A limited number (typically a dozen) of paid Summer scholarships are offered to Physics undergraduate students between their 2nd and 3rd year or 3rd and 4th year of their course to enable them to undertake a research project with a research group in the School. The scholarships pay approximately £200 per week and are between 8-10 weeks in duration (start date is agreed to be mutually convenient to Academic and Student). The selection process takes place in February each year.
Please complete the form and email it to Olga Fernholz by 6pm on Monday 4 February 2019.
Professor Alfonso Aragón-Salamanca and Professor Mike Merrifield
Slicing galaxies in space and time
As progress has been made in studying the formation of galaxies, it has become apparent that the inter-relationship between their various components – disks, bulges, bars, spiral arms– are quite complex, with interactions and exchanges of stars a key part of the evolutionary process. Clearly, a definitive picture of galaxy evolution requires that we have a full understanding of not only where stars are today, but also how they got there. Integral field spectroscopy surveys of nearby galaxies are revolutionizing both the quantity and quality of spatially resolved spectral data available to address this question. At the same time, powerful analytic tools have been developed to extract the star-formation histories from the observed spectra.
In this project we will use integral field spectroscopic data obtained by the MaNGA survey (www.sdss.org/surveys/manga/) to derive and visualise the star-formation history at each spatial location of many galaxies. This project will start by developing tools to visualise the data (e.g., create maps of equal-age stars; develop animations to see how stellar populations evolve with time). Using these will be able to address questions such as: Do the bulges of spiral galaxies form earlier than their disks? Are the stars in galactic bars similar to those in the rest of the disks? Can we measure different ages on different locations across spiral arms?
This project is heavily computational in nature. Some knowledge of Python will be very useful.
Dr Matthew Brookes
Optically Pumped Magnetometers for biomagnetic measurements
Recent years have seen significant progress in the use of quantum sensors to measure magnetic fields generated by the human body. Optically pumped magnetometers (OPMs) exploit the quantum properties of alkali atoms (in our case rubidium) to provide a quantifiable metric of magnetic fields at the femto-tesla scale. This has allowed us to measure magnetic fields generated by current flow through assemblies of neurons in the brain, and in this way characterise brain function evoked by specific mental tasks – a process known as magnetoencephalography (MEG) (see Boto et al, Nature, 2018). In this summer placement, the student will join our OPM-MEG team to work on development of our prototype MEG instrument.
Specifically, the student will work on new ways to achieve very high spatial resolution images of cortical current flow (Barratt et al, NeuroImage, 2018). We will use the known topographical organisation of the human sensorimotor system to evoke brain activity in subtly different cortical locations separated by just millimetres. We will then use newly developed mmathematical models applied to our OPM-MEG data to separate those cortical representations.
The student must have a strong interest in experimental medical physics and be highly proficient in matlab programming.
E. Boto, N. Holmes, J. Leggett, G. Roberts, V. Shah, S.S. Meyer, L.D. Muñoz, K.J. Mullinger, T.M. Tierney, S. Bestmann, G.R. Barnes, R. Bowtell, M.J. Brookes, Moving magnetoencephalography towards real-world applications with a wearable system, Nature 555 (7698), 657, 2018
E.L. Barratt, S.T. Francis, P.G. Morris, M.J. Brookes, Mapping the topological organisation of beta oscillations in motor cortex using MEG, NeuroImage, 181, 831-844, 2018
Dr Janette Dunn and Dr Anastasios Avgoustidis
Migration of computing provision from MATLAB to Python
The School of Physics & Astronomy is in the process of converting all programming provision from MATLAB to Python, starting with the 1st year computing module in 2019-20. The School of Mathematical Sciences is also interested in converting their provision to Python. This project seeks an undergraduate student with good prior knowledge of Python to:
- Determine current knowledge of Python among Physics and Mathematics students, including details of the environments and packages / versions used.
- Test Python material created by Dr Dunn and Dr Avgoustidis by converting the notes and workshop material for their 1st year computing module, and help iron out any problems. The student will determine whether the material follows best-practice for scientific and mathematical use in both academia and industry. If it is not, they will help update the material appropriately.
- If any time remains, the student will discuss with the leaders of the second year core modules any changes needed for 2020-21.
The second step above will be carried out in collaboration with a postgraduate student who will be appointed to work for ~33 hours on this project.
Note that there is a total of £1500 (£200 over 7.5 weeks) available to support this project.
Prof Juan P Garrahan and Dr Adam Moss Deep learning applied to statistical physics
Deep learning has recently revolutionised fields such as computer vision, speech recognition, natural language processing, search, and many more. It is a class of machine learning which aims to "teach" a computer an abstract representation of data. This representation is encoded by the weights of a neural network (NN), which consists of many layers of non-linear processing.
Learning can be supervised, partly supervised or unsupervised. In supervised learning training data is provided with known labels, whereas in unsupervised learning data is unlabelled and the machine must try and find hidden structure in the data itself. It is not yet fully understood why deep learning is so effective. It has been shown in computer vision problems, for example, that deep neural networks learn better representations of data than wider, shallower networks.
