The 2022 programme is not closed. Please check again in February 2023 for next year's summer programme.

Oxford Astrophysics will run a summer research programme for undergraduate physics students again in Summer 2022. The selected students will work with a supervisor in the department, usually a postdoctoral researcher or lecturer, on a self-contained research project. The programme will also include lectures on current astrophysics topics. Students will be encouraged to take part in department life (depending on restrictions at that time), joining researchers for coffee, discussions and seminars (virtually or in person).

The projects run for typically 8 weeks, nominally from 4 July to 26 August. The duration may be adjusted slightly to be shorter or longer, or to accommodate summer travel. Students will be paid as employees of the University, receiving a payment of £10.50 per hour (subject to tax and National Insurance deductions). Students are normally expected to work full time on their project, but hours can be discussed with your supervisor.

In the event that the COVID pandemic prevents us from carrying out the programme in person, measures will be put in place to facilitate remote work and interaction, as we were able to do last year. In this case we will make sure that the computing resources needed for the selected projects are available to all selected candidates.

Application instructions, and the list of projects offered for 2022 can be found below. Please check the eligibility criteria below before applying. The window for applications is now closed.

Eligibility

Students currently in third year of a relevant undergraduate degree are eligible to apply. Students who have completed a 3-year undergraduate degree and are now taking a taught Masters course are also eligible, as long as they are not in their final year. Applications are welcome from institutes outside of Oxford. Unfortunately, due to UK visa regulations, we are only able to accept applications from candidates who do not require a visa to work in the UK. EU students currently in the UK who have been granted Pre-Settled status are also welcome to apply along with current students in the UK on a Tier 4 visa that allows vacation employment. If you have queries about your personal circumstances, please get in touch with ashling.gordon@physics.ox.ac.uk.

How to apply

The window for applications for the 2022 programme is now closed.

Projects offered

  • Likelihood-free (Simulation-based) inference for future weak lensing surveys
    Supervisor:
    Arrykrishna Mootoovaloo
    Description: Existing sampling techniques such as Markov Chain Monte Carlo (MCMC) method require many forward simulations to reconstruct the full posterior distribution of both the cosmological and nuisance parameters. These simulations can be computationally expensive, and we expect future weak lensing analyses to have hundreds of nuisance parameters. This suggests that we might need even more MCMC samples to reconstruct a faithful posterior distribution. With a view to mitigating the complexity of these types of analyses, recent approaches have proposed techniques which combine data compression and likelihood-free inference, see for example,
    Alsing et al. 2018. However, these techniques work well for low-dimensional problem (around 10) and the main objective for a robust and principled analysis would be to develop scalable algorithms for future weak lensing surveys. We will start the project with a simple Gaussian Linear model and scale the idea to, for example, the recent KiDS-1000 analysis. Contingent on the amount of work we cover (not necessarily during the 8-weeks period), it will also be possible to publish our results in a journal.
    Recommended experience: Python, Numerical/Analytical Linear Algebra, sound knowledge of astrophysics/cosmology, some knowledge of deep neural networks
  • Mapping the vorticity field from the angular momentum of pair of galaxies
    Supervisor: Carlos Garcia-Garcia
    Description: We want to map the projected vorticity field and compute its angular correlation function This field is only sourced by non-linearities in the standard cosmological model, and will probably have a low signal. However, it is interesting to know if we can detect it with this technique. In this project, the student will have to match gravitationally linked pairs of galaxies, and estimate their angular momentum using their redshift difference, which will be mainly driven by their proper motion. We will use the public spectroscopic galaxy catalogs of BOSS DR12 or eBOSS LRGs. Once the angular momentum field is constructed, the student will have to project it onto the celestial sphere, compute its correlation function, and compare its result with theoretical expectations for cosmic vorticity. The project will involve coding, mainly in Python, and the use of different codes of interest in cosmology and data analysis.
    Recommended experience: Knowledge of physics and statistics and coding (or willingness to learn to code) in Python.
  • Dark matter in galactic outskirts
    Supervisor: Martin Rey
    Description: Modern cosmology predicts the existence of significant amounts of invisible, “dark” matter in our Universe. Particles of dark matter interact gravitationally with the rest of the Universe, clumping together to form spherical haloes surrounding visible galaxies. The relationship between the properties of galaxies, which we can observe, with that of their surrounding, invisible dark matter halo is key to constraining our understanding of dark matter. In this project, the student will analyse numerical simulations of structure formation, to better understand how stars and dark matter are co-distributed in the outskirts of galaxies. They will develop and implement new numerical and analytical tools to extract each component’s orbital configuration from the simulations, to map how they reflect each galaxy’s assembly over cosmic time.
  • Probing the atmosphere of a newborn exoplanet with high-resolution spectrometers
    Supervisors: Baptiste Klein, Annabella Meech
    Description: During the transit of an exoplanet, a small fraction of the incoming stellar flux goes through the planet atmosphere. As a result, the spectra collected during that time enclose key information about the composition, temperature and dynamics of this atmosphere. These properties are most robustly retrieved using near-infrared high-resolution spectroscopy, where the extremely fine sampling of wavelength space allows one to resolve the absorption lines from the planet atmosphere. In this internship, we propose to analyse the transit observations of the very young (22 Myr) planet AU Mic b, recently observed with two high-resolution spectrographs: SPIRou, at the Canada-France-Hawaii Telescope (Hawaii), and IGRINS, at the GEMINI South Observatory (Chile). These observations represent a unique opportunity to probe the atmosphere of a baby planet for the very first time, opening the door to exciting new insights into the formation of planets and their early evolution. In collaboration with theoreticians and observers from the University of Oxford, the successful applicant will generate simple planet atmosphere models and compare them with the data using state-of-the-art analysis techniques. This preliminary work will serve as a basis for a publication in astrophysics.
    Recommended experience: Moderate coding ability (python, bash), Basis-to-moderate knowledge in statistics
  • Creating empirical dark matter halo profiles with symbolic regression
    Supervisors: Pedro Ferreira, Deaglan Bartlett, Harry Desmond,Tariq Yasin
    Description: The dynamics of stars and gas (baryonic matter) within galaxies depends on both the baryonic and dark matter density profiles. The latter is often assumed to take a fixed form motivated by simulations, and different profiles are then compared (and their free parameters estimated) by fitting to dynamical data. The aim of this project is to reverse this: to create and assess (an) empirical halo profile(s) from dynamical galaxy data without any input from simulations. We will then see what features of the galaxy the properties of the halo profile depend on, and attempt to determine an empirical mapping between local baryonic and dynamical variables. We will do this using a machine learning technique called symbolic regression, which learns analytic forms for the relationships between variables.

