The Complex Systems and Statistical Physics Group
Who we are
The Complex Systems and Statistical Physics Group is part of the Theoretical Physics Division in the School of Physics and Astronomy at the University of Manchester.
Our interests focus on the application of techniques from statistical physics and nonlinear dynamics to study complex systems. We work on a wide range of topics, in particular on problems in biology, in the social sciences and in economics. This includes the modelling of horizontal gene transfer, stochastic dynamics in biological pathways, epidemic spread, problems in game theory and evolutionary dynamics, social complexity, agent-based modelling of evacuation and the analysis of time series from financial markets.
We maintain close links with researchers in other disciplines, including colleagues in the School of Social Sciences, in the Manchester Interdisciplinary Biocentre, the Manchester Business School, and the Centre for Policy Modelling at Manchester Metropolitan University.
We have 2 permanent academic members of staff, five postdoctoral research associates, six PhD students and usually a few visitors.
Edited by John Preston, Jane M Binner, Layla Branicki, Tobias Galla, Nick Jones, James King, Magdalini Kolokitha and Michalis Smyrnakis
Quantitative Decision-Making Rules for the Next Generation of Smarter Evacuations
Fry, John, Tobias Galla, and Jane M. Binner
City Evacuations: An Interdisciplinary Approach. Springer Berlin Heidelberg, 63-87 (2015)
The statistics of fixation times for systems with recruitment
T. Biancalani, L. Dyson and A. J. McKane
J. Stat Mech P01013 (2015)
Models of Genetic Drift as Limiting Forms of the Lotka-Volterra Competition Model
G. W. A. Constable and A. J. McKane
Phys. Rev. Lett. 114, 038101 (2015)
Gaussian approximations for stochastic systems with delay: Chemical Langevin equation and application to a Brusselator system
Brett T and Galla T.
J. Chem. Phys. 140, 124112 (2014)
The importance of volume exclusion in modelling cellular migration
L. Dyson and R.E. Baker J. Math. Biol. (2014)