标题： 活性物质中的延迟诱导相变 显示英文标题

标题： Delays-induced Phase Transitions in Active Matter

摘要： 我们考虑当许多对齐、自推进单元在二维空间中运动时出现的集体运动模式，这些单元通过排斥势相互作用，并且还受到延迟和随机扰动的影响。 在这种方法中，延迟起到类似于反应时间的作用，使得给定粒子会受到关于其附近其他粒子的速度和位置信息的一定时间延迟的影响。 为了深入了解涉及的复杂流动及其之间的转换，我们使用一个简单的模型，通过微调其少量参数，可以观察和分析通过实验或解析计算难以获得的行为，同时也能再现实验结果。 我们首次报告了随着时间延迟的增加，有序的极化集体运动向无序的转变。 对于延迟的一个固定中间值，当排斥半径增加时，类似的转变（从有序到无序）也会发生。 我们的模拟显示，从完全极化过渡到两种状态：完全无序的状态以及一种混合状态，这种混合状态是在有序运动的其他粒子背景下的完全无序运动的区域。 当延迟时间增加时会发生这种转变，并且是尖锐的，这表明这种有序-无序转变的性质要么是一阶的，要么是由一个急剧下降的线性函数描述的。 我们的模型是实际情况下的一种简化版本，因为时间延迟在许多密集分布的自主无人机在准二维空中空间移动时预计将发挥越来越重要的作用，这种情况正迅速引起关注。 显示英文摘要

摘要： We consider the patterns of collective motion emerging when many aligning, self-propelling units move in two dimensions while interacting through a repulsive potential and are also subject to delays and random perturbations. In this approach, delay plays the role analogous to reaction time so that a given particle is influenced by the information about the velocity and the position of the other particles in its vicinity with some time delay. To get insight into the involved complex flows and the transitions between them we use a simple model allowing, by fine-tuning of its few parameters, the observation and analysis of behaviours that are less accessible by experiments or analytic calculations and at the same time make the reproduction of experimental results possible. We report for the first time about a transition from an ordered, polarized collective motion to disorder as a function of the increasing time delay. For a fixed intermediate value of the delay similar transition (from order to disorder) is obtained as the repulsion radius is increased. Our simulations show a transition from total polarization to two kinds of states: fully disordered and a kind of state which is a mixture of patches of fully disordered motion in the background of orderly moving other particles. The transition occurs as the delay time is increased and is sharp, indicating that the nature of this order-disorder transition is either of first-order or is described by a sharply decreasing linear function. Our model is a simplified version of a practical situation of quickly growing interest because time delays are expected to play an increasingly important role when the traffic of many, densely distributed autonomous drones will move around in a quasi-two-dimensional air space.