You may contact a Proposer directly about a specific project or contact our Postgraduate Admin with general enquiries.
Title  Equations over groups  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Martin Edjvet  
Description  Let G be a group. An expression of the form g_{1} t … g_{k} t=1 where each g_{i} is an element of G and the unknown t is distinct from G is called an equation over G. The equation is said to have a solution if G embeds in a group H containing an element h for which the equation holds. There are two unsettled conjectures here. The first states that if G is torsionfree then any equation over G has a solution. The second due to Kervaire and Laudenbach states that if the sum of the exponents of t is nonzero then the equation has a solution. There have been many papers published in this area. The methods are geometric making use of diagrams over groups and curvature. This subject is related to questions of asphericity of groups which could also be studied. 

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Title  Quadratic forms and forms of higher degree, nonassociative algebras  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Susanne Pumpluen  
Description  Dr. Pumplün currently studies forms of higher degree over fields, i.e. homogeneous polynomials of degree d greater than two (mostly over fields of characteristic zero or greater than d). The theory of these forms is much more complex than the theory of homogeneous polynomials of degree two (also called quadratic forms). Partly this can be explained by the fact that not every form of degree greater than two can be “diagonalized”, as it is the case for quadratic forms over fields of characteristic not two. (Every quadratic form over a field of characteristic not two can be represented by a matrix which only has nonzero entries on its diagonal, i.e. is diagonal.) A modern uniform theory for these forms like it exists for quadratic and symmetric bilinear forms (cf. the standard reference books by Scharlau or Lam) seems to be missing, or only exists to some extent. Many questions which have been settled for quadratic forms quite some time ago are still open as as soon as one looks at forms of higher degree. It would be desirable to obtain a better understanding of the behaviour of these forms. First results have been obtained. Another related problem would be if one can describe forms of higher degree over algebraic varieties, for instance over curves of genus zero or one. Dr. Pumplün is also studying nonassociative algebras over rings, fields, or algebraic varieties. Over rings, as modules these algebras are finitely generated over the base ring. Their algebra structure, i.e. the multiplication, is given by any bilinear map, such that the distributive laws are satisfied. In other words, the multiplication is not required to be associative any more, as it is usually the case when one talks about algebras. Her techniques for investigating certain classes of nonassociative algebras (e.g. octonion algebras) include elementary algebraic geometry. One of her next projects will be the investigation of octonion algebras and of exceptional simple Jordan algebras (also called Albert algebras) over curves of genus zero or one. Results on these algebras would also imply new insights on certain algebraic groups related to them. Another interesting area is the study of quadratic or bilinear forms over algebraic varieties. There are only few varieties of dimension greater than one where the Witt ring is known. One wellknown result is due to Arason (1980). It says that the Witt ring of projective space is always isomorphic to the Witt ring of the base field. If you want to investigate algebras or forms over algebraic varieties, this will always involve the study of vector bundles of that variety. However, even for algebraically closed base fields it is usually very rare to have an explicit classification of the vector bundles. Hence, most known results on quadratic (or symmetric bilinear) forms are about the Witt ring of quadratic forms, e.g. the Witt ring of affine space, the projective space, of elliptic or hyperelliptic curves. An explicit classification of symmetric bilinear spaces is in general impossible because it would involve an explicit classification of the corresponding vector bundles (which admit a form). There are still lots of interesting open problems in this area, both easier and very difficult ones. 

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Title  Cohomology Theories for Algebraic Varieties  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Alexander Vishik  
Description  After the groundbreaking works of V. Voevodsky, it became possible to work with algebraic varieties by completely topological methods. An important role in this context is played by the socalled Generalized Cohomology Theories. This includes classical algebraic Ktheory, but also a rather modern (and more universal) Algebraic Cobordism theory. The study of such theories and cohomological operations on them is a fascinating subject. It has many applications to the classical questions from algebraic geometry, quadratic form theory, and other areas. One can mention, for example: the Rost degree formula, the problem of smoothing algebraic cycles, and uinvariants of fields. This is a new and rapidly developing area that offers many promising directions of research. 

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Title  Quadratic Forms: Interaction of Algebra, Geometry and Topology  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Alexander Vishik  
Description  From the beginning of the 20th century it was observed that quadratic forms over a given field carry a lot of information about that field. This led to the creation of rich and beautiful Algebraic Theory of Quadratic Forms that gave rise to many interesting problems. But it became apparent that quite a few of these problems can hardly be approached by means of the theory itself. In many cases, solutions were obtained by invoking arguments of a geometric nature. It was observed that one of the central questions on which quadratic form theory depends is the socalled "Milnor Conjecture". This conjecture, as we now understand it, relates quadratic forms over a field to the socalled motivic cohomology of this field. Once proven, this would provide a lot of information about quadratic forms and about motives (algebrogeometric analogues of topological objects) as well. The Milnor Conjecture was finally settled affirmatively by V. Voevodsky in 1996 by means of creating a completely new world, where one can work with algebraic varieties with the same flexibility as with topological spaces. Later, this was enhanced by F. Morel, and now we know that quadratic forms compute not just the cohomology of a point in the "algebro geometric homotopic world", but also the socalled stable homotopy groups of spheres as well. It is thus no wonder that these objects indeed have nice properties. Therefore, by studying quadratic forms, one actually studies the stable homotopy groups of spheres, which should shed light on the classical problem of computing such groups (one of the central questions in mathematics as a whole). So it is fair to say that the modern theory of quadratic forms relies heavily on the application of motivic topological methods. On the other hand, the Algebraic Theory of Quadratic Forms provides a possibility to view and approach the motivic world from a rather elementary point of view, and to test the new techniques developed there. This makes quadratic form theory an invaluable and easy access point to the forefront of modern mathematics. 

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Title  Regularity conditions for Banach function algebras  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Joel Feinstein  
Description  Banach function algebras are complete normed algebras of bounded, continuous, complexvalued functions defined on topological spaces. There are very many different examples with a huge variety of properties. Two contrasting examples are the algebra of all continuous complexvalued functions on the closed unit disc, and the subalgebra of this algebra consisting of those functions which are continuous on the closed disc and analytic on the interior of the disc. In the second of these algebras, any function which is zero throughout some nonempty open set must be constantly zero. This is very much not the case in the bigger algebra: indeed Urysohn’s lemma shows that for any two disjoint closed subsets of the closed disc, there is a continuous, complexvalued function defined on the disc which is constantly 0 on one closed set and constantly 1 on the other (algebras of this type are called regular algebras). Most Banach function algebras have some features in common with one or the other of these two algebras. The aim of this project is to investigate a variety of conditions, especially regularity conditions, for Banach function algebras, and to relate these conditions to each other, and to other important conditions that Banach function algebras may satisfy. Regularity conditions have important applications in several areas of functional analysis, including automatic continuity theory and the theory of Wedderburn decompositions. There is also a close connection between regularity and the theory of decomposable operators on Banach spaces. 

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Title  Properties of Banach function algebras and their extensions  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Joel Feinstein  
Description  Banach function algebras are complete normed algebras of bounded continuous, complexvalued functions defined on topological spaces. There are very many different examples with a huge variety of properties. Two contrasting examples are the algebra of all continuous complexvalued functions on the closed unit disc, and the subalgebra of this algebra consisting of those functions which are continuous on the closed disc and analytic on the interior of the disc. In the second of these algebras, any function which is zero throughout some nonempty open set must be constantly zero. This is very much not the case in the bigger algebra: indeed Urysohn’s lemma shows that for any two disjoint closed subsets of the closed disc, there is a continuous, complexvalued function defined on the disc which is constantly 0 on one closed set and constantly 1 on the other (algebras of this type are called regular algebras). Most Banach function algebras have some features in common with one or the other of these two algebras. The aim of this project is to investigate a variety of conditions (including regularity conditions) for Banach function algebras, to relate these conditions to each other, and to other important conditions that Banach function algebras may satisfy, and to investigate the preservation or introduction of these conditions when you form various types of extension of the algebras (especially ‘algebraic’ extensions such as ArensHoffman or Cole extensions). 

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Title  Meromorphic Function Theory  

Group(s)  Algebra and Analysis  
Proposer(s)  Prof James Langley  
Description  A meromorphic function is basically one convergent power series divided by another: such functions arise in many branches of pure and applied mathematics. Professor Langley has supervised ten PhD students, and specific areas covered by his and their research include those in the list below. Please note that since Professor Langley is close to retirement age he may not be available to supervise further students, and potential applicants are advised to contact him before applying.


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Title  Relative presentations and asphericity  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Martin Edjvet  
Description  The subject area is Combinatorial Group Theory. The objects of study are relative pesentations which can be viewed as onerelator products. In particular we consider the questions: when is a relative presentation aspherical; what is the order of the group defined by a given relative presentation? This has applications to cyclically presented groups for example. The methods are geometric (borrowing ideas from algebraic topology); algebraic; and may involve computational group theory via GAP or automatic groups. 

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Title  Compensated convex transforms and their applications  

Group(s)  Algebra and Analysis  
Proposer(s)  Prof Kewei Zhang  
Description  This aim of the project is to further develop the theory and numerical methods for compensated convex transforms introduced by the proposer and to apply these tools to approximations, interpolations, reconstructions, image processing and singularity extraction problems arising from applied sciences and engineering. 

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Title  Endomorphisms of Banach algebras  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Joel Feinstein  
Description  Compact endomorphisms of commutative, semisimple Banach algebras have been extensively studied since the seminal work of Kamowitz dating back to 1978. More recently the theory has expanded to include power compact, Riesz and quasicompact endomorphisms of commutative, semiprime Banach algebras. This project concerns the classification of the various types of endomorphism for specific algebras, with the aid of the general theory. The algebras studied will include algebras of differentiable functions on compact plane sets, and related algebras such as Lipschitz algebras. 

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Title  Iteration of quasiregular mappings  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Daniel Nicks  
Description  Complex dynamics is the study of iteration of analytic functions on the complex plane. A rich mathematical structure is seen to emerge amidst the chaotic behaviour. Its appeal is enhanced by the intricate nature of the Julia sets that arise, and fascinating images of these fractal sets are widely admired. 

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Title  Mean field limits of GinzburgLandau equations  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Matthias Kurzke  
Description  Many quantum physical systems (for example superconductors, superfluids, BoseEinstein condensates) exhibit vortex states that can be described by GinzburgLandau type functionals. For various equations of motion for the physical systems, the dynamical behaviour of finite numbers of vortices has been rigorously established. We are interested in studying systems with many vortices (this is the typical situation in a superconductor). In the hydrodynamic limit, one obtains an evolution equation for the vortex density. Typically, these equations are relatives of the Euler equations of incompressible fluids: for the GrossPitaevskii equation (a nonlinear Schrödinger equation), one obtains Euler, for the timedependent GinzburgLandau equation (a nonlinear parabolic equation), one obtains a dissipative variant of the Euler equations. The goal of the project is to study the dissipative equations and to understand instabilities and low regularity solutions. 

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Title  Dynamics of boundary singularities  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Matthias Kurzke  
Description  Some physical problems can be modelled by a function or vector field with a near discontinuity at a point. Specific examples include boundary vortices in thin magnetic films, and some types of dislocations in crystals. Typical static configurations can be found by minimizing certain energy functionals. As the core size of the singularity tends to zero, these energy functionals are usually well described by a limiting functional defined on point singularities. This project investigates how to obtain dynamical laws for singularities (typically in the form of ordinary differential equations) from the partial differential equations that describe the evolution of the vector field. For some such problems, results for interior singularities are known, but their boundary counterparts are still lacking. This project requires some background in the calculus of variations and the theory of partial differential equations. 

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Title  Where graphs and partial differential equations meet  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Yves van Gennip  
Description  Many problems in image analysis and data analysis can be represented mathematically as a network based This has lead to an interesting mix of theoretical questions (what is the dynamics on the network induced This project will investigate graph curvature and related quantities and make links to established 

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Title  Graph limits for faster computations  

Group(s)  Algebra and Analysis  
Proposer(s)  Dr Yves van Gennip  
Description  Many problems in image analysis and data analysis, such as image segmentation or data clustering, require Recent developments in the theory of (dynamics on) graph limits offer the hope that this subset can be This project will investigate this possibility and can be taken in a theoretical and/or application 

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Title  Vectorial Calculus of Variations, Material Microstructure, ForwardBackward Diffusion Equations and Coercivity Problems  

Group(s)  Algebra and Analysis, Algebra and Analysis  
Proposer(s)  Prof Kewei Zhang  
Description  This aim of the project is to solve problems in vectorial calculus of variations, forwardbackward diffusion equations, partial differential inclusions and coercivity problems for elliptic systems. These problems are motivated from the variational models for material microstructure, image processing and elasticity theory. Methods involve quasiconvex functions, quasiconvex envelope, quasiconvex hull, Young measure, weak convergence in Sobolev spaces, elliptic and parabolic partial differential equations, and other analytic and geometric tools. 

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Title  Dynamics of vortex singularities in nonlinear PDE  

Group(s)  Algebra and Analysis, Algebra and Analysis  
Proposer(s)  Dr Matthias Kurzke  
Description  Nonlinear PDE of GinzburgLandau type can be used to model a wide range of phenomena, from ferromagnetic materials and superconductors to quantum field theory. For certain ranges of the GinzburgLandau parameter (for selfduality and for point vortices), the equations can be reduced to ODEs. The focus of the present project will be to study the equations of motion in a wider setting, with the aim to extend the range of validity of the reductions and to compare almost singular solutions of the PDEs with simplified ODEs that describe the motion of the singularities. The project will use mostly rigorous analysis and possibly numerical simulation. 

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Title  Model reduction and homogenisation for filtration and adsorption  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Dr Matteo Icardi  
Description  Porous media are ubiquitous in natural and engineered transport processes. When colloids or diffusive particles flows through their complex geometrical structure, nontrivial interactions arise between the advection, diffusion, particleparticle and particlewall interactions. These processes can be modelled and simulated with computationally intensive threedimensional simulations. In this project, a combination of rigorous multiscale analytical and numerical techniques will be used to derive and calibrate faster and simple models for filtration and adsorption processes. Extensions to include electrostatic forces and electrochemical reactions will be also considered. The project is part of a wider research effort that sees the collaboration of several UK and international academic partners, and industrial partners in the Automotive and Oil&Gas sector. 

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Title  Crystallisation in polymers  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Prof Richard Graham  
Description  Polymers are very long chain molecules and many of their unique properties depend upon their long chain nature. Like simple fluids many polymer fluids crystallise when cooled. However, the crystallisation process is complicated by the way the constituent chains are connected, leading to many curious and unexplained phenomena. Furthermore, if a polymer fluid is placed under flow, this strongly affects both the ease with which the polymer crystallises and the arrangement of the polymer chains within the resulting crystal. This project will develop and solve models for polymer dynamics and phase transitions using a range of analytical, numerical and stochastic techniques, with the ultimate aim of improving our understanding of polymer crystallisation. The project offers the opportunity to collaborate with a wide range of scientists working in the field, including several worldleading experimental groups. 

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Title  Dynamics of entangled polymers  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Prof Richard Graham  
Description  Polymers are extraordinarily long molecules, made out of chains of simpler molecules. They occur everywhere in our everyday lives, including in the DNA chains that make up our genetics, in many hightech consumer products and in the simple plastic bag. Often these applications depend crucially on the way that the polymer chains move. This is especially true in concentrated polymer liquids, where the chain dynamics are controlled by how the chains become entangled with each other. A powerful mathematical framework for describing these entangled systems has been under development for some time now, but the ideas have yet to be fully developed, tested and exploited in practical applications. Working on this PhD project will give the opportunity to train in a wide range of mathematical techniques including analytical work, numerical computations and stochastic simulation and to apply these to problems of real practical impact. This lively research field involves mathematicians, scientists and engineers and a keenness to learn from and cooperate with researchers from a range of backgrounds would be a real asset in this project. 

