论文标题
越过高能屏障的活性药物的目标搜索
Target search of active agents crossing high energy barriers
论文作者
论文摘要
在坚固的能量景观中，主动剂的目标搜索仍然是一个挑战，因为标准增强的采样方法不适用于不可逆的动态。我们通过开发一种将过渡路径采样到主动的布朗动力学来克服了这个非平衡稀有事实问题。该方法被示例和基准测试，以具有高屏障的范式二维电位。我们发现，即使在如此简单的景观中，过渡路径合奏的结构和动力学在存在活动的情况下发生了巨大变化。实际上，遵循更长和违反直觉的搜索模式，活跃的布朗颗粒比被动的布朗颗粒更频繁地到达目标。
Target search by active agents in rugged energy landscapes has remained a challenge because standard enhanced sampling methods do not apply to irreversible dynamics. We overcome this non-equilibrium rare-event problem by developing an algorithm generalizing transition-path sampling to active Brownian dynamics. This method is exemplified and benchmarked for a paradigmatic two-dimensional potential with a high barrier. We find that even in such a simple landscape the structure and kinetics of the ensemble of transition paths change drastically in the presence of activity. Indeed, active Brownian particles reach the target more frequently than passive Brownian particles, following longer and counterintuitive search patterns.
