Computational Modelling Group

A novel approach to analysing fixed points in complex systems

James Dyke (Investigator), Iain Weaver

This work aims to contribute to our understanding of the relationship between complexity and stability. By describing an abstract coupled life-environment model, we are able to employ novel analytical, and computational techniques to shed light on the properties of such a system.

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.

Automated Algorithmic Trading with Intelligent Execution

Frank McGroarty, Enrico Gerding (Investigators), Ash Booth

In this project, we introduce the first fully automated trading system for real-world stock trading that uses time-adaptive execution algorithm to minimise market impact while increasing profitability com- pared to benchmark strategies.

Automated Trading with Performance Weighted Random Forests and Seasonality

Frank McGroarty, Enrico Gerding (Investigators), Ash Booth

This project proposes an expert system that uses novel machine learning techniques to predict the price return over these seasonal events, and then uses these predictions to develop a profitable trading strategy.

Automatic Image Retrieval with Soft Biometrics for Surveillance

Mark Nixon, John Carter (Investigators), Daniel Martinho-Corbishley

We're investigating ways to automatically describe and identify pedestrians from surveillance footage using human understandable, soft biometric labels. Our goal is to enable surveillance operators to search for pedestrians in a video network using soft biometric descriptions, and to automatically retrieve these descriptions from CCTV images.

Bioclimatic Architecture

Seth Bullock (Investigator), Nicholas Hill

This was a review report on bioclimatic architecture and how such architecture may be designed by agent-based models inspired by the building behaviour of insects.

Can the principle of Maximum Entropy Production be used to predict the steady states of a Rayleigh-Bernard convective system?

Kevin Oliver, Iain Weaver, James Dyke (Investigators)

The principle of Maximum Entropy Production (MEP) has been successfully used to reproduce the steady states of a range of non-equilibrium systems. Here we investigate MEP and maximum heat flux extremum principles directly via the simulation of a Rayleigh-Bérnard convective system implemented as a lattice gas model.

Centre for Doctoral Training in Next Generation Computational Modelling

Hans Fangohr, Ian Hawke, Peter Horak (Investigators), Susanne Ufermann Fangohr, Thorsten Wittemeier, Kieran Selvon, Alvaro Perez-Diaz, David Lusher, Ashley Setter, Emanuele Zappia, Hossam Ragheb, Ryan Pepper, Stephen Gow, Jan Kamenik, Paul Chambers, Robert Entwistle, Rory Brown, Joshua Greenhalgh, James Harrison, Jonathon Waters, Ioannis Begleris, Craig Rafter

The £10million Centre for Doctoral Training was launched in November 2013 and is jointly funded by EPSRC, the University of Southampton, and its partners.

The NGCM brings together world-class simulation modelling research activities from across the University of Southampton and hosts a 4-year doctoral training programme that is the first of its kind in the UK.

Controlling Ant-Based Construction

Seth Bullock (Investigator), Lenka Pitonakova

This paper investigates dynamics of ant nest building and shows that algorithms capable of generating ant-like structures can also be used to create nests, shapes of which are imposed from outside of the system.

Deep Optimisation

Jamie Caldwell

The project will develop the implementation and application of a new optimisation technique. 'Deep optimisation' combines deep learning techniques in neural networks with distributed optimisation methods to create a dynamically re-scalable optimisation process. This project will develop this technique to better-understand its capabilities and limitations and develop GPU implementations. The protein structure prediction problem will be used as the main test application.

Development of wide-ranging functionality in ONETEP

Chris-Kriton Skylaris (Investigator), Jacek Dziedzic

ONETEP is at the cutting edge of developments in first principles calculations. However, while the fundamental difficulties of performing accurate first-principles calculations with linear-scaling cost have been solved, only a small core of functionality is currently available in ONETEP which prevents its wide application. In this collaborative project between three Universities, the original developers of ONETEP will lead an ambitious workplan whereby the functionality of the code will be rapidly and significantly enriched.

Fluid Structure Interactions of Yacht Sails

Stephen Turnock (Investigator), Daniele Trimarchi

The research is the main subject of the PhD topic. It regards the application of fluid structure interaction techniques to the domain of yacht sails simulation

Generic Operational Simulation of Civil Unmanned Air Vehicle Operations

Hans Fangohr, James Scanlan (Investigators)

This project creates a generic operational simulation of Unmanned Air Vehicle Operations. UAVs can be valued for their mission-suitability and compared against various configurations.