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Title  Power converters  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Dr Stephen Cox, Dr Stephen Creagh  
Description  In a wide range of applications, it is necessary to convert one electrical power supply to another, of different voltage or frequency. Power converters are devices which achieve this, but they often suffer highly undesirable instabilities, which significantly compromise their operation. The goal of this project is to develop mathematical models for existing power converter technologies and to use these to provide a detailed description of their operation and a thorough understanding of the instability. Through mathematical modelling, it may prove possible to improve existing power converter designs to reduce or eliminate the stability problems! This project will be theoretical in nature, relying largely on analytical and numerical techniques for differential equations, and will involve significant interaction with the Power Electronics Group in the Department of Electrical and Electronic Engineering. 

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Title  ClassD audio amplifiers  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Dr Stephen Cox, Dr Stephen Creagh  
Description  The holy grail for an audiophile is distortionfree reproduction of sound by amplifier and loudspeaker. This project concerns the mathematical modelling and analysis of classD audio amplifiers, which are highly efficient and capable of very low distortion. Designs for such amplifiers have been known for over 50 years, but only much more recently have electronic components been up to the job, making classD amplifiers a reality. (ClassD amplifiers rely on very high frequency – around 1MHz – sampling of the input signal, and so test their components to the limit.) Unfortunately, while the standard classD design offers zero distortion, it has poor noise characteristics; when the design is modified by adding negative feedback to reduce the noise, the amplifier distorts. By a further modification to the design it is possible to eliminate (most of) the distortion. This project involves modelling various classD designs and determining their distortion characteristics, with the aim of reducing the distortion. The project will be largely analytical, applying asymptotic methods and computer algebra to solve the mathematical models. Simulations in matlab or maple will be used to test the predictions of the mathematical models. 

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Title  Mathematical modelling and analysis of composite materials and structures  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Dr Konstantinos Soldatos  
Description  Nottingham has established and maintained, for more than half a century, worldwide research leadership in developing the Continuum Theory of fibrereinforced materials and structures. Namely, a theoretical mechanics research subject with traditional interests to engineering and, more recently, to biological material applications. The subject covers extensive research areas of mathematical modelling and analysis which are of indissoluble adherence to basic understanding and prediction of the elastic, plastic, viscoelastic or even viscous (fluidtype) behaviour observed during either manufacturing or real life performance of anisotropic, composite materials and structural components. Typical research projects available in this as well as in other relevant research subjects are related with the following interconnected areas:
The large variety of topics and relevant problems emerging in these subjects of Theoretical Mechanics and Applied Mathematics allow considerable flexibility in the formation of PhD projects. A particular PhD project may accordingly be formed/designed around the strong subjects of knowledge of a potential postgraduate student. The candidate’s relevant cooperation is accordingly desirable and, as such, will be appreciated at the initial, but also at later stages of tentative research collaboration. 

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Title  Dynamics of coupled nonlinear oscillators  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Dr Paul Matthews  
Description  Coupled oscillators arise in many branches of science and technology and also have applications to biological systems. One spectacular example is swarms of fireflies that flash in synchrony. This research field is an expanding area in applied mathematics because of the many applications within physics and biology and because of the variety of behaviour which such systems can exhibit. Recent work on coupled oscillators has revealed some interesting novel results: nonlinear oscillators can synchronise to a common oscillation frequency even if they have different natural frequencies, provided the coupling is above some threshold; the breakdown of synchronisation as the coupling strength decreases involves periodic behaviour and chaos. The project involves extending and improving this work in two ways. First, the oscillator model used in earlier work was simple and idealised; the model will be refined to make it more realistic. Second, most earlier work used a simple linear global coupling so that each oscillator is equally coupled to all of the others. In most practical examples this is not the case and a coupling law over a two or threedimensional lattice would be more appropriate, with stronger coupling between nearer pairs of oscillators. The research will be carried out using a combination of numerical and analytical techniques. 

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Title  Dynamo action in convection  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Dr Paul Matthews  
Description  The magnetic fields of the Earth and Sun are maintained by dynamo action. Fluid motions are generated by thermal convection. The kinetic energy of these fluid motions is then converted to magnetic energy, in a manner similar to that of a bicycle dynamo. Dynamo theory studies how this conversion takes place. It is known that in order for a dynamo to work efficiently, the fluid flow must exhibit chaos. This project will investigate dynamo action in convection, using 3D numerical simulation of the equations for the fluid motion and the magnetic field. An existing computer program will be used to study the dynamo problem. A sequence of numerical simulations will be carried out to determine
The project is also suitable for analytical work, either based on an asymptotic analysis of the equations, or in investigating or proving 'antidynamo' theorems. 

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Title  Nonlinear penetrative convection  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Dr Paul Matthews  
Description  The phenomenon of convection, in which heat is transferred by fluid motion, occurs very commonly in nature. Examples include in the Earth's atmosphere, the interior of the Sun, the Earth's liquid outer core, lakes and oceans. The most commonly used mathematical model for convection assumes that a layer of fluid is bounded above and below by boundaries that are maintained at a fixed temperature. This is not a good model for most of the environmental applications, where typically part of the fluid layer is thermally unstable and part is stable. Convection in the unstable layer overshoots and penetrates into the stable layer. This phenomenon, known as 'penetrative convection', has received relatively little investigation. The research project will study penetrative convection in the nonlinear regime. An existing computer program will be adapted to investigate penetrative convection numerically, and analytical work will be carried out using asymptotic methods and methods of bifurcation theory. In particular, the extent of penetration into the stable layer and the possibility of instability to a mean flow will be explored. 

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Title  Coupling between optical components  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Dr Stephen Creagh  
Description  Evanescent coupling between different optical components is a very important process in optical communications. In this effect, light travelling along an optical fibre effectively spills out a little bit into the region of space immediately surrounding the fibre itself and can then leak into and become captured by other, nearby optical components. Among other uses, this mechanism forms a basis for optical switches, which transfer light from one fibre to another, and for wavelength filters, which selectively transmit or redirect light in only certain frequency ranges. This project will investigate the coupling between cylindrical and spherical optical components in two and three dimensions using the geometry of the underlying ray solutions. The aim will be to exploit and generalise approximations which have been developed in the context of quantum waves but which should be equally applicable to the optics problem. 

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Title  Uncertainties in multiphase flows through porous media  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Dr Matteo Icardi  
Description  Despite the recent significant developments in Digital Rock Physics (DRP), twophase flows in complex pore geometries are still not fully predictable, understood, and quantitatively reproducible. This is due to a number of factors including incorrect physical models, insufficient mesh resolution, unknown parameters and pore heterogeneity. The qualitative and quantitative effects of these uncertainties have not been studied yet. In this project, we aim to develop a modelling and simulation workflow to quantify uncertainty and assess the validity of simplified multiphase flow models in digitalised porous media images. Deterministic and MonteCarlo techniques, together with twophase flow solvers, will be used to perform a global sensitivity analysis of the problem. The project will see a collaboration of an industrial partner and the Geoenergy Research Centre in Nottingham. 

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Title  Datadriven coarsegraining and multiscale model reduction for ODEs and PDEs  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Dr Matteo Icardi  
Description  Many theoretical tools have been recently developed to reduce the complexity of highdimensional nonlinear ODEs or highlyresolved multiscale PDEs. These have now an enormous importance in computational chemistry, continuum mechanics, fluid dynamics, and dynamical systems in general. One of these bottomup formal approaches is the MoriZwanzig projection formalism for dynamical systems. At the same time, also datadriven topdown methods, have been widely studied in machine learning and in numerical analysis. In this project, we aim to connect these theoretical and numerical tools to make them applicable for practical applications, such as the molecular dynamics simulation of complex molecule chains, or the relaxation to equilibrium of nonlinear reactiondiffusion equations. In the first case, we can rely on the Hamiltonian structure of the fullresolution model, while the latter can be analysed through model decomposition or spectral analysis. The objective is to develop and implement flexible numerical approaches to deal with the model reduction of different model problems, by combining analytical derivations with numerical simulation data. 

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Title  Solitons in higher dimensions  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Prof Jonathan Wattis  
Description  The localisation of energy and its transport is of great physical interest in many applications. The mechanisms by which this occurs have been widely studied in onedimensional systems; however, in two and threedimensional systems a greater variety of waves and wave phenomena can be observed; for example, waves can be localised in one or both directions. This project will start with an analysis of the nonlinear Schrodinger equation (NLS) in higher space dimensions, and with more general nonlinearities (that is, not just $\gamma=1$). Current interest in the BoseEinstein Condensates which are being investigated in the School of Physics and Astronomy at Nottingham makes this topic particularly timely and relevant. The NLS equation also arises in the study of astrophysical gas clouds, and in the reduction of other nonlinear wave equations using small amplitude asymptotic expansions. For example, the reduction of the equations of motion for atoms in a crystal lattice; this application is particularly intriguing since the lattice structure defines special directions, which numerical simulations show are favoured by travelling waves. Also the motion of a wave through a hexagonal arrangement of atoms will differ from that through a square array of atoms. The project will involve a combination of theoretical and numerical techniques to the study such systems. 

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Title  Modelling the vibroacoustic response of complex structures  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Prof Gregor Tanner  
Description  The vibroacoustic response of mechanical structures (cars, airplanes, ...) can in general be well approximated in terms of linear wave equations. Standard numerical solution methods comprise the finite or boundary element method (FEM, BEM) in the low frequency regime and socalled Statistical Energy Analysis (SEA) in the highfrequency limit. Major computational challenges are posed by socalled midfrequency problems  that is, composite structures where the local wave length may vary by orders of magnitude across the components. The PhD project wil deal with extending these techniques towards a DEA/FEM hybrid method as well as considering FEM formulations of the method. The work will comprise a mix of analytic and numerical skills and will be conducted in close collaboration with our industrial partners CDH AG, Germany and Jaguar/Landrover, Gaydon, UK. 

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Title  Impulsivelygenerated fluid motions  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Prof John Billingham  
Description  In a series of papers over the past few years [13], my collaborators and I have studied how the motion of a solid body into an expanse of fluid generates complex and unexpected flow patterns. In this project, you will use numerical and asymptotic methods to study the impulsive motion of a plate into a 2D layer of inviscid fluid. In the case of a 90 degree intersection between the plate and the free surface, a jet is driven up the plate. At other angles, the dynamics are not clear, and will form the subject of this project. 

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Title  Nonlocal reaction diffusion equations  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Prof John Billingham  
Description  Nonlocal reactiondiffusion equations arise in many scientific areas, including population ecology and neuroscience. In this project, you will use numerical and asymptotic methods to study these equations. For example, the nonlocal Fisher equation, [2], with small diffusivity has recently been shown to have travelling wave solutions that consist of a sequence of localized spikes, [3]. Other interesting dynamics that can occur in similar equations, [1], include accelerating and decelerating travelling waves. Possible extensions include nonlocal equations in more than one spatial dimension and nonmonotonic kernels. 

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Title  Numerical Upscaling and model identification for LithiumIon batteries  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Dr Matteo Icardi  
Description  Lithiumion battery models for control applications are typically defined by system identification techniques and fail to capture the intrinsic functional dependence of the parameters on the material attributes and to predict irreversible and complex nonlinear phenomena such as fast (dis)charge and degradation. In this project, we propose new mathematical techniques to develop simple and efficient reduced order models, as an alternative to classical equivalent circuit models, to enable the fast, yet accurate, simulation of short and longterm behavior of lithiumion cells. Starting from the wellknown porous electrode theory and Newman’s model, we aim to derive simple differential equations that can retain the interesting features of the full model (e.g., solid diffusion, nonlinearities). We also propose a new integrated framework to incorporate both micro and system scale experimental data into our model via machinelearning approaches. This is collaborative project with the University of Warwick (Mathematics and WMG) and two industrial partners. 

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Title  Machine learning for firstprinciples calculation of physical properties.  

Group(s)  Industrial and Applied Mathematics  
Proposer(s)  Prof Richard Graham  
Description  The physical properties of all substances are determined by the interactions between the molecules that make up the substance. The energy surface corresponding to these interactions can be calculated from firstprinciples, in theory allowing physical properties to be derived abinitio from a molecular simulation; that is by theory alone and without the need for any experiments. Recently we have focussed on applying these techniques to model carbon dioxide properties, such as density and phase separation, for applications in Carbon Capture and Storage. However, there is enormous potential to exploit this approach in a huge range of applications. A significant barrier is the computational cost of calculating the energy surface quickly and repeatedly, as a simulation requires. In collaboration with the School of Chemistry we have recently developed a machinelearning technique that, by using a small number of precomputed abinitio calculations as training data, can efficiently calculate the entire energy surface. This project will involve extending the approach to more complicated molecules and testing its ability to predict macroscopic physical properties. This project will be jointly supervised by Dr Richard Wheatley in the School of Chemistry. 

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Title  Electromagnetic compatibility in complex environments: predicting the propagation of electromagnetic waves using wavechaos theory  

Group(s)  Industrial and Applied Mathematics, Mathematical Physics  
Proposer(s)  Dr Stephen Creagh, Prof Gregor Tanner  
Description  The focus of this project is the development of a mathematical framework to understand the propagation of electromagnetic fields within complicated environments – a challenging task especially in the high frequency limit. Modern technology is typically stuffed with electronic componentry. Devices ranging from a mobile phone to a pc to an Airbus A380 will have many internal electronic components operating at high frequencies and therefore radiating electromagnetic waves. If the waves radiated from one component are strong enough, they can interfere with the functioning of another component somewhere else in the unit. The field of Electromagnetic Compatibility (EMC) aims to mitigate these effects by better understanding the emitted radiation. The outcome of the research will help to design electronic devices, which are protected from interference from other EM sources within buildings, pc enclosures or even planes. The innovative idea in the proposed approach rests on combining EMfield propagation with ideas of chaos theory and nonlinear dynamics. In particular, the representation of waves emitted from a complex source is described in terms of their raydynamics in phase space using the socalled Wigner distribution function (WDF) formalism. It allows us to replace the wave propagation problem with one of propagating classical densities within phase space.


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Title  Wave propagation in complex builtup structures – tackling quasiperiodicity and inhomogeneity  

Group(s)  Industrial and Applied Mathematics, Mathematical Physics  
Proposer(s)  Prof Gregor Tanner, Dr Stephen Creagh  
Description  Computing the dynamic response of modern aerospace, automotive and civil structures can be a computationally challenging task. Characterising the structural dynamics in terms of waves in a uniform or periodic medium is often an important first step in understanding the principal propagating wave modes. Real mechanical structures are rarely fully periodic or homogeneous – variations in shape or thickness, boundaries and intersections as well as curvature destroy the perfect symmetry. The aim of the project is to extend periodic structure theory to wave propagation in quasiperiodic and inhomogeneous media such as stiffened structures. The modelling of waves can then be recast in terms of Bloch theory, which will be modified by using appropriate energy or flux conservation assumptions. The information about the propagating modes will then be implemented into modern highfrequency wave methods – such as the socalled Dynamical Energy Analysis developed in Nottingham  making it possible to compute the vibrational response of structures with arbitrary complexity at large frequencies.


