Computational Modelling Group

A Fortran Based Mesh Viewer

Gabriel Amine-Eddine (Investigator)

During my final year as an undergraduate, I developed a fully functional software program for visualising geometry, grid and grid quality for a custom developed CFD software tool. It has and now in use in conjunction with the HARTREE CFD code by some of the other fellow postgrads working in my supervisors team.

A habitat suitability model for predicting coral reef distributions in the Galápagos Islands

Terence Dawson (Investigator)

As part of a wider project developing a conservation strategy for the marine environment of the Galapagos Islands, this research used multi-variate modelling techniques to develop a habitat suitability prediction model for coral reefs.

Adding social ties to the Schelling model

Seth Bullock, Sally Brailsford (Investigators), Elisabeth zu-Erbach-Schoenberg

The Schelling model is an abstract model for segregation in
a spatially arranged population. We extended the traditional model by the addition of a dynamic social network. The social network influences the spatial dynamics of agents moving on the grid by changing the agents’ evaluation of their neighbourhood. In turn, the spatial arrangement influences the change of the social network.

Amorphous Computation, Random Graphs and Complex Biological Networks

Seth Bullock (Investigator)

This interdisciplinary research collaboration arose within the Simple Models of Complex Networks research cluster funded by the EPSRC www.epsrca.ac.uk through the Novel Computation Initiative. Here, leading groups from the Universities of Leeds, Sheffield, Nottingham, Southampton, Royal Holloway and King’s College and industrial partners BT are brought together for the first time to develop novel amorphous computation methods based on the theory of random graphs.

An investigation in to the effects of information provision on driver learning

Ben Waterson, Hans Fangohr (Investigators), James Snowdon

This work aims to better understand and model the role of individual learning and experience on driver route choice. We intend to demonstrate that vehicle-driver agent based models stand alone in being able to capture the complex reciprocal interactions between drivers and their environment, and allow us to incorporate the effects of prior knowledge from previous trips and advice from official information sources and social networks.

An Investigation into the Cascade Effect of Mergers on the Global Financial Markets

Seth Bullock, Antonella Ianni (Investigators), Camillia Zedan

An investigation into the external effects that horizontal mergers have on the interconnected global markets.

Antimicrobial Peptide and E. coli Membrane Interactions

Syma Khalid (Investigator), Thomas Piggot, Nils Berglund

Antimicrobial peptides (AMPs) are known to disrupt the membranes of bacterial cells such as E. coli. I work on investigating the nature of these interactions using molecular dynamics (MD) simulations.

Automated selection of suitable atmospheric calibration sites for satellite imagery

Robin Wilson (Investigator)

Ground calibration targets (GCTs) play a vital role in atmospheric correction of satellite sensor data in the optical region, but selecting suitable targets is a subjective and time- consuming task. This project is developing methods to automatically select suitable GCTs, using a combination of remotely sensed multispectral and topographic data.

B-meson coupling with relativistic heavy quarks

Jonathan Flynn (Investigator), Patrick Fritzsch, Dirk Broemmel

We non-perturbatively compute the coupling between B* and B pi meson states relying on relativistic heavy quarks and domain wall light fermions. The coupling is of importance for an effective description of hadronic heavy meson decays.

Bioinformatic identification and physiological analysis of ethanol-related genes in C. elegans

Richard Edwards, Vincent O'Connor, Lindy Holden-Dye (Investigators), Ben Ient

Investigating the broad molecular, cellular and systems level impacts of acute and chronic ethanol in the nematode, Caenorhabditis elegans, as a model.

BioSimGrid

Jonathan Essex, Hans Fangohr (Investigators), Richard Boardman, Syma Khalid, Steven Johnston

The aim of the BioSimGrid project is to make the results of large-scale computer simulations of biomolecules more accessible to the biological community. Such simulations of the motions of proteins are a key component in understanding how the structure of a protein is related to its dynamic function.

