论文标题
在无序系统中加快第一次通行时间的控制
Controls that expedite first passage times in disordered systems
论文作者
论文摘要
广泛研究了表现出量表不变性的无序系统中的第一个通道时间统计。特别是，能量或熵陷阱的较长陷阱是脂肪尾分布的，这会减慢整体运输过程。我们研究了不同模型中有偏见过程的第一个通过时间的统计特性，并采用了大跳跃原理，该原理显示了第一个通道时间上最大捕获时间的优势。受重新启示范式的启发，我们证明了这种最大值的去除是显着加速运输的。随着疾病的增加，该系统进入了去除效果显着的阶段。我们的结果表明，我们如何在利用量表不变性的强烈混乱系统中加快运输速度。与此处研究的无序系统相反，去除原理在同质系统中基本没有影响。这表明，与均匀的系统相比，从理论上讲，改善导电系统不良的电导相对容易。
First passage time statistics in disordered systems exhibiting scale invariance are studied widely. In particular, long trapping times in energy or entropic traps are fat-tailed distributed, which slow the overall transport process. We study the statistical properties of the first passage time of biased processes in different models, and employ the big jump principle that shows the dominance of the maximum trapping time on the first passage time. Inspired by the restart paradigm, we demonstrate that the removal of this maximum significantly expedites transport. As the disorder increases, the system enters a phase where the removal shows a dramatic effect. Our results show how we may speed up transport in strongly disordered systems exploiting scale invariance. In contrast to the disordered systems studied here, the removal principle has essentially no effect in homogeneous systems; this indicates that improving the conductance of a poorly conducting system is, theoretically, relatively easy as compared to a homogeneous system.