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Title  Excitability in biology  the role of noisy thresholds  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Ruediger Thul, Prof Stephen Coombes  
Description  Excitability is ubiquitous in biology. Two important examples are the membrane potential of neurons or the dynamics of the intracellular calcium concentration. What characterises excitable systems is the presence of a threshold. For instance, neurons only fire when the membrane potential crosses a critical value. Importantly, the dynamics of excitable systems is often driven by fluctuations such as the opening of ion channels or the binding of hormones to a receptor. A mathematically and computationally appealing approach is to represent this biological noise by a random excitability threshold. This concept has already provided great insights into the dynamics of neurons that process sounds [1]. In this project, we will investigate the role of correlations of the noisy threshold in shaping cellular responses. Our applications will come from neuroscience in the form of single cell and neural field models as well as from cell signalling when we investigate travelling calcium waves. This will help us to understand the emergence of unusual firing patterns in the brain as well as of the wide variety of travelling calcium waves observed in numerous cell types. 

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Title  Spatiotemporal patterns with piecewiselinear regulatory networks  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Etienne Farcot  
Description  A number of fascinating and important biological processes involve 

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Title  Spine morphogenesis and plasticity  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Stephen Coombes, Dr Ruediger Thul  
Description  Mathematical Neuroscience is increasingly being recognised as a powerful tool to complement neurobiology to understand aspects of the human central nervous system. The research activity in our group is concerned with developing a sound mathematical description of subcellular processes in synapses and dendritic trees. In particular we are interested in models of dendritic spines [1], which are typically the synaptic contact point for excitatory synapses. Previous work in our group has focused on voltage dynamics of spineheads [2]. We are now keen to broaden the scope of this work to include developmental models for spine growth and maintenance, as well as models for synaptic plasticity [3]. Aberrations in spine morphology and density are well known to underly certain brain disorders, including Fragile X syndrome (which can lead to attention deficit and developmental delay) and depression [4]. Computational modelling is an ideal method to do insilico studies of drug treatments for brain disorders, by modelling their action on spine development and plasticity. This is an important complementary tool for drug discovery in an area which is struggling to make headway with classical experimental pharmaceutical tools. The mathematical tools relevant for this project will be drawn from dynamical systems theory, biophysical modelling, statistical physics, and scientific computation. 

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Title  Multiscale mechanochemical modelling of exerciseinduced asthma  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Bindi Brook, Dr Reuben O'Dea  
Description  Inflammation and airway hyperresponsiveness (leading to bronchoconstriction) are hallmarks of asthma. Detailed measurements of exhaled inflammatory markers during rest and exercise provide an indicator of the inflammatory processes that arise during exerciseinduced asthma. By combining this data with mechanistic models of cellsignalling, inflammatory cell recruitment and continuumbased nonlinear tissue mechanics models of the airways this project will provide insight into the development of bronchoconstriction during exercise. Model development will inform future experiments and interventions in human subjects. 

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Title  Rare event modelling for the progression of cancer  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Richard Graham, Prof Markus Owen  
Description  Purpose This project will apply cuttingedge mathematical modelling techniques to solve computational and modelling issues in predicting the evolution of cancerous tumours. The project will combine rare event modelling from the physical sciences and cellularlevel models from mathematical biology. The aim is to produce new cancer models with improved biological detail that can be solved on clinically relevant timescales, which can be decades.
Background A widespread problem in treating cancer is to distinguish indolent (benign) tumours from metastaticcapable primary tumours (tumours that can spread to other parts of the body). Although therapies for metastatic disease exist, metastatic disease is a significant cause of death in cancer patients. This problem can lead to misdiagnosis, unnecessary treatment and a lack of clarity on which treatments are most effective.
A predictive mathematical model of cancer development could assist with the above issues. However, as the progression of cancer to metastasis is a rare event, in a direct simulation, virtually all of the computational time is consumed in simulating the quasistable behaviour of the indolent tumour, revealing no information about progression. This generic problem of rare events is common in the physical sciences, where modern techniques have enabled rare events to be simulated and understood. This project will extend these techniques to cancer modelling. The project will build on a stateoftheart spatiotemporal cancer model, which models individual cancer cells in a host tissue, vascular networks and angiogenesis. In this model cells can divide, migrate or die, in response to their microenvironment of cell crowding and cell signalling. To this framework the project will add transitions between cell types, driven by random mutation events and intravasation events.
The project will use a rare event algorithm, forward flux sampling (FFS), to create a statistical map of the transition from indolent cancer to metastatic cancer. In a typical rare event transition the system spends the overwhelming majority of the time close to the start. Consequently, the sampling of the trajectory space is very uneven. Thus, despite a very long simulation the statistical resolution of the mechanism and crossing rate are very poor. FFS solves this problem by dividing the phase space into a series of interfaces that represent sequential advancement towards the rare event. The algorithm logs forward crossings of these interfaces and a series of trajectories are begun at these crossing points. This produces a far more even sampling of the trajectory space and so better statistics of the whole mechanism from a shorter simulation.


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Title  Stochastic Neural Network Modelling  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Stephen Coombes, Dr Ruediger Thul  
Description  Large scale studies of spiking neural networks are a key part of modern approaches to understanding the dynamics of biological neural tissue. One approach in computational neuroscience has been to consider the detailed electrophysiological properties of neurons and build vast computational compartmental models. An alternative has been to develop minimal models of spiking neurons with a reduction in the dimensionality of both parameter and variable space that facilitates more effective simulation studies. In this latter case the single neuron model of choice is often a variant of the classic integrateandfire model, which is described by a nonsmooth dynamical system with a threshold [1]. It has recently been shown [2] that one way to model the variability of neuronal firing is to introduce noise at the threshold level. This project will develop the analysis of networks of synaptically coupled noisy neurons. Importantly it will go beyond standard phase oscillator approaches to treat strong coupling and nonGaussian noise. One of the main mathematical challenges will be to extend the MasterStability framework for networks of deterministic limit cycle oscillators to the noisy nonsmooth case that is relevant to neural modelling. This work will determine the effect of network dynamics and topology on synchronisation, with potential application to psychiatric and neurological disorders. These are increasingly being understood as disruptions of optimal integration of mental processes subserved by distributed brain networks [3]. 

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Title  Cell signalling  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof John King  
Description  Cell signalling effects have crucial roles to play in a vast range of biological processes, such as in controlling the virulence of bacterial infections or in determining the efficacy of treatments of many diseases. Moreover, they operate over a wide range of scales, from subcellular (e.g. in determining how a particular drug affects a specific type of cell) to organ or population (such as through the quorum sensing systems by which many bacteria determine whether or not to become virulent). There is therefore an urgent need to gain greater quantitative understanding of these highly complex systems, which are wellsuited to mathematical study. Experience with the study of nonlinear dynamical systems would provide helpful background for such a project. 

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Title  Modelling DNA Chain Dynamics  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Jonathan Wattis  
Description  Whilst the dynamics of the DNA double helix are extremely complicated, a number of welldefined modes of vibration, such as twisting and bending, have been identified. At present the only accurate models of DNA dynamics involve largescale simulations of molecular dynamics. Such approaches suffer two major drawbacks: they are only able to simulate short strands of DNA and only for extremely short periods (nanoseconds). the aim of this project is to develop simpler models that describe vibrations of the DNA double helix. The resulting systems of equations will be used to simulate the dynamics of longer chains of DNA over long timescales and, hence, allow largerscale dynamics, such as the unzipping of the double helix, to be studied. 

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Title  Multiscale modelling of vascularised tissue  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Markus Owen  
Description  Most human tissues are perfused by an evolving network of blood vessels which supply nutrients to (and remove waste products from) the cells. The growth of this network (via vasculogenesis and angiogenesis) is crucial for normal embryonic and postnatal development, and its maintenance is essential throughout our lives (e.g. wound healing requires the repair of damaged vessels). However, abnormal remodelling of the vasculature is associated with several pathological conditions including diabetic retinopathy, rheumatoid arthritis and tumour growth. The phenomena underlying tissue vascularisation operate over a wide range of time and length scales. These features include blood flow in the existing vascular network, transport within the tissue of bloodborne nutrients, cell division and death, and the expression by cells of growth factors such as VEGF, a potent angiogenic factor. We have developed a multiscale model framework for studying such systems, based on a hybrid cellular automaton which couples cellular and subcellular dynamics with tissuelevel features such as blood flow and the transport of growth factors. This project will extend and specialise our existing model to focus on particular applications in one of the following areas: wound healing, retinal angiogenesis, placental development, and corpus luteum growth. This work would require a significant element of modelling, numerical simulation and computer programming. 

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Title  Selfsimilarity in a nanoscale islandgrowth  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Jonathan Wattis  
Description  Molecular Beam Epitaxy is a process by which single atoms are slowly deposited on a surface. These atoms diffuse around the surface until they collide with a cluster or another atom and become part of a cluster. Clusters remain stationary. The distribution of cluster sizes can be measured, and is observed to exhibit selfsimilarity. Various systems of equations have been proposed to explain the scaling behaviour observed. The purpose of this project is to analyse the systems of differential equations to verify the scalings laws observed and predict the shape of the sizedistribution. The relationship of equations with other models of deposition, such as reactions on catalytic surfaces and polymer adsorption onto DNA, will also be explored. 

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Title  Sequential adsorption processes  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Jonathan Wattis  
Description  The random deposition of particles onto a surface is a process which arises in many subject areas, and determining its efficiency in terms of the coverage attained is a difficult problem. In onedimension the problem can be viewed as how many cars can be parked along a road of a certain length; this problem is similar to a problem in administering gene therapy in which polymers need to be designed to package and deliver DNA into cells. Here one wishes to know the coverage obtained when one uses a variety of polymer lengths to bind to strands of DNA. The project will involve the solution of recurrence relations, and differential equations, by a mixture of asymptotic techniques and stochastic simulations. 

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Title  Robustness of biochemical network dynamics with respect to mathematical representation  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Etienne Farcot  
Description  In the recent years, a lot of multidisciplinary efforts have been 

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Title  Neurocomputational models of hippocampusdependent place learning and navigation  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Stephen Coombes  
Description  This project will be based at the University of Nottingham in the School of Mathematical Sciences and the School of Psychology. 

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Other information  Eligibility/Entry Requirements: We require an enthusiastic graduate with a 1st class degree in Mathematics (or other highly mathematical field such as Physics or Chemistry), preferably at MMath/MSc level, or an equivalent overseas degree (in exceptional circumstances a 2:1 class degree, or equivalent, can be considered). Apply: This studentship is available to start from September 2017 and remain open until it is filled. To apply please visit the University Of Nottingham application page: http://www.nottingham.ac.uk/pgstudy/apply/applyonline.aspx Funding NotesSummary: UK/EU students  Tuition Fees paid, and full Stipend at the RCUK rate, which is £14,296 per annum for 2016/17. There will also be some support available for you to claim for limited conference attendance. The scholarship length will be 3 or 3.5, depending on the qualifications and training needs of the successful applicant. 
Title  Spirals and autosoliton scattering: interface analysis in a neural field model  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Stephen Coombes, Dr Daniele Avitabile  
Description  Neural field models describe the coarse grained activity of populations of interacting neurons. Because of the laminar structure of real cortical tissue they are often studied in 2D, where they are well known to generate rich patterns of spatiotemporal activity. Typical patterns include localised solutions in the form of travelling spots as well as spiral waves [1]. These patterns are naturally defined by the interface between low and high states of neural activity. This project will derive the dimensionally reduced equations of motion for such interfaces from the full nonlinear integrodifferential equation defining the neural field. Numerical codes for the evolution of the interface will be developed, and embedded in a continuation framework for performing a systematic bifurcation analysis. Weakly nonlinear theory will be developed to understand the scattering of multiple spots that behave as autosolitons, whilst strong scattering solutions will be investigated using the scattor theory that has previously been developed for multicomponent reaction diffusion systems [2]. 

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Other information  S Coombes, H Schmidt and I Bojak 2012 Interface dynamics in planar neural field models, Journal of Mathematical Neuroscience, 2:9 
Title  Modelling signal processing and sexual recognition in mosquitoes: neural computations in insect hearing systems  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Daniele Avitabile, Prof Stephen Coombes  
Description  Insects have evolved diverse and delicate morphological structures in order to When a sound wave reaches the head of a mosquito, the antenna oscillates under the Recent studies have shown that mosquitoes of either sex use both their antenna and Even though some models of mosquitoes hearing systems have been proposed in the past, 

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Title  Nonsmooth dynamical systems: from nodes to networks  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Stephen Coombes, Dr Ruediger Thul  
Description  There is a growing appreciation in the applied mathematics community that many real world systems can be described by nonsmooth dynamical systems. This is especially true of impacting mechanical systems or systems with switches [1]. The latter are ubiquitous in fields ranging from electrical engineering to biology. In a neuroscience context nonsmooth models now pervade the field, with exemplars being low dimensional piecewise linear models of excitable tissue, integrateandfire neurons, and the Heaviside nonlinearity invoked in neural mass models of cortical populations. Despite the relevance and preponderance of such models their mathematical analysis lags behind that of their smooth counterparts. This PhD project will redress this balance, by translating recent advances from nonsmooth dynamical systems to neuroscience as well as developing new approaches. The initial phase of the project will consider the periodic forcing of a nonsmooth node, as a precursor to exploring recurrent network dynamics. The Arnol'd tongue structure will be explored for modelocked states of oscillatory systems, as well as bifurcation diagrams for excitable systems. This will rely heavily on the construction of socalled saltation operators, to ensure the proper propagation of perturbations. Similarly, chaos will be studied using a suitable generalisation of the Liapunov exponent. The subsequent work will address emergent network dynamics, particularly in neural systems with chemical and electrical connections. Explicit analysis at the network level will build upon results at the single node level, with a focus on understanding patterns of synchrony, clustering, and more exotic chimera states [2]. This aspect of the project will first pursue the extension of the Master Stability framework for assessing stability of the synchronous state to treat nonsmooth systems with nonsmooth interactions [3]. The next stage will develop more general techniques, tapping into tools from computational group theory [4], to provide a more complete understanding of the spatiotemporal states that can be generated in realistic neural networks. 

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Title  Pattern formation in biological neural networks with rebound currents  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Stephen Coombes  
Description  Waves and patterns in the brain are well known to subserve natural computation. In the case of spatial navigation the geometric firing fields of grid cells is a classic example. Grid cells fire at the nodes of a hexagonal lattice tiling the environment. As an animal approaches the centre of a grid cell firing field, their spiking output increases in frequency. Interestingly the spacing of the hexagonal lattice can range from centimetres to metres and is thought to underly the brain's internal positioning system. The mechanism for controlling this global spatial scale is linked to a local property of neurons within an inhibitory coupled population, namely rebound firing. This arises through the activation of hyperpolarisationactivated channels. For the case of grid cells in the medial enthorinal cortex this gives rise to a socalled I_h current. Many other cells types also utilise rebound currents for firing, and in particular thalamocortical relay cells do so via slow Ttype calcium channels (the I_T current). This gives rise to saltatory lurching waves in thalamic slices. Both of these examples show that rebound currents can contribute significantly to important spatiotemporal brain dynamics. This project will investigate such important phenomenon from a mathematical perspective. One of the most successful approaches to modelling a spiking neuron involves using an integrateandfire process. This couples an ODE model with a reset rule for generating firing events. Almost by definition this precludes analysis using traditional approaches from the theory of smooth dynamical systems. This mathematical challenge is compounded at the network level when recognising that synaptic currents that mediate interactions between neurons are event driven rather than directly state dependent. Fortunately there is a growing appreciation that these mathematical biology challenges can benefit from a crossfertilisation of ideas with those being developed in the engineering community for impact oscillators and piecewise linear systems. This PhD will translate and develop mathematical methodologies from nonsmooth dynamical systems and apply them to two important neurobiological problems. The first being to analytically determine grid cell firing fields in a two dimensional spiking neural field model with an I_h rebound current, and the second to determine lurching wave speed and stability in a firing rate neural field model with an I_T rebound current. As well as mathematical techniques from nonsmooth dynamics, the project will involve large scale simulations of spiking networks, Evans functions for determining wave stability, and require an enthusiasm for learning about neuroscience. 