Cellular Automata Modelling of Membrane Formation and Protocell Evolution

Seth Bullock (Investigator), Stuart Bartlett

We simulate the meso-level behaviour of lipid-like particles in a range of chemical and physical environments. Self-organised protocellular structures can be shown to emerge spontaneously in systems with random, homogeneous initial conditions. We aim to take the current model further and explore more complex chemical scenarios in which a broad range of evolutionary behaviours will be exhibited.

Complex Systems Simulations Centre for Doctoral Training

Jonathan Essex, Seth Bullock, Hans Fangohr (Investigators)

The centre for doctoral training brings together students from a variety of backgrounds, ranging from mathematics, physics and chemistry to oceanography, geography, biology, computer science, and engineering. Students carry out a four-year programme combining taught courses with a PhD project.

Complexity in Modelling Electric Marine Propulsive Devices

Suleiman Sharkh, Neil Bressloff, Hans Fangohr (Investigators), Aleksander Dubas

This project involves the simulation of turbulent flow around a marine rim-driven thruster and the complex interaction of flow features involved through computational fluid dynamics.

DePuy Technology Partnership

Mark Taylor (Investigator), Adam Briscoe

This initiative concerns the transfer of knowledge between three key institutions (University of Southampton, University of Leeds and University of Hamburg) and DePuy International limited. The project is concerned with the ongoing advancement of technology used in orthopaedic devices.

Designer 3D Magnetic Mesostructures

Hans Fangohr (Investigator), Matteo Franchin, Andreas Knittel

A new electrodeposition self-assembly method allows for the growth of well defined mesostructures. This project's aim is to use this method in order to fabricate supraconducting and ferromagnetic mesostructures. Numerical methods based on well-established models are used in order to characterise the grown structures.

Dynamag: computational magnonics

Hans Fangohr, Atul Bhaskar (Investigators), Matteo Franchin, Andreas Knittel

Analytical treatment of long range magneto-dipole interactions is a bottle-neck of magnonics and more generally of the theory of spin waves in non-uniform media. This project develops a theoretical framework for analysis of magnonic phenomena in magnetic nano-structures, including isolated nano-elements, arrays of those, and extended magnonic crystals. The DYNAMAG project is funded by the EU FP7 and the DST of India.

Dynamics of interacting magnetic nanoparticles

Thomas Fischbacher (Investigator), Maximilian Albert

The project aims at extending the micromagnetic simulation framework 'nmag' developed at the University of Southampton to enable it to handle dynamic geometries. The extended framework will then be used to study systems such as interacting magnetic nanoparticles.

Flow and sedimentation processes in submarine meandering channels

Stephen Darby (Investigator)

The overall aim of this project is to generate a step-change in our understanding of the interactions between flow,
morphology & sedimentology within an active submarine channel fed by saline density currents. This central aim will be addressed through a combination of field measurements and innovative numerical modelling of gravity current morphodynamics

Fracturing of small social networks

Seth Bullock, Sally Brailsford (Investigators), Elisabeth zu-Erbach-Schoenberg

A connected social network is a very important factor for the success of groups and organisations. We investigate which factors make a group more resistant to the effects of disagreements which commonly happen in small social networks.

Hadronic structure on the computer

Jonathan Flynn (Investigator), Dirk Broemmel, Thomas Rae, Ben Samways

In experiments at the Large Hadron Collider (LHC) at CERN, Geneva, the interactions that occur between the colliding particles (protons in this case) can be factorised into a simple scattering between two constituent particles, called quarks, followed by a hadronisation process, which describes the dynamics of forming the bound proton states. Quarks are particles within the proton that bind to form composite particles (hadrons) such as a proton. The scattering process can be computed relatively easily, but hadronisation is intrinsically non-perturbative and hard to calculate. Lattice QCD (computer simulation of QCD on a discrete space-time lattice) provides our only known first-principles and systematically-improvable method to address problems like hadronisation. This project uses Iridis to extract parton distribution amplitudes which are experimentally inaccessible, but needed to describe the quark structure of hadrons.

