astrophysics

In this project, we will use machine learning techniques to study the morphology of fast radio bursts (FRBs) as a function of time and radio frequency. FRBs are now known to originate in distant galaxies, but their physical nature remains mysterious. The short durations and extreme luminosities imply a compact source and high energy density. For that reason, most models focus on a neutron star or black hole progenitor - with the magnetically powered neutron stars known as "magnetars" being a particularly compelling model. However, both repeating and apparently non-repeating FRB sources are known, and we've found FRBs in a variety of surprising environments. Can they all be from magnetars, or is the mystery even richer than a single progenitor model can explain? A previous MSc project developed new machine learning techniques to probe the temporal and spectral properties of FRBs, and in this bachelor project, we will apply these new techniques to explore the properties of different repeating FRBs observed with the FAST telescope. Do they all have the same properties? Or can we find clues to the differences between them, which may in turn give us clues about their progenitors? The student will gain experience with both radio data and modern machine learning techniques.

Developing robust statistical techniques for the determination of chromatic periodic activities in repeating fast radio burst sources

Supervisors:  Ziggy Pleunis (z.pleunis@uva.nl) and Daniela Huppenkothen (d.huppenkothen@uva.nl)

Project type:  Applied Data Science, Observational Astrophysics

Fast radio bursts (FRBs) are one of the most exciting mysteries in contemporary astrophysics. These impulses of radio waves last only a fraction of a second but are bright enough to be detectable from halfway across the Universe. They were discovered in 2007 and have puzzled astrophysicists ever since: What sort of object can produce this amount of energy in such a short time? Various kinds of neutron stars and black holes are likely candidates because of the high energy density in their surroundings. One active repeating source, FRB 20180916B, exhibits a chromatic periodic activity, that provides strong constraints on possible models for the source: the source is active in a few-day window every 16.4 days, first at higher and then at lower frequencies. Monitoring observations of other repeating FRB sources can reveal whether or not other sources show similar behavior, but the cadence of observations can strongly bias the range of periodicities we are sensitive to. In this project, the student will develop new statistical techniques for timeseries analysis that they apply on data from the CHIME/FRB experiment and FRB follow-up observations conducted in the AstroFlash group and that will be used to schedule future observations. 

Predicting rates of fast radio transient sources using binary population synthesis

Supervisors:  Silvia Toonen (s.g.m.toonen@uva.nl) and Ziggy Pleunis (z.pleunis@uva.nl)

Project type:  Computational Astrophysics

Fast radio bursts (FRBs) and long period radio transients (LPTs) are two novel classes of fast (milliseconds--minutes) radio transients with disputed origins, though most theories have them produced by different configurations of neutron stars and white dwarfs, isolated or in binary systems. The observed variety in fast radio transients suggests that multiple of the proposed models may actually exist in nature, and it is imperative to know their relative occurrence rates. In this project, the student will simulate a galaxy of single and binary stars to measure the abundance of the kind of systems we think could be producing fast radio transients. The student will get a better understanding of (binary) stellar evolution, running simulations and connecting the results of population synthesis to theories for radio transient emission.

Modelling Escaping Atmospheres of Exoplanets

Supervisor:  Antonija Oklopčić  (A.Oklopcic@uva.nl)

Project type: Theoretical Astrophysics

A significant fraction of exoplanets discovered to date orbit their host stars at very close orbital separations. The upper layers of planetary atmospheres can get heated to temperatures of several thousand degrees, creating pressure gradients that drive supersonic outflows and allow a significant fraction of the atmosphere to escape from the planet. Atmospheric escape and mass loss can have profound influence on the extent, composition, and evolution of close-in exoplanets, and consequently, on the demographics of planetary systems. My group uses a variety of modelling tools to simulate atmospheric escape and make synthetic spectroscopic data, which we then compare with real observations to infer the properties of escaping atmospheres. This project will make use of a large database of pre-calculated spectra to investigate which planets are the most promising targets for conducting new spectroscopic observations.

