Trajectory ensemble methods for understanding complex stochastic systems
Mey, Antonia S.J.S. (2013) Trajectory ensemble methods for understanding complex stochastic systems. PhD thesis, University of Nottingham.
This thesis investigates the equilibrium and dynamic properties of stochastic systems of varying complexity. The dynamic properties of lattice models -- the 1-d Ising model and a 3-d 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 non-equilibrium ensembles of trajectories, classified according to a dynamical order parameter. The phase structure of the ensembles of trajectories is deduced from the properties of large-deviation functions, representing dynamical free-energies.
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