具有高阶相互作用的自适应多层网络中爆炸同步过渡的滞后调节控制。

IF 3.2 2区 数学 Q1 MATHEMATICS, APPLIED
Chaos Pub Date : 2025-09-01 DOI:10.1063/5.0289362
Richita Ghosh, Md Sayeed Anwar, Manish Dev Shrimali, Dibakar Ghosh
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引用次数: 0

摘要

最近的研究结果表明,高阶(群)相互作用为耦合振荡器网络中的爆炸现象提供了一般途径。虽然这些突然的一阶过渡,称为爆炸同步,具有重要的理论意义,但在许多现实世界的系统中,它们通常是不受欢迎的,并且具有潜在的危险。基于此,我们研究了一种控制机制,通过在系统中引入相位滞后来抑制包含高阶相互作用的自适应多层网络中的爆炸同步。通过适当调整自适应指数和相位挫折参数,我们证明即使在存在高阶相互作用的情况下,相位滞后也能有效地减轻爆炸行为,将一阶过渡转换为二阶。随着相位滞后的增大,迟滞宽度逐渐变窄,由突变变为平滑、连续的过渡。这种驯服效应在现实世界的网络中仍然很强大,比如猕猴的大脑网络。总的来说,我们的研究探索了一种有效的爆炸同步控制策略,并推进了我们对如何在合成和生物复杂系统中调节关键集体动力学的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lag-mediated control of explosive synchronization transitions in adaptive multilayer networks with higher-order interactions.

Recent findings suggest that higher-order (group) interactions provide a general pathway to explosive phenomena in networks of coupled oscillators. While these abrupt, first-order transitions, termed explosive synchronization, are of significant theoretical interest, they are often undesirable and potentially dangerous in many real-world systems. Motivated by this, we investigate a control mechanism to suppress explosive synchronization in adaptive multilayer networks incorporating higher-order interactions by introducing a phase lag into the system. By appropriately tuning the adaptation exponents and the phase frustration parameter, we demonstrate that phase lag effectively mitigates explosive behavior even in the presence of higher-order interactions, converting the transition from first order to second order. As the phase lag increases, the hysteresis width progressively narrows, and the abrupt transition gives way to a smooth, continuous one. This taming effect remains robust in real-world networks, such as the Macaque brain network. Overall, our study explores an effective control strategy for explosive synchronization and advances our understanding of how critical collective dynamics can be regulated in both synthetic and biological complex systems.

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来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
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