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Title  Mechanistic models of force adaptation in airway smooth muscle cells  application to asthma  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Bindi Brook  
Description  Lung inflammation and airway hyperresponsiveness (AHR) are hallmarks of asthma, but their interrelationship is unclear. Excessive shortening of airway smooth muscle (ASM) in response to bronchoconstrictors is likely an important determinant of AHR. Hypercontractility of ASM could stem from a change in the intrinsic properties of the muscle, or it could be due to extrinsic factors such as chronic exposure of the muscle to inflammatory mediators in the airways with the latter being a possible link between lung inflammation and AHR. The aim of this project will be to investigate the influence of chronic exposure to a contractile agonist on the forcegenerating capacity of ASM via a celllevel model of an ASM cell. Previous experimental studies have suggested that the muscle adapts to basal tone in response to application of agonist and is able to regain its contractile ability in response to a second stimulus over time. This is thought to be due to a transformation in the cytoskeletal components of the cell enabling it to bear force, thus freeing up subcellular contractile machinery to generate more force. Force adaptation in ASM as a consequence of prolonged exposure to the many spasmogens found in asthmatic airways could be a mechanism contributing to AHR seen in asthma. We will develop and use a cell model in an attempt to either confirm this hypothesis or determine other mechanisms that may give rise to the observed phenomenon of force adaptation. 

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Title  Synchronisation and propagation in human cortical networks  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Reuben O'Dea  
Description  Around 25% of the 50million epilepsy sufferers worldwide are not responsive to antiepileptic medication; improved understanding of this disorder has the potential to improve diagnosis, treatment and patient outcomes. The idea of modelling the brain as a complex network is now well established. However, the emergence of pathological brain states via the interaction of large interconnected neuronal populations remains poorly understood. Current theoretical study of epileptic seizures is flawed by dynamical simulation on inadequate network models, and by the absence of customised network measures that capture pathological connectivity patterns. 

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Title  Multiscale modelling of cell signalling and mechanics in tissue development and cancer  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof John King, Dr Reuben O'Dea  
Description  Cells respond to their physical environment through mechanotransduction, the translation of mechanical forces into biochemical signals; evoked cell phenotypic changes can lead to an altered cell microenvironment, creating a developmental feedback. Interplay between such mechanosentive pathways and other inter and intracellular signalling mechanisms determines cell differentiation and, ultimately, tissue development. Such developmental mechanisms have key relevance to the initiation and development of cancer, a disease of such inherent complexity (involving the interaction of a variety of processes across disparate spatiotemporal scales, from intracellular signalling cascades to tissuelevel mechanics) that, despite a wealth of theoretical and experimental studies, it remains a leading cause of mortality and morbidity: in the UK, more than one in three people will develop some form of cancer. There is therefore an urgent need to gain greater quantitative understanding of these highly complex systems, which are wellsuited to mathematical study. 

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Title  Patterns of synchrony in discrete models of gene networks  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Etienne Farcot  
Description  One of the greatest challenges of biology is to decipher the relation between genotype and 

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Title  Cell cycle desynchronization in growing tissues  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Etienne Farcot  
Description  A very general phenomenon is the fact that coupled oscillators tend to naturally 

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Title  Mechanical models of growthfactor activation in asthmatic airway remodelling.  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Bindi Brook, Dr Reuben O'Dea, Prof Markus Owen  
Description  Airway remodelling in asthma has until recently been associated almost exclusively with inflammation over long timescales. Recent evidence suggests that stretchinduced activation of a proremodelling growth factor from the extracellular matrix during bronchoconstriction (as a result of airway smooth muscle contraction) plays an important role in airway remodelling. Traditional topdown continuummechanics approaches fail to account for the movement of cells relative to extracellular matrix and the corresponding adhesionmediated opening of latent stores of the growth factor. Multiscale mechanics models of the airway tissue accounting for both cells, ECM and their interactions, will be developed in this project, building on a previous model of cellECM interactions [1]. The models will be informed by ongoing experiments of stretchinduced TGFbeta activation in precisioncut lung slices at the tissue scale, as well as atomic force microscopy experiments at the subcellular scale. There will also be the opportunity to design new experiments based on model results. 

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Title  From molecular dynamics to intracellular calcium waves  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Ruediger Thul, Prof Stephen Coombes  
Description  Intracellular calcium waves are at the centre of a multitude of cellular processes. Examples include the generation of a heartbeat or the beginning of life when egg cells are fertilised. A key driver of intracellular calcium waves are ion channels, which are large molecules that control the passage of calcium ions across a cell. Importantly, these ion channels display stochastic behaviour such as random opening and closing. A key challenge in mathematical physiology and computational biology is to link this molecular stochasticity to travelling calcium waves. In this project, we will use a firediffusefire (FDF) model of intracellular calcium waves and couple it to Markov chains of ion channels. Traditionally, simulating large numbers of Markov chains is computationally expensive. Our goal is to derive an effective description for the stochastic ion channel dynamics. This will allow us to incorporate the molecular fluctuations from the ion channels into the FDF model without having to evolve Markov chains. This will put us in an ideal position to answer current questions in cardiac dynamics (How does an irregular heart beat emerge, leading to a potentially lifethreatening condition?) as well as to elucidate fundamental concepts in cell signalling.


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Title  Waves on a folded brain  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Daniele Avitabile, Prof Stephen Coombes  
Description  The human brain has a wonderfully folded cortex with regions of both negative and positive curvature at gyri and sulci respectively. As the state of the brain changes waves of electrical activity spread and scatter through this complicated surface geometry. This project will focus on the mathematical modelling of realistic cortical tissue and the analysis of wave propagation and scattering using techniques from dynamical systems theory and scientific computation. 

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Title  Modelling macrophage extravasation and phenotype selection  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Prof Markus Owen  
Description  Macrophages are a type of white blood cell, a vital component of the immune system, and play a complex role in tumour growth and other diseases. Macrophage precursors, called monocytes, are produced in the bone marrow and enter the blood, before leaving the bloodstream (extravasating). Monocyte extravasation requires adhesion to, and active movement through, the blood vessel wall, both of which are highly regulated processes. Once in the tissue, monocytes begin to differentiate into macrophages, and it has become clear that the tissue microenvironment is a crucial determinant of macrophage function [1]. A spectrum of phenotypes have been identified: at one end, macrophages produce a variety of signals that are beneficial to a tumour, including those that promote the formation of new blood vessels and suppress inflammation. At the other end of the scale, inflammation is promoted and appropriately stimulated macrophages can kill tumour cells. 

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Title  Next generation neural field models on spherical domains  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Rachel Nicks  
Description  The number of neurons in the brain is immense (of the order of 100 billion). A popular approach to modelling such cortical systems is to use neural field models which are mathematically tractable and which capture the large scale dynamics of neural tissue without the need for detailed modelling of individual neurons. Neural field models have been used to interpret EEG and brain imaging data as well as to investigate phenomena such as hallucinogenic patterns, shortterm (working) memory and binocular rivalry. A typical formulation of a neural field equation is an integrodifferential equation for the evolution of the activity of populations of neurons within a given domain. Neural field models are nonlinear spatially extended pattern forming systems. That is, they can display dynamic behaviour including spatially and temporally periodic patterns beyond a Turing instability in addition to localised patterns of activity. The majority of research on neural field models has been restricted to the line or planar domains, however the cortical white matter system is topologically close to a sphere. It is relevant to study neural field models as pattern forming systems on spherical domains, particularly as the periodic boundary conditions allow for natural generation (via interference) of the standing waves observed in EEG signals. This project will build on recent developments in neural field theory, focusing in particular on extending to spherical geometry the neural field equations arising from “Next generation neural mass models” (which incorporate a description of the evolution of synchrony within the system). Techniques from dynamical systems theory, including linear stability analysis, weakly nonlinear analysis, symmetric bifurcation theory and numerical simulation will be used to consider the global and local patterns of activity that can arise in these models. 

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Title  Multiscale modelling of signalling microdomains  

Group(s)  Mathematical Medicine and Biology  
Proposer(s)  Dr Ruediger Thul, Prof Stephen Coombes  
Description  A key role of cells is to translate external signals into appropriate cellular responses. For example, when cells that line blood vessels experience weak stimulation, they initiate the expression of certain genes, while for strong stimuli, they begin to move. How cells accomplish such diverse responses is still an open question. What has transpired, though, is that so called microdomains are vital for cellular decisionmaking. Microdomains are small parts of a cell where molecular mediators and switches are concentrated in close proximity. This is advantageous since cell signalling intrinsically relies on molecules interacting, and if they are close to each other, chances are higher that signal transduction is successful. In many cases, these signalling pathways rely on small molecules that diffuse through the microdomain and hence can carry information from one molecular partner to the next. To appreciate the full potential of the signalling micordomains, it is crucial to have a comprehensive understanding of the dynamics of these diffusible messengers. In this project, we will use a combination of semianalytical and numerical techniques to develop three dimensional models of signalling microdomains. In particular, we will investigate how the intracellular calcium concentration changes in space and time within microdomains, and how these changes affect signal transduction. Gaining deeper insights into microdomains is key for understanding for understanding healthy physiology such as fertilisation and muscle contraction as well as diseases such as immunodeficiency and neurological disorders. The model will be informed by experiments conducted at Oxford and Penn State University. 

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Title  Exploiting network symmetries for analysis of dynamics on neural networks  

Group(s)  Mathematical Medicine and Biology, Industrial and Applied Mathematics  
Proposer(s)  Dr Rachel Nicks, Prof Stephen Coombes, Dr Paul Matthews  
Description  Networks of interacting dynamical systems occur in a huge variety of applications including gene regulation networks, food webs, power networks and neural networks where the interacting units can be individual neurons or brain centres. The challenge is to understand how emergent network dynamics results from the interplay between local dynamics (the behaviour of each unit on its own), and the nature and structure of the interactions between the units. Recent work has revealed that real complex networks can exhibit a large number of symmetries. Network symmetries can be used to catalogue the possible patterns of synchrony which could be present in the network dynamics, however which of these exist and are stable depends on the local dynamics and the nature of the interactions between units. Additionally, the more symmetry a network has the more possible patterns of synchrony it may possess. Computational group theory can be used to automate the process of identifying the spatial symmetries of synchrony patterns resulting in a catalogue of possible network cluster states. This project will extend current methods for analysing dynamics on networks of (neural) oscillators through automating the process of determining possible phase relations between oscillators in large networks in addition to spatial symmetries. This will be used to investigate dynamics on coupled networks of simplified (phaseamplitude reduced or piecewiselinear) neuron and neural population models. We will also consider the effect on the network dynamics of introducing delays in the coupling between oscillators which will give a more realistic representation of interactions in real world networks. 

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Title  Analysing and interpreting neuroimaging data using mathematical frameworks for network dynamics  

Group(s)  Mathematical Medicine and Biology, Mathematical Medicine and Biology  
Proposer(s)  Prof Stephen Coombes  
Description  Modern noninvasive probes of human brain activity, such as magnetoencephalography (MEG), give high temporal resolution and increasingly improved spatial resolution. With such a detailed picture of the workings of the brain, it becomes possible to use mathematical modelling to establish increasingly complete mechanistic theories of spatiotemporal neuroimaging signals. There is an ever expanding toolkit of mathematical techniques for addressing the dynamics of oscillatory neural networks allowing for the analysis of the interplay between local population dynamics and structural network connectivity in shaping emergent spatial functional connectivity patterns. This project will be primarily mathematical in nature, making use of notions from nonlinear dynamical systems and network theory, such as coupledoscillator theory and phaseamplitude network dynamics. Using experimental data and data from the output of dynamical systems on networks with appropriate connectivities, we will obtain insights on structural connectivity (the underlying network) versus functional connectivity (constructed from similarity of real time series or from timeseries output of oscillator models on networks). The project will focus in particular on developing techniques for the analysis of dynamics on “multilayer networks” to better understand functional connectivity within and between frequency bands of neural oscillations. This project will be in collaboration with Dr Matt Brookes from the Nottingham MEG group. 

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Title  Mathematical modelling of macromolecular capillary permeability  

Group(s)  Mathematical Medicine and Biology, Scientific Computation  
Proposer(s)  Dr Reuben O'Dea, Dr Matthew Hubbard  
Description  The primary function of blood vessels is to transport molecules to tissues. In diseases such as cancer and diabetes this transport, particularly of large molecules such as albumin, can be an order of magnitude higher than normal. The project is to model transient flow of macromolecules across the vascular wall in physiology and pathology. With additional supervision from Dr Kenton Arkill and Professor David Bates (Medicine), the doctoral student will join a team that includes medical researchers, biophysicists and mathematicians acquiring structural and functional data. Detailed microscale models of vascular wall hydrodynamics and transport properties will be employed; in addition, powerful multiscale homogenisation techniques will be exploited that enable permeability and convection parameters on the nanoscale to be linked through the microscale into translatable information on the tissue scale. Computational simulations will be used to investigate and understand the model behaviour, including, for example, stochastic and multiphysics effects in the complex diffusionconvection nanoscale environment. The project will afford a great opportunity to form an information triangle where modelling outcomes will determine physiological experiments to feedback to the model. Furthermore, the primary results will inform medical researchers on potential molecular therapeutic targets. 

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Title  Modelling lymphatic vessel pumping  

Group(s)  Mathematical Medicine and Biology, Scientific Computation  
Proposer(s)  Dr Bindi Brook, Dr Matthew Hubbard  
Description  The efficacy of lymphatic vessels for collecting and pumping lymph from interstitial tissues is key in returning fluid back to the cardiovascular system. Impaired pumping can lead to debilitating conditions such as lymphedema (often as a result of lymph node removal during breast cancer surgery). Upscaling current models of lymphatic pumping to large networks is currently computationally inefficient. This project aims to develop network models of lymphatic vessels that accounts for the complex active mechanics as well as valve behaviour of these vessels to provide deeper insights into how mechanical therapies can be developed to alleviate lymphedema. 

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Title  Parameter estimation and uncertainty quantification in a multidisciplinary study of asthmatic airway remodelling  

Group(s)  Mathematical Medicine and Biology, Statistics and Probability  
Proposer(s)  Dr Bindi Brook, Dr Reuben O'Dea, Dr Theodore Kypraios  
Description  Inflammation, airway hyperresponsiveness and airway remodelling are key characteristics of asthma, but it is unclear how they are interconnected. A recent comprehensive experimental in vivo asthma mouse study quantifying structural changes and how they relate to the inflammatory state in the airway, has generated an unprecedented amount of data to inform a mechanistic model airway remodelling in asthma [1]. Some parameter sets are welldefined from experimental data but others provide high levels of uncertainty in parameter value and model selection. This project seeks to understand how uncertainties in parameter estimation and model selection influence prediction, adding significant value to ongoing experiments, and dramatically increase the predictive power of the mechanistic model. 

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Title  Optimising experiments for developing ion channel models  

Group(s)  Mathematical Medicine and Biology, Statistics and Probability  
Proposer(s)  Dr Gary Mirams, Dr Simon Preston  
Description  Background: in biological systems ion channel proteins sit in cell membranes and selectively allow the passage of particular types of ions, creating currents. Ion currents are important for many biological processes, for instance: regulating ionic concentrations within cells; passing signals (such as nerve impulses); or coordinating contraction of muscle (skeletal muscle and also the heart, diaphragm, gut, uterus etc.). Mathematical ion channel electrophysiology models have been used for thousands of studies since their development by Hodgkin & Huxley in 1952 [1], and are the basis for whole research fields, such as cardiac modelling and brain modelling [2]. It has been suggested that there are problems in identifying which set of equations is most appropriate as an ion channel model. Often it appears different structures and/or parameter values could fit the training data equally well, but they may make different predictions in new situations [3]. Eligibility/Entry Requirements: this PhD will suit a graduate with a 1st class degree in Mathematics (or other highly mathematical field such as Physics), ideally at the MMath/MSc level, or an equivalent overseas degree. Prior knowledge of biology is not essential. 