This project is about applying deep learning to problems in statistical mechanics. One such area is the automatic classification of features in systems undergoing phase transitions. Questions to be addressed include: can one train (via supervised learning) a NN to classify microstates belonging to distinct thermodynamic phases, to identify the features that distinguish such phases, and to anticipate the critical values of parameters that control the transitions; and what are optimal NN architectures for optimal performance of these tasks.
This project has a mixture of analytical and computational work, and requires a good grasp of thermal and statistical physics and of computer simulations.
See e.g. J. Carrasquilla and R.G. Melko, “Machine learning phases of matter”, Nature Phys. 13, 431 (2017).
Professor Penny Gowland
Development of whole body imaging at 7T
MR is an indispensable tool in clinical medicine, and its unique capacity to monitor multiple aspects of tissue function. However sensitivity is limited for some measures, but this can be overcome by using ultra-high field (7T). The benefits of 7T are already being exploited in neurology and neuroscience, but significant challenges have limited progress in the body. Recent advances in scanner technology have made body imaging feasible but opened up the opportunity to extend the application of ultra-high field into the body but there many problems in applying 7T in the human body.
This project can be designed to suit the student’s interest and capabilities (theoretical, computational, experimental) but could involve investigating methods to segment images to determine the RF power deposited in the body at 7T, validating quantitative measures made at 7T, developing methods of analysing novel data acquired at 7T or comparing data acquired at 3T and 7T.
Dr. Lucia Hackermueller
Quantum information in an atom-fibre system
The development of laser cooling techniques has led to a rapid growth of the field of cold and ultracold atoms, which deals with (mainly alkali) atoms at micro- and nanokelvin temperatures. At these record low temperatures, quantum phenomena are important and can be directly observed. Cold atoms are interesting quantum systems, because they are comparatively easy to model theoretically and at the same time they can be used to study genuine quantum effects.
In that sense cold atom systems can be applied in the area of “quantum technologies”, where quantum effects are used for precise sensing, imaging, information processing or quantum computing. In our experiment, we are trapping clouds of cold atoms at a temperature of a few microkelvin in a microscopic void created in an optical fibre. For this we first cool atoms in a magneto-optical trap and then load them into an optical dipole trap. The dipole trap passes through the hole in the fibre. This is an ideal system to map photons travelling in the fibre onto the atomic cloud. This situation can be used to store information carried by the photons in the atoms (quantum memory), to precisely probe the atomic cloud or to create entangled photons from re-emission of the atoms.
The summer project student will learn how to operate the system and create a cold cloud of caesium atoms at microkelvin regime and characterise the performance of the system. Several parameters will be tested for optimal trap loading with respect to a large number of atoms as well as reaching low temperatures. Photon sources will be tested, detectors optimised, data analysed. The project will involve work on the laser system for the cooling light and the read-write operations, including spectroscopy, locking electronics and computer control of the experiment.
This project will enable insights into the everyday life in an experimental lab and will be a great opportunity to learn a wide range of experimental techniques from adjusting and dealing with optics to atomic physics, building electronic circuits and processing data and controlling the experiment.
Dr Yong Mao and Professor John Owers-Bradley
Impedance characterisation of a human lung as a fractal network
Human lungs are fantastic examples of fractal networks, typically consisting of around 1500 miles of branching airways connecting to some 400 million alveoli. Common lung diseases, such as asthma, arise from the obstruction of the airways, and are estimated to affect hundreds of millions of people globally. Yet, clinically available lung function testing is very limited, and impedance characterisation potentially shows the way forward.
The vast network of a lung’s airways may be regarded as a composite transmission line for pressure waves. For example, each single airway tube may be understood in terms of the Poisseuille flow, and our knowledge of the lung’s fractal structure allows us to model the entire lung. This project intends to establish the impedance characteristics of a rigid lung model as a basis for exploring the variations arising from differing obstruction mechanisms.
Whilst the work is mainly theoretical/computational, there is the opportunity to experiment with a life-sized 3D printed lung model.
Dr Chris Mellor
Imaging Spectroscopic Ellipsometry
In May 2019 we will install a new instrument for measuring the optical properties and thicknesses of 2D materials such as graphene and boron nitride as well as dielectric layers such as electron beam resists and self-assembled molecular monolayers. This will be the third such instrument in the UK.
The instrument, an EP4 from Accurion (www.accurion.de) is called an imaging spectroscopic ellipsometer. Imaging because it has a lateral resolution of a few microns and can record an image of the sample, spectroscopic because it measures light from 250nm to 1000nm in wavelength and ellipsometer because it analyses changes in the polarisation of the light reflected from the sample. The EP4 software takes care of the ellipsometric analysis, allowing the user to focus on the interpretation of the image.
The aim of the Summer Scholarship Project will be to use the EP4 to make initial measurements on a wide range of samples so that we can learn about the particular strengths and weaknesses of the instrument when applied to samples of interest to Nottingham researchers. We also want to learn how long typical measurements take so that we can provide time estimates to research groups who are considering using the instrument.