Investigating Accretion Physics and Compact Objects in the Ultraviolet

Supervisor: Rudy Wijnands (R.A.D.Wijnands@uva.nl)

Project type:  Observational Astrophysics

Accretion is a fundamental and fascinating process in astrophysics, driving extreme energy releases in systems ranging from stellar-mass compact objects (white dwarfs, neutron stars, black holes) to supermassive black holes. The ultraviolet (UV) wavelength regime provides a unique view of these energetic environments, where accretion disks, jets, and other high-energy processes dominate. Despite its importance, the UV remains an understudied regime due to the absorption of UV radiation by Earth’s atmosphere and the high cost of space-based instrumentation.

Fortunately, UV facilities do exist. The UV and Optical Telescope (UVOT) aboard the Swift satellite, with over 20 years of data, provides an unparalleled opportunity to study the long-term behavior of accreting systems. These include accreting white dwarfs, neutron stars, stellar-mass black holes in binary systems, and supermassive black holes in active galactic nuclei (AGN). By analyzing this extensive dataset, we can uncover variability patterns and long-term trends that reveal key insights into the physical processes driving accretion.

Project Details

• Exploring compact objects: Investigate accreting white dwarfs, neutron stars, stellar-mass black holes, and supermassive black holes to understand how they power their extreme emissions and how these emissions evolve over time.
• Studying long-term UV variability: Analyze two decades of UVOT data to identify variability trends, periodicities, and flaring events that reflect the physics of accretion disks and compact objects.
• Applying Python tools: Use our in-house, state-of-the-art Python-based pipeline, specifically developed by our team, to process UVOT data, identify variable sources, and extract meaningful physical insights.
• Independent research focus: Work independently on a carefully selected UVOT dataset, focusing on a specific subset of compact objects or accretion-related phenomena.
• Collaboration opportunities: Collaborate with the supervisor and other group members, participating in weekly one-on-one meetings and contributing to group discussions.
• Python knowledge: Familiarity with Python is highly recommended, as the pipeline heavily relies on it for data analysis and visualization.
• Interest in compact objects and accretion physics: Enthusiasm for understanding the fundamental physics of extreme astrophysical systems is essential.

Preparing for Atmospheric Science with an Upcoming Ground-Based Astronomical Near-UV Telescope

Supervisor:  Rudy Wijnands (R.A.D.Wijnands@uva.nl)

Project type:  Observational Astrophysics, Instrumentation

We are building a new ground-based near-UV telescope, expected to become operational in about a year. This facility, optimized for near-ultraviolet (NUV; 300-350 nm) observations, will support both astronomical and atmospheric research. The project will explore the telescope’s potential for studying ozone layer variability and auroral emissions, expanding its use beyond traditional astronomy.

The NUV sensitivity of the telescope makes it ideal for investigating how Earth’s atmosphere interacts with solar and cosmic radiation. NUV light triggers photochemical reactions critical for ozone dynamics, and auroral emissions arise from energetic solar wind particles interacting with Earth’s magnetosphere, providing insight into magnetospheric processes.

Project Details

• Telescope context and applications: The student will explore the scientific potential of the NUV telescope for atmospheric studies, focusing on the physical processes in ozone layer dynamics and auroral emissions, as well as its role in future astronomy observations.
• Ozone layer studies: Study the interaction of near-UV radiation with the ozone layer, focusing on photodissociation and its role in ozone variability. The student will assess how the telescope can monitor nocturnal ozone depletion and recovery, complementing satellite data.
• Auroral emissions in the NUV: Investigate the origin of auroral emissions in the NUV, including solar wind particle interactions with the atmosphere, and evaluate how the telescope can provide insights into energy deposition and ionospheric heating.
• Actual work: The student will conduct a literature review and explore the underlying physical models related to ozone layer dynamics and auroral emissions. They will also develop observational strategies, calibration methods, and data collection techniques for the telescope’s future use in atmospheric studies. Additionally, the student may identify potential improvements or modifications to the telescope’s design to better suit atmospheric studies without compromising its astronomical capabilities.
• Independent research focus: The student will select one of the two main themes (ozone or auroral emissions) for independent research, guided by the supervisor.
• Collaboration: The student will participate in weekly one-on-one meetings with the supervisor to discuss progress and delve into atmospheric and magnetospheric physics. Additionally, the student will contribute to team discussions and group meetings, fostering collaboration within the research group.

