2015
DOI: 10.1088/1742-5468/2015/12/p12008
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Inequivalence of nonequilibrium path ensembles: the example of stochastic bridges

Abstract: We study stochastic processes in which the trajectories are constrained so that the process realises a large deviation of the unconstrained process. In particular we consider stochastic bridges and the question of inequivalence of path ensembles between the microcanonical ensemble, in which the end points of the trajectory are constrained, and the canonical or s ensemble in which a bias or tilt is introduced into the process. We show how ensemble inequivalence can be manifested by the phenomenon of temporal co… Show more

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Cited by 38 publications
(38 citation statements)
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“…Here, we find "temporal condensates" in the form of trajectories for the fluctuations of A τ that are localized in time compared to τ and whose height scales with τ . A related condensation was reported recently in the context of sums of random variables, which can be dominated in some cases by a single, extensive or "giant" value [69][70][71][72][73][74].…”
supporting
confidence: 53%
“…Here, we find "temporal condensates" in the form of trajectories for the fluctuations of A τ that are localized in time compared to τ and whose height scales with τ . A related condensation was reported recently in the context of sums of random variables, which can be dominated in some cases by a single, extensive or "giant" value [69][70][71][72][73][74].…”
supporting
confidence: 53%
“…Equation (B7) also represents the variance of a Brownian bridge (see, e.g., Refs. [84,88]). For a Dirichlet profile whose area is constrained to vanish, the averaged path results instead as…”
Section: Dirichlet Boundary Conditionsmentioning
confidence: 99%
“…An important observation is that the bounds on fluctuations of a counting observable and its FPTs are controlled by the average dynamical activity, in analogy to the role played by the entropy production in the case of currents [1,13]. We hope these results will add to the growing body of work applying large deviation ideas and methods to the study of dynamics in driven systems [29][30][31][32][33][34][35][36][37][38][39][40][41], glasses [25,[42][43][44][45][46][47], protein folding and signaling networks [48][49][50][51], open quantum systems [52][53][54][55][56][57][58][59][60][61][62][63][64], and many other problems in nonequilibrium [65][66][67][68][69][70][71][72].…”
Section: Introductionmentioning
confidence: 98%