论文标题
从有限的间隔中漂移
Drifted escape from the finite interval
论文作者
论文摘要
噪声驱动的逃逸动力学的性能主要取决于系统动力学的随机组件。然而，逃生动力学也对确定性力也很敏感。在这里，我们正在探索在对称$α$稳定的噪声的作用下，从有限间隔中脱离有限间隔的过度脱落的属性。我们表明，正确重新缩放的平均第一个通道时间遵循通用模式作为广义pécklet数的函数，可用于有效区分漂移或随机力占主导地位的域。 $α$稳定类型的随机驾驶能够降低漂移占上风时漂移的重要性。
Properties of the noise-driven escape kinetics are mainly determined by the stochastic component of the system dynamics. Nevertheless, the escape dynamics is also sensitive to deterministic forces. Here, we are exploring properties of the overdamped drifted escape from finite intervals under the action of symmetric $α$-stable noises. We show that the properly rescaled mean first passage time follows the universal pattern as a function of the generalized Pécklet number, which can be used to efficiently discriminate between domains where drift or random force dominate. Stochastic driving of the $α$-stable type is capable of diminishing the significance of the drift in the regime when the drift prevails.