The Survival of the fittest - Interstellar hydrocarbons edition

Supervisor: Alessandra Candian (A.Candian2@uva.nl)

Project type:  Computational Astrophysics

We live in a Molecular Universe. More than 300 molecules have been identified in the harsh conditions of the interstellar medium where they can survive destruction by energetic photons and cosmic rays.  In this project, you will study the chance of survivability of cyanonaphthalene molecule, a large organic molecule, in regions of star formation. You will create a simple model that takes into account the different mechanisms affecting the molecule's lifetime (for IR emission, ionization, photodissociation) and evaluate under which interstellar conditions this molecule can exist.  Requirements:  Basic command of Python. Knowledge about chemistry is not needed.

Investigating Multi-Frequency Emission in Sagittarius A*

Supervisors:  Rittick Roy (R.Roy@uva.nl), Leon Sosapanta Salas (l.d.sosapantasalas@uva.nl), Sera Markoff (S.B.Markoff@uva.nl)

Project type:  Theoretical Astrophysics, Computational Astrophysics

Polarization measurements by the Event Horizon Telescope (EHT) of the Galactic Centre supermassive black hole Sagittarius A* (Sgr A*) suggest the presence of a  dynamically strong magnetic field, the characteristic of a magnetically arrested  (MAD) state. In this regime, the magnetic field can become strong enough to  suppress the accretion flow, leading to episodic flux eruptions that could explain observed flares. Salas et al. (2024) introduced two temperature (2T) MAD general  relativistic magnetohydrodynamic (GRMHD) simulations of Sgr A*, which evolve the temperatures of ions and electrons and include electron radiative cooling.  Recent observations by von Fellenberg et al. (2025) detected the first mid- infrared (MIR) flare from Sgr A*, highlighting the role of synchrotron cooling as a significant process. Importantly, non-thermal electrons are required to  reproduce the observed spectrum between 12–100 THz and to recover the  correct spectral index of these MIR flares. Observations at 228 GHz suggest a  possible counterpart flare in the mm-radio lagging the MIR flare. The goal of this project is to investigate the relationship between magnetic flux eruptions and peaks in light curves  across a range of frequencies (43, 86, 214, 228, 230, 345, and 1360 GHz).  Furthermore, the project aims to identify potential time lags between emission at these various frequencies, offering valuable insights into the physical mechanisms  driving variability in Sgr A*. This research will involve using python in Jupyter notebooks to analyse simulation data, comparing synthetic light curves with observational data, and developing  a deeper understanding of the dynamics of accretion flows in the MAD state.

Hunting for stellar bow shocks with MeerKAT and ASKAP

Supervisors:  Jakob van den Eijnden (a.j.vandeneijnden@uva.nl) and Lex Kaper (l.kaper@uva.nl)

Project type:  Observational Astrophysics

Massive stars powerfully impact their surrounding interstellar medium, both during their lifetime and in their explosive death. During their relatively short lives, massive stars can launch powerful stellar winds that energize and shape their environments, potentially even powering the acceleration of charged particles to extreme energies. In this project, you will search for potential sites where these stellar winds impact the ISM, focusing specifically on runaway massive stars: stars that move faster than the speed of sound through surrounding space, creating a bow shock akin to a ship on the seas. More specifically, you will search for radio emission of these bow shocks in state-of-the-art survey data from the MeerKAT and ASKAP telescopes. Depending on your interests, the project can either focus on the automization of these searches or on the physical implications of the detected radio shocks. In either case, your project will contribute to expanding the small but growing number of radio-detected massive star bow shocks.