Relevant Publications 


Other information  Please see Gary Mirams' research homepage for more information. 
Title  Operational tasks in quantum information science and beyond  

Group(s)  Mathematical Physics  
Proposer(s) 
Prof Gerardo Adesso Notice: Undefined index: pmzll in /maths/www/html/postgraduate/projects/index.php on line 560 Notice: Undefined index: pmzll in /maths/www/html/postgraduate/projects/index.php on line 560 , 

Description  Over the last decades, quantum information has taught us that many operational tasks are much more efficiently performed exploiting quantum mechanics than it would be possible in a purely classical world. If one wants to assess the performance of a real device, a comparison with its ‘intrinsic’ limitations as deriving from theoretical considerations has to be made. Determining those bounds is one of our goals as information scientists. This raises the problem of choosing what theoretical framework to use for the above considerations. There are two main alternatives: (i) one could choose to ‘trust’ quantum mechanics; or (ii) one could instead look at limitations arising only from ‘deeper’ requirements, such as the nosignaling constraint. Limitations of this second kind do not determine uniquely the mathematical features of the theory, leaving room for several different alternatives. Thus, in order to pursue the program (ii), one needs to handle a wider class of theories (generically called ‘general probabilistic theories’ or GPTs) that encompasses classical probability theory and quantum mechanics as special cases. For an introduction to the GPT formalism, see for instance [1] or [2, §II]. The main goal of this PhD project is to look at various operationally relevant tasks and analyse their ultimate performances in the sense of (ii), following the blueprint of [2] at a higher degree of generality. Despite the ‘postquantum’ nature of the project, an analysis of the quantum case (i) has to be carried out whenever it is not already covered by the existing literature. A distinctive feature of this project is that it can be adapted to the personal taste and preferences of the candidate. In fact, many possible directions can be taken, one for each task one chooses to focus on. For the sake of concreteness, let us give three explicit examples: a) Shared quantum entanglement can enhance the classical communication capability of a noiseless channel, a property known as quantum superdense coding (see [3, §6.2.3] or [4, §2.3]. Is there an analogous protocol for other GPTs? And if the answer is affirmative, what is the ultimate limit on the information gain that one can achieve by sending a local share of dimension d of a suitable entangled state? b) Grover’s search algorithm [4, §6.1] allows us to exploit quantum mechanics to conduct a search in an unstructured database of N objects using only √N oracle calls. This is known to be optimal in the quantum case [4, §6.6]. Can one do better in other GPTs? How much better? c) Quantum data locking [5] rests on the existence of bipartite quantum states whose locally accessible correlations can be greatly boosted by means of a small amount of classical communication between the parties. Are there GPTs that perform better than quantum mechanics at data locking? 

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Title  Quantum Thermal Engineering  

Group(s)  Mathematical Physics  
Proposer(s) 
Prof Gerardo Adesso Notice: Undefined index: pmzlac in /maths/www/html/postgraduate/projects/index.php on line 560 Notice: Undefined index: pmzlac in /maths/www/html/postgraduate/projects/index.php on line 560 , 

Description  In essence, quantum thermodynamics aims at unveling the connections between quantum physics and thermodynamics. Even if statistical mechanics teaches us that thermodynamics is only an effective theory emerging in the limit of large particle numbers, an individual quantum system can, in fact, convert heat to work or produce refrigeration in pretty much the same way as a car engine or a household refrigerator. Understanding the extent of this analogy would help us answer fundamental questions such as: Which ingredients are necessary for thermodynamic behaviour on an individual quantum system?, as well as more pragmatic questions such as: Can quantum effects help to bend the laws of quantum thermodynamics? Even if they cannot, can quantum thermodynamic devices assist in the deployment of quantum technologies? Quantum thermodynamics was born side by side with the theory of open quantum systems, back in the late 1970s, and developped slowly for over two decades. Only very recently, has the field started to attract an everincreasing interest from a wide variety of communnities, encompassing condensed matter physics, quantum information theory, statistical mechanics, or quantum manybody physics. Most of the existing restuls in the field are limited to the canonical scenario of systems weakly coupled to equilibrium environments. In this research programme, we shall use instead cuttingedge tools for the treatment of open quantum systems srontgly coupled to their environments—i.e. exact methods, such as quantum Langevin equations, as well as perturbative techniques such as the polaron transformation, the reaction coordinate mapping, collisional models, dissipation into finite baths, etc.—. The goal of this programme is to generalise the existing results in the literature about the performance limitations of quantum thermodynamic cycles to the strong coupling regime. In turn, understanding the thermodynamics of strongly coupled open quantum systems would ultimately allow to formulate systembath coupling schemes tailormade so as to e.g. maximise the energy efficiency of a heat devise, or its power output, or both. The successful candidate should have a strong background in quantum mechanics and, ideally, also on thermodynamics, statistical mechanics, fluid mechanics, quantum optics, and/or molecular physics. Good analytical skills and high motivation are essential. No specific programming/numerical skills are required, although familiarity with e.g. Matlab, Mathematica or Python would be desirable. 

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Title  Coherent state path integrals in manybody physics  

Group(s)  Mathematical Physics  
Proposer(s)  Dr Alexander Ossipov  
Description  Path integrals were originally introduced by Richard Feynman as an alternative formulation of a single particle quantum mechanics [1]. The advantage of this approach is that it deals with the classical action calculated on all possible quantum trajectories instead of noncommutative operators.
The coherent state path integrals generalise this idea and can be applied to more complicated Hamiltonians such as manybody interacting systems [2]. Despite a wide range of successful applications of the coherent state path integrals in many areas of modern theoretical physics, usually they are calculated only perturbatively.
The aim of this project is to develop a new nonperturbative approach for evaluation of the coherent state path integrals applied to manybody systems such as the BoseHubbard model. 

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Title  Quantum Resource Theories  

Group(s)  Mathematical Physics  
Proposer(s)  Prof Gerardo Adesso  
Description  The emergence of quantum information theory in the last three decades has led to a crucial reassessment of quantum effects such as superposition and entanglement: from poorly understood and even paradoxical concepts, these are now regarded as fundamental ingredients to achieve tasks otherwise impossible within the realm of classical physics, thus enabling a wealth of innovative technologies. At the core of this revolution lies the formalisation and characterisation of such phenomena as physical resources. Initiated with quantum entanglement, and successfully applied e.g. to purity, coherence [1], and informational nonequilibrium in thermodynamics, this applicationdriven viewpoint motivates the formulation of resource theories, that is, quantitative theories capturing the resource character of physical traits in a mathematically rigorous fashion. In very general terms, resource theories can be thought of as a radically new way of doing science, that takes the perspective of restricted agents who want to optimize given tasks of practical relevance. This project aims to advance the current frontiers of knowledge on resource theories for quantum phenomena and physics more broadly. In particular, possible directions include: i) Develop the mathematical foundations of resource theories, including an operational formalism for multiple, possibly competing resources and their interconnections, and a general framework to study the relations between different subjective agents; ii) Further apply the concept of resource theories to physical quantities such as nonclassicality, coherence, uncertainty, etc., providing rigorous methods to validate existing experimental approaches to quantum optics and information, and delivering new tools to quantify the tradeoff of different resources in operational tasks (e.g. distillation, activation, etc.); iii) Apply results from resource theories to draw conclusions on fundamental limitations of physical processes, e.g. to characterise the structure of thermodynamics from macro to nano and quantum scale, and the ultimate performance of quantum clocks and sensors in realistic conditions.
More details on resource theories are provided in the following. A resource theory is a framework to study the possible actions of agents given certain constraints, which may stem e.g. from fundamental physical laws such as energy conservation, or technical limitations in experimental settings. The agents’ constraints are specified by a set of operations which are considered free to implement. Any other operation comes at a cost, requiring the use of a resource. Similarly, the states of the system which can be prepared using only free operations are named free states, while any other is a resource state. Once this structure is in place, one can address a number of key questions, such as: Under which conditions can a state be converted into another by using only free operations? What makes a good quantifier of the resource content of a state? Which are the most resourceful states for practical applications given the physical constraints in place? The conventional paradigm of entanglement in quantum information theory is based on two or more agents in distant laboratories, so that local operations and classical communication (LOCC) are assumed to be free. Quantum entanglement is then the resource which allows agents to perform operations beyond LOCC, enabling tasks such as teleportation and dense coding. The theory of entanglement manipulation, quantification, and operational interpretation is precisely the resource theory defined by LOCC as the free operations. It is a remarkable fact that the developments in this resource theory have been pivotal for the quantum technology revolution we are witnessing in this century, leading e.g. to commercial quantum communication devices. Similarly, successful applications of resource theories to informational nonequilibrium, asymmetry, and coherence (among all) have led in the last decade to fundamental insights, such as revisions to the second law of thermodynamics for smallscale systems and an extension of Noether’s theorem, and hold a tremendous – and still largely unexplored – potential impact on further technological advances.
This project is motivated by questions such as:  Can we describe all useful signatures of nonclassicality from first principles, compiling a family tree of quantum resources and their functional interrelations?  Are there universal laws underpinning the conversion between different resources and entailing an operational framework to quantify them, irrespective of specific nature?  How best can quantum devices operate under competing constraints, such as energy conservation, locality, and the inability to create superposition in a reference basis?  What does thermodynamics allow or deny for physical machines at the quantum scale, once coherence effects and the subjectivity of agents are incorporated into the theory?  Can we derive practical bounds on the performance of quantum technologies, i.e. metrological precision and secure key rate, tailored to experimental costs and imperfections?


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Title  Models of Quantum Geometry  

Group(s)  Mathematical Physics  
Proposer(s)  Prof John Barrett  
Description  Noncommutative geometry is a generalisation of differential geometry where the "functions" on the space are not required to commute when multiplied together. This study is based on the approach to noncommutative geometry pioneered by Alain Connes. It has a number of applications, the most spectacular being the discovery that the fields in the standard model of particle physics have the structure of a noncommutative geometry. This noncommutativity relates to the "internal space" i.e. a geometric structure at every point of spacetime, and reveals itself in the nonabelian gauge groups, the Higgs and their couplings to fermion fields. The new idea is to use the noncommutative geometry also for spacetime itself, which one hopes will eventually give a coherent explanation of the structure of spacetime at the Planck scale. There are a number of projects investigating aspects of these quantum geometry models and related mathematics. It also uses techniques from topology, algebra, category theory and geometry, as well as numerical computations. The motivation is to study models that include gravity, working towards solving the problem of quantum gravity, and to study implications for particle physics. For the latest information on this research, please see my homepage https://johnwbarrett.wordpress.com/ 

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Title  Hydrodynamic simulations of rotating black holes  

Group(s)  Mathematical Physics  
Proposer(s)  Dr Silke Weinfurtner  
Description  We are currently carrying out an experiment to study the effects occurring around effective horizons in an analogue gravity system. In particular, the scientific goals are to explore superradiant scattering and the black hole evaporation process. To address this issue experimentally, we utilize the analogy between waves on the surface of a stationary draining fluid/superfluid flows and the behavior of classical and quantum field excitations in the vicinity of rotating black. This project will be based at the University of Nottingham at the School of Mathematical Sciences. The two external collaborators are Prof. Josef Niemela (ICTP, Trieste in Italy) and Prof. Stefano Liberati (SISSA, Trieste in Italy). The external consultant for the experiment is Prof. Bill Unruh, who will be a regular visitor. The PhD student will be involved in all aspects of the experiments theoretical as well experimental. We require an enthusiastic graduate with a 1st class degree in Mathematics/Physics/Engineering (in exceptional circumstances a 2(i) class degree can be considered), preferably of the MMath/MSc level. Candidates would need to be keen to work in an interdisciplinary environment and interested in learning about quantum field theory in curved spacetimes, fluid dynamics, analogue gravity, and experimental techniques such as flow visualisation (i.g. Particle Imaging or Laser Doppler Velocimetry) and surface measurements (i.g. profilometry methods). 

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Title  Acceleration, black holes and thermality in quantum field theory  

Group(s)  Mathematical Physics  
Proposer(s)  Dr Jorma Louko  
Description  Hawking's 1974 prediction of black hole radiation continues to inspire the search for novel quantum phenomena associated with global properties of spacetime and with motion of observers in spacetime, as well as the search for laboratory systems that exhibit similar phenomena. At a fundamental level, a study of these phenomena provides guidance for developing theories of the quantum mechanical structure of spacetime, including the puzzle of the microphysical origin of black hole entropy. At a more practical level, a theoretical control of the phenomena may have applications in quantum information processing in situations where gravity and relative motion are significant, such as quantum communication via satellites. Specific areas for a PhD project may include: Model particle detectors as a tool for probing nonstationary quantum phenomena in spacetime, such as the onset of Hawking radiation during gravitational collapse. See arXiv:1406.2574, arXiv:1605.01316 and arXiv:1610.08455, and the references therein. Black hole structure behind the horizons as revealed by quantum field observations outside the horizons. See arXiv:1001.0124 and references therein. Quantum fields in accelerated cavities. See arXiv:1210.6772 and arXiv:1411.2948 and references therein. Theory supporting analogue spacetime laboratory experiments for detecting Hawking radiation and related effectsl. See arXiv:1807.04584 and references therein. 

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Title  Quantum learning for large dimensional quantum systems  

Group(s)  Mathematical Physics  
Proposer(s)  Dr Madalin Guta  
Description  Statistical inference and learning play an increasing role in Quantum Engineering and Quantum Metrology. The efficient statistical reconstruction of quantum states is a crucial enabling tool for current quantum engineering experiments in which multiple qubits can be prepared in exotic states. However, standard estimation methods such as maximum likelihood become practically unfeasible for systems of merely 10 qubits, due to the exponential growth in size of the Hilbert space. The aim of this project is to develop mathematical theory and investigate new methods for learning quantum states of large dimensional quantum systems. This stems from ongoing collaborations with Theo Kypraios and Ian Dryden (Statistics group, Nottingham), Cristina Butucea (Univesite Paris Est), Michael Nussbaum (Cornell), Jonas Kahn (Toulouse) and Richard Kueng (Caltech). In [1,2] we proposed and analysed faster estimation methods with close to optimal accuracy. The first goal is to better understand the behaviour of the estimators with respect to different measurement scenarios. Next, we would like to equip them with reliable confidence regions (error bars) which are crucial for experimental applications. Going beyond "full state tomography" new methods are needed which are able to "learn" the structure of the quantum state by making use of prior information encoded in physically relevant low dimensioanal models. Possible directions to be explored include models based on matrix product states, neural networks, quantum time series, compressed sensing [3] and the study of the asymptotical structure of the statistical models [4]. The project will involve both theoretical and computational work at the overlap between quantum information theory and modern statistical inference. 

