Summer Research Programme 2017
Oxford Astrophysics will run a summer research programme for undergraduate physics students again in 2017. We anticipate taking about 7 students, and students from the second year and above are welcome to apply. Applications are welcome from institutes outside of Oxford. Unfortunately, due to UK visa regulations, we are only able to accept applications from candidates within the EU.
Students will work with a supervisor in the department, usually a postdoctoral researcher or lecturer, on a self-contained research project. There will also be some lectures on current astrophysics topics. Students are encouraged to take part in department life, joining researchers for coffee, discussions and seminars.
The projects run for typically 8 weeks, nominally July 3rd - August 25th. The duration may be adjusted to be shorter or longer, or to accommodate summer travel. Students will be paid via a stipend (provisionally £230 per week). The project is full-time but hours can be discussed with your supervisor.
You should email a one-page-only application, in pdf format, to the Graduate Administrator (Astrogradadmin [at] physics [dot] ox [dot] ac [dot] uk) by Feb 20 2017, with 'Summer intern application' in the subject line. Students should ask for a short academic reference letter to be emailed to the above email address by the same date. Offers will be made in March.
On your 1-page application you should tell us why you are interested in the programme and which project(s) most interest you. Also include your contact details, your year and course, any undergraduate exam results so far, and contact details (including email) of your academic referee. Please also mention any computer programming experience and any previous research experience.
You are encouraged to informally contact the supervisor(s) to find out more details about the projects that interest you. For any administrative queries, contact the Administrator on the email address above.
Here are the projects that are available for 2017. They span a range of our interests. Most of the research activity involves analytic and computing work.
The growth of galaxies in the first 2 billion years
Supervisors: Rebecca Bowler
The Hubble Space Telescope has provided high resolution images of galaxies from the Local universe to early times. One of the fundamental properties revealed by this data is the galaxy size and shape, and how this evolves. While there are now large sample of galaxies known at early times, in the first billion years of the universe, the images of these objects have not been carefully studied. In this project you will extract Hubble data for a sample of galaxies that probe the first 2 billion years of the Universe, and study their morphologies and sizes for the first time.
The project will be computational. Some coding experience would be helpful, but is not mandatory.
Signatures of non-Gaussianity in the cosmic web
Supervisors: David Alonso
The large-scale distribution of matter in the Universe contains information about its initial conditions. In particular, studying the dimensionality of the main components of this web-like distribution may allow us to place constraints on the level of primordial non-Gaussianity. This project will focus on computing the expected theoretical signatures of non-Gaussianity on cosmic web statistics and comparing these predictions with numerical simulations.
Searching for high-redshift radio galaxy candidates with new low-frequency radio surveys
Supervisors: Leah Morabito
Many high-redshift radio galaxies have been found by selecting radio galaxies with ultra-steep spectral energy distributions (SED) and following up with optical observations to determine the redshift. High-redshift radio galaxies are indicative of dense environments in the distant Universe, and are thought to evolve into the most massive galaxies we see today. They are therefore an interesting link in studying the evolution of massive galaxies. Recent work has shown that simply selecting based on radio SEDs will bias high-redshift samples towards only extreme galaxies. In order to select a more representative sample of candidate high-redshift radio galaxies, it is necessary to consider other indicators like compact size. New low-frequency radio surveys with unprecedented sensitivity and resolution offer the possibility to select samples of more ""normal"" high-redshift radio galaxies. This project will involve (1) determining a strategy based on the available data to select a complete sample of high-redshift galaxy candidates and (2) applying the strategy to low-frequency radio surveys.
Basic ability to manipulate catalogues, via TOPCAT, python, R, IDL, or any other language.
Cosmology with galaxy sizes
Supervisors: Chris Duncan
ight bending due to gravity distorts the shape, size and brightness of distant galaxies. Whilst the shape distortion is routinely used in a range of cosmological analyses (with many current and upcoming surveys designed to use this measure), the use of size and flux measures is comparatively less mature, however recent studies have suggested there are significant gains to using these measures on top of traditional shape measurements. In this project, you will investigate the use of statistical methods to mitigate potential inaccuracies in galaxy size measurement, and investigate the use of galaxy sizes from large surveys for cosmological applications, such as measuring the mass profile of large astrophysical bodies such as galaxy clusters.
Coding is expected, although there is scope on the level necessary. Basic to moderate computing skills (Python or C++ preferred) are desirable. This project would suit someone with an interest in applying probabilistic analysis to cosmological datasets and image analysis.
Probing Intergalactic Magnetic Fields
Supervisors: Rafael Alves Batista
The origin of cosmic magnetic fields in the universe is an open problem in cosmology. There are essentially two classes of models to explain the cosmological magnetogenesis: primordial and astrophysical mechanisms. The existence of non-zero magnetic fields permeating the whole universe, henceforth called intergalactic magnetic fields (IGMFs), may be deemed a signature of the former process, thus suggesting the existence of a ubiquitous field since early times. High-energy gamma rays can probe the universe up to relatively high redshifts as they are electrically neutral and their arrival directions can be approximately traced back to their source. The interaction of the high-energy gamma rays with ambient photons from the cosmic microwave background and the extragalactic background light may produce electromagnetic cascades whose short-lived charged component is affected by intervening magnetic fields, allowing us to study these fields. The goal of this project is to model the development of gamma-ray-induced electromagnetic cascades in the intergalactic medium in order to constrain properties of IGMFs.
