Effective driven dynamics for one-dimensional conditioned Langevin processes in the weak-noise limit
Identificadores
URI: https://hdl.handle.net/10481/101131Metadatos
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IOP Science / IOP Publishing
Fecha
2019-01-03Referencia bibliográfica
N. Tizón-Escamilla, V. Lecomte y E. Bertin. Effective driven dynamics for one-dimensional conditioned Langevin processes in the weak-noise limit. Journal of Statistical Mechanics: Theory and Experiment 2019 (1), 013201 (2019).
Resumen
In this work we focus on fluctuations of time-integrated observables for a particle diffusing in a one-dimensional periodic potential in the weak-noise asymptotics. Our interest goes to rare trajectories presenting an atypical value of the observable, that we study through a biased dynamics in a large-deviation framework. We determine explicitly the effective probability-conserving dynamics which makes rare trajectories of the original dynamics become typical trajectories of the effective one. Our approach makes use of a weak-noise path-integral description in which the action is minimised by the rare trajectories of interest. For 'current-type' additive observables, we find criteria for the emergence of a propagative trajectory minimising the action for large enough deviations, revealing the existence of a dynamical phase transition at a fluctuating level, whose singular behaviour is between first and second order. In addition, we provide a new method to determine the scaled cumulant generating function of the observable without having to optimise the action. It allows one to show that the weak-noise and the large-time limits commute in this problem. Finally, we show how the biased dynamics can be mapped in practice to an explicit effective driven dynamics, which takes the form of a driven Langevin dynamics in an effective potential. The non-trivial shape of this effective potential is key to understand the link between the dynamical phase transition in the large deviations of current and the standard depinning transition of a particle in a tilted potential.