Integrating Automated Vehicles into the Transport Network

Bani Anvari, Ben Waterson (Investigators), Craig Rafter

Innovative new designs to transportation infrastructure - with a strong evidence base - that will support automated vehicles to maximize sustainability in the transport network.

Lattice Holographic Cosmology

Andreas Juttner (Investigator), Matthew Mostert

This project will aim to develop new theoretical field methods and massively parallel computational algorithms to be utilised on both new computational architectures (e.g. Intel Xeon Phi) and existing high performance computers (HPCs).

The ultimate goal is to make predictions for the power spectrum and non-gaussianties of the CMB which would then be falsifiable by comparison to the Planck and WMAP data.

Network Analysis of Roman Transport Routes in the Imperial Roman Mediterranean

David Potts

This research is designed to explore the nature of the relationships between Portus, Rome, and other selected ports in the Mediterranean and to establish patterns and the changing nature of trading networks derived from the distribution of known Roman artefacts.

New Forest Cicada Project

Alexander Rogers, Geoff Merrett (Investigators), Davide Zilli, Oliver Parson

Rediscover the critically endangered New Forest cicada with crowdsourced smartphone biodiversity monitoring techniques.

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.

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.

Origins of Evolvability

Richard Watson, Markus Brede (Investigators), William Hurndall

This project examined the putative evolvability of a Lipid World model of fissioning micelles. It was demonstrated that the model lacked evlovability due to poor heritability. Explicit structure for micelles was introduced along with a spatially localised form of catalysis which increased the strength of selection as coupling between potential chemical units of heredity were reduced.

Predicting Available Energy in Energy Harvesting Wireless Sensor Networks

Geoff Merrett (Investigator), Davide Zilli

Is it possible to predict how much energy a sun-light or wind powered wireless sensor node can harvest and tune its sensing pattern accordingly?

Pushing the Envelope of Planetary Formation and Evolution Simulations

Peter Bartram

A full understanding of the formation and the early evolution of the Solar System and extrasolar planetary systems ranks among natural science's grand challenges, and at present, even the dominant processes responsible for generating the observed planetary architecture remain elusive.

Quantifying Collective Construction

Seth Bullock (Investigator), Nicholas Hill

This was an initial investigation into how best to develop quantifying and discriminating measures of both the processes and results of collective construction.

Renormalisation group approach to 1D cellular automata with large updating neighbourhoods

Iain Weaver, Adam Prugel-Bennett (Investigators)

We study self-similarity in one-dimensional probabilistic cellular automata (PCA) by applying a real-space renormalisation technique to PCA with increasingly large updating neighbourhoods. By studying the flow about the critical point of the renormalisation, we may produce estimates of the spatial scaling properties of critical PCA.

Renormalisation of 2D cellular automata with an absorbing state

Adam Prugel-Bennett, Iain Weaver (Investigators)

We describe a real-space renormalisation scheme for non-equilibrium probablistic cellular automata (PCA) models, and apply it to a two-dimensional binary PCA. An exact renormalisation scheme is rare, and therefore we provide a method for computing the stationary probability distribution of states for such models with which to weight the renormalisation, effectively minimising the error in the scale transformation.

Sensitivity of the critical depth to the choice of particle movement rules in Lagrangian models and the consequences for the predicted timing of the spring bloom

Tom Anderson (Investigator), Melissa Saeland

Individual-based (Lagrangian) models lend themselves to the study of the controls of the spring bloom in the ocean, due to their ability to represent both the turbulence and the phytoplankton motion. Here, we use a Lagrangian phytoplankton model to test some of the most prevalent hypotheses (e.g. critical depth and critical turbulence).

Software Sustainability Institute

Simon Hettrick (Investigator)

A national facility for cultivating world-class research through software

Software helps researchers to enhance their research, and improve the speed and accuracy of their results. The Software Sustainability Institute can help you introduce software into your research or improve the software you already use.

The Institute is based at the universities of Edinburgh, Manchester, Oxford and Southampton, and draws on a team of experts with a breadth of experience in software development, project and programme management, research facilitation, publicity and community engagement.

We help people build better software, and we work with researchers, developers, funders and infrastructure providers to identify key issues and best practice in scientific software.

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.

Stability of chiral structures in magnetic nanodisks

Hans Fangohr, Weiwei Wang (Investigators), David Cortes

This project is aimed to study the stability of skyrmionic and helical equilibrium states in magnetic nanodisks, using computational simulations.