This project is simulation-based, so familiarity with Python would be advantageous.
Magnetohydrodynamic simulations: cosmic ray acceleration and data visualisation
Cosmic rays are high energy particles that arrive at earth with energies as high as 10^20 electron volts. The origin of the highest energy cosmic rays is still unknown, and so testing ways in which they can be accelerated is important. One of the best ways to do so is with magnetohydrodynamic (MHD) simulations, in particular by investigating ways in which the magnetic field -- a crucial parameter in explaining particle acceleration -- can be amplified. The student will work with me, to investigate how the magnetic field in MHD simulations depends on the various input parameters, using an existing MHD code. As a result, the student will need good computing skills and have experience with programming in a language such as python, IDL or Fortran. We will also be exploring how best to visualise the outputs from the code. Data visualisation is increasingly important in modern academia and data science, so this will provide the student with relevant transferable experience. If progress is good, there will also be time to learn more about plasma physics, active galactic nuclei and the mathematics behind MHD.
Exploring Galaxy Evolution with Galaxy Zoo
Supervisors: Chris Lintott
The Galaxy Zoo project has provided reliable morphological catalogues of galaxies out to a redshift of z~1.5. This project will use this data to explore galaxy evolution, for example by investigating our sample of bulgeless galaxies, systems which have grown despite a lack of major mergers.
The project requires moderate computing skills (or a willingness to learn) and would suit someone who is also interested in outreach.
Machine Learning in the Zooniverse
Supervisors: Chris Lintott
The Zooniverse allows volunteers to interact with large astronomical datasets to discover planets and supernovae, classify galaxies, and map nearby galaxies. In each case, the size of the dataset has already overwhelmed the capacity of professional scientists, but forthcoming surveys will increase the volume and velocity of data still further. The solution is to combine human and machine classifications, and this project will involve working with the Zooniverse development team to develop such solutions for multiple projects.
The project involves strong computing skills and would suit someone who wants to learn new techniques and tools.
Radiative cooling of shocked gas
Supervisors: Miguel Pereira Santaella
Shock waves are ubiquitous in the interstellar medium. They are produced by violent events such as supernova explosions, jets originated in black holes, stellar winds, or by the collision of two galaxies. When these shock waves encounter interstellar gas clouds, part of their kinetic energy is transferred to the clouds, heating the gas to high temperatures. After being heated, the clouds cool radiatively through the emission of atomic and molecular lines. The detailed modeling of this emission allows us to establish the properties of both the shock wave and the shocked gas, and, therefore, to quantify the effects of these energetic events in their surrounding medium. In this summer project, we will use available radiative transfer codes to determine how the emission of shocked gas evolves in time as a function of its initial density and composition (from primordial pristine gas to high metallicity clouds). If time allows, the modeling results will be used to interpret observations of local galaxies. This project will introduce the student to the basic theory of interstellar shocks and non local thermodynamic equilibrium (non-LTE) radiative transfer.
Basic knowledge of Python is required.
Kinematics and multiplicity of young low-mass stars using a new radial velocity technique
Supervisors: Suzanne Aigrain & Vinesh Rajpaul
Radial velocity (RV) measurements are an important probe of low-mass stars in young open clusters. The distribution of RVs measured for stars of different masses can be used a) to determine which are genuine members of the cluster and b) to search for signs of mass segregation (where the spatial distribution and kinematics of stars of different masses differ). Furthermore, multi-epoch RV measurements can be used to detect close binary stars and measure their orbits. However, precise RV measurements for young low-mass stars are very difficult to obtain. The traditional method consists in cross-correlating a spectrum with a theoretical or observed template or mask, but this approach doesn’t work well for young low-mass stars, which are intrinsically faint and have non-standard spectra. We have recently developed a new method to extract RVs by modelling the stars spectra using a type of non-parametric Bayesian model called a Gaussian Process, and cross-correlating them with each other (thereby doing away with the external template). The project will consist in applying this method, which has so far been tested on high-resolution spectra of “normal” Sun-like stars, to a large databased of moderate resolution spectra of young low-mass stars in young open clusters and star forming regions.
basic understanding of stellar astrophysics, basic programming skills (ideally Python and/or Matlab). Familiarity with spectroscopy, Bayesian statistical methods and/or young stars desirable but not required.
Diffraction grating characterization for HARMONI
Supervisors: John Capone
HARMONI will be a first-light instrument on the 39-metre diameter European Extremely Large Telescope (E-ELT). The performance of diffractive gratings is key to the success of the project. Volume Phase Holographic Gratings (VPHGs) will be used to maximize the fraction of light from a given bandpass diffracted into a selected order. The design of the spectrograph requires dozens of gratings which will eventually be characterized in a semi-automated fashion. In preparation for this undertaking, this project will help develop the measurement procedures which will be used to characterize HARMONI's VPHGs. The project will conclude with an analysis of measurements of a prototype grating.
Experience with a scripting language for data analysis (e.g. Python, R or MATLAB) would be an advantage.