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Other information  Click here to find more information on this topic and some illustrations of different types of estimators. For more about my reasearch interests you can visit my homepage. 
Title  Feedback control of quantum dynamical systems and applications in metrology  

Group(s)  Mathematical Physics  
Proposer(s)  Dr Madalin Guta  
Description 
The ability to manipulate, control and measure quantum systems is a central issue in Quantum Technology applications such as quantum computation, cryptography, and high precision metrology [1]. Most realistic systems interact with an environment and it is important to understand how this affects the performance of quantum protocols and how it can be used to improve it. The inputoutput theory of quantum open systems [2] offers a clear conceptual understanding of quantum dynamical systems and continuoustime measurements, and has been used extensively at interpreting experimental data in quantum optics. Mathematically, we deal with an extension of the classical filtering theory used in control engineering at estimating an unobservable signal of interest from some available noisy data [3]. This projects aims at investigating the identification and control of quantum dynamical systems in the framework of the inputoutput formalism. As an example, consider a quantum system (atom) interacting with an incoming "quantum noise" (electromagnetic field); the output fields (emitted photons) emerging from the interaction can be measured, in order to learn about the system's dynamical parameters (e.g. its hamiltonian). The goal is to find optimal system identification strategies which may involve input state preparation, output measurement design, and quantum feedback control. An interesting related question is to understand the informationdisturbance tradeoff which in the context of quantum dynamical systems becomes identificationcontrol tradeoff. The first steps in this direction were made in [4] which introduce the concept of asymptotic quantum Fisher information for "nonlinear" quantum Markov processes, and [5] which investigates system identification for linear quantum systems, using transfer functions techniques from control theory. A furhter goal is to develop genearal Central Limit theory for quantum output processes as a probablistic underpinning of the asymptotic estimation theory. Another direction is the recently found connection between dynamical phase transitions in manybody open systems and high precision metrology for dynamical parameters (see arXiv:1411.3914).


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Other information  Click here to find more information on this topic and some illustrations of different types of estimators. For more about my reasearch interests you can visit my homepage. 
Title  Using artificial intelligence to design quantum optics experiments  

Group(s)  Mathematical Physics  
Proposer(s) 
Prof Gerardo Adesso Notice: Undefined index: pmzpk in /maths/www/html/postgraduate/projects/index.php on line 560 Notice: Undefined index: pmzpk in /maths/www/html/postgraduate/projects/index.php on line 560 , 

Description  In order for technologies to benefit from the inherent power of quantum mechanics, quantum states with specific properties must be engineered for particular applications. This project explores the use of an evolutionary algorithm – a subset of artificial intelligence which mimics natural selection – that has been previously developed to design quantum states for performing quantumenhanced measurements [1]. PhD students will have the opportunity to extend this work in one or more of the following veins: i) Extend this technique to design quantum states and quantum experiments for a wide range of applications, including quantum computing, quantum cryptography, high precision measurements, and tests of fundamental physics. This strand will involve developing an understanding of the structure of quantum states – and the state space they live in – in order to design new quantum states with novel properties. ii) Incorporate realistic experimental imperfections, such as photon loss and imperfect detectors, into the evolutionary algorithm. This will enable the algorithm to find quantum states that can then be made in the laboratory, including in our collaborators’ labs in Bristol, Oxford, Stuttgart (Germany), and MIT (Boston, USA). This strand of the project will involve working closely with experimentalists to enhance and optimise their current experiments, and to design new experiments that they will subsequently perform. iii) As the algorithms used in i) and ii) become more complicated, more advanced artificial intelligence methods will need to be utilised and developed in order to make the simulations tractable. The use of machine learning (in particular reinforcement learning) and genetic algorithms will be explored, and the student will have the opportunity to collaborate with artificial intelligence researchers. 

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Title  Developing new relativistic quantum technologies  

Group(s)  Mathematical Physics  
Proposer(s)  Prof Ivette Fuentes  
Description  Relativistic quantum information is an emerging field which studies how to process information using quantum systems taking into account the relativistic nature of spacetime. The main aim of this PhD project is to find ways to exploit relativity to improve quantum information tasks such as teleportation and to develop new relativistic quantum technologies. Moving cavities and UnruhDewitt type detectors promise to be suitable systems for quantum information processing [1,2]. Interestingly, motion and gravity have observable effects on the quantum properties of these systems [2,3]. In this project we will find ways to implement quantum information protocols using localized systems such as cavities and detectors. We will focus on understanding how the protocols are affected by taking into account the nontrivial structure of spacetime. We will look for new protocols which exploit not only quantum but also relativistic resources for example, the nonlocal quantum correlations present in relativistic quantum fields. 

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Title  Homotopical algebra and quantum gauge theories  

Group(s)  Mathematical Physics  
Proposer(s)  Dr Alexander Schenkel  
Description  A problem which frequently arises in mathematics is that one would like to treat certain classes of maps as if they were isomorphisms, even though they are not in the strict sense. Examples are homotopy equivalences between topological spaces  remember the famous doughnut and coffee mug  or quasiisomorphisms between chain complexes of modules. Homotopical algebra was introduced by Quillen in the late 1960s as an abstract framework to address these and related problems. Since then it has found many important applications in algebra, topology, geometry and also in mathematical physics. In quantum field theory, homotopical algebra turns out to be essential as soon as one deals with models involving gauge symmetries. Recent results showed that quantum gauge theories do not satisfy the standard axioms of algebraic quantum field theory (AQFT), hence they are not quantum field theories in this strict sense. To solve these problems, we initiated the development of a novel and promising approach called “homotopical algebraic quantum field theory”, which combines the basic concepts of AQFT with homotopical algebra and which is expected to be a suitable mathematical framework for quantum gauge theories. Specific problems for a PhD project include modelindependent developments in hoAQFT or explicit contructions of examples of quantum gauge theories within this framework. 

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Title  Quantum optomechanics: radiation pressure at the single photon level  

Group(s)  Mathematical Physics  
Proposer(s)  Dr Tommaso Tufarelli  
Description  Optomechanics investigates the interaction of quantised light (photons) with microscopic vibrating objects such as mirrors, dielectric membranes or levitated nanoparticles [1]. Such interaction takes place via radiation pressure, a phenomenon initially predicted by Johannes Kepler in 1619 in the context of astronomy, and nowadays observed even at the singlephoton level. Among other applications, optomechanics embodies a promising experimental platform to probe quantum effects in massive objects, and hence investigate the classical/quantum boundary. The student will initially review a widely used effective Hamiltonian for cavity optomechanics (the "linear model") [2], which is analytically solvable and predicts the generation of nonclassical states of light as well as lightmatter entanglement. Subsequently, he/she will delve into the more rigorous canonical quantization of an optomechanical system [3], and assess the crucial limitations of the more basic model. Unfortunately, the more rigorous "mircoscopic" Hamiltonian is currently intractable both analytically and numerically, so that novel approximation techniques will need to be developed to improve the basic model while retaining computability. An example of a preliminary study in this direction can be found in Ref. [4]. The broad objective of the project will be to develop new optomechanical models that strike an optimal balance between reliability and tractability. These will then be used to verify and refine a number of theoretical predictions that have been made in the literature, tipically based on the linear model alone. Such predictions pertain a variety of applications of optomechanical systems, ranging from quantum information science to gravitational wave detection and Planckscale physics [5]. At the same time, an improved theoretical description will give us an opportunity to explore new physical effects and applications of these systems. A futher ambitious goal of the project will be to develop a rigorous open quantum system model for optomechanics, improving the phenomenological approaches that are currently used in the literature. Depending on the inclinations of the student, more emphasis can be put on either analytical or numerical work (e.g. via Matlab, Python or Mathematica). 

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Title  Manybody localization in quantum spin chains and Anderson localization  

Group(s)  Mathematical Physics  
Proposer(s)  Dr Alexander Ossipov  
Description  Properties of wave functions in manybody systems is very active topic of research in modern condensed matter theory. Quantum spin chains are very useful models for studying quantum manybody physics. They are known to exhibit complex physical behaviour such as quantum phase transitions. Recently, they have been studied intensively in the context of manybody localization. 

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Title  Entanglement of noninteracting fermions at criticality  

Group(s)  Mathematical Physics  
Proposer(s)  Dr Alexander Ossipov  
Description  Entanglement of the ground state of manyparticle systems has recently attracted a lot of attention. For noninteracting fermions, the ground state entanglement can be calculated from the eigenvalues of the correlation matrix of the single particle wavefunctions. For this reason, the nature of the single particle wavefunctions is crucially important for understanding of the entanglement properties of a manybody system. 

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Title  Gravity and differential forms  

Group(s)  Mathematical Physics  
Proposer(s)  Prof Kirill Krasnov  
Description  It turns out that solutions of 4D gravity can be lifted to solutions of a certain theory of differential 3forms in 7 dimensions. This suggests a new perspective on 4D gravity and its problems, such as nonrenormalisability. The aim of this project is to further study the geometry in 7 dimensions, in its relation to 4D geometry. Another aim is to understand the quantum properties of diffeomorphism invariant theories of differential forms in dimensions 7 and 6, and in particular understand how such theories renormalise at one and possibly two loops. This project lies at the intersection of differential geometry and quantum field theory. 

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Title  Gravity at all scales  

Group(s)  Mathematical Physics  
Proposer(s)  Prof Thomas Sotiriou  
Description  Various projects are available on the interplay between any of the following areas: quantum gravity, alternative theories of gravity, strong gravity and black holes. 

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Title  Quantum control of nonlinear interactions  

Group(s)  Mathematical Physics  
Proposer(s)  Dr Tommaso Tufarelli  
Description  Photons do not directly interact with each other, but effective interactions between them can be obtained by exploiting the mediation of matter. Perhaps the most common systems in which these effective interactions are achieved are nonlinear crystals. The sophistication of modern experiments, however, allows us to consider the mediation of quantum systems such as single atoms and optomechanical devices, where light is coupled to the vibrational degrees of freedom of a mesoscopic mirror via radiation pressure.


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Other information  This project will involve close collaboration with Dr. Florian Mintert of the Controlled Quantum Dynamics theory group, Imperial College London. 
Title  Scattering approach to topological insulators and superconductors  

Group(s)  Mathematical Physics  
Proposer(s)  Dr Alexander Ossipov  
Description  Topological insulators and superconductors are one of the hottest topics in the modern condensed matter theory. They represent a new phase of matter characterised by a rather unusual quantummechanical behaviour of electrons. Topological insulators are insulating materials, but they conduct electricity via special surface states. The surface states are topologically protected due to quantum symmetries and cannot be destroyed by disorder. Nevertheless the role of disorder is essential for understanding the properties of topological insulators.
A novel approach to disordered quantum system based on the scattering formalism has been proposed recently [1]. The aim of the project is to generalise and apply this approach to topological insulators and superconductors. 

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Title  Topological Resonances on Graphs  

Group(s)  Mathematical Physics, Industrial and Applied Mathematics  
Proposer(s)  Dr Sven Gnutzmann  
Description  If a light wave in a resonator between two almost perfect mirrors shows resonance if the wavelength is commensurate with the distance between the two mirrors. If this condition is satisfied it will decay much slower than at other wavelengths which are not commensurate. This is one of the simplest mechanisms for a resonace in a wave system. There are other weill known mechanisms that rely on complexity and disorder. It has recently been observed that a netork of wire may have a further mechanism that leads to resonances. This mechanism relies on cycles in the network and leads to various signatures which cannot be explained using other wellknown mechanisms for resonances. In this project these signatures will be analysed in detail. 

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Title  Quantum Chaos in Combinatorial Graphs  

Group(s)  Mathematical Physics, Industrial and Applied Mathematics  
Proposer(s)  Dr Sven Gnutzmann  
Description  Graphs consist of V vertices connected by B bonds (or edges). They are used in many branches of science as simple models for complex structures. In mathematics and physics one is strongly interested in the eigenvalues of the V x V connectivity matrix C of a graph. The matrix element C_ij of the latter is defined to be the number of bonds that connect the i'th vertex to the j'th vertex. In this PhD project the statistical properties of the connectivity spectra in (generally large) graph structures will be analysed using methods known from quantum chaos. These methods have only recently been extended to combinatorial graphs (Smilansky, 2007) and allow to represent the density of states and similar spectral functions of a graph as a sum over periodic orbits. The same methods have been applied successfully to metric graphs and quantum systems in the semiclassical regime for more than two decades. 

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Title  Quantum Searching in Random Networks  

Group(s)  Mathematical Physics, Industrial and Applied Mathematics  
Proposer(s)  Prof Gregor Tanner, Dr Sven Gnutzmann  
Description  The project deals with properties of quantum networks, that is, of networks on which unitary (wave) evolution takes place along edges with scattering at the vertices. Such systems have been studied in the context of quantum information as well as in quantum chaos. It has been noted that a quadratic speed up of quantum random walks on these networks over Recently, it has been shown, that quantum searching can also been undertaken on random graphs, that is, graphs for which connections between edges are given only wth a certain probability  so called ErdösRényi graphs. We will explore this new setup for quantum searching and develop statisticsal models for the arrival times and success probabilities as well extend the model to realistic graph setups. 

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Title  Supersymmetric field theories on quantum graphs and their application to quantum chaos  

Group(s)  Mathematical Physics, Industrial and Applied Mathematics  
Proposer(s)  Dr Sven Gnutzmann  
Description  Quantum graphs are a paradigm model for quantum chaos. They consist of a system of wires along which waves can propagate. Many properties of the excitation spectrum and the spatial distribution of standing waves can be mapped exactly onto a supersymmetric field theory on the network. In a meanfield approximation one may derive various universal properties for large quantum graphs. In this project we will focus on deviations from universal behaviour for finite quantum graphs with the fieldtheoretic approach. 

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Title  Pseudoorbit expansions in quantum graphs and their application  

Group(s)  Mathematical Physics, Industrial and Applied Mathematics  
Proposer(s)  Dr Sven Gnutzmann  
Description  Quantum graphs are a paradigm model to understand and analyse the effect of complexity on wave propagation and excitations in a network of wires. They have also been used as a paradigm model to understand topics in quantum and wave chaos where the complexity has a different origin while the mathematical framework is to a large extent analogous. Many properties of the waves that propagate through such a network can be described in terms of trajectories of a point particle that propagates through the network. The ideas is to write a property of interest as a sum over amplitudes (complex numbers) connected to all possible trajectories of the point particle. These sums remain challenging objects for explicit evaluations. Recently a numer of advanced methods for their summation have been introduced. The latter are built on socalled pseudoorbits. In this project these methods will be develloped further and applied to questions related to quantum chaos and randommatrix theory. 

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Title  The tenfold way of symmetries in quantum mechanics. An approach using coupled spin operators.  

Group(s)  Mathematical Physics, Industrial and Applied Mathematics  
Proposer(s)  Dr Sven Gnutzmann  
Description  About 50 years ago Wigner and Dyson proposed a threefold symmetry classification for quantum mechanical systems  these symmetry classes consisted of timereversal invariant systems with integer spin which can be described by real symmetric matrices, timereversal invariant systems with halfinteger spin which can be described by real quaternion matrices, and systems without any timereversal symmetry which are described by complex hermitian matrices. These three symmetry classes had their immediate application in the three classical Gaussian ensembles of randommatrix theory: the Gaussian orthogonal ensemble GOE, the Gaussian symplectic ensemble GSE, and the Gaussian unitary ensemble GUE. In the 1990's this classification was extended by adding charge conjugation symmetries  symmetries which relate the positive and negative part of a spectrum and which are described by anticommutators. 

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Title  Nonlinear waves in waveguide networks  

Group(s)  Mathematical Physics, Industrial and Applied Mathematics  
Proposer(s)  Dr Sven Gnutzmann  
Description  Many wave guides (such as optical fibres) show a Kerrtype effect that leads to nonlinear wave propagation. If th wave guides are coupled at junctions then there is an additional element of complexity due to the nontrivial connectivity of wave guides. In this project the impact of the structure and topology of the network on wave propagation will be studied starting from simple geometries such as a Yjunctions (three waveguides coupled at one junction), a star (many waveguides at one junction), or a lasso (a waveguide that forms a loop and is connected at one point to a second waveguide). 

