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Rare behavior of growth processes via umbrella sampling of trajectories

Katherine Klymko1, Phillip L. Geissler1, Juan P. Garrahan2, and Stephen Whitelam3,*

  • 1Department of Chemistry, University of California at Berkeley, Berkeley, California 94720, USA
  • 2School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD, England, United Kingdom
  • 3Molecular Foundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA

  • *swhitelam@lbl.gov
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Phys. Rev. E 97, 032123 – Published 19 March, 2018

DOI: https://doi.org/10.1103/PhysRevE.97.032123

Abstract

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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Outline

Information

Phys. Rev. E 97, 032123– Published 19 March, 2018
  • Received 10 August 2017
  • Revised 3 February 2018
Article part of CHORUS
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