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Efficient characterisation of large deviations using population dynamics

MPG-Autoren
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Clark,  S. R.
Department of Physics, University of Bath;
Quantum Condensed Matter Dynamics, Condensed Matter Dynamics Department, Max Planck Institute for the Structure and Dynamics of Matter, Max Planck Society;

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Zitation

Brewer, T., Clark, S. R., Bradford, R., & Jack, R. L. (2018). Efficient characterisation of large deviations using population dynamics. Journal of Statistical Mechanics: Theory and Experiment, 053204. doi:10.1088/1742-5468/aab3ef.


Zitierlink: https://hdl.handle.net/21.11116/0000-0001-A7BC-F
Zusammenfassung
We consider population dynamics as implemented by the cloning algorithm for analysis of large deviations of time-averaged quantities. We use the simple symmetric exclusion process with periodic boundary conditions as a prototypical example and investigate the convergence of the results with respect to the algorithmic parameters, focussing on the dynamical phase transition between homogeneous and inhomogeneous states, where convergence is relatively difficult to achieve. We discuss how the performance of the algorithm can be optimised, and how it can be efficiently exploited on parallel computing platforms.