Rare behavior of growth processes via umbrella sampling of trajectories

We compute probability distributions of trajectory observables for reversible and irreversible growth processes. These results reveal a correspondence between reversible and irreversible processes, at particular points in parameter space, in terms of their typical and atypical trajectories. Thus key...

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Main Authors: Klymko, Katherine, Geissler, Phillip L., Garrahan, Juan P., Whitelam, Stephen
Format: Article
Language:English
Published: American Physical Society 2018
Online Access:https://eprints.nottingham.ac.uk/51137/
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author Klymko, Katherine
Geissler, Phillip L.
Garrahan, Juan P.
Whitelam, Stephen
author_facet Klymko, Katherine
Geissler, Phillip L.
Garrahan, Juan P.
Whitelam, Stephen
author_sort Klymko, Katherine
building Nottingham Research Data Repository
collection Online Access
description We compute probability distributions of trajectory observables for reversible and irreversible growth processes. These results reveal a correspondence between reversible and irreversible processes, at particular points in parameter space, in terms of their typical and atypical trajectories. Thus key features of growth processes can be insensitive to the precise form of the rate constants used to generate them, recalling the insensitivity to microscopic details of certain equilibrium behavior. We obtained these results using a sampling method, inspired by the “s-ensemble” large-deviation formalism, that amounts to umbrella sampling in trajectory space. The method is a simple variant of existing approaches, and applies to ensembles of trajectories controlled by the total number of events. It can be used to determine large-deviation rate functions for trajectory observables in or out of equilibrium.
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spelling nottingham-511372018-04-14T02:55:56Z https://eprints.nottingham.ac.uk/51137/ Rare behavior of growth processes via umbrella sampling of trajectories Klymko, Katherine Geissler, Phillip L. Garrahan, Juan P. Whitelam, Stephen We compute probability distributions of trajectory observables for reversible and irreversible growth processes. These results reveal a correspondence between reversible and irreversible processes, at particular points in parameter space, in terms of their typical and atypical trajectories. Thus key features of growth processes can be insensitive to the precise form of the rate constants used to generate them, recalling the insensitivity to microscopic details of certain equilibrium behavior. We obtained these results using a sampling method, inspired by the “s-ensemble” large-deviation formalism, that amounts to umbrella sampling in trajectory space. The method is a simple variant of existing approaches, and applies to ensembles of trajectories controlled by the total number of events. It can be used to determine large-deviation rate functions for trajectory observables in or out of equilibrium. American Physical Society 2018-03-19 Article PeerReviewed application/pdf en https://eprints.nottingham.ac.uk/51137/1/atypical-revised.pdf Klymko, Katherine, Geissler, Phillip L., Garrahan, Juan P. and Whitelam, Stephen (2018) Rare behavior of growth processes via umbrella sampling of trajectories. Physical Review E, 97 (3). 032123. ISSN 1550-2376 https://journals.aps.org/pre/abstract/10.1103/PhysRevE.97.032123 doi:10.1103/PhysRevE.97.032123 doi:10.1103/PhysRevE.97.032123
spellingShingle Klymko, Katherine
Geissler, Phillip L.
Garrahan, Juan P.
Whitelam, Stephen
Rare behavior of growth processes via umbrella sampling of trajectories
title Rare behavior of growth processes via umbrella sampling of trajectories
title_full Rare behavior of growth processes via umbrella sampling of trajectories
title_fullStr Rare behavior of growth processes via umbrella sampling of trajectories
title_full_unstemmed Rare behavior of growth processes via umbrella sampling of trajectories
title_short Rare behavior of growth processes via umbrella sampling of trajectories
title_sort rare behavior of growth processes via umbrella sampling of trajectories
url https://eprints.nottingham.ac.uk/51137/
https://eprints.nottingham.ac.uk/51137/
https://eprints.nottingham.ac.uk/51137/