近日，法国里昂高等师范学院的Denis Bartolo及其研究团队取得一项新进展。经过不懈努力，他们证实大规模人群中出现集体振荡现象。相关研究成果已于2025年2月5日在国际权威学术期刊《自然》上发表。

该研究团队分析了西班牙圣费尔明节上数千名密集聚集者的动态，并推断出了受限空间内密集人群的物理理论。测量结果显示，密集人群能够自发组织成宏观的手性振荡器，无需外部引导即可协调数百人的轨道运动。在这些测量结果和对称性原理的指导下，研究人员构建了密集人群运动的力学模型。

这一模型表明，涌现的奇数摩擦力驱动了一种非互易相变，转向集体手性振荡，这捕捉到了所有的实验观察结果。为了验证发现的稳健性，研究人员指出，在2010年爱心大游行灾难发生时，也出现了类似的手性动态，并提出了一种协议，可能有助于预测这些以往无法预测的动态。

据悉，密集人群构成了现代社会中最危险的环境之一。危险源于无法控制的集体运动，导致人群被挤压到墙边，进而引发窒息和死亡。人们目前对人群动态的理解主要依赖于启发式碰撞模型，这些模型能够有效地捕捉小群体人的行为。然而，由数千人组成的密集人群所展现出的动态仍然是一个棘手的多体问题，缺乏基于第一性原理的定量实验表征和解释。

附：英文原文

Title: Emergence of collective oscillations in massive human crowds

Author: Gu, Franois, Guiselin, Benjamin, Bain, Nicolas, Zuriguel, Iker, Bartolo, Denis

Issue&Volume: 2025-02-05

Abstract: Dense crowds form some of the most dangerous environments in modern society. Dangers arise from uncontrolled collective motions, leading to compression against walls, suffocation and fatalities. Our current understanding of crowd dynamics primarily relies on heuristic collision models, which effectively capture the behaviour observed in small groups of people. However, the emergent dynamics of dense crowds, composed of thousands of individuals, remains a formidable many-body problem lacking quantitative experimental characterization and explanations rooted in first principles. Here we analyse the dynamics of thousands of densely packed individuals at the San Fermín festival (Spain) and infer a physical theory of dense crowds in confinement. Our measurements reveal that dense crowds can self-organize into macroscopic chiral oscillators, coordinating the orbital motion of hundreds of individuals without external guidance. Guided by these measurements and symmetry principles, we construct a mechanical model of dense-crowd motion. Our model demonstrates that emergent odd frictional forces drive a non-reciprocal phase transition7 towards collective chiral oscillations, capturing all our experimental observations. To test the robustness of our findings, we show that similar chiral dynamics emerged at the onset of the 2010 Love Parade disaster and propose a protocol that could help anticipate these previously unpredictable dynamics.

DOI: 10.1038/s41586-024-08514-6

Source: https://www.nature.com/articles/s41586-024-08514-6