Recovery of synchronized oscillations on multiplex networks by tuning dynamical time scales

被引:0
|
作者
Vadakkan, Aiwin T. [1 ]
Verma, Umesh Kumar [2 ]
Ambika, G. [3 ]
机构
[1] Indian Inst Sci Educ & Res Tirupati, Tirupati 517619, India
[2] Indian Inst Technol Indore, Khandwa Rd, Indore 453552, India
[3] Indian Inst Sci Educ & Res Thiruvananthapuram, Thiruvananthapuram 695551, India
关键词
Multiplex network; Recovery of synchronized oscillation; Chimera states; CLUSTER SYNCHRONIZATION; COMPLEX NETWORKS; CHIMERA STATES; AMPLITUDE; PATTERNS; DEATH;
D O I
10.1016/j.physleta.2024.129842
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The heterogeneity among interacting dynamical systems or variations in the pattern of their interactions occur naturally in many real complex systems. Often they lead to partially synchronized states like chimeras or oscillation suppressed states like in-homogeneous or homogeneous steady states. In such cases, it is a challenge to get synchronized oscillations in spite of prevailing heterogeneity. In this study, we present a formalism for controlling multi layer, multi timescale systems and show how synchronized oscillations can be restored by tuning the dynamical time scales between the layers. Specifically, we use the model of a multiplex network, where the first layer of coupled oscillators is multiplexed with an environment layer, that can generate various types of chimera states and suppressed states. We show that by tuning the time scale mismatch between the layers, we can revive the synchronized oscillations. We analyse the nature of the transition of the system to synchronization from various dynamical states and the role of time scale mismatch and strength of inter layer coupling in this scenario. We also consider a three-layer multiplex system, where two system layers interact with the common environment layer. In this case, we observe anti synchronization and in-homogeneous steady states on the system layers and by tuning their time scale difference with the environment layer, they undergo transition to synchronized oscillations.
引用
收藏
页数:7
相关论文
共 50 条
  • [41] Collective behavior of interacting locally synchronized oscillations in neuronal networks
    Jalili, Mahdi
    COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2012, 17 (10) : 3922 - 3933
  • [42] Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks
    Marlene Bartos
    Imre Vida
    Peter Jonas
    Nature Reviews Neuroscience, 2007, 8 : 45 - 56
  • [43] On Time Scales of Intrinsic Oscillations in the Climate System
    Tsonis, Anastasios A.
    Wang, Geli
    Lu, Wenxu
    Kravtsov, Sergey
    Essex, Christopher
    Asten, Michael W.
    ENTROPY, 2021, 23 (04)
  • [44] Spontaneous Recovery in Directed Dynamical Networks
    Liu, Xueming
    Yan, Xian
    Stanley, H. Eugene
    ENGINEERING, 2024, 37 : 208 - 214
  • [45] Perturbations of Dynamical Systems on Simple Time Scales
    Pilyugin, S. Yu.
    LOBACHEVSKII JOURNAL OF MATHEMATICS, 2023, 44 (03) : 1215 - 1222
  • [46] Finite-time synchronization of nonlinear complex dynamical networks on time scales via pinning impulsive control
    Lu, Xiaodong
    Zhang, Xianfu
    Liu, Qingrong
    NEUROCOMPUTING, 2018, 275 : 2104 - 2110
  • [47] DYNAMICAL-SYSTEMS WITH MULTIPLE TIME SCALES
    BERNE, BJ
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 1995, 209 : 104 - PHYS
  • [48] Recent Trends in Dynamical Systems on Time Scales
    Eid, George
    Neugebauer, Jeffry
    Raffoul, Youssef Naim
    Tunc, Cemil
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2018, 2018
  • [49] Perturbations of Dynamical Systems on Simple Time Scales
    S. Yu. Pilyugin
    Lobachevskii Journal of Mathematics, 2023, 44 : 1215 - 1222
  • [50] Anti-periodic Oscillations of Fuzzy Delayed Cellular Neural Networks with Impulse on Time Scales
    Xu, Changjin
    Liao, Maoxin
    Li, Peiluan
    Liu, Zixin
    NEURAL PROCESSING LETTERS, 2020, 51 (03) : 2379 - 2402