    Recommended experience: Ability to code in python (and willingness to learn machine learning techniques).
  • Studying diverse chemical compositions of exoplanet atmospheres
    Supervisor:
    Chloe Fisher
    Description: By observing exoplanets with ground- and space-based telescopes, we can obtain spectra of their atmospheres. Analysing these spectra and comparing them to physical models can allow us to determine the chemical composition of these planets, which can give us clues about their potential habitability. Modelling the chemical processes occurring in these atmospheres can be challenging, but the theory of chemical equilibrium is well-understood. In this project, we propose using an open-source chemical equilibrium code to study the relationship between the atmospheric composition and parameters such as temperature, metallicity, and carbon-to-oxygen ratio. By considering a wide range of equilibrium atmospheres, we can determine which molecules could indicate the presence of disequilibrium processes. We will also use these compositions to produce atmospheric spectra, which will help us find degeneracies that could prevent confident detections of these molecules. The successful applicant will collaborate with experts in exoplanet atmospheres at the University of Oxford, with the possibility to extend the project further into modelling disequilibrium chemistry and performing data analysis.
    Recommended experience: Moderate programming (python or C++, bash)
  • Scattered pulsars with MeerKAT
    Supervisor: Lucy Oswald
    Description: This project offers a student the chance to develop programming skills suitable for astrophysical research; gain experience of working as part of an international collaboration; and perform completely new measurements on astrophysical data which may lead to publication-quality results. The student can expect consistent support and guidance throughout the project, to enable them to make the best use of the time available. Pulsars are some of the most exciting objects in the Universe: neutron stars with intense gravitational and magnetic fields that rotate and send out a beam of radio waves. They may be used as laboratories to test physics under extreme conditions, and as clocks in space to test the theory of General Relativity and search for gravitational waves. As pulsars rotate, their radio beam sweeps through space like the beam of a lighthouse, so that once per rotation the beam is directed towards the Earth and can be detected as a series of pulses by radio telescopes. The new MeerKAT telescope is expanding our understanding of pulsars with very high quality broad-band observations of their radio emission. However, the pulsar's radio beam must first pass through the gas, dust and plasma of the Interstellar Medium (ISM) before arriving at the telescope. Plasma structures in the ISM can scatter the radio waves so that the shape of the radio pulse profile observed is distorted. By modelling these distortions, we can build our understanding of both pulsars themselves and of the plasma structures causing the scattering. The goal of this project is to investigate and model how scattering in the ISM affects observations of pulsars, made with the MeerKAT telescope as part of the international Thousand Pulsar Array project. The student will learn to use the scatter-modelling software SCAMP-I to measure the scattering properties of pulsars with simple profile shapes. This will be followed by an investigation of extending this scatter modelling to more complex pulse profiles. The student will have the opportunity to develop this investigation along a path of their choice: this can be focused on developing programming skills to improve the modelling software, deeper investigation of the science behind the modelling process, or applying the modelling to completely new pulsars. At all points, ample guidance will be provided to ensure that the student feels supported. We will have a half-hour meeting every morning to discuss the direction of the project and address any problems that arise. I will also help set things up computationally at the beginning of the project and provide guidance about developing computational and scientific skills over the course of the project. At the end of the project, we will focus on creating a presentation and a short written report for the student to demonstrate the progress achieved.
    Recommended experience: This project will greatly improve the student’s coding skills in Python, focusing on the ability to run software, analyse results and generate plots. If the student has no previous experience with computer programming that is fine: I am happy to provide guidance on this and the project will be a useful foundation for developing programming skills in an astrophysical research context. If the student has previous experience with programming (particularly Python) then this will allow time to take the project further and analyse a large number of pulsars, which may lead to results which can be included in a publication.
  • Constraining the galaxy-matter connection with phase correlations
    Supervisors:
    David Alonso, Felipe Oliveira Franco
    Description: The relation between the distribution of galaxies and the underlying dark matter structures is highly uncertain. While some information has been traditionally gleaned by studying the two-point galaxy correlation function, a lot more can be gained by accessing higher-order, non-Gaussian observables. In this project we will explore phase correlations, a unique signature of non-Gaussianity. The project will involve developing a theoretical framework for three-point phase correlations, and using it together with measurements from existing data to constrain the galaxy-halo connection.
    Recommended experience: Some experience with python or C++.