论文标题
计算过渡路径理论数量具有轨迹分层
Computing transition path theory quantities with trajectory stratification
论文作者
论文摘要
过渡路径理论从反应性轨迹的集合中计算统计。抽样反应轨迹的一种常见策略是控制轨迹的分支和修剪，以增强低概率段的采样。但是，将过渡路径理论应用于此类方法的数据可能是一项挑战，因为确定配置和轨迹段是否是反应性轨迹的一部分，需要及时向后看。在这里，我们展示了如何通过引入简单的数据结构来有效克服这个问题。我们说明了在非平衡保护伞采样（NEU）的背景下进行的方法，但是该策略是一般的，可用于从其他采样无偏轨迹段的方法中获得过渡路径理论统计。
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 (NEUS), but the strategy is general and can be used to obtain transition path theory statistics from other methods that sample segments of unbiased trajectories.