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Title  The statistics of nodal sets in wavefunctions  

Group(s)  Mathematical Physics, Industrial and Applied Mathematics  
Proposer(s)  Dr Sven Gnutzmann  
Description  If a membrane vibrates at one of its resonance frequencies there are certain parts of the membrane that remain still. These are called nodal points and the collection of nodal points forms the nodal set. Building on earlier work this project will look at the statistical properties of the nodal set  e.g. for 3dimensional waves the nodal set consists of a coillection of surfaces and one may ask questions about how the area of the nodal set is distributed for an ensemble of membranes or for an ensemble of different resonances of the same membrane. This project will involve a strong numerical component as wavefunctions of irregular membranes need to be found and analysed on the computer. Effective algorithms to find the area of the nodal set, or the number of domain in which the sign does not change (nodal domains) will need to be developed andimplemented. 

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Title  Coherent states, nonhermitian Quantum Mechanics and PTsymmetry  

Group(s)  Mathematical Physics, Industrial and Applied Mathematics  
Proposer(s)  Dr Sven Gnutzmann  
Description  Heisenberg's uncertainty principle states that momentum and position cannot be sharp at the same time because there is a lower bound for the product of the uncertaincies. Coherent states can be defined as the states that minimize the uncertainty  in this sense they are as close as quantum mechanics allows to describe a classical point particle. When a quantum system starts in a coherent states it's expectation values follow the classical equations of motion while the shape of the wave function often changes only very slowly. Coherent states are an important tool to understand the corresp[ondence between quantum and classical dynamics. In this project this correspondence will be analysed for a generalized quantum dynamics where the Hamilton operator is not required to be Hermitian. Such dynamics can arise in practice as an effective description for an open quantum system with eitehr decay or gain. Accordingly the energy eigenvalues may have an imaginary part that describes the loss or gain. Recently there have also be suggestions that nonhermitian Hamilton operators could play a fundamental role in quantum mechanics if the Hamilton operator remains symmetric with respect to a combined operatyion of parity P and time reversal T. Such PTsymmetric dynamics have a balance between gain and loss which can lead to real energy eigenvalues. Classical to quantum correspondence for such systems remains an open research topic and this project will aim at getting a clear understanding of the underlying classical dynamics using coherent states as the main tool. 

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Title  Geometry and analysis of Schubert varieties  

Group(s)  Number Theory and Geometry  
Proposer(s)  Dr Sergey Oblezin  
Description  Schubert varieties is a basic tool of classical algebraic and enumerative geometry. In modern mathematics these geometric object arise widely in representation theory, theory of automorphic forms and in harmonic analysis. In particular, it appears that the classical geometric structures can be naturally extended to infinitedimensional setting (loop groups and, more generally, KacMoody groups), and such generalizations provide new constructions in infinitedimensional geometry. Moreover, many of the arising constructions are supported by (hidden) symmetries and dualities of quantum (inverse) scattering theory and quantum integrability. Possible PhD projects will be devoted to extensive development of harmonic analysis on Schubert varieties with further applications to automorphic forms, arithmetic goemetry and number theory. 

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Title  Orthogonal polynomials in probability, representation theory and number theory  

Group(s)  Number Theory and Geometry  
Proposer(s)  Dr Sergey Oblezin  
Description  Orthogonal ensembles play a crucial role in many areas including random matrix theory, probability and harmonic analysis. In the recent decades a new striking connections with the theory of automorphic forms and number theory appeared. However, there is a definite lack of general results and implementations at present. Possible PhD projects will be aiming at developing these recent interactions among the group theory, harmonic analysis and number theory. 

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Title  Number theory in a broad context  

Group(s)  Number Theory and Geometry  
Proposer(s)  Prof Ivan Fesenko  
Description  Ivan Fesenko studies zeta functions in number theory using zeta integrals. These integrals are better to operate with than the zeta functions, they translate various properties of zeta functions into properties of adelic objects. This is a very powerful tool to understand and prove fundamental properties of zeta functions in number theory. In the case of elliptic curves over global fields, associated zeta functions are those of regular models of the curve, i.e. the zeta function of a two dimensional object. Most of the classical work has studied arithmetic of elliptic curves over number fields treating them as one dimensional objects and working with with generally noncommutative Galois groups over the number field, such as the one generated by all torsion points of the curve. The zeta integral gadget works with adelic objects associated to the two dimensional field of functions of the curve over a global field and using commutative Galois groups. The latter has already been investigated in two dimensional abelian class field theory and it is this theory which supplies adelic objects on which the zeta integral lives. For example, Fourier duality on adelic spaces associated to the model of the curve explains the functional equation of the zeta function (and of the Lfunction of the curve). The theory uses many parts of mathematics: class field theory, higher local fields and several different adelic structures, translation invariant measure and integration on higher local fields (arithmetic loop spaces), functional analysis and harmonic analysis on such large spaces, groups endowed with sequential topologies, parts of algebraic Ktheory, algebraic geometry. This results in a beautiful conceptual theory. There are many associated research problems and directions at various levels of difficulty and opportunities to discover new objects, structures and laws. 

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Title  Computational methods for elliptic curves and modular forms  

Group(s)  Number Theory and Geometry  
Proposer(s)  Dr Christian Wuthrich  
Description  Computational Number Theory is a fairly recent part of pure mathematics even if computations in number theory are a very old subject. But over the last few decades this has changed dramatically with the modern, powerful and cheap computers. In the area of explicit computations on elliptic curves, there are two subjects that underwent a great development recently: elliptic curves over finite fields (which are used for cryptography) and 'descent' methods on elliptic curves over global fields, such as the field of rational numbers. It is a difficult question for a given elliptic curve over a number field to decide if there are infinitely many solutions over this field, and if so, to determine the rank of the MordellWeil group. Currently, there are only two algorithms implemented for finding this rank, one is the descent method that goes back to Mordell, Selmer, Cassels,... and the other is based on the work of Gross, Zagier, Kolyvagin... using the link of elliptic curves to modular forms. While the first approach works very well over number fields of small degree, it becomes almost impossible to determine the rank of elliptic curves over number fields of larger degree. The second method unfortunately is not always applicable, especially the field must be either the field of rational numbers or a quadratic extension thereof. There is another way of exploiting the relation between elliptic curves and modular forms by using the padic theory of modular forms and the socalled Iwasawa theory for elliptic curves. Results by Kato, Urban, Skinner give us a completely new algorithm for computing the rank and other invariants of the elliptic curve, but not much of this has actually been implemented. Possible PhD projects could concern the further development of these new methods and their implementation. 

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Title  Variants of automorphic forms and their Lfunctions  

Group(s)  Number Theory and Geometry  
Proposer(s)  Dr Nikolaos Diamantis  
Description  Classical automorphic forms are a powerful tool for handling difficult number theoretic problems. They provide links between analytic, algebraic and geometric aspects of the study of arithmetic problems and, as such, they are at the heart of the major research programmes in Number Theory, e.g. Langlands programme. Crucial for these links are certain functions associated to automorphic forms, called Lfunctions, which are the subject of some of the most important conjectures of Mathematics. 

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Title  Thermal characterisation of the building fabric under uncertainty  

Group(s)  Scientific Computation  
Proposer(s)  Dr Marco Iglesias  
Description  The built environment is responsible for 45% of all UK carbon emissions with approximately 27% attributed to the domestic sector and 18% to nondomestic buildings. Reducing the energy demand in the builtenvironment is thus essential for the UK decarbonisation policy which legislates an 80% reduction of its 1990 green house gas emissions by 2050. The existing housing stock is a primary target for reductions of the energy demand since it is estimated that up to 85% of existing buildings will be standing by 2050. An accurate characterisation of the thermal performance of the existing housing stock in the UK is thus needed to inform largescale costeffective policies for retrofit intervention that can effectively contribute towards achieving those decarbonisation targets. Unfortunately, existing approaches for the insitu characterisation of the building fabric (including ISO standards) cannot accurately characterise the thermal performance of buildings in the presence of thermal bridge effects that arise from heterogeneities, irregularities and/or abrupt changes and discontinuities in the thermophysical properties of the building fabric. In particular, these approaches cannot capture thermal bridge effects due to fabric degradation and moisture condensation which are likely to be found in existing dwellings. This challenging research will develop novel thermal imaging algorithms capable of characterising, with an accurate measure of uncertainty, the thermal performance of the building fabric in the presence of a general class of thermal bridge effects. This project will build upon stateoftheart Bayesian algorithms for inverse problems that have been successfully applied for tomographic inversions in the context of groundwater flow [1], electrical impedance tomography [1], resin transfer moulding [2], and the characterisation of thermophysical properties of walls [3,4]. The techniques developed in this project will be validated with real experiments. Although highly ambitious, this proposed research has enormous potential to revolutionise current approaches for insitu characterisation of the thermal performance of buildings thereby enhancing the predictive capabilities of existing housing stock models. 

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Title  Bayesian geometric inverse problems  

Group(s)  Scientific Computation  
Proposer(s)  Dr Marco Iglesias  
Description  The aim of this project is to develop computational Bayesian techniques for the solution of geometric inverses problems that arise in a wide range of applications such as subsurface geophysics, manufacturing engineering and the built environment. Examples of geometric inverse problem that will be addressed with the techniques developed in this project are: (i) inference of fracture networks and/or conduits in Karst aquifers during the injection of CO2 for its geologic storage; (ii) detection of defects in reinforced preform during the resin infusion process in the fabrication of composite materials; (iii) inference of internal structures (e.g. cavities) in building structures such as walls with the aim of improving estimates of energy consumption. These problems have an underlying (forward) model described by Partial Differential Equation(s) (PDE) with input parameters associated to some (unknown) physical property of interest; the inverse problem is to infer this property from noisy observations of the solution of the PDE. In the context of problems (i)(iii), sophisticated geometric parameterizations are often required to enable an accurate and realistic characterization of these properties (e.g. channelized structures in Karst networks). This project will develop computational hierarchical Bayesian methodologies to infer those geometryconstrained properties within an infinitedimensional Bayesian framework for PDEconstrained inverse problems. 

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Title  Discontinuous Galerkin Finite Elements for Moving Boundary Problems  

Group(s)  Scientific Computation  
Proposer(s)  Dr Matthew Hubbard  
Description  Many physical and chemical processes, typified by those related to fluid flow, can be modelled mathematically using partial differential equations. These can usually only be solved in the simplest of situations, but solutions in far more complex cases can be approximated using numerical and computational techniques. Traditional approaches to providing these computational simulations have typically modelled the evolution of the system by approximating the equations on a uniform mesh of points covering a domain with a fixed boundary. However, many situations (consider the spreading of a droplet, for example), naturally suggest a domain which evolves with the flow, while the main focus of interest in others (say the movement of a shock wave up and down an aeroplane wing) is in following the motion of a sharp internal feature. For accuracy and efficiency a computational method should not only approximate the partial differential equations appropriately, but also move the computational mesh in a manner which follows such features. Recent research has developed a finite element approach to the adaptive approximation of timedependent physical problems involving moving boundaries or interfaces. It has been deliberately designed to preserve inherent properties (such as conservation principles and invariances) of the underlying partial differential equations and hence of the system the mathematics is intended to represent. Extremely promising results have been obtained for a wide range of problems in one and two space dimensions, but the applicability of the approach is still limited (as are all moving mesh methods) by the potential for the computational mesh to ``tangle''. The aim of this project will be to develop an alternative approach, derived within the same framework, which takes advantage of the additional flexibility inherent in the discontinuous Galerkin finite element framework. This has the potential to reduce the occurrence of mesh tangling and to greatly improve the robustness of the method when modelling problems involving complex, interacting features and when using different monitor to govern the movement of the mesh. 

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Title  Foundations of adaptive finite element methods for PDEs  

Group(s)  Scientific Computation, Algebra and Analysis  
Proposer(s)  Dr Kris van der Zee  
Description  Foundations of adaptive finite element methods for PDEs Adaptive finite element methods allow the computation of solutions to partial differential equations (PDEs) in the most optimal manner that is possible. In particular, these methods require the least amount of degreesoffreedom to obtain a solution up to a desired accuracy! In recent years a theory has emerged that explains this behaviour. It relies on classical a posteriori error estimation, Banach contraction, and nonlinear approximation theory. Unfortunately, the theory so far applies only to specific model problems. Challenges for students: Depending on the interest of the student, several of these issues (or others) can be addressed. 

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Title  Partitioneddomain concurrent multiscale modelling  

Group(s)  Scientific Computation, Mathematical Medicine and Biology  
Proposer(s)  Dr Kris van der Zee  
Description  Partitioneddomain concurrent multiscale modelling Multiscale modeling is an active area of research in all scientific disciplines. The main aim is to address problems involving phenomena at disparate length and/or time scales that span several orders of magnitude! An important multiscalemodeling type is known as partitioneddomain concurrent modelling. This type addresses problems that require a finescale model in only a small part of the domain, while a coarse model is employed in the remainder of the domain. By doing this, significant computational savings are obtained compared to a full finescale model. Unfortunately, it is far from trivial to develop a working multiscale model for a particular problem. Challenges for students: Depending on the interest of the student, several of these issues (or others) can be addressed. 

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Title  Phasefield modelling of evolving interfaces  

Group(s)  Scientific Computation, Mathematical Medicine and Biology  
Proposer(s)  Dr Kris van der Zee  
Description  Phasefield modelling of evolving interfaces Evolving interfaces are ubiquitous in nature, think of the melting of the polar ice caps, the separation of oil and water, or the growth of cancerous tumours. Two mathematical descriptions exist to model evolving interfaces: those with sharpinterface descriptions, such as parametric and levelset methods, and those with diffuseinterface descriptions, commonly referred to as phasefield models. Challenges for students: Depending on the interest of the student, one of these issues (or others) can be addressed. 

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Title  Uncertainty quantification in geoelectrical imaging and monitoring  

Group(s)  Scientific Computation, Scientific Computation  
Proposer(s)  Dr Marco Iglesias  
Description  Over the past decade, geoelectrical imaging has become the leading technology for continuously monitoring the shallow subsurface volumetrically and in real time. This technology plays a crucial role in assisting industrial and governmental stakeholders in addressing some of the most pressing societal challenges that impact on the subsurface, such as unconventional energy sources, carbon sequestration, waste management and groundwater contamination. However, current geoelectrical imaging techniques do not allow appropriate quantification of the uncertainty intrinsic to (1) the subsurface and (2) conventional image reconstruction methods based on deterministic inversion. The absence of uncertainty quantification in the subsurface has profound detrimental effects on evidencebased decisionmaking, the assessment and management of risks associated with subsurface hazards, the design of costeffective remediation strategies and the improvement of stakeholder and public acceptance in the context of potentially controversial uses of the subsurface (e.g. unconventional hydrocarbons, CO2 storage). This project will develop Bayesian methodologies for geoelectrical imaging with the ultimate aim of inferring and quantify uncertainty in subsurface properties in the presence of realistic geologies. The project will be focused on applications that include carbon capture and storage, unconventional hydrocarbons and underground gas storage 

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Title  Geometric integration of stochastic differential equations  

Group(s)  Scientific Computation, Statistics and Probability  
Proposer(s)  Prof Michael Tretyakov  
Description  For many applications (especially, in molecular dynamics and Bayesian statistics), it is of interest to compute the mean of a given function with respect to the invariant law of the diffusion, i.e. the ergodic limit. To evaluate these mean values in situations of practical interest, one has to integrate large dimensional systems of stochastic differential equations over long time intervals. Computationally, this is a challenging problem. Stochastic geometric integrators play an important role in longtime simulation of dynamical systems with high accuracy and relatively low cost. The project involves construction of new efficient numerical methods for ergodic stochastic differential equations and stochastic numerical analysis of properties of the methods. We require an enthusiastic graduate with a 1st class degree in Mathematics, preferably at MMath/MSc level (in exceptional circumstances a 2:1 class degree, or equivalent, can be considered). We are expecting that the successful applicant has a very good background in Probability and has good computational skills. 