High-resolution shock-capturing (HRSC) methods for elastic matter in general relativity

Carsten Gundlach, Ian Hawke (Investigators)

We are designing HRSC methods for numerical simulation of elastic matter coupled to general relativity and later magnetic fields, with the ultimate aim of simulating old neutron stars, which have elastic crusts.

How far can we stretch the MARTINI?

Syma Khalid (Investigator), Ric Gillams

To date, coarse-grained lipid models have generally been parameterised to ensure the correct prediction of structural properties of membranes, such as the area per lipid and the bilayer thickness. The work described here explores the extent to which coarse-grained models are able to predict correctly bulk properties of lipids (phase behaviour) as well as the mechanical properties, such as lateral pressure profiles and stored elastic stress in bilayers. Such an evaluation is crucial for understanding the predictive capabilities of coarse-grained models.

Hybrid quantum and classical free energy methods in computational drug optimisation

Jonathan Essex, Chris-Kriton Skylaris (Investigators), Christopher Cave-Ayland

This work is based around the application of thermodynamics and quantum mechanics to the field of computational drug design and optimisation. Through the application of these theories the calculation of the physical properties of drug-like molecules is possible and hence some predictive power for their pharmaceutical activity in vivo can be obtained.

Identification of novel Crustacean Pathogen Receptor Proteins

Richard Edwards, Chris Hauton, Timothy Elliott (Investigators), Oyindamola Lawal, Lloyd Mushambadzi

We are mining EST libraries (sequence fragments of expressed genes) for novel proteins that might play a role in the immune response of crustaceans.

Identification of phage DNA, common insertion sites and their effect on genes within S.pneumoniae

Richard Edwards, Amy Dean

This study seeks to find if there are any common insertion sites across different strains of S.pneumoniae and discover genes that undergo frequent mutation due to phages and if these mutations can be linked to virulence of the strains.

Impacts of Climate and Sea-Level Change on Coastal Gullies

Stephen Darby (Investigator), Chris Hackney, Julian Leyland

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Integrated in silico prediction of protein-protein interaction motifs

Richard Edwards (Investigator), Kieren Lythgow

Many vital protein-protein interactions are mediated by Short Linear Motifs (SLiMs) which are short proteins typically 5-15 amino acids long containing only a few positions crucial to function. This project integrates a number of leading computational techniques to predict novel SLiMs and add crucial detail to protein-protein interaction networks.

Interactome-wide prediction of short linear protein interaction motifs in humans

Richard Edwards (Investigator)

Short Linear Motifs (SLiMs) are important in many protein-protein interactions. In previous work, we have developed a computational tool, SLiMFinder, which places the interpretation of evidence for motifs within a statistical framework with high specificity, and subsequently enhanced sensitivity through application of conservation-based sequence masking. We are now applying these tools to a comprehensive set of human protein-protein interactions in order to predict novel human SLiMs in silico.

Kaon to two pion decays in lattice QCD

Jonathan Flynn (Investigator), Elaine Goode, Dirk Broemmel

We calculate kaon decay amplitudes on the lattice so we may compare the Standard Model to experiment.

Lagrangian modelling of ecosystem dynamics at the Bermuda Atlantic Time-series Study station

Tom Anderson, Seth Bullock (Investigators), Melissa Saeland

Focus in the marine ecosystem modelling community is starting to shift towards the use of Lagrangian, agent-based models as these are believed to produce more realistic results. The basic assumptions behind these models have not been thoroughly tested, and this project aims to undertake a detailed study of Lagrangian marine ecosystem models, before creating one to investigate the dynamics at the Bermuda Atlantic Time-series Study station (BATS).

Lyotropic phase transitions of lipids studied by CG MD simulation and experimental techniques

Syma Khalid (Investigator), Josephine Corsi

A study of the phase behaviour of cationic lipid - DNA complexes such as those used for transfection by coarse grained molecular dynamics simulation. Lipid systems studied include DOPE, DOPE/DNA and DOPE/DOTAP/DNA. Structural parameters and phase behaviour observed computationally have been compared with those gained using Small Angle X-ray Scattering (SAXS) and polarising light microscopy techniques.

