具有自走方向逆转效应的集体运动

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
C. Wang , C.R. Li , W. Guo , L.C. Du
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引用次数: 0

摘要

自然界中的一些生物,包括黄粘菌和蝗虫,为了获得更多的营养或避开障碍物,会表现出随机的方向逆转。在这项研究中,我们构建了一个类似维克塞克的模型,并通过调整噪声强度和平均数量密度,研究了具有自走方向逆转效应的集体运动。研究结果表明(1) 自走方向反转效应通常会降低集体运动的方向一致性。(2) 在弱噪声区域,自推进方向逆转效应增强了具有拓扑相互作用模式的群体的全局有序参数。(3) 不同相关时间的定向反转不会改变秩参数与密度之间的幂律关系,但记忆效应的存在会导致幂指数在某些密度阈值附近出现不同的符号。(4) 机器学习分析表明,集群现象与系统中局部阶次参数高和全局阶次参数低有关。总之,我们的研究为具有方向反转效应的集体运动提供了一种见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Collective motion with the self-propelled directional reversals effect
Some organisms in nature, including myxococcus xanthus and locusts, exhibit random reversals of direction for the purpose of obtaining more nutrients or avoiding obstacles. In this study, we have constructed a Vicsek-like model and investigated collective motion with the self-propelled directional reversals effect by adjusting the strength of noise and the average number density. Our study results show that: (1) The self-propelled directional reversals effect generally reduces the directional consistency of collective motion. (2) In the weak noise region, the self-propelled directional reversals effect enhances the global order parameter of the group with topological interaction pattern. (3) Directional reversals with different correlation time do not alter the power-law relation between the order parameter and the density, but the presence of memory effect can lead to different sign of power exponent near certain density thresholds. (4) Machine learning analysis reveals the clusters phenomenon is associated with high local and low global order parameters in system. Overall, our study provides an insight to the collective motion with the directional reversals effect.
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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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