Trajectory ensemble methods for understanding complex stochastic systemsTools Mey, Antonia S.J.S. (2013) Trajectory ensemble methods for understanding complex stochastic systems. PhD thesis, University of Nottingham.
AbstractThis thesis investigates the equilibrium and dynamic properties of stochastic systems of varying complexity. The dynamic properties of lattice models  the 1d Ising model and a 3d protein model  and equilibrium properties of continuous models  particles in various potentials  are presented. Dynamics are studied according to a large deviation formalism, by looking at nonequilibrium ensembles of trajectories, classified according to a dynamical order parameter. The phase structure of the ensembles of trajectories is deduced from the properties of largedeviation functions, representing dynamical freeenergies.
Actions (Archive Staff Only)