Mass Spec identification of proteins utilising EST libraries

Richard Edwards, Maria Debora Iglesias-Rodriguez (Investigators), Bethan Jones

Expressed Sequence Tag (EST) data presents a particular challenge for the identification of proteins using mass spectrometry (MS): it is often redundant (multiple copies of the same gene), consists primarily of short fragments of coding sequence, contains many sequencing errors and is generally poorly annotated. We are developing computational pipelines to maximise robust protein identifications from EST data despite these challenges.

Mathematical modelling of plant nutrient uptake

Tiina Roose (Investigator)

In this project I will describe a model of plant water and nutrient uptake and how to translate this model and experimental data from the single root scale to the root branching structure scale.

Modelling mechanoreceptor reaction to tissue deformation

Mark Taylor (Investigator), Gwen Palmer

This project involved the modelling of a piece of knee joint capsule, which will produce an electrical output when mechanically stimulated. The model is based on expermental work carried out by P. Grigg and A.H. Hoffman (1982).

Modelling micromagnetism at elevated temperature

Hans Fangohr (Investigator), Dmitri Chernyshenko

The project aim is to develop a multiscale multiphysics model of
micromagnetism at elevated temperatures combining finite
element/finite difference modelling with atomistic simulations for
material parameter. The tool will be used to guide the development of the next generation magnetic data storage technology: heat assisted magnetic recording.

Modelling neuronal activity at the knee joint

Mark Taylor, Tiina Roose (Investigators), Gwen Palmer

The function of the knee joint is reliant on proprioception, which involves the response of nerve endings in the tissues at the joint. This project will be concentrating on the neuronal activity, caused by mechanical stimuli, of the more common receptors found at the knee (Ruffini, Paciniform, Golgi and Nociceptor).

There are three stages to this project:
1. Modelling the behaviour of each individual receptor, with the use of the Hodgkin-Huxley model [1].
2. These models will then be applied to the soft tissues around a knee, where a global deformation of the tissue will result in local stimulation of receptors.
3. The soft tissue models will then be applied to structures in the knee.

[1] - Hodgkin, A.L. and A.F. Huxley, A quantitative description of membrane current and its application to conduction and excitation in nerve. Journal of Physiology, 1952. 117: p. 500-544.

Molecular Fragments in Inhibitor Design

Jonathan Essex (Investigator), Michael Bodnarchuk

Fragment-Based Drug Discovery (FBDD) has emerged as an important tool in the drug discovery process. Instead of screening entire drug molecules, FBDD screens molecular fragments; constituents which make up drug molecules. A computational approach to identifying fragment binding is currently being sought which also yield binding free energy estimation.

Multi-scale simulations of bacterial outer-membrane proteins

Syma Khalid (Investigator), Jamie Parkin

Using Iridis to run multiple simulations, I aim to simulate the outer membrane proteins of Pseudomonas aeruginosa, using X-ray crystal structures of proteins only recently resolved by Bert van den Berg, University of Massachusetts. By modelling the proteins in a realistic P. aeruginosa outer membrane, I am to gain insight into the binding of these proteins to specific substrates and their function.

Multiscale modelling of biological membranes

Jonathan Essex (Investigator), Mario Orsi

Biological membranes are complex and fascinating systems, characterised by proteins floating in a sea of lipids. Biomembranes, besides being the fundamental structures employed by nature to encapsulate cells, play crucial roles in many phenomena indispensable for life, such as growth, energy storage, and in general information transduction via neural activity. In this project, we develop and apply multiscale computational models to simulate biological membranes and obtain molecular-level insights into fundamental structures and phenomena.

Multiscale Modelling of Electrochemical Processes in Neurons

John Chad (Investigator), Stuart George

Using asymptotic expansions to determine how the signalling behaviour of neurons is related to their microstructure.