Sustainable domain-specific software generation tools for extremely parallel particle-based simulations

Chris-Kriton Skylaris (Investigator)

A range of particle based methods (PBM) are currently used to simulate materials in chemistry, engineering, physics and biophysics. The 4 types of PBM considered directly in the proposed are molecular dynamics (MD), the ONETEP quantum mechanics-based program, discrete element modelling (DEM), and smoothed particle hydrodynamics (SPH).
The overall research objective is to develop a sustainable tool that will deliver, in the future, cutting edge research applicable to applications ranging from dam engineering to atomistic drug design.

Testing an interaction game on relationships.

Seth Bullock (Investigator), Anastasia Eleftheriou

The aim of this project is to examine how attractiveness is related to hypothetical risky sexual behaviour. The term `risky sexual behaviour' refers to having multiple sexual partners without the use of a condom. Data will be collected using questionnaires in order to investigate the influence of attractiveness on intentions towards engaging in unprotected sexual intercourse. A primary research question is whether perceived attractiveness of a potential partner affects the reported likelihood of having sex and/or using a condom.

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 importance of timescales for the emergence of environmental self-regulation

Iain Weaver, James Dyke (Investigators)

Models which explore the possibilities of emergent self-regulation in the Earth system often assume the timescales associated with changes in various sub-systems to be predetermined. We analyse a classic model of environmental self-regulation, Daisyworld, and interpret the original equations for model temperature, changes in insolation, and self-organisation of the biota as an important separation of timescales.

THE NORM MATE TRANSPORTER FROM N. GONORRHEAE: INSIGHTS INTO DRUG & ION BINDING FROM ATOMISTIC MOLECULAR DYNAMICS SIMULATIONS

Syma Khalid (Investigator), Daniel Holdbrook, Thomas Piggot, Yuk Leung

The multidrug and toxic compound extrusion (MATE) transporters extrude a wide variety of substrates out of both mammalian and bacterial cells via the electrochemical gradient of protons and cations across the membrane. Multiple atomistic simulation are performed on a MATE transporter, NorM from Neisseria gonorrheae (NorM_NG) and NorM from Vibrio cholera (NorM_VC). These simulations have allowed us to identify the nature of the drug-protein/ion-protein interactions, and secondly determine how these interactions contribute to the conformational rearrangements of the protein.

The Perks of Complexity Reduction

Lajos Hanzo (Investigator), Chao Xu

Reliable high-speed modems facilitate ubiquitous communications in our daily lives amongst people and/or machines. The communication technologies we need for the future have to have a high reliability and a low cost. My research aims for reducing the complexity of state-of-the-art communication systems, so that they can communicate in real time at an increased throughput. Naturally having access to parallel computers such as Iridis gives my research a competitive advantage over other researchers, relying on slower simulations.

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.

The Social-cognitive Niche: An Exploration of the Co-evolutionary Relationship between Human Mind and language, with a Particular Focus of the Self-organisational properties of the Emergence of Symbolic Representation.

Jason Noble, Glyn Hicks (Investigators), Lewys Brace

This work explored the relationship between the origin and subsequent evolution of the human mind and language; a relationship that is believed to be symbiotic in nature. This piece aimed to achieve two objectives. Firstly, it set out a theoretical framework, using the principles of complexity theory and self-organisation, which attempts to explain this relationship from a holistic perspective.

Secondly, it presented an agent-based model of a vervet monkey social group, which sought to investigate the variables that were perceived to underpin the emergence of symbolic representation within a population of language users.

The belief here was that, by understanding the influence of these variables, one would be able to better understand the genesis of the aforementioned relationship.

Traveling and movement during European Late Prehistory

Patricia Murrieta Flores

This project has as main purpose to investigate through spatial analysis and computational modelling the variables and factors that influenced how humans traveled during prehistoric times.
One of the principal objectives will be to clarify the role that certain landscape elements (i.e megalithic monuments) played in terrestrial navigation and territorial definition.

This project is supported by CONACYT (Mexico) as a doctoral research by Patricia Murrieta-Flores under the supervision of Dr. David Wheatley (University of Southampton) and Dr. Leonardo Garcia Sanjuan (University of Seville, Spain). It also counts with the collaboration of Dr. Dimitrij Mlekuz (Gent University, Belgium).

Understanding the Role of Recruitment in Robot Foraging

Seth Bullock, Richard Crowder (Investigators), Lenka Pitonakova

It is shown that recruitment among foraging robots is useful when resources are hard to find, but that the extra cost associated with such robots is not returned when there are many locations to gather from or simply when the relative gain from using communication is low.