Shake, rattle, and help each other along In classical statistical mechanics, the deterministic dynamics of a many-body system are replaced by a probabilistic description. Chvykov et al. work toward a similar description for the nonequilibrium self-organization of collectives of active particles. In these systems, continuously input energy drives localized fluctuations, but larger-scale ordering can emerge, such as in the flight of a flock of birds. A key concept in their theory is the importance of rattling, whereby ordered patterns emerge through local collisions between neighbors at specific frequencies. The authors demonstrate this behavior using a set of flapping robots and produce related simulations of the robot behavior. Science, this issue p. 90 Long-range dynamic order in active systems is connected to the driving energy and particle response. Self-organization is frequently observed in active collectives as varied as ant rafts and molecular motor assemblies. General principles describing self-organization away from equilibrium have been challenging to identify. We offer a unifying framework that models the behavior of complex systems as largely random while capturing their configuration-dependent response to external forcing. This allows derivation of a Boltzmann-like principle for understanding and manipulating driven self-organization. We validate our predictions experimentally, with the use of shape-changing robotic active matter, and outline a methodology for controlling collective behavior. Our findings highlight how emergent order depends sensitively on the matching between external patterns of forcing and internal dynamical response properties, pointing toward future approaches for the design and control of active particle mixtures and metamaterials.

中文翻译：

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低噪音：活跃集体中自组织的预测原则

摇晃、摇晃和互相帮助 在经典统计力学中，多体系统的确定性动力学被概率描述所取代。切维科夫等人。努力对活性粒子集合的非平衡自组织进行类似的描述。在这些系统中，持续输入的能量会驱动局部波动，但可能会出现更大规模的排序，例如在一群鸟类的飞行中。他们理论中的一个关键概念是嘎嘎声的重要性，有序模式通过特定频率的邻居之间的局部碰撞而出现。作者使用一组扑翼机器人演示了这种行为，并生成了机器人行为的相关模拟。科学，这个问题 p。90 有源系统中的长程动态顺序与驱动能量和粒子响应有关。在活跃的集体中经常观察到自组织，如蚂蚁筏和分子马达组件。描述远离平衡的自组织的一般原则一直难以确定。我们提供了一个统一的框架，该框架将复杂系统的行为建模为很大程度上是随机的，同时捕获它们对外部强迫的依赖于配置的响应。这允许推导出类似玻尔兹曼的原理来理解和操纵驱动的自组织。我们通过使用形状变化的机器人活性物质，通过实验验证了我们的预测，并概述了一种控制集体行为的方法。