Multiscale Simulation of Cellular Calcium Signalling

Hans Fangohr, Jonathan Essex (Investigators), Dan Mason

Calcium ions play a vitally important role in signal transduction and are key to many cellular processes including muscle contraction and cell apoptosis (cell death). This importance has made calcium an active area in biomedical science and mathematical modelling.

MXL Project

Mark Taylor, Junfen Shi (Investigators)

‘MXL’ is short for “Enhanced patient safety by computational Modelling from clinically available X-rays to minimise the risk of overload and instability for optimised function and Longevity”. This is an international EU-funded project which the Bioengineering Sciences Research Group at Southampton is involved in. For more information, visit http://www.m-x-l.eu

Nmag - computational micromagnetics

Hans Fangohr, Thomas Fischbacher (Investigators), Matteo Franchin, Andreas Knittel, Maximilian Albert, Dmitri Chernyshenko, Massoud Najafi, Richard Boardman

Nmag is a micromagnetic simulation package based on the general purpose multi-physics library nsim. It is developed by the group of Hans Fangohr and Thomas Fischbacher in the School of Engineering Sciences at the University of Southampton and released under the GNU GPL.

Nmag finite difference

Hans Fangohr (Investigator), Dmitri Chernyshenko, Matteo Franchin, Massoud Najafi

The goal of this project is to extends the finite element based micromagnetic simulation tool Nmag by the finite difference based extension Nmagfd and so to get an simulation tool where the user can easily switch between the used discretization method.

Non-Perturbative Renormalisation on the Lattice

Jonathan Flynn (Investigator), Dirk Broemmel, Thomas Rae

In this project we compute renormalisation factors for various physical observables in a non-perturbative lattice framework. Renormalisation hereby arises due to a fundamental scale dependence of the physical processes.

Nonequilibrium Dynamics of Atomic Gases in Optical Lattices

Sophie Marika Reed

Many-body, quantum systems exhibit emergent properties which allows for quantum events to influence properties on macroscopic scales. Such emergent properties are studied using stochastic phase-space techniques.

OMSys Towards a system model of a bacterial outer membrane

Syma Khalid (Investigator)

Many bacteria have an outer membrane which is the interface between the cell and its environment. The components of this membrane are well studied at an individual level, but there is a need to model and understand the outer membrane as a whole. In this project we aim to develop such a model of a bacterial outer membrane, linking computer simulations of the component molecules through to a more "systems biology" approach to modelling the outer membrane as a whole. Such an approach to modelling an OM must be multi-scale i.e. it must embrace a number of levels ranging from atomistic level modelling of e.g. the component proteins through to higher level "agent-based" modelling of the interplay of multiple components within the outer membrane as a whole. The different levels of description will be integrated to enable predictive modelling in order to explore the roles of outer membrane changes in e.g. antibiotic resistance.

On Simulations investigating drop diameter-charge distributions in electrostatically atomized liquid sprays

Gabriel Amine-Eddine (Investigator), John Shrimpton

Liquid sprays are atomized using electrostatic methods in many scientific, industrial and engineering applications. Due to jet and droplet breakup mechanisms, these spray plumes contain a range of drop diameters with a range of droplet charges. As a result of space charge repulsion forces between droplets, a wide range of inertial characteristics is observed. Past experimental evidence suggests a complex correlation between drop charge and drop diameter. It is suspected that this correlation is based on parameters such as spray specic charge, injection velocity and atomizer orice diameter. Since primary atomization is a strongly non-linear process, with electrical and aerodynamic forces contributing to the atomization process, it is reasonable to suspect a distribution of charge levels across each drop diameter class. Using an transient charged spray CFD code we have performed simulations to investigate standard charge-diameter models for predicting the dynamics of poly-disperse hydrocarbon sprays. Using PDA data from previously published experiments and comparing statistical observations and trends to our simulations, we hope to gain some understanding as to the exact statistical and physical relationship to the drop charge-diameter correlations for electrostatically atomized liquid sprays.

