Many biological, chemical, and physical systems are underpinned by stochastic transitions between equilibrium states in a potential energy. Here, we consider such transitions in a minimal model with two possible competing pathways, both starting from a local potential energy minimum and eventually finding the global minimum. There is competition between the distance to travel in state space and the height of the potential energy barriers to be surmounted, for the transition to occur. One pathway has a higher energy barrier to go over, but requires traversing a shorter distance, whereas the other pathway has a lower potential barrier but it is substantially further away in configuration space. The most likely pathway taken depends on the available time for the transition process; when only a relatively short time is available, the most likely path is the one over the higher barrier. We find that upon varying temperature the overall most likely pathway can switch from one to the other. We calculate the statistics of where the barrier crossing occurs and the distribution of times taken to reach the potential minimum. Interestingly, while the configuration space statistics is complex, the time of arrival statistics is rather simple, having an exponential probability density over most of the time range. Taken together, our results show that empirically observed rates in nonequilibrium systems should not be used to infer barrier heights.
翻译:许多生物、化学和物理系统的本质在于势能中平衡态之间的随机跃迁。本文研究此类跃迁在一个具有两条可能竞争路径的最小模型中:两条路径均始于局部势能极小点,最终抵达全局极小点。跃迁的发生需要在状态空间中的行进距离与所需克服的势垒高度之间进行权衡。其中一条路径需要跨越更高的能垒,但所需穿越的距离较短;另一条路径的势垒较低,但在构型空间中距离显著更远。实际采取的路径取决于跃迁过程可用的时间:当可用时间相对较短时,最可能路径为跨越较高势垒的路径。我们发现,通过改变温度,整体最可能路径会在两条路径之间发生切换。我们计算了势垒穿越发生位置的统计特性以及抵达势能极小点所需时间的分布。有趣的是,虽然构型空间统计特性较为复杂,但到达时间的统计特性却相当简单——在大部分时间范围内呈现指数型概率密度。综合来看,我们的研究结果表明,不应利用非平衡系统中经验观测到的速率来推断势垒高度。