Efficient characterisation of large deviations using population dynamics
Efficient characterisation of large deviations using population dynamics
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DOI：
10.1088/1742-5468/aab3ef
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发表时间：
2017-11
期刊：
影响因子：
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通讯作者：
T. Brewer;S. Clark;R. Bradford;R. Jack
中科院分区：
文献类型：
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作者：
T. Brewer;S. Clark;R. Bradford;R. Jack
我们认为种群动力学是通过克隆算法来实现的，用于分析时间平均量的大偏差。我们以具有周期边界条件的简单对称排斥过程为例，研究了结果关于算法参数的收敛，重点讨论了均态和非均质态之间的动力学相变，其中收敛是相对困难的。我们讨论了如何优化算法的性能，以及如何在并行计算平台上有效地利用算法。
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.