Operational Simulation of the Solent Search-and-Rescue environment

James Scanlan, Kenji Takeda, Hans Fangohr (Investigators), Ben Schumann

This project aims to identify useful metrics for a proposed Search-and-Rescue UAV and test it virtually in a realistic environment.

Scalability of Energy Efficient Routing Algorithms in WSN

Davide Zilli

This project compares two broad classes of routing algorithms for Wireless Sensor Networks, message flooding and single path, by means of a simulation model. In particular, we want to understand how the two scale in terms of energy efficiency on large networks of sensors.

Selection pressure for language and theory-of-mind in monkeys

Jason Noble (Investigator)

To what extent are the alarm calls of putty-nosed monkeys likely to be a good model for human language evolution? Simulation is used to classify evolutionary trajectories as either plausible or implausible, and to put lower bounds on the cognitive complexity required to perform particular behaviours.

Separation of timescales in models of complex networks

Seth Bullock (Investigator), Elisabeth zu-Erbach-Schoenberg, Connor McCabe

In many real-world systems several processes act on the system state. The way these processes interact can have implications for the resulting system state. We investigate how separation of the timescales of two processes influences the system's equilibrium state.

Simulating Hydro-geomorphic Changes in European Climate Hotspots

John Dearing (Investigator), Ying Wang

This project will simulate the behaviour of hydro-geomorphological processes in a fluvial system over decadal timescales is an important basis for research on catchment environmental management, especially with regards climate changes and human impacts on fluvial system.

Simulating the Write Process in Perpendicular Magnetic Media

Hans Fangohr (Investigator), Stuart Curtis

The project aims to use Nmag, a micromagnetics software package developed by the CMG to model the writing process in perpendicular magnetic recording.

Simulation modelling of habitat permeability for mammalian wildlife

Patrick Doncaster, Jason Noble (Investigators), Angela Watkins

Using and integrating least-cost models and agent-based simulations to explore the way in which mammals interact with, and hence move, through fragmented landscapes.

Simulation of Parking Choice Behaviour

Ben Waterson, Hans Fangohr (Investigators), James Snowdon

Exploring how psychological models of individual parking search behaviours can be combined into an accurate simulation of vehicle flows, allowing for assessment of the impact on searching traffic of different demand/ supply ratios, different driver population characteristics and different charging regimes.

Soft x-ray science on a tabletop

Peter Horak, Jeremy Frey, Bill Brocklesby (Investigators), Patrick Anderson

Complex numerical simulations are being performed to aid experimentalists at Southampton realize the next generation of high brightness tabletop sources of coherent soft x-rays.


Spatial Mobility in the Formation of Agent-Based Economic Networks

Antonella Ianni, Seth Bullock (Investigators), Camillia Zedan

An investigation into the effect of spatial mobility on endogenous economic network formation.

Spatially Embedded Complex Systems Engineering

Seth Bullock (Investigator)

SECSE brought together an interdisciplinary team of scientists working on an ambitious three-and-a-half year project titled. The research cluster spanned neuroscience, artificial intelligence, geography, and complex systems in an attempt to understand the role of spatial organization and spatial processes in complex networks within the domains of neural control, geo-information systems and distributed IT systems such as those implicated in air-traffic control.

Statistical model of the knee

Mark Taylor (Investigator), Francis Galloway, Prasanth Nair

Development of methods for large scale computational testing of a tibial tray incorporating inter-patient variability.

Tag based transcriptome analysis of gene expression in a promising green algae

Richard Edwards, Andreas Johansson

We use SuperSAGE in combination with next-generation sequencing to compare differences in gene expression between selected mutants and the wild type of a green algae. The data in the form of millions of 26 bp tags representing short stretches of expressed genes, will be analysed to find patterns of variation in gene expression under different conditions.