Prof John Owers-Bradley
Producing hyperpolarised liquids for magnetic resonance
The idea of the project is that the samples to be used for MRI or NMR can be pre-polarised before they are used giving an increase in NMR signal of more than 1,000. This is an experimental project based in my low temperature labs. I have a new system from the USA that is designed to cool samples in high magnetic fields so that the nuclear spin system aligns with the B field. It is then possible to shoot the frozen highly polarised sample out much like an air gun and subsequently thaw it with hot water to produce highly spin polarised liquid.
During the project we will be attempting to improve the system by trying different materials and conditions. It will be challenging at times, and we are sure to get upset as it may not always work – but it‘s all the more exciting when it does. Once we have the hyperpolarised liquid, we can see what we have achieved in an nearby NMR spectrometer or run very fast with it to my MRI scanner next door – we won’t be injecting it into anyone just yet!
You will learn a lot about experimental techniques in general, especially a knowledge of cryogenics and magnetic resonance including NMR and MRI.
Dr James Sharp
Interfacial instabilities and bubble ejection in the Hele-Shaw cell
The Hele-Shaw cell consists of two parallel plates separated by a thin gap. When immiscible fluids of different viscosities are forced through the gap, some striking patterns can be observed.
In this project you will use a Hele-Shaw cell to study an instability between water and a trapped air bubble which results as the interface vibrates in the flow. Under conditions of fast flow, the vibration of the air-water interface results in the ejection of lots of tiny bubbles.
You will use a high-speed camera (200-500fps) to study the oscillations of the bubble interface. The use of a variety of illumination strategies and image analysis techniques will enable you to measure changes in the shape of the fluctuating air-water interface and to develop a better understanding of the physics of the bubble ejection mechanism. A high level of confidence with using Matlab (or Python) is therefore required for this project.
If time allows you will study the influence of changing key experimental parameters on the observed phenomenon. This will include (but not be limited to) varying parameters such as the thickness of the gap, the surface tension of the air/water interface and through modification of the viscosity of the water.
Dr Mike Smith
Development of emulsion based microfluidics
This project will develop the use of microfluidics to produce emulsions (oil droplets in water that are stabilised with a surfactant). The internship will have a number of different parts:
The project will require a mixture of practical hands on development of the devices and the development of code. The coding will use and build on our existing Arduino and Python code. It is not expected that applicants will have used these languages before.
Development of outreach – Visualising stress transmission in photoelastic discs.
This project will develop a visual demo for use at various school open days and outreach events. The aim is to show how forces are transmitted in a strongly heterogeneous manner through amorphous solids. The project will use photoelastic discs which display bright colours between crossed polarisers when subjected to stress. We hope to make a 2D set of discs which can be subjected to a load by a motorised plunger. The addition of additional discs which alter the pattern of force chains will be linked with an educational understanding of the physics’ applications, but also provide the opportunity to turn the activity into a memorable game for younger children.
Applicants will design and build the demo rig and electronic controls, develop its use for different outreach scenarios and put together supporting educational materials for communicating the underlying physics to a variety of audiences. Enthusiasm for communicating science in an imaginative way is the main pre-requisite.
Please note the duration of this project is 8 weeks.
Dr Mike Swift and Dr Mike Smith
Collective Behaviour of Active Brownian Mixtures.
Groups of particles driven out of equilibrium often exhibit complex collective behaviour. An interesting class of non-equilibrium systems is active matter: collections of particles in which energy is injected at the particle scale and dissipated through interactions. Examples in nature include vibrated granular materials, the dynamics of bacteria colonies and flocking of birds .
A simple model system that has been studied recently is a collection of active Brownian particles with alignment . Each particle has a preferred speed of travel but the direction of motion is influenced by particle interactions and 'thermal' noise. The aim of this project is to simulate such a system and investigate the nature of the collective behaviour. Under appropriate conditions a system of identical particles phase separates into dense and dilute phases . It would be interesting to generalise the model to investigate mixtures of particles with different interactions. Such a model could give insight into bacterial dynamics in biofilms.
 "The Physics of Life", G. Popkin, Nature, 529, 16 (2016).
 "Velocity alignment promotes motility-induced phase separation", E. Sesé-Sansa, I. Pagonabarraga and D. Levisar, arXiv:1807.07497 [cond-mat.soft].
Dr Silke Weinfurtner and Professor John Owers-Bradely
Superfluid rotating black holes
The dynamics of the early universe and black holes are deeply linked to the interplay between general relativity and quantum fields. The essential physical processes occur in situations that are hard to observe and impossible to experiment with: when gravitational interactions are strong and/or when quantum effects are important. We propose to study these processes in experiments by employing analogue classical and quantum analogue simulators.
We are currently setting up an experiment to study the effects occurring around effective horizons in an analogue gravity system. In particular, the scientific goals are to explore rotating black hole processes in a superfluid vortex flow. To address this issue experimentally, we utilize the analogy between waves on the surface of a stationary draining fluid/superfluid flows and the behaviour of classical and quantum field excitations in the vicinity of rotating black.
We are looking for an enthusiastic and talented summer student to get involved in the initial stages of this ambitious project.
More information of the overall program of analogue gravity studies at the University of Nottinghams can be found online at www.gravitylaboratory.com
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