Statistical sampling in neutron star pulse profile modeling

Supervisors:  Anna Watts (A.L.Watts@uva.nl)  & Mariska Hoogkamer

Project type:  Applied Data Science

Rotation-powered millisecond X-ray pulsars emit X-rays as return currents heat the magnetic polar caps.  Applying relativistic ray-tracing models allows us to derive = not only the properties of the hot magnetic poles but also the neutron star mass and radius – which depend on the nature of the supranuclear density matter in neutron star cores.  Our group are currently applying this technique to data from NICER, the Neutron Star Interior Composition Explorer, a telescope on the International Space Station.  Our computations involve the use of large-scale open-source statistical sampling packages to derive the most probable values of the model parameters, and the results can vary depending on the settings chosen way that these samplers explore the probability space.   Different samplers can also have very different computational costs, which is important when our production runs can cost up to a million hours on the national supercomputer Snellius!  Currently we have two well-known samplers  – MultiNest and Ultranest –  being used with our ray-tracing simulation code X-PSI, and are comparing their performance.  In this project you will couple a third very widely-used sampling package – Dynesty – to our software, test it, and carry out cross-comparisons on test problems. In doing so you will help us to find the most efficient – and the most robust – way to measure neutron star properties!

Why so weird? Pulse profile modeling for the uncooperative rotation-powered millisecond pulsar PSR J1231-1411.

Supervisor:  Anna Watts (A.L.Watts@uva.nl) & Mariska Hoogkamer

Project type:  Theoretical Astrophysics

By modeling X-ray data from the Neutron Star Interior Composition Explorer (NICER), we are able to measure the masses and radii of neutron stars, and the properties of their hot magnetic polar caps.   So far we have done this successfully for three neutron stars – and less successfully for a fourth, PSR J1231-1411.   Even with very intensive runs on the national supercomputer, our relativistic ray-tracing models failed to deliver converged results.  Only by restricting the the parameter space were we even able to check whether this source was consistent in its behaviour with the others.   Before we invest any more computing or observing time on this source we would like to know the answer to the following questions:  are our attempts to model this source doomed by properties of the data set, and degeneracies in the models?   Or is this something that can in theory be solved, and if so what is the best strategy?   You will explore these questions using both the output from our existing analysis, and by generating simulated data sets to test your hypotheses about why this source has proven to be so uncooperative. In doing so you will help to determine our future plans for this pulsar.

GPU-accelerated magnetohydrodynamics

Supervisors: Philipp Mösta ( P.Moesta@uva.nl) , Sara Azizi (S.Azizi@uva.nl)

Project Type:  Computational Astrophysics

This project will involve porting and profiling individual computation kernels for our GPU-GRMHD code GRaM-X. GRaM-X is a dynamical-spacetime general-relativistic magnetohydrodynamics code for simulation binary neutron-star mergers and supernova explosions. The project is flexible and can be focused on performance testing and optimization of existing modules of the code for specific GPU architectures or developing new physics modules (e.g. neutrinos, equation of state, magnetic fields). The former will give the student experience working with state-of-the-art GPU systems and gain insights into modern GPU programming while the latter also involves algorithm development for computational physics in astrophysical magnetohydrodynamic simulations.

Machine Learning Identification of Gaia Exoplanet Candidates

Supervisor: Gudmundur Stefansson (G.K.Stefansson@uva.nl)

Project Type: Applied Data Science, Observational Astrophysics

Through its astrometric monitoring of the whole sky, Gaia is revolutionizing our understanding of numerous areas of astrophysics. For exoplanet science, Gaia is expected to detect hundreds if not thousands of exoplanets especially at intermediate orbital distances which have been relatively poorly probed for planets. However, close-to-equal-mass binary stars can masquerade as planetary signals, and can require observationally expensive follow-up observations to confirm or rule out. In this project, we will investigate using machine learning classification methods to test if we can better validate and/or prioritize Gaia exoplanet candidates for further follow-up observations. Knowledge of python for this project is required.

Improving the determination of the metallicity of  hot-gas giant exoplanet  atmospheres with JWST

Supervisor:  Jean-Michel Désert (J.M.L.B.Desert@uva.nl)

Project type:  Observational Astrophysics

This project aims to improve the accuracy of metallicity measurements in hot gas giant exoplanet atmospheres using data from the James Webb Space Telescope (JWST). The student will work with a radiative transfer code applied to JWST spectra. By mapping atmospheric characterization methods in various conditions, we aim at better understanding uncertainties and inaccuracies in metallicity estimates. The goal is to obtain more precise interpretations of JWST exoplanet observations.