Computing transition path theory quantities with trajectory stratification
Computing transition path theory quantities with trajectory stratification
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DOI：
10.1063/5.0087058
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发表时间：
2022-07-21
影响因子：
4.4
通讯作者：
Dinner, Aaron R.
中科院分区：
文献类型：
--
作者：
Vani, Bodhi P.;Weare, Jonathan;Dinner, Aaron R.
过渡路径理论从反应轨迹的集合中计算统计数据。对反应性轨迹进行采样的常见策略是控制轨迹的分支和修剪，以便增强对低概率段的采样。然而，将过渡路径理论应用于来自这种方法的数据可能是具有挑战性的，因为确定配置和轨迹段是否是反应轨迹的一部分需要在时间上向后看和向前看。在这里，我们展示了如何通过引入简单的数据结构来有效地克服这个问题。我们说明的方法在非平衡伞抽样的背景下，但该策略是一般的，可以用来获得过渡路径理论统计数据的其他方法，样本段的无偏轨迹。由AIP Publishing独家授权发布。
Transition path theory computes statistics from ensembles of reactive trajectories. A common strategy for sampling reactive trajectories is to control the branching and pruning of trajectories so as to enhance the sampling of low probability segments. However, it can be challenging to apply transition path theory to data from such methods because determining whether configurations and trajectory segments are part of reactive trajectories requires looking backward and forward in time. Here, we show how this issue can be overcome efficiently by introducing simple data structures. We illustrate the approach in the context of nonequilibrium umbrella sampling, but the strategy is general and can be used to obtain transition path theory statistics from other methods that sample segments of unbiased trajectories. Published under an exclusive license by AIP Publishing.