The application of automated pattern metrics to surface moisture influences on modelled dune field development

Robin Wilson, Joanna Nield (Investigators)

Areas of sand dunes (known as dunefields) develop complex patterns over time. These are influenced by both the past and present environmental conditions, including surface moisture, vegetation distribution and human impact. This project develops a method of automated pattern analysis which allow the patterns produced by a large number of sand dune evolution simulations (performed using the DECAL model) to be quantified over time.

The autotransporter β domain: insights into structure and function through multi scale molecular dynamics simulations

Syma Khalid (Investigator), Daniel Holdbrook, Thomas Piggot

We are performing a series of molecular dynamics simulations involving all autotransporters with known structure. We aim to identify key structural and dynamic properties in this family of proteins.

The Endogenous Formation of Economic Networks

Antonella Ianni, Seth Bullock (Investigators), Camillia Zedan

An investigation into endogenous network formation using a simple agent-based approach.

The Origins of Communication Revisited

Jason Noble (Investigator), Jordi Arranz

Quinn (2001) sought to demonstrate that communication be- tween simulated agents could be evolved without pre-defined communication channels. Quinn’s work was exciting because it showed the potential for ALife models to look at the real origin of communication; however, the work has never been replicated. In order to test the generality of Quinn’s result we use a similar task but a completely different agent architecture. We find that qualitatively similar behaviours emerge, but it is not clear whether they are genuinely communicative. We extend Quinn’s work by adding perceptual noise and internal state to the agents in order to promote ritualization of the nascent signal. Results were inconclusive; philosophical implications are discussed.

The Role of Information in Price Discovery

Antonella Ianni, Seth Bullock (Investigators), Camillia Zedan

The recent economic crisis has highlighted a continued vulnerability and lack of understanding in the financial markets. In order to overcome this, many believe that current market models must be improved. Recently, a trend towards agent-based modelling has emerged. Viewing the economy as a complex system is beginning to be seen as key to explaining certain market characteristics that were originally considered anomalies.

One of the fundamental assumptions in economics is that of information efficiency: that the price of a stock reflects its worth, that all possible information about a security is publicly known, and that any changes to price take place instantaneously. In reality, however, this is not the case.

This project considers the use of agents in modelling economic systems and demonstrates the effect of information levels on price discovery using a simple market simulation.

Tissue Engineering

Tiina Roose (Investigator)

This project deals with applying mathematical and computational modelling techniques to answer questions that are useful for tissue engineering applications.

Vortex Dynamics in High-Tc superconductors

Hans Fangohr (Investigator)

The dynamics of vortices in high temperature superconductors exhibits the complex and rich physics we expect from many body systems with competing interactions. Molecular Dynamics, Langevin Dynamics and Monte Carlo Computer simulations are carried out to understand this system in more detail.

Vortices in Spinor Bose-Einstein Condensates

Janne Ruostekoski (Investigator), Justin Lovegrove

We numerically study the effect of spin degrees of freedom on the structure of a vortex in a Bose-Einstein Condensate. Such objects are of interest as macroscopic examples of quantum phenomena, as well as for their analogies in other fields, such as cosmology and high energy physics.

Water Molecules in Protein Binding Sites

Jonathan Essex (Investigator), Michael Bodnarchuk

Water molecules are commonplace in protein binding sites, although the true location of them can often be hard to predict from crystallographic methods. We are developing tools which enable the location and affinity of water molecules to be found.

µ-VIS Computed Tomography Centre

Ian Sinclair, Richard Boardman, Dmitry Grinev, Philipp Thurner, Simon Cox, Jeremy Frey, Mark Spearing, Kenji Takeda (Investigators)

A dedicated centre for computed tomography (CT) at Southampton, providing complete support for 3D imaging science, serving Engineering, Biomedical, Environmental and Archaeological Sciences. The centre encompasses five complementary scanning systems supporting resolutions down to 200nm and imaging volumes in excess of one metre: from a matchstick to a tree trunk, from an ant's wing to a gas turbine blade.