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Title  Numerical methods for stochastic partial differential equations  

Group(s)  Scientific Computation, Statistics and Probability  
Proposer(s)  Prof Michael Tretyakov  
Description  Numerics for stochastic partial differential equations (SPDEs) is one of the central topics in modern numerical analysis. It is motivated both by applications and theoretical study. SPDEs essentially originated from the filtering theory and now they are also widely used in modelling spatially distributed systems from physics, chemistry, biology and finance acting in the presence of fluctuations. The primary objectives of this project include construction, analysis and testing of new numerical methods for SPDEs.


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Title  Bayesian inversion in resin transfer moulding  

Group(s)  Scientific Computation, Statistics and Probability  
Proposer(s)  Prof Michael Tretyakov  
Description  Supervisors: Dr Marco Iglesias^{1}, Dr Mikhail Matveev^{2}, Prof Michael Tretyakov^{1} University of Nottingham, University Park, Nottingham NG7 2RD, UK 1 School of Mathematical Sciences 2 Polymer Composites Group, Faculty of Engineering This project will be based at the University of Nottingham in the School of Mathematical Sciences and the Faculty of Engineering. The use of fibrereinforced composite materials in aerospace and automotive industries and other areas has seen a significant growth over the last two decades. One of the main manufacturing processes for producing advanced composites is resin transfer moulding (RTM). The crucial stage of RTM is injection of resin into the mould cavity to fill empty spaces between fibres; the corresponding process is described by an elliptic PDE with moving boundaries. Imperfections of the preform result in uncertainty of its permeability, which can lead to defects in the final product. Consequently, uncertainty quantification (UQ) of composites’ properties is essential for optimal RTM. One of important UQ problems is quantification of the uncertain permeability. The objectives of this PhD project include (i) to construct, justify and test efficient algorithms for the Bayesian inverse problem within the moving boundary setting and (ii) to apply the algorithms to real data from composite laboratory experiments. Eligibility/Entry Requirements: We require an enthusiastic graduate with a 1st class degree in Mathematics, preferably at MMath/MSc level (in exceptional circumstances a 2:1 class degree, or equivalent, can be considered). We are expecting that the successful applicant has a background in PDEs, Probability and Statistics and has exceptional computational skills. For any enquiries please email: Marco.Iglesias@nottingham.ac.uk or Michael.Tretyakov@nottingham.ac.uk or Mikhail.Matveev@nottingham.ac.uk


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Title  Computational Finance  

Group(s)  Scientific Computation, Statistics and Probability  
Proposer(s)  Prof Michael Tretyakov  
Description  Computational Finance is the key element for successful risk management at investment banks and hedge funds and it is also a growing area on the interface between finance, computational mathematics and applied probability. Pricing and hedging financial derivatives, evaluating risks of default for financial product and firms, satisfying requirements of the Basel Accord, etc.  all require sophisticated modelling and reliable calibration of the models. These aims cannot be achieved without efficient numerical techniques which form the area of computational finance. The project will aim at developing new, efficient computational techniques related to finance. Eligibility/Entry Requirements: We require an enthusiastic graduate with a 1st class degree in Mathematics, preferably at MMath/MSc level (in exceptional circumstances a 2:1 class degree, or equivalent, can be considered). We are expecting that the successful applicant has a good background in Probability and Stochastic Analysis, some knowledge of Finance and has exceptional computational skills. 

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Title  Index policies for stochastic optimal control  

Group(s)  Statistics and Probability  
Proposer(s)  Dr David Hodge  
Description  Since the discovery of Gittins indices in the 1970s for solving multiarmed bandit processes the pursuit of optimal policies for this very wide class of stochastic decision processes has been seen in a new light. Particular interest exists in the study of multiarmed bandits as problems of optimal allocation of resources (e.g. trucks, manpower, money) to be shared between competing projects. Another area of interest would be the theoretical analysis of computational methods (for example, approximative dynamic programming) which are coming to the fore with ever advancing computer power.


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Other information  Keywords: multiarmed bandits, dynamic programming, Markov decision processes 
Title  SemiParametric Time Series Modelling Using Latent Branching Trees  

Group(s)  Statistics and Probability  
Proposer(s)  Dr Theodore Kypraios  
Description  A class of semiparametric discrete time series models of infinite order where we are be able to specify the marginal distribution of the observations in advance and then build their dependence structure around them can be constructed via an artificial process, termed as Latent Branching Tree (LBT). Such a class of models can be very useful in cases where data are collected over long period and it might be relatively easy to indicate their marginal distribution but much harder to infer about their correlation structure. The project is concerned with the development of such models in continuoustime as well as developing efficient methods for making Bayesian inference for the latent structure as well as the model parameters. Moreover, the application of such models to real data would be also of great interest. 

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Title  New analytical and simulation tools in clinical oncology  

Group(s)  Statistics and Probability  
Proposer(s)  Dr Gilles Stupfler, Dr Christopher Brignell  
Description  Cancer drug developers seek to show that satisfactory drug exposure increases the rate of beneficial patient responses, but without accounting for the risk of adverse effects. The student will develop fully parametric subdistribution hazard models that account for such competing events, handle covariate information such as body weight and are more flexible than the standard proportional hazards model, so that a patient's individual risk of wasting limited life expectancy during treatment can easily be quantified and drug exposure optimised. This project will be led jointly by the School of Mathematical Sciences and the private company BAST Inc Ltd., based in Loughborough, through their scientific director Dr Joachim Grevel. Weekly supervisory meetings with BAST, with at least two years based there, will provide excellent training and career development opportunities. 

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Other information  Studentship fully funded by BAST Inc Ltd. 
Title  Ion channel modelling  

Group(s)  Statistics and Probability  
Proposer(s)  Prof Frank Ball  
Description  The 1991 Nobel Prize for Medicine was awarded to Sakmann and Neher for developing a method of recording the current flowing across a single ion channel. Ion channels are protein molecules that span cell membranes. In certain conformations they form pores allowing current to pass across the membrane. They are a fundamental part of the nervous system. Mathematically, a single channel is usually modelled by a continuous time Markov chain. The complete process is unobservable but rather the state space is partitioned into two classes, corresponding to the receptor channel being open or closed, and it is only possible to observe which class of state the process is in. The aim of single channel analysis is to draw inferences about the underlying process from the observed aggregated process. Further complications include (a) the failure to detect brief events and (b) the presence of (possibly interacting) multiple channels. Possible projects include the development and implementation of Markov chain Monte Carlo methods for inferences for ion channel data, Laplace transform based inference for ion channel data and the development and analysis of models for interacting multiple channels. 

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Title  Optimal control in yield management  

Group(s)  Statistics and Probability  
Proposer(s)  Dr David Hodge  
Description  Serious mathematics studying the maximization of revenue from the control of price and availability of products has been a lucrative area in the airline industry since the 1960s. It is particularly visible nowadays in the seemingly incomprehensible price fluctuations of airline tickets. Many multinational companies selling perishable assets to mass markets now have large Operations Research departments inhouse for this very purpose. This project would be working studying possible innovations and existing practices in areas such as: customer acceptance control, dynamic pricing control and choicebased revenue management. Applications to social welfare maximization, away from pure monetary objectives, and the resulting game theoretic problems are also topical in home energy consumption and mass online interactions. 

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Title  Stochastic Processes on Manifolds  

Group(s)  Statistics and Probability  
Proposer(s)  Prof Huiling Le  
Description  As well as having a wide range of direct applications to physics, economics, etc, diffusion theory is a valuable tool for the study of the existence and characterisation of solutions of partial differential equations and for some major theoretical results in differential geometry, such as the 'Index Theorem', previously proved by totally different means. The problems which arise in all these subjects require the study of processes not only on flat spaces but also on curved spaces or manifolds. This project will investigate the interaction between the geometric structure of manifolds and the behaviour of stochastic processes, such as diffusions and martingales, upon them. 

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Title  Statistical Theory of Shape  

Group(s)  Statistics and Probability  
Proposer(s)  Prof Huiling Le  
Description  Devising a natural measure between any two fossil specimens of a particular genus, assessing the significance of observed 'collinearities' of standing stones and matching the observed systems of cosmic 'voids' with the cells of given tessellations of 3spaces are all questions about shape. It is not appropriate however to think of 'shapes' as points on a line or even in a euclidean space. They lie in their own particular spaces, most of which have not arisen before in any context. PhD projects in this area will study these spaces and related probabilistic issues and develop for them a revised version of multidimensional statistics which takes into account their peculiar properties. This is a multidisciplinary area of research which has only become very active recently. Nottingham is one of only a handful of departments at which it is active. 

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Title  Asymptotic techniques in Statistics  

Group(s)  Statistics and Probability  
Proposer(s)  Prof Andrew Wood  
Description  Asymptotic approximations are very widely used in statistical practice. For example, the largesample likelihood ratio test is an asymptotic approximation based on the central limit theorem. In general, asymptotic techniques play two main roles in statistics: (i) to improve understanding of the practical performance of statistics procedures, and to provide insight into why some proceedures perform better than others; and (ii) to motive new and improved approximations. Some possible topics for a Ph.D. are


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Title  Computational methods for fitting stochastic epidemic models to data  

Group(s)  Statistics and Probability  
Proposer(s)  Dr Theodore Kypraios, Prof Philip O'Neill  
Description  Despite recent advances in the development of computational methods for fitting epidemic models to data, many of these methods work best in smallscale settings where the study population is not especially big or the models have relatively few parameters. There is a need to develop methods which are appropriate to largescale settings. Furthermore, nearly all existing methods rely on parametric approaches (e.g. models based on specific underlying assumptions), but recent work has shown that Bayesian nonparametric approaches can be successfully adapted to this area. This project involves developing novel computationally efficient methods to fit both parametric and nonparametric models to data in situations where the existing methods are infeasible. 

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Title  Statistical shape analysis with applications in structural bioinformatics  

Group(s)  Statistics and Probability  
Proposer(s)  Dr Christopher Fallaize  
Description  In statistical shape analysis, objects are often represented by a configuration of landmarks, and in order to compare the shapes of objects, their configurations must first be aligned as closely as possible. When the landmarks are unlabelled (that is, the correspondence between landmarks on different objects is unknown) the problem becomes much more challenging, since both the correspondence and alignment parameters need to be inferred simultaneously. 

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Title  Highdimensional molecular shape analysis  

Group(s)  Statistics and Probability  
Proposer(s)  Prof Ian Dryden  
Description  In many application areas it is of interest to compare objects 

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Title  Geometrybased methods for statistics on functions and curves  

Group(s)  Statistics and Probability  
Proposer(s)  Dr Karthik Bharath  
Description  How can we define an average closed curve on the plane from a random sample of many such curves, such that it is invariant to certain transformations (e.g. rotations)? Answers to such questions have farreaching impact on analysis of images arising in numerous discplines (e.g. images of brain tumours). Extending statistical methodology from finite to infinitedimensional linear and nonlinear settings requires an improved understanding of probability distributions on constrained function spaces. Employing stochastic processes as a tool to study the interplay between probability and geometry, the project will address some fundamental issues that arise in the development of statistical theory and methodology for data in the form of functions and curves.


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Title  Analysis and forecasts of long hospital stays  

Group(s)  Statistics and Probability  
Proposer(s)  Dr Gilles Stupfler, Prof Ian Dryden  
Description  Most hospital stays are very short, typically lasting a few days. This project will take the opposite view of estimating the length of the longest hospital stays, which place a strong material and financial burden on hospital trusts and the NHS. We will develop estimation techniques for a novel extreme value model which will be able to link a variable of interest (here, length of stays) to with a large set of covariates (here, such as age, gender, socioeconomic status…) and that will be able to handle the problem of missing data caused by the random censoring typically present in medical data sets. The method will be applied to real data from the English NHS. 

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Title  Extreme quantile estimation with dependent censoring  

Group(s)  Statistics and Probability  
Proposer(s)  Dr Gilles Stupfler, Prof Andrew Wood  
Description  Statistical analysis of extremes in missing data frameworks is a recent developing field. It has been exploited to estimate survival times of very strong/weak patients to chronic diseases. The literature on this topic has focused on the case of independent censoring. However, cases when there are suspicions of dependence have been reported several times over the last decades; in medical studies, a common cause of the violation of the independence hypothesis is a sizeable number of patient dropouts. This project will exploit very recent results on extremes with dependent rightcensoring to design estimators of extreme quantiles. The methods will be showcased on real sets of medical data. 

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Title  Modelling hospital superbugs  

Group(s)  Statistics and Probability, Mathematical Medicine and Biology  
Proposer(s)  Prof Philip O'Neill, Dr Theodore Kypraios  
Description  The spread of socalled superbugs such as MRSA and other Antimicrobial Resistant pathogens within healthcare settings provides one of the major challenges to patient welfare within the UK. However, many basic questions regarding the transmission and control of such pathogens remain unanswered. This project involves stochastic modelling and data analysis using highly detailed data sets from studies carried out in hospital, addressing issues such as the effectiveness of patient isolation, the impact of different antibiotics, the way in which different strains interact with each other, and the information contained in data on highresolution data (e.g. whole genome sequences). 

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Title  Modelling of Emerging Diseases  

Group(s)  Statistics and Probability, Mathematical Medicine and Biology  
Proposer(s)  Prof Frank Ball  
Description  When new infections emerge in populations (e.g. SARS; new strains of influenza), no vaccine is available and other control measures must be adopted. This project is concerned with addressing questions of interest in this context, e.g. What are the most effective control measures? How can they be assessed? The project involves the development and analysis of new classes of stochastic models, including intervention models, appropriate for the early stages of an emerging disease. 

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Title  StructuredPopulation Epidemic Models  

Group(s)  Statistics and Probability, Mathematical Medicine and Biology  
Proposer(s)  Prof Frank Ball  
Description  The structure of the underlying population usually has a considerable impact on the spread of the disease in question. In recent years the Nottingham group has given particular attention to this issue by developing, analysing and using various models appropriate for certain kinds of diseases. For example, considerable progress has been made in the understanding of epidemics that are propogated among populations made up of households, in which individuals are typcially more likely to pass on a disease to those in their household than those elsewhere. Other examples of structured populations include those with spatial features (e.g. farm animals placed in pens; school children in classrooms; trees planted in certain configurations), and those with random social structure (e.g. using random graphs to describe an individual's contacts). Projects in this area are concerned with novel advances in the area, including developing and analysing appropriate new models, and methods for statistical inference (e.g. using pseudolikelihood and Markov chain Monte Carlo methods). 

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Title  Bayesian Inference for Complex Epidemic Models  

Group(s)  Statistics and Probability, Mathematical Medicine and Biology  
Proposer(s)  Prof Philip O'Neill, Dr Theodore Kypraios  
Description  Dataanalysis for reallife epidemics offers many challenges; one of the key issues is that infectious disease data are usually only partially observed. For example, although numbers of cases of a disease may be available, the actual pattern of spread between individuals is rarely known. This project is concerned with the development and application of methods for dealing with these problems, and involves using the latest methods in computational statistics (e.g. Markov Chain Monte Carlo (MCMC) methods, Approximate Bayesian Computation, Sequential Monte Carlo methods etc). 

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Title  Epidemics on random networks  

Group(s)  Statistics and Probability, Mathematical Medicine and Biology  
Proposer(s)  Prof Frank Ball  
Description  There has been considerable interest recently in models for epidemics on networks describing social contacts. In these models one first constructs an undirected random graph, which gives the network of possible contacts, and then spreads a stochastic epidemic on that network. Topics of interest include: modelling clustering and degree correlation in the network and analysing their effect on disease dynamics; development and analysis of vaccination strategies, including contact tracing; and the effect of also allowing for casual contacts, i.e. between individuals unconnected in the network. Projects in this area will address some or